Community Ecology and Phylogeography of Bats in the Guianan Savannas of Northern South America
Bibliographic record
Abstract
The Guiana Shield of South America contains savannas within one of the largest contiguous expanses of pristine tropical rainforest remaining in the world, but biodiversity in the grasslands is poorly known. In lowland Neotropical areas, bats typically comprise the most species-rich group of mammals. We compare the bat faunal community and phylogeography in the savanna habitats of the Llanos in Venezuela, Rupununi in Guyana, and Sipaliwini in Suriname. Measures of species diversity and relative abundance from standardized field survey methodology enable comparison among these three grassland regions. Genetic variation is summarized by DNA barcoding to examine biogeographic patterns across larger forest–savanna landscapes. A total of 76 species of bats is documented, of which 18 species are reported from all 3 savannas and 30 species are reported from only 1 of the savannas. Endemism is low with 5 taxa restricted primarily to dry, open habitats. However, 7 other species have divergent phylogeographic lineages associated with savanna populations. Although bat species are usually distributed over wide regions of the Neotropics, the habitat mosaics of the Guiana Shield have different faunal assemblages. Going back into the Miocene, the contractions and expansions of forest–savanna paleoenvironments over time have contributed to speciation and the current high levels of biodiversity in South America.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".