Spatial Ecology of Jaguars in a Coastal Amazon Island Ecosystem
Bibliographic record
Abstract
Abstract Understanding the spatial ecology of large carnivores is essential for effective conservation, particularly in insular or fragmented systems where movement is constrained. Jaguars are particularly important to study, as they are opportunistic predators whose diet and behaviour shifts flexibly with local prey availability. We investigated the movement patterns, home range dynamics, and social interactions of jaguars ( Panthera onca ) on Maracá-Jipioca Island, a pair of small, seasonally flooded islands, in a low-disturbance reserve in the Brazilian Amazon. Using GPS collars, we tracked seven individuals and found that males had significantly larger home ranges (mean: 77.8 km²) than females (mean: 19.5 km²). Despite the island’s limited area, home-range overlap was low, and direct encounters were rare. This mirrored the territorial behaviour seen in more expansive mainland populations, but contradicted patterns seen in other populations that specialised on aquatic prey. Jaguars on Maracá-Jipioca moved an average of 7.3 km/day, with no significant differences across sex, age, nor body size. However, movement speed and probability of activity varied significantly across habitats: individuals moved faster in grasslands, wetlands, and water, and more slowly in forests and mangroves. Animals also spent more time resting while in forests and mangroves as compared to grasslands, water, and wetlands. In contrast to the predominantly nocturnal habits reported in continental populations, jaguar activity on Maracá-Jipioca peaked during daylight hours, especially among females. Jaguars showed a marked preference for coastal areas but did not appear to adjust habitat use in response to tidal variation in sea level. Collectively, these findings suggest that the spatial ecology of Maracá-Jipioca jaguars is comprised of typical and novel behaviours, shaped by both the species evolutionary history, and the island’s unique ecological context. These findings highlight the species’ behavioural flexibility and offer rare insights into how a large carnivore persists in an insular Amazonian landscape.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".