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Integralprojektionsmodel×Analyse af populationslevedygtighed×
FagområdeØkologiØkologi
FamilieProcess / pipelineProcess / pipeline
Oprindelsesår20001981
OphavspersonStephen Ellner and Mark ReesMark Shaffer
Typesize-structured population projectionextinction risk assessment
Oprindelig kildeEasterling, M. R., Ellner, S. P., & Dixon, P. M. (2000). Size-specific sensitivity: applying a new structured population model. Ecology, 81(3), 694-708. DOI ↗Shaffer, M. L. (1981). Minimum population sizes for species conservation. BioScience, 31(2), 131-134. DOI ↗
AliasserIPM, continuous size structure, kernel model, size-structured populationPVA, extinction risk, minimum viable population, MVP
Relaterede44
ResuméIntegral projection models (IPMs) are a class of structured population models that use continuous traits (size, age, height) to describe population dynamics. Introduced by Easterling and colleagues (2000) and developed extensively by Ellner, Rees, and collaborators, IPMs overcome limitations of age- or stage-structured models by treating individual traits as continuous. They use integration to project populations forward in time, making them particularly suitable for organisms with continuous size distributions or flexible developmental pathways. IPMs enable estimation of population growth rate (λ), sensitivity analysis, and projection under changing environmental conditions.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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ScholarGateSammenlign metoder: Integral Projection Model · Population Viability Analysis. Hentet 2026-06-17 fra https://scholargate.app/da/compare