Agreement and uncertainty among climate change impact models: A synthesis of sagebrush steppe vegetation predictions

Ecologists have built numerous models to predict how climate change will impact vegetation, but these predictions are difficult to validate, making their utility for land management planning unclear. In the absence of direct validation, researchers can ask whether predictions from varying models are consistent. Here, we analyzed 43 models of climate change impacts on sagebrush (Artemisia tridentata Nutt.), cheatgrass (Bromus tectorum L.), pinyon-juniper (Pinus spp. and Juniperus spp.), and forage production on Bureau of Land Management (BLM) lands in the United States Intermountain West. These models consistently projected pinyon-juniper declines, forage production increases, and the potential for sagebrush increases in some regions of the Intermountain West. In contrast, models of cheatgrass did not predict consistent changes, making cheatgrass projections uncertain. While differences in emission scenarios had little influence on model projections, predictions from different modeling approaches were inconsistent in some cases. This model-choice uncertainty emphasizes the importance of comparisons such as this. The projected vegetation changes have important management implications for agencies such as the BLM. Pinyon-juniper declines would reduce the BLM’s need to control pinyon-juniper encroachment, and increases in forage production could benefit livestock and wildlife populations in some regions. Sagebrush habitat may benefit where sagebrush is predicted to increase, but sagebrush conservation and restoration projects will be challenged in areas where climate may not remain hospitable. Projected vegetation changes may also interact with increasing future wildfire risk, potentially impacting vegetation and increasing management challenges related to fire. Included in this page are the data and code used to complete this analysis and visualize results. This includes the original images of model results used in our analysis, and the code used to process and analyze these images to produce our final results.生态学家已构建诸多模型以预测气候变化对植被的影响，但此类预测往往难以验证，导致其在土地管理规划中的应用价值尚不明确。在缺乏直接验证手段的情况下，研究人员可通过比较不同模型的预测结果是否一致来开展相关分析。本研究针对美国内陆西部（United States Intermountain West）地区美国土地管理局（Bureau of Land Management, BLM）所辖土地上的43个气候变化影响模型展开分析，涉及山艾树（sagebrush, Artemisia tridentata Nutt.）、旱雀麦（cheatgrass, Bromus tectorum L.）、松桧灌丛（pinyon-juniper, Pinus spp. 与 Juniperus spp.）以及草料产量四类研究对象。这些模型一致预测松桧灌丛将出现衰退、草料产量将有所提升，且美国内陆西部部分区域的山艾树存在扩张潜力。与之形成对照的是，针对旱雀麦的模型并未得出统一的变化预测，导致其相关预测结果存在不确定性。尽管排放情景差异对模型预测结果的影响较小，但不同建模方法生成的预测结果在部分场景下仍存在不一致。这种模型选择层面的不确定性凸显了此类对比研究的重要性。 本次预测的植被变化对美国土地管理局等相关机构具有重要的管理指导意义。松桧灌丛的衰退将降低美国土地管理局防控其扩张的需求，而草料产量的提升则可在部分区域惠及畜禽与野生生物种群。在山艾树预测扩张的区域，其栖息地将得到保护，但在气候不再适宜的区域，山艾树的保护与修复项目将面临挑战。此外，预测的植被变化还可能与未来愈发严峻的野火风险产生交互作用，进而对植被造成影响，并加剧火灾相关的管理难题。 本页面包含本次分析与结果可视化所用的全部数据与代码，其中涵盖本研究分析所用的模型结果原始图像，以及用于处理、分析这些图像以生成最终研究结果的代码。