DOI: 10.5061/dryad.1jwstqjtc
title: From canopy complementarity to asymmetric competition: the negative relationship between structural diversity and productivity during succession

description: 1. Positive relationships between structural diversity and forest
 productivity have been documented in controlled experiments and early
 secondary forests, however, negative relationships have also been observed
 in late successional forests. The mechanisms causing observed
 relationships between structural diversity and productivity are not well
 established, but complementarity among crowns and asymmetric competition
 have been suggested. 2. We used LiDAR and repeated census data to examine
 relationship between canopy structural diversity and productivity in nine
 1-ha subtropical forest plots along a disturbance gradient in southeastern
 China. We quantified the relative importance of community composition,
 species diversity, canopy structural diversity, leaf area index (LAI), and
 disturbance regime on productivity using piecewise structural equation
 modelling. We also tested how vertical leaf area distribution effected
 productivity. 3. Contrary to many prior observations, we found a negative
 relationship between canopy structural diversity and forest productivity.
 The negative effect may stem from asymmetric competition between overstory
 and understory leaves, leading to a lower leaf area efficiency (i.e., wood
 production per leaf area). Asymmetric competition was suggested by a
 negative relationship between understory leaf area and total productivity.
 Changes in community composition over the disturbance gradient, but not
 species diversity, had a significant effect on productivity. 4. Synthesis.
 Our study suggests that leaf area and canopy structural diversity have
 contrasting effects on productivity in this subtropical forest, and this
 need to be considered when estimating rates of carbon sequestration in
 secondary forests. The negative effect of asymmetric competition on
 productivity is comparable to that of the shift in species composition
 over succession, highlighting the role of canopy structural diversity in
 shaping forest productivity.
description: We established nine 1-ha (100m × 100m) permanent plots in GNNR
 that included twice-logged forest, once-logged forest and old-growth
 forest (three 1-ha plots for each type). We divided each 1-ha plot into 16
 25m×25m quadrats and calculated coarse woody productivity in each quadrat
 using all individuals with DBH larger than 5cm. We estimated the
 above-ground biomass (AGB) of each individual stem using species-specific
 allometric equations for some species (Lin<i> et al.</i>,
 2015) and the non-species specific allometric equation of Chave<i>
 et al.</i> (2005) for other species (detailed descriptions can be
 found in Lin<i> et al.</i> (2015)). The coarse woody
 productivity (CWP) per quadrat was quantified as the sum of the increment
 of individual alive and the AGB of recruits divided by the census length
 in years following the methods of Chisholm<i> et al.</i>
 (2013). LiDAR data of the ~3 km<sup>2</sup> of the GNNR were
 collected in September 2016 using a UAV-borne LiDAR system with a Velodyne
 Puck VLP-16 sensor, yielding a wavelength of 905 nm and an average point
 density of 19.7 points m<sup>−2 </sup>from approximately 200 m
 above ground. More details about LiDAR data acquisition can be found in
 Guo<i> et al.</i> (2017). We clipped each nine 1-ha plot with
 a 20m buffer from the entire LiDAR data. To eliminate the effects of point
 density at different plots, we subsampled plots with higher point density
 to ensure all plots had as similar point density as possible. We used
 first returns to calculate LAI, canopy height, and several indices
 representing canopy structural complexity such as entropy and standardized
 deviation of canopy height (height.sd) at a spatial grain of 25 m × 25
 m.