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Dansereau G, Barros C, Poisot T. Spatially explicit predictions of food web structure from regional-level data. Philos Trans R Soc Lond B Biol Sci 2024; 379:20230166. [PMID: 39034704 PMCID: PMC11293859 DOI: 10.1098/rstb.2023.0166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Revised: 12/18/2023] [Accepted: 01/23/2024] [Indexed: 07/23/2024] Open
Abstract
Knowledge about how ecological networks vary across global scales is currently limited given the complexity of acquiring repeated spatial data for species interactions. Yet, recent developments in metawebs highlight efficient ways to first document possible interactions within regional species pools. Downscaling metawebs towards local network predictions is a promising approach to using the current data to investigate the variation of networks across space. However, issues remain in how to represent the spatial variability and uncertainty of species interactions, especially for large-scale food webs. Here, we present a probabilistic framework to downscale a metaweb based on the Canadian mammal metaweb and species occurrences from global databases. We investigated how our approach can be used to represent the variability of networks and communities between ecoregions in Canada. Species richness and interactions followed a similar latitudinal gradient across ecoregions but simultaneously identified contrasting diversity hotspots. Network motifs revealed additional areas of variation in network structure compared with species richness and number of links. Our method offers the potential to bring global predictions down to a more actionable local scale, and increases the diversity of ecological networks that can be projected in space. This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.
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Affiliation(s)
- Gabriel Dansereau
- Département de Sciences Biologiques, Université de Montréal, Montreal, QuebecH2V 0B3, Canada
- Quebec Centre for Biodiversity Science, Montréal, QuebecH3A 1B1, Canada
| | - Ceres Barros
- Department of Forest Resources Management, University of British Columbia, Vancouver, British ColumbiaV6T 1Z4, Canada
| | - Timothée Poisot
- Département de Sciences Biologiques, Université de Montréal, Montreal, QuebecH2V 0B3, Canada
- Quebec Centre for Biodiversity Science, Montréal, QuebecH3A 1B1, Canada
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Zhu C, Li W, Campos-Arceiz A, Dalsgaard B, Ren P, Wang D, Zhang X, Sun M, Si Q, Kang Y, Ding P, Si X. The reliability of regional ecological knowledge to build local interaction networks: a test using seed-dispersal networks across land-bridge islands. Proc Biol Sci 2023; 290:20231221. [PMID: 37464753 PMCID: PMC10354482 DOI: 10.1098/rspb.2023.1221] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 06/21/2023] [Indexed: 07/20/2023] Open
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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Affiliation(s)
- Chen Zhu
- MOE Key Laboratory of Biosystems Homeostasis & Protection, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, People's Republic of China
| | - Wande Li
- 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
| | - Ahimsa Campos-Arceiz
- 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
| | - Bo Dalsgaard
- Section for Molecular Ecology and Evolution, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Peng Ren
- MOE Key Laboratory of Biosystems Homeostasis & Protection, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, People's Republic of China
| | - Duorun Wang
- 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
| | - Xue Zhang
- MOE Key Laboratory of Biosystems Homeostasis & Protection, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, People's Republic of China
| | - Minghao Sun
- MOE Key Laboratory of Biosystems Homeostasis & Protection, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, People's Republic of China
| | - Qi Si
- MOE Key Laboratory of Biosystems Homeostasis & Protection, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, People's Republic of China
| | - Yi Kang
- 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
| | - Ping Ding
- MOE Key Laboratory of Biosystems Homeostasis & Protection, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, People's Republic of China
| | - Xingfeng Si
- 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
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Wang P, Li S, Yang X, Si X, Li W, Shu W, Jiang L. Spatial scaling of soil microbial co-occurrence networks in a fragmented landscape. MLIFE 2023; 2:209-215. [PMID: 38817624 PMCID: PMC10989968 DOI: 10.1002/mlf2.12073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 03/23/2023] [Accepted: 04/02/2023] [Indexed: 06/01/2024]
Abstract
Habitat loss has been a primary threat to biodiversity. However, species do not function in isolation but often associate with each other and form complex networks. Thus, revealing how the network complexity and stability scale with habitat area will give us more insights into the effects of habitat loss on ecosystems. In this study, we explored the relationships between the island area and the network complexity and stability of soil microbes. We found that the complexity and stability of soil microbial co-occurrence networks scale positively with island area, indicating that habitat loss will potentially simplify and destabilize soil microbial networks.
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Affiliation(s)
- Pandeng Wang
- State Key Laboratory of Biocontrol, School of Ecology & School of Life SciencesSun Yat‐Sen UniversityGuangzhouChina
- School of Biological SciencesGeorgia Institute of TechnologyAtlantaGeorgiaUSA
| | - Shao‐Peng Li
- Zhejiang Tiantong Forest Ecosystem National Observation and Research Station, School of Ecological and Environmental SciencesEast China Normal UniversityShanghaiChina
- Institute of Eco‐Chongming (IEC)ShanghaiChina
| | - Xian Yang
- State Key Laboratory of Biocontrol, School of Ecology & School of Life SciencesSun Yat‐Sen UniversityGuangzhouChina
- School of Biological SciencesGeorgia Institute of TechnologyAtlantaGeorgiaUSA
| | - Xingfeng Si
- Zhejiang Tiantong Forest Ecosystem National Observation and Research Station, School of Ecological and Environmental SciencesEast China Normal UniversityShanghaiChina
- Institute of Eco‐Chongming (IEC)ShanghaiChina
| | - Wen‐Jun Li
- State Key Laboratory of Biocontrol, School of Ecology & School of Life SciencesSun Yat‐Sen UniversityGuangzhouChina
| | - Wensheng Shu
- School of Life SciencesSouth China Normal UniversityGuangzhouChina
| | - Lin Jiang
- School of Biological SciencesGeorgia Institute of TechnologyAtlantaGeorgiaUSA
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Durand‐Bessart C, Cordeiro NJ, Chapman CA, Abernethy K, Forget P, Fontaine C, Bretagnolle F. Trait matching and sampling effort shape the structure of the frugivory network in Afrotropical forests. THE NEW PHYTOLOGIST 2023; 237:1446-1462. [PMID: 36377098 PMCID: PMC10108259 DOI: 10.1111/nph.18619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 10/13/2022] [Indexed: 06/16/2023]
Abstract
Frugivory in tropical forests is a major ecological process as most tree species rely on frugivores to disperse their seeds. However, the underlying mechanisms driving frugivore-plant networks remain understudied. Here, we evaluate the data available on the Afrotropical frugivory network to identify structural properties, as well as assess knowledge gaps. We assembled a database of frugivory interactions from the literature with > 10 000 links, between 807 tree and 285 frugivore species. We analysed the network structure using a block model that groups species with similar interaction patterns and estimates interaction probabilities among them. We investigated the species traits related to this grouping structure. This frugivory network was simplified into 14 tree and 14 frugivore blocks. The block structure depended on the sampling effort among species: Large mammals were better-studied, while smaller frugivores were the least studied. Species traits related to frugivory were strong predictors of the species composition of blocks and interactions among them. Fruits from larger trees were consumed by most frugivores, and large frugivores had higher probabilities to consume larger fruits. To conclude, this large-scale frugivory network was mainly structured by species traits involved in frugivory, and as expected by the distribution areas of species, while still being limited by sampling incompleteness.
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Affiliation(s)
- Clémentine Durand‐Bessart
- Biogeosciences, UMR 6282Université Bourgogne Franche Comte‐CNRS21000DijonFrance
- Centre d'Ecologie et des Sciences de la ConservationCESCO, UMR 7204, MNHN‐CNRS‐SU75005ParisFrance
| | - Norbert J. Cordeiro
- Department of Biology (mc WB 816)Roosevelt University430 S. Michigan AvenueChicagoIL60605USA
- Science & EducationThe Field Museum1400 S. Lake Shore DriveChicagoIL60605USA
| | - Colin A. Chapman
- Wilson Center1300 Pennsylvania Avenue NWWashingtonDC20004USA
- Department of AnthropologyCenter for the Advanced Study of Human Paleobiology, The George Washington UniversityWashingtonDC20037USA
- School of Life SciencesUniversity of KwaZulu‐NatalScottsville3201PietermaritzburgSouth Africa
- Shaanxi Key Laboratory for Animal ConservationNorthwest University710069Xi'anChina
| | - Katharine Abernethy
- African Forest Ecology Group, School of Natural SciencesUniversity of StirlingStirlingFK9 4LAUK
- Institut de Recherches en Ecologie TropicaleCENARESTGros Bouquet2144LibrevilleGabon
| | - Pierre‐Michel Forget
- Muséum National d'Histoire NaturelleUMR 7179 MECADEV CNRS‐MNHN1 Avenue du Petit Château91800BrunoyFrance
| | - Colin Fontaine
- Centre d'Ecologie et des Sciences de la ConservationCESCO, UMR 7204, MNHN‐CNRS‐SU75005ParisFrance
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