Abstract

Populations of Atlantic salmon are crashing across most of its natural range: understanding the underlying causes and predicting these collapses in time to intervene effectively are urgent ecological and socioeconomic priorities. Current management techniques rely on phenomenological analyses of demographic population time-series and thus lack a mechanistic understanding of how and why populations may be declining. New multidisciplinary approaches are thus needed to capitalize on the long-term, large-scale population data that are currently scattered across various repositories in multiple countries, as well as marshaling additional data to understand the constraints on the life cycle and how salmon operate within the wider food web. Here, we explore how we might combine data and theory to develop the mechanistic models that we need to predict and manage responses to future change. Although we focus on Atlantic salmon-given the huge data resources that already exist for this species-the general principles developed here could be applied and extended to many other species and ecosystems.

Keywords

Atlantic salmon (Salmo salar); marine and freshwater fisheries; ecosystem-based management (EBM); matrix projection models; metabolic theory of ecology (MTE); life-stage models; size structure

Published in

Frontiers in Ecology and Evolution
2021, Volume: 9, article number: 675261
Publisher: FRONTIERS MEDIA SA

SLU Authors

• Belgrano, Andrea

  • Department of Aquatic Resources (SLU Aqua), Swedish University of Agricultural Sciences
    

Sustainable Development Goals

Conserve and sustainably use the oceans, seas and marine resources for sustainable development


UKÄ Subject classification

Ecology


Publication identifier

DOI: https://doi.org/10.3389/fevo.2021.675261

Permanent link to this page (URI)

https://res.slu.se/id/publ/115411