Cattle production in Southern Amazonia: implications for land and water management
Bibliographic record
Abstract
Abstract The expansion of cattle in central western Brazil has been under scrutiny because of the region’s historic reliance on Amazon and Cerrado deforestation for cropland and pastureland expansion. In this study, we determined the volumetric water footprint (VWF) and the land footprint (LF) of cattle in Mato Grosso state for the years 2000, 2005, 2010 and 2014 using official statistics and remote sensing imagery. We found the average VWF of cattle for the time period to be 265–270 l kg −1 LW −1 (LW as live weight of cattle) and a LF which decreased from 71 to 47 m 2 kg −1 LW −1 . The largest contribution to VWF came from farm impoundments whose total area increased from roughly 46 000 to 51 000 ha between 2000 and 2014, leading to a total evaporation as high as 7.31 × 10 11 l yr −1 in 2014. Analysis at the municipality level showed a tendency towards greater density of cattle with respect to both pasture area and impoundments. While cattle intensification on current pastureland is commonly viewed as a means to prevent further deforestation and greenhouse gas emissions, we stress the need to also consider the increasing demand for water associated with a growing cattle herd and the potential appropriation of additional resources for feed for feedlot finishing. Land and water resource management need to be considered together for future planning of cattle intensification at the Brazilian agricultural frontier as illustrated by the footprints reported here.
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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) | 0.001 | 0.001 |
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".