地形是影响森林生产力和碳收支空间分布格局的主要环境因素。青藏高原地形复杂，森林类型丰富，是研究地形对森林碳收支格局影响的理想场所。然而，由于青藏高原森林区域的野外调查存在难度，目前对于地形因子对青藏高原森林碳收支动态的影响缺乏全面认识。因此，本研究旨在模拟青藏高原森林碳收支变化的时空格局并分析不同地形条件下森林生产力及碳收支动态的差异。本研究利用生态系统过程模型(FORMIND)模拟了青藏高原中高海拔森林总初级生产力(GPP)、地上生物量(AGB)及净生态系统交换量(NEE)在不同地形条件下的时空动态，并对模型在研究区的适用性及模拟结果的精确性进行验证，分析当前(2000-2014年)及未来(2015-2040年)生产力、碳收支状况，并利用XGBoost机器学习算法分析地形因子对GPP、AGB和NEE影响的相对重要性。结果表明，FORMIND模型模拟的青藏高原森林GPP(6。73±0。53 t C·hm-2·a-1)、AGB(167。23±17。45 t·hm-2)和 NEE(0。32±0。12 t C·hm-2·a-1)与样地调查数据和遥感观测数据基本一致，模拟结果可信。未来青藏高原森林AGB呈明显增加的趋势，GPP增加趋势不明显，NEE呈减少的趋势，但总体上仍表现为碳汇。森林AGB和GPP与海拔呈负相关，AGB和NEE与坡度呈微弱正相关，阳坡森林GPP、AGB和NEE均高于阴坡。相较于坡度和坡向，海拔对青藏高原森林生产力和碳收支动态的影响更大。本研究结果有利于深入了解青藏高原森林生产力和碳收支空间分布格局。
Productivity and carbon budget dynamics of forests under different topographic conditions on Tibetan Plat-eau
Topography is a main environmental factor affecting the spatial distribution of productivity and carbon budget of forests.Tibetan Plateau is an ideal place to study the effects of topography on the pattern of forest carbon budget due to its complex topography and abundant forest types.However,due to the difficulty of field investigation in the Tibetan Plateau forest area,there is a lack of comprehensive understanding of the impacts of topographic factors on forest carbon budget dynamics on Tibetan Plateau.Therefore,this study aimed to simulate the spatiotemporal vari-ations of forest carbon budget on the Tibetan Plateau and analyze the differences of forest productivity and carbon budget dynamics under different topographic conditions.The temporal and spatial dynamics of gross primary produc-tivity(GPP),above-ground biomass(AGB),and net ecosystem exchange(NEE)in middle-high altitude forests were simulated by using process-based model(FORMIND)under different topographic conditions,and the model ap-plicability in the study area and the accuracy of the simulation results were verified.We analyzed current(2000-2014)and future(2015-2040)productivity and carbon budget.Furthermore,we quantified the relative importance of topographic factors on GPP,AGB,and NEE using XGBoost machine learning algorithm.The results showed that GPP(6.73±0.53 t C·hm-2·a-1),AGB(167.23±17.45 t·hm-2),and NEE(0.32±0.12 t C·hm-2·a-1)simula-ted by FORMIND model were basically consistent with the data of plot survey and remote sensing observation,which verified the accuracy of the simulation results.In the future(2014-2040),there is an obvious increase in AGB,a slight increase in GPP,and a decreased but positive value in NEE,which indicated that forests would be carbon sinks.AGB and GPP were negatively correlated with elevation.AGB and NEE were weakly positively corre-lated with slope.The GPP,AGB,and NEE of forests on sunny slope were higher than those on shady slope.Com-pared with slope and aspect,elevation had a greater effect on productivity and carbon budget dynamics of forests on the Tibetan Plateau.Our results are helpful to further understand the spatial distribution of forest productivity and carbon budget on the Tibetan Plateau.
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