The distribution of coastal fish eDNA sequences in the Anthropocene

Aim

Coastal fishes have a fundamental role in marine ecosystem functioning and contributions to people, but face increasing threats due to climate change, habitat degradation and overexploitation. The extent to which human pressures are impacting coastal fish biodiversity in comparison with geographic and environmental factors at large spatial scale is still under scrutiny. Here, we took advantage of environmental DNA (eDNA) metabarcoding to investigate the relationship between fish biodiversity, including taxonomic and genetic components, and environmental but also socio-economic factors.

Location

Tropical, temperate and polar coastal areas.

Time period

Present day.

Major taxa studied

Marine fishes.

Methods

We analysed fish eDNA in 263 stations (samples) in 68 sites distributed across polar, temperate and tropical regions. We modelled the effect of environmental, geographic and socio-economic factors on α- and β-diversity. We then computed the partial effect of each factor on several fish biodiversity components using taxonomic molecular units (MOTU) and genetic sequences. We also investigated the relationship between fish genetic α- and β-diversity measured from our barcodes, and phylogenetic but also functional diversity.

Results

We show that fish eDNA MOTU and sequence α- and β-diversity have the strongest correlation with environmental factors on coastal ecosystems worldwide. However, our models also reveal a negative correlation between biodiversity and human dependence on marine ecosystems. In areas with high dependence, diversity of all fish, cryptobenthic fish and large fish MOTUs declined steeply. Finally, we show that a sequence diversity index, accounting for genetic distance between pairs of MOTUs, within and between communities, is a reliable proxy of phylogenetic and functional diversity.

Main conclusions

Together, our results demonstrate that short eDNA sequences can be used to assess climate and direct human impacts on marine biodiversity at large scale in the Anthropocene and can further be extended to investigate biodiversity in its phylogenetic and functional dimensions.     

Spatial graphs highlight how multi-generational dispersal shapes landscape genetic patterns

Current approaches that compare spatial genetic structure of a given species and the dispersal of its mobile phase can detect a mismatch between both patterns mainly due to processes acting at different temporal scales. Genetic structure result from gene flow and other evolutionary and demographic processes over many generations, while dispersal predicted from the mobile phase often represents solely one generation on a single time-step. In this study, we present a spatial graph approach to landscape genetics that extends connectivity networks with a stepping-stone model to represent dispersal between suitable habitat patches over multiple generations. We illustrate the approach with the case of the striped red mullet Mullus surmuletus in the Mediterranean Sea. The genetic connectivity of M. surmuletus was not correlate with the estimated dispersal probability over one generation, but with the stepping-stone estimate of larval dispersal, revealing the temporal scale of connectivity across the Mediterranean Sea. Our results highlight the importance of considering multiple generations and different time scales when relating demographic and genetic connectivity. The spatial graph of genetic distances further untangles intra-population genetic structure revealing the Siculo-Tunisian Strait as an important corridor rather than a barrier for gene flow between the Western- and Eastern Mediterranean basins, and identifying Mediterranean islands as important stepping-stones for gene flow between continental populations. Our approach can be easily extended to other systems and environments.     

A unifying quantitative framework for exploring the multiple facets of microbial biodiversity across diverse scales

Recent developments of molecular tools have revolutionized our knowledge of microbial biodiversity by allowing detailed exploration of its different facets and generating unprecedented amount of data. One key issue with such large datasets is the development of diversity measures that cope with different data outputs and allow comparison of biodiversity across different scales. Diversity has indeed three components: local (α), regional (γ) and the overall difference between local communities (β). Current measures of microbial diversity, derived from several approaches, provide complementary but different views. They only capture the β component of diversity, compare communities in a pairwise way, consider all species as equivalent or lack a mathematically explicit relationship among the α, β and γ components. We propose a unified quantitative framework based on the Rao quadratic entropy, to obtain an additive decomposition of diversity (γ = α + β), so the three components can be compared, and that integrate the relationship (phylogenetic or functional) among Microbial Diversity Units that compose a microbial community. We show how this framework is adapted to all types of molecular data, and we highlight crucial issues in microbial ecology that would benefit from this framework and propose ready‐to‐use R‐functions to easily set up our approach.     

Environmental heterogeneity among lakes promotes hyper β‐diversity across phytoplankton communities

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