Evaluating the ability of occurrence models to predict nest locations and associated vegetation

Abstract

Occurrence models are frequently used to infer characteristics of habitat and inform management plans for large areas, but the extent to which these models predict reproduction, or the environmental characteristics associated with reproduction, is uncertain. We examined whether occurrence models based on point‐count data, and vegetation attributes within 50 m of presences, predicted the locations where birds were nesting in the Great Basin, USA. This work has practical relevance given that occurrence data require less time and effort to collect than direct measures of reproduction. We hypothesized that occurrence models would better characterize where two nest stratum generalists, Brewer's Sparrow Spizella breweri and Green‐tailed Towhee Pipilo chlorurus, nest than where a nest stratum specialist, American Dusky Flycatcher Empidonax oberholseri, nests. First, we compared which environmental covariates were associated with occurrence, via a model fitted to point‐count data, and nest locations, via a model fitted to data from confirmed nests. Second, we used data on the vegetation within 50 m of known nests to evaluate whether predictions from our occurrence model accurately classified the presence of nests. Third, we examined whether vegetation within 5 m of a known nest differed from vegetation at randomly chosen locations of equal size within 20–80 m of the nest. Occurrence models classified nest locations with relatively high accuracy for Brewer's Sparrow and American Dusky Flycatcher, and with moderate accuracy for Green‐tailed Towhee. Vegetation within 5 m of nests differed from that of random locations within 20–80 m, suggesting that even the nest stratum generalists based nest selection on fine‐grained attributes. Models that rely on point‐count data to examine species–habitat relationships assume that occupancy indicates breeding activity. Our results suggest that for some species, this is a valid assumption, although it is probably conditional on a well‐fitted occurrence model.

Multiple‐region,N‐mixture community model to assess associations of riparian area, fragmentation, and species richness

“…In some cases, measures of the species composition of riparian vegetation, rather than total area of riparian vegetation, may be associated strongly with species richness of riparian birds (Strong & Bock, 1990). Previous work has demonstrated that finer resolution characterizations of riparian vegetation, especially vertical structure and floristics, improved inferences about occupancy dynamics and nesting of riparian bird species in the Great Basin (Dickson et al, 2009;Fleishman et al, 2014;Fogarty et al, 2022). There is substantial uncertainty on how riparian areas in the Great Basin, and other arid systems, will respond to the direct and indirect effects of increasing levels of atmospheric CO 2 , and future land-use change and climate may interact to produce heterogeneous changes in riparian areas across space (Albano et al, 2020;Cayan et al, 2013;Snyder et al, 2019).…”