Environmental Assessment at the Bakhuis Bauxite Concession: Small- Sized Mammal Diversity and Abundance in the Lowland Humid Forests of Suriname
Bibliographic record
Abstract
A small mammal survey was conducted in the Bakhuis Mountains of western Suriname in South America as part of a larger environmental and social impact assessment for a proposed bauxite mining concession. The objectives were to establish a baseline study of species diversity and relative abundance for comparison of seasonality, areas, and habitats to facilitate the identification and monitoring of potential impacts of mining to the environment. There were 83 species of small mammals documented comprising 68 species of bats, 8 species of rats and mice, and 7 species of opossums. The most abundant bat was the Seba’s short-tailed bat, Carollia perspicillata Linnaeus, which was recorded at all six study sites. The most abundant non-volant small mammal was the Guianan spiny rat, Proechimys guyannensis E. Geoffroy. Noteworthy discoveries during the survey include the documentation of four species of bats new to the fauna of Suriname ( Cyttarops alecto Thomas, smoky sheath-tailed bat; Saccopteryx gymnura Thomas; least two-lined sac-winged bat; Diaemus youngi Jentink; bird-feeding vampire bat; and Lasiurus egregius Peters, greater red bat). There were no obvious differences between the dry and wet season samplings that were attributable directly to climatic conditions. In terms of spatial variation, the relative abundance of bats among the five study sites within the concession area was similar to each other, but significantly different from a sixth study site at a nearby ecotourism operation, which had large numbers of three species ( C. perspicillata; Molossus molossus, common free-tailed bat; and Sturnira lilium , little yellowshouldered bat) that are better adapted to human modified surroundings. This suggests that the recent mining explorations in Bakhuis have had a relatively minor impact on bats and that the otherwise pristine forests within the concession can tolerate low levels of disturbance in proportionally small areas over a short duration. For specific habitats, the xeric forest on plateaus had a reduced subset of species of small mammals that were found in the mesic forest of the surrounding lowland regions, which was acting as a species reservoir for upland areas. Small mammals, in particular bats as primary seed dispersers and flower pollinators, are important components of the ecosystem for the successful reforestation of natural habitats, and factors related to community structure are good indicators of the health of the environment.
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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 | 0.002 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".