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Table 1 Twenty seven variables used in predicting suitable habitats of WNV mosquito vectors in St. John’s County, Fl

From: Ecological niche modeling of mosquito vectors of West Nile virus in St. John’s County, Florida, USA

Variable

Variable name

Data source

% Contribution

Alt

Elevation in meters

WorldClimc

Not included

Aspect

Aspect ratio

Generatedd

Not included

Bio1

Annual Mean Temperature

WorldClimc

Not included

Bio10

Mean Temperature of Warmest Quarter

WorldClimc

Not included

Bio11

Mean Temperature of Coldest Quarter

WorldClimc

16.6a

Bio12

Annual Precipitation

WorldClimc

14.1a

Bio13

Precipitation of Wettest Month

WorldClimc

13.6a

Bio14

Precipitation of Driest Month

WorldClimc

1.9a

Bio15

Precipitation Seasonality (Coefficient of Variation)

WorldClimc

Not included

Bio16

Precipitation of Wettest Quarter

WorldClimc

Not included

Bio17

Precipitation of Driest Quarter

WorldClimc

Not included

Bio18

Precipitation of Warmest Quarter

WorldClimc

Not included

Bio19

Precipitation of Coldest Quarter

WorldClimc

Not included

Bio2

Mean Diurnal Range (Mean of monthly (max temp - min temp))

WorldClimc

1.5b

Bio3

Isothermality (BIO2/BIO7) (* 100)

WorldClimc

13.5a

Bio4

Temperature Seasonality (standard deviation *100)

WorldClimc

2.4a

Bio5

Max Temperature of Warmest Month

WorldClimc

Not included

Bio6

Min Temperature of Coldest Month

WorldClimc

Not included

Bio7

Temperature Annual Range (BIO5-BIO6)

WorldClimc

Not included

Bio8

Mean Temperature of Wettest Quarter

WorldClimc

Not included

Bio9

Mean Temperature of Driest Quarter

WorldClimc

Not included

Curvature

Curvature

Generatedd

Not included

Hill shade

Hill shade

Generatedd

12.4a

LAI

Leaf Area Index

MODISe

98.5b

Slope

Slope

Generatedd

Not included

Surface water

Lakes/ponds/streams

USGSf

Not included

Urbanization

Human population settlements

USGSf

25.5a

  1. aPredicting variables for Culex nigripalpus, using linear regression analysis
  2. bPredicting variables for Culex quinquefasciatus, using linear regression analysis
  3. cWorldClim Global Climate database v1.4, available at: http://www.worldclim.org/(accessed 7/3/2015).
  4. dDigital elevation model using the surface spatial analyst tool in Arc tool box of ArcGIS ver. 10.1.
  5. eModerate Resolution Imaging Spectrometer (MODIS), available at: https://lpdaac.usgs.gov/(accessed 7/3/2015)
  6. fUSGS available at: http://water.usgs.gov/GIS/dsdl/ds240/(accessed 7/3/2015)
  7. All layers of variables data used in producing species distribution model gridded to ~1 Km spatial resolution and projected into the MODIS sinusoidal projection