Journal of Ecology and Environment

The Ecological Society of Korea (한국생태학회)
권호 표지
DOI QR코드

DOI QR Code

Modeling the potential climate change-induced impacts on future genus Rhipicephalus (Acari: Ixodidae) tick distribution in semi-arid areas of Raya Azebo district, Northern Ethiopia

  • Received : 2019.07.23
  • Accepted : 2019.11.12
  • Published : 2019.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

Background: Climate change is believed to be continuously affecting ticks by influencing their habitat suitability. However, we attempted to model the climate change-induced impacts on future genus Rhipicephalus distribution considering the major environmental factors that would influence the tick. Therefore, 50 tick occuance points were taken to model the potential distribution using maximum entropy (MaxEnt) software and 19 climatic variables, taking into account the ability for future climatic change under representative concentration pathways (RCPs) 4.5 and 8.5, were used. Results: MaxEnt model performance was tested and found with the AUC value of 0.99 which indicates excellent goodness-of-fit and predictive accuracy. Current models predict increased temperatures, both in the mid and end terms together with possible changes of other climatic factors like precipitation which may lead to higher tick-borne disease risks associated with expansion of the range of the targeted tick distribution. Distribution maps were constructed for the current, 2050, and 2070 for the two greenhouse gas scenarios and the most dramatic scenario; RCP 8.5 produced the highest increase probable distribution range. Conclusions: The future potential distribution of the genus Rhipicephalus show potential expansion to the new areas due to the future climatic suitability increase. These results indicate that the genus population of the targeted tick could emerge in areas in which they are currently lacking; increased incidence of tick-borne diseases poses further risk which can affect cattle production and productivity, thereby affecting the livelihood of smallholding farmers. Therefore, it is recommended to implement climate change adaptation practices to minimize the impacts.

Keywords

References

  1. Araujo MB, Pearson RG, Thuiller W, Erhard M. Validation of species-climate impact models under climate change. Global Change Biol. 2005;11:1504-13. https://doi.org/10.1111/j.1365-2486.2005.01000.x
  2. Aydinalp C, Cresser MS. The effects of global climate change on agriculture. Am Eurasian J Agric Environ Sci. 2008;3:672-6.
  3. Baldwin RA. Use of maximum entropy modeling in wildlife research. Entropy. 2009;11:854-66. https://doi.org/10.3390/e11040854
  4. Beaumont LJ, Hughes L, Pitman A. Why is the choice of future climate scenarios for species distribution modelling important? Ecol Lett. 2008;11:1135-46. https://doi.org/10.1111/j.1461-0248.2008.01231.x
  5. W Bewket, MAO Radeny, C Mungai (2015). Agricultural Adaptation and Institutional Responses to Climate Change Vulnerability in Ethiopia.
  6. Bourou S, Bowe C, Diouf M, Van Damme P. Ecological and human impacts on stand density and distribution of tamarind (Tamarindus indica L.) in Senegal. Afr J Ecol. 2012;50:253-65. https://doi.org/10.1111/j.1365-2028.2012.01319.x
  7. Buermann W, Saatchi S, Smith TB, Zutta BR, Chaves JA, Mila B, Graham CH. Predicting species distributions across the Amazonian and Andean regions using remote sensing data. J Biogeography. 2008;35:1160-76. https://doi.org/10.1111/j.1365-2699.2007.01858.x
  8. Calvosa, C., Chuluunbaatar, D., and Fara, K. (2009). Livestock and climate change. In "Livestock and climate change". International Fund for Agricultural Development (IFAD).
  9. Cumming G. Comparing climate and vegetation as limiting factors for species ranges of African ticks. Ecology. 2002;83:255-68. https://doi.org/10.1890/0012-9658(2002)083[0255:ccaval]2.0.co;2
  10. Cumming GS, Van Vuuren DP. Will climate change affect ectoparasite species ranges? Glob Ecol Biogeography. 2006;15:486-97. https://doi.org/10.1111/j.1466-822X.2006.00241.x
  11. de la Fuente J, Almazan C, Blouin EF, Naranjo V, Kocan KM. Reduction of tick infections with Anaplasma marginale and A. phagocytophilum by targeting the tick protective antigen subolesin. Parasitol Res. 2006;100:85-91. https://doi.org/10.1007/s00436-006-0244-6
  12. Duan R-Y, Kong X-Q, Huang M-Y, Varela S, Ji X. The potential effects of climate change on amphibian distribution, range fragmentation and turnover in China. PeerJ. 2016;4:e2185. https://doi.org/10.7717/peerj.2185
  13. Elith J, Kearney M, Phillips S. The art of modelling range-shifting species. Methods Ecol Evol. 2010;1:330-42. https://doi.org/10.1111/j.2041-210X.2010.00036.x
  14. Engler R, Guisan A, Rechsteiner L. An improved approach for predicting the distribution of rare and endangered species from occurrence and pseudoabsence data. J Appl Ecol. 2004;41:263-74. https://doi.org/10.1111/j.0021-8901.2004.00881.x
  15. Estrada-Pena A, Bouattour A, Camicas JL, Guglielmone A, Horak I, Jongejan F, Latif A, Pegram R, Walker AR. The known distribution and ecological preferences of the tick subgenus Boophilus (Acari:Ixodidae) in Africa and Latin America. Exp Appl Acarol. 2006;38(2-3):219-35. https://doi.org/10.1007/s10493-006-0003-5
  16. Estrada-Pena A, Corson M, Venzal JM, Mangold AJ, Guglielmone A. Changes in climate and habitat suitability for the cattle tick Boophilus microplus in its southern Neotropical distribution range. J Vector Ecol. 2006;31(1):158-67. https://doi.org/10.3376/1081-1710(2006)31[158:CICAHS]2.0.CO;2
  17. Estrada-Pena A, Salman M. Current limitations in the control and spread of ticks that affect livestock: A review. Agriculture. 2013;3:221-35. https://doi.org/10.3390/agriculture3020221
  18. Feilhauer H, He KS, Rocchini D. Modeling species distribution using niche-based proxies derived from composite bioclimatic variables and MODIS NDVI. Remote Sensing. 2012;4:2057-75. https://doi.org/10.3390/rs4072057
  19. Fielding AH, Bell JF. A review of methods for the assessment of prediction errors in conservation presence/absence models. Environ Conservation. 1997;24:38-49. https://doi.org/10.1017/S0376892997000088
  20. Gashaw T. Climate change and livestock production in Ethiopia. Adv Life Sci Technol. 2014;22:39-42.
  21. Gonzalez C, Wang O, Stavana S, Gonzalez-Salazar C, Sanchez-Cordero V, Sarkar S. Climate Change and Risk of Leishmaniosis in North America: Predictions from Ecological Niche Models of Vector and Reservoir Species. PLoS Negl Trop Dis. 2010;4(1). https://doi.org/10.1371/journal.pntd.0000585.
  22. Gray, J., Dautel, H., Estrada-Pena, A., Kahl, O., and Lindgren, E. (2009). Effects of climate change on ticks and tick-borne diseases in Europe. Interdisciplinary perspectives on infectious diseases 2009.
  23. Hadgu M, Taddele H, Girma A, Abrha H, Hagos H. Prevalence of ixodid ticks infesting Raya cattle breeds in Semi-arid areas of Raya Azebo district, northern Ethiopia. Ethiop Vet J. 2018;22:53-64. https://doi.org/10.4314/evj.v22i2.5
  24. Hay S, Omumbo J, Craig M, Snow R. Earth observation, geographic information systems and Plasmodium falciparum malaria in sub-Saharan Africa. Adv Parasitol. 2000;47:173-215. https://doi.org/10.1016/S0065-308X(00)47009-0
  25. Hernandez PA, Graham CH, Master LL, Albert DL. The effect of sample size and species characteristics on performance of different species distribution modeling methods. Ecography. 2006;29:773-85. https://doi.org/10.1111/j.0906-7590.2006.04700.x
  26. Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A. Very high resolution interpolated climate surfaces for global land areas. Int J Climatol. 2005;25:1965-78. https://doi.org/10.1002/joc.1276
  27. Hoffmann I. Climate change and the characterization, breeding and conservation of animal genetic resources. Anim Genet. 2010;41:32-46. https://doi.org/10.1111/j.1365-2052.2010.02043.x
  28. Howden SM, Soussana J-F, Tubiello FN, Chhetri N, Dunlop M, Meinke H. Adapting agriculture to climate change. Proc Natl Acad Sci. 2007;104:19691-6. https://doi.org/10.1073/pnas.0701890104
  29. IPCC. Climate change 2007: The physical science basis. Agenda. 2007;6:333.
  30. Khormi HM, Kumar L. Climate change and the potential global distribution of Aedes aegypti: spatial modelling using GIS and CLIMEX. Geospat Health. 2014;8:405-15. https://doi.org/10.4081/gh.2014.29
  31. Lafaye M, Sall B, Ndiaye Y, Vignolles C, Tourre YM, Borchi F, Soubeyroux J-M, Diallo M, Dia I, Ba Y. Rift Valley fever dynamics in Senegal: a project for proactive adaptation and improvement of livestock raising management. Geospatial Health. 2013;8:279-88. https://doi.org/10.4081/gh.2013.73
  32. Leger E, Vourc'h G, Vial L, Chevillon C, McCoy KD. Changing distributions of ticks: causes and consequences. Exp Appl Acarol. 2013;59:219-44. https://doi.org/10.1007/s10493-012-9615-0
  33. Leta S, De Clercq EM, Madder M. High-resolution predictive mapping for Rhipicephalus appendiculatus (Acari: Ixodidae) in the Horn of Africa. Exp Appl Acarol. 2013;60:531-42. https://doi.org/10.1007/s10493-013-9670-1
  34. Lindgren, E., and Jaenson, T. G. (2006). Lyme borreliosis in Europe: influences of climate and climate change, epidemiology, ecology and adaptation measures. WHO Regional Office for Europe Copenhagen.
  35. Mannelli A, Bertolotti L, Gern L, Gray J. Ecology of Borrelia burgdorferi sensu lato in Europe: transmission dynamics in multi-host systems, influence of molecular processes and effects of climate change. FEMS Microbiol Rev. 2012;36:837-61. https://doi.org/10.1111/j.1574-6976.2011.00312.x
  36. Mbatudde M, Mwanjololo M, Kakudidi EK, Dalitz H. Modelling the potential distribution of endangered Prunus africana (Hook. f.) Kalkm. in East Africa. Afr J Ecol. 2012;50:393-403. https://doi.org/10.1111/j.1365-2028.2012.01327.x
  37. Medlock JM, Hansford KM, Bormane A, Derdakova M, Estrada-Pena A, George J-C, Golovljova I, Jaenson TG, Jensen J-K, Jensen PM. Driving forces for changes in geographical distribution of Ixodes ricinus ticks in Europe. Parasit Vectors. 2013;6:1. https://doi.org/10.1186/1756-3305-6-1
  38. Min S-K, Zhang X, Zwiers FW, Hegerl GC. Human contribution to more-intense precipitation extremes. Nature. 2011;470:378-81. https://doi.org/10.1038/nature09763
  39. Niguse, A., and Aleme, A. (2015). Modeling the Impact of Climate Change on Production of Sesame in Western Zone of Tigray, Northern Ethiopia. Journal of Climatology & Weather Forecasting 2015.
  40. Ogden N, Bigras-Poulin M, Hanincova K, Maarouf A, O'callaghan C, Kurtenbach K. Projected effects of climate change on tick phenology and fitness of pathogens transmitted by the North American tick Ixodes scapularis. J Theoretical Biol. 2008;254:621-32. https://doi.org/10.1016/j.jtbi.2008.06.020
  41. Ogden N, Bigras-Poulin M, O'callaghan C, Barker I, Lindsay L, Maarouf A, Smoyer-Tomic K, Waltner-Toews D, Charron D. A dynamic population model to investigate effects of climate on geographic range and seasonality of the tick Ixodes scapularis. Int J Parasitol. 2005;35:375-89. https://doi.org/10.1016/j.ijpara.2004.12.013
  42. Ogden N, Lindsay L, Beauchamp G, Charron D, Maarouf A, O'callaghan C, Waltner-Toews D, Barker I. Investigation of relationships between temperature and developmental rates of tick Ixodes scapularis (Acari: Ixodidae) in the laboratory and field. J Med Entomol. 2004;41:622-33. https://doi.org/10.1603/0022-2585-41.4.622
  43. Ogden N, Maarouf A, Barker I, Bigras-Poulin M, Lindsay L, Morshed M, O'callaghan C, Ramay F, Waltner-Toews D, Charron D. Climate change and the potential for range expansion of the Lyme disease vector Ixodes scapularis in Canada. Int J Parasitol. 2006;36:63-70. https://doi.org/10.1016/j.ijpara.2005.08.016
  44. Olwoch J, Reyers B, Engelbrecht F, Erasmus B. Climate change and the tick-borne disease, Theileriosis (East Coast fever) in sub-Saharan Africa. J Arid Environ. 2008;72:108-20. https://doi.org/10.1016/j.jaridenv.2007.04.003
  45. Ostfeld RS, Brunner JL. Climate change and Ixodes tick-borne diseases of humans. Phil. Trans. R. Soc. B. 2015;370:20140051. https://doi.org/10.1098/rstb.2014.0051
  46. Parmesan C, Burrows MT, Duarte CM, Poloczanska ES, Richardson AJ, Schoeman DS, Singer MC. Beyond climate change attribution in conservation and ecological research. Ecol Lett. 2013;16:58-71. https://doi.org/10.1111/ele.12098
  47. Parola P, Socolovschi C, Jeanjean L, Bitam I, Fournier P-E, Sotto A, Labauge P, Raoult D. Warmer weather linked to tick attack and emergence of severe rickettsioses. PLoS Negl Trop Dis. 2008;2:e338. https://doi.org/10.1371/journal.pntd.0000338
  48. Parry, M., Canziani, O., Palutikof, J., Van der Linden, P., and Hanson, C. (2007). Contribution of working group II to the fourth assessment report of the intergovernmental panel on climate change, 2007. Climate Change 2007: Working Group II: Impacts, Adaptation and Vulnerability.
  49. Phillips SJ, Anderson RP, Schapire RE. Maximum entropy modeling of species geographic distributions. Ecol Model. 2006;190:231-59. https://doi.org/10.1016/j.ecolmodel.2005.03.026
  50. Phillips SJ, Dudik M. Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography. 2008;31:161-75. https://doi.org/10.1111/j.0906-7590.2008.5203.x
  51. Pindyck RS. Climate change policy: What do the models tell us? J Eco Lit. 2013;51:860-72. https://doi.org/10.1257/jel.51.3.860
  52. Porretta D, Mastrantonio V, Amendolia S, Gaiarsa S, Epis S, Genchi C, Bandi C, Otranto D, Urbanelli S. Effects of global changes on the climatic niche of the tick Ixodes ricinus inferred by species distribution modelling. Parasit Vectors. 2013;6:271. https://doi.org/10.1186/1756-3305-6-271
  53. Roura-Pascual N, Suarez AV. The utility of species distribution models to predict the spread of invasive ants ( Hymenoptera : Formicidae ) and to anticipate changes in their ranges in the face of global climate change. Myrmecol News. 2008;11:67-77.
  54. Ruane AC, Cecil LD, Horton RM, Gordon R, McCollum R, Brown D, Killough B, Goldberg R, Greeley AP, Rosenzweig C. Climate change impact uncertainties for maize in Panama: Farm information, climate projections, and yield sensitivities. Agricul Forest Meteorol. 2013;170:132-45. https://doi.org/10.1016/j.agrformet.2011.10.015
  55. Scheldeman, X., and Zonneveld, M. v. (2010). "Training manual on spatial analysis of plant diversity and distribution."
  56. Signorini M, Cassini R, Drigo M, Frangipane di Regalbono A, Pietrobelli M, Montarsi F, Stensgaard A-S. Ecological niche model of Phlebotomus perniciosus, the main vector of canine leishmaniasis in north-eastern Italy. Geospat Health. 2014;9:193-201. https://doi.org/10.4081/gh.2014.16
  57. Slater H, Michael E. Predicting the Current and Future Potential Distributions of Lymphatic Filariasis in Africa Using Maximum Entropy Ecological Niche Modelling. PLoS ONE. 2012;7(2). https://doi.org/10.1371/journal.pone.0032202.
  58. Thornton P, Van de Steeg J, Notenbaert A, Herrero M. The impacts of climate change on livestock and livestock systems in developing countries: A review of what we know and what we need to know. Agricul Syst. 2009;101:113-27. https://doi.org/10.1016/j.agsy.2009.05.002
  59. Tokarevich NK, Tronin AA, Blinova OV, Buzinov RV, Boltenkov VP, Yurasova ED, Nurse J. The impact of climate change on the expansion of Ixodes persulcatus habitat and the incidence of tick-borne encephalitis in the north of European Russia. Global Health Action. 2011;4:8448. https://doi.org/10.3402/gha.v4i0.8448
  60. Ward DF. Modelling the potential geographic distribution of invasive ant species in New Zealand. Biol Invasions. 2007;9:723-35. https://doi.org/10.1007/s10530-006-9072-y
  61. Wardrop NA, Kuo C-C, Wang H-C, Clements AC, Lee P-F, Atkinson PM. Bayesian spatial modelling and the significance of agricultural land use to scrub typhus infection in Taiwan. Geospatial Health. 2013;8:229-39. https://doi.org/10.4081/gh.2013.69
  62. Weyant, J., Azar, C., Kainuma, M., Kejun, J., Nakicenovic, N., Shukla, P., La Rovere, E., and Yohe, G. (2009). Report of 2.6 versus 2.9 Watts/m2 RCPP evaluation panel. Integrated Assessment Modeling Consortium.
  63. Williams HW, Cross DE, Crump HL, Drost CJ, Thomas CJ. Climate suitability for European ticks: assessing species distribution models against null models and projection under AR5 climate. Parasit Vectors. 2015;8:440. https://doi.org/10.1186/s13071-015-1046-4
  64. Yost AC, Petersen SL, Gregg M, Miller R. Predictive modeling and mapping sage grouse (Centrocercus urophasianus) nesting habitat using Maximum Entropy and a long-term dataset from Southern Oregon. Ecol Inform. 2008;3:375-86. https://doi.org/10.1016/j.ecoinf.2008.08.004
  65. Young, N., Carter, L., and Evangelista, P. (2011). A MaxEnt model v3. 3.3 e tutorial (ArcGIS v10). Fort Collins, Colorado.
  66. Zeman P, Lynen G. Conditions for stable parapatric coexistence between Boophilus decoloratus and B. microplus ticks: a simulation study using the competitive Lotka-Volterra model. Exp Appl Acarol. 2010;52:409-26. https://doi.org/10.1007/s10493-010-9376-6

Cited by

  1. Models for Studying the Distribution of Ticks and Tick-Borne Diseases in Animals: A Systematic Review and a Meta-Analysis with a Focus on Africa vol.10, pp.7, 2019, https://doi.org/10.3390/pathogens10070893
  2. Impact of climate change on Asiatic black bear (Ursus thibetanus) and its autumn diet in the northern highlands of Pakistan vol.27, pp.18, 2019, https://doi.org/10.1111/gcb.15743