Seasonal food webs with migrations: multi-season models reveal indirect species interactions in the Canadian Arctic tundra

• Published in: Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
• Main Authors: Hutchison, Chantal, Guichard, Frédéric, Legagneux, Pierre, Gauthier, Gilles, Bêty, Joël, Berteaux, Dominique, Fauteux, Dominique, Gravel, Dominique
• Other Authors: Centre d'Etudes Nordiques et Département de Biologie, Université Laval Québec (ULaval), Centre d'Études Biologiques de Chizé - UMR 7372 (CEBC), Université de La Rochelle (ULR)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2020
• Subjects: [SDE]Environmental Sciences; Arctic; Climate change; Global warming; Tundra
• Online Access: https://hal.archives-ouvertes.fr/hal-03024995; https://doi.org/10.1098/rsta.2019.0354

International audience Models incorporating seasonality are necessary to fully assess the impact of global warming on Arctic communities. Seasonal migrations are a key component of Arctic food webs that still elude current theories predicting a single community equilibrium. We develop a multi-season model of predator–prey dynamics using a hybrid dynamical systems framework applied to a simplified tundra food web (lemming–fox–goose–owl). Hybrid systems models can accommodate multiple equilibria, which is a basic requirement for modelling food webs whose topology changes with season. We demonstrate that our model can generate multi-annual cycling in lemming dynamics, solely from a combined effect of seasonality and state-dependent behaviour. We compare our multi-season model to a static model of the predator–prey community dynamics and study the interactions between species. Interestingly, including seasonality reveals indirect interactions between migrants and residents not captured by the static model. Further, we find that the direction and magnitude of interactions between two species are not necessarily accurate using only summer time-series. Our study demonstrates the need for the development of multi-season models and provides the tools to analyse them. Integrating seasonality in food web modelling is a vital step to improve predictions about the impacts of climate change on ecosystem functioning.