Efficacy of labile carbon addition to reduce fast‐growing, invasive non‐native plants: A review and meta‐analysis
Bibliographic record
Abstract
Abstract Elevated soil nitrogen (N) resulting from pollution, fertilizer and woody encroachment in grasslands enhances invasion pressures from weedy plant species. Sawdust, sucrose and other labile carbon (C) sources can be used as a soil amendment to combat the growth of fast‐growing, invasive non‐native plants by immobilizing soil N. Here, we present a systematic review of 83 publications, and a meta‐analysis from 48 publications. Using hierarchical mixed‐effects meta‐analytic models, we synthesized 655 responses from native plants and 486 responses from non‐native weeds to quantify the overall effect of C addition. We explored the possible explanations for variation in effect, such as differences in study conditions and how C was applied. Carbon addition studies were almost exclusively reported from the United States, Australia and Canada (93%). The majority of papers (63%) did not include any cost information. Overall, C addition significantly decreased non‐native weed abundance, but did not significantly affect native plant abundance. A C application rate of at least 210 g C m−2 year−1 (5 Mg sucrose ha−1 year−1 or 4.6 Mg sawdust ha−1 year−1) decreased non‐native weed abundance, but a rate of 2110–3000 g C m−2 year−1 (50–71 Mg sucrose ha−1 year−1 or 46–65 Mg sawdust ha−1 year−1) was required to significantly increase native plant abundance. Carbon addition was most effective in the western USA and southeastern Australia, and when used to suppress non‐native grasses (annual or perennial) and annual forbs. Simultaneous seeding of native species prevented an overall decrease in native plant abundance. Synthesis and application. When there is a nearby and inexpensive source of C available, we recommend C addition with simultaneous seeding of native species to control invasive non‐native grasses and annual forbs in semi‐arid and arid regions of the western USA and southeast Australia. In contrast to other weed control measures, especially herbicide, C addition does not significantly harm native perennial plants. Future studies should implement longer‐term monitoring, establish larger plots and include cost analysis to improve guidance for land managers.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.019 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".