DOI: 10.5061/dryad.nk98sf84h
title: Data from: Infection and host-feeding patterns of West Nile virus vectors varies by urban greenspace composition

description: Greenspaces are integral to the urban environment, enhancing climate
 resilience and providing several additional environmental, social, and
 public health benefits, yet the extent to which they affect vector-borne
 disease transmission is not clear. We explored this question in the
 context of mosquito and West Nile virus (WNV) host populations, infection
 rates, and foraging behavior. We collected mosquitoes from greenspaces
 along a transect spanning a range of urban development. Mosquitoes were
 tested for West Nile virus, and the host species that were fed on was
 determined for blood-fed specimens. Bird counts and camera traps were used
 to assess avian and mammal species availability. We explored landcover
 associations with vector abundance, vector infection prevalence,
 host-feeding pattern,s and host community composition. Different
 components that contribute to WNV transmission intensity responded to
 different landcover variables. Abundance of Culex mosquitoes was most
 strongly tied to impervious surface, while prevalence of WNV infection was
 positively associated with increasing amounts of turf grass, but not
 through an indirect effect of vapor pressure deficit. The amount of turf
 was itself correlated with a measure of avian community reservoir
 competence. Blood meal analysis suggested the majority of blood meals in
 Cx. pipiens and Cx. restuans came from American robins and northern
 cardinals. This work provides novel insights into how reliance on managed
 turf grass for urban landscaping may have adverse consequences for WNV
 transmission risk and furthers our understanding of how the design of
 urban greenspaces could benefit from consideration of vector-host-virus
 interactions.
description: # Data from: Infection and host-feeding patterns of West Nile virus
 vectors varies by urban greenspace composition Dataset DOI:
 [10.5061/dryad.nk98sf84h](10.5061/dryad.nk98sf84h) ## Description of the
 data and file structure These files contain data required to reproduce
 analyses in the associated paper examining how the composition and extent
 of urban greenspace influences the abundance, host feeding behavior and
 West Nile virus (WNV) infection prevalence of *Culex (Cx.)* spp.
 mosquitoes at ten locations along a gradient of urban development
 intensity in the Greater Chicago area. Mosquitoes were collected weekly
 from multiple traps at each location, 25 June to 25 September 2019. Unfed,
 female specimens were pooled and tested by RT-PCR for the presence of WNV
 RNA. Vertebrate DNA was extracted from blood engorged *Culex (Cx.)* spp.
 females and sequenced to determine host identity. Point count surveys and
 camera traps were used at each site to estimate relative abundance of
 avian and mammalian host species, respectively. Estimates of land cover
 were extracted from a 1000 m radius of each sampling site. ### Files and
 variables #### File: bloodmeal_data.csv **Description:** Contains
 vertebrate host identification for individual bloodfed Culex (Cx.) spp.
 females. ##### Variables * Samples: unique specimen ID code * Site: unique
 site ID * Trap type: sampling device used (Gravid = CDC gravid trap; Light
 = CDC light trap, BGS = BG Sentinel-2 trap) * Mosq_Species: mosquito
 species * Coll_date:  date of collection * Major host: species with the
 highest read number (number of sequences mapping to that host species)
 based on MiSeq sequencing #### File: avian_data.csv
 **Description:** Contains the average number of detections of each avian
 species in 15-minute point count surveys conducted at each study site.
 ##### Variables * Site: unique site ID * Species: total number of avian
 species detected * Visits: total number of point counts performed at the
 site *All values in all other columns below ("American Crow" to
 "Yellow-throated Warbler") indicate the average number of
 detections of each species* #### File: camera_trap_data.csv
 **Description:** Contains the frequency of detection of ten mammalian
 hosts at each site in camera traps operating between June 17 and August
 14, and between September 17 and November 14, 2019 ##### Variables *
 Species: vertebrate species detected * CameraID: unique camera trap ID *
 Site: unique site ID * Start: start date of camera trap observations *
 End: end date of camera trap observations * Y: number of days on which the
 mammal was detected * J: number of days the camera trap was active *
 PropDetect: proportion of days where the mammal was detected #### File:
 Culex_F_per_trap.csv **Description:** Contains the number of female *Culex
 (Cx.)* spp. specimens collected per trap sample ##### Variables *
 Site: unique site ID * Trap_Loc: unique trap location within site (A, B,
 C, D or E) * Trap_Type: mosquito collection device (Light = CDC light
 trap; Gravid = CDC gravid trap; BGS = BG Sentinel 2 trap) *
 Full_sample: binary field identifying sampling dates when trap samples
 were collected at all 10 sites (Full_sample = 1), and sampling dates when
 mosquito sampling was not conducted at one or more sites (Full_sample = 0)
 * Coll_Date: date when trap sample was collected * F_Cx_pipi: total number
 of female *Culex pipiens* in sample * F_Cx_rest: total number of female
 *Culex restuans* in sample * F_Cx_sali: total number of female *Culex
 salinarius* in sample * F_Cx_sp: total number of *Culex (Cx.)* spp.
 females in sample that were not identified to species #### File:
 MULC_1000m.csv **Description:** Percent area within a 1000 m radius buffer
 around trap locations at each site that is represented by each land cover
 class in a modified version of the USEPA EnviroAtlas “Meter-Scale Urban
 Land Cover” dataset ##### Variables * Site: unique site ID *
 MULC_BLDG_1000m: % area represented by building footprints *
 MULC_NISA_1000m: % area represented by impervious surface, excluding
 building footprints * MULC_TREE_1000m: % area represented by tree canopy
 (vegetation &gt; 2 m in height) * MULC_TURF_1000m: % area represented by
 turf grass * MULC_NGRS_1000m: % area represented by grass / herbaceous
 vegetation (&lt;= 2 m height), excluding turf grass cover *
 MULC_BARE_1000m: % area represented by soil and barren surfaces *
 MULC_CROP_1000m: % area represented by row crops * MULC_WATR_1000m: % area
 represented by open water * MULC_WWET_1000m: % area represented by woody
 wetlands * MULC_EWET_1000m: % area represented by emergent wetlands ####
 File: NLCD_1000m.csv **Description:** Average percent 2019 NLCD impervious
 and tree canopy cover within a 1000 m radius buffer around trap locations
 at each site ##### Variables * Site: unique site ID * NLCD_ISA_1000m: %
 impervious surface cover * NLCD_TCA_1000m: % tree canopy cover #### File:
 iButton_bydate_bysite.csv **Description:** Contains average air
 temperature, % relative humidity and vapor pressure deficit values for
 each site, for each sampling date. These aggregate values were derived
 from 10-minute interval records obtained from iButton logger suspended 30
 cm from a CDC light trap, at a height of ~1.5 m, below an inverted 250 ml
 white paper cup to shield the logger from exposure to rain or direct
 sunlight. ##### Variables * Start_date: date of sunset * Site: unique site
 ID * T_NOC: mean air temperature at site from sunset to sunrise (° C) *
 RH_NOC: mean % relative humidity at site from sunset to sunrise *
 T_NOC_GA: overall mean air temperature, averaged across all 10 sites, from
 sunset to sunrise (° C) * RH_NOC_GA: overall mean % relative humidity,
 averaged across all 10 sites, from sunset to sunrise * T_NOC_dev: average
 difference between site air temperature and overall mean air temperature
 across all 10 sites (° C) * RH_NOC_dev: average difference between site %
 relative humidity and overall mean % relative humidity across all 10 sites
 * VPD_SSto4: mean vapor pressure deficit at site, sunset to 4-hours
 post-sunset (kPa) * VPD_4toSR: mean vapor pressure deficit at site,
 4-hours post-sunset to sunrise (kPa) #### File: pools_WNV_inf.csv
 **Description:** Contains description of all pools of Culex (Cx.) spp.
 females screened for WNV RNA by RT-PCR ##### Variables * Pool_ID: unique
 ID assigned to mosquito pool * Site: unique site ID * Coll_Date: date when
 trap sample was collected * Full_sample: binary field identifying sampling
 dates when trap samples were collected at all 10 sites (Full_sample = 1),
 and sampling dates when mosquito sampling was not conducted at one or more
 sites (Full_sample = 0) * Species: mosquito species * Source: sampling
 device(s) used to collect specimens in pool (GRAV = CDC gravid trap only;
 LT/BG = CDC light trap and/or BG Sentinel-2 trap only; MIX = CDC gravid
 trap + CDC light trap and/or BG Sentinel-2 trap) * Specimens: number of
 female specimens in pool * INF_STATUS: binary field indication whether
 pool was negative (INF_STATUS = 0), or positive (INF_STATUS = 1), for WNV
 RNA ## Code/software Statistical analyses were performed in R version
 4.4.1 ([https://www.r-project.org/](https://www.r-project.org/)).
 The PoolTestR package was used to estimate maximum likelihood estimates of
 the prevalence of infection for West Nile virus in mosquito pools
 ([https://doi.org/10.32614/CRAN.package.PoolTestR](https://doi.org/10.32614/CRAN.package.PoolTestR)). Correlation matrices were created using the PerformanceAnalytics package ([https://doi.org/10.32614/CRAN.package.PerformanceAnalytics](https://doi.org/10.32614/CRAN.package.PerformanceAnalytics)). Monte Carlo multinomial tests were performed using the EMT package ([https://doi.org/10.32614/CRAN.package.EMT](https://doi.org/10.32614/CRAN.package.EMT)). Structural equation models were performed using the piecewiseSEM package (Lefcheck, 2016, [https://doi.org/10.32614/CRAN.package.piecewiseSEM](https://doi.org/10.32614/CRAN.package.piecewiseSEM)). ## Access information Land cover data (NLCD_1000m.csv, MULC_1000m.csv) were derived from the following sources: * National Land Cover Database: 2019 Fractional Impervious Surface, 2019 Tree Canopy Cover ([https://www.mrlc.gov/data](https://www.mrlc.gov/data)) * US EPA EnviroAtlas Meter-Scale Urban Land Cover ([https://doi.org/10.3390/rs12121909](https://doi.org/10.3390/rs12121909)) * Microsoft US Building Footprint Dataset ([https://github.com/microsoft/USBuildingFootprints](https://github.com/microsoft/USBuildingFootprints)) * Chicago Metropolitan Agency for Planning (CMAP) Land Use Inventory ([https://cmap.illinois.gov/data/land-use/land-use-inventory/](https://cmap.illinois.gov/data/land-use/land-use-inventory/)) * 2018 Illinois Cropland Data Layer ([https://nassgeodata.gmu.edu/CropScape/IL](https://nassgeodata.gmu.edu/CropScape/IL)) * ESRI World Imagery ([https://www.arcgis.com/home/item.html?id=10df2279f9684e4a9f6a7f08febac2a9](https://www.arcgis.com/home/item.html?id=10df2279f9684e4a9f6a7f08febac2a9))