Detecting successional changes in tropical forest structure using GatorEye drone-borne lidar

Author(s):Show less -

Alves de Almeida, Danilo Roberti ^{[1, 2]} ; Almeyda Zambrano, Angelica Maria ^[3] ; Broadbent, Eben North ^[2] ; Wendt, Amanda L. ^{[4, 5]} ; Foster, Paul ^{[6, 7]} ; Wilkinson, Benjamin E. ^[8] ; Salk, Carl ^[9] ; Papa, Daniel de Almeida ^[10] ; Stark, Scott Christopher ^[11] ; Valbuena, Ruben ^[12] ; Gorgens, Eric Bastos ^[13] ; Silva, Carlos Alberto ^{[14, 15]} ; Santin Brancalion, Pedro Henrique ^[1] ; Fagan, Matthew ^[16] ; Meli, Paula ^{[1, 17]} ; Chazdon, Robin ^{[18, 19]}

Affiliation:Show less -

^[1] Univ Sao Paulo USP ESALQ, Luiz de Queiroz Coll Agr, Dept Forest Sci, Piracicaba, SP - Brazil

^[2] Univ Florida, Sch Forest Resources & Conservat, Spatial Ecol & Conservat Lab, Gainesville, FL 32611 - USA

^[3] Univ Florida, Dept Tourism Recreat & Sport Management, Spatial Ecol & Conservat Lab, Gainesville, FL - USA

^[4] Org Trop Studies, San Pedro - Costa Rica

^[5] EARTH Univ, Guacimo - Costa Rica

^[6] Univ Michigan, Dept Ecol & Evolutionary Biol, Ann Arbor, MI 48109 - USA

^[7] Reserva Ecol Bijagual, Sarapiqui - Costa Rica

^[8] Univ Florida, Sch Forest Resources & Conservat, Geomat Program, Gainesville, FL - USA

^[9] Univ Agr Sci, Alnarp - Sweden

^[10] EMBRAPA Acre, Rio Branco - Brazil

^[11] Michigan State Univ, Dept Forestry, E Lansing, MI 48824 - USA

^[12] Bangor Univ, Sch Nat Sci, Bangor, Gwynedd - Wales

^[13] Fed Univ Jequitinhonha & Mucuri Valleys UFVJM, Dept Forestry, Diamantina - Brazil

^[14] Univ Florida, Sch Forest Resources & Conservat, Gainesville, FL 32611 - USA

^[15] Univ Maryland, Dept Geog Sci, College Pk, MD 20742 - USA

^[16] Univ Maryland Baltimore Cty, Baltimore, MD 21228 - USA

^[17] Univ La Frontera, Dept Forest Sci, Temuco - Chile

^[18] Univ Connecticut, Dept Ecol & Evolutionary Biol, Storrs, CT - USA

^[19] Univ Sunshine Coast, Trop Forests & People Res Ctr, Sippy Downs, Qld - Australia

• Document type: Journal article
• Source: Biotropica; v. 52, n. 6 JUL 2020.
• Web of Science Citations: 4

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. (AU)

• FAPESP's process: 19/14697-0 - Monitoring the demography and diversity of forests undergoing restoration using a drone-lidar-hyperspectral system
• Grantee: Danilo Roberti Alves de Almeida
• Support Opportunities: Scholarships abroad - Research Internship - Post-doctor
• FAPESP's process: 18/21338-3 - Monitoring forest landscape restoration from unmanned aerial vehicles using Lidar and hyperspectral remote sensing
• Grantee: Danilo Roberti Alves de Almeida
• Support Opportunities: Scholarships in Brazil - Post-Doctoral