Forest drought resistance distinguished by canopy height

Abstract

How are the survival and growth of trees under severe drought affected by their size? While some studies have shown that large trees are more vulnerable to drought than smaller trees, others found that small trees are the more vulnerable. We explored the potential relationships between canopy height and forest responses to drought indicated by tree mortality, tree ring width index (RWI), and normalized difference vegetation index (NDVI) in the southwestern United States (SWUS) in 2002.In that year many trees had zero tree ring growth due to mortality and dieback, presumably related to drought-stress. With RWI data from a tree ring data base and climate data co-located with the field measurements, we found size-dependent linear correlations between these forest responses and canopy height in SWUS under severe drought condition. During that drought period, both trunk growth (RWI) and leaf growth (NDVI) were positively correlated with canopy height of the smaller trees (less than 18 m) and negatively correlated with canopy height of greater than 18 m. Tree mortality was negatively correlated with canopy height up to 15 m. Both local-scale and regional-scale data are consistent in showing that forests with medium canopy height (around 18 meters) showed the greatest resistance to severe drought. We suggest that negative impacts of severe drought on forests could be modified with active management of canopy structure.

Physics‐Constrained Machine Learning of Evapotranspiration

“…Specifically, LE predictions by the hybrid model are most sensitive to h_canopy and SM. The strong dependence of ET and surface resistance on SM is well known (e.g., Akbar et al, ; Dirmeyer, ; Douville et al, ; Entekhabi et al, ; Gentine et al, ; Koster et al, ; Koster et al, ; Seneviratne et al, ; Seneviratne et al, ; Vogel et al, ), but the impact of vegetation height has been only recently recognized (Groh et al, ; Klein et al, ; Ringgaard et al, ; Xu et al, ), and not thoroughly quantified. Here we find that canopy height is even more important than SM.…”

“…We then test the sensitivity of the hybrid model to different environmental variables by adding a perturbation to each input variable (10-90% standard deviation increase, with 10% increment) to understand which variables are the most important regulators of r s and LE (Figures 4a and 4b), as well as to assess their nonlinearity. The most important variables (ranked by their mean R 2 with and without perturbation in Dirmeyer, 2011; Douville et al, 2016;Entekhabi et al, 1996;Gentine et al, 2012;Koster et al, 2004;Koster et al, 2006;Seneviratne et al, 2006;Seneviratne et al, 2010;Vogel et al, 2017), but the impact of vegetation height has been only recently recognized (Groh et al, 2019;Klein et al, 2015;Ringgaard et al, 2014;Xu et al, 2018), and not thoroughly quantified. Here we find that canopy height is even more important than SM.…”

Drought and the interannual variability of stem growth in an aseasonal, everwet forest

“…The lower evapotranspirative demand of smaller, sub‐canopy trees also means they are generally less‐affected by the drought in the first place (Kempes, West, Crowell, & Girvan, ; McDowell & Allen, ; McDowell, Michaletz et al., ; Santiago et al., ; Wolfe et al., ; Xu et al., ) allowing them to take advantage of an increase in light and grow well in the year following the drought. Such ontogenetic differences illustrate the need to better understand the interplay between individuals, size, and physiology in terms of resource allocation and growth for tropical trees in the context of drought and global change (McDowell, Michaletz et al., ; Uriarte et al., ).…”

Spatial Upscaling of Tree-Ring-Based Forest Response to Drought with Satellite Data

“…The frequencies and intensities of drought events are increasing under the influence of warming climate [1,2], with impacts on forest ecosystems such as increased tree mortality and decreased forest productivity [3][4][5][6]. Data from multiple sources, ranging from ground-based to satellite-based observations, have been used to demonstrate forest response to climate change [7][8][9][10][11]. However, these datasets are often utilized independently, each specialized in their unique spatial and temporal scales [12].…”

“…Multispectral sensors have spectral bands from the visible and infrared wavelengths that can be combined into vegetation indexes [29,30]. Several vegetation indexes (VI) have been used in disturbance and drought studies [10,31,32], many of which utilize the NIR and red bands. The normalized difference vegetation index (NDVI) is the most widely used vegetation index to document and monitor drought and related impacts in forests [26,33,34].…”