The reliability of regional ecological knowledge to build local interaction networks: a test using seed-dispersal networks across land-bridge islands

Author:

Zhu Chen1ORCID,Li Wande2ORCID,Campos-Arceiz Ahimsa3,Dalsgaard Bo4,Ren Peng1ORCID,Wang Duorun2,Zhang Xue1ORCID,Sun Minghao1,Si Qi1ORCID,Kang Yi2,Ding Ping1ORCID,Si Xingfeng2ORCID

Affiliation:

1. MOE Key Laboratory of Biosystems Homeostasis & Protection, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, People's Republic of China

2. Zhejiang Zhoushan Archipelago Observation and Research Station, Institute of Eco-Chongming, Zhejiang Tiantong Forest Ecosystem National Observation and Research Station, School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241, People's Republic of China

3. Southeast Asia Biodiversity Research Institute, Chinese Academy of Sciences & Center for Integrative Conservation, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Yunnan 666303, People's Republic of China

4. Section for Molecular Ecology and Evolution, Globe Institute, University of Copenhagen, Copenhagen, Denmark

Abstract

Building ecological networks is the fundamental basis of depicting how species in communities interact, but sampling complex interaction networks is extremely labour intensive. Recently, indirect ecological information has been applied to build interaction networks. Here we propose to extend the source of indirect ecological information, and applied regional ecological knowledge to build local interaction networks. Using a high-resolution dataset consisting of 22 locally observed networks with 17 572 seed-dispersal events, we test the reliability of indirectly derived local networks based on regional ecological knowledge (REK) across islands. We found that species richness strongly influenced ‘local interaction rewiring’ (i.e. the proportion of locally observed interactions among regionally interacting species), and all network properties were biased using REK-based networks. Notably, species richness and local interaction rewiring strongly affected estimations of REK-based network structures. However, locally observed and REK-based networks detected the same trends of how network structure correlates to island area and isolation. These results suggest that we should use REK-based networks cautiously for reflecting actual interaction patterns of local networks, but highlight that REK-based networks have great potential for comparative studies across environmental gradients. The use of indirect regional ecological information may thus advance our understanding of biogeographical patterns of species interactions.

Funder

China Scholarship Council

Qianjiangyuan National Park Scientific Research Program

Danmarks Frie Forskningsfond

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province

Southeast Asia Biodiversity Research Institute

Program for Professor of Special Appointment

Publisher

The Royal Society

Subject

General Agricultural and Biological Sciences,General Environmental Science,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine

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