Assessing shoreline dynamics over multiple scales on the northern Yucatan Peninsula
Bibliographic record
Abstract
Coastal erosion is critical in many locations along the northern Yucatan Peninsula. The area is characterized by a micro-tidal regime and low-energy wave conditions, with a high-incidence angle with respect to the shoreline. Port and harbor infrastructure for fisheries, commercial, and tourist activities has promoted the growth of coastal communities settled on barrier islands. However, the human settlements have degraded the coastal ecosystems and interrupted the littoral transport . Due to coastal development in the region, the land use of the remaining pristine coastal areas is expected to change in forthcoming years. Thus, understanding coastal changes occurring along the northern Yucatan Peninsula is fundamental for improving coastal planning. We employed open access remote sensing data sets and reanalysis information to investigate shoreline changes at different spatial and temporal scales. Shoreline position was obtained along a 150-km stretch of coast from satellite imagery using CoastSat. Firstly, reanalysis and satellite-derived information were validated with in situ measurements in the vicinity of coastal structures. A satisfactory agreement was found for characterizing the forcing conditions (waves and sea level) and shoreline evolution at different temporal scales. A dominant direction of alongshore sediment transport (50,000–80,000 m 3 /year) make the shoreline highly sensitive to any nearshore disturbance. We found that coastal erosion occurred in 50% of the analyzed transects, whereas beach accretion occurred in only 30%, suggesting net beach losses. Erosive trends are strongly correlated with the presence of coastal structures. The 6-km long Progreso pier induced significant beach erosion along O (10) km, while sheltered harbors induced downdrift erosion along O (1) km. Detached breakwaters and groins have an overall negative impact on downdrift areas ( O (100) m). On the other hand, significant erosion was also observed in pristine areas located downdrift of a coastal lagoon due to the sediment impoundment associated with the growth of a sand spit. Moreover, shoreline sand waves drive 40-m shoreline oscillations and propagate (alongshore) at a rate of 300 m/year. The generation of sand waves seems to be related to both natural and anthropogenic perturbations, in combination with the high-incidence wave angle. Their propagation plays a key role in the shoreline dynamics of this region.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".