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	Distance Sampling	Analys av topologi i födovävar	Populationslivskraftanalys
Ämnesområde	Ekologi	Ekologi	Ekologi
Familj	Process / pipeline	Process / pipeline	Process / pipeline
Ursprungsår	1993	2000	1981
Upphovsperson	Stephen Buckland	Richard Williams and Neo Martinez	Mark Shaffer
Typ	population abundance estimation	ecological network characterization	extinction risk assessment
Ursprungskälla	Buckland, 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.	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.	Shaffer, M. L. (1981). Minimum population sizes for species conservation. BioScience, 31(2), 131-134.
Alias	line transect, point transect, distance estimation, detection probability	food web structure, network topology, trophic network, food chain analysis	PVA, extinction risk, minimum viable population, MVP
Närliggande	4	4	4
Sammanfattning	Distance 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.	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.	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.