Comparar métodos

	Análisis con Circuitscape	Análisis de la topología de redes tróficas	Modelado de Nicho	Análisis de Viabilidad Poblacional
Campo	Ecología	Ecología	Ecología	Ecología
Familia	Process / pipeline	Process / pipeline	Process / pipeline	Process / pipeline
Año de origen	2008	2000	1999	1981
Autor original	Brad McRae	Richard Williams and Neo Martinez	Steven Phillips and David Stockwell	Mark Shaffer
Tipo	movement and connectivity modeling	ecological network characterization	species distribution prediction	extinction risk assessment
Fuente seminal	Bradford, D. F., McCreary, D. D., & Groves, C. R. (2014). Optimizing sampling for large-area habitat assessment. Ecological Monographs, 84(3), 351-375.	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.	Phillips, S. J., Anderson, R. P., & Schapire, R. E. (2006). Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190(3-4), 231-259.	Shaffer, M. L. (1981). Minimum population sizes for species conservation. BioScience, 31(2), 131-134.
Alias	circuit theory, resistance distance, connectivity analysis, landscape conductance	food web structure, network topology, trophic network, food chain analysis	species distribution modeling, habitat suitability modeling, ecological niche model, MaxEnt	PVA, extinction risk, minimum viable population, MVP
Relacionados	4	4	4	4
Resumen	Circuitscape, 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.