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Análisis con Circuitscape×Muestreo por Distancia×Análisis de Viabilidad Poblacional×
CampoEcologíaEcologíaEcología
FamiliaProcess / pipelineProcess / pipelineProcess / pipeline
Año de origen200819931981
Autor originalBrad McRaeStephen BucklandMark Shaffer
Tipomovement and connectivity modelingpopulation abundance estimationextinction risk assessment
Fuente seminalBradford, 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 ↗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 probabilityPVA, extinction risk, minimum viable population, MVP
Relacionados444
ResumenCircuitscape, 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.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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ScholarGateComparar métodos: Circuitscape · Distance Sampling · Population Viability Analysis. Recuperado el 2026-06-20 de https://scholargate.app/es/compare