Inferring plant–plant interactions using remote sensing

Bin J.W. Chen, Shuqing N. Teng, Guang Zheng, Lijuan Cui, Shao peng Li, Arie Staal, Jan U.H. Eitel, Thomas W. Crowther, Miguel Berdugo, Lidong Mo, Haozhi Ma, Lalasia Bialic-Murphy, Constantin M. Zohner, Daniel S. Maynard, Colin Averill, Jian Zhang, Qiang He, Jochem B. Evers, Niels P.R. Anten, Hezi YizhaqIlan Stavi, Eli Argaman, Uri Basson, Zhiwei Xu, Ming Juan Zhang, Kechang Niu, Quan Xing Liu, Chi Xu

Research output: Contribution to journalReview articlepeer-review

4 Scopus citations

Abstract

Rapid technological advancements and increasing data availability have improved the capacity to monitor and evaluate Earth's ecology via remote sensing. However, remote sensing is notoriously ‘blind’ to fine-scale ecological processes such as interactions among plants, which encompass a central topic in ecology. Here, we discuss how remote sensing technologies can help infer plant–plant interactions and their roles in shaping plant-based systems at individual, community and landscape levels. At each of these levels, we outline the key attributes of ecosystems that emerge as a product of plant–plant interactions and could possibly be detected by remote sensing data. We review the theoretical bases, approaches and prospects of how inference of plant–plant interactions can be assessed remotely. At the individual level, we illustrate how close-range remote sensing tools can help to infer plant–plant interactions, especially in experimental settings. At the community level, we use forests to illustrate how remotely sensed community structure can be used to infer dominant interactions as a fundamental force in shaping plant communities. At the landscape level, we highlight how remotely sensed attributes of vegetation states and spatial vegetation patterns can be used to assess the role of local plant–plant interactions in shaping landscape ecological systems. Synthesis. Remote sensing extends the domain of plant ecology to broader and finer spatial scales, assisting to scale ecological patterns and search for generic rules. Robust remote sensing approaches are likely to extend our understanding of how plant–plant interactions shape ecological processes across scales—from individuals to landscapes. Combining these approaches with theories, models, experiments, data-driven approaches and data analysis algorithms will firmly embed remote sensing techniques into ecological context and open new pathways to better understand biotic interactions.

Original languageEnglish
Pages (from-to)2268-2287
Number of pages20
JournalJournal of Ecology
Volume110
Issue number10
DOIs
StatePublished - 1 Oct 2022

Keywords

  • alternative stable states
  • community structure
  • competition
  • facilitation
  • non-invasive imaging
  • plant–plant interactions
  • remote sensing
  • self-organization
  • spatial pattern
  • transient dynamics

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Ecology
  • Plant Science

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