Linking human well‐being and jellyfish: ecosystem services, impacts, and societal responses
Bibliographic record
Abstract
Jellyfish are usually perceived as harmful to humans and are seen as “pests”. This negative perception has hindered knowledge regarding their value in terms of ecosystem services. As humans increasingly modify and interact with coastal ecosystems, it is important to evaluate the benefits and costs of jellyfish, given that jellyfish bloom size, frequency, duration, and extent are apparently increasing in some regions of the world. Here we explore those benefits and costs as categorized by regulating, supporting, cultural, and provisioning ecosystem services. A geographical perspective of human vulnerability to jellyfish over four categories of human well‐being (health care, food, energy, and freshwater production) is also discussed in the context of thresholds and trade‐offs to enable social adaptation. Whereas beneficial services provided by jellyfish likely scale linearly with biomass (perhaps peaking at a saturation point), non‐linear thresholds exist for negative impacts to ecosystem services. We suggest that costly adaptive strategies will outpace the beneficial services if jellyfish populations continue to increase in the future.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".