Present and future thermal regimes of intertidal groundwater springs in a threatened coastal ecosystem
Bibliographic record
Abstract
In inland settings, groundwater discharge thermally modulates receiving surface water bodies and provides localized thermal refuges; however, the thermal influence of intertidal springs on coastal waters and their thermal sensitivity to climate change are not well studied. We addressed this knowledge gap with a field- and model-based study of a threatened coastal lagoon ecosystem in southeastern Canada. We paired analyses of drone-based thermal imagery with in situ thermal and hydrologic monitoring to estimate discharge to the lagoon from intertidal springs and groundwater-dominated streams in summer 2020. Results, which were generally supported by independent radon-based groundwater discharge estimates, revealed that combined summertime spring inflows (0.047 m 3 s −1 ) were comparable to combined stream inflows (0.050 m 3 s −1 ). Net advection values for the streams and springs were also comparable to each other but were 2 orders of magnitude less than the downwelling shortwave radiation across the lagoon. Although lagoon-scale thermal effects of groundwater inflows were small compared to atmospheric forcing, spring discharge dominated heat transfer at a local scale, creating pronounced cold-water plumes along the shoreline. A numerical model was used to interpret measured groundwater temperature data and investigate seasonal and multi-decadal groundwater temperature patterns. Modelled seasonal temperatures were used to relate measured spring temperatures to their respective aquifer source depths, while multi-decadal simulations forced by historic and projected climate data were used to assess long-term groundwater warming. Based on the 2020–2100 climate scenarios (for which 5-year-averaged air temperature increased up to 4.32 ∘ ), modelled 5-year-averaged subsurface temperatures increased 0.08–2.23 ∘ in shallow groundwater (4.2 m depth) and 0.32–1.42 ∘ in the deeper portion of the aquifer (13.9 m), indicating the depth dependency of warming. This study presents the first analysis of the thermal sensitivity of groundwater-dependent coastal ecosystems to climate change and indicates that coastal ecosystem management should consider potential impacts of groundwater warming.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".