Using a Conservation Biology Blueprint to Protect Seven Species found in the Frontenac Arch Biosphere Reserve, Canada
Bibliographic record
Abstract
This project developed a conservation biology blueprint for the Frontenac Arch Biosphere Reserve (FABR) region that can be used towards assessing current conservation practices as well as making future recommendations. The findings of the study can be used towards the Ten Year Biosphere Review for UNESCO, which the FABR submits to keep their biosphere designation. By gathering information in real time, appropriate actions can be taken much more quickly than if the information was only gathered every ten years. This means that different actors can alter their actions to preserve species diversity and success as different factors influence those species through time. For this study, seven species (bald eagle, red-headed woodpecker, common five-lined skink, black rat snake, milksnake, spotted turtle, and great blue heron) were mapped in the area between Frontenac Provincial Park and Charleston Lake Provincial Park. The black rat snake, spotted turtle, and great blue heron were specifically explored in an online survey as well. This study area was chosen on the suggestion of the FABR because it connects Crown Land with the provincial parks, making implementing any new policies easier than land found in the North-South corridor of Ontario which contains a high amount of private development. Using the predicted tree species data, county land usage, eBird data, and endangered species general distribution, this paper hopes to identify where key areas of protection are. By quickly locating hotspots for endangered species, stricter conservation regulations can be implemented to help the recovery of these species.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".