Insights for policy-based conservation strategies for the Rio de la Plata Grasslands through the IPBES framework
Bibliographic record
Abstract
Abstract The Río de la Plata Grasslands (RPG) are one of the most modified biomes in the world. Changes in land use and cover affect the RPG’s rich biodiversity. In particular, the expansion of crops, overgrazing, afforestation, and the introduction of exotic species pose a major threat to the conservation of biodiversity and ecosystem services (BES). In this study, we applied the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) conceptual framework as a new lens to approach biodiversity conservation enactments in the RPG. First, we systematically reviewed published scientific literature to identify direct and indirect drivers that affect the RPG’s BES. Further, we conducted an extensive analysis of management policies affecting the BES directly in the region, at a national and international level. We conclude by offering recommendations for policy and praxis under the umbrella of the IPBES framework.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".