Canopy area of large trees explains aboveground biomass variations across neotropical forest landscapes

Abstract

Abstract. Large tropical trees store significant amounts of carbon in woody components and their distribution plays an important role in forest carbon stocks and dynamics. Here, we explore the properties of a new lidar-derived index, the large tree canopy area (LCA) defined as the area occupied by canopy above a reference height. We hypothesize that this simple measure of forest structure representing the crown area of large canopy trees could consistently explain the landscape variations in forest volume and aboveground biomass (AGB) across a range of climate and edaphic conditions. To test this hypothesis, we assembled a unique dataset of high-resolution airborne light detection and ranging (lidar) and ground inventory data in nine undisturbed old-growth Neotropical forests, of which four had plots large enough (1 ha) to calibrate our model. We found that the LCA for trees greater than 27 m (∼ 25–30 m) in height and at least 100 m2 crown size in a unit area (1 ha), explains more than 75 % of total forest volume variations, irrespective of the forest biogeographic conditions. When weighted by average wood density of the stand, LCA can be used as an unbiased estimator of AGB across sites (R2 = 0.78, RMSE = 46.02 Mg ha−1, bias = −0.63 Mg ha−1). Unlike other lidar-derived metrics with complex nonlinear relations to biomass, the relationship between LCA and AGB is linear and remains unique across forest types. A comparison with tree inventories across the study sites indicates that LCA correlates best with the crown area (or basal area) of trees with diameter greater than 50 cm. The spatial invariance of the LCA–AGB relationship across the Neotropics suggests a remarkable regularity of forest structure across the landscape and a new technique for systematic monitoring of large trees for their contribution to AGB and changes associated with selective logging, tree mortality and other types of tropical forest disturbance and dynamics.

Ground and Volume Decomposition as a Proxy for AGB from P-Band SAR Data

“…The observed sensitivity expressed as ∂AGB/∂σ was found to be about 50 Mg/ha per dB across the range of AGB values from about 200 to 500 t/ha. These findings are supported by recent ecological studies in dense tropical forests revealing that: Correlation between AGB and the area occupied at different heights by large trees (as derived from LiDAR) is maximal at a height of about 30 m [25]; about one-third of the total volume tends to be concentrated at the same height above the ground [26]. These results are further confirmed by the prediction obtained with the TROLL ecological model that for dense tropical forests the fraction of biomass contained between 20 m and 40 m accounts for about 35% to 40% of the total AGB.…”

Quantifier les dimensions des houppiers à l’aide d’images aériennes à haute résolution pour estimer l’accroissement diamétrique des arbres dans les forêts d’Afrique centrale

“…L'utilisation d'ortho-images à haute résolution s'avère prometteuse pour quantifier et spatialiser la biomasse stockée en forêt tropicale, ce qui constitue un prérequis essentiel pour mettre en oeuvre des politiques environnementales comme le mécanisme REDD+ (Réduction des effets dus à la déforestation et à la dégradation des forêts) (Birdsey et al, 2013). Bien que cet aspect n'ait pas été testé dans cette étude, il a déjà été montré à plusieurs reprises que la taille des houppiers est un bon prédicteur de la biomasse, à l'échelle de l'arbre (Goodman et al, 2014 ;Jucker et al, 2017 ;Ploton et al, 2016) ou de la parcelle (Meyer et al, 2018).…”

Carbon storage potential in degraded forests of Kalimantan, Indonesia

“…where MCH is the top mean forest height (m), LCR represents the percentage of each 1 ha pixel covered by large trees (height>27 m and crown radius >5.6 m 2 , (Meyer et al 2018) and PC is the percentage of vegetation cover taller than 5 m height. These products were also developed using the RF algorithm trained by lidar-derived samples (SI1.4).…”