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Ramos Martins, Manuel

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  • Reduced global genetic differentiation of exploited marine fish species
    Publication . Gandra, Miguel; Assis, Jorge; Ramos Martins, Manuel; Abecasis, David
    Knowledge on genetic structure is key to understand species connectivity patterns and to define the spatiotemporal scales over which conservation management plans should be designed and implemented. The distribution of genetic diversity (within and among populations) greatly influences species ability to cope and adapt to environmental changes, ultimately determining their long-term resilience to ecological disturbances. Yet, the drivers shaping connectivity and structure in marine fish populations remain elusive, as are the effects of fishing activities on genetic subdivision. To investigate these questions, we conducted a meta-analysis and compiled genetic differentiation data (FST/ΦST estimates) for more than 170 fish species from over 200 published studies globally distributed. We modeled the effects of multiple life-history traits, distance metrics, and methodological factors on observed population differentiation indices and specifically tested whether any signal arising from different exposure to fishing exploitation could be detected. Although the myriad of variables shaping genetic structure makes it challenging to isolate the influence of single drivers, results showed a significant correlation between commercial importance and genetic structure, with widespread lower population differentiation in commercially exploited species. Moreover, models indicate that variables commonly used as proxy for connectivity, such as larval pelagic duration, might be insufficient, and suggest that deep-sea species may disperse further. Overall, these results contribute to the growing body of knowledge on marine genetic connectivity and suggest a potential effect of commercial fisheries on the homogenization of genetic diversity, highlighting the need for additional research focused on dispersal ecology to ensure long-term sustainability of exploited marine species.
  • Biologically meaningful distribution models highlight the benefits of the Paris Agreement for demersal fishing targets in the North Atlantic Ocean
    Publication . Ramos Martins, Manuel; Assis, Jorge; Abecasis, David
    Aim: With climate change challenging marine biodiversity and resource management, it is crucial to anticipate future latitudinal and depth shifts under contrasting global change scenarios to support policy-relevant biodiversity impact assessments [e.g., Intergovernmental Panel on Climate Change (IPCC)]. We aim to demonstrate the benefits of complying with the Paris Agreement (United Nations Framework Convention on Climate Change) and limiting environmental changes, by assessing future distributional shifts of 10 commercially important demersal fish species. Location: Northern Atlantic Ocean. Time period: Analyses of distributional shifts compared near present-day conditions (2000–2017) with two Representative Concentration Pathway (RCP) scenarios of future climate changes (2090–2100): one following the Paris Agreement climate forcing (RCP2.6) and another without stringent mitigation measures (RCP8.5). Major taxa studied: Demersal fish. Methods: We use machine learning distribution models coupled with biologically meaningful predictors to project future latitudinal and depth shifts. Structuring projections with information beyond temperature-based predictors allowed us to encompass the physiological limitations of species better. Results: Our models highlighted the additional roles of temperature, primary productivity and dissolved oxygen in shaping fish distributions (average relative contribution to the models of 32.12 ± 10.24, 15.6 ± 7.5 and 12.1 ± 6.1%, respectively). We anticipated a generalized trend of poleward shifts in both future scenarios, with aggravated changes in suitable area with RCP8.5 (average area loss with RCP2.6 = 13.3 ± 4.1%; RCP8.5 = 40.9 ± 13.3%). Shifts to deeper waters were also predicted to be of greater magnitude with RCP8.5 (average depth gain = 25.4 ± 21.5 m) than with RCP2.6 (average depth gain = 10.4 ± 7.9 m). Habitat losses were projected mostly in the Mediterranean, Celtic and Irish Seas, the southern areas of the North Sea and along the NE coast of North America. Main conclusions: Inclusion of biologically meaningful predictors beyond temperature in species distribution modelling can improve predictive performances. Limiting future climate changes by complying with the Paris Agreement can translate into reduced distributional shifts, supporting biodiversity conservation and resource management.