Abstract
Bird counting inevitably suffers from imperfect detection, which varies across species, habitats, period of the day, and seasons. Although various modeling techniques have recently been developed to account for this phenomenon, the biological basis of natural variation in detection remains insufficiently known. This study examined the bird species’ detection rate throughout the day, considering their body mass and diet type, concerning the environment and weather characteristics. Species detection rates were significantly affected by the number of individuals of that species but were unrelated to body mass. Overall, species with the highest detection rate were Corn bunting, Blackbird, European robin, House sparrow and Common chiffchaff. Granivores-insectivores and insectivores showed significant differences in detection rates throughout the day among habitats, with higher detection rates in grasslands during the afternoon. Insectivores showed higher detection rates in farmland during midday (warmest time of the day). Granivores, omnivores and scavengers did not show changes in detection rates in different day periods. Such patterns in daily detection rates were significant even when considering abundance and total species richness in each community. Finally, cloudiness was unrelated to the overall detection rate of birds, while temperature and wind affected detection rates in some guilds. Our findings provide some advice for choosing a suitable ornithological sampling method by considering the avian communities composition in combination with the type of environment, the diet of bird species, and the period of the day.
Highlights
Birds are often used in ecological studies as potential bioindicators (Padoa-Schioppa et al, 2006; Drever et al, 2008; Morelli, 2015)
We detected 79 species belonging to four trophic guilds: 8 granivorous, 29 granivorous-insectivorous, 37 insectivorous and 5 omnivorous/scavengers (Supplementary Table 1)
The species inventory appeared nearly complete as the rarefaction curves reached asymptotes, and their confidence intervals covered or closely approximated the expected total richness calculated by the Chao2 estimator at most of the sites (Supplementary Figure 3)
Summary
Birds are often used in ecological studies as potential bioindicators (Padoa-Schioppa et al, 2006; Drever et al, 2008; Morelli, 2015). Point-count surveying is a popular method for collecting data on species distribution and estimation of indices of bird abundance (Bibby et al, 2000; Farnsworth et al, 2002). This method is commonly used for studies at several spatial scales—from local to regional studies and even nationwide monitoring programs (Fuller and Langslow, 1984; Surmacki and Tryjanowski, 2000; Budka and Kokocinski, 2015; Kwiecinski et al, 2017; Morelli et al, 2017). We can briefly mention the bias related to observers’ skills recognizing different bird species, especially when compounded over large spatial scales (Celis-Murillo et al, 2009)
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