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Full-Text Articles in Life Sciences
Pedigree Validation Using Genetic Markers In An Intensively-Managed Taonga Species, The Critically Endangered Kakī (Himantopus Novaezelandiae), Ashley Overbeek, Stephanie Galla, Liz Brown, Simon Cleland, Cody Thyne, Richard Maloney, Tammy Steeves
Pedigree Validation Using Genetic Markers In An Intensively-Managed Taonga Species, The Critically Endangered Kakī (Himantopus Novaezelandiae), Ashley Overbeek, Stephanie Galla, Liz Brown, Simon Cleland, Cody Thyne, Richard Maloney, Tammy Steeves
Biology Faculty Publications and Presentations
Many species recovery programmes use pedigrees to understand the genetic ancestry of individuals to inform conservation management. However, incorrect parentage assignment may limit the accuracy of these pedigrees and subsequent management decisions. This is especially relevant for pedigrees that include wild individuals, where misassignment may not only be attributed to human error, but also promiscuity (i.e. extra-pair parentage) or egg-dumping (i.e. brood parasitism). Here, we evaluate pedigree accuracy in the socially monogamous and critically endangered kakī (black stilt, Himantopus novaezelandiae) using microsatellite allele-exclusion analyses for 56 wild family groups across three breeding seasons (2014–2016, n= 340). We identified …
Improved Supervised Classification Of Accelerometry Data To Distinguish Behaviors Of Soaring Birds, Maitreyi Sur, Srisarguru Sridhar
Improved Supervised Classification Of Accelerometry Data To Distinguish Behaviors Of Soaring Birds, Maitreyi Sur, Srisarguru Sridhar
Biology Faculty Publications and Presentations
Soaring birds can balance the energetic costs of movement by switching between flapping, soaring and gliding flight. Accelerometers can allow quantification of flight behavior and thus a context to interpret these energetic costs. However, models to interpret accelerometry data are still being developed, rarely trained with supervised datasets, and difficult to apply. We collected accelerometry data at 140Hz from a trained golden eagle (Aquila chrysaetos) whose flight we recorded with video that we used to characterize behavior. We applied two forms of supervised classifications, random forest (RF) models and K-nearest neighbor (KNN) models. The KNN model was substantially …