Multi‐species, multi‐country analysis reveals North Americans are willing to pay for transborder migratory species conservation
Bibliographic record
Abstract
Abstract Migratory species often provide ecosystem service benefits to people in one country while receiving habitat support in other countries. The multinational cooperation that could help ensure continued provisioning of these benefits by migration may be informed by understanding the economic values people in different countries place on the benefits they derive from migratory wildlife. We conducted contingent valuation surveys to estimate the willingness of 3733 respondents from Canada, the United States and México to invest in conservation for two disparate migratory species, the northern pintail duck Anas acuta and the Mexican free‐tailed bat Tadarida brasiliensis mexicana . With zero‐inflated mixed‐effects negative binomial regression (explaining 87% of the variation in willingness to pay for conservation), we found that respondents from each nation, after controlling for both household income and per capita national Gross Domestic Product, were willing to invest in conservation in other countries. This willingness to pay for conservation, even when respondents knew that funds would be used to support benefits accruing primarily in other countries, demonstrates the potential for support of multinational conservation policies and programmes that direct resources to locations where the most critical habitat is located, rather than where the funding is generated. These findings could be used to support the development or expansion of new and existing international conservation programmes for migratory species. Read the free Plain Language Summary for this article on the Journal blog.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 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".