Detecting successional changes in tropical forest structure using GatorEye drone-borne lidar
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Date
2020-07-30
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Citation of Original Publication
de Almeida, DRA, Almeyda Zambrano, AM, Broadbent, EN, et al. Detecting successional changes in tropical forest structure using GatorEye drone-borne lidar. Biotropica. 2020; 52: 1155– 1167. https://doi.org/10.1111/btp.12814
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This is the peer reviewed version of the following article: de Almeida, DRA, Almeyda Zambrano, AM, Broadbent, EN, et al. Detecting successional changes in tropical forest structure using GatorEye drone-borne lidar. Biotropica. 2020; 52: 1155– 1167. https://doi.org/10.1111/btp.12814, which has been published in final form at https://doi.org/10.1111/btp.12814. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.
Access to this item will begin on 7/30/2022
Access to this item will begin on 7/30/2022
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Abstract
Drone-based remote sensing is a promising new technology that combines the benefits of ground-based and satellite-derived forest monitoring by collecting fine-scale data over relatively large areas in a cost-effective manner. Here, we explore the potential of the GatorEye drone-lidar system to monitor tropical forest succession by canopy structural attributes including canopy height, spatial heterogeneity, gap fraction, leaf area density (LAD) vertical distribution, canopy Shannon index (an index of LAD), leaf area index (LAI), and understory LAI. We focus on these variables’ relationship to aboveground biomass (AGB) stocks and species diversity. In the Caribbean lowlands of northeastern Costa Rica, we analyze nine tropical forests stands (seven second-growth and two old-growth). Stands were relatively homogenous in terms of canopy height and spatial heterogeneity, but not in their gap fraction. Neither species density nor tree community Shannon diversity index was significantly correlated with the canopy Shannon index. Canopy height, LAI, and AGB did not show a clear pattern as a function of forest age. However, gap fraction and spatial heterogeneity increased with forest age, whereas understory LAI decreased with forest age. Canopy height was strongly correlated with AGB. The heterogeneous mosaic created by successional forest patches across human-managed tropical landscapes can now be better characterized. Drone-lidar systems offer the opportunity to improve assessment of forest recovery and develop general mechanistic carbon sequestration models that can be rapidly deployed to specific sites, an essential step for monitoring progress within the UN Decade on Ecosystem Restoration.