ORIGINAL RESEARCH article
Front. Sustain. Food Syst.
Sec. Agroecology and Ecosystem Services
Volume 9 - 2025 | doi: 10.3389/fsufs.2025.1665233
What regulates decomposition in agroecosystems? Insights from reading the tea leaves
Provisionally accepted- 1Iowa State University of Science and Technology Iowa State Online, Ames, United States
- 2Iowa State University of Science and Technology, Ames, United States
- 3Oklahoma State University, Stillwater, United States
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Litter decomposition is a critical Earth process, recycling nutrients and setting a portion of plant tissue on a path toward soil organic matter. Despite this importance, we still lack a good understanding of local factors that regulate decomposition, especially in agroecosystems where management plays an outsized role. We used a narrow range of climate and soils and buried 1,308 pre-manufactured "litter bags" of differing residue quality (i.e. green and rooibos tea leaves) in 109 plots across several management practices to 1) explore the local controls on decomposition in agroecosystems and 2) test the robustness of the Tea Bag Index (TBI). We found management practices intended to increase soil ecosystem services, i.e., soil health, altered decomposition of both teas. For example, adding nitrogen fertilizer and perennial cropping decreased the extent of decomposition of green tea (carbon-to-nitrogen ratio or C:N = 12.8). No-tillage increased, but perennial cropping decreased, rate of rooibos tea decomposition (C:N = 50.1). Cropped prairie accelerated green tea decomposition and increased the extent of red tea decomposition. A random forest regression model showed that soil temperature was the strongest predictor of green tea decomposition, but a soil health score also being important in predicting mass remaining. Soil texture and nutrient availability best predicted rooibos tea decomposition. Finer textured soils seemed to decelerate rooibos decomposition but increased the extent of decomposition. Furthermore, we demonstrated that the TBI metrics correlated somewhat well with empirically derived decomposition constants and were similarly sensitive to the effects of management, but green tea stabilization factor had a substantial prediction bias. Our study increased our basic understanding of regulators of decomposition in agroecosystems and showed that the TBI can be a scientifically rigorous citizen science approach to monitoring changes in soil health.
Keywords: machine learning, nutrient cycling, Regenerative agriculture, Random ForestRegression, Soil Organic Carbon, Tea Bag Index (TBI)
Received: 13 Jul 2025; Accepted: 01 Sep 2025.
Copyright: © 2025 McDaniel, Mohammadiarvejeh, Hu and Middleton. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Marshall Douglas McDaniel, Iowa State University of Science and Technology Iowa State Online, Ames, United States
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