50 years of invertebrate conservation under the United States Endangered Species Act—history and threats to species
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
Introduction The United States Endangered Species Act celebrated its 50th anniversary in 2023. As a hallmark piece of environmental legislation, the Act has successfully prevented the extinction of hundreds of species. During these last 50 years, we have observed the decline of many species of invertebrates, resulting in the listing of 356 species. Methods Here, we summarize the state of endangered invertebrates using text mining to review all listing documents, including listing decisions, species status assessments, critical habitat designations, and status reviews. In our review, we evaluate the most prevalent threats for aquatic and terrestrial invertebrates. Results We found that invertebrates have been assessed and listed consistently in the past 50 years, and the last eight years have seen an uptick in status reviews. Further, we find that pollution, natural system modifications (such as dams), and intrinsic factors (such as small population sizes or number of populations) are the major contributing threats to aquatic invertebrates. On the other hand, problematic biotic factors (such as invasive species), climate change, residential and commercial development, and pollution are the major threats to terrestrial invertebrates. Discussion Overall, our study reviews the current threats to invertebrates and provides a baseline for the next 50 years in the face of a shifting threat and conservation arena.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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