Sébastien Villéger’s research while affiliated with French National Centre for Scientific Research and other places

Anthropogenic activities are eroding biodiversity and its contributions to nature and people worldwide. Yet, the dual imperative to protect nature and sustain human well-being raises potential trade-offs that remain to be quantified. Using standardized fish surveys across 1,237 tropical reefs worldwide, we converted the presence and abundance data of 1,024 species into 29 fish community contributions that primarily benefit either nature or people. We show that “Nature-for-Nature” contributions are mostly positively correlated to total fish biomass, while “Nature-for-People” contributions are more independent. Trade-offs among contributions are not the rule, with some tropical fish communities simultaneously providing high levels of different contributions. High mean contributions have been found in all tropical oceans, so sustaining healthy tropical reefs while promoting human well-being seems achievable within most countries, rather than mutually exclusive. Our framework offers an opportunity to explore different management strategies and pathways on tropical reefs between the use and sparing of nature, towards more favorable and sustainable ecological and social futures.

While extinction risk categorization is fundamental for building robust conservation planning for marine fishes, empirical data on occurrence and vulnerability to disturbances are still lacking for most marine teleost fish species, preventing the assessment of their International Union for the Conservation of Nature (IUCN) status. In this article, we predicted the IUCN status of marine fishes based on two machine learning algorithms, trained with available species occurrences, biological traits, taxonomy, and human uses. We found that extinction risk for marine fish species is higher than initially estimated by the IUCN, increasing from 2.5% to 12.7%. Species predicted as Threatened were mainly characterized by a small geographic range, a relatively large body size, and a low growth rate. Hotspots of predicted Threatened species peaked mainly in the South China Sea, the Philippine Sea, the Celebes Sea, the west coast Australia and North America. We also explored the consequences of including these predicted species’ IUCN status in the prioritization of marine protected areas through conservation planning. We found a marked increase in prioritization ranks for subpolar and polar regions despite their low species richness. We suggest to integrate multifactorial ensemble learning to assess species extinction risk and offer a more complete view of endangered taxonomic groups to ultimately reach global conservation targets like the extending coverage of protected areas where species are the most vulnerable.

The influential concept of the rare biosphere in microbial ecology has underscored the importance of taxa occurring at low abundances yet potentially playing key roles in communities and ecosystems. Here, we refocus the concept of rare biosphere through a functional trait-based lens and provide a framework to characterize microbial functional rarity, a combination of numerical scarcity across space or time and trait distinctiveness. We demonstrate how this novel interpretation of the rare biosphere, rooted in microbial functions, can enhance our mechanistic understanding of microbial community structure. It also sheds light on functionally distinct microbes, directing conservation efforts towards taxa harboring rare yet ecologically crucial functions.

While many ecology studies require estimations of species abundance, doing so for mobile animals in an accurate, non‐invasive manner remains a challenge. One popular stopgap method involves the use of remote video‐based surveys using several cameras, but abundance estimates derived from this method are computed with conservative metrics (e.g., maxN computed as the maximum number of individuals seen simultaneously on a single video). We propose a novel methodological framework based on a remote‐camera network characterized by known positions and non‐overlapping field‐of‐views. This approach involves a temporal synchronization of videos and a maximal speed estimate for studied species. Such a design allows computing a new abundance metric called Synchronized maxN ( SmaxN ). We provide a proof‐of‐concept of this approach with a network of nine remote underwater cameras that recorded fish for three periods of 1 h on a fringing reef in Mayotte (Western Indian Ocean). We found that abundance estimation with SmaxN yielded up to four times higher values than maxN among the six fish species studied. SmaxN performed better with an increasing number of cameras or longer recordings. We also found that using a network of synchronized cameras for a short time period performed better than using a few cameras for a long duration. The SmaxN algorithm can be applied to many video‐based approaches. We built an open‐sourced R package to encourage its use by ecologists and managers using video‐based censuses, as well as to allow for replicability with SmaxN metric.

Coastal ecosystems of the Mediterranean Sea are among the richest in non‐indigenous species, mostly due to the establishment of species coming from the Red Sea through the Suez Canal. Two herbivorous rabbitfishes, Siganus rivulatus and Siganus luridus , are already invasive in the south‐eastern part of the Mediterranean Sea where they cause ecological damage by overgrazing algae. The early detection and the counting of these non‐indigenous species in the rest of the Mediterranean Sea is thus a major challenge for scientists and ecosystem managers. However, analysing images from divers or remote cameras is a demanding task. Here, a dataset of 31,285 images of Siganus spp. and of six common native fishes to the Mediterranean Sea was built from 40 underwater videos recorded at three reef habitats. A deep learning algorithm was then trained to identify Siganus spp. on images containing the eight Mediterranean species. Finally, the algorithm and a post‐processing filtering were tested with an independent dataset of 2024 images. The model had a recall of 0.92 for the Siganus genus (i.e., two Siganus species combined). After a confidence‐based post‐processing, the recall increased to 0.98 with only 4 out of 272 images of Siganus spp. being misclassified. Accuracy reached a score of 0.61 meaning that experts would have to discard false positives. Images of five native species not present in the training dataset yielded similar false positive rates than species present in the training dataset. Overall, the automatic processing of images by the model and then the checking of putative Siganus images by experts required up to five times less effort than a full processing by experts. The algorithm can help to efficiently detect these two invasive fishes in underwater images to evaluate progress towards conservation objectives and accelerate citizen‐based monitoring of coastal ecosystems.

Global environmental change drives diversity loss and shifts in community structure. A key challenge is to better understand the impacts on ecosystem function and to connect species and trait diversity of assemblages with ecosystem properties that are in turn linked to ecosystem functioning. Here we quantify shifts in species composition and trait diversity associated with ocean acidification (OA) by using field measurements at marine CO 2 vent systems spanning four reef habitats across different depths in a temperate coastal ecosystem. We find that both species and trait diversity decreased, and that ecosystem properties (understood as the interplay between species , traits, and ecosystem function) shifted with acidification. Furthermore, shifts in trait categories such as autotrophs, filter feeders, herbivores, and habitat-forming species were habitat-specific, indicating that OA may produce divergent responses across habitats and depths. Combined, these findings reveal the importance of connecting species and trait diversity of marine benthic habitats with key ecosystem properties to anticipate the impacts of global environmental change. Our results also generate new insights on the predicted general and habitat-specific ecological consequences of OA.

The establishment of protected areas to face global diversity declines has mainly prioritized taxonomic diversity, leaving aside phylogenetic and functional diversities, which determine ecosystem functioning and resilience. Furthermore, the assessment of protected areas' effectiveness is mainly done using short‐duration surveys (<2 h), which may undermine the detection of rare species. Through a long‐duration video approach, reef fish taxonomic, phylogenetic and functional facets of diversity were assessed for 3 days within a fully protected area and a nearby poorly protected area in Mayotte Island (Western Indian Ocean). We found that temporally rare species contributed to more than 60% of the taxonomic facet and 85% of the functional facet of biodiversity found on each site. Those rare species, which harbour the most distinct trait values, also make reef fish diversity particularly vulnerable to their loss. Taxonomic, phylogenetic and functional richness were similar between the fully protected area and the poorly protected area, while the species, lineage and trait compositions were markedly different. These results pinpoint the importance of considering taxonomic, functional and phylogenetic dissimilarities while assessing protected areas' effectiveness, instead of using only richness. In addition, benefits of the fully protected area were detected only using more than 15 h of video survey, which emphasizes the importance of long‐duration remote approaches to capture the within‐ and between‐day temporal variations.

Feeding activities by fishes are among the key ecological processes that sustain coral reef functioning. Those trophic-based processes are known to vary across space and across seasons or years. However, there is still little knowledge about their variability within and between days as well as whether these processes are dominated by the same species across time. Using remote underwater cameras, we quantified rates of three feeding activities (corallivory, herbivory and invertivory) for three one-hour time slots (morning, midday, afternoon) over two days on two coral reefs around Mayotte Island (Western Indian Ocean). Feeding activities were highly variable at within and between-day scales and concentrated in a few pulses. Herbivory was the highest in the afternoon which aligns with previous findings regarding activity of herbivorous fishes. Corallivory was the highest in the morning, which highlights the advantage of long-duration benthic remote underwater videos to accurately assess all trophic activities. Trophic-related processes were dominated by the same few species in both sites and across time of the day. This study pinpoints the importance of including within-day and between-day variations when studying ecological processes, as neglecting these variations may introduce biases into our understanding of these processes.