Biology subjects

Violet, C.

Publications and source records attributed to Violet, C..

4 recordsLinked to original sources

bioRxiv2025

Expanding on the portuarization syndrome from an ecological perspective: eDNA reveals rich diversity, non-indigenous hotspots, and biotic homogenization in ports

Ports are well-known entry points for marine non-indigenous species (NIS), which arrive as hitchhikers on ships. Ports are also expected to be gateways for the spread of NIS in the wild and resemble each other more than communities outside due to their singular characteristics. However, the uniqueness of species assemblages in ports and how they differ from natural habitats have only been marginally investigated, notably at regional scale. Using eDNA metabarcoding, we obtained a comprehensive and standardized overview of metazoan community diversity in 12 paired ports and adjacent natural areas along the northwestern Mediterranean Sea. As expected, we found that NIS are more abundant in ports than in natural habitats, and that the species assemblages in ports differ from those in natural habitats. In addition, we observed that communities in ports are far more homogeneous than their natural counterparts. This finding supports the hypothesis of biotic homogenization in highly anthropized habitats. We also observed a pattern that had previously been documented mainly in fish, but that we identified here in every phylum studied except Arthropoda: species richness detected in ports is comparable to, and in some case even greater than, that observed in natural habitats. Overall, our findings broaden, through an ecological perspective, the "portuarization syndrome" concept, which originally defined ports as unique replicated environments that promote specific evolutionary processes.

ecology↗

bioRxiv2025

Glucocorticoid receptors mediate reprogramming of astrocytes in depression.

Psychiatric disorders are among the most pressing problems of the modern society, with various forms of depression affecting more than 300 millions of people worldwide. Dysfunction of glial cells has consistently been reported in major depressive disorder (MDD); however, no comprehensive resource detailing glial dysfunction is available. To provide insight into neurobiological mechanisms behind severe psychiatric symptoms, we performed transcriptional analysis of post-mortem samples from a subpopulation of suicide completers with previously reported glial abnormalities. We focused on BA25, a subregion of the prefrontal cortex prioritized for targeted medical interventions, due to its metabolic aberrations in disease. We found that a significant portion of genes deregulated in MDD is enriched in glia, with astrocyte-specific genes representing the highest fraction. Then we employed a novel protocol for enriching astrocytic nuclei to provide a detailed molecular signature of astrocytes in MDD. The analysis of the gene set revealed the glucocorticoid receptor (GR) as a key regulatory transcription factor. We found that astrocyte-specific elimination of the GR in mice largely prevented transcriptional, metabolic and behavioral changes elicited by chronic stress. We also demonstrated that regional manipulation of glutamate turnover in astrocytes suffices to elicit discrete traits of depressive-like behavior. Our data points to astrocytes as a key cellular site of convergence of multiple traits of depression and provide a resource for exploring novel targets for glia-focused therapeutic approaches.

neuroscience↗

bioRxiv2024

From local seafloor imagery to global patterns in benthic habitat states: contribution of citizen science to habitat classification across latitudes

AimThe aim of this study was to define reef benthic habitat states and explore their spatial and temporal variability at a global scale using an innovative clustering pipeline. LocationThe study uses data on the transects surveyed on shallow (< 20m) reef ecosystems across the globe. Time period: Transects sampled between 2008 and 2021. Major taxa studied: Macroalgae, sessile invertebrates, hydrozoans, seagrass, corals. MethodsPercentage cover was estimated for 24 functional groups of sessile biota and substratum from annotated underwater photoquadrats taken along 6,554 transects by scuba divers contributing to the Reef Life Survey dataset. A clustering pipeline combining a non-linear dimension-reduction technique (UMAP), with a density-based clustering approach (HDBSCAN), was used to identify benthic habitat states. Spatial and temporal variation in habitat distribution was then explored across ecoregions. ResultsThe UMAP-HDBSCAN pipeline identified 17 distinct clusters representing different benthic habitats and gradients of ecological state. Certain habitat states displayed clear biogeographic patterns, predominantly occurring in temperate regions or tropical waters. Notably, some reefs dominated by turf algae were ubiquitous across latitudinal zones. Transition zones between temperate and tropical waters emerged as spatial hotspots of habitat state diversity. Temporal analyses revealed changes in the proportion of certain states over time, notably an increase in turf algae occurrence. Main ConclusionsThe UMAP-HDBSCAN clustering pipeline effectively characterised fine-scale benthic habitat states at a global scale, confirming known broader biogeographic patterns, including the importance of temperate-tropical transition zones as hotspots of habitat state diversity. This fine-scale, yet broadly-scalable habitat classification could be applied as a standardised template for tracking benthic habitat change across space and time at a global scale. The UMAP-HDBSCAN pipeline has proven to be a powerful and versatile approach for analysing complex biological datasets and can be applied in various ecological domains.

ecology↗

bioRxiv2022

Essential ingredients in Joint Species Distribution Models: influence on interpretability, explanatory and predictive power

Joint Species Distribution Models (jSDM) are increasingly used to explain and predict biodiversity patterns. By accounting for species co-occurrence patterns and potentially including species-specific information, jSDMs capture the processes that shape ecological communities. Yet, factors like missing covariates or omitting ecologically-important species may alter the interpretability and effectiveness of jSDMs. Additionally, while the specific formulation of a jSDM directly affects its performances, the effects of choices related to model structure, such as inclusion, or not of phylogeny or trait information, are not well-explored. Here, we developed a multifaceted framework to comprehensively assess performances of alternative jSDM formulations at both species and community levels. We applied this framework to four alternative models fitted on presence/absence and abundance data of a polychaete assemblage sampled in two coastal habitats over 500 km and 8 years. Relative to a benchmark jSDM only capturing the effects of abiotic predictors and residual co-occurrence patterns, we explored the performance of alternative formulations that also included species phylogeny, traits, or some additional 179 non-target species, which were sampled alongside the species of interest. For both presence/absence and abundance data, explanatory power was good for all models but their interpretability and predictive power varied. Relative to the benchmark model, predictive errors on species abundances decreased by 95% or 53%, when including non-target species, or phylogeny, respectively. These differences across models relate to changes in both species-environment relationships and residual co-occurrence patterns. While considering trait data did not improve explanatory or predictive power, it facilitated interpretation of trait-mediated species response to environmental gradients. This study demonstrates trade-offs in jSDM formulation for explaining or predicting species data, highlighting the importance of using a comprehensive framework to compare models. Furthermore, our study provides some guidance for model selection tailored to specific objectives and available data.

ecology↗