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Modelling the climatic suitability of Chagas disease vectors on a global scale

  1. Fanny E Eberhard  Is a corresponding author
  2. Sarah Cunze
  3. Judith Kochmann
  4. Sven Klimpel
  1. Goethe University, Institute for Ecology, Evolution and Diversity, Germany
  2. Senckenberg Biodiversity and Climate Research Centre, Senckenberg Gesellschaft für Naturforschung, Germany
Research Article
Cite this article as: eLife 2020;9:e52072 doi: 10.7554/eLife.52072
3 figures, 2 tables and 10 additional files

Figures

Modelled current climatic suitability.

(A–J) Modelled climatic suitability (consensus map) of 10 triatomine species under current climate conditions. Hatched areas indicate regions where the projection is uncertain. Maps were built using WGS 84 as geographical system and ESRI ArcGIS (ESRI, 2018).

Modelled current climatic suitability of T. rubrofasciata (consensus map) and observed occurrence records outside the Americas.

Hatched areas indicate regions where the projection is uncertain. Maps were built using WGS 84 as geographical system and ESRI ArcGIS (ESRI, 2018).

Species diversity.

The map is based on the combined binary modelling results highlighting potential hotspots of triatomine species diversity. Hatched areas indicate regions where the projection is uncertain. Maps were built using WGS 84 as geographical system and ESRI ArcGIS (ESRI, 2018).

Tables

Key resources table
Reagent type
(species) or resource
DesignationSource or referenceIdentifiersAdditional information
Software, algorithmRStudioR Development Core Team, 2019RRID:SCR_000432
Software, algorithmArcGIS for DesktopESRI, 2018RRID:SCR_011081
Software, algorithmbiomod2 packageThuiller et al., 2019Available at https://cran.r-project.org/package=biomod2
Table 1
Model specifications.

Occurrence points for all considered species used for modelling and model evaluation (AUC).

SpeciesOccurrence recordsAUC ensemble models
Panstrongylus geniculatus11800.985
Panstrongylus megistus4010.976
Rhodnius brethesi850.991
Rhodnius ecuadoriensis310.989
Rhodnius prolixus5400.981
Triatoma brasiliensis1780.994
Triatoma dimidiata3000.962
Triatoma infestans6310.977
Triatoma maculata1320.992
Triatoma rubrofasciata2680.98
Triatoma sordida4090.978
Total4155

Additional files

Source code 1

Source code for species distribution modelling executed in the R environment (R Development Core Team, 2019) using the biomod2 package (Thuiller et al., 2019).

https://cdn.elifesciences.org/articles/52072/elife-52072-code1-v2.docx
Supplementary file 1

Modelled climatic suitability [%] for all occurrences of T. rubrofasciata outside of the Americas.

https://cdn.elifesciences.org/articles/52072/elife-52072-supp1-v2.docx
Supplementary file 2

AUC values of all algorithms for all considered species.

https://cdn.elifesciences.org/articles/52072/elife-52072-supp2-v2.docx
Supplementary file 3

Sensitivity and specificity metrics of the South American training dataset for all considered species and the independent global sensitivity analysis of T. rubrofasciata.

https://cdn.elifesciences.org/articles/52072/elife-52072-supp3-v2.docx
Supplementary file 4

Modelled current climatic suitability and occurrence data from all considered species in South and Central America (Carcavallo et al., 1998; Fergnani et al., 2013).

https://cdn.elifesciences.org/articles/52072/elife-52072-supp4-v2.jpg
Supplementary file 5

Distribution of all considered species in South and Central America as extracted from the ‘Atlas of Chagas disease vectors in America’ (Carcavallo et al., 1998; Fergnani et al., 2013).

https://cdn.elifesciences.org/articles/52072/elife-52072-supp5-v2.jpg
Supplementary file 6

Juxtaposition of the occurrence data obtained from the ‘Atlas of Chagas disease vectors’ (Carcavallo et al., 1998; Fergnani et al., 2013) (black dots), Ceccarelli et al., 2018 (blue triangles) and (GBIF.org, 2019b; GBIF.org, 2019c; GBIF.org, 2019d; GBIF.org, 2019e; GBIF.org, 2019f; GBIF.org, 2019g; GBIF.org, 2019h; GBIF.org, 2019i; GBIF.org, 2019j; GBIF.org, 2019k; GBIF.org, 2019l) (red triangles) of all considered species.

https://cdn.elifesciences.org/articles/52072/elife-52072-supp6-v2.jpg
Supplementary file 7

Clamping mask indicating areas in which one or more environmental variables are outside the values of their training range.

The climatic suitability projections in these areas can be regarded as uncertain.

https://cdn.elifesciences.org/articles/52072/elife-52072-supp7-v2.jpg
Supplementary file 8

Sensitivity and specificity metrics of all algorithms for all considered species.

https://cdn.elifesciences.org/articles/52072/elife-52072-supp8-v2.docx
Transparent reporting form
https://cdn.elifesciences.org/articles/52072/elife-52072-transrepform-v2.pdf

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