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Circuitscape-Analyse×Distanz-Erfassung×Analyse der Nahrungsnetzt-Topologie×
FachgebietÖkologieÖkologieÖkologie
FamilieProcess / pipelineProcess / pipelineProcess / pipeline
Entstehungsjahr200819932000
UrheberBrad McRaeStephen BucklandRichard Williams and Neo Martinez
Typmovement and connectivity modelingpopulation abundance estimationecological network characterization
Wegweisende QuelleBradford, D. F., McCreary, D. D., & Groves, C. R. (2014). Optimizing sampling for large-area habitat assessment. Ecological Monographs, 84(3), 351-375. link ↗Buckland, S. T., Anderson, D. R., Burnham, K. P., Laake, J. L., Borchers, D. L., & Thomas, L. (1993). Distance Sampling: Estimating Abundance of Biological Populations. Chapman and Hall, London. link ↗Dunne, J. A., Williams, R. J., & Martinez, N. D. (2002). Network structure and robustness of marine food webs. The American Naturalist, 160(1), 117-129. link ↗
Aliasnamencircuit theory, resistance distance, connectivity analysis, landscape conductanceline transect, point transect, distance estimation, detection probabilityfood web structure, network topology, trophic network, food chain analysis
Verwandt444
ZusammenfassungCircuitscape, developed by Brad McRae (2008), applies circuit theory from electrical engineering to predict organism movement and genetic connectivity across landscapes. The method treats landscapes as electrical networks where habitat quality is resistance and organism movement is electrical current. By analogy, organisms diffusing through a landscape follow paths determined by landscape resistance: corridors of low resistance (good habitat) are preferentially used. Circuitscape predicts movement probabilities, identifies critical corridors, and quantifies connectivity between habitat patches.Distance sampling is a statistical method for estimating population abundance from data on distances between observers and detected individuals. Developed by Buckland and colleagues (1993) and formalized in the software Distance, this approach accounts for imperfect detection: animals far from an observer are less likely to be detected. By modeling the detection function (probability of detecting an animal at various distances), distance sampling produces unbiased estimates of abundance and density even when detection is incomplete.Food web topology analysis characterizes the structure of predator-prey interactions within ecological communities using network metrics. Pioneered by Williams and Martinez (2000) and extended by Dunne and colleagues (2002), this approach maps which species eat which and quantifies network properties (connectivity, clustering, robustness). Understanding food web structure reveals how ecosystems are organized, how stable they are to species loss, and what roles different species play in ecosystem function.
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ScholarGateMethoden vergleichen: Circuitscape · Distance Sampling · Food Web Topology. Abgerufen am 2026-06-20 von https://scholargate.app/de/compare