Christophe Foltête

Françoise Burel

Jean-Yves Barnagaud

Yves Meinard
email: yves.meinard@lamsade.dauphine.fr

Douglas Macmillan

Keywords: Conservation policies, decision analysis, habitats conservation, knowledge gaps, legitimacy, phytosociology, policy evaluation

Je voulais tout d'abord remercier le jury qui a bien voulu évaluer mon

Resumé

Le constat actuel d'une perte de biodiversité est largement partagé au sein de la communauté scientique mais également auprès du public et du monde politique. L'attention portée depuis plus d'une décennie aux changements climatiques et à leurs eets sur la biodiversité a parfois conduit à négliger le principal facteur d'érosion de la biodiversité : la destruction des habitats. Même s'il n'est pas oublié, ce facteur reste cependant moins étudié car plus dicile à cerner ou mesurer. En eet, les relations qui lient les espèces à leurs habitats sont complexes et mesurer un changement de température semble plus abordable dans l'absolu qu'analyser un changement dans l'habitat, surtout quand ce dernier n'est pas clairement déni. La question de la dénition et de la représentation de l'habitat en écologie est ainsi à la base de ce projet de thèse, qui vise à mieux connaître les relations qui lient espèces et habitats pour mieux comprendre l'érosion de la biodiversité.

Le but de cette thèse est d'étudier les relations entre espèces et habitats avec un focus particulier sur leurs diérentes composantes : (i) l'habitat, à travers la question de sa dénition en écologie et de son importance en conservation, (ii) les liens entre espèces et habitats, à travers la question des échelles spatiales et (iii) les espèces, à travers la question de leur spécialisation aux habitats. J'ai donc abordé dans une première partie l'histoire et l'évolution du concept d'habitat en écologie et à ses implications en conservation. Je me suis ensuite focalisé sur divers aspects qui régissent les relations écologiques entre espèces et habitats.

En particulier, dans une seconde partie et à travers le prisme de l'écologie du paysage, je me suis intéressé aux problématiques autour des eets d'échelles spatiales via une étude sur la distribution d'espèces d'arthropodes dans les paysages métropolitains mesurés à diérentes échelles spatiales. J'ai pu mettre en évidence que les échelles spatiales de réponses des espèces aux mesures du paysage sont très variables et ceci indépendamment de la représentation choisie du paysage. La théorie prédirait pourtant une certaine cohérence en fonction par exemple de certains traits écologiques. Ce cas d'étude démontre plus largement que les relations entre espèces et mesures de l'environnement ne sont pas forcément substituables et que l'échelle spatiale en est l'une des principales raisons.

Dans une troisième partie, je me suis concentré sur la spécialisation des espèces et j'ai tâché de comprendre comment des espèces dites spécialistes pouvaient se répartir le long d'un gradient continu d'habitat. Selon leurs niveaux de spécialisation, j'ai pu montrer que les espèces ne se répartissaient pas de manière similaire le long du gradient. Les espèces spécialistes sont plus particulièrement présentes dans les milieux homogènes du gradient viii et semblent s'eacer au prot d'espèces plus généralistes dans les milieux hétérogènes. Il apparait donc qu'il n'y aurait pas de spécialisations particulières des espèces aux milieux hétérogènes.

La dernière partie aborde l'implication du concept d'habitat dans les politiques publiques de conservation en prenant comme exemple l'une des plus importantes politiques de conservation au niveau mondial, la directive Habitats de l'Union européenne. J'ai pu évaluer la directive Habitats en analysant diérents critères, touchant autant à ses aboutissements qu'à sa construction et à sa légitimation en matière de conservation. A travers des exemples concrets et l'analyse du corpus bibliographique, j'ai pu identier d'importantes lacunes de connaissances au sein de la directive qui entravent ces critères. Ce travail met en évidence un découplage entre les aspects scientiques et leurs applications dans la directive et questionne l'opportunité d'utiliser le niveau habitat pour répondre à des problématiques de conservation.

Finalement, ce travail de thèse a permis de mettre en évidence certaines complexités qui gouvernent les relations entre espèces et habitats et il ore des pistes pour mieux les appréhender et pousse aussi à penser autrement ces relations pour mieux les comprendre.

Chapitre 1 Introduction 1

1.1 La crise de la biodiversité : diérents facteurs et un mauvais focus

Le constat d'un déclin important de la biodiversité du fait de changement environnementaux d'origine anthropique est aujourd'hui largement partagé dans la communauté scientique et même dans la société [START_REF] Collen | Monitoring change in vertebrate abundance : the living planet index[END_REF][START_REF] Pimm | The biodiversity of species and their rates of extinction, distribution, and protection[END_REF]. Derrière le terme biodiversité , on peut mettre beaucoup de choses mais force est de constater que quel que soit le référentiel de biodiversité considéré, on montre actuellement une baisse, que ce soit en termes de nombres d'espèces au niveau global, en termes d'abondances ou encore de complexité des interactions entre espèces ou même de nos relations, de nos expériences, en tant qu'humain, à cette biodiversité [START_REF] Soga | Extinction of experience : the loss of human-nature interactions[END_REF][START_REF] Chan | Opinion : Why protect nature ? Rethinking values and the environment[END_REF]. Pourtant, il est aussi largement reconnu que la biodiversité joue un rôle central et important, par exemple en octroyant à l'humanité des services gratuits, dits services écosystémiques [START_REF] Mace | Biodiversity and ecosystem services : a multilayered relationship[END_REF][START_REF] Bennett | Linking biodiversity, ecosystem services, and human well-being : three challenges for designing research for sustainability[END_REF][START_REF] Oliver | The pitfalls of ecological forecasting[END_REF].

Les facteurs anthropiques de cette baisse sont multiples et eux aussi de mieux en mieux reconnus. Les changements d'utilisation des sols, le changement climatique, les pollutions, la surexploitation ou encore les espèces invasives sont parmi les facteurs principaux (Pereira et al., 2012) mais ils sont rarement étudiés de manière conjointe dans les scénarios de biodiversité qui visent à comprendre et prédire l'impact de ces facteurs sur la biodiversité (Titeux et al., 2016a). La création du Groupe d'experts intergouvernemental sur l'évolution du climat (GIEC) en 1988 et les travaux de recherche qui en ont découlé ont joué un rôle majeur dans la prise de conscience de l'importance du changement clima-1. Ce chapitre introductif reprend certains passages du rapport de synthèse bibliographique sur les relations entre les espèces et leurs habitats publiés pour le compte du Ministère de l'écologie (dernière dénomination en date : Ministère de l'environnement, de l'énergie et de la mer) via le Service du Patrimoine Naturel (SPN, [START_REF] Jeanmougin | Synthèse bibliographique des changements d'échelles cartographiques et des relations écologiques entre les espèces et leurs habitats[END_REF]. Ce rapport est consultable depuis le site internet du SPN. Cependant, le changement climatique n'a jamais été caractérisé comme la première cause d'érosion de la biodiversité même si son impact pourrait aller en se renforçant dans les prochaines décennies [START_REF] Bellard | Impacts of climate change on the future of biodiversity[END_REF]. Les changements de mode d'occupation des sols induits par les activités anthropiques et donc la dégradation et la destruction des habitats sont depuis longtemps considérés comme la première cause du déclin de la biodiversité [START_REF] Dirzo | Global State of Biodiversity and Loss[END_REF][START_REF] Newbold | Global eects of land use on local terrestrial biodiversity[END_REF]. Au niveau global, ces changements sont principalement dus à l'augmentation des terres agricoles et à l'urbanisation. décalée dans le temps (e.g. le principe de la dette d'extinction ; [START_REF] Tilman | Habitat destruction and the extinction debt[END_REF].

Ainsi, la fragmentation des habitats est l'un des principaux facteurs qui tend à réduire la persistance des populations.

Les mécanismes expliquant l'impact de la fragmentation sur les espèces ont été largement étudiés et plusieurs théories générales ont émergé pour expliquer ces patrons [START_REF] Haila | A Conceptual Genealogy of Fragmentation Research : From Island Biogeography to Landscape Ecology*[END_REF]. La théorie de la biogéographie insulaire [START_REF] Macarthur | The Theory of Island Biogeography[END_REF] est l'un des cadres théoriques majeurs permettant de prédire les eets de la perte d'habitat et de la fragmentation sur les espèces (Figure 1.2). Cette théorie, d'abord pensée par l'exemple insulaire, s'applique également pour comprendre la persistance des espèces dans un paysage comme une dichotomie entre une matrice, négative ou neutre pour l'espèce et des îlots d'habitat dans cette matrice où l'espèce persiste. L'autre grande théorie est la théorie des métapopulations [START_REF] Hanski | Metapopulation dynamics[END_REF] qui découle de la théorie de la biogéographie insulaire et met en exergue les relations existant entre les populations pour expliquer leurs persistance. Cependant, d'un point de vue empirique, les résultats sur l'impact de la fragmentation montrent certaines contradictions [START_REF] Betts | A species-centered approach for uncovering generalities in organism responses to habitat loss and fragmentation[END_REF] et les modèles théoriques, leurs limites. Même si la destruction des habitats est la première cause du déclin de la biodiversité ou de populations ayant une histoire évolutive indépendante d'autres populations. Cependant, malgré ce consensus, des questions similaires demeurent car lorsqu'il s'agit de ségréger concrètement les unités évolutives indépendantes, on retombe sur les mêmes critères : interfertilité, divergence moléculaire, caractères morphologiques, niche écologique, biogéographie, etc. Le débat est encore aujourd'hui important au sein de la communauté scientique autour de cette notion d'espèce et surtout autour des critères applicables en pratique [START_REF] Hey | Understanding and confronting species uncertainty in biology and conservation[END_REF][START_REF] Queiroz | Species Concepts and Species Delimitation[END_REF] pour délimiter ces entités taxonomiques.

Cependant, lorsque l'on aborde la question des relations entre les espèces et leurs habitats, on s'intéresse à diérents niveaux d'organisation biologique. Dans cette relation, l'espèce, qui à la base désigne donc une entité taxonomique, est en fait généralement abordée au niveau de la population et de l'individu. Ainsi, dans ce manuscrit, le débat scientique autour de la notion d'espèce sera laissé de côté car répondant plus à des problématique taxonomiques. Les travaux eectués n'apportent pas de réponses pour ce qui est de la dénition même de l'espèce en général mais nous utilisons le concept pour simplement délimiter les entités taxonomiques. Par contre, pour ce qui est du concept d'habitat, beaucoup plus central dans les questions écologiques abordées dans la thèse, une réexion plus importante est nécessaire ici.

L'habitat

Le concept d'habitat est, comme celui d'espèce, complexe dans sa dénition [START_REF] Boullet | Réexions sur la notion d'habitat d'espèce végétale[END_REF] mais c'est pourtant un terme extrêmement courant aujourd'hui dans le langage scientique, technique mais aussi politique. En écologie scientique, c'est un terme ancien [START_REF] Carpenter | An ecological glossary[END_REF][START_REF] Yapp | The Concept of Habitat[END_REF]. Lorsque Ernest Haeckel introduit le terme écologie en 1866, celui-ci signie littéralement science de l'habitat (dérivé d'oikos signiant demeure en grec). Malgré son importance centrale en écologie, c'est un concept qui n'a reçu que peu d'attention sémantique du fait de sa grande complexité.

Certains auteurs ont tout de même relevé le dé et ils ont tous, au minimum, pointé le ou qui entoure le concept d'habitat et les confusions que cela engendre (e.g. [START_REF] Block | The habitat concept in ornithology[END_REF][START_REF] Gaillard | Habitatperformance relationships : nding the right metric at a given spatial scale[END_REF][START_REF] Udvardy | Notes on the Ecological Concepts of Habitat, Biotope and Niche[END_REF][START_REF] Mitchell | How useful is the concept of habitat ? -a critique[END_REF]. Tous ont également plaidé pour qu'une rationalisation des diérentes dénitions existantes soit entreprise [START_REF] Davis | Proposals Concerning the Concept of Habitat and A Classication of Types[END_REF][START_REF] Hall | The Habitat Concept and a Plea for Standard Terminology[END_REF] ou encore appelé à une redénition du concept basée sur des approches diérentes [START_REF] Dennis | Ten years of the resource-based habitat paradigm : the biotope-habitat issue and implications for conserving buttery diversity[END_REF][START_REF] Dennis | Towards a Functional Resource-Based Concept for Habitat : A Buttery Biology Viewpoint[END_REF]. Le concept d'habitat reste ainsi l'un des paradigmes de l'écologie scientique le plus fondamental mais aussi le moins discuté et le moins remis en question. [START_REF] Elton | The Classication of Habitats[END_REF] écrivait d'ailleurs à ce propos Denitions of habitats, or rather lack of it, is one of the chief blind spots in Zoology . Conserver une dénition imprécise pour un concept aussi fondamental ne peut qu'engendrer des discussions et conclusions ambiguës et des problèmes au sein des pratiques de conservation 1.2 Espèces et habitats : des dénitions complexes [START_REF] Dennis | Ten years of the resource-based habitat paradigm : the biotope-habitat issue and implications for conserving buttery diversity[END_REF][START_REF] Mitchell | How useful is the concept of habitat ? -a critique[END_REF]. Dès 1991, [START_REF] Peters | A critique for ecology[END_REF] soutient qu'il faut rendre opérationnel les concepts en écologie et cela en passant par de meilleures dénitions, en particulier celle de l'habitat. [START_REF] Murphy | Coping with uncertainty in wildlife biology[END_REF] montrent par exemple que les termes habitat et critique n'ont jamais été dénis précisément et indépendamment, ce qui a engendré des dicultés dans la détermination de ce qu'était un habitat critique pour la réalisation de listes d'espèces protégées (voir aussi [START_REF] Camaclang | Current practices in the identication of critical habitat for threatened species[END_REF].

Finalement, il est encore aujourd'hui impossible de donner une dénition consensuelle de l'habitat même si plusieurs idées maîtresses se sont structurées lors du développement de l'écologie. L'habitat peut ainsi se dénir par :

une association avec les individus et/ou des communautés d'espèces un espace géographique, plus ou moins étendu, des conditions de vie caractérisées et spéciques, un changement possible au cours du temps.

Ces quatre larges idées ont fait émerger une grande quantité de représentations et de dénitions de l'habitat. Nous regrouperons celles-ci dans trois approches principales permettant une caractérisation de l'habitat : l'habitat espèce-centré, l'habitat communautécentré et l'habitat anthropocentré (ces deux derniers pouvant être qualiés d'habitats catégoriels).

Habitat espèce-centré L'approche espèce-centrée s'appuie sur la théorie de la niche pour représenter les habitats des espèces. Le concept de niche est apparu pour la première fois dans les travaux de [START_REF] Grinnell | The niche-relationships of the California Thrasher[END_REF] comme la place occupée par une espèce dans son assemblage (via des interactions biotiques mais aussi des variables abiotiques). Il a ensuite été réutilisé par [START_REF] Elton | Animal ecology[END_REF] dans un sens proche et compatible avec l'approche de Grinnell (Pocheville, 2015;[START_REF] Chase | Ecological Niches : Linking Classical and Contemporary Approaches. Interspecic Interactions[END_REF] mais redéni sous le concept de niche fonctionnelle [START_REF] Whittaker | Niche, Habitat, and Ecotope[END_REF]. [START_REF] Hutchinson | Concluding Remarks[END_REF] a grandement popularisé et conceptualisé la niche écologique en s'appuyant largement sur l'approche développée par Grinnell. La niche écologique est ainsi dénie sous la forme d'un hypervolume déni par les n variables environnementales aectant une espèce. Cette niche fondamentale représente l'entièreté des possibilités de présence d'une espèce dénie par les variables environnementales. Cependant, du fait des interactions entre espèces (par exemple la compétition), l'espèce peut être exclue de certaines parties de la niche fondamentale. La niche résultante est alors appelé la niche réalisée (Figure 1.3). L'utilisation de cette approche espèce-centrée s'explique facilement. D'une part parce que la théorie de la niche écologique a été particulièrement développée pour mieux expliquer les règles d'assemblage et de coexistence des communautés à la suite de son développement par [START_REF] Hutchinson | Concluding Remarks[END_REF]. Ceci correspond à l'âge d'or de la théorie de la niche écologique et contribue à sa très large diusion [START_REF] Pocheville | The Ecological Niche : History and Recent Controversies[END_REF]. D'autre part, l'accès à des données d'habitats catégoriels n'est pas toujours possible ou peu pertinent dans les études scientiques selon les questions posées. Ainsi, l'habitat est assez largement décrit comme un ensemble de variables, soit relevées sur le terrain en même temps que les relevés des espèces par l'observateur, soit rassemblées à partir de mesures à large échelle.

L'habitat peut ainsi être variablement décrit au niveau local comme une matrice complexe de variables environnementales. Cette matrice est pertinente principalement dans l'étude pour laquelle elle est utilisée et s'apparente plus globalement à une formalisation simple de la niche écologique des espèces (en lien avec la dénition de [START_REF] Hutchinson | Concluding Remarks[END_REF] de la 1.2 Espèces et habitats : des dénitions complexes niche écologique).

Habitat communauté-centré

En milieu terrestre, l'approche communauté trouve ses racines dans les principes de la phytosociologie. La phytosociologie vise à caractériser les assemblages d'espèces homogènes (groupements végétaux, notamment les associations végétales) pour in ne décrire les habitats naturels. Cette approche scientique s'est particulièrement développée en Europe de l'ouest [START_REF] Chytrý | Vegetation survey : a new focus for Applied Vegetation Science[END_REF]. Les premiers travaux s'intéressant aux associations d'espèces végétales remontent au début du XXème siècle [START_REF] Braun-Blanquet | [END_REF][START_REF] Flahault | Phytogeographische Nomenklatur : Berichte und Vorschläge[END_REF] jusqu'aux prémices de l'écologie en générale [START_REF] Guinochet | Phytosociologie[END_REF].

La phytosociologie connaît également des développements récents comme les approches dites symphytosociologiques (ou phytosociologie paysagère) qui permettent de décrire le paysage végétal sur une base phytosociologique mais à l'échelle du paysage [START_REF] Chalumeau | Méthodologie de cartographie phytosociologique en Europe : approches symphytosociologique et géosymphytosociologique. Synthèse bibliographique[END_REF].

La gestion des espaces naturels en Europe s'appuie principalement sur les référentiels d'habitats basés sur les résultats d'études phytosociologiques [START_REF] Blasi | Dening and mapping typological models at the landscape scale[END_REF][START_REF] Bredenkamp | Vegetation mapping : theory, methods and case studies[END_REF][START_REF] Chytrý | Vegetation survey : a new focus for Applied Vegetation Science[END_REF][START_REF] Rekdal | Mapping of vegetation in Norway[END_REF]. La catégorisation des habitats sur une base phytosociologique à l'échelle européenne a commencé avec le référentiel CORINE biotope (Coordination of Information on the Environment ; [START_REF] Devillers | CORINE Biotopes Manual[END_REF] pour aujourd'hui s'harmoniser au sein du programme EUNIS (European Union Nature Information System ; [START_REF] Davies | EUNIS Habitat Classication Revised[END_REF][START_REF] Moss | How was EUNIS habitats constructed ? How were the original divisions made and levels decided ? Rapport technique[END_REF]. Les habitats ainsi décrits sont aujourd'hui devenus l'un des piliers des politiques européennes de conservation de la nature [START_REF] Bunce | The signicance of habitats as indicators of biodiversity and their links to species[END_REF] en particulier par leur caractère potentiellement intégrateur (voir partie 1.4 sur la surrogacy ). Ce caractère intégrateur pourrait permettre d'utiliser les habitats de manière pertinente pour surmonter l'obstacle que représente l'étude des espèces seules.

Ainsi, [START_REF] Evans | The Habitats of the European Union Habitats Directive[END_REF] indique que la majorité des types d'habitats de la Directive

Habitats européenne sont dénis à partir de communautés végétales et il reconnait d'ailleurs que ces types d'habitats sont plus correctement dénissables comme des biotopes ou des complexes de biotopes. En eet, l'approche phytosociologique (et donc communauté-centrée) de la description des habitats est critiquée par certains auteurs à cause du raccourci qu'elle engendre entre habitat et association végétale ou type de végétation (e.g. [START_REF] Hall | The Habitat Concept and a Plea for Standard Terminology[END_REF].

Habitat anthropocentré L'approche anthropocentrée dénit les habitats par l'usage des sols, souvent à l'échelle du paysage. Cependant, dans cette dénition, on ne parle pas explicitement d'habitats mais de mode d'occupation du sol ou de mode d'utilisation du sol ( landcover et landuse ). La distinction sémantique est ainsi plus marquée. A partir de cartographie de modes d'occupation du sol (MOS ; [START_REF] Zonneveld | The land unit ? A fundamental concept in landscape ecology, and its applications[END_REF], les acteurs de la conservation (scientiques, gestionnaires, etc.) cherchent à regrouper des zones homogènes (par exemple :

forêts, prairies, milieux agricoles, paysage ouvert, etc.). Ces classes de mode d'occupation ou d'usage du sol sont le principal moyen utilisé pour caractériser les unités qui composent les paysages 2 . L'utilisation de ce type de données comme substitut à des données d'habi- tats se justie aujourd'hui avec le besoin de données d'habitat à large échelle (nationale, continentale ou mondiale), qui ne sont tout simplement pas disponibles dans les deux autres approches.

Diérents outils existent pour cartographier les modes d'occupation du sol [START_REF] Ichter | La Liste rouge des écosystèmes en France, Habitats forestiers de France métropolitaine, Bilan de l'exercice d'application et préconisations. Rapport technique[END_REF]. Certaines cartographies sont ainsi basées sur des analyses de photo-interprétation à partir d'orthophotographies aériennes. Des études de terrain sont menées conjointement pour valider les photo-interprétations du mode d'occupation du sol. Un autre type d'outil passe par l'analyse de données d'images satellitaires (télédétection) et permet de s'intéresser à des échelles encore plus larges [START_REF] Blaschke | Object based image analysis for remote sensing[END_REF][START_REF] Horning | Remote sensing for ecology and conservation : a handbook of techniques[END_REF][START_REF] Kerr | From space to species : ecological applications for remote sensing[END_REF][START_REF] Recio | Landscape resource mapping for wildlife research using very high resolution satellite imagery[END_REF][START_REF] Pettorelli | Satellite remote sensing for applied ecologists : opportunities and challenges[END_REF]. A partir de données satellitaires, les analyses permettent de regrouper des zones homogènes selon diérentes variables (e.g. la réponse spectrale de la végétation). Cela permet aujourd'hui de caractériser des zones homogènes qui sont regroupées et reliées à des dénitions d'habitats, produisant ainsi une nouvelle typologie associée à l'outil et à une cartographie. La combinaison des approches permet d'obtenir des cartographies de MOS ayant un bon compromis entre précision des données et étendue spatiale. Par exemple, à l'échelle européenne, une base de données du MOS existe dans le cadre du programme Corine de l'Agence Européenne de l'Environnement. Il s'agit de la base de données géographique Corine Land Cover (CLC, Figure 1.4).

Les outils de télédétection sont particulièrement mis en avant aujourd'hui pour l'obtention de données d'habitat à large échelle [START_REF] Pereira | Essential Biodiversity Variables[END_REF][START_REF] Tuanmu | A global 1-km consensus land-cover product for biodiversity and ecosystem modelling[END_REF], par exemple dans les projets MODIS Global Land Cover [START_REF] Friedl | Global land cover mapping from MODIS : algorithms and early results[END_REF], GlobCover [START_REF] Arino | GLOBCOVER : The most detailed portrait of Earth[END_REF] et DISCover [START_REF] Loveland | The IGBP-DIS global 1km land cover data set, DISCover : First results[END_REF]. Cependant, l'exploitation des données de télédétection reste dicile pour les acteurs de la conservation, surtout d'un point de vue technique, principalement du fait d'un manque de dialogue avec la communauté scientique de la télédétection, quand bien même ces données pourraient 2. La dénition de paysage est elle même un sujet de débat. Elle est variable en fonction des taxons et des études. Généralement, le paysage va être déni en fonction de l'échelle spatiale et selon les organismes considérés. C'est un niveau d'organisation intermédiaire entre l'échelle locale (i.e. environnement direct) et l'échelle régionale (i.e. macro-échelle ; [START_REF] Dunning | Ecological processes that aect populations in complex landscapes[END_REF][START_REF] Turner | Landscape Ecology : The Eect of Pattern on Process[END_REF]. Voir ci-dessous 1.3.1. Cependant, le développement de l'écologie du paysage a montré que les espèces pouvaient avoir des relations plus complexes avec les paysages. Au-delà de la simple dichotomie entre un habitat et une matrice, les paysages peuvent aussi être considérés comme un ensemble de patchs de diérentes natures que l'on peut classier en fonction de leur homogénéité. Ces unités paysagères et en particulier leur conguration et composition dans les paysages sont aujourd'hui la principale approche utilisée pour étudier les liens entre les espèces et les paysages. L'un des facteurs le plus important est l'hétérogénéité de ces paysages [START_REF] Fahrig | Functional landscape heterogeneity and animal biodiversity in agricultural landscapes[END_REF]. En eet, le paysage n'étant plus considéré en fonction de l'espèce (i.e. habitat/matrice), une espèce peut être reliée particulièrement à un type de patch ou à plusieurs types de patch en fonction des ressources nécessaires à l'espèce 3. Ou écologie du paysage. Les deux appellations sont possibles en français sans qu'un consensus existe. Sauf erreur d'habitude, je préfèrerai dans le manuscrit la dénomination écologie des paysages plutôt que écologie du paysage car cette dernière induit qu'il n'y a qu'un paysage unique, ce qui, à la vue de la diversité des paysages existants, n'est pas fondé.

1.3 Les mesures écologiques des relations entre espèces et habitats présentes dans chacun des types de patch.

Le rôle de l'hétérogénéité sur la biodiversité est complexe et va tout autant dépendre du groupe taxonomique considéré que de la manière dont les paysages sont caractérisés [START_REF] Benton | Farmland biodiversity : is habitat heterogeneity the key ?[END_REF][START_REF] Stein | Terminology and quantication of environmental heterogeneity in species-richness research[END_REF][START_REF] Fahrig | Farmlands with smaller crop elds have higher within-eld biodiversity[END_REF]. Il est dicile de statuer sur un eet consensus positif ou négatif de l'hétérogénéité sur la biodiversité car les mécanismes sous-jacents sont diciles à détecter. Plusieurs approches théoriques ont été néanmoins proposées dans la littérature. Un eet positif de l'hétérogénéité des paysages sur la biodiversité peut par exemple s'expliquer par le fait que des espèces peuvent avoir besoins de diérents types d'unités du paysage simultanément (pour l'accès à des ressources particulières) ou successivement (par exemple, les insectes hémimétaboles ne vivent pas dans les mêmes conditions environnementales entre la phase larvaire et la phase imago). Dans ces cas là, on parle de l'hypothèse de landscape complementation (Figure 1.5). Cependant, il faut noter que cet eet de complémentation peut s'observer à deux échelles d'organisation biologique diérentes : l'espèce et la communauté. Au niveau de l'espèce, une population pourra montrer une abondance plus importante lorsqu'une combinaison de ressources particulières est présente. Au niveau de la communauté, du fait de la diversité des unités paysagères, un plus grand nombre d'espèces pourra s'observer (cf. Figure 1.5) . La complémentation s'observe à ces deux échelles d'organisation biologique mais pas forcément aux mêmes échelles spatiales.

Pour s'aranchir de la complexité de mesurer les paysages à l'aide de métriques qui rendent compte de l'hétérogénéité et de la problématique de la caractérisation les unités paysagères, [START_REF] Fischer | Beyond fragmentation : the continuum model for fauna research and conservation in human-modied landscapes[END_REF] ont proposé un modèle théorique où il ne s'agit plus de décrire les paysages comme un ensemble d'entités mais plutôt comme un continuum ou un gradient environnemental. Ce modèle semble plus à même d'identier les processus écologiques régissant les relations entre les espèces et les paysages qu'un modèle basé sur une représentation catégorisée de l'espace. En eet, il permet de relâcher certaines hypothèse inhérentes à une approche catégorisée du paysage, comme celle sur la dénition des patchs tout en permettant d'analyser plus directement les relations entre les processus écologiques et les patrons de distribution des espèces [START_REF] Fischer | Beyond fragmentation : the continuum model for fauna research and conservation in human-modied landscapes[END_REF].

Échelle spatiale Cependant, que les relations entre espèces et habitats soient explicitées dans des paysages catégoriels ou continus, elles n'échappent pas à l'une des problématiques majeures de l'écologie du paysage : l'échelle spatiale. Les écologues ont mis longtemps avant de s'approprier la notion d'échelle dans toute sa complexité. [START_REF] Wiens | Spatial Scaling in Ecology[END_REF] [START_REF] Lechner | Are landscape ecologists addressing uncertainty in their remote sensing data ?[END_REF][START_REF] Borcard | Partialling out the Spatial Component of Ecological Variation[END_REF] plutôt que de développer des méthodes pour modier correctement l'échelle spatiale des données, bien que les avancées dans ces deux champs s'inuencent considérablement l'une et l'autre [START_REF] Wu | Eects of changing scale on landscape pattern analysis : scaling relations[END_REF]. C'est en jouant sur la taille du grain et l'étendue spatiale que les études actuelles cherchent à mieux comprendre les relations existantes entre l'échelle d'analyse et l'observation des phénomènes écologiques. D'un point de vue purement théorique, il s'agit de réduire ou agrandir la taille du grain et celle de l'étendue, soit dans le but d'observer le comportement d'un même phénomène à plusieurs échelles d'analyse, soit dans le but de trouver la meilleure échelle d'analyse pour un phénomène étudié.

De nombreuses études traitent ainsi du comportement des mesures du paysage (i.e. composition, conguration, etc.) à travers les échelles spatiales et ses trois composantes [START_REF] Cain | A multi-scale analysis of landscape statistics[END_REF][START_REF] Schindler | Multiscale performance of landscape metrics as indicators of species richness of plants, insects and vertebrates[END_REF][START_REF] Lechner | Recent Progress on Spatial and Thematic Resolution in Landscape Ecology[END_REF]. Par exemple, Buyantuyev et [START_REF] Buyantuyev | Eects of thematic resolution on landscape pattern analysis[END_REF] ont montré que selon la résolution thématique des données, il peut y avoir de grandes diérences dans les valeurs des métriques de composition ou de conguration du paysage. Ceci corroborant les résultats aussi observés pour le grain. Cependant, au-delà du comportement des mesures du paysage à travers les échelles spatiales, il convient aussi d'étudier quelle est l'échelle spatiale des relations entre les espèces et les paysages 4 . Cette question est cependant moins étudiée même si les travaux traitant de ces problématiques se sont développés rapidement. C'est sur cet aspect précis que portera le troisième chapitre de cette thèse. Cette échelle spatiale est considérée comme l'échelle de perception du paysage par les espèces [START_REF] Miguet | What determines the spatial extent of landscape eects on species ?[END_REF]. Elle est généralement mesurée comme l'échelle spatiale pour laquelle la relation statistique entre les mesures du paysage et la variable écologique considérée de l'espèce (e.g. l'abondance ou la présence-absence) est la plus forte. Nous avons particulièrement étudié comment cette mesure se comporte en fonction de la description du paysage utilisée et des espèces considérées.

Spécialisation des espèces

Si la première cause du déclin de la biodiversité est bien la dégradation et la destruction des habitats, ce facteur n'aecte pas toutes les espèces de la même façon. Par exemple, les espèces dites spécialistes sont plus sensibles à la perte de leurs habitats (par la fragmentation par exemple) que des espèces dites généralistes. De récents travaux 4. Dans la littérature scientique, les dénominations sont nombreuses pour désigner l'échelle spatiale à laquelle une espèce perçoit le paysage : scale of eect , intrinsic scale , characteristic scale ou encore scale of response . On essayera dans ce manuscrit d'utiliser de manière constante la traduction d'échelle caractéristique théoriques, corroborés par les études empiriques, ont montré que l'altération des habitats des espèces spécialistes étaient la principale cause de l'homogénéisation des communautés d'espèces au prot des espèces généralistes [START_REF] Teyssèdre | Contrasting eects of habitat reduction, conversion and alteration on neutral and non neutral biological communities[END_REF]. Cette notion de spécialisation et de généralisme découle de la notion de niche écologique (cf. partie 1.2.2). L'idée est que les espèces spécialistes, ayant de fortes exigences écologiques, vont pouvoir utiliser une partie plus réduite d'un gradient environnemental (Figure 1.6) alors que les espèces dites généralistes ont des exigences écologiques moindres leur permettant de croître et de se reproduire en utilisant une large gamme du gradient environnemental considéré [START_REF] Futuyma | The Evolution of Ecological Specialization[END_REF][START_REF] Devictor | Dening and measuring ecological specialization[END_REF]. [START_REF] Henckel | Eet de l'hétérogénéité des paysages agricoles (composition et conguration) et de l'intensication des pratiques culturales sur la structure des communautés écologiques (oiseaux et adventices) en systèmes intensifs tempérés[END_REF]. Les principales hypothèses sont résumés dans la gure 1.8. Théoriquement, ces processus écologique en relation avec un gradient d'hétérogénéité devrait amener à ce que l'on retrouve tant des espèces spécialistes des extremums de ce gradient, mais aussi des espèces qui vont persister dans les milieux hétérogènes et même en être spécialiste, principalement via l'hypothèse de complémentation. Cette hypothèse a déjà été observé plusieurs fois dans la littérature mais principalement pour des études à l'échelle du paysage. A l'échelle macro-écologique, la relation de complémentation a été observé pour le niveau d'organisation des communautés d'espèce mais n'a été que peu exploré pour les espèces prisent indépendamment [START_REF] Clavero | Functional homogenization of bird communities along habitat gradients : accounting for niche multidimensionality[END_REF]. Dans le quatrième chapitre, nous utilisons un gradient du paysage pour étudier cette hypothèse de complémentation à l'échelle macro-écologique en lien avec la spécialisation des espèces (Figure 1.8).

Les relations espèces-habitats dans les sciences de la conservation

Au-delà des questions théoriques et écologiques abordées dans les parties précédentes qui entourent les relations entre les espèces et leurs habitats, la question cruciale pour la conservation qui se pose aujourd'hui est donc de savoir si le niveau d'organisation du vivant habitat peut-être utilisé comme un outil performant pour la conservation. D'un point de vue appliqué, l'habitat se pose comme un proxy à conserver pour permettre la conservation de la biodiversité (en particulier, des espèces). C'est une vision englobante ou parapluie de l'habitat qui est généralement mise en avant dans ce contexte et traduite sous le terme de surrogate 5 dans la littérature scientique.

Ce concept de surrogacy reste très divers [START_REF] Caro | Conservation by proxy : indicator, umbrella, keystone, agship, and other surrogate species[END_REF][START_REF] Lawler | Assessing the mechanisms behind successful surrogates for biodiversity in conservation planning[END_REF][START_REF] Noon | Multispecies conservation planning on U. S. federal lands[END_REF][START_REF] Hunter | Two roles for ecological surrogacy : Indicator surrogates and management surrogates[END_REF] [START_REF] Noss | The Naturalists Are Dying o[END_REF]. C'est dans ce contexte que la liste rouge IUCN des écosystèmes a par exemple vu le jour (Keith et al., 2013). Ces approches permettent de ne pas seulement se restreindre à une approche espèce-centrée, d'ailleurs souvent décriée pour ne cibler que les espèces remarquables, mais prennent également en compte les processus de maintien de la biodiversité (connectivité, interactions, etc.) qui, au-delà d'une biodiversité remarquable, sont soutenues par une biodiversité dite ordinaire , à même de pérenniser les services écosystémiques, importants pour l"homme [START_REF] Kremen | Managing ecosystem services : what do we need to know about their ecology[END_REF]. De plus, au-delà de la valeur instrumentale de la biodiversité, s'aranchir de l'approche espèce-centrée de la conservation et donc du choix des espèces et des déséquilibres que celui-ci impose (Cardoso, 2012) 6. Vigie-Nature est dispositif coordonné au niveau national, en particulier par le Muséum National d'Histoire Naturelle, et déployé au niveau régional pour permettre le suivi de l'état de santé de la nature dite ordinaire à travers des groupes indicateurs (oiseaux, papillons, chauve-souris, plantes et amphibiens) et s'appuyant sur les réseaux naturalistes volontaires ou de simples citoyens prêts à s'engager.

Introduction

The concept of habitat emerged with the beginnings of ecology as a science. To illustrate how this concept is deeply entrenched in the history of ecology, picture two naturalists walking into the wild, one of them being an expert of a taxonomic group and the other a beginner. If the beginner sees a species they do not know, one of their rst questions to the specialist would be : In which habitats can this species be found ? Only in this one ?

And while saying this, they would point at their surrounding area. This is how habitat was dened in the oldest times of ecology and naturalist sciences. This is often still the case for naturalists in the eld and this is not an issue per se. In this sense, habitat is perceived more as an atmosphere than as a state ; it can be considered a mood of nature described by a human being. This mood of nature cannot be dened scientically because it is primarily subjective, a projection of people emotions that are not easily converted into a scientic concept. The long history and the profound entrenchment of the concept of habitat in ecology is one particular proof of the diculty to nd a consensual denition for a subjective concept.

One may ask why it would be important to question concepts in ecology. Actually, many ecologists overlook or take for granted the importance of concepts for their practices. Recently, [START_REF] Reiners | 100 years of ecology : what are our concepts and are they useful ?[END_REF] stressed that knowing our scientic discipline is essential because it allows evaluating and understanding our collective priorities given limited resources ; shaping sociopolitical strategies for making a more eective science, and designing a more applicable science for satisfying societal and environmental wants and needs. They dened a scientic concept as a mental representation of an entity, process or relationship with distinctive application to ecology that allows prediction, control or explanation [START_REF] Reiners | 100 years of ecology : what are our concepts and are they useful ?[END_REF]. This denition thus perfectly matches with the view of habitat as a concept.

If concepts are considered important, why should we particularly focus on the concept of habitat ? First, the results of [START_REF] Reiners | 100 years of ecology : what are our concepts and are they useful ?[END_REF] on a large survey of ecologists showed that the concept of habitat is the third most useful concept. In a paradoxical way, it is one of the rare concepts that was never classied as unfamiliar by the survey respondents although this concept is largely acknowledged as imprecise or ambiguous [START_REF] Tellería | Wildlife Habitat Requirements : Concepts and Research Approaches[END_REF].

Second, beyond the clarication of the philosophical basis of ecology, the concept of habitat also has great implications for wildlife management and conservation. Although ecology literally means the science of habitat and can be dened as the study of relationships between organisms and their environments, the concept of habitat remains poorly dened [START_REF] Tellería | Wildlife Habitat Requirements : Concepts and Research Approaches[END_REF]. On the one hand, habitat studies vary considerably in concepts and methodologies, which may hamper the understanding of species-habitat relationships, especially when comparisons are attempted among studies [START_REF] Krausman | Another plea for standard terminology[END_REF].

This creates diculties to link theoretical work with applied approaches in the design of management plans [START_REF] Cook | Conservation in the dark ? The information used to support management decisions[END_REF]. On the other hand, habitat destruction and degradation is considered the main driver of biodiversity loss [START_REF] Barnosky | Approaching a state shift in Earth/'s biosphere[END_REF].

The concept of habitat has thus important implications for conservation of biodiversity, with relevance not only for researchers but also for managers, stakeholders and politicians.

Habitat has become a concept with a huge importance in the scientic literature but also in the grey literature and conservation policies, due to its potential as a powerful surrogate for conservation purposes [START_REF] Bunce | The signicance of habitats as indicators of biodiversity and their links to species[END_REF]. It is now a key conservation unit enshrined in environmental legislations. For example, the European Habitats Directive, which is considered the main network of protected areas in the world, has an important focus on habitats [START_REF] Lockwood | Global protected area framework. Managing protected areas : A global guide[END_REF]. The diculty to link theoretical work with applied approaches in habitat-related studies and the ambition to eectively apply habitat-focused conservation approaches seem therefore conicting.

The aim of this work is to evaluate how the concept of habitat, due to its ambiguity, may have impeded conservation advances by confusing the dierent communities of people involved in its development. First, we provide a historical evaluation of the concept of habitat through a literature review of past and current seminal papers on the subject.

Second, we work through some examples to show how the ambiguity of this concept in ecology, with no proper denition, can be misleading for the understanding of some habitat-related terms and even impede conservation purposes. Finally, we provide new perspectives for the concept with a particular focus on habitat quality, which should be better understood and assessed to reach conservation goals.

A historical look back on the concept of habitat

The concept of habitat was discussed numerous times by dierent authors throughout the 20th century. In European scientic ecology, the importance of phytosociology to describe landscape and vegetation associations has fed most of the controversy on the denition of habitat. For example, in one of the rst papers dealing with the denition of the concept of habitat, [START_REF] Yapp | The Concept of Habitat[END_REF] presented the concept of habitat as one of the oldest and most fundamental concepts in plant ecology. Yet, he acknowledged that this concept was less rigorously examined than others and that the ecological literature contained a lot of denitions without any consensus or critical assessment. The aim of his work was an attempt to examine critically and analytically the concept of habitat. He conceded that if he succeeded only in focusing attention on the subject, it would be a good rst step. His rapid review of the concept showed that the concept of habitat has been largely

subjective and he cited among others [START_REF] Clements | Plant succession : an analysis of the development of vegetation[END_REF], who referred to the application of the term habitat as completely a matter of individual opinion. Nevertheless, [START_REF] Yapp | The Concept of Habitat[END_REF] retained four main statements from his literature analysis that could help to frame the concept : (i) the area idea of habitat, (ii) change and development in the habitat, (iii) uniformity of life-conditions in habitat, and (iv) the habitat of individuals.

The area idea of habitat The rst idea relied on the fact that a habitat occupies an area that is geographically dened (i.e. a locality). This idea seemed to be largely accepted among the main authors of the beginning of the 20th century (e.g. [START_REF] Clements | Research methods in ecology[END_REF][START_REF] Nichols | The interpretation and application of certain terms and concepts in the ecological classication of plant communities[END_REF]. Finally, this idea of habitat as a place or a location where an organism lives is considered to be the simplest one, i.e. the basic idea of the denition of habitat [START_REF] Haskell | Mathematical Systematization of "Environment[END_REF][START_REF] Kearney | Habitat, environment and niche : what are we modelling ?[END_REF][START_REF] Mitchell | How useful is the concept of habitat ? -a critique[END_REF][START_REF] Odum | Fundamentals of ecology, 3rd edn[END_REF]. [START_REF] Davis | Proposals Concerning the Concept of Habitat and A Classication of Types[END_REF] exploring formal distinctions between concepts of habitat and environment also concluded that the former emphasized the location in addition to conditions (see [START_REF] Mason | Language Analysis and the Concept "Environment[END_REF].

He also incorporated the notion of resources, which seemed central to him but often neglected or omitted, into the concept of habitat. He dened resources as various forms of energy and matter that are potentially or actively useful to the organisms. This denition was broad but Davis pointed out that the main aspect of resources is that they must be available for the organism above its minimum requirements. However, this minimum requirement also seems dicult to dene. This work of [START_REF] Davis | Proposals Concerning the Concept of Habitat and A Classication of Types[END_REF] is a turning point in the history of the habitat concept. It's the rst time that resources are highlighted in the denition of habitat and that this denition is accompanied by a particular typology.

Change and development in the habitat

The second idea referred to the idea of plant succession that emerged clearly at this time and is a convenient means to include time and space into the concept of habitat. This idea is similar to the symphytosociological view of landscape developed later in the history of botany [START_REF] Ansseau | Symphytosociologie du paysage végétal[END_REF]). However, few authors have combined time and space in their theoretical work on habitat. [START_REF] Davis | Proposals Concerning the Concept of Habitat and A Classication of Types[END_REF] habitats. He was the rst to accompany his denition with a specic typology.

Uniformity of life-conditions in habitat

The third idea dealt with the physical counterpart of an association of species (e.g. the plant association of phytosociology).

The denition of this physical counterpart can be strict among several authors (uniform habitat-conditions) or more related with a diversity of conditions under which communities may exist (ecological amplitude or range of conditions).

Habitat of individuals or communities ? Finally, whereas these three previous ideas developed by [START_REF] Yapp | The Concept of Habitat[END_REF] are related to the habitat of a community, linked with plant associations, the fourth one raised the question of a habitat dened from a species-centered point of view. [START_REF] Yapp | The Concept of Habitat[END_REF] therefore confronted two conceptions of ecology, synecology and autecology, through the prism of the denition of habitat. Yet at this time, there was evidence for an investigation of the habitat of a single plant rather than that of the whole plant association even for synecologists ; however, according to them, this had been investigated under another semantic scheme (see for example the Standort term proposed by [START_REF] Gams | Prinzipienfragen der Vegetationsforschung[END_REF] to dene the habitat of a plant association).

This dichotomy between a species-centered and a community-centered denition of habitat is central in the development of the concept of habitat [START_REF] Mitchell | How useful is the concept of habitat ? -a critique[END_REF][START_REF] Tellería | Wildlife Habitat Requirements : Concepts and Research Approaches[END_REF]. Following the seminal paper of [START_REF] Hutchinson | Concluding Remarks[END_REF] on the ecological niche, [START_REF] Udvardy | Notes on the Ecological Concepts of Habitat, Biotope and Niche[END_REF] wrote about denitions in ecology, particularly the concepts of habitat, biotope and ecological niche that according to him were basic but inadequately dened. A major issue was that biotope and niche were often used as two synonyms of habitat. From his references, he described the biotope as the habitat of biotic communities, and emphasized that biotope is not used consistently in dierent countries, being sometimes used as a species-centered term. The term Standort dened by [START_REF] Gams | Prinzipienfragen der Vegetationsforschung[END_REF] is here a clear synonym of biotope and belongs to the realm of synecology as already concluded by [START_REF] Yapp | The Concept of Habitat[END_REF]. [START_REF] Udvardy | Notes on the Ecological Concepts of Habitat, Biotope and Niche[END_REF] rearmed this denition and proposed that misuses of biotope (as a species-centered term) should be eliminated. [START_REF] Davis | Proposals Concerning the Concept of Habitat and A Classication of Types[END_REF] also discarded the use of vegetation types and plant communities to describe the habitat of animals because the biotope denition is too vague and belongs to the realm of synecology. In the same idea, [START_REF] Elton | The Classication of Habitats[END_REF] wrote that ecologists in general acknowledged that botanists have done part of the job by describing habitats via plant associations. He refuted this statement because plant associations cannot describe all animal habitats (e.g. parasites).

Regarding the ecological niche, [START_REF] Udvardy | Notes on the Ecological Concepts of Habitat, Biotope and Niche[END_REF] started from Grinnell (1917b)'s denition. He demonstrated its compatibility with the denition of [START_REF] Elton | Animal ecology[END_REF], as also more recently acknowledged [START_REF] Chase | Ecological Niches : Linking Classical and Contemporary Approaches. Interspecic Interactions[END_REF][START_REF] Pocheville | The Ecological Niche : History and Recent Controversies[END_REF] : the ecological niche is thus a functional entity merging the denitions of these two authors and is the product of a synecological thinking. In other words, although habitat and ecological niche are related, the former came from autecological thinking, such that habitat should be species-centered.

In contrast, the concept of ecological niche was born under community-level thinking :

although it can also be viewed as species-centered, it was built to understand co-existence patterns in ecological communities (see the Volterra-Gause principle and details in [START_REF] Hutchinson | Concluding Remarks[END_REF]. So these two related concepts do not tackle the same levels of biological organization and thus have dierent aims. [START_REF] Whittaker | Niche, Habitat, and Ecotope[END_REF] mainly focused on the niche concept, compared with the concept of habitat, to really highlight for the rst time the consequences of a confusion of concepts [START_REF] Pocheville | The Ecological Niche : History and Recent Controversies[END_REF]. In summary, [START_REF] Whittaker | Niche, Habitat, and Ecotope[END_REF] oered to resolve the confusion around niche, and related terms such as habitat, using a parallel with levels of biological organization. The authors related both the niche and habitat terms to the population level. For example, they dene a habitat hyperspace describing the complete set of physical and chemical variables in the environment that form spatial gradients (at the scale of the landscape but also in an area). From a species point of view, the part of this hyperspace that is occupied by the species (i.e. by all populations of the species) is dened as the habitat hypervolume and nally, a particular species population response to variables in this hypervolume describe the habitat. They also, as [START_REF] Udvardy | Notes on the Ecological Concepts of Habitat, Biotope and Niche[END_REF], dene a biotope as the environment of a particular community in the landscape.

The same framework was used to dene a niche : the niche hyperspace represented axes of all variables by which species in a community are adaptively related. This denition clearly focused on the functional denition of niche. [START_REF] Whittaker | Niche, Habitat, and Ecotope[END_REF] ended their recommendations by clarifying level-dependent uses of terms : in ecology, niche should describe the role of species within the community and habitat their distributional response to inter-community environmental factors. There was symmetry in denitions of [START_REF] Whittaker | Niche, Habitat, and Ecotope[END_REF] for niche and habitat, since they were truncated in a hyperspace, a hypervolume and nally to the word itself at the population level, showing a willingness to simplify these concepts. However, the denitions remained highly theoretical and there was a lack of examples that in ne left these concepts non-operational.

Linking habitat with population dynamics Southwood, in his 1977 presidential address to the British Ecological Society [START_REF] Southwood | Habitat, the Templet for Ecological Strategies[END_REF], chose to talk about habitat and asked whether it was a template for ecological strategies. The article did not refer directly to the denition of habitat but it addressed new questions about the concept.

Southwood's paper examined time and space issues in the habitat concept, particularly with regards to the favorableness of habitat and its relations with population demography.

The level of favorableness is directly related to the reproductive rate of an organism.

It can vary depending on time (period of reproduction for example) and space (site of reproduction). The idea of linking habitat with demographic parameters is one of the major current trends in ecology [START_REF] Tellería | Wildlife Habitat Requirements : Concepts and Research Approaches[END_REF], particularly through the question of habitat selection by individuals [START_REF] Matthiopoulos | Establishing the link between habitat selection and animal population dynamics[END_REF].

Synthesis The concept of habitat was thus dened repeatedly by several authors who all pointed to the same issues. Nevertheless, the call for focusing attention on this subject by most of the authors was not answered by the community of ecologists. It can be useful to wonder why. The easiest explanation is that the subject is neither interesting nor crucial for the purpose and advance of ecology and ecologists may have viewed a semantic analysis as a waste of time. We can cite Southwood who explained this idea in his seminal paper [START_REF] Southwood | Habitat, the Templet for Ecological Strategies[END_REF] : As always with classication of nature [classication of habitats are clearly part of it even if Southwood did not refer to habitats here], it is easy to nd exceptions ; the real challenge, the constructive work, is not to nd the exception, but to use this to improve, modify or even change the general pattern. However, as [START_REF] Murphy | Coping with uncertainty in wildlife biology[END_REF] emphasized, the main issue is that, over the long term, this strategy can lead to misuse and a lack of operationnality of concepts. Moreover, all arguments and issues raised by the authors that tried to dene concept of habitat seem relevant and important for the development of ecology.

Finally, over its long history, the concept of habitat was always dened using either a species-centered denition or a community-centered denition, depending on the author and context [START_REF] Tellería | Wildlife Habitat Requirements : Concepts and Research Approaches[END_REF]. The current schism between the habitat as appreciated by stakeholders and politics and the habitat that is manipulated by scientists induces a polarization of the concept between an ecological habitat and an operational habitat respectively. Operational habitat is the current interpretation of the former synecological view of habitat (i.e. habitat of a community) whereas the ecological habitat is more related to the development of the ecological niche and thus to the former autecological view of habitat (see above on [START_REF] Yapp | The Concept of Habitat[END_REF].

A mismatch of a same concept, due to multiple uses in dierent contexts, is also observed for other key concepts of conservation. Recently, Hunter Jr. et al. (2016) argued that the concept of ecological surrogacy should be split into two dierent approaches :

indicator surrogate and management surrogate. This dichotomy is mainly due to dierent goals of users who do not share a same foundational understanding of ecological surrogacy.

Dierent goals may also drive the observed dichotomy in the concept of habitat. However, this dichotomy impedes shared eorts to reach conservation goals. Despite a century of ambiguity and conceptualization, the concept of habitat is still consistently used vaguely in the literature, with no reference to a particular denition. The concept of habitat should remain a subject of stimulating debates, in line with the many related concepts generated by its age and importance in ecology.

Habitat related terms : impacts of ambiguity for conservation

Beyond the semantic analysis of a word, its ambiguity can lead to misleading concepts.

Misleading concepts imply wasting time and funding that are crucial in the conservation of biodiversity today [START_REF] Krausman | Another plea for standard terminology[END_REF][START_REF] Murphy | Coping with uncertainty in wildlife biology[END_REF]. Here, we take four examples of phrases related to the concept of habitat that have impeded and still affect conservation actions : critical habitat, habitat fragmentation, habitat suitability and habitat quality.

One of the most important policies for conservation in the USA is considered to be the Endangered Species Act of 1973 (ESA). However, studies that evaluate this policy have

shown that its applications rely on an ambiguous scientic basis [START_REF] Murphy | Guidance on the Use of Best Available Science under the U.S. Endangered Species Act[END_REF][START_REF] Wilhere | The role of scientists in statutory interpretation of the endangered species act[END_REF]. [START_REF] Murphy | Coping with uncertainty in wildlife biology[END_REF] were the rst to address the impact of vague and ambiguous terminology in ecology on policy and decision-making process. To illustrate their point, they used an example from the ESA where the designation of critical habitat was not dened, partly because the words critical and habitat did not have clear denition themselves. They did not contribute directly to the debate about the concept of habitat but they identied the denitions best suited with respect to the ESA (i.e. with an autecological restriction). They concluded that a context-dependent denition of habitat is required for the eective application of conservation science. More generally, they argued that the lack of precision and clarity in legal-scientic terminology causes short-term problems in decision-making but the real harm is done over the long term. For example, Camaclang et al. ( 2014) reviewed the last ten years practices in the identication of critical habitat for threatened species. They highlighted a mismatch between (1) the intent of critical habitat identication, which should rely on information on population viability and (2) its practice, where this information was used to identify critical habitat for only 1% of the species they reviewed. This mismatch may be partly due to conceptual ambiguity of the term. However, using context dependent denition for a concept as proposed by [START_REF] Murphy | Coping with uncertainty in wildlife biology[END_REF] can lead to the multiplicity of operational objects (e.g. typologies) and nally add to the confusion of terms.

A term used in such a variety of ways as to become meaningless is called a panchreston. This denition was applied to the concept of habitat fragmentation [START_REF] Bunnell | Let's kill a panchreston : giving fragmentation meaning[END_REF]. In an attempt to tackle this panchreston, [START_REF] Lindenmayer | Tackling the habitat fragmentation panchreston[END_REF] pointed to the ambiguous nature of the concept of habitat as one of the main issues for the denition of habitat fragmentation. They considered that the failure to specify a focus on a particular denition of habitat has created signicant problems. For instance, if patches of the so-called habitat are loosely dened, it may prevent the observation of expected patterns such as the decrease of species abundance or species richness 1 . Hence, they stressed the importance to stay with a species-centered denition of habitat after [START_REF] Hall | The Habitat Concept and a Plea for Standard Terminology[END_REF] and to discard the use of vegetation cover approaches to dene habitat. This distinction is crucial because for example some species can survive in modied landscapes even if there 1. Even if at intermediate levels, fragmentation can lead to increased species richness up to a point, see [START_REF] Duelli | Biodiversity evaluation in agricultural landscapes : An approach at two dierent scales[END_REF]; [START_REF] Fahrig | Functional landscape heterogeneity and animal biodiversity in agricultural landscapes[END_REF].

is a loss of native vegetation cover. These species are able to shift their requirements on resources located outside of their original occurrence area. In this case, restricting the habitat to native vegetation cover may thus lead to improper conclusions in case of a fragmentation analysis.

Finally, in species distribution and abundance modelling, there is also growing confusion about terminology, especially with concepts such as habitat suitability and habitat quality. For [START_REF] Hall | The Habitat Concept and a Plea for Standard Terminology[END_REF], the term habitat suitability should not be used because habitat is by denition suitable for a species (see above). Hence, an unsuitable habitat does not exist because it is the quality of the habitat that changes, not its suitability per se. However, habitat suitability is still largely used in the species distribution modelling literature mainly because habitat itself is poorly dened. For example, [START_REF] Hirzel | Habitat suitability modelling and niche theory[END_REF] wrote about an obvious relationship between niche theory and habitat suitability models. As they proposed an operational denition for the ecological niche that was the exact denition of habitat proposed by [START_REF] Hall | The Habitat Concept and a Plea for Standard Terminology[END_REF], they did not explain why they used habitat suitability to refer to species distribution modeling approaches.

These three examples of habitat-related terms consistently remain ambiguous. For each of them, one reason for this ambiguity was the poor denition of habitat. The aim of this article is not to provide a denitive denition of the habitat concept, which was attempted numerous times without success. Instead of trying to tackle the whole concept of habitat, it may be easier to start by redening related terms using the most recent scientic advances. It is the perspective chosen here, starting with the habitat quality concept.

Habitat quality, which perspectives for a key conservation concept ?

Habitat quality is still a concept that is plagued by the complex semantic of habitat.

For example, recent work on a Habitat Quality Index at the European level [START_REF] Vallecillo | A habitat quality indicator for common birds in Europe based on species distribution models[END_REF] relied on a synecological denition of habitat maintaining the ambiguity of the concept when this index is aimed at becoming a key operational tool for European conservation policies.

As proposed by [START_REF] Southwood | Habitat, the Templet for Ecological Strategies[END_REF], the easiest way to link habitat quality (the fact that habitat is intrinsically good for a species) with measurable parameters in a population of a species is to base measures on demography and population dynamics. However, choosing which measures of a population are relevant and useful to determine the quality of habitat is not easy [START_REF] Horne | Density as a Misleading Indicator of Habitat Quality[END_REF]. [START_REF] Matthiopoulos | Establishing the link between habitat selection and animal population dynamics[END_REF] presented a conceptual framework with more realistic connections between a population's use of space and its subsequent dynamics (and hence a contribution to the ongoing eorts to estimate a species' critical habitat and fundamental niche).

The recent study of [START_REF] Bean | Species distribution models of an endangered rodent oer conicting measures of habitat quality at multiple scales[END_REF] is focused on the relationship between habitat quality and habitat suitability in the sense of species distribution modeling. As mentioned above, the use of habitat suitability was questioned by [START_REF] Hall | The Habitat Concept and a Plea for Standard Terminology[END_REF], so that I prefer to use environmental suitability to describe the likelihood to observe a species in a site on the basis of environmental variables. Linking environmental suitability to demographic parameters is of key importance to improve our denition of habitat quality.

Habitat quality can only be dened on the basis of demographic parameters of indivi- This approach is of particular interest for the continuous model of landscape developed by [START_REF] Fischer | Beyond fragmentation : the continuum model for fauna research and conservation in human-modied landscapes[END_REF].

duals
These studies are the rst that really make an urgent and important move, which is key for conservation scientists to use species distribution modelling as proxy for habitat quality : link them with population dynamics [START_REF] Guisan | Predicting species distributions for conservation decisions[END_REF][START_REF] Wisz | The role of biotic interactions in shaping distributions and realised assemblages of species : implications for species distribution modelling[END_REF]. Habitat quality is still of major importance in conservation actions and conservation scientists should focus on a quality that is based on demographic parameters even if it demands a more powerful dataset than a quality assessed solely with species occurrence, abundance or density data. Environmental suitability can be a helpful tool for stakeholders to make choices, for example in sampling areas for inventories that are potentially suitable according to a species distribution modelling framework, but not known as a occurrence sites. If environmental suitability can go beyond and be more easily linked with demographic parameters, it will be a very powerful tool for conservation. To achieve this aim, population biologists and conservation scientists have to work together.

Final words

More broadly, the future of conservation science is challenging, torn between the ascertainment of biodiversity loss that urges conservation actors to actions and a certain blindness on the understanding of some of its scientic bases. The risk is that conservation becomes a giant with feet of clay, a science with a huge strike force but weak scientic bases, potentially leading to counter-productive eects such as a loss of credibility towards the main involved force in conservation : people.

Chapitre 3

Pollinisateurs et échelle spatiale : impact de la dénition de l'habitat et de sa mesure

Abstract

The eects of landscape on species or communities depend greatly on spatial scale.

Many studies have sought to assess the `characteristic scale of eect', the most appropriate spatial scale to study the relationship between landscape and ecological variables.

Because the true scale of interaction between species and landscape is never known, the reliability of estimation methods has to be evaluated indirectly, for example by comparing theoretical predictions related to expected characteristic scale patterns among species, landscape metrics or thematic resolutions with empirical observations, which is rarely done. Here, we applied the widely-used focal site multiscale study design to identify the characteristic scale of eect of landscape structures on species presence, using an original, nationwide dataset of ower-visitor arthropods in France. This method infers the spatial scale (buer size) at which the relationship between probability of species presence and landscape structure is the strongest. Characteristic scales of eect thus identied were compared across 42 arthropod species, four landscape typologies of land cover and a large set of landscape metrics, to analyze their consistencies. The method identied characteristic scales of eect for a large proportion of species and landscape metrics. Signicant dierences in characteristic scale were detected among species, landscape metrics and thematic resolutions used. However, overall the characteristic scale of landscape eects was highly unstable, both within and among species and landscape metrics. This result was true regardless of the thematic resolution of the typology. Our results suggest that the outcome of the focal site multiscale study framework cannot be easily interpreted and that the method validates little of the expected theoretical patterns. This questions the relevance of the method to identify the spatial scale of species-landscape relationships as well as our ability to use correlative approaches to evaluate the spatial scale of perception and interaction of species with the landscape.

Introduction

A large part of ecological research aims at understanding the determinants of species distribution. The succession of environmental lters and particularly those related to landscape (i.e. how a species can move through the landscape to reach suitable habitat patches) are believed to be a major proximal mechanism [START_REF] Kraft | Community assembly, coexistence and the environmental ltering metaphor[END_REF]. Because no experimental manipulation is possible at large scale, environmental lters are often explored through correlative approaches on the basis of observational data. Hence numerous studies focus on the neighboring landscape to demonstrate its importance as a predictor of species presence and abundance at a particular site [START_REF] Mazerolle | Patch characteristics and landscape context as predictors of species presence and abundance : A review[END_REF]. In these studies, it has been repeatedly found that the relationship between an ecological variable (e.g. species abundance or abundance) and landscape metrics, i.e. quantitative descriptors of landscape composition (e.g. proportion, richness or diversity) and conguration (e.g. patch shape, edge length or isolation ; [START_REF] Gustafson | Quantifying Landscape Spatial Pattern : What Is the State of the Art ?[END_REF], depends greatly on the spatial scale at which these metrics are measured [START_REF] Wiens | Spatial Scaling in Ecology[END_REF][START_REF] Turner | Eects of changing spatial scale on the analysis of landscape pattern[END_REF][START_REF] Miguet | What determines the spatial extent of landscape eects on species ?[END_REF].

Multiscale analyses have developed rapidly over the last decades to address such spatial scale issues in ecology, including the eect of grain, extent or resolution on landscape metrics [START_REF] Wiens | Spatial Scaling in Ecology[END_REF][START_REF] Wu | Eects of changing scale on landscape pattern analysis : scaling relations[END_REF][START_REF] Lechner | Recent Progress on Spatial and Thematic Resolution in Landscape Ecology[END_REF]. With respect to spatial extent, the focal site multiscale study design [START_REF] Brennan | Focal patch landscape studies for wildlife management : Optimizing sampling eort across scales[END_REF] is a widespread method to identify the so-called characteristic scale of eect of landscape metrics on an ecological variable [START_REF] Jackson | What size is a biologically relevant landscape ?[END_REF]. Landscape metrics are measured within a buer around observation sites and spatial scale is dened as the radius of such buer. The aim of this method is to infer the spatial scale at which the relationship between an ecological variable of a focal site and a landscape metric (e.g. percentage of forest area) is the strongest. This `characteristic' scale is often interpreted as the scale at which a given species perceives and interacts with the landscape [START_REF] Miguet | What determines the spatial extent of landscape eects on species ?[END_REF]. The identity of the landscape metric correlating with species distribution is thought to be informative on which landscape features are the most important drivers. However, landscape and species distribution can be so complex that any correlation between a given pair of landscape metric and species distribution can always receive an ad hoc explanation, while our ability to make a priori prediction is low. There is thus a strong need for a posteriori validation of correlative methods such as the focal site multiscale study design.

Because the true characteristic scale of interaction between species and landscape is never known, the reliability of the focal site multiscale study design method has to be assessed indirectly. For example, [START_REF] Jackson | Are ecologists conducting research at the optimal scale ?[END_REF] analyzed, in a literature review, the distribution of characteristic scales of eect obtained using the focal site multiscale study design method and showed that the largest and smallest scales evaluated in studies are more often the best predictors of the inferred characteristic scale than expected by chance. They concluded that many ecologists therefore seem to not conduct their study at the optimal characteristic scale. Alternatively, [START_REF] Miguet | What determines the spatial extent of landscape eects on species ?[END_REF] outlined several methodological issues that can, in principle, inuence estimates of the scale of eect, such as resolution of landscape data or correlation of landscape metrics among spatial scales.

The choice of a landscape thematic resolution is one such major methodological issue with the focal site multiscale study design, which may aect the strength of the observed correlation between landscape metrics and ecological variables, but this source of variability is rarely assessed [START_REF] Bailey | The inuence of thematic resolution on metric selection for biodiversity monitoring in agricultural landscapes[END_REF][START_REF] Lechner | Recent Progress on Spatial and Thematic Resolution in Landscape Ecology[END_REF]. Although landscape units should be dened on the basis of their potential usage by the species or ecological community under study, data availability is often the main driver of choice for landscape ecologists. Land use maps are among the most used because remote sensing and machine learning methods make them widely available [START_REF] Verburg | Challenges in using land use and land cover data for global change studies[END_REF]. In addition, a common practice in ecology is to redene the thematic resolution of land use to improve its ecological meaning with respect to the study species or community (e.g. merging all forest types into a single type named forest). When working at a large scale, most scientists match the thematic resolution with the spatial resolution, decreasing the available thematic resolution to assess correlation between landscape metrics and their ecological system. In this way, they also reduce the number of landscape units facilitating subsequent statistical analyses. Consequently, a same raw thematic resolution can be used to describe a same landscape but with dierent landscape units depending for example on the spatial resolution (e.g. minimum patch size). [START_REF] Miguet | What determines the spatial extent of landscape eects on species ?[END_REF] predict that a coarse thematic resolution should lead to relatively less accurate landscape metrics at small vs. large scales, leading to an overestimation of the characteristic scale, but there is no proper empirical assessment of this potential bias so far.

A complementary approach to assess the consistency of estimates of the characteristic scale is to infer the characteristic scale over a large number of species or landscape metrics and to compare the patterns observed with theoretical expectations. [START_REF] Miguet | What determines the spatial extent of landscape eects on species ?[END_REF] compiled such predictions put forward in studies using the focal site multiscale study design. They concluded that species traits and landscape metrics were among the most important ecological factors likely to control the scale of eect. Regarding species traits, several predictions can be made on purely theoretical grounds. In particular, Miguet et al.

(2016) expect broader scales of eects with larger species mobility. The latter can be assessed using body size or dispersal distance. Despite an important corpus of studies about ecological traits relationships with scale of eect, there is still weak empirical support for these predictions and contradictory results across studies [START_REF] Jackson | Are ecologists conducting research at the optimal scale ?[END_REF], especially for species-centered approaches.

In contrast to species traits, there is little theory regarding the inuence of landscape metrics on the scale of eect, such that most predictions are purely empirical. A number of empirical studies showed that the characteristic scale of eect may depend on which landscape metrics is used and cannot be readily transferred to other metrics or other thematic resolutions. For example, Schindler et al. ( 2013), comparing 52 metrics and their relation with species richness of dierent taxonomic groups, found that no landscape variable was consistently signicant across all spatial scales. A question that deserves attention is whether some patterns can be found despite the strong variability in characteristic scale across metrics. Landscape metrics can be classied as composition vs. conguration variables, but also as structural (without explicit reference to ecological processes) vs.

functional (e.g. connectivity) metrics [START_REF] Mcgarigal | FRAGSTATS v4 : Spatial Pattern Analysis Program for Categorical and Continuous Maps[END_REF]. If species interact with the landscape at a given (characteristic) scale, it seems reasonable to expect that this scale is more consistent among metrics with a type (e.g. composition) than between types (e.g. composition and conguration). For instance, Duren et al. (2011) showed that northern bobwhite (Colinus virginianus) presence was aected by composition metrics within a 1km radius, whereas conguration metrics aected the species at larger scale. However, to our knowledge, there is no proper meta-analysis of the literature that compiled the consistency of spatial scale of species-landscape relationships among landscape metrics types.

Here, we estimate and analyze the consistency of characteristic spatial scales of the relationship between landscape metrics and the probability of presence of numerous species of ower-dwelling arthropods, in an attempt to assess the validity of the focal site multiscale study design to inform on true characteristic scales. We specically address the following questions : (1) does characteristic scale depend on species identity and landscape variable in a way consistent with predictions by Miguet et al. ( 2016) ? (2) Does the choice of a thematic resolution inuence the inferred characteristic scale ? We focused on pollinators because they dier greatly in their ecological traits, particularly dispersal ability, such that we may expect a broad range of characteristic scales of eect, yet with similarities for ecologically close species as observations are due to similar ecological interactions with their environment (e.g. species are observed on owers because they usually feed on owers). Also, characteristic scales of eect of landscape metrics are poorly studied for this group, although landscape context is known to be an important driver of insect distribution (Stean-Dewenter et al., 2002;[START_REF] Patrício-Roberto | Aspects of Landscape and PollinatorsWhat is Important to Bee Conservation ?[END_REF][START_REF] Senapathi | The impact of over 80 years of land cover changes on bee and wasp pollinator communities in England[END_REF]. For example, [START_REF] Rossi | Towards indicators of buttery biodiversity based on a multiscale landscape description[END_REF] focused the relationship between buttery species richness and a variety of metrics reecting both landscape conguration and composition. In this community approach, they found that the correlation between landscape metrics and species richness varied greatly with buer size, which was attributed to the diversity of processes shaping species-landscape relationships.

We used the focal site multiscale study design to assess the characteristic scale of landscape eect on predicting species presence/absence, across multiple species, landscape thematic resolutions and metrics. We then compared the patterns in inferred characteristic scale with the following predictions : (i) the characteristic scale varies systematically across species, such that species identity explains an appreciable part of the observed variation in characteristic scale. In addition, this variability is shaped by ecological characteristics of species. In particular, species from the same taxonomic group are expected to share common biological traits and should have systematic similar pattern of spatial scale response across dierent metrics of the landscape ; (ii) the characteristic scale also varies consistently across landscape metrics. In particular, we expect to nd systematic dierences in characteristic scale for composition vs. conguration metrics ; (iii) a coarse thematic resolution yields a systematic overestimation of the characteristic scale of eect [START_REF] Miguet | What determines the spatial extent of landscape eects on species ?[END_REF].

Methods

Sampling protocol and data All biological records come from the French citizen science program Spipoll, a nationwide survey of ower-visitors using a standardized observation protocol. This database is unique in providing assemblages of a wide range of species sampled with the same standardized protocol over thousands of geo-localized sampling points, thereby oering an ideal dataset for our purpose. The protocol consists in compiling a photographic collection of ower-visiting invertebrates interacting with a plant species at a given place and for a given duration (see [START_REF] Deguines | The Whereabouts of Flower Visitors : Contrasting Land-Use Preferences Revealed by a Country-Wide Survey Based on Citizen Science[END_REF] for details). The dataset covers ve years (2010-2014) and represents a total of 12,272 picture collections, i.e. 12,272 sites distributed across France (appendix 1). Observation duration is variable among samples, due to the existence of two protocols : observers take pictures of all ower-visitors feeding or landing on the owers either during 20-minutes (8,603 sites)

or over a longer but recorded duration (3,669 sites). Many taxa observed in Spipoll cannot be identied to species level on the basis of pictures and are described as morphospecies.

Hence, we selected a subset of 42 taxa (appendix 2) that were both identied to species level and frequent enough (at least 100 observations). They include Lepidoptera ( 14), Hymenoptera (9), Diptera (9), Coleoptera (7), Hemiptera (2) and Araneidae (1). Statistical analysis For each species, generalized linear models (GLM) with a binomial error and a logit-link function were used to analyze the relationship between presenceabsence of species and landscape explanatory variables. First, a model was built using the following independent variables : (1) latitude to account for a possible northing eect on species distribution, (2) total precipitation and (3) minimum temperature on the day of (4) observation date (day of the year), ( 5) quadratic observation date to account for ower visitors phenology, and (6) duration of data collection to take account of sampling eort.

Climate data were obtained from the ECA&D project (www.ecad.eu, [START_REF] Haylock | A European daily high-resolution gridded data set of surface temperature and precipitation for 19502006[END_REF] where daily minimum temperature and precipitation data are available throughout the sampling period at a resolution of 0.25 degree on a regular grid.

Then, a landscape metric was added to the model and the Akaike Information Criterion (AIC) was calculated, and this was repeated for each landscape thematic resolution (i.e. four dierent resolutions), each landscape metric (17 metrics, or more depending on the thematic resolution considered) and each buer size (13 radii from 150 to 5000 m).

For a given metric and thematic resolution, the 13 model AICs (one for each buer size)

were compared. To assess whether the relationship between presence/absence and a given landscape variable depended on spatial scale, we examined the relationship between AIC values and buer size (Figure 3.1). If all AIC values were similar (∆AIC < 5, Figure 3.1a), models were considered similar regardless of the buer size used to calculate the landscape index. In this case, we concluded that this species did not have a characteristic scale of eect for this landscape metric. If AIC values diered by more than 5, the observed characteristic scale of response to landscape was inferred from the model with the minimum value of AIC (Figure 3.1b). When the minimum AIC value was observed at 150 m, the species was concluded to be inuenced by landscape at a local scale (< 150 m). In contrast, when the observed characteristic scale was 5,000 m, the true characteristic scale of eect is less easily dened, because it could be much broader than 5,000 m [START_REF] Jackson | Are ecologists conducting research at the optimal scale ?[END_REF]. To deal with this issue, results were analyzed with and without observed characteristic scales of 5,000 m.

Explanatory power of models at the observed characteristic scale of eect were evaluated using McFadden's pseudo-R

2 : 1 -(ResidualDeviance/N ullDeviance) ; [START_REF] Faraway | Extending the Linear Model with R : Generalized Linear, Mixed Eects and Nonparametric Regression Models[END_REF]. To test the reliability of observed patterns, we selected among the models with a characteristic scale of eects, the 50% models with highest pseudo-R 2 for the landscape metric. Results obtained with this subset of models were compared to results from the entire dataset. We also compared the characteristic scales of eect with those obtained when species were randomly distributed across sites, while maintaining their number of occurrences constant. Finally, we veried the absence of spatial autocorrelation on the residuals of these models using Moran's I index and correlograms.

We nally analyzed the dataset consisting of all characteristic scales observed across all 42 species and all 17 landscape metrics (or more depending on the thematic resolution considered), for each of the four thematic resolutions of land cover. To assess the consistency of species-landscape relationships, an analysis of variance (ANOVA) was performed on characteristic scale, with species and landscape metrics as factorial explanatory variables. Post-hoc Tukey Honest Signicant Dierences (HSD) test was used to explore the true dierence between species and between landscape metrics. ANOVA and post-hoc Tukey HSD tests were used to assess systematic dierences of observed characteristic scales among the four most represented taxonomic groups (i.e. Lepidoptera, Hymenoptera, Diptera and Coleoptera) and a miscellaneous group combining the two last taxonomic groups with few species each (Hemiptera and Araneidae). Under the assumption of niche conservation stating that species within a taxonomic group are more likely to share similar ecological traits [START_REF] Webb | Phylogenies and Community Ecology[END_REF], we expected signicant dierences in characteristic scale among taxonomic groups. The same analysis was performed to test dierences in The main results are presented only for the lowest thematic resolution with three land cover classes : urban, natural and agricultural land cover and the corresponding 17 landscape metrics. Complete results on ner thematic resolutions CLC than the previous are qualitatively similar and are generally not shown (but see appendix 4 and 5). To assess the eect of thematic resolutions on characteristic landscape scale, we performed an ANOVA on characteristic scale, pooling all 42 species and the 7 metrics that were dened across all thematic resolutions (Table 3.1). We also illustrated how landscape thematic resolution inuenced the characteristic scale of eect by examining the distribution of absolute values of the dierence in characteristic scales between pairs of thematic resolution.

Results

Across all species and landscape metrics, 714 models were tted on all spatial scales studied. Three quarters showed a characteristic scale of eect (e.g. 3.1b and c), i.e. there was enough variation in AIC values to identify the minimum across scales. McFadden's pseudo-R 2 of full models at the observed characteristic scale ranged from 1.36 % for Apis mellifera and the connectance index (CONNECT) to 31.04% for Colletes hederae and the connectance index of natural landscape class (CONNECT.nat). In comparison, only 17% of models using a random distribution of species showed a characteristic scale of eect and pseudo-R 2 of those models ranged between 0.01 and 1.46%. Also, results obtained from the 50% subset of species with models exhibiting the highest pseudo-R 2 were consistent with the entire dataset (see appendix 4). Therefore, subsequent results are presented for the entire dataset.

Across species, the number of landscape metrics with an observed characteristic scales ranged from 4 (26 %) for Vanessa atalanta to 17 (100 %) for Sphaerophoria scripta (Figure 3.2 and see appendix 5 for raw data). Signicant dierences in characteristic scale were detected among species (ANOVA, p.value < 0.001). For example, Anthophora plumipes and Pyrrhocoris campestris appeared to respond mainly to local scales (median = 250 m) while Aglais io mainly responded to large scales (median = 5,000 m), but this was the only signicant dierence between species as identied by a post-hoc Tukey HSD test.

Overall, the observed characteristic scale was highly variable within species, most of which exhibited a large range of variation of the characteristic scale across landscape metrics from local (< 150 m) to the maximum scale evaluated in our framework (i.e. 5,000 m, Figure 3.2). Even Vanessa atalanta, with only four observed characteristic scales, responded from local to large scales ; the same was true for Sphaerophoria scripta with observed characteristic scales for all metrics. Consistent with this large within-species variation, no eect of taxonomic group on observed characteristic scale was found (ANOVA, p.value > 0.1).

Similarly, across landscape metrics (Figure 3. nearest-neighbor distance metric of urban landscape class (ENN_CV.urban) aected species at larger scale (median = 3,500 m). However, here again this example was the only signicant dierence between metrics (post-hoc Tukey HSD test). Most landscape metrics exhibited a large range of variation of the characteristic scale across species with observed characteristic scales for each metric that ranged from 150 m to 5,000 m (Figure 3.3).

However, signicant dierences in characteristic scale were found between the three metrics types (ANOVA, p.value < 0.001, see appendix 6 for detailed statistics). A post-hoc Tukey HSD test revealed that the average characteristic scale was signicantly lower for Some inferred characteristic scales laid at one of the boundaries of the range of buer sizes, with 6% of observed characteristic scales at 150 m and 12% at 5,000 m (to be compared to an average of 6 ± 2% across all buer sizes). Despite the higher frequency of observed characteristic scales at the upper boundary, removing the observed scales of 5,000 m did not inuence the main patterns of results. In particular there was still a signicant eect of species and landscape variables on the observed characteristic scale (ANOVA test, p.value < 0.001). Post-hoc Tukey HSD tests did show signicant dierences between more pairs of species (n = 3) and landscape metrics (n = 7) than when the 5,000 m characteristic scale was included. However, the large variation in characteristic scale both within species and within metrics was still present.

Discussion

Using the standard focal site multiscale study framework to identify the spatial scale of species-landscape relationships, we show on a non-simulated dataset that patterns of characteristic scales of landscape eect do not follow any of the expected consistent patterns theoretically predicted, such as similar characteristic scales in closely ecological related species. Instead, the characteristic scale of landscape eect was highly variable, both within and among species and landscape metrics. This result is true regardless of the thematic resolution. We argue that two main hypotheses may explain such inconsistency :

(i) the focal site multiscale study framework fails to characterize the spatial scale of species-landscape relationships or (ii) species-landscape relationships are too complex and context-dependent to be amenable to generalizations. Either way, our results suggest that the interpretation of results obtained with the focal site multiscale study framework is highly problematic. Below we discuss all the expected patterns rejected by our results and the possible sources of such variability in characteristic scales, starting with the species level and its consequences for landscape ecology studies. Then, we focus on the impact of landscape metrics and thematic resolution on the observed characteristic spatial scale.

Predictions about what determines the spatial extent of landscape eect on species are numerous but there is little evidence to support them [START_REF] Miguet | What determines the spatial extent of landscape eects on species ?[END_REF]. For example, [START_REF] Jackson | Are ecologists conducting research at the optimal scale ?[END_REF] expected that characteristic scale of eect should vary among taxonomic groups. Our observation of a signicant, but small, species eect on observed characteristic scale partly supports this prediction : some species appeared to respond to landscape metrics at a ner scale than others and the number of landscape metrics with a characteristic scale varied greatly across species. These dierences among species could be explained in part by species ecology and traits inuencing their relationship to landscape metrics. Some lines of theoretical evidence suggest that the scale of eect is principally a function of species traits such as mobility [START_REF] Jackson | What size is a biologically relevant landscape ?[END_REF]. Holland et al.

(2005) found that the scale of beetle species response to landscape was positively related with body size. In a community approach, Schindler et al. (2013) showed that the species richness of dierent taxonomic groups responded at dierent scales across a large pool of landscape metrics. They concluded that the main reasons for the poor performance of landscape metrics as indicators for small terrestrial birds across all spatial scales can be their high mobility. Here, we used taxonomic order as a proxy for ecological similarity, with the assumption of niche conservatism which states that closely related species tend to be ecologically similar in many respects [START_REF] Wiens | Niche conservatism as an emerging principle in ecology and conservation biology[END_REF][START_REF] Peterson | Ecological niche conservatism : a time-structured review of evidence[END_REF]. Our analyses revealed no signicant dierence between taxonomic orders, suggesting either that species ecology is a poor indicator of characteristic scale of response to landscape metrics or that our assumption of niche conservatism is unwarranted. The latter can

unfortunately not be veried for insect pollinators, for which information on dispersal abilities or other traits involved in species-landscape relationship are scarce. Regardless, species with similar, large body size such as Vespa sp., Xylocopa violaceae and Bombus pascuorum all belonging to Hymenoptera responded on average at large, medium and ne scales, respectively. Similarly, Lepidoptera species, the most represented taxonomic order analyzed in our study, all share common ecological traits but are clearly spread from ne to large scales in their responses to landscape. Besides, we cannot lean on other empirical studies testing the relation between traits and spatial scales of eect on arthropods, which are rare as shown by the brief review of [START_REF] Jackson | Are ecologists conducting research at the optimal scale ?[END_REF] uncovering a single study that was not focused on birds or mammals.

The large variation in characteristic scales of eect across landscape metrics within a species may be due to several caveats of our approach. First, regional context can be an important factor driving spatial scale of species-landscape relationships [START_REF] Miguet | What determines the spatial extent of landscape eects on species ?[END_REF]. Our data encompass many dierent regional contexts thanks to the citizen science program used, which provides a unique opportunity to analyze species-landscape relationship at a national level. Species traits and landscape context can vary among regions, contributing to the observed variation in our characteristic scale of response [START_REF] Miguet | What determines the spatial extent of landscape eects on species ?[END_REF]. It is also possible that our study framework does not encircle the relevant scale, as shown by [START_REF] Jackson | Are ecologists conducting research at the optimal scale ?[END_REF] in other studies. However, the range of spatial scales was chosen to cover arthropod relationships with landscape on the basis of the limited existing ecological knowledge, especially for small species (Stean-Dewenter et al., 2002). The smallest and largest scale evaluated here represent a low proportion of all observed spatial scales and are thus unlikely to bias strongly the identication of characteristic scales of eect as highlighted by [START_REF] Jackson | Are ecologists conducting research at the optimal scale ?[END_REF]. Finally, one can argue that, due to our data sampling, the distribution modelling fails to infer the true distribution of species and only examines species detectability, with a possible inuence on estimation of characteristic scales. Here, we expect a monotonous relationship between the probability of species detection and species abundance, the latter being variable across dierent landscapes. However this issue is only problematic when species are absent from a large part of the considered distribution due to dierent biogeographical constraints for instance. In our case, all 42 taxa are common across France and widely distributed across landscapes. Therefore, this bias can be considered negligible and not related to the assessment of the characteristic scale of specie-landscape relationships. Regardless of the underlying mechanisms, the general inconsistency in the scale of species response to landscape has important implications because it can also lead to conduct research at the wrong spatial scale. This is particularly true with community-based analyses, which often use a single characteristic scale of eect to investigate communities composed of multiple dierent species [START_REF] Rossi | Towards indicators of buttery biodiversity based on a multiscale landscape description[END_REF][START_REF] Schindler | Multiscale performance of landscape metrics as indicators of species richness of plants, insects and vertebrates[END_REF], although each is likely to respond at a dierent spatial scale.

Beyond the large variation in characteristic scale of eect across species, signicant differences are also observed among landscape metrics and types of landscape metrics, which can have major consequences for the choice of relevant metrics. Previous studies exploring spatial scale association between landscape metrics and species mainly described the landscape with a single metric (e.g. habitat amount). We perform our analysis using numerous landscape metrics, grouped into three main types (composition, conguration and functional metrics) because the complexity of species relations with landscape can generally not be encapsulated in a single metric. Targeting dierent landscape metrics underlies dierent questions related to dierent species traits, with potentially dierent scales of response, such that the spatial scale at which a species perceive landscape composition or spatial conguration can be dierent [START_REF] Duren | An improved multiscale approach to modeling habitat occupancy of northern bobwhite[END_REF]. For example, species of butteries with high sensitivity to urbanization exhibit a ne-scale of response to proportion of urban land cover [START_REF] Bergerot | Landscape variables impact the structure and composition of buttery assemblages along an urbanization gradient[END_REF] while having high dispersal abilities and therefore responding at larger scales for functional metrics such as connectivity than for composition metrics related to urban cover. Our observation of signicant lower characteristic scales for composition metrics than for conguration or functional metrics partly supports this hypothesis. However, the eect remains small due to the large variability observed in spatial scale among landscape metrics. Therefore, the expected pattern that should display a reasonable consistency in spatial scale among types of landscape metrics cannot be veried. These results highlight that even if you are looking to similar based landscape metrics, they could respond to highly variable spatial scale. Also, our results show that dierent metrics should not be used together in a modelling approach with a single specic spatial scale. This is consistent with previous results, for example by Ordóñez-Gómez et al. (2015), who used four dierent metrics in relation to diet and behavior of spider monkeys. They concluded that the scale of eect cannot be generalized to all ecological variables and to all predictors. Similarly, Schindler et al. ( 2013) also found that that no landscape variable was constantly signicant across all landscape scales. Finally, Rossi et van Halder (2010) used multiple landscape metrics and showed that the level of metrics correlation with buttery diversity varied greatly across spatial scales.

Finally, the inferred characteristic scale of eect was slightly aected on average by the dierent landscape thematic resolutions used with higher spatial scales on average for the coarse thematic resolution, but no systematic change in spatial scale at ner resolutions.

In addition, the eect of thematic resolution is small implying that a coarse thematic resolution does not necessarily lead to a systematic overestimation of the characteristic scale of eect, rejecting the prediction of [START_REF] Miguet | What determines the spatial extent of landscape eects on species ?[END_REF]. Increasing the thematic resolution modies landscape metrics (e.g. increasing Shannon diversity), which should improve the description of species-landscape relationships for species with specic habitat requirements that can be masked with a coarse thematic resolution. For example, Holland et al. (2005) noted that if the denition of landscape units (habitat) in a thematic resolution is not suciently meaningful for the species under consideration, the relationship between the species and the landscape metric can be weak. However, our results suggest that using a complex thematic resolution of a land cover dataset is not a way to overcome this situation. This is consistent with the study of [START_REF] Bailey | The inuence of thematic resolution on metric selection for biodiversity monitoring in agricultural landscapes[END_REF], who found that an intermediate thematic resolution appeared the most promising for biodiversity monitoring and that using detailed thematic resolutions did not improve the correlation between biodiversity data and landscape metrics. Therefore, instead of trying to decrease or increase a thematic resolution, it would be better to look into dierent sources of data (e.g. raw remote sensing dataset and their associated texture measures, (St-Louis et al., 2014) to test the impact of landscape description in scale-dependent species-landscape relationships more in depth. In our study, even if CLC is one of the best trade-os between data availability and resolution in Europe, this land cover dataset shows some limitations in representing accurately the mosaic of species habitat units.

Species-landscape relationships are complex. This statement is not new and can be viewed as an advantage, in the sense that any scale-dependent species-landscape relationship can receive an ad-hoc explanation. However, such complexity and variability should also be considered a major diculty that impedes our understanding of the importance of spatial scale. When analyzing the spatial scale of species-landscape relationships, we often have no other way but to trust the results produced by whichever method was used to identify the relevant spatial scale. Our results suggest using caution when interpreting the results of the focal site multiscale study framework, which may be misleading in evaluating the scale of such relationships. To overcome this situation, one advice would be to assess independently the spatial scale of eect of all landscape metrics used in the modelling of a particular ecological variable (e.g. species abundance or presence-absence).

It also seems important to partition communities into species to ensure that the scales of species response to landscape are consistent across species of the community and therefore that the scale of landscape eect at the whole community level is not driven by one or few species. However, the large variability in characteristic scales observed in the present study questions our aptitude to evaluate the spatial scale of species-landscape relationships and especially, the relevance of the focal site multiscale method. Each species appears to have its own spatial scale of perception of the description of landscape that we use as scientists (i.e. through metrics and thematic resolutions) and it seems that we do not have an accurate way to assess it yet. Undoubtedly, identifying the characteristic spatial scale of eect remains a central issue in landscape ecology and we need to challenge the way we think about species-landscape relationships. Signicant dierences in characteristic scale were detected between species (ANOVA, p.value < 0.001) and also between taxonomic orders (ANOVA, p.value < 0.05). terogeneity has shaped the evolution of species specialization [START_REF] Débarre | Evolution of specialization in a spatially continuous environment[END_REF][START_REF] Holt | Conservation implications of niche conservatism and evolution in heterogeneous environments[END_REF][START_REF] Ravigné | Live Where You Thrive : Joint Evolution of Habitat Choice and Local Adaptation Facilitates Specialization and Promotes Diversity[END_REF], dened as the (restricted) ecological niche breadth of a species [START_REF] Futuyma | The Evolution of Ecological Specialization[END_REF][START_REF] Devictor | Dening and measuring ecological specialization[END_REF]. Generalist species, which have broader niches than specialist species, are considered to be more adapted than specialist species to persist in heterogeneous landscapes [START_REF] Teyssèdre | Contrasting eects of habitat reduction, conversion and alteration on neutral and non neutral biological communities[END_REF][START_REF] Devictor | Dening and measuring ecological specialization[END_REF].

In addition to the classical specialist/generalist dichotomy, several species may also have evolved to specialize on heterogeneous environmental conditions when heterogeneity does not involve too many dierent resources [START_REF] Fahrig | Functional landscape heterogeneity and animal biodiversity in agricultural landscapes[END_REF]. This type of specialization is illustrated for example by the landscape complementation hypothesis [START_REF] Brotons | Eect of adjacent agricultural habitat on the distribution of passerines in natural grasslands[END_REF], which states that a species may require a number of complementary resources located in dierent landscape units. Therefore the combined presence of these landscape units is mandatory for the species to persist [START_REF] Dunning | Ecological processes that aect populations in complex landscapes[END_REF]. Such complementing species, because they are specialized on particular resources, should outcompete generalist species with broader niches [START_REF] Büchi | Coexistence of Specialist and Generalist Species Is Shaped by Dispersal and Environmental Factors[END_REF]. As a result, generalist species should display lower abundances in heterogeneous landscapes and complementing species can be considered specialists of heterogeneous landscapes. This specialization may be due to complex life cycles, with dierent niche requirements for dierent life stages such as hemimetabolous insects or amphibians [START_REF] Pope | Landscape Complementation and Metapopulation Eects on Leopard Frog Populations[END_REF], but can also result from an adaptation to rapid current anthropogenic landscape changes [START_REF] Barnagaud | When species become generalists : on-going large-scale changes in bird habitat specialization[END_REF].

Anthropogenic landscape alteration is the main factor of biodiversity loss, particularly via the destruction and fragmentation of natural habitats [START_REF] Newbold | Global eects of land use on local terrestrial biodiversity[END_REF].

As a consequence, species are more and more likely to encounter heterogeneous landscapes. This increased landscape heterogeneity is associated with profound changes in the structure of ecological communities [START_REF] Fahrig | Functional landscape heterogeneity and animal biodiversity in agricultural landscapes[END_REF]. A large corpus of studies particularly demonstrates that biodiversity is facing widespread functional homogenization with more abundant generalist species and a general loss of specialist species [START_REF] Clavel | Worldwide decline of specialist species : toward a global functional homogenization ?[END_REF][START_REF] Kerbiriou | More species, fewer specialists : 100 years of changes in community composition in an island biogeographical study[END_REF]. Although landscape heterogeneity tends to modify species communities, its recent expansion may also oer new opportunities for species.

Species previously adapted to heterogeneous conditions such as complementing species may benet from increased landscape heterogeneity and expand their range or abundances [START_REF] Fahrig | Functional landscape heterogeneity and animal biodiversity in agricultural landscapes[END_REF]. Alternatively, they may evolve de novo from generalist species or species specialized on homogeneous landscapes. However, the presence and distribution of complementing species in heterogeneous landscapes has received little attention so far (but see e.g. [START_REF] Dulaurent | A case of habitat complementation in forest pests : Pine processionary moth pupae survive better in open areas[END_REF][START_REF] Mueller | Scale-sensitive landscape complementation determines habitat suitability for a territorial generalist[END_REF][START_REF] Ouin | Complementation/supplementation of resources for butteries in agricultural landscapes[END_REF].

Species can be classied continuously as more or less generalist (i.e. niche width) on the basis of the coecient of variation of species densities among categorical landscape units [START_REF] Julliard | Spatial segregation of specialists and generalists in bird communities[END_REF]. Additional information is needed to characterize their preferences along an environmental gradient (i.e. niche position), which requires a continuous representation of landscapes [START_REF] Clavero | Functional homogenization of bird communities along habitat gradients : accounting for niche multidimensionality[END_REF]. For example, niche position can be assessed by examining the relationship between species abundances and the environmental gradient, as the part of the gradient where abundance is maximal. The aim of the study is to analyze the relationship between bird specialization and their niche preference along a continuous heterogeneous environmental gradient. On a nationwide breeding bird dataset and using remote sensing vegetation cover as a proxy for continuous environmental gradient, we calculate species specialization index and species preferences along the gradient (i.e. their niche positions). We test the following expectations : (i) species with a monotonous relationship between abundance and environmental gradient should exhibit high levels of specialization ; (ii) according to the landscape complementation hypothesis, some species displaying an intermediate niche position in the environmental gradient may exhibit high levels of specialization ; (iii) the resulting relationship between specialization level and niche position should thus be at, with generalist and specialist species spread along the environmental gradient.

Methods

Bird data We used data from the French Breeding Bird Survey (BBS), a standardized monitoring scheme in which skilled volunteer ornithologists identify breeding birds by song or visual contact [START_REF] Julliard | Un suivi intégré des populations d'oiseaux communs en France[END_REF]. Twice a year in spring, each observer prospects 10 evenly distributed points within a 2x2 km plot, randomly selected within 10km of the observer location. Each visit lasts 5 minutes, during which all individuals seen or heard within a distance of 100 m are identied to species level and recorded. Point counts are located 300 m apart and sampled in the same order. Out of the full database from 2001 to 2014, the ca. 10,000 point counts (hereafter sites) with four consecutive years of sampling were retained. We focused on relatively common species only, observed in 200 sites or more across France, i.e. with enough data for meaningful statistical analyses. Also, species restricted to wetlands or species that spend most of their active time airborne (e.g. raptor, swifts) were removed, because the BBS protocol is not designed for such species and because we were interested in investigating local scale species-landscape relationships.

This selection resulted in a set of 82 species (appendix A). For each species, abundance was measured as the average, over the four years, of the sum of counts over the two annual visits. In Europe, where landscapes are predominantly shaped by human activities, the heterogeneous environmental gradient ranges from open semi-natural landscapes to mature forests [START_REF] Vera | Grazing ecology and forest history[END_REF]. The environmental gradient was therefore chosen to contrast woody vegetation, measured as percent tree cover (PTC) vs. treeless vegetation (low PTC values).

Landscape variables

The latter was obtained by merging the two remaining land cover types : herbaceous and woodland-shrub vegetation and bare ground. All VCF pixels intersecting with a buer were used (up to four) and averaged when there was more than one value. To check that the spatial resolution of the VCF dataset (250m) did not bias the PTC measurement, we compared the latter to PTC values obtained with two other remote sensing datasets that have similar land cover types but ner spatial resolution : High Resolution Layer (20m ; [START_REF] Langanke | GIO land (GMES/Copernicus initial operations land) High Resolution Layers (HRLs) summary of product specications[END_REF] and LandSat (30m ; [START_REF] Sexton | Global, 30-m resolution continuous elds of tree cover : Landsat-based rescaling of MODIS vegetation continuous elds with lidar-based estimates of error[END_REF]. All PTC values were highly correlated (r > 0.85, see appendix B). The VCF dataset was preferred because it is updated annually, such that bird and vegetation data could be matched temporally :

the PTC value for each site was the average over the four years of bird census.

Second, we discarded all sites in which the VCF pixel values were unlikely to reect vegetation cover. This includes (i) sites located near water (in which case no VCF value was available) and (ii) urban sites, where the bare ground class is most likely built and hence never vegetated, as opposed to agricultural areas where bare ground is generally temporary. The CORINE Land Cover (CLC) dataset [START_REF] Bossard | CORINE Land Cover[END_REF] Statistical analysis First, we analyzed the non-linear relationship between the abundance of each species and the PTC gradient to nd their optimum values. Generalized linear models (GLM) with a Poisson error distribution and a log link function were used for each species, with species abundance (S) as the dependent variable and a linear and quadratic term for PTC as explanatory numerical variables. It is largely acknowledged that species abundance is inuenced by climate [START_REF] Howard | The drivers of avian abundance : patterns in the relative importance of climate and land use[END_REF], so we also included climatic region (CLIM_REG) as a categorical explanatory variable, using the breakdown of France into eight climatic regions from Joly et al. (2010). The xed eect structure of our model for each site i was thus :

S i = αP T C i + βP T C 2 i + CLIM REG i (1)
To estimate the optimum value of PTC maximizing the abundance of a species, we proceeded as follows (see Figure 4.1 for some examples) : (i) if estimates for the linear and the quadratic term of PTC were non-signicant, species abundance was considered unrelated to PTC and thus no optimum value of PTC was calculated for this species. (ii)

If only the estimate for the linear term of PTC was signicant, species abundance was considered linearly related with PTC. The optimum PTC was therefore either the minimum (negative relationship) or the maximum (positive relationship) PTC value observed in the dataset for the species under consideration. (iii) Regardless of the signicance of the linear term, if the estimate of the quadratic term of PTC was signicant and negative, the optimum value was the vertex point of the curve, obtained as -β/2α using estimates of eqn (1). As the vertex point sometimes lay outside the range of PTC values, the optimum PTC value was set at the minimum (respectively maximum) observed PTC value where the species is present, when the vertex was below (respectively above) these values. Finally, if the estimate for the quadratic term was signicant and positive, the vertex point was a local minimum. In these cases, the relationship between abundance and PTC values was in general plateauing, i.e. with either an increase or a decrease in abundance followed by a stabilization (or vice-versa, see Figure 4.1c-d). This implies that the signicant quadratic term is constrained by the model tted, and does not represent a true local minimum. Instead, the between abundance and PTC values was highly asymmetrical, with one end of the gradient exhibiting much larger (and maximal) abundance than the other one ; this end of the gradient was chosen as the optimum PTC values for these species.

We then explored the relationship across species between optimum PTC values and SSI values, using a linear regression with SSI as the dependent variable and optimum PTC values, as well as squared optimum PTC values as explanatory continuous variables. Also, to compare the response of specialist vs. generalist species along the habitat gradient, the distribution of optimum PTC values of the 50 % most specialist species was compared to the distribution of the 50 % the most generalist using a Kolmogorov-Smirnov test.

Finally, indices of specialization were calculated at the community level (hereafter CSI) as the mean of SSI of species that occurred in each community. Similarly, Mean Community Optimum (MCO) was calculated as the mean of optimum PTC values of species that occurred in each community. Relationship between CSI and MCO was explored using linear regression with CSI as the dependent variable, and MCO and squared MCO as explanatory continuous variables.

Results

Among the 82 species, SSI ranged from 0.132 for the most generalist species (Streptopelia turtur) to 1.920 for the most specialist species (Phylloscopus sibilatrix, see appendix A for all SSI values). Optimum PTC values ranged from 0.36 for Carduelis chloris to 96.96 for Turdus philomelos (appendix A). Most species abundances exhibited a signicant negative quadratic relationship with the PTC gradient (67 of 82, i.e. 82%), such that optimum PTC values were generally calculated using the vertex point formula. Among

Discussion

The unseen complementation hypothesis The complementation hypothesis states that a species may need complementary resources from dierent landscape units to thrive.

Here we analyzed simultaneously bird species preferences (i.e. niche position) and their levels of specialization along a continuous environmental gradient. Our methodology was aimed at detecting complementation, linking species preference (i.e. niche position) and species specialization. We did not detect any species specialized on heterogeneous portions of the environmental gradient. Even if some species showed signicant preferences for intermediate values of tree cover percentage, they were not specialized on these portions of the environmental gradient. On the other hand, species that preferred forested or open and agricultural landscape units generally showed high specialization indices.

These results therefore do not support the complementation hypothesis, but instead are consistent with most theoretical predictions on the evolution of specialization, which state that specialists should be favored in stable [START_REF] Devictor | Functional biotic homogenization of bird communities in disturbed landscapes[END_REF][START_REF] Futuyma | The Evolution of Ecological Specialization[END_REF] or stressful [START_REF] Cacho | Occupation of bare habitats, an evolutionary precursor to soil specialization in plants[END_REF][START_REF] Carboni | Measuring ecological specialization along a natural stress gradient using a set of complementary niche breadth indices[END_REF] environments. We showed that specialists tend to prefer either extreme of the analyzed environmental gradient, at least one of which (forests) is highly stable. The other end of the gradient is dened by open land cover types, most of which is agricultural areas in France. Agricultural areas are considered as more disturbed than forested areas and frequent disturbance can be considered stressful for some bird species [START_REF] Bonthoux | Contrasting spatial and temporal responses of bird communities to landscape changes[END_REF][START_REF] Clavero | Functional homogenization of bird communities along habitat gradients : accounting for niche multidimensionality[END_REF]. [START_REF] Carboni | Measuring ecological specialization along a natural stress gradient using a set of complementary niche breadth indices[END_REF] observed congruent results (i.e. no detection of a complementation pattern) in plants communities of a coastal dune ecosystem. They concluded that specialist species tend to dominate in the most extreme environmental conditions, but are subordinate in mild conditions of the gradient. The detection of complementation is variable across studies, which may be related to the spatial resolution used to describe resources. Complementation was also not detected in another study in birds ( [START_REF] Clavero | Functional homogenization of bird communities along habitat gradients : accounting for niche multidimensionality[END_REF], examining several landscape gradients built using principal component analysis) or in other taxonomic groups (spiders : [START_REF] Entling | Niche properties of Central European spiders : shading, moisture and the evolution of the habitat niche[END_REF] ; plants : [START_REF] Thuiller | Relating Plant Traits and Species Distributions Along Bioclimatic Gradients for 88 Leucadendron Taxa[END_REF]). Other studies, all focused on a single species, did detect landscape complementation : e.g. [START_REF] Dulaurent | A case of habitat complementation in forest pests : Pine processionary moth pupae survive better in open areas[END_REF] on the pine processionary moth (Thaumetopoea pityocampa); [START_REF] Mueller | Scale-sensitive landscape complementation determines habitat suitability for a territorial generalist[END_REF] on the common raven (Corvus corax) and [START_REF] Ouin | Complementation/supplementation of resources for butteries in agricultural landscapes[END_REF] on a buttery species (Maniola jurtina). The apparent contradictory observation of complementation across studies may be due to dierent resolutions of resource description.

Here we worked on numerous bird species over a large spatial extent using an environmental gradient as a surrogate for resource heterogeneity, which represents a single niche dimension. However, there is growing evidence that accounting for the multidimensionality of niche is of primary importance to better understand patterns of homogenization or species distribution [START_REF] Barnagaud | Relating Habitat and Climatic Niches in Birds[END_REF][START_REF] Carboni | Measuring ecological specialization along a natural stress gradient using a set of complementary niche breadth indices[END_REF][START_REF] Clavero | Functional homogenization of bird communities along habitat gradients : accounting for niche multidimensionality[END_REF].

Landscape complementation may be invisible with our environmental gradient but could be hidden in other niche dimensions we did not explore. Additionally, using a ner-grained description of resources, adapted to dierent species may help reveal the landscape complementation hypothesis. This was not possible here because of the widespread trade-os between precision and extent of data [START_REF] Braunisch | Predicting species distributions based on incomplete survey data : the trade-o between precision and scale[END_REF][START_REF] Thuiller | Eects of restricting environmental range of data to project current and future species distributions[END_REF].

One solution may be to use so-called landscape-centred approaches, which provide more functional descriptions of landscapes. Such approaches may better capture dierent dimensions of the niche and allow the simultaneous study of species with dierent ecological requirements [START_REF] Mimet | Towards a unique landscape description for multi-species studies : A model comparison with common birds in a human-dominated French region[END_REF].

Finally, our approach relied on the realized niche only (i.e. the niche resulting from a combination of abiotic and biotic factors) and thus captures ecological processes beyond species-landscape relationships, such as interspecic competition. As a result, species with inferred niche position at intermediate values of the environmental gradient could be generalist species that are excluded by competition with specialist species in homogeneous landscapes, rather than species potentially exhibiting a specialization to heterogeneous landscapes (i.e. complementing species). This may explain why our methodology did not detect any species with a at relationship between abundance and the environmental gradient. Measures related to more intrinsic species attributes (i.e. informing on the fundamental niche) may thus be more adapted to capture the complementation hypothesis than those using the realized niche. However, as pointed by [START_REF] Carboni | Measuring ecological specialization along a natural stress gradient using a set of complementary niche breadth indices[END_REF], estimating specialization of species in the absence of competitors is probably less relevant from a conservation point of view than an approach based on the realized niche.

Measurement of specialization A measure of species specialization based on a simple environmental gradient (percent tree cover), derived from widely distributed remote sensing tools with a coarse spatial resolution, was very close to measures derived from habitats categorized by observers in the eld. The value of expertise in categorizing habitats for specialization measurement can therefore be discussed, because a remote sensing approach performed as eciently as an expert approach. The level of species specialization has often been calculated on the basis of categorical representation of landscapes, whereas the niche breadth, a conceptual representation of specialization, is better dened through continuous variables, dened as niche dimensions.

Identifying the key environmental variables that determine a particular niche dimension is one of the most crucial steps in the study of specialization. One of the usual methods to estimate niche dimensions is to apply principal component analysis on various land-scape metrics and infer gradients on the basis of the resulting principal components. While this synthetic approach reduces the complexity of the system, principal components may be dicult to interpret as ecological gradients [START_REF] Hirzel | Habitat suitability modelling and niche theory[END_REF]. Here we chose to use a direct continuous measure of the landscape gradient as a niche dimension, because this approach is more easily interpreted, and more straightforward than an approximation of a niche dimension via multivariate statistics. Nevertheless, as pointed above, our approach relied on a single niche dimension and it would be therefore desirable to extend our approach using other direct measures of niche dimension, especially those based on remote sensing datasets.

Conclusion This work sheds a new light on specialization of species along environmental gradient at large scale and brings further support to the hypothesis of a human-driven homogenization of natural species communities. Current heterogeneous landscapes are mainly due to anthropogenic change of natural areas and this fast modication of landscape does not seem to provide bird species with enough time to adapt and specialize to these landscapes [START_REF] Holt | Conservation implications of niche conservatism and evolution in heterogeneous environments[END_REF]. Hence, heterogeneous landscapes do not host species specialized on intermediate parts of the environmental gradient. The next step is to move to more continuous descriptions of landscape to reveal and understand these patterns of homogenization.

Appendix A Sensivity of SSI values to the number of classes in the PTC gradient is low (Figure 4.5).

SSI calculated on a range of 6-12 classes are only statistically dierent for 6 categories vs.

all other numbers of categories (one-way ANOVA, Tukey honestly signicant dierence (HSD)). Appendix D

A Bayesian approach was used to assess the precision of the turning point estimate (i.e.

the vertex) of the quadratic relationships between species abundances and the Percent Tree Cover (PTC) gradient (see Plassmann et Khanna, 2007). Hence, this approach could be applied only for optimum PTC values inferred from the vertex of a signicant quadratic relationship between species abundance and the PTC gradient (see Appendix A). For other species, we could not calculate precision because optimum PTC was therefore either the minimum or the maximum PTC value observed in the dataset for the species under consideration (see Methods). Convergence of models were done using Gelman plots. All Bayesian Poisson models showed good convergence. 4).

The habitat aspect of this policy embodies the largely justified ambition to overcome species-focused approaches by targeting ecosystems (Keith et al. 2013). Be-yond the acknowledged importance of assessing public policies [START_REF] Ferraro | Money for nothing? A call for empirical evaluation of biodiversity conservation investments[END_REF], SI-Table 1-D1), its evaluation therefore has a particular significance for conservation. However, although several studies address the impact of N2000 on various taxa (birds: Pellissier et al. 2013;[START_REF] Sanderson | Assessing the performance of EU nature legislation in protecting target bird species in an era of climate change: impacts of EU nature legislation[END_REF]terrestrial vertebrates: Maiorano et al. 2015;bats: Lis ón et al. 2013)), its habitat aspect has not been systematically assessed (SI-Table 1-A2).

We address this lacuna through an analysis mostly focused on France, used as an example to draw lessons for Europe as a whole. Indeed, according to the subsidiarity principle (SI-Table 1-B3), N2000 is orchestrated at EUscale, but Member States implement it as they see fit. This diversity of implementations provides opportunities to learn from local experiences, which is our approach here.

Conservation Letters, xxx 2016, 00(0), 1-11 Copyright and Photocopying: C 2016 The Authors. Conservation Letters published by Wiley Periodicals, Inc.

1

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Evaluating the European habitat policy M. Jeanmougin et al. We used the references enlisted by Garnier et al. (2015; see Table 6.1) to identify a representative list of publications in functional ecology dealing with the influence of plant traits on ecosystem processes (column 1). We reported the categories used in these articles to describe habitats (column 2) and identified in each case a series of HCI and non-HCI categories (including syntaxons) to which each category could correspond (column 3). This table illustrates that, on the basis of the information given in published articles, it is impossible to translate unequivocally the language used by functional ecologists to describe habitats into the one used by HCI practitioners.

To develop our evaluation, we first introduce a new normative framework inspired by recent advances in decision-aiding methodologies. Although the abovementioned assessments exclusively focus on the impact of N2000 on conservation targets, this framework encompasses several dimensions of evaluation. Then, exploring the literature and unpublished reports and databases, we identify knowledge gaps (KG) plaguing HD's habitat policy. Gaps between research and practice have been studied on numerous conservation-related topics [START_REF] Knight | Knowing but not doing: selecting priority conservation areas and the research-implementation gap[END_REF][START_REF] Matzek | Closing the Knowing-Doing gap in invasive plant management: accessibility and interdisciplinarity of scientific research[END_REF]), but the habitat case is poorly documented. We unveil important problems in this area, pertaining not only to how ecological advances can translate into practice, but also to capacity building and institutional design. We then use our framework to investigate the implications of these KG for the policy. Finally, we articulate concrete recommendations, and highlight the global significance of our study.

Policy analytics as evaluation framework

Numerous normative frameworks have been developed to rationalize evaluations and associated decision-aiding [START_REF] De Marchi | From evidence-based policy making to policy analytics[END_REF]. Among them, "policy analytics" states that decision-aiding should be "value-adding" (i.e. help policies reaching their objectives), science-based, operational, and legitimating [START_REF] Tsoukias | Policy analytics: an agenda for research and practice[END_REF]. We propose to use and adapt this framework because these criteria are of particular relevance to the evaluation of HD's habitat policy, for the following reasons:

-HD aims to "maintain or restore natural habitats" (SI-Table 1-B1). Assessing its contribution to habitat conservation is therefore crucial to evaluate it (criterion C1). -It is largely admitted that scientific evidence and knowledge should contribute to assess and, in turn, to improve the effectiveness of conservation actions [START_REF] Knight | Knowing but not doing: selecting priority conservation areas and the research-implementation gap[END_REF][START_REF] Dicks | A Transparent process for "evidence-informed" policy making[END_REF][START_REF] Senior | Increasing the scientific evidence base in the "high conservation value" (HCV) approach for biodiversity conservation in managed tropical landscapes[END_REF]. The evaluation should therefore investigate whether the policy is sciencebased (C2). -Because impractical policies are pointless, the evaluation should assess whether the policy is operational (C3). -Because N2000 sites witness highly diverse human activities [START_REF] Tsiafouli | Human activities in Natura 2000 sites: a highly diversified conservation network[END_REF], it is pivotal that N2000 initiatives be considered legitimate by local stakeholders and the general public (C4).

These criteria should not be seen as absolute requirements, because optimizing one criterion can have detrimental consequences on others. For example, a policy exceedingly reliant on cutting-edge science could become nonoperational because too demanding in technology and highly specific skills. Similarly, in some situations, non-scientific knowledge can contribute more efficiently than science to conservation [START_REF] Mazzocchi | Western science and traditional knowledge: despite their variations, different forms of knowledge can learn from each other[END_REF].

We accordingly only assume that, for each criterion C1-4, all other things held equal, the better the criterion is satisfied, the more positively the policy should be evaluated (Figure 1a). We now highlight knowledge gaps relating to HD's habitat policy, and investigate their consequences for C1-4.

…can not be positively evaluated 1 (a) Our evaluation framework, based on "policy analytics," explained and exemplified. C1-4 stand for the four criteria of evaluation of the policy under scrutiny. The four criteria should be understood as "all other things held equal" conditions: for any of these criteria, all other things held equal, the better the criterion is satisfied, the more positively the policy is evaluated. Notice that, in a general setting, maximizing the satisfaction of one criterion can impair the satisfaction of one or several of the others. Elaborating whether and how the various criteria can be aggregated in such cases falls beyond the scope of the present article. (b) Our framework applied to habitat conservation policy as part of the Habitat Directive. KG1-4 stand for the four knowledge gaps (see section Knowledge gaps). Because of KG1, C1 is indeterminate. Because of KG2, C2 is unsatisfied. Both notions apply to EU as a whole. Because of KG3, C3 is unsatisfied in France, where phytosociology is marginal in biology curricula. The French example should set off alarm bells for EU as a whole. KG4 testifies for a fragility of the European system as a whole, implying that C4 is not satisfied. Based on C1-4, one cannot positively evaluate HD's habitat conservation policy. Green dashed boxes mean that search is done on title, abstract and keywords of each publication. Red dashed boxes mean that search is done on entire text. We first identified a corpus of articles (n) dealing with habitats conservation in the N2000 sense, by selecting all the articles containing occurrences of "Habitat(s) Directive" or "Habitat(s) of Community Interest" or "Special Area(s) of conservation" in their abstracts, titles or keywords in the Web of Science Core Collection (timespan: 1970Collection (timespan: -2016; extensive list of articles can be found in SI-Table 5). On this first corpus, we then performed three parallel analyses to detect the available scientific knowledge on HCI pertaining to three prominent branches of ecology and conservation: functional ecology (a), invasive ecology (b), and conservation planning (c). The first step of each of the three analyses selects a branch-specific corpus by selecting articles containing occurrences of keywords of the corresponding branch in their title, abstract or keywords (corpuses n func , n inva , n cons , respectively). In a second step, we detect occurrences of keywords of the concerned discipline in the whole text of each article in corpuses n func , n inva , n cons . In a third step, we categorize these occurrences. Occurrences of branch-specific keywords are termed "irrelevant" when the detected words are actually homonyms of the searched words, used in another sense (e.g. searching for occurrences of "function" to detect occurrences of keywords of functional ecology, we select an article where the term "function" is used to refer to a mathematical function). Occurrences of branch-specific keywords are termed "contextual" when they are used to contextualize the study (e.g. in the introduction or the conclusion of the article) or when they appear in articles that do not mention any HCI in their main text. Occurrences are termed "relevant" when they appear in the formulation of scientific results dealing with both HCI and notions pertaining to the concerned branch. The sum of irrelevant, contextual and relevant occurrences can be greater than the size of the corresponding corpus because some words can appear multiple times in the same publication. Notice that, in analysis (a), among the n func articles, none is published in what we considered to be influential journals specialized in functional ecology (Ecosystems, Functional Ecology, Biogeochemistry), influential journals in ecology with sections devoted to functional ecology (New Phytologist, Ecology, Journal of Ecology, Oikos, Oekologia, Ecology Letters, Global Change Biology, Basic and Applied Ecology) or important review journals (Trends in Ecology and Evolution, Annual Reviews of Ecology, Evolution and Systematics, Biological Reviews). As addendum to analysis (b), all invasive species names from DAISIE, TAXREF v9 and EPPO Lists of Invasive Alien Plants (see SI-Table 3) were also searched in the general corpus (n = 742) on title, abstract and keywords. Linnaean binomial Latin names were used for each species because complete names (with authors and date) are not always given in articles. All synonyms were also checked using the French Taxonomic Reference Source TAXREFv9 (SI-

Original results in the publication

Figure 3 Schematic explanation of the analyses needed to translate typical results published in scientific journals into results usable in the field by N2000 practitioners, using results in functional ecology as a focal example. The left panel schematizes the results of a fictive scientific article, demonstrating a linear relation between a given ecosystem parameter and a given ecosystem process, for a series of habitats represented by black crosses and described in the original article using one or several of the categories exemplified in Table 1, column 2. Green and red crosses in the right panel respectively represent habitats that would be categorized as HCI and non-HCI using HD practitioners' categories, as exemplified in Table 1, column 3.

Evaluating HD's habitat policy

Knowledge gaps

Lack of data on HCI conservation status (KG1)

HD requires that Member States periodically perform conservation status assessments of HCI along three ecological parameters: range, coverage, and structure and function (article 17 evaluation: A17E). In each country, each HCI is evaluated in each biogeographical region (SI- 1-C2). According to these databases, in France, evaluations based on a "complete survey or a statistically robust estimate" (in the official terminology: SI-Table 1-A4) are marginal (6.3%). 52.5% of evaluations are admitted to be based on data that are "partial" and 38% are "based on expert opinion." The lack of data is especially patent for structure and function: 85% of evaluations are expert opinions (SI-Table 1-C2). This can be compared with evaluations of population size and population trends of Bird SCI in France in the BD reporting (SI-Table 1-C3), among which 44% are complete surveys and 7% are expert opinions. At European level, complete or statistically robust surveys are more important but in minority (16.6%), experts opinion are less dominating but still important (22.7%), and significantly more so (χ ²-test: P < 0.001) for structure and function (43.4%).

For each biogeographical zone/country/HCI combination, A17E provides an aggregate conservation status for all sites inside and outside N2000. A handful of countries (France, UK, Belgium, Germany, and Austria: SI-Table 1-A4) also produce evaluations at site level. However, these initiatives lack coordination [START_REF] Maciejewski | État de conservation des habitats: propositions de d éfinitions et de concepts pour l' évaluation à l'échelle d'un site Natura 2000[END_REF]. The site-level French database (SI-Table 1-C4) contains information encoded in categories different from the ones used in A17E, with admitted ambiguities of translations between the two (SI-Table 1-A5). Besides, standardized evaluation methods are available only for a minority of HCI (in France: 52 HCI out of 132).

To sum-up, the data on the conservation status of HCI are of two sorts, too heterogeneous to be aggregated: r A17E, which lumps together all sites at biogeo- graphic/country level and is weakly based on complete or statistically robust estimates.

r Evaluations at site level, which are scarce and non- standardized.

Gap between research and practice (KG2)

Following the CORINE (SI-Table 1-A6) and Palearctic habitat classifications [START_REF] Devilliers | A classification of palaearctic habitats[END_REF], the denomination and descriptions of HCI (detailed in regional manuals such as the French "Habitat Books": SI-Table 1-A7) are largely based on phytosociological categories ("syntaxons"; Evans 2010).

To establish whether conservation actions based on HCI or phytosociological categories can take advantage of ecological advances, we explored the peer-reviewed literature in three disciplines that we take, for complementary reasons, to be the ones that should be the most useful for HD practitioners:

(a) Functional ecology because European texts emphasize the importance of preserving ecological functioning, and the A17E structure and function evaluation patently lacks data (3.1.1). We identified 113 articles in the literature about ecological functioning on N2000 habitats (Figure 2a). However, key terms of functional ecology are used there mainly to describe the context; only five articles refer both to HCI and functional ecology in their results. This illustrates that functional ecology and N2000 do not have a shared ontology: functional ecologists do not use HCI categories to elaborate and design their projects and never articulate results in this language. To be able to use these results, practitioners would have to reanalyze raw data to reclassify them in HCI terms, and redo analyses to see whether published results persist when translated (Figure 3).

(b) Invasive ecology because other European policies target invasive species [START_REF] Beninde | Ambitious advances of the European Union in the legislation of invasive alien species[END_REF] and A17E takes them as an important threat to habitats (SI-Table 1-A4). Definitions of habitats in practitioner's manuals (SI-Table 1-A7) are however based on lists of "index species" often including invasive species. Depending on the invasive database used, 8-28% of the HCI present in France have, among their "index species," at least one species considered invasive in France (SI-Table 3). Robust knowledge on the impact of invasive species on HCI is therefore greatly needed, especially for HCI with index invasive species. However, to date, only four articles display results on the impact of invasive species on HCI (Figure 2b).

(c) Conservation planning because [START_REF] Popescu | Species, habitats, society: an evaluation of research supporting EU's Natura 2000 Network[END_REF] identified it as the dominant discipline in the N2000 literature. We identified only 24 articles pertaining to this discipline on habitats (suggesting that the literature identified by [START_REF] Popescu | Species, habitats, society: an evaluation of research supporting EU's Natura 2000 Network[END_REF] mainly dealt with the species aspects of N2000), and only two referred both to HCI and conservation planning in their results (Figure 2c).

The three corpuses, therefore, illustrate the same problem: despite their potential usefulness for HD practitioners, published results are not usable because they are not expressed in the categories that practitioners use, and translating them would be a scientific task on its own. As a consequence, it is not surprising that, among the 3117 evaluations performed as part of A17E, only 312 (10%) refer to articles published in journals listed in the Journal of Citation Reports (SI-Table 2).

Gap between teaching and practice (KG3)

Associated with the fact that academics rarely use phytosociological categories, phytosociology tends to disappear from ecology curricula. In France, all biology universities have marginalized phytosociology teaching (Bouzill é 2007); only four 1-week-long continuing formations are dispensed in phytosociology per year (SI-Table 1-D4). Phytosociology teaching remains more developed for example in Italy, Spain, or Eastern countries (e.g. SI-Table 1-D5). But the durability of this situation is uncertain if phytosociological categories vanish from the scientific literature.

Deficiencies in the structure of the epistemic community (KG4)

One of the strengths of N2000 is that numerous international experts were involved in its construction through seminars and experts groups (Evans 2012;[START_REF] Popescu | Species, habitats, society: an evaluation of research supporting EU's Natura 2000 Network[END_REF]. However, the French A17E database reveals problems in the structure of these panels. Although A17E involved more than 800 contributors, writing was largely confined to expertise institutions (81%), whereas research and teaching institutions played a marginal role (<5%). Among the 319 evaluations by expert institutions, all but one were performed by "Conservatoires Botaniques," institutions representing botanists and phytosociologists. The relevance of these actors for A17E is indisputable but others, including researchers and managers, also have insights to contribute, and the panel is biased against them (Figure 4). Social and economic scientists or experts could also contribute by improving the identification of threats impacting habitats and policies contradicting N2000 actions. Going beyond Figure 4 Institutional and disciplinary balance in the composition of the panel involved in the latest A17E in France. These information are from the French A17E database (SI-Table 1-C2). The database provides names and institutional affiliations for most of the experts involved in the evaluation. Part (a) of the graph reproduces the data from this database. To construct part (b), we used the disciplinary affiliation presented by the various experts on the websites of their institutions. "Conservatoires Botaniques" are the only exception, because most of the experts from these institutions do not have a personal page presenting them in the website of the "Conservatoire Botaniques" to which they belong. Since "Conservatoires Botaniques" are institutions devoted to botany and phytosociology, we classified experts from Conservatoires Botaniques in the disciplinary category "phytosociology."

European guidelines, the French database, therefore, unveils problematic biases invisible at European level. Moreover, as far as reports indicate (SI-Table 1-A8), it has not been verified that the various A17E evaluators agreed in their understanding of "conservation status". The European guidelines (SI-Table 1-A4) do not require any such verification. Similarly, the construction of site scale methods (SI-Table 1-A9-A19) admits that "conservation status" is unproblematic for the panel of experts involved. Recent discussions [START_REF] Epstein | A Legal-ecological understanding of favorable conservation status for species in Europe[END_REF]

How knowledge gaps undermine HD's habitat policy (Figure 1)

Assessing HD's contribution to habitats conservation requires sorting out its proper effect from confounding factors such as historical trends or unrelated policies [START_REF] Ferraro | Money for nothing? A call for empirical evaluation of biodiversity conservation investments[END_REF]. This requires data on conservation status in sites inside and outside the network. But data on conservation status at site level are scarce and A17E lumps together statuses inside and outside the network (KG1). The contribution of N2000 to conserving habitats is therefore unproven due to a lack of data (C1 indeterminate).

KG2 shows that N2000 practice cannot take advantage of an important part of published scientific results. Although knowledge relevant to conservation is not confined to the academic world [START_REF] Burgman | Redefining expertise and improving ecological judgment[END_REF], and A17E and HD practices are based on an extensive unpublished literature, they accordingly appear insulated from a large part of cutting-edge science (C2 unsatisfied).

In terms of operationality (C3), countries like France are additionally plagued by a lack in capacity building in phytosociology (KG3), and one can consequently hardly expect to find enough phytosociological competences in the field to produce robust management practices. In countries where phytosociology teaching remains important, the situation is less problematic, but due to the links between research and teaching, its durability is fragile.

KG also have implications for legitimacy (C4). Indeed, the procedural organization of collective scientific expertise, and in particular a balance between various knowledge-holders (in terms of institutions, discipline or background), is increasingly considered pivotal to achieve the pluralist knowledge liable to inform policies while bestowing legitimacy on them [START_REF] Montana | IPBES and biodiversity expertise: regional, gender, and disciplinary balance in the composition of the interim and 2015 multidisciplinary expert panel: IPBES and biodiversity expertise[END_REF]. KG4 is therefore detrimental to the legitimacy of HD.

To sum up, C1 is indeterminate (due to KG1) and C2 unsatisfied (due to KG2) for Europe as a whole. Concerning C3, due to KG3 in France it is unsatisfied, and in countries where phytosociology is more developed the situation remains problematic. Concerning C4, KG4 testifies for a fragility of the European system as a whole. Based on C1-4, one therefore cannot positively evaluate this policy.

Improving European habitat conservation policies

Updating scientific basis

To ensure that HD's habitat policy becomes more sciencebased, a two-steps European-wide initiative is needed:

(1) First, the identifiability of HCI without referring to syntaxons should be assessed, and new characterizations clarified in up-to-date guidelines. The point is not to discard phytosociology, because valorizing phytosociological knowledge about species assemblages and repartition (Ewald 2003;[START_REF] Biondi | Phytosociology today: methodological and conceptual evolution[END_REF]) is undoubtedly a cogent strategy for HD. A pervasive usage of phytosociological vocabulary, however, insulates HD from ecological advances. For some HCI, such as the easily identifiable " In this process, scientific journals will have a prominent responsibility. Publishing and valorizing catalogues of plant communities could help increase scientific quality control and ensure a wider diffusion. This would also incite researchers to develop collaborations with local knowledge-holders, which would strengthen the link between researchers and practitioners.

Ecology journals could also require that authors integrate in their manuscripts a discussion of the translatability of their results in terms of HCI. If this translation is possible, articulating it will be helpful for practitioners. If it is impossible, making it clear prevents misinterpretations.

Building capacity

Strengthening scientific bases is, however, only one aspect of the improvements needed. By adopting HD, Member States committed to equip themselves with the capacity to implement it. In France, reference institutions for habitats are "Conservatoires Botaniques." Their botanical competence is indisputable but they have neither the obligation nor the financial and human means to perform teaching (SI-Table 1-B4) and have more limited access to scientific bibliographical databases than research institutions. This condemns France to competence scarcity. To perform the two tasks above, the EU and Member States should learn from this counterexample. They should provide financial and organizational support to retrieve the competence to learn, critically assess and renew phytosociological knowledge.

Reforming A17E

Our analysis also highlights A17E reforms that should be moved to the top of the ETC-BD agenda:

(1) The structuration of epistemic communities involved should be rationalized, e.g. through the work of a dedicated committee involving ecologists, social scientists, philosophers and practitioners; (2) Evaluations at site level should become mandatory, inside and outside the network; (3) Requirements should be specified in terms of quantitative data content and publication for sources used.

Our recommendations are all costly initiatives. But numerous N2000 funding instruments (SI-Table 1-A26) could contribute by integrating them in their guidelines. In particular, they represent opportunities for Life-Nature, the main EU conservation financial instrument, to fix its inability to address conservation priorities [START_REF] Hermoso | EU's conservation efforts need more strategic investment to meet continental conservation needs[END_REF].

Conclusions

The weaknesses of HD's habitat policy that we highlight should not overshadow the undeniable strengths of N2000: its coherence with international environmental agreements [START_REF] Beresford | The contributions of the EU nature directives to the CBD and other multilateral environmental agreements[END_REF], its contribution to conserving species [START_REF] Sanderson | Assessing the performance of EU nature legislation in protecting target bird species in an era of climate change: impacts of EU nature legislation[END_REF], or the breadth of the network. Our point is not to vilify the policy, but to identify how to improve it. In this respect, our analysis highlights knowledge gaps that have a more general bearing than N2000. In particular, problems encountered if categories used by practitioners and researchers differ carry lessons for conservation initiatives focused on habitats whatever their geographical and political context. The same goes for associated problems of capacity building and biased epistemic communities. Accordingly, our concrete recommendations can be transposed in other contexts, such as e.g. the emergent IUCN red list ecosystem initiative (SI-Table 1-A27).

Supporting information (SI)

The following listed Supporting Information (SI) mentioned in the main text are not presented in this manuscript, as they are oversized. However, an URL for dowloading these SI is provided : SI-Table 2 (source or direct downloading url) List of evaluations in A17E referring to peer-reviewed sources in scientic journals. This list is an excerpt from the European A17E database (SI-Table 1-C1). In the original ETC-BD A17E database, peer-reviewed sources from scientic journals are not distinguished, and are rather lumped together with grey literature, websites, references to personal communication and the like. To detect these references, we used the list of journals in the categories BIODIVERSITY CONSERVATION, BIOLOGY, ECOLOGY, ENGI-NEERING C. ENVIRONMENTAL, ENTOMOLOGY, ENVIRONMENTAL SCIENCES, ENVIRONMENTAL STUDIES, GEOCHEMISTRY & GEOPHYSICS, GEOGRA-PHY, GEOGRAPHY C. PHYSICAL, GEOLOGY, GEOSCIENCES C. MULTIDIS-CIPLINARY, PLANT SCIENCES, REMOTE SENSING, ZOOLOGY in the Journal of Citations Reports. We then searched in the European A17E database (SI-Table 1-C1) the occurrences of the names and abbreviated names of all these journals and extracted references on this basis. References are reproduced in the table in the format in which they appear in the original database, except for minor homogenization allowing to detect duplications. This analysis shows that, among the 3117 evaluations at the country/HCI/biogeographic zone level, 312 (10%) refer to sources published in one of the selected journals. Moreover, references to these published sources are highly redundant, since they concern only 203 articles. Among these articles, those published in 2006 or earlier are of limited signicance for the evaluation of the conservation status of habitats in the 20072012 period. Among the 203 articles, 109 were published in 2007 or after.

They concern 200 evaluations (6.4%).

SI-Table 4 (source or direct downloading url)

Complete list of HCI, with codes and ocial denomination ; and list of the HCI present in France, in the dierent biogeographic region. HCI 4030,5120,6210,6230,6510,6520,9420,9430 and 4060/4070) was also eliminated because Festuca rubra is a notoriously ambiguous binomial name whose mentions in the Habitats Books can be considered ambiguous.

SI-

Chapitre 6

Discussion générale, limites et perspectives 6.1 La spécialisation comme mesure des relations espèces-habitats ?

Dans le contexte actuel de la crise de la biodiversité, mieux comprendre les relations entre les espèces et leurs habitats est crucial pour la conservation. Ces relations se matérialisent de façons extrêmement diverses, d'une part du fait de la diversité importante des espèces et de leurs écologies mais aussi de la diversité des contextes environnementaux dans lesquels une même espèce peut se retrouver ou encore en fonction des diérences interindividuelles au sein d'une même espèce, ajoutant à chaque fois un niveau supplémentaire de complexité (Elton, 1966, p.62). Les scientiques s'intéressent depuis longtemps à ces relations qui sont à la base de l'établissement de l'écologie comme science à part entière. L'émergence de théories pour expliquer ces relations, comme par exemple les premières formulations de la théorie de la niche écologique (Grinnell, 1917a;[START_REF] Elton | Animal ecology[END_REF][START_REF] Pocheville | The Ecological Niche : History and Recent Controversies[END_REF], est intrinsèquement liée au développement de l'écologie.

6.1 La spécialisation comme mesure des relations espèceshabitats ? probable que les espèces perçoivent le paysage comme nous l'avons classé en tant qu'humain [START_REF] Elton | The Classication of Habitats[END_REF]. Cependant, on peut s'attendre à ce que plus l'emprise spatiale d'une étude diminue, plus les variables environnementales locales (dont les mesures de l'habitat) seront importantes pour expliquer les patrons observés, en partie aussi car celles-ci seront dénies plus précisément [START_REF] Mykrä | Scale-related patterns in the spatial and environmental components of stream macroinvertebrate assemblage variation[END_REF][START_REF] Reif | The Eect of Scale-Dependent Habitat Gradients on the Structure of Bird Assemblages in the Czech Republic[END_REF][START_REF] Diví²ek | Natural habitats matter : Determinants of spatial pattern in the composition of animal assemblages of the Czech Republic[END_REF].

Les travaux de cette thèse couvrent l'échelle nationale pour laquelle des données sur les paysages sont rares et, lorsqu'elles existent, ne sont pas les plus précises. Ainsi, l'étude du troisième chapitre s'appuie sur les données Corine Land Cover pour laquelle les patchs doivent avoir une aire minimum de 25 ha, i.e. une résolution grossière pour mesurer la structure du paysage [START_REF] Gimona | CORINE-based landscape indices weakly correlate with plant species richness in a northern European landscape transect[END_REF]. Dans une synthèse bibliographique s'intéres- n'induit pas forcément que les espèces vont en réalité répondre à cette échelle spatiale. En fait, le risque est de nir par confondre corrélation et causalité [START_REF] Gosselin | Improving approaches to the analysis of functional and taxonomic biotic homogenization : beyond mean specialization[END_REF]. Il semble donc important d'analyser plus systématiquement ces échelles spatiales pour en quelque sorte certier qu'elles ont une représentation tangible pour l'espèce [START_REF] Betts | A species-centered approach for uncovering generalities in organism responses to habitat loss and fragmentation[END_REF].

Nos résultats se montrent cependant peu optimistes sur ce point. L'opinion d'expert peut donc fournir des informations qualitatives pour mesurer les habitats. Cette information reste néanmoins plus complexe à obtenir qu'une simple mesure de télédétection, gratuite et standardisée pour l'ensemble de la planète [START_REF] Turner | Free and open-access satellite data are key to biodiversity conservation[END_REF].

Des approches continues centrées sur l'espèce L'arrivée de nouvelles méthodes basées sur la télédétection permet d'entrevoir aujourd'hui les faiblesses d'une approche catégorielle de l'habitat [START_REF] Gillespie | Measuring and modelling biodiversity from space[END_REF][START_REF] Cord | Inclusion of habitat availability in species distribution models through multi-temporal remote-sensing data ?[END_REF]. [START_REF] Cord | Comparing the suitability of classied land cover data and remote sensing variables for modeling distribution patterns of plants[END_REF], dans une étude récente, avancent que les variations locales des conditions environnementales ne peuvent pas être représentées par des données catégorielles d'utilisation du sol.

Cependant, les données continues de télédétection pourraient outrepasser ce problème.

Limites de l'analyse multi-échelles sur les paysages

Le paysage peut expliquer de manière très variable la distribution des espèces [START_REF] Luoto | The role of land cover in bioclimatic models depends on spatial resolution[END_REF]Thuiller et al., 2004a). En eet, les modèles que l'on utilise font l'hypothèse que la distribution est fonction de nombreux paramètres biotiques et abiotiques (e.g. En partie car d'autres aspects importants viennent complexier leurs élaborations.

Dans nos travaux, nous avons donc aussi utilisé d'autres critères pour évaluer la directive Habitats . Cependant, dans l'élaboration de la directive Habitats, si un choix important a été fait, c'est celui de la dénition de l'habitat (Evans, 2012). Cette dénition s'appuie sur une représentation catégorielle des habitats, non centrée sur les espèces mais dénie en fonction de communautés d'espèces végétales (i.e. une approche phytosociologique).

On s'approche donc de la dénition d'habitat traduite par biotope dans la littérature historique sur le concept (cf. deuxième chapitre).

La présence d'une telle dénition de l'habitat dans une directive européenne est due à la forte prédominance de la phytosociologie dans le développement de l'écologie de nombreux pays européens [START_REF] Bouzillé | Gestion des habitats naturels et biodiversité[END_REF]Ewald, 2003). L'approche phytosociologique en elle-même n'est pas un problème mais elle nécessite de se réformer pour mieux s'inclure dans les développements actuels en écologie (Ewald, 2003). Cependant, ce que l'on a pu révéler dans la quatrième partie de cette thèse est que le choix d'une telle approche pèse sur le dialogue potentiel entre les communautés d'acteurs de la conservation. En eet, on observe une confrontation entre deux visions de l'habitat qui ne sont pas interopérables.

On agrandit donc le fossé qui sépare les communautés d'acteurs qu'il est pourtant urgent de faire travailler de concert. D'un côté, les acteurs de terrains (e.g. gestionnaires d'espaces naturels et politiques) se basent sur les outils législatifs mis à leur disposition comme la Directive Habitats pour appliquer des actions de conservation. Ils vont donc utiliser la dénition de l'habitat intégrée à cette politique (i.e. une dénition communauté-centrée).

De l'autre côté, les scientiques, écologues, biologistes de la conservation qui mènent leurs recherches dans le champ de la conservation mais en privilégiant généralement une dénition de l'habitat centrée sur l'espèce. Nos résultats démontrent ce décalage important dans la description de l'habitat. En particulier en évaluant la bibliographie scientique sur les aspects fonctionnels dans le cadre de la Directive Habitats, il n'y a pas de traduction dans le langage scientique des dénominations utilisées par les acteurs de terrain. Ce décalage freine ainsi les actions de conservation. Les recommandations apportées dans ce travail sont de nature à améliorer cet état de fait. Cependant pour que scientiques et acteurs de terrain puissent dialoguer sur les mêmes bases, il semble aussi important qu'ils aient un vocabulaire commun [START_REF] Young | Improving the science-policy dialogue to meet the challenges of biodiversity conservation : having conversations rather than talking at one-another[END_REF]. S'astreindre à dénir correctement les termes utilisés en écologie peut sembler une perte de temps mais de nombreuses études montrent un eet positif de ces réexions [START_REF] Reiners | 100 years of ecology : what are our concepts and are they useful ?[END_REF].

6.4 Conclusion et perspectives générales 6.4.1 Urgence et précipitation ?

Les sciences de la conservation sont confrontées à l'urgence de la crise de la biodiversité.

Cependant, urgence ne veut pas dire précipitation. Le développement des connaissances et des outils utilisés pour la protection de la biodiversité s'est semble-t-il fait de manière empirique sans que l'on prenne le temps d'un dialogue important entre les communautés d'acteurs qui font la conservation. Gestionnaires, politiques et scientiques ont l'obligation de parler la même langue s'ils veulent atteindre les objectifs de conservation (H2020).

Ce travail de thèse, au-delà de mettre en en évidence le fossé maintes fois étudié entre les communautés d'acteurs en conservation (i.e. science-policy gap ), en apporte un éclairage nouveau en passant par le prisme de l'un des plus importants concepts de l'écologie : le concept d'habitat.

Un habitat vaut mieux que deux tu l'auras

Le développement historique de ce concept en écologie a polarisé deux visions des relations entre espèces et habitats. L'une dénit d'abord les habitats comme des entités à part entière, des habitats per se, qui forment des catégories ou des types dans lesquels il va s'agir de caser les espèces ou du moins pour lesquelles on pourra étudier les liens avec les espèces. On cherche donc à relier deux objets catégoriels (i.e. habitats et espèces) dénies de manière indépendante. C'est cette vision qui prédomine dans les approches appliquées de la conservation à travers l'importance des préceptes de la phytosociologie en particulier.

Elle s'oppose à l'autre vision de l'habitat, non pas dénie indépendamment de l'espèce mais en fonction de l'espèce. On dénit donc autant d'habitats que d'espèces. L'espèce n'étant pas elle-même une entité homogène (par exemple, diérentes populations d'une même espèce), l'habitat ne représente pas une entité gée mais contexte-dépendante.

Les travaux développés dans cette thèse apportent chacun un éclairage particulier sur l'opposition de ces deux visions de l'habitat : (i) l'analyse historique montre l'origine et le développement du schisme du concept d'habitat (ii) les analyses paysagères posent la question de l'importance de la représentation de l'environnement et donc de l'habitat et (iii) l'évaluation de la directive Habitats informe directement sur l'impact des diérentes interprétations de l'habitat entre des acteurs opérationnels et les scientiques.

Ces résultats peuvent être perçus globalement comme des critiques accompagnés de préconisations naïves. Par exemple, si l'émergence d'une approche continue des paysages grâce à la richesse des informations de télédétection disponibles aujourd'hui prend forme au sein de la communauté scientique, l'appropriation rapide de ces outils par les acteurs opérationnels semble une utopie. Non pas parce que les acteurs opérationnels sont réticents à de nouvelles approches mais plutôt parce que les scientiques ne font pas forcément l'eort de traduire leurs résultats dans les catégories (cf. le cinquième chapitre) et que les institutions ne se réforment pas assez vite (Cardoso, 2012).

Au-delà des considérations scientiques, la dichotomie entre un habitat opérationnel et un habitat écologique s'explique aussi par des pratiques, des échelles (spatiotemporelles) et des buts qui divergent fortement entre les communautés d'acteurs de la conservation. Quand un acteur de terrain veut pouvoir utiliser un outil habitat pour améliorer la gestion d'un espace naturel, celui-ci n'aura évidemment pas la même dénition que l'habitat d'une espèce modélisé. Cependant, cette distinction semble dicile à assumer car nalement très peu mise en avant.

6.4.3

Un langage commun pour les futurs outils de la conservation ?

La liste rouge des espèces de l'IUCN est considérée comme l'un des outils phares de la conservation. Elle est utilisée à tous les niveaux, tant scientique que par des acteurs opérationnels soucieux de décliner les listes rouges à des échelles plus locales dans le but d'alerter autant les politiques que le public, qui y trouve un discours cohérent et clair sur l'état de la biodiversité. On ne peut que souhaiter un même avenir aux futures listes rouges des écosystèmes (Keith et al., 2013). Cependant, si l'espèce ore un cadre relativement commun et accessible de réexion, la liste rouge des écosystèmes pourrait se heurter à l'ambiguïté nichée derrière la dénition des entités qui seront évaluées (Boitani et al., 2015).

En France par exemple, les écosystèmes en cours d'évaluation sont pour l'instant dénis dans une démarche habitat très proche de celle observée dans la directive Habitats , en s'appuyant sur le référentiel européen de classication des habitats EUNIS (IUCN, 2014). Le risque semble donc que cette liste rouge soit exclue des études scientiques (au contraire des listes rouges espèces, dont les critères ont été élaborés par les scientiques, [START_REF] Mace | The role of taxonomy in species conservation[END_REF], car principalement basée sur des entités peu identiées dans la littérature scientique. Les enjeux de la conservation des écosystèmes deviendraient donc inaudibles pour les acteurs extérieurs au processus scientique (en particulier pour le public). Pourtant le débat scientique existe autour de l'élaboration de ces listes rouges et des bases scientiques qui les supportent [START_REF] Keith | The IUCN red list of ecosystems : Motivations, challenges and applications[END_REF]Boitani et al., 2015) mais celui-ci reste relativement restreint. Malgré l'urgence, il semble pourtant important de ne pas céder à la précipitation pour mieux favoriser l'appropriation par tous (scientique, gestionnaire, politique, citoyen, etc.) des outils puissants mis à la disposition de notre objectif commun de conservation de la biodiversité.

1. 1

 1 La crise de la biodiversité : diérents facteurs et un mauvais focus tique, accentuant d'autant plus la recherche en écologie sur ce facteur (i.e. le changement climatique). En eet, le changement climatique est devenu central dans l'étude des scénarios de biodiversité. Dans une récente analyse Titeux et al. (2016b) ont montré que 85% des recherches qui s'intéressent à des projections futures de biodiversité ne s'intéressent qu'aux changements dans les conditions climatiques (Figure 4.4).

Figure 1 . 1

 11 Figure 1.1 Estimation des l'utilisation de données issues des scénarios de changement climatique, de mode d'occupation et d'utilisation des terres et des deux combinés pour expliquer les scénarios de biodiversité. Tiré de Titeux et al. (2016b).

Figure 1 . 2

 12 Figure 1.2 Représentation graphique de la théorie de la biogéographie insulaire (Ma-cArthur et Wilson, 1967). Le nombre d'espèces sur une île va dépendre de sa surface (plus l'île est grande, plus elle contiendra d'espèces) et de sa distance au continent (i.e. la source, plus l'île en est proche, plus elle contiendra d'espèces) régit par les mécanismes écologiques de colonisation/extinction. Les points A, B, C et D correspondent à des compromis entre ces deux facteurs. Cette théorie peut être transposée à un paysage théorique composé d'une dichotomie entre matrice et habitat. Plus le patch d'habitat dans la matrice sera grand, plus il contiendra d'espèces (ou d'individus) et plus il sera proche d'un autre patch source, plus le nombre d'espèces ou d'individus sera important.

Figure 1 . 3

 13 Figure 1.3 Représentation de la niche écologique fondamentale (traits pointillés) et réalisée (traits pleins) le long de deux axes environnementaux hypothétiques. Adapté de Poisot et al. (2011).

Figure 1 . 4

 14 Figure 1.4 Exemple de la cartographie Corine Land Cover (CLC) pour la France. Cette cartographie des modes d'occupations et d'utilisation des sols se décline à l'échelle européenne.

  Figure 1.5 L'hypothèse de landscape complementation au niveau de la communauté. Dans cet exemple, si un paysage est composé d'une combinaison des unités paysagères 1 et 2, on s'attend à observer plus de biodiversité (i.e. plus d'espèces) car on observera dans ce paysage les espèces spécialistes des deux unités mais aussi les espèces qui tirent partie de la combinaison de ces deux types d'unité paysagère ainsi que les espèces présentes dans l'une ou l'autre des unités paysagères. Tiré de Fahrig et al. (2011).

Figure 1 . 6

 16 Figure 1.6 Spécialisation des espèces le long d'un gradient de ressource. L'espèce spécialiste (en rouge) a niche plus étroite que l'espèce généraliste (en bleu). Cependant, elle est plus ecace pour utiliser la ressource dans sa niche réduite. Ici la performance de l'espèce est mesurée avec l'abondance mais il peut s'agir d'autres mesures (e.g. tness).

Figure 1 . 7

 17 Figure 1.7 Les habitats des espèces généralistes englobent diérents types d'habitats d'espèces spécialistes. Dans cet exemple l'habitat écologique (niche) est déni vis-à-vis de grandes catégories d'habitats de type occupation du sol, liant ainsi deux niveaux du concept d'habitat.

Figure 1 . 8

 18 Figure 1.8 Hypothèses de réponse de diérentes espèces à un gradient environnemental : (a) espèce avec une forte anité pour l'extrenum gauche du gradient et ses réponses selon les processus suivant : A : Eet de la fragmentation après une perte d'habitat continu le long du gradient environnemental, B : Perte d'habitat continu le long du gradient environnemental, C : Hypothèse de supplémentation, i.e. l'espèce peut substituer son habitat primaire dans d'autres portions du gradient environnemental jusqu'à ce qu'il devienne trop rare entrainant un eondrement de la population, D : Compensation possible de l'habitat préféré au détriment de l'abondance de l'espèce du fait de la qualité moindre de l'habitat de compensation, (b) espèce avec une anité intermédiaire ou sans anité particulière avec le gradient et ses réponses selon les processus : E : Hypothèse de complémentation, i.e. l'espèce a besoin d'une complémentarité des ressources oerte par le gradient environnementale et F : Compensation totale sur tout le long du gradient environnemental. L'espèce va piocher indépendamment ses ressources tout le long du gradient. C'est en particulier le cas pour les espèces généralistes, (c) espèce avec une forte anité pour l'extrenum droit du gradient. Les processus impliqués sont les mêmes que pour (a). (d) Implication théorique de ces mécanismes sur la relation entre la spécialisation des espèces et leurs préférences le long du gradient environnemental. Les couleurs des courbes

6.

  photographier un maximum d'espèces diérentes (Figure1.9).

Figure 1

 1 Figure 1.9 (a) Schéma présentant les étapes de participation au Suivi photographique des insectes pollinisateurs (Spipoll) (b) Participant du Spipoll sur le terrain.

1. 5

 5 Utilisation des données de sciences citoyennes L'objectif pour le participant est d'obtenir une photo par espèce, de qualité susante pour diérencier une espèce des autres espèces photographiées. L'ensemble de ces photos constitue une collection . Cependant, le participant ne s'arrête pas à collecter simplement les données car il doit ensuite déposer ses photos sur le site internet (website Spipoll) ou il identie aussi précisément que possible chaque espèce à l'aide d'une clé d'identication en ligne. La détermination se fait aussi précisément que possible, c'est-à-dire que l'observateur, s'il en a les moyens techniques (e.g. une photographie de bonne qualité présentant bien les critères distinctifs) peut aller jusqu'à déterminer l'individu au niveau taxonomique de l'espèce. En eet, la clé conçue dans le cadre de ce programme permet des identications sur photos d'une centaine d'espèces (Figure 1.10).

Figure 1 .

 1 Figure 1.10 Exemple de la clé d'identication du Spipoll. Il s'agit d'une clé à entrées multiples qui permet d'améliorer la pertinence des identications par les observateurs eux-mêmes.

  discriminated habitats according to the mechanisms of temporal change : abiotic factors (tidal habitats for example), biotic factors (such as succession of biotic communities) or no temporal change. Hence, he came up with a denition dividing the concept of habitat into what he called inconstant vs. constant (or monotonous)

Figure 3 . 1

 31 Figure 3.1 Example plots of AIC values of GLM models at 13 spatial scales for two species : Paracorymbia fulva (a-c) and Xylocopa violacea (b-d) and two landscape metrics : edge density (ED, a-b) and Shannon diversity (SHDI, c-d). In (b) and (c), the specieslandscape relationship is considered to be structured spatially : characteristic scales (black arrows) are dened at the minimum AIC value, i.e. 2,000 m and 5,000 m respectively. In (a) and (d), AIC values are not considered statistically dierent across models (∆AIC < 5) : there are no characteristic scale of eect. Error bars correspond to ±2.5 AIC.

  Figure 3.2 Box plot of the range of observed characteristic scales across landscape metrics (maximum n = 17) for each species. The thick black vertical lines represent the median characteristic scale ; boxes represent the interquartile range ; the whiskers represent values that are 1.5 times the interquartile range from boxes. Black dots represent outlier characteristic scales for some landscape metrics.

Figure 3 . 3

 33 Figure 3.3 Box plot of the range of observed characteristic scale across species (maximum n = 42) for each landscape metrics. The thick black vertical lines represent the median characteristic scale ; boxes represent the interquartile range ; the whiskers represent values that are 1.5 times the interquartile range from boxes. Black dots represent outlier characteristic scales for some landscape metrics. See Table 3.1 for denitions of metric codes.

Figure 3 . 4

 34 Figure 3.4 Box plot of absolute dierence values of the observed characteristic scales of eect between the dierent thematic resolutions (44 classes, 12 classes, 6 classes and 3 classes). Observed characteristic scale of eect are obtained from the combination of species (n = 42) and landscape level metrics (n = 7).

Figure 3 . 6

 36 Figure 3.6 Box plot of the range of observed characteristic scale across species (maximum n = 42) for each landscape metrics (calculated on the typology with 44 classes). The thick black vertical lines represent the median characteristic scale ; boxes represent the interquartile range ; the whiskers represent values that are 1.5 times the interquartile range from boxes. Black dots represent outlier characteristic scales for some landscape metrics. Metrics are described in Appendix 3. Signicant dierences in characteristic scale were detected between landscape metrics (ANOVA, p.value < 0.001) but not between landscape metrics type (i.e. composition, conguration and functional, ANOVA, p.value > 0.05).

Figure 3 . 7

 37 Figure 3.7 Box plot of the range of observed characteristic scales across landscape metrics (calculated on the typology with 12 classes, maximum n = 27) for each species. The thick black vertical lines represent the median characteristic scale ; boxes represent the interquartile range ; the whiskers represent values that are 1.5 times the interquartile range from boxes. Black dots represent outlier characteristic scales for some landscape metrics. Signicant dierences in characteristic scale were detected between species and between taxonomic orders (ANOVA, p.value < 0.001).

Figure 3 . 8 Figure 3 . 9

 3839 Figure 3.8 Box plot of the range of observed characteristic scale across species (maximum n = 42) for each landscape metrics (calculated on the typology with 12 classes). The thick black vertical lines represent the median characteristic scale ; boxes represent the interquartile range ; the whiskers represent values that are 1.5 times the interquartile range from boxes. Black dots represent outlier characteristic scales for some landscape metrics. Metrics are described in Appendix 3. Signicant dierences in characteristic scale were detected among landscape metrics (ANOVA, p.value < 0.001) but not between landscape metrics type (ANOVA, p.value > 0.05)

Figure 3 .1

 3 Figure 3.10 Box plot of the range of observed characteristic scale across species (maximum n = 42) for each landscape metrics (calculated on the typology with 6 classes). The thick black vertical lines represent the median characteristic scale ; boxes represent the interquartile range ; the whiskers represent values that are 1.5 times the interquartile range from boxes. Black dots represent outlier characteristic scales for some landscape metrics. Metrics are described in Appendix 3. Signicant dierences in characteristic scalewere detected between landscape metrics (ANOVA, p.value < 0.001) and also between landscape metrics type (ANOVA, p.value < 0.01).

  Finally, the relationship between specialization level and niche position provides information on specialization types : (i) species with high values of specialization and niche position on either side of the gradient are considered specialists of homogeneous landscapes (ii) species with high values of specialization and niche position at intermediate part of the landscape gradient are considered complementing species ; and (iii) species with low values of specialization are considered generalists regardless of their niche position. To our knowledge, this relationship between preference of species and their eective levels of specialization is rarely assessed at large scale in the literature.

  To obtain a continuous description of the landscape around each site, with a gradient from forests to open natural or semi-natural landscape units, a twostep approach was chosen. First, 200 m circular buers were intersected with the Terra MODIS Vegetation Continuous Fields (VCF) dataset[START_REF] Dimiceli | Annual Global Automated MODIS Vegetation Continuous Fields (MOD44b) at 250 m Spatial Resolution for Data Years Beginning Day[END_REF]. Remote sensing tools such as VCF provide large scale, continuous and standardized datasets of environmental variables[START_REF] Pettorelli | Satellite remote sensing for applied ecologists : opportunities and challenges[END_REF]. They are particularly ecient to evaluate spatial gradients of vegetation cover and how they correlate with species abundances. The VCF dataset provides continuous proportional estimates (percent cover) for three land cover types : woody vegetation, herbaceous and woodland-shrub vegetation, and bare ground. The distance of 200 m represents twice the maximum bird sampling distance.Although bird distributions are driven by relatively large scale response to landscape features[START_REF] St-Louis | Satellite image texture and a vegetation index predict avian biodiversity in the Chihuahuan Desert of New Mexico[END_REF], local abundance, hence niche position, is likely to depend more on resource use at local scales[START_REF] Mueller | Scale-sensitive landscape complementation determines habitat suitability for a territorial generalist[END_REF].

Figure 4 . 1

 41 Figure 4.1 Example of four relationships between predicted values of species abundance and the Percent Tree Cover (PTC) gradient used to estimate the niche position of each species (black arrows, see methods for more details). (a) Signicant negative quadratic relationship for Anthus trivialis : optimum PTC value (i.e. niche position) is calculated as the vertex point of the quadratic curve (i.e. -β/2α, eqn 1). (b) Signicant (positive) linear relationship for Streptopelia turtur : optimum PTC is estimated as the maximum PTC value in the dataset for this species. (c-d) Signicant positive quadratic relationship for Carduelis cannabina (c) and Oenanthe oenanthe (d) : optimum PTC values are estimated as the minimum PTC value observed in the dataset for these species.

Figure 4 . 2

 42 Figure 4.2 Relationship between specialization indices and optimum values of Percent Tree Cover at the species (a) and community (b) levels. The blue lines depict the second order polynomial regression ; the corresponding adjusted R-squared are shown (a) Relationship between Species Specialization Index (SSI) values and optimum values of Percent Tree Cover (PTC) for 82 common breeding bird species in France. The ribbon corresponds to 95% condence intervals. Horizontal error bars represent 95% condence intervals approximated from a Bayesian framework on optimum values of PTC calculated from -β/2α (see methods and appendix D). (b) Relationship between Community Specialization Index (CSI) values and Mean Community Optimum (MCO) for bird communities in 9869 sites in France.

Figure 4 . 5

 45 Figure 4.5 Boxplot of dierence values between Species Specialisation Index (SSI) calculated on a range of 6 to 12 classes with SSI values calculated on 10 landscape classes for the 82 species (see Appendix A).

Figure 2

 2 Figure 2Flow chart explaining the bibliographical analyses performed on Web of Science Core Collection (Thomson Reuters, NY) and their results. Dashed boxes represent search on bibliographical corpus. Green dashed boxes mean that search is done on title, abstract and keywords of each publication. Red dashed boxes mean that search is done on entire text. We first identified a corpus of articles (n) dealing with habitats conservation in the N2000 sense, by selecting all the articles containing occurrences of "Habitat(s) Directive" or "Habitat(s) of Community Interest" or "Special Area(s) of conservation" in their abstracts, titles or keywords in the Web of Science CoreCollection (timespan: 1970Collection (timespan: -2016; extensive list of articles can be found in SI-Table5). On this first corpus, we then performed three parallel analyses to detect the available scientific knowledge on HCI pertaining to three prominent branches of ecology and conservation: functional ecology (a), invasive ecology (b), and conservation planning (c). The first step of each of the three analyses selects a branch-specific corpus by selecting articles containing occurrences of keywords of the corresponding branch in their title, abstract or keywords (corpuses n func , n inva , n cons , respectively). In a second step, we detect occurrences of keywords of the concerned discipline in the whole text of each article in corpuses n func , n inva , n cons . In a third step, we categorize these occurrences. Occurrences of branch-specific keywords are termed "irrelevant" when the detected words are actually homonyms of the searched words, used in another sense (e.g. searching for occurrences of "function" to detect occurrences of keywords of functional ecology, we select an article where the term "function" is used to refer to a mathematical function). Occurrences of branch-specific keywords are termed "contextual" when they are used to contextualize the study (e.g. in the introduction or the conclusion of the article) or when they appear in articles that do not mention any HCI in their main text. Occurrences are termed "relevant" when they appear in the formulation of scientific results dealing with both HCI and notions pertaining to the concerned branch. The sum of irrelevant, contextual and relevant occurrences can be greater than the size of the corresponding corpus because some words can appear multiple times in the same publication. Notice that, in analysis (a), among the n func articles, none is published in what we considered to be influential journals specialized in functional ecology (Ecosystems, Functional Ecology, Biogeochemistry), influential journals in ecology with sections devoted to functional ecology(New Phytologist, Ecology, Journal of Ecology, Oikos, Oekologia, Ecology Letters, Global Change Biology, Basic and Applied Ecology) or important review journals (Trends in Ecology and Evolution, Annual Reviews ofEcology, Evolution and Systematics, Biological Reviews). As addendum to analysis (b), all invasive species names from DAISIE, TAXREF v9 and EPPO Lists of Invasive Alien Plants (see SI-Table3) were also searched in the general corpus (n = 742) on title, abstract and keywords. Linnaean binomial Latin names were used for each species because complete names (with authors and date) are not always given in articles. All synonyms were also checked using the French Taxonomic Reference Source TAXREFv9 (SI-Table1-C5). This supplementary analysis does not reveal any other relevant articles than those previously detected by the principal analysis with n inva .

Figure 6 . 1

 61 Figure 6.1 Exemple de la méthodologie du focal site multiscale study design . (a) La réponse écologique (e.g. abondance de l'espèce) est échantillonnée sur des sites (i.e. focal sites ). (b) La structure du paysage (composition ou conguration) est mesurée à diérentes échelles spatiales à l'aide de zones tampons. (c) La relation entre la réponse écologique et la structure du paysage est évaluée pour chaque échelle spatiale (i.e. chaque zone tampon). (d) L'échelle caractéristique est déduite de l'échelle spatiale à laquelle la réponse écologique est la mieux prédite par la structure du paysage considérée (ici, 4 km).Tiréde Jackson et Fahrig (2015).

  sant à la modélisation des habitats d'espèces à partir de données d'occupation des sols,[START_REF] Schlossberg | Modeling Animal Habitats Based on Cover Types : A Critical Review[END_REF] montrent les limites d'une telle approche et pointent quatre raisons principales : (i) l'avis d'expert des études, qui est inclus dans 97% des études de la synthèse, montre une grande variabilité sur une même question, (ii) les modèles ignorent les dynamiques des populations, entraînant une surestimation de l'aire d'occupation des habitats, (iii) l'habitat n'est pas synonyme d'occupation du sol et (iv) la sur-simplication des patrons d'utilisation de l'habitat : les préférences à l'habitat des espèces varient de manière continue et pas de façon discrète comme les catégories des modes d'occupations du sol le font dans ces modèles.Perspectives Il serait intéressant de développer cette même approche systématique d'analyse des patrons d'échelle caractéristique sur d'autres groupes taxonomiques. Cependant, l'approche ne peut être identique car le choix des métriques pour mesurer le paysage est contexte dépendant. En eet, il n'existe pas de métrique consensuelle du paysage. L'ensemble de variables choisi dans notre étude l'a été sur la base de la bibliographie (i.e. quelles métriques sont connues pour avoir un impact sur le groupe d'espèces considérées ?) mais il résulte aussi d'une démarche purement méthodologique dans le but d'éviter les redondances corrélatives entre les variables. Comparer les résultats entre diérents groupes taxonomiques paraît donc une tâche complexe.Il semble aussi important de ne pas considérer la détermination des échelles spatiales de réponse des espèces au paysage seulement comme une étape méthodologique mais plutôt d'encourager les études qui les abordent comme une question à part entière. En eet, il apparaît souvent que les approches multi-échelles sont appliquées dans le seul but d'optimiser l'eet corrélatif observé et pour prouver que l'on a bien pris en compte le facteur important qu'est l'échelle spatiale. Cependant, la justication statistique (corrélative)

  systématiquement appliquer à l'aveugle des méthodes similaires au focal site multiscale study design , il semble important de se poser la question de l'échelle à laquelle la relation que l'on veut explorer est attendue. Cependant, poser cette hypothèse n'est possible que quand la relation attendue met à contribution des mécanismes connus. Par exemple, dans le quatrième chapitre, nous basons notre analyse sur une zone tampon de 200 m autour de chaque point STOC sans appliquer d'analyse multi-échelles. Cette analyse pourrait se justier sachant que nous cherchons à modéliser la relation entre l'abondance d'une espèce et une valeur spatiale (le pourcentage de couverture arborée). Cependant, nous avons considéré que cette relation était locale, en faisant l'hypothèse que si les individus étaient comptés sur le site lors du point d'écoute, c'était qu'ils avaient une relation forte avec l'environnement immédiat. Opinion d'expert Cette justication s'apparente à ce que l'on nomme généralement l'opinion d'expert. C'est une approche largement utilisée pour caractériser les relations espèces-habitats mais avec des limites importantes (McBride et al., 2012). Ainsi, Reif et al. (2010) proposent que l'avis d'expert soit réservé aux seuls cas où les données ne sont pas disponibles pour eectuer des mesures quantitatives. De même, Chytrý et al. (2002) montrent que leur mesure de la délité des espèces à des unités de végétation est plus ecace pour déterminer des espèces diagnostics que les avis d'experts. Cependant, dans le chapitre quatre, nous montrons que les mesures des habitats faites à dire d'expert sur la base d'une liste catégorielle prédénie[START_REF] Julliard | Un suivi intégré des populations d'oiseaux communs en France[END_REF] sont aussi ecaces pour mesurer la spécialisation des espèces que la mesure issue du gradient environnemental.

  précipitations, température, latitude) dont certains sont issus du paysage. Nous avons analysé chaque espèce en relation avec chaque métrique du paysage et dans une approche exploratoire, il apparaît que les espèces ne sont pas aectées par toutes les métriques de la même manière (Figure6.3). C'est-à-dire qu'une même métrique peut permettre d'expliquer 30 % de la distribution d'une espèce alors que pour une autre espèce, elle n'expliquera presque rien. Dans l'approche que nous avons développé, la seule variable qui 6.3 Politique publique et habitat était mesurée à diérentes échelles était la métrique paysagère. Ainsi, en cas d'observation d'un patron spatial en comparant les modèles via l'AIC aux diérentes échelles, on pouvait conclure que ce patron était due à la variable paysagère. Cependant, dans certains cas, même si une échelle caractéristique était mesurée, la métrique paysagère expliquait peu le patron de présence/absence (Figure6.3). Ce constat permet d'entrevoir la limite de ces approches statistiques où les seuils de prise en compte des résultats jouent un rôle important.6.3 Politique publique et habitatDans la quatrième partie, la problématique de la représentation de l'habitat est abordée au niveau d'une politique de la conservation. Dans le domaine de la conservation, l'élaboration d'une politique s'appuie en partie sur les connaissances scientiques disponibles.

Figure 6 . 3

 63 Figure 6.3 Partition de la variance expliquée par les variables des meilleures modèles (i.e. les modèles permettant de caractériser l'échelle spatiale de relation entre les espèces et le paysage. Il y a modèle par métrique du paysage.) pour l'espèce (a) Ruptela maculata et (b)Colletes hederae. L'importance des métriques paysagères est très variable au sein des modèles, que ce soit entre les espèces mais aussi au sein d'une même espèce entre les métriques du paysage. Exemples tirés du troisième chapitre. Pour certaines variables, il n'a pas été observé d'échelle caractéristique.

Figure 6 . 4

 64 Figure 6.4 Quand René Magritte peint en 1938 son tableau "Les marches de l'été", il dénonce la régulation mathématique du monde et les théoriciens de l'art, qui depuis l'antiquité, se sont eorcés de xer normes et proportions aux architectures, à l'espace ou encore à la représentation du corps humain. En organisant le chaos des canons de beautés antiques, Magritte tourne en dérision l'ambition normative et le projet de rationalisation du monde. Il pousse ironiquement cette mathématisation du monde en l'appliquant méthodiquement à l'ensemble de son tableau. Il va ainsi jusqu'à soumettre à la géométrie les formes qui lui sont le plus réfractaires : Magritte met le sol et le ciel en équation[START_REF] Ottinger | Surréalisme[END_REF]. On peut faire ici un parallèle avec la représentation que nous avons de l'environnement en tant qu'écologue. Quand le surréaliste artiste dénonce la mathématisation artistique du monde, le réaliste scientique met en équation le monde pour mieux le comprendre. En tant qu'écologue, ce tableau nous appelle aussi à ne pas nous détacher trop du monde réel présent derrière nos chires et modèles mathématiques.

  or populations. As presented by[START_REF] Bean | Species distribution models of an endangered rodent oer conicting measures of habitat quality at multiple scales[END_REF], two majors problems hide the potential interest of environmental suitability to determine habitat quality : good datasets and scale issues.[START_REF] Monnet | Evidence of a link between demographic rates and species habitat suitability from post release movements in a reinforced bird population[END_REF] attempted also to link demographic parameters to environmental suitability obtained from species distribution modeling but the study is based on an outstanding dataset that allows lling this gap. Nevertheless, more and more studies are trying to uncover processes that link environmental suitability with demographic parameters (e.g.Pellissier et al., 2013;[START_REF] Tôrres | Can species distribution modelling provide estimates of population densities ? A case study with jaguars in the Neotropics[END_REF][START_REF] Unglaub | Linking habitat suitability to demography in a pond-breeding amphibian[END_REF].

  Landscape analysisThe CORINE Land Cover dataset[START_REF] Bossard | CORINE Land Cover[END_REF] was used as a representation of landscape. Four dierent thematic resolutions were used, from

	the highly detailed 3	rd level of CLC (44 classes) to a simple description of landscape with
	three classes only (urban, agricultural and natural patches), as often used in the ecological
	literature to facilitate interpretation of processes under study (Suárez-Seoane et Baudry,
	2002). See appendix 3 for more details on these thematic resolutions.
	Circular buers were created around each site with a broad range of 13 radii : 150,
	250, 500, 750, 1000 m and every 500 m between 1,000 and 5,000 m. The smallest radius
	(150 m) was chosen to be relevant to dene a landscape considering the spatial resolution
	of CLC (i.e. 25 m for a pixel, the minimum identiable unit of measurement). The largest
	radius (5000 m) was based on known movement ability of some species in our dataset (e.g.

The rst four taxonomic orders are representative of the diversity of pollinators in Europe

[START_REF] Orford | The forgotten ies : the importance of non-syrphid Diptera as pollinators[END_REF][START_REF] Rader | Non-bee insects are important contributors to global crop pollination[END_REF]

. Presence-absence data for these 42 species over 12,272 sites were used in subsequent analyses. All species identications were validated by expert entomologists.

foraging range of honey bees can reach these distance,

[START_REF] Hagler | Foraging range of honey bees, Apis mellifera, in alfalfa seed production elds[END_REF]

. Each buer was intersected with the four dierent thematic resolutions of CLC at each site, thereby generating a total of ca. 60,000 landscapes. Each of these landscapes was analyzed using Fragstats v4

[START_REF] Mcgarigal | FRAGSTATS v4 : Spatial Pattern Analysis Program for Categorical and Continuous Maps[END_REF]

, which calculates a large set of landscape statistics.

Metrics were calculated either at class level (each thematic resolution dening its own classes, metrics were therefore dierent for each thematic resolution) or for landscape as a whole using the eight cells neighborhood rule for patch delineation. At the landscape level, conguration (e.g. patch density, diversity or shape) and functional (e.g. connectivity and isolation) metrics were calculated. The same metrics were also used to describe each class (e.g. number of patch of forest class) in addition to composition metrics (i.e. percentage of cover of each class in the buer area). All metrics were chosen on the basis of their demonstrated or purported eect on ower-visitors reported in the literature

[START_REF] Carré | Landscape context and habitat type as drivers of bee diversity in European annual crops[END_REF][START_REF] Kennedy | A global quantitative synthesis of local and landscape eects on wild bee pollinators in agroecosystems[END_REF][START_REF] Moreira | Spatial Heterogeneity Regulates Plant-Pollinator Networks across Multiple Landscape Scales[END_REF]

. For example, percentage of agricultural area around observation sites is known to aect negatively pollinators abundance at local scale

[START_REF] Benjamin | Pollinator body size mediates the scale at which land use drives crop pollination services[END_REF]

. Only metrics with low correlation among them (< 0.6) were retained for subsequent analyses resulting in 17 dierent metrics for the coarsest thematic resolution used (Table

3

.1, appendix 3 for other thematic resolutions). All these metrics are fully described in

[START_REF] Mcgarigal | FRAGSTATS v4 : Spatial Pattern Analysis Program for Categorical and Continuous Maps[END_REF]

. All other landscape analyses were performed using R (v3.1.2, R Development Core Team, 2014) and the PostGIS extension of PostgreSQL object-relational database system.

Table 3 .

 3 1 Metrics used to describe the landscape around each Spipoll study site for the nest thematic resolution (n = 17). Acronyms, complete names and codes correspond to the terminology of McGarigal et al. (2012). The complete description of each metric is available in McGarigal et al. (2012). Types of metrics are derived from these descriptions.

	Acronym	Complete name	Code	Metric
					type
	Landscape	Class
	ENN_CV		Euclidean nearest-neighbor distance	P1	Functional
			(coecient of variation)
		ENN_CV.nat	ENN_CV of natural land cover class	P1	Functional
		ENN_CV.urban	ENN_CV of urban land cover class	P1	Functional
	ED		Edge density	L4	Conguration
		ED.nat	Edge density of natural land cover	C5	Conguration
			class
		ED.urban	Edge density of urban land cover	C5	Conguration
			class
	CONNECT		Connectance index	L30	Functional
		CONNECT.nat	Connectance index of natural land	C31	Functional
			cover class
		CONNECT.urban Connectance index of urban land co-	C31	Functional
			ver class
	SHAPE_CV		Shape index (coecient of variation)	P2	Conguration
	AREA_CV		Patch area (in hectares, coecient of	P1	Conguration
			variation)
	SHDI		Shannon's diversity index	L4	Conguration
	PRD		Patch richness density	L2	Conguration
		PLAND.nat	Proportion (%) of natural land cover	C2	Composition
			class
		PLAND.urban	Proportion (%) of urban land cover	C2	Composition
			class
		NP.nat	Number of natural patches	C8	Composition
		NP.urban	Number of urban patches	C8	Composition
	data collection as proxy for weather condition which may aect ower visitors' activity,

Table 3 .

 3 3 Details of other typologies (i.e. thematic resolutions) of Corine Land Cover (CLC) used in the study and their relationships (hierarchical classication). For the typology with 3 classes, water bodies are not taken into account in the calculation of landscape metrics. CLC Code referred to the level 3 of the ocial code denomination of CLC.

	Diptera Coleoptera Coccinellidae Coccinella septempunctata Syrphidae Syritta pipiens Coleoptera Cetoniidae Oxythyrea funesta Hymenoptera Apidae Xylocopa violacea Diptera Syrphidae Myathropa orea Diptera Calliphoridae Stomorhina lunata Coleoptera Cetoniidae Cetonia aurata Hymenoptera Megachilidae Anthidium sp.* Lepidoptera Sphingidae Macroglossum stellatarum Lepidoptera Hesperiidae Ochlodes sylvanus Hemiptera Pentatomidae Graphosoma lineatum Lepidoptera Nymphalidae Aglais io Diptera Muscidae Musca autumnalis Coleoptera Cerambycidae Paracorymbia fulva Lepidoptera Nymphalidae Vanessa atalanta Lepidoptera Lycaenidae Lycaena phlaeas Coleoptera Cleridae Trichodes alvearius Hemiptera Pyrrhocoridae Pyrrhocoris campestris Diptera Syrphidae Rhingia campestris Coleoptera Cerambycidae Ruptela maculata Lepidoptera Nymphalidae Melarnargia galatha Diptera Syrphidae Volucella zonaria Lepidoptera Papilionidae Iphiclides podalirius Lepidoptera Nymphalidae Pararge aegeria Lepidoptera Pieridae Gonepteryx rhamni Lepidoptera Nymphalidae Polygonia c-album Lepidoptera Nymphalidae Argynnis paphia Coleoptera Cetoniidae Valgus hemipterus Lepidoptera Nymphalidae Vanessa cardui	Continued on next page

For Anthidium sp., species are assumed to have similar ecological requirements.

Table 3 .

 3 4 List of landscape metrics (n = 27) used in analysis for the typology of 44 classes. Acronyms, complete names and codes correspond to the terminology of McGarigal et al. (2012). The complete description of each metric is available in McGarigal et al.

	(2012).
	Acronym

Table 3 .

 3 5 List of landscape metrics (n = 27) used in analysis for the typology of 12 classes. Acronyms, complete names and codes correspond to the terminology of McGarigal et al. (2012). The complete description of each metric is available in McGarigal et al.

	(2012).
	Acronym

Table 3 .

 3 6 List of landscape metrics (n = 22) used in analysis for the typology of 6 classes. Acronyms, complete names and codes correspond to the terminology of McGarigal et al. (2012). The complete description of each metric is available in McGarigal et al.

	(2012).
	Acronym		Complete name	Code Metric type
	Landscape	Class
	ENN_CV		Euclidean nearest-neighbor distance (coecient of variation)	P1	Functional
		ENN_CV.urban	ENN_CV of urban areas land cover class	P1	Functional
		ENN_CV.forest	ENN_CV of forest land cover class	P1	Functional
		ENN_CV.othernat	ENN_CV of other natural areas land cover class	P1	Functional
	ED		Edge density	L4	Conguration
		ED.urban	Edge density of urban areas land cover class	C5	Conguration
		ED.forest	Edge density of forest land cover class	C5	Conguration
		ED.othernat	Edge density of other natural areas land cover class	C5	Conguration
	CONNECT		Connectance index	L30	Functional
		CONNECT.urban	Connectance index of urban areas land cover class	C31 Functional
		CONNECT.forest	Connectance index of forest land cover class	C31 Functional
		CONNECT.othernat Connectance index of other natural areas land cover class	C31 Functional
	SHAPE_CV		Shape index (coecient of variation)	P2	Conguration
	AREA_CV		Area (in hectares, coecient of variation)	P1	Conguration
	SHDI		Shannon's diversity index	L4	Conguration
	PRD		Patch richness density	L2	Conguration
		PLAND.urban	Proportion (%) of urban areas land cover class	C2	Composition
		PLAND.forest	Proportion (%) of forest land cover class	C2	Composition
		PLAND.othernat	Proportion (%) of other natural areas land cover class	C2	Composition
		NP.urban	Number of urban areas land cover class	C8	Composition
		NP.forest	Number of forest land cover class	C8	Composition
		NP.othernat	Number of other natural areas land cover class	C8	Composition

  Species specialization measurement For each of 82 species, we used the species specialization index (SSI) as a measure of specialization to categorical landscape units following[START_REF] Julliard | Spatial segregation of specialists and generalists in bird communities[END_REF]. SSI is calculated as the coecient of variation of species density across categories of landscape units. Ten balanced landscape classes were created on the basis of PTC values, all containing the same number of sites (n = 987 except for the last category with 986 sites). The range of PTC values varied between 2.55%

	was used to
	discard sites with dominant urban land cover. All sites with 25% or more urban land cover
	within the 200 m circular buer were discarded, resulting in a nal dataset of 9,869 sites.
	Therefore, a low forest cover in our dataset is indicative of a landscape composed of a
	mosaic of open land cover types (e.g. agricultural or semi-natural areas such as permanent
	grasslands).

([5.54%-8

.09%]) for the narrowest category to 17.36% [58.39%-75.75%] for the broadest one (appendix C). The SSI values calculated on the basis of these categories of PTC are highly correlated with the more classical SSI

[START_REF] Julliard | Spatial segregation of specialists and generalists in bird communities[END_REF]

calculated on the basis of ground-truth landscape units reported by observers in the eld (spearman r = 0.74, p < 0.001, see appendix C).

Table 4 .

 4 1 List of species used in the study and their french names. Species Specialization Index (SSI) and optimum Percent Tree Cover (PTC) values were calculated as described in the methods. Optimum calculation method referred to the method used to infer the optimum PTC values (see methods). SSI values are highly correlated with other specialization measures such as the specialization index of[START_REF] Clavero | Functional homogenization of bird communities along habitat gradients : accounting for niche multidimensionality[END_REF] based on standard deviation of relative occurrences (spearman r = 0.97, p < 0.001).

	Species names	French names	SSI Optimum	Optimum
			PTC		calculation
					method
	Aegithalos caudatus	Mésange à longue queue	0.46	42.82	-b/2a
	Alauda arvensis	Alouette des champs	1.17	0.45	NA
	Alectoris rufa	Perdrix rouge	1.02	1.3	NA
	Anthus pratensis	Pipit farlouse	0.68	4.62	-b/2a
	Anthus trivialis	Pipit des arbres	0.43	39.61	-b/2a
	Carduelis cannabina	Linotte mélodieuse	0.79	0.45	NA
	Carduelis carduelis	Chardonneret élégant	0.52	0.86	min quad
	Carduelis chloris	Verdier d'Europe	0.51	0.36	-b/2a
	Certhia brachydactyla	Grimpereau des jardins	0.58	59.68	-b/2a
	Certhia familiaris	Grimpereau des bois	1.71	87.77	-b/2a
	Cettia cetti	Bouscarle de Cetti	0.58	24.63	-b/2a
	Cisticola juncidis	Cisticole des joncs	0.78	16.01	-b/2a
	Coccothraustes coccothraustes Grosbec casse-noyaux	1.66	73.24	NA
	Columba livia	Pigeon biset	1,00	1.93	min quad
	Columba oenas	Pigeon colombin	0.76	73.24	NA
	Columba palumbus	Pigeon ramier	0.15	75.75	NA
	Corvus corone	Corneille noire	0.3	13.37	-b/2a
	Corvus frugilegus	Corbeau freux	1.02	2.06	NA
	Corvus monedula	Choucas des tours	0.73	1.8	min quad
	Coturnix coturnix	Caille des blés	1.14	0.45	NA
	Cuculus canorus	Coucou gris	0.32	46.26	-b/2a
	Dendrocopos major	Pic épeiche	0.7	61.05	-b/2a
	Dendrocopos medius	Pic mar	1.89	72.91	NA
	Dendrocopos minor	Pic épeichette	0.6	51.97	-b/2a
	Dryocopus martius	Pic noir	1.29	70.84	-b/2a
	Emberiza cirlus	Bruant zizi	0.43	17.75	-b/2a
	Emberiza citrinella	Bruant jaune	0.4	12.13	-b/2a
	Erithacus rubecula	Rougegorge familier	0.64	61.2	-b/2a
	Fringilla coelebs	Pinson des arbres	0.35	71.72	-b/2a
	Garrulus glandarius	Geai des chênes	0.52	55.06	-b/2a
	Hippolais polyglotta	Hypolais polyglotte	0.38	18.76	-b/2a
					Continued on next page

Figure 4.4 Relationship between Percent Tree Cover (PTC) values of MODIS VCF dataset and PTC values of LandSat dataset. The blue line corresponds to a simple linear

Table 4 .

 4 3 For 61 species (i.e. the 67 species with a signicant negative quadratic terms minus six with a vertex point inferred outside of the range 0-100 of PTC), we were able to calculate precision values of the vertex point of the quadratic relationships between species abundances and Percent Tree Cover (PTC) gradient. Standard Deviation (SD)

	Species Aegithalos caudatus Anthus pratensis Anthus trivialis Carduelis chloris Certhia brachydactyla Certhia familiaris Cettia cetti Cisticola juncidis Corvus corax Cuculus canorus Dendrocopos major Dendrocopos minor Dryocopus martius Emberiza cirlus Emberiza citrinella Erithacus rubecula Fringilla coelebs	Optimum PTC SD 2.5% CI 97.5% CI 42.82 0.58 41.72 43.99 4.62 2.77 -2.29 8.74 39.61 0.44 38.76 40.52 0.36 1.98 -3.90 3.83 59.68 1.24 57.55 62.35 87.77 15.20 71.17 130.73 24.63 0.80 23.07 26.22 16.01 1.90 11.44 18.97 13.37 1.25 10.79 15.65 46.26 1.23 44.16 49.01 61.05 1.13 59.14 63.58 51.97 3.72 47.11 61.64 70.84 7.66 62.09 90.14 17.75 0.72 16.20 19.03 12.13 0.97 10.12 13.94 61.20 0.74 59.64 62.58 71.72 1.89 68.47 75.75 Continued on next page

and Condence Interval (CI) were inferred from the a posteriori distribution of vertex points (sample : 5000, thining interval : 1, number of chains : 3). CI are those used in Figure 4.2 of the manuscript.

Table 1

 1 Indeterminacy of translation between the functional ecology literature and HCI practice Th. M üll. & G örs 1969 Plantaginetalia majoris T üxen ex von Rochow 1951 Agropyretalia intermedii-repentis Oberd., Th.M üll. & G örs in Th. M üll. Conservation Letters, xxx 2016, 00(0), 1-11 Copyright and Photocopying: C 2016 The Authors. Conservation Letters published by Wiley Periodicals, Inc.M.Jeanmougin et al.

	The ontology of functional ecology	The ontology of HCI practitioners
			Nonexhaustive list of HCI and non-HCI categories (including syntaxons) to
	Reference	Categories used to describe habitats	which the habitat could belong
	Andueza et al. 2010	Grassland rich in grasses, Grassland	6430 Hydrophilous tall herb fringe communities of plains and of the
		rich in Forbs	montane to alpine levels
	Ansquer et al. 2009	Grazed grasslands	6510 Lowland hay meadows (Alopecurus pratensis, Sanguisorba
			officinalis) Agrostietea stoloniferae Th. M üll. & G örs 1969
	de Vries et al. 2012	Unimproved grassland,	Plantaginetalia majoris T üxen ex von Rochow 1951
		semi-improved and improved
		grasslands
	Gardarin et al. 2014	Grazed and mown permanent
		grasslands
	Garnier et al. 2004;	A successional sere following	Agropyretalia intermedii-repentis Oberd., Th.M üll. & G örs in Th. M üll.
	Cortez et al. 2007	vineyard abandonment in the	& G örs 1969
		Mediterranean region of France	Artemisietea vulgaris Lohmeyer, Preising & T üxen ex von Rochow
			1951
			Crataego monogynae-Prunetea spinosaee T üxen 1962
			6220 * Pseudo-steppe with grasses and annuals of the
			Thero-Brachypodietea
	Vile et al. 2006 ;	Agroecosystems	6430 Hydrophilous tall herb fringe communities of plains and of the
	Garnier et al. 2007 ;		montane to alpine levels
	Fortunel et al. 2009		6510 Lowland hay meadows (Alopecurus pratensis, Sanguisorba
			officinalis)
			Agrostietea stoloniferae & G örs 1969
			Artemisietea vulgaris Lohmeyer, Preising & T üxen ex von Rochow
			1951
			Crataego monogynae-Prunetea spinosae T üxen 1962
			Polygono arenastri-Poetea annuae Rivas Mart. 1975 corr. Rivas
			Mart., B áscones, T.E.Di áz, Fern.Gonz. & Loidi 1991
			Sisymbrietea officinalis Gutte & Hilbig 1975
	Qu étier et al. 2007,	Arable rotation	Stellarietea mediae T üxen, Lohmeyer & Preising ex von Rochow 1951
	Lavorel & Gargulis	Fertilized hay meadow	CORINE Biotopes 81
	2012, Lavorel et al.	Unfertilized hay meadow without	Agrostietea stoloniferae Th. M üll. & G örs 1969
	2010	Festuca paniculata	6430 Hydrophilous tall herb fringe communities of plains and of the
			montane to alpine levels
			6170 Alpine and subalpine calcareous grasslands
			Festucetum paniculatae austro-occidentale centuretosum Lacoste
			1970
		Unfertilized hay meadow with Festuca	6170 Alpine and subalpine calcareous grasslands
		paniculata	Festucetum paniculatae austro-occidentale centuretosum Lacoste
			1970
		Grazed pasture without Festuca	6170 Alpine and subalpine calcareous grasslands
		paniculata	Plantaginetalia majoris T üxen ex von Rochow 1951
		Grazed pasture with Festuca	6170 Alpine and subalpine calcareous grasslands
		paniculata	Plantaginetalia majoris T üxen ex von Rochow 1951
			Festucetum paniculatae austro-occidentale centuretosum Lacoste
			1970
		Never mown >2000m grasslands	6170 Alpine and subalpine calcareous grasslands
			6110 * Rupicolous calcareous or basophilic grasslands of the
			Alysso-Sedion albi
		Steep grazed slopes	6170 Alpine and subalpine calcareous grasslands
			Festucetum paniculatae austro-occidentale centuretosum Lacoste
			1970
			Plantaginetalia majoris T üxen ex von Rochow 1951
			Continued
	2

Table 1 -

 1 C5). This supplementary analysis does not reveal any other relevant articles than those previously detected by the principal analysis with n inva .

				The sample studied only contains HCI	+	+ +	+ + + + + + + + + + + + + + + +	+
									The result
									holds true in
	Ecosystem process	+ + Measurable parameter + + + + + + + + + + + + + + + + + +	• Reclassify the data in terms of HCI • Rerun the analysis	HCI are an unbiaised subsample of the sample studied The sample studied only contains non-HCI	+ +	+ + + +	+ + + + + + + + + + + + + + + + ++ + + + + + + + + + + + + + +	+ +	terms of HCI
		(e.g. effect trait)							The result does
									not hold true in
				HCI are a biaised subsample of the sample studied	+	+ +	+ + + + + + + + + + + + + + + +	+	terms of HCI

Table 1 -

 1 D2) where it occurs. The latest A17E (SI-Table 1-A3) spans over 2007-2012. The methods and results of A17E are gathered by the European Topic Center on Biological Diversity (ETC-BD: SI-Table 1-D3) in a European-wide database (SI-Table 1-C1). France produced an additional, more detailed, database (SI-Table

  on species,Boitani et al. (2015) on ecosystems,[START_REF] Maciejewski | État de conservation des habitats: propositions de d éfinitions et de concepts pour l' évaluation à l'échelle d'un site Natura 2000[END_REF] on habitats), however, prove that the notion of conservation status is still open to largely divergent interpretations-despite purported clarifications in an internal European note (SI-Table 1-A20).

Table 5 (

 5 source or direct downloading url) Tercerie, S., Régnier, C.,Ramage, T., Schoelinck, C., Dupont, P., Vandel, E., Daszkiewicz, P. & Poncet, L. 2015. TAXREF v9.0, référentiel taxonomique pour la France : méthodologie, mise en oeuvre et diusion. Muséum national d'Histoire naturelle, Paris. Rapport SPN 2015 -64. 126 pp. inpn.mnhn.fr/programme/referentiel-taxonomique-taxref (accessed : 2 april 2016) only for DAISIE list with 24 HCI (21%) for 37 species. Some other species were not considered in any analysis : Alnus cordata (Loisel.) Duby, 1828 (index species for HCI 9260, 9380, 9580 and 92A0) was not considered because, though it is listed as Established invasive by DAISIE and as Introduced in TAXREF v9, in France it is mainly present in Corsica, where it is locally considered endemic. Festuca rubra L., 1753 (index species for

	Extensive list of articles analysed in Figure 2 (n = 742)

results

Conservation Letters, xxx 2016, 00(0), 1-11 Copyright and Photocopying: C 2016 The Authors. Conservation Letters published by Wiley Periodicals, Inc.

Conservation Letters, xxx 2016, 00(0), 1-11 Copyright and Photocopying: C 2016 The Authors. Conservation Letters published by Wiley Periodicals, Inc.

Remerciements

Acknowledgements I would like to thank Emmanuelle Porcher for constructive comments and criticisms on earlier drafts of this manuscript.

See the general list of references at the end of the manuscript.

Acknowledgments

We wish to thanks the hundreds of participants of the Spipoll, the OPIE team (Oce Pour les Insectes et leur Environnement) who validated insect identications, Mathieu de Flores and Colin Fontaine for their insights on a previous version of the manuscript, and Reto Schmucki for his help with spatial analysis. M. Jeanmougin was funded by the French Ministère de l'écologie, du développement durable et de l'énergie (DIT/MEDDE), convention n o 2101137682 and the Université Pierre et Marie Curie (UPMC), convention n o 611-13.

See the general list of references at the end of the manuscript.

Acknowledgments

We wish to thanks the hundreds of participants who took part in the national breeding bird survey to whom this paper is dedicated (STOC EPS program).

See the general list of references at the end of the manuscript.

Acknowledgments

We thank P. Castets, S. Coq, S. Gerber, R. Julliard, J.-J. Lazare, M. Lelièvre, M. Martin, G. Meunier, J. Rouchier, E. Porcher, A. Tsoukias, and anonymous reviewers.

Code

A. Unpublished reports

Appendix 4

Results and gures (i.e. box plot) summarizing raw results for the other thematic resolutions that are not showed directly in the manuscript (i.e. typology of 44, 12 and 6 classes, see Appendix 3 for more details about these thematic resolutions). Appendix 5

This appendix is not presented in this manuscript, as it is oversized. However, an URL for dowloading this the appendix is provided :

Appendix 5 (direct downloading url)

This appendix contains in dierent tables the raw results of the observed characteristic scale between species and landscape metrics for each typology used in the study (Tables 1234) and values of Mcfadden pseudo-R 2 for each model (Tables 5678).

Description of each tables : Appendix C SI-Table 4. Complete list of HCI, with codes and official denomination; and list of the HCI present in France, in the different biogeographic region.

SI-Table 5. Extensive list of articles analyzed in Figure 2.

Supporting information 1 (SI-Table 1)

Unpublished sources cited in the article.

Supporting information 3 (SI-Table 3)

List of habitats of community interest present in France, for the identication of which the presence of alien invasive species plays a key role because they are considered index species in the Habitat Books (SI-Table 1-A7). Valid names are from the latest version of the French Taxonomic Reference Source TAXREF v9 (SI-Table 1-C5). To identify invasive statuses, we used three dierent databases : (i) TAXREF v9, which identies a series of invasive species at national level in the list of species present in France, (ii) the European DAISIE database (SI-Table 1-D6), which identies a series of species invasive for Europe as a whole and a series of species native to parts of Europe but invasive in France and (iii) the EPPO Lists of Invasive Alien Plants (SI-Table 1-D7), identifying a series of species invasive at European level. The three lists are markedly dierent. In the context of the present article, we are not in a position to criticize the methodologies used to establish the dierent databases. We therefore take all three sources as equally relevant. All together, these three dierent sources gave us a total of 48 alien invasive species used as index species for 31 dierent HCI. Among the 132 HCI in France, 20 (HCI 1100(HCI , 1120(HCI , 1130(HCI , 1140(HCI , 1150(HCI , 1160(HCI , 1170(HCI , 2150(HCI , 2240, 4080, 5320, 5430, 6150, 6310, 7130, 8240, 8310, 8330, 8340 and 9220) , 4080, 5320, 5430, 6150, 6310, 7130, 8240, 8310, 8330, 8340 and 9220) were not considered in the analysis because their denition in Habitat Books is not based on index species. The ratio of HCI having at least one invasive species as index is hence 31/112 i.e. 28%. Each database taken separately, we obtained 31 HCI (28%) for 46 species in DAISIE, 9 HCI (8%) for 7 species in EPPO and 9 HCI (8%) for 10 species in TAXREF. Trifolium squamosum L., 1759 (index species for HCI 1410), Stratiotes aloides L., 1753 (index species for HCI 3150), Melomphis arabica (L.) Raf., 1837 (index species for HCI 1430), Macrosyringion glutinosum (M.Bieb.) Rothm., 1943 (index species for HCI 4090 and 6210), Angelica archangelica L., 1753 (index species for HCI 6430) and Bupleurum longifolium L., 1753 (index species for HCI 6430), though considered invasive in France according to the DAISIE list, are protected under local conservation regulations in some regions in France. Also, Lindernia palustris Hartmann, 1767 (index species for HCI 3130), Ranunculus macrophyllus Desf., 1798 (index species for HCI 6420) and Aldrovanda vesiculosa L., 1753 (index species for HCI 3150) are considered invasive in the DAISIE list whereas these species are protected at the national level. Removing all these species from the DAISIE list, we found 29 HCI (26%) for 37 species. None of these species is cited in EPPO lists. Native statuses of species were also checked in Euro+Med Plantbase (SI-Table 1-D8). Removing all native species according to Euro+Med Plantbase from DAISIE list, we found 27 HCI (24%) for 38 species. For EPPO lists, one species (Cyperus esculentus L., 1753) was considered native in France by the Euro+Med Plantbase giving 9 HCI (8%) for 6 species. We also checked native status using the national TAXREF database.

Removing these species in the dierent invasive species lists, we obtained slightly dierent