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Modeling habitat for Marbled Murrelets on the Siuslaw National Forest, Oregon, using lidar data

March 28, 2018

Habitat models using lidar-derived variables that quantify fine-scale variation in vegetation structure can improve the accuracy of occupancy estimates for canopy-dwelling species over models that use variables derived from other remote sensing techniques. However, the ability of models developed at such a fine spatial scale to maintain accuracy at regional or larger spatial scales has not been tested. We tested the transferability of a lidar-based habitat model for the threatened Marbled Murrelet (Brachyramphus marmoratus) between two management districts within a larger regional conservation zone in coastal western Oregon. We compared the performance of the transferred model against models developed with data from the application location. The transferred model had good discrimination (AUC = 0.73) at the application location, and model performance was further improved by fitting the original model with coefficients from the application location dataset (AUC = 0.79). However, the model selection procedure indicated that neither of these transferred models were considered competitive with a model trained on local data. The new model trained on data from the application location resulted in the selection of a slightly different set of lidar metrics from the original model, but both transferred and locally trained models consistently indicated positive relationships between the probability of occupancy and lidar measures of canopy structural complexity. We conclude that while the locally trained model had superior performance for local application, the transferred model could reasonably be applied to the entire conservation zone.

Citation Information

Publication Year 2018
Title Modeling habitat for Marbled Murrelets on the Siuslaw National Forest, Oregon, using lidar data
DOI 10.3133/ofr20181035
Authors Joan C. Hagar, Ramiro Aragon, Patricia Haggerty, Jeff P. Hollenbeck
Publication Type Report
Publication Subtype USGS Numbered Series
Series Title Open-File Report
Series Number 2018-1035
Index ID ofr20181035
Record Source USGS Publications Warehouse
USGS Organization Forest and Rangeland Ecosystem Science Center