Kenai National Wildlife Refuge, U. S. Fish and Wildlife Service, Soldotna, Alaska, United States of America.
PLoS One. 2018 Dec 26;13(12):e0208883. doi: 10.1371/journal.pone.0208883. eCollection 2018.
Managers need information about the vulnerability of historical plant communities, and their potential future conditions, to respond appropriately to landscape change driven by global climate change. We model the climate envelopes of plant communities on the Kenai Peninsula in Southcentral Alaska and forecast to 2020, 2050, and 2080. We assess 6 model outputs representing downscaled climate data from 3 global climate model outputs and 2 representative concentration pathways. We use two lines of evidence, model convergence and empirically measured rates of change, to identify the following plausible ecological trajectories for the peninsula: (1.) alpine tundra and sub-alpine shrub decrease, (2.) perennial snow and ice decrease, (3.) forests remain on the Kenai Lowlands, (4.) the contiguous white-Lutz-Sitka spruce complex declines, and (5.) mixed conifer afforestation occurs along the Gulf of Alaska coast. We suggest that converging models in the context of other lines of evidence is a viable approach to increase certainty for adaptation planning. Extremely dynamic areas with multiple outcomes (i.e., disagreement) among models represent ecological risk, but may also represent opportunities for facilitated adaptation and other managerial approaches to help tip the balance one way or another. By reducing uncertainty, this eclectic approach can be used to inform expectations about the future.
经理们需要了解历史植物群落的脆弱性及其未来的潜在状况,以便对全球气候变化驱动的景观变化做出适当的反应。我们在阿拉斯加中南部的基奈半岛上对植物群落的气候环境进行建模,并对 2020 年、2050 年和 2080 年的情况进行预测。我们评估了 6 个模型输出,这些输出代表了 3 个全球气候模型输出和 2 个代表性浓度途径的气候数据的细化。我们使用了两条证据线,即模型收敛和经验测量的变化率,来确定半岛的以下几种可能的生态轨迹:(1.)高山苔原和亚高山灌丛减少,(2.)常年积雪和冰减少,(3.)基奈低地的森林保持不变,(4.)连续的白-卢茨-锡特卡云杉复合体减少,(5.)混合针叶林在阿拉斯加湾沿岸造林。我们认为,在其他证据线的背景下,模型的收敛是一种提高适应规划确定性的可行方法。具有多种结果(即意见分歧)的极其动态的区域代表了生态风险,但也可能代表了促进适应和其他管理方法的机会,以帮助使平衡朝着一个或另一个方向倾斜。通过减少不确定性,这种折衷的方法可以用来告知对未来的期望。