BioOne Complete (complete.BioOne.org) is a full-text database of 200 subscribed and open-access titles in the biological, ecological, and environmental sciences published by nonprofit societies, associations, museums, institutions, and presses.
The United States Fish and Wildlife Service (USFWS) recommends using a Bayesian modeling framework to predict the annual golden eagle (Aquila chrysaetos) fatality rate at a wind energy facility, and the modeling approach defines prior distributions for collision rate and exposure rate from data at existing wind projects. Collision rate is defined as the number of collisions per exposure. Exposure rate is a function of minutes of eagle activity and survey effort; we used site-specific data to update the prior distribution, resulting in the posterior distribution. An expansion factor adjusts the fatality prediction by accounting for daylight hours and the hazardous area within a wind project footprint. The product of the collision rate, posterior exposure rate, and expansion factor is the predicted annual fatality rate. We reviewed the input data for the prior distribution for collision rate, and provided an updated prior distribution for collision rate using more contemporary information. As suggested by the current USFWS guidance, we updated the prior distribution for collision rate from the USFWS baseline model with data from a site with modern specifications to obtain an updated prior distribution. We also created alternative prior distributions by estimating parameters for the distributions from data at 26 modern facilities only. Using more recent data and a larger data set, we determined the predictions using the alternative prior distributions for collision rate are approximately half the estimates using the original distribution. Ó 2016 The Wildlife Society.KEY WORDS Aquila chrysaetos, Bayesian, collision, fatality prediction, golden eagles, USFWS Eagle Conservation Plan Guidance, wind energy.Statistical models in the Bayesian framework use existing information about model parameters to develop prior probability distributions, and as more data become available prior distributions can be updated. The United States Fish and Wildlife Service (USFWS) developed a statistical collision risk model (CRM) in the Bayesian framework using observational data of golden eagles (Aquila chrysaetos). The USFWS Eagle Conservation Plan Guidance published prior distributions for the CRM as a baseline and suggests that other candidate models should be developed and compared to the baseline model. The USFWS states that a major goal of the modeling process is to reduce uncertainty by including new information into an adaptive modeling framework (USFWS 2013; Appendix A). A formal policy of adaptive management has been adopted by the USFWS (Walters 1986), in which key uncertainties regarding the impact on golden eagles by wind facilities are to be minimized through a sequential process of model development, model testing and comparison, accumulation of updated information, and new data, followed by model rebuilding and renewed model testing. New et al. (2015) recently published an update to the prior probability distribution for exposure rate to be used in the CRM, demonstrating a pathway for providing updates so that the...
Current research estimates hundreds of thousands of turbine-related bat fatalities in North America annually. In an effort to reduce impacts of wind energy production on bat populations, many facilities implement operational curtailment strategies that limit turbine blade rotation during conditions when nighttime wind speeds are low. Incorporating real-time bat activity data into wind speed-only curtailment (WOC) strategies may increase operational flexibility by allowing turbines to operate normally when bats are not present near turbines. We evaluated costs and benefits of implementing the Turbine Integrated Mortality Reduction (TIMR) system, an approach that informs a curtailment-triggering algorithm based on wind speed and real-time bat acoustic data, compared to a WOC strategy in which turbines were curtailed below 4.5 meters per second (m/s) at a wind energy facility in Fond Du Lac County, Wisconsin. TIMR is a proprietary system and we had no access to the acoustic data or bat call analysis software. Operational parameters for the TIMR system were set to allow curtailment at all wind speeds below 8.0 m/s during the study period when bats were acoustically detected. Overall, the TIMR system reduced fatalities by 75% compared to control turbines, while the WOC strategy reduced fatalities by 47%. An earlier analysis of the same TIMR data neglected to account for carcasses occurring outside the plot boundary and estimated an 84.5% fatality reduction due to the TIMR system. Over the study period, bat activity led to curtailment of TIMR turbines during 39.4% of nighttime hours compared to 31.0% of nighttime hours for WOC turbines, and revenue losses were approximately 280% as great for TIMR turbines as for turbines operated under the WOC strategy. The large cost difference between WOC and TIMR was driven by the 4.5 m/s versus 8.0 m/s wind speed thresholds for curtailment, but our study site has a relatively low average wind speed, which may also have contributed; other wind operators considering the TIMR system will need to consider their ability to absorb production losses in relation to their need to reduce bat fatality rates.
Given the uncertain population status of low-density, widely-occurring raptors, monitoring changes in abundance and distribution is critical to conserving populations. Nest-based monitoring is a common, useful approach, but the difficulty and expense of monitoring raptor nests and importance of reliable trend data to conservation requires that limited resources are allocated efficiently. Power analyses offer a helpful tool to ensure that monitoring programs have the ability to detect trends and to optimize financial resources devoted to monitoring. We evaluated alternative monitoring designs for raptors to identify appropriate survey effort to detect population trends. We used data collected from a territory-occupancy study of ferruginous hawks throughout Wyoming to guide simulations and evaluate the ability to detect trends in occupancy rates. Results suggest that greater gains in precision of trend estimation may be achieved through the addition of more sites and not more visits; statistical power was ≥80% when monitoring lasted 20 years and population declines were 20%; and probability of detection affected statistical power less than rates of population decline. Monitoring at least 150 sites for 20 years would provide reasonable estimates of trend in occupancy given certain rates of detection and occupancy, but only for population declines of 20%. Removal sampling did not result in substantial changes of any metrics used to evaluate simulations, providing little justification for employing the standard design if territory occupancy is the variable of interest. Initial rates of territory occupancy may be biased high, a problem inherent to many studies that monitor territory occupancy. We explored the effects of lower rates of initial occupancy on the ability to detect trends. Although we present data from a study of ferruginous hawks, our simulations can be applied to other raptor species with similar life history and population dynamics to provide guidance for future trend estimation of territory occupancy.
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