Plant litter chemistry alters the content and composition of organic carbon associated with soil mineral and aggregate fractions in invaded ecosystems
Bibliographic record
Abstract
Through the input of disproportionate quantities of chemically distinct litter, invasive plants may potentially influence the fate of organic matter associated with soil mineral and aggregate fractions in some of the ecosystems they invade. Although context dependent, these native ecosystems subjected to prolonged invasion by exotic plants may be instrumental in distinguishing the role of plant-microbe-mineral interactions from the broader edaphic and climatic influences on the formation of soil organic matter (SOM). We hypothesized that the soils subjected to prolonged invasion by an exotic plant that input recalcitrant litter (Japanese knotweed, Polygonum cuspidatum) would have a greater proportion of plant-derived carbon (C) in the aggregate fractions, as compared with that in adjacent soil inhabited by native vegetation that input labile litter, whereas the soils under an invader that input labile litter (kudzu, Pueraria lobata) would have a greater proportion of microbial-derived C in the silt-clay fraction, as compared with that in adjacent soils that receive recalcitrant litter. At the knotweed site, the higher C content in soils under P. cuspidatum, compared with noninvaded soils inhabited by grasses and forbs, was limited to the macroaggregate fraction, which was abundant in plant biomarkers. The noninvaded soils at this site had a higher abundance of lignins in mineral and microaggregate fractions and suberin in the macroaggregate fraction, partly because of the greater root density of the native species, which might have had an overriding influence on the chemistry of the above-ground litter input. At the kudzu site, soils under P. lobata had lower C content across all size fractions at a 0-5 cm soil depth despite receiving similar amounts of Pinus litter. Contrary to our prediction, the noninvaded soils receiving recalcitrant Pinus litter had a similar abundance of plant biomarkers across both mineral and aggregate fractions, potentially because of the higher surface area of soil minerals at this site. The plant biomarkers were lower in the aggregate fractions of the P. lobata-invaded soils, compared with noninvaded pine stands, potentially suggesting a microbial co-metabolism of pine-derived compounds. These results highlight the complex interactions among litter chemistry, soil biota, and minerals in mediating soil C storage in unmanaged ecosystems; these interactions are particularly important under global changes that may alter plant species composition and hence the quantity and chemistry of litter inputs in terrestrial ecosystems.
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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 | 0.000 |
| 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 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".