Bat cellular immunity varies by year and dietary habit amidst land conversion
Bibliographic record
Abstract
Abstract Monitoring the health of wildlife populations is essential in the face of increased agricultural expansion and forest fragmentation. Loss of habitat and habitat degradation can negatively affect an animal’s physiological state, possibly resulting in immunosuppression and increased morbidity or mortality. We sought to determine how land conversion may differentially impact cellular immunity and infection risk in Neotropical bats species regularly infected with bloodborne pathogens, and to evaluate how effects may vary over time and by dietary habit. We studied common vampire bats (Desmodus rotundus), northern yellow-shouldered bats (Sturnira parvidens) and Mesoamerican mustached bats (Pteronotus mesoamericanus), representing the dietary habits of sanguivory, frugivory and insectivory respectively, in northern Belize. We compared estimated total white blood cell count, leukocyte differentials, neutrophil to lymphocyte ratio and infection status with two bloodborne bacterial pathogens (Bartonella spp. and hemoplasmas) of 118 bats captured in a broadleaf, secondary forest over three years (2017–2019). During this period, tree cover decreased by 14.5% while rangeland expanded by 14.3%, indicating increasing habitat loss and fragmentation. We found evidence for bat species-specific responses of cellular immunity between years, with neutrophil counts significantly decreasing in S. parvidens from 2017 to 2018, but marginally increasing in D. rotundus. However, the odds of infection with Bartonella spp. and hemoplasmas between 2017 and 2019 did not differ between bat species, contrary to our prediction that pathogen prevalence may increase with land conversion. We conclude that each bat species invested differently in cellular immunity in ways that changed over years of increasing habitat loss and fragmentation. We recommend further research on the interactions between land conversion, immunity and infection across dietary habits of Neotropical bats for informed management and conservation.
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".