Journal of The Korean Society of Grassland and Forage Science (한국초지조사료학회지)

The Korean Society of Grassland and Forage Science (한국초지조사료학회)
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Ensemble Projection of Climate Suitability for Alfalfa (Medicago Sativa L.) in Hamkyongbukdo

함경북도 내 미래 알팔파 재배의 기후적합도 앙상블 전망

  • Hyun Seung Min (Department of Agriculture, Forestry and Bioresources, Seoul National University) ;
  • Hyun Shinwoo (Department of Agriculture, Forestry and Bioresources, Seoul National University) ;
  • Kim Kwang Soo (Department of Agriculture, Forestry and Bioresources, Seoul National University)
  • 현승민 (서울대학교 농림생물자원학부) ;
  • 현신우 (서울대학교 농림생물자원학부) ;
  • 김광수 (서울대학교 농림생물자원학부)
  • Received : 2024.04.09
  • Accepted : 2024.06.03
  • Published : 2024.06.30
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Abstract

It would be advantageous to grow legume forage crops in order to increase the productivity and sustainability of sloped croplands in Hamkyongbukdo. In particular, the identification of potential cultivation areas for alfalfa in the given region could aid decision-making on policies and management related to forage crop production in the future. This study aimed to analyze the climate suitability of alfalfa in Hamkyongbukdo under current and future climate conditions using the Fuzzy Union model. The climate suitability predicted by the Fuzzy Union model was compared with the actual alfalfa cultivation area in the northern United States. Climate data obtained from 11 global climate models were used as input data for calculation of climate suitability in the study region to examine the uncertainty of projections under future climate conditions. The area where the climate suitability index was greater than a threshold value (22.6) explained about 44% of the variation in actual alfalfa cultivation areas by state in the northern United States. The climatic suitability of alfalfa was projected to decrease in most areas of Hamkyongbukdo under future climate scenarios. The climatic suitability in Onseong and Gyeongwon County was analyzed to be over 88 in the current climate conditions. However, it was projected to decrease by about 66% in the given areas by the 2090s. Our study illustrated that the impact of climate change on suitable cultivation areas was highly variable when different climate data were used as inputs to the Fuzzy Union model. Still, the ensemble of the climate suitability projections for alfalfa was projected to decrease considerably due to summer depression in Hamkyongbukdo. It would be advantageous to predict suitable cultivation areas by adding soil conditions or to predict the climate suitability of other leguminous crops such as hairy vetch, which merits further studies.

함경북도의 개간된 경사지의 작물 생산성과 지속 가능성을 증가시키기 위해 두과 조사료를 활용하는 것이 유리하다. 특히, 함경북도에서 두과 조사료인 알팔파를 대상으로 재배 가능지역을 파악하는 것이 미래를 대비한 사료작물 재배 관련 정책 결정에 도움이 될 수 있다. 본 연구에서는 작물의 기후적합도를 예측하는 Fuzzy Union 모형을 사용하여 현재와 미래조건에서 함경북도 내 알팔파의 기후적합도를 분석하고자 하였다. Fuzzy Union 모형으로 예측된 기후적합도와 미국 북부 지역의 실제 알팔파 재배 면적을 비교하였다. 또한, 전지구 기후모형 11종으로부터 얻어진 기후자료를 기후적합도를 계산하기 위한 입력자료로 사용하여 미래 기후변화 조건에서의 예측 불확도를 확인하였다. 미국 북부 지역을 대상으로 기후적합도의 주별 면적은 실제 알팔파 재배면적 변이의 약 44%를 설명하였다. 미래 기후조건에서 알팔파의 기후적합도는 함경북도 대부분의 지역에서 감소할 것으로 전망되었다. 예를 들어, 온성군과 경원군의 경우 현재 기후조건에서 기후적합도가 88 이상으로 분석되었지만 2090년대에 약 66%가 감소하였다. 본 연구에서 Fuzzy Union 모델을 사용하여 기후변화에 따른 알팔파 재배 적합지의 변동을 공간적으로 확인할 수 있었다. 특히, 21세기 후반에는 함경북도 지역에서 알팔파의 기후적합도가 하고현상으로 인해 크게 감소할 것으로 분석되었다. 추후에는 토양 조건을 반영하여 알팔파의 재배 적합지를 예측하고, 이와 함께 헤어리베치 등의 타 두과 사료작물의 기후적합도의 예측하는 연구가 필요할 것으로 사료되었다.

Keywords

Acknowledgement

본 연구는 농업 빅데이터 및 활용모델 통합 연계체계 개발(과제번호: RS-2022-RD010426)의 지원에 의해 수행되었습니다.

References

  1. Bak, G.R. and Lee, J.T. 2021. Effects of alfalfa cultivation on soil erosion and maize production in highland agriculture. Journal of Environmental Science International. 30(2):145-152.
  2. Balasubramanian, A. 2017. Soil erosion - causes and effects. Technical Report 10:1-7. doi:10.13140/RG.2.2.26247.39841.
  3. Barnes, D.K. and Sheaffer, C.C. 1985. Alfalfa. In: M.E. Heath, R.F. Barnes and D.S. Metcalfe (Eds.), Forages: the science of grassland agriculture - Four. Iowa State University. Press. Ames. pp.89-97.
  4. Bi, D., Dix, M., Marsland, S., O'Farrell, S., Sullivan, A., Bodman, R., Law, R., Harman, I., Srbinovsky, J., Rashid, H.A., Dobrohotoff, P., Mackallah, C., Yan, H., Hirst, A., Savita, A., Dias, F.B., Woodhouse, M., Fiedler, R. and Heerdegen, A. 2020. Configuration and spin-up of ACCESS-CM2, the new generation Australian community climate and earth system simulator coupled model. Journal of Southern Hemisphere Earth System Science. 70(1):225-251. https://doi.org/10.1071/ES19040
  5. Boucher, O., Servonnat, J., Albright, A.L., Aumont, O., Balkanski, Y., Bastrikov, V., et al. 2020. Presentation and evaluation of the IPSL-CM6A-LR climate model. Journal of Advances in Modeling Earth Systems. 12(7):e2019MS002010.
  6. Chen, J., Huang, J. and Hu, J. 2011. Mapping rice planting areas in southern China using the China Environment Satellite data. Mathematical and Computer Modelling. 54(3-4):1037-1043. https://doi.org/10.1016/j.mcm.2010.11.033
  7. Cherchi, A., Fogli, P.G., Lovato, T., Peano, D., Iovino, D., Gualdi, S., Masina, S., Scoccimarro, E., Materia, S., Bellucci, A. and Navarra, A. 2018. Global mean climate and main patterns of variability in the CMCC-CM2 Coupled Model. Journal of Advances in Modeling Earth Systems. 11(1):185-209. https://doi.org/10.1029/2018MS001369
  8. Crotty, F.V., Fychan, R., Scullion, J., Sanderson, R. and Marley, C.L. 2015. Assessing the impact of agricultural forage crops on soil biodiversity and abundance. Soil Biology and Biochemistry. 91:119-126. doi:10.1016/j.soilbio.2015.08.036.
  9. Doscher, R., Acosta, M., Alessandri, A., Anthoni, P., Arneth, A., Arsouze, T., et al. 2021. The EC-Earth3 Earth System model for the climate model intercomparison project 6. Geoscientific Model Development. 15:2973-3020. doi:10.5194/gmd-2020-446.
  10. Duke, J.A. 1981. Handbook of Legumes of World Economic Importance (2nd Ed.). Plenum Press. New York. N.Y. p. 345.
  11. Fageria, N.K. and Baligar, V.C. 2003. Fertility management of tropical acid soils for sustainable crop production. In: Z. Rengel (Ed.), Handbook of soil acidity, Marcel Dekker. Inc. New York. USA. pp. 359-385.
  12. Fick, S.E. and Hijmans, R.J. 2017. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology. 37(12):4302-4315. doi:10.1002/joc.5086
  13. GBIF. 2023. https://doi.org/10.15468/dl.qd37y7, accessed on 2023, 11, 9.
  14. Gulser, C. 2006. Effect of forage cropping treatments on soil structure and relationships with fractal dimensions. Geoderma. 131(1-2):33-44. doi:10.1016/j.geoderma.2005.03.004.
  15. Heo, D. 2008. Trends in the U.S. Forage supply: Recent imbalances and factors. World Agriculture. 97:9-24.
  16. Hong, I.P. 2003. North Korea's meteorological disasters and disaster response measures. Journal of Hydro-environment Research. 36(6):111-114.
  17. Hong, K.C., Choi, B.S., Joo, J.H. and Ok, Y.S. 2010. Soil organic matter and aggregate stability of sloping uplands in Gangwon Province, Korea. Journal of Agricultural, Life and Environmental Sciences. 22:19-24.
  18. Jeong, S.T., Jang, K.C., Hong, S.K. and Kang, S.K. 2011. Detection of irrigation timing and the mapping of paddy cover in Korea using MODIS images data. Korean Journal of Agricultural and Forest Meteorology. 13(2):69-78. https://doi.org/10.5532/KJAFM.2011.13.2.069
  19. Jo, S., Lee, J.L., Shim, K.M., Ahn, J.B., Hur, J., Kim, Y.S., Choi, W.J. and Kang, M. 2022. The advanced bias correction method based on quantile mapping for long-range ensemble climate prediction for improved applicability in the agriculture field. Korean Journal of Agricultural and Forest Meteorology. 24(3):155-163.
  20. Joh, Y.S., Hyun, S.W. and Kim, K.S. 2023. Comparison between uncertainties of cultivar parameter estimates obtained using error calculation methods for forage rice Cultivars. Korean Journal of Agricultural and Forest Meteorology. 25(3):129-141.
  21. Kang, M., Hyun, S. and Kim, K.S. 2022. Spatial assessment of climate suitability for summer cultivation of potato in North Korea. Korean Journal of Agricultural and Forest Meteorology. 24(1):35-47. doi:10.5532/KJAFM.2022.24.1.35
  22. Kelly, M., Schmidt, G.A., Nazarenko, L.S., Bauer, S.E., Ruedy, R., Russell, G.L., et al. 2020. GISS-E2.1: Configurations and climatology. Journal of Advances in Modeling Earth Systems. 12(8):e2019MS002025.
  23. Kim, D.J., Kim, J.H., Roh, J.H. and Yun, J.I. 2012. Geographical migration of winter barley in the Korean Peninsula under the RCP 8.5 projected climate condition. Korean Journal of Agricultural and Forest Meteorology. 14(4):161-169. https://doi.org/10.5532/KJAFM.2012.14.4.161
  24. Kim, H., Hyun, S.W., Hoogenboom, G., Porter, C.H. and Kim K.S. 2018. Fuzzy union to assess climate suitability of annual Ryegrass (Lolium multiflorum), Alfalfa (Medicago sativa) and Sorghum (Sorghum bicolor). Scientific Report. 8(1):10220.
  25. Kim, H.A., Hyun, S.W. and Kim, K.S. 2014. A study on the prediction of suitability change of forage crop Italian ryegrass (Lolium multiflorum L.) using spatial distribution model. Korean Journal of Agricultural and Forest Meteorology. 16(2):103-113. https://doi.org/10.5532/KJAFM.2014.16.2.103
  26. Kim, J.Y., Kim, M.J., Jo, H.W., Lee, B.H., Jo, M.H., Kim, B.W. and Sung, K.I. 2021. Assessment of contribution of climate and soil factors on alfalfa yield by yield prediction model. Journal of The Korean Society of Grassland and Forage Science. 41(1):47-55. doi:10.5333/kgfs.2021.41.1.47
  27. Kim, S.W., Seo, Y.H., Choi, Y.B., Ahn, M.S. and Kang, A.S. 2011. Effect of mixed sowing of hairy vetch and rye on green manure yield in mountainous highland. Korean Journal of Soil Science and Fertilizer. 44(3):442-447. https://doi.org/10.7745/KJSSF.2011.44.3.442
  28. Kim, T.H. and Kim, B.H. 1994. Changes in protein contents and activities of proteolytic enzymes in Medicago sativa during regrowth. Journal of Plant Biology. 37(3):357-363.
  29. Kim, Y.H. and Lee, B.O. 2002. Cultivator's crop selection and uncertainty (in Korean with English abstract). Journal of Social Science. 41:41-54.
  30. Kim. M.T., Lee, Y.H., Jeon, W.T., Kim, S.J., Yun, D.H., Ku, J.H., Song, H.N., Lee, H.B., Seo, M.C. and Kang, H.W. 2013. Effects of water-soaking and mechanical and chemical scarifications on seed germination of hairy vetch (Vicia villosa Roth). Korean Journal of Soil Science and Fertilizer. 46(1):49-52. https://doi.org/10.7745/KJSSF.2013.46.1.049
  31. Kim. Y.H., Choi, Y.H. and Lee, S.A. 2021. FAO's food supply outlook for North Korea in 2020/21. KERI North Korean Agricultural Trends. 23(1):162.
  32. Lee, J.H., Lee, G.J., Park, C.S., Hwang, S.W. and Yeoung, Y.R. 2005. Effect of hairy vetch (Vicia villosa Roth) sod culture on reducing soil loss and providing nitrogen for Chinese cabbage in highland. Korean Journal of Soil Science and Fertilizer. 38(5):72-78.
  33. Lee, M.B., Han, U., Kim, N.S., Han, J.Y. and Shin, K.H. 2003. Analysis on the spatial characteristics caused by the cropland increase using multitemporal landsat images in lower reach of Duman River, Northeast Korea. Journal of the Korean Geographical Society. 38(4):630-639.
  34. Lee, M.B., Kim, N.S., Kang, C.S., Shin, K.H., Choe, H.S. and Han, U. 2003. Estimation of soil loss due to cropland increase in Hoeryeung, Northeast Korea. Journal of The Korean Association of Regional Geographers. 9(3):373-384.
  35. Lee, M.K., Chun, J.H. and Lee, C.B. 2021. Prediction of distribution changes of Carpinus laxiflora and C. tschonoskii based on climate change scenarios using MaxEnt model. Korean Journal of Agricultural and Forest Meteorology. 23(1):55-67.
  36. Lee, S.A., Lee, S.H., Ji, S.Y. and Choi, J.Y. 2016. Predicting change of suitable plantation of Schisandra chinensis with ensemble of climate change scenario. Journal of Environmental Impact Assessment. 25(1):77-87. https://doi.org/10.14249/eia.2016.25.1.77
  37. Liebman, M., Graef, R.L., Nettleton, D. and Cambardella, C.A. 2012. Use of legume green manures as nitrogen sources for corn production. Renewable Agriculture and Food Systems. 27(3):180-191. https://doi.org/10.1017/S1742170511000299
  38. Martre, P., Wallach, D., Asseng, S., Ewert, F., Jones, J.W., Rotter, R.P., et al. 2015. Multimodel ensembles of wheat growth: Many models are better than one. Global Change Biology. 21(2):911-925. https://doi.org/10.1111/gcb.12768
  39. Mauritsen, T., Bader, J., Becker, T., Behrens, J., Bittner, M., Brokopf, R., et al. 2019. Developments in the MPI-M earth system model version 1.2 (MPI-ESM1.2) and its response to increasing CO2. Journal of Advances in Modeling Earth Systems. 11(4):998-1038. https://doi.org/10.1029/2018MS001400
  40. Park, C.H. and You, J.S. 2009. Investigation of North Korea's forest degradation using remote sensing. Journal of Environmental Studies. 48:3-24.
  41. Park, H.B., Lee, Y.J. and Park, S.Y. 2023. Satellite-based cabbage and radish yield prediction using deep learning in Gangwon-do. Korean Journal of Remote Sensing. 39(5):1031-1042.
  42. Park. C.S., Jung, Y.S., Joo, J.H. and Lee, J.T. 2005. Best management practices reducing soil loss in the Saprolite piled upland in Hongcheon highland. Korean Society of Soil Science and Fertilizer. 38(3):119-126.
  43. Pessotto, M.V., Roberts, T.L., Bertucci, M., dos Santos, C., Ross, J. and Savin, M. 2023. Determining cardinal temperatures for eight cover crop species. Agrosystems, Geosciences & Environment. 6(3):e20393.
  44. Pimental, D. and Kounang, N. 1998. Ecology of soil erosion in ecosystems. Ecosystems. 1:416-426. https://doi.org/10.1007/s100219900035
  45. Ramirez-Villegas, J., Jarvis, A. and Laderach, P. 2013. Empirical approaches for assessing impacts of climate change on agriculture: The EcoCrop model and a case study with grain sorghum. Agricultural and Forest Meteorology. 170:67-78. doi:10.1016/j.agrformet.2011.09.005
  46. Randall, D.A., Wood, R.A., Bony, S., Colman, R., Fichefet, T., Fyfe, J., Kattsov, V., Pitman, A., Shukla, J., Srinivasan, J., Stouffer, R.J., Sumi, A. and Taylor, K.E. 2007. Cilmate models and their evaluation. In: S. Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (Eds.), Climate change 2007: The physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press. Cambridge. United Kingdom and New York. NY. USA.
  47. Roh. G.G., Lee, J.G., Choi, J.W. and Han, S.W. 2001. A study on the agricultural production base in North Korea, p. 144.
  48. Ryoo, J.W. 2008. Growth characteristics and green manure productivities of hairy vetch and woolly pod vetch under different sowing seasons in the highland area. Korean Journal of Organic Agriculture. 16(4):409-420.
  49. Sellar, A.A., Jones, C.G., Mulcahy, J., Tang, Y., Yool, A., Wiltshire, A., et al. 2019. UKESM1: Description and evaluation of the UK earth system model. Journal of Advances in Modeling Earth Systems. 11(12):4513-4558. https://doi.org/10.1029/2019MS001739
  50. Seo, J.H., Lee, H.J. and Heo, I.B. 2000. Comparisons of chemical composition and forage yield among winter green manure crops. The Korean Society of Grassland and Forage Science. 20(3):193-198.
  51. Seo, J.H., Park, J.Y. and Song, D.Y. 2005. Effect of cover crop hairy vetch on prevention of soil erosion and reduction of nitrogen fertilization in sloped upland. Korean Journal of Soil Science and Fertilizer. 38(3):134-141.
  52. Shewmaker, G.E., Allen, R.G. and Neibling, W.H., 2013. Alfalfa irrigation and drought. University of Idaho, College of Agricultural and Life Sciences: Moscow. ID. USA.
  53. Suh, M.S., Oh, S.G., Lee, D.K., Cha, D.H., Choi, S.J., Jin, C.S. and Hong, S.Y. 2012. Development of new ensemble methods based on the performance skills of regional climate models over South Korea. Journal of Climate. 25:7067-7085. https://doi.org/10.1175/JCLI-D-11-00457.1
  54. Tatebe, H., Ogura, T., Nitta, T., Komuro, Y., Ogochi, K., Takemura, T., et al. 2019. Description and basic evaluation of simulated mean state, internal variability, and climate sensitivity in MIROC6. Geoscientific Model Development. 12(7):2727-2765. https://doi.org/10.5194/gmd-12-2727-2019
  55. Undersander, D.J., Vassalotti, P. and Cosgrove, D. 1997. Alfalfa germination & growth (Vol. 3681). University of Wisconsin-Extension. Cooperative Extension. p. 22.
  56. Utomo, M., Frye, W.W. and Bevins, R.L. 1990. Sustaining soil nitrogen for corn using hairy vetch cover crop. Agronomy Journal. 82(5):979-983. https://doi.org/10.2134/agronj1990.00021962008200050028x
  57. Volodin, E. and Gritsun, A. 2018. Simulation of observed climate changes in 1850-2014 with climate model INM-CM5. Earth System Dynamics. 9(4):1235-1242. https://doi.org/10.5194/esd-9-1235-2018
  58. Wu, T., Lu, Y., Fang, Y., Xin, X., Li, L., Li, W., et al. 2019. The Beijing climate center climate system model (BCC-CSM): The main progress from CMIP5 to CMIP6. Geoscientific Model Development. 12(4):1573-1600. https://doi.org/10.5194/gmd-12-1573-2019
  59. Yoon, S.T. and Lee, J.H. 2006. Crop cultivation and climate characteristics of different agricultural zone in North Korea. The Journal of the Korean Society of International Agriculture. 18(1):7-16.
  60. Yukimoto, S., Kawai, H., Koshiro, T., Oshima, N., Yoshida, K., Urakawa, S., et al. 2019. The meteorological research institute earth system model version 2.0(MRI-ESM2.0): Description and basic evaluation of the physical component. Journal of the Meteorological Society of Japan. 97(5):931-965. https://doi.org/10.2151/jmsj.2019-051