Bibliographic record
Abstract
In this century, it is expected that both coastal land development and sea level rise will pose a major threat to tidal wetlands. Historically, tidal salt marshes and mangroves have adjusted to sea level rise, but how they will adjust to the accelerated sea level rise associated with anthropogenic climate change is uncertain. Future adjustments are likely to be limited both by the capacity of the wetlands to accrete, the ability of the vegetation at the seaward edge to tolerate greater hydroperiods and the suitability of inland areas for wetland migration. With the presence of natural and anthropogenic barriers inland, the capacity of wetlands to adjust to sea level rise and the provision of their ecosystem services are likely to be compromised. Using spatially explicit analyses in a geographic information system (GIS), this thesis presents a series of studies modelling magnitude and impacts associated with sea level rise and how these threats will affect two ecosystem services-habitat provision and carbon storage. An index quantifying threats to migration space or 'coastal squeeze' was developed based upon elevation, accretion, slope and degree of imperviousness of intertidal zone. The index was used to rank the threats of coastal squeeze to three marshes at different sea level rise rates. A modification of the coastal squeeze index, using global datasets, was applied to rank the level of threat to North American salt marshes and mangroves. Using a suite of landscape ecology metrics, I examined the impacts of coastal squeeze and different rates of sea level rise on the spatial distribution, size, shape and orientation of wetland patches as they relate to the quality, quantity and availability of fish habitat. The results of different assumptions of accretion rates (i.e., constant rate vs. accretion rate equals sea level rise rate) were compared. Finally, using a spatially and temporally explicit model, I evaluated the sensitivity of carbon storage in a marsh relative to the different rates and trends (i.e., linear vs. non-linear) of sea level rise, spatial variations in vertical accretion, creek expansion, inland migration and topography.
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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".