Morrison Bailey D, Heath Katy, Greenberg Jonathan A
Environmental and Climate Sciences Department Brookhaven National Laboratory Upton New York.
Department of Plant Biology University of Illinois at Urbana-Champaign Urbana Illinois.
Ecol Evol. 2019 Sep 30;9(21):12026-12044. doi: 10.1002/ece3.5511. eCollection 2019 Nov.
The formation of novel and disappeared climates between the last glacial maximum (LGM) and the present is important to consider to understand the expansion and contraction of species niches and distributions, as well as the formation and loss of communities and ecological interactions over time. Our choice in climate data resolution has the potential to complicate predictions of the ecological impacts of climate change, since climate varies from local to global scales and this spatial variation is reflected in climate data. To address this issue, we downscaled LGM and modern (1975-2005) 30-year averaged climate data to 60-m resolution for the entire state of Alaska for 10 different climate variables, and then upsampled each variable to coarser resolutions (60 m to 12 km). We modeled the distributions of novel and disappeared climates to evaluate the locations and fractional area of novel and disappeared climates for each of our climate variables and resolutions. Generally, novel and disappeared climates were located in southern Alaska, although there were cases where some disappeared climates existed within coastal and interior Alaska. Climate resolution affected the fractional area of novel and disappeared climates in three patterns: As the spatial resolution of climate became coarser, the fractional area of novel and disappeared climates (a) increased, (b) decreased, or (c) had no explainable relationship. Overall, we found the use of coarser climate data increased the fractional area of novel and disappeared climates due to decreased environmental variability and removal of climate extremes. Our results reinforce the importance of downscaling coarse climate data and suggest that studies analyzing the effects of climate change on ecosystems may overestimate or underestimate their conclusions when utilizing coarse climate data.
考虑末次盛冰期（LGM）与现在之间新气候的形成和消失气候，对于理解物种生态位和分布的扩张与收缩，以及群落的形成与丧失和生态相互作用随时间的变化非常重要。我们对气候数据分辨率的选择可能会使气候变化生态影响的预测变得复杂，因为气候在局部到全球尺度上存在差异，且这种空间变化反映在气候数据中。为解决这一问题，我们将阿拉斯加州整个区域的LGM和现代（1975 - 2005年）30年平均气候数据，针对10个不同气候变量下采样到60米分辨率，然后将每个变量上采样到更粗的分辨率（从60米到12千米）。我们对新气候和消失气候的分布进行建模，以评估每个气候变量和分辨率下新气候和消失气候的位置及面积占比。一般来说，新气候和消失气候位于阿拉斯加南部，不过在阿拉斯加沿海和内陆也存在一些消失气候的情况。气候分辨率以三种模式影响新气候和消失气候的面积占比：随着气候空间分辨率变粗，新气候和消失气候的面积占比（a）增加，（b）减少，或（c）没有可解释的关系。总体而言，我们发现使用更粗的气候数据会增加新气候和消失气候的面积占比，这是由于环境变异性降低和极端气候的去除。我们的结果强化了对粗分辨率气候数据进行降尺度处理的重要性，并表明在利用粗分辨率气候数据分析气候变化对生态系统的影响时，相关研究可能会高估或低估其结论。
