From Industry to Recreation: The Role of Land Use Changes in Shaping an Estuarine Urban Beach System
Bibliographic record
Abstract
Meury, S.W.; Bernier, J.-F.; Lajeunesse, P., and Chassiot, L., 2025. From industry to recreation: The role of land use changes in shaping an estuarine urban beach system. Journal of Coastal Research, 41(5), 856–872. Charlotte (North Carolina), ISSN 0749-0208. Densely urbanized coastlines, such as those of the St. Lawrence Estuary in eastern Canada, form complex coastal systems shaped by the co-evolution of anthropogenic and natural processes over time. However, the long history of urbanization within estuaries often leads to significant land use changes that are frequently overlooked in monitoring studies focused on assessing and predicting the evolution of such sedimentary systems. Therefore, it is critical to gain deeper insights into these key moments in the evolution of socionatural systems to facilitate the development of sustainable management practices and decision-making. Located within the St. Lawrence Fluvial Estuary in the Québec City urban agglomeration, Tibbits Cove is a dynamic urban beach that has experienced substantial erosion and undergone numerous transformations due to land use changes over the past two centuries. The alteration of its coastline led to the development of a sandy beach, an atypical but highly valued regional coastal socionatural system. By combining a geohistorical approach with hydrometeorological data and coastline migration rates, this study document the disturbance complex, including natural and human factors, that has driven the development of Tibbits Cove beach and identify the morphosedimentary response and resilience of this urban beach over time. This geohistorical approach revealed that socioeconomic factors, particularly land use changes, have been a greater driver of coastal landscape transformation than natural forces. As human influence increasingly outpaces natural processes in these systems, and this new paradigm stresses the need to thoroughly understand how human decisions and policies act as geomorphic drivers, either altering or facilitating the creation of hybrid landforms, to develop more effective and sustainable management strategies.
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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 | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".