Skip to main content

Predicting temporal shifts in the spring occurrence of overwintered Scotinophara lurida (Hemiptera: Pentatomidae) and rice phenology in Korea with climate change

Abstract

Climate change could shift the phenology of insects and plants and alter their linkage in space and time. We examined the synchrony of rice and its insect pest, Scotinophara lurida (Burmeister), under the representative concentration pathways (RCP) 8.5 climate change scenario by comparing the mean spring immigration time of overwintered S. lurida with the mean rice transplanting times in Korea. The immigration time of S. lurida was estimated using an overwintered adult flight model. The rice transplanting time of three cultivars (early, medium, and medium-late maturing) was estimated by forecasting the optimal cultivation period using leaf appearance and final leaf number models. A temperature increase significantly advanced the 99 % immigration time of S. lurida from Julian day 192.1 in the 2000s to 178.4 in the 2050s and 163.1 in the 2090s. In contrast, rice transplanting time was significantly delayed in the early-maturing cultivar from day 141.2 in the 2000s to 166.7 in the 2050s and 190.6 in the 2090s, in the medium-maturing cultivar from day 130.6 in the 2000s to 156.6 in the 2050s and 184.7 in the 2090s, and in the medium-late maturing cultivar from day 128.5 in 2000s to 152.9 in the 2050s and 182.3 in the 2090s. These simulation results predict a significant future phenological asynchrony between S. lurida and rice in Korea.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

References

  1. Allen JC (1976) A modified sine wave method for calculating degree days. Environ Entomol 5:388–396

    Article  Google Scholar 

  2. Bouman BAM, Kropff MJ, Tuong TP, Wopereis MCS, Ten Berge HFM, Van Laar HH (2001) ORYZA2000: modeling lowland rice. International rice research institute, Los Banos

    Google Scholar 

  3. Cho JR, Lee M, Kim HS, Boo KS (2007) Effect of the juvenile hormone analog, fenoxycarb on termination of reproductive diapause in Scotinophara lurida (Burmeister) (Heteroptera: Pentatomidae). J Asia Pac Entomol 10:145–150

    CAS  Article  Google Scholar 

  4. Cho JR, Lee M, Kim HS, Boo KS (2008) Effect of photoperiod and temperature on reproductive diapause of Scotinophara lurida (Burmeister) (Heteroptera: Pentatomidae). J Asia Pac Entomol 11:53–57

    Article  Google Scholar 

  5. Choi K-J, Lee J-I, Chung N-J, Yang W-H, Shin J-C (2006) Effects of temperature and day-length on heading habit of recently developed Korean rice cultivars. Korean J Crop Sci 51:41–47

    Google Scholar 

  6. Choi W, Park Y-K, Park Y-S, Ryoo M, Lee H-P (2011) Changes in voltinism in a pine moth Dendrolimus spectabilis (Lepidoptera: Lasiocampidae) population: implications of climate change. Appl Entomol Zool 46:319–325

    Article  Google Scholar 

  7. Dale D (1994) Insect pests of the rice plant—their biology and ecology. In: Heinrichs EA (ed) Biology and management of rice insects. Wiley Eastern, New Delhi

    Google Scholar 

  8. Ellis RH, Qi A, Summerfield RJ, Roberts EH (1993) Rates of leaf appearance and panicle development in rice (Oryza sativa L.): a comparison at three temperatures. Agric For Meteorol 66:129–138. doi:10.1016/0168-1923(93)90066-Q

    Article  Google Scholar 

  9. ESRI (2010) ArcGIS 10.0. Redlands, California, USA

  10. Gao LZ, Jin ZQ, Li L (1987) Photo-thermal models of rice growth duration for various varietal types in China. Agric For Meteorol 39:205–213. doi:10.1016/0168-1923(87)90038-4

    Article  Google Scholar 

  11. Gao L, Jin Z, Huang Y, Zhang L (1992) Rice clock model—a computer model to simulate rice development. Agric For Meteorol 60:1–16. doi:10.1016/0168-1923(92)90071-B

    Article  Google Scholar 

  12. Grant RF (1989) Simulation of maize phenology. Agron J 81:451–457. doi:10.2134/agronj1989.00021962008100030011x

    Article  Google Scholar 

  13. IPCC (2007) Climate change 2007: the physical science basis. Contribution of working group 1 to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, United Kingdom and New York, USA

  14. Kim H, Lee J-H (2007) Scotinophara lurida (Hemiptera: Pentatomidae) in Korea. In: Joshi RC, Barrion AT, Sebastin LS (eds) Rice black bugs: taxonomy, ecology, and management of invasive species. Philippine rice research institute, Nueva Ecija

    Google Scholar 

  15. Kim H, Lee J-H (2008) Phenology simulation model of Scotinophara lurida (Hemiptera: Pentatomidae). Environ Entomol 37:660–669. doi:10.1603/0046-225X(2008)37[660:PSMOSL]2.0.CO;2

    Article  Google Scholar 

  16. Kim H, Kim S-T, Jung M-P, Lee J-H (2007) Spatio-temporal dynamics of Scotinophara lurida (Hemiptera: Pentatomidae) in rice fields. Ecol Res 22:204–213. doi:10.1007/s11284-006-0305-4

    Article  Google Scholar 

  17. KMA (2012) Korea Meteorological Administration website. http://www.climate.go.kr

  18. Lee C-K (2008) Development and application of model for estimating grain weight and grain nitrogen content in rice. Dissertation, Seoul National University

  19. Lee C-K, Lee BW, Shin JC, Yoon YH (2001a) Heading date and final leaf number as affected by sowing date and prediction of heading date based on leaf appearance model in rice. Korean J Crop Sci 46:195–201

    Google Scholar 

  20. Lee C-K, Lee BW, Yoon YH, Shin JC (2001b) Temperature response and prediction model of leaf appearance rate in rice. Korean J Crop Sci 46:202–208

    Google Scholar 

  21. Lee K-Y, Ahn K-S, Kang H-J, Park S-K, Kim T-S (2001c) Host plants and life cycle of rice black bug, Scotinophara lurida Burmeister (Hemiptera: Pentatomidae). Korean J Appl Entomol 40:309–313

    Google Scholar 

  22. Lee C-K, Kwak K-S, Kim JH, Son J-Y, Yang W-H (2011) Impacts of climate change and follow-up cropping season shift on growing period and temperature in different rice maturity types. Korean J Crop Sci 56:233–243

    Article  Google Scholar 

  23. Matsui M (1985) Temperature dependence of flight muscle development and flight activity of overwintered adults of the rice water weevil, Lissorhoptrus oryzophilus KUSCHEL (Coleoptera: Curculionidae). Jpn J Appl Entomol Z 29:67–72. doi:10.1303/jjaez.29.67

    Article  Google Scholar 

  24. Miller BC, Foin TC, Hill JE (1993) CARICE: a rice model for scheduling and evaluating management actions. Agron J 85:938–947

    Article  Google Scholar 

  25. Olsen J, McMahon C, Hammer G (1993) Prediction of sweet corn phenology in subtropical environments. Agron J 85:410–415

    Article  Google Scholar 

  26. Patterson DT, Westbrook JK, Joyce RJV, Lingren PD, Rogasik J (1999) Weeds, insects, and diseases. Clim Chang 43:711–727

    CAS  Article  Google Scholar 

  27. R Core Team (2011) R: a language and environment for statistical computing. R foundation for statistical computing, Vienna, Austria http://www.R-project.org/

  28. Saulich AK, Musolin DL (2012) Diapause in the seasonal cycle of stink bugs (Heteroptera, Pentatomidae) from the temperate zone. Entomol Rev 92:1–26

    Article  Google Scholar 

  29. Teixeira EI, Fischer G, Van Velthuizen H, Walter C, Ewert F (2013) Global hot-spots of heat stress on agricultural crops due to climate change. Agric For Meteorol 170:206–215. doi:10.1016/j.agrformet.2011.09.002

    Article  Google Scholar 

  30. Tollenaar M, Daynard T, Hunter R (1979) Effect of temperature on rate of leaf appearance and flowering date in maize. Crop Sci 19:363–366

    Article  Google Scholar 

  31. van Asch M, van Tienderen PH, Holleman LJM, Visser ME (2007) Predicting adaptation of phenology in response to climate change, an insect herbivore example. Glob Change Biol 13:1596–1604. doi:10.1111/j.1365-2486.2007.01400.x

    Article  Google Scholar 

  32. Vergara BS, Chang TT (1985) The flowering response of the rice plant to photoperiod: a review of the literature, 4th edn. International Rice Research Institute, Los Banos

    Google Scholar 

  33. Yin X, Kropff MJ (1996) Use of the Beta function to quantify effects of photoperiod on flowering and leaf number in rice. Agric For Meteorol 81:217–228

    Article  Google Scholar 

  34. Yoshida S (1981) Fundamentals of rice crop science. International rice research institute, Los Banos

    Google Scholar 

  35. Yun J, Yi D, Choi J, Cho S, Park E, Hwang H (1999) Elevation-corrected spatial interpolation for near-real time generation of meteorological surfaces from point observations. AgroInformatics J 1:28–33

    Google Scholar 

Download references

Acknowledgments

This research was funded by grants from the Rural Development Administration (project no. PJ009394022013) and the Brain Korea 21 Plus Project.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Joon-Ho Lee.

Electronic supplementary material

ESM 1

(DOC 78 kb)

ESM 2

(DOC 40 kb)

ESM 3

(DOC 41 kb)

ESM 4

(DOC 39 kb)

ESM 5

(DOC 39 kb)

ESM 6

(DOC 39 kb)

ESM 7

(DOC 39 kb)

ESM 8

(DOC 39 kb)

ESM 9

(DOC 39 kb)

Appendix

Appendix

Table 3

Table 3 Equations and estimated parameters for the final leaf number in the main stem of rice (Lee 2008)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Lee, H., Kang, W.S., Ahn, M.I. et al. Predicting temporal shifts in the spring occurrence of overwintered Scotinophara lurida (Hemiptera: Pentatomidae) and rice phenology in Korea with climate change. Int J Biometeorol 60, 53–61 (2016). https://doi.org/10.1007/s00484-015-1004-z

Download citation

Keywords

  • RCP 8.5 scenario
  • Rice
  • Scotinophara lurida
  • Phenology
  • Asynchrony