Implications of pasture improvement for bird conservation in the high plains of the Colombian Llanos
Bibliographic record
Abstract
The high plains of the Colombian Llanos are emerging as a new agricultural frontier, where native tropical savannas are increasingly being converted into improved pastures to facilitate grazing intensification. However, the impacts of this land conversion have not been adequately addressed, especially in the context of biodiversity conservation. In this study, I conducted bird surveys at Hacienda San José (HSJ), a private cattle farm that established improved pastures with a focus on sustainable intensification while preserving an area of native savanna vegetation. I evaluated bird density, species richness, and community similarity across three land-use management regimes: improved pastures with rotational grazing and burning exclusion (IP), preserved native savanna with no burning or grazing (PNS), and conventionally managed savanna (CMS) subject to burning and grazing, located outside of HSJ. Results showed that IP had the highest bird species richness and density. However, PNS and CMS supported unique populations of savanna specialist birds at higher abundances, while CMS had the lowest overall species diversity of the three management regimes. These findings (1) highlight the importance of preserving native savanna vegetation within agricultural landscapes of the Colombian Llanos and (2) suggest that improved pastures, coupled with sustainable management practices, can help sustain a diverse savanna bird community. Future land use intensification projects should maintain a range of different habitats alongside production areas to ensure the persistence of both generalist and savanna specialist birds in this relatively understudied region of Colombia.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".