A global comparative analysis of local recreation behaviors and values in peri-urban forests
Bibliographic record
Abstract
Recreation is an essential ecosystem service (ES) provided by urban and peri-urban forests. In the context of adapting forest management to social demands, it is important to understand recreation behavior and the value that people place on their recreation. This study presents a comparison of recreation behavior and willingness to pay (WTP) across four peri-urban forests located in Freiburg (Germany), Oakville (Canada), Xi'an (China) and Zomba (Malawi). WTP was asked under two contingent valuation scenarios, one to improve the forest management according to the respondents' preferences for forest characteristics and the other to sustain the forest under climate change impacts. We conducted on-site surveys, focusing on the inhabitants of the associated cities. While the recreationists were generally satisfied with the forest infrastructure (e.g., paths), they were rather dissatisfied with the facilities (e.g., sanitation and drinking water). The mean annual WTP (adjusted by purchasing-power-parity, PPP) to improve the forest management was 21.07US$ PPP in Freiburg, 18.53US$ PPP in Oakville, 8.32US$ PPP in Xi'an, and 3.52US$ PPP in Zomba. Under climate change impacts, the mean annual WTP was 27.96US$ PPP in Freiburg, 19.29US$ PPP in Oakville, 7.52US$ PPP in Xi'an, and 3.53US$ PPP in Zomba. The statistical analysis revealed a positive effect of income on WTP in Freiburg, Oakville, and Xi'an. In addition, in Freiburg, education increased WTP, while in Xi'an, younger participants were more likely to pay. In Freiburg and Zomba, belief in climate change was found to increase the probability of WTP under the climate change scenario. Regarding the payment vehicle, a local tax and a voluntary donation were preferred in Freiburg and Oakville, an entry fee in Xi'an, and there was no preference in Zomba.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".