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Аналіз топології харчових мереж×Дистанційне вибіркове обстеження×
ГалузьЕкологіяЕкологія
РодинаProcess / pipelineProcess / pipeline
Рік появи20001993
Автор методуRichard Williams and Neo MartinezStephen Buckland
Типecological network characterizationpopulation abundance estimation
Основоположне джерелоDunne, 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 ↗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. link ↗
Інші назвиfood web structure, network topology, trophic network, food chain analysisline transect, point transect, distance estimation, detection probability
Пов'язані44
ПідсумокFood 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.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.
ScholarGateНабір даних
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  2. 3 Джерела
  3. PUBLISHED
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  2. 3 Джерела
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ScholarGateПорівняння методів: Food Web Topology · Distance Sampling. Отримано 2026-06-19 з https://scholargate.app/uk/compare