Costa Rica mosquito community species occurrence and site environmental data, July - August 2017
Data files
Dec 18, 2023 version files 1.37 MB
Abstract
Land use change is an important driver of both biodiversity loss and zoonotic disease transmission in tropical countryside landscapes. Developing solutions for protecting biodiversity, public health, and livelihoods in working landscapes requires understanding the spatial scales at which habitat characteristics such as land cover shape biodiversity, especially for arthropods that transmit pathogens. A growing body of evidence shows that species richness for many taxa correlates with tree cover at small spatial scales of <100 m, indicating that local tree cover management is a promising conservation tool. To investigate whether mosquito species richness, community composition, and presence of specific disease vector species respond to tree cover—and if so, whether at spatial scales similar to other taxa—we surveyed mosquito communities along a tree cover gradient and across agricultural, residential, and forested land uses in rural southern Costa Rica. We found that tree cover was both positively correlated with mosquito species richness and negatively correlated with the presence of the common invasive dengue vector Aedes albopictus, particularly at small spatial scales of 80 – 200m. Beyond tree cover, land use type predicted community composition and Ae. albopictus presence, but not species richness. The results suggest that preservation and expansion of tree cover at local scales can protect biodiversity for a wide range of taxa and also confer protection against disease vector occurrence.
README: Costa Rica mosquito community species occurrence and site environmental data, July - August 2017
https://doi.org/10.5061/dryad.p8cz8w9xg
Description of the data and file structure
The file "SpeciesSiteData_CRMosquitoes_4Dec2023.csv" contains, for each site included in the survey, presence-absence data for each species observed, and environmental variables relating to land use, tree cover, and climate.
OTU = identifier code for operational taxonomic units defined by 97% or greater sequence similarity
Site = site ID code
PresAbs = 0 if the OTU was absent, 1 if the OTU was present
Species = taxonomic identification for the OTU, determined by comparison with BOLD and Genbank sequence databases
Canton = administrative unit in which the site was located
Region = larger geographic region in which the site was located
num_collection_events = number of times traps were set at the site during the survey period
num_pres = number of collection events during which Aedes albopictus was morphologically identified
albo_PresAbs = 0 if Aedes albopictus was never observed at the site, 1 if Aedes albopictus was observed at least once
LUclass = land use category of the survey site: forest, agriculture, or residential
Latitude = site latitude
Longitude = site longitude
T.Aedes = count of specimens morphologically identified as Aedes albopictus or Aedes aegypti
Elevation = site elevation (m)
NT = count of specimens identified via sequencing (Nontarget species, i.e. all individuals not identified morphologically as Aedes albopictus or Aedes aegypti)
Total = total count of mosquitoes trapped at the site
Type = finer categorizations of land use (e.g., "coffee plantation" instead of "agriculture")
Extraction = whether the DNA samples were sequenced during the first or second sequencing run
TempMean = mean annual site temperature (ºC), extracted from WorldClim 30s bioclim dataset
tree_cover_XXm = percent tree cover at XX m radius surrounding the site, calculated from fine scale tree cover map in Echeverri et al. 2022. XX values range from 30 to 1000 meters.
The file "OTUSequences_8Feb2021.csv" contains the cleaned DNA sequences, grouped by OTU, that were used for taxonomic identification.
cluster = OTU ID number, converted to the convention "OTUXX" in the species and site data file
sequence = cleaned DNA sequence corresponding to the OTU ID
The file "CR_Site_Coords_ForAnalysis.csv" is a subset of "SpeciesSiteData_CRMosquitoes_4Dec2023.csv" containing just the Site, Latitude, and Longitude columns used to extract environmental data from WorldClim tree cover rasters.
Sharing/Access information
Data was derived from the following sources:
- tree cover data from Echeverri et al. 2022: https://datadryad.org/stash/dataset/doi:10.5061/dryad.1ns1rn8w7
- climate data from WorldClim: https://www.worldclim.org/data/worldclim21.html
Code/Software
R code to explore the species observation data and run the analyses of species richness and Aedes albopictus presence/absence is contained in the file "4Dec2023_Costa Rica Mosquito Community Assembly.R". R code to perform the community turnover analyses (NMDS, PERMANOVA, and GDM) is contained in the file "4Dec2023_CommunityTurnover_CRMosquitoes.R". R code to extract percent tree cover from the fine-scale tree cover map in Echeverri et al. 2022 is contained in the file "tree cover data extraction.R".
Methods
Field-caught mosquitoes captured from sites with varying land uses and land cover in southwestern Costa Rica were identified by DNA sequencing and morphologically (Aedes genus only). The file "SpeciesSiteData_CRMosquitoes_4Dec2023.csv" contains, for each site included in the survey, presence-absence data for each species observed, and environmental variables relating to land use, tree cover, and climate. Land use categories, GPS coordinates, and elevation were recorded by the field team at the time of sample collection. Tree cover values were calculated from a raster of fine-scale tree cover created by Echeverri et al., available at https://doi.org/10.5061/dryad.1ns1rn8w7. Mean annual temperature was extracted from the WorldClim bioclim dataset (https://www.worldclim.org/data/worldclim21.html). The file "OTUSequences_8Feb2021.csv" contains the cleaned DNA sequences, grouped by OTU, that were used for taxonomic identification.