IDEAS home Printed from https://ideas.repec.org/a/spr/climat/v131y2015i2p259-272.html
   My bibliography  Save this article

Simulation of climatic change impact on crop-pest interactions: a case study of rice pink stem borer Sesamia inferens (Walker)

Author

Listed:
  • Selvaraj Krishnan
  • Subhash Chander

Abstract

As climatic change impacts would depend upon complex interactions between climatic and biological factors, crop simulation models would play an important role in predicting such an impact. Present study thus aimed at simulating climatic change impacts on crop-pest interactions through a coupled crop-pest model. Based on temperature-dependent development of pink stem borer, Sesamia inferens (Walker) at six constant temperatures viz., 18, 21, 24, 27, 30, 33 and 35 ± 1 °C, thermal constants for eggs, larvae and pupae were determined as 47.6, 700 and 166.7° days, respectively through a linear model with corresponding lower development thresholds being 13.8, 10.6 and 12.7 °C. Besides, optimum temperature and upper developmental threshold, respectively were found to be 34.6 and 36.2 °C for eggs, 34.5 and 36.4 °C for larvae, and 31.7 and 37.0 °C for pupae of the pink stem borer through a non-linear model. Based on the thermal requirements, and biotic and abiotic mortalities, a mechanistic holometabolous population simulation model for S. inferens was developed and coupled to InfoCrop-rice model. This coupled InfoCrop model could satisfactorily simulate the PSB dynamics and crop-pest interactions. Validated model was used to simulate the impacts of climatic change on S. inferens population and rice crop in accordance with four ‘standard special report on emissions scenarios’, A1, A2, B1 and B2. Simulations revealed that S. inferens population would decline to the extent of 5.82–22.8 % by 2020 and 19.0–42.7 % by 2050 under Delhi conditions. Following decline in pest population, S. inferens induced yield losses also revealed a declining trend under changed climate. The coupled crop-pest model can be easily adapted to diverse agro-environments and applied to simulate the pest dynamics and crop losses under location-specific situations. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Selvaraj Krishnan & Subhash Chander, 2015. "Simulation of climatic change impact on crop-pest interactions: a case study of rice pink stem borer Sesamia inferens (Walker)," Climatic Change, Springer, vol. 131(2), pages 259-272, July.
    • Handle: RePEc:spr:climat:v:131:y:2015:i:2:p:259-272
    DOI: 10.1007/s10584-015-1385-3
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10584-015-1385-3
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10584-015-1385-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Aggarwal, P.K. & Banerjee, B. & Daryaei, M.G. & Bhatia, A. & Bala, A. & Rani, S. & Chander, S. & Pathak, H. & Kalra, N., 2006. "InfoCrop: A dynamic simulation model for the assessment of crop yields, losses due to pests, and environmental impact of agro-ecosystems in tropical environments. II. Performance of the model," Agricultural Systems, Elsevier, vol. 89(1), pages 47-67, July.
    2. Pinnschmidt, H. O. & Batchelor, W. D. & Teng, P. S., 1995. "Simulation of multiple species pest damage in rice using CERES-rice," Agricultural Systems, Elsevier, vol. 48(2), pages 193-222.
    3. Kropff, M. J. & Teng, P. S. & Rabbinge, R., 1995. "The challenge of linking pest and crop models," Agricultural Systems, Elsevier, vol. 49(4), pages 413-434.
    4. M. Sujithra & Subhash Chander, 2013. "Simulation of rice brown planthopper, Nilaparvata lugens (Stal.) population and crop-pest interactions to assess climate change impact," Climatic Change, Springer, vol. 121(2), pages 331-347, November.
    5. Aggarwal, P.K. & Kalra, N. & Chander, S. & Pathak, H., 2006. "InfoCrop: A dynamic simulation model for the assessment of crop yields, losses due to pests, and environmental impact of agro-ecosystems in tropical environments. I. Model description," Agricultural Systems, Elsevier, vol. 89(1), pages 1-25, July.
    6. Maximilian Auffhammer & V. Ramanathan & Jeffrey Vincent, 2012. "Climate change, the monsoon, and rice yield in India," Climatic Change, Springer, vol. 111(2), pages 411-424, March.
    7. Terry L. Root & Jeff T. Price & Kimberly R. Hall & Stephen H. Schneider & Cynthia Rosenzweig & J. Alan Pounds, 2003. "Fingerprints of global warming on wild animals and plants," Nature, Nature, vol. 421(6918), pages 57-60, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. M. Sujithra & Subhash Chander, 2013. "Simulation of rice brown planthopper, Nilaparvata lugens (Stal.) population and crop-pest interactions to assess climate change impact," Climatic Change, Springer, vol. 121(2), pages 331-347, November.
    2. Kattarkandi Byjesh & Soora Kumar & Pramod Aggarwal, 2010. "Simulating impacts, potential adaptation and vulnerability of maize to climate change in India," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 15(5), pages 413-431, June.
    3. Fargue-Lelièvre, A. & Le Cœur, D. & Baudry, J., 2011. "Integrating farming techniques in an ecological matrix model: Implementation on the primrose (Primula vulgaris)," Ecological Modelling, Elsevier, vol. 222(4), pages 1002-1015.
    4. Sulav Paudel & Lalit P. Sah & Mukti Devkota & Vijaya Poudyal & P.V. Vara Prasad & Manuel R. Reyes, 2020. "Conservation Agriculture and Integrated Pest Management Practices Improve Yield and Income while Reducing Labor, Pests, Diseases and Chemical Pesticide Use in Smallholder Vegetable Farms in Nepal," Sustainability, MDPI, vol. 12(16), pages 1-16, August.
    5. Singh, P. & Aggarwal, P. K. & Bhatia, V. S. & Murty, M. V. R. & Pala, M. & Oweis, T. & Benli, B. & Rao, K. P. C. & Wani, S. P., 2009. "Yield gap analysis: modelling of achievable yields at farm level," IWMI Books, Reports H041995, International Water Management Institute.
    6. K. Viswanath & P. Sinha & S. Naresh Kumar & Taru Sharma & Shalini Saxena & Shweta Panjwani & H. Pathak & Shalu Mishra Shukla, 2017. "Simulation of leaf blast infection in tropical rice agro-ecology under climate change scenario," Climatic Change, Springer, vol. 142(1), pages 155-167, May.
    7. Kalra, Naveen & Chakraborty, Debashis & Ramesh Kumar, P. & Jolly, Monica & Sharma, P.K., 2007. "An approach to bridging yield gaps, combining response to water and other resource inputs for wheat in northern India, using research trials and farmers' fields data," Agricultural Water Management, Elsevier, vol. 93(1-2), pages 54-64, October.
    8. Faramarzi, Monireh & Yang, Hong & Schulin, Rainer & Abbaspour, Karim C., 2010. "Modeling wheat yield and crop water productivity in Iran: Implications of agricultural water management for wheat production," Agricultural Water Management, Elsevier, vol. 97(11), pages 1861-1875, November.
    9. Mohammed Khalil Mellal & Rassim Khelifa & Abdelmadjid Chelli & Naima Djouadi & Khodir Madani, 2023. "Combined Effects of Climate and Pests on Fig ( Ficus carica L.) Yield in a Mediterranean Region: Implications for Sustainable Agricultural Strategies," Sustainability, MDPI, vol. 15(7), pages 1-12, March.
    10. Dhakar, Rajkumar & Sehgal, Vinay Kumar & Chakraborty, Debasish & Sahoo, Rabi Narayan & Mukherjee, Joydeep & Ines, Amor V.M. & Kumar, Soora Naresh & Shirsath, Paresh B. & Roy, Somnath Baidya, 2022. "Field scale spatial wheat yield forecasting system under limited field data availability by integrating crop simulation model with weather forecast and satellite remote sensing," Agricultural Systems, Elsevier, vol. 195(C).
    11. Verma, Amit Kumar & Garg, Pradeep Kumar & Prasad, K.S. Hari & Dadhwal, Vinay Kumar, 2023. "Variety-specific sugarcane yield simulations and climate change impacts on sugarcane yield using DSSAT-CSM-CANEGRO model," Agricultural Water Management, Elsevier, vol. 275(C).
    12. Naresh Soora & P. Aggarwal & Rani Saxena & Swaroopa Rani & Surabhi Jain & Nitin Chauhan, 2013. "An assessment of regional vulnerability of rice to climate change in India," Climatic Change, Springer, vol. 118(3), pages 683-699, June.
    13. Dubey, Rachana & Pathak, Himanshu & Chakrabarti, Bidisha & Singh, Shivdhar & Gupta, Dipak Kumar & Harit, R.C., 2020. "Impact of terminal heat stress on wheat yield in India and options for adaptation," Agricultural Systems, Elsevier, vol. 181(C).
    14. Tapendra Kumar Srivastava & Pushpa Singh & Ram Ratan Verma, 2022. "Weather variability trends in Gangetic plains of Uttar Pradesh, India: influence on cropping systems and adaptation strategies," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(3), pages 3588-3618, March.
    15. Tiecheng Bai & Nannan Zhang & Youqi Chen & Benoit Mercatoris, 2019. "Assessing the Performance of the WOFOST Model in Simulating Jujube Fruit Tree Growth under Different Irrigation Regimes," Sustainability, MDPI, vol. 11(5), pages 1-16, March.
    16. Shirsath, Paresh B. & Aggarwal, P.K. & Thornton, P.K. & Dunnett, A., 2017. "Prioritizing climate-smart agricultural land use options at a regional scale," Agricultural Systems, Elsevier, vol. 151(C), pages 174-183.
    17. Alobid, Mohannad & István, Szűcs, 2019. "Evaluation Of Crop And Irrigation Water Requirements For Some Selected Crops In Apulia Region -Southern Italy," APSTRACT: Applied Studies in Agribusiness and Commerce, AGRIMBA, vol. 13(3-4), December.
    18. Jha, Brajesh & Tripathi, Amarnath, 2011. "Isn’t Climate Change Affecting Wheat Productivity in India?," Indian Journal of Agricultural Economics, Indian Society of Agricultural Economics, vol. 66(3), pages 1-12.
    19. Paresh B. Shirsath & Vinay Kumar Sehgal & Pramod K. Aggarwal, 2020. "Downscaling Regional Crop Yields to Local Scale Using Remote Sensing," Agriculture, MDPI, vol. 10(3), pages 1-14, March.
    20. Trnka, M. & Muška, F. & Semerádová, D. & Dubrovský, M. & Kocmánková, E. & Žalud, Z., 2007. "European Corn Borer life stage model: Regional estimates of pest development and spatial distribution under present and future climate," Ecological Modelling, Elsevier, vol. 207(2), pages 61-84.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:climat:v:131:y:2015:i:2:p:259-272. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.