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

FOREST ECOLOGY AND MANAGEMENT

卷:434

Article

Fricker, Geoffrey A.^1,2,3  Synes, Nicholas W.³  Serra-Diaz, Josep M.^4,5,6  North, Malcolm P.⁷  Davis, Frank W.⁸  Franklin, Janet^1,3 

[1] Univ Calif Riverside, Dept Bot & Plant Sci, Riverside, CA 92507 USA

[2] CALTECH, Social Sci Dept, San Luis Obispo, CA 93407 USA

[3] Arizona State Univ, Sch Geog Sci & Urban Planning, POB 875302, Tempe, AZ 85287 USA

[4] Univ Lorraine, UMR Silva, AgroParisTech, INRA, F-54000 Nancy, France

[5] Aarhus Univ, Sect Ecoinformat & Biodivers, Dept Biosci, Ny Munkegade 114, DK-8000 Aarhus, Denmark

[6] Aarhus Univ, Dept Biosci, Ctr Biodivers Dynam Changing World BIOCHANGE, Ny Munkegade 114, DK-8000 Aarhus, Denmark

[7] USFS Pacific Southwest Res Stn, Davis, CA 95618 USA

[8] Univ Calif Santa Barbara, Bren Sch Environm Sci & Management, Santa Barbara, CA 93106 USA

关键词: Tree height;    LiDAR;    Mixed-conifer forest;    Foothill oak woodland;    Water-energy limitation;    Climate;    Soils;    Topography;   

DOI  :  10.1016/j.foreco.2018.12.006

来源: Elsevier

【 摘 要 】

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 to 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 (CHMax)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 CHMax (18-52% relative importance) than soil and topographic variables, and models at intermediate (50-500 m) scales explained the most variance in CHMax (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 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).

【 授权许可】

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