Understanding the Coastal Ecocline: Assessing Sea–Land Interactions at Non-tidal, Low-Lying Coasts Through Interdisciplinary Research
Bibliographic record
Abstract
Coastal zones connect terrestrial and marine ecosystems forming a unique environment that is under increasing anthropogenic pressure. Rising sea levels, sinking coasts, and changing precipitation patterns modify hydrodynamic gradients and may enhance sea-land exchange processes in both tidal and non-tidal systems. Furthermore, the removal of flood protection structures as restoration measure contributes locally to the changing coastlines. A detailed understanding of the ecosystem functioning of coastal zones and the interactions between connected terrestrial and marine ecosystems is still lacking. Here, we propose an interdisciplinary approach to the investigation of interactions between land and sea at shallow coasts, and discuss the advantages and the first results provided by this approach as applied by the research training group Baltic TRANSCOAST. A low-lying fen peat site including the offshore shallow sea area on the southern Baltic Sea coast has been chosen as a model system to quantify hydrophysical, biogeochemical, sedimentological, and biological processes across the land-sea interface. Recently introduced rewetting measures might have enhanced submarine groundwater discharge as indicated by distinct patterns of salinity gradients in the near shore sediments, making the coastal waters in front of the study site a mixing zone of fresh- and brackish water. High nutrient loadings, dissolved inorganic carbon, and dissolved organic matter originating from the degraded peat may affect micro- and macro-phytobenthos, with the impact propagating to higher trophic levels. The terrestrial part of the study site is subject to periodic brackish water intrusion caused by occasional flooding, which has altered the hydraulic and biogeochemical properties of the prevailing peat soils. The stable salinity distribution in the main part of the peatland reveals the legacy of flooding events. Generally, elevated sulfate concentrations are assumed to influence greenhouse gas emissions, mainly by inhibiting methane production, yet our investigations indicate complex interactions between the different biogeochemical element cycles (e.g. carbon and sulfur) caused by connected hydrological pathways. In conclusion, sea-land interactions are far reaching, occurring on either side of the interface, and can only be understood when both long-term and event-based patterns and different spatial scales are taken into account in interdisciplinary research that involves marine and terrestrial expertise.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".