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Circuitscape analízis×A táplálékhálózat-topológia elemzése×Modellezés a fajok élőhelyigénye alapján (Niche Modeling)×Populáció-életképességi analízis×
TudományterületÖkológiaÖkológiaÖkológiaÖkológia
MódszercsaládProcess / pipelineProcess / pipelineProcess / pipelineProcess / pipeline
Keletkezés éve2008200019991981
MegalkotóBrad McRaeRichard Williams and Neo MartinezSteven Phillips and David StockwellMark Shaffer
Típusmovement and connectivity modelingecological network characterizationspecies distribution predictionextinction risk assessment
AlapműBradford, D. F., McCreary, D. D., & Groves, C. R. (2014). Optimizing sampling for large-area habitat assessment. Ecological Monographs, 84(3), 351-375. link ↗Dunne, J. A., Williams, R. J., & Martinez, N. D. (2002). Network structure and robustness of marine food webs. The American Naturalist, 160(1), 117-129. 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 ↗
Alternatív nevekcircuit theory, resistance distance, connectivity analysis, landscape conductancefood web structure, network topology, trophic network, food chain analysisspecies distribution modeling, habitat suitability modeling, ecological niche model, MaxEntPVA, extinction risk, minimum viable population, MVP
Kapcsolódó4444
ÖsszefoglalóCircuitscape, 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.Food web topology analysis characterizes the structure of predator-prey interactions within ecological communities using network metrics. Pioneered by Williams and Martinez (2000) and extended by Dunne and colleagues (2002), this approach maps which species eat which and quantifies network properties (connectivity, clustering, robustness). Understanding food web structure reveals how ecosystems are organized, how stable they are to species loss, and what roles different species play in ecosystem function.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.
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ScholarGateMódszerek összehasonlítása: Circuitscape · Food Web Topology · Niche Modeling · Population Viability Analysis. Letöltve 2026-06-20, forrás: https://scholargate.app/hu/compare