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Modelització de nius×Anàlisi de la topologia de xarxes tròfiques×
CampEcologiaEcologia
FamíliaProcess / pipelineProcess / pipeline
Any d'origen19992000
Autor originalSteven Phillips and David StockwellRichard Williams and Neo Martinez
Tipusspecies distribution predictionecological network characterization
Font seminalPhillips, S. J., Anderson, R. P., & Schapire, R. E. (2006). Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190(3-4), 231-259. DOI ↗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 ↗
Àliesspecies distribution modeling, habitat suitability modeling, ecological niche model, MaxEntfood web structure, network topology, trophic network, food chain analysis
Relacionats44
ResumNiche 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.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.
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ScholarGateCompara mètodes: Niche Modeling · Food Web Topology. Recuperat el 2026-06-19 de https://scholargate.app/ca/compare