Miguel A Cruz

Oscar Godoy

Inês Fragata

Vitor C Sousa

Sara Magalhães

Flore Zélé
email: flore.zele@cnrs.fr

Sex in the kitchen: non-additive effects of competition for food and reproductive interference on coexistence outcomes between closely related species

Competition for food and negative interspecific sexual interactions (reproductive interference) have been identified as major drivers of species exclusion. These interactions likely do not act independently, as they often involve the same actors and may be modulated by the same underlying traits. However, how they determine competitive dominance when acting in combination has not yet been studied. Here, we address this issue using two closely related species, the spider mites Tetranychus urticae and T. cinnabarinus. First, by measuring species interactions in small-scale experiments, we revealed that the strength and symmetry of reproductive interference between species changed in presence of food competition. Next, using a population model, we showed that such non-additive effects induce significant changes in predicted competitive outcomes, specifically, a change in priority effects from favouring the inferior competitor for food in the sole presence of reproductive interference to favouring the superior competitor instead. Finally, we confirmed the accuracy of the model predictions for short-term population dynamics in a large-scale experiment. Together, these lines of evidence show that food competition and reproductive interference have non-additive effects on the population dynamics of interacting species, and highlight the necessity of incorporating both mechanisms to better predict competitive outcomes.

Introduction

Competitive interactions between organisms, be they for food, mates, or hosts, shape population dynamics and affect species distributions. Indeed, all these interactions generally have negative consequences for population growth of one or both species involved. They are also often modulated by the same underlying traits. For example, size is a mediator of competition for food, but also for mates [START_REF] Pollo | The better, the choosier: A meta-analysis on interindividual variation of male mate choice[END_REF][START_REF] Kvarnemo | The dynamics of operational sex ratios and competition for mates[END_REF][START_REF] Grainger | Rapid evolution of life-history traits in response to warming, predation and competition: A meta-analysis[END_REF][START_REF] Tan | Body size and shape responses to warming and resource competition[END_REF] . Still, despite all the potential for interaction among these types of competition, they have mostly been addressed in disparate bodies of literature [START_REF] Rodrigues | Integrating Competition for Food, Hosts, or Mates via Experimental Evolution[END_REF] .

The impact of competition for food (i.e., exploitative competition) in shaping species coexistence has been predicted and analysed by means of modern coexistence theory [START_REF] Macarthur | Species Packing and Competitive Equilibrium for Many Species[END_REF][START_REF] Amarasekare | Interference competition and species coexistence[END_REF][START_REF] Chesson | Updates on mechanisms of maintenance of species diversity[END_REF][START_REF] Spaak | Mapping species niche and fitness differences for communities with multiple interaction types[END_REF][START_REF] Chesson | Mechanisms of maintenance of species diversity[END_REF] . This framework posits that two species can coexist when niche differences, arising when intraspecific competition exceeds interspecific competition, are greater than fitness differences (i.e., differences in species' intrinsic growth rate weighted by their overall sensitivity to competition). Otherwise, the species with higher fitness outcompetes the inferior competitor.

Alternatively, priority effects can occur when species limit their competitor's growth more than their own (negative niche differences). In that case, the species that arrives first in a community, or is at an initial higher frequency, dominates it locally [START_REF] Amarasekare | Interference competition and species coexistence[END_REF][START_REF] Ke | Coexistence theory and the frequency-dependence of priority effects[END_REF] .

Although the validity of this framework to predict the population dynamics of interacting species has been shown in a wide variety of biological systems [START_REF] Godoy | Phenology effects on invasion success: Insights from coupling field experiments to coexistence theory[END_REF][START_REF] Narwani | Experimental evidence that evolutionary relatedness does not affect the ecological mechanisms of coexistence in freshwater green algae[END_REF][START_REF] Fragata | Specific sequence of arrival promotes coexistence via spatial niche preemption by the weak competitor[END_REF][START_REF] Grainger | Applying modern coexistence theory to priority effects[END_REF][START_REF] Li | Niche and fitness differences determine invasion success and impact in laboratory bacterial communities[END_REF] , it has largely overlooked competition for other types of resource beyond food. This is at odds with the fact that other types of competition can arise between those same individuals that are competing for food. For instance, closely related species are likely to engage in competition for food, due to sharing similar niches [START_REF] Denno | Interspecific Interactions in Phytophagous Insects: Competition Reexamined and Resurrected[END_REF] , and they can also compete for mates. This can result in reproductive interference, i.e., any sexual interaction between genetically differentiated organisms with negative fitness consequences for at least one of them, ranging from signal jamming to hybrid infertilty [START_REF] Burdfield-Steel | Reproductive interference[END_REF][START_REF] Gröning | Reproductive Interference Between Animal Species[END_REF] . Several laboratory [START_REF] Kishi | Reproductive interference in laboratory experiments of interspecific competition[END_REF] and field studies [START_REF] Whitton | Co-occurrence of related asexual, but not sexual, lineages suggests that reproductive interference limits coexistence[END_REF][START_REF] Liu | Asymmetric Mating Interactions Drive Widespread Invasion and Displacement in a Whitefly[END_REF][START_REF] Konishi | Impact of Asymmetrical Hybridization Followed By Sterile F1 Hybrids on Species Replacement in Pseudorasbora[END_REF] have shown that reproductive interference is an important mechanism driving exclusion, precluding interacting species from long-term persistence [START_REF] Whitton | Co-occurrence of related asexual, but not sexual, lineages suggests that reproductive interference limits coexistence[END_REF][START_REF] Hochkirch | Sympatry with the devil: Reproductive interference could hamper species coexistence[END_REF][START_REF] Ting | Demographic consequences of reproductive interference in multi-species communities[END_REF] . Indeed, species are increasingly affected by reproductive interference as they become rarer due to reduced encounter rates with conspecifics [START_REF] Gröning | Reproductive Interference Between Animal Species[END_REF] .

Theoretically, reproductive interference is thus predicted to cause priority effects, thereby leading to the exclusion of the initially less common species [START_REF] Kishi | Analysis of species coexistence co-mediated by resource competition and reproductive interference[END_REF] . However, theoretical studies also predict that the outcome of reproductive interference may change depending on its interplay with trophic interactions [START_REF] Kishi | Reproductive interference in laboratory experiments of interspecific competition[END_REF][START_REF] Kishi | Analysis of species coexistence co-mediated by resource competition and reproductive interference[END_REF][START_REF] Yamamichi | Frequency-dependent community dynamics driven by sexual interactions[END_REF] .

It is thus clear that the integration of trophic interactions such as competition for food and sexual interactions such as reproductive interference is key to our understanding of species dynamics and distribution [START_REF] Gómez-Llano | When Ecology Fails: How Reproductive Interactions Promote Species Coexistence[END_REF] . Some theoretical and empirical developments have been done in this direction [START_REF] Kishi | Reproductive interference in laboratory experiments of interspecific competition[END_REF][START_REF] Kuno | Competitive exclusion through reproductive interference[END_REF][START_REF] Yoshimura | Population Dynamics of Sexual and Resource Competition[END_REF][START_REF] Kishi | Reproductive interference determines persistence and exclusion in species interactions[END_REF][START_REF] Takafuji | Reproductive interference and its consequences on the competitive interactions between two closely-related Panonychus spider mites[END_REF] . They predict that both interactions may act synergistically to accelerate exclusion, but if both processes are asymmetric in opposite directions (such that the species most affected by food competition is equally less affected by reproductive interference and vice-versa), coexistence is possible [START_REF] Kishi | Analysis of species coexistence co-mediated by resource competition and reproductive interference[END_REF][START_REF] Schreiber | When rarity has costs: coexistence under positive frequency-dependence and environmental stochasticity[END_REF] . However, these theoretical models assumed that food competition and reproductive interference operate independently from one another, whereas mechanisms involved in both interactions may interact or be correlated, which should result in non-additive effects when both act in combination.

Food competition and reproductive interference may directly or indirectly affect each other's intensity if the same (or correlated) traits are involved in both interactions (e.g., body size [START_REF] Okuzaki | Resource partitioning or reproductive isolation: The ecological role of body size differences among closely related species in sympatry[END_REF] ), or due to density-dependent behaviours affecting the strength of both interactions [START_REF] Yamamichi | Frequency-dependent community dynamics driven by sexual interactions[END_REF] (e.g., increased dispersal and/or conspecific aggregation [START_REF] Ruokolainen | Stable coexistence of ecologically identical species: Conspecific aggregation via reproductive interference[END_REF][START_REF] Kyogoku | Species coexist more easily if reinforcement is based on habitat preferences than on species recognition[END_REF] ). In line with this, several empirical studies revealed that food competition can affect the reproductive success of individuals [START_REF] Fisher | Female swordtail fish use chemical cues to select wellfed mates[END_REF][START_REF] Sigurjónsdóttir | Food competition among Scatophaga stercoraria Iarvae with emphasis on its effects on reproductive success[END_REF] , or reciprocally, that different reproductive strategies may result in different investment in food competition [START_REF] Boussens-Dumon | Sex, competition and mimicry: an ecoevolutionary model reveals unexpected impacts of ecological interactions on the evolution of phenotypes in sympatry[END_REF][START_REF] Anderson | Non-additive effects of intra-and interspecific competition between two larval salamanders[END_REF] . However, these studies have largely focused on intraspecific interactions, whereas trophic and sexual interactions can also simultaneously occur between closely-related species, and jointly affect their traits [START_REF] Boussens-Dumon | Sex, competition and mimicry: an ecoevolutionary model reveals unexpected impacts of ecological interactions on the evolution of phenotypes in sympatry[END_REF] . In addition, while both empirical and theoretical studies investigated the impact of non-additivity between different types of trophic interactions (e.g., intra-and interspecific competition [START_REF] Anderson | Non-additive effects of intra-and interspecific competition between two larval salamanders[END_REF] , food competition, predation, or parasitism [START_REF] Lai | Non-additive biotic interactions improve predictions of tropical tree growth and impact community size structure[END_REF][START_REF] Morin | Functional Redundancy, Non-Additive Interactions, and Supply-Side Dynamics in Experimental Pond Communities[END_REF][START_REF] Coors | Synergistic, antagonistic and additive effects of multiple stressors: Predation threat, parasitism and pesticide exposure in Daphnia magna[END_REF] ) on species growth rates, potential non-additive effects between trophic and sexual interactions, such as between food competition and reproductive interference, have been considered only very recently in coexistence theory [START_REF] Yamamichi | Frequency-dependent community dynamics driven by sexual interactions[END_REF] , and remain to be tested experimentally.

Spider mites pose an ideal system to study the single and combined effects of food competition and reproductive interference on competitive outcomes. Some herbivorous species have been shown to compete for food when sharing host plants [START_REF] Fragata | Specific sequence of arrival promotes coexistence via spatial niche preemption by the weak competitor[END_REF][START_REF] Sarmento | A Herbivorous Mite Down-Regulates Plant Defence and Produces Web to Exclude Competitors[END_REF] , and some mites are closely related enough that reproductive interference can occur [START_REF] Takafuji | Reproductive interference and its consequences on the competitive interactions between two closely-related Panonychus spider mites[END_REF][START_REF] Clemente | Despite reproductive interference, the net outcome of reproductive interactions among spider mite species is not necessarily costly[END_REF][START_REF] Sato | Reproductive interference and sensitivity to female pheromones in males and females of two herbivorous mite species[END_REF][START_REF] Sato | Why do males choose heterospecific females in the red spider mite?[END_REF][START_REF] Smith | Spider Mites: Population Suppression by Interspecific Hybridization[END_REF] . Here, we used two such species, Tetranychus urticae and T. cinnabarinus, also often referred to as the green and red forms of T. urticae [START_REF] Auger | Evidence for synonymy between Tetranychus urticae and Tetranychus cinnabarinus (Acari, Prostigmata, Tetranychidae): Review and new data[END_REF] . These two share several host plants [START_REF] Xie | The two-spotted spider mite Tetranychus urticae Koch and the carmine spider mite Tetranychus cinnabarinus (Boisduval) in China mixed in their Wolbachia phylogenetic tree[END_REF] , on which they compete for food. In addition, reproductive incompatibilities between the two, owing to significant differentiation across their genomes [START_REF] Xue | Incomplete reproductive barriers and genomic differentiation impact the spread of resistance mutations between green-and red-colour morphs of a cosmopolitan mite pest[END_REF] , lead to variable degrees of unfit hybridization (i.e., from partial to complete hybrid sterility and hybrid breakdown [START_REF] De Boer | Partial hybrid sterility between strains of the arrhenotokous spider mite, Tetranychus urticae complex (Acari, Tetranychidae)[END_REF][START_REF] Sugasawa | Hybrid affinities between the green and the red forms of the two-spotted spider mite Tetranychus urticae (Acari: Tetranychidae) under laboratory and semi-natural conditions[END_REF][START_REF] Cruz | Wolbachia and host intrinsic reproductive barriers contribute additively to postmating isolation in spider mites[END_REF] ). This results in strong reproductive interference [START_REF] Smith | Spider Mites: Population Suppression by Interspecific Hybridization[END_REF] . With this experimental system, we used recent modelling advances rooted in coexistence theory [START_REF] Schreiber | When rarity has costs: coexistence under positive frequency-dependence and environmental stochasticity[END_REF] and its recent extensions [START_REF] Ke | Coexistence theory and the frequency-dependence of priority effects[END_REF][START_REF] Grainger | Applying modern coexistence theory to priority effects[END_REF][START_REF] Schreiber | When rarity has costs: coexistence under positive frequency-dependence and environmental stochasticity[END_REF] , and parameterised them with a set of experiments manipulating the presence or absence of food competition and reproductive interference. This combination of theory, modelling, and experiments allowed to predict their single and joint contribution to competitive outcomes. Such predictions were ultimately validated with an independent largescale cage population experiment, to distinguish which combination of food competition and reproductive interference best fit the observed population dynamics of interacting mite species.

Results

Food competition affects the strength and symmetry of reproductive interference.

Small-scale experiments, in which we assessed the strength of interactions by exposing females of each species to competition for food (Experiment 1), mates (Experiment 2), or both (Experiment 3), revealed large asymmetries between species. Indeed, females grown in absence of any competitors for food and heterospecific mates (controls) consistently differed in their intrinsic growth rates across all 3 experiments: T. cinnabarinus (Tc) females produced, on average, more offspring than T. urticae (Tu) females (λTc > λTu; Figures 1 and2a; Supplementary Table S1). When species competed only for food (Experiment 1), both species were more sensitive to heterospecific than to conspecific competitors (αTcTu > αTcTc and αTuTc > αTuTu), but Tc females were generally more sensitive to competition than Tu females, regardless of competitor identity (αTcTc*αTcTu > αTuTu*αTuTc ; Figures 1a and2b; Table S1). Conversely, when the two species were only exposed to reproductive interference (Experiment 2), Tu females suffered more from the presence of heterospecifics than Tc females (βTuTc > βTcTu; Figures 1b and2c; Table S1). Finally, when both interactions occurred simultaneously (Experiment 3), both species had lower intrinsic growth rates (λ) and were overall less sensitive to competition (α) than in the previous experiments (Figures 2a,b; see also Table S2 vs. S1), but the relationship between λ and α values was conserved, with Tc females producing more offspring and being more affected by competition than Tu females (Figure 2a,b). However, we found a drastic difference in the strength and symmetry of reproductive interference, as the sensitivity of Tc females to reproductive interference slightly increased, whereas that of Tu females strongly decreased. Thus, Tu females suffered less from reproductive interference (βTcTu > βTuTc; Figure 2c), and became overall less affected by the presence of heterospecific individuals than Tc females (Figure 1c; see also Table S2 vs S1).

The non-additivity of food competition and reproductive interference impacts theoretical predictions for coexistence

Interaction strength estimated from the aforementioned experiments subsequently served to parameterise a population model that predicted the long-term consequences of both types of interaction. This model is a generalization of a Lotka-Volterra model that describes changes in population abundances over time as a function of species intrinsic growth rates (λ) and the negative linear effects of competition for food (α) and reproductive interference (β) due to the presence of competitors [START_REF] Schreiber | When rarity has costs: coexistence under positive frequency-dependence and environmental stochasticity[END_REF] . Therefore, non-additive effects between competition for food and reproductive interference can only arise from changes in the strength of the estimated parameters (rather than from an interactive term of these two effects within the population model; see Eq. 1).

We found that when acting alone, food competition should promote positive densitydependent effects (denoted as negative niche differences), as each species was more affected by heterospecifics than by conspecifics. This result, combined with the fact that fitness differences between the two species were large enough (both for 3 replicate populations and for all data), should lead to the exclusion of Tc (but note that we also found high variability among replicate populations, suggesting that priority effects are also possible; Figure 3a). We also found that, in absence of food competition, reproductive interference should always generate priority effects, such that the outcome should depend on the combination between the relative 'fecundity differences' between the two species (cf. Eq. S6 in supplementary Box S3) and their initial relative frequency (Figure 3b). However, in our system (i.e., with the parameter values we measured experimentally), we predicted that Tc should be favoured even when rare, as Tu should be excluded not only when both species are initially at equal relative frequency (as in our experimental conditions), but also when it is initially twice as abundant as Tc (predicted for all data and 3 replicate populations; Figure 3b). Thus, food competition and reproductive interference are, overall, predicted to generate rather opposite outcomes when acting in the absence of each other.

Then, to determine how both interactions would jointly affect long-term population dynamics, we performed simulations in which they would have either additive (using parameters estimated from Experiment 1 and 2) or non-additive (using parameters estimated from Experiment 3) effects on species growth rates. In both cases, and as predicted for reproductive interference alone, we found priority effects, as the identity of the species that excludes the other depended on the initial conditions (both initial relative frequency and absolute density in this case; Figure 3c,d). However, when considering that the two interactions had additive effects, reproductive interference should counterbalance the asymmetries in food competition, with the weaker competitor for food (Tc) excluding the stronger competitor (Tu) when the former is initially more abundant (Figure 3c; see Figure S1 and S2 for variation among replicate populations). In contrast, when accounting for the non-additive effects of the two interactions, reproductive interference should have a much lower buffering effect against the effects of food competition. In this case, Tu always excluded Tc, except when extremely rare (Figures 3d; see Figures S1 andS3 for variation among replicate populations).

The model accurately predicts dynamics in cage populations

Finally, to validate our hypothesis that accounting for non-additive effects of food competition and reproductive interference improves the accuracy of model predictions, we performed a large-scale experiment in which we followed, in 5 replicate cage populations, the short-term dynamics of the two species starting at equal initial densities (Experiment 4). We also extended the population model to fit the procedure used in this experiment (cf. Methods and Box S4) and predict the production of sterile hybrid females along with Tu and Tc females. Then, we parameterised the model using estimates obtained either in Experiments 1 and 2 or in Experiment 3, to predict population dynamics with additive or non-additive effects of food competition and reproductive interference, respectively. In the experiment, all replicate populations showed very consistent dynamics, with Tc and hybrids being fully excluded by Tu by the 6 th and 8 th generations, respectively (Figure 4a; Table S3). A similar pattern was also predicted by the model, both when accounting for additive or non-additive effects of food competition and reproductive interference. However, simulated population dynamics considering only additive effects showed extremely large variance, indicating a strong uncertainty concerning which species should exclude the other (Figure S4a). Conversely, predictions showed much lower variance when including non-additive effects instead, with Tu always excluding Tc (Figure S4b). Hence, these results further confirmed the importance of incorporating non-additivity in the model to better predict population dynamics. Still, as compared to experimental observations (Figure 4a), the model predicted lower proportions of hybrids (from generations 2 to 6), and a faster exclusion of Tc. Thus, to improve these predictions, we performed additional simulations in which we varied the sensitivity of hybrid females to food competition, as compared to purebred females, and quantitatively compared observed and predicted data with linear regressions. These analyses revealed that hybrid females should be at least 10 times less sensitive to food competition than purebred ones (Figure 4b; Table S3) to obtain the best fit between observed and predicted dynamics (Figure 4c, Table S4).

Discussion

Our study provides the first empirical evidence that reproductive interference interacts in a non-additive way with food competition, such that their combined effect on population dynamics and competitive outcomes could not be predicted by their independent action. The species that benefitted most from this non-additivity in our system was the superior competitor for food (Tu), which also became the least sensitive to interference.

Why food competition directly affected both the strength and the symmetry of reproductive interference could be explained by a positive correlation between traits involved in each of these interactions, or by the same traits being involved in both interactions [START_REF] Maan | Ecology, sexual selection and speciation[END_REF] . One such trait that could explain our results is body size [START_REF] Okuzaki | Resource partitioning or reproductive isolation: The ecological role of body size differences among closely related species in sympatry[END_REF] . Indeed, because food availability can affect body size in spider mites [START_REF] Li | Does size matter? Fecundity and longevity of spider mites (Tetranychus urticae) in relation to mating and food availability[END_REF] , and Tu individuals were less sensitive than Tc to food competition, the size of Tu individuals might also be less negatively affected by food competition than that of Tc individuals. This, in turn, could reduce the sensitivity of Tu to reproductive interference while increasing that of Tc, because bigger spider mite males are generally superior competitors for mates [START_REF] Potter | Aggression and Mating Success in Male Spider Mites[END_REF][START_REF] Enders | The effect of male size and operational sex ratio on male mating success in the common spider mite, Tetranychus urticae Koch (Acari: Tetranychidae)[END_REF] , and bigger females preferred over smaller ones [START_REF] Zahradnik | Choosy males in a littorinid gastropod: Male Littorina subrotundata prefer large and virgin females[END_REF][START_REF] Edward | The evolution and significance of male mate choice[END_REF] . Another possibility could be that reduced food availability (or quality) leads to slower offspring development in spider mites as in other systems [START_REF] Teng | Development and Survival of Immature Aedes albopictus and Aedes triseriatus (Diptera: Culicidae) in the Laboratory: Effects of Density, Food, and Competition on Response to Temperature[END_REF][START_REF] Wilson | Plant-Quality Effect on Life-History Parameters of the Twospotted Spider Mite (Acari: Tetranychidae) on Cotton[END_REF] , such that under competition for food, males of the superior competitor (Tu) develop faster and secure conspecific mates, before males of the inferior competitor (Tc) became sexually mature. Moreover, although our experiments aimed at revealing whether food competition affected the strength of reproductive interference, non-additive effects may also occur in the opposite direction. For instance, male mating harassment 63 could either decrease or increase the intensity of food competition by inducing changes in female feeding behaviour (e.g., reduced female feeding time to escape males [START_REF] Bancroft | Allocating time between feeding, resting and moving by the two-spotted spider mite, Tetranychus urticae and its predator Phytoseiulus persimilis[END_REF] , or increased spatial aggregation to create refuges from males [START_REF] Yamamichi | Frequency-dependent community dynamics driven by sexual interactions[END_REF] ). Theoretically, such density-dependent phenomenological effect of reproductive interference on the intensity of food competition can cause changes in niche differences, thereby shifting competitive outcomes from coexistence to priority effects, or the reverse [START_REF] Yamamichi | Frequency-dependent community dynamics driven by sexual interactions[END_REF] . However, the long-term consequences of the opposite (i.e., changes in the strength of reproductive interference in response to food competition) had not yet been investigated theoretically.

Our ability to inform population models with such detailed experiments allowed us to predict the long-term consequences of the interaction between food competition and reproductive interference. Following principles from modern coexistence theory, we observed that food competition promoted a combination of reduced niche differences and fitness differences favouring Tu. Thus, predicted ecological outcomes based on the effect of food competition alone showed that Tc should overall be excluded, although in some replicate populations, Tc could exclude Tu when initially present at a higher frequency. Reproductive interference was instead found to promote priority effects [START_REF] Kishi | Analysis of species coexistence co-mediated by resource competition and reproductive interference[END_REF][START_REF] Kyogoku | When does reproductive interference occur? Predictions and data[END_REF] that should favour Tc over Tu. Indeed, we predicted that Tc should exclude Tu except when the latter was initially much more abundant. Our findings are thus in line with several studies reporting reproductive interference as a mechanism of exclusion, whether based on theory [START_REF] Kishi | Analysis of species coexistence co-mediated by resource competition and reproductive interference[END_REF][START_REF] Takafuji | Reproductive interference and its consequences on the competitive interactions between two closely-related Panonychus spider mites[END_REF][START_REF] Kyogoku | Heterospecific mating interactions as an interface between ecology and evolution[END_REF] , or on empirical data for a variety of systems [START_REF] Whitton | Co-occurrence of related asexual, but not sexual, lineages suggests that reproductive interference limits coexistence[END_REF][START_REF] Hochkirch | Sympatry with the devil: Reproductive interference could hamper species coexistence[END_REF][START_REF] Ting | Demographic consequences of reproductive interference in multi-species communities[END_REF][START_REF] Kishi | Reproductive interference determines persistence and exclusion in species interactions[END_REF][START_REF] Takakura | Alien dandelion reduces the seed-set of a native congener through frequency-dependent and one-sided effects[END_REF] . However, although food competition and reproductive interference acting asymmetrically in opposing directions is a condition previously predicted to favour stable coexistence [START_REF] Kishi | Analysis of species coexistence co-mediated by resource competition and reproductive interference[END_REF] , this was not the case in our system.

In this study, we provided the first experiment-based predictions of modern coexistence theory incorporating both food competition and reproductive interference. Our simulated population dynamics revealed that priority effects driven by reproductive interference remained even in the presence of food competition. Hence, reproductive interference is a key determinant of population dynamics in this system, whereas food competition determined which species was dominant by reducing the threshold frequency at which the superior competitor for food (Tu) was able to invade. Moreover, we showed that non-additive effects of the two interactions increased the importance of food competition relative to that of reproductive interference in determining competitive outcomes in this system, as the lower sensitivity of the superior competitor (Tu) to reproductive interference served as a buffer against priority effects. This was evidenced by an even greater reduction of the threshold frequency required for Tu to exclude Tc. The apparent discrepancy between this result and previous theoretical predictions, whereby coexistence should be possible via a trade-off between reproductive interference and food competition [START_REF] Kishi | Analysis of species coexistence co-mediated by resource competition and reproductive interference[END_REF] , lies in the fact that we found negative niche differences in our system, a scenario yet unexplored until very recently. Indeed, recent theoretical work showed that only a shift towards positive niche differences, due to changes in food competition intensity mediated by reproductive interference, could drive coexistence in systems in which niche differences are initially negative [START_REF] Yamamichi | Frequency-dependent community dynamics driven by sexual interactions[END_REF] . Finally, using independent data for model parameterisation and validation, we demonstrated, for the first time, the importance of accounting for non-additive effects between trophic and sexual interactions to accurately predict coexistence outcomes between closelyrelated species. These findings further showed that it is possible to generate very accurate predictions for population dynamics using a simple model that incorporates all possible mechanisms of reproductive interference [START_REF] Burdfield-Steel | Reproductive interference[END_REF][START_REF] Gröning | Reproductive Interference Between Animal Species[END_REF] , without explicitly modelling each individual mechanism (i.e., the concept of 'demographic reproductive interference' [START_REF] Ting | Demographic consequences of reproductive interference in multi-species communities[END_REF] ). Interestingly, we also show that including the ecological impact of hybrids by adjusting their sensitivity to food competition further improved our ability to predict the system's dynamics. Indeed, since hybrid females are mostly sterile in our system [START_REF] Cruz | Wolbachia and host intrinsic reproductive barriers contribute additively to postmating isolation in spider mites[END_REF] , they may require much less resources than purebred females. A direct consequence of this, predicted by our model and observed experimentally, is an increased relative frequency of hybrid females in the populations. This, in turn, may generate cascading density-dependent effects, potentially affecting both reproductive interference and food competition's intensities. Thus, while studies of speciation mainly focus on the ecological impact of hybrids in the context of adaptation [START_REF] Seehausen | Hybridization and adaptive radiation[END_REF][START_REF] Gow | Ecological selection against hybrids in natural populations of sympatric threespine sticklebacks[END_REF] , our results highlight how even hybrids that do not contribute genetically to the following generations may have a significant ecological impact through competitive interactions.

In conclusion, our results highlight that food competition and reproductive interference interact in a non-additive way. Such results, which were overlooked by ecological theory, have significant consequences for understanding the short-term population dynamics of interacting species as well as their long-term competitive outcomes. We believe these non-additive effects are not specific to spider mites, but can rather be a general feature of many other ecological systems, as has recently been proposed [START_REF] Yamamichi | Frequency-dependent community dynamics driven by sexual interactions[END_REF] . In fact, this can be expected in any system where the same (or correlated) traits are involved in both sexual and trophic interactions (cf. above), and even more particularly in systems where the two types of interactions are intertwined, such as in species with sexual cannibalism [START_REF] Fea | Fatal attraction: sexually cannibalistic invaders attract naive native mantids[END_REF] . The potential ubiquity of such non-additive effects should be considered in future work for two main reasons. From a theoretical perspective, it indicates that studies accounting for several types of interactions, such as the combination of trophic and sexual interactions [START_REF] Schreiber | When rarity has costs: coexistence under positive frequency-dependence and environmental stochasticity[END_REF] , or exploitative and apparent competition [START_REF] Chesson | The interaction between predation and competition[END_REF] , must more systematically explore theory beyond assuming simple additive effects [START_REF] Thompson | Species interactions cause non-additive effects of multiple environmental stressors on communities[END_REF] . From an empirical perspective, it highlights the necessity to consider several types of interactions in isolation and together to better understand the magnitude of non-additive effects. In sum, species interactions have been intensively studied for more than a century as a major determinant of species distribution and competitive outcomes. Yet, our results collectively show that we are still in the infancy of understanding how different mechanisms interact to determine the population dynamics of interacting species. Combining theoretical and empirical progress is still needed to obtain a more holistic view of the causes and consequences of species interactions. heterospecific males. This was done over 2 generations to encompass the costs resulting from the production of sterile F1 hybrids (Figure 5b). Third, to quantify the combined effect of food competition and reproductive interference on the growth rate of each species, we assessed their per capita production of daughters when they interacted sexually and shared a common resource over 3 generations (Figure 5c). In all three experiments, controls with no competitors for food (nor heterospecific mates) were also used to estimate the individual growth rate of each species in absence of any interactions.

Theoretical approach for parameter estimations and to predict the outcome of interactions between populations

To estimate key interaction coefficients from data obtained in each of the experiments described above, we adapted a discrete-time population model developed by Schreiber et al [START_REF] Schreiber | When rarity has costs: coexistence under positive frequency-dependence and environmental stochasticity[END_REF] , in which a reproductive interference term was added to the Beverton-Holt function used to predict population dynamics under food competition [START_REF] Godoy | Phenology effects on invasion success: Insights from coupling field experiments to coexistence theory[END_REF] . In this model, the number of individuals of a species i (Ni) is predicted at each generation t, accounting for interactions with individuals of a species j (Nj), with the following equation:

N i, t+1 = N i,t δ λ i • ! 1+α ii (N i,t -1) + α ij N j,t • N i,t N i,t + β ij N j,t (Eq. 1)
In this equation, the leftmost term represents population growth in absence of limiting interactions for species i. The δ, corresponds to the oviposition period in days, and λi is the percapita daily intrinsic growth rate of species i in absence of any type of interactions. The middle term represents the effect of food competition. αii and αij are, respectively, the per capita effects of food competition with N i -1 competitors of species i (we excluded the focal individual here as the quantity of food provided to single individuals in our experiments is not limiting: we assume its growth to be limited only by the presence of competitors), and N j competitors of species j (i.e., intraspecific and interspecific competition, respectively). The rightmost term represents the per capita effect of reproductive interference, where βij is the per capita effect of interspecific sexual interactions with N j individuals of species j on the growth rate of species i.

Detailed procedure used for estimations of parameter values (and their 95% confidence interval) in each of the experiments 1, 2 and 3, is provided in the Supplementary Box S3. Estimated parameter values were then used to compute three different key metrics allowing to infer the impact of food competition and reproductive interference in the long-term: the average fitness differences (k j /k i computed using the λ and α parameters), which refers to the competitive advantage of one species over the other; the niche overlap (ρ computed using the α parameters), which represents the degree to which each species limits its own growth as compared to how it limits the growth of the competitor species 10 ; and the relative strength of reproductive interference (γ computed using the β parameters), which corresponds to the degree to which one species is more sensitive to reproductive interference than the other [START_REF] Schreiber | When rarity has costs: coexistence under positive frequency-dependence and environmental stochasticity[END_REF] . Equations used to compute these key metrics, as well as analytical solutions and numerical analyses used to predict the long-term outcome of interactions between species (when food competition and reproductive interference act alone or simultaneously, respectively), are fully described in the Supplementary Box S3.

Empirical test of model predictions: Dynamics in cage populations

To determine whether our estimated interaction coefficients enable accurate predictions of short-term population dynamics, we performed a larger-scale experiment (Experiment 4) in which we followed the relative frequencies of Tu and Tc female mites, as well as that of hybrid females, in cage populations over eight discrete generations (Figure 6 and detailed procedure in Box S4). We also adapted our mathematical model to fit the procedure used in the population cage experiment (cf. details and equations in Box S4). In short, the model was extended to account for random sampling of the females used to start each new generation, and for the differences between species when populations only compete for food or depending on the relative strength of reproductive interference and fecundity differences when populations only interact during reproduction, respectively. In (A), the two solid black lines define the space in which species can coexist (grey area) or enter alternative stable states (priority effects; white area). Otherwise, the species with higher fitness will exclude the other. In (B), due to priority effects, coexistence is possible if reproductive interference equalises the fecundity differences between populations at equal initial frequency of both species (solid line: NTu/NTc = 1), or if the initial frequency of the inferior competitor is sufficiently high to compensate for the combined effects of its fecundity disadvantage and/or higher sensitivity to reproductive interference (dotted lines from left to right: NTu/NTc = 2/1, 4/3, 3/4, and 1/2). In (A) and (B), grey circles and black diamonds are means (± 95% confidence intervals) for each replicate population and for all data, respectively. Note that negative parameter values and confidence intervals are not displayed. (C) and (D) show predicted outcomes for different initial absolute densities and relative frequencies of the two species, obtained from simulations using parameters estimated with all data (cf. Figure S1 for each replicate population) when both types of competition had additive or non-additive effects, respectively.

In both panels, heat maps show that the identity of the remaining species after 20 generations depends on the initial conditions due to priority effects (see also Figures S2 andS3 for the full population dynamics). Red area: Tc excludes Tu; Blue area: Tu excludes Tc (only for equal initial frequency of the two species in panel B). (C) The combined effect of food competition and reproductive interference were measured across three consecutives generations (G1 to G3) by using common (food and mating) patches for the entire life cycle of the individuals. As females mated with males from their own population were used at the onset of the experiment, the first generation (G0 to G1) allowed re-estimating food competition in absence of reproductive interference (to correct for testing time). The next generations of offspring (G2 to G3) allowed re-estimating reproductive interference in the presence of food competition. Red: Tc females; Blue: Tu females; Purple: hybrid females.

Figure 1 .

 1 Figure 1. Single and combined effects of food competition and reproductive interference on the daily per capita production of daughters by Tetranychus urticae (Tu) and T. cinnabarinus (Tc) populations. In (A), lines represent the average number of females produced under increasing densities of either conspecific or heterospecific competitors (dark and light colours, respectively) on a common food patch, but in absence of reproductive interference. In (B), lines represent the average number of females produced in absence or presence of heterospecific individuals (dark and light colours, respectively) on a common mating patch, in absence of food competition. In (C), violin plots show the distribution of mean number of females produced when individuals competed for the same food and shared their mating patches over 3 generations. In all panels, individual points show the mean number of females produced daily by a single female (per capita) for each of 5 different replicate populations. Red: Tc females; Blue: Tu females.

Figure 2 .

 2 Figure 2. Comparison of parameter values estimated across experiments for both Tetranychus urticae (Tu) and T. cinnabarinus (Tc) populations. (A) Intrinsic growth rate (λ) estimated as the mean number of daughters produced daily by single isolated females, averaged for Experiments 1 and 2, or measured in Experiment 3. (B) Per capita effect of food competition (α) estimated from Experiments 1 and 3. (C) Per capita effect of reproductive interference (β) estimated from Experiments 2 and 3. In all panels, dots show parameter values (± 95% confidence intervals) estimated across 5 replicate populations, dark and light colours represent within-and between-species effects, respectively, and parameter values for Tc and Tu are displayed in red and blue, respectively.

Figure 3 .

 3 Figure 3. Theoretical predictions for the outcome of competition between Tetranychus urticae (Tu) and T. cinnabarinus (Tc) populations. (A) and (B) show predicted outcomes depending on the niche and fitness

29

 29

Figure 4 .

 4 Figure 4. Observed and predicted dynamics of Tetranychus urticae (Tu), T. cinnabarinus (Tc), and of their hybrids, in cage populations over 8 generations. (A) Observed proportions of females in experimental cage populations. Dots show the observed proportions in each replicate population, and coloured lines and shaded areas show the averages and associated 95% confidence intervals across all replicate populations. (B) Predicted proportions of females assuming non-additive effects of food competition and reproductive interference (parameters estimated from Experiment 3), and hybrid females 10 times less affected by food competition than purebred females. Coloured lines and shaded areas show predicted proportions and associated 95% confidence intervals using parameters estimated across all replicate populations. (C) Linear regression between observed and predicted proportions. Dots show each replicate population, the solid line shows the linear regression between observed and predicted proportions, and the dashed line shows the 1:1 relationship between values in the two axes. Blue: Tu females; Red: Tc females; Purple: hybrid females.

Figure 5 .

 5 Figure 5. Experimental procedures used to quantify the effects of food competition and/or reproductive interference on Tetranychus urticae (Tu) and T. cinnabarinus (Tc) offspring production. (A) Food competition in absence of reproductive interference was measured by placing females mated with conspecific males on food patches where their juveniles would develop. The two different types of competition, intraspecific

Figure 6 .

 6 Figure 6. Experimental procedure used to follow the dynamics of Tetranychus urticae (Tu) and T. cinnabarinus (Tc) populations simultaneously interacting through food competition and reproductive interference. Common plants were used for the entire life cycle of individuals of both species. This procedure enabled food competition between females and developing juveniles, as well as reproductive interference between virgin adult individuals of both species. The figure depicts the initial installation of mated females (G0), the transfer of 400 randomly sampled mated females to start each subsequent discrete generation (G1 onward), as well as random sampling and phenotyping of 50 virgin females every two generations. Red: Tc females; Blue: Tu females; Purple: hybrid females.

Acknowledgements

We are grateful to Inês Santos, Cátia Eira and Miguel Cunha for the maintenance of the spider mite populations and Lucie de Sousa for the plants, to André Mira and Alexandra Balola for assistance with data collection, and to Emanuel A. Fronhofer and Jhelam N. Deshpande for useful discussions. This work was funded by an ERC Consolidator Grant (COMPCON, GA asymmetrical production of sterile hybrid females in our system (due to sex-ratio distortion in crosses between Tu females and Tc males 54 ). Then, we compared the proportion of Tu, Tc, and hybrid females observed in the cage populations every two generations, with those predicted under different scenarios: (1) assuming additive vs. non-additive effects of food competition and reproductive interference (by parametrizing the model with estimates from Experiments 1 and 2, or from Experiment 3, respectively; parameter values in Table S1 vs. S2); (2) assuming different sensitivity of the hybrids to food competition by evaluating a range of scale factors of the α parameters in the equation used to predict hybrid production. We then used linear regressions to determine which model parameterization leads to the best fit between predicted and observed dynamics (cf. detailed procedure in Box S4).

MC was funded through an FCT PhD fellowship (SFRH/BD/136454/2018) and IF through a Junior researcher contract (CEECIND/02616/2018). VCS acknowledges financial support provided by FCT (CEECINST/00032/2018/CP1523/CT0008), including national funds to cE3c (UIDB/00329/2021). This is contribution ISEM-2023-XXX of the Institute of Evolutionary Science of Montpellier (ISEM). OG acknowledges financial support provided by the Spanish Ministry of Economy and Competitiveness and by the European Social Fund through a Ramón y Cajal contract (RyC 2017-23666).

Data availability

All datasets and R scripts are available at Zenodo (https://doi.org/10.5281/zenodo.10086125).

Conflict of interest

The authors declare that they have no conflict of interest with the content of this article.

Methods

Spider mite populations

We used one population of T. urticae ('Tu') and one of T. cinnabarinus ('Tc'), for which preand post-zygotic isolation were previously assessed: heterospecific crosses result in fully sterile hybrids (most hybrid females do not lay eggs and the few eggs laid do not hatch [START_REF] Cruz | Wolbachia and host intrinsic reproductive barriers contribute additively to postmating isolation in spider mites[END_REF] ), but males of both colour forms prefer to mate with red females (i.e., red males mate assortatively, while green males mate disassortative; Cruz et al. in prep.). Such incomplete pre-zygotic isolation, coupled with strong post-zygotic isolation, is expected to result in strong reproductive interference when populations of these two species share the same environment [START_REF] Gröning | Reproductive Interference Between Animal Species[END_REF][START_REF] Smith | Spider Mites: Population Suppression by Interspecific Hybridization[END_REF] . Prior to performing experiments, we ensured that both populations were free of endosymbionts, and either fully homozygous for the presence (Tu) or absence (Tc) of a recessive nonsynonymous mutation that can be used to differentiate populations of each species (see detailed procedure in Supplementary Box S1).

Measuring food competition, reproductive interference, and their combined effects

To determine whether food competition and reproductive interference have additive or nonadditive effects on the growth of interacting species, we derived 5 replicate populations from each of the Tu and Tc populations, and performed a set of three different experiments (cf. detailed procedure in Box S2). First, to quantify how food competition affected the growth of both species in absence of reproductive interference, focal females that had already mated with conspecific males were exposed to increasing densities of conspecific and heterospecific competitors [START_REF] Hart | How to quantify competitive ability[END_REF] , and their number of descendants was counted (Figure 5a). Second, to quantify the strength of reproductive interference while restricting competition for food, we counted the number of offspring produced by females isolated on individual food patches after they interacted sexually with only conspecific males (control), or with both conspecific and


Olivier Dézerald

Stanislas Talaga

Céline Leroy

Jean-François Carrias

Bruno Corbara

Alain Dejean

Régis Céréghino
email: regis.cereghino@univ-tlse3.fr

J.-F Carrias

J.-F Carrias

Environmental determinants of macroinvertebrate diversity in small water bodies: insights from tank-bromeliads

Keywords: Freshwater biodiversity, Linear mixed effect modelling, Microcosms, Phytotelmata, Ponds

The interlocking leaves of tank-forming bromeliads (Bromeliaceae) collect rainwater and detritus, thus creating a freshwater habitat for specialized organisms. Their abundance and the possibility of quantifying communities with accuracy give us unparalleled insight into how changes in local to regional environments influence community diversity in small water bodies. W e sampled 365 bromeliads (365 invertebrate communities) along a southeastern to northwestern range in French Guiana. Geographie locality determined the species pool for bromeliad invertebrates, and local environments determined the

Introduction

Ponds are subject to anthropogenic pressure (e.g., agriculture, industry, urbanism, deforestation) even though these ecosystems have obvious ecological functions [START_REF] Hansson | Conflicting demands on wetland ecosystem services: nutrient retention, biodiversity or both?[END_REF] and recognized social and economie uses [START_REF] Chapman | Wetlands of East-Africa: biodiversity, exploitation and policy perspectives[END_REF]. In light of recent economie development, a major challenge is to understand the turnover of pond communities in relation to changes in local-regional environments and pond habitat characteristics [START_REF] Epcn | The pond manifesta[END_REF]. More specifically, our ability to predict the responses of the biota to changes in landscape and aquatic habitat resources will contribute to the success of future conservation actions. Incoming detritus (e.g., leaf litter, an important food resource at the base of the food webs) and light regime (i.e., energy available for photosynthesis) play key roles in shaping community diversity in ponds through nutrient availability [START_REF] Ruggiero | The alternative stable state concept and the management of Apennine mountain ponds[END_REF]. The surrounding land-cover ( <200 rn, [START_REF] Declerck | Ecological characteristics of small farmland ponds: associations with land use practices at multiple spatial scales[END_REF] can therefore exp lain significant variation in pond community diversity, because the extent and nature of perennial vegetation affects allochthonous and autochthonous contributions to the aquatic food webs through direct (nutrient inputs) and indirect (light) effects, ultimatel y changing the communities [START_REF] Céréghino | The ecology of European ponds: defining the characteristics of a neglected freshwater habitat[END_REF]. However, the responses of biological communities to these variables also depend on interactions between environmental changes and intrinsic pond features, such as size [START_REF] Oertli | Does size matter? The relationship between pond area and biodiversity[END_REF] or trophic status [START_REF] Ruggiero | The alternative stable state concept and the management of Apennine mountain ponds[END_REF].

It is challenging to study the effects of environments on entire pond communities, first because different taxonomie groups with high species diversity do not respond equally to environmental changes [START_REF] Oertli | Does size matter? The relationship between pond area and biodiversity[END_REF], and, second, because high population densities and the diversity of pond microhabitats often preclude the accurate quantification of biological diversity [START_REF] Oertli | Conservation and monitoring of pond biodiversity: introduction[END_REF]. To tackle these issues, we focused on small, spatially discrete pools that are highly frequent and naturally span a broad range of environmental gradients. Bromeliaceae are flowering plants represented by 59 genera and sorne 3,140 species native mainly to the Neotropics [START_REF] Givnish | Phylogeny, adaptive radiation, and historical biogeography in Bromeliaceae: insights from an eight-locus plastid phylogeny[END_REF]. The interlocking leaves of tankbromeliads form pools that collect rainwater (from a few millilitres to a few litres), leaf litter and other organic detritus. These pools, or phytotelmata ("plantheld waters"), provide a habitat for aquatic organisms, notably bacteria, algae, fungi, protozoa, zooplankton, macroinvertebrates, and amphibians [START_REF] Kitching | Food Webs and Container Habitats: The Natural History and Ecology of Phytotelmata[END_REF][START_REF] Frank | Insect and allies associated with bromeliads: a review[END_REF]. Because they host simple communities but yet contain multiple trophic levels, bromeliad pools and their aquatic biota have proven to be ideal model systems for studying the rules by which communities are assembled [START_REF] Armbruster | Factors influencing community structure in a South American tank bromeliad fauna[END_REF].

While there bas been increasing interest in the study of habitat and the spatial distribution of invertebrates in ponds and pools [START_REF] Boix | Pond research and management in Europe -small is beautiful[END_REF], most studies have focused on one scale, e.g., a region [START_REF] Trigal | Macroinvertebrate communities of mediterranean ponds (North Iberian Plateau): importance ofnatural and humaninduced variability[END_REF], a network of ponds [START_REF] Angélibert | Dispersal characteristics of three odonate species in a patchy habitat[END_REF], or the sui table micro habitats within a pond (V an de [START_REF] Van De Meutter | The effect of turbidity state and microhabitat on macroinvertebrate assemblages: a pilot study of six shallow lakes[END_REF]. Our study focused on the macroinvertebrate communities inhabiting tank-bromeliads in French Guiana, where the juxtaposition of contrasting environments (i.e., pioneer growths, plantations, savannahs, primary forest) offered us opportunities to analyse patterns of invertebrate diversity at multiple spatial scales. Specifically, we sampled 365 bromeliads (i.e., 365 invertebrate communities) representing a range of food and habitat resources (i.e., amount of detritus and pool size), surrounding vegetation (i.e., open to closed forest environments), and geographie locations (i.e., southeastern to northwestern French Guiana). Assurning that the bromeliads that grow in primary forests consistently receive higher litter inputs and lower incident radiation than bromeliads in more open sites, we predicted that, for a given geographicallocation (or species pool), local environments and bromeliad habitats shape community composition and, more specifically, the proportions of detritivores and predators. To test these assumptions, multivariate ordination was used to interpret changes in the quantitative and qualitative structure of the macroinvertebrate communities in relation to geography. Then, we used linear mixed effect modelling to further examine the effects of small-scale variables on species richness and abundance and on predator:detritivore ratios (both in tenDs of richness and abondance), while controlling the effects of SUIIUunding vegetaûon types ("site") and geography ("locality"). We discuss bromeliad freshwater invertebrate diveJsi.ty and distribution in the context of pond research and conservation in an attempt to dmw the attention of pond ecologists to miniahJte pools tbat effeclively nmror what can be seen in larger systems.

Materials aad methods

Study aoea and bromeliads

This study was conducted in French Guiana, East Amazonia, from March 2006 to October 2011. The climate is tropical moist with 3,000-3,400 mm of yearly precipitation mainly distributed over 280 days. There i.s a major drop in rainfall between September and November and another shorter and more iiTegular dry period in March. The maximum monthly temperature averages 33.5°C (32.1-35.8°C), and the monthly minimum averages 20.3°C (19.7-21 °C).

We selccted five sampling localitics distributed across a south-east to north-west range (Fig. 1) and sampled 365 bromeliad pools in the understorey of primary fo.rests, in pioueer growths, a rock savannah, The main characteristics of the sampling localiti.es, vegetation types (hereafter "sites", within localities) and number of sampled bromeliads are provided in Table 1. The seven bromeliad specics represented here were either epiphytes ( <2 m above ground) or had taken root on the ground.

The percentages of total incident radiation above the bromeliads (IR) were cal.culated using hemispherical photographs and an image processing software (Gap Light Analyzer 2.0) [START_REF] Frazer | Gap Light Analyzer (GLA) 2.0: Imaging Software to Extract Canopy Structure and Gap Light Transmission Indices from True-Colour Fisheye Photographs: Users Manual and Program Documentation[END_REF] ml). In order to prevent the inftuence of seasonality (i.e., dry vs. rainy season) on water volume, we sampled bromeliad tanks that were full of water at the time of sampling. The amount of fine particulate organic matter (FPOM; 1000-0.45 J.1.111 in size, the food resources at the base of the food webs) was expressed as preserved volum.e (ml after decantation into graduated test-tubes; see also [START_REF] Paradise | Relationship of water and leaf litter variability to insects inhabiting treeholes[END_REF]).

Aquatic invertebrate communities

For both ethical (extensive sampling could des troy local populations) and legal reasons (the Nouragues Research Station is located in a nature reserve), we used a non-destructive sampling technique. To sample the water retained in the tanks, we used 5-and 10-ml micropipettes with the end trimmed to widen the orifice. Although less efficient than plant dissection, we and other researchers have already successfully used this technique [START_REF] Céréghino | Ants mediate the structure of phytotelm communities in an antgarden bromeliad[END_REF]Jocqué et al., 2010a). It was consistent! y used for ail of the samples. The samples were preserved in the field in 4% formalin (final concentration). The invertebrates were sorted in the laboratory and preserved in 70% ethanol. They were identified to genus, species or morphospecies and enumerated. Species abundance data were expressed as number of individuals per plant. lnvertebrate taxa were partitioned into predators (carnivorous species which attack and consume living prey organisms) and detritivores (species which sift fine particulates from the water column and/or gather FPOM from the accumulated debris), and these functional groups were used to calculate predator:detritivore richness ratios (PDRR) and predator:detritivore abundance ratios (PDAR). The distribution of invertebrate taxa (and the corresponding functional groups) among sites is given in the supplementary online material.

Data analysis

First, a correspondence analysis (CA; [START_REF] Jongman | Data Analysis in Community and Landscape Ecology[END_REF] was used to ordinate the samples (bromeliads) according to macroinvertebrate morphospecies abundances (after log n + 1 transformation), thus summarizing the variability of the data and providing insights for the elaboration of the subsequent richness and abundance models. The significance of the axes was determined at P < 0.05 by testing the eigenvalues of the inertia matrix. The plots of the first two ordination axes usually capture most of the variance and consequently contain most of the information that is likely to be interpretable [START_REF] Waite | Comparing strength of geographie and nongeographic classifications of stream benthic macroinvertebrates in the Mid-Atlantic Highlands, USA[END_REF]. The bromeliads which were neighbours in the scatterplot were expected to host similar invertebrate communities.

Conversely, the bromeliads that were separated from each other by a large distance were expected to be distant in the feature space based on their macroinvertebrate communities.

To further analyze the relationship between species richness, overall invertebrate abundance, PDAR and PDRR (dependent variables) and environmental variables (independent variables), we used linear mixed effect modelling. "Site" (vegetation types) was nested within 'locality'. In contrast, a given bromeliad species could be sampled in many localities or many sites, therefore the variable "bromeliad species" was not nested within the former or the latter. Since "locality", "site", "site nested within locality" or "bromeliad species" (i.e., various spatial components) could be included as random factors, we conducted a model selection based on the Bayesian Information Criterion (BIC) of the full models (models considering ail environmental variables) for each dependent variable. This procedure allowed us to identify the spatial scale that best accounted for patterns for each dependent variable. Then, for a selected random factor (lowest BIC), the relationships between dependent and independent variables were explored using a stepwise backwards removal procedure and only the final models containing significant variables were presented. We used the glmer function in R software V.2.14.1 (nlme package) to analyse species richness and invertebrate abundance because these dependent variables followed a Poisson distribution. PDAR and PDRR were ranked because they were not normalized by the usual transformations [START_REF] Aulchenko | GenABEL: an R library for genome-wide association analysis[END_REF], and we used the lme function (lme4 package) to analyse these variables. Generalized linear mixed models with species richness and abundance were fit using the Laplace approximation while models with predator-to-prey ratios were fit using restricted maximum likelihood (REML). Based on model residuals, the violation of homogeneity and normality was assessed graphically. All statistical analyses were evaluated under a 95% confidence level.

Results

When a CA was carried out on the invertebrate abundance matrix (Fig. 2), the first two axes contributed 18.6 and 10.4% to the overall variance, respectively. The distribution of invertebrate taxa (Fig. 2b) compared to the grouping of samples by locality (envelopes in Fig. 2a) showed that (i) with the exception of the Nouragues locality, invertebrate taxa found in species-poor localities (e.g., Saint Elie, Kaw) Overall, mean invertebrate abundance was higher in open areas than in the primary forest understorey (see Table 1), while mean taxonomie richness showed little variability (10--14 morphospecies) between sites and localities; for instance, abundance was up to 48-times higher in A. aquilega bromeliads in a rock savannah (242.25 ± 32.15 individuals per plant) compared to G. lingulata in a nearby primary forest (5.1 ± 1.2 ind. planC 1 ). Invertebrate abundance was also higher in pioneer growths and plantations (37 ± 5.17 to 76.47 ± 10.63 ind. planC 1 ) than in the primary forest (up to 25 ± 6.03 ind. planC 1 ).

The lowest BIC values were obtained with "locality" as the random factor for the species richness model (138.92; Table 2), and with "site" a random factor for the abundance, PDRR and PDAR models (14238.47, 1002.05, and 980.64, respectively; Table 2). Whatever the geographicallocality, the number of taxa per pool increased with water volume (P < 0.0001; Table 3).

Other variables were not significantly correlated with taxonomie richness in a given locality. At the scale of "site", there was a negative correlation between invertebrate abundance and the ratios IR:WV and WV:FPOM (P < 0.0001; Table 3). For a fixed water volume, the number of individuals per pool thus decreased with increasing incident radiation and amounts of FPOM. There was also a positive correlation between abundance and the ratio IR:FPOM (P < 0.0001), so that, for a given light environment, invertebrate abundance increased with increasing amounts of FPOM. In terms of taxonomie richness, the predator to detritivore ratio (PDRR) had a mean value (±SE) of0.38 ± 0.01. In terms of abundance, the predator to detritivore ratio (PDAR) had a mean value of 0.27 ± 0.01. Both PDRR and PDAR increased with increasing water volume (P = 0.004 and P = 0.002, respectively) and decreased with increasing incident radiation (P = 0.001 in both cases). Moreover, both models showed a positive and significant interaction between incident radiation and amounts of FPOM (P = 0.03 for the two models; Table 3).

Discussion

Not surprisingly, in our study there was a trend for invertebrate communities from different localities to exhibit differences in taxonomie composition and species abundance, a common pattern in freshwater invertebrate communities. Nevertheless, it is worth noting that patterns of taxonomie richness and overall invertebrate abundance mostly emerged from patterns of predator species occurrence and abundance across local/regional environments, while a set of generalist species remained relatively constant at lower trophic levels ("detritivores" sensu lata). Future research could therefore examine whether the composition of the biological traits of pond detritivores is independent of geography (on a regional scale) de spi te a spatial turnover in the taxonomie composition. If generalist detritivores share biological traits that determine sensitivity to disturbance (e.g., resistance to desiccation, dispersal ability), then larger changes in community diversity could be expected under future regional development scenarios.

The model selection based on BICs for taxonomie richness and invertebrate abundance suggested that geographical locality determined the potential species richness for bromeliad pools, then local conditions (sites) determined species abundance patterns through the selection of traits that are best adapted to the bromeliad habitats. In general, ponds and pools tend to show positive species-area relationships (e.g., [START_REF] Ruggiero | Farm ponds make a contribution to the biodiversity of aquatic insects in a French agricultural landscape[END_REF] with larger habitats being more easily colonized by immigrants [START_REF] Drakare | The imprint of the geographical, evolutionary and ecological context on species-area relationships[END_REF]. W e also noted that, regardless of locality or site, water volume (habitat size) had a strong correlation with both invertebrate richness and abundance, making it a biologically relevant measure of the pools' carrying capacity. There was, however, a trend for pools with higher radiation incidence to accumulate more water (WV to IR ratio, r = 0.32, P < 0.05, log-transformed data) certainly because in open areas there are fewer overhanging trees to keep most or ail of the rain from reaching the bromeliads. Hence, even for a given bromeliad species and/or bromeliad size, the containers hold more water at sun-exposed sites. In any case, larger pools hosted more species, and richer pools contained higher proportions of large-bodied predators (e.g., Coenagrionidae damselfties, Tabanidae and Tox- orhynchites dipterans). In addition to their intrinsic value for biodiversity (e.g., damselfiies), predators satisfy the criterion of "more easily surveyed taxa" because they are mostly represented by large organisms. They are easier to observe and, thus, more difficult to overlook. Surrogacy, or how easily surveyed taxa do well at representing other taxa, is a critical question in pond conservation planning [START_REF] Oertli | Conservation and monitoring of pond biodiversity: introduction[END_REF]. However, [START_REF] Heino | Searching for biodiversity indicators in running waters: do bryophytes, macroinvertebrates, and fish show congruent diversity patterns?[END_REF] demonstrated that congruence in species richness among freshwater taxa is generally low, mainly because of their di:ffering responses to major environmental gradients. Our results therefore suggest a functional (rather than taxonomie) approach to surrogacy for small water bodies where the diversity of predators could be an efficient surrogate for the assessment of the broadest communities they belong to. Our models did show that the predator to detritivore ratio (both in terms of richness and abundance) is positively correlated with water volume, thus suggesting that predators largely account for patterns in overall diversity. As a first approximation, the number of predator taxa indeed shows linear relationships with the overall number of taxa (Pearson's r = 0.75). Hence, further analyses could test the relationship between the species richness of predators and the overall invertebrate species richness in ponds and pools. Detritus in the form of leaf litter is a main source of energy in tank-bromeliad ecosystems [START_REF] Benzing | Bromeliaceae: Profile of an Adaptive Radiation[END_REF]. Debris-chewing invertebrates process incoming litter. Small particles of organic matter, including faeces, then collect in the plant pools and are further processed in the gut of invertebrate collectors and filterers [START_REF] Kitching | Food Webs and Container Habitats: The Natural History and Ecology of Phytotelmata[END_REF]. In a review of leaf traits and decomposition, Hattenschwiler et al. (20 11) reported that tree species native to French Guiana share traits that provide an exceptionally poor decomposer substrate. Citrus grandis (Saint Elie and Angoulème plantations) has an Asiatic origin, but the waxy coating of its leaves, and not its origin, probably accounts for its poor quality as a decomposer substrate. Therefore, leaf species origin probably has little or marginal effect on invertebrate community patterns. However, while the bromeliads in plantations and in the rock savannah had only one leaf species (Citrus grandis trees and Clusia minor shrubs, respectively), overhanging trees in pioneer growths (Vismia spp. Clusiaceae; Miconia sp. and Bellucia sp. Melastomataceae) and primary forests (mostly species from the Caesalpiniaceae family, namely Eperua spp., Vouacapoua americana, Dicorynia guianensis, and Hymenaea sp. and also species from the Burseraceae, Meliaceae, and Sapotaceae families) contributed a higher number of leaf species to individual bromeliads. Although this aspect should be tested in bromeliads pools, it has been demonstrated that leaf species mixtures decompose slightly faster than single leaf species in freshwater, a pattern determined by the responses of detritivores to resource heterogeneity [START_REF] Sanpera-Calbet | Leaf diversity influences in-stream litter decomposition through effects on shredders[END_REF]. Nevertheless, whilst bromeliads in primary forests consistently had more diverse leaf species and higher litter inputs than bromeliads in other sites, the amount of FPOM inside bromeliad pools from primary forests was not necessarily higher than those from more open areas (see, e.g., Aechmea aquilega and A. mertensii in a rock savannah and a plantation, respectively; Table 1). However, FPOM concentrations (the FPOM to WV ratios) show that bromeliads in primary forests had higher concentrations (0.011-0.018 ml FPOM/ml WV) than bromeliads in open areas (0.047--0.088 ml FPOM/ml WV). This indicates that particle concentration rather than amount sensu stricto affects species abundance. Hence, the ratio WV:FPOM negatively correlated with invertebrate abundance at a given site (fewer individuals at a higher particulate concentration for a fixed water volume), and invertebrate abundance was the lowest at forested sites (higher FPOM concentrations). FPOM concentration is related to the extent of open water in small pools. Higher FPOM concentration could therefore decrease the amount of available space in tank-bromeliads to the detriment of open-water swimmers (culicid larvae are typically less abundant in FPOM-rich pools). The amount of FPOM is seen as a relevant indicator of available resources at the lower end of the food chain in plant-held waters [START_REF] Frank | Bromeliad phytotelmata and their biota, especially mosquitoes[END_REF][START_REF] Céréghino | Ants mediate the structure of phytotelm communities in an antgarden bromeliad[END_REF], and nutrient rich habitats are expected to sustain more species than nutrient-poor habitats [START_REF] Paradise | Relationship of water and leaf litter variability to insects inhabiting treeholes[END_REF]. Hence, our results suggest that the relationship between FPOM and community diversity in small pools is not exclusively generated through trophic effects, but also through the physical quality of the habitats.

Throughout the world, ponds and pools come in ali shapes and sizes. Ecologists have a long history of documenting freshwater organisms from even the smallest pools like bromeliads [START_REF] Picado | Les broméliacées épiphytes comme milieu biologique[END_REF], tree hales [START_REF] Kitching | Spatial and temporal variation in food webs in water-filled treeholes[END_REF] and rockpools (Jacqué et al., 2010b) to the largest shallow lakes [START_REF] Batzer | Ecology of insect communities in nontidal wetlands[END_REF]. However, natural microcosms have on1y recently been exploited as "shortcuts" to highlighting ecological patterns in nature [START_REF] Srivastava | Are natural microcosms useful model systems for ecology?[END_REF][START_REF] Brendonck | Pools 'on the rocks' : freshwater rock pools as model system in ecological and evolutionary research[END_REF]. The success of current and forthcoming pond action plans will be measured in terms of biodiversity and/or the status of target species of conservation interest. A related problem is the lack of understanding of the potential colonisation of rehabilitated systems by "desired" species and/or assemblages. Previous studies suggested that insect predators play an important role in small water bodies with rapid community development and strong abiotic constraints [START_REF] Magnusson | Top-down control by insect predators in an intermittent pond -a field experiment[END_REF]. The significant effects of water volume, fine detritus (amount and concentration), light environment, and certainly predation (this study) show that local-scale factors play a crucial role in shaping community structure, and, more importantly, that changes in local environments (e.g., the conversion of forest to cropping systems, pioneer growths along forest roads) strongly influence freshwater communities. Moreover, because local environments do not equally impact the abundance and richness patterns of detritivores and predators, one may expect functional shifts ( e.g., nutrient dynamics in bottom-up vs. top-down controls) as sets of invertebrate species with particular traits are either replaced or complemented by other sets with different traits when shifting from forest under stories to anthropogenically-disturbed, open areas.

Fig. 1

 1 Fig. 1 Distribution of sampling localities (Nouragues. Kaw, Petit Saut. Angoulème. Saint Elie) across a south-eastern to nordt-westem range in Fmu:h Guiana

plantationCB:

  Catopsis berteroniana; AA: Aechmea aquilega; VP: Vriesea pleiosticha; AB: Aechmea bromeliifolia; VS: Vriesea splendens; GL: Guzmania lingulata; AM: Aechmea mertensii; N number of plants sampled; IR incident radiation (% ); WV water volume extracted (ml); FPOM fine particulate organic matter (ml after decantation in test-tubes); Taxa number of taxa per plant. /nd number of individuals per plant. Values are means ± standard errors were mostly subsets of the taxa found in richer localities (e.g., Angoulème, Petit Saut), (ii) a small set of detritivores (e.g., Culex spp., Wyeomyia spp., Cyphon sp1, Telmatoscopus sp1, Limoninae, Forcypomyia sp1, Aulophorus superterrenus) remained fairly common across localities and sites, and (iii) localities with larger species pools (i.e., Petit Saut, Nouragues, Saint Elie) had additional detritivores (e.g., Tanytarsus sp., Telmatoscopus sp2, Anopheles sp., Orthocladinae, Elpidium sp., Aeolosoma), but notably included predators (e.g., Toxorhynchites pur- pureus, Microvelia spp., Tabanidae, Coenagrionidae) in the bromeliad communities.

Fig. 2

 2 Fig. 2 Correspondence analysis (CA) of invertebrate taxa and bromeliads (axes 1 and 2). Distribution of: a bromeliads according to geographical locations, and b taxa on the first two axes of the CA

  , as described in[START_REF] Leroy | Ants mediate foliar structure and nitrogen acquisition in a tankbromeliad[END_REF]. To characterize habitat size, we emptied the wells in each plant by sucking the water out (see invertebrate sampling) and recorded the corresponding volume of water (WV,

Table 1

 1 Main characteristics of the sampling sites and plants sampled (seven bromeliad species)

	Locality	Site	Bromeliad N IR	wv	FPOM	Taxa	Ind
	Nouragues Rock	CB	29	73.3 ± 2.4	40.62 ± 3.75	0.74 ± 0.08 10.55 ± 0.15 32.96 ± 3.83
		savannah
			AA	31 66.97 ± 2.73 949.23 ± 102.64 10.84 ± 1.26 14.87 ± 0.42 242.25 ± 32.15
		Transition	VP	30 25.12 ± 0.29	73.2 ± 9.11	1.7 ± 0.28 10.3 ± 0.35	9.4 ± 1.85
		forest
			AB	26 25.69 ± 0.47 137.85 ± 21.1	1.08 ± 0.25 11.23 ± 0.32	16.5 ± 2.76
		Primary forest vs	26 18.75 ± 0.4	48.54 ± 5.03	4.29 ± 0.42 10.35 ± 0.25 11.11 ± 1.55
		Primary forest GL	19	15.9 ± 0.6	17.46 ± 2.53	1.04 ± 0.16 10.21 ± 0.29	5.1 ± 1.2
	Petit Saut	Pioneer	AM	63 39.33 ± 2.63 84.38 ± 10.1	6.16 ± 1.26 12.49 ± 0.28 76.47 ± 10.63
		growth
		Primary forest vs	34 16.64 ± 0.38 26.18 ± 3.84	3.46 ± 0.71 10.68 ± 0.23	25 ± 6.03
	Kaw	Pioneer	AM	45	35.1 ± 2.98 92.46 ± 11.82	4.3 ± 0.68 11.78 ± 0.28 71.88 ± 11.56
		growth
	Angoulème Citrus	AM	35 33.03 ± 2.95 31.01 ± 4.54	2.32 ± 0.31	11.8 ± 0.34 75.68 ± 30.71
		plantation
	Saint Elie	Citrus	AM	27 32.07 ± 1.3	56.41 ± 8.29	4.58 ± 0.86 14.22 ± 0.36	37 ± 5.17

Table 2

 2

	Models	Random effects
		Site	Locality	Locality/ Bromeliad
				site	species
	Richness	143.57	138.92a	144.82	145.00
	Abundance 14238.47a 16810.9	14244.28 15591.84
	PDRR	1002.05a	1002.6	1007.04	1005.41
	PDAR	980.64a	984.77	984.44	995.35
	a Lowest BIC values

BICs of the full models with species richness, overall invertebrate abundance, predator:detritivore richness ratio (PDRR), and predator:detritivore abundance ratio (PDAR) as dependent variables and four random effects: site, locality, the site nested within the locality (locality/site), and the bromeliad species

Table 3

 3 Models assessing the influence of environmental variables and their interactions on the overall species richness, overall invertebrate abundance, predator:detritivore richness ratio (PDRR), and predator:detritivore abundance ratio (PDAR) WV water volume, FPOM fine particulate organic matter

	Fixed effect	Estimate ± SE	DF	z	p	Random effect
	Richness					Locality
	Intercept	2.043 ± 0.067	359	30.334	<0.0001
	Slope
	wv	0.116 ± 0.013	359	9.117	<0.0001
	Abundance					Site
	Intercept	1.119 ± 0.35	350	3.198	0.0014
	Slope
	IR	-0.243 ± 0.05	350	-4.817	<0.0001
	wv	0.859 ± 0.04	350	17.18	<0.0001
	FPOM	0.522 ± 0.066	350	7.957	<0.0001
	IR:WV	-0.061 ± 0.012	350	-4.961	<0.0001
	IR:FPOM	0.142 ± 0.018	350	7.700	<0.0001
	WV:FPOM	-0.141 ± 0.007	350	-19.412	<0.0001
	PDRR					Site
	lntercept	1.067 ± 0.644	352	1.655	0.099
	Slope
	IR	-0.495 ± 0.168	352	-2.947	0.003
	wv	0.161 ± 0.055	352	2.908	0.004
	FPOM	-0.835 ± 0.386	352	-2.163	0.031
	IR:FPOM	0.242 ± 0.108	352	2.231	0.026
	PDAR					Site
	Intercept	1.233 ± 0.656	352	1.879	0.061
	Slope
	IR	-0.542 ± 0.167	352	-3.239	0.001
	wv	0.173 ± 0.054	352	3.174	0.002
	FPOM	-0.831 ± 0.375	352	-2.215	0.027
	IR:FPOM	0.231 ± 0.105	352	2.201	0.028
	Only significant variables are presented in the table (SE = standard error)

IR incident radiation,

Acknowledgments

We are grateful to the Nouragues Field Station of the French Centre National de la Recherche Scientifique (CNRS) and to the lAboratoire Environnement de Petit Saut (HYDRECO) for their logistical help. This study bas benefited from an "Investissement d'A venir" grant managed by Agence Nationale de la Recherche (CEBA, ref. ANR-10-LABX-0025). Andrea Yockey-Dejean proofread the English text, and two anonymous reviewers made relevant comments on an earlier version of this paper.