本頁只刊出中文翻譯與中文說明；英文原文請見下方原文連結。
原文連結
論文資訊
- 類型：已發表論文
- 日期：2020-05-01
摘要
Ecosystems functioning is based on an intricate web of interactions among living entities. Most of these interactions are difficult to observe, especially when the 多樣性 of interacting entities is large and they are of small size and abundance. To sidestep this limitation, it has become common to infer the 網絡 structure of ecosystems from time series of 物種 abundance, but it is not clear how well can 網絡s be reconstructed, especially in the presence of 隨機ity that propagates through ecological 網絡s. We evaluate the effects of intrinsic noise and 網絡 topology on the performance of different methods of inferring 網絡 structure from time-series data. Analysis of seven different four-物種 motifs using a 隨機 model demonstrates that star-shaped motifs are differentially detected by these methods while rings
※ 此為已發表論文，全文需透過期刊付費取得