Habitat loss in the restricted range of the endemic Ghanaian cichlid <i>Limbochromis robertsi</i>
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 Remote sensing has become an integral and invaluable tool to inform biodiversity conservation and monitoring of habitat degradation and restoration over time. Despite the disproportionately high levels of biodiversity loss in freshwater ecosystems worldwide, ichthyofauna are commonly overlooked in favor of other keystone species. Freshwater fish, as indicators of overall aquatic ecosystem health, can also be indicators of larger scale problems within an ecosystem. As a case study with multi‐temporal, multi‐resolution satellite imagery, we examined deforestation and forest fragmentation around the Atewa Forest Reserve, Ghana. Within small creeks, Limbochromis robertsi , a unique freshwater cichlid with an extremely limited distribution range, can be found. Historically, the land cover in the area has undergone substantial deforestation for agriculture and artisanal small‐scale mining. In the 1389‐km 2 study area, we found deforestation accelerated along with increased forest fragmentation in the 2014–2017 period (167.4 km 2 of deforestation) with the majority of the forest loss along the river and creek banks due to small‐scale mining operations and increased agriculture. Field visits indicated a decrease in the total L. robertsi population by approximately 90% from the early 1990s to 2018. Its distribution has been reduced to higher elevations by anthropogenic habitat barriers at low elevations and the presence of predatory species. Loss of riparian forest through land use and cover change to mining and agriculture contributes to the habitat degradation for this endemic species. Fine spatial‐ and temporal‐scale studies are required to assess habitat characteristics are not captured by global‐ or continental‐scale datasets.
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 | 0.001 | 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