Skip to Main Content
Habitat classification modelling with incomplete data: Pushing the habitat envelopeAuthor(s): Phoebe L. Zarnetske; Thomas C. Edwards; Gretchen G. Moisen
Source: Ecological Applications. 17(6): 1714-1726.
Publication Series: Miscellaneous Publication
PDF: View PDF (385 B)
DescriptionHabitat classification models (HCMs) are invaluable tools for species conservation, land-use planning, reserve design, and metapopulation assessments, particularly at broad spatial scales. However, species occurrence data are often lacking and typically limited to presence points at broad scales. This lack of absence data precludes the use of many statistical techniques for HCMs. One option is to generate pseudo-absence points so that the many available statistical modeling tools can be used. Traditional techniques generate pseudoabsence points at random across broadly defined species ranges, often failing to include biological knowledge concerning the species-habitat relationship. We incorporated biological knowledge of the species-habitat relationship into pseudo-absence points by creating habitat envelopes that constrain the region from which points were randomly selected. We define a habitat envelope as an ecological representation of a species, or species feature's (e.g., nest) observed distribution (i.e., realized niche) based on a single attribute, or the spatial intersection of multiple attributes. We created HCMs for Northern Goshawk (Accipiter gentilis atricapillus) nest habitat during the breeding season across Utah forests with extant nest presence points and ecologically based pseudo-absence points using logistic regression. Predictor variables were derived from 30-m USDA Landfire and 250-m Forest Inventory and Analysis (FIA) map products. These habitat-envelope-based models were then compared to null envelope models which use traditional practices for generating pseudo-absences. Models were assessed for fit and predictive capability using metrics such as kappa, threshold-independent receiver operating characteristic (ROC) plots, adjusted deviance (D2 adj), and cross-validation, and were also assessed for ecological relevance. For all cases, habitat envelope-based models outperformed null envelope models and were more ecologically relevant, suggesting that incorporating biological knowledge into pseudo-absence point generation is a powerful tool for species habitat assessments. Furthermore, given some a priori knowledge of the species-habitat relationship, ecologically based pseudo-absence points can be applied to any species, ecosystem, data resolution, and spatial extent.
- You may send email to email@example.com to request a hard copy of this publication.
- (Please specify exactly which publication you are requesting and your mailing address.)
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
CitationZarnetske, Phoebe L.; Edwards, Thomas C., Jr.; Moisen, Gretchen G. 2007. Habitat classification modelling with incomplete data: Pushing the habitat envelope. Ecological Applications. 17(6): 1714-1726.
KeywordsAccipiter gentilis atricapillus, Forest Inventory and Analysis (FIA), habitat classification model, habitat envelope, Landfire, management indicator species, Northern Goshawk, pseudo-absence
- Modeling forest bird species' likelihood of occurrence in Utah with Forest Inventory and Analysis and Landfire map products and ecologically based pseudo-absence points
- Invasive Species Distribution Modeling (iSDM): Are absence data and dispersal constraints needed to predict actual distributions?
- Evaluating habitat suitability models for nesting white-headed woodpeckers in unburned forest
XML: View XML