Analysis of micropollutant traces in complex environmental solid matrices is a huge challenge, as it requires efficient analytical techniques to reach appropriate sensitivity and specificity. Extraction and purification are crucial steps that must be optimized. Comparing to other classical techniques, QuEChERS method [1],[2],[3] (Quick, Easy, Cheap, Effective, Rugged and Safe) presents the advantage to be rapid, simple, cheap, environment friendly and provides relatively clean extracts. This study aims to optimize two methods for the extraction of 14 pesticides from leaves and 49 urban micropollutants from sediments by QuEChERS.

INTRODUCTION

The authors thank the Loire-Brittany Water Agency and the Rhone Sediment Observatory for financial support.

ACKNOWLEDGEMENT

[1] M. Anastassiades, K. Maštovská and S. J. Lehotay: J. Chromatogr. A ( 2003).

Betaxolol d7 BETd7

Metronidazole METRO -0.0 Salbutamol SALBU 0.6

Carbamazepine d10 CARBAd10

Norfloxacin NORFLO 0.5 Theophylline THEO -0.0

Clarithromycin d3 CLARId3

Ofloxacin OFLO -0.4 Alprazolam APZ 2.1

Diclofenac d4 DICLOd4

Sulfamethoxazole SMX 0.9 Diazepam DIAZ 2.8

Diuron d6 DIUd6

Trimethoprim TRIM 0.9 Nordiazepam NDZ 2.9

Imidacloprid d4 IMId4

Norfloxacin d5 NORFLOd5

Norfluoxetine NORFLUO Metab-Ad 3.8 Diuron DIU 2.7

Ofloxacin d3 OFLOd3

Metformin METFOR Adi -0.5 Imidacloprid IMI 0.6

Paracetamol d3 PARAd3

Carbamazepine CARBA Ae 2.5 Isoproturon IPU 2.9

Propanolol d7 PROPd7

Carbamazepine

Study of matrix effects

Three types of leaves (alder, poplar and oak leaves -decomposed or not) were spiked at three concentration levels.

To limit strong matrix effects, several steps of SPE purification and extract dilution were tested:

-2 Oasis Prime HLB: 6 cc 200 mg and 3cc 60mg -3 dilution factors: 1/2, 1/5, 1/10.

Signal inhibition decreased to less than 16 % after "Pass through" SPE purification (Oasis HLB 6cc 200 mg) and extract dilution (1/10).

Pass through SPE Purification step

We observed a 2 -4 fold increase of the extraction recoveries with the addition of the step of ultrasonic bath during 1 min.

To enhance recoveries, the use of ultrasonic bath during one minute was tested.

  [2] N.F.15662 E.N, 01 Méthode polyvalente de détermination des résidus des pesticides par GC-MS et SL/SM/SM avec extraction/partition avec de l'acétonitrile et nettoyage par SPE disperses (Méthode QuEChERS) (2009). [3] AOAC Official Method 2007.01 Pesticide Residues in Foods by Acetonitrile Extraction and Partitioning with Magnesium Sulfate (2007) REFERENCES CONCLUSIONS AND PERSPECTIVES Two reliable, specific and sensitive methods were developed for the determination of 14 pesticides concentrations in leaves and of 49 urban contaminants concentrations in sediments. Good recoveries and low LOQ were obtained using the QuEChERS method. Such developments now offer new perspectives to better evaluate the effects of organic micropollutants on aquatic ecosystems in laboratory experiments and in situ studies. Optimization of QuEChERS method for the determination of organic micropollutants in complex environmental matrices: applications for agricultural and urban contaminants in leaf litter and sediments FRESHWATER SYSTEMS, ECOLOGY AND POLLUTIONS RESEARCH UNIT -Irstea, Lyon -Villeurbanne Center -France C. Guillemain, A. Daval, C. Miège, C. Margoum Contact : celine.guillemain@irstea.fr

  ANALYSIS FOR AGRICULTURAL AND URBAN CONTAMINANTS F: Fungicide, H: Herbicide, I: Insecticide Metab : metabolite Log Kow: Octanol-water partition coefficient Pesticides UHPLC-MS-MS analysis UHPLC-ESI(+)-QqQ-MS-MS Shimadzu Nexera 2 -API4000 ABSciex, Columns HSS T3 (Pest. analysis) / BEH C18 (Urb. analysis) Waters® 100 mm*2.1 mm, 1.8 µm Mobile phase : gradient with acidified water and acidified acetonitrile 14 pesticides (pest.) indicator of agricultural release and 49 urban micropollutants (urb.) indicator of domestic wastewater release were selected Urban contaminants Ab: Antibiotic, Ac: Anticancer agent, Ad: Antidepressant, Adi: Antidiabetic, Ae: Antiepileptic, AI : Anti-inflammatories, An: Analgesic, Ap: Antilipemic drug, BB: Beta-blocker, Br : Bronchodilator, Bz: Benzodiazepine, D: Diuretic, P: Pesticide, Metab : Metabolite

Use of ultrasonic bath Choice of extraction method

Mass and type of extraction salts, mass and type of purification salts and centrifugation durations were optimized using an experimental design. We compared Accelerated Solvent Extraction (ASE) with QuEChERS by spiking sediment triplicate at 20 ng/g dry weight (dw). QuEChERS method presents better or same recoveries for 90 % of the compounds, shows lower RSD (15 % vs 27 %, n = 3), and is quicker and easier than ASE.

VALIDATION: Linearity range, Limits of quantification (LOQ), Accuracy and repeatability

Linearity range and LOQ were validated for all compounds. Linearity ranges varied from 0.01 to 250 µg/L depending on the compound. LOQ ranged from 2 to 200 ng/g dw.

For both methods, recoveries ranged from 46 to 118 % (except for 12 compounds < 46 %) with RSD ranged from 2 to 26 % (n = 12).


Evangelia G Drakou
email: evangelia.drakou@univ-brest.fr

Robert W Dunford
email: robert.dunford@ouce.ox.ac.uk

Benis Egoh
email: begoh@csir.co.za

Markus Erhard
email: markus.erhard@eea.europa.eu

Estrada Carmona
email: n.e.carmona@cgiar.org

Nora Fagerholm

Susanne Frank
email: s.frank@gicon.de

Christine Fürst
email: christine.fuerst@geo.uni-halle.de

Marina García-Llorente
email: marina.garcia.llorente@madrid.org

Davide Geneletti
email: davide.geneletti@unitn.it

Alberto Giordano

Adrienne Grêt-Regamey

Charly Griffiths

Julen Gonzalez-Redin

Grunewald
email: k.grunewald@ioer.de

Karsten

Carlos Guerra
email: carlos.guerra@idiv.de

Paula A Harrison
email: paharriso@aol.com

Anna-Stiina Heiskanen
email: anna-stiina.heiskanen@ympar-isto.fi

Violeta Hevia
email: violeta.hevia@uam.es

Roland Hiederer
email: roland.hiederer@ec.europa.eu

Tara Hooper

Maud Huynen
email: m.huynen@maastrichtuniversity.nl

Sander Jacobs
email: sander.jacobs@inbo.be

Sarah Jones
email: s.jones@cgiar.org

Nadja Kabisch
email: nadja.kabisch@geo.hu-berlin.de

Eszter Kelemen

Hans Keune
email: hans.keune@inbo.be

Hermann Klug
email: hermann.klug@sbg.ac.at

Leena Kopperoinen
email: leena.kopperoinen@ymparisto.fi

Marion Kruse
email: mkruse@ecology.uni-kiel.de

Ida Kubiszewski
email: ida.kubiszewski@anu.edu.au

Dries Landuyt

Joerg A Priess
email: joerg.priess@ufz.de

Jianxiao Qiu
email: qiujiangxiao@gmail.com

Sven-Erik Rabe
email: rabes@ethz.ch

Inés Rivero
email: ines.mari-rivero@ec.europa.eu

Marí

Anik Schneiders
email: anik.schneiders@inbo.be

Matthias Schröter
email: matthias.schroeter@idiv.des

Nynke Schulp
email: nynke.schulp@vu.nl

Suneetha M Subramanian
email: subramanian@unu.edu

Paul Sutton
email: paul.sutton@du.edu

Ralf Syrbe
email: r.syrbe@ioer.de

-Uwe

Léa Tardieu
email: lea.tardieu@inra.fr

Anne Teller
email: anne.teller@ec.europa.eu

Patrizia Tenerelli

Lida Teneva
email: lteneva@stanford.edu

Christoph Traun
email: christoph.traun@sbg.ac.a

David Vačkář
email: david.vackar@czp.cuni.cz

Sara Vallecillo
email: sara.vallecillo-rodriguez@ec.euro-pa.eu

Ine Vandecasteele
email: ine.vandecasteele@ec.europa.eu

Clara J Veerkamp
email: clara.veerkamp@pbl.nl

Wim Verheyden
email: wim.verheyden@inbo.be

Petteri Vihervaara

Arto Viinikka
email: arto.viinikka@ymparisto.fi

Markku Viitasalo
email: markku.viitasalo@ymparisto.fi

Pilar Vizcaino
email: pilar.vizcaino-martinez@ec.euro-pea.eu

Ulrich Walz
email: ulrich.walz@htw-dresden.de

Bettina Weibel
email: weibel@nsl.ethz.ch

Louise Willemen
email: .l.l.willemen@utwente.nl

Grazia Zulian
email: grazia.zulian@ec.europa.eu

Petteri Vihervaara

Laura Mononen

Fernando Santos
email: fernando.santos.martin@uam.es

Mihai Adamescu

Constantin Cazacu

Sandra Luque

Joachim Maes

Mapping Ecosystem Services 12

List of Contributors

To quantify ES along the different components of the ES cascade, we need to address two questions: what do we measure and how do we measure (Figure 1)? For the purpose of this chapter, we assume that the question as to why we measure (e.g., policy questions, scope of an ecosystem assessment) has been answered.

The first question is addressed in the scientific literature by developing and proposing indicators. Ecosystem service indicators are used to monitor the state or trends of ecosystems and ecosystem service delivery within a determined time interval. In recent years a substantial indicator base has been developed world wide to assess or measure ES.

Once an indicator is proposed or selected for inclusion in an ecosystem assessment, the second question becomes important: how can we measure the service or the indi-

Mapping Ecosystem Services 94

cator in biophysical terms or units? Which methods or procedures should be applied to come to an reasonable estimate of the quantity of service provided?

What

Direct measurements of ecosystem services

Direct measurements of an ecosystem service indicator is the actual measurement of a state, a quantity or a process from observations, monitoring, surveys or questionnaires which cover the entire study area in a representative manner. Direct measurements of ES deliver a biophysical value of ES in physical units which correspond to the units of the indicator. Direct measurements quantify or measure a stock or a flow value. Direct measurements are also referred to as primary data.

Examples of direct measurements of ES (see also As many of these indicators are effectively measured for other reasons, it is not always needed to set up expensive measurement schemes. Most provisioning ES including crops, fish, timber and water are recorded by national and regional governments. Furthermore, certain species groups and taxa are monitored to assess trends in biodiversity.

TESSA1 is a toolkit for rapid assessment of ES at site level which provides many procedures and suggestions for on-site measurement of ES.

Direct measurements and the use of primary data are the most accurate way to quantify ES but they become impractical and expensive beyond the site level or they are simply not available for all ES.

Therefore the next step to consider for biophysical quantification is indirect measurements.

Indirect measurements of ES

Indirect measurements of ES deliver a biophysical value in physical units but this value needs further interpretation, certain assumptions or data processing, or it needs to be combined in a model with other sources of environmental information before it can be used to measure an ecosystem service. Indirect measurements of ES deliver a biophysical value of ES in physical units which are different from the units of the selected indicator.

In For regulating services, modelling is sometimes the only option in order to quantify actual ecosystem service flows. This is particularly evident when ecosystems are regulating or mediating stocks and flows of soil, carbon, nitrogen, water or pollutants. Consider soil protection -also termed as erosion regulation or erosion control -which is the role ecosystems and vegetation plays in retaining soil or avoiding soil being eroded as a result of wind or run-off water. Soil erosion can be measured directly on sites which are prone to erosion, usually cropland on slopes. However, estimating the quantity of soil that is not eroded due to the protective cover of vegetation cannot be measured. It can however be modelled by comparing the amount of soil erosion with a model which simulates the presence of vegetation with a model where the protective vegetation cover is deliberately set to zero or to parameters which correspond to parameters for cropland or bare soil. The difference between these two models results in an estimate of avoided soil erosion and can represent the realised service flow. A similar rationale applies to water purification, air quality regulation or other services which exert control on the fate and transport of abiotic and organic material.

Implementing biophysical methods for decision-making

Ecosystem service assessments have increasingly been used to support environmental management policies, mainly based on biophysical and economic indicators. Therefore ES assessments have to integrate data and information on biophysical ecosystem components, including biodiversity, with socio-economic system components and the societal and policy contexts in which they are embedded.

Quantification of ES using biophysical methods have been used for a number of perspectives and for a variety of purposes, Chapter 4 101 including landscape management, natural capital accounting, awareness raising, priority setting of projects or policies and policy instrument design. However, transferring the outcomes of the biophysical assessments to policy is not straightforward and some additional work is required to ensure a minimum degree of consistency and avoid over-simplistic conclusions.

Different methods are relevant at different policy levels (ranging from international, EU, national, regional and local scales).

Existing literature frequently acknowledges that, in these cases, the interrelationship between different scales must be taken into consideration, which can pose significant challenges. Broad framings for these methods include the work done globally of the Inter-governmental Platform on Biodiversity and Ecosystem Services (IPBES) and the Mapping and Assessment of Ecosystems and their Services (MAES) in the context of the EU Biodiversity Strategy. The initial methodological work on biophysical methods will be the basis for the assessment of the economic value of ES and promote the integration of these values into accounting and reporting systems.

Conclusions

"You can't manage what you don't measure". This well-known expression is also valid for ES which is, in essence, a concept to guide and support the management of natural resources, ecosystems and socio-ecological systems. ES represent the flows of material, energy and information from ecosystems to society. Accurate measurement of these flows as well as the extent and the condition of ecosystems which support these flows is therefore key to base decisions, to monitor progress to biodiversity targets and to create a sound knowledge base for natural capital.

Figure 1 .

 1 Figure 1. Biophysical quantification of ecosystem services (Icons by Freepik).

How to measure? Select an appropriate indicator Select an appropriate method Biophysical quantification of ecosystem services

	tem service. A scientist could be interested usually they are composed of normalised ver-	receive from ecosystems. A stock refers to planning, natural resources management
	in the diversity and density of different bee sions of indicators for single services which are	the capacity of ecosystems to deliver those and conservation has created additional in-
	and bumblebee populations; a farmer may summed or aggregated. They cannot be quan-	benefits. Flows are always expressed per unit dicators. Therefore we list in Table 1 some
	wish to know how far he can rely on wild tified directly but depend on separate quanti-	of time. Timber production serves as a good important initiatives where readers can find
	pollination to help pollinate his fruit trees; a fication of their individual components.	example to illustrate the difference between a selection of indicators, organised from
	biodiversity policy officer may need to know	an indicator which measures the stock and global to sectorial initiatives.
	if, at national scale, pollination services are This chapter does not provide a list with	an indicator which measures the flow. Tim-
	declining or increasing. Clearly, these stake-indicators for ES for the simple reason that	ber production is often measured by quan-In summary, ES indicators express what to
	holders have different information requests there are hundreds of indicators available.	tifying the harvest (how much timber is cut, measure when quantifying ES in a biophys-
	which require different indicators with dif-Many countries and regions have developed	usually expressed in a volume of wood per ical manner. Good ES indicators come with
	ferent biophysical units although pollina-ES indicator sets; the setting of global or re-	unit area and per unit of time, for example, information on their place on the ES cas-
	tion is the common denominator. gional biodiversity targets has also spurred	m 3 /ha/year). Sometimes timber production cade, on the available data, on the targeted
	the development of indicators. Further-	can also be indicated by the available timber audience and the objective and on whether
	The above example also illustrates the im-more, the application of the ES concept for	stock which can be harvested. This difference they assess a stock or a flow.
	portance of spatial and temporal scales. The	is subtle for the case of timber. If the stock is
	issue of scale is frequently presented in all	harvested, stock becomes flow. However, for
	textbooks on ecology as biodiversity and the	other services, the difference between stock
	ecological processes it supports (and thus also the delivery of ES) are heavily dependent on time and space. Processes are influenced by different time cycles (day-night, seasons) and take place at different rates (see also Chapter Scale Location Measuring Nature's Benefits: A Preliminary Roadmap for Improving and flow is important because indicators for Publication stock and flow cannot always be expressed in the same units. Wetlands have a certain Ecosystem Service Indicators (http://pdf.wri.org/measuring_natures_ capacity to clean water but it is not always straightforward to express this capacity in benefits.pdf )
	5.3). The self-purifying capacity of water is, for instance, highly dependent on the veloc-http://www.bipindicators.net/ (report ISBN 92-9225-376-X) terms of pollutant removal (e.g., amount of nitrogen removed or immobilised in the
	ity at which water flows. Water purification services, for example, which can be measured by the amount of pollutant removed, differ Measuring ecosystem services: Guidance on developing ecosystem sediment in kg/ha/year). Often the size of the wetland (in ha) is used as proxy to indi-cate this capacity. The rationale is that larger Global service indicators (ISBN: 978-92-807-4919-5)
	between fast running streams and stagnant lakes with the latter ecosystems having, in general, a higher capacity (more time) to re-http://es-partnership.org/community/workings-groups/thematic-work-wetlands have more capacity to purify water than smaller wetlands. In this context, the concept of ecosystem condition is import-ing-groups/twg-3-es-indicators/
	move nitrogen but a lower capacity to clean organic pollution. Also spatial scale matters. Bees and bumblebees deliver their polli-A Global System for Monitoring Ecosystem Service Change (doi: ant as well (see Chapter 3.5). Not only the quantity (spatial extent) of an ecosystem is important to assess the physical values of 10.1525/bio.2012.62.11.7)
	nation services within a distance of a few hundred metres whereas the storage of car-European website: http://biodiversity.europa.eu/maes/mapping-ecosystems ES capacity, ecosystem quality or ecosystem condition is also an important determinant Sub-global Union article: doi:10.1016/j.ecoser.2015.10.023
	bon in trees operates at almost global scale. Indicators and, in particular, their units of measurement have to consider the scale at which ES are relevant. Sometimes indicators Finland website: http://www.biodiversity.fi/ecosystemservices/home of ecosystem delivery. Changes in ecosys-tems through degradation can thus alter the article: doi:10.1016/j.ecolind.2015.03.041 flows of ES and should thus be measured as Canada Website: https://www.ec.gc.ca/indicateurs-indicators/ well by indicators. Switzerland Website: http://www.bafu.admin.ch/publikationen/publikation/01587/ are designed to be scale independent. This means they can be upscaled or downscaled, a very useful technique for mapping. National index.html?lang=en A final remark on indicators relates to com-Germany article: Towards a national set of ecosystem service indicators: Insights posite indicators or indices which aggregate different sorts of information into a single from Germany (doi:10.1016/j.ecolind.2015.08.050)
	An important question often raised in litera-Spain Website: http://www.ecomilenio.es/informe-de-resultados-eme/1760 number. Usually such indicators are made
	ture on ES is: should indicators measure the Article: doi:10.1371/journal.pone.0073249 for specific purposes or to inform on partic-
	stock and the flow? A service flow refers to	ular challenges with a single value. In a sim-
	the actual use of the actual benefits people	ilar context for ES, such indicators exist but
	Chapter 4	95

Table 1 .

 1 Examples of sources, websites and key publications for ecosystem service indicators.

	Chapter 4

Table 2

 2

	) are counting the number
	of visitors visiting a national park (nature
	based recreation); measuring the total vol-
	ume of timber in a forest stand (timber pro-
	duction); monitoring the release of nitrous
	oxides of a reed bed or deposition of sulphur
	dioxide on leaves (water and air filtration);
	recording the crop yield of a farm (crops);
	measuring the volumetric capacity of a flood
	plain (flood control); monitoring over time
	the improvement of water quality (water
	purification); measuring the abstraction of

http://tessa.tools/


Vincent Roubeix
email: vincent.roubeix@irstea.fr

Michel Coste

A case of close interspecific interactions between diatoms: selective attachment on a benthic motile species

Keywords: Amphora, Nitzschia, Bacillariophyta, bioindicators, niche

Although diatoms are extensively used as bioindicators, positive interactions between species have been rarely investigated. In this study, the attachment of diatoms of the genus Amphora on benthic motile diatoms is described. The analysis of a river biofilm sample shows that the attached diatoms clearly select large sigmoid Nitzschia hosts. The examination of a regional database suggests that the attachment of Amphora copulata may be common in rivers and that the preferred host is Nitzschia sigmoidea.

The extensive use of diatoms as bioindicators of water quality assumes that the composition of diatom communities is largely driven by abiotic environmental filtering [START_REF] Lobo | Diatoms as Bioindicators in Rivers[END_REF]). However, neutral processes and especially biotic interactions may also considerably shape microalgal communities [START_REF] Bottin | Diatom Cooccurrence Shows Less Segregation than Predicted from Niche Modeling[END_REF]. The most studied interactions among diatom species are those mediated by competition for light and nutrients [START_REF] Titman | Ecological Competition between Algae -Experimental Confirmation of Resource-Based Competition Theory[END_REF]. Cases of positive interactions between species have been rarely documented (e.g. [START_REF] Vanelslander | Complementarity effects drive positive diversity effects on biomass production in experimental benthic diatom biofilms[END_REF]. Epiphytism generally implies a large difference in size between the epiphytes and their host. Diatoms are well known epiphytes on filamentous algae and aquatic macrophytes. However, the attachment of a diatom on another diatom is less common and has been rarely reported. In this study, we present the selective attachment of a small freshwater diatom species on another benthic motile species. This interaction was qualitatively described by [START_REF] Round | Studies on freshwater Amphora species IV. The Amphora epiphytic on other diatoms[END_REF] from observations on glasses placed on top of sediment surfaces. We provide here a quantitative analysis from a local to a regional scale.

A biofilm sample was scraped in the Arc river (43°30'41.7''N, 5°28'57.2''E), France, on the flank of a large rock near the river bank. The fresh sample was observed under a light microscope. Diatoms were the most abundant microalgal group. Amongst a large amount of filaments of Melosira varians, many long and often sigmoid diatoms belonging to the genus Nitzschia were seen covered with a variable number of small diatoms (Fig. 1). The attached diatoms exhibit a cymbal shape when they are located on the edge of the host valve and have a biconvex outline when seen in the middle of the host valve. These observations typically correspond to the valve and girdle views of diatoms belonging to the genus Amphora. Nevertheless, it is difficult to identify species from fresh material [START_REF] Cox | Identification of freshwater diatoms from live material[END_REF]) and a sample digestion with boiling H 2 O 2 (1 hour) is necessary to remove organic matter, and observe the specific ornamentation of the siliceous frustules. The attached diatoms and their host were separated during the treatment. The most abundant Amphora species (4.8 %) and the most likely to correspond to the high number of attached diatoms was Amphora copulata (Kützing) Schoeman & Archibald 1986 (ACOP) (Table 1). However, the attached diatoms may also belong to the less abundant Amphora species identified in the sample, such as Amphora pediculus (1 %) or Amphora indistincta (0.2 %). The long sigmoid Nitzschia could be either N. sigmoidea or N. vermicularis, which had similar relative abundance in the sample. These species of Nitzschia are able to move on a substrate in curved directions. The Nitzschia observed in the river sample moved at a speed about 20 µm.s -1 which did not seem reduced when attached diatoms were present (S 1).

After observation of the live material, the sample was fixed with dilute lugol to stop cell movement before counting. There was no visible effect of fixation on cell associations. In order to assess the host specificity of the attached diatoms, five groups of abundant and large diatom forms were considered as potential hosts for ACOP (Table 2). The cells from each group, with and without attached diatoms, were counted under a light microscope at ×100 magnification (Table 2). About two thirds of the long Nitzschia had attached diatoms. However, no epiphyte was seen on more than one hundred observed individuals of the genus Gyrosigma, which have several common characteristics with the Nitzschia species that were observed in the sample: a large size, a sigmoid shape and a similar motility. There were only five cases (3 %) of attachment on filaments of Melosira varians and in each case, only one cell of ACOP was visible on the filament (Fig. 1). No attachment was observed on any large Navicula species and neither on the other genera of large diatoms represented in the river sample. These results demonstrated a clear host selection. The significance of attachment of ACOP at larger spatial scale was assessed through the analysis of co-occurrences in a recently published regional database of species incidence and environmental conditions among 196 sites in western France [START_REF] Bottin | Diatom Cooccurrence Shows Less Segregation than Predicted from Niche Modeling[END_REF]. ACOP was present in 44% of the samples in the regional database and in 86% of the samples in which N. sigmoidea occurred. Focus was given to the potential hosts observed in the Arc river sample: N. sigmoidea (in 11% of total samples), N. vermicularis (7%), M. varians (78%). Cymatopleura solea (13%) was also considered due to its presence in the river sample and the database, its large size, and because it presents fibulae on its frustule which may be a criterion of host selection by ACOP [START_REF] Round | Studies on freshwater Amphora species IV. The Amphora epiphytic on other diatoms[END_REF]. Two hypotheses were tested. The first one assumes that there is no more co-occurrences of ACOP with its potential host in the database than there may be by chance if the occurrences of ACOP were distributed randomly among sites. Therefore, the exact probability to get at least as many cooccurrences with ACOP as observed in the database was calculated from the number of possible combinations (Table 3, S 2). Also, random permutations (n=9999) of incidence data of ACOP across sites were carried out and the observed number of co-occurrences with each potential host species was compared with the distribution of simulated co-occurrences by permutations (Fig. 2). The co-occurrences of ACOP with N. sigmoidea and C. solea were significant (p < 0.05) whereas they were not significant with the two other species. Thus, there is no sign in the database of an association of ACOP with N. vermicularis or M. varians. This suggests that among the two Nitzschia species, N. sigmoidea may be a preferred host for ACOP and that attachment on M. varians is probably rare. Table 3. Number of occurrences and co-occurrences with Amphora copulata of 4 potential host species among the 196 samples of a regional database [START_REF] Bottin | Diatom Cooccurrence Shows Less Segregation than Predicted from Niche Modeling[END_REF], and probability to obtain randomly at least as many co-occurrences under the random and the abiotic environmental-control hypothesis. The second hypothesis is that the occurrences of ACOP are only driven by abiotic environmental factors and are not favored by the presence of a potential host species (N. sigmoidea or C. solea). Therefore, as with permutations, new patterns of occurrences of ACOP among sites were simulated, taking this time into account the species' ecological preferences. Following Bottin et al [START_REF] Bottin | Diatom Cooccurrence Shows Less Segregation than Predicted from Niche Modeling[END_REF], random forests were used (R package 'randomForest', Liaw and Wiener ( 2002)) to predict the occurrence of ACOP from the sixteen abiotic environmental parameters describing each sample of the database (elevation, slope, distance to the source and water quality parameters). The presence of ACOP at the sites where a potential host was present, was predicted from a random forest (500 trees) trained with observed occurrences of ACOP at the sites where the potential host did not occur (R² = 0.34 with N. sigmoidea and 0.25 with C. solea). The obtained pseudoprobabilities of presence (prediction scores) at all sites were used to simulate n=10000 patterns of occurrence of ACOP by drawing for each site, n times in a Bernoulli law. They were also used to derive the probabilities to get at least as many co-occurrences as observed in the database (Table 3, S 2). Under this second hypothesis, the observed co-occurrences of ACOP with C. solea were not significant. However, the co-occurrences with N. sigmoidea were still significant (p < 0.05) and suggest that N. sigmoidea may facilitate the presence of ACOP by providing an adequate substrate for attachment. Nevertheless, the tests only show that the data are consistent which a common attachment of ACOP on N. sigmoidea in rivers but the extent of this phenomenon can only be demonstrated by microscopic observations. Moreover, the power of the tests is limited for several reasons. The main one is the difference in mean abundance of ACOP and N. sigmoidea across sites which results from the size-abundance ecological relationship [START_REF] White | Relationships between body size and abundance in ecology[END_REF], 6:1 ratio in our sample), whereas the counting effort is usually constant among samples. Co-occurrences of the two species may be therefore underestimated. Thus, it cannot be concluded from the high proportion of sites where ACOP is present but N. sigmoidea is not (39% = (87-19)/ , Table 3), that ACOP may have other hosts or other habitats.

Diatom species

This case of attachment is particularly interesting because it involves a large number of diatoms on the frustule of a single motile diatom (Fig. 1) which can move in spite of the numerous attached cells. Moreover, this attachment is selective and probably widespread as the co-occurrences of ACOP and N. sigmoidea in a regional database suggest. ACOP may benefit from this interaction because the host moves relatively fast and can transport it where light and nutrients are available [START_REF] Cohn | Environmental-Factors Influencing Diatom Cell Motility[END_REF][START_REF] Bondoc | Selective silicate-directed motility in diatoms[END_REF]). This can be at the expense of N. sigmoidea which may suffer higher competition for resources with attached cells, undergo stronger drag and increased downstream drift, and be less mobile in dense biofilms. Ecophysiological studies on the association of the two species are needed to check the possibility that this relation may be an epiphytism, a parasitism or even a mutualism, if benefits for N. sigmoidea could be demonstrated. More generally, there is a need to clarify positive interactions between species for a more accurate use of diatoms as bioindicators in neo-or paleolimnology. Indeed, if the presence of a species is more determined by biotic interactions than by water quality, this species will have a poor indicator value. Moreover, for paleo-environmental reconstructions, it makes a difference whether a species is epiphytic on macrophytes or on epilithic diatoms.

S 1. Video sequence made from the river Arc sample divided into three parts: (a) movement of a 120 µm-long Nitzschia species, (b) same species with two attached Amphora cells. The cell swings from connective to valve side without slowing down (LM ×100). (c) Nitzchia sigmoidea moving with several Amphora cells attached to its frustule (LM ×200) (Material: Leica DFC290 hd camera on a Leica DM5500B microscope, frame rate=30/s).

S 2. Calculation of conditional probabilities given the observed occurrences of a potential host species in the regional database. where Pk are the possible combinations of k sites among the sites where a potential host is present, p i is the random forest-derived pseudo-probability of occurrence of ACOP at site i. https://www.int-res.com/articles/suppl/a080p055_supp/

Figure 1 .

 1 Figure 1. Light microscope photographs. A frustule of Nitzschia sigmoidea (a). A cell of N. sigmoidea covered with Amphora sp. (b, c, d), two conspicuous droplets (arrows, d) are characteristics of Amphora and can be seen in some attached cells (d). Frustules of N. sigmoidea and A. copulata probably accidentally re-associated after sample H 2 O 2 treatment (e). A single cell of A. copulata on a filament of Melosira varians (f). Scalebar = 10 µm

Figure 2 .

 2 Figure 2. Distribution of the F ratio of observed over simulated co-occurrences of Amphora copulata with 4 potential host species. The vertical segments represent the lower 95 % of the distribution and the cross is the median. The results of permutations (n=9999) of A. copulata's occurrences among sites are represented in grey. The black segments correspond to simulations of A. copulata's occurrences using an environmental model (random forest) taking into account physico-chemical conditions at each site.

C

  = number of co-occurrences of ACOP and a potential host n= number of sampled sites n 1 = number of occurrences of ACOP n 2 = number of occurrences of a potential host Random hypothesis:

Table 1 . List of taxa present in the H 2 O 2 -treated epilithic sample with estimation of their relative abundance (total abundance = 501). Taxon Relative abundance (%)

 1

	Melosira varians Agardh

Table 2 .

 2 Number of diatom forms with and without attached diatoms, identified in the fresh biofilm sample (2 microscope slides were completely screened). The different forms listed in the table were assumed large enough to be potential hosts. In brackets are indicated the taxa representing each form which were identified after sample treatment with boiling H 2 O 2 .

		With	Without
	Potential host diatom forms	attached	attached
		diatoms	diatoms
	Long Nitzschia (>100 µm, N.	39	20
	sigmoidea, N. vermicularis, ...)
	Gyrosigma (G. sciotense and G.	0	105
	attenuatum)
	Filaments of Melosira varians	5*	149
	Large Navicula (N. tripunctata, N.	0	94
	lanceolata, N. capitatoradiata, ...)
	Others (>50 µm, Cymatopleura,	0	48
	Surirella, Nitzschia, Diatoma, ...)

*In each case, only one cell was attached on the filament.

Acknowledgments

The authors are grateful to Françoise Chalié for laboratory assistance, Adrien Morel for help with the microscope and Marie-Hélène Lizée for advice and discussion. Special thanks to Milena Borissova for text edition.