Dataset Information

Constant and seasonal drivers of bird communities in a wind farm: implications for conservation.

ABSTRACT: Background. One of the most difficult challenges for conservation biology is to reconcile growing human demands for resources with the rising need for protecting nature. Wind farms producing renewable energy have been recognised to be a threat for birds, but clear directives for environmental planning are still missing. Methods. Point counts were performed to study the relationship between eight environmental variables and bird populations in different parts of a year on the largest Polish wind farm between March 2011 and February 2013. Variables potentially related to species richness (Chao 1 estimator) and the abundance of the entire bird community as well as five selected farmland species were analysed with the use of generalized linear mixed models. Results. Some associations between the studied variables and bird populations were season/year specific, while others had a constant direction (positive or negative) across seasons and/or years. The latter were distance to the nearest turbine, field size, number of wind turbines, proximity of settlements and water bodies. Spatial autocorrelation and counting time were significantly correlated with bird population estimates but the directions of these relationships varied among seasons and years. Associations between abundance of individual species and environmental variables were species-specific. Conclusions. The results demonstrated a constant negative relationship between wind turbine proximity and bird numbers. Other environmental variables, such as field size, proximity of settlements and water bodies that also had constant associations with bird populations across seasons may be taken into account when minimizing adverse effects of wind farm development on birds or choosing optimal locations of new turbines.

SUBMITTER: Rosin ZM

PROVIDER: S-EPMC4957985 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Bird-building collisions are a major source of wild bird mortality, with hundreds of millions of fatalities each year in the United States and Canada alone. Here, we use two decades of daily citizen science monitoring to characterize day-to-day variation in building collisions and determine the factors that predict the highest risk times in two North American cities. We use these analyses to evaluate three potential causes of increased collision risk: heightened migration traffic during benign weather, increased navigational and flight errors during inclement weather, and increased errors in response to highly directional sunlight that enhances reflected images. The seasonal phenology of collisions was consistent across sites and years, with daily collision rates approximately twofold higher in autumn as compared to spring. During both migration seasons, collision risk was best predicted by the weather conditions at dawn. In spring, peak collision risk occurs on days with warm temperatures, south winds, and a lack of precipitation at dawn. In autumn, peak collision occurs on days with cool temperatures, north winds, high atmospheric pressure, a lack of precipitation, and clear conditions with high visibility. Based on these results, we hypothesize that collisions are influenced by two main weather-driven mechanisms. First, benign weather at dawn and winds that are favorable for migration cause an increase in migration traffic in both spring and autumn, creating greater opportunity for collisions to occur. Second, for autumnal migrants, cold clear conditions may cause an additional increase in collision risk. We propose that these conditions may be particularly hazardous in autumn because of the high abundance of naïve and diurnal migrants at that time of year. Our analysis also establishes that a relatively small proportion of days (15%) are responsible for 50% of the total collision mortality within a season, highlighting the importance of targeting mitigation strategies to the most hazardous times.

Dataset Information

Constant and seasonal drivers of bird communities in a wind farm: implications for conservation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets