DOI: 10.5061/dryad.fbg79cnzk
title: Low-severity winds reduce tropical forest structural complexity regardless of climate, topography or forest age

description: Forests are often exposed to regular, non-severe winds (chronic wind
 exposure), yet the effect of such winds on canopy structure in tropical
 forests remains understudied. The height and structural complexity of a
 forest canopy are strongly and positively correlated with biodiversity and
 carbon accumulation. Understanding the drivers of canopy structural
 complexity across broad environmental gradients can therefore improve the
 mapping and modeling of diversity and carbon dynamics. Here we predict the
 height and structural complexity of forests in the heterogeneous island of
 Puerto Rico, with a particular focus on the impacts of chronic wind
 exposure. To do so, we used remote sensing to randomly sample ~20,000,
 0.28 ha forested sites stratified by forest age, and used airborne LiDAR
 data from 2016 to quantify canopy height and a key metric of structural
 complexity, rugosity – the standard deviation in canopy height. We then
 ran random forest models to predict canopy height and rugosity based on
 chronic wind exposure, forest age, mean annual precipitation, elevation,
 slope, soil type, soil available water storage, and exposure to two
 previous hurricanes (in 1989 and 1998). Canopy height was 4 m taller on
 average (41%) between forests aged 17-25 years and old-growth forests and
 by 4 m on average (41%) between 1,000 and 2,000 mm-yr precipitation,
 leveling off at 2,000 mm-yr. Height was 2.12 m (16%) shorter on average
 between sites exposed to chronic winds and protected sites after
 accounting for all other factors. Rugosity was 1 m (32%) greater between
 the tallest and shortest forests, by 0.5 m (15%) between 1,000 and 2,000
 mm-yr precipitation, and smaller by 0.5 m (15%) between forests above and
 below 1,000 m elevation. Rugosity was highest in forests of intermediate
 age (25-40 years), and lowest in old-growth forests, possibly because of
 higher elevation and chronic wind exposure in old-growth forests. We found
 no effect of slope, soil characteristics or previous hurricane exposure on
 either height or rugosity. Our results suggest that alongside forest age
 and climate context, chronic wind exposure plays an integral role in
 shaping the structure and carbon cycle of tropical forests.
description: We measured canopy height and rugosity for ~20,000 30 m-radius
 forested sites in Puerto Rico using airborne LiDAR data from a 2016 flight
 collected by the USGS (Carswell Jr. 2016) with aggregate nominal pulse
 spacing of ≤0.35 m and pulse density of ≥8.0
 pulses/m<sup>2</sup>. We then used 16 years of wind direction
 and speed data from 9 weather stations to calculate a map of chronic wind
 exposure using a 30 m DEM from the USGS. We then ran random forest models
 to predict drivers of canopy height and rugosity based on chronic wind
 exposure, mean annual precipitation, forest age class, elevation, slope,
 soil type, soil available water storage, and exposure to two previous
 hurricanes (Hugo in 1989 and Georges in 1998).
description: # Drivers of tropical forest height and canopy structural complexity
 across heterogeneous landscapes: --- This dataset was used for analyses
 and figures in Ankori-Karlinsky et al., 2023 in *Ecosystems*. The dataset
 contains 20,660 30 m-radius forested sites in Puerto Rico stratified by
 forest age class (see Martinuzzi et al., 2020 for details). For each site,
 we quantified canopy height and rugosity using 2016 airborne USGS LiDAR
 data. The dataset was used to predict both metrics based on forest age,
 exposure to chronic winds, precipitation, topography, soil properties, and
 exposure to previous hurricanes. ## Metadata Each row is a 30 m-radius
 site. Below is information on each column: *x* - longitude in NAD83 (EPSG
 4269) *y* - latitude in NAD83 *Forest_Age* - Forest age class (1-5): *
 5-16 years * 17-25 years * 26-39 years * 40-65 years * 66+ years *CHM* -
 Mean height (m) from canopy height model *Max_Height* - Maximum height (m)
 *Rugosity* - Stdev in height from 15m moving windows *MAP* - Mean annual
 precipitation (mm/year) from PRISM *Wind_Binary* - Protected (0) vs.
 exposed (1) *Elev_Mean* - Mean elevation (m) from USGS DEM *Slope* - Mean
 slope (in degrees) *Soil* - Soil type (e.g. volcanic vs. limestone) from
 USGS *Hugo/Georges exposure* - Mean exposure from 0-1 to hurricanes Hugo
 (1989) and Georges (1998) from Boose et al., (2004) *AWS_mean* - Available
 water storage in soils from gSSURGO ## Sharing/access Information Please
 cite Ankori-Karlinsky et al., 2023 *Ecosystems* if you use these data.