Effects of land‐use changes on Brazilian bats: a review of current knowledge
Bibliographic record
Abstract
Abstract One third of Brazil has been converted to human‐modified lands, emphasising the need to understand biodiversity’s responses to land‐use changes. To address this issue, we reviewed 53 studies on the effects of land‐use changes on bats in the country from 1990 to 2018. Bats were chosen because they contribute towards numerous ecosystem services, including seed dispersal and insect control. For each study, we obtained data on the biome where fieldwork was conducted, participating institutes, sampling method, sampling effort, main results and academic impact. Spatial scales of studies were divided into ‘local’, ‘fragment’, ‘landscape’ or ‘metapopulation’. Our results indicate an increasing interest in bats and land‐use changes in Brazil over time; however, no trend in academic impact factor was found. Studies carried out in the Atlantic Forest were the most common, appearing earlier in the literature, but studies in Amazonia, often from long‐term research, had larger sampling efforts, were published in higher impact factor journals and received more citations. We identified several gaps in the literature: 1) lack of acoustic surveys complementing mist‐netting, 2) telemetry studies were rare, 3) underrepresentation of the Caatinga biome, along with Pantanal and Grasslands (= Pampa), and 4) fewer studies using the landscape and fragment scale than local studies. We suggest that future research should focus on filling those gaps. Bat diversity is often found to be positively related to forest cover, fragment size and natural vegetation. Logging and agroforestry seem to have the lesser impact on bats compared to agriculture and urbanisation. Only haematophagous bats are benefited by pastures. We found guild‐specific responses to land‐use changes. Haematophagous batsseem to be the least impacted by them compared to other guilds, while animalivorous bats are particularly impacted by habitat fragmentation. Facing continuous deforestation, we can expect that bat diversity in Brazil will possibly reduce. Conservation efforts should focus on species shown to be sensitive to land‐use changes, especially where higher deforestation rates are expected.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".