Locating and monitoring nests are among the most widely used approaches in studies of avian ecology, evolution, and conservation. While several papers outline “best practices” for nest studies, nest-searching techniques are seldom standardized in field investigations because observers generally use strategies that work best for them. In this study, I examined if field observers differed in the cues they used to locate nests, the species they found, and the fate of their nests (i.e., successful or failed), and the extent to which nest-searching cues were associated with either nest fate or vegetation characteristics surrounding the nest. My field assistants and I monitored 355 songbird nests on 10 forested sites in central Pennsylvania in 1998–99. Parental behavior was the most frequently used cue for locating nests (41%), followed by systematic searching of nesting substrate (37%). Accidental flushing of the parent (5%) and luck (17%) were involved in fewer located nests. Field observers differed in the cues they used to find nests, and these nest-searching cues were associated with finding certain species. In addition, estimates of nesting success (percentage of nests fledging young) differed among field observers by up to 2.35×. Nest-searching cues were related to nest-placement (e.g., nest height) and vegetation characteristics (e.g., leaf litter) within nest-patches for Ovenbirds (Seiurus aurocapillus), Red-eyed Vireos (Vireo olivaceus), and Scarlet Tanagers (Piranga olivacea), although cues were not significantly related to the fate of nests. Overall, nest-searching cues were associated with nest placement, nest-patch habitat, and species composition of nest samples, all of which can ultimately influence findings from nesting studies. Consequently, investigators should exercise caution when allocating individual effort across experimental units and consider assigning each observer to ≥1 treatment, multiple observers to each site, and addressing nest-patch and nest-placement differences among cues through training and data analysis.
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Vol. 75 • No. 1