The impact of long-term agricultural drainage on concentration and composition of Dissolved Organic Carbon (DOC) in a boreal peatland in western Newfoundland
Bibliographic record
Abstract
Although peatlands cover only 2.84% of the world’s land area, they play a key role in the global C cycle and store one-third of the global soil carbon. Dissolved Organic Carbon (DOC) is one of the available forms of carbon in peatlands, which is lost from the peatland together with other forms of carbon, including dissolved inorganic carbon (DIC) and as the gases carbon dioxide (CO2) and methane (CH4). DOC contains both biologically available (labile) and recalcitrant components. In peatlands, the influence of DOC on the C cycle is more significant than in terrestrial and aquatic ecosystems, and thus understanding of any changes in DOC quality induced by peatland drainage is critical. The quality and quantity of DOC determine the further role of DOC in biogeochemical cycles. Accordingly, this study investigated the effects of agricultural drainage on DOC in a boreal peatland in western Newfoundland, by quantifying (concentration) and qualifying (composition) of DOC in two drained and natural peatland sites. The effect of microforms in the natural site on quality and quantity of DOC, was also examined. This study showed that long-term drainage increased DOC concentration both at the peat surface (10 cm) and at a depth of 40 cm by 32% and 47%, respectively. The quality of DOC was also affected by agricultural drainage and microforms (hummock or hollow). Agricultural drainage reduced the DOC aromaticity and transformed DOC from refractory to labile forms. In the natural sites, hummock had higher DOC concentration and showed more recalcitrant and humified DOC. Although DOC in both the drained and the natural site was mainly plant-driven regardless of the different vegetation compositions and microforms, DOC at the drained site was of a plant-derived source over microbially processed DOC throughout the peat layers. Increasing DOC concentration following agricultural drainage shifts the Dissolved Organic Matter (DOM) from the microbial-derived source to a plant-derived source. Similarly, agricultural drainage increased the degree of humification at both peat depths. Comparing two different depths of sampling revealed that the shallower sampling depth had greatest differences in DOC quantity and quality across the drained and natural sites. It means that the variation in DOC caused by any management changes has an intensive effect on shallower peat layers. Furthermore, there is more humified microbially-sourced DOC found at the deeper peat layers. Results also demonstrated the different DOC concentration and composition associated with different plant communities in the drained site and different microforms in the natural site. Our study showed that establishment of reed canary grass followed by drainage in the drained peatland pasture site could introduce labile carbon compounds with a high degree of humification into the below ground environment during the growing season. Results of this study support the fact that land management activities (such as agricultural drainage) have effects on DOC quantity together with quality of peatlands and also have a profound effect in increasing labile DOC at the deeper layers, which can affect the carbon balance of boreal peatland ecosystems. This raises the possibility of managing the plant community to control DOC concentration to reduce carbon losses from peatlands. The effect of land management, plant community, and its effects on peat properties should be given more weight in large-scale carbon modeling.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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 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".