, Volume 185, Issue 4, pp 607–618 | Cite as

Using eco-physiological traits to understand the realized niche: the role of desiccation tolerance in Chagas disease vectors

  • Gerardo J. de la Vega
  • Pablo E. SchilmanEmail author
Physiological ecology - original research


Small ectotherms, such as insects, with high surface area-to-volume ratios are usually at risk of dehydration in arid environments. We hypothesize that desiccation tolerance in insects could be reflected in their distribution, which is limited by areas with high relative values of water vapor pressure deficit (VPD) (e.g., hot and dry). The main goal of this study was to explore whether incorporation of eco-physiological traits such as desiccation tolerance in arid environments can improve our understanding of species distribution models (SDM). We use a novel eco-physiological approach to understand the distribution and the potential overlap with their fundamental niche in triatomine bugs, Chagas disease vectors. The desiccation dimension for T. infestans, T. delpontei, T. dimidiata, and T. sordida niches seems to extend to very dry areas. For T. vitticeps, xeric areas seem to limit the geographical range of their realized niche. The maximum VPD limits the western and southern distributions of T. vitticeps, T. delpontei, and T. patagonica. All species showed high tolerance to desiccation with survival times (35 °C-RH ~ 15%) ranging from 24 to 38 days, except for T. dimidiata (9 days), which can be explained by a higher water-loss rate, due to a higher cuticular permeability along with a higher critical water content. This approach indicates that most of these triatomine bugs could be exploiting the dryness dimension of their fundamental niche. Incorporating such species-specific traits in studies of distribution, range, and limits under scenarios of changing climate could enhance predictions of movement of disease-causing vectors into novel regions.


Physiological ecology Desiccation tolerance SDM Chagas disease vectors 



The authors thanks to Dr. Brian Aukema and Jake Wittman from the Aukema Lab ( for critical reading of the manuscript, Amir Dyzenchauz for English corrections, Carmen Rolandi for helping with figures, and Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT, Argentina) (PICT2008-0035 and PICT2008-0268) and CONICET for past financial support. We also thank two anonymous reviewers and a handling editor, whose constructive comments improved the paper.

Author contribution statement

Conceived the idea and designed the experiments: PES and GJdlV. Experimental assay: GJdlV and PES. Data analysis: GJdlV. Led the writing of the manuscript: GJdlV. Contributed reagents/materials: PES.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All applicable institutional and/or national guidelines for the care and use of animals were followed.

Supplementary material

442_2017_3986_MOESM1_ESM.docx (196 kb)
Supplementary material 1 (DOCX 196 kb)


  1. Araújo M, Ferri-Yáñez F, Bozinovic F, Marquet P, Valladares F, Chown S (2013) Heat freezes niche evolution. Ecol Lett 16:1206–1219CrossRefPubMedGoogle Scholar
  2. Balsalobre A (2016) Ph-D Thesis: ¿Qué especies de vinchucas modificarán su distribución geográfica en la Argentina? Un análisis de los microhábitats y microclimas de los triatominos vectores de la enfermedad de Chagas. Facultad de Ciencias Naturales y Museo, Universidad Nacional de La Plata, ArgentinaGoogle Scholar
  3. Belliard S (2015) Degree Thesis. Plasticidad de la tolerancia térmica por aclimatación en la vinchuca Rhodnius prolixus. Universidad de Buenos Aires, ArgentinaGoogle Scholar
  4. Benoit J, Denlinger D (2010) Meeting the challenges of on-host and off-host water balance in blood-feeding arthropods. J Insect Physiol 56(10):1366–1376CrossRefPubMedPubMedCentralGoogle Scholar
  5. Buckley L, Urban M, Angilletta M, Crozier L, Rissler L, Sears M (2010) Can mechanism inform species’ distribution models? Ecol Lett 13(8):1041–1054PubMedGoogle Scholar
  6. Bujan J, Yanoviak SP, Kaspari M (2016) Desiccation resistance in tropical insects: causes and mechanisms underlying variability in a Panama ant community. Ecol Evol 6(17):6282–6291CrossRefPubMedPubMedCentralGoogle Scholar
  7. Bulleri F, Bruno JF, Silliman BR, Stachowicz JJ (2016) Facilitation and the niche: implications for coexistence, range shifts and ecosystem functioning. Funct Ecol 30(1):70–78CrossRefGoogle Scholar
  8. Carcavallo RU, Curto de Casas SI, Sherlock IA, Galíndez-Girón I, Jurberg J, Galvão C, Noireau F (1999) Geographical distribution and alti-latitudinal dispersion. Atlas Chagas Dis Vect Am 3:747–792Google Scholar
  9. Chown S, Nicolson S (2004) Insect physiological ecology. Oxford University Press, New York, p 244CrossRefGoogle Scholar
  10. Chown S, Sørensen J, Terblanche J (2011) Water loss in insects: an environmental change perspective. J Insect Physiol 57(8):1070–1084CrossRefPubMedGoogle Scholar
  11. Clark N (1935) The effect of temperature and humidity upon the eggs of the bug, Rhodnius prolixus (Heteroptera, Reduviidae). J Anim Ecol 4:82–87CrossRefGoogle Scholar
  12. Coast GM (2009) Neuroendocrine control of ionic homeostasis in blood-sucking insects. J Exp Biol 212:378–386CrossRefPubMedGoogle Scholar
  13. Colwell RK, Rangel TF (2009) Hutchinson’s duality: the once and future niche. Proc Natl Acad Sci USA 106(Suppl. 2):19651–19658CrossRefPubMedPubMedCentralGoogle Scholar
  14. de la Vega GJ, Schilman PE (2017) Ecological and physiological thermal niches in vectors of Chagas disease. Med Vet Entomol. doi: 10.1111/mve.12262 Google Scholar
  15. de la Vega GJ, Medone P, Ceccarelli S, Rabinovich J, Schilman PE (2015) Geographical distribution, climatic variability and thermo-tolerance of Chagas disease vectors. Ecography 38(8):851–860CrossRefGoogle Scholar
  16. de Souza R, Diotaiuti L, Lorenzo M, Gorla DE (2010) Analysis of the geographical distribution of Triatoma vitticeps (Stal, 1859) based on data of species occurrence in Minas Gerais, Brazil. J Infec Genet Evol 10(6):720–760CrossRefGoogle Scholar
  17. Denny M (2016) Ecological mechanics. Principles of life’s physical interactions. Princeton University Press, PrincetonGoogle Scholar
  18. Diniz-Filho JAF, Ceccarelli S, Hasperué W, Rabinovich J (2013) Geographical patterns of Triatominae (Heteroptera: Reduviidae) richness and distribution in the Western Hemisphere. Insect Conserv Divers 6:704–714CrossRefGoogle Scholar
  19. Edney E (1977) Water balance in land arthropods. Springer, GermanyCrossRefGoogle Scholar
  20. Elith J, Kearney M, Phillips S (2010) The art of modelling range-shifting species. Methods Ecol Evol 1(4):330–342CrossRefGoogle Scholar
  21. Felsenstein J (1985) Phylogenies and comparative method. Am Nat 125(1):1–15CrossRefGoogle Scholar
  22. Fergnani P, Ruggiero A, Ceccarelli S, Menu F, Rabinovich J (2013) Large-scale patterns in morphological diversity and species assemblages in Neotropical Triatominae (Heteroptera: Reduviidae). Mem Inst Oswaldo Cruz 108(8):997–1008CrossRefPubMedPubMedCentralGoogle Scholar
  23. Fourcade Y, Engler JO, Rödder D, Secondi J (2014) Mapping species distributions with MAXENT using a geographically biased sample of presence data: a performance assessment of methods for correcting sampling bias. PLoS One 9(5):e97122CrossRefPubMedPubMedCentralGoogle Scholar
  24. Gibbs A (2002) Water balance in desert Drosophila: lessons from non-charismatic. Comp Biochem Physiol Part A 133:781–789CrossRefGoogle Scholar
  25. Gouveia S, Hortal J, Tejedo M, Duarte H, Cassemiro F, Navas C, Diniz-filho JAF (2014) Climatic niche at physiological and macroecological scales: the thermal tolerance geographical range interface and niche dimensionality. Glob Ecol Biogeogr 23:446–456CrossRefGoogle Scholar
  26. Graham CH, Hijmans RJ (2006) A comparison of methods for mapping species ranges and species richness. Glob Ecol Biogeogr 15(6):578–587CrossRefGoogle Scholar
  27. Gurgel-Gonçalves R, Galvao C, Costa J, Peterson AT (2012) Geographic distribution of Chagas disease vectors in Brazil based on ecological niche modeling. J Trop Med 2012:1–15CrossRefGoogle Scholar
  28. Hadley NF (1994) Water relations of terrestrial arthropods. Academic Press Inc, San Diego, California, p 356Google Scholar
  29. Hijmans RJ, van Etten J (2015) raster: Geographic data analysis and modeling. R package version 2(1-49):2013Google Scholar
  30. Hijmans RJ, Phillips S, Leathwick J, Elith J (2015) dismo: Species distribution modeling. R package version 1.0-12Google Scholar
  31. Hill M, Hoffmann A, Macfadyen S, Umina P, Elith J (2012) Understanding niche shifts: using current and historical data to model the invasive redlegged earth mite, Halotydeus destructor. ‎Divers Distrib 18(2):191–203CrossRefGoogle Scholar
  32. Hutchinson GE (1957) Concluding remarks. Cold Spring Harb Symp Quant Biol 22:415–427CrossRefGoogle Scholar
  33. Hypsa V, Tietz D, Zrzavý J, Rego R, Galvao C, Jurberg J (2002) Phylogeny and biogeography of Triatominae (Hemiptera: Reduviidae): molecular evidence of a New World origin of the Asiatic clade. Mol Phylogenet Evol 23(3):447–457CrossRefPubMedGoogle Scholar
  34. Intergovernmental Panel on Climate Change (2014) Impacts, adaptation and vulnerability: regional aspects. Cambridge University Press, New YorkGoogle Scholar
  35. Jiménez-Valverde A, Lobo JM (2007) Threshold criteria for conversion of probability of species presence to either-or presence-absence. Acta Oecol 31:361–369CrossRefGoogle Scholar
  36. Jurenka R, Terblanche JS, Klok CJ, Chown SL, Krafsur ES (2007) Cuticular lipid mass and desiccation rates in Glossina pallidipes: interpopulation variation. Physiol Entomol 32(3):287–293CrossRefPubMedPubMedCentralGoogle Scholar
  37. Kearney M (2006) Habitat, environment and niche: what are we modelling? Oikos 115(1):186–191CrossRefGoogle Scholar
  38. Kleynhans E, Terblanche J (2009) The evolution of water balance in Glossina (Diptera: Glossinidae): correlations with climate. Biol Lett 5:93–96CrossRefPubMedGoogle Scholar
  39. Kleynhans E, Terblanche J (2011) Complex interactions between temperature and relative humidity on water balance of adult tsetse (Glossinidae, Diptera): implications for climate change. Front Physiol 2(74):1–10Google Scholar
  40. Klok J, Chown S (1997) Critical Thermal Limits, Temperature Tolerance and Water Balance of a Sub-Antarctic Caterpillar, Pringleophaga marioni (Lepidoptera: Tineidae). J Insect Physiol 43(7):685–694CrossRefGoogle Scholar
  41. Lapinski W, Tschapka M (2014) Desiccation resistance reflects patterns of microhabitat choice in a Central American assemblage of wandering spiders. J Exp Biol 217(15):2789–2795CrossRefPubMedGoogle Scholar
  42. Lorenzo M, Lazzari CR (1999) Temperature and relative humidity affect the selection of shelters by Triatoma infestans, vector of Chagas disease. Acta Trop 72:241–249CrossRefPubMedGoogle Scholar
  43. Losos JB (2008) Phylogenetic niche conservatism, phylogenetic signal and the relationship between phylogenetic relatedness and ecological similarity among species. Ecol Lett 11(10):995–1003CrossRefPubMedGoogle Scholar
  44. Luz C, Fargues J, Grunewald J (1999) Development of Rhodnius prolixus (Hemiptera: Reduviidae) under constant and cyclic conditions of temperature and humidity. Mem Inst Oswaldo Cruz 94(3):403–409CrossRefPubMedGoogle Scholar
  45. Lyons CL, Coetzee M, Terblanche J, Chown S (2012) Thermal limits of wild and laboratory strains of two African malaria vector species, Anopheles arabiensis and Anopheles funestus. Malar J 11:226CrossRefPubMedPubMedCentralGoogle Scholar
  46. Mac Arthur R (1984) Geographical ecology: patterns in the distribution of species. Harper and Row, New York, p 288Google Scholar
  47. Martin P, Lefebvre M (1995) Malaria and climate: sensitivity of potential transmission to climate. Ambio 24(4):200–207Google Scholar
  48. Mitchell T, Carter T, Jones P, Hulme M, New M (2004) A comprehensive set of climate scenarios for Europe and the globe: the observed record (1900–2000) and 16 scenarios (2000–2100). University of East Anglia, Norwich, p 30Google Scholar
  49. Monahan WB (2009) A mechanistic niche model for measuring species’ distributional responses to seasonal temperature gradients. PLoS One 4(11):e7921CrossRefPubMedPubMedCentralGoogle Scholar
  50. Nenzén HK, Araújo MB (2011) Choice of threshold alters projections of species range shifts under climate change. Ecol Modell 222(18):3346–3354CrossRefGoogle Scholar
  51. Orme D (2013) The caper package: comparative analysis of phylogenetics and evolution in R. R package version 5(2):1–36Google Scholar
  52. Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecol Modell 190(3):231–259CrossRefGoogle Scholar
  53. Pinheiro J, Bates D, DebRoy S, Sarkar D (2014) The nlme package: linear and nonlinear mixed effects models. R package version 3:1–131Google Scholar
  54. Pires H, Lazzari CR, Schilman PE, Diotaiuti L, Lorenzo M (2002) Dynamics of thermopreference in the Chagas disease vector Panstrongylus megistus (Hemiptera: Reduviidae). J Med Entomol 39(5):716–719CrossRefPubMedGoogle Scholar
  55. R Core Team (2015) R: a language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
  56. Richmond O, McEntee J, Hijmans R, Brashares J (2010) Is the climate right for pleistocene rewilding? Using species distribution models to extrapolate climatic suitability for mammals across continents. PLoS One 5(9):e12899CrossRefPubMedPubMedCentralGoogle Scholar
  57. Roca M, Lazzari CR (1994) Effects of the relative humidity on the haematophagous bug Triatoma infestans. Higropreference and eclosion success. J Insect Physiol 40:901–907CrossRefGoogle Scholar
  58. Rolandi C, Schilman PE (2012) Linking global warning, metabolic rate of haematophagous vectors and the transmission of infectious diseases. Front Physiol 3(75):1–3Google Scholar
  59. Rolandi C, Iglesias M, Schilman PE (2014) Metabolism and water loss rate of the haematophagous insect Rhodnius prolixus: effect of starvation and temperature. ‎J. Exp Biol 217:4414–4422CrossRefGoogle Scholar
  60. Schilman PE, Lighton JRB, Holway DA (2005) Respiratory and cuticular water loss in insects with continuous respiration: comparison across five different ant species. J Insect Physiol 51(12):1295–1305CrossRefPubMedGoogle Scholar
  61. Schilman PE, Lighton JRB, Holway D (2007) Water balance in the Argentine ant (Linepithema humile) compared with five common native ant species from southern California. Physiol Entomol 32(1):1–7CrossRefGoogle Scholar
  62. Schilman PE, Minoli S, Lazzari CR (2009) The adaptive value of hatching towards the end of the night: lessons from eggs of the haematophagous bug Rhodnius prolixus. Physiol Entomol 34(3):231–237CrossRefGoogle Scholar
  63. Svenning J, Normand S, Kageyama M (2008) Glacial refugia of temperate trees in Europe: insights from species distribution modelling. J Ecol 96(6):1117–1127CrossRefGoogle Scholar
  64. Tee H, Lee C (2015) Water balance profiles, humidity preference and survival of two sympatric cockroach egg parasitoids Evania appendigaster and prostocetus hagenowii (Hymenoptera: Evaniidae; Eulophidae). J Insect Physiol 77:45–54CrossRefPubMedGoogle Scholar
  65. Tingley R, Vallinoto M, Sequeira F, Kearney M (2014) Realized niche shift during a global biological invasion. Proc Natl Acad Sci USA 111(28):10233–10238CrossRefPubMedPubMedCentralGoogle Scholar
  66. Weldon CW, Boardman L, Marlin D, Terblanche JS (2016) Physiological mechanisms of dehydration tolerance contribute to the invasion potential of Ceratitis capitata (Wiedemann) (Diptera: Tephritidae) relative to its less widely distributed congeners. Front Zool 13:15CrossRefPubMedPubMedCentralGoogle Scholar
  67. WHO Expert Committee World Health Organization (2002) Control of Chagas disease Second report of the WHO. Tech Rep Ser 905:1–119Google Scholar
  68. Wigglesworth VB (1945) Transpiration through the cuticle of insects. J Exp Biol 21(3–4):97–114Google Scholar
  69. Zachariassen K (1996) The water conserving physiological compromise of desert insects. Eur J Entomol 3:359–367Google Scholar
  70. Zuur A, Ieno E, Elphick C (2010) A protocol for data exploration to avoid common statistical problems. Methods Ecol Evol 1(1):3–14CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Laboratorio de Eco-fisiología de Insectos, Departamento de Biodiversidad y Biología Experimental, Facultad de Ciencias Exactas y NaturalesUniversidad de Buenos AiresBuenos AiresArgentina
  2. 2.Instituto de Biodiversidad y Biología Experimental y Aplicada-IBBEA, CONICET-UBA, Ciudad Universitaria, Pabellón IIBuenos AiresArgentina
  3. 3.Grupo de Ecología de Poblaciones de Insectos (GEPI)INTA EEA BarilocheRio NegroArgentina

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