Modeling habitat suitability is beneficial for management and conservation of a species. Although data-rich models are commonly used, opinion-based models may be a beneficial alternative to estimate suitable habitat locations. Despite the increasing use of habitat models, few studies have linked habitat model covariates (i.e., land cover, weather, and normalized difference vegetation indexes (NDVI)) to demographic parameters. This study evaluates model performance and transferability of maximum entropy (MaxEnt) and expert opinion models for predicting American beaver (Castor canadensis) distribution in the southeastern US. I also investigated the relationship of environmental and habitat model covariates to beaver survival. The model’s predictive performance and transferability were evaluated using the area under the curve (AUC) index. Both model approaches performed well at predicting beaver presence. While MaxEnt had better performance, the expert models predicted greater areas as suitable for beaver. Beaver survival was estimated for northern Alabama and was found to be influenced by NDVI and weather covariates in this study.
| Identifer | oai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-5773 |
| Date | 14 December 2018 |
| Creators | Barela, Isidro A |
| Publisher | Scholars Junction |
| Source Sets | Mississippi State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
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