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Table 1 Most important variables per species and per model

From: Modelling the potential spatial distribution of mosquito species using three different techniques

SPECIES NLDA RF GLM
Cs. annulata • Population density • NLST P2 • EVI VR
  • WORLDCLIM precipitation P2 • Population density • DEM
  • WORLDCLIM precipitation A0 MIR A2 • DLST A2
  • WORLDCLIM precipitation D1 • DLST A2 • NLST P3
  • WORLDCLIM precipitation DA • MIR MX • CMORPH precipitation VR
  • CMORPH precipitation A1 • NDVI A2 • CMORPH precipitation A3
  • DLST DA • MIR P1 • DLST D1
  • DLST P1 • EVI MN • DLST D3
  • DLST A0 • CMORPH precipitation P1 • MIR A2
  • DLST P2 • WORLDCLIM precipitation P1 • MIR 03
   • DLST A3  
An. claviger • WORLDCLIM precipitation P2 • NLST MX • EVI P2
  • WORLDCLIM precipitation A0 • MIR MN • DEM
  • Population density • NLST A0 • NLST MN
  • MIR A3 • WORLDCLIM precipitation P3 • NLST A2
  • WORLDCLIM precipitation DA • NLST MN • CMORPH precipitation A 1
  • EVI D2 • DLST A0 • MIR D3
  • NLST P3 • DLST A1 • WORLDCLIM precipitation D3
  • EVI P2 • DLST MX • CMORPH precipitation A2
  • NLST A3 • NDVI A2 • NLST A0
  • DLST A0 • NDVI VR • Population density
Oc. punctor • Population density • Population density • NDVI D1
  • MIR P1 • MIR P1 • MIR P1
  • EVI P3 • EVI P3 • DLST P2
  • NDVI P3 • NDVI P3 • EVI P2
  • NDVI P2 • NDVI P2 • MIR A3
  • DLST MN • DLST MN • WORLDCLIM precipitation A3
  • DEM • DEM • NDVI A3
  • CMORPH precipitation A2 • CMORPH precipitation A2 • WORLDCLIM P3
  • CMORPH precipitation A1 • CMORPH precipitation A1 • EVI MN
  • WORLDCLIM precipitation P3 • WORLDCLIM precipitation P3 • CMORPH precipitation A2
  1. For non-linear discriminant analysis (NLDA) and generalised linear model (GLM) the top 10 variables average ranks are reported, for random forest (RF) the most important variables are expressed by the mean decrease in Gini index.