Search

Marine protected areas (MPAs) are major tools to protect biodiversity and sustain fisheries. For species with a sedentary adult phase and a dispersive larval phase, the effectiveness of MPA networks for population persistence depends on connectivity through larval dispersal. However, connectivity patterns between MPAs remain largely unknown at large spatial scales. Here, we used a biophysical model to evaluate connectivity between MPAs in the Mediterranean Sea, a region of extremely rich biodiversity that is currently protected by a system of approximately a hundred MPAs. The model was parameterized according to the dispersal capacity of the dusky grouper Epinephelus marginatus, an archetypal conservation-dependent species, with high economic importance and emblematic in the Mediterranean. Using various connectivity metrics and graph theory, we showed that Mediterranean MPAs are far from constituting a true, well-connected network. On average, each MPA was directly connected to four others and MPAs were clustered into several groups. Two MPAs (one in the Balearic Islands and one in Sardinia) emerged as crucial nodes for ensuring multi-generational connectivity. The high heterogeneity of MPA distribution, with low density in the South-Eastern Mediterranean, coupled with a mean dispersal distance of 120 km, leaves about 20% of the continental shelf without any larval supply. This low connectivity, here demonstrated for a major Mediterranean species, poses new challenges for the creation of a future Mediterranean network of well-connected MPAs providing recruitment to the whole continental shelf. This issue is even more critical given that the expected reduction of pelagic larval duration following sea temperature rise will likely decrease connectivity even more. [ABSTRACT FROM AUTHOR]

Evidence of large‐scale biodiversity degradation in marine ecosystems has been reported worldwide, yet most research has focused on few species of interest or on limited spatiotemporal scales. Here we assessed the spatial and temporal changes in the taxonomic and functional composition of fish communities in European seas over the last 25 years (1994–2019). We then explored how these community changes were linked to environmental gradients and fishing pressure. We show that the spatial variation in fish species composition is more than two times higher than the temporal variation, with a marked spatial continuum in taxonomic composition and a more homogenous pattern in functional composition. The regions warming the fastest are experiencing an increasing dominance and total abundance of r‐strategy fish species (lower age of maturity). Conversely, regions warming more slowly show an increasing dominance and total abundance of K‐strategy species (high trophic level and late reproduction). Among the considered environmental variables, sea surface temperature, surface salinity and chlorophyll‐a most consistently influenced communities' spatial patterns, while bottom temperature and oxygen had the most consistent influence on temporal patterns. Changes in communities' functional composition were more closely related to environmental conditions than taxonomic changes. Our study demonstrates the importance of integrating community‐level species traits across multi‐decadal scales and across a large region to better capture and understand ecosystem‐wide responses and provides a different lens on community dynamics that could be used to support sustainable fisheries management. [ABSTRACT FROM AUTHOR]

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. Empirical data on occurrences and vulnerability are still lacking for most marine teleost fish species, preventing assessment of their IUCN extinction risk status. This study uses machine learning with occurrence data, species biological traits, taxonomy and human usage to infer a 12.8% extinction risk for marine fish species, surpassing existing estimates. [ABSTRACT FROM AUTHOR]

Aim: Environmental DNA metabarcoding has recently emerged as a non‐invasive tool for aquatic biodiversity inventories, frequently surpassing traditional methods for detecting a wide range of taxa in most habitats. The major limitation currently impairing the large‐scale application of eDNA‐based inventories is the lack of species sequences available in public genetic databases. Unfortunately, these gaps are still unknown spatially and taxonomically, hindering targeted future sequencing efforts. Innovation: We propose GAPeDNA, a user‐friendly web interface that provides a global overview of genetic database completeness for a given taxon across space and conservation status. As an application, we synthetized data from regional checklists for marine and freshwater fishes along with their IUCN conservation status to provide global maps of species coverage using the European Nucleotide Archive public reference database for 19 metabarcoding primers. This tool automatizes the scanning of gaps in these databases to guide future sequencing efforts and support the deployment of eDNA inventories at larger scale. This tool is flexible and can be expanded to other taxa and primers upon data availability. Main conclusions: Using our global fish case study, we show that gaps increase towards the tropics where species diversity and the number of threatened species are the highest. It highlights priority areas for fish sequencing like the Congo, the Mekong and the Mississippi freshwater basins which host more than 60 non‐sequenced threatened fish species. For marine fishes, the Caribbean and East Africa host up to 42 non‐sequenced threatened species. By presenting the global genetic database completeness for several primers on any taxa and building an open‐access, updatable and flexible tool, GAPeDNA appears as a valuable contribution to support any kind of eDNA metabarcoding study. [ABSTRACT FROM AUTHOR]

Background: Biodiversity exists at different levels of organisation: e.g. genetic, individual, population, species, and community. These levels of organisation all exist within the same system, with diversity patterns emerging across organisational scales through several key processes. Despite this inherent interconnectivity, observational studies reveal that diversity patterns across levels are not consistent and the underlying mechanisms for variable continuity in diversity across levels remain elusive. To investigate these mechanisms, we apply a spatially explicit simulation model to simulate the global diversification of tropical reef fishes at both the population and species levels through emergent population-level processes. Results: We find significant relationships between the population and species levels of diversity which vary depending on both the measure of diversity and the spatial partitioning considered. In turn, these population-species relationships are driven by modelled biological trait parameters, especially the divergence threshold at which populations speciate. Conclusions: To explain variation in multi-level diversity patterns, we propose a simple, yet novel, population-to-species diversity partitioning mechanism through speciation which disrupts continuous diversity patterns across organisational levels. We expect that in real-world systems this mechanism is driven by the molecular dynamics that determine genetic incompatibility, and therefore reproductive isolation between individuals. We put forward a framework in which the mechanisms underlying patterns of diversity across organisational levels are universal, and through this show how variable patterns of diversity can emerge through organisational scale. [ABSTRACT FROM AUTHOR]

Summary: The geographic distribution of plant diversity matches the gradient of habitat heterogeneity from lowlands to mountain regions. However, little is known about how much this relationship is conserved across scales.Using the World Checklist of Vascular Plants and high‐resolution biodiversity maps developed by species distribution models, we investigated the associations between species richness and habitat heterogeneity at the scales of Eurasia and the Hengduan Mountains (HDM) in China.Habitat heterogeneity explains seed plant species richness across Eurasia, but the plant species richness of 41/97 HDM families is even higher than expected from fitted statistical relationships. A habitat heterogeneity index combining growing degree days, site water balance, and bedrock type performs better than heterogeneity based on single variables in explaining species richness. In the HDM, the association between heterogeneity and species richness is stronger at larger scales.Our findings suggest that high environmental heterogeneity provides suitable conditions for the diversification of lineages in the HDM. Nevertheless, habitat heterogeneity alone cannot fully explain the distribution of species richness in the HDM, especially in the western HDM, and complementary mechanisms, such as the complex geological history of the region, may have contributed to shaping this exceptional biodiversity hotspot. This article is part of the Special Collection 'Global plant diversity and distribution'. See https://www.newphytologist.org/global-plant-diversity for more details. [ABSTRACT FROM AUTHOR]

Environmental DNA (eDNA) metabarcoding provides an efficient approach for documenting biodiversity patterns in marine and terrestrial ecosystems. The complexity of these data prevents current methods from extracting and analyzing all the relevant ecological information they contain, and new methods may provide better dimensionality reduction and clustering. Here we present two new deep learning‐based methods that combine different types of neural networks (NNs) to ordinate eDNA samples and visualize ecosystem properties in a two‐dimensional space: the first is based on variational autoencoders and the second on deep metric learning. The strength of our new methods lies in the combination of two inputs: the number of sequences found for each molecular operational taxonomic unit (MOTU) detected and their corresponding nucleotide sequence. Using three different datasets, we show that our methods accurately represent several biodiversity indicators in a two‐dimensional latent space: MOTU richness per sample, sequence α‐diversity per sample, Jaccard's and sequence β‐diversity between samples. We show that our nonlinear methods are better at extracting features from eDNA datasets while avoiding the major biases associated with eDNA. Our methods outperform traditional dimension reduction methods such as Principal Component Analysis, t‐distributed Stochastic Neighbour Embedding, Nonmetric Multidimensional Scaling and Uniform Manifold Approximation and Projection for dimension reduction. Our results suggest that NNs provide a more efficient way of extracting structure from eDNA metabarcoding data, thereby improving their ecological interpretation and thus biodiversity monitoring. [ABSTRACT FROM AUTHOR]

• Environmental DNA samples were taken seasonally in a Marine Protected Area. • Vulnerable species were mostly detected in the Fully Protected Area. • eDNA metabarcoding revealed seasonal changes in community composition. • Fish composition changes were detected along a depth gradient. • eDNA is useful for frequent monitoring in MPAs to guide management strategies. Marine fish communities suffer from anthropogenic pressures and climate change, which influence their spatio-temporal dynamics. Marine Protected Areas (MPAs) have been established worldwide to preserve these communities, while mesophotic ecosystems could provide natural refugia. Assessing the extent to which MPAs and deeper ecosystems can mitigate human and climate change impacts requires regular monitoring of temporal community dynamics. Environmental DNA (eDNA) surveys – being time- and cost-effective – can provide valuable insights on biodiversity change. Here, we initiated a long-term study based on eDNA monitoring in an MPA in the north-western Mediterranean Sea that includes areas with various protection levels. Specifically, from June 2021 to January 2023, we collected eDNA samples during the summer, fall, and winter seasons from shallow water (20 m depth), at 40 m depth, and from the mesophotic zone (80 m depth) in a Fully Protected Area (FPA) and in a nearby Lightly Protected Area (LPA) in the Riou archipelago (France). In this short period and relatively small area, we detected a total of 113 actinopterygian and chondrichthyan taxa. Species with high fishing vulnerability had higher detection rates in the FPA than in the LPA, suggesting a positive impact of FPAs on the conservation of these threatened species. A marked seasonal signal in species detections, including significantly lower detections of several species in winter, indicated a combined effect of species biological changes and migration behavior. The seasonality trend was stronger in the FPA than in the LPA, indicating that such areas may modify sub-yearly patterns in communities and ecosystem processes. Fish composition was associated with water depth, with marked species dissimilarities between shallow waters and the mesophotic zone, implying that multiple depths should be considered in MPA monitoring to fully capture the response of biodiversity to management. Our results point to the importance of temporal information combined with extensive sampling across depths and protection levels to fully understand the ecological dynamics and structure of coastal fish communities. [ABSTRACT FROM AUTHOR]

High-throughput DNA sequencing is becoming an increasingly important tool to monitor and better understand biodiversity responses to environmental changes in a standardized and reproducible way. Environmental DNA (eDNA) from organisms can be captured in ecosystem samples and sequenced using metabarcoding, but processing large volumes of eDNA data and annotating sequences to recognized taxa remains computationally expensive. Speed and accuracy are two major bottlenecks in this critical step. Here, we evaluated the ability of convolutional neural networks (CNNs) to process short eDNA sequences and associate them with taxonomic labels. Using a unique eDNA data set collected in highly diverse Tropical South America, we compared the speed and accuracy of CNNs with that of a well-known bioinformatic pipeline (OBITools) in processing a small region (60 bp) of the 12S ribosomal DNA targeting freshwater fishes. We found that the taxonomic labels from the CNNs were comparable to those from OBITools, with high correlation levels for the composition of the regional fish fauna. The CNNs enabled the processing of raw fastq files at a rate of approximately 1 million sequences per minute, which was about 150 times faster than with OBITools. Given the good performance of CNNs in the highly diverse ecosystem considered here, the development of more elaborate CNNs promises fast deployment for future biodiversity inventories using eDNA. [ABSTRACT FROM AUTHOR]

[Display omitted] • The spatiotemporal dynamics of demersal fish communities were investigated in the Bay of Biscay (BoB) and Celtic Sea (CS). • Two decades of changes in temperature, trophic resources, habitat and fishing pressure on community were assessed. • Diversity patterns showed greater variability in space than in time and species richness and abundance weakly changed. • Communities are becoming more spatially similar (homogeneous) in the CS and differentiated in the BoB. • Such patterns are best explained by the dynamics of trophic resources mediated by small pelagic species. Climate change and resource exploitation represent strong selection pressure affecting the spatio-temporal dynamics of marine assemblages that ensure food provision for humans. However, such dynamics remain poorly documented, and their drivers unclear. Here, we investigate changes in fish assemblages of two key European fishing areas, the Bay of Biscay (BoB) and the Celtic Sea (CS), during the last two decades. We quantify the relative contribution of change in energy (i.e. temperature and trophic resources), habitat (depth, substrate, oxygen) and fishing pressure to explaining observed spatial and temporal variations in fish diversity. We used long-term scientific surveys to evaluate the spatio-temporal changes in species richness (SR), abundance and composition of demersal fish (Actinopterygii) assemblages at different spatial scales combined with a range of regression models and variance partitioning. Diversity patterns showed greater variability in space than in time: SR weakly changed over time, while compositional dissimilarity showed local patterns of taxonomic homogenization in the CS and differentiation in the southern BoB, where local assemblages were becoming more similar and dissimilar over time, respectively. Energy funnelled through small pelagic species as a potential trophic link affecting the dynamics of demersal assemblages was the most important driver, while habitat and fishing pressure had limited importance. Our study revealed contrasted dynamics of demersal fish assemblages at a regional scale that were best explained by the dynamics of small pelagic species. Direct effects of environmental forcing and fishing pressure were limited in both regions which have a long history of fishing and still remain relatively buffered from global warming effects. This research paved the way to combine methods inspired by biogeography with scientific monitoring surveys to detect spatio-temporal dynamics of fish assemblages and their drivers in marine ecosystems under multiple pressures. [ABSTRACT FROM AUTHOR]