Analysis of gains and losses in area between 2050 and 2070 models. From left to right: Malaria (NASA (top), Hadley (bottom)), An. darlingi (NASA (top), Hadley (bottom)), An. nuneztovari (NASA (top), Hadley (bottom)). (TIFF 310086Â kb

Douglas Fuller (3530039)

John Beier (4490)

Marcus Lacerda (742724)

Martha Quinones (3530033)

Myriam Arevalo-Herrera (232093)

Socrates Herrera (238888)

Temitope Alimi (3530042)

Whitney Qualls (3530036)

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Additional file 6: of Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population

Response curves of An. darlingi model to: (A) Elevation (srtm); (B) Annual precipitation (bio 12); (C) Population; (D) Precipitation seasonality (bio 15); and (E) Jacknife of variable importance (Red bar shows the gain when all variables are used. The light blue bar shows the gain when a specific variable is excluded from analysis, a lower gain indicating that the specific variable has more information not contained in other variables. The dark blue bar indicates gain when the specific variable is used in isolation). (PDF 255Â kb

Additional file 5: of Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population

Projected LULC changes obtained using LCM: 2010 (top panel), 2050 (middle panel), and 2070 (bottom panel). (TIFF 24675Â kb

Alimi, Temitope

Fuller, Douglas

Qualls, Whitney

Herrera, Socrates

Arevalo-Herrera, Myriam

Quinones, Martha

Lacerda, Marcus

Beier, John

University of Miami: Scholarship Miami

Additional file 2: of Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population

Response curves of An. nuneztovari model to: (A) Elevation (srtm); (B) Temperature seasonality (bio 4); (C) Annual precipitation (bio 12); (D) Population; (E) LULC; and (F) Jacknife of variable importance (Red bar shows the gain when all variables are used. The light blue bar shows the gain when a specific variable is excluded from analysis, a lower gain indicating that the specific variable has more information not contained in other variables. The dark blue bar indicates gain when the specific variable is used in isolation) (PDF 258Â kb

Additional file 4: of Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population

Projected LULC changes obtained using LCM: 2010 (top panel), 2050 (middle panel), and 2070 (bottom panel). (TIFF 24675Â kb

Cross-tabulation of present and future distribution to show likely shifts in An. nuneztovari s.l. habitat suitability: NASA 2050 (top left), 2070 (bottom left) and Hadley 2050 (top right), 2070 (bottom right). (TIFF 24676Â kb

Additional file 8: of Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population

Cross-tabulation of present and future distribution to show likely shifts in Malaria habitat suitability: NASA 2050 (top left), 2070 (bottom left) and Hadley 2050 (top right), 2070 (bottom right). (TIFF 2525Â kb

Additional file 7: of Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population

Response curves of Malaria model to: (A) Elevation (srtm); (B) Precipitation of the driest quarter (bio 17); (C) Mean temperature of the coldest month (bio 6); (D) Precipitation of the driest month (bio 14); and (E) Jacknife of variable importance (Red bar shows the gain when all variables are used. The light blue bar shows the gain when a specific variable is excluded from analysis, a lower gain indicating that the specific variable has more information not contained in other variables. The dark blue bar indicates gain when the specific variable is used in isolation). (PDF 257Â kb

Additional file 3: of Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population

Differences in annual precipitation between current and future conditions. NASA 2050 (top left), 2070 (bottom left) and Hadley 2050 (top right), 2070 (bottom right). (TIFF 24678Â kb

Additional file 1: of Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population

Cross-tabulation of present and future distribution to show likely shifts in Malaria habitat suitability: NASA 2050 (top left), 2070 (bottom left) and Hadley 2050 (top right), 2070 (bottom right). (TIFF 2525Â kb

https://figshare.com/articles/Additional_file_8_of_Predicting_potential_ranges_of_primary_malaria_vectors_and_malaria_in_northern_South_America_based_on_projected_changes_in_climate_land_cover_and_human_population/4419863

Additional file 6: of Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population

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