Marketing birds: The traits birdwatching tourism companies highlight in Costa Rican tour itineraries
Bibliographic record
Abstract
Abstract Birdwatching tourism has blossomed into a profitable industry, promoting peoples’ connections to nature and contributing billions of dollars to local economies annually. Understanding which species birdwatchers value and why could help distinguish flagship species for ecotourism and conservation marketing. Here, we draw from ecological, psychological, and economic perspectives to test hypotheses about which species’ attributes (i.e., traits) are most prevalent among birds marketed to birdwatchers. To do so, we implemented a multi-year course-based undergraduate research experience to quantify how often >750 bird species appeared in >150 itineraries describing tours traversing Costa Rica. We then associated itinerary mentions with data on species’ appearances, vocalizations, distributions, conservation statuses, and behaviors. We found that larger, more attractive species appeared frequently in trip itineraries, but species with pleasing vocalizations did not. We also found that range-restricted species appeared 10 times more frequently in trip itineraries than cosmopolitan species. Species with tropical distributions that rarely associate with humans were also more frequently mentioned, suggesting that companies recognize the high value dedicated birdwatchers place on novel species. Surprisingly, IUCN status was not associated with itinerary scores, and commonly encountered species were more likely to be mentioned in trip itineraries than rarely encountered species. These findings suggest tour companies may balance species’ perceived novelty to birdwatchers against the likelihood that they can “deliver” them to their clients. Our findings broadly contribute to a deeper understanding of how human preferences shape interactions with biodiversity and may help bridge the gap between cultural ecosystem services and conservation strategies. Insights into which traits drive birdwatcher preferences could help conservation practitioners and tour operators identify species potentially at risk from unregulated birdwatching tourism as well as species that could be used as flagships to motivate ecotourism and conservation actions.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".