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Population Viability Analysis×Матрица на Лесли×
ОбластЕкологияЕкология
СемействоProcess / pipelineProcess / pipeline
Година на възникване19811945
СъздателMark ShafferPatrick Leslie
Типextinction risk assessmentstructured population dynamics
Основополагащ източникShaffer, M. L. (1981). Minimum population sizes for species conservation. BioScience, 31(2), 131-134. DOI ↗Leslie, P. H. (1945). On the use of matrices in certain population mathematics. Biometrika, 33(3), 183-212. DOI ↗
Други названияPVA, extinction risk, minimum viable population, MVPLeslie model, age-structured population model, matrix population model, population dynamics
Свързани44
РезюмеPopulation 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.The Leslie matrix is a deterministic model of age-structured population dynamics, introduced by Patrick Leslie (1945). It projects population size and structure forward in time using age-specific fertility and survival rates. A Leslie matrix encodes these vital rates in a square matrix; multiplying the matrix by a population vector yields the population's composition at the next time step. This approach enables calculation of the population's asymptotic growth rate (λ), identification of stable age structure, and sensitivity analysis—understanding which vital rates most strongly influence population growth.
ScholarGateНабор от данни
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  2. 3 Източници
  3. PUBLISHED
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ScholarGateСравнение на методи: Population Viability Analysis · Leslie Matrix. Извлечено на 2026-06-18 от https://scholargate.app/bg/compare