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Habitat modelling of key copepods species in the Northwest Atlantic using depth-integrated data to model past and future changes in distribution and productivity

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conference contribution
posted on 2024-04-25, 08:29 authored by Séverine Albouy-Boyer, Stéphane Plourde, Pierre Pepin, Caroline Lehoux, Catherine Johnson, Peter S. Galbraith, Dave Hebert, Diane Lavoie, Joël Chassé, David Brickman, Nicolas Lambert, Gordana Lazin, Caroline Lafleur

No abstracts are to be cited without prior reference to the author.

Fourteen years of data from the Atlantic Zone Monitoring Program (AZMP) were used to model habitatsof key copepod species (Calanus glacialis, C. hyperboreus, C. finmarchicus, Paracalanus sp.) on the continentalshelf and Slope water in the Northwest Atlantic Ocean. Habitat modelling was performed withGeneralized Additive Mixed Models (GAMMs) based on environmental indices representing the habitatof Calanus species, throughout their whole life history, which includes an active population growth phasedominated by early stages in the surface layer, and a dormant phase dominated by overwintering stagesin deeper habitats. Our analyses allowed habitat modelling where species could be encountered(occurrence models) and the productivity of the species when present (abundance models) andunderlined the importance of using depth-integrated data encompassing all developmental stages andenvironmental indices representative of all habitats occupied during their life cycle to accurately modelthe distribution of Calanus species. In context of global change, the models developed in this studyprovide essential tools to predict changes in productivity and/or occurrence of keystone species in theNorthwest Atlantic Ocean.

History

Symposia

2015 Annual Science Conference, Copenhagen, Denmark

Session

Theme session S: Basin-scale dynamics at lower trophic levels in the North Atlantic ​

Abstract reference

S:13

Recommended citation

[Authors]. 2015. Habitat modelling of key copepods species in the Northwest Atlantic using depth-integrated data to model past and future changes in distribution and productivity. 2015 Annual Science Conference, Copenhagen, Denmark. CM 2015/S:13. https://doi.org/10.17895/ices.pub.25682769