A framework to identify priority wetland habitats and movement corridors for urban amphibian conservation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Cities worldwide are expanding in area and human population, posing multiple challenges to amphibian populations, including habitat loss from removal of wetlands and terrestrial upland habitat, habitat fragmentation due to roads and the built environment, and habitat degradation from pollutants, extensive human use and introduced species. We developed an eight‐step urban amphibian conservation framework based on established monitoring, analytical methods and community engagement to enable amphibian conservation in a large urban centre. The framework outlines a process used to conserve biodiversity in a complex landuse and decision‐making environment supported by a series of successive complementary modelling techniques to measure amphibian presence, priority habitat and functional connectivity. We applied the framework in Calgary, Alberta, Canada to illustrate its potential. Here, urbanization has reduced wetlands by 90% and ecological knowledge on amphibians was poor. We improved knowledge on amphibian diversity and distribution, identified core wetlands and movement pathways for amphibian species and identified barriers in the wetland network where construction or restoration measures could re‐establish amphibians or increase their densities. This knowledge was shared with ecologists and city planners for implementation through appropriate policies and plans. Our framework provides a series of stepwise products to improve an urban municipality's ability to restore or conserve priority habitat and movement pathways necessary for amphibian survival under pressure from multiple land uses. The framework provides a platform to identify city plans, policy and or programmes and to derive necessary information to support amphibian conservation.
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.
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 | 0.000 |
| Science and technology studies | 0.001 | 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 it