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. 2013;8(1):e53371.
doi: 10.1371/journal.pone.0053371. Epub 2013 Jan 9.

Window area and development drive spatial variation in bird-window collisions in an urban landscape

Stephen B Hager  1 , Bradley J Cosentino, Kelly J McKay, Cathleen Monson, Walt Zuurdeeg, Brian Blevins
Affiliations

Window area and development drive spatial variation in bird-window collisions in an urban landscape

Stephen B Hager et al. PLoS One. 2013.

Abstract

Collisions with windows are an important human-related threat to birds in urban landscapes. However, the proximate drivers of collisions are not well understood, and no study has examined spatial variation in mortality in an urban setting. We hypothesized that the number of fatalities at buildings varies with window area and habitat features that influence avian community structure. In 2010 we documented bird-window collisions (BWCs) and characterized avian community structure at 20 buildings in an urban landscape in northwestern Illinois, USA. For each building and season, we conducted 21 daily surveys for carcasses and nine point count surveys to estimate relative abundance, richness, and diversity. Our sampling design was informed by experimentally estimated carcass persistence times and detection probabilities. We used linear and generalized linear mixed models to evaluate how habitat features influenced community structure and how mortality was affected by window area and factors that correlated with community structure. The most-supported model was consistent for all community indices and included effects of season, development, and distance to vegetated lots. BWCs were related positively to window area and negatively to development. We documented mortalities for 16/72 (22%) species (34 total carcasses) recorded at buildings, and BWCs were greater for juveniles than adults. Based on the most-supported model of BWCs, the median number of annual predicted fatalities at study buildings was 3 (range = 0-52). These results suggest that patchily distributed environmental resources and levels of window area in buildings create spatial variation in BWCs within and among urban areas. Current mortality estimates place little emphasis on spatial variation, which precludes a fundamental understanding of the issue. To focus conservation efforts, we illustrate how knowledge of the structural and environmental factors that influence bird-window collisions can be used to predict fatalities in the broader landscape.

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Conflict of interest statement

Competing Interests: The authors have the following interests. Mr. McKay is the owner of BioEco Research and Monitoring Center. He conducts consulting work for businesses and agencies requiring ecological assessments of birds. Mr. McKay has never consulted on nor anticipates future business related to the research in this manuscript. This does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials.

Figures

Figure 1
Figure 1. Effect of proportion of developed land on avian community structure.
Relationships of avian (A) abundance, (B) richness, and (C) diversity are characterized for winter (closed circles), spring (closed triangles), summer (open circles), and fall (open triangles). Best-fit lines are indicated for each season and are based on parameter estimates from the most-supported models of each response variable (see Table 1).
Figure 2
Figure 2. Effect of distance to vegetated lots on avian community structure.
Relationships of avian (A) abundance, (B) richness, and (C) diversity are characterized for winter (closed circles), spring (closed triangles), summer (open circles), and fall (open triangles). Best-fit lines are indicated for each season and are based on parameter estimates from the most-supported models of each response variable (see Table 1).
Figure 3
Figure 3. Factors driving bird-window collisions.
The most-supported model explaining mortality included the effects of (A) window area and (B) development (% impervious surfaces) (see Table 3).
Figure 4
Figure 4. Predicted annual fatalities for the study area in Illinois, USA.
Predicted fatalities were spatially interpolated from 1,956 model buildings using ordinary kriging.
See this image and copyright information in PMC

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