Remotely sensed forest understory density and nest predator occurrence interact to predict suitable breeding habitat and the occurrence of a resident boreal bird species ...
Habitat suitability models (HSM) based on remotely sensed data are useful tools in conservation work. However, they typically use species occurrence data rather than robust demographic variables, and their predictive power is rarely evaluated. These shortcomings can result in misleading guidance for...
| Main Authors: | , , , , |
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| Format: | Dataset |
| Language: | English |
| Published: |
Dryad
2020
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| Subjects: | |
| Online Access: | https://dx.doi.org/10.5061/dryad.p2ngf1vmq https://datadryad.org/stash/dataset/doi:10.5061/dryad.p2ngf1vmq |
| Summary: | Habitat suitability models (HSM) based on remotely sensed data are useful tools in conservation work. However, they typically use species occurrence data rather than robust demographic variables, and their predictive power is rarely evaluated. These shortcomings can result in misleading guidance for conservation. Here, we develop and evaluate a HSM based on correlates of long term breeding success of an open nest building boreal forest bird, the Siberian jay. In our study site in northern Sweden, nest failure of this permanent resident species is driven mainly by visually hunting corvids that are associated with human settlements. Parents rely on understory nesting cover as protection against these predators. Accordingly, our HSM includes a light detection and ranging (LiDAR) based metric of understory density around the nest and the distance of the nest to the closest settlement to predict breeding success. It reveals that a high understory density 15-80 m around nests is associated with increased breeding ... : See the methods part of the article for more information. ... |
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