Inferring plant–plant interactions using remote sensing

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.

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“…2007). The sizes and numbers of those patches can be readily quantified from remote-sensing images, and such patterns can be used to infer whether facilitation occurs between plants (Chen et al . 2022; Xu et al .…”

“…Arid systems provide a good illustration of this approach: in those systems, plants often facilitate each other, which results in their aggregation into patches, and has important consequences for the resilience of those systems to changes in aridity (Kéfi et al 2007). The sizes and numbers of those patches can be readily quantified from remote-sensing images, and such patterns can be used to infer whether facilitation occurs between plants (Chen et al 2022;Xu et al 2015). This is traditionally done by summarizing the spatial structure into spatial statistics, such as spatial autocorrelation (Sankaran et al 2017) or type of patch size distribution (Kéfi et al 2011;Siteur et al 2023), and linking the observed changes in those metrics to theoretical results (Kéfi et al 2011;Scanlon et al 2007).…”

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“…Close-range remote sensing, the application of remote sensing tools at small spatial scales [ 15 ], includes imaging technologies that are not conventionally classified as remote sensing like close-range photogrammetry and terrestrial LiDAR. Close-range remote sensing can be used to enhance morphological and physiological measurement efficiency for individual plants, and it is a valuable tool for verifying sensing reliability at larger scales [ 16 ].…”

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“…Among the most promising tools for scale-up of ecological processes, remote sensing has been used across different ecological scales and systems 34 – 38 . In salt marsh, application of remote sensing tools (e.g., satellite and unmanned aerial vehicle UAV images) has been limited to plant community discrimination 39 , 40 , plant phenology detection 41 , 42 , plant-plant interactions 43 and to survey overall ecosystem properties 44 . In these ecosystems, while remote sensing has been applied for the monitoring of some gross ecosystem properties (e.g., net primary production), linking the mechanistic response of individual plants (e.g., growth traits, physiological response) to the ecosystem level remains unexplored and promising.…”