Present and future biodiversity risks from fossil fuel exploitation
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 Currently, human society is predominantly powered by fossil fuels—coal, oil, and natural gas—yet also ultimately depends on goods and services provided by biodiversity. Fossil fuel extraction impacts biodiversity indirectly through climate change and by increasing accessibility, and directly through habitat loss and pollution. In contrast to the indirect effects, quantification of the direct impacts has been relatively neglected. To address this, we analyze the potential threat to >37,000 species and >190,000 protected areas globally from the locations of present and future fossil fuel extraction in marine and terrestrial environments. Sites that are currently exploited have higher species richness and endemism than unexploited sites, whereas known future hydrocarbon activities will predominantly move into less biodiverse locations. We identify 181 “high‐risk” locations where oil or gas extraction suitability coincides with biodiversity importance, making conflicts between extraction and conservation probable. In total, protected areas are located on $3‐15 trillion of unexploited hydrocarbon reserves, posing challenges and potentially opportunities for protected area management and sustainable financing.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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