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Although we are currently experiencing worldwide biodiversity loss, local species richness does not always decline under anthropogenic pressure. This conservation paradox may also apply in protected areas but has not yet received conclusive evidence in marine ecosystems. Here, we survey fish assemblages in six Mediterranean no-take reserves and their adjacent fishing grounds using environmental DNA (eDNA) while controlling for environmental conditions. We detect less fish species in marine reserves than in nearby fished areas. The paradoxical gradient in species richness is accompanied by a marked change in fish species composition under different managements. This dissimilarity is mainly driven by species that are often overlooked by classical visual surveys but detected with eDNA: cryptobenthic, pelagic, and rare fishes. These results do not negate the importance of reserves in protecting biodiversity but shed new light on how under-represented species groups can positively react to fishing pressure and how conservation efforts can shape regional biodiversity patterns.

Background Adaptive genomics may help predicting how a species will respond to future environmental changes. Genomic signatures of local adaptation in marine organisms are often driven by environmental selective agents impacting the physiology of organisms. With one of the highest salinity level, the Mediterranean Sea provides an excellent model to investigate adaptive genomic divergence underlying salinity adaptation. In the present study, we combined six genome scan methods to detect potential genomic signal of selection in the striped red mullet ( Mullus surmuletus ) populations distributed across a wide salinity gradient. We then blasted these outlier sequences on published fish genomic resources in order to identify relevant potential candidate genes for salinity adaptation in this species. Results Altogether, the six genome scan methods found 173 outliers out of 1153 SNPs. Using a blast approach, we discovered four candidate SNPs belonging to three genes potentially implicated in adaptation of M. surmuletus to salinity. The allele frequency at one of these SNPs significantly increases with salinity independently from the effect of longitude. The gene associated to this SNP, SOCS2 , encodes for an inhibitor of cytokine and has previously been shown to be expressed under osmotic pressure in other marine organisms. Additionally, our results showed that genome scan methods not correcting for spatial structure can still be an efficient strategy to detect potential footprints of selection, when the spatial and environmental variation are confounded, and then, correcting for spatial structure in a second step represents a conservative method. Conclusion The present outcomes bring evidences of potential genomic footprint of selection, which suggest an adaptive response of M. surmuletus to salinity conditions in the Mediterranean Sea. Additional genomic data such as sequencing of a full-genome and transcriptome analyses of gene expression would provide new insights regarding the possibility that some striped red mullet populations are locally adapted to their saline environment.

The rapidly emerging field of macrogenetics focuses on analysing publicly accessible genetic datasets from thousands of species to explore large-scale patterns and predictors of intraspecific genetic variation. Facilitated by advances in evolutionary biology, technology, data infrastructure, statistics and open science, macrogenetics addresses core evolutionary hypotheses (such as disentangling environmental and life-history effects on genetic variation) with a global focus. Yet, there are important, often overlooked, limitations to this approach and best practices need to be considered and adopted if macrogenetics is to continue its exciting trajectory and reach its full potential in fields such as biodiversity monitoring and conservation. Here, we review the history of this rapidly growing field, highlight knowledge gaps and future directions, and provide guidelines for further research.Leigh and colleagues describe the potential of the emerging field of macrogenetics to improve conservation and biodiversity management. Challenges preventing the field from reaching its full promise are highlighted and possible solutions and a framework for future macrogenetic studies are proposed.

Genetic diversity is estimated to be declining faster than species diversity under escalating threats, but its spatial distribution remains poorly documented at the global scale. Theory predicts that similar processes should foster congruent spatial patterns of genetic and species diversity, but empirical studies are scarce. Using a mined database of 50,588 georeferenced mitochondrial DNA barcode sequences (COI) for 3,815 marine and 1,611 freshwater fish species respectively, we examined the correlation between genetic diversity and species diversity and their global distributions in relation to climate and geography. Genetic diversity showed a clear spatial organisation, but a weak association with species diversity for both marine and freshwater species. We found a predominantly positive relationship between genetic diversity and sea surface temperature for marine species. Genetic diversity of freshwater species varied primarily across the regional basins and was negatively correlated with average river slope. The detection of genetic diversity patterns suggests that conservation measures should consider mismatching spatial signals across multiple facets of biodiversity.

Spatial differences in environmental selective pressures interact with the genomes of organisms, ultimately leading to local adaptation. Landscape genomics is an emergent research area that uncovers genome–environment associations, thus allowing researchers to identify candidate loci for adaptation to specific environmental variables. In the present study, we used latent factor mixed models (LFMMs) and Moran spectral outlier detection/randomization (MSOD-MSR) to identify candidate loci for adaptation to 10 environmental variables (climatic, soil and atmospheric) among 43 515 single nucleotide polymorphisms (SNPs) from 202 accessions of the model legume Medicago truncatula. Soil variables were associated with a large number of candidate loci identified through both LFMMs and MSOD-MSR. Genes tagged by candidate loci associated with drought and salinity are involved in the response to biotic and abiotic stresses, while those tagged by candidates associated with soil nitrogen and atmospheric nitrogen, participate in the legume-rhizobia symbiosis. Candidate SNPs identified through both LFMMs and MSOD-MSR explained up to 56% of variance in flowering traits. Our findings highlight the importance of soil in driving adaptation in the system and elucidate the basis of evolutionary potential of M. truncatula to respond to global climate change and anthropogenic disruption of the nitrogen cycle.

Assessing species geographic distributions is critical to approximate their ecological niches, understand how global change may reshape their occurrence patterns, and predict their extinction risks. Yet, species records are over-aggregated across taxonomic, geographic, environmental, and anthropogenic dimensions. The under-sampling of remote locations biases the quantification of species geographic distributions and ecological niche for most species. Here, we used nearly one thousand environmental DNA (eDNA) samples across the world’s oceans, including polar regions and tropical remote islands, to determine the extent to which the geographic and ecological niche ranges of marine fishes are underestimated through the lens of global occurrence records based on conventional surveys. Our eDNA surveys revealed that the known geographic ranges for 93% of species and the ecological niche ranges for 7% of species were underestimated, and contributed to filling them. We show that the probability to detect a range filling for a given species is primarily shaped by the GBIF/OBIS sampling effort in a cell, but also by the number of occurrences available for the species. Most gap fillings were achieved by addressing a methodological sampling bias, notably when eDNA facilitated the detection of small fishes in previously sampled locations using conventional methods. Using a machine learning model, we found that a local effort of 10 eDNA samples would detect 24 additional fish species on average and a maximum of 98 species in previously unsampled tropical areas. Yet, a null model revealed that only half of ecological niche range fillings would be due to eDNA surveys, beyond a random allocation of classical sampling effort. Altogether, our results suggest that sampling in remote areas and performing eDNA surveys in over-sampled areas may both increase fish ecological niche ranges toward unexpected values with consequences in biodiversity modeling, management, and conservation.

Key message Using a much higher number of SNP markers and larger sample sizes than all the previous studies, we characterized the genetic relationships among wild and cultivated plants of section Beta. We analyzed the genetic variation of Beta section Beta , which includes wild taxa ( Beta macrocarpa , B. patula , B. vulgaris subsp. adanensis and B. vulgaris subsp. maritima ) and cultivars (fodder beet, sugar beet, garden beet, leaf beet, and swiss chards), using 9724 single nucleotide polymorphism markers. The analyses conducted at the individual level without a priori groups confirmed the strong differentiation of B. macrocarpa and B. vulgaris subsp. adanensis from the other taxa. B. vulgaris subsp. maritima showed a complex genetic structure partly following a geographical pattern, which confounded the differences between this taxon and the cultivated varieties. Cultivated varieties were structured into three main groups: garden beets, fodder and sugar beets, and leaf beets and swiss chards. The genetic structure described here will be helpful to correctly estimate linkage disequilibrium and to test for statistical associations between genetic markers and environmental variables.

KEY MESSAGE : The genetic variation of Beta section Beta is structured into four taxonomic and spatial clusters. There are significant associations between molecular markers and environmental variables. We investigated the genetic diversity of Beta section Beta, which includes the wild and cultivated relatives of the sugar beet. The taxa included in the study were: Beta vulgaris subsp. maritima, B. vulgaris subsp. adanensis, B. macrocarpa, B. patula and B. vulgaris subsp. vulgaris (garden beet, leaf beet and swiss chards). We collected 1264 accessions originating from the entire distribution area of these taxa and genotyped them for 4436 DArT markers (DArTs). We showed that the genetic variation of these accessions is structured into four taxonomic and spatial clusters: (1) samples of Beta macrocarpa, (2) samples of Beta vulgaris subsp. adanensis, (3) Mediterranean and Asian samples and (4) Atlantic and Northern European samples. These last two clusters were mainly composed of samples of Beta vulgaris subsp. maritima. We investigated in deeper detail the genetic structure of B. vulgaris subsp. maritima, which constituted the majority (80 %) of the wild samples. This subspecies exhibited a clinal genetic variation from South-East to North-West. We detected some markers significantly associated to environmental variables in B. vulgaris subsp. maritima. These associations are interpreted as results of natural selection. The variable most often involved in the associations was annual mean temperature. Therefore, these markers can be useful for the development of frost-tolerant winter beets and drought-tolerant rain-fed beets.

Population genetics is a powerful tool for studying evolutionary processes and informing conservation biology. Traditional approaches typically rely on tissue sampling, which poses challenges in aquatic environments where specimen collection is often difficult. Recent efforts to conduct non‐invasive studies using environmental DNA (eDNA) have shown promise but face limitations. For instance, the use of a limited number of markers or the unintended capture of DNA fragments from off‐target species can hinder their effectiveness for population genetic studies. As a proof of concept of species‐specific genome‐wide nuclear loci detection from eDNA, we targeted the common frog, Rana temporaria, using a comparative experimental design. Field eDNA replicates were collected from four Alpine ponds, alongside tissue samples from 20 live tadpoles per pond. These tadpoles were also placed in separate tanks to collect eDNA under controlled conditions. Frog DNA from a subset of individuals was analysed through ddRAD genotyping and subsequently used to design custom probes for capturing frog nuclear loci from eDNA samples and individually collected tissues, using a modified hyRAD protocol. Although we observed substantial heterogeneity in the genetic data retrieved across replicates, the number of nuclear loci recovered in eDNA samples using hyRAD was in line with those obtained through classical ddRAD, proving sufficient to investigate genetic variation. We identified a total of 17,617 nuclear single nuclear polymorphisms shared across individual, pond eDNA and tank eDNA samples, enabling us to detect genetic structuring across sampling locations, consistent with individual‐based estimates. Our study opens new perspectives and corroborates the potential of eDNA for conducting non‐invasive population genomics analyses by using, for the first time, thousands of genome‐wide nuclear markers and highlights areas for further improvement.

Landscape genetics plays an increasingly important role in the management and conservation of species. Here, we highlight some of the opportunities and challenges in using landscape genetic approaches in conservation biology. We first discuss challenges related to sampling design and introduce several recent methodological developments in landscape genetics (analyses based on pairwise relatedness, the application of Bayesian methods, inference from landscape resistance and a shift from population-based to individual-based analyses). We then show how simulations can foster the field of landscape genetics and, finally, elaborate on technical developments in sequencing techniques that will dramatically improve our ability to study genetic variation in wild species, opening up new and unprecedented avenues for genetic analysis in conservation biology.