The long-term impact of manure application on soil microbial properties and nutrient cycling in Manitoban soils
Bibliographic record
Abstract
The impact of long-term manure application on soil microbial properties was studied at ten sites across the south portion of Manitoba. Each site had different management histories, but consisted of adjacent non-amended and manure-amended (hog or cattle) fields. With no long-term manure-amended field plots available in Manitoba, this study provided a survey of the impacts of long-term manure-amendment on range of soil properties. Biological, physical and chemical soil aspects as well as predictive measures of N mineralization (KC1 extractable NH4+, laboratory incubations) were tested against field N mineralization as influenced by manure treatment. Site differences dominated most parameters examined; suggesting that approaches to N mineralization prediction must include site-specific characteristics. Many parameters responded differently to manure treatment. In general, manure application stimulated microbial community size and activity as demonstrated by higher levels of microbial biomass C (MBC), microbial biomass N (MBN), glutaminase, urease, and dehydrogenase. These parameters were correlated to extractable organic carbon levels, which were greater in manure-amended soils. Hence, manure application by increasing the availability of carbon substrate, enhanced the microbial community and increased the mineralization potential of the soil. The influence of manure amendment was most consistently expressed in sites with longer manure management histories (>35 years). Step-wise regression analyses demonstrated distinct relationships between selected variables on manure-amended and non manure-amended sites. The variation in field N mineralization in manure-amended soils was best described by MBN, urease, organic carbon, pH, and sand content (R2 = 0.76, RMSE 1.07). Manure application did not significantly impact on soil microbial diversity as measured by substrate ultilization patterns; however, longer histories of manure application tended to have greater microbial diversity as shown by the Shannon Diversity Index and partial RDA analyses. Texture, current crop and manure type also affect the diversity of the microbial community and other biological and chemical observed in this study. This study demonstrated that biological parameters are critical to the understanding of nutrient dynamics in manure-amended soil, but no one single measure can be used. Site-specific characterisitics and the potential for nitrogen loss via leaching and denitrification also need to be considered to allow estimation of plant available N.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".