Quantitative assessment of plant-arthropod interactions in forest canopies: A plot-based approach

Martin Volf, Petr Klimeš, Greg P.A. Lamarre, Conor M. Redmond, Carlo L. Seifert, Tomokazu Abe, John Auga, Kristina Anderson-Teixeira, Yves Basset, Saul Beckett, Philip T. Butterill, Pavel Drozd, Erika Gonzalez-Akre, Ondřej Kaman, Naoto Kamata, Benita Laird-Hopkins, Martin Libra, Markus Manumbor, Scott E. Miller, Kenneth MolemOndřej Mottl, Masashi Murakami, Tatsuro Nakaji, Nichola S. Plowman, Petr Pyszko, Martin Šigut, Jan Šipoš, Robert Tropek, George D. Weiblen, Vojtech Novotny

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Research on canopy arthropods has progressed from species inventories to the study of their interactions and networks, enhancing our understanding of how hyper-diverse communities are maintained. Previous studies often focused on sampling individual tree species, individual trees or their parts. We argue that such selective sampling is not ideal when analyzing interaction network structure, and may lead to erroneous conclusions. We developed practical and reproducible sampling guidelines for the plot-based analysis of arthropod interaction networks in forest canopies. Our sampling protocol focused on insect herbivores (leaf-chewing insect larvae, miners and gallers) and non-flying invertebrate predators (spiders and ants). We quantitatively sampled the focal arthropods from felled trees, or from trees accessed by canopy cranes or cherry pickers in 53 0.1 ha forest plots in five biogeographic regions, comprising 6,280 trees in total. All three methods required a similar sampling effort and provided good foliage accessibility. Furthermore, we compared interaction networks derived from plot-based data to interaction networks derived from simulated non-plot-based data focusing either on common tree species or a representative selection of tree families. All types of non-plot-based data showed highly biased network structure towards higher connectance, higher web asymmetry, and higher nestedness temperature when compared with plot-based data. Furthermore, some types of non-plot-based data showed biased diversity of the associated herbivore species and specificity of their interactions. Plot-based sampling thus appears to be the most rigorous approach for reconstructing realistic, quantitative plant-arthropod interaction networks that are comparable across sites and regions. Studies of plant interactions have greatly benefited from a plot-based approach and we argue that studies of arthropod interactions would benefit in the same way. We conclude that plot-based studies on canopy arthropods would yield important insights into the processes of interaction network assembly and dynamics, which could be maximised via a coordinated network of plot-based study sites.

Original languageEnglish (US)
Article numbere0222119
JournalPloS one
Volume14
Issue number10
DOIs
StatePublished - Oct 1 2019

Bibliographical note

Funding Information:
MV acknowledges funding by Alexander von Humboldt Foundation and the Federal Ministry for Education and Research Ref.3.3-CZE-1192673HFST-P (https://www.humboldt-foundation.de). GPAL thanks Grant Agency of the Czech Republic 19-15645Y (https://gacr.cz) for the support during writing the article. PD and M? acknowledge the Ministry of Education, Youth and Sports of the Czech Republic LO1208 (http://www.msmt.cz), and the Institute of Environmental Technologies CZ.1.05/2.1.00/03.0100 (http://www.ietech.eu/ index.php/iet). NK acknowledges Japan Society for the Promotion of Science (Grant-in-Aid for Challenging Exploratory Research 26550087, https://www.jsps.go.jp). J? acknowledges long-term research development project RVO 67985939 from the Czech Academy of Sciences (https:// www.avcr.cz). GDW acknowledges US National Science Foundation grants DEB-0515678 and DEB-0841885. VN acknowledges the European Science Foundation grant 669609 (www.esf.org), Darwin Initiative project no. 22-002 (www.darwininitiative. org.uk), and Grant Agency of the Czech Republic 17-23862S (https://gacr.cz). RT was supported by the Charles University (PRIMUS/17/SCI/8 and UNCE204069). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Publisher Copyright:
Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

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