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Please use this identifier to cite or link to this item: http://hdl.handle.net/10023/2008
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Title: Comparing pre- and post-construction distributions of long-tailed ducks Clangula hyemalis in and around the Nysted offshore wind farm, Denmark : a quasi-designed experiment accounting for imperfect detection, local surface features and autocorrelation
Authors: Petersen, Ib Krag
MacKenzie, Monique Lea
Rexstad, Eric
Wisz, Mary S.
Fox, Anthony D.
Keywords: Aerial surveys
Distance sampling
Environmental impact assessment
Feeding desities
Generalized additive models
Parametric bootstrap
Spatially-adaptive model
Generalized estimating equations
Seaducks
Spatial autocorrelation
Temporal autocorrelation
QA Mathematics
QH Natural history
QL Zoology
Issue Date: 2011
Citation: Petersen , I K , MacKenzie , M L , Rexstad , E , Wisz , M S & Fox , A D 2011 , Comparing pre- and post-construction distributions of long-tailed ducks Clangula hyemalis in and around the Nysted offshore wind farm, Denmark : a quasi-designed experiment accounting for imperfect detection, local surface features and autocorrelation . CREEM Technical Report , no. 2011-1 , University of St Andrews .
Series/Report no.: CREEM Technical Report
Abstract: We report a novel technique to model abundance patterns of wintering seaducks in relation to the construction of an offshore wind farm (OWF) based on seven years of aerial survey transect data. Distance sampling was used to estimate seaduck densities adjusted for covariates affecting detection probabilities. A generalized additive model (GAM) generated seaduck densities in sampling units in relation to spatially explicit covariates, using bootstrapping to account for uncertainties in both processes. Generalized estimating equations generated precision measures for the GAM robust to spatial and temporal autocorrelation. Comparison of pre- and post-construction model generated surfaces showed significant reductions in long-tailed duck numbers only within the OWF (despite the fact that the model was uninformed about the OWF location), although the absolute numbers involved were trivial in a flyway population context. This method provides quantification of distributional effects on organisms over a gradient in space and time that offers an alternative to Before-After/Control-Impact designs in environmental impact assessment.
Version: Postprint
URI: http://hdl.handle.net/10023/2008
Type: Report
Publisher: University of St Andrews
Appears in Collections:University of St Andrews Research
Mathematics & Statistics Research
Centre for Research into Ecological & Environmental Modelling (CREEM) Research



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