Bi Mohan, Li Huiying, Meidl Peter, Zhu Yanjie, Ryo Masahiro, Rillig Matthias C
Freie Universität Berlin, Institute of Biology, Berlin, Germany.
Berlin-Brandenburg Institute of Advanced Biodiversity Research (BBIB), Berlin, Germany.
Nat Commun. 2024 Sep 18;15(1):8188. doi: 10.1038/s41467-024-52511-2.
Soil biota and functions are impacted by various anthropogenic stressors, including climate change, chemical pollution or microplastics. These stressors do not occur in isolation, and soil properties and functions appear to be directionally driven by the number of global change factors acting simultaneously. Building on this insight, we here hypothesize that co-acting factors with more diverse effect mechanisms, or higher dissimilarity, have greater impacts on soil properties and functions. We created a factor pool of 12 factors and calculated dissimilarity indices of randomly-chosen co-acting factors based on the measured responses of soil properties and functions to the single factors. Results show that not only was the number of factors important, but factor dissimilarity was also key for predicting factor joint effects. By analyzing deviations of soil properties and functions from three null model predictions, we demonstrate that higher factor dissimilarity and a larger number of factors could drive larger deviations from null models and trigger more frequent occurrence of synergistic factor net interactions on soil functions (decomposition rate, cellulase, and β-glucosidase activity), which provides mechanistic insights for understanding high-dimensional effects of factors. Our work highlights the importance of considering factor similarity in future research on interacting factors.
土壤生物群和功能受到各种人为压力源的影响，包括气候变化、化学污染或微塑料。这些压力源并非孤立存在，土壤性质和功能似乎受到同时作用的全球变化因素数量的定向驱动。基于这一见解，我们在此假设，具有更多样化作用机制或更高差异度的共同作用因素，对土壤性质和功能的影响更大。我们创建了一个包含12个因素的因素库，并根据土壤性质和功能对单一因素的测量响应，计算了随机选择的共同作用因素的差异指数。结果表明，不仅因素数量很重要，因素差异度也是预测因素联合效应的关键。通过分析土壤性质和功能与三个零模型预测的偏差，我们证明，更高的因素差异度和更多的因素数量可能导致与零模型的更大偏差，并引发土壤功能（分解速率、纤维素酶和β-葡萄糖苷酶活性）上协同因素净相互作用更频繁地发生，这为理解因素的高维效应提供了机制性见解。我们的工作强调了在未来关于相互作用因素的研究中考虑因素相似性的重要性。
