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Islands have been used as model systems to study ecological and evolutionary processes, and they provide an ideal set-up for validating new biodiversity monitoring methods. The application of environmental DNA metabarcoding for monitoring marine biodiversity requires an understanding of the spatial scale of the eDNA signal, which is best tested in island systems. Here, we investigated the variation in Actinopterygii and Elasmobranchii species composition recovered from eDNA metabarcoding along a gradient of distance-to-reef in four of the five French Scattered Islands in the Western Indian Ocean. We collected surface water samples at an increasing distance from reefs (0 m, 250 m, 500 m, 750 m). We used a metabarcoding protocol based on the 'teleo' primers to target marine reef fishes and classified taxa according to their habitat types (benthic or pelagic). We investigated the effect of distance-to-reef on β diversity variation using generalised linear mixed models and estimated species-specific distance-to-reef effects using a model-based approach for community data. Environmental DNA metabarcoding analyses recovered distinct fish species compositions across the four inventoried islands and variations along the distance-to-reef gradient. The analysis of β - diversity variation showed significant taxa turnover between the eDNA samples on and away from the reefs. In agreement with a spatially localised signal from eDNA, benthic species were distributed closer to the reef than pelagic ones. Our findings demonstrate that the combination of eDNA inventories and spatial modelling can provide insights into species habitat preferences related to distance-to-reef gradients at a small scale. As such, eDNA can not only recover large compositional differences among islands but also help understand habitat selection and distribution of marine species at a finer spatial scale., Competing Interests: The authors declare there are no conflicts of interests., (© 2024 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

Quantifying fish species diversity in rich tropical marine environments remains challenging. Environmental DNA (eDNA) metabarcoding is a promising tool to face this challenge through the filtering, amplification, and sequencing of DNA traces from water samples. However, because eDNA concentration is low in marine environments, the reliability of eDNA to detect species diversity can be limited. Using an eDNA metabarcoding approach to identify fish Molecular Taxonomic Units (MOTUs) with a single 12S marker, we aimed to assess how the number of sampling replicates and filtered water volume affect biodiversity estimates. We used a paired sampling design of 30 L per replicate on 68 reef transects from 8 sites in 3 tropical regions. We quantified local and regional sampling variability by comparing MOTU richness, compositional turnover, and compositional nestedness. We found strong turnover of MOTUs between replicated pairs of samples undertaken in the same location, time, and conditions. Paired samples contained non-overlapping assemblages rather than subsets of one another. As a result, non-saturated localized diversity accumulation curves suggest that even 6 replicates (180 L) in the same location can underestimate local diversity (for an area <1 km). However, sampling regional diversity using ~25 replicates in variable locations (often covering 10 s of km) often saturated biodiversity accumulation curves. Our results demonstrate variability of diversity estimates possibly arising from heterogeneous distribution of eDNA in seawater, highly skewed frequencies of eDNA traces per MOTU, in addition to variability in eDNA processing. This high compositional variability has consequences for using eDNA to monitor temporal and spatial biodiversity changes in local assemblages. Avoiding false-negative detections in future biomonitoring efforts requires increasing replicates or sampled water volume to better inform management of marine biodiversity using eDNA., Competing Interests: None declared., (© 2021 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

Monitoring large marine mammals is challenging due to their low abundances in general, an ability to move over large distances and wide geographical range sizes.The distribution of the pygmy ( Kogia breviceps ) and dwarf ( Kogia sima ) sperm whales is informed by relatively rare sightings, which does not permit accurate estimates of their distribution ranges. Hence, their conservation status has long remained Data Deficient (DD) in the Red list of the International Union for Conservation of Nature (IUCN), which prevent appropriate conservation measures.Environmental DNA (eDNA) metabarcoding uses DNA traces left by organisms in their environments to detect the presence of targeted taxon, and is here proved to be useful to increase our knowledge on the distribution of rare but emblematic megafauna.Retrieving eDNA from filtered surface water provides the first detection of the Dwarf sperm whale ( Kogia sima ) around the remote Malpelo island (Colombia).Environmental DNA collected during oceanic missions can generate better knowledge on rare but emblematic animals even in regions that are generally well sampled for other taxa., Competing Interests: The authors declare no competing interest., (© 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

Livestock farmers rely on a high and stable grassland productivity for fodder production to sustain their livelihoods. Future drought events related to climate change, however, threaten grassland functionality in many regions across the globe. The introduction of sustainable grassland management could buffer these negative effects. According to the biodiversity-productivity hypothesis, productivity positively associates with local biodiversity. The biodiversity-insurance hypothesis states that higher biodiversity enhances the temporal stability of productivity. To date, these hypotheses have mostly been tested through experimental studies under restricted environmental conditions, hereby neglecting climatic variations at a landscape-scale. Here, we provide a landscape-scale assessment of the contribution of species richness, functional composition, temperature, and precipitation on grassland productivity. We found that the variation in grassland productivity during the growing season was best explained by functional trait composition. The community mean of plant preference for nutrients explained 24.8% of the variation in productivity and the community mean of specific leaf area explained 18.6%, while species richness explained only 2.4%. Temperature and precipitation explained an additional 22.1% of the variation in productivity. Our results indicate that functional trait composition is an important predictor of landscape-scale grassland productivity., Competing Interests: The authors declare no competing interests., (© 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

Coral reefs and their associated fauna are largely impacted by ongoing climate change. Unravelling species responses to past climatic variations might provide clues on the consequence of ongoing changes. Here, we tested the relationship between changes in sea surface temperature and sea levels during the Quaternary and present-day distributions of coral reef fish species. We investigated whether species-specific responses are associated with life-history traits. We collected a database of coral reef fish distribution together with life-history traits for the Indo-Pacific Ocean. We ran species distribution models (SDMs) on 3,725 tropical reef fish species using contemporary environmental factors together with a variable describing isolation from stable coral reef areas during the Quaternary. We quantified the variance explained independently by isolation from stable areas in the SDMs and related it to a set of species traits including body size and mobility. The variance purely explained by isolation from stable coral reef areas on the distribution of extant coral reef fish species largely varied across species. We observed a triangular relationship between the contribution of isolation from stable areas in the SDMs and body size. Species, whose distribution is more associated with historical changes, occurred predominantly in the Indo-Australian archipelago, where the mean size of fish assemblages is the lowest. Our results suggest that the legacy of habitat changes of the Quaternary is still detectable in the extant distribution of many fish species, especially those with small body size and the most sedentary. Because they were the least able to colonize distant habitats in the past, fish species with smaller body size might have the most pronounced lags in tracking ongoing climate change.

The trend of closely related taxa to retain similar environmental preferences mediated by inherited traits suggests that several patterns observed at the community scale originate from longer evolutionary processes. While the effects of phylogenetic relatedness have been previously studied within a single genus or family, lineage-specific effects on the ecological processes governing community assembly have rarely been studied for entire communities or flora. Here, we measured how community phylogenetic structure varies across a wide elevation gradient for plant lineages represented by 35 families, using a co-occurrence index and net relatedness index (NRI). We propose a framework that analyses each lineage separately and reveals the trend of ecological assembly at tree nodes. We found prevailing phylogenetic clustering for more ancient nodes and overdispersion in more recent tree nodes. Closely related species may thus rapidly evolve new environmental tolerances to radiate into distinct communities, while older lineages likely retain inherent environmental tolerances to occupy communities in similar environments, either through efficient dispersal mechanisms or the exclusion of older lineages with more divergent environmental tolerances. Our study illustrates the importance of disentangling the patterns of community assembly among lineages to better interpret the ecological role of traits. It also sheds light on studies reporting absence of phylogenetic signal, and opens new perspectives on the analysis of niche and trait conservatism across lineages.

The ability to model biodiversity patterns is of prime importance in this era of severe environmental crisis. Species assemblage along environmental gradients is subject to the interplay of biotic interactions in complement to abiotic filtering and stochastic forces. Accounting for complex biotic interactions for a wide array of species remains so far challenging. Here, we propose using food web models that can infer the potential interaction links between species as a constraint in species distribution models. Using a plant-herbivore (butterfly) interaction dataset, we demonstrate that this combined approach is able to improve species distribution and community forecasts. The trophic interaction network between butterfly larvae and host plant was phylogenetically structured and driven by host plant nitrogen content allowing forecasting the food web model to unknown interactions links. This combined approach is very useful in rendering models of more generalist species that have multiple potential interaction links, where gap in the literature may occur. Our combined approach points toward a promising direction for modeling the spatial variation in entire species interaction networks.

Environmental gradients have been postulated to generate patterns of diversity and diet specialization, in which more stable environments, such as tropical regions, should promote higher diversity and specialization. Using field sampling and phylogenetic analyses of butterfly fauna over an entire alpine region, we show that butterfly specialization (measured as the mean phylogenetic distance between utilized host plants) decreases at higher elevations, alongside a decreasing gradient of plant diversity. Consistent with current hypotheses on the relationship between biodiversity and the strength of species interactions, we experimentally show that a higher level of generalization at high elevations is associated with lower levels of plant resistance: across 16 pairs of plant species, low-elevation plants were more resistant vis-à-vis their congeneric alpine relatives. Thus, the links between diversity, herbivore diet specialization, and plant resistance along an elevation gradient suggest a causal relationship analogous to that hypothesized along latitudinal gradients.