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- Multi-generation dispersal shapes the genetic structure of the canopy-forming seaweed Ericaria amentacea syn. Cystoseira amentacea in the north-western Mediterranean SeaPublication . Reynes, Lauric; Legrand, Térence; Blanfuné, Aurélie; Assis, Jorge; Thibaut, Thierry; Bottin, LorraineCanopy-forming seaweeds, especially fucoids (Fucales, Phaeophyceae), constitute marine forests in the Mediterranean Sea that deliver key ecosystem services. However, escalating human pressures in coastal areas have led to habitat fragmentation, significantly impacting the dynamics of gene flow and evolutionary trajectories. In this study, we investigated population connectivity among 43 sites with Ericaria amentacea in the northwestern Mediterranean Sea. By integrating microsatellite genotyping and biophysical modelling, we aimed to evaluate the hypothesis that population connectivity is approximated by oceanographic connectivity, rather than coastal distance. While traditional approaches to oceanographic connectivity had focused on single-generation dispersal models, we adopted a multi-generation perspective. This involves employing a biophysical model that considers gene flow through multiple stepping-stone populations across the E. amentacea distribution and over distinct generations of dispersal. Using distance-based redundancy analysis (dbRDA), we found that multi-generation dispersal significantly contributes to genetic differentiation, surpassing the influence of coastal distance. Even so, genetic differentiation remained significant among all population pairs, suggesting that gene flow may be hindered by differential selection acting against migrants and/or obscured by the effects of local genetic drift. The latter is likely, given the species' low dispersal potential and self-compatibility, both of which promote small, spatially restricted breeding units. In addition, our results emphasized that oceanographic connectivity promoted long-distance dispersal across northern Corsica and Eastern Provence over a single generation through the drifting of fertile thalli, which might have contributed to moderate differentiation between local populations. Overall, this framework highlights the value of considering multi-generation dispersal across numerous intermediate stepping-stones for informing management strategies aimed at enhancing population connectivity and safeguarding genetic diversity in seaweeds.
- AI-driven conservation of the endangered twisted yew (Taxus contorta Griff.) in the western himalayaPublication . Din, Salahud; Ali, Haidar; Panagopoulos, Thomas; Alam, Jan; Malik, Saira; Sher, HassanConserving the threatened West Himalayan endemic T. contorta (Taxaceae) is critical due to extinction risks from skewed male- or female-only populations. This study employs ChatGPT-driven artificial intelligence (AI) analysis for textual synthesis and preliminary hypothesis generation to identify favorable propagation sites for T. contorta within the Swat district of Pakistan. Over three years (2019–2021), eleven male- or female-only populations of T. contorta were surveyed. Environmental data from NASA POWER were analyzed using ChatGPT 3.5 to predict suitable propagation sites, which were then mapped in Google Earth Pro. PCA and hierarchical clustering were applied to identify key environmental variables. Out of 63 generated points, 58 were accurately located in Swat with 92% geographic accuracy, while species-specific general knowledge accuracy was 100%. All points fell within the pre-established T. contorta spatial range in Pakistan, with 21 unique sites meeting optimal conditions. Field surveys confirmed 16 new populations. These findings underscore the promising role of AI-driven analysis in conservation planning by identifying and supporting habitat restoration efforts. A bidirectional integration of AI and SDM, combined with remote sensing technologies, represents a novel approach for the effective conservation of endangered plant species.