Estimating Bat and Bird Mortality Occurring at Wind Energy Turbines from Covariates and Carcass Searches Using Mixture Models

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Abstract

Environmental impacts of wind energy facilities increasingly cause concern, a central issue being bats and birds killed by rotor blades. Two approaches have been employed to assess collision rates: carcass searches and surveys of animals prone to collisions. Carcass searches can provide an estimate for the actual number of animals being killed but they offer little information on the relation between collision rates and, for example, weather parameters due to the time of death not being precisely known. In contrast, a density index of animals exposed to collision is sufficient to analyse the parameters influencing the collision rate. However, quantification of the collision rate from animal density indices (e.g. acoustic bat activity or bird migration traffic rates) remains difficult. We combine carcass search data with animal density indices in a mixture model to investigate collision rates. In a simulation study we show that the collision rates estimated by our model were at least as precise as conventional estimates based solely on carcass search data. Furthermore, if certain conditions are met, the model can be used to predict the collision rate from density indices alone, without data from carcass searches. This can reduce the time and effort required to estimate collision rates. We applied the model to bat carcass search data obtained at 30 wind turbines in 15 wind facilities in Germany. We used acoustic bat activity and wind speed as predictors for the collision rate. The model estimates correlated well with conventional estimators. Our model can be used to predict the average collision rate. It enables an analysis of the effect of parameters such as rotor diameter or turbine type on the collision rate. The model can also be used in turbine-specific curtailment algorithms that predict the collision rate and reduce this rate with a minimal loss of energy production. © 2013 Korner-Nievergelt et al.

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  • Table 1. Characteristics of the two data sets analysed, including the number of turbines investigated, the total number of turbinenights, the number of bat call recordings, the total number of carcasses found, and the average wind speed with standard deviation.
  • Table 2. Carcass search data for the 30 turbines sampled.
  • Table 3. Notation of parameters, variables and indices.
  • Table 4. Parameter estimates (mean and 95% credible interval) for our two models (see text) fitted to different data sets (2007, 2008), and the mortality estimates (mean and range of the total number of collisions at all turbines during n nights) based both on the model (second last column), and on the conventional ‘‘corrected count’’ method.
  • Figure 1. Ratio of the estimated and the true number of collisions per turbine for 50 simulated data sets. 17 turbines were used to fit the model (1700 data points for each box, left panels), collisions were then predicted for a new turbine not used to fit the model (50 data points for each box, right panels). The y-axis is log-scaled so that equivalent proportional increases and decreases result in the same change on the y-axis. Grey boxes indicate model estimates using the one- (upper panels) and three-level (lower panels) observation model (see text). White boxes give the conventional ‘‘corrected count’’ estimates (see text) using only carcass count data and estimates for carcass detection probability. The data has been simulated for two settings with different sample sizes (100 and 300 nights per turbine). The average total numbers of collisions per turbine for these two settings were 4.5 and 14.2 bats respectively. Bold horizontal line = median, box = 50% range of the data, whiskers = last value within 1.5 times the interquartile range, circles = data points further away. doi:10.1371/journal.pone.0067997.g001
  • Table 5. Observed frequencies of the numbers of carcasses found per search in the 2007 data set compared to the ones predicted from our two models (see text).
  • Table 6. Observed frequencies of the numbers of carcasses found per search in the 2008 data set compared to the ones predicted from our two models (see text).
  • Figure 2. Estimated number of collisions for each turbine in the two data sets (2007 and 2008) based on the one- and three-level observation model vs. the conventional ‘‘corrected count’’ estimate. Segments give the 95% credible intervals. The dotted line indicates perfect coincidence. doi:10.1371/journal.pone.0067997.g002

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Korner-Nievergelt, F., Brinkmann, R., Niermann, I., & Behr, O. (2013). Estimating Bat and Bird Mortality Occurring at Wind Energy Turbines from Covariates and Carcass Searches Using Mixture Models. PLoS ONE, 8(7). https://doi.org/10.1371/journal.pone.0067997

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