Explore the vast range of titles available.

Ecological interactions uphold ecosystem structure and functioning. However, as species richness increases, the number of possible interactions rises exponentially. More than 6,000 species of coral reef fishes exist across the world’s tropical oceans, resulting in an almost innumerable array of possible trophic interactions. Distilling general patterns in these interactions across different bioregions stands to improve our understanding of the processes that govern coral reef functioning. Here, we show that across bioregions, tropical coral reef food webs exhibit a remarkable congruence in their trophic interactions. Specifically, by compiling and investigating the structure of six coral reef food webs across distinct bioregions, we show that when accounting for consumer size and resource availability, these food webs share more trophic interactions than expected by chance. In addition, coral reef food webs are dominated by dietary specialists, which makes trophic pathways vulnerable to biodiversity loss. Prey partitioning among these specialists is geographically consistent, and this pattern intensifies when weak interactions are disregarded. Our results suggest that energy flows through coral reef communities along broadly comparable trophic pathways. Yet, these critical pathways are maintained by species with narrow, specialized diets, which threatens the existence of coral reef functioning in the face of biodiversity loss.

Understanding species’ roles in food webs requires an accurate assessment of their trophic niche. However, it is challenging to delineate potential trophic interactions across an ecosystem, and a paucity of empirical information often leads to inconsistent definitions of trophic guilds based on expert opinion, especially when applied to hyperdiverse ecosystems. Using coral reef fishes as a model group, we show that experts disagree on the assignment of broad trophic guilds for more than 20% of species, which hampers comparability across studies. Here, we propose a quantitative, unbiased, and reproducible approach to define trophic guilds and apply recent advances in machine learning to predict probabilities of pairwise trophic interactions with high accuracy. We synthesize data from community-wide gut content analyses of tropical coral reef fishes worldwide, resulting in diet information from 13,961 individuals belonging to 615 reef fish. We then use network analysis to identify 8 trophic guilds and Bayesian phylogenetic modeling to show that trophic guilds can be predicted based on phylogeny and maximum body size. Finally, we use machine learning to test whether pairwise trophic interactions can be predicted with accuracy. Our models achieved a misclassification error of less than 5%, indicating that our approach results in a quantitative and reproducible trophic categorization scheme, as well as high-resolution probabilities of trophic interactions. By applying our framework to the most diverse vertebrate consumer group, we show that it can be applied to other organismal groups to advance reproducibility in trait-based ecology. Our work thus provides a viable approach to account for the complexity of predator–prey interactions in highly diverse ecosystems.

The persistence of reef-building corals is threatened by macroalgal competitors leading to a major demographic bottleneck in coral recruitment. Whether parental effects exist under coral–algal competition and whether they influence offspring performance via microbiome alterations represent major gaps in our understanding of the mechanisms by which macroalgae may hinder coral recovery. We investigated the diversity, variability and composition of the microbiome of adults and larvae of the coral Pocillopora acuta and surrounding benthic substrate on algal-removed and algal-dominated bommies. We then assessed the relative influence of parental and offspring environmental effects on coral recruitment processes by reciprocally exposing coral larvae from two parental origins (algal-removed and algal-dominated bommies) to algal-removed and algal-dominated environmental conditions. Dense macroalgal assemblages impacted the microbiome composition of coral larvae. Larvae produced by parents from algal-dominated bommies were depleted in putative beneficial bacteria and enriched in opportunistic taxa. These larvae had a significantly lower survival compared to larvae from algal-removed bommies regardless of environmental conditions. In contrast, algal-induced parental and offspring environmental effects interacted to reduce the survival of coral recruits. Together our results demonstrate negative algal-induced parental and offspring environmental effects on coral recruitment that could be mediated by alterations in the offspring microbiome.

Over the past decades, human impacts have changed the structure of tropical benthic reef communities towards coral depletion and macroalgal proliferation. However, how these changes have modified chemical and microbial waterscapes is poorly known. Here, we assessed how the experimental removal of macroalgal assemblages influences the chemical and microbial composition of two reef boundary layers, the benthic and the momentum. Chemical and microbial waterscapes were spatially structured, both horizontally and vertically, according to macroalgal dominance and boundary layers. Microbes associated with reef degradation were enriched in the boundary layers surrounding macroalgal-dominated substrata. Dominant macroalgae were surrounded by a distinct chemical pool of diverse lipid classes (e.g., diterpenoids and glycerolipids) and labile organic matter (e.g., organooxygen compounds), which diffused from algal tissues to boundary layers according to their polarity. Finally, our results highlighted strong co-variations between specific algal-derived metabolites and planktonic microbes, giving insight into their roles in coral reef functioning and resilience. A field study demonstrates that macroalgae generate complex chemical and microbial waterscapes, which could play essential roles in the function and resilience of coral reefs

L'accumulation des pertubations environnementales a profondément altéré les communautés benthiques des récifs coralliens, où les macroalgues remplacent souvent les coraux. Ces changements de phase sont favorisés par une compétition intense des algues, limitant la récupération des communautés coralliennes. Si, lors de contacts directs, les molécules allopathiques et les microbes des algues peuvent provoquer la mortalité des coraux, leurs diffusions et leurs impacts au-delà de l'espace physique occupé par les algues demeurent encore largement méconnus. Cette thèse a eu pour objectif de répondre à deux questions majeures: comment les macroalgues modifient les paysages chimiques et microbiens et en quoi ces modifications altèrent la santé de l'holobionte corallien et son recrutement ? En manipulant la présence/absence de macroalgues, cette thèse a permis de mettre en évidence une structuration spatiale à fine échelle des microbes et métabolites selon l'abondance de macroalgues et les couches de diffusion (i.e., couches benthique et momentum). Les eaux autour des algues étaient enrichies en bactéries opportunistes, potentiellement pathogènes, et molécules toxiques (i.e., diterpènes). Ces recherches ont ensuite montré que l'exposition aux macroalgues pouvait altérer le microbiome des larves coralliennes (Pocillopora acuta) et impacter négativement la survie des larves et recrues, au travers d'effets parentaux et environnementaux. L'influence relative des effets par contact vs. médiés par l'eau (i.e., 2 cm) sur l'holobiont corallien a été testée en utilisant l'algue allélopathique Dictyota bartayresiana. Chaque type d'interaction a perturbé distinctement le microbiome et métabolome corallien suggérant un ajustement du métabolisme lipidique pour répondre au coût énergétique de la compétition et à la production de métabolites de défense. En combinant métabarcoding et métabolomique non ciblée, ce travail de thèse a permis de décrire l'identité et la distribution des microbes et métabolites associés à la compétition corail-algues afin de mieux comprendre la conséquence des changements de phase sur la résilience des récifs coralliens.

The diversity of life on our planet has produced a remarkable variety of biological traits that characterize different species. Such traits are widely employed instead of taxonomy to increase our understanding of biodiversity and ecosystem functioning. However, for species’ trophic niches, one of the most critical aspects of organismal ecology, a paucity of empirical information has led to inconsistent definitions of trophic guilds based on expert opinion. Using coral reef fishes as a model, we show that experts often disagree on the assignment of trophic guilds for the same species. Even when broad categories are assigned, 60% of the evaluated trait schemes disagree on the attribution of trophic categories for at least 20% of the species. This disagreement greatly hampers comparability across studies. Here, we introduce a quantitative, unbiased, and fully reproducible framework to define species’ trophic guilds based on empirical data. First, we synthesize data from community-wide visual gut content analysis of tropical coral reef fishes, resulting in trophic information from 13,961 individuals belonging to 615 reef fish species across all ocean basins. We then use network analysis to cluster the resulting global bipartite food web into distinct trophic guilds, resulting in eight trophic guilds, and employ a Bayesian phylogenetic model to predict trophic guilds based on phylogeny and maximum body size. Our model achieved a misclassification error of 5%, indicating that our approach results in a quantitative and reproducible trophic categorization scheme, which can be updated as new information becomes available. Although our case study is for reef fishes, the most diverse vertebrate consumer group, our approach can be applied to other organismal groups to advance reproducibility in trait-based ecology. As such, our work provides an empirical and conceptual advancement for trait-based ecology and a viable approach to monitor ecosystem functioning in our changing world.