长白山阔叶红松林是全球为数不多的大面积原始针阔混交林,对其开展模拟研究尤为必要.本研究基于植被功能性状的新一代动态全球植被模式CLM5-FATES(Community Land Model version 5-Functionally Assembled Terrestrial Ecosystem Simula...长白山阔叶红松林是全球为数不多的大面积原始针阔混交林,对其开展模拟研究尤为必要.本研究基于植被功能性状的新一代动态全球植被模式CLM5-FATES(Community Land Model version 5-Functionally Assembled Terrestrial Ecosystem Simulator),选取25℃时最大羧化速率、比叶面积和叶寿命三个叶片特性参数,对长白山针阔混交林分布进行模拟,探讨模式中长白山针阔混交林分布的参数敏感性,检验模式对长白山针阔混交林分布的模拟能力.研究表明,不同的性状参数组合显著影响该地区两种植被类型分布的模拟结果,且25℃时最大羧化速率和比叶面积的影响大于叶寿命.适当的性状参数组合下,模式能再现观测结果中的长白山针阔混交林分布.本研究验证了该模式在长白山针阔混交林的适用性,可为进一步的气候植被相互作用研究提供重要支持.展开更多
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
文摘长白山阔叶红松林是全球为数不多的大面积原始针阔混交林,对其开展模拟研究尤为必要.本研究基于植被功能性状的新一代动态全球植被模式CLM5-FATES(Community Land Model version 5-Functionally Assembled Terrestrial Ecosystem Simulator),选取25℃时最大羧化速率、比叶面积和叶寿命三个叶片特性参数,对长白山针阔混交林分布进行模拟,探讨模式中长白山针阔混交林分布的参数敏感性,检验模式对长白山针阔混交林分布的模拟能力.研究表明,不同的性状参数组合显著影响该地区两种植被类型分布的模拟结果,且25℃时最大羧化速率和比叶面积的影响大于叶寿命.适当的性状参数组合下,模式能再现观测结果中的长白山针阔混交林分布.本研究验证了该模式在长白山针阔混交林的适用性,可为进一步的气候植被相互作用研究提供重要支持.
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.
