Predicting avian herbivore responses to changing food availability and competition

Kevin A. Wood, Richard A. Stillman, Julia L. Newth, Rascha J.M. Nuijten, Geoff M. Hilton, Bart A. Nolet and Eileen C. Rees

Ecological Modelling, 2021, vol. 441, issue C

Abstract: Many species of large herbivore rely on agricultural land for their feeding habitats, but available food resources are highly variable in space and time. The conservation and management of farmland-dependant herbivores would therefore benefit from predictions about how species will respond to changes in their environment. We developed an individual-based model (IBM) to provide such predictions for three overwintering avian herbivore species that feed on agricultural land: Bewick's swans (Cygnus columbianus bewickii), whooper swans (Cygnus cygnus), and mute swans (Cygnus olor). Our validated model predicted how potential future changes in food availability and competition would affect (i) the proportion of the current swan population that could be supported, (ii) the proportion of swans that successfully departed on migration at the end of winter, (iii) swan daily foraging effort, and (iv) late winter crop biomasses. Regardless of competitor numbers or food availability, all individuals were predicted to avoid starvation and depart successfully. Individual swans offset higher competition and reduced food availability by increasing the proportion of daylight spent foraging. Our simulations indicate that swans have considerable capacity to buffer against losses of food resources and increased competition by increasing their foraging effort, but this may result in additional grazing damage to agricultural crops. Our findings suggest that the recent c.40% decline in Bewick's swan numbers was unlikely to be linked to changes in winter food resources or competition.

Keywords: Agent-based simulation; Agricultural landscape; Ecological forecasting; Food resources; Global environmental change; Land use change (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:441:y:2021:i:c:s0304380020304798

DOI: 10.1016/j.ecolmodel.2020.109421

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