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The reliability of regional ecological knowledge to build local interaction networks: a test using seed-dispersal networks across land-bridge islands.
Zhu, Chen; Li, Wande; Campos-Arceiz, Ahimsa; Dalsgaard, Bo; Ren, Peng; Wang, Duorun; Zhang, Xue; Sun, Minghao; Si, Qi; Kang, Yi; Ding, Ping; Si, Xingfeng.
Afiliación
  • Zhu C; MOE Key Laboratory of Biosystems Homeostasis & Protection, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, People's Republic of China.
  • Li W; 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.
  • Campos-Arceiz A; 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.
  • Dalsgaard B; Section for Molecular Ecology and Evolution, Globe Institute, University of Copenhagen, Copenhagen, Denmark.
  • Ren P; MOE Key Laboratory of Biosystems Homeostasis & Protection, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, People's Republic of China.
  • Wang D; 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.
  • Zhang X; MOE Key Laboratory of Biosystems Homeostasis & Protection, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, People's Republic of China.
  • Sun M; MOE Key Laboratory of Biosystems Homeostasis & Protection, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, People's Republic of China.
  • Si Q; MOE Key Laboratory of Biosystems Homeostasis & Protection, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, People's Republic of China.
  • Kang Y; 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.
  • Ding P; MOE Key Laboratory of Biosystems Homeostasis & Protection, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, People's Republic of China.
  • Si X; 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.
Proc Biol Sci ; 290(2003): 20231221, 2023 07 26.
Article en En | MEDLINE | ID: mdl-37464753
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.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Dispersión de Semillas Idioma: En Revista: Proc Biol Sci Asunto de la revista: BIOLOGIA Año: 2023 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Dispersión de Semillas Idioma: En Revista: Proc Biol Sci Asunto de la revista: BIOLOGIA Año: 2023 Tipo del documento: Article