Where to go when all options are terrible: ranging behavior of brown-throated three-toed sloths (<i>Bradypus variegatus</i>) in central Amazonian flooded igapó forests
Bibliographic record
Abstract
Ranging behaviors performed by animals are influenced by both biotic and abiotic factors. For herbivorous mammals, seasonality in forage production is considered to be the main driver of movement patterns. Here, we investigated the home range and movement of one of the most abundant herbivores in the Americas and their relationship with plant phenology in an Amazon igapó — a seasonally flooded riverine forest with strongly pulsed leaf production phenology. Using a combination of telemetry and phenological analysis, the study recorded movement patterns of five brown-throated three-toed sloths (Bradypus variegatus Schinz, 1825) over a 6-month period and related these to seasonal and within-forest differences in food availability through monitoring young leaf production of 570 trees. All monitored animals were shown to be permanently resident within the igapó flooded forest, maintaining their home range even during flood periods when most trees lacked leaves. We found that seasonal variation in leaf production had no effect on the extent of displacement of the sloths. Accordingly, for herbivores with low metabolism, variation in young leaf availability may not be the main driver of their ranging behavior. In addition, an arboreal habit and well-developed swimming capacity allow igapó sloths to occupy a niche ecologically inaccessible to other mammals.
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 | 0.000 | 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 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".