Modeling an aspirational connected network of protected areas across North America
Bibliographic record
Abstract
Connecting protected areas remains an important global conservation strategy in the face of ongoing and future threats to biodiversity. Amid our growing understanding of how species' distributions will respond to climate change, conservation scientists need to plan for connectivity conservation across entire continents. We modeled multiscale connectivity priorities based on the least human-modified lands between large protected areas of North America using least-cost and circuit theory approaches. We first identified priority corridors between large protected areas, then characterized the network's structure to unveil priority linkages most important for maintaining network- and regional-level connectivity. Agreement between least-cost corridors and current flow varied throughout North America, reflecting permeable landscape conditions and "pinch points" where potential ecological flows may concentrate between protected areas. Priority network-level linkages derived from each approach were similar throughout the continental network (e.g., Rocky Mountains and Canadian boreal), but critical linkages that bridged regional protected-area networks varied. We emphasize the importance of planning for connectivity at continental scales and demonstrate the utility of multiple methods when mapping connectivity priorities across large spatial extents with wide gradients in landscape conditions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.003 | 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 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".