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Developing and testing a landscape habitat suitability model for the American marten (Martes americana) in the Cascades mountains of California

Informally Refereed

Abstract

We used field surveys and Geographic Information System data to identify landscape-scale habitat associations of American martens (Martes americana) and to develop a model to predict their occurrence in northeastern California. Systematic surveys using primarily enclosed track plates, with 10-km spacing, were conducted across a 27,700 km2 area of largely forested, mountain terrain. Martens were detected at 20/184 (10.8%) of the sample units, aggregated in three distinct regions. We investigated habitat selection at multiple scales using circular assessment areas of 3, 20, and 80 km2. The model for the largest assessment area best fit the data and included the following predictors: amount of reproductive habitat, number of habitat patches and land ownership category. These results support the hypothesis that martens select habitat based upon broad scale landscape conditions and that these conditions vary with ownership. We tested the model using an independent set of data, collected primarily during the winter. Poor fit of the test data in some locations raised concerns that our model, which was developed using data collected during the snow-free season, may not predict winter distribution well. We are investigating possible causes for the seasonal variation and until they can be incorporated our model represents a conservative view of marten habitat suitability based on summer occupancy. During the summer months, which is the reproductive season, martens are predicted to occur largely in relatively undisturbed landscapes where high-elevation, late-successional forests are common.

Citation

Kirk, T.A.; Zielinski, W.J. (2009) Developing and testing a landscape habitat suitability model for the American marten (Martes americana) in the Cascades mountains of California. Landscape Ecol 24:(6)759-773.
Citations
https://www.fs.usda.gov/research/treesearch/33456