Analyzing Environmental Stress Counter-Measures in Agricultural Heritage Sites in China
Why this work is in the frame
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Bibliographic record
Abstract
In recent years, with climate change, many agricultural systems are facing severe environmental stress, which are seriously threatening the food security and sustainable development of agricultural system. Although mainstream agro-system can effectively reduce the adverse agro-production effect rapidly by using modern technology, but many of them bring serious ecological crisis at the same time. For the sustainable development of agro-systems, the stress mitigation options must give full consideration to ecological protection. The Globally Important Agricultural Heritage Systems (GIAHS) sites, relying on its unique land use, water conservancy facilities, traditional crops, etc., form unique production system creating a better match with local natural conditions. Based on disaster mitigation system theory and practice, this paper analyzes environmental stress counter-measures of several GIAHS sites in China. The water requirement of millet, a drought-tolerant crop in Aohan Dryland Farming System (recognized as a GIAHS pilot site in 2012), has a better match with local water conditions. By reducing vulnerability of crops, agriculture survived healthily in semi-arid regions. Honghe Hani Rice Terraces System (recognized as a GIAHS pilot site in 2010), relying on the unique land and water use patterns, has successfully reshape disaster inducing environment, and effectively reduce the risk/effects of droughts. Besides, due to the high price, rich crop diversity and variety of income channel, the Agricultural Heritage sites can ensure the economic income and agro-system health when facing environmental stress. Stress counter-measures of traditional agricultural systems make full use of the regulation and spontaneity ability of the natural system, which is an important way to achieve sustainable development of ecological agriculture.
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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 it