Biodiversity Institute and Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, Kansas.
Centro de Agroecología y Ambiente, Instituto de Ciencias, Benemérita Universidad Autónoma de Puebla, Puebla, Puebla, México.
Ann N Y Acad Sci. 2018 Oct;1429(1):66-77. doi: 10.1111/nyas.13873. Epub 2018 Jun 20.
Species-level forecasts of distributional potential and likely distributional shifts, in the face of changing climates, have become popular in the literature in the past 20 years. Many refinements have been made to the methodology over the years, and the result has been an approach that considers multiple sources of variation in geographic predictions, and how that variation translates into both specific predictions and uncertainty in those predictions. Although numerous previous reviews and overviews of this field have pointed out a series of assumptions and caveats associated with the methodology, three aspects of the methodology have important impacts but have not been treated previously in detail. Here, we assess those three aspects: (1) effects of niche truncation on model transfers to future climate conditions, (2) effects of model selection procedures on future-climate transfers of ecological niche models, and (3) relative contributions of several factors (replicate samples of point data, general circulation models, representative concentration pathways, and alternative model parameterizations) to overall variance in model outcomes. Overall, the view is one of caution: although resulting predictions are fascinating and attractive, this paradigm has pitfalls that may bias and limit confidence in niche model outputs as regards the implications of climate change for species' geographic distributions.
在过去的 20 年里,物种层面的分布潜力预测和可能的分布变化预测在文献中变得越来越流行。多年来,该方法已经得到了许多改进,其结果是采用了一种方法,该方法考虑了地理预测中多种来源的变化,以及这种变化如何转化为具体的预测以及对这些预测的不确定性。尽管之前有许多关于该领域的评论和概述都指出了该方法存在一系列假设和注意事项,但该方法的三个方面具有重要影响,但以前并未详细讨论。在这里,我们评估这三个方面:(1)生态位模型对未来气候条件的模型转移中生态位狭窄的影响,(2)模型选择过程对生态位模型未来气候转移的影响,以及(3)几个因素(点数据的重复样本、通用环流模型、代表性浓度途径和替代模型参数化)对模型结果总体方差的相对贡献。总的来说,我们的观点是谨慎的:尽管预测结果很吸引人,但这种模式存在陷阱,可能会对物种地理分布对气候变化影响的生态位模型输出产生偏见和限制信心。