Habitat connectivity and island biogeography: A call for community-engaged scholarship to address isolated parks and protected areas
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
Using the theory of island biogeography as a framework, we seek to determine the potential impact of the lack of connectivity between parks and protected areas on large-scale conservation efforts. We analyze lessons learned from the current Yellowstone to Yukon (Y2Y) initiative and develop recommendations to improve connectivity while incorporating the motivations, needs, and emotions of stakeholder groups. We strongly encourage ecologists, geographers, biologists, and other academics and activists to partake wholly and enthusiastically in community-engaged scholarship through outreach, capacity building, and social capital building through the proven frameworks of consensus-based and structured decisionmaking. Further, we argue that large-scale conservation initiatives may greatly benefit from an approach focused on small, more tangible actions when working toward a larger goal. As human populations and urban–wildland interfaces continue to grow rapidly, former models of park and protected area development become increasingly ineffective. We must adopt new strategies, such as those listed here, in order to increase landscape connectivity and provide effective conservation for all species. [This is a paper from “Systemic Threats to Parks & Protected Areas,” the 2020 George Wright Society Student Summit.]
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| 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 it