The effect of repeated liquid swine manure applications on soil nutrient supply rates and growth of different hybrid poplar clones
Bibliographic record
Abstract
Intensive hog operations generate large amounts of manure that must be dealt with in an environmentally responsible and economically practical manner. Repeated applications of liquid swine manure within nearby hybrid poplar plantations recently has been proposed as an effective alternative manure management practice, given that these fast-growing tree species have high soil moisture and nutrient demands and, therefore, represent a tremendous sink for the applied effluent. The objectives of this two-year study were to: i) evaluate the effect of repeated broadcast applications of liquid swine manure on soil nutrient supply rates and growth of five hybrid poplar clones (CanAm, Hill, Katepwa, Walker, and WT-66V) and, ii) assess the relationship between growing season soil nutrient supply rates, measured using in situ burials of ion-exchange membrane (Plant Root Simulator™-probes), and growth of different hybrid poplar clones. There was a limited effect of applied hog effluent on soil nutrient supply rates after the first year and hybrid poplar growth after two years, which is surprising considering the application rate was three times larger than the agronomic rate typically applied. The limited measureable difference following manure addition may be attributable to a number of factors, including: substantial volatilization, microbial immobilization, increased leaching and denitrification losses, timing of manure application being out of sync with temporal nature of nutrient uptake by the trees, and a delayed growth response as absorbed nutrients are retranslocated within the trees. Determining the effects of repeated applications of hog effluent on soil nutrient supply rates and subsequent tree growth should help to support effective management strategies, in terms of developing practical effluent management practices required to mitigate any adverse environmental effects, but also increasing plantation productivity and the concomitant non-wood product benefit of increasing biodiversity within the agricultural landscape.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".