Microbial community composition and activity in paired irrigated and non-irrigated pastures in New Zealand
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Context Microorganisms are key for carbon (C) and nitrogen (N) cycling in soils supporting agricultural production. Aims We investigated the impacts of irrigation on microbial community structure and activity in New Zealand on 28 paired non-irrigated and irrigated grazed pasture sites where C and N had decreased under irrigation. Methods Microbial community structure and microbial biomass (phospholipid fatty acids) and activity (basal respiration, substrate-induced respiration (SIR), aerobically mineralisable N (AerMN)) were assessed. Key results Microbial biomass did not differ between irrigated and non-irrigated soils, but irrigated soils had increased gram-negative bacteria (P < 0.05), lower gram-positive:gram-negative ratio (P < 0.001) and lower fungal:bacterial ratio (P < 0.001) compared to non-irrigated soils. SIR and AerMN were greater in irrigated compared to non-irrigated soils. There were no differences in basal respiration between irrigation treatments. Greater prevalence of gram-negative bacteria (r-strategist) as well as decreases in actinomycetes and fungal to bacterial ratio, and increased SIR and AerMN suggest more rapid cycling of C and nutrients in irrigated systems where C had been lost. Conclusions We found clear evidence that irrigation alters microbial community structure and activity in New Zealand pasture systems. Implications Irrigation driven alteration of microbial populations may contribute to losses of soil SOM and soils’ ability to deliver ecosystem services.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it