Prediction of forest aboveground net primary production from high‐resolution vertical leaf‐area profiles

Abstract

Temperature and precipitation explain about half the variation in aboveground net primary production (ANPP) among tropical forest sites, but determinants of remaining variation are poorly understood. Here, we test the hypothesis that the amount of leaf area, and its vertical arrangement, predicts ANPP when other variables are held constant. Using measurements from airborne lidar in a lowland Neotropical rain forest, we quantify vertical leaf‐area profiles and develop models of ANPP driven by leaf area and other measurements of forest structure. Vertical leaf‐area profiles predict 38% of the variation among plots. This number is 4.5 times greater than models using total leaf area (disregarding vertical arrangement) and 2.1 times greater than models using canopy height alone. Furthermore, ANPP predictions from vertical leaf‐area profiles were less biased than alternate metrics. Variation in ANPP not attributable to temperature or precipitation can be predicted by the vertical distribution of leaf area in this system.

Defining a spectrum of integrative trait‐based vegetation canopy structural types

“…Our results indicate that CSTs can provide additional explanatory power beyond that of broad eco‐climatic domains and forest functional types in predicting ecosystem processes and functions. The importance of CSTs was especially apparent when assessed within domains, suggesting that variation in canopy physical structure could be an particularly important predictor of functioning at the landscape scale within regions (Cushman & Kellner ). Although individual canopy traits have previously been shown to be highly influential on ecosystem functions (Reich ; Atkins et al ; Jucker et al ), a focus on multivariate suites of canopy traits could help further elucidate fundamental ecological mechanisms underpinning ecosystem structure–function relationships and isolate the distinct role of physical structure (e.g.…”

“…Reich 2012). However, vegetation canopies are inherently three-dimensional (3D) and the integrated vertical and horizontal arrangement of canopy elements provides additional predictive capacity on ecosystem processes and functions such as light harvesting and light use efficiency (LUE; Ellsworth & Reich 1993;Ishii & Asano 2010;Fotis & Curtis 2017;Atkins et al 2018b), air movement (Reich et al 1990;Parker et al 2004b;Maurer et al 2015), vertical temperature and humidity gradients (Niinemets 2007), productivity (Hardiman et al 2011;Cushman & Kellner 2019;Gough et al 2019), and disturbance resilience (Gough et al 2013;Hardiman et al 2013b;Fahey et al 2016). There is no widely accepted framework or set of metrics to characterise the 3D structure of vegetation canopies (Nadkarni et al 2008).…”

“…1a; Whittaker 1970). These vegetation structural types can be viewed as an agglomeration of canopy traits describing the arrangement of vegetation elements in canopy space and generally relate to three primary components of variation: canopy height, vertical layering and horizontal openness/patchiness (Aber et al 1982;Brokaw & Lent 1999;Ehbrecht et al 2016;Paynter et al 2018;Cushman & Kellner 2019), as well as higher-order metrics that combine or describe variation in these traits to characterise the arrangement of canopy elements in two-dimensional (2D) or 3D space (Hardiman et al 2011;Chen et al 2012;Seidel et al 2016).…”

Estimating Tree Diameters from an Autonomous Below-Canopy UAV with Mounted LiDAR

“…Recent years have seen major advances in the use of cameras [10,11] and LiDAR [12][13][14] for forest scanning, and in the software used to turn the scans into digital models from which forests' physical structures can be measured [1,3,15]. Most UAV-based surveys of forests to date have used above-canopy UAVs [2,10,12,[16][17][18][19][20][21]. These are effective in temperate and boreal forests [2,20,21], where trees are deciduous or foliage is relatively sparse, so that sensors can penetrate through the entire forest profile.…”

Prediction of Biomass in Dry Tropical Forests: An Approach on the Importance of Total Height in the Development of Local and Pan-tropical Models

“…in locations where no generic allometric equation is available, or to develop locationspecific equations. Another important point that must be considered for the development of equations is related to the intra and interspecific factors of the species, such as variations in the basic wood density (Henry et al 2010; Bastin et al 2015; Ali and Mattsson 2018); the tree canopy (Duncanson et al 2010; Gara et al 2014; Bastin et al 2014; Salas-Morales et al2018), leaf area index and height profiles(Helmer et al 2010;Greaves et al 2015; Wagner et al 2016;Cushman and Kellner 2019). Considering that such factors may still be influenced by changes in structural parameters such as richness, density, frequency and dominance, the development of specific allometric equations for locations and even more at the species level is fundamental for understanding the concentration of carbon stocks(Abich et al 2018).…”