Assessing accuracy of GAP and LANDFIRE land cover datasets in winter habitats used by greater sage-grouse in Idaho and Wyoming, USA

Remotely sensed land cover datasets have been increasingly employed in studies of wildlife habitat use. However, meaningful interpretation these is dependent on how accurately they estimate features that are important to wildlife. We evaluated the accuracy GAP dataset, which commonly used classify broad categories (e.g., vegetation communities) and LANDFIRE datasets, classifies narrower plant species) structural vegetation. To evaluate accuracy, we compared classification types estimates percent height sagebrush (Artemisia spp.) derived from field-collected data winter habitats by greater sage-grouse (Centrocercus urophasianus). Accuracy was type dataset as well spatial scale (point, 500-m, 1-km) biological level (community versus dominant investigated. had highest overall (49.8%) for (39.1% community-level; 31.9% species-level). Percent were not estimated dataset. Our results suggest researchers must be cautious when applying or narrow predict within sagebrush-dominated landscapes. conclude ground-truthing critical successful application landscape-scale evaluations management planning, particularly use relatively rare what available.