Exploring the relation between remotely sensed vertical canopy structure and tree species diversity in Gabon. (9th September 2019)

• Record Type: Journal Article
• Authors: Marselis, Suzanne Mariëlle; Tang, Hao; Armston, John; Abernethy, Katharine; Alonso, Alfonso; Barbier, Nicolas; Bissiengou, Pulchérie; Jeffery, Kathryn; Kenfack, David; Labrière, Nicolas; Lee, Seung-Kuk; Lewis, Simon L; Memiaghe, Hervé; Poulsen, John R; White, Lee; Dubayah, Ralph
• Is Part Of: Environmental research letters. Volume 14:Number 9(2019:Sep.)
• Publication Date: 2019-09-09
• Subjects: biodiversity -- radar -- lidar -- LVIS -- ICESat -- GEDI -- TanDEM-X; Environmental sciences -- Periodicals; Human ecology -- Research -- Periodicals; Environmental health -- Periodicals; 333.7
• DOI: 10.1088/1748-9326/ab2dcd
• Languages: English
• ISSNs: 1748-9326

Abstract

Abstract: Mapping tree species diversity is increasingly important in the face of environmental change and biodiversity conservation. We explore a potential way of mapping this diversity by relating forest structure to tree species diversity in Gabon. First, we test the relation between canopy height, as a proxy for niche volume, and tree species diversity. Then, we test the relation between vertical canopy structure, as a proxy for vertical niche occupation, and tree species diversity. We use large footprint full-waveform airborne lidar data collected across four study sites in Gabon (Lopé, Mabounié, Mondah, and Rabi) in combination with in situ estimates of species richness (S) and Shannon diversity (H′). Linear models using canopy height explained 44% and 43% of the variation in S and H′ at the 0.25 ha resolution. Linear models using canopy height and the plant area volume density profile explained 71% of this variation. We demonstrate applications of these models by mapping S and H′ in Mondah using a simulated GEDI-TanDEM-X fusion height product, across the four sites using wall-to-wall airborne lidar data products, and across and between the study sites using ICESat lidar waveforms. The modeling results are encouraging in the context of developing pan-tropical structure-diversity models applicable to data from current and upcoming spaceborne remote sensing missions.