Silvopastoral agroforestry systems for dryland corners in Canterbury farms
Bibliographic record
Abstract
Potential future water constraints on dry areas of Canterbury farms, combined with existing animal welfare requirements, have spurred interest in practices such as agroforestry that can help future proof farming. Agroforestry is the deliberate integration of trees within a livestock grazing system. We surveyed farmers to investigate their understanding of agroforestry, including enablers and barriers to change; and conducted a literature review to identify key agroforestry concepts. We partnered with Ngāi Tahu Farming and Claxby Farms in Canterbury Region to co-develop agroforestry planting plans and completed economic analysis of the agroforestry component of each farm. We also identified other unquantifiable potential benefits of integrating trees on farms. We found that the agroforestry systems designed have positive net present value, internal rate of return, and a positive post carbon income annual cashflow. We have demonstrated that agroforestry is potentially economically viable in Canterbury. Agroforestry systems can be designed to align with the New Zealand Emissions Trading Scheme (NZ ETS) and in turn this would provide financial incentives for establishing trees on dryland corners. The quantified economic outcomes and the identified unquantified benefits warrant further research into integrating agroforestry into dairy and other farming systems around New Zealand.
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How this classification was reachedexpand
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".