Environmental review of geyser basins: resources, scarcity, threats, and benefits
Bibliographic record
Abstract
The world’s geysers are known for providing one of nature’s most unusual water spectacles, with most sending water upwards of about 3 m, but a few “grand” or tall geysers erupt to heights of 60 m or more. A geyser basin is a composite resource made up of geysers and hot springs that cluster around a common hydrothermal reservoir, and might also contain other hydrothermal features like fumaroles and mud pots. The world’s remaining geyser basins are exceptionally rare, and are increasingly important recreation, economic, scientific, cultural, spiritual, therapeutic, and national heritage assets. Geyser basins harbor thermophilic microorganisms that contain heat-adapted biomolecules that can be harvested to provide vital components for DNA testing, and other high-temperature industrial processes. However, geysers and other surface hydrothermal features are increasingly vulnerable, and can be quickly and irreversibly damaged. Energy development projects quenched about 249 geysers, or about half of all geysers that were not protected in a national park or reserve. About 100 geysers were driven to extinction in New Zealand, about 46 in Iceland, and about 48 in the USA. Sustaining the world’s remaining geyser basins requires protecting the hydrothermal reservoirs that support them based on an integrated management approach that takes into account the distinctive characteristics of surface hydrothermal features and the benefits that society derives from them. A framework is provided that defines geyser basin resources, the scarcity of the remaining geysers, the environmental threats, and preservation benefits. Multiple case studies of mass geyser extinction are highlighted, including a summary of the landscape changes that can accompany geothermal energy development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".