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Explaining and predicting animal migration under global change.
- Source :
- Diversity & Distributions; Feb2024, Vol. 30 Issue 2, p1-11, 11p
- Publication Year :
- 2024
-
Abstract
- Many migratory species are declining due to global environmental change. Yet, their complex annual cycles make unravelling the impacts of potential drivers such as climate and land‐use change on migrations a major challenge. Identifying where, when and how threatening processes impact species' migratory journeys and population dynamics is crucial for identifying effective conservation actions. Here, we describe how a new migration modelling framework – Spatially explicit Adaptive Migration Models (SAMMs) – can simulate the optimal behavioural decisions required to migrate across open land‐ or seascapes varying in character over space and time, without requiring predefined behavioural rules. Models of adaptive behaviour have been used widely in theoretical ecology but have great untapped potential in real‐world contexts. Applying adaptive behaviour models across open environments will allow users to explore how migratory species may adapt their routes and usage of intermediate sites in response to environmental change. We outline how SAMMs can be used to model migratory journeys through aerial, terrestrial and aquatic environments, demonstrating their potential using a case study on the common cuckoo (Cuculus canorus) and comparing modelled to observed behaviours. SAMMs offer a tool to identify the key threats faced by migratory species, how they could adapt to future migratory journeys in response to changing environmental conditions and the consequences of not being able to adapt to change. [ABSTRACT FROM AUTHOR]
- Subjects :
- GLOBAL environmental change
MIGRATORY animals
POPULATION dynamics
CLIMATE change
Subjects
Details
- Language :
- English
- ISSN :
- 13669516
- Volume :
- 30
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Diversity & Distributions
- Publication Type :
- Academic Journal
- Accession number :
- 174712855
- Full Text :
- https://doi.org/10.1111/ddi.13797