TY - JOUR

T1 - The reliability of regional ecological knowledge to build local interaction networks

T2 - a test using seed-dispersal networks across land-bridge islands

AU - Zhu, Chen

AU - Li, Wande

AU - Campos-Arceiz, Ahimsa

AU - Dalsgaard, Bo

AU - Ren, Peng

AU - Wang, Duorun

AU - Zhang, Xue

AU - Sun, Minghao

AU - Si, Qi

AU - Kang, Yi

AU - Ding, Ping

AU - Si, Xingfeng

N1 - Publisher Copyright: © 2023 The Author(s).

PY - 2023

Y1 - 2023

N2 - 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.

AB - 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.

KW - ecological networks

KW - habitat fragmentation

KW - island biogeography

KW - local interaction rewiring

KW - plant-animal interactions

KW - seed dispersal

U2 - 10.1098/rspb.2023.1221

DO - 10.1098/rspb.2023.1221

M3 - Journal article

C2 - 37464753

AN - SCOPUS:85165520844

VL - 290

JO - Proceedings of the Royal Society B: Biological Sciences

JF - Proceedings of the Royal Society B: Biological Sciences

SN - 0962-8452

IS - 2003

M1 - 20231221

ER -