Opportunities and limitations to detect climate-related regime shifts in inland Arctic ecosystems through eco-hydrological monitoring
Bibliographic record
Abstract
This study has identified and mapped the occurrences of three different types of climate-driven and hydrologically mediated regime shifts in inland Arctic ecosystems: (i) from tundra to shrubland or forest, (ii) from terrestrial ecosystems to thermokarst lakes and wetlands, and (iii) from thermokarst lakes and wetlands to terrestrial ecosystems. The area coverage of these shifts is compared to that of hydrological and hydrochemical monitoring relevant to their possible detection. Hotspot areas are identified within the Yukon, Mackenzie, Barents/Norwegian Sea and Ob river basins, where systematic water monitoring overlaps with ecological monitoring and observed ecosystem regime shift occurrences, providing opportunities for linked eco-hydrological investigations that can improve our regime shift understanding, and detection and prediction capabilities. Overall, most of the total areal extent of shifts from tundra to shrubland and from terrestrial to aquatic regimes is in hydrologically and hydrochemically unmonitored areas. For shifts from aquatic to terrestrial regimes, related water and waterborne nitrogen and phosphorus fluxes are relatively well monitored, while waterborne carbon fluxes are unmonitored. There is a further large spatial mismatch between the coverage of hydrological and that of ecological monitoring, implying a need for more coordinated monitoring efforts to detect the waterborne mediation and propagation of changes and impacts associated with Arctic ecological regime shifts.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".