State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of the State Forestry Administration, Chinese Academy of Forestry, Beijing, 100091, China; Research Institute of Forestry, Chinese Academy of Forestry, Beijing, 100091, China.
J Environ Manage. 2021 Feb 15;280:111633. doi: 10.1016/j.jenvman.2020.111633. Epub 2020 Dec 17.
Understanding the distribution, net primary productivity (NPP) and environmental constraints of Larix kaempferi is crucial to predict how global climate change will affect its growth and future dynamics. We simulated future changes in the globally suitable distribution patterns and the NPP dynamics under different representative concentration pathways (RCPs) using MaxEnt and Physiological Principles in Predicting Growth (3-PG) models. The results showed that suitable distribution areas for Larix kaempferi were concentrated in Europe and Asia, followed by North America, under current climate conditions. Globally, about 33.75% of the suitable area was in China. Suitable areas decreased and shifted northward in Asia, Europe and China in the RCP scenarios. Larix kaempferi could adapt or move to higher latitudes/altitudes to mitigate the negative impacts of climate change. The NPP of Larix kaempferi in China was 241.85-863.57 g m a simulated by the 3-PG model after local parameterization, which was consistent with the measured NPP. Changes in NPP were predicted in future climates. When the correlations between climate factors and NPP were examined, under the more optimistic scenarios, NPP would increase significantly. The key parameters of the 3-PG model were the optimal temperature for growth, forest age, and the number of days of lost productivity in each frost period. Therefore, climate change has a quantitative and significant impact on the distribution and productivity of L. kaempferi, which was estimated successfully with the two modeling approaches. Our results will contribute to the improved cultivation, environment and management of L. kaempferi and potentially of other deciduous gymnosperms.
了解日本落叶松的分布、净初级生产力（NPP）和环境限制对于预测全球气候变化如何影响其生长和未来动态至关重要。我们使用 MaxEnt 和生理原理预测生长模型（3-PG）模拟了在不同代表性浓度路径（RCP）下未来全球适宜分布模式和 NPP 动态的变化。结果表明，在当前气候条件下，日本落叶松的适宜分布区集中在欧洲和亚洲，其次是北美。全球范围内，约有 33.75%的适宜区在中国。在 RCP 情景下，亚洲、欧洲和中国的适宜区减少并向北转移。日本落叶松可以适应或迁移到更高的纬度/海拔，以减轻气候变化的负面影响。经过本地化参数化后，3-PG 模型模拟的中国日本落叶松的 NPP 为 241.85-863.57 g m。未来气候下 NPP 的变化是可以预测的。当检验气候因素与 NPP 之间的相关性时，在更乐观的情景下，NPP 会显著增加。3-PG 模型的关键参数是生长的最佳温度、林龄和每个霜期损失生产力的天数。因此，气候变化对日本落叶松的分布和生产力具有定量和显著的影响，这两种建模方法都成功地进行了估计。我们的研究结果将有助于改善日本落叶松的栽培、环境和管理，并且可能对其他落叶裸子植物也有帮助。
