Comparative effect of alternative fertilisers on pasture production, soil properties and soil microbial community structure
Bibliographic record
Abstract
Different fertiliser products are commonly promoted for use on pastures in order to improve pasture productivity and support a more ‘healthy’ soil microbial environment. However, minimal field research has been conducted to validate such claims. A 6-year study (2009–14) was conducted on phosphorus (P)-deficient soils at three sites near Yass, New South Wales, to investigate the effect of topdressing perennial native-based pastures with a range of alternative fertilisers compared with single superphosphate and an unfertilised control treatment. The alternative fertiliser products included manures, composts, crushed rock, rock-phosphate-derived products, concentrated ash and microbial products. Annual measurements were made of soil chemical properties, botanical composition and pasture yield during spring and/or winter + spring, as well as the relative effectiveness of products per unit of pasture grown. Soil microbial community structure under each fertiliser treatment was also analysed in the sixth year of the study. Fertiliser products with substantial quantities of P increased extractable soil P and resulted in significantly higher pasture growth and clover content compared with the unfertilised control. Superphosphate was found to be the most P-effective fertiliser for increasing pasture growth, along with a range of other products that showed differential responses. However, the cost and P-effectiveness of the products in relation to pasture growth varied considerably and was a function of rate and frequency of application as well as amount and solubility of the P applied. Despite large differences in pasture growth across the various fertiliser treatments, there was no significant effect of the alternative fertiliser products on microbial community structure compared with either the superphosphate or unfertilised control treatments. The observed variation in bacterial, fungal and archaeal community structures across all fertiliser treatments was best explained by soil pH or aluminium (Al) concentration, which was influenced differentially by the fertiliser products. Fungal community structure was also correlated with pasture-productivity parameters (i.e. spring pasture yield, clover content and soil-available P). Our findings reveal a highly resilient soil microbial community that was influenced minimally by use of the alternative fertiliser products, thus highlighting that on-farm management decisions regarding fertiliser product choice should primarily focus on pasture response and cost-effectiveness.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".