UAV‐Lidar reveals that canopy structure mediates the influence of edge effects on forest diversity, function and microclimate

Abstract

Widespread forest loss and fragmentation dramatically increases the proportion of forest areas located close to edges. Although detrimental, the precise extent and mechanisms by which edge proximity impacts remnant forests remain to be ascertained. By combining unmanned aerial vehicle laser scanning (UAV‐LS) with field data from 46 plots distributed at varying distances from the edge to the forest interior in a fragmented forest of New‐Caledonia, we investigated edge influence on forest structure, composition, function, above‐ground biomass (AGB) and microclimate. Using simple linear regressions, structural equation modelling and variance partitioning, we analysed the direct and indirect relationships between distance to edge, UAV‐LS‐derived canopy structural metrics, understorey microclimate, AGB, taxonomic and functional composition while accounting for the potential influence of fine‐scale variation in topography. We found that the distance to the closest forest edge was strongly correlated with canopy structure and that canopy structure was better correlated to forest composition, function, biomass and microclimate than distance to the closest forest edge. This suggests that the influence of edge is mediated by changes in canopy structure. Plots located near the edge exhibited a lower canopy with more gaps, higher microclimate extremes, lower biomass, lower taxonomic and functional diversity as well as denser wood and lower specific leaf area. UAV‐LS‐derived canopy structural metrics were relevant predictors of understorey microclimate, biomass and taxonomic and functional composition. Overall, the influence of topography was marginal compared to edge effects. Synthesis. Accounting for fine‐scale variation in canopy structure captured by UAV‐LS provides insights on the multiple edge impacts on key forest properties related to structure, diversity, function, biomass and microenvironmental conditions. Integrating UAV‐LS‐derived data can foster our understanding of cascading and interacting impacts of anthropogenic influence on tropical forest ecosystems and should help to improve conservation strategies and landscape management policies.

Towards complex applications of active remote sensing for ecology and conservation

“…1. Stand-, canopy-and tree-level structural analysis by active RS data (Atkins et al, 2023;Blanchard et al, 2023;Coverdale & Davies, 2023;Hardenbol et al, 2022;Schlund et al, 2022;Singh et al, 2023;Tatsumi et al, 2022;Zhang & Liu, 2023).…”

“…Of the accepted papers, four are published in Journal of Animal Ecology , two in Journal of Applied Ecology , four in Journal of Ecology and eight in Methods in Ecology and Evolution . When assessing the general trends being covered by the contributions, a few general (and partly overlapping) trends can be distinguished, including: Stand‐, canopy‐ and tree‐level structural analysis by active RS data (Atkins et al, 2023; Blanchard et al, 2023; Boucher et al, 2023; Coverdale & Davies, 2023; Hardenbol et al, 2022; Schlund et al, 2022; Singh et al, 2023; Tatsumi et al, 2022; Zhang & Liu, 2023). Climate‐mediated response of animal populations (from insects to ungulates) as investigated by active RS data (Brlík et al, 2022; Hockridge et al, 2022).…”

“…Among the nonterrestrial active remote sensing tools, state‐or‐the‐art UAV‐borne active payloads now enable capturing up to >1000 points/m 2 point densities, which is on the way to being effectively used for ecological applications like restoration (see novel insights in Robinson et al, 2022). Blanchard et al (2023) applied UAV‐borne laser scanner data to relate edge effects to forest structure, composition, function and microclimate, and showed correlations between distance to forest edge and canopy structure. They also showed how UAV‐LiDAR could help in predicting a range of microclimate, biomass and taxonomic and functional properties at very high spatial resolutions and relate them to the mediatory effect of forest edges, derived vertical structural attributes and related them to height and fractional cover.…”

“…Blanchard et al (2023) applied UAV-borne laser scanner data to relate edge effects to forest structure, composition, function and microclimate, and showed correlations between distance to forest edge and canopy structure. They also showed how UAV-LiDAR could help in predicting a range of microclimate, biomass and taxonomic and functional properties at very high spatial resolutions and relate them to the mediatory effect of forest edges, derived vertical structural attributes and related them to height and fractional cover.In savannas,Boucher et al (2023) compared multiple UAV-LiDAR point clouds sampled at various flight altitudes and patterns and suggested flight altitude to be of greater effect than flight pattern on the derived savanna structural metrics.…”

Overgrazing on unmanaged grassland interfered with the restoration of adjacent grazing-banned grassland by affecting soil properties and microbial community

“…Light, energy utilization rate, soil temperature, and soil physicochemical properties in such areas changed with the changes in the biological community ( Schmidt et al, 2017 ; Koelemeijer et al, 2023 ). Thus, edge effects induced by anthropogenic interference have been confirmed to negatively influence species diversity, community dynamics, and ecosystem functions ( Guerra et al, 2017 ; Krishnadas et al, 2018 ; Fischer et al, 2021 ; Blanchard et al, 2023 ; Lapola et al, 2023 ).…”