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Habitat classification modelling with incomplete data: Pushing the habitat envelope


Zarnetske, 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.

Habitat 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, thresholdindependent receiver operating characteristic (ROC) plots, adjusted deviance (D2 adj), and crossvalidation, and were also assessed for ecological relevance. For all cases, habitat envelopebased 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.

Keywords: Accipiter gentilis atricapillus, Forest Inventory and Analysis (FIA), habitat classification model, habitat envelope, Landfire, management indicator species, Northern Goshawk, pseudo-absence


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Title: RMRS Other Publications: Habitat classification modelling with incomplete data: Pushing the habitat envelope
Electronic Publish Date: November 7, 2007
Last Update:
November 7, 2007

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