Abstract
The consequences of bird mortality caused by collisions with wind turbines are increasingly receiving attention. So‐called acceptable mortality limits of populations, that is, those that assume that 1%–5% of additional mortality and the potential biological removal (PBR), provide seemingly clear‐cut methods for establishing the reduction in population viability.We examine how the application of these commonly used mortality limits could affect populations of the Common Starling, Black‐tailed Godwit, Marsh Harrier, Eurasian Spoonbill, White Stork, Common Tern, and White‐tailed Eagle using stochastic density‐independent and density‐dependent Leslie matrix models.Results show that population viability can be very sensitive to proportionally small increases in mortality. Rather than having a negligible effect, we found that a 1% additional mortality in postfledging cohorts of our studied populations resulted in a 2%–24% decrease in the population level after 10 years. Allowing a 5% mortality increase to existing mortality resulted in a 9%–77% reduction in the populations after 10 years.When the PBR method is used in the density‐dependent simulations, the proportional change in the resulting growth rate and carrying capacity was species‐independent and largely determined by the recovery factor (F r). When F r = 1, a value typically used for robust populations, additional mortality resulted in a 50%–55% reduction in the equilibrium density and the resulting growth rate. When F r = 0.1, used for threatened populations, the reduction in the equilibrium density and growth rate was about 5%. Synthesis and applications. Our results show that by allowing a mortality increase from wind farm collisions according to both criteria, the population impacts of these collisions can still be severe. We propose a simple new method as an alternative that was able to estimate mortality impacts of age‐structured stochastic density‐dependent matrix models.
Highlights
We investigate how populations of bird species with different life histories that are prone to wind turbine collision are affected by mortality thresholds used in wind energy impact assessment
Our results show that when applying the potential biological removal (PBR), the impacts were independent of growth rate at low densities (λ0)
We show that the use of the ORNIS 1%, the 5% mortality criterion, and potential biological removal criteria are inadequate for providing safe thresholds with respect to the impact of wind turbine collisions on populations
Summary
In order to assess the effects of extra mortality upon bird populations, we used Leslie matrix population models with a one-year time step. Each simulation started with the stable population structure of a matrix model parameterized with the mean vital rates of a specific species (separately per population and time period; see Table 1). Here we used an environmental stochastic approach in which each time step the vital rates of the matrix were randomly drawn from a Gaussian curve determined by their mean and standard deviation This means that the harvesting fraction is scaled to the population growth rate at low densities (r0) and the recovery factor (Fr). 1% additional mortality to natural mortality reduced population size in 10 years between 2% and 3% in Black-tailed Godwit, Marsh Harrier, Spoonbill, White Stork, and White-tailed Eagle, by 5% in Common Terns, and by 10%–24% in Starlings (depending on the mean population growth rate). The response, R, of both response parameters can be approximated by the equation: RN∗
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