Biodiversity Science

   

Determination of key species in the food web and its impact on the robustness

Fengzhen Wang1, 2, Yi Tang1, 2   

  1. 1. School of Life Sciences, Liaoning University
    2. School of Life Sciences, Liaoning University
  • Received:2019-07-01 Online:2019-11-12
  • Yi Tang

Determining quantitatively key species helps to reveal the relationship between species and plays a vital role in protecting key species prior. Here, we calculated the indicators, i.e., Betweenness Centrality(BC), Closeness Centrality(CC), and Degree Centrality(DC) in a food web with 49 species. We conducted the clustering analysis according to the indicators mentioned above, analyzed the influence of species in kinds of classes on the connectivity robustness, and explore the effects of the number of removed nodes on connectivity robustness under removal modes. The results showed that species in this food web could be divided into three categories. Class I species have relatively higher values in BC, CC, and DC; Class II species have relatively lower values in BC, CC, and DC. The values of BC, CC, and DC of Class III species are between Class I species and Class II species. Class I species are more important in the food web and could be considered as key species. This finding contributes to how to determine quantitatively key species in food webs. Besides, the connectivity robustness decreased along with the increase in removed nodes under the ascending order removal mode. In the descending order and random removal modes, the connectivity robustness slightly increased after a continuous decrease along with the increase in removed nodes. It indicates that removal modes significantly affect the connectivity robustness. Moreover, under the three removal methods, the significant change in the connectivity robustness corresponds to almost the same number of removed nodes. It suggests key species play an essential role in maintaining the connectivity robustness of the food web.

Key words: Cluster analysis, Complex network, Ecological network, Node degree, Connectivity robustness

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