A meta-analysis exploring associations between habitat degradation and Neotropical bat virus prevalence and seroprevalence
Cite this dataset
Heckley, Alexis; Lock, Lauren; Becker, Daniel (2023). A meta-analysis exploring associations between habitat degradation and Neotropical bat virus prevalence and seroprevalence [Dataset]. Dryad. https://doi.org/10.5061/dryad.866t1g1wd
Abstract
Habitat degradation can increase zoonotic disease risks by altering infection dynamics in wildlife and increasing wildlife–human interactions. Bats are an important taxonomic group to consider these effects, because they harbour many relevant zoonotic viruses and have species- and context-dependent responses to degradation that could affect zoonotic virus dynamics. Yet our understanding of the associations between habitat degradation and bat virus prevalence and seroprevalence are limited to a small number of studies, which often differ in the bats or viruses sampled, the study region, and methodology. To develop a broad understanding of the associations between bat viruses and habitat degradation, we conducted an initial phylogenetic meta-analysis that combines published prevalence and seroprevalence (“(sero)prevalence”) with remote-sensing habitat degradation data. Our dataset includes 588 unique records of (sero)prevalence across 16 studies, 64 bat species, and five virus families. We quantified the overall strength and direction of the relationship between habitat degradation and bat virus outcomes and tested how this relationship is moderated by the time between habitat degradation and bat sampling and by ecological traits of bat hosts while controlling for phylogenetic nonindependence among bat species. We found no effect of degradation on prevalence overall, although a weak effect may exist when forest loss occurs the year prior to bat sampling. In contrast, we detected a negative but weak association between degradation and seroprevalence overall that was strengthened when forest loss occurred the year prior to bat sampling. No bat traits that we investigated interacted with habitat degradation to impact virus outcomes, suggesting observed trends are independent of these traits. Biases in our initial dataset highlight opportunities for future work; prevalence was highly zero-inflated, and seroprevalence was dominated by Desmodus rotundus and rabies virus. These findings and subsequent analyses will improve our understanding of how global change affects host–pathogen dynamics.
README: A meta-analysis exploring associations between habitat degradation and Neotropical bat virus prevalence and seroprevalence
Authors:
Alexis Heckley (corresponding): Redpath Museum and Biology Department, McGill University
ORCID:000-0002-5644-3535
(alexis.heckley@mail.mcgill.ca)
Lauren Lock: Department of Biology, University of Oklahoma, Norman
ORCID: 0009-0003-1731-1235
(laurenlock@ou.edu)
Daniel Becker: Department of Biology, University of Oklahoma, Norman
ORCID: 0000-0003-4315-8628
(danbeck@ou.edu)
Description of study:
We conducted a phylogenetic meta-analysis to investigate how habitat degradation affects the prevalence and seroprevalence of Neotropical bat viruses. We looked at habitat degradation overall and tested how the relationships between habitat degradation and bat virus prevalence and seroprevalence are moderated by the time between degradation and bat sampling. We finally tested how this relationship is moderated by ecological traits of bat hosts (maximum colony size, roost duration, diet, wing aspect ratio, echolocation traits).
Data consists of:
- 'metaFragData.csv'.
One author asked that we not share their data, and so the corresponding rows have been excluded from this dataset.
Owing to conservation concerns, coordinates for sampling locations are not included in this dataset.
Description of variables:
- study_title - the full title of the study
- authors - a short citation of study (name of first author and year that study was published)
- country - country where bats were sampled
- sample_year - year when bats were sampled
- prev_or_sero - indicates whether the authors reported prevalence or seroprevalence data
- host_species - bat species
- virus_family - virus family
- sample_size - the total number of bats sampled
- host_positive - the number of bats that tested positive
- diagnostic_method - single or multi assay. NAs in this column represent cases where this information was not available or clear in the methods of the original paper.
- max_col_size - the maximum colony size that the bat species is reported to roost in. NAs in this column represent cases where we could not find maximum colony size information for a given species.
- wing_aspect_ratio - wing aspect ratio of the bat species. NAs in this column represent cases where we could not find wing aspect ratio information for a given species.
- diet - the primary diet of the bat species (animalivorous or non-animalivorous)
- roost_duration - a numeric score to indicate whether the bat roosts in more ephemeral roosts (lower value) or more permanent roosts (higher value). NAs in this column represent cases where we could not find roost duration information for a given species.
- pc1 - echolocation trait values. NAs in this column represent cases where we could not find echolocation information for a given species.
frag_year - the year that fragmentation occurred
In the time year lag columns below (oneLag:seventeenLag), NAs represent cases where habitat degradation data were not available.
oneLag - degradation score for for degradation that occurred 1 year prior to bat sampling.
twoLag - degradation score for for degradation that occurred 2 years prior to bat sampling.
threeLag- degradation score for for degradation that occurred 3 years prior to bat sampling.
fourLag - degradation score for for degradation that occurred 4 years prior to bat sampling.
fiveLag- degradation score for for degradation that occurred 5 years prior to bat sampling.
sixLag- degradation score for for degradation that occurred 6 years prior to bat sampling.
sevenLag- degradation score for for degradation that occurred 7 years prior to bat sampling.
eightLag- degradation score for for degradation that occurred 8 years prior to bat sampling.
nineLag - degradation score for for degradation that occurred 9 years prior to bat sampling.
tenLag - degradation score for for degradation that occurred 10 years prior to bat sampling.
elevenLag - degradation score for for degradation that occurred 11 years prior to bat sampling.
twelveLag - degradation score for for degradation that occurred 12 years prior to bat sampling.
thirteenLag - degradation score for for degradation that occurred 13 years prior to bat sampling.
fourteenLag - degradation score for for degradation that occurred 14 years prior to bat sampling.
fifteenLag - degradation score for for degradation that occurred 15 years prior to bat sampling.
sixteenLag - degradation score for for degradation that occurred 16 years prior to bat sampling.
seventeenLag - degradation score for degradation that occurred 17 years prior to bat sampling.
hft_mean - the mean degradation score calculated from the Human Footprint dataset (Venter, O. et al. 2018. Last of the Wild Project, Version 3 (LWP-3): 2009 Human Footprint, 2018 Release.)
ghmt_mean - the mean degradation score calculated from the Global Human Modification of Terrestrial Systems dataset (Kennedy, C. M. et al. 2020. Global Human Modification of Terrestrial Systems.)
hansen_mean - the mean forest loss score calculated from the Hansen Global Forest Change dataset (Hansen, M. C. et al. 2013. High-Resolution Global Maps of 21st-Century Forest Cover Change. - Science 342: 850–853.)
Funding
National Science Foundation, Award: BII 2213854
Research Corporation for Science Advancement, Award: 28365
Natural Sciences and Engineering Research Council