Modelling decadal trends and the impact of extreme events on carbon fluxes in a temperate deciduous forest using a terrestrial biosphere model
Bibliographic record
Abstract
Abstract. Changing climatic conditions pose a challenge to accurately estimating the carbon sequestration potential of terrestrial vegetation, which is often mediated by nitrogen availability. The close coupling between the nitrogen and carbon cycles controls plant productivity and shapes the structure and functional dynamics of ecosystems. However, how carbon and nitrogen interactions affect both carbon fluxes and plant functional traits in dynamic ecotones, which are experiencing biotic and abiotic changes, remains unclear. In this work, we use in situ measurements of leaf chlorophyll content (ChlLeaf, 2013–2016) and the leaf area index (LAI, 1998–2018) to parameterize the seasonal dynamics of the QUINCY (QUantifying Interactions between terrestrial Nutrient CYcles and the climate system) terrestrial biosphere model (TBM) to simulate the carbon fluxes at the Borden Forest Research Station flux tower site, Ontario, Canada, over 22 years from 1996 to 2018. Our goals are to assess the additional value of using ChlLeaf in the model parameterization, to study how well QUINCY can capture observed trends related to the carbon cycle at the site, and to investigate how well the processes associated with a drought year and its legacy effects are captured by the model. QUINCY was able to simulate leaf-level maximum carboxylation capacity (Vc(max),25), ChlLeaf and leaf nitrogen in a manner quite consistent with observations. The model with the improved parameterization captured observed daily gross primary production (GPP) well (r2=0.80, root mean square error (RMSE) = 2.2 µmolm-2s-1). Nevertheless, we found that although observed GPP increased significantly during the study period (22.4 gCm2yr-1yr-1) and net ecosystem exchange (NEE) shifted towards a stronger sink, these trends were not captured in the model. Instead, QUINCY showed a significant increasing trend for total ecosystem respiration (TER) that was not present in the observations. The severe drought in 2007 strongly affected observed carbon fluxes, lowering both GPP and TER in the following year as well. QUINCY was able to capture some of the decrease in GPP and TER in 2007. However, the legacy effect of the drought in 2008 was not captured by the model. These results call for further work on representing legacy effects in TBMs, as these can have long-lasting impacts on ecosystem functioning.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".