Thu, Aug 18, 2022: 5:00 PM-6:30 PM
ESA Exhibit Hall
Background/Question/Methods: eBird, a large citizen science project, has made massive amounts of data available to ornithologists. While eBird data has primarily been applied at continental scales to minimize the sources of error associated with citizen science projects, small-scale application has nonetheless accurately predicted novel insights. We apply eBird data to identify and explain small, previously undocumented gaps in the range of the Chestnut-backed Chickadee (CBCH; Poecile rufescens, Townsend 1837). eBird-derived range maps indicate the absence of CBCH in parts of the Greater Vancouver Region (GVR), British Columbia, Canada, and in the Willamette Valley of Washington and Oregon, United States, but the persistence of a congeneric, the Black-capped Chickadee (BCCH; Poecile atricapillus L. 1766), despite their co-occurrence in the surrounding area. We ask whether these absence predictions for CBCH are supported by more robust point-count methodology, and whether landscape factors related to cavity-nesting substrates may generate this pattern. Using checklists from the 2021 eBird Basic Dataset to examine CBCH and BCCH detections around these regions, we performed chi-squared tests to assess habitat associations for detections of each species. In May-June 2022, we will conduct point-count transects and apply land-satellite data to verify these distribution patterns and identify relevant landscape features.
Results/Conclusions: Analyses of eBird data from the GVR support pockets of absence of CBCH. In the 1004 checklists with CBCH and/or BCCH detections in the GVR from 2008-2019 (“complete” checklists, < 10 observers, < 5km travelled, < 1.5hr duration), BCCH was detected in 986 checklists while CBCH was only detected in 138 checklists. Of the 986 checklists with BCCH detections, 25.2% were in large ( > 0.5 km2) urban parks, while 52.2% of the 138 checklists with CBCH detections were in large urban parks. The association between species and detection in large parks were found to be significantly different than expected if the species were randomly distributed (χ2 = 42.089, p = 8.723-11). Many CBCH detections outside of parks were in suburban areas, near pockets of forest outside the GVR, while BCCH detections occurred more evenly across the cityscape. These preliminary results mirror established species-habitat relationships, where abundance of CBCH decreases with forest cover in urban areas, while BCCH are more tolerant of land conversion. While these data provide insight into the gap in CBCH distribution in the GVR, our point-counts will allow us to test whether these eBird-derived conclusions are reflected in more robust protocols.
Results/Conclusions: Analyses of eBird data from the GVR support pockets of absence of CBCH. In the 1004 checklists with CBCH and/or BCCH detections in the GVR from 2008-2019 (“complete” checklists, < 10 observers, < 5km travelled, < 1.5hr duration), BCCH was detected in 986 checklists while CBCH was only detected in 138 checklists. Of the 986 checklists with BCCH detections, 25.2% were in large ( > 0.5 km2) urban parks, while 52.2% of the 138 checklists with CBCH detections were in large urban parks. The association between species and detection in large parks were found to be significantly different than expected if the species were randomly distributed (χ2 = 42.089, p = 8.723-11). Many CBCH detections outside of parks were in suburban areas, near pockets of forest outside the GVR, while BCCH detections occurred more evenly across the cityscape. These preliminary results mirror established species-habitat relationships, where abundance of CBCH decreases with forest cover in urban areas, while BCCH are more tolerant of land conversion. While these data provide insight into the gap in CBCH distribution in the GVR, our point-counts will allow us to test whether these eBird-derived conclusions are reflected in more robust protocols.