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Table 1 Explanatory variables analysed during the modelling process and their source. Variable names (second and forth columns), their codes (first and third columns) and factors grouping them (inserted sections). The resolution of the variables when coming from a raster are indicated in brackets next to the factor in which are grouped, in italics. The codes of the variables selected after the multicollinearity evaluation are shown in bold

From: Using fuzzy logic to compare species distribution models developed on the basis of expert knowledge and sampling records

Code

Variables

Code

Variables

Spatial

 YSp

Spatial logit (linear polynomial combination of Latitude (°N) and Longitude (°E) from the spatial logistic regression)(1)

Topography (1 km × 1 km of original resolution)

 A

Average altitude (m)(2)

S

Slope (◦) (calculated from Altitude)

 Ori-NS

Orientation; degrees of exposure NS (calculated from Slope)

Ori-EW

Orientation; degrees of exposure EW (calculated from Slope)

Climatic (1 km × 1 km of original resolution)

 BIO1

Average annual temperature (°C)(3)

BIO11

Mean annual temperatures of the coldest quarter (°C)(3)

 BIO2

Mean diurnal range temperatures (°C)(3)

BIO12

Annual precipitation (mm)(3)

 BIO3

Isothermality (BIO2/BIO17) (*100) (°C)(3)

BIO13

Precipitation of the wettest month (mm)(3)

 BIO4

Seasonality of temperatures (°C)(3)

BIO14

Precipitation of the driest month (mm)(3)

 BIO5

Maximum temperatures of the warmest month (°C)(3)

BIO15

Seasonality of precipitation (mm)(3)

 BIO6

Minimum temperatures of the coldest month (°C)(3)

BIO16

Precipitation of wettest quarter (mm)(3)

 BIO7

Annual temperature range (BIO5-BIO6)(3)

BIO17

Precipitation of dry quarter(3)

 BIO8

Mean annual temperatures of the wetter quarter(3)

BIO18

Precipitation of warmest quarter(3)

 BIO9

Mean annual temperatures of the dry quarter(3)

BIO19

Precipitation of coldest quarter(3)

 BIO10

Mean annual temperatures of the warmest quarter(3)

PMax

Maximum average precipitation in 24 h (mm)(3)

 BhPri

Spring water balance (mm)(3)

ETR

Monthly real evapotranspiration (mm)(3)

Vegetation (1 km × 1 km of original resolution)

 NDVI

Index of greenness(4)

  

Geography

 DistCost

Distance to coast (km)(5)

  

Hydrology

 DistRiver

Minimum distance to rivers (km)(6)

LonRiver

Longitude of rivers (km)(6)

Land use

 Forests

Forests (%)(7)

Reforests

Reforestation (%)(7)

 NatField

Natural field (%)(7)

Crops

Crops (%)(7)

 Wetland

Wetland (%)(7)

  

Lithology

 DepthSoil

Depth of soil(8)

TextSoil

Soil texture(8)

 RockySoil

Rocky soil(8)

FloodSoil

Flood soil(8)

Human activities (1 km × 1 km of original resolution)

 PobDen

Population density(9)

DistUrban

Minimum distance to the main urban centers (Km)(10)

 DistRoad

Minimum distance to paved roads (km)(11)

DistUnpavRoad

Distance to unpaved roads (km)(11)

  1. Sources:
  2. (1) Spatial variables, latitude, and longitude, were generated using the vector geometry tools of QGIS (http://www.qgis.org) software: (a) "centroids of polygons" was used to calculate the centroid of each grid cell was calculated; and (b) "Export/Add columns of geometry" was used to express the length and latitude values (1984 World Geodetic System) assigned to each centroid (WGS84)
  3. (2) United States Geological Survey (1996). GTOPO30. Land Processes Distributed Active Archive Center. EROS Data Center: https://lta.cr.usgs.gov/GTOPO30. (accessed April 2016)
  4. (3) Ceroni (2008) from DNM-INIA. Monthly data series for 30 years for Uruguay (from 1980 to 2009). We calculated the bioclimatic variables (BIO1–BIO19) following the proposal used in WorldClim (Fick & Hijmans, 2017)
  5. (4) https://www.vito-eodata.be: from SPOT-VEGETATION – S10 NDVI
  6. (5) Generated using QGIS (http://www.qgis.org) software by calculating the average distance from the centroid of the grid cell to the coastline
  7. (6) United States Geological Survey (2006). HydroShed. Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales. Available at: http://hydrosheds.cr.usgs.gov/index.php/ (accessed May 2016)
  8. (7) GlobCover (2009). Global land cover map. Available at: http://due.esrin.esa.int/page_globcover.php (accessed April 2016)
  9. (8) Panario & Gutiérrez (2011). Mapa de ambientes: Cartografía implementada en un SIG. In: Mapa de Ambientes de Uruguay y Distribución potencial de especies, Convenio MGAP/PPR-CIEDUR, Montevideo
  10. (9) Gridded Population of the World (GPWv4) (2010). Socioeconomic Data and Applications Center (SEDAC). A Data Center in NASA's Earth Observing System Data and Information System (EOSDIS)—Hosted by CIESIN at Columbia University (accessed June 2016)
  11. (10) Natural Earth Data. North American Cartographic Information Society (NACIS). Available at: http://www.naturalearthdata.com/ (accessed April 2016)
  12. (11) Digital Chart of the World. Available at: https://worldmap.harvard.edu/data/geonode:Digital_Chart_of_the_World (accessed April 2016)
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Frontiers in Zoology

ISSN: 1742-9994