2020 ESA Annual Meeting (August 3 - 6)

PS 31 Abstract - Leveraging GIS platforms to conduct landscape scale avian occupancy analysis

Elizabeth Moore1, Scott Gibson1, Russell Norvell1, Liza Rossi2, Scott Somershoe3 and Jon Runge2, (1)Utah Division of Wildlife, (2)Colorado Parks and Wildlife, (3)U.S. Fish & Wildlife Service
Background/Question/Methods

Pinyon jay (Gymnorhinus cyanocephalus) populations declined considerably across their breeding range over the past 50 years. We know little about the cause of this decline because the social behavior of pinyon jays makes them difficult to study. Specifically, locating nesting colonies is challenging because pinyon jays have large home ranges (3000-5000 ha), occupy different areas of their home range throughout the annual cycle, frequently break into sub-flocks based on age or breeding condition, and can fly far from their home range outside of their breeding season. To understand pinyon jay habitat requirements and population dynamics we developed a rigorous, repeatable method to detect pinyon jays and nesting colonies. To set up our survey design and collect field data, we leveraged the capabilities of multiple geographic information systems (GIS) platforms including R, ArcGIS Pro, and ERSI mobile applications. First, we divided our study area into 3 strata based on the number of previous pinyon jay observations in public and agency datasets and equally divided our sampling effort between strata. Second, we identified components of suitable habitat for pinyon jays based on expert opinion and used available GIS layers to omit cells with less than 20% habitat and less than 10 km of roads. Third, we used R to select a spatially balanced survey sample (Generalized Random Tessellation Stratified). Finally, we used ESRIs Survey123, Collector, and Web AppBuilder to collect and submit field data, conduct quality control, and to host shared data.

Results/Conclusions

We surveyed 70 grid cells in Colorado and Utah during 2019 and found pinyon jay colonies in 53 (75%) surveyed cells and evidence of breeding in 22 (31%) surveyed cells. Using multiple GIS platforms to set up our survey design and collect field data allowed us to efficiently survey a large study area and share survey results among partners for analyses. During our first season, we modeled occupancy to be 94% (95% CI [33-100%] ). In 2020, we will repeat our methods over an expanded study area. Our systematic approach to detect pinyon jay and locate colonies will inform conservation and land management decisions in pinyon-juniper woodlands that may be subject to competing land management goals.