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Second North American Sea Duck Conference - Patuxent Wildlife ...

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SECOND NORTH AMERICAN SEA DUCK CONFERENCE<br />

Mark Desholm<br />

AVIAN SENSITIVITY TO WIND FARM-RELATED MORTALITY:<br />

MATRIX POPULATION MODELS IN AN APPLIED CONTEXT<br />

National Environmental Research Institute, Grenåvej 12, DK-8410 Rønde, Denmark; mde@dmu.dk<br />

The main aim of this study was to develop a general modeling framework for setting management<br />

priorities by categorizing species according to their relative vulnerability to wind farm-related<br />

mortality. To do this, I compared the elasticity patterns generated by the life tables of a finite numbers<br />

of theoretical matrix population models representing the spectra of avian values of adult survival and<br />

adult female fecundity. The comparisons were generalized by developing simplified stage-classified<br />

models (two stages: pre-breeding and breeding) parameterized by invariant values of juvenile survival,<br />

mean adult survival, and mean annual fecundity. Such generalized and relatively simple models<br />

have earlier been shown to capture the essentials of full age-classified Leslie matrices, and they may<br />

therefore represent a useful tool for a first assessment of the relative influence of wind energy related<br />

mortality on different bird populations. Thus, if prioritization between species is necessary, for either<br />

technical or economical reasons, applying relatively simple matrix population models could optimize<br />

this classification process. Estimating the absolute demographic effects (e.g., the direct impact on<br />

the population size) of wind farm related mortality necessitate the use of much more detailed matrix<br />

population models. The predictive power of such models is determined by the degree to which the<br />

estimated input-parameters reflect the true mean values and their associated variance. Furthermore,<br />

details about density dependence, population age structure, age at first breeding, number of nonbreeders<br />

and environmental and demographic stochasticity must be incorporated. Especially if the<br />

researcher wants to predict what will happen through forecasting rather than just describe what would<br />

happen given certain hypotheses through population projection. Often such detailed data do not exist<br />

for the species of interest making the construction of such complex matrix population models an<br />

impossible task.<br />

78 ANNAPOLIS, MARYLAND, USA NOV. 7-11, 2005

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