T Michael Anderson
email: anderstm@wfu.edu

Staci A Hepler

Ricardo M Holdo

Jason E Donaldson

Robert J Erhardt

J Grant

C Hopcraft

Matthew C Hutchinson

Sarah E Huebner

Thomas A Morrison

Jeffry Muday

Issack N Munuo

Meredith S Palmer

Johan Pansu

Robert M Pringle

Robert Sketch

Craig Packer

Interplay of competition and facilitation in grazing succession by migrant Serengeti herbivores

Keywords:

Competition, facilitation, and predation offer alternative explanations for successional patterns of migratory herbivores. However, these interactions are difficult to measure, leaving uncertainty about the mechanisms underlying body-size dependent grazing-and even whether succession occurs at all. We used data from an eight-year camera-trap survey, GPS-collared herbivores, and fecal DNA metabarcoding to analyze the timing, arrival order, and interactions among migratory grazers in Serengeti National Park. Temporal grazing succession is characterized by a "push-pull" dynamic: competitive grazing nudges zebra ahead of co-migrating wildebeest, while grass consumption by these large-bodied migrants attracts trailing, smallbodied gazelles that benefit from facilitation. "Natural experiments" involving intense wildfires and rainfall respectively disrupted and strengthened these effects. Our results highlight a balance between facilitative and competitive forces in co-regulating large-scale ungulate migrations.

One-Sentence Summary: Movement,

Main Text: Seasonal migrations, defining features of many terrestrial and marine ecosystems worldwide [START_REF] Putman | Marine migrations[END_REF][START_REF] Kauffman | Causes, consequences, and conservation of ungulate migration[END_REF], are threatened by habitat destruction, overhunting, and climate change [START_REF] Wilcove | Going, going, gone: Is animal migration disappearing[END_REF]. Although migration is common in large mammalian herbivore species [START_REF] Abraham | Evolutionary causes and consequences of ungulate migration[END_REF], the mechanisms underlying multi-species migration dynamics remain poorly understood [START_REF] Kauffman | Causes, consequences, and conservation of ungulate migration[END_REF]. The annual ungulate migration in Serengeti National Park is the archetypal example of body-size dependent "grazing succession," [START_REF] Bell | A grazing ecosystem in the Serengeti[END_REF], where zebra (Equus quagga; ~230 kg), wildebeest (Connochaetes taurinus; ~180 kg), and Thomson's gazelle (Eudorcas thomsonii; ~20 kg; 'gazelle' hereafter) sequentially follow the same migratory routes.

Early descriptions of grazing succession invoked facilitation to explain this pattern [START_REF] Vesey-Fitzgerald | Grazing succession among East African game animals[END_REF]. In this scenario, bulk consumption by larger grazers keeps grasses short and regrowing, creating nutritious forage for smaller grazers that require less food [START_REF] Arsenault | Facilitation versus competition in grazing herbivore assemblages[END_REF]. Removal of grass biomass may also increase accessibility and abundance of low-growing, high-quality herbaceous eudicots favored by smaller species [START_REF] Louthan | Mechanisms of plant-plant interactions: concealment from herbivores is more important than abiotic-stress mediation in an African savannah[END_REF][START_REF] Gwynne | Selection of vegetation components by grazing ungulates in the Serengeti National Park[END_REF]. In Serengeti, evidence for facilitation is based largely on (i) staggered arrival times of zebra, wildebeest, and gazelles, as measured at a single location over three years [START_REF] Bell | A grazing ecosystem in the Serengeti[END_REF], (ii) partitioning of grass stem, leaf, and sheath observed in a small sample of stomach contents [START_REF] Gwynne | Selection of vegetation components by grazing ungulates in the Serengeti National Park[END_REF], and (iii) gazelle preference for habitat patches previously grazed by wildebeest [START_REF] Mcnaughton | Serengeti migratory wildebeest: facilitation of energy flow by grazing[END_REF].

Other lines of evidence suggest that grazing succession is instead driven by competition [START_REF] Sinclair | Does competition or facilitation regulate migrant ungulate populations in the Serengeti? A test of hypotheses[END_REF]. An indirect competitive process (exploitation; Table S1) may operate if multiple species use the same resource patches, but smaller grazers delay their arrival due to resource depletion by larger grazers. A direct competitive process (interference; Table S1) may operate if species comingle and smaller herbivores propel larger herbivores onwards into taller vegetation by grazing swards down to heights unprofitable for the larger species [START_REF] Illius | The allometry of food intake in grazing ruminants[END_REF][START_REF] Du Toit | Generalities in grazing and browsing ecology: using across-guild comparisons to control contingencies[END_REF]. Citing "invasion" of wildebeest during their northernmost path, Sinclair [START_REF] Sinclair | Does interspecific competition or predation shape the African ungulate community?[END_REF] proposed that interspecific competition forced zebra to stay ahead of migrating wildebeest. A third possibility is that predators regulate migration dynamics. Mixed-species migration could reduce individuals' risk through increased vigilance and predator satiation [START_REF] Sinclair | Does interspecific competition or predation shape the African ungulate community?[END_REF][START_REF] Stears | Mixed-species herding levels the landscape of fear[END_REF], especially in areas of high vulnerability to ambush predators [START_REF] Beaudrot | Mixed-species groups of Serengeti grazers: a test of the stress gradient hypothesis[END_REF].

Disentangling the potential mechanisms that drive the movement patterns, arrival times, and foraging behaviors of the three migrating species has been hampered by a lack of long-term, detailed data at the appropriate scale [START_REF] Kauffman | Causes, consequences, and conservation of ungulate migration[END_REF]. We conducted a landscape-scale analysis of animal movements in Serengeti by integrating three spatially and temporally overlapping datasets: (i) the citizen-science-supported Snapshot Serengeti camera trap survey (Ncameras = 48 -130; coverage = 1000 km 2 ; Fig. S1) that operated continuously between 2011 -2018 (17; Fig. 1), (ii) GPS collar data collected in 2017 and 2018 for migratory zebra and wildebeest (18; Fig. 1), and (iii) dietary analysis of fecal DNA for each migrant species collected in 2017 and 2018 [START_REF] Kartzinel | DNA metabarcoding illuminates dietary niche partitioning by African large herbivores[END_REF]. Our study area, in the fire-prone grassland-to-woodland transition north of the Serengeti plains, lies in the center of the Serengeti migration (Fig. 1). We focused on the 'transition season' (April -August), when migrants move off the plains to the north-west and plants undergo dry season senescence [START_REF] Mcnaughton | Grazing as an optimization process: grass-ungulate relationships in the Serengeti[END_REF].

The biotic interactions influencing grazing succession are modulated by disturbance. Rainfall and fire may decouple associations between migratory species by controlling food availability through biomass reduction (fire) or stimulating plant growth (both) [START_REF] Bond | Fire as a global 'herbivore': the ecology and evolution of flammable ecosystems[END_REF]. The extent of fire within the study area varied 33-fold across years (range: 21.3 -694.4 km 2 ; Fig. S2), rainfall in the four months prior to the transition period varied three-fold (217 -621 mm; Fig. S2), and vegetation greenness (normalized difference vegetation index; NDVI) varied over ten-fold (1.9 -29.0; Supplementary Materials). We exploited these extremes to probe the mechanistic underpinnings of co-migration and test three alternative hypotheses: facilitation (H1), competition (H2), and predation (H3) (Table S1) that make contrasting predictions about the order, timing, and strength of species associations.

The facilitation hypothesis predicts consistent separation in migrant arrival time: zebra followed by wildebeest then gazelles [START_REF] Bell | A grazing ecosystem in the Serengeti[END_REF]. Grazing by larger herbivores is expected to attract smaller herbivores, but not the reverse. Digestible energy per unit mass decreases with grass biomass [START_REF] Fryxell | Landscape scale, heterogeneity, and the viability of Serengeti grazers[END_REF]; by creating patches of high-quality regrowth [START_REF] Donaldson | Ecological engineering through fire-herbivory feedbacks drives the formation of savanna grazing lawns[END_REF], fire should disrupt grazing succession and uncouple any positive associations between species because regrowth will not be restricted to previously grazed areas. In contrast, high pre-migration rainfall promotes accumulation of stem-dominated grass biomass and should strengthen species associations by enhancing facilitation (otherwise, small herbivores would constantly encounter tall, stem-dominated swards with low digestible energy). Finally, diets should be dominated by grasses with low species partitioning between each migratory herbivore (5, 9 -10). As hind-gut fermenters [START_REF] Van Soest | Allometry and ecology of feeding behavior and digestive capacity in herbivores: a review[END_REF], zebra can digest low-quality food and maximize intake from tall grass, while smaller ruminant species select nutritious short grasses.

The competition hypothesis predicts the same species arrival order and high dietary overlap as facilitation, but timing and species associations should depend on the form of competition. Under indirect competition (H2i), species should arrive several weeks apart (to allow for grass regrowth), and the lag should be greater after longer occupancy by the first-arriving species (Table S1). Under direct competition (H2d) we expected little to no separation in arrival time, with larger migrants avoiding dense herds of smaller migrants that deplete food availability (Table S1). In both scenarios, higher pre-migration rainfall should weaken negative associations between migrants of similar size by reducing feeding competition, whereas pre-migration fire should intensify negative associations.

The predation hypothesis predicts closer spatial proximity especially for small-bodied species, as they are vulnerable to a wider range of carnivore species [START_REF] Sinclair | Patterns of predation in a diverse predator-prey system[END_REF]. Positive spatial associations should be stronger in open grasslands in wet years, when taller grasses provide cover for ambush predators, and in areas with high-risk landscape features such as river courses (based on a 50year spatial dataset of lion predation risk; 26) regardless of rainfall or fire. We rely on lion predation as an overall proxy for ambush risk as cheetahs select the same small-scale areas as lions [START_REF] Swanson | Cheetahs and wild dogs show contrasting patterns of suppression by lions[END_REF] and leopards' habitat preferences are highly congruent with lions' [START_REF] Strampelli | Spatial cooccurrence patterns of sympatric large carnivores in a multi-use African system[END_REF]. In contrast, spotted hyenas and African wild dogs make no attempt at concealment and first disturb the herds to identify vulnerable individuals [START_REF] Kruuk | Surplus killing by carnivores[END_REF][START_REF] Fitzgibbon | Stotting in Thomson's gazelles: an honest signal of condition[END_REF]. Hence, we consider it unlikely that risks from coursing predators would confer strong advantages either from forming mixed-species herds or from migrating separately.

RESULTS

Arrival order and time lags

The classic formulation of grazing succession (5) predicts consistent ~2-month separations in peak abundance of each species (Fig. 1C). However, dates of migration and peak abundance for zebra and wildebeest varied across years and did not exhibit separation consistent with hypotheses based on either facilitation (H1) or indirect competition (H2i). In most years, zebra and wildebeest entered the study area simultaneously. Wildebeest numbers accumulated rapidly and reached peak abundance 7.3 ± 9.3 d (range: 22 to -6 d) before zebra, although this difference was inconsistent (Wilcoxon signed-rank test: v = 3.5, P = 0.09, df = 6). In contrast, wildebeest and zebra abundance both consistently peaked 27.6 ± 15.4 d before gazelle (Wilcoxon sign rank test: v = 105, P < 0.001, df = 12). These time lags are smaller than those reported by Bell (5), and only the separation between the larger migrants and gazelle is qualitatively consistent with classic predictions (Fig. 1). Furthermore, the observed lags are inconsistent with direct competition (H2d) or predation (H3), which predict that smaller herbivores should maintain adjacency to larger herbivores either because their foraging drives large herbivores to sites with more food [START_REF] Illius | The allometry of food intake in grazing ruminants[END_REF][START_REF] Du Toit | Generalities in grazing and browsing ecology: using across-guild comparisons to control contingencies[END_REF][START_REF] Sinclair | Does interspecific competition or predation shape the African ungulate community?[END_REF] or because they benefit most from increased predator vigilance when foraging in mixed-species herds [START_REF] Sinclair | Does interspecific competition or predation shape the African ungulate community?[END_REF][START_REF] Stears | Mixed-species herding levels the landscape of fear[END_REF].

Directionality and reciprocity of interactions

Facilitation (H1) predicts positive effects of larger herbivores on the probability of occupancy by smaller herbivores, with negligible reciprocal effects of small on large herbivores (Fig. 1). Using two-step, conditional Bayesian occupancy models [START_REF] Sun | Bayesian analysis of cross classified spatial data with autocorrelation[END_REF][START_REF] Hepler | Identifying drivers of spatial variation in occupancy with limited replication camera trap data[END_REF], we analyzed four-day and sixteenday temporal windows to quantify concurrent and lagged associations between each pair of species for each transition season. Each model included static (i.e., landscape) and dynamic (i.e., rainfall and vegetation) environmental predictors as covariates to control for potentially confounding factors [START_REF] Caragea | A centered bivariate spatial regression model for binary data with an application to presettlement vegetation data in the Midwestern United States[END_REF] and included a unique species-specific conditional term (𝛾 !"#$%#! '|!"#$%#! ) ) that measured the effect of one species on the occupancy probability of another.

Over four-day windows, we found reciprocal positive effects of zebra and wildebeest occupancy throughout the migration. Zebra increased wildebeest occupancy in 6 of 8 years (with marginally positive effects in the other 2), and wildebeest increased zebra occupancy in 3 of 8 years (and marginally in another) (Fig. 1G; Fig. S3; Table S2). On this four-day scale, gazelles were not firmly associated with zebra or wildebeest occupancy in any year (Table S2), exhibiting only marginal negative overall associations reflecting the temporal separation between the arrival time of gazelles and larger herbivores (Fig. 1F,1G).

At sixteen-day intervals, and consistent with the facilitation hypothesis, we detected positive effects of larger grazers on gazelles in 5 of 8 years, and gazelles were more strongly associated with locations previously occupied by wildebeest than by zebra (Fig. 1H; Fig. S3; Table S3). Zebra-wildebeest associations on this longer timescale were consistently negative, reflecting their positive associations on shorter time scales (Fig. 1F,1H).

Influences of fire and rainfall on species' associations

Exceptions to the prevailing patterns were related to environmental extremes. The two years without four-day conditional effects of zebra and wildebeest also showed the most extensive fires (2013 and 2016). Further, 2 of the 3 years without sixteen-day lagged effects of larger species on gazelles had the lowest rainfall in the entire study period (2014 and 2017; Fig. S3; Table S2), suggesting that species associations were resource-dependent.

To test the effect of environmental conditions, we analyzed the relative strength of association between species (RSAi) as functions of fire and rainfall from January-June each year (Fig. S3).

We predicted that RSAi should be negatively associated with fire and positively associated with pre-migration rainfall. Indeed, RSAi in four-day intervals declined with area burned (Fig. 2; Table S4). This correlation was directionally consistent but strongest for zebra on wildebeest and for wildebeest on gazelles-size-adjacent species that precede each other in the migrationlikely because fire mimics large herbivores by reducing grass height and promoting regrowth in ways that benefit small herbivores [START_REF] Donaldson | Ecological engineering through fire-herbivory feedbacks drives the formation of savanna grazing lawns[END_REF]. RSAi in sixteen-day intervals increased with rainfall for gazelles trailing wildebeest and zebra (Fig. 2). Thus, gazelles more closely tracked the larger migrants in years with higher herbaceous production, suggesting greater reliance on the facilitative effects of biomass removal (H1).

RSAi for zebra and wildebeest occupancies did not vary in response to rainfall at either timescale, despite their reciprocal spatial associations (Fig. 2). For additional insight, we examined paths of GPS-collared individuals for one dry (2017) and one wet (2018) year to test whether movements measured at four-hour intervals revealed subtler responses to heterospecifics. Wildebeest habitat selection was independent of proximity to dense herds of zebra (Fig. 3A). In contrast, zebra selected habitat distant from dense wildebeest herds in both years, and farther in the dry (1.4 km) than the wet (0.8 km) year (Fig. 3B, Table S5). Wildebeest and zebra step lengths and turn angles also depended on rainfall and distance to heterospecifics. During the leaner dry year, wildebeest used larger step lengths of ~400 m as they searched for food, especially when near dense zebra herds; in the more plentiful wet year, wildebeest used smaller step lengths indicative of active foraging (Fig. 3; Table S5). Zebra step lengths in the dry year were larger than the null expectation. However, in the wet year, zebra migrating close to dense wildebeest herds had smaller step lengths and more circuitous turn angles, indicating greater local food availability (Fig. 3; Table S5). This last inference is also supported by evidence that both species avoided senescing vegetation more strongly in the wet than the dry year (scaled change in NDVI from Table S5). Altogether, these fine-scale movements are most consistent with asymmetric direct competition (H2d) between the two species: wildebeest habitat selection is governed by resource availability independent of zebra, while zebra are subject to interference competition and locally repelled from massive wildebeest herds, especially in dry years [START_REF] Sinclair | Does interspecific competition or predation shape the African ungulate community?[END_REF].

No evidence for a role of predation risk

We tested whether spatial associations were stronger in risky areas (H3) by analyzing conditional occupancy probabilities relative to the distribution of ambush-predation risk inferred from lion densities and kills (Fig. S4; 34). Conditional species associations were indistinguishable between high-and low-risk areas at both four-day and sixteen-day timescales (figs. S5-S12). The results are also incongruent with the predictions from H3 that associations in high-risk areas would be stronger in years with higher rainfall and more pronounced for associations involving gazelle.

Diet selection and overlap

We used fecal DNA metabarcoding in 2017 and 2018 to identify plant taxa and estimate their relative abundance in herbivore diets [START_REF] Kartzinel | DNA metabarcoding illuminates dietary niche partitioning by African large herbivores[END_REF][START_REF] Pansu | The generality of cryptic dietary niche differences in diverse large-herbivore assemblages[END_REF]; Supplemental Materials). Zebra diets consisted almost exclusively of grasses (96.9% of sequence reads on average); wildebeest diets were grassdominated (73.9%) but included substantial proportions of herbaceous eudicots, mostly legumes (Fig. 4A,B; Table S6). In contrast, grasses were a minority of gazelle diets (26.2%), especially in earlier months (May-July) before the larger species departed from the study area (Fig. 4A,B). In both years, zebra and wildebeest ate highly overlapping sets of plant taxa (mean niche overlap 0.82), while overlap was lower for wildebeest and gazelles (0.53) and lowest for zebra and gazelles (0.34). Wildebeest and gazelles avoided common tall grasses of middling to low quality, whereas zebra showed higher selectivity for these taxa (Fig. 4C). In later months, however, gazelles increased consumption of high-quality grasses such as Digitaria macroblephara that were likely regrowing after being grazed earlier in the season (figs. S14, S15; Supplemental Materials).

Accounts that grazers partition grass stems and leaves without reference to plant identity [START_REF] Gwynne | Selection of vegetation components by grazing ungulates in the Serengeti National Park[END_REF] were integral to the classic grazing-succession model ( 5) and later elaborations [START_REF] Arsenault | Facilitation versus competition in grazing herbivore assemblages[END_REF][START_REF] Sinclair | Does competition or facilitation regulate migrant ungulate populations in the Serengeti? A test of hypotheses[END_REF][START_REF] Illius | The allometry of food intake in grazing ruminants[END_REF][START_REF] Du Toit | Generalities in grazing and browsing ecology: using across-guild comparisons to control contingencies[END_REF][START_REF] Fryxell | Spatial dynamics and coexistence of the Serengeti grazer community[END_REF].

The generally high overlap in plant taxa eaten by zebra and wildebeest is compatible with this mechanism, and with both facilitative and competitive interpretations, although the differential selectivity for grass species (Fig. 4C) aligns with the fine-scale competitive displacement inferred from movement data (Fig. 3B). However, we also find new support for a facilitative mechanism first proposed in 1968 (9) whereby larger migrants benefit gazelles by opening the grass canopy and providing access to nutrient-rich prostrate eudicots (Fig. S15), at least until the late dry season when gazelles switch to high-quality grasses grazed by earlier migrants (Fig. 4B; Fig. S14). Coupled with the observed lags in occupancy, these dietary differences are incompatible with the idea that gazelles competitively displace larger migrants [START_REF] Du Toit | Generalities in grazing and browsing ecology: using across-guild comparisons to control contingencies[END_REF] and may also help explain the gazelles' stable population size following the rapid increase in wildebeest numbers following rinderpest eradication in the 1960s [START_REF] Fryxell | Spatial dynamics and coexistence of the Serengeti grazer community[END_REF].

Discussion -Our findings provide insight into the drivers of the iconic Serengeti migration. We found no evidence that the grazing succession is driven by predation risk (H3). Risk from lions, leopards, and cheetahs is especially high in the northwestern region of our study area (Fig. S4; [START_REF] Mosser | Serengeti real estate: density vs. fitness-based indicators of lion habitat quality[END_REF], and if risk mitigation were a key reason for co-migration, strong species associations should have persisted near high-risk landscape features (26) even after fire. Previous analyses had suggested that high herbaceous biomass promotes mixed species group formation to reduce predation risk [START_REF] Beaudrot | Mixed-species groups of Serengeti grazers: a test of the stress gradient hypothesis[END_REF]; however, the low prevalence of multi-species associations in camera-trap photos (only 1.1% of gazelle detections, 5.7% of wildebeest detections, and 4.6% of zebra detections included any of the other species), does not support a general anti-predator response.

Instead, our analyses of occupancy, animal movement, and diet provide strong evidence that foraging processes underlie grazing succession, occurring at short intervals (< four-day) between zebra and wildebeest and longer intervals (sixteen-to thirty-two-day) between larger migrants and gazelles. Multiple lines of evidence point to a "push-and-pull" dynamic in which wildebeest, the dominant grazer, push zebra ahead by reducing grass biomass (H2d) while pulling along gazelles via facilitation (H1). Our study helps to reconcile decades of conflicting results [START_REF] Bell | A grazing ecosystem in the Serengeti[END_REF][START_REF] Vesey-Fitzgerald | Grazing succession among East African game animals[END_REF][START_REF] Gwynne | Selection of vegetation components by grazing ungulates in the Serengeti National Park[END_REF][START_REF] Mcnaughton | Serengeti migratory wildebeest: facilitation of energy flow by grazing[END_REF][START_REF] Sinclair | Does competition or facilitation regulate migrant ungulate populations in the Serengeti? A test of hypotheses[END_REF][START_REF] Illius | The allometry of food intake in grazing ruminants[END_REF][START_REF] Du Toit | Generalities in grazing and browsing ecology: using across-guild comparisons to control contingencies[END_REF][START_REF] Sinclair | Does interspecific competition or predation shape the African ungulate community?[END_REF] by demonstrating that competition and facilitation operate concurrently during animal migration with effect sizes that depend on resource availability [START_REF] Arsenault | Facilitation versus competition in grazing herbivore assemblages[END_REF].

A similar seasonal shift between competition and facilitation was observed in Kenyan rangeland, where interactions between cattle and wild grazers shifted from facilitation during the wet season to competition in the dry season [START_REF] Odadi | African wild ungulates compete with or facilitate cattle depending on season[END_REF]. In our study, smaller migratory herbivores benefitted both during both dry and wet periods [START_REF] Mcnaughton | Grazing as an optimization process: grass-ungulate relationships in the Serengeti[END_REF], when they selected regrowing high-quality grasses previously consumed by the preceding larger-bodied migrants (Fig. 4C; Fig. S13) and/or gained improved access to protein-and mineral-rich legumes and other forbs (Fig. S14, Fig. S15). In a typical year, habitat use by gazelles tracks co-migrating zebra and wildebeest migration, and this association intensifies with increasing rainfall. In high-fire years, short-term movements among grazers are largely uncoupled, indicating that gazelles benefit from grass removal and regrowth, regardless of whether it results from migratory herbivores or fire. We do not claim that effects of zebra on wildebeest or of both species on gazelles are purely facilitative, but rather that facilitation is an important process during herbivore migration, likely helping to stabilize populations of smaller herbivores [START_REF] Fryxell | Landscape scale, heterogeneity, and the viability of Serengeti grazers[END_REF]. Herbivore population dynamics are not strongly coupled at the ecosystem level [START_REF] Sinclair | Does competition or facilitation regulate migrant ungulate populations in the Serengeti? A test of hypotheses[END_REF], which implies that extrinsic factors are important, but facilitation may still be a key stabilizing force and driver of individual behavior during critical periods of the annual migration.

Multi-species migratory systems were once common across tropical savannas [START_REF] Wilcove | Going, going, gone: Is animal migration disappearing[END_REF][START_REF] Owen-Smith | Movement ecology of large herbivores in African savannas: current knowledge and gaps[END_REF] and probably involved similarly nuanced interplay of positive and negative interactions [START_REF] Harris | Global decline in aggregated migrations of large terrestrial mammals[END_REF]. Large herbivores have suffered disproportionate extinction since the Quaternary (41), especially among migratory species (4), resulting in concomitant degradation of ecosystem functions [START_REF] Lundgren | Introduced herbivores restore Late Pleistocene ecological functions[END_REF]. Our findings identify a previously unappreciated role of plant functional diversity in sustaining megafaunal migratory systems and indicate that fire management can help to maintain species persistence. Any disruption of the vegetative phenology that underlies herbivore movements would alter the strong systemwide consequences of migration [START_REF] Aikens | Drought reshuffles plant phenology and reduces the foraging benefit of green-wave surfing for a migratory ungulate[END_REF] and portends additional challenges associated with extreme climate and weather events in coming years [START_REF] Pörtner | Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change[END_REF]. Based on GPS collaring data collected between 1999-2020 [START_REF] Hopcraft | Competition, predation, and migration: individual choice patterns of Serengeti migrants captured by hierarchical models[END_REF], 96% of collared wildebeest (n = 54, grey lines in A) and 100% of zebra (n = 28, black lines in B) passed through the study area. Grey boxes show monthly mean locations for wildebeest (A) and zebra (B) across the entire dataset with orange arrows indicating the direction of movements. Camera traps (points in A, B) are separated by ~2.2 km and operated almost continuously between July 2010 and August 2018.

Bell's [START_REF] Bell | A grazing ecosystem in the Serengeti[END_REF] foundational study was from a single plot in the Western corridor (asterisk in A, B) at a time when the wildebeest population was approximately 25% of their current size [START_REF] Hopcraft | Competition, predation, and migration: individual choice patterns of Serengeti migrants captured by hierarchical models[END_REF]. Thomson's gazelles have not been collared in the Serengeti National Park; consequently, we focused our analysis of individual movements on zebra and wildebeest. (C-E) Classically hypothesized expectations from grazing succession [START_REF] Bell | A grazing ecosystem in the Serengeti[END_REF][START_REF] Du Toit | Generalities in grazing and browsing ecology: using across-guild comparisons to control contingencies[END_REF], including migratory species' abundance over the dry season (C) and species-specific effects on the probability of other species' occurrence at four-day (D) and sixteen-to thirty-two-day intervals (C). The classic model predicts unidirectional spatial associations between migrants at substantial time lags (E) driven by activities of large herbivores (foraging, trampling, nutrient redistribution) that facilitate foraging by small herbivores. Negative interactions, not explicitly considered in early work (5, 9; cf. 13), would appear on short timescales (D) because of lagged positive associations. (F-H) Associations observed in this study. Average abundance during the transition season (F) supported the classic model for gazelles, but not for zebra and wildebeest, which co-migrated through the study area (Fig. S3); standardized species abundances were plotted against satellitederived vegetation greenness (an index of plant senescence during the dry season) to control for variation in migration timing across years. Within four-day windows, zebra and wildebeest had strong reciprocal effects on each other's occupancy throughout migration, while lagged arrival times led to negative associations with gazelles (G). Within sixteen-thirty-two-day windows, zebra and wildebeest had positive effects on occupancy of gazelles, and negative effects on each other due to their concurrent migration (H). Each arrow represents the average positive (black) or negative (grey) conditional association strength (𝛾 !"#$%#! '|!"#$%#! ) ) from Bayesian occupancy models fit at four-day (G) or sixteen-day (H) time intervals across the entire study period (Supplemental Materials). Values are mean ± 95% confidence intervals (CI; tables S2 and S3) with arrow widths proportional to the magnitude of the effect size. Dashed lines represent weak effects that were below included zero in the 95% CI.

Fig. 2. Fire weakens but rainfall strengthens species associations during grazing succession.

The relative strength of species association (RSA) is the difference between species associations from Bayesian occupancy models fit at four-day or sixteen-day time interval for a given year minus the mean across all years (𝑅𝑆𝐴 % = 𝛾 ( % -𝛾̅ ̅ ; Supplementary Materials). 𝑅𝑆𝐴 % values are gazelles tracking larger migrants (TG|ZB and TG|WB). Pearson correlation coefficients (r) are shown in each graph. Active camera density during the 2015 transition season was lower than for other years (Fig. S1) and was therefore excluded from these analyses.

Fig. 3. Wildebeest and zebra movements during one dry and one wet year.

(A-B) Movement models of collared individuals were analyzed in relation to distances from large heterospecific herds as determined by camera trap data (see Supplementary Materials). In both dry (2017) and wet (2018) years, wildebeest selected habitat independent of distance to large, dense zebra herds (A). In contrast, zebra selected sites at moderate distances from dense wildebeest herds (B), with greater distances in the dry (light grey line, mode = 1383 m) compared to wet year (dark grey line; mode = 800 m). (C-J) Foraging behaviors inferred from movement data. In the dry year, wildebeest moved with large step lengths of ~400 m between GPS fixes (4-hour fixed rate), especially individuals towards the front of the migration nearest to zebra (C), indicating directed movement (D). Zebra step lengths during the dry year were marginally larger than the expected from the tentative distribution (E). In the wet year (2018) wildebeest used smaller step lengths than expected from the tentative distribution (G), consistent with greater local resource availability and foraging behavior. Zebra movement changed dramatically in the wet year, with smaller step lengths and wide, circuitous turn angles, especially for individuals within 1000 m from dense wildebeest herds (I, J), suggesting decreased competitive effects of heterospecifics. Black dashed lines show 'tentative' distributions derived from the average movement of animals during a migration season. Color gradients represent binned zebra (C, D) or wildebeest (E, F) distances to large heterospecific herds as determined by camera trap data (see Supplementary Materials).

Fig. 1 .

 1 Fig. 1. Movements (1999-2020), temporal dynamics, and species interactions of migratory grazers in the Serengeti ecosystem. Our study area (blue polygons in A, B) is a migratory transition zone linking the Serengeti plains, Western corridor, and Masai Mara Game Reserve.

Fig. 4 .

 4 Fig. 4. Differential consumption of plant taxa of varying nutritional quality. (A) Mean diet composition by plant family (colors) during the migration period in dry (2017) and wet years (2018), showing unexpectedly high consumption of high-quality (Fig. S15) forbs by wildebeest and gazelles, notably legumes (Fabaceae). (B) Proportional grass consumption by gazelles shifted throughout the migration, increasing late in the season after zebra and wildebeest had moved on (beta regression, effect of date: β = 0.02, Z = 6.15, P < 0.001, R 2 adj = 0.35). (C) Ivlev's selectivity (proportion consumed/proportion of available forage) for the six most heavily eaten grass taxa; taxa are identified to the lowest possible level based on fecal DNA sequences,

Acknowledgments: We thank the >130,000 volunteers from 77 countries who classified images on Snapshot Serengeti as well as the team at Zooniverse for their support in hosting imagery. The Minnesota Supercomputing Institute and Wake Forest University High Performance Computing Cluster provided resources that contributed to data storage and processing. Snapshot Serengeti was publicized by the Association of Zoos and Aquariums' 'Saving Animals from Extinction' (SAFE) program and Disney Conservation Fund's 'Protect the Pride' campaign. We acknowledge Ciara Nutter for her laboratory work that facilitated the construction of the local DNA reference library for Serengeti grasses. Research clearance was provided by the Tanzania Wildlife Research Institute and Tanzania National Parks. Funding: National Geographic Society grant WW-025R-17 (TMA) National Geographic Society grant NGS-52921R-18 (TMA) National Science Foundation grant BCS-1461728 (TMA, RMH) European Union's Horizon 2020 research and innovation program grant 641918 (JGCH, TAM) National Science Foundation grant PRFB-1810586 (CP) National Science Foundation grant IIS-1619177 (CP) National Science Foundation grant OAC-1835530 (CP) National Science Foundation grant IOS-1656527 (RMP) National Science Foundation grant DEB-1457697 (RMP) Frankfurt Zoological Society (JGCH, TAM) British Ecological Society (JGCH, TAM)

Data and materials availability:

Movement data collected with GPS collars for migratory Serengeti wildebeest and zebra presented in Figure 1 are made available through MoveBank with unique identifiers: "Wildebeest (Western White-Bearded) Hopcraft Serengeti-Mara" and "Plains zebra Hopcraft Serengeti-Mara". Raw and filtered dietary sequencing data are deposited in DRYAD with the unique doi: 10.5061/dryad.brv15dvcj. Data, code, and materials used for the Bayesian occupancy models, integrated step selection models of migratory herbivores, and R scripts to produce the dietary results presented here are made available through DRYAD with the unique doi: 10.5061/dryad.7sqv9s4zk.

Supplementary Materials: Materials and Methods Supplementary Text

Tables S1 -S6

Figs. S1 -S15 References (45-115) Data S1 -S5 plotted against (A) the natural log of the burned area and (B) cumulative rainfall from January-June of year i. Fire was negatively related to variation in 𝑅𝑆𝐴 % calculated from four-day spatial associations (A; Table S4), with the strongest correlations between smaller migrants conditioned on the presence of larger migrants (WB|ZB and TG|WB); rainfall was positively related to variation in 𝑅𝑆𝐴 % calculated from sixteen-day spatial associations (B), but only for Thomson's 20 show C:N ratio (colors, lower values indicate higher quality) and leaf height (length) of each grass taxon. Dashed line at selectivity 1 indicates consumption in proportion to availability; positive values, selection; negative values, avoidance. Data underlying (A) are in Table S6.


Vincent Hamani
email: hamani.vincent@orange.fr

Isabelle Brenon

Thibault Coulombier

Jean-Remy Huguet

Laurence Murillo

The forgotten ones of ports: The filter feeders at the heart of siltation processes

Keywords: Siltation, Port, Mud, Filter feeders, Bivalves, Ascidians

Siltation is a major concern in dynamic and complex ecosystems, such as ports. The mud must be regularly dredged to avoid disturbing the navigation channels. Sediments are carried by the waters entering the port and are partially trapped by harbour structures.

Numerous studies have been conducted on the physical factors influencing siltation in port areas, whereas, few have focused on the role of biotic factors in mud formation. However, research in other contexts has shown that organisms that are abundant in pontoons, such as bivalves and tunicates, play an important role in this siltation process. All of these organisms belong to the filter feeder group. The sediments sucked in by the filter feeders are excreted in the form of faeces or mucus-bound pseudo-faeces. These waste materials, called bioproducts, settle efficiently and are involved in the composition of the mud. This study aimed to highlight the role of filter feeders in the siltation process in port areas and to determine the factors that influence the production of bioproducts by filter feeders. To investigate the role of filter feeders in the siltation processes, an experimental analysis was conducted in the largest marina in Europe (La Rochelle, France). It is divided into four basins with distinct filter feeder communities and environmental conditions, allowing for a detailed study of the environmental factors that influence the production of bioproducts. This analysis consisted of recovering and studying the bioproducts generated by the filter feeders using sediment traps fixed under pontoons. To explore the evolution of this biological production, 16 campaigns were conducted from January to March 2020 and May to July 2020.

Introduction

Ports are dynamic, constantly evolving socio-ecosystems, tugged on the one hand by environmental conditions and on the other hand by anthropic developments. Sediments and their flow have been at the heart of this turmoil. The sediments are carried by the water entering the port [START_REF] Eysink | Sedimentation in harbour basins. Small density differences may cause serious effects[END_REF][START_REF] Van Rijn | Harbour siltation and control measures[END_REF] and are partially trapped by port infrastructure [START_REF] Van Maren | The effect of dock length on harbour siltation[END_REF][START_REF] Van Rijn | Harbour siltation and control measures[END_REF][START_REF] Huguet | Dynamics and management of siltation in a macro-tidal marina: The case of La rochelle marina, France[END_REF]. These sediments are part of the siltation process and must be dredged regularly to avoid disturbing the navigation channels. This siltation is influenced by many environmental factors, widely described in the literature: sediment inputs, internal and external hydrodynamics, weather, salinity etc. [START_REF] Langendoen | Flow patterns and transport of dissolved matter in tidal harbours[END_REF][START_REF] Van Maren | The effect of dock length on harbour siltation[END_REF][START_REF] Van Rijn | Harbour siltation and control measures[END_REF][START_REF] Huguet | Dynamics and management of siltation in a macro-tidal marina: The case of La rochelle marina, France[END_REF]. Numerous studies have been conducted on the physical factors influencing siltation in port areas. However, few studies have focused on the role of biotic factors in siltation processes. To our knowledge, between 2000 and 2020 (search conducted on 15 April 2021 by combining the keywords Mud, Siltation, and Sediment with Port, Marina, and Harbour yielding 680 articles), only four articles explored this topic [START_REF] Droppo | The effect of depositional history on contaminated bed sediment stability[END_REF][START_REF] Friend | Day-night variation of intertidal flat sediment properties in relation to sediment stability[END_REF][START_REF] Kirby | Emerging concepts for managing fine cohesive sediment[END_REF][START_REF] Gerbersdorf | Exploring flowbiofilm-sediment interactions: Assessment of current status and future challenges[END_REF]. Among these four studies, none addressed the role of macro-organisms in mud formation. However, research in other contexts has shown that organisms that are abundant in pontoons, such as bivalves and tunicates [START_REF] Connell | Floating pontoons create novel habitats for subtidal epibiota[END_REF], could play an important role in the siltation process [START_REF] Giles | Sedimentation from mussel (Perna canaliculus) culture in the Firth of Thames, New Zealand: Impacts on sediment oxygen and nutrient fluxes[END_REF][START_REF] Forrest | Review of the Ecological Effects of Intertidal Oyster Aquaculture Review of the Ecological Effects of Intertidal Oyster Aquaculture[END_REF][START_REF] Mckindsey | Biodeposit production and benthic loading by farmed mussels and associated tunicate epifauna in Prince Edward Island[END_REF][START_REF] Wang | Potential role of scallops Argopecten irradians in deposition of particulate nutrient and trace elements in a eutrophic estuary, northern China[END_REF].

The sediments sucked in by the filter feeders are excreted after digestion as faeces or mucus-covered pseudo-faeces [START_REF] Beninger | Principles of pseudofeces rejection on the bivalve mantle: Integration in particle processing[END_REF][START_REF] Ward | Separating the grain from the chaff: Particle selection in suspension-and deposit-feeding bivalves[END_REF]. These excretions are referred to as bioproducts. The bioproducts generated by filter feeders strongly influence the amount of mud; small particles are aggregated into larger flocs that settle quickly and successfully [START_REF] Giles | Sedimentation from mussel (Perna canaliculus) culture in the Firth of Thames, New Zealand: Impacts on sediment oxygen and nutrient fluxes[END_REF][START_REF] Mckindsey | Biodeposit production and benthic loading by farmed mussels and associated tunicate epifauna in Prince Edward Island[END_REF][START_REF] Wang | Potential role of scallops Argopecten irradians in deposition of particulate nutrient and trace elements in a eutrophic estuary, northern China[END_REF]. A study carried out on a mussel farm showed that the presence of mussels led to a two-to-five times increase in sedimentation [START_REF] Weise | Shellfish-DEPOMOD: Modelling the biodeposition from suspended shellfish aquaculture and assessing benthic effects[END_REF]. [START_REF] Mckindsey | Biodeposit production and benthic loading by farmed mussels and associated tunicate epifauna in Prince Edward Island[END_REF] reported that tunicates present on mussel lines tended to double their sedimentation rate. The bioproducts also influence the settling velocity [START_REF] Mckindsey | Biodeposit production and benthic loading by farmed mussels and associated tunicate epifauna in Prince Edward Island[END_REF][START_REF] Walker | Influence of suspended mussel lines on sediment erosion and resuspension in Lagune de la Grande Entrée, Îles-de-la-Madeleine[END_REF]; the agglomerates formed by these bioproducts are heavy and sink rapidly through the water column. This change in speed also affects the spatial distribution of the mud (McKindsey et al., 2009). As sediments reach the bottom fast, their propagation distance is short [START_REF] Mckindsey | Biodeposit production and benthic loading by farmed mussels and associated tunicate epifauna in Prince Edward Island[END_REF]. Bioproducts also affect the structure and composition of mud [START_REF] Mckindsey | Influence of suspended and off-bottom mussel culture on the sea bottom and benthic habitats: A review[END_REF][START_REF] Walker | Influence of suspended mussel lines on sediment erosion and resuspension in Lagune de la Grande Entrée, Îles-de-la-Madeleine[END_REF][START_REF] Wang | Potential role of scallops Argopecten irradians in deposition of particulate nutrient and trace elements in a eutrophic estuary, northern China[END_REF]. A study of mud collected near mussel farms showed that the rate of erosion was higher in the presence of mussels; this could be linked, in particular, to changes in the composition of the mud [START_REF] Walker | Influence of suspended mussel lines on sediment erosion and resuspension in Lagune de la Grande Entrée, Îles-de-la-Madeleine[END_REF]. As bioproducts are notably the result of digestion processes, their composition is directly influenced by the metabolism of organisms. Changes in the carbohydrate and protein content of the bioproducts, both of which are correlated with sediment cohesion [START_REF] Malarkey | The pervasive role of biological cohesion in bedform development[END_REF][START_REF] Kameda | Influence of biopolymers on the rheological properties of seafloor sediments and the runout behavior of submarine debris flows[END_REF], could explain this behavioural change in the resulting mud.

The amount of bioproducts produced depends on the species [START_REF] Fiala-Médioni | Ethologie alimentaire d'invertébrés benthiques filtreurs (ascidies). II. Variations des taux de filtration et de digestion en fonction de l'espèce[END_REF][START_REF] Hawkins | Some general relationships in comparing the feeding physiology of suspension-feeding bivalve molluscs[END_REF][START_REF] Ward | Separating the grain from the chaff: Particle selection in suspension-and deposit-feeding bivalves[END_REF][START_REF] Mckindsey | Biodeposit production and benthic loading by farmed mussels and associated tunicate epifauna in Prince Edward Island[END_REF] and is related to the filtration rate [START_REF] Hawkins | Some general relationships in comparing the feeding physiology of suspension-feeding bivalve molluscs[END_REF][START_REF] Ward | Separating the grain from the chaff: Particle selection in suspension-and deposit-feeding bivalves[END_REF]. The filtration rate varies according to each organism's metabolism, which is influenced by environmental factors, such as sediment supply, amount of organic matter, season, temperature, and salinity [START_REF] Ward | Separating the grain from the chaff: Particle selection in suspension-and deposit-feeding bivalves[END_REF][START_REF] Riisgård | Effect of Salinity-Changing Rates on Filtration Activity of Mussels from Two Sites within the Baltic Mytilus Hybrid Zone: The Brackish Great Belt (Denmark) and the Low Saline Central Baltic Sea[END_REF]Zuñiga et al., 2014, Ehrich and[START_REF] Ehrich | A review of existing eastern oyster filtration rate models[END_REF].

Filter feeders appear predominantly during siltation in some contexts. Therefore, it is important to not neglect their role in the siltation of port areas. This study aimed to highlight the role of filter feeders in the siltation process in port areas and to determine the factors that influence their production in bioproducts. An experimental analysis was performed at La Rochelle marina. The bioproducts of the filter feeders were collected and analysed using sediment traps fixed under the pontoons. The study was performed over a period of 2 months, in two distinct seasons, to precisely determine the evolution of this production.

The La Rochelle marina is the largest marina in Europe, with an area of 70 ha. Its maintenance requires the dredging of approximately 200,000 m 3 of mud per year (Direction Départementale des Territoires et de la Mer de la Charente-Maritime, 2018). It is divided into four basins with distinct filter feeder communities and environmental conditions, allowing for a detailed study of the environmental factors that influence the production of bioproducts. This makes it an ideal site for studying the role of filter feeders in the siltation process in port areas.

Materials and methods

Study site

The La Rochelle marina is located along the French Atlantic coast in the central part of the Bay of Biscay (Fig. 1). This port was created in 1972 and is one of the largest marinas in the world with 5,000 moorings. [START_REF] Huguet | Dynamics and management of siltation in a macro-tidal marina: The case of La rochelle marina, France[END_REF] described the hydrosedimentary dynamics of this port. Five sampling points were selected in areas with different hydrosedimentary profiles (Fig. 1) [START_REF] Huguet | Dynamics and management of siltation in a macro-tidal marina: The case of La rochelle marina, France[END_REF]:

Pontoon 13 (200 m), in the centre of the Lazaret Basin, is characterised by strong tidal currents and considerable siltation. Far behind the breakwater, it is protected from winds and waves.

Pontoon 43 (150 m) was the most distant from the marina openings at the end of the Marillac basin. At the back of the basin, the hydrodynamics are low, and the siltation is constant and low.

Pontoon 51 (125 m), at the west of the Tamaris basin, is located close to the channel but is protected by a breakwater. The hydrodynamics and siltation are considerable.

Pontoon 61 (170 m), at the east of the Tamaris basin, is close to an opening to the sea.

It is also characterised by considerable siltation, and its hydrodynamics are strongly influenced by wind.

The Capitainerie pontoon (150 m) is at the centre of the channel. The hydrodynamics are the strongest at this level. Siltation is constant and considerable.

Experimental design and sample analysis

To sample the bioproducts rejected by the filter feeders living under the pontoons, we created an experimental protocol. Sixteen campaigns were conducted in two different seasons (eight from January to March 2020 and eight from May to July 2020). For each campaign, 50 sediment traps were deployed for 24 h under five pontoons (Fig. 1), that is, 10 traps per pontoon. As the sampled pontoons were of different sizes, the traps were distributed equidistant from each other along the length of the pontoons. This process allowed precise monitoring of bioproduct production within each pontoon. To avoid damage to the organisms living under the pontoons, the traps were carefully placed and removed by a professional diver. The diver first cleaned the organisms by stirring the surrounding water. This ensured that only bioproducts were recovered and not the sediment deposited on the organisms. Of these 10 traps, two were used as controls and were placed in areas of the pontoon that were devoid of organisms (the organisms being previously removed by the diver).

To prevent the loss of bioproducts or external incoming fluxes from the surrounding environment, the traps were made of 25-cm diameter plastic cylinders and placed as close as possible to the pontoon (Fig. 2). The traps were set for 24 h -this is the optimal duration to maximize the harvest of bioproducts; beyond this time, the average quantity of bioproducts harvested per trap decreases (Personal observation, obtained during a preliminary study conducted in May 2019, to optimize the protocol under the same pontoons). To allow decantation while preventing degradation of the samples, the contents of the traps were placed in a cold room at 3 °C for 24 h. After decanting (by pouring off or aspiration), the remaining sediment was centrifuged at 1500 ×g for 3 min. After removing the supernatant (by pouring off and aspiration), the pellet was placed in an oven at 60 °C for 72 h and then weighed to obtain the total dry mass of the bioproducts of each sample. Loss on ignition analysis was then carried out for 5 h at 550 °C to obtain the mineral content. The organic content was calculated by subtracting the mineral content from the total dry mass. To obtain only the quantity of matter produced by the organisms, the average mass of matter in the control traps per pontoon was subtracted from that of each sample.

Environmental data

To precisely understand the elements that influence the quantity of the bioproducts, a census of the filter feeders present under each pontoon was carried out. Three samples per season were collected from each pontoon: one from each end and one from the centre. To carry out this sampling, a 0.64-m 2 floating quadrat was placed under the pontoon, and all the organisms found therein were collected by a scientific diver. Only the four most abundant taxa were counted (Fig. 3).

-Mussels: Mytilus edulis (Linnaeus, 1758).

-Oysters: Crassostrea gigas (Thunberg, 1793).

-Scallops: Mimachlamys varia (Linnaeus, 1758).

-Ascidians: Ciona intestinalis (Linnaeus, 1767) and Clavelina sp. (Müller, 1776).

The size (width × length × height) of the bivalves was recorded. Individuals below 1 cm were considered juveniles and were not measured. During the two sampling periods, the multiparameter YSI 6600 V2 probes were positioned under pontoons 43 and 51. The same probe was also placed under pontoon 13 in summer. This probe provides the temperature, oxygen, salinity, and turbidity data ( During the second sampling period, the sestonic charge was measured to estimate the organic and mineral matter available for the filter feeders. At the port entrance, the day before each sampling, a water sample was collected from just under the pontoon using a horizontal Niskin bottle. The water was filtered through a 0.7-μm gf/f filter, and the collected sediments were analysed according to the same protocol as for the sediment traps. This sample was used to calibrate the probes and models.

Data analysis

The production of bioproducts has been studied at different scales. It has been examined between different pontoons as well as between different campaigns and seasons.

We analysed the bioproducts as a whole using the dry matter produced, and the composition of the bioproducts was determined through the percentage of organic matter. The results of All statistical tests were carried out using R software (Version 3.6.3 "Holding the Windsock") with a rejection threshold of 5%. As the data did not satisfy the conditions for applying parametric tests (normality of the distributions and homoscedasticity), nonparametric tests were used. The Wilcoxon-Mann-Whitney test was used to compare the average production of the controls and replicas as well as to compare the average amounts of dry and organic matter produced between seasons for each pontoon. For multiple comparisons, the Kruskal-Wallis test and Wilcoxon pairwise post-hoc test were used.

To estimate the relationships between the average dry matter production rate and environmental conditions, the Pearson correlation test was used with a rejection threshold (r) of 0.5 to estimate the relationships between the average dry matter rate produced and environmental conditions.

Results

Preamble

For each season and pontoon, the amount of dry matter in the controls was significantly lower than that in the replicates. The average amount of total dry matter per trap was 9.4510.6 g for the replicas and 1.812.85 g for the control traps in winter and 6.606.97 g for the replicas and 0.9020.787 g for the control traps in summer. The organism-free control traps allowed us to verify that the data pertaining to the replica traps were indeed related to bioproduction. In both seasons, the production of bioproducts was homogeneous within each pontoon, allowing accurate comparisons between the pontoons.

All data presented hereafter are expressed as the amount of matter produced by the organisms per square meter, that is, the average mass of materials in the control traps per pontoon subtracted from the mass in each sample.

.1. Study of bioproduction

The amount of dry matter produced differed between winter (chi-squared = 80.72, df = 4, p < 2.2e-16) and summer (chi-squared = 118.29, df = 4, p < 2.2e-16). In both seasons, the average dry matter produced in the Capitainerie pontoon was significantly higher than that produced in the other pontoons, whereas that of pontoon 43 was significantly lower (Fig. 4 A,B). The bioproduction in Capitainerie pontoon was, on average, eight times greater than that in pontoon 43 in winter and almost 10 times greater in summer (Fig. 4 A andB).

For all pontoons, the average dry matter production was different between winter campaigns (chi-squared = 87.65, df = 6, p-value < 2.2e-16) and between summer campaigns (chi-squared = 66.46, df = 7, p-value = 7.619e-12) (Fig. 4 C and D). However, this difference seemed to be pronounced for the winter season; the weekly cyclicity showed an alternating increase and decrease in average production (Fig. 4 C and D).

The average dry matter production did not differ between the two seasons, both for the pontoons as a whole (W = 40431, p = 0.054) and per pontoon. The amount of organic matter found in the bioproducts was found to be similar between pontoons (Fig. 4 A and B). In winter, the amount fluctuated from 11.972.65% for pontoon 61 to 15.974.09% for pontoon 43. In summer, the amount fluctuated from 15.536.2% for pontoon 61 to 19.326.33% for pontoon 13. For all pontoons, the amount of organic matter found in the bioproducts was higher in summer (17.45.62%) than in winter (13.83.43%) (W = 12023, p-value < 2.2e-16).

The within-season variation between campaigns was low (Fig. 4 C and D), with organic matter amounts ranging between 12.891.44% and 15.924.57% in the winter campaigns and 13.344.53% and 19,678,69% in the summer campaigns.

.2. Factors influencing bioproduction

Filter feeders

In both seasons, production was not related to the number of organisms present under the pontoons (winter: t = 2.98, df= 58, r = 0.36; summer: t = 1.54, df = 58, r = 0.19). Whereas the average production between winter and summer seasons was similar, yet the number of individuals present under the pontoons was four times higher in summer than in winter (Fig. 5 and Table 2). Production appeared to be taxon-dependent (Fig. 5). There was more production in areas where mussels were present during winter (t = 5.38, df = 13, r = 0.83) and summer (t =2.57, df = 13, r = 0.58). Production also correlated with the presence of oysters in winter (t = 2.34, df = 13, r = 0.54).

Table.2.

The average number of individuals and their size, as well as the average number of juveniles, collected under the pontoons for each season

For both seasons and each taxon, there was no relationship observed between production and the size of the individuals (r ∈ [-0.5> < 0.5]). For each taxon, the size of the individuals was not significantly different between the seasons (Table 2), but the number of juveniles, all taxa combined, was almost 20 times higher in summer (W=56.5, p=0.02).

Abiotic factors

In winter, for all the pontoons, bioproduction was positively correlated with the sediment concentration and the tidal range (r > 0.5) (Fig. 6 and Fig. 7). A marked weekly alternation in sediment concentration was observed, and it seemed to correspond to the observed production patterns (Fig. 6 and Fig. 7). The sediment concentration was not uniformly distributed among the pontoons: the Capitainerie pontoon was the most supplied with sediment, whereas pontoon 43 was the least supplied with sediment (Fig. 6). For the Capitainerie pontoon, which was the most exposed, production was also In summer, production did not seem to correlate with the selected factors (r ∈ [-0.5> < 0.5]). Except for the Capitainerie pontoon, where production was correlated with sediment

Discussion

Filter feeders are often overlooked in studies on the sedimentary process. In La Rochelle marina, considering the 15 km stretch of pontoons that make up this port, filter feeders release nearly 3.2 tons of bioproducts per day (130 g/m 2 /d of dry matter). The distribution of the bioproducts among the pontoons was spatiotemporally heterogeneous. The factors influencing the distribution can be classified into two categories: abundance of various organisms and sediment availability.

.1. Filter feeders' contribution

The filter feeders are heterogeneously distributed in the La Rochelle marina, and the areas abundant in oysters and mussels seem to be the areas with the most pronounced bioproduction. Thus, the hypothesis that bioproduction is a taxa-dependent process seems to be valid. In this sense, a study by [START_REF] Mckindsey | Biodeposit production and benthic loading by farmed mussels and associated tunicate epifauna in Prince Edward Island[END_REF] showed that sedimentation rates are influenced by the species present; sedimentation rates had almost doubled from 3.9 g/d to 7.2 g/d when tunicates were present in addition to mussel populations [START_REF] Mckindsey | Biodeposit production and benthic loading by farmed mussels and associated tunicate epifauna in Prince Edward Island[END_REF]. This study highlights the fact that bioproduction should be examined not only on a species-by-species basis but also at a community scale. However, given the small number of replicates available and the complexity of the filter feeder communities present under the pontoons, we only examined the taxa that seemed to be strongly correlated with bioproduction.

The maximum filtration rate (found in literature) of a mussel (Mytilus edulis) is almost twice that of an oyster (Crassostrea gigas), respectively, at 0.014 m 3 /g/h [START_REF] Riva | Etude écophysiologique de quelques mollusques bivalves[END_REF]) and 0.007 m 3 /g/h [START_REF] Ehrich | A review of existing eastern oyster filtration rate models[END_REF]. Thus, mussels are expected to capture and release more sediments than oysters do. This hypothesis is in accordance with the results of the present study, where the correlation between bioproduction and the presence of mussels (Mytilus edulis) was stronger than that between bioproduction and the presence of oysters (Crassostrea gigas). This hypothesis also supports the fact that bioproduction is a speciesdependent process.

The amount of bioproducts formed is directly related to the filtration rate [START_REF] Hawkins | Some general relationships in comparing the feeding physiology of suspension-feeding bivalve molluscs[END_REF][START_REF] Ward | Separating the grain from the chaff: Particle selection in suspension-and deposit-feeding bivalves[END_REF], which depends on the metabolism of the organism, which in turn is modulated by environmental conditions [START_REF] Riisgård | Effect of Salinity-Changing Rates on Filtration Activity of Mussels from Two Sites within the Baltic Mytilus Hybrid Zone: The Brackish Great Belt (Denmark) and the Low Saline Central Baltic Sea[END_REF]Zuñiga et al., 2014;[START_REF] Ehrich | A review of existing eastern oyster filtration rate models[END_REF]. In the present study, the rate of bioproduct formation in one pontoon was found to be related to salinity and oxygen levels. Oxygen is a basic requirement for metabolism; therefore, the hypothesis that production rates are inversely correlated with oxygen levels seems coherent. Oxygen content has been found to limit the filtration rate in oysters in some models [START_REF] Cerco | Evaluating Ecosystem Effects of Oyster Restoration in Chesapeake Bay A Report to the Maryland Department of Natural Resources[END_REF].

Salinity also affects the filtration rate. [START_REF] Riisgård | Effect of Salinity-Changing Rates on Filtration Activity of Mussels from Two Sites within the Baltic Mytilus Hybrid Zone: The Brackish Great Belt (Denmark) and the Low Saline Central Baltic Sea[END_REF] demonstrated that the filtration rate of the two mussel species was closely related to salinity. In their review, [START_REF] Ehrich | A review of existing eastern oyster filtration rate models[END_REF] showed that salinity had an impact on the filtration rate of oysters; in fact, similar to our results, several studies showed that an increase in salinity increased the filtration rate and vice versa (Powell et al., 1992;[START_REF] Cerco | Evaluating Ecosystem Effects of Oyster Restoration in Chesapeake Bay A Report to the Maryland Department of Natural Resources[END_REF][START_REF] Fulford | Effects of oyster population restoration strategies on phytoplankton biomass[END_REF].

Lavaud et al. showed that changes in salinity had an impact on the filtration rate of oysters, and any disturbance in the filtration rate affected the growth and reproduction of organisms [START_REF] Lavaud | Integrating the effects of salinity on the physiology of the eastern oyster, Crassostrea virginica, in the northern Gulf of Mexico through a Dynamic Energy Budget model[END_REF].

Studies on pearl oysters (Pinctada margaritifera) and mussels (Mytilus edulis) have shown that the rates of filtration and clearance are size dependent [START_REF] Pouvreau | Filtration by the pearl oyster, Pinctada margaritifera, under conditions of low seston load and small particle size in a tropical lagoon habitat[END_REF][START_REF] Jacobs | Length-and weight-dependent clearance rates of juvenile mussels (Mytilus edulis) on various planktonic prey items[END_REF]. This result could explain the correlation between bioproduction and the number of oysters in winter, but not in summer. Indeed, if we only examine the number of oysters, we can see that some areas rich in oysters are not very productive. However, considering the size of the oysters in parallel, we notice that it is mainly the areas with small oysters that are less productive in summer. This is probably linked to the hazard of recruitment: oyster larvae settle where they find support, but this is not necessarily the most suitable place for their survival. Long-term monitoring would provide a better understanding of the evolution of communities and their relationship to bioproduction.

For each taxon and pontoon, the amount of matter produced did not depend on the number of individuals present under the pontoons. If we consider the example of mussels, we can see that they are 10 times more densely present in summer than in winter, yet their bioproduction amounts are the same between the two seasons. Size is an important factor, as we have seen previously, and the number of juveniles is important in summer. However, mussels live for several years, so we expect to find a large proportion of mussels in winter and summer. This shows that production is not limited by the number of individuals, but by another factor: sediment availability.

.2. Contribution of sediments

The availability of sediments is a limiting factor for bioproduction. Organisms that produce bioproducts must have sedimentary input. Filter feeders do not create material, instead they trap it, consume some of it, and release some of the modified material as waste.

In the present study, we found that the distribution of these sediment inputs was spatially and temporally heterogeneous, and that filter feeder bioproducts are closely correlated with sediment availability. Indeed, if we look at the bioproduction on a seasonal scale, we notice that although the average quantity is relatively similar, the campaigns with the highest production corresponded to the times when the sediment supply was the highest (Fig. 6 and Fig. 7). Similarly, the pontoon with the least amount of production (pontoon 43) had the least sediment input, and the pontoon with the highest production (Capitainerie pontoon) had the highest input. Several studies have shown that the filtration rates of oysters and mussels are strongly influenced by sediment input [START_REF] Ward | Separating the grain from the chaff: Particle selection in suspension-and deposit-feeding bivalves[END_REF][START_REF] Ehrich | A review of existing eastern oyster filtration rate models[END_REF].

For these two species, the filtration rate tends to increase up to a threshold with the sestonic charge [START_REF] Ward | Separating the grain from the chaff: Particle selection in suspension-and deposit-feeding bivalves[END_REF][START_REF] Ehrich | A review of existing eastern oyster filtration rate models[END_REF] and is also modulated by the size of the particles (Benniger et al., 1999;[START_REF] Ward | Separating the grain from the chaff: Particle selection in suspension-and deposit-feeding bivalves[END_REF]) and organic input [START_REF] Hawkins | Some general relationships in comparing the feeding physiology of suspension-feeding bivalve molluscs[END_REF][START_REF] Jacobs | Length-and weight-dependent clearance rates of juvenile mussels (Mytilus edulis) on various planktonic prey items[END_REF]. These saturation and sorting phenomena are regulated by several mechanisms, which are well documented in the literature, and depend on both the quantity and quality of the available sediment [START_REF] Ward | Separating the grain from the chaff: Particle selection in suspension-and deposit-feeding bivalves[END_REF][START_REF] Ehrich | A review of existing eastern oyster filtration rate models[END_REF][START_REF] Jacobs | Length-and weight-dependent clearance rates of juvenile mussels (Mytilus edulis) on various planktonic prey items[END_REF]. Indeed, bivalves filter water with their gills to recover nutrient particles. The gills have dual functions: respiratory and alimentary. They ensure the circulation of seawater through the movement of the lateral gill cilia. The particles were transported to the mouth by the action of the lateral and frontal cilia. Before being carried to the mouth, the labial palps (which surround the mouth) select particles; those that are not ingested are rejected in aggregates, known as pseudo-faeces. The ingested particles are digested, a fraction is used for metabolism by the organism, and the rejects are evacuated through the anus in the form of faeces. [START_REF] Wildish | Effect of the PSP-causing dinoflagellate, Alexandrium sp. on the initial feeding response of Crassostrea gigas[END_REF][START_REF] Castrec | Impacts des efflorescences du dinoflagellé toxique Alexandrium minutum sur la reproduction et le développement de l'huître Crassostrea gigas[END_REF]. Several studies have shown that the filtration rate and particle selection process can be affected by variables, such as particle content, size and type of particles ingested, and the presence of trace elements in the environment [START_REF] Cognie | Selective feeding of the oyster Crassostrea gigas fed on a natural microphytobenthos assemblage[END_REF][START_REF] Loayza-Muro | Responses of the mussel Anodontites trapesialis (Unionidae) to environmental stressors: effect of pH, temperature and metals on filtration rate[END_REF]Enriquezoceaña et al., 2012;[START_REF] Rosa | Selective capture and ingestion of particles by suspension-feeding bivalve molluscs: a review[END_REF]. The quantity and quality of available plankton as well as the ratio of plankton-to-mineral matter, influence the particle selection, filtration, and assimilation of organisms [START_REF] Hawkins | Some general relationships in comparing the feeding physiology of suspension-feeding bivalve molluscs[END_REF][START_REF] Jacobs | Length-and weight-dependent clearance rates of juvenile mussels (Mytilus edulis) on various planktonic prey items[END_REF][START_REF] Rosa | Selective capture and ingestion of particles by suspension-feeding bivalve molluscs: a review[END_REF]. This directly affects the type of bioproducts (faeces vs. pseudo-faeces) and their compositions and quantity [START_REF] Smaal | Goods and services of marine bivalves[END_REF]. Several bivalves, for example, increase the proportion of pseudo-faeces in their rejects when the particulate content of the environment is high or low in organic matter [START_REF] Ward | Separating the grain from the chaff: Particle selection in suspension-and deposit-feeding bivalves[END_REF][START_REF] Smaal | Goods and services of marine bivalves[END_REF]. It is thus expected that summer waters, which are richer in plankton, are better assimilated by organisms and that the quality and quantity as well as the type of bioproducts rejected, are directly impacted.

Considering the composition of the bioproducts, we can see that they contain a higher proportion of organic matter in summer than in winter. This result is in accordance with that of a study conducted in the Iberian Peninsula on mussels (Mytilus galloprovincialis) (Zuñiga et al., 2014). This difference could be related to the presence of plankton, which are more abundant and of higher nutritional quality in summer than in winter (Zuñiga et al., 2014).

However, we did not discriminate between pseudo-faeces and faeces produced nor analyse their precise composition. Furthermore, the precise sediment composition of the La Rochelle marina is unknown. Additional studies on the composition of the available sediments in relation to the composition of the bioproducts would allow for further analysis and would help to understand the inter-seasonal differences in the organic matter produced. These results may be related to the metabolic needs of the organisms, which will also directly affect the composition of the bioproducts.

The sediment concentration is determined by many environmental factors. One of the main factors related to sediment concentration on the Atlantic coast is the tide [START_REF] Van Rijn | Harbour siltation and control measures[END_REF][START_REF] Huguet | Dynamics and management of siltation in a macro-tidal marina: The case of La rochelle marina, France[END_REF]. This explains the close correlation between the tidal range and production rate. [START_REF] Huguet | Dynamics and management of siltation in a macro-tidal marina: The case of La rochelle marina, France[END_REF] showed that wind and waves are also significant factors to be considered when studying sediment concentrations. This could explain the correlation between wind direction and bioproduction rate in the Capitainerie pontoon and between wave height and production in pontoon 43. The Capitainerie pontoon is in the fairway and is probably the most exposed to the wind, which could explain why it is the only pontoon to be directly influenced by this factor. Pontoon 43 is the least productive pontoon, but it is also the pontoon whose production amounts showed the lowest variability; therefore, the small variations, such as the contribution of the waves, may be easily observed.

The future of bioproducts and their implications

Our analysis of the impact of filter feeders on the composition of mud has highlighted the fact that filter feeders interact with a considerable proportion of the sediment, trapping it during feeding and releasing it as a bioproduct during excretion. However, before these bioproducts become an integral part of mud, they are released into the water column where they are affected by a number of environmental variables. These rejects flocculate and aggregate with other particles; hence, their composition as well as their movement in the water column changes [START_REF] Jarvis | A review of floc strength and breakage[END_REF][START_REF] Liu | Comprehensive review of floc growth and structure using electrocoagulation: characterization, measurement, and influencing factors[END_REF]. Conversely, they are also affected by hydrodynamic variables and fragments [START_REF] Jarvis | A review of floc strength and breakage[END_REF][START_REF] Liu | Comprehensive review of floc growth and structure using electrocoagulation: characterization, measurement, and influencing factors[END_REF]. These behaviours are constrained by variables such as pH, temperature, salinity, presence of microalgae, and water flow (Xiao et al., 2007;[START_REF] Verney | Flocculation potential of estuarine particles: The importance of environmental factors and of the spatial and seasonal variability of suspended particulate matter[END_REF][START_REF] Mietta | Influence of shear rate, organic matter content, pH and salinity on mud flocculation[END_REF][START_REF] Kumar | Floc properties and settling velocity of San Jacinto estuary mud under variable shear and salinity conditions[END_REF]. The study of their behaviour in relation to the variables of the La Rochelle marina is, therefore, necessary to fully understand how bioproducts evolve before being incorporated into the mud.

The behaviour of these bioproducts in the water column and mud is also influenced by their initial structure and composition. Several studies [START_REF] Mietta | Influence of shear rate, organic matter content, pH and salinity on mud flocculation[END_REF][START_REF] Larsen | Morphologic and transport properties of natural organic floc[END_REF] have shown that flocs containing a high proportion of organic matter, such as those produced in the summer by the organisms in our study, would be larger in size. These larger flocs are also more resistant to fragmentation owing to the high organic content [START_REF] Eisma | Terrigenous Late Quaternary Sediment Components North and South of the Scotland-Greenland Ridge and in the Norwegian Sea[END_REF][START_REF] Jarvis | A review of floc strength and breakage[END_REF]. This large size would also lead to quicker sedimentation [START_REF] Fan | Characterisation of floc size, effective density and sedimentation under various flocculation mechanisms[END_REF]. Our analysis has provided some clues about their composition (share of organic and mineral matter), but further studies on their structure (size, density, mineral, and organic composition) would complete our data and inform us of the behaviour of these products in the water column and in the mud.

Bioproducts settle to the bottom faster than suspended matter and thus increase the flux of organic matter to the bottom, depending on the depth, currents, and resuspension process [START_REF] Chamberlain | Impacts of deposits from suspended mussel (Mytilus edulis L.) culture on the surrounding surficial sediments[END_REF][START_REF] Mckindsey | Biodeposit production and benthic loading by farmed mussels and associated tunicate epifauna in Prince Edward Island[END_REF][START_REF] Walker | Influence of suspended mussel lines on sediment erosion and resuspension in Lagune de la Grande Entrée, Îles-de-la-Madeleine[END_REF]. Thus, the presence of filter feeders in port areas could affect the frequency of dredging. Similarly, physicochemical changes in bioproducts can modify the texture of mud, making it more or less cohesive and, therefore, more or less difficult to remove [START_REF] Walker | Influence of suspended mussel lines on sediment erosion and resuspension in Lagune de la Grande Entrée, Îles-de-la-Madeleine[END_REF][START_REF] Wang | Potential role of scallops Argopecten irradians in deposition of particulate nutrient and trace elements in a eutrophic estuary, northern China[END_REF]. Dredging vessels are used for removing excess mud and maintaining a water depth suitable for navigation. They can be divided into two categories: mechanical and hydraulic dredgers [START_REF] Vlasblom | Dredging Equipment and Technology[END_REF][START_REF] Winterwep | Reducing harbor siltation. I: Methodology[END_REF]. Mechanical dredgers dig or collect mud from the bottom surface using a bucket or grab [START_REF] Vlasblom | Dredging Equipment and Technology[END_REF][START_REF] Winterwep | Reducing harbor siltation. I: Methodology[END_REF]. Hydraulic dredges suck up or resuspend the mud that has accumulated at the bottom [START_REF] Vlasblom | Dredging Equipment and Technology[END_REF][START_REF] Winterwep | Reducing harbor siltation. I: Methodology[END_REF]. Both methods are directly influenced by the texture and structure of the mud that needs to be removed. The former can be used is only on very cohesive muds, and the latter on less cohesive muds. Knowledge of the factors affecting the behaviour of muds, such as those presented in this study, is therefore an advantage for port managers and would allow them to anticipate and improve dredging operations by studying the communities present under the pontoons. This is all the more important because dredging activities have numerous impacts on the marine environment. By removing bottom sediments, dredging destroys habitats and modifies the topography and hydrography of the seabed [START_REF] Miller | Reducing risks of maintenace dredging on freshwater mussels (Unionidae) in the Big Sunflower River, Mississippi[END_REF][START_REF] Becker | Estimating source terms for far field dredge plume modelling[END_REF][START_REF] Manap | Environmental management for dredging sediments-the requirement of developing nations[END_REF]. Similarly, the dredging industry presents a real economic challenge to ports. The costs of dredging and processing of dredged materials represent a considerable part of the port budget. For example, in 2021, these costs amounted to 5.33 billion euros worldwide (IADC 2021). Given the economic and environmental challenges, ports need to adapt their dredging strategy to achieve a balance between profitability, environmental impact, and efficiency, which could involve studying the filter feeder communities present under the pontoons and analysing their rejects.

Conclusion

Understanding the factors that govern the production and behaviour of mud is a major aspect in port operations. In these hyper-anthropic environments, where life seems to have no place, the roles of the organisms that live there are often ignored. However, considerable communities grow in these areas, protected by pontoons and some, as highlighted here, play an important role in siltation processes, such as filter feeders. These organisms are able to trap and release a large amount of sediment, approximately 3.2 tons per day, if we extrapolate our results to the scale of the port.

Our study showed that bioproduction is modulated by many factors, such as the taxa of the organisms, tidal range, and environmental sediment concentration. However, in addition to their capacity to collect and release sediment, filter feeders also modify the physicochemical properties of sediments [START_REF] Walker | Influence of suspended mussel lines on sediment erosion and resuspension in Lagune de la Grande Entrée, Îles-de-la-Madeleine[END_REF][START_REF] Mclean | Erodibility and transport behavior of dreissenid mussel deposits in an annular flume[END_REF][START_REF] Wang | Potential role of scallops Argopecten irradians in deposition of particulate nutrient and trace elements in a eutrophic estuary, northern China[END_REF]. Thus, it is important to focus on the future of these rejects. How will the changes in their physicochemical properties influence their behaviour in the water column and mud?

Similarly, as shown in other contexts, filter feeder bioproducts have an influence on benthic communities and their exchange with different compartments [START_REF] Callier | Responses of benthic macrofauna and biogeochemical fluxes to various levels of mussel biodeposition: An in situ "benthocosm" experiment[END_REF][START_REF] Lavoie | Influence of intertidal Manila clam Venerupis philippinarum aquaculture on biogeochemical fluxes[END_REF][START_REF] Murphy | Bioreactivity and microbiome of biodeposits from filter-feeding bivalves[END_REF]. But what about in harbour areas? This study and all the questions it raises (and the list is not exhaustive) show that the involvement of organisms such as filter feeders in the hydro-sedimentation and siltation processes must not be ignored. This study may also help port management by providing managers with a better understanding of the factors governing their environment.

of Higher Education and Research, the European Regional Development Fund, the regional state plan and the National Centre for Scientific Research.

Fig. 1 .

 1 Fig.1. Study area, La Rochelle marina (Les Minimes). Surrounded by red: the sampled

Fig. 2 .

 2 Fig.2. Photograph of a trap placed under the pontoon

Fig. 3 .

 3 Fig.3. Photographs of ascidians (A), scallops (B), mussels (C), and oysters (D) under pontoons

Fig. 4 .

 4 Fig.4. Averages of dry matter produced and associated standard deviation in two different seasons, per pontoon (A and B) and per campaign (C and D). ***statistically distinct average. In red the average fraction of associated organic matter and its standard deviation

Fig. 5 .Fig. 6 .

 56 Fig.5. Average number of individuals and associated standard deviation, per pontoon and per taxon. In red, the average dry matter produced per pontoon and their standard deviation

  correlated with wind direction (t = 4.16, df = 40, r = 0.55). For pontoon 43, production was also related to other factors such as salinity (t= 3.95, df = 19, r = 0.67), amount of dissolved oxygen (t = -4.40, df = 19, r = -0.71), and wave height (t= 5.28, df = 48, r = 0.60).

  concentration and tidal range (t = 5.46, df = 54, r= 0.59; t = 4.71, df = 54, r = 0.54) (Fig.A.2).

Fig. 7 .

 7 Fig.7. Top (A): average dry matter produced was associated standard deviation per winter campaign for each pontoon. Bottom (B): trends of two abiotic factors -tidal range (in black) and average sediment concentration (in red) -over the winter campaigns

Fig.A. 2 .

 2 Fig.A.2. Maps of average environmental sediment concentration and average daily bioproduction (in red) for the summer campaigns. The intensity of the red is proportional to the amount of bioproducts formed.

Table 1

 1

, Fig.A.1). Meteorological and hydrodynamic data were also collected for all the campaigns (Table 1, Fig.A.1).

Table . 1

 . . Environmental variables of the study area and their sources campaign 6 are not presented here because the field conditions did not allow us to recover all traps correctly.

Acknowledgements

We gratefully thank the Marina of La Rochelle for their assistance in particularly for the data transmission and the "Musée Mer Marine Bordeaux" for the involvement in the V. HAMANI PhD. This work has also been supported from bodies such as the French Ministry