Habitat models to predict wetland bird occupancy influenced by scale, anthropogenic disturbance, and imperfect detection

Wesley J. Glisson, Courtney J. Conway, Christopher P. Nadeau, Kathi L. Borgmann

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


Abstract. Understanding species–habitat relationships for endangered species is critical for their conservation. However, many studies have limited value for conservation because they fail to account for habitat associations at multiple spatial scales, anthropogenic variables, and imperfect detection. We addressed these three limitations by developing models for an endangered wetland bird, Yuma Ridgway’s rail (Rallus obsoletus yumanensis), that examined how the spatial scale of environmental variables, inclusion of anthropogenic disturbance variables, and accounting for imperfect detection in validation data influenced model performance. These models identified associations between environmental variables and occupancy. We used bird survey and spatial environmental data at 2473 locations throughout the species’ U.S. range to create and validate occupancy models and produce predictive maps of occupancy. We compared habitat-based models at three spatial scales (100, 224, and 500 m radii buffers) with and without anthropogenic disturbance variables using validation data adjusted for imperfect detection and an unadjusted validation dataset that ignored imperfect detection. The inclusion of anthropogenic disturbance variables improved the performance of habitat models at all three spatial scales, and the 224-m-scale model performed best. All models exhibited greater predictive ability when imperfect detection was incorporated into validation data. Yuma Ridgway’s rail occupancy was negatively associated with ephemeral and slow-moving riverine features and high-intensity anthropogenic development, and positively associated with emergent vegetation, agriculture, and low-intensity development. Our modeling approach accounts for common limitations in modeling species–habitat relationships and creating predictive maps of occupancy probability and, therefore, provides a useful framework for other species.

Original languageEnglish (US)
Article numbere01837
Issue number6
StatePublished - Jun 2017

Bibliographical note

Funding Information:
Funding was provided by the Department of Defense Legacy Program (no. W9132T-12-2-0026), the Gap Analysis Program of the U.S. Geological Survey, the Nebraska Game and Parks Commission, and the U.S. Fish and Wildlife Service. Thomas Laxson helped with processing spatial data. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. government

Publisher Copyright:
© 2017 Glisson et al.


  • Anthropogenic disturbance
  • Area under the curve (AUC)
  • Detection probability
  • Marsh bird
  • Model validation
  • Multi-scale
  • National Wetland Inventory
  • Occupancy model
  • Species distribution model
  • Yuma Ridgway’s rail


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