Forests are an important component of the global carbon balance, and climate sensitive growth and yield models are an essential tool when predicting future forest conditions. In this study, we used the dynamic climate capability of the Forest Vegetation Simulator (FVS) to simulate future (100 year) forest conditions on four National Forests in the northwestern USA: Payette National Forest (NF), Ochoco NF, Gifford Pinchot NF, and Siuslaw NF. Using Forest Inventory and Analysis field plots, aboveground carbon estimates and species compositions were simulated with Climate-FVS for the period between 2016 and 2116 under a no climate change scenario and a future climate scenario. We included a sensitivity analysis that varied calculated disturbance probabilities and the dClim rule, which is one method used by Climate-FVS to introduce climate-related mortality. The dClim rule initiates mortality when the predicted climate change at a site is greater than the change in climate associated with a predetermined shift in elevation. Results of the simulations indicated the dClim rule influenced future carbon projections more than estimates of disturbance probability. Future aboveground carbon estimates increased and species composition remained stable under the no climate change scenario. The future climate scenario we tested resulted in less carbon at the end of the projections compared to the no climate change scenarios for all cases except when the dClim rule was disengaged on the Payette NF. Under the climate change scenario, species compositions shifted to climatically adapted species or early successional species. This research highlights the need to consider climate projections in long-term planning or future forest conditions may be unexpected. Forest managers and planners could perform similar simulations and use the results as a planning tool when analyzing climate change effects at the National Forest level.

中文翻译：

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美国西北部四个国家森林的百年预计碳负荷和物种组成。

森林是全球碳平衡的重要组成部分，气候敏感的生长和产量模型是预测未来森林状况的重要工具。在这项研究中，我们使用森林植被模拟器 (FVS) 的动态气候能力来模拟美国西北部四个国家森林的未来（100 年）森林状况：Payette 国家森林 (NF)、Ochoco NF、Gifford Pinchot NF、和 Siuslaw NF。使用森林清单和分析实地图，在无气候变化情景和未来气候情景下，使用气候-FVS 模拟了 2016 年至 2116 年期间的地上碳估算和物种组成。我们包括了一个敏感性分析，该分析改变了计算出的干扰概率和 dClim 规则，这是 Climate-FVS 用来引入气候相关死亡率的一种方法。当一个地点的预测气候变化大于与预定海拔变化相关的气候变化时，dClim 规则会启动死亡率。模拟结果表明，dClim 规则对未来碳预测的影响大于对干扰概率的估计。在没有气候变化的情况下，未来的地上碳估计值增加，物种组成保持稳定。除了在 Payette NF 上解除 dClim 规则外，我们测试的未来气候情景在预测结束时与没有气候变化情景相比导致碳排放减少。在气候变化情景下，物种组成转变为适应气候的物种或早期演替物种。这项研究强调了在长期规划中考虑气候预测的必要性，否则未来的森林状况可能会出乎意料。在分析国家森林层面的气候变化影响时，森林管理者和规划者可以进行类似的模拟并将结果用作规划工具。