Inferring the extinction risk of marine fish to inform global conservation priorities.

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 aesthetic value of reef fishes is globally mismatched to their conservation priorities.

Reef fishes are closely connected to many human populations, yet their contributions to society are mostly considered through their economic and ecological values. Cultural and intrinsic values of reef fishes to the public can be critical drivers of conservation investment and success, but remain challenging to quantify. Aesthetic value represents one of the most immediate and direct means by which human societies engage with biodiversity, and can be evaluated from species to ecosystems. Here, we provide the aesthetic value of 2,417 ray-finned reef fish species by combining intensive evaluation of photographs of fishes by humans with predicted values from machine learning. We identified important biases in species' aesthetic value relating to evolutionary history, ecological traits, and International Union for Conservation of Nature (IUCN) threat status. The most beautiful fishes are tightly packed into small parts of both the phylogenetic tree and the ecological trait space. In contrast, the less attractive fishes are the most ecologically and evolutionary distinct species and those recognized as threatened. Our study highlights likely important mismatches between potential public support for conservation and the species most in need of this support. It also provides a pathway for scaling-up our understanding of what are both an important nonmaterial facet of biodiversity and a key component of nature's contribution to people, which could help better anticipate consequences of species loss and assist in developing appropriate communication strategies.

The ecological causes of functional distinctiveness in communities.

Recent work has shown that evaluating functional trait distinctiveness, the average trait distance of a species to other species in a community offers promising insights into biodiversity dynamics and ecosystem functioning. However, the ecological mechanisms underlying the emergence and persistence of functionally distinct species are poorly understood. Here, we address the issue by considering a heterogeneous fitness landscape whereby functional dimensions encompass peaks representing trait combinations yielding positive population growth rates in a community. We identify four ecological cases contributing to the emergence and persistence of functionally distinct species. First, environmental heterogeneity or alternative phenotypic designs can drive positive population growth of functionally distinct species. Second, sink populations with negative population growth can deviate from local fitness peaks and be functionally distinct. Third, species found at the margin of the fitness landscape can persist but be functionally distinct. Fourth, biotic interactions (positive or negative) can dynamically alter the fitness landscape. We offer examples of these four cases and guidelines to distinguish between them. In addition to these deterministic processes, we explore how stochastic dispersal limitation can yield functional distinctiveness. Our framework offers a novel perspective on the relationship between fitness landscape heterogeneity and the functional composition of ecological assemblages.

Plant community impact on productivity: Trait diversity or key(stone) species effects?

Outside controlled experimental plots, the impact of community attributes on primary productivity has rarely been compared to that of individual species. Here, we identified plant species of high importance for productivity (key species) in >29,000 diverse grassland communities in the European Alps, and compared their effects with those of community-level measures of functional composition (weighted means, variances, skewness and kurtosis). After accounting for the environment, the five most important key species jointly explained more deviance of productivity than any measure of functional composition alone. Key species were generally tall with high specific leaf areas. By dividing the observations according to distinct habitats, the explanatory power of key species and functional composition increased and key-species plant types and functional composition-productivity relationships varied systematically, presumably because of changing interactions and trade-offs between traits. Our results advocate for a careful consideration of species' individual effects on ecosystem functioning in complement to community-level measures.

Functionally distinct tree species support long-term productivity in extreme environments.

Despite evidence of a positive effect of functional diversity on ecosystem productivity, the importance of functionally distinct species (i.e. species that display an original combination of traits) is poorly understood. To investigate how distinct species affect ecosystem productivity, we used a forest-gap model to simulate realistic temperate forest successions along an environmental gradient and measured ecosystem productivity at the end of the successional trajectories. We performed 10 560 simulations with different sets and numbers of species, bearing either distinct or indistinct functional traits, and compared them to random assemblages, to mimic the consequences of a regional loss of species. Long-term ecosystem productivity dropped when distinct species were lost first from the regional pool of species, under the harshest environmental conditions. On the contrary, productivity was more dependent on ordinary species in milder environments. Our findings show that species functional distinctiveness, integrating multiple trait dimensions, can capture species-specific effects on ecosystem productivity. In a context of an environmentally changing world, they highlight the need to investigate the role of distinct species in sustaining ecosystem processes, particularly in extreme environmental conditions.

Niche breadth affects bacterial transcription patterns along a salinity gradient.

Understanding the molecular mechanisms that determine a species' life history is important for predicting their susceptibility to environmental change. While specialist species with a narrow niche breadth (NB) maximize their fitness in their optimum habitat, generalists with broad NB adapt to multiple environments. The main objective of this study was to identify general transcriptional patterns that would distinguish bacterial strains characterized by contrasted NBs along a salinity gradient. More specifically, we hypothesized that genes encoding fitness-related traits, such as biomass production, have a higher degree of transcriptional regulation in specialists than in generalists, because the fitness of specialists is more variable under environmental change. By contrast, we expected that generalists would exhibit enhanced transcriptional regulation of genes encoding traits that protect them against cellular damage. To test these hypotheses, we assessed the transcriptional regulation of fitness-related and adaptation-related genes of 11 bacterial strains in relation to their NB and stress exposure under changing salinity conditions. The results suggested that transcriptional regulation levels of fitness- and adaptation-related genes correlated with the NB and/or the stress exposure of the inspected strains. We further identified a shortlist of candidate stress marker genes that could be used in future studies to monitor the susceptibility of bacterial populations or communities to environmental changes.

Leveraging social media and deep learning to detect rare megafauna in video surveys.

Deep learning has become a key tool for the automated monitoring of animal populations with video surveys. However, obtaining large numbers of images to train such models is a major challenge for rare and elusive species because field video surveys provide few sightings. We designed a method that takes advantage of videos accumulated on social media for training deep-learning models to detect rare megafauna species in the field. We trained convolutional neural networks (CNNs) with social media images and tested them on images collected from field surveys. We applied our method to aerial video surveys of dugongs (Dugong dugon) in New Caledonia (southwestern Pacific). CNNs trained with 1303 social media images yielded 25% false positives and 38% false negatives when tested on independent field video surveys. Incorporating a small number of images from New Caledonia (equivalent to 12% of social media images) in the training data set resulted in a nearly 50% decrease in false negatives. Our results highlight how and the extent to which images collected on social media can offer a solid basis for training deep-learning models for rare megafauna detection and that the incorporation of a few images from the study site further boosts detection accuracy. Our method provides a new generation of deep-learning models that can be used to rapidly and accurately process field video surveys for the monitoring of rare megafauna.

El aprendizaje profundo se ha convertido en una importante herramienta para el monitoreo automatizado de las poblaciones animales con video-censos. Sin embargo, la obtención de cantidades abundantes de imágenes para preparar dichos modelos es un reto primordial para las especies elusivas e infrecuentes porque los video-censos de campo proporcionan pocos avistamientos. Diseñamos un método que aprovecha los videos acumulados en las redes sociales para preparar a los modelos de aprendizaje profundo para detectar especies infrecuentes de megafauna en el campo. Preparamos algunas redes neurales convolucionales con imágenes tomadas de las redes sociales y las pusimos a prueba con imágenes tomadas en los censos de campo. Aplicamos nuestro método a los censos aéreos en video de dugongos (Dugong dugon) en Nueva Caledonia (Pacífico sudoccidental). Las redes neurales convolucionales preparadas con 1,303 imágenes de las redes sociales produjeron 25% de falsos positivos y 38% de falsos negativos cuando las probamos en video-censos de campo independientes. La incorporación de un número pequeño de imágenes tomadas en Nueva Caledonia (equivalente al 12% de las imágenes de las redes sociales) dentro del conjunto de datos usados en la preparación dio como resultado una disminución de casi el 50% en los falsos negativos. Nuestros resultados destacan cómo y a qué grado las imágenes recolectadas en las redes sociales pueden ofrecer una base sólida para la preparación de modelos de aprendizaje profundo para la detección de megafauna infrecuente. También resaltan que la incorporación de unas cuantas imágenes del sitio de estudio aumenta mucho más la certeza de detección. Nuestro método proporciona una nueva generación de modelos de aprendizaje profundo que pueden usarse para procesar rápida y acertadamente los video-censos de campo para el monitoreo de megafauna infrecuente.

The dimensionality and structure of species trait spaces.

Trait-based ecology aims to understand the processes that generate the overarching diversity of organismal traits and their influence on ecosystem functioning. Achieving this goal requires simplifying this complexity in synthetic axes defining a trait space and to cluster species based on their traits while identifying those with unique combinations of traits. However, so far, we know little about the dimensionality, the robustness to trait omission and the structure of these trait spaces. Here, we propose a unified framework and a synthesis across 30 trait datasets representing a broad variety of taxa, ecosystems and spatial scales to show that a common trade-off between trait space quality and operationality appears between three and six dimensions. The robustness to trait omission is generally low but highly variable among datasets. We also highlight invariant scaling relationships, whatever organismal complexity, between the number of clusters, the number of species in the dominant cluster and the number of unique species with total species richness. When species richness increases, the number of unique species saturates, whereas species tend to disproportionately pack in the richest cluster. Based on these results, we propose some rules of thumb to build species trait spaces and estimate subsequent functional diversity indices.

How community adaptation affects biodiversity-ecosystem functioning relationships.

Evidence is growing that evolutionary dynamics can impact biodiversity-ecosystem functioning (BEF) relationships. However the nature of such impacts remains poorly understood. Here we use a modelling approach to compare random communities, with no trait evolutionary fine-tuning, and co-adapted communities, where traits have co-evolved, in terms of emerging biodiversity-productivity, biodiversity-stability and biodiversity-invasion relationships. Community adaptation impacted most BEF relationships, sometimes inverting the slope of the relationship compared to random communities. Biodiversity-productivity relationships were generally less positive among co-adapted communities, with reduced contribution of sampling effects. The effect of community-adaptation, though modest regarding invasion resistance, was striking regarding invasion tolerance: co-adapted communities could remain very tolerant to invasions even at high diversity. BEF relationships are thus contingent on the history of ecosystems and their degree of community adaptation. Short-term experiments and observations following recent changes may not be safely extrapolated into the future, once eco-evolutionary feedbacks have taken place.

Species diversity and composition drive the aesthetic value of coral reef fish assemblages.

Cultural and recreational values of biodiversity are considered as important dimensions of nature's contribution to people. Among these values, the aesthetics can be of major importance as the appreciation of beauty is one of the simplest forms of human emotional response. Using an online survey, we disentangled the effects of different facets of biodiversity on aesthetic preferences of coral reef fish assemblages that are among the most emblematic assemblages on Earth. While we found a positive saturating effect of species' richness on human preference, we found a net negative effect of species abundance, no effect of species functional diversity and contrasting effects of species composition depending on species' attractiveness. Our results suggest that the biodiversity-human interest relationship is more complex than has been previously stated. By integrating several scales of organization, our study is a step forward in better evaluating the aesthetic value of biodiversity.

Integrating the aesthetic value of landscapes and biological diversity.

As a cultural ecosystem service, the aesthetic value of landscapes contributes to human well-being, but studies linking biodiversity and ecosystem services generally do not account for this particular service. Therefore, congruence between the aesthetic perception of landscapes, ecological value and biodiversity remains poorly understood. Here, we describe the conceptual background, current methodologies and future challenges of assessing landscape aesthetics and its relationship with biodiversity. We highlight the methodological gaps between the assessment of landscape aesthetics, ecological diversity and functioning. We discuss the challenges associated with connecting landscape aesthetics with ecological value, and the scaling issues in the assessment of human aesthetics perception. To better integrate aesthetic value and ecological components of biodiversity, we propose to combine the study of aesthetics and the understanding of ecological function at both the species and landscape levels. Given the urgent need to engage society in conservation efforts, this approach, based on the combination of the aesthetic experience and the recognition of ecological functioning by the general public, will help change our culture of nature and promote ecologically oriented conservation policies.

Experimental niche evolution alters the strength of the diversity­productivity relationship.

The relationship between biodiversity and ecosystem functioning (BEF) has become a cornerstone of community and ecosystem ecology and an essential criterion for making decisions in conservation biology and policy planning. It has recently been proposed that evolutionary history should influence the BEF relationship because it determines species traits and, thus, species' ability to exploit resources. Here we test this hypothesis by combining experimental evolution with a BEF experiment. We isolated 20 bacterial strains from a marine environment and evolved each to be generalists or specialists. We then tested the effect of evolutionary history on the strength of the BEF relationship with assemblages of 1 to 20 species constructed from the specialists, generalists and ancestors. Assemblages of generalists were more productive on average because of their superior ability to exploit the environmental heterogeneity. The slope of the BEF relationship was, however, stronger for the specialist assemblages because of enhanced niche complementarity. These results show how the BEF relationship depends critically on the legacy of past evolutionary events.

Size evolution in microorganisms masks trade-offs predicted by the growth rate hypothesis.

Adaptation to local resource availability depends on responses in growth rate and nutrient acquisition. The growth rate hypothesis (GRH) suggests that growing fast should impair competitive abilities for phosphorus and nitrogen due to high demand for biosynthesis. However, in microorganisms, size influences both growth and uptake rates, which may mask trade-offs and instead generate a positive relationship between these traits (size hypothesis, SH). Here, we evolved a gradient of maximum growth rate (µmax) from a single bacterium ancestor to test the relationship among µmax, competitive ability for nutrients and cell size, while controlling for evolutionary history. We found a strong positive correlation between µmax and competitive ability for phosphorus, associated with a trade-off between µmax and cell size: strains selected for high µmax were smaller and better competitors for phosphorus. Our results strongly support the SH, while the trade-offs expected under GRH were not apparent. Beyond plasticity, unicellular populations can respond rapidly to selection pressure through joint evolution of their size and maximum growth rate. Our study stresses that physiological links between these traits tightly shape the evolution of competitive strategies.

Rare species support vulnerable functions in high-diversity ecosystems.

Around the world, the human-induced collapses of populations and species have triggered a sixth mass extinction crisis, with rare species often being the first to disappear. Although the role of species diversity in the maintenance of ecosystem processes has been widely investigated, the role of rare species remains controversial. A critical issue is whether common species insure against the loss of functions supported by rare species. This issue is even more critical in species-rich ecosystems where high functional redundancy among species is likely and where it is thus often assumed that ecosystem functioning is buffered against species loss. Here, using extensive datasets of species occurrences and functional traits from three highly diverse ecosystems (846 coral reef fishes, 2,979 alpine plants, and 662 tropical trees), we demonstrate that the most distinct combinations of traits are supported predominantly by rare species both in terms of local abundance and regional occupancy. Moreover, species that have low functional redundancy and are likely to support the most vulnerable functions, with no other species carrying similar combinations of traits, are rarer than expected by chance in all three ecosystems. For instance, 63% and 98% of fish species that are likely to support highly vulnerable functions in coral reef ecosystems are locally and regionally rare, respectively. For alpine plants, 32% and 89% of such species are locally and regionally rare, respectively. Remarkably, 47% of fish species and 55% of tropical tree species that are likely to support highly vulnerable functions have only one individual per sample on average. Our results emphasize the importance of rare species conservation, even in highly diverse ecosystems, which are thought to exhibit high functional redundancy. Rare species offer more than aesthetic, cultural, or taxonomic diversity value; they disproportionately increase the potential breadth of functions provided by ecosystems across spatial scales. As such, they are likely to insure against future uncertainty arising from climate change and the ever-increasing anthropogenic pressures on ecosystems. Our results call for a more detailed understanding of the role of rarity and functional vulnerability in ecosystem functioning.

Predicting biotic interactions and their variability in a changing environment.

Global environmental change is altering the patterns of biodiversity worldwide. Observation and theory suggest that species' distributions and abundances depend on a suite of processes, notably abiotic filtering and biotic interactions, both of which are constrained by species' phylogenetic history. Models predicting species distribution have historically mostly considered abiotic filtering and are only starting to integrate biotic interaction. However, using information on present interactions to forecast the future of biodiversity supposes that biotic interactions will not change when species are confronted with new environments. Using bacterial microcosms, we illustrate how biotic interactions can vary along an environmental gradient and how this variability can depend on the phylogenetic distance between interacting species.

Metacommunity speciation models and their implications for diversification theory.

The emergence of new frameworks combining evolutionary and ecological dynamics in communities opens new perspectives on the study of speciation. By acknowledging the relative contribution of local and regional dynamics in shaping the complexity of ecological communities, metacommunity theory sheds a new light on the mechanisms underlying the emergence of species. Three integrative frameworks have been proposed, involving neutral dynamics, niche theory, and life history trade-offs respectively. Here, we review these frameworks of metacommunity theory to emphasise that: (1) studies on speciation and community ecology have converged towards similar general principles by acknowledging the central role of dispersal in metacommunities dynamics, (2) considering the conditions of emergence and maintenance of new species in communities has given rise to new models of speciation embedded in the metacommunity theory, (3) studies of diversification have shifted from relating phylogenetic patterns to landscapes spatial and ecological characteristics towards integrative approaches that explicitly consider speciation in a mechanistic ecological framework. We highlight several challenges, in particular the need for a better integration of the eco-evolutionary consequences of dispersal and the need to increase our understanding on the relative rates of evolutionary and ecological changes in communities.

Islands as model systems in ecology and evolution: prospects fifty years after MacArthur-Wilson.

The study of islands as model systems has played an important role in the development of evolutionary and ecological theory. The 50th anniversary of MacArthur and Wilson's (December 1963) article, 'An equilibrium theory of insular zoogeography', was a recent milestone for this theme. Since 1963, island systems have provided new insights into the formation of ecological communities. Here, building on such developments, we highlight prospects for research on islands to improve our understanding of the ecology and evolution of communities in general. Throughout, we emphasise how attributes of islands combine to provide unusual research opportunities, the implications of which stretch far beyond islands. Molecular tools and increasing data acquisition now permit re-assessment of some fundamental issues that interested MacArthur and Wilson. These include the formation of ecological networks, species abundance distributions, and the contribution of evolution to community assembly. We also extend our prospects to other fields of ecology and evolution - understanding ecosystem functioning, speciation and diversification - frequently employing assets of oceanic islands in inferring the geographic area within which evolution has occurred, and potential barriers to gene flow. Although island-based theory is continually being enriched, incorporating non-equilibrium dynamics is identified as a major challenge for the future.

The paradox of enrichment in metaecosystems.

The paradox of enrichment has been studied almost exclusively within communities or metacommunities, without explicit nutrient dynamics. Yet local recycling of materials from enriched ecosystems may affect the stability of connected ecosystems. Here we study the effect of nutrient, detritus, producer, and consumer spatial flows-combined with changes in regional enrichment-on the stability of a metaecosystem model. We considered both spatially homogeneous and heterogeneous enrichment. We found that nutrient and detritus spatial flows are destabilizing, whereas producer or consumer spatial flows are either neutral or stabilizing. We noticed that detritus spatial flows have only a weak impact on stability. Our study reveals that heterogeneity no longer stabilizes well-connected systems when accounting for explicit representation of nutrient dynamics. We also found that intermediate consumer diffusion could lead to multiple equilibria in strongly enriched metaecosystems. Stability can emerge from a top-down control allowing the storage of materials into inorganic form, a mechanism never documented before. In conclusion, local enrichment can be stabilized if spatial flows are strong enough to efficiently redistribute the local excess of enrichment to unfertile ecosystems. However, high regional enrichment can be dampened only by intermediate consumer diffusion rates.

Asynchrony of taxonomic, functional and phylogenetic diversity in birds.

AIM: We assessed the temporal trends of taxonomic, functional and phylogenetic diversities in the French avifauna over the last two decades. Additionally, we investigated whether and how this multifaceted approach to biodiversity dynamics can reveal an increasing similarity of local assemblages in terms of species, traits and/or lineages. LOCATION: France. METHODS: We analysed a large-scale dataset that recorded annual changes in the abundance of 116 breeding birds in France between 1989 and 2012. We decomposed and analysed the spatio-temporal dynamics of taxonomic, phylogenetic and functional diversities and each of their α-, ß- and γ-components. We also calculated the trend in the mean specialization of bird communities to track the relative success of specialist versus generalist species within communities during the same period. RESULTS: We found large variation within and among the temporal trends of each biodiversity facet. On average, we found a marked increase in species and phylogenetic diversity over the period considered, but no particular trend was found for functional diversity. Conversely, changes in ß-diversities for the three facets were characterized by independent and nonlinear trends. We also found a general increase in the local occurrence and abundance of generalist species within local communities. MAIN CONCLUSIONS: These results highlight a relative asynchrony of the different biodiversity facets occurring at large spatial scales. We show why a multifaceted approach to biodiversity dynamics is needed to better describe and understand changes in community composition in macroecology and conservation biogeography.

Multifaceted diversity-area relationships reveal global hotspots of mammalian species, trait and lineage diversity.

AIM: To define biome-scale hotspots of phylogenetic and functional mammalian biodiversity (PD and FD, respectively) and compare them to 'classical' hotspots based on species richness (SR) only. LOCATION: Global. METHODS: SR, PD & FD were computed for 782 terrestrial ecoregions using distribution ranges of 4616 mammalian species. We used a set of comprehensive diversity indices unified by a recent framework that incorporates the species relative coverage in each ecoregion. We build large-scale multifaceted diversity-area relationships to rank ecoregions according to their levels of biodiversity while accounting for the effect of area on each diversity facet. Finally we defined hotspots as the top-ranked ecoregions. RESULTS: While ignoring species relative coverage led to a relative good congruence between biome top ranked SR, PD and FD hotspots, ecoregions harboring a rich and abundantly represented evolutionary history and functional diversity did not match with top ranked ecoregions defined by species richness. More importantly PD and FD hotspots showed important spatial mismatches. We also found that FD and PD generally reached their maximum values faster than species richness as a function of area. MAIN CONCLUSIONS: The fact that PD/FD reach faster their maximal value than SR may suggest that the two former facets might be less vulnerable to habitat loss than the latter. While this point is expected, it is the first time that it is quantified at global scale and should have important consequences in conservation. Incorporating species relative coverage into the delineation of multifaceted hotspots of diversity lead to weak congruence between SR, PD and FD hotspots. This means that maximizing species number may fail at preserving those nodes (in the phylogenetic or functional tree) that are relatively abundant in the ecoregion. As a consequence it may be of prime importance to adopt a multifaceted biodiversity perspective to inform conservation strategies at global scale.