Visualizing climatic and non-climatic drivers of coastline change in the Town of Lincoln, Ontario, Canada
Bibliographic record
Abstract
Increased urbanization leads to greater anthropogenic stresses of coastal zones. Threats faced by coastal communities, such as natural hazards, are being exacerbated with changing environmental and climatic conditions. Many studies have measured coastline change; however, they fail to address non-climatic drivers, such as land use changes. The enclosed research included three separate but complementary articles to examine climatic and non-climatic drivers of change for the Lake Ontario coastline in the Town of Lincoln, Ontario. \nIn the first article, a novel approach combining a coastline change analysis using historical aerial photographs in a geographic information system with the exploration of climatic and non-climatic drivers of change was developed. The novel approach will be useful for planners and residents in understanding factors that drive coastline erosion. \nIn the second article, this methodology was applied to the Town of Lincoln. The case study identified vulnerable areas of the coastline and included a narrative of how certain drivers may have contributed to the erosion. The results suggested that Lincoln has erosion issues, largely concentrated in four main areas, with rates of erosion between 0.32 and 0.66 m/yr over an 84-year period. Between 1934 and 2018, the Town of Lincoln lost approximately 30 hectares of land, a fiscal loss of approximately $1M. The east side of Lincoln has shown more erosion due to many interacting drivers, such as the orientation of the coast, the sandier substrate, and the proximity of the highway constructed in the late 1930s. \nThere are many barriers to climate change adaptation, including a general lack of understanding of how climate change may impact communities directly. The third article explored the utility of visualizations as a tool for science communication. Visualizing the impacts of climate change may be an important tool to help cities, regions, and countries prioritize adaptation. \nReplication of the methodology in an area such as the Great Lakes may produce a more comprehensive understanding of whether erosion is driven primarily by climatic or non-climatic factors. This can advance our understanding of coastline change and coastal vulnerability, as understanding the current state is essential before imagining a more sustainable future.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".