November 1997 Ÿ NREL/SR-440-23088
Development of a Practical Modeling Framework for Estimating the Impact of Wind Technology on Bird Populations
Michael L. Morrison California State University Sacramento, California Kenneth H. Pollock North Carolina State University Raleigh, North Carolina
National Renewable Energy Laboratory 1617 Cole Boulevard Golden, Colorado 80401-3393 A national laboratory of the U.S. Department of Energy Managed by Midwest Research Institute for the U.S. Department of Energy under contract No. DE-AC36-83CH10093 November 1997
NREL/SR-440-23088 Ÿ UC Category: 1210
Development of a Practical Modeling Framework for Estimating the Impact of Wind Technology on Bird Populations
Michael L. Morrison California State University Sacramento, California Kenneth H. Pollock North Carolina State University Raleigh, North Carolina NREL technical monitor: Karin Sinclair
National Renewable Energy Laboratory 1617 Cole Boulevard Golden, Colorado 80401-3393 A national laboratory of the U.S. Department of Energy Managed by Midwest Research Institute for the U.S. Department of Energy under contract No. DE-AC36-83CH10093 Work performed under Subcontract No. CCD-5-15367-01 November 1997
NOTICE This report was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercialproduct, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States government or any agency thereof. The views and opinions of authord expressed herein do not necessarily state or reflect those of the United States government or any agency thereof.
Available to DOE and DOE contractors from: Office of Scientific and Technical Information (OSTI) P.O. Box 62 Oak Ridge, TN 37831 Prices available by calling (423) 576-8401 Available to the public from: National Technical Information Service (NTIS) U.S. Department of Commerce 5285 Port Royal Road Springfield, VA 22161 (703) 487-4650
Printed on paper containing at least 50% wastepaper, including 10% postconsumer waste
Foreword One of the most pressing environmental concerns related to wind project development is the potential for avian fatalities caused by the turbines. In order to understand the potential for this problem, pre-construction avian surveys are often required. However, these can be expensive and require significant amounts of time in order to gather the empirical data necessary to fully understand the potential impacts. Then, the results may suggest that moving forward with such a project in the wind resource area just evaluated may be ill advised. This report describes a modeling framework for evaluating potential windplant impacts that can be generalized to most bird species. This modeling framework could be used to get a preliminary understanding of the likelihood of significant impacts to birds in a cost-effective way. Drs. Morrison and Pollock produced this report under a subcontract with the National Wind Technology Center of the National Renewable Energy Laboratory, with funding from the Wind Program at the U. S. Department of Energy.
Karin C. Sinclair National Wind Technology Center National Renewable Energy Laboratory 1617 Cole Boulevard Golden, Colorado 80401 Internet Address:
[email protected] Phone: 303 - 384 - 6946 Fax: 303 - 384 - 6901
iii
EXECUTIVE SUMMARY The goal of this project is to develop a useful, practical modeling framework for evaluating potential wind power plant impacts that can be generalized to most bird species. We accomplish this by (1) reviewing the major factors that can influence the persistence of a wild population; (2) briefly reviewing various models that can aid in estimating population status and trend, including methods of evaluating model structure and performance; (3) reviewing survivorship and population projections; and (4) developing a framework for using models to evaluate the potential impacts of wind development on birds. We begin with a review of demography. Demography is the study of population statistics, including births, deaths, immigration, and emigration. From demography, we know that conditions leading to extinction are most likely to occur in small populations. Demographic rates vary because individuals do not survive for the same length of time, individuals vary in the number of offspring they bear, individuals often have low birth rates, and so forth. Adult survivorship is usually very high, especially in long-lived species (such as raptors). Therefore, estimating adult survivorship tells one a lot about population status. In addition, in most monogamous species, it is female survivorship that is most important to population persistence. At a minimum, then, quantifying adult survivorship provides a preliminary, basic indication of the status of the population. Modeling genetics is not likely to be as important as modeling demographic and ecological processes in evaluating population persistence. This is based, in part, on the lack of our sufficient understanding of genetics to use it as a basis for management. Thus, practical considerations were the overriding factor in this conclusion. Still, genetics may be a priority in small, isolated populations. Random environmental events such as catastrophic fires, hurricanes, and disease can also have pronounced effects on small populations. Such factors can also have pronounced effects on large populations that are spatially divided into subpopulations. Here, factors such as dispersal will determine the fate of a subpopulation driven to very low numbers, or even to extinction, by a catastrophic event. Thus, the relative importance of environmental stochasticity must be based on an understanding of the spatial distribution of the population under study. Next we review the parameters necessary to develop rigorous population-projection models. Life-history parameters are essential components of population-projection models. The characteristics that we collectively call life-history parameters of animals include quantifiable longevity, lifetime reproductive output, the young produced per breeding attempt, the age of dispersal, survivorship, sex ratio, and the time between breeding attempts. For example, combining various ranges of parameters can yield substantially different rates of population change. Such analyses provide guidance on whether the population can be sustained under varying expressions of life history traits. Once such relationships are understood, researchers have the opportunity to monitor selected life history traits as part of an assessment of the status of a population. A central part of impact assessment--such as in wind power plants--is developing a model that estimates the survival rates required to maintain a constant population. The strategy is to determine the survival rates required to sustain the populations that exhibit the various combinations of the other parameters governing population size. To be useful in a wide range of environmental situations and useable for people with varying expertise, the model should be based on simple mathematics. Leslie matrix and similar stage-structured models can give great insight into the processes of population growth. For example, the sensitivity of the population growth rate, r, to perturbations in vital rates for a Leslie-type model can be solved analytically. Understanding how growth rate iv
changes in response to perturbations at various stages in the life table may help direct management strategies. For example, adult survival tends to be a parameter to which a model is extremely sensitive in long-lived species, whereas fecundity can be more important in short-lived species. To aid in providing general guidelines concerning the potential impacts of wind developments on bird populations, we developed Leslie matrix models and conducted sensitivity analyses to determine the effects of survival of age classes on population growth rates. We gathered data from the literature on passerines, ducks, geese, gulls, and eagles. These analyses provide a first approximation of how populations of these types of birds respond to hypothetical changes in fecundity and survivorship. They can be used to help focus attention on species most likely to be adversely affected by changes in fecundity and survivorship. The simplest models assume that the number of animals in a population goes up or down by a constant ratio, usually designated as lambda, with each unit of time. The annual geometric growth rate of a population is thus represented by lambda, which is also known as the finite rate of population increase. The population is increasing if lambda >1, is constant if lambda = 1, and is decreasing if lambda 1, is constant if lambda = 1, and is decreasing if lambda 1, then the population will be assumed to be stable or increasing. If lambda is 4 years old); adult floaters (non-territory holders >4 years old); subadults (1-4 years old); and juveniles (
