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Predicting the current and future suitable distribution range of Trilocha varians (Walker, 1855) (Lepidoptera: Bombycidae) in China

Published online by Cambridge University Press:  03 May 2024

Qianqian Qian
Affiliation:
College of Life Science, China West Normal University, Nanchong 637002, China
Danping Xu
Affiliation:
College of Life Science, China West Normal University, Nanchong 637002, China
Wenkai Liao
Affiliation:
College of Life Science, China West Normal University, Nanchong 637002, China
Zhihang Zhuo*
Affiliation:
College of Life Science, China West Normal University, Nanchong 637002, China
*
Corresponding author: Zhihang Zhuo; Email: zhuozhihang@foxmail.com

Abstract

Trilocha varians is one of the major pests of Ficus spp. Based on 19 bioclimatic variables provided by the Worldclim, our study analysed the suitable distribution areas of T. varians under current and future climate changes (SSP1-2.6, SSP2-4.5, SSP5-8.5) for two periods (the 2050s and 2090s) using the maximum entropy algorithm (MaxEnt) model. Key environmental variables affecting the geographic distribution of T. varians were also identified, and the changes in the area of suitable range under current and future climate changes were compared. The results showed that the key environmental variables affecting the distribution of T. varians were temperature and precipitation, comprising annual mean temperature (bio1), temperature seasonality (standard deviation × 100) (bio4), precipitation of driest month (bio14), and precipitation of driest quarter (bio17). Under the current climatic conditions, the suitable distribution area of T. varians is within the range of 92°13′E–122°08′E, 18°17′N–31°55′N. The current high, medium, and low suitable areas for T. varians predicted by the MaxEnt model are 14.00 × 104, 21.50 × 104, and 71.95 × 104 km2, of which the high suitable areas are mainly distributed in southern Guangdong, southwestern Guangxi, western Taiwan, Hong Kong, and Hainan. Under different future climatic conditions, some of the high, medium, and low suitability zones for T. varians increased and some decreased, but the mass centre did not migrate significantly. The Pearl River Basin is predicted to remain the main distribution area of T. varians.

Type
Research Paper
Copyright
Copyright © The Author(s), 2024. Published by Cambridge University Press

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Footnotes

*

These authors contributed equally to this work and should be regarded as co-first authors.

References

Aidoo, O, Souza, PG, Silva, R, Santana Júnior, P, Picanço, M, Osei-owusu, J, Setamou, M, Ekesi, S and Borgemeister, C (2022) A machine learning algorithm-based approach (MaxEnt) for predicting invasive potential of Trioza erytreae on a global scale. Ecological Informatics 71, 101792.CrossRefGoogle Scholar
Arya, P (2019) Recent Diversity and Potentia Biological Control Studies on Major Ornamental Ficus sp. Defoliating Moth Bombycid Trilocha (=Ocinara) varians (Walker) (Lepidoptera: Bombycidae).Google Scholar
Barrett, B, Charles, JW and Temte, JL (2015) Climate change, human health, and epidemiological transition. Preventive Medicine 70, 6975.CrossRefGoogle ScholarPubMed
Basari, N, Mustafa, N, Yusrihan, N, Chin, W and Ibrahim, Z (2019) The effect of temperature on the development of Trilocha varians (Lepidoptera: Bombycidae) and control of the Ficus plant pest. Tropical Life Sciences Research 30, 2331.CrossRefGoogle ScholarPubMed
Boullis, A, Detrain, C, Francis, F and Verheggen, F (2016) Will climate change affect insect pheromonal communication? Current Opinion in Insect Science 17, 8791.CrossRefGoogle ScholarPubMed
Chen, S (2020) Application and suitable planting of Ficus microcarpa in urban greening. Guangdong Landscape Architecture 42, 5558.Google Scholar
Daimon, T, Yago, M, Hsu, Y, Fujii, T, Nakajima, Y, Kokusho, R, Abe, H, Katsuma, S and Shimada, T (2012) Molecular phylogeny, laboratory rearing, and karyotype of the bombycid moth, Trilocha varians. Journal of Insect Science (Online) 12, 49.CrossRefGoogle ScholarPubMed
Duan, R, Huang, G, Li, Y, Zhou, X, Ren, J and Tian, C (2020) Stepwise clustering future meteorological drought projection and multi-level factorial analysis under climate change: a case study of the Pearl River Basin, China. Environmental Research 196, 110368.CrossRefGoogle ScholarPubMed
Falsafi, H, Alipanah, H, Ostovan, H, Hesami, S and Zahiri, R (2022) Forecasting the potential distribution of Spodoptera exigua and S. littoralis (Lepidoptera, Noctuidae) in Iran. Journal of Asia-Pacific Entomology 25, 101956.CrossRefGoogle Scholar
Fekrat, L and Farashi, A (2022) Impacts of climatic changes on the worldwide potential geographical dispersal range of the leopard moth, Zeuzera pyrina (L.) (Lepidoptera: Cossidae). Global Ecology and Conservation 34, e2050.CrossRefGoogle Scholar
Gu, X, Qiang, Z, Vijay, S and Peijun, S (2016) Hydrological response to large-scale climate variability across the Pearl River Basin, China: spatiotemporal patterns and sensitivity. Global and Planetary Change 149, 113.CrossRefGoogle Scholar
He, P, Li, J, Li, Y, Xu, N, Gao, Y, Guo, L, Huo, T, Peng, C and Meng, F (2021) Habitat protection and planning for three Ephedra using the MaxEnt and Marxan models. Ecological Indicators 133, 108399.CrossRefGoogle Scholar
Hirsch, A, Guillod, B, Seneviratne, S, Beyerle, U, Boysen, L, Brovkin, V, Davin, E, Doelman, J, Kim, H, Mitchell, D, Nitta, T, Shiogama, H, Sparrow, S, Stehfest, E, Vuuren, D and Wilson, S (2018) Biogeophysical impacts of land-use change on climate extremes in low-emission scenarios: results from HAPPI-land. Earth's Future 6, 396409.CrossRefGoogle ScholarPubMed
Hodkinson, ID (1997) Progressive restriction of host plant exploitation along a climatic gradient: the willow psyllid Cacopsylla groenlandica in Greenland. Ecological Entomology 22, 4754.CrossRefGoogle Scholar
Islam, KN, Rana, LRS, Islam, K, Hossain, MS, Hossain, MM and Hossain, MA (2021) Climate change and the distribution of two Ficus spp. in Bangladesh – predicting the spatial shifts. Trees, Forests and People 4, 100086.CrossRefGoogle Scholar
Jactel, H, Koricheva, J and Castagneyrol, B (2019) Responses of forest insect pests to climate change: not so simple. Current Opinion in Insect Science 35, 103108.CrossRefGoogle Scholar
Jie, L, Yang, J and Li, W (2020) Potential distribution analysis of an invasive alien species Parapediasia teterrella (Lepidoptera, Crambidae) in East Asia. Journal of Asia-Pacific Entomology 23, 219223.CrossRefGoogle Scholar
Kedar, SC, Malllaiah, K and Saini, R (2014) First report of Trilocha (=Ocinara) varians and its natural enemies on Ficus spp. from Haryana, India. Journal of Entomology and Zoology Studies 2, 268270.Google Scholar
Li, X, Xu, D, Jin, Y, Zhuo, Z, Yang, H, Hu, J and Wang, R (2020) Predicting the current and future distributions of Brontispa longissima (Coleoptera: Chrysomelidae) under climate change in China. Global Ecology and Conservation 25, e1444.Google Scholar
Logan, J, Regniere, J, Gray, D and Munson, S (2007) Risk assessment in the face of a changing environment: gypsy moth and climate change in Utah. Ecological Applications: A Publication of the Ecological Society of America 17, 101117.CrossRefGoogle ScholarPubMed
Millien, V, Lyons, S, Olson, L, Smith, F, Wilson, A and Yom-Tov, Y (2006) Ecotypic variation in the context of global climate change: revisiting the rules. Ecology Letters 9, 853869.CrossRefGoogle ScholarPubMed
Mugiyo, H, Chimonyo, V, Kunz, R, Sibanda, M, Nhamo, L, Masemola, C, Modi, A and Mabhaudhi, T (2022) Mapping the spatial distribution of underutilised crop species under climate change using the MaxEnt model: a case of KwaZulu-Natal, South Africa. Climate Services 28, 100330.CrossRefGoogle Scholar
Naeem-Ullah, U, Ramzan, M, Saeed, S, Iqbal, N, Umar, U, Sarwar, Z, Ali, M, Saba, S, Abid, A, Khan, K and Ghramh, H (2020) Toxicity of four different insecticides against Trilocha varians (Bombycidae: Lepidoptera). Journal of King Saud University - Science 32, 18531855.CrossRefGoogle Scholar
Qin, A, Jin, K, Batsaikhan, M, Nyamjav, J, Li, G, Jia, L, Xue, Y, Sun, G, Wu, L, Indree, T, Shi, Z and Xiao, W (2020) Predicting the current and future suitable habitats of the main dietary plants of the Gobi bear using MaxEnt modeling. Global Ecology and Conservation 22, e1032.CrossRefGoogle Scholar
Ramzan, M (2020) Effect of temperature on the life cycle of Trilocha varians (Lepidoptera: Bombycidae) in Pakistan. Pure and Applied Biology 9, 436442.CrossRefGoogle Scholar
Rödder, D, Schmitt, T, Gros, P, Ulrich, W and Habel, J (2021) Climate change drives mountain butterflies towards the summits. Scientific Reports 11, 1202114382.CrossRefGoogle ScholarPubMed
Sirois-Delisle, C and Kerr, J (2018) Climate change-driven range losses among bumblebee species are poised to accelerate. Scientific Reports 8, 110.CrossRefGoogle ScholarPubMed
Sutton, GF and Martin, GD (2022) Testing MaxEnt model performance in a novel geographic region using an intentionally introduced insect. Ecological Modelling 473, 110139.CrossRefGoogle Scholar
Timoner, P, Fasel, M, AshrafVaghefi, S, Marle, P, Castella, E, Moser, F and Lehmann, A (2021) Impacts of climate change on aquatic insects in temperate alpine regions: complementary modeling approaches applied to Swiss rivers. Global Change Biology 27, 35653581.CrossRefGoogle ScholarPubMed
Wu, G, Wang, N, Hu, S, Tian, L and Tian, J (2008) Physical Geography. Beijing, China: Higher Education Press.Google Scholar
Xu, D, Li, X, Jin, Y, Zhuo, Z, Yang, H, Hu, J and Wang, R (2020) Influence of climatic factors on the potential distribution of pest Heortia vitessoides Moore in China. Global Ecology and Conservation 23, e1107.CrossRefGoogle Scholar
Xu, D, Zhuo, Z, Li, X and Wang, R (2022) Distribution and invasion risk assessment of Oryctes rhinoceros (L.) in China under changing climate. Journal of Applied Entomology 146, 385395.CrossRefGoogle Scholar
Yang, J, Huang, Y, Jiang, X, Chen, H, Liu, M and Wang, R (2022a) Potential geographical distribution of the endangered plant isoetes under human activities using MaxEnt and GARP. Global Ecology and Conservation 38, e2186.CrossRefGoogle Scholar
Yang, L, Wen, X, Barzegar, R, Adamowski, J, Meng, Z and Yin, Z (2022b) Contributions of climate, elevated atmospheric CO2 concentration and land surface changes to variation in water use efficiency in Northwest China. Catena 213, 106220.CrossRefGoogle Scholar
Zhang, H, Lai, PY and Jim, CY (2017) Species diversity and spatial pattern of old and precious trees in Macau. Landscape and Urban Planning 162, 5667.CrossRefGoogle Scholar
Zhang, S, Liu, X, Li, R, Wang, X, Cheng, J, Yang, Q and Kong, H (2021) AHP-GIS and MaxEnt for delineation of potential distribution of Arabica coffee plantation under future climate in Yunnan, China. Ecological Indicators 132, 108339.CrossRefGoogle Scholar
Zhao, Z, Xiao, N, Shen, M and Li, J (2022) Comparison between optimized MaxEnt and random forest modeling in predicting potential distribution: a case study with Quasipaa boulengeri in China. Science of the Total Environment 842, 156867.CrossRefGoogle ScholarPubMed
Zhou, T, Chen, Z and Xiao, L (2021) Interpreting IPCC AR6: future global climate based on projection under scenarios and on near-term information. Advances in Climate Change Research 17, 652663.Google Scholar
Zhuo, Z, Xu, D, Pu, B, Wang, R and Ye, M (2020) Predicting distribution of Zanthoxylum bungeanum Maxim. in China. BMC Ecology 20, 46.CrossRefGoogle ScholarPubMed