2007
DOI: 10.1111/j.1466-8238.2007.00352.x
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Geostatistical approaches and optimal additional sampling schemes for spatial patterns and future sampling of bird diversity

Abstract: Aim To evaluate geostatistical approaches, namely kriging, co-kriging and geostatistical simulation, and to develop an optimal sampling design for mapping the spatial patterns of bird diversity, estimating their spatial autocorrelations and selecting additional samples of bird diversity in a 2450 km 2 basin. Location Taiwan.Methods Kriging, co-kriging and simulated annealing are applied to estimate and simulate the spatial patterns of bird diversity. In addition, kriging and co-kriging with a genetic algorithm… Show more

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Cited by 48 publications
(50 citation statements)
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“…The annealing algorithm perturbs the image by simulating thermal perturbation [1,25,26]. In SAS, swapping the values in pairs of grid nodes that do not contain a conditioning datum, modifies the initial field, reproducing a histogram [1,11].…”
Section: Simulated Annealingmentioning
confidence: 99%
“…The annealing algorithm perturbs the image by simulating thermal perturbation [1,25,26]. In SAS, swapping the values in pairs of grid nodes that do not contain a conditioning datum, modifies the initial field, reproducing a histogram [1,11].…”
Section: Simulated Annealingmentioning
confidence: 99%
“…Despite considerable advances in the theory and practice of optimal spatial sampling (e.g. Braunisch and Suchant 2010, Lin et al 2008), trade-offs between optimal spatial and optimal temporal sampling are not yet completely resolved. The advances for habitat monitoring achieved by the EBONE project (Brus et al 2011, Metzger et al 2013) will be taken up and EU BON will tackle these challenges with new statistical and virtual ecological approaches (Railsback and Grimm 2012).…”
Section: Linking Biodiversity Trends To Natural and Anthropogenic Drimentioning
confidence: 99%
“…Evaluations of the effects of scale of sampling are generally difficult with idiosyncratic sampling, but can be achieved with a few sites with standardized infrastructure. Where coverage is inadequate, geostatistical techniques may help to define priorities for locations of new sampling sites (Lin et al 2008). Modular designs allow flexibility in answering local questions, while permitting different stakeholders to adjust the system to their questions .…”
Section: Uncertainty About the Stakeholdersmentioning
confidence: 99%
“…Reyers et al 2002, Ilg et al 2012) and selection of sites for additional sampling when initial sampling is inadequate (e.g. Lin et al 2008). However, spatially standardized sampling is generally the easiest option to evaluate the assumptions of analyses, and standardized sampling has allowed evaluation of the effects of scale and position of sampling units in RAPELD plots ) and elsewhere (Chisholm et al 2013).…”
Section: Uncertainty About Complementaritymentioning
confidence: 99%