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Аналіз Circuitscape×Дистанційне вибіркове обстеження×Аналіз життєздатності популяцій×
ГалузьЕкологіяЕкологіяЕкологія
РодинаProcess / pipelineProcess / pipelineProcess / pipeline
Рік появи200819931981
Автор методуBrad McRaeStephen BucklandMark Shaffer
Типmovement and connectivity modelingpopulation abundance estimationextinction risk assessment
Основоположне джерелоBradford, 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 ↗
Інші назвиcircuit theory, resistance distance, connectivity analysis, landscape conductanceline transect, point transect, distance estimation, detection probabilityPVA, extinction risk, minimum viable population, MVP
Пов'язані444
ПідсумокCircuitscape, 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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ScholarGateПорівняння методів: Circuitscape · Distance Sampling · Population Viability Analysis. Отримано 2026-06-20 з https://scholargate.app/uk/compare