Comparer des méthodes

	Analyse Circuitscape	Analyse de la topologie des réseaux trophiques	Analyse de Viabilité des Populations
Domaine	Écologie	Écologie	Écologie
Famille	Process / pipeline	Process / pipeline	Process / pipeline
Année d'origine	2008	2000	1981
Auteur d'origine	Brad McRae	Richard Williams and Neo Martinez	Mark Shaffer
Type	movement and connectivity modeling	ecological network characterization	extinction risk assessment
Source fondatrice	Bradford, D. F., McCreary, D. D., & Groves, C. R. (2014). Optimizing sampling for large-area habitat assessment. Ecological Monographs, 84(3), 351-375.	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.	Shaffer, M. L. (1981). Minimum population sizes for species conservation. BioScience, 31(2), 131-134.
Alias	circuit theory, resistance distance, connectivity analysis, landscape conductance	food web structure, network topology, trophic network, food chain analysis	PVA, extinction risk, minimum viable population, MVP
Apparentées	4	4	4
Résumé	Circuitscape, 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.	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.