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Rethinking experiments that explore multiple global change factors

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Abstract

Our current capacity to predict the responses of ecosystem functions under global change factors is limited. We propose new and more efficient approaches to experimental design and modeling that utilize interactions between ecosystem functions to improve our understanding of their sensitivity to global change factors.

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Multiple global change factors are influencing terrestrial ecosystems

Increased atmospheric carbon dioxide concentrations, climate warming, and shifts in rainfall patterns are examples of post-Industrial Revolution global changes that have profoundly affected the functioning and diversity of terrestrial ecosystems [1]. Although these issues have generated significant concern among scientists, politicians, and the general public, various other global changes beyond warming and drought are also occurring, including widespread alterations in land use, increases in

Limitations to global change factor experiments

Illustrating this issue, a recent review of the sensitivity of terrestrial carbon cycles to multiple global change factors determined that the vast majority of experiments (>98% of studies) incorporated only one or two factors, with a very small minority of relevant studies considering three or more factors simultaneously [4]. It should be noted that many of these experiments determined that variations in the studied global change factors produced consistent linear responses in carbon cycle

Plant productivity as an indicator of critical thresholds in global change factors

As an example, we considered the cascade of effects from interacting global change drivers to net primary productivity (NPP), then to soil methane efflux which is a critical ecosystem function [1]. NPP and soil methane efflux are both affected by various global change factors, such as temperature and rainfall [6], but changes in NPP can also affect soil methane efflux [7]. Increased NPP enhances litterfall and root exudation, providing more organic material for methanogenesis [7]. Conditions

Simplifying global change factor experiments by incorporating plant data

On the basis of the large amount of field vegetation dynamic data provided by the long-term biodiversity monitoring and research network, and the newly developed remote sensing technology, we are confident that sufficient observational data will be available to model and identify critical thresholds in multiple global change factors simultaneously. This information can then be used to design more efficient trials and experiments that test precise combinations of the levels of global change

Concluding remarks

We acknowledge the need and urgency to study the impact of multiple global change factors simultaneously on ecosystem functioning [2., 3., 4.]. Through the pathways outlined here (exploration of the interactions among ecosystem functions, the long-term biodiversity monitoring and research network, and model development), we can further improve our understanding of the multifactorial effects of global change on ecosystem functions. We believe that, as we work towards this goal, we will become

Acknowledgments

The research was jointly supported by the National Natural Science Foundation of China (No. 32171635 and No. 31870497) and the Fundamental Research Funds for the Central Universities and the Resilient Forests program, which is funded by the New Zealand Ministry of Business, Innovation and Employment (MBIE) Strategic Science Investment Fund, and in part by the New Zealand Forest Growers Levy Trust (C04X1703). We thank editor Professor Andrea Stephens and the anonymous reviewers for their many

References (12)

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