Centre for Functional Ecology, University of Coimbra, 3000-456, Coimbra, Portugal.
Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado, 80309, USA.
Ecology. 2018 May;99(5):1184-1193. doi: 10.1002/ecy.2199.
The relationship between the spatial variability of soil multifunctionality (i.e., the capacity of soils to conduct multiple functions; SVM) and major climatic drivers, such as temperature and aridity, has never been assessed globally in terrestrial ecosystems. We surveyed 236 dryland ecosystems from six continents to evaluate the relative importance of aridity and mean annual temperature, and of other abiotic (e.g., texture) and biotic (e.g., plant cover) variables as drivers of SVM, calculated as the averaged coefficient of variation for multiple soil variables linked to nutrient stocks and cycling. We found that increases in temperature and aridity were globally correlated to increases in SVM. Some of these climatic effects on SVM were direct, but others were indirectly driven through reductions in the number of vegetation patches and increases in soil sand content. The predictive capacity of our structural equation modelling was clearly higher for the spatial variability of N- than for C- and P-related soil variables. In the case of N cycling, the effects of temperature and aridity were both direct and indirect via changes in soil properties. For C and P, the effect of climate was mainly indirect via changes in plant attributes. These results suggest that future changes in climate may decouple the spatial availability of these elements for plants and microbes in dryland soils. Our findings significantly advance our understanding of the patterns and mechanisms driving SVM in drylands across the globe, which is critical for predicting changes in ecosystem functioning in response to climate change.
土壤多功能性(即土壤执行多种功能的能力;SVM)的空间变异性与主要气候驱动因素(如温度和干旱)之间的关系在全球范围内从未在陆地生态系统中得到评估。我们调查了来自六大洲的 236 个旱地生态系统,以评估干旱和年平均温度以及其他非生物(例如质地)和生物(例如植物覆盖)变量作为 SVM 驱动因素的相对重要性,SVM 计算为与养分储量和循环相关的多个土壤变量的平均变异系数。我们发现,温度和干旱的增加与 SVM 的增加在全球范围内相关。这些气候对 SVM 的一些影响是直接的,但其他影响则是通过减少植被斑块数量和增加土壤砂含量间接产生的。我们的结构方程模型的预测能力对于与 N 相关的土壤变量的空间变异性明显高于与 C 和 P 相关的土壤变量。就 N 循环而言,温度和干旱的影响既直接又通过土壤特性的变化间接产生。对于 C 和 P,气候的影响主要是通过植物属性的变化间接产生的。这些结果表明,未来气候的变化可能会使旱地土壤中这些元素对植物和微生物的空间可用性脱钩。我们的研究结果极大地促进了我们对全球旱地 SVM 驱动模式和机制的理解,这对于预测气候变化对生态系统功能的影响至关重要。