Aquatic Fauna in the Driest Desert on Earth: First Report on the Crustacean Fauna of the Loa River (Atacama Desert, Antofagasta Region, Chile)
Bibliographic record
Abstract
The longest river in Chile, the Loa, is in fact found in the Atacama Desert in the far north of the country. Being an important resource for the dry Antofagasta region, this river experiences high anthropogenic impacts due to water use for mining, urban, and agricultural activities. Unfortunately, few biological surveys have been conducted in the Loa, and the invertebrate fauna in particular is poorly known. The aim of this study is to characterize the microcrustacean species associations at various sites of the Loa River and some of its tributaries. Unexpectedly high species richness was detected at high-altitude sites, where the amphipods Hyalella fossamanchini and H. kochi were reported. At low-altitude sites only the ostracod Heterocypris panningi was found. No significant correlation was detected between species richness and salinity, nor between richness and conductivity. Although a null model community analysis indicated that the microcrustacean species associations in the Loa are largely random, species richness and altitude were significantly and positively correlated. Potential causes of this pattern include the accumulation of nutrients and pollution along the course of the river, as well as increasing temperatures in the lower-altitude zones of the river. The biogeography of the constituent members of the Loa fauna is discussed. © 2010 Brill Academic Publishers.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".