Publisher | Wildfowl & Wetlands Trust |
Source | Brian Tavernia |
Volume / Issue | 65 |
Pages | 100-120 |
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Article Link | http://wildfowl.wwt.org.uk/index.php/wildfowl/article/view/2628 |
PDF Link | http://wildfowl.wwt.org.uk/index.php/wildfowl/article/view/2628/1750 |
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Tags | ducks, migration |
Other | Print ISSN: 0954-6324, Electronic ISSN: 2052-6458 |
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Abstract | The development of robust modelling techniques to derive inferences from largescale migratory bird monitoring data at appropriate scales has direct relevance to their management. The Integrated Waterbird Management and Monitoring programme (IWMM) represents one of the few attempts to monitor migrating waterbirds across entire flyways using targeted local surveys. This dataset included 13,208,785 waterfowl (eight Anas species) counted during 28,000 surveys at nearly 1,000 locations across the eastern United States between autumn 2010 and spring 2013 and was used to evaluate potential predictors of waterfowl abundance at the wetland scale. Mixed-effects, loglinear models of local abundance were built for the Atlantic and Mississippi flyways during spring and autumn migration to identify factors relating to habitat structure, forage availability, and migration timing that influence target dabbling duck species abundance. Results indicated that migrating dabbling ducks responded differently to environmental factors. While the factors identified demonstrated a high degree of importance, they were inconsistent across species, flyways and seasons. Furthermore, the direction and magnitude of the importance of each covariate group considered here varied across species. Given our results, actionable policy recommendations are likely to be most effective if they consider species-level variation within targeted taxonomic units and across management areas. The methods implemented here can easily be applied to other contexts, and serve as a novel investigation into local-level population patterns using data from broad-scale monitoring programmes. |
Created: 12/14/2017 10:29 AM (ET)
Modified: 12/14/2017 10:29 AM (ET)