DIET OF A RECENTLY REINTRODUCED RIVER OTTER (<em>LONTRA CANADENSIS</em>) POPULATION IN TAOS COUNTY, NEW MEXICO
Bibliographic record
Abstract
North American river otters (Lontra canadensis), native to every U.S. state and Canada, experienced extensive population decreases and range reduction until the mid-20th century as a result of overexploitation and habitat loss during European colonization. The last known river otter in New Mexico was killed on the Gila River in 1953, although unverified reports continued thru 2008. After a nearly 60-year absence from New Mexico, 33 adult river otters were reintroduced to the Rio Pueblo de Taos in the northern part of the state between 2008-2010; however, they were not subsequently monitored or studied. I characterized diet of this reintroduced otter population by collecting 877 scat samples from 20 latrine sites located on major rivers (Rio Grande = 16, Red River = 2, Rio Pueblo = 2) in Taos County, New Mexico between February, and December 2018. Hard prey remains were identified to family for fish and order for crayfish. Crayfish (66.2%) and fish (61.8%) were the most frequently occurring prey items in this study. Other prey items included mollusks and clams, birds, reptiles, and mammals. Salmonidae (39.6%) and Catostomidae (37.1%) were the most frequently identified fish families in otter scats, followed by Esocidae (14.3%), Cyprinidae (12.4%), and Centrarchidae (3.2%). Significant seasonal differences in occurrence of scat prey items was found for fish as a main prey group (p < 0.001), including the families Salmonidae (p < 0.001), Catostomidae (p < 0.001), Esocidae (p < 0.01), and Cyprinidae (p < 0.001), and for crayfish (p < 0.001). In summary, otters in the Upper Rio Grande appear to similarly consume prey to that found in other studies conducted in the U.S. My study provides the first dietary description of river otters in New Mexico and should inform otter management in the state.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".