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Дистанционно изследване×Моделиране на ниши×Population Viability Analysis×
ОбластЕкологияЕкологияЕкология
СемействоProcess / pipelineProcess / pipelineProcess / pipeline
Година на възникване199319991981
СъздателStephen BucklandSteven Phillips and David StockwellMark Shaffer
Типpopulation abundance estimationspecies distribution predictionextinction risk assessment
Основополагащ източникBuckland, 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 ↗Phillips, S. J., Anderson, R. P., & Schapire, R. E. (2006). Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190(3-4), 231-259. DOI ↗Shaffer, M. L. (1981). Minimum population sizes for species conservation. BioScience, 31(2), 131-134. DOI ↗
Други названияline transect, point transect, distance estimation, detection probabilityspecies distribution modeling, habitat suitability modeling, ecological niche model, MaxEntPVA, extinction risk, minimum viable population, MVP
Свързани444
РезюмеDistance 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.Niche modeling, also called species distribution modeling (SDM), predicts the geographic range and habitat suitability of species using presence-only or presence-background occurrence data and environmental variables. MaxEnt (Maximum Entropy, Phillips et al. 2006) and GARP (Genetic Algorithm for Rule-set Prediction, Stockwell & Peters 1999) are two prominent algorithms. These methods identify the environmental conditions under which species are likely to occur, enabling prediction of distribution beyond sampled areas and assessment of habitat suitability across landscapes.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.
ScholarGateНабор от данни
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ScholarGateСравнение на методи: Distance Sampling · Niche Modeling · Population Viability Analysis. Извлечено на 2026-06-20 от https://scholargate.app/bg/compare