Changing processes flooding a salt marsh in a microtidal estuary with a drying climate
Bibliographic record
Abstract
Estuarine salt marshes globally face numerous threats, not least of which include changing hydrological conditions from human alteration and climate change impact to river flows, sea levels and coastal processes. While changing inundation is evident in many systems, often, the detail of which estuarine processes are changing and to what extent they contribute to flooding and habitat distribution remains unknown. Water levels in the microtidal Swan River Estuary (Derbarl Yerrigan), Western Australia, which has experienced significant climate drying since the 1970's, were disaggregated to assess contributions from tides, mean sea level, barometric effects, river flows and river-tide interactions. These contributions were mapped to the habitat of a salt marsh community. The effect of declining river flows on tides were further assessed by wavelet and harmonic analyses. We found that tides and barometric effects presently dominate flooding events of relevance to the salt marsh community. Declining winter runoff resulted in an increase in the tidal amplitude in the upper estuary. There was also a positive winter mean sea level pressure trend, associated with the winter rainfall decline. Altogether, there was zero net change to flooding of a salt marsh in the estuary from these processes. Therefore, steady sea level rise masked changes in the relative contribution of flooding mechanisms in the estuary which have implications for the stability of the marsh ecosystem. Disaggregating process contributions to salt marsh water levels offers a means to better assess the hydrodynamic processes presently sustaining salt marsh communities and to inform how they might change in the future. These results show that numerous hydrological processes can interact to mask non-stationary changes to estuarine hydrology supporting salt marsh habitat.
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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".