Impact of urbanization and landscape changes on the vegetation of coastal dunes along the Gulf of Mexico
Bibliographic record
Abstract
In Mexico, as in other countries, coastal urbanization and landscape changes are occurring at an unprecedented scale and rate, with potential negative impacts on local biodiversity. Nevertheless, studies of the impacts that such changes have on coastal dune vegetation are relatively scarce. In this study, we examined (a) the trends of urban sprawl and landscape changes along the coast of Veracruz for more than 20 years; (b) the impact of urban sprawl on plant species richness and plant functional groups; c) how landscape changes have affected plant diversity and community structure. Our results show an increasing urbanization along the coasts of the Gulf of Mexico, occurring at different rates, and being higher in locations closest to tourist areas. Plant species richness decreased with urban expansion while the proportion of plant functional types was altered. Inland species not tolerant to the beach-dune environment became more abundant in the most urbanized locations while the abundance of psammophytes decreased. Community structure (the dominant species) was modified with landscape changes. Our results are useful for an adaptive management strategy and will help develop sustainable beach management plans that should include the conservation of native and highly specialized species, such as psammophytes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".