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Choice of baseline climate data impacts projected species' responses to climate change

机译:选择基准气候数据会影响预计物种对气候变化的反应

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摘要

Climate data created from historic climate observations are integral to most assessments of potential climate change impacts, and frequently comprise the baseline period used to infer species-climate relationships. They are often also central to downscaling coarse resolution climate simulations from General Circulation Models (GCMs) to project future climate scenarios at ecologically relevant spatial scales. Uncertainty in these baseline data can be large, particularly where weather observations are sparse and climate dynamics are complex (e.g. over mountainous or coastal regions). Yet, importantly, this uncertainty is almost universally overlooked when assessing potential responses of species to climate change. Here, we assessed the importance of historic baseline climate uncertainty for projections of species' responses to future climate change. We built species distribution models (SDMs) for 895 African bird species of conservation concern, using six different climate baselines. We projected these models to two future periods (2040-2069, 2070-2099), using downscaled climate projections, and calculated species turnover and changes in species-specific climate suitability. We found that the choice of baseline climate data constituted an important source of uncertainty in projections of both species turnover and species-specific climate suitability, often comparable with, or more important than, uncertainty arising from the choice of GCM. Importantly, the relative contribution of these factors to projection uncertainty varied spatially. Moreover, when projecting SDMs to sites of biodiversity importance (Important Bird and Biodiversity Areas), these uncertainties altered site-level impacts, which could affect conservation prioritization. Our results highlight that projections of species' responses to climate change are sensitive to uncertainty in the baseline climatology. We recommend that this should be considered routinely in such analyses.
机译:从历史气候观察中获得的气候数据是大多数潜在气候变化影响评估的组成部分,并且通常包含用于推断物种与气候关系的基准期。它们通常对于降低通用气候模式(GCM)的粗分辨率气候模拟的规模,以预测与生态相关的空间尺度的未来气候情景也很重要。这些基准数据的不确定性可能很大,尤其是在天气观测稀疏且气候动态复杂的地方(例如在山区或沿海地区)。然而,重要的是,在评估物种对气候变化的潜在反应时,这种不确定性几乎被普遍忽略。在这里,我们评估了历史基准气候不确定性对于预测物种对未来气候变化的反应的重要性。我们使用六种不同的气候基准,为895种受保护的非洲鸟类建立了物种分布模型(SDM)。我们使用缩减的气候预测,将这些模型预测到两个未来时期(2040-2069、2070-2099),并计算了物种周转率和特定物种的气候适应性变化。我们发现,基线气候数据的选择构成了物种更新和特定物种气候适宜性预测的不确定性的重要来源,通常与选择GCM所产生的不确定性相当或比其重要。重要的是,这些因素对投影不确定性的相对贡献在空间上变化。此外,在将SDM投影到具有生物多样性重要性的地点(重要鸟类和生物多样性地区)时,这些不确定性改变了地点一级的影响,这可能会影响保护优先级。我们的结果突出表明,物种对气候变化的反应的预测对基准气候学的不确定性敏感。我们建议在此类分析中应常规考虑这一点。

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