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.H...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 avail-ability)and biotic factors(forest biome,leaf form and leaf phenol-ogy)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 r2 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 includ-ing 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.展开更多
基金supported by the National Natural Science Foundation of China[Grant No.42041004]the“Innovation Star”Project for Outstanding Postgraduates of Gansu Province[Grant No.2022CXZX-107]the Central Universities[Grant No.lzujbky-2019-kb30].
文摘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 avail-ability)and biotic factors(forest biome,leaf form and leaf phenol-ogy)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 r2 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 includ-ing 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.
