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| 食物网拓扑结构分析× | 生态位建模× | |
|---|---|---|
| 领域 | 生态学 | 生态学 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 2000 | 1999 |
| 提出者≠ | Richard Williams and Neo Martinez | Steven Phillips and David Stockwell |
| 类型≠ | ecological network characterization | species distribution prediction |
| 开创性文献≠ | 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 ↗ |
| 别名≠ | food web structure, network topology, trophic network, food chain analysis | species distribution modeling, habitat suitability modeling, ecological niche model, MaxEnt |
| 相关 | 4 | 4 |
| 摘要≠ | 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. |
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