Models that describe species distributions are valuable in guiding management decisions. We compared and combined two avian datasets during the 2010 breeding season in northern California, USA. These datasets were a large-scale avian diversity survey from McGrann and Furnas (2016; 2018) and combined data from Biological Information Serving Our Nation (BISON) and Global Biodiversity Information Facility (GBIF). Our objective was to compare the utility of these two datasets, that employ separate field protocols, to model habitat use for the Black-headed Grosbeak, Hairy Woodpecker, and Yellow-rumped Warbler, three common forest birds in our study area that occupy distinctive habitat types. We also tested whether combining the datasets together would create a model with greater generality over the study area and determine if the data will create response curves that explain certain relationships between environmental characteristics and species occurrences. We found that fine-scale data along a single, albeit extensive, transect built models that predicted suitability well for the section of trail, but did not predict occurrences well for areas beyond the trail in two of the three species. We also found that data from Biological Information Serving Our Nation (BISON) and Global Biodiversity Information Facility (GBIF) did not have the sampling structure required for finer scale modeling and lacked observations in areas that may be critical for sampling, such as fire-impacted areas. By combining these two datasets, we produced models that captured the range of these species throughout the study area, and we created response curves that explained anticipated habitat associations for each species.
Pruhsmeier, Holli N.; McGrann, Michael C.; and Graham, Jim
"Combined Use of Data From Avian Surveys Along the Pacific Crest Trail With Biodiversity Repositories to Model Habitat Suitability Throughout Northern California,"
IdeaFest: Interdisciplinary Journal of Creative Works and Research from Humboldt State University: Vol. 5
, Article 3.
Available at: https://digitalcommons.humboldt.edu/ideafest/vol5/iss1/3