Comparing microbial and chemical kinetics for modelling soil organic carbon decomposition using the DecoChem v1.0 and DecoBio v1.0 models
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract. Soil organic matter is a vast store of carbon, with a critical role in the global carbon cycle. Despite its importance, the dynamics of soil organic carbon decomposition, under the impact of climate change or changing litter inputs, are poorly understood. Current biogeochemical models usually lack microbial processes and thus miss an important feedback when considering the fate of carbon. Here we use a series of modelling experiments to evaluate two different model structures: one with a standard first-order kinetic representation of soil decomposition (DecoChem v1.0, hereafter chemical model) and one with control of soil decomposition through microbial activity (DecoBio v1.0, hereafter biological model). The biological model includes cycling of organic matter into and out of microbial biomass, and simulates the decay rate as a functional of microbial activity. We tested two hypotheses. First, we hypothesized different responses in the two models to increased litter inputs and glucose additions. In the microbial model we hypothesized that this perturbation would prime microbial activity and reduce soil carbon stocks; in the chemical model we expected this perturbation to increase C stocks. In the biological model, responses to changed litter quantity were more rapid, but with the residence time of soil C altering such that soil C stocks were buffered. However, in the biological model there was a strong response to increased glucose additions (i.e. changes in litter quality), with significant losses to soil C stocks over time, driven by priming. Secondly, we hypothesized that warming will stimulate decomposition in the chemical model and loss of C, but in the biological model soil C will be less sensitive to warming, due to complex microbial feedbacks. The numerical experiments supported this hypothesis, with the chemical model soil C residence times and steady-state C stocks adjusting strongly with temperature changes, extending over decades. On the other hand, the biological model showed a rapid response to temperature that subsided after a few years, with total soil C stocks largely unchanged. The microbial model shows qualitative agreement with experimental warming studies that found transient increases in soil respiration that decline within a few years. In conclusion, the biological model is largely buffered against bulk changes in litter inputs and climate, unlike the chemical model, while the biological model displays a strong priming response to additions of labile litter. Our results have therefore highlighted significantly different sensitivities between chemical and biological modelling approaches for soil decomposition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it