Nelson Center for Climatic Research and Department of Geography, University of Wisconsin, Madison, WI 53706, USA.
Proc Natl Acad Sci U S A. 2013 Jun 4;110(23):9374-9. doi: 10.1073/pnas.1220228110. Epub 2013 May 20.
"Space-for-time" substitution is widely used in biodiversity modeling to infer past or future trajectories of ecological systems from contemporary spatial patterns. However, the foundational assumption--that drivers of spatial gradients of species composition also drive temporal changes in diversity--rarely is tested. Here, we empirically test the space-for-time assumption by constructing orthogonal datasets of compositional turnover of plant taxa and climatic dissimilarity through time and across space from Late Quaternary pollen records in eastern North America, then modeling climate-driven compositional turnover. Predictions relying on space-for-time substitution were ∼72% as accurate as "time-for-time" predictions. However, space-for-time substitution performed poorly during the Holocene when temporal variation in climate was small relative to spatial variation and required subsampling to match the extent of spatial and temporal climatic gradients. Despite this caution, our results generally support the judicious use of space-for-time substitution in modeling community responses to climate change.
“空间代替时间”替换在生物多样性建模中被广泛应用，用于根据当代空间格局推断生态系统过去或未来的轨迹。然而，这一基本假设——即物种组成空间梯度的驱动因素也驱动多样性的时间变化——很少得到检验。在这里，我们通过构建北美东部晚第四纪花粉记录中植物分类群组成周转率和时空气候差异的正交数据集，从经验上检验了空间代替时间的假设，然后对气候驱动的组成周转率进行建模。依赖于空间代替时间的预测的准确性约为 72%，与“时间代替时间”的预测相当。然而，在全新世期间，当气候的时间变化相对于空间变化较小时，空间代替时间的预测效果不佳，并且需要进行抽样以匹配空间和时间气候梯度的程度。尽管存在这种谨慎性，但我们的结果总体上支持在建模群落对气候变化的响应时明智地使用空间代替时间。
