SHIMMER (1.0): a novel mathematical model for microbial and biogeochemical dynamics in glacier forefield ecosystems
Bibliographic record
Abstract
Abstract. SHIMMER (Soil biogeocHemIcal Model for Microbial Ecosystem Response) is a new numerical modelling framework which is developed as part of an interdisciplinary, iterative, model-data based approach fully integrating fieldwork and laboratory experiments with model development, testing, and application. SHIMMER is designed to simulate the establishment of microbial biomass and associated biogeochemical cycling during the initial stages of ecosystem development in glacier forefield soils. However, it is also transferable to other extreme ecosystem types (such as desert soils or the surface of glaciers). The model mechanistically describes and predicts transformations in carbon, nitrogen and phosphorus through aggregated components of the microbial community as a set of coupled ordinary differential equations. The rationale for development of the model arises from decades of empirical observation on the initial stages of soil development in glacier forefields. SHIMMER enables a quantitative and process focussed approach to synthesising the existing empirical data and advancing understanding of microbial and biogeochemical dynamics. Here, we provide a detailed description of SHIMMER. The performance of SHIMMER is then tested in two case studies using published data from the Damma Glacier forefield in Switzerland and the Athabasca Glacier in Canada. In addition, a sensitivity analysis helps identify the most sensitive and unconstrained model parameters. Results show that the accumulation of microbial biomass is highly dependent on variation in microbial growth and death rate constants, Q10 values, the active fraction of microbial biomass, and the reactivity of organic matter. The model correctly predicts the rapid accumulation of microbial biomass observed during the initial stages of succession in the forefields of both the case study systems. Simulation results indicate that primary production is responsible for the initial build-up of substrate that subsequently supports heterotrophic growth. However, allochthonous contributions of organic matter are identified as important in sustaining this productivity. Microbial production in young soils is supported by labile organic matter, whereas carbon stocks in older soils are more refractory. Nitrogen fixing bacteria are responsible for the initial accumulation of available nitrates in the soil. Biogeochemical rates are highly seasonal, as observed in experimental data. The development and application of SHIMMER not only provides important new insights into forefield dynamics, but also highlights aspects of these systems that require further field and laboratory research. The most pressing advances need to come in quantifying nutrient budgets and biogeochemical rates, in exploring seasonality, the fate of allochthonous deposition in relation to autochthonous production, and empirical studies of microbial growth and cell death, to increase understanding of how glacier forefield development contributes to the global biogeochemical cycling and climate in the future.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".