Explaining and predicting animal migration under global change
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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 speciesâ migratory journeys and population dynamics is crucial for identifying effective conservation actions. Here, we describe how a new migration modelling framework â Spatially-explicit Adaptive Migration Models (SAMMs) â 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 flexibility in how migratory strategies respond to environmental change and the ..., , Example code for running Spatially-explicit Adaptive Migration Models (SAMMs) is provided in R scripts, # Explaining and predicting animal migration under global change
This README file was generated on 10th November 2023 by Christine Howard
## GENERAL INFORMATION
1. Title of the Dataset: Explaining and predicting animal migration under global change
2. Author Information
A. Principal Investigator Contact Information
Names: Steve G. Willis
Institution: Durham University
Address: Department of Biosciences, Durham University, South Road, Durham, UK, DH1 3LE
Email: [s.g.willis@durham.ac.uk](mailto:s.g.willis@durham.ac.uk)
B. Associate or Co-Investigator Contact Information
Names: Christine Howard
Institution: Durham University
Address: Department of Biosciences, Durham University, South Road, Durham, UK, DH1 3LE
Email: [christine.howard@durham.ac.uk](mailto:christine.howard@durham.ac.uk)
3. Date of data collection (single date, range, approximate date): 2012-2016
4. Geographic location of data collection: Europe and Africa
5. Information abou...
创建时间：
2025-07-31
