Clustering Community Science Data to Infer Migratory Connectivity Patterns for Migratory Songbirds in the Western Hemisphere
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Migratory connectivity describes the spatial linkage between individuals through time and is necessary for full annual cycle conservation. However, conventional methods used to study migratory connectivity can be expensive and expertise intensive. In Chapter 2, we infer migratory connectivity patterns for songbirds using relative abundance models created from eBird, a global community science program, and an underlying broad-scale parallel migration assumption. We compare migratory connectivity inferences for two species with previously described connectivity estimates from the literature. We find that our method is a fast and inexpensive way to infer broad patterns on connectivity for these two species, though it cannot predict leapfrog migration or extreme deviations from parallel migration. In Chapter 3, a literature review of migration patterns shows that broad-scale parallel migration is commonly observed for songbirds in the Western hemisphere, and thus the methodology presented in Chapter 2 should be widely applicable to other species.
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Copyright © 2020 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.
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- 2020
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vincent-clusteringcommunitysciencedatatoinfermigratory.pdf | 2023-05-05 | Public | Download |