Substrate availability regulates the suppressive effects of Canada goldenrod invasion on soil respiration
Bibliographic record
Abstract
Abstract Invasive alien plants not only decrease riparian vegetation diversity but also alter wetland ecosystem carbon processes, especially when they displace the original vegetation. Invasive Canada goldenrod (Solidago canadensis L.) has colonized large areas of disturbed and undisturbed land in southeastern China, yet little is known regarding how it affects soil carbon cycling. To explore the response patterns of soil respiration following S. canadensis invasion and their driving mechanisms, an observational field study and a greenhouse experiment simulating invasion were performed. In the field study, soil respiration was measured weekly from 21th July 2018 to 15th December 2018. In the greenhouse experiment, soil, autotrophic and heterotrophic respiration were measured every 1st and 15th of the month from 15th July 2019 to 15th December 2019. Soil, autotrophic and heterotrophic respiration were measured using a closed-chamber system with the deep gauze collar root exclusion method. Solidago canadensis invasion appeared to decrease the total soil CO2 emissions in both the field study and the greenhouse experiment. The suppressive effects on soil respiration may be attributed to S. canadensis invasion-induced alterations in the quality and quantity of available soil substrate, suggesting that S. canadensis invasion may impact soil carbon cycling via plant-released substrates and by competing for the soil available substrate with native plant and/or soil microbes. These results have substantial implications for estimations of the effects of invasive plants on belowground carbon dynamics and their contribution to the warming world.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".