Department of Biology, University of Oxford, Oxford, UK.
School of the Environment, University of Queensland, Brisbane, QLD, Australia.
Nat Commun. 2024 Nov 28;15(1):10352. doi: 10.1038/s41467-024-54540-3.
Perturbations such as climate change, invasive species and pollution, impact the functioning and diversity of ecosystems. However diversity has many meanings, and ecosystems provide a plethora of functions. Thus, on top of the various perturbations that global change represents, there are also many ways to measure a perturbation's ecological impact. This leads to an overwhelming response variability, which undermines hopes of prediction. Here, we show that this variability can instead provide insights into hidden features of functions and of species responses to perturbations. By analysing a dataset of global change experiments in microbial soil systems we first show that the variability of functional and diversity responses to perturbations is not random; functions that are mechanistically similar tend to respond coherently. Furthermore, diversity metrics and broad functions (e.g. total biomass) systematically respond in opposite ways. We then formalise these observations to demonstrate, using geometrical arguments, simulations, and a theory-driven analysis of the empirical data, that the response variability of ecosystems is not only predictable, but can also be used to access useful information about species contributions to functions and population-level responses to perturbations. Our research offers a powerful framework for understanding the complexity of ecological responses to global change.
诸如气候变化、入侵物种和污染等干扰因素会影响生态系统的功能和多样性。然而，多样性有多种含义，而生态系统提供了大量的功能。因此，除了全球变化所代表的各种干扰之外，还有许多方法可以衡量干扰对生态的影响。这导致了压倒性的响应可变性，从而破坏了预测的希望。在这里，我们表明这种可变性反而可以深入了解功能和物种对干扰的响应的隐藏特征。通过分析微生物土壤系统全球变化实验的数据集，我们首先表明，对干扰的功能和多样性响应的可变性并非随机的；在机制上相似的功能往往会一致响应。此外，多样性指标和广泛的功能（例如总生物量）系统地以相反的方式响应。然后，我们通过使用几何论证、模拟和对经验数据的理论驱动分析，正式证明了这些观察结果，表明生态系统的响应可变性不仅是可预测的，而且还可以用于获取有关物种对功能的贡献和种群水平对干扰的响应的有用信息。我们的研究为理解生态系统对全球变化的复杂响应提供了一个强大的框架。
