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Temperature-based phenology model for predicting the present and future establishment and distribution of recently invasive Spodoptera frugiperda (J. E. Smith) in India

Published online by Cambridge University Press:  11 October 2021

T. V. Prasad
Affiliation:
ICAR-Central Research Institute for Dryland Agriculture, Hyderabad-500 059, Telangana, India
M. Srinivasa Rao*
Affiliation:
ICAR-Central Research Institute for Dryland Agriculture, Hyderabad-500 059, Telangana, India
K. V. Rao*
Affiliation:
ICAR-Central Research Institute for Dryland Agriculture, Hyderabad-500 059, Telangana, India
S. K. Bal
Affiliation:
ICAR-Central Research Institute for Dryland Agriculture, Hyderabad-500 059, Telangana, India
Y. Muttapa
Affiliation:
ICAR-Central Research Institute for Dryland Agriculture, Hyderabad-500 059, Telangana, India
J. S. Choudhary
Affiliation:
ICAR-RCER, Farming System Research Centre for Hill and Plateau Region, Plandu, Ranchi-834 010, Jharkhand, India
V. K. Singh
Affiliation:
ICAR-Central Research Institute for Dryland Agriculture, Hyderabad-500 059, Telangana, India
*
Author for correspondence: M. Srinivasa Rao, Email: [email protected], [email protected]
Author for correspondence: M. Srinivasa Rao, Email: [email protected], [email protected]

Abstract

Fall armyworm, Spodoptera frugiperda (J. E. Smith) is a polyphagous and highly destructive invasive insect pest of many crops. It was recently introduced into India and widely reported in almost all parts of India. Development of a temperature-based phenology model for predicting its rate of development and distribution will help in understanding the establishment and further spread of introduced invasive insect pests. Development, survival and reproduction parameters of S. frugiperda at six constant temperature conditions (15, 20, 25, 27, 30 and 35°C) were investigated and further validated with data generated under fluctuating temperature conditions. The estimated lower developmental threshold temperatures were 12.1°C for eggs, 11°C for larvae, 12.2°C for pupae, 15.13°C for males and 12.66°C for females. Degree-day (DD) requirements for the development of the different stages of S. frugiperda were 50, 250 and 200 DD for egg, larva and pupa, respectively. The best-fitted functions were compiled for each life stage to yield a phenology model, which was stochastically simulated to estimate the life table parameters. The developed phenology model predicted temperature ranges between 27 and 30°C as favourable for S. frugiperda development, survival and reproduction. The results revealed that maximum net reproductive rate (215.66 females/female/generation) and total fecundity (981.08 individuals/female/generation) were attained at 30°C constant temperature. The mean length of generations decreased from 74.29 days at 15°C to 38.74 days at 30°C. The maximum intrinsic rate of increase (0.138 females/female/day) and shortest doubling time (4.9 days) were also observed at 30°C. Results of simulated life table parameters showed high temperature-dependent development of S. frugiperda and complete development within all the tested constant temperature ranges (15–35°C). Simulated life table parameters for predicting risk indices of S. frugiperda in India indicated a significant increase in activity indices and establishment risk indices with a higher number of generations during future (2050 and 2070) climatic change scenarios compared to present conditions. Our results indicate that India will be highly suitable for the establishment and survival of S. frugiperda in future time periods.

Type
Research Paper
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

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References

Ahmed, K, Sachindra, DA, Shahid, S, Demirel M, C and Chung, ES (2019) Selection of multi-model ensemble of GCMs for the simulation of precipitation based on spatial assessment metrics. Hydrology and Earth System Sciences 23, 48034824.CrossRefGoogle Scholar
Ali, A, Luttrell, RG and Schneider, JC (1990) Effects of temperature and larval diet on development of the fall army worm (Lepidoptera: Noctuidae). Annals of the Entomological Society of America 83, 725733.CrossRefGoogle Scholar
Bale, JS, Masters, GJ, Hodkinson, ID, Awmack, C, Bezemer, TM, Brown, VK, Butterfield, J, Buse, A, Coulson, JC and Farrar, J (2002) Herbivory in global climate change research: direct effects of rising temperature on insect herbivores. Global Change Biology 8, 116.CrossRefGoogle Scholar
Barfield, CS, Mitchell, ER and Poe, SL (1978) A temperature-dependent model for fall armyworm development. Annals of the Entomological Society of America 71, 7074.CrossRefGoogle Scholar
Bollen, KA and Jackman, RW (1990) Regression diagnostics: an expository treatment of outliers and influential cases. Modern Methods of Data Analysis 13, 257291.Google Scholar
Bueno, RCOF, Carneiro, TR, Bueno, AF, Pratissoli, D, Fernandes, OA and Vieira, SS (2010) Parasitism capacity of Telenomus remus Nixon (Hymenoptera: Scelionidae) on Spodoptera frugiperda (Smith) (Lepidoptera: Noctuidae) eggs. Brazilian Archives of Biology and Technology 53, 133139.CrossRefGoogle Scholar
Busato, GR, Grützmacher, AD, Garcia, MS, Giolo, FP, Zotti, MJ and Bandeira, JDM (2005) Exigências térmicas e estimative do número de gerações dos biótipos ‘milho’ e ‘arroz’ de Spodoptera frugiperda. Pesquisa Agropecuária Brasileira 40, 329335.CrossRefGoogle Scholar
Cammell, ME and Knight, JD (1992) Effects of climatic-change on the population dynamics of crop pests. Advances in Ecological Research 22, 117162.CrossRefGoogle Scholar
Choudhary, JS, Mali, SS, Mukherjee, D, Kumari, A, Moanaro Rao, MS, Das, B, Singh, AK and Bhatt, BP (2019) Spatio-temporal temperature variations in MarkSim multimodel data and their impact on voltinism of fruit fly, Bactrocera species on mango. Scientific Reports 9, 9708.CrossRefGoogle ScholarPubMed
Choudhary, JS, Mali, SS, Naaz, N, Mukherjee, D, Moanaro Das, B, Singh, AK, Srinivasa Rao, M and Bhatt, BP (2020) Predicting the population growth potential of Bactrocera zonata (Saunders) (Diptera: Tephritidae) using temperature development growth models and their validation in fluctuating temperature condition. Phytoparasitica 48, 113.CrossRefGoogle Scholar
Clark, PL, Molina-Ochoa S, J. Martinelli, SR, Skoda, DJ, Isenhour, DJ, Lee, JT, Krumm, and Foster, JE (2007) Population variation of the fall armyworm, Spodoptera frugiperda, in the Western Hemisphere. Journal of Insect Science 7, 110.CrossRefGoogle ScholarPubMed
Clavijo, S, Fernández, A, Ramírez, A, Delgado, A and Lathullerie, J (1991) Influencia de la temperatura sobre el desarrollo de Spodoptera frugiperda (Smith) (Lepidoptera: Noctuidae). Agronomía Tropical 41, 245256.Google Scholar
Curry, GL, Fieldman, RM and Smith, KC (1978) A stochastic model for a temperature-dependent population. Theoretical Population Biology 13, 197213.CrossRefGoogle ScholarPubMed
Du Plessis, H, Schlemmer, M-L and Van den Berg, J (2020) The effect of temperature on the development of Spodoptera frugiperda (Lepidoptera: Noctuidae). Insects 11, E228.CrossRefGoogle Scholar
Fand, BB, Sul, NT, Bal, SK and Minhas, PS (2015) Temperature impacts the development and survival of common cutworm (Spodoptera litura): simulation and visualization of potential population growth in India under warmer temperatures through life cycle modelling and spatial mapping. PLoS ONE 10, e0124682.CrossRefGoogle ScholarPubMed
Ganiger, PC, Yeshwanth, HM, Muralimohan, K, Vinay, N, Kumar, ARV and Chandrashekara, K (2018) Occurrence of the new invasive pest, fall armyworm, Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae), in the maize fields of Karnataka, India. Current Science 115, 621623.CrossRefGoogle Scholar
Gilbert, N and Raworth, D (1996) Insects and temperature: a general theory. Canadian Entomologist 128, 114.CrossRefGoogle Scholar
Goergen, G, Kumar, PL, Sankung, SB, Togola, A and Tamò, M (2016) First report of outbreaks of the fall armyworm Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae), a new alien invasive pest in West and Central Africa. PLoS ONE, 11, e0165632.CrossRefGoogle Scholar
Guang, HS, Cheng, XN and Zhang, XX (2000) Simulation on developmental and survival rate of brown plant hopper nymphs. Chinese Journal of Rice Science 14, 157160.Google Scholar
Hance, T, van Baaren, J, Vernon, P and Boivin, G (2007) Impact of extreme temperatures on parasitoids in a climate change perspective. Annual Review of Entomology 52, 107126.CrossRefGoogle Scholar
Hardev, S, Sandhu Garegg, S, Nueddly Susan, E, Webb Ronald, H and Cherry Robert Gilbert, A (2013) Temperature dependent reproductive and life table parameters of Elasmopalpus lignosellus (Lepidoptera:Pyralidae) on sugarcane. Florida Entomologist 96, 380390.Google Scholar
Heinrichs, E, Foster, J, Rice, M and Molina, J (2000) Insectos plaga del maíz en Norteamérica. University of Minnesota. Minnesota, USA. 340–341pp.Google Scholar
Her, Y, Yoo, S, Seong, C, Jeong, J, Cho, J and Hwang, S (2016) Comparison of uncertainty in multi parameter and multi model ensemble hydrologic analysis of climate change. Hydrology and Earth System Sciences Discussions 144. https://doi.org/10.5194/hess2016-160.Google Scholar
Hijmans, RJ, Cameron, SE, Parra, JL, Jones, PG and Jarvis, A (2005) Very high-resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25, 19651978.CrossRefGoogle Scholar
Hogg, DB, Pitre, HN and Anderson, RE (1982) Assessment of early-season phenology of the fall armyworm (Lepidoptera: Noctuidae) in Mississippi. Environmental Entomology 11, 705710.CrossRefGoogle Scholar
Jallow, MFA and Matsumura, M (2001) Influence of temperature on the rate of development of Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae). Applied Entomology and Zoology 36, 427430.CrossRefGoogle Scholar
Kim, DS and Lee, JH (2003) Oviposition model of Carposina sasakii (Lepidoptera: Carposinidae). Ecological Modelling 162, 145153.CrossRefGoogle Scholar
Kim, J, Ivanov, VY and Fatichi, S (2016) Climate change and uncertainty assessment over a hydroclimatic transect of Michigan. Stochastic Environmental Research and Risk Assessment 30, 923944. https://doi.org/10.1007/s00477-015-1097-2.CrossRefGoogle Scholar
Kroschel, J, Sporleder, M, Tonnang, HEZ, Juarez, H, Carhuapoma, P and Gonzales, JC (2013) Predicting climate-change-caused changes in global temperature on potato tuber moth Phthorimaea operculella (Zeller) distribution and abundance using phenology modeling and GIS mapping. Agricultural and Forest Meteorology 15, 228241.CrossRefGoogle Scholar
Marco, V, Taberner, A and Castañera, P (1997) Development and survival of immature Aubeonymus mariaefranciscae (Coleoptera: curculionidae) at constant temperatures. Annals of the Entomological Society of America 90, 169176.CrossRefGoogle Scholar
McCornack, BP, Ragsdale, DW and Venette, RC (2004) Demography of soybean aphids (Homoptera: Aphididae) at summer temperatures. Journal of Economic Entomology 97, 854861.CrossRefGoogle ScholarPubMed
Milosavljević, I, McCalla, KA, Ratkowsky, DA and Hoddle, MS (2019) Effects of constant and fluctuating temperatures on development rates and longevity of Diaphorencyrtus aligarhensis (Hymenoptera: Encyrtidae). Journal of Economic Entomology 112, 10621072.CrossRefGoogle Scholar
Montezano, DG, Specht, A, Sosa-Gómez, DR, Roque-Specht, VF, Souza Silva, JC, Peterson, JA and Hunt, TE (2018) Host plants of Spodoptera frugiperda (Lepidoptera: Noctuidae) in the Americas. African Entomology 26, 286300.CrossRefGoogle Scholar
Moss, RH, Jae, AE, Kathy, AH, Martin, RM, Steven, KR, Detlef, PV, Timothy, RC, Emori, S, Kainuma, M, Kram, T, Gerald, AM, John, FBM, Nakicenovic, N, Riahi, K, Steven, JS, Ronald, JS, Allison, MT, John, PW and Thomas, JW (2010) The next generation of scenarios for climate change research and assessment. Nature 463, 747756.CrossRefGoogle ScholarPubMed
Nagoshi, RN, Adamczyk, JJ, Meagher, J, Gore, RL and Jackson, R (2007) Using stable isotope analysis to examine fall armyworm (Lepidoptera: Noctuidae) host strains in a cotton habitat. Journal of Economic Entomology 100, 15691576.CrossRefGoogle Scholar
Padmavathi, C, Katti, G, Sailaja, V, Padmakumari, AP, Jhansilakshmi, V, Prabhakar, M and Prasad, YG (2013) Temperature thresholds and thermal requirements for the development of the rice leaf folder. Cnaphalocrocis medinalis. Journal of Insect Science 13, 96.CrossRefGoogle ScholarPubMed
Patel, HR and Shekh, AM (2006) Pest epidemics and role of meteorological services: an overview. Journal of Agrometeorology 8, 104113.Google Scholar
Patil, RA, Mehta, DM and Jat, BL (2014) Studies on life fecundity tables of Spodoptera litura Fabricius on tobacco Nicotiana tabacum Linnaeus. Entomology, Ornithology and Herpetology 3, 15.Google Scholar
Pogue, MG (2002) A world revision of the genus Spodoptera Guenee (Lepidoptera: Noctuidae). Memoirs of American Entomological Society 43, 1201.Google Scholar
Prowell, DP, McMichael, M and Silvain, JF (2004) Multilocus genetic analysis of host use, introgression, and speciation in host strains of fall armyworm (Lepidoptera: Noctuidae). Annals of the Entomological Society of America 97, 10341044.CrossRefGoogle Scholar
Rakshit, S, Ballal, CR, Prasad, YG, Sekhar, JC, Lakshmi Soujanya, P, Suby, SB, Jat, SL, Siva Kumar, G and Prasad, JV (2019) Fight Against Fall Armyworm Spodoptera frugiperda (J. E. Smith). Ludhiana, Punjab: ICAR-Indian Institute of Maize Research, pp. 52.Google Scholar
Ratkowsky, DA and Reddy, GV (2017) Empirical model with excellent statistical properties for describing temperature-dependent developmental rates of insects and mites. Annals of the Entomological Society of America 110, 302309.CrossRefGoogle Scholar
Shahout, HA, Xu, JX, Yao, XM and Jia, QD (2011) Influence and mechanism of different host plants on the growth, development and, fecundity of reproductive system of common cutworm, Spodoptera litura (Fabricius) (Lepidoptera: Noctuidae). Asian Journal of Agricultural Science 3, 291300.Google Scholar
Sharanabasappa, D, Kalleshwaraswamy, CM, Asokan, R, Mahadeva Swamy, HM, Maruthi, MS, Pavithra, HB, Hedge, K, Navi, S, Prabhu, ST and Goergen, G (2018) First report of the fall armyworm, Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae), an alien invasive pest on maize in India. Pest Management in Horticultural Ecosystems 24, 2329.Google Scholar
Sharpe, PJH, Curry, GL and DeMichele, DW (1977) Distribution models of organism development times. Journal of Theoretical Biology 66, 2138.CrossRefGoogle ScholarPubMed
Shi, P and Ge, F (2010) A comparison of different thermal performance functions describing temperature-dependent development rates. Journal of Thermal Biology 35, 225231.CrossRefGoogle Scholar
Shi, PJ, Reddy, GV, Chen, L and Ge, F (2015) Comparison of thermal performance equations in describing temperature-dependent developmental rates of insects: (I) empirical models. Annals of the Entomological Society of America 109, 211215.CrossRefGoogle Scholar
Shylesha, AN, Jalali, SK, Gupta, A, Varshney, R, Venkatesan, T, Shetty, P, Ojha, R, Ganiger, PC, Navik, O, Subaharan, K, Bakthavatsalam, N and Ballal, CR (2018) Studies on new invasive pest Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae) and its natural enemies. Journal of Biological Control 32, 17.CrossRefGoogle Scholar
Simmons, AM (1993) Fall armyworm symposium: effects of constant and fluctuating temperatures and humidities on the survival of Spodoptera frugiperda pupae (Lepidoptera: Noctuidae). Florida Entomologist 76, 333340.CrossRefGoogle Scholar
Soh, BSB, Kekeunou, S, Nanga Nanga, S, Dongmo, M and Rachid, H (2018) Effect of temperature on the biological parameters of the cabbage aphid Brevicoryne brassicae. Ecology and Evolution 8, 1181911832.CrossRefGoogle ScholarPubMed
Sporleder, M, Kroschel, J, Gutierrez Quispe, MR and Lagnaoui, A (2004) A temperature-based simulation model for the potato tuberworm, Phthorimaea operculella Zeller (Lepidoptera; Gelechiidae). Environmental Entomology 33, 477486.CrossRefGoogle Scholar
Srinivasa Rao, M and Prasad, TV (2020) Temperature based phenology model for predicting establishment and survival of Spodoptera litura (Fab.) on groundnut during climate change scenario in India. Journal of Agrometeorology 22, 2432.CrossRefGoogle Scholar
Srinivasa Rao, M, Manimanjari, D, Rama Rao, CA, Swathi, P and Maheswari, M (2014) Effect of climate change on Spodoptera litura Fab. on peanut: a life table approach. Crop Protection 66, 98106.CrossRefGoogle Scholar
Srinivasa Rao, M, Dammua, M, Sengottaiyan, V, Ongolua, S, Biradara, AK, Kondrua, VR, Srinivas, K, Murali, KRB, Rama Rao, AC and Srinivasa Rao, C (2016) Prediction of Helicoverpa armigera Hubner on pigeon pea during future climate change periods using MarkSim multimodel data. Agricultural and Forest Meteorology 228, 130138.Google Scholar
Stinner, RE, Gutierrez, AP and Butler, GD (1974) An algorithm for temperature-dependent growth rate simulation. Canadian Entomology 106, 519524.CrossRefGoogle Scholar
Swamy, HMM, Asokan, R, Kalleshwaraswamy, CM, Sharanabasappa, D, Prasad, YG, Maruthi, MS, Shashank, PR, Devi, NI, Anusha, S, Adarsha, S, Srinivas, A, Rao Srinivasa, M, Vidyasekhar, M, Shali, R, Shyam Sunder Reddy, G and Nagesh, SN (2018) Prevalence of ‘R’ strain and molecular diversity of fall army worm Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae) in India. Indian Journal of Entomology 80, 544553.CrossRefGoogle Scholar
Tonnang, EZH, Juarez, H, Carhuapoma, P, Gonzales, JC, Mendoza, D, Sporleder, M, Simon, R and Kroschel, J (2013) ILCYM – Insect Life Cycle Modeling. A software package for developing temperature-based insect phenology models with applications for local, regional and global analysis of insect population and mapping, International Potato Center, Lima, Peru, pp. 175.Google Scholar
Tshiala, MF, Botaim, JO and Olwoch, JM (2012) Leaf miner agromyzid pest distribution over Limpopo province under changing climate. African Journal of Agricultural Research 7, 65156522.Google Scholar
Tsoukanas, VI, Papadopoulos, GD, Fantinou, AA and Papadoulis, GT (2006) Temperature-dependent development and life table of Iphiseius degenerans (Acari: Phytoseiidae). Environmental Entomology 35, 212218.CrossRefGoogle Scholar
Vincent, P, Jones Carrie, HM, Lois, T and Caprio, C (1997) Life tables for the Koa seed worm (Lepidoptera: Tortricidae) based on degree-day demography. Population Ecology 26, 12911298.Google Scholar
Wagner, TL, Wu, HI, Sharpe, PJH and Coulson, RN (1984) Modeling distributions of insect development time: a literature review and application of the Weibull function. Annals of the Entomological Society of America 77, 474487.Google Scholar
Wang, R, Lan, Z and Ding, Y (1982) Studies on mathematical models of the relationship between insect development and temperature. Acta Ecologica Sinica 2, 4757.Google Scholar
Zajac, MA, Hall, FR and Wilson, MC (1989) Heat unit model for the development of meadow spittlebug (Homoptera: Cercopidae) on strawberry. Environmental Entomology 18, 347350.CrossRefGoogle Scholar
Zamani, AA, Talebi, AA, Fathipour, Y and Baniameri, V (2006) Effect of temperature on biology and population growth parameters of Aphis gossypii Glover (Homoptera: Aphididae) on greenhouse cucumber. Journal of Applied Entomology 130, 453460.CrossRefGoogle Scholar