America the Beautiful: Meeting “30 × 30” Conservation Goals Through Connected Protected Areas
Bibliographic record
Abstract
Protected areas are a primary instrument for biodiversity conservation, and area-based targets have become a hallmark of global efforts with the 2022 Kunming-Montreal Global Biological Framework recommending at least 30 percent of land and water be protected by 2030. In parallel, the United States has implemented “America the Beautiful,” a call for local, state, and regionally led efforts to conserve, connect, and restore 30 percent of U.S. lands and waters by 2030. Achieving these goals is complicated, however, by the multiple policy scales at which conservation decisions are made and governed and the limited guidance provided on how gains to protected and connected areas should be evaluated. We assess the connectedness of U.S. protected areas at multiple scales and find that less than 3 percent of the United States is protected and connected. Connectedness increases when the area under investigation is partitioned into smaller policy units (e.g., counties), a product of the modifiable areal unit problem. Similarly, connectedness values increase by an order of magnitude when assessed relative to the protected area network rather than considering all land area. Both findings support the need for standardized reporting frameworks and highlight the challenges in coordinating conservation goals across administrative units.
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 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 | 0.003 |
| 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 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".