Luo Dawei, O'Neill Gregory A, Yang Yuqing, Galeano Esteban, Wang Tongli, Thomas Barb R
Department of Renewable Resources, University of Alberta, 442 Earth Science Buildings, Edmonton, AB T6G 2E3 Canada.
Department of Forest and Conservation Sciences, University of British Columbia, Vancouver, BC V6T 1Z4 Canada.
Eur J For Res. 2024;143(5):1349-1364. doi: 10.1007/s10342-024-01694-w. Epub 2024 May 13.
Growth and yield (G&Y) of forest plantations can be significantly impacted by maladaptation resulting from climate change, and assisted migration has been proposed to mitigate these impacts by restoring populations to their historic climates. However, genecology models currently used for guiding assisted migration do not account for impacts of climate change on cumulative growth and assume that responses of forest population to climate do not change with age. Using provenance trial data for interior lodgepole pine ( subsp. Douglas) and white spruce ( (Moench) Voss) in western Canada, we integrated Universal Response Functions, representing the relationship of population performance with their provenance and site climates, into top height curves in a G&Y model (Growth and Yield Projection System, GYPSY) to develop population-specific climate sensitive top height curves for both species. These new models can estimate the impact of climate change on top height of local populations and populations from a range of provenances to help guide assisted migration. Our findings reveal that climate change is expected to have varying effects on forest productivity across the landscape, with some areas projected to experience a slight increase in productivity by the 2050s, while the remainder are projected to face a significant decline in productivity for both species. Adoption of assisted migration, however, with the optimal populations selected was projected to maintain and even improve productivity at the provincial scale. The findings of this study provide a novel approach to incorporating assisted migration approaches into forest management to mitigate the negative impacts of climate change.
人工林的生长和产量（G&Y）会受到气候变化导致的适应性不良的显著影响，有人提出通过将种群恢复到其历史气候条件来减轻这些影响，即采用辅助迁移的方法。然而，目前用于指导辅助迁移的遗传生态学模型没有考虑气候变化对累积生长的影响，并且假定森林种群对气候的响应不会随年龄而变化。利用加拿大西部内陆黑松（亚种道格拉斯松）和白云杉（(Moench) Voss）的种源试验数据，我们将代表种群表现与其种源和立地气候关系的通用响应函数整合到一个生长和产量模型（生长和产量预测系统，GYPSY）的树高曲线中，为这两个物种开发了特定种群的气候敏感型树高曲线。这些新模型可以估计气候变化对当地种群和一系列种源种群树高的影响，以帮助指导辅助迁移。我们的研究结果表明，气候变化预计会对整个景观的森林生产力产生不同影响，预计到2050年代，一些地区的生产力将略有增加，而其余地区预计这两个物种的生产力都将大幅下降。然而，采用辅助迁移并选择最优种群预计将在省级尺度上维持甚至提高生产力。本研究结果提供了一种将辅助迁移方法纳入森林管理以减轻气候变化负面影响的新方法。
