Keywords: climat, chorématique, modélisation graphique, carte, planification urbaine climate, chorematic method, graphical modeling, map, urban planning

graphiques pour exprimer les recommandations concernant les enjeux de climat urbain à Toulouse. La procédure a utilisé une table des chorèmes étendue de modèles dynamiques, en suivant la méthode proposée par H. Théry (1988). Les modèles graphiques produits entrent désormais dans une phase de test, pour en discuter la méthode et l'intérêt avec les acteurs de la planification urbaine.

Proposals for the use of graphical models in urban climatic maps Laurent Jégou

Toulouse II University, Laboratoire Interdisciplinaire Solidarités, Societés, Territoires (LISST), Toulouse, France Najla Touati Toulouse II University, Laboratoire Interdisciplinaire Solidarités, Societés, Territoires (LISST), Toulouse, France Julia Hidalgo National Centre for Scientific Research (CNRS), Laboratoire Interdisciplinaire Solidarités, Societés, Territoires (LISST), Toulouse II University, Toulouse, France

Martha Evonuk

We propose applying the chorematic methodology to the processes and issues addressed by the urban climatic mapping framework, i.e., the interdisciplinary discussion and analysis of thematic data, the production of analytic maps, and the creation of recommendation maps to advise urban planners. After introducing the method, its theoretical basis, and its process, we discuss its fitness and present the possibility of its application in this thematic context. We then propose a first series of applications, for diurnal heat stress and nocturnal urban heat island analysis, as an example and basis for further discussions, based on recent work in the Toulouse agglomeration. We also propose graphical models to express recommendations concerning urban climate issues in Toulouse. The process used the choremes table expanded with dynamic models, according to the multi-step method proposed by H. [START_REF] Théry | Modélisation graphique et analyse régionale. Une méthode et un exemple[END_REF]. The produced models are now entering a test phase to discuss the method with urban planners.

Nous proposons d'appliquer la méthode chorématique au processus et aux questions traitées par la cartographie climatique urbaine, c'est-à-dire dans le cadre de la discussion et de l'analyse des données thématiques et de la création de cartes de recommandations pour l'aide à la décision des acteurs de la planification urbaine. Après une introduction qui présente la méthode, ses bases théoriques et sa procédure, nous discutons de son adaptation et de la possibilité de son application dans ce contexte thématique. Ensuite, nous proposons une première série d'application, pour l'analyse du stress thermique diurne et de l'ilot de chaleur urbain nocturne, en tant qu'exemple et base de discussion, en s'appuyant sur nos travaux récents à l'échelle de l'agglomération toulousaine. Nous proposons aussi des modèles

Introduction

After several research projects on urban climatology in Toulouse (see [START_REF] Dumas | Mise en place de services climatiques au sein de la métropole toulousaine à base d'un réseau d'observation pour le monitoring de l'îlot de chaleur urbain[END_REF] for a comprehensive summary), several challenges have arisen concerning the cartographic representation of the urban climate in Toulouse for urban planing purposes.

Concerning urban climate mapping, there is a whole line of international work initiated by German researchers and disseminated throughout the world [START_REF] Ng | The urban climatic map: a methodology for sustainable urban planning[END_REF]. This dissemination process was greatly pushed by the dynamism of the Asian research teams, especially in Japan and then in China. As part of the french ANR-MApUCE (2014[START_REF] Kwok | How well does the Local Climate Zone scheme discern the thermal environment of Toulouse (France) ? An analysis using numerical simulation data[END_REF] and ADEME-PAENDORA (2017[START_REF] Kwok | How well does the Local Climate Zone scheme discern the thermal environment of Toulouse (France) ? An analysis using numerical simulation data[END_REF] projects, we have tested different cartographic approaches. First of all, an approach which consists in characterizing the urban surface from the microclimatic point of view (inspired by the German and Asian approaches) based on climatopes (Xi et al. 2022). Then, through an approach that takes advantage of the strong skills we have in France in microclimate modeling, and which makes it possible to identify the areas at stake by crossing data on the one hand and urban expertise on the other [START_REF] Hidalgo | Mapping the urban climate for summer comfort management in urban planning: climate analysis and semiology of graphics[END_REF].

Complex spatial data were represented for different uses: analyses, group reflection, and communication with urban planners and city representatives. Several interdisciplinary discussions led to numerous exchanges concerning data generation and processing, as well as data analysis, visualization, and communication. Many diverse types of graphical representations were used, evoking different and sometimes unfamiliar techniques and disciplinary habits in urban climatology. These discussions, concerning complex and interacting spatial phenomena, needed to be based on shared definitions, methods, and effective representation tools that were easily understandable within the entire interdisciplinary team.

As [START_REF] Hidalgo | Mapping the urban climate for summer comfort management in urban planning: climate analysis and semiology of graphics[END_REF] shows, one of the solutions used for the final representation of urban climate issues, aimed at local urban planners, was the schematic form, that is, sketches or graphical simplifications. This solution was the result, in particular, of discussions initiated during the "Climate Geo-Visu" workshops, which focused on a discussion and review of possibilities for graphical representations. In this paper, we explore one of the ideas that emerged: the possibility to use the chorematic method, with graphical models [START_REF] Brunet | La composition des modèles dans l'analyse spatiale[END_REF]. Indeed, graphical models, as per the chorematic method, have an advantage in that they can be used both as discussion and analytic tools and as a means of communication. First, they constitute a combinatorial assembly of simple models, with a graphical representation. Second, they deliberately deviate from a faithful, scaled representation of the spatial reality. This method allows issues to be considered at different scales, in terms of both physical scales and complexity, by distinguishing and comparing individual issues before combining them into a progressively more complex and interactive model. Finally, being models, they can be used to construct predictions based on different scenarios, which is particularly useful in the context of urban climatology. Note that this method is considered as a process and not solely for its resulting graphic form. This paper presents how the chorematic method can be applied to the context and issues classically addressed using the urban climatic map framework (Ng and Ren, 2015) and proposes a first series of applications, as an example and a basis for further discussion.

Graphical models, choremes, and urban climate cartography

The chorematic method, based on graphical models called choremes, marked a milestone in geography and cartographical representation in France at the start of the 1980s, as a result of its contributions and the controversy it triggered (cf. the 76 th issue of the Hérodote journal, published in 1995). Nevertheless, as a method and process of thinking about spatial phenomena, its interest has not been challenged and it constitutes the basis of research in several domains (cf. [START_REF] Lardon | Les Chorèmes face à l'évolution des thématiques et pratiques de recherche, en agronomie et aménagement des territoires[END_REF][START_REF] Enault | La modélisation graphique de phénomènes émergents pour répondre aux besoins de la prospective[END_REF][START_REF] Garbolino | Ecosystem and territorial resilience: a geoprospective approach[END_REF]. Before presenting how the chorematic method can be used in urban climate studies, a short introduction is required.

The chorematic method: a graphical spatial modeling tool Chorematics is a spatial analysis method, that is, the "formalized study of the configuration and properties of the space of societies" (from the Dictionnaire de la géographie by [START_REF] Lévy | Dictionnaire de la géographie[END_REF]. These configurations, patterns, structures, or recurrent spatial forms can be integrated with theories and models of the functioning and evolution of systems (from D. Pumain for the Hypergéo online dictionary, 2004). Originally developed in the framework of regional and modeling geography, the chorematic method expanded into other fields linked with geography, such as urban and land use planning, territorial foresight, and geopolitics.

In a seminal paper in 1980, Roger Brunet proposed a graphical representation of individual spatial configurations based on simple forms, or choremes. With these choremes, one can model complex situations by combination and assembly, in a progressive manner, step by step. This process is the chorematic method. Brunet constructed the first choremes table (Figure 1) and proposed several examples of use to produce models of different territories. Over the years, some complements have been added to this first table, by Brunet and other authors, to develop new choremes and new patterns, including dynamic patterns. The choremes table is often regarded as an alphabet of forms that can be combined as a grammar of graphics to describe territorial patterns.

Figure 1: The first choremes table developed by [START_REF] Brunet | La carte-modèle et les chorèmes[END_REF] Following different applications and experimentations, Brunet published a new synthetic paper on chorematics in 1986 to better describe and structure the method within spatial analyses. Modeling a territory with choremes begins with a search to identify its fundamental structures and dynamics by defining hypotheses about the concepts involved. These hypotheses can be translated into simple graphical forms chosen from the choremes table. Then, these hypotheses can be tested by verifying if the basic models are expressing the fundamental structures, that is, if the produced patterns resemble the observed spatial processes, by adjusting and swapping them into various combinations. It is therefore necessary to go back and forth between the model and reality, combining induction and deduction. Elementary models are combined to produce progressively more complex spatial configurations, which should increasingly mimic the observed reality and, consequently, allow better possibilities for descriptions and explanations. Note that this method is, from the beginning, based upon a graphical representation and visual approach to phenomena, with a strong link to cartography. The creation of a chorematic model is not the simple production of a summary or generalization of a territory, which could result in an oversimplifying schema. This is often the case in examples of simplistic or incomplete applications of the method, cf. [START_REF] Brunet | D'une erreur commune à propos de cartes et de modèles. Commentaire sur « Quel fond de carte pour l'Australie ?[END_REF].

A multi-step method based on two hypotheses

As an example, we can refer to the very enlightening methodological papers of Hervé Théry on Brazil in 1988 and Sébastien Velut on Argentina in 2001. Here, we describe the method using the example of Brazil. According to [START_REF] Théry | Modélisation graphique et analyse régionale. Une méthode et un exemple[END_REF], two hypotheses underlie the chorematic method.

"... [T]he basic assumption is that each point of space is situated in a series of fields which structure space and whose local interference forms a system, that each situation is defined in relation to flows, thus in relation to centers, directions, gradients, limits." "Another strong hypothesis is that these structures and their combinations can be accounted for by models. These models are a simplification of reality, reductive and provisional. They constitute a simple approach to complexity, a tool to be used provisionally until a better one can be constructed."

The method proposed by Théry is summarized by the diagram in Figure 2. The application of this method to the "basic structure" of the progressive settlement of Brazil by Théry is illustrated in Figure 3. The analysis of the spatial distribution of the phenomena, coupled with knowledge of the territory, allows a hypothesis to be formulated about the basic structures, i.e., the individual choremes, that are suitable to model the territory. These choremes are picked from a generic table, either the seminal one of [START_REF] Brunet | La carte-modèle et les chorèmes[END_REF] or from variants developed since by several authors. The assembly of these choremes produces a basic model. Then, it is necessary to identify and model the modifying elements, which are specific to the territory and will transform or disrupt the basic structures. Examples used by [START_REF] Théry | Modélisation graphique et analyse régionale. Une méthode et un exemple[END_REF] include the pioneer front toward the Amazon and the presence of a climatic anomaly, which gives the Nordeste region in Brazil its distinct semi-arid climate. Similarly, we incorporate smaller-scale spatial structures, such as the presence of secondary centers, local dynamics, and/or an active subdivision of the territory. In this way, we obtain derived structures that complicate the model and refine it. However, at this step, the model is still composed of simplified geometric choremes. It is then necessary to consider the contingencies caused by the form of the territory, the general delineation of the borders, and the presence of irregularities or fine transitions to transform the model so that its simplified form looks like that of the territory. Square models are deformed toward a polygonal model whose extension, indentations, projections, or stretching better represent reality.

As the method describes, this process is based on the selection and the simplification of spatial structures, by experts of the domain via a progressive discussion. It goes without saying that the results are eminently of a qualitative kind, the original spatial indicators are simplified and summarized to help model a situation. The value of the results lies in the quality of the analysis by the experts, their discussion and in the quality of the selection and combination of the graphical basic and intermediate models into final models. This final polygonal model is not the only result of the method: the production process itself involves several significant operations that require exchanges, the stabilization of definitions and discussion points, the development of hypotheses, the analysis of elementary phenomena, and a reflection on their combination. The process itself is therefore also an important result of the method. Moreover, this represents a working method that encourages discussion and produces communication tools that are efficient and adapted because they are simple and shared among the team. To quote [START_REF] Théry | Modélisation graphique et analyse régionale. Une méthode et un exemple[END_REF]: "The synthetic and attractive form that is the graphic model -if it is successful at leastmakes it a convenient and quick communication support."

In the framework of interdisciplinary urban climate research between atmospheric physics, climatology, urban geography, urban planning, and cartography and complex spatial phenomena and issues, the chorematic method constitutes an interesting possibility for both the analysis of spatial phenomena and interdisciplinary communication. Before exploring the application possibilities using a local example, it is necessary to quickly present the types of analyses and representations used in the field.

Urban climate cartography: different representations for distinct objectives

Cartographic representations are often used in the field of urban climatology. This type of representation takes several forms depending on the type of analysis, the stage reached in the methodological process, the objectives, and the target audience. The objective here is not to replace effective and validated cartographic representations but to see how the chorematic method can help to compliment these approaches to make them more accessible in an interdisciplinary framework and to accompany a complex process.

A grouping of the different types of spatial data and associated representations was proposed by [START_REF] Ng | The urban climatic map: a methodology for sustainable urban planning[END_REF], as shown in Figure 4. In the 1980s, the introduction of spatial data information and geographic information system tools facilitated the communication of meteorological and climatic information, which are important assets for urban climatic maps. These maps are the result of microclimatic analyses and were found to be a good translation tool for environmental issues. This technique is widely used in Germany, Asian countries, and above all Japan. Many climatic maps have been produced for several cities, such as Kobe and Osaka in Japan (Ashie et al., 2009), Hong Kong [START_REF] Ng | Final Report of Hong Kong Urban Climatic Map and Standards for Wind Environment-Feasibility Study[END_REF], and Singapore. 1Within this approach, the concept of urban climatic maps (UCMaps) is defined via two types of maps: the Urban Climatic Analysis Map (UC-AnMap) and the Urban Climatic Planning Recommendation Map (UC-ReMap).

Urban Climate Maps

A UC-AnMap combines climatic situations and simulations with other urban factors, including land use, topography, and urban geometry. A UC-ReMap, based on the UC-AnMap analysis, proposes orientations for urban planning. Recommendations are defined for different areas and are based on adaptations to strongly exposed climate zones. In Europe, Germany initiated similar microclimatic analyses in several cities (e.g., in the Ruhr region, Berlin, and Stuttgart) and became the leader in UCMap studies in Europe with the construction of synthetic climatic function maps to guide their urban planning.

In Germany, the method developed is the result of work starting in the 1970s and has contributed to the international dissemination of climatic maps in terms of methodology and standards. The VDI 3787 directives published by the Association of German Engineers (VDI) in 1997 and updated in 2015 (Figure 5), have become an international benchmark in the field of urban climatic maps that has inspired many other cities and researchers around the world (Ng and Ren, 2015). UC-AnMaps often reveal a mapping conception closely related to the disciplinary field of the researcher. The German and Hong Kong maps are influenced, in their spatial representation and semiology choices (symbolic representations), by the visions of their urban space-oriented architects and urban planners. The scale and the cartographic legend used also contribute to this pattern. This indicates that climatic maps are designed in a close partnership between town planners (and their internal structures) and researchers. The resulting UC-ReMaps are characterized by a direct approach to the recommendations, indicating precisely what should be done at a fine scale in the city and what actions are required to preserve and/or to improve the climatic conditions (Figure 6).

UCMaps and choremes

How can the chorematic method fit into this well-defined process of producing maps to analyze the urban climate and to advise planners? First, the UC-AnMap is a synthesis of several thematic maps, combining different indicators on climatic characteristics and the geography of the city. Each of these maps can potentially be graphically modeled with basic choremes. The combination of choremes into a synthetic UC-AnMap can then follow the chorematic method of defining and testing specific elements to obtain derived structures and a final graphical model.

As simplified graphical versions of the different elements of a climate analysis, individual choremes can then also be used as discussion tools linking experts from different fields to assess situations and refine positions. They can help communicate a vision or the apprehension of a phenomenon and facilitate discussions to form an awareness, a progessive consensus. Moreover, their graphical form and schematic legend, explaining the processes used, are very pedagogical and enable a non-specialist audience to understand complex phenomena (i.e., spatial, multiple in conjunction, and dynamic phenomena). As Garbolino and Canicio-Voiron (2020) state: "Graphic models are at the same time vectors of communication of expert knowledge and supports for collective thinking."

This pedagogical aspect of choremes was well used in the context of geography textbooks in France in the 1990s, even though they were received at times with criticism and taken as oversimplified models of reality. However, the chorematic method is a process, not just its (graphical) results, as we explain here. A chorematic map model cannot be disseminated alone, its progressive legend and commentary are essential. This is even more important for the UC-ReMap, which is a description of recommendations for urban planners. This map is the result of the interpretation of the UC-AnMap in terms of advice for the evolution of the urbanization of a city, with an emphasis on several key points, such as patterns to preserve or, inversely, to counter. Destined for urban planners, these maps show concrete ideas translated into actions and instructions, e.g., zones that should be preserved or improved. In this case, the chorematic mapping process can play the role of an introduction and an explanation of the instructions to emphasize the proposed actions at the city scale. Here, we are considering the capacity of choremes to model patterns and dynamics at play at the global scale of a city; then, planners can look at the finer details of the instructions, zone by zone or city block by city block.

To illustrate these propositions, we use the example of the UCMaps for the Toulouse Metropole agglomeration in the south of France (cf., [START_REF] Hidalgo | Mapping the urban climate for summer comfort management in urban planning: climate analysis and semiology of graphics[END_REF]. In the continuation of this work, we will test their pertinence and effectiveness with urban planners and local elected officials by the way of workshops.

Application to the case of Toulouse

The work in Toulouse, in the context of two successive research programs and seminars, served as an opportunity to test the potential of the chorematic approach. Here, we present the processes leading to a UC-AnMap concerning the urban heat island and diurnal heat stress issues and UC-ReMaps adapted to the current urban planning policies.

A graphical model of night-time Toulouse's urban heat island

The Toulouse Metropole worked on its last Urban Master Plan, from 2015 to 2019, incorporating several ongoing scientific studies characterizing its main environmental and social issues. As part of this work, the urban heat island (UHI) at night, the thermal comfort during the day, and the wind conditions were investigated using a meteorological model [START_REF] Kwok | How well does the Local Climate Zone scheme discern the thermal environment of Toulouse (France) ? An analysis using numerical simulation data[END_REF] to define their spatial structures. A typical summertime meteorological situation with high daytime temperatures and a strong nocturnal UHI was selected using the local weather type approach developed by [START_REF] Hidalgo | On the use of local weather types classification to improve climate understanding: An application on the urban climate of Toulouse[END_REF]. Climatic analysis and recommendation maps (the terminology used in French was "strategic maps") were developed for the diurnal heat stress levels, nocturnal UHI, and wind (Figure 7). The maps produced (Figure 7) are the result of the analysis of several indicators: air temperature for the nocturnal UHI and a synthetic indicator of diurnal heat stress (the Universal Thermal Climate Index, UTCI2 ) that involves air humidity, wind speed, and solar radiation. These indicators are themselves synthetic, the result of a statistical analysis, from a numerical simulation that produce continuous spatial values.

The maps show multiple spatial structures. The spatial extension of the exposure to the UHI is not the only feature shown on the maps; several spatial co-occurrence and geographical issues are implied for the urban planner, e.g., types of land use and zoning, natural cooling areas.

A first attempt to produce simplified forms resulted in sketches and schematic maps, as shown in Figure 7 (bottom). To better explain and represent the spatial structures found in the analysis and discuss them with the diverse team members, a chorematic method was engaged. Following the method described earlier in Section 2, several individual basic models were selected to start the process. The UHI illustration presents a classic concentric spatial structure, with a central part showing high exposure and a peripheral zone with a lesser but worrying level of exposure. These classes (and their spatial limits) were defined by the experts of urban climate. To these researchers, the crucial issues were the spatial extents of these areas, as well as their evolution (changeover line), constraints, impacts and their relationship with the geographical terrain (the thermal regulation zones and the river). To take this into account, different basic graphical models were selected and tested. They formed the starting point of the chorematic method and the resulting illustration legend. The models were selected from the choremes table, with the addition of color and dithering to express the dynamics. The resulting basic model was very simple (Figure 8), a starting point for discussions about the involved phenomena.

The second step, as per the method, was to determine the modifiers to the basic structures and to express them graphically using variants of the choremes. The UHI is in fact complicated by the existing suburbs and suburban cities. The contact area between the different exposure-level zones, the changeover line, is central to the representation, and this contact area is dynamic. The thermal regulation areas (the green and blue zones) are distorted by the relief and the watershed effect. The river effect has a large impact on the city center. These modifications were graphically modeled, producing the graphical models in the middle column of Figure 9. Then, these modifiers were applied to the basic structures to produce more pertinent models of the situation, models that more efficiently represent the interpretation of the indicators: the UHI with peripheral zones, a transition area, dynamic cooling patterns, and a subdued river effect in the city center. The theoretical model obtained after this third step (Figure 10) represents the situation more closely. Its general form remains circular and abstract; therefore, the final step was to refine it to look more like the form and disposition of the agglomeration. The final model was then ready to be shown to local partners and discussed, in relation to urbanplanning policies, at the agglomeration scale. This model expresses, in a synthetic and spatial manner, the main issues of the UHI in Toulouse and offers a basis for discussions between researchers, urban planners, and representatives of inhabitants.

A graphical model of diurnal thermal comfort in Toulouse A thermal comfort analysis was conducted using the UTCI, following the recommendations of the International Society of Biometeorology,3 considering several factors and indicators. The results show a complex situation for the Toulouse agglomeration, again with several spatial patterns that we have attempted to graphically model using choremes. The basic choremes used (Figure 11) for the modeling process were approximately the same as those used for the UHI; the implicated spatial structures revolved round the same patterns: centerperiphery, punctual evolutions, axes of propagation, contacts, and catchment areas. The final graphical model shows (Figure 12) the expert's interpretation that the peripheral municipalities are less intensely impacted by diurnal heat stress than nocturnal UHI and that the thermal discomfort tension is higher between the center fresh island (in white) and the first ring of suburbs (in red).

As mentioned in the introduction, the chorematic method can also be used to communicate recommendations derived from analyses of urban climate issues.

Graphical models to express recommendations to planners

Tentative models of recommendation choremes were produced (Figure 13), building on analyses of the UHI and the thermal comfort. These graphical models complement each other to express advice and the means to alleviate climatic issues occurring by day (thermal comfort) and night (UHI) at the scale of the agglomeration. The UC-ReMap models used the same graphical modeling process following the chorematic method; however, the recipients, the urban planners, and the local representatives working on the master plans, were less available for long and progressive work on basic models, modifiers, and derivative structures. Therefore, we plan to organize workshops, perhaps as serious games, to present these results, the chorematic urban climate analysis and recommendation models and discuss their adequation, usefulness and communication efficiency, allowing the possibility of their modification.

A sort of executive summary was designed by providing a single image with an expansive legend. This design must be supported by a descriptive text or a presentation of the basic choremes, their combination, and the resulting recommendations, highlighting the progressive process. To alleviate the cognitive difference between a classic map and a simplified form model, a comparison chart should also be provided.

Conclusions

This work contributes to international studies of urban climatic mapping by presenting how the chorematic method can be applied to the process of producing maps to analyze the urban climate and to advise urban planners. From a theoretical point of view, the chorematic method is based on graphical models called choremes. Choremes can be treated as an alphabet of forms, which can be combined as a grammar of graphics to describe territorial patterns. This approach, historically used in other fields linked with geography, such as urban and land use planning, territorial foresight, and geopolitics, is proposed here as a method and a process of thinking about climatic spatial phenomena.

After an introduction to the theoretical basis of graphical models and its potential use in urban climatic maps, a proposed application in Toulouse was presented as an extension of previous urban climatic mapping research using more classical representations based on grids and sketches. The proposed models are the result of a long process of interdisciplinary discussion, analysis, and thematic reflection on the UHI (nocturnal) and heat stress (diurnal) issues. The represented spatial objects, or choremes, are the result of a decomposition of the elements of the thematic map into selected basic structures, influenced by specific modifiers and recomposed as graphical models. This method moves away from the original complexity of quantitative indicators to propose a simplified but, we hope, an effective modelling vision of the issues and solutions.

The example of Toulouse demonstrates that graphical models are good communication tools that can enrich exchanges between disciplines. For our team, the process provided a very interesting context in which to define concepts, spatial patterns and interactions between researchers from various disciplines. This experience provides a reminder that our cities, as opposed to being just microclimatic study objects, are, first and foremost, organized geographical and social spaces impacted by environmental issues. It will be interesting to see if a more general and systemic model can emerge through the study of a larger corpus of cities; this idea is currently being explored. Graphical modeling therefore allows us to prioritize our knowledge through its role of synthesis while remaining close to a thematic map [START_REF] Lardon | Les Chorèmes face à l'évolution des thématiques et pratiques de recherche, en agronomie et aménagement des territoires[END_REF]. It can then be presented as a tool to help in decision-making and to facilitate the expression of ideas, contributing to a collaborative approach in the implementation of diagnoses and recommendations. Collaboration with the urban planners and local elected officials in Toulouse is ongoing to test the effectiveness of the models and the process.

Figure 2 :

 2 Figure 2: Diagram of the graphical modeling process using choremes

Figure 3 :

 3 Figure 3: Basic structure example of the progressive settlement of Brazil

Figure 4 :

 4 Figure 4: Structure of urban climatic maps (adapted from[START_REF] Ng | The urban climatic map: a methodology for sustainable urban planning[END_REF]

Figure 5 :

 5 Figure 5: Climate analysis of the city of Berlin

Figure 6 :

 6 Figure 6: Berlin's Climate Atlas: the 2015 planning advice map

Figure 7a :

 7a Figure 7a: Examples of Urban Climatic Planning Recommendation Maps for Toulouse, nighttime

Figure 8 :

 8 Figure 8: Urban heat island (UHI) model step 1: the basic structures

Figure 9 :

 9 Figure 9: UHI model steps 2 and 3: modifiers and derived structures

Figure 10 :

 10 Figure 10: UHI model final step: adaptation to the general form of the Toulouse agglomeration

Figure 11 :

 11 Figure 11: Universal Thermal Climate Index (UTCI) model steps 2 and 3: modifiers and derived structures

Figure 12 :

 12 Figure 12: UTCI final modeling step

Figure 13 :

 13 Figure 13: Graphical recommendation models for the Toulouse UHI (night) and UTCI (day) issues

https://www.coolingsingapore.sg/journal-papers

http://www.utci.org/

http://www.utci.org/

Acknowledgments

We thank Martha Evonuk, PhD, from Evonuk Scientific Editing (http://evonukscientificediting.com) for editing a draft of this manuscript. Acero, J. A., Arrizabalaga, J., Kupski, S., Fernandez, J. G., Katzschner, L., 2012,, "Analyzing urban heat island in Bilbao (Spain), a coastal region." In 8th International Conference on Urban Climate and 10th Symposium on the Urban Environment. International Association for Urban Climate and American Meteorological Society, Dublin,.


Florentine Riquet
email: florentine.riquet@ird.fr

Cécile Fauvelot
email: cecile.fauvelot@ird.fr

Pauline Fey
email: pauline.fey@gmail.com

Daphné Grulois
email: daphne.grulois@hotmail.com

Marc Leopold
email: marc.leopold@ird.fr

Hatchery-produced sandfish (Holothuria scabra) show altered genetic diversity in New Caledonia

Keywords: stock structure, sustainable fishery, genetic outcome, sea cucumber, reseeding

Facing an alarming continuing decline of wild sea cucumber resources, management strategies were developed over the past three decades to sustainably promote development, maintenance, or regeneration of wild sea cucumber fisheries. In New Caledonia (South Pacific), dedicated management efforts via restocking and sea ranching programs were implemented to cope with the overharvesting of the sandfish Holothuria scabra and the recent loss of known populations. In order to investigate genetic implications of a major H. scabra restocking program, we assessed the genetic diversity and structure of wild stocks and hatchery-produced sandfish and compared the genetic outcomes of consecutive spawning and juvenile production events. For this, 1358 sandfish collected at four sites along the northwestern coasts of New Caledonia, as well as during five different restocking events in the Tiabet Bay, were genotyped using nine polymorphic microsatellite markers. We found that wild H. scabra populations from the northwestern coast of New Caledonia likely belonged to one panmictic population with high level of gene flow observed along the study scale. Further, this panmictic population displayed an effective size of breeders large enough to ensure the feasibility of appropriate breeding programs for restocking. In contrast, hatchery-produced samples did suffer from an important reduction in the effective population size: the effective population size were so small that genetic drift was detectable over one generation, with the presence of inbred individuals, as well as more related dyads than in wild populations. All these results suggest that dedicated efforts in hatcheries are further needed to maintain genetic diversity of hatchery-produced individuals in order to unbalance any negative impact during this artificial selection.

Introduction

To meet the rising demand for trepang or bêche-de-mer in the Asian market, sea cucumber fisheries expanded in the 1990s and progressively spread to most tropical countries, while exacerbating fishing pressure and generating major resource sustainability issues [START_REF] Anderson | Serial exploitation of global sea cucumber fisheries[END_REF][START_REF] Purcell | Sea cucumber fisheries: global analysis of stocks, management measures and drivers of overfishing[END_REF]. Wild tropical sea cucumbers are particularly vulnerable to overfishing, as they are easy to harvest in shallow waters. Further, when heavily exploited, wild populations usually show low recovery rate, with scattered spawners impairing the species reproductive success [START_REF] Uthicke | Restricted gene flow between Holothuria scabra (Echinodermata: Holothuroidea) populations along the north-east coast of Australia and the Solomon Islands[END_REF][START_REF] Uthicke | Local examples of beche-de-mer overfishing: An initial summary and request for information[END_REF]. As a result, most sea cucumber stocks keep declining worldwide and show decreasing recovery rate despite implemented management strategies to sustain fisheries, as for instance the fishing moratoria adopted in the Indo-Pacific region [START_REF] Baker-Médard | Sea cucumber management strategies: challenges and opportunities in a developing country context[END_REF][START_REF] Conand | Tropical sea cucumber fisheries: changes during the last decade[END_REF][START_REF] Léopold | Spatial sea cucumber management in Vanuatu and New Caledonia [WWW Document[END_REF][START_REF] Purcell | Sea cucumber fisheries: global analysis of stocks, management measures and drivers of overfishing[END_REF][START_REF] Uthicke | Local examples of beche-de-mer overfishing: An initial summary and request for information[END_REF].

Although ecological function of sea cucumber species in coral reef ecosystems and associated soft substrates are well established [START_REF] Purcell | Ecological roles of exploited sea cucumbers[END_REF], knowledge gaps in the biology and the ecology (e.g. growth rate, mortality, and juvenile recruitment) of most sea cucumbers trigger wild population dynamics difficult to predict and, therefore, to manage [START_REF] Conand | Tropical sea cucumber fisheries: changes during the last decade[END_REF].

Facing the rapid depletion of wild sea cucumber resources, technical advances in artificial reproduction and farming of few high-value species of holothurians have considerably increased over the past three decades (Lovatelli, 2004). Releasing cultured benthic invertebrates such as sea cucumbers in the wild was viewed as a possible strategy to promote development, sustainability, or regeneration of fisheries at national or global scale [START_REF] Bell | Restocking and stock enhancement of marine invertebrate fisheries[END_REF]. Specifically, the sandfish Holothuria scabra has attracted most research effort in the Indo-Pacific region [START_REF] Bermudes | Did you say pislama, dairo, bislama, kereboki or bêche-de-mer?[END_REF][START_REF] Hair | The sea cucumber Holothuria scabra (Holothuroidea: Echinodermata): Its biology and exploitation as Beche-de-mer[END_REF][START_REF] Hair | Optimising methods for community-based sea cucumber ranching: Experimental releases of cultured juvenile Holothuria scabra into seagrass meadows in Papua New Guinea[END_REF]Lovatelli, 2004) due to its high commercial value (e.g. [START_REF] Purcell | Chinese market prices of beche-de-mer: Implications for fisheries and aquaculture[END_REF] and its high potential for restocking [START_REF] Battaglene | Culture of tropical sea cucumbers for stock restoration and enhancement[END_REF][START_REF] Bell | Restocking and stock enhancement of marine invertebrate fisheries[END_REF]. Nevertheless, aquaculture-based stock enhancing strategies may alter genetic diversity of wild populations, depending on the number and geographical origin(s) of the breeders and the highly unpredictable number of released juveniles that will survive and reproduce [START_REF] Hair | Optimising methods for community-based sea cucumber ranching: Experimental releases of cultured juvenile Holothuria scabra into seagrass meadows in Papua New Guinea[END_REF][START_REF] Purcell | Sea cucumber culture, farming and sea ranching in the tropics: Progress, problems and opportunities[END_REF][START_REF] Utter | Genetic problems of hatchery-reared progeny released into the wild, and how to deal with them[END_REF]. Releasing genetically similar sea cucumber juveniles has been recommended to reduce both the introduction of exogenous alleles and outbreeding depression in the target wild population [START_REF] Cross | Genetic implications of translocation and stocking of fish species, with particular reference to Western Australia[END_REF][START_REF] Uthicke | Preservation of genetic diversity in restocking of the sea cucumber Holothuria scabra investigated by allozyme electrophoresis[END_REF][START_REF] Ward | The importance of identifying spatial population structure in restocking and stock enhancement programmes[END_REF]. In that perspective, several studies have recently assessed the genetic diversity and structure of wild sandfish resources to inform restocking projects [START_REF] Ninwichian | Population genetics of sandfish (Holothuria scabra) in the Andaman Sea, Thailand inferred from 12S rDNA and microsatellite polymorphism[END_REF][START_REF] Nowland | Elucidation of fine-scale genetic structure of sandfish (Holothuria scabra) populations in Papua New Guinea and northern Australia[END_REF][START_REF] Ravago-Gotanco | Regional genetic structure of sandfish Holothuria (Metriatyla) scabra populations across the Philippine archipelago[END_REF]. However, to our knowledge, genetic diversity of wild stocks, broodstock, and hatchery-produced juveniles of sandfish has not been concurrently investigated, although such information is critical to assess the genetic effects of hatchery and restocking initiatives, especially in this species listed in the IUCN Red List of Threatened Species [START_REF] Hamel | Holothuria scabra. The IUCN Red List of Threatened Species 2013[END_REF].

To address that concern, we investigated the genetic implications of distinct restocking events of H. scabra in New Caledonia (South Pacific). Exploitation of sea cucumbers in New Caledonia initiated in the 1840s following trade opportunities in China [START_REF] Conand | The fishery resources of Pacific island countries. Part 2[END_REF]. Increasing harvest severely affected sandfish resources in the 2000s [START_REF] Purcell | Sea cucumber culture, farming and sea ranching in the tropics: Progress, problems and opportunities[END_REF], which prompted the provincial fisheries divisions to implement management regulations (e.g. [START_REF] Léopold | Comanaging small-scale sea cucumber fisheries in New Caledonia and Vanuatu using stock biomass estimates to set spatial catch quotas[END_REF] while seeking for sandfish stock enhancement opportunity in shallow, inshore and depleted areas [START_REF] Purcell | Developing optimal strategies for restocking sandfish: a collaborative project in New Caledonia[END_REF]. Genetic homogeneity of sandfish populations was observed along the northwestern coast of New Caledonia using allozyme polymorphism [START_REF] Uthicke | Preservation of genetic diversity in restocking of the sea cucumber Holothuria scabra investigated by allozyme electrophoresis[END_REF], suggesting that releasing hatcheryproduced juveniles from broodstock collected within that area would not cause adverse genetic effects. These results encouraged the fisheries division of the Northern Province of New Caledonia to plan reseeding of hatchery-produced juveniles in the Tiabet area (Northern Province, New Caledonia), where sandfish had locally disappeared due to overfishing. From 2011 to 2014, more than 100 000 hatchery-produced juveniles were released in large sea pens (from 2011 to 2013) or open habitat (in 2014) for restocking the Tiabet Bay. In the present study, we 1) examined the genetic diversity and structure of sandfish wild individuals, including broodstock, and hatchery-produced individuals using highly polymorphic microsatellite markers, and 2) compared the genetic outcomes of different restocking events. Recommendations for future sandfish restocking, stock enhancement and fishery management are eventually discussed based on the survey results.

Materials and Methods

Sampling design

The survey was conducted in the northwestern lagoon area of New Caledonia, from Kone to the north tip of Grande Terre, the Tiabet Bay, chosen as the restocking area consequently to the collapse of wild H. scabra population (Fig. 1). Wild and cultured sea cucumbers were all sampled in 2014 through tegument biopsies and stored in 80% EtOH for genetic study as follows.

First, to assess the spatial genetic diversity and structure of the wild sandfish population at the study scale (ca. 90 km), 400 adults were collected at four sites along the northwestern lagoon of New Caledonia (100 individuals per site), where suitable habitats for sandfish are found on coastal reef flats and seagrass beds. Adults were sampled in the lagoons of Koumac, Tinip, Boyen and Kone (from north to south, sites 1 -4, respectively, Fig. 1) where local fishermen regularly harvest wild populations of H.

scabra.

Second, to assess genetic effects of restocking events, samples from five distinct batches of hatcheryproduced individuals were collected as follow:

-Three batches corresponded to adults produced in hatchery from 2011 to 2013, grown in sea pens in the restocking Tiabet Bay and whose breeders came from a single site (i.e. site 1 or 4; batches A-C, Table 1). Samples were directly collected in the sea pens while being fished.

-One batch was composed of adults that accidentally escaped from damaged sea pens (batch D; Table 1). Batch D was an undetermined subsample of batches A-C (Table 1). This sample was also directly collected in the sea pen while being fished.

Batches A -D therefore represented the bay's new pool of breeders that survived from 2011 to 2013 and were pooled under the BAY label in subsequent analyses.

-The last batch corresponded to hatchery-produced juveniles whose breeders came from site 4 and that were sampled before their release in the restocking Tiabet Bay (batch E, Table 1).

A total of 1626 sandfish (400 wild adults and 1226 hatchery-produced individuals) has been sampled for subsequent genetic analyses.

DNA extraction and microsatellite genotyping

Genomic DNA was extracted using a cetyltrimethyl ammonium bromide (CTAB) protocol [START_REF] Hillis | Molecular Systematics[END_REF]. Forward primers of H. scabra specific microsatellite loci [START_REF] Fitch | Isolation and characterisation of eighteen microsatellite markers from the sea cucumber Holothuria scabra (Echinodermata : Holothuriidae)[END_REF] were labelled with ABI fluorescent dyes and 16 loci were amplified into two multiplex PCRs as follows:

Multiplex1: Hsc1/6-FAM, Hsc20/6-FAM, Hsc12/NED, Hsc42/NED, Hsc11/VIC, Hsc28/VIC, Hsc44/PET and Hsc62/PET; Multiplex2: Hsc4/6-FAM, Hsc49/6-FAM, Hsc17/NED, Hsc24/NED, Hsc48/VIC, Hsc59/VIC, Hsc31/PET and Hsc40/PET. Multiplex PCR reactions were completed in a thermocycler (GeneAmp PCR System 2700, Applied Biosystems, Foster City, CA, USA) using the Type-it Microsatellite PCR Kit (Qiagen) in a final volume of 5 µL containing 2X Master Mix, 0.5X of Q-solution, 0.1μM of each primer (fluorescent-labeled forward primer 6-FAM, PET, NED or VIC) and 50 to 150ng of DNA template. Thirty-three PCR cycles were used with an annealing temperature of 57°C. Amplified fragments were sent to GENTYANE platform (INRA, Clermont-Ferrand, France), where they were resolved on an ABI 3730XL sequencer along with a GeneScan LIZ-500 internal size standard (Applied Biosystems). Alleles were sized using GENEMAPPER v. 4.0 (Applied Biosystems). We used GMCONVERT [START_REF] Faircloth | gmconvert: file conversion for genemapper output files[END_REF] to convert the exported GENEMAPPER table of genotypes.

Data Analysis

Genetic diversity analyses

Genetic diversity was estimated for each sample through (1) allele frequencies, (2) the average number of alleles (N all ), and (3) the average allelic richness per locus per sample (A r ) using the DiveRsity package [START_REF] Keenan | diveRsity: An R package for the estimation and exploration of population genetics parameters and their associated errors[END_REF][START_REF] Team | A language and environment for statistical computing[END_REF]. A second approach, implemented in the ARES package [START_REF] Van Loon | ARES: software to compare allelic richness between uneven samples[END_REF], was also used to estimate allelic richness: while the first approach estimates the expected number of alleles corrected for sampling size based on a rarefaction procedure, the second approach extrapolates (and/or rarifies) the allelic richness beyond the sampling size and provides confidence intervals for any sample size. A sample size up to 100 individuals was used to estimate the allelic richness using the ARES package (A r-ARES ). Genetic diversity was also assessed through expected heterozygosity (H e ) and fixation index (F IS ) using GENEPOP 4.1 [START_REF] Rousset | genepop'007: a complete re-implementation of the genepop software for Windows and Linux[END_REF], which was also used to test for departures from Hardy-Weinberg equilibrium in each sample (10 000 dememorization steps, 500 batches and 5 000 iterations per batch).

Genetic population structure analyses

The genetic structure among samples was assessed by calculating an estimate of F ST [START_REF] Weir | Estimating F-Statistics for the analysis of population structure[END_REF] using GENEPOP 4.1. Exact tests for population differentiation (10 000 dememorization steps, 500 batches and 5 000 iterations per batch) were carried out to test for differences in allele distributions across samples and between pairwise samples. Then, we estimated the assignment of individuals to the different genetic clusters using the individual-based Bayesian clustering method implemented in STRUCTURE v. 2.3.4 [START_REF] Falush | Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies[END_REF][START_REF] Pritchard | Inference of population structure using multilocus genotype data[END_REF]. For each value of the K parameter (ranging from 1 to 7), five replicate chains of 500 000 Markov Chain Monte Carlo (MCMC) iterations were run after discarding 50 000 burn-in iterations. STRUCTURE was first run using the natural populations (sites 1 -4, Fig. 1) using default parameters. As that approach leads to erroneous results when populations are unevenly sampled [START_REF] Puechmaille | The program structure does not reliably recover the correct population structure when sampling is uneven: subsampling and new estimators alleviate the problem[END_REF][START_REF] Wang | The computer program structure for assigning individuals to populations: easy to use but easier to misuse[END_REF], an admixture model with uncorrelated allele frequencies and the alternative prior was applied when adding hatchery-produced samples. Following Wang (2017)'s recommendations, several models were tested, in which the initial alpha parameter varied from 0.15 (c.a. ⅙, if K=6) to one (K=1, suggesting one panmictic population). Since varying alpha parameter led to very similar results, results with alpha = 0.5 (½, with a "true" K=2) were thereafter presented. To determine individual ancestry proportions that best matched across all replicate runs, CLUMPP [START_REF] Jakobsson | CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure[END_REF] was used and individuals' assignment was visualized using the R software.

The use of multiple methods for determining genetic structure is usually advocated, STRUCTURE making strong priors and hypotheses that are usually challenged (e.g. requirements of Hardy-Weinberg and Linkage equilibria; [START_REF] Jombart | Discriminant analysis of principal components: a new method for the analysis of genetically structured populations[END_REF]. In addition to F ST estimates and in order to graphically visualize the overall genetic distance between samples, the genetic structure among sampling sites was also depicted using Principal Component Analysis (PCA) was performed using the R package ADEGENET 1.4-2 (Jombart, 2008;[START_REF] Jombart | Reconstructing disease outbreaks from genetic data: a graph approach[END_REF], a distance-based approach for which few (nearly no) assumptions may be violated. In addition, the model-free Discriminant Analysis of Principal Components, DAPC [START_REF] Jombart | Discriminant analysis of principal components: a new method for the analysis of genetically structured populations[END_REF], which is also a multivariate genetic clustering method that does not make use of linkage equilibrium or Hardy-Weinberg Equilibrium, or any genetic model, was applied as well.

Kinship analyses

To investigate whether released hatchery-produced individuals are more related one to each other than with wild individuals, relatedness coefficients between all pairs of individuals were computed using the approach described in [START_REF] Wang | Triadic IBD coefficients and applications to estimating pairwise relatedness[END_REF][START_REF] Wang | coancestry: a program for simulating, estimating and analysing relatedness and inbreeding coefficients[END_REF]. Briefly, this approach uses maximum likelihood to infer the relatedness coefficient between two individuals given population allele frequencies.

As a prerequisite, we tested the performance of the six different estimators described by [START_REF] Wang | coancestry: a program for simulating, estimating and analysing relatedness and inbreeding coefficients[END_REF], aiming to choose with accuracy the relatedness estimator that most suited our dataset. We simulated individuals of known relatedness (e.g. fullsibs or parent-offspring should have a relatedness coefficient of 0.5 in a large random-mating population) using the same locus characteristics than our dataset. Based on these simulations, none of the six estimators of relatedness proposed by [START_REF] Wang | coancestry: a program for simulating, estimating and analysing relatedness and inbreeding coefficients[END_REF] consistently performed better than another (Fig. SI1). Relatedness coefficients were computed with the triadic likelihood estimator (triML) estimator in the subsequent analyses, which showed the highest correlation coefficient among the six tested estimators (Supporting Information 1).

Simulations based on all genotypes were also performed prior to the estimation of relatedness coefficients based on the real dataset to assess variation in relatedness coefficients for four categories targeted in the analysis (full-sibs, half-sibs, parent-offspring and unrelated individuals). The distributions of simulated relatedness coefficients overlapped between the four targeted categories, making it difficult to unambiguously assign a pair of individuals as full-sibs, half-sibs, parent-offsping or unrelated individuals (SI2). Simulated unrelated, half-sibs, full-sibs, and parent-offspring individuals were defined by a relatedness coefficients ranging from 0 to 0.55, 0 to 0.89, 0.02 to 1, and 0.06 to 1, respectively. Pairs with a relatedness coefficient higher than 0.55 were then unambiguously identified as related individuals.

Finally, relatedness estimates, mean relatedness coefficients and their 95% confidence intervals were estimated based on our dataset with a bootstrap procedure (500 iterations). All these analyses were performed using the related package [START_REF] Pew | related: an R package for analysing pairwise relatedness from codominant molecular markers[END_REF].

Inbreeding analyses

To further test for possible inbreeding occurring within samples of hatchery-raised juveniles, individual Multi-Locus Heterozygosity (MLH) was calculated for each individual. MLH is defined as the number of heterozygote locus standardized by the number of loci genotyped [START_REF] David | Reliable selfing rate estimates from imperfect population genetic data[END_REF][START_REF] Szulkin | Heterozygosity-Fitness correlations: a time for reappraisal[END_REF]. In a population with variance in inbreeding, inbred individuals are less heterozygous (i.e. lower MLH). Inbreeding variance generates Identity Disequilibria (ID) -i.e. correlations in homozygosity across loci, a measure of departure from random associations between loci [START_REF] Szulkin | Heterozygosity-Fitness correlations: a time for reappraisal[END_REF]. IDs were measured for each sampling site by calculating the g 2 parameter and its standard deviation using the RMES software [START_REF] David | Reliable selfing rate estimates from imperfect population genetic data[END_REF]. The g 2 parameter measures the excess of double heterozygotes at two loci relative to the expectation under a random association, standardized by average heterozygosity [START_REF] Szulkin | Heterozygosity-Fitness correlations: a time for reappraisal[END_REF], providing a measure of genetic association and inbreeding variance in the population. To test for the significance of g 2 , random reassortments of single-locus heterozygosities among individuals were tested using 1 000 iterations [START_REF] David | Reliable selfing rate estimates from imperfect population genetic data[END_REF].

Effective number of breeders (N b ) estimation

The effective number of breeders that produced the sample N b [START_REF] Waples | Genetic estimates of contemporary effective population size: to what time periods do the estimates apply?[END_REF] was estimated within each sample. We measured the non-random association of alleles at different loci within F1 population [START_REF] Hill | Estimation of effective population size from data on linkage disequilibrium1[END_REF] using a bias correction [START_REF] Waples | Seed banks, salmon, and sleeping genes: effective population size in semelparous, age-structured species with fluctuating abundance[END_REF][START_REF] Waples | ldne: a program for estimating effective population size from data on linkage disequilibrium[END_REF] implemented in NeEstimator v2 software [START_REF] Do | NeEstimator v2: reimplementation of software for the estimation of contemporary effective population size (N e ) from genetic data[END_REF]. Following [START_REF] Waples | Linkage disequilibrium estimates of contemporary N e using highly variable genetic markers: a largely untapped resource for applied conservation and evolution[END_REF]'s recommendations, we excluded alleles with frequencies below 0.02 and random mating was applied according to H. scabra reproductive characteristics.

Results

Heterogeneous genetic diversity among sampling sites

From the originally amplified 16 loci, seven loci were removed from downstream analyses due to either high frequencies of missing genotypes (indicative of null homozygotes caused by null alleles) or multiple peaks profile. A total of 1358 individuals was successfully genotyped at nine polymorphic loci (9.28 % of missing data, two to 32 alleles/locus, Table 2). Mean allelic richness per locus per sample (A r ) and expected heterozygosity (H e ) were homogeneous across samples, ranging from 4.04 (batch B) to 6.59 (site 4) and from 0.453 (batch B) to 0.581 (site 4), respectively (Table 2). Allelic richness (A r-ARES ) varied from 53.7 (95% CI = [42.4 -67.0], batch B) to , site 4, Table 2) at an extrapolated/rarefied sample size of 100. Allelic accumulation curves revealed no significant difference across wild samples (t-test p-values > 0.05, Fig. 2a). However, when comparing the genetic diversity of hatchery-produced samples to that of their respective breeder population(s), we found that the total number of distinct alleles significantly differed between site 1 and batch B (t-test pvalues < 0.05 at a minimum sample size of 24, Fig. 2b and2d) and between site 4 and batches C and E, and BAY (t-test p-values < 0.05 at a minimum sample size of 22, 1 and 53, respectively, Fig. 2c and2e) as the extrapolated/rarefied sample size increased.

Weak but significant genetic structure between wild and released H. scabra

Distance-based analyzes (PCA and DAPC) did not reveal any genetic differentiation across all sampling sites, which was consistent with the observed genetic panmixia among all sampling sites (F IS-wild populations = 0.080 ns, F IS-all populations = 0.091 ns). Only site 2 slightly, though significantly, differed from the three other wild populations (F ST = 0.003 -0.006, Table 3). No wild individual was completely assigned to any new cluster based on STRUCTURE, but rather to an equal admixture for each individual within a cluster (data not shown). However, running STRUCTURE with all populations (i.e. wild and released populations) revealed a different genetic pattern. The K value of 3 provided the best meaningful result with most individuals of batch E assigned to an additional cluster (Fig. 3). Further increases in K did not result in meaningful geographic clusters. F ST analyses converged toward very similar results, indicating weak, yet significant genetic differentiation between batch E and all other sites (from 1% to 2%), and to a lesser extent, between hatchery-produced samples and all other sites (Table 3).

Slightly higher relatedness in released populations than in wild populations

In each sample, relatedness estimates ranged from 0, i.e. unrelated individuals, to 1, i.e.

unambiguously highly related individuals. Most relatedness estimates were however lower than 0.125, meaning that most individuals were unrelated (from 63.61 % in batch A to 74.96 % in site 4, Fig. 4a, without taking batch B into account (see below)). For the relatedness estimates ranging from 0.125 to 0.25, i.e. considered as halfsibs, avuncular or a grandparent-grandchild relatedness, from 13.36 % (site 4) to 16.47 % (site 2) were observed (Fig. 4b). Finally, less than 2.5 % (0.46 % in site 2 to 2.30 % in batch D, Fig. 4d) were identified with a relatedness coefficient higher than 0.55, i.e. the simulated value for which pairs were unambiguously identified as related. Interestingly, batch B showed a different pattern: 33.04 % of relatedness estimates were identified to unrelated dyads while 20.87 % of dyads corresponded to a relatedness coefficient higher than 0.55 (i.e. unambiguously identified as related individuals). Overall, the mean relatedness coefficients ranged from 0.087 (site 2) to 0.317 (batch B) and were not significantly different between wild populations and hatcheryproduced batches (bootstrap p-value > 0.5), with the exception of batch B.

Inbreeding and small effective number of breeders (N b ) in released populations

Individual Multi -Locus Heterozygosity (MLH), i.e. the number of heterozygote locus standardized by the number of genotyped loci, ranged from 1 (batches D and E) to 8 (all sampling sites, except site 2, and batches B and C). MLHs were normally distributed (Shapiro test p-values > 0.5) and no difference was observed in MLH distributions (ANOVA p-value > 0.5). Identity disequilibrium, i.e. a measure of departure from random associations of homozygosity between loci, was identified in four samples, in site 2, in batch D, in batch E, as well as at the BAY scale (Table 2), suggesting that few inbred individuals were present in those samples. All hatchery-produced samples showed a clear reduction in the effective number of breeders (N b ≥ 90%), which greatly contributed to the loss of genetic variation among sandfish juveniles (Tables 2 and4). While large point estimates (N b > 300, with infinite CIs) were inferred in wild populations (Table 2), smaller values of N b (N b < 55) were estimated in hatcheryproduced samples, especially in batch B (N b = 6.9, CI = [3.6, 11.5]).

Cross-analysis of genetic indicators within the hatchery-produced samples

When comparing population genetic estimates among the five batches of hatchery-produced individuals, batch B displayed the smallest N b point estimate, the strongest decrease in genetic diversity, the strongest increase in highly related individuals, and the most important structure when compared to the breeders' site (Table 4). Interestingly, batch A showed the less reduction in N b point estimate, exhibited the less difference in genetic diversity, as well as the less highly related dyads when compared to the breeding site, while it displayed a similar sampled size than batch B (Table 4).

Further, despite the largest sampled size in batch E, all genetic indicators were lower in that batch than in the breeders' population, in the same order of magnitude than batch B. Batches of hatcheryproduced individual with several breeders' origin did not change the decrease in all genetic indicators (e.g. batch D and BAY; Table 4).

Discussion

Setting the scene for restocking events: genetic diversity and structure of wild sandfish stocks

Using nine microsatellite markers, we found that wild sandfish individuals were genetically homogeneous from site 1 to site 4, i.e. over ca. 90 km. This result suggested a large and panmictic population over the northwestern coastline of New Caledonia, as previously observed in the study species by [START_REF] Uthicke | Preservation of genetic diversity in restocking of the sea cucumber Holothuria scabra investigated by allozyme electrophoresis[END_REF] using seven allozyme markers. Restocking, stock enhancement, and fishing regulations of sandfish may therefore be appropriately defined at that scale. The genetic homogeneity observed based on nine microsatellite markers is consistent with the estimated genetic connectivity patterns of H. scabra populations at similar scales (ca. 100km) outside New Caledonia: in Northern Australia [START_REF] Gardner | Population genetic structure of sea cucumbers (bêche-de-mer) in northern Australia (Seafood CRC final report Project 2008/733[END_REF], Papua New Guinea [START_REF] Nowland | Elucidation of fine-scale genetic structure of sandfish (Holothuria scabra) populations in Papua New Guinea and northern Australia[END_REF], Philippines [START_REF] Ravago-Gotanco | Regional genetic structure of sandfish Holothuria (Metriatyla) scabra populations across the Philippine archipelago[END_REF], and Thailand [START_REF] Ninwichian | Population genetics of sandfish (Holothuria scabra) in the Andaman Sea, Thailand inferred from 12S rDNA and microsatellite polymorphism[END_REF]. Although the oceanographic features of the studied areas may differ and should be carefully taken into account, all these studies were however pointing towards genetic homogeneity over a 100km scale. This may question, at the first site, the microsatellite power resolution. Indeed, the four above-mentioned studies used the same microsatellite markers specifically developed for H. scabra [START_REF] Fitch | Isolation and characterisation of eighteen microsatellite markers from the sea cucumber Holothuria scabra (Echinodermata : Holothuriidae)[END_REF] as those of the present study. The set of markers used were however able to detect significant genetic structure among wild populations, although at larger spatial scales. For instance, significant genetic differentiation was observed along the Adaman coast of Thailand, at a 240-360 km study scale [START_REF] Ninwichian | Population genetics of sandfish (Holothuria scabra) in the Andaman Sea, Thailand inferred from 12S rDNA and microsatellite polymorphism[END_REF], suggesting that this set of markers seems thus likely reliable to observe genetic structure. Moreover, despite the genetic homogeneity observed from site 1 to site 4 in the present study, evidence of weak, although significant, population structure among wild populations was found at small spatial scale here (i.e. site 2), possibly due to the geomorphology of the semi-enclosed bay where samples were collected. On the one hand, accordingly to the relationship between dispersal capacities and pelagic larval duration of marine species [START_REF] Shanks | Propagule dispersal distance and the size and spacing of marine reserves[END_REF], the pelagic larval duration of 10-14 days of that species (Hamel et al., 2001) seemed likely consistent with the genetic homogeneity observed from site 1 to site 4. On the other hand, the existence of hydrological and ecological barriers, such as currents, temperature, or salinity [START_REF] Durand | Impact of temperature inversions on SST evolution in the South-Eastern Arabian Sea during the presummer monsoon season[END_REF] as well as species' life history traits (e.g. larval behavior; Whitaker, 2004) may limit gene flow, sometimes over relatively short distances (e.g. [START_REF] Shanks | Pelagic larval duration and dispersal distance revisited[END_REF]. Local retention of water masses in site 2 may limit water exchanges with surrounding habitats and therefore impede larvae movements and consecutive gene flow among local sandfish populations, despite a pelagic larval duration of 10-14 days .

The effective number of breeders (N b ) in the wild sandfish populations in sites 1 and 4 was estimated with infinite upper confidence limit, large, and of the same order of magnitude as the effective population size estimated in the Philippines archipelago [START_REF] Ravago-Gotanco | Regional genetic structure of sandfish Holothuria (Metriatyla) scabra populations across the Philippine archipelago[END_REF]. Although N b estimation accuracy should be cautiously interpreted [START_REF] Hare | Understanding and estimating effective population size for practical application in marine species management[END_REF], such large N b estimates would likely ensure that genetic variation is maintained within these populations in long term, provided that sustainable management practices are enforced. Specifically, following [START_REF] Frankham | Genetics in conservation management: revised recommendations for the 50/500 rules, Red List criteria and population viability analyses[END_REF], N b estimates were close or higher than the reference threshold (N b = 1 000) that would allow for maintaining evolutionary potential in perpetuity in both sites (sites 1 and 4), while lower limit of N b confidence intervals, i.e. an indicator of the lowest possible level of N b [START_REF] Hare | Understanding and estimating effective population size for practical application in marine species management[END_REF], was higher than the critical threshold of inbreeding depression (N b = 100) in sites 2 and 3. Because panmixia was observed among wild populations from site 1 to site 4 -site 2 significantly differing from these sites-, N b estimates would be closer to a metapopulation size of contemporary generations than the local effective population size (N e , [START_REF] Palstra | Genetic estimates of contemporary effective population size: what can they tell us about the importance of genetic stochasticity for wild population persistence?[END_REF][START_REF] Waples | Genetic estimates of contemporary effective population size: to what time periods do the estimates apply?[END_REF], which would partly explain the high effective population size estimates in the study area. Although we used a unique approach to estimate N e while estimations would gain in confidence by using several approaches, the high N b estimates appeared not supportive of the worldwide IUCN endangered status of the sandfish. Such a high effective number of breeders would theoretically allow for developing hatchery procedures and subsequent restocking and stock enhancement programs that can maintain wild genetic diversity if properly managed (see section 4.2).

Effective population size (N e ) should however be interpreted in comparison to census population size (N c ) in the conservation management context. The N e /N c ratio is indeed important for disentangling the relative risks that demographic, environmental and genetic factors might pose for population persistence in short term [START_REF] Frankham | Effective population size/adult population size ratios in wildlife: a review[END_REF][START_REF] Palstra | Genetic estimates of contemporary effective population size: what can they tell us about the importance of genetic stochasticity for wild population persistence?[END_REF]. The theoretical N e /N c ratio is expected to be ca. 0.5 for a wide range of species displaying different demographic and reproductive life traits [START_REF] Nunney | The influence of mating system and overlapping generations on effective population size[END_REF][START_REF] Nunney | The influence of variation in female fecundity on effective population size[END_REF], a ratio reevaluated to 0.1 [START_REF] Frankham | Effective population size/adult population size ratios in wildlife: a review[END_REF]. However, this ratio may greatly decrease for species displaying high fecundity and high mortality in the early stages [START_REF] Palstra | Genetic estimates of contemporary effective population size: what can they tell us about the importance of genetic stochasticity for wild population persistence?[END_REF], such as encountered in many marine invertebrates [START_REF] Eldon | Current hypotheses to explain genetic chaos under the sea[END_REF][START_REF] Hedgecock | Does variance in reproductive success limit effective population sizes of marine organisms?[END_REF], and sea cucumbers in particular. In case of a very low ratio, i.e. when only a few breeders effectively reproduce, the N e /N c ratio may be approximated by N b /N c [START_REF] Hedrick | Large variance in reproductive success and the N e /N ratio[END_REF]. In this study, the census population sizes (N c ) were estimated at around 500 000 and 220 000 individuals in sites 3 and 4, respectively, based on previous surveys by [START_REF] Léopold | Comanaging small-scale sea cucumber fisheries in New Caledonia and Vanuatu using stock biomass estimates to set spatial catch quotas[END_REF][START_REF] Léopold | Spatial sea cucumber management in Vanuatu and New Caledonia [WWW Document[END_REF]. N c is thus three orders of magnitude higher than the effective population size in both cases (N b /N c =0.6 10 -3 in site 3 and 4.4 10 -3 in site 4). Such very low, estimated N e /N c ratios were therefore typical of species exhibiting high variance in reproductive success [START_REF] Eldon | Current hypotheses to explain genetic chaos under the sea[END_REF][START_REF] Hedgecock | Does variance in reproductive success limit effective population sizes of marine organisms?[END_REF], but also of species displaying fluctuations in population size through time [START_REF] Nunney | The influence of mating system and overlapping generations on effective population size[END_REF][START_REF] Vucetich | Fluctuating population size and the ratio of effective to census population size[END_REF]. It should then be carefully taken into account in sandfish population restocking programs as an indicative parameter for tracking temporal trends in wild populations and that rapid and low-coast genetic monitoring can be used to detect fluctuations in abundance.

Lowering the genetic risk of diversity alteration in hatchery-produced sandfish population

In the present study, five interrelated genetic indicators (A r , F ST , relatedness coefficient, inbreeding coefficient, and effective number of breeders) provided relevant insights for restocking and stock enhancement of H. scabra. During any of the spawning event in hatchery for the present study, estimated N b was lower than the critical threshold defined by [START_REF] Frankham | Genetics in conservation management: revised recommendations for the 50/500 rules, Red List criteria and population viability analyses[END_REF], which increases the likelihood of extinction of hatchery-produced populations in the short term. This finding means that the genetic diversity of hatchery-produced sandfish, lowered by ca. 5-35% when compared to wild populations, was too small to prevent evolutionary potential loss and, ultimately, population extinction if these individuals were grown-out for restocking or stock enhancement. This is likely attributed to the typically-small number of breeders that effectively reproduce in fish and invertebrate hatcheries [START_REF] Araki | Effective population size of steelhead trout: influence of variance in reproductive success, hatchery programs, and genetic compensation between life-history forms[END_REF][START_REF] Boudry | High variance in reproductive success of the Pacific oyster (Crassostrea gigas, Thunberg) revealed by microsatellite-based parentage analysis of multifactorial crosses[END_REF][START_REF] Chapman | Spatial homogeneity and temporal heterogeneity of red drum (Sciaenops ocellatus) microsatellites: effective population sizes and management implications[END_REF][START_REF] Lemay | Microsatellite pedigree analysis reveals high variance in reproductive success and reduced genetic diversity in hatchery-spawned northern abalone[END_REF][START_REF] Rourke | Polygamy and low effective population size in a captive Murray cod (Maccullochella peelii peelii) population: genetic implications for wild restocking programs[END_REF], and particularly in sandfish. Indeed, [START_REF] Gardner | Population genetic structure of sea cucumbers (bêche-de-mer) in northern Australia (Seafood CRC final report Project 2008/733[END_REF] showed that only five out of the 40 breeders were effectively reproducing, being responsible for around 71% of the descendants. The present genetic study is the first to assess the risk of genetic diversity alteration in sandfish restocking and stock enhancement programs and highlighted some weaknesses associated with hatchery-produced samples for restocking, i.e. the important decrease in genetic diversity that will detrimentally affect the released populations. To maximize the effective number of breeders (N b ) and subsequent genetic variability of hatchery-produced juveniles, particular attention must therefore be paid to broodstock management, not only at the initial stages of sandfish restocking and stock enhancement programs, but also at each step during and after reseeding. Large and random subsets of breeders should be collected within the wild panmictic sandfish population to capture a high proportion of the natural genetic diversity as proposed by [START_REF] Purcell | Sea cucumber culture, farming and sea ranching in the tropics: Progress, problems and opportunities[END_REF][START_REF] Quinn | Comment: sperm competition in salmon hatcheries-the need to institutionalize genetically benign spawning protocols[END_REF] and [START_REF] Waples | Genetic interactions between hatchery and wild salmonids: lessons from the Pacific Northwest[END_REF], among others. Moreover, the exchange of broodstocks between hatcheries, the distribution of artificial seedlings to different regions, as well as genetic rescue in the field, can be additional guidance in hatchery-produced samples for restocking. Finally, given the high variance in reproductive success of spawning inducement events and the uncontrolled natural selection during spawning and at early-life stages, long term and appropriate genetic monitoring should be conducted to ensure that genetic variation is maintained throughout the restocking steps and after reseeding.

Conclusion

Using nine microsatellite markers, our study of H. scabra population genetics in New Caledonia revealed one large and panmictic stock in the northwest lagoon area. Restocking and stock enhancement programs and fishery regulations may therefore be defined at that spatial scale. Smallscale genetic variation was however detected in a restricted area, suggesting that locally-based resource management may be suitable in specific environmental context. The relative low resolution of microsatellite markers, thought proven to be efficient for identifying in the present study spatial scales of genetic structure in site 2, would prevent to identify subtle pattern of very low genetic differentiation, difficult to grasp with the limited statistical power of our dataset. To get higher resolution, the easiest way would be to increase the number of markers, e.g. the use of RADassociated SNPs, which also would allow gaining in confidence about N e estimates [START_REF] Luikart | Estimation of census and effective population sizes: the increasing usefulness of DNA-based approaches[END_REF] and investigating the genetic load [START_REF] Plough | Genetic load in marine animals: a review[END_REF]) in a conservation frame. Genetic diversity loss was however found within hatchery-produced populations, which would predictably lead to detrimental effects of genetic drift and inbreeding. Hatcheries should therefore define wild broodstock collection and management procedures to maintain genetic diversity of hatchery-produced stock. Further genetic implications of restocking and stock enhancement programs should be monitored to determine the impacts of hatchery-produced populations on neighbor wild populations. , and population at site 4 and all samples implying breeders originated from site 4 (c). P-values when testing the differences in mean allelic richness are presented between site 1 and all samples implying breeders originated from site 1 (d) and between site 4 and all samples implying breeders originated from site 4 (e). Curves are colored following the hatchery-produced samples (Fig. 1). When a curve falls below the 0.05 horizontal line (grey dotted line), the null hypothesis of equal richness is rejected with a 0.05 confidence level.

Tables

Figures caption Figure 1 :

 caption1 Figures caption

Figure 2 :

 2 Figure2: Allelic accumulation curves of Holothuria scabra of wild populations (a), population at site 1 and all samples implying breeders originated from site 1 (b), and population at site 4 and all samples implying breeders originated from site 4 (c). P-values when testing the differences in mean allelic richness are presented between site 1 and all samples implying breeders originated from site 1 (d) and between site 4 and all samples implying breeders originated from site 4 (e). Curves are colored following the hatchery-produced samples (Fig.1). When a curve falls below the 0.05 horizontal line (grey dotted line), the null hypothesis of equal richness is rejected with a 0.05 confidence level.

Figure 3 :

 3 Figure3: Individual Bayesian ancestry proportions determined using STRUCTURE for wild populations and released samples (A-, B-, C-, D-, E-batches) with K=3 clusters identified. Dotted black lines separate each study site. Sites are labeled as in Fig.1. Each individual is depicted as a vertical bar with colors distinguishing its ancestries to the three clusters.

Figure 4 :

 4 Figure 4: Frequency of pairs of individuals distribution with a relatedness ranging from 0 to 0.125 (a), 0.125 to 0.25 (b), 0.25 to 0.5 (c) and above 0.5 (d). Each study site is colored and labeled following Fig. 1.

  Figure 2 4

Table 1 .

 1 Batches characteristics of hatchery-produced sandfish juvenile that were sampled for further genetic analyses.

	Batch ID	N collected	Release area	Release date	Breeder's site
	A	50	Sea pen (700 m²)	October 2011	site 1
				July 2013
	B	50	Sea pen (1700 m²)	December 2013	site 1
	C	50	Sea pen (2900 m²)	October 2012	site 4
	D*	76	Sea pen	October 2011	sites 1 and 4
				to December 2013
	E	1000	Sea pens (13800 m²)	June to October	site 4
			then open habitats	2014

* Batch D was composed of an unknown percentage of juveniles of sea pens A, B, and C that escaped following sea pen damage and were captured in neighbor open habitat.

Table 2 .

 2 Genetic diversity indices of the study samples using nine microsatellite markers. N: number of individuals, A : effective number of breeders and its 95% CI. A total of 40 individuals were used to estimate A r , which took into account variation of sample size, when examining A r of all samples, and 80 individuals were used when examining A r of the BAY and all other samples (A r given in brackets). Note that A r of the Bay is only estimated in the letter case, while A r of A-, B-, C-, D-and Ebatches in the former case.

	site	N	A r	A r100	CI r100	H e	F IS	g 2	N b	CI -Nb
	Wild populations
	1	98	5.66 (6.61)	69.4	[62.3 -79.0]	0.536	0.074	0.008	∞	[914.3, ∞[
	2	94	6.46 (7.49)	77.1	[70.3 -90.3]	0.572	0.185*	0.035*	369.4	[132.9, ∞[

r : allelic richness, A r100 : allelic richness rarefied/extrapolated at a sampling size of 100 and its 95% CI, H e : expected heterozygosity, F IS : fixation index (p-values of the exact test associated with Hardy-Weinberg non-significant for all samples except for site 2 where a deficit in heterozygotes is observed, F IS > 0), g 2 : estimate of the identity disequilibrium. Probability values for g 2 = 0 were corrected for multiple comparisons: (non-significant, p-value >0.05), * (p-value <0.05), ** (p-value <0.01), *** (p-value <0.001). N b

Table 3 .

 3 Genetic structure (pairwise F ST estimates and probability values from exact tests) between samples. P-values were all significant (p-value <0.001, after Bonferroni correction), except for F ST estimates in bold.

		1	2	3	4	BAY	A	B	C	D
	2	0.004
	3	0.000	0.006
	4	0.000	0.003	0.000
	BAY	0.005	0.013	0.005	0.006
	A	0.007	0.017	0.007	0.009
	B	0.077	0.082	0.079	0.075		0.085
	C	0.014	0.016	0.011	0.008		0.020	0.121
	D	0.005	0.012	0.002	0.007		0.003	0.073	0.018
	E	0.012	0.014	0.017	0.014	0.019	0.016	0.083	0.023	0.021

Table 4 .

 4 Comparison of the genetic diversity, structure and kinship of restocking events regarding the breeding site As N b point estimate of site 1 is infinite, we used the lower bound of the confident interval when comparisons involved this point estimate ** p-values < 10 -3 for all comparisons

		N	Breeding site	Difference in N b point estimates with the breeding site* (%)	Difference in A r-100 with the breeding site (%)	F ST with the breeding site**	Difference in highly related dyads (r>0.5, %)
	A	49	1	-89.95	-6.12	0.007	-10.71
	B	46	1	-99.25	-36.26	0.077	+1053.41
	C	43	4	-96.06	-31.14	0.008	+68.36
	E	771	4	-96.79	-25.48	0.014	-4.77
	BAY	207	1 4	-94.29 -94.62	-6.88 -17.71	0.005 0.006	+33.24 +129.07
	D	69	1 4	-93.18 -93.57	+3.33 -8.70	0.005 0.007	+27.21 +118.72

*

Acknowledgments

We are grateful to Claire Marty, Zacharie Moenteapo, Loïc Bourgine, Yoané Tein-Bai, Jérôme Azzaro, and Jean-François Kayara from the Fisheries Division of the Northern Province of New Caledonia for their support for fieldwork, maintenance of enclosures for sandfish, and facilitating relationships with the Tiabet community. We thank the Tiabet's Kanak chief, fishers and other community members for their kindness and commitment during the 3-year project. We also thank Gérard Mou-Tham, Christophe Peignon and Joseph Baly from the IRD center of Noumea for their technical contribution, as well as the SEA (Société d'Elevage Aquacole) sandfish hatchery at Boulouparis, New Caledonia for their collaboration. This study was supported by the Northern Province of New Caledonia as part of the RESCA N°14C212 grant and by the Laboratoire d'Excellence CORAIL (French National Research Agency) through a postdoctoral fellowship.

Data availability

Microsatellite data has been deposited at DRYAD: to be completed after the manuscript is accepted for publication

Author contributions

Florentine Riquet: Data analyses, Writing-Original draft preparation; Cécile Fauvelot: [27.4, 35.1]