Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, USA.
Glob Chang Biol. 2020 Jan;26(1):287-299. doi: 10.1111/gcb.14894. Epub 2019 Nov 29.
This commentary summarizes the publication history of Global Change Biology for works on experimental manipulations over the past 25 years and highlights a number of key publications. The retrospective summary is then followed by some thoughts on the future of experimental work as it relates to mechanistic understanding and methodological needs. Experiments for elevated CO atmospheres and anticipated warming scenarios which take us beyond historical analogs are suggested as future priorities. Disturbance is also highlighted as a key agent of global change. Because experiments are demanding of both personnel effort and limited fiscal resources, the allocation of experimental investments across Earth's biomes should be done in ecosystems of key importance. Uncertainty analysis and broad community consultation should be used to identify research questions and target biomes that will yield substantial gains in predictive confidence and societal relevance. A full range of methodological approaches covering small to large spatial scales will continue to be justified as a source of mechanistic understanding. Nevertheless, experiments operating at larger spatial scales encompassing organismal, edaphic, and environmental diversity of target ecosystems are favored, as they allow for the assessment of long-term biogeochemical feedbacks enabling a full range of questions to be addressed. Such studies must also include adequate investment in measurements of key interacting variables (e.g., water and nutrient availability and budgets) to enable mechanistic understanding of responses and to interpret context dependency. Integration of ecosystem-scale manipulations with focused process-based manipulations, networks, and large-scale observations will aid more complete understanding of ecosystem responses, context dependence, and the extrapolation of results. From the outset, these studies must be informed by and integrated with ecosystem models that provide quantitative predictions from their embedded mechanistic hypotheses. A true two-way interaction between experiments and models will simultaneously increase the rate and robustness of Global Change research.
本述评总结了《全球变化生物学》自 25 年前创刊以来发表的有关实验操作的出版物历史，并重点介绍了一些关键出版物。回顾总结之后，作者对未来的实验工作进行了一些思考，包括其与机制理解和方法需求的关系。作者建议未来的实验工作应优先考虑大气中 CO2 浓度升高和预期变暖情景的实验，这些实验将超出历史模拟。干扰也被强调为全球变化的关键因素。由于实验既需要人员投入，又需要有限的财政资源，因此应在具有关键重要性的生态系统中分配实验投资。不确定性分析和广泛的社区咨询应被用来确定研究问题和目标生物群落，以提高预测信心和社会相关性。涵盖从小尺度到大尺度空间的各种方法学方法仍将被证明是获得机制理解的一个来源。然而，在目标生态系统中运作的更大空间尺度的实验，包括生物体、土壤和环境多样性，更有利于进行长期生物地球化学反馈的评估，从而能够解决更广泛的问题。此类研究还必须包括对关键相互作用变量（如水分和养分的可利用性和预算）进行充分测量，以实现对响应的机制理解，并解释上下文依赖性。生态系统尺度的操作与重点过程操作、网络和大规模观测的整合将有助于更全面地了解生态系统的响应、上下文依赖性以及结果的外推。从一开始，这些研究就必须得到包含其嵌入机制假设的生态系统模型的指导和整合，以提供定量预测。实验和模型之间的真正双向互动将同时提高全球变化研究的速度和稳健性。
