Assessing the Permanence of Land-Use Change Induced by Payments for Environmental Services: Evidence From Nicaragua
Bibliographic record
Abstract
Gains achieved by conservation interventions such as payments for environmental services (PES) may be lost upon termination of the program, a problem known as permanence. However, there have been few efforts to evaluate the permanence of conservation results. This article examines the permanence of land-use changes induced by a short-term PES program implemented between 2003 and 2008 in Matiguás-Río Blanco, Nicaragua. Under this program, PES had induced substantial adoption of silvopastoral practices. To assess the long-term permanence of these changes, participants were resurveyed in 2012, 4 years after the last payment was made. We find that the land-use changes that had been induced by PES were broadly sustained in intervening years, with minor differences across specific practices and subgroups of participants. The patterns of change in the period after the PES program were completed to help us understand the reasons for the program’s success and rule out alternative explanations for the program’s success. Our results suggest that, at least in the case of productive land uses such as silvopastoral practices, PES programs can be effective at encouraging land owners to adopt environmentally beneficial practices and that the benefits will persist after payments cease.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".