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Publication
Towards a unified eco-evolutionary framework for fisheries management: Coupling advances in next-generation sequencing with species distribution modelling
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Advisor(s)
Abstract(s)
The establishment of high-throughput sequencing technologies and
subsequent large-scale genomic datasets has flourished across fields of
fundamental biological sciences. The introduction of genomic resources in
fisheries management has been proposed from multiple angles, ranging from
an accurate re-definition of geographical limitations of stocks and connectivity,
identification of fine-scale stock structure linked to locally adapted subpopulations, or even the integration with individual-based biophysical
models to explore life history strategies. While those clearly enhance our
perception of patterns at the light of a spatial scale, temporal depth and
consequently forecasting ability might be compromised as an analytical
trade-off. Here, we present a framework to reinforce our understanding of
stock dynamics by adding also a temporal point of view. We propose to
integrate genomic information on temporal projections of species
distributions computed by Species Distribution Models (SDMs). SDMs have
the potential to project the current and future distribution ranges of a given
species from relevant environmental predictors. These projections serve as
tools to inform about range expansions and contractions of fish stocks and
suggest either suitable locations or local extirpations that may arise in the
future. However, SDMs assume that the whole population respond
homogenously to the range of environmental conditions. Here, we
conceptualize a framework that leverages a conventional Bayesian joint-SDM
approach with the incorporation of genomic data. We propose that introducing
genomic information at the basis of a joint-SDM will explore the range of
suitable habitats where stocks could thrive in the future as a function of their
current evolutionary potential.
Description
Keywords
High-throughput sequencing genomics Species distribution model (SDMs) Fisheries applications Evolutionary ecology
Citation
Baltazar-Soares, M., Lima, A. R. A., Silva, G., & Gaget, E. (2023). Towards a unified eco-evolutionary framework for fisheries management: Coupling advances in next-generation sequencing with species distribution modelling. Frontiers in Marine Science, 9 https://doi.org/10.3389/fmars.2022.1014361o
Publisher
Frontiers Media S.A.