Above‐ground biomass in forests is critical to the global carbon cycle as it stores and sequesters carbon from the atmosphere. Climate change will disrupt the carbon cycle hence understanding how climate and other abiotic variables determine forest biomass at broad spatial scales is important for validating and constraining Earth System models and predicting the impacts of climate change on forest carbon stores. We examined the importance of climate and soil variables to explaining above‐ground biomass distribution across the Australian continent using publicly available biomass data from 3130 mature forest sites, in 6 broad ecoregions, encompassing tropical, subtropical and temperate biomes. We used the Random Forest algorithm to test the explanatory power of 14 abiotic variables (8 climate, 6 soil) and to identify the best‐performing models based on climate‐only, soil‐only and climate plus soil. The best performing models explained ~50% of the variation (climate‐only: R² = 0.47 ± 0.04, and climate plus soils: R² = 0.49 ± 0.04). Mean temperature of the driest quarter was the most important climate variable, and bulk density was the most important soil variable. Climate variables were consistently more important than soil variables in combined models, and model predictive performance was not substantively improved by the inclusion of soil variables. This result was also achieved when the analysis was repeated at the ecoregion scale. Predicted forest above‐ground biomass ranged from 18 to 1066 Mg ha⁻¹, often under‐predicting measured above‐ground biomass, which ranged from 7 to 1500 Mg ha⁻¹. This suggested that other non‐climate, non‐edaphic variables impose a substantial influence on forest above‐ground biomass, particularly in the high biomass range. We conclude that climate is a strong predictor of above‐ground biomass at broad spatial scales and across large environmental gradients, yet to predict forest above‐ground biomass distribution under future climates, other non‐climatic factors must also be identified.

中文翻译：

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在大陆范围内，气候比土壤更重要于预测森林生物量

森林中的地上生物质对全球碳循环至关重要，因为它可以存储和隔离大气中的碳。气候变化将破坏碳循环，因此了解气候和其他非生物变量如何在广泛的空间尺度上确定森林生物量对于验证和约束地球系统模型以及预测气候变化对森林碳储量的影响非常重要。我们使用来自6个广泛的生态区域（包括热带，亚热带和温带生物群落）的3130个成熟森林站点的公开可用生物量数据，研究了气候和土壤变量对解释澳大利亚大陆上地上生物量分布的重要性。我们使用随机森林算法测试了14种非生物变量（8种气候，6个土壤），并根据“仅气候”，“仅土壤”和“气候加土壤”确定最佳性能模型。效果最好的模型解释了〜50％的变化（仅限气候：R²  = 0.47±0.04，并且气候加上土壤：R ²  = 0.49±0.04）。最干燥季度的平均温度是最重要的气候变量，容重是最重要的土壤变量。在组合模型中，气候变量始终比土壤变量重要，并且通过将土壤变量包括在内，模型的预测性能并未得到实质性改善。当在生态区域范围内重复进行分析时，也获得了这一结果。预测的森林地上生物量范围从18到1066 Mg ha ^-1，经常低估了测得的地上生物量，范围从7到1500 Mg ha ^-1。这表明，其他非气候，非泛化变量对森林地上生物量，特别是在高生物量范围内，具有重大影响。我们得出结论，气候是广泛空间尺度上和整个大环境梯度下地上生物量的有力预测指标，但要预测未来气候下森林地上生物量的分布，还必须确定其他非气候因素。