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Analyse Circuitscape×Échantillonnage par distance×Analyse de la topologie des réseaux trophiques×Analyse de Viabilité des Populations×
DomaineÉcologieÉcologieÉcologieÉcologie
FamilleProcess / pipelineProcess / pipelineProcess / pipelineProcess / pipeline
Année d'origine2008199320001981
Auteur d'origineBrad McRaeStephen BucklandRichard Williams and Neo MartinezMark Shaffer
Typemovement and connectivity modelingpopulation abundance estimationecological network characterizationextinction risk assessment
Source fondatriceBradford, 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 ↗Shaffer, M. L. (1981). Minimum population sizes for species conservation. BioScience, 31(2), 131-134. DOI ↗
Aliascircuit theory, resistance distance, connectivity analysis, landscape conductanceline transect, point transect, distance estimation, detection probabilityfood web structure, network topology, trophic network, food chain analysisPVA, extinction risk, minimum viable population, MVP
Apparentées4444
RésuméCircuitscape, 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.Population Viability Analysis (PVA), introduced by Shaffer (1981), estimates the probability that a population will persist over a given time period under specified conditions. PVA combines demographic models (Leslie matrices, IPMs) with stochastic simulation to project population trajectories, quantifying extinction risk. This allows conservation planners to assess whether a population will likely persist, evaluate management scenarios, and estimate the minimum viable population (MVP) size for long-term persistence. PVA is a decision-support tool, not a precise predictor.
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ScholarGateComparer des méthodes: Circuitscape · Distance Sampling · Food Web Topology · Population Viability Analysis. Consulté le 2026-06-20 sur https://scholargate.app/fr/compare