Will Global Climate Change Favor the Kissing bug (Triatoma infestans)?

Öz

Triatoma infestans, known as the kissing bug, is one of the main causes of Chagas disease in the South American. Due to the parasite secreted by this species, many protection studies have been carried out by the World Health Organization. However, it has been determined that the conservation efforts are not model-based and at a sufficient level. This study was carried out to determine the effects of changing climate conditions on the kissing bug on a global scale. MaxEnt was preferred as the modelling method and Chelsa V2.1. was preferred as the climate variables. Kissing bug is in the “good” model category with ROC values of 0.867/0.866 on the training/test dataset of current model. According to the variable value results contributing to the present model, the Chelsa climate envelope models for the year 2100 were simulated. As a result, it was determined that the distribution of the kissing bug expanded according to different climate envelope models for the year 2100. This study raises alarms that serious health problems from Chagas disease will emerge in 2100 due to the expansion of the kissing bug.

Anahtar Kelimeler

• Insecta
• Chagas disease
• Chelsa climate
• Habitat suitability

Proje Numarası

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Küresel iklim Değişikliği Öpücük Böceğinin (Triatoma infestans) Yararına Mı Olacak?

Öz

Öpücük böceği olarak bilinen Triatoma infestans Güney Amerika’da Chagas hastalığının başlıca sebeplerinden biridir. Bu türün salgıladığı parazit nedeniyle Dünya Sağlık Örgütü tarafından çok sayıda koruma çalışması yapılmıştır. Ancak koruma çalışmalarının modelleme tabanlı ve yeterli düzeyde olmadığı tespit edilmiştir. Bu çalışma, küresel ölçekte değişen iklim koşullarının öpücük böceği üzerindeki etkilerini belirlemek amacıyla yürütülmüştür. Modelleme yöntemi olarak MaxEnt, iklim değişkenleri olarak ise Chelsea V2.1 tercih edilmiştir. Öpücük böceği, günümüz modeli eğitim/test veri seti ROC değerleri 0,867/0,866 olmasıyla “iyi” model kategorisindedir. Modele katkı sağlayan değişkenlerin sırasıyla yıllık ortalama sıcaklık, mevsimsel sıcaklık, yağış mevsimselliği, engebelilik ve yükseklik olduğu tespit edilmiştir. Mevcut modele katkıda bulunan değişken değer sonuçlarına göre, 2100 yılı için Chelsa iklim zarfı modelleri simüle edilmiştir. Sonuç olarak öpücük böceğinin yayılışının 2100 yılına kadar farklı iklim zarfı modellerine göre genişlediği belirlenmiştir. Bu çalışma, öpücük böceğinin 2100 yılına kadar yayılmasıyla Chagas hastalığından kaynaklanan ciddi sağlık sorunlarının ortaya çıkacağına dair alarmlar vermektedir.

Anahtar Kelimeler

• Böcek
• Chagas hastalığı
• Chelsa iklim
• Habitat uygunluk

Destekleyen Kurum

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Proje Numarası

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Etik Beyan

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Teşekkür

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Kaynakça

1. Abrahan, L. B., Gorla, D. E., & Catalá, S. S. (2011). Dispersal of Triatoma infestans and other Triatominae species in the arid Chaco of Argentina: flying, walking or passive carriage? The importance of walking females. Memórias do Instituto Oswaldo Cruz, 106, 232-239. https://doi.org/10.1590/S0074-02762011000200019
2. Acarer, A. (2024a). Brown bear (Ursus arctos L.) distribution model in Europe: Current situation and the potential role of climate change. Sumarski list, 148(5-6), 1-12. https://doi.org/10.31298/sl.148.5-6.4
3. Acarer, A. (2024b). Will cinereous vulture (Aegypius monachus L.) become extinct in the forests of Türkiye in the future?. Sumarski list, 148(7-8), 375-387. https://doi.org/10.31298/sl.148.7-8.5
4. Acarer, A. (2024c). A scenario-driven strategy for future habitat management of the Andean bear. Journal of Wildlife and Biodiversity, 8(4), 56-77. https://doi.org/10.5281/zenodo.13822908
5. Acarer, A. (2024d). Role of climate change on Oriental spruce (Picea orientalis L.): Modeling and mapping. BioResources, 19(2), 3845-3856. https://doi.org/10.15376/biores.19.2.3845-3856
6. Acarer, A. (2024e). Response of Black Pine (Pinus nigra) in Southwestern Anatolia to Climate Change. BioResources, 19(4), 8594-8607. https://doi.org/10.15376/biores.19.2.3845-3856
7. Acarer, A. (2024f). Saz kedisi (Felis chaus S.) habitat uygunluk modellemesi ve haritalaması. Artvin Çoruh Üniversitesi Orman Fakültesi Dergisi, 25(2), 154-166. https://doi.org/10.17474/artvinofd.1472349
8. Acarer, A. (2024g). Yaban Keçisi (Capra aegagrus Erxleben, 1777) Habitat Uygunluk Modellemesi ve Haritalaması: Akdeniz Bölgesi Örneği. 21. Yüzyılda Fen ve Teknik, 11(21), 22-31.

9. Acarer, A. (2024h). Habitat Suitability Modelling and Mapping of Anatolian Wild Sheep (Ovis gmelinii anatolica Valenciennes, 1856). Int. j. adv. multidisc. res. stud. 4(5):945-952.
10. Acarer, A., & Mert, A. (2024). 21st Century Climate Change Threatens on the Brown Bear. CERNE, 30, e-103305. https://doi.org/10.1590/01047760202430013305
11. Alotaibi, K. D., Alharbi, H. A., Yaish, M. W., Ahmed, I., Alharbi, S. A., Alotaibi, F., & Kuzyakov, Y. (2023). Date palm cultivation: A review of soil and environmental conditions and future challenges. Land Degradation & Development, 34(9), 2431-2444. https://doi.org/10.1002/ldr.4619
12. Alves, R. R., & Alves, H. N. (2011). The faunal drugstore: Animal-based remedies used in traditional medicines in Latin America. Journal of Ethnobiology and Ethnomedicine, 7, 1-43. https://doi.org/10.1186/1746-4269-7-9
13. Andrew, N. R., & Hill, S. J. (2017). Effect of climate change on insect pest management. Environmental pest management: challenges for agronomists, ecologists, economists and policymakers, 195-223. https://doi.org/10.1002/9781119255574.ch9
14. Bargues, M. D., Klisiowicz, D. R., Panzera, F., Noireau, F., Marcilla, A., Perez, R., & Mas-Coma, S. (2006). Origin and phylogeography of the Chagas disease main vector Triatoma infestans based on nuclear rDNA sequences and genome size. Infection, Genetics and Evolution, 6(1), 46-62. https://doi.org/10.1016/j.meegid.2005.01.00
15. Bonney, K. M. (2014). Chagas disease in the 21st century: a public health success or an emerging threat? Parasite, 21,11. https://doi.org/10.1051/parasite/2014012
16. Buarque, D. S., Braz, G. R., Martins, R. M., Tanaka-Azevedo, A. M., Gomes, C. M., Oliveira, F. A., & Tanaka, A. S. (2013). Differential expression profiles in the midgut of Triatoma infestans infected with Trypanosoma cruzi. PLoS One, 8(5), e61203. https://doi.org/10.1371/journal.pone.0061203
17. Camiz, S., Poscolieri, M., & Roverato, M. (2017). Geomorphometric comparative analysis of Latin-American volcanoes. Journal of South American Earth Sciences, 76, 47-62. https://doi.org/10.1016/j.jsames.2017.02.011 Cohen, J. E., & Gurtler, R. E. (2001). Modeling household transmission of American trypanosomiasis. Science, 293(5530), 694-698. https://doi.org/10.1126/science.1060638
18. Costa, J., Dornak, L. L., Almeida, C. E., & Peterson, A. T. (2014). Distributional potential of the Triatoma brasiliensis species complex at present and under scenarios of future climate conditions. Parasites & Vectors, 7, 1-10. https://doi.org/10.1186/1756-3305-7-238
19. Cushman, S. A., Kilshaw, K., Campbell, R. D., Kaszta, Z., Gaywood, M., & Macdonald, D. W. (2024). Comparing the performance of global, geographically weighted and ecologically weighted species distribution models for Scottish wildcats using GLM and Random Forest predictive modeling. Ecological Modelling, 492, 110691. https://doi.org/10.1016/j.ecolmodel.2024.110691
20. Delgado, S., Ernst, K. C., Pumahuanca, M. L. H., Yool, S. R., Comrie, A. C., Sterling, C. R., & Chagas Disease Working Group in Arequipa, Peru. (2013). A country bug in the city: urban infestation by the Chagas disease vector Triatoma infestans in Arequipa, Peru. International journal of health geographics, 12(48), 1-12. https://doi.org/10.1186/1476-072X-12-48
21. Di Luciano, V. S. (1983). Orientation of Triatoma infestans (Hemiptera: Reduviidae) to environmental temperatures. Journal of Medical Entomology, 20(4), 446-454. https://doi.org/10.1093/jmedent/20.4.446
22. Dias, J. C. P., Silveira, A. C., & Schofield, C. J. (2002). The impact of Chagas disease control in Latin America: a review. Memórias do Instituto Oswaldo Cruz, 97, 603-612. https://doi.org/10.1590/S0074-02762002000500002
23. Dubos, N., Fieldsend, T. W., Roesch, M. A., Augros, S., Besnard, A., Choeur, A., & Crottini, A. (2023). Choice of climate data influences predictions for current and future global invasion risks for two Phelsuma geckos. Biological Invasions, 25(9), 2929-2948. https://doi.org/10.1007/s10530-023-03082-8
24. Dujardin, J. P., Schofield, C. P., & Tibayrenc, M. (1998). Population structure of Andean Triatoma infestans: allozyme frequencies and their epidemiological relevance. Medical and Veterinary Entomology, 12(1), 20-29. https://doi.org/10.1046/j.1365-2915.1998.00076.x
25. Elith, J., Phillips, S. J., Hastie, T., Dudík, M., Chee, Y. E., & Yates, C. J. (2011). A statistical explanation of MaxEnt for ecologists. Diversity and Distributions, 17(1), 43-57. https://doi.org/10.1111/j.1472-4642.2010.00725.x
26. Elliot, S. L., Rodrigues, J. D. O., Lorenzo, M. G., Martins-Filho, O. A., & Guarneri, A. A. (2015). Trypanosoma cruzi, etiological agent of Chagas disease, is virulent to its triatomine vector Rhodnius prolixus in a temperature-dependent manner. PLoS neglected tropical diseases, 9(3), e0003646.https://doi.org/10.1371/journal.pntd.0003646
27. Ertuğrul, E. T., Mert, A., & Oğurlu, İ. (2017). Mapping habitat suitabilities of some wildlife species in Burdur Lake Basin. Turkish Journal of Forestry, 18(2), 149-154. https://doi.org/10.18182/tjf.330950
28. Galvão, C., & Justi, S. A. (2015). An overview on the ecology of Triatominae (Hemiptera: Reduviidae). Acta Tropica, 151, 116-125. https://doi.org/10.1016/j.actatropica.2015.06.006
29. Garreaud, R. D., Vuille, M., Compagnucci, R., & Marengo, J. (2009). Present-day south american climate. Palaeogeography, Palaeoclimatology, Palaeoecology, 281(3-4), 180-195.https://doi.org/10.1016/j.palaeo.2007.10.032
30. GBIF, (2024). GBIF.org (01 September 2024) GBIF Occurrence Download https://doi.org/10.15468/dl.ynhkhy Gürtler, R. E., Cecere, M. C., Vazquez, D. P., Chuit, R., & Cohen, J. E. (1996). Host-feeding patterns of domiciliary Triatoma infestans (Hemiptera: Reduviidae) in Northwest Argentina: seasonal and instar variation. Journal of Medical Entomology, 33(1), 15-26. https://doi.org/10.1093/jmedent/33.1.15
31. Jiménez-Valverde, A., Peterson, A. T., Soberón, J. O. J. M., Overton, J. M., Aragón, P., & Lobo, J. M. (2011). Use of niche models in invasive species risk assessments. Biological Invasions, 13, 2785-2797. https://doi.org/10.1007/s10530-011-9963-4
32. Johnson, C. J., Hurley, M., Rapaport, E., & Pullinger, M. (2012). Using expert knowledge effectively: lessons from species distribution models for wildlife conservation and management. Expert knowledge and its application in landscape ecology, 153-171. https://doi.org/10.1007/978-1-4614-1034-8_8
33. Karger, D. N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R. W., & Kessler, M. (2017). Climatologies at high resolution for the earth’s land surface areas. Scientific Data, 4(1), 1-20. https://doi.org/10.1038/sdata.2017.122
34. Karger, D. N., Nobis, M. P., Normand, S., Graham, C. H., & Zimmermann, N. E. (2023). CHELSA-TraCE21k–high-resolution (1 km) downscaled transient temperature and precipitation data since the Last Glacial Maximum. Climate of the Past, 19(2), 439-456. https://doi.org/10.5194/cp-19-439-2023
35. Karger, D. N., Wilson, A. M., Mahony, C., Zimmermann, N. E., & Jetz, W. (2021). Global daily 1 km land surface precipitation based on cloud cover-informed downscaling. Scientific Data, 8(1), 307. https://doi.org/10.1038/s41597-021-01084-6
36. Klotz, S. A., Dorn, P. L., Mosbacher, M., & Schmidt, J. O. (2014). Kissing bugs in the United States: risk for vector-borne disease in humans. Environmental Health Insights, 8, EHI-S16003. https://doi.org/10.4137/EHI.S16003
37. Lazzari, C. R. (2021). The behaviour of kissing bugs. Triatominae-The Biology of Chagas Disease Vectors, 5, 215-238. https://doi.org/10.1007/978-3-030-64548-9_10
38. Levy, M. Z., Bowman, N. M., Kawai, V., Waller, L. A., Del Carpio, J. G. C., Benzaquen, E. C., & Bern, C. (2006). Periurban Trypanosoma cruzi–infected Triatoma infestans, Arequipa, Peru. Emerging Infectious Diseases, 12(9), 1345. http://dx.doi.org/10.3201/eid1209.051662
39. Lorenzo, M. G., & Lazzari, C. R. (1999). Temperature and relative humidity affect the selection of shelters by Triatoma infestans, vector of Chagas disease. Acta tropica, 72(3), 241-249. https://doi.org/10.1016/S0001-706X(98)00094-1
40. Margalef‐Marrase, J., Pérez‐Navarro, M. Á., & Lloret, F. (2020). Relationship between heatwave‐induced forest die‐off and climatic suitability in multiple tree species. Global Change Biology, 26(5), 3134-3146. https://doi.org/10.1111/gcb.15042
41. Merow, C., Smith, M. J., & Silander Jr, J. A. (2013). A practical guide to MaxEnt for modeling species’ distributions: what it does, and why inputs and settings matter. Ecography, 36(10), 1058-1069. https://doi.org/10.1111/j.1600-0587.2013.07872.x
42. Mert, A., & Acarer, A. (2018). Wildlife Diversity in Reed Beds Around Beyşehir Lake. Bilge International Journal of Science and Technology Research, 2(1), 110-119.
43. Mert, A., & Acarer, A. (2021). Usage Rates of Reed Beds in Beysehir Lake of Some Wild Mammals. Feb Fresenıus Environmental Bulletin, 845.
44. Mert, A., Kıraç, A. (2017). Habitat Suitability Mapping of Anatololacerta danfordi (Günter, 1876) in Isparta-Sütçüler District. Bilge International Journal of Science and Technology Research, 1(1), 16-22.
45. Mert, A., Yalçınkaya, B. (2016). The relation of edge effect on some wild mammals in Burdur-Ağlasun (Turkey) district. Biological Diversity and Conservation, 9(2), 193-201.
46. Miller, J. (2010). Species distribution modeling. Geography Compass, 4(6), 490-509. https://doi.org/10.1111/j.1749-8198.2010.00351.x
47. Morera‐Pujol, V., Mostert, P. S., Murphy, K. J., Burkitt, T., Coad, B., McMahon, B. J., & Ciuti, S. (2023). Bayesian species distribution models integrate presence‐only and presence–absence data to predict deer distribution and relative abundance. Ecography, 2023(2), e06451. https://doi.org/10.1111/ecog.06451
48. Noireau, F. (2009). Wild Triatoma infestans, a potential threat that needs to be monitored. Memórias do Instituto Oswaldo Cruz, 104, 60-64. https://doi.org/10.1590/S0074-02762009000900010
49. Özdemir, S. (2024). Testing the Effect of Resolution on Species Distribution Models Using Two Invasive Species. Polish Journal of Environmental Studies, 33(2), 1325-1335. https://doi.org/10.15244/pjoes/166353
50. Özdemir, S., Gülsoy, S., & Mert, A. (2020). Predicting the effect of climate change on the potential distribution of Crimean Juniper. Kastamonu University Journal of Forestry Faculty, 20(2), 133-142. https://doi.org/10.17475/kastorman.801847
51. Özdemir, S., Özkan, K., & Mert, A. (2020). An ecological perspective on climate change scenarios. Biological Diversity and Conservation, 13(3), 361-371. https://doi.org/10.46309/biodicon.2020
52. Özkan, K. (2012). Modelling ecological data using classification and regression tree technique (CART), Süleyman Demirel University, Forestry Faculty of Journal, 13(1), 1-4.
53. Paranaiba, L. F., Guarneri, A. A., Torrecilhas, A. C., Melo, M. N., & Soares, R. P. (2019). Extracellular vesicles isolated from Trypanosoma cruzi affect early parasite migration in the gut of Rhodnius prolixus but not in Triatoma infestans. Memórias do Instituto Oswaldo Cruz, 114, e190217. https://doi.org/10.1590/0074-02760190217
54. Phillips, S. J. (2005). A brief tutorial on Maxent. At&t Research, 190(4), 231-259.
55. Phillips, S. J., & Dudík, M. (2008). Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography, 31(2), 161-175. https://doi.org/10.1111/j.0906-7590.2008.5203.x
56. Phillips, S. J., Anderson, R. P., Dudík, M., Schapire, R. E., & Blair, M. E. (2017). Opening the black box: An open‐source release of Maxent. Ecography, 40(7), 887-893. https://doi.org/10.1111/ecog.03049
57. Picanço, M. M., Guedes, R. N. C., da Silva, R. S., Galvão, C., Souza, P. G. C., Barreto, A. B., & Picanço, M. C. (2024). Unveiling the overlooked: Current and future distribution dynamics of kissing bugs and palm species linked to oral Chagas disease transmission. Acta Tropica, 107367. https://doi.org/10.1016/j.actatropica.2024.107367
58. Pinto, J., Bonacic, C., Hamilton-West, C., Romero, J., & Lubroth, J. (2008). Climate change and animal diseases in South America. Rev Sci Tech, 27(2), 599-613.
59. Pureswaran, D. S., Roques, A., & Battisti, A. (2018). Forest insects and climate change. Current Forestry Reports, 4, 35-50. https://doi.org/10.1007/s40725-018-0075-6
60. Raven, P. H., & Wagner, D. L. (2021). Agricultural intensification and climate change are rapidly decreasing insect biodiversity. Proceedings of the National Academy of Sciences, 118(2), e2002548117. https://doi.org/10.1073/pnas.2002548117
61. Ribeiro, G. F. D. O. M. A. L., Castro, G. V. D. S., Menezes, A. L. R., Lima, R. A., Silva, R. P. M., & Meneguetti, D. U. D. O. (2018). Retrospective study of the epidemiological overview of the transmission of Chagas disease in the State of Acre, South-Western Amazonia, from 2009 to 2016. Journal of Human Growth and Development, 28(3), 329-336. https://doi.org/10.7322/jhgd.152187
62. Roca, M. J., & Lazzari, C. R. (1994). Effects of relative humidity on the haematophagous bug Triatoma infestans: hygropreference and eclosion success. Journal of Insect Physiology, 40(10), 901-907. https://doi.org/10.1016/0022-1910(94)90024-8
63. Rolandi, C., & Schilman, P. E. (2012). Linking global warming, metabolic rate of hematophagous vectors, and the transmission of infectious diseases. Frontiers in Physiology, 3, 75. https://doi.org/10.3389/fphys.2012.00075 Sbaraglia, C., Samraoui, K. R., Massolo, A., Bartoňová, A. S., Konvička, M., & Fric, Z. F. (2023). Back to the future: Climate change effects on habitat suitability of Parnassius apollo throughout the Quaternary glacial cycles. Insect Conservation and Diversity, 16(2), 231-242. https://doi.org/10.1007/s10841-024-00617-9
64. Schmidt, J. O., Miller, M. L., & Klotz, S. A. (2022). Seasonal flight pattern of the kissing bugs Triatoma rubida and T. protracta (Hemiptera: Reduviidae: Triatominae) in southern Arizona, United States. Insects, 13(3), 265. https://doi.org/10.3390/insects13030265
65. Schofield CJ (1988). Biosystematics of the Triatominae. In M Service (ed.), Biosystematics of Haematophagous Insects, Clarendon Press, Oxford, p. 284-312.
66. Schowalter, T. D. (2022). Insect Ecology: An Ecosystem Approach, London: Academic press.
67. Shikanai-Yasuda, M. A., & Carvalho, N. B. (2012). Oral transmission of Chagas disease. Clinical Infectious Diseases, 54(6), 845-852. https://doi.org/10.1093/cid/cir956
68. Stange, E. E., & Ayres, M. P. (2010). Climate change impacts: Insects. Eiley, Chichester, England, Encyclopedia of life sciences (ELS), 1. https://doi.org/10.1002/9780470015902.a0022555
69. Strasen, J., Williams, T., Ertl, G., Zoller, T., Stich, A., & Ritter, O. (2014). Epidemiology of Chagas disease in Europe: many calculations, little knowledge. Clinical Research in Cardiology, 103, 1-10. https://doi.org/10.1007/s00392-013-0613-y
70. Tekeş, A., Cürebal, İ. (2019). Analysis Of Relationship Between Land Use and Elevation & Slope Properties In Sehzadeler (Manisa - Turkey) District. Turkish Studies Social Sciences, 14(4), 1787-1806. http://dx.doi.org/10.29228/TurkishStudies.23337
71. Tekin, S., Yalçınkaya, B., Acarer, A., & Mert, A. (2018). A research on usage possibilities of satellite data in wildlife: Modeling habitat suitability of Roe deer (Capreolus capreolus L.) with MaxEnt. Bilge International Journal of Science and Technology Research, 2(2), 147-156.
72. Usinger, R. L., Wygodzinsky, P., & Ryckman, R. E. (1966). The biosystematics of Triatominae. Annual Review of Entomology, 11(1), 309-330. https://doi.org/10.1146/annurev.en.11.010166.001521
73. Vassena, C. V., Picollo, M. I., & Zerba, E. N. (2000). Insecticide resistance in Brazilian Triatoma infestans and Venezuelan Rhodnius prolixus. Medical and Veterinary Entomology, 14(1), 51-55. https://doi.org/10.1186/s13071-024-06276-8
74. WHO, (2024). World Health Organization, World Chagas Disease Day 2023, Access date: 15.01.2024. https://www.who.int/campaigns/world-chagas-disease-day/2023
75. Zeledon, R., & Rabinovich, J. E. (1981). Chagas’ disease: an ecological appraisal with special emphasis on its insect vectors. Annual Review of Entomology, 26, 101-133. https://doi.org/10.1146/annurev.en.26.010181.000533
76. Zhang, K., Yao, L., Meng, J., & Tao, J. (2018). Maxent modeling for predicting the potential geographical distribution of two peony species under climate change. Science of the Total Environment, 634, 1326-1334. https://doi.org/10.1016/j.scitotenv.2018.04.112
77. Zimmermann, N. E., Edwards, T. C., Graham C. E., Pearman P. B., Svenning J. C., (2010). New trends in species distribution modelling. Ecography, 33, 985-989. https://doi.org/10.1111/j.1600-0587.2010.06953.x