Forest biomass is strongly shaped by forest height across boreal to tropical forests in China

doi:10.1093/jpe/rtv001

Abstract

Abstract: Aims Forest height is a major factor shaping geographic biomass patterns, and there is a growing dependence on forest height derived from satellite light detecting and ranging (LiDAR) to monitor large-scale biomass patterns. However, how the relationship between forest biomass and height is modulated by climate and biotic factors has seldom been quantified at broad scales and across various forest biomes, which may be crucial for improving broad-scale biomass estimations based on satellite LiDAR.
Methods We used 1263 plots, from boreal to tropical forest biomes across China, to examine the effects of climatic (energy and water availability) and biotic factors (forest biome, leaf form and leaf phenology) on biomass–height relationship, and to develop the models to estimate biomass from forest height in China.
Important findings (i) Forest height alone explained 62% of variation in forest biomass across China and was far more powerful than climate and other biotic factors. (ii) However, the relationship between biomass and forest height were significantly affected by climate, forest biome, leaf phenology (evergreen vs. deciduous) and leaf form (needleleaf vs. broadleaf). Among which, the effect of climate was stronger than other factors. The intercept of biomass–height relationship was more affected by precipitation while the slope more affected by energy availability. (iii) When the effects of climate and biotic factors were considered in the models, geographic biomass patterns could be well predicted from forest height with an r 2 between 0.63 and 0.78 (for each forest biome and for all biomes together). For most biomes, forest biomass could be well predicted with simple models including only forest height and climate. (iv) We provided the first broad-scale models to estimate biomass from forest height across China, which can be utilized by future LiDAR studies. (v) Our results suggest that the effect of climate and biotic factors should be carefully considered in models estimating broad-scale forest biomass patterns with satellite LiDAR.

Key words: biomass, climate, forest biome, forest height, leaf phenology, needleleaf vs, broadleaf forest

摘要：
Aims Forest height is a major factor shaping geographic biomass patterns, and there is a growing dependence on forest height derived from satellite light detecting and ranging (LiDAR) to monitor large-scale biomass patterns. However, how the relationship between forest biomass and height is modulated by climate and biotic factors has seldom been quantified at broad scales and across various forest biomes, which may be crucial for improving broad-scale biomass estimations based on satellite LiDAR.
Methods We used 1263 plots, from boreal to tropical forest biomes across China, to examine the effects of climatic (energy and water availability) and biotic factors (forest biome, leaf form and leaf phenology) on biomass–height relationship, and to develop the models to estimate biomass from forest height in China.
Important findings (i) Forest height alone explained 62% of variation in forest biomass across China and was far more powerful than climate and other biotic factors. (ii) However, the relationship between biomass and forest height were significantly affected by climate, forest biome, leaf phenology (evergreen vs. deciduous) and leaf form (needleleaf vs. broadleaf). Among which, the effect of climate was stronger than other factors. The intercept of biomass–height relationship was more affected by precipitation while the slope more affected by energy availability. (iii) When the effects of climate and biotic factors were considered in the models, geographic biomass patterns could be well predicted from forest height with an r 2 between 0.63 and 0.78 (for each forest biome and for all biomes together). For most biomes, forest biomass could be well predicted with simple models including only forest height and climate. (iv) We provided the first broad-scale models to estimate biomass from forest height across China, which can be utilized by future LiDAR studies. (v) Our results suggest that the effect of climate and biotic factors should be carefully considered in models estimating broad-scale forest biomass patterns with satellite LiDAR.

Xian Wu, Xiangping Wang, Yulian Wu, Xinli Xia, Jingyun Fang. Forest biomass is strongly shaped by forest height across boreal to tropical forests in China[J]. J Plant Ecol, 2015, 8(6): 559-567.

[1]	Wei Wang, Xiaodan Sun, Wenhao Huang, Xiaoting Men, Shijie Yi, Fengrong Zheng, Zhaohui Zhang, Zongling Wang. Soil P solubilization and plant growth promotion by a saline-alkali-tolerant P-solubilizing bacterium, Bacillus sp. DYS211 [J]. J Plant Ecol, 2023, 16(6): 0-rtad028.
[2]	Le Sun, Jian Sun, Jun-Xi Wu, Zi-Yin Du, You-Jun Chen, Yi Wang, Miao Liu, Wen-Cheng Li, Er-Yuan Liang. Plant community traits and functions mediate the biomass trade-off of alpine grasslands along precipitation gradients on the Tibetan Plateau [J]. J Plant Ecol, 2023, 16(5): 0-rtad009.
[3]	Yong-Gang Li, Xiao-Bing Zhou, Yongxing Lu, Yuan-Ming Zhang. Moss C, N, P and K stoichiometry and their relationships are related to soil nutrients and environment in a temperate desert of central Asia [J]. J Plant Ecol, 2023, 16(3): 0-rtac070.
[4]	Zheng-Bing Yan, Di Tian, Han-Yue Huang, Yuan-Feng Sun, Xing-Hui Hou, Wen-Xuan Han, Ya-Long Guo, Jing-Yun Fang. Interactive effects of plant density and nitrogen availability on the biomass production and leaf stoichiometry of Arabidopsis thaliana [J]. J Plant Ecol, 2023, 16(3): 0-rtac101.
[5]	Shu Wang, Dao-Wei Zhou. Dynamic architectural responses of morphological traits to emergence timing in Abutilon theophrasti (Malvaceae) [J]. J Plant Ecol, 2023, 16(3): 0-rtac095.
[6]	Jie Liu, Zong-Shan Li, Maierdang Keyimu, Xiaochun Wang, Haibin Liang, Xiaoming Feng, Guangyao Gao and Bojie Fu. Accelerated warming in the late 20th century promoted tree radial growth in the Northern Hemisphere [J]. J Plant Ecol, 2023, 16(1): 0-.
[7]	Ravi Mohan Tiwari, Jinliang Liu, Yuchu Xie, Shenhao Yao, Shenglong Liu, Sumei Wu, Julian Liu, Haiyuan Qian, Zupei Lei, Hongwei Zhang, Lei Zhong, Boliang Wei and Mingjian Yu. Decoupling the impact of biodiversity and environmental factors on the biomass and biomass growth of trees in subtropical forests [J]. J Plant Ecol, 2023, 16(1): 0-.
[8]	Brian Njoroge, Yuelin Li, Dennis Otieno, Shizhong Liu, Simin Wei, Ze Meng, Qianmei Zhang, Deqiang Zhang, Juxiu Liu, Guowei Chu, Fasih Ullah Haider and John Tenhunen. Seasonal droughts drive up carbon gain in a subtropical forest [J]. J Plant Ecol, 2023, 16(1): 0-.
[9]	Huajie Diao, Xiaopeng Chen, Ge Wang, Qiushi Ning, Shuya Hu, Wei Sun, Kuanhu Dong and Changhui Wang. The response of soil respiration to different N compounds addition in a saline–alkaline grassland of northern China [J]. J Plant Ecol, 2022, 15(5): 897-910.
[10]	Mingjie Xu, Tingting An, Zhoutao Zheng, Tao Zhang, Yangjian Zhang and Guirui Yu. Variability in evapotranspiration shifts from meteorological to biological control under wet versus drought conditions in an alpine meadow [J]. J Plant Ecol, 2022, 15(5): 921-932.
[11]	Bowen Li, Wangwang Lv, Jianping Sun, Lirong Zhang, Lili Jiang, Yang Zhou, Peipei Liu, Huan Hong, Qi Wang, Wang A, Suren Zhang, Lu Xia, Zongsong Wang, Tsechoe Dorji, Ailing Su, Caiyun Luo, Zhenhua Zhang and Shiping Wang. Warming and grazing enhance litter decomposition and nutrient release independent of litter quality in an alpine meadow [J]. J Plant Ecol, 2022, 15(5): 977-990.
[12]	Bingqian Su and Zhouping Shangguan. Stoichiometric homeostasis in response to variable water and nutrient supply in a Robinia pseudoacacia plant–soil system [J]. J Plant Ecol, 2022, 15(5): 991-1006.
[13]	Ting Ma, Thomas Parker, Ned Fetcher, Steven L. Unger, Jon Gewirtzman, Michael L. Moody and Jianwu Tang. Leaf and root phenology and biomass of Eriophorum vaginatum in response to warming in the Arctic [J]. J Plant Ecol, 2022, 15(5): 1091-1105.
[14]	Zhongmin Hu, Minqi Liang, Alan Knapp, Jianyang Xia, and Wenping Yuan. Are regional precipitation–productivity relationships robust to decadal-scale dry period? [J]. J Plant Ecol, 2022, 15(4): 711-720.
[15]	Zhen Liu, Hongwei Yu, Xiao Sun and Jianqing Ding. Effects of elevated temperature on chemistry of an invasive plant, its native congener and their herbivores [J]. J Plant Ecol, 2022, 15(3): 450-460.