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A Short Guide to the Climatic Variables of the Last Glacial Maximum for Biogeographers

机译：生物地理学家最后一次冰川最大值的气候变量简短指南

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Ecological niche models are widely used for mapping the distribution of species during the last glacial maximum (LGM). Although the selection of the variables and General Circulation Models (GCMs) used for constructing those maps determine the model predictions, we still lack a discussion about which variables and which GCM should be included in the analysis and why. Here, we analyzed the climatic predictions for the LGM of 9 different GCMs in order to help biogeographers to select their GCMs and climatic layers for mapping the species ranges in the LGM. We 1) map the discrepancies between the climatic predictions of the nine GCMs available for the LGM, 2) analyze the similarities and differences between the GCMs and group them to help researchers choose the appropriate GCMs for calibrating and projecting their ecological niche models (ENM) during the LGM, and 3) quantify the agreement of the predictions for each bioclimatic variable to help researchers avoid the environmental variables with a poor consensus between models. Our results indicate that, in absolute values, GCMs have a strong disagreement in their temperature predictions for temperate areas, while the uncertainties for the precipitation variables are in the tropics. In spite of the discrepancies between model predictions, temperature variables (BIO1-BIO11) are highly correlated between models. Precipitation variables (BIO12- BIO19) show no correlation between models, and specifically, BIO14 (precipitation of the driest month) and BIO15 (Precipitation Seasonality (Coefficient of Variation)) show the highest level of discrepancy between GCMs. Following our results, we strongly recommend the use of different GCMs for constructing or projecting ENMs, particularly when predicting the distribution of species that inhabit the tropics and the temperate areas of the Northern and Southern Hemispheres, because climatic predictions for those areas vary greatly among GCMs. We also recommend the exclusion of BIO14 and BIO15 from ENMs because those variables show a high level of discrepancy between GCMs. Thus, by excluding them, we decrease the level of uncertainty of our predictions. All the climatic layers produced for this paper are freely available in .
机译：生态位模型被广泛用于绘制最后一次冰川最大期（LGM）期间物种分布的图。尽管用于构建那些图的变量和通用循环模型（GCM）的选择确定了模型预测，但我们仍然缺少关于哪些变量和哪个GCM应该包括在分析中以及为什么的讨论。在这里，我们分析了9个不同GCM的LGM的气候预测，以帮助生物地理学家选择他们的GCM和气候层以绘制LGM的物种范围。我们1）绘制LGM可用的9个GCM的气候预测之间的差异，2）分析GCM之间的异同并将它们分组以帮助研究人员选择合适的GCM来校准和投影其生态位模型（ENM）在LGM期间，以及3）量化每个生物气候变量的预测结果的一致性，以帮助研究人员避免在模型之间达成较差共识的环境变量。我们的结果表明，就绝对值而言，GCM在温带地区的温度预测方面存在很大分歧，而降水变量的不确定性在热带地区。尽管模型预测之间存在差异，但模型之间的温度变量（BIO1-BIO11）高度相关。降水变量（BIO12-BIO19）在模型之间没有相关性，特别是BIO14（最干旱月份的降水）和BIO15（降水季节（变异系数））显示了GCM之间的最高差异。根据我们的结果，我们强烈建议使用不同的GCM来构建或预测ENM，尤其是在预测居住于热带和北半球和南半球温带地区的物种的分布时，因为这些地区的气候预测在GCM之间存在很大差异。我们还建议从ENM中排除BIO14和BIO15，因为这些变量显示出GCM之间的高度差异。因此，通过排除它们，我们降低了预测的不确定性水平。本文产生的所有气候层都可在。

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