Development and Application of a Geo-temporal Atlas for Climate Change Adaptation in Bay of Fundy Dykelands
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Bibliographic record
Abstract
van Proosdij, D; Perrott, B and Carroll, K., 2013. Development and Application of a Geo-temporal Atlas for Climate Change Adaptation in Bay of Fundy Dykelands.Globally, dykelands (former marsh areas protected by dykes) are of strategic importance for climate change adaptation. Many were originally designed to protect agricultural land, yet now protect valuable infrastructure. The purpose of this project was to develop a comprehensive digital atlas incorporating historical plans, shore protection, coastal geomorphology and LiDAR to serve as a basis for climate change adaptation planning in the Bay of Fundy. 110 paper plans were scanned, geo-referenced and features such as current and historical dykes, aboiteaux (tide gates), armouring, ditches, creeks, property boundaries, foreshore marsh, and geodetic elevations were digitized using ArcGIS. Attributes included age of structure, material, dimensions, and ownership. Dyke elevations were surveyed using an RTK GPS, and individual sections were identified as being vulnerable to storm surge and sea level rise. Erosion rates and width of foreshore marsh were calculated per dyke segment. At present, 55% of dykes within Nova Scotia are within 0.5 m of critical elevations established in the 1960s, 2% are more than 0.5 m below critical and all are below the predicted rates of SLR by 2055. There is also a strong relationship between the placement of armouring along the dyke toe and foreshore erosion. Conversely, timely placement of armouring along the foreshore marsh decreased rates of erosion. This was most effective in areas with the largest fetch; less effective where erosion was driven by tidal currents. All data were integrated into ArcReader for use by Agriculture personnel and have been essential for cost effective climate change adaptation planning including dyke topping, hazard mitigation and education.
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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 | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 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 it