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Ben Rais Lasram, F., Hattab, T., Nogues, Q., Beaugrand, G., Dauvin, J. C., Halouani, G., et al. (2020). An open-source framework to model present and future marine species distributions at local scale. Ecological Informatics, 59, 101130.
Résumé: Species Distribution Models (SDMs) are useful tools to project potential future species distributions under climate change scenarios. Despite the ability to run SDMs in recent and reliable tools, there are some misuses and proxies that are widely practiced and rarely addressed together, particularly when dealing with marine species. In this paper, we propose an open-source framework that includes (i) a procedure for homogenizing occurrence data to reduce the influence of sampling bias, (ii) a procedure for generating pseudo-absences, (iii) a hierarchical-filter approach, (iv) full incorporation of the third dimension by considering climatic variables at multiple depths and (v) building of maps that predict current and potential future ranges of marine species. This framework is available for non-modeller ecologists interested in investigating future species ranges with a user-friendly script. We investigated the robustness of the framework by applying it to marine species of the Eastern English Channel. Projections were built for the middle and the end of this century under RCP2.6 and RCP8.5 scenarios.
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Benedetti, F., Vogt, M., Righetti, D., Guilhaumon, F., & Ayata, S. - D. (2018). Do functional groups of planktonic copepods differ in their ecological niches? J. Biogeogr., 45(3), 604–616.
Résumé: Aim: To assess the degree of overlap between the environmental niches of marine planktonic copepods and test if the distribution of copepod functional groups differs across environmental gradients. Location: The Mediterranean Sea. Methods: Functional groups were defined based on clustering of functional traits in 106 marine copepod species using a multivariate ordination analysis. Functional traits included maximum body length, feeding mode, spawning strategy and trophic group. Simultaneously, the global distribution of the species was used to model their environmental niches with six environmental variables. For each of these predictors, four niche parameters were derived from the univariate response curve of each species to summarise their environmental preferences and ordinate the species in niche space through a PCA. Finally, the differences in the position in niche space of functional groups were tested with variance analysis. Results: We identified seven copepod functional groups with different distributions along the environmental gradients covered by our study. While carnivorous functional groups were affiliated with oligotrophic and tropical conditions, large and small current-feeding herbivores are associated with colder, more seasonally varying and productive conditions. Small cruising detritivores and other small current-feeding herbivores were not affiliated with specific conditions as their constituting species were scattered in niche space. Main conclusions: Since copepod functional groups occupy distinct ecological niches, ecosystem processes related to these groups are expected to vary across environmental gradients. Conditions favouring large current-feeding herbivores should allow for enhanced fluxes of energy and nutrients through Mediterranean Sea ecosystems, while such fluxes should be weakened where large carnivores and small passive ambush-feeding copepods dominate. Our study supports the development of trait-based zooplankton functional groups in marine ecosystem models.
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Chambault, P., Hattab, T., Mouquet, P., Bajjouk, T., Jean, C., Ballorain, K., et al. (2021). A methodological framework to predict the individual and population-level distributions from tracking data. Ecography, .
Résumé: Despite the large number of species distribution modelling (SDM) applications driven by tracking data, individual information is most of the time neglected and traditional SDM approaches commonly focus on predicting the potential distribution at the species or population-level. By running classical SDMs (population approach) with mixed models including a random factor to account for the variability attributable to individual (individual approach), we propose an innovative five-steps framework to predict the potential and individual-level distributions of mobile species using GPS data collected from green turtles. Pseudo-absences were randomly generated following an environmentally-stratified procedure. A negative exponential dispersal kernel was incorporated into the individual model to account for spatial fidelity, while five environmental variables derived from high-resolution Lidar and hyperspectral data were used as predictors of the species distribution in generalized linear models. Both approaches showed a strong predictive power (mean: AUC > 0.93, CBI > 0.88) and goodness-of-fit (0.6 < adjusted R2 < 0.9), but differed geographically with favorable habitats restricted around the tagging locations for the individual approach whereas favorable habitats from the population approach were more widespread. Our innovative way to combine predictions from both approaches into a single map provides a unique scientific baseline to support conservation planning and management of many taxa. Our framework is easy to implement and brings new opportunities to exploit existing tracking dataset, while addressing key ecological questions such as inter-individual plasticity and social interactions.
Mots-Clés: GPS tracking; green turtles; Indian Ocean; pseudo-absences; Shannon index; spatial modelling
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