More than climate? Predictors of tree canopy height vary with scale in complex terrain, Sierra Nevada, CA (USA)

Abstract

Tall trees and vertical forest structure are associated with increased productivity, biomass and wildlife habitat quality. While climate has been widely hypothesized to control forest structure at broad scales, other variables could be key at fine scales, and are associated with forest management. In this study we identify the environmental conditions (climate, topography, soils) associated with increased tree height across spatial scales using airborne Light Detection and Ranging (LiDAR) data to measure canopy height. The study was conducted over a large elevational gradient from 200-3000 m in the Sierra Nevada Mountains (CA, USA) spanning sparse oak woodlands to closed canopy conifer forests. We developed Generalized Boosted Models (GBMs) of forest height, ranking predictor variable importance against Maximum Canopy Height (CH Max) at six spatial scales (25, 50, 100, 250, 500, 1000 m). In our study area, climate variables such as the climatic water deficit and mean annual precipitation were more strongly correlated with CH Max (18-52% relative importance) than soil and topographic variables, and models at intermediate (50-500 m) scales explained the most variance in CH Max (R 2 0.77-0.83). Certain soil variables such as soil bulk density and pH, as well as topographic variables such as the topographic wetness index, slope curvature and potential solar radiation, showed consistent, strong associations with canopy structure across the gradient, but these relationships were scale dependent. Topography played a greater role in predicting forest structure at fine spatial scales, while climate variables dominated our models, particularly at coarse scales. Our results indicate that multiple abiotic factors are associated with increased maximum tree height; climatic water balance is most strongly associated with this component of forest structure but varies across all spatial scales examined (6.9-54.8% relative importance), while variables related 2 to topography also explain variance in tree height across the elevational gradient, particularly at finer spatial scales (37.15%, 20.26% relative importance at 25, 50 m scales respectively).

Climate more important than soils for predicting forest biomass at the continental scale

“…Consistent with global relationships, we hypothesised that MAT and MAP would be the most important climate variables to explain AGB distribution. Due to the importance of phosphorus to photosynthesis (Kirschbaum et al 1992) and consistent with several studies that have demonstrated the importance of soil phosphorus (Sankaran et al 2005, Quesada et al 2012, Fedrigo et al 2014, Navarrete‐Segueda et al 2018, van der Sande et al 2018, Fricker et al 2019, Cheng et al 2020) to forest AGB we further hypothesised that phosphorus would be the most important edaphic variable.…”

“…Physical characteristics such as the proportion of clay (Laurance et al 1999, Aldana et al 2017, Toledo et al 2017, Ali et al 2020), sand (Toledo et al 2018, Ali et al 2020) and fine sand (Laurance et al 1999) as well as the structure (Quesada et al 2012), bulk density (Ali et al 2020), depth (Laurance et al 1999) and rooting depth (Navarrete‐Segueda et al 2018) of soil have been associated with AGB trends in forests. Chemical characteristics such as the concentration of soil nutrients like phosphorus (Sankaran et al 2005, Quesada et al 2012, Fedrigo et al 2014, Navarrete‐Segueda et al 2018, van der Sande et al 2018, Fricker et al 2019, Cheng et al 2020) and nitrogen (Laurance et al 1999, Fedrigo et al 2014), or the concentration of trace elements including Al (Laurance et al 1999, de Assis et al 2019), Ca (Quesada et al 2012), K (Quesada et al 2012, Fedrigo et al 2014), Mg (Laurance et al 1999, Quesada et al 2012, Fedrigo et al 2014), Fe (de Assis et al 2019) and Zn (Laurance et al 1999) as well as other measures of soil fertility (Slik et al 2010, Toledo et al 2017, Ali et al 2019), and pH (Santiago‐Garcia et al 2019) can also influence forest AGB.…”

Cross-scale interaction of host tree size and climatic water deficit governs bark beetle-induced tree mortality

“…Indeed, we did find a negative two-way interaction between site CWD and overall density, suggesting denser stands experienced lower rates of ponderosa mortality in hotter, drier sites, which comports with Restaino et al 9 in results from their unmanipulated gradient of overall density in the same region during the same hot drought. In the absence of active management, forest structure is largely a product of climate and, with increasing importance at finer spatial scales, topographic conditions 63 . Denser forest patches in our study may indicate greater local water availability, more favorable conditions for tree growth and survivorship, and increased resistance to beetle-induced tree mortality, especially when denser patches are found in hot, dry sites 9 , 63 , 64 .…”

“…In the absence of active management, forest structure is largely a product of climate and, with increasing importance at finer spatial scales, topographic conditions 63 . Denser forest patches in our study may indicate greater local water availability, more favorable conditions for tree growth and survivorship, and increased resistance to beetle-induced tree mortality, especially when denser patches are found in hot, dry sites 9 , 63 , 64 .…”

Using Spatial Regression Models in Identifying the Drivers of Forest Structure in the Hyrcanian Forests of Iran

“…And tree height also correlates positively with terrestrial plant diversity at various spatial scales (Lindenmayer et al 2012;Slik et al 2013;Marks et al 2016;Gatti et al 2017;Lutz et al 2018). Hence understanding which, and how, abiotic factors affect forest height will be indispensable to connect ecological theory with ecosystem management in an era of global change (Fricker et al 2019). In spite of signi cant local variations in tree height, the environmental predictors determining it have been mostly assessed at large scales (Tao et al 2016;Zhang et al 2016).…”