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Influences of agricultural phenology dynamic on land surface biophysical process and climate feedback

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Abstract

Response and feedback of land surface process to climate change is one of the research priorities in the field of geoscience. The current study paid more attention to the impacts of global change on land surface process, but the feedback of land surface process to climate change has been poorly understood. It is becoming more and more meaningful under the framework of Earth system science to understand systematically the relationships between agricultural phenology dynamic and biophysical process, as well as the feedback on climate. In this paper, we summarized the research progress in this field, including the fact of agricultural phenology change, parameterization of phenology dynamic in land surface progress model, the influence of agricultural phenology dynamic on biophysical process, as well as its feedback on climate. The results showed that the agriculture phenophase, represented by the key phenological phases such as sowing, flowering and maturity, had shifted significantly due to the impacts of climate change and agronomic management. The digital expressions of land surface dynamic process, as well as the biophysical process and atmospheric process, were improved by coupling phenology dynamic in land surface model. The agricultural phenology dynamic had influenced net radiation, latent heat, sensible heat, albedo, temperature, precipitation, circulation, playing an important role in the surface energy partitioning and climate feedback. Considering the importance of agricultural phenology dynamic in land surface biophysical process and climate feedback, the following research priorities should be stressed: (1) the interactions between climate change and land surface phenology dynamic; (2) the relations between agricultural phenology dynamic and land surface reflectivity at different spectrums; (3) the contributions of crop physiology characteristic changes to land surface biophysical process; (4) the regional differences of climate feedbacks from phenology dynamic in different climate zones. This review is helpful to accelerate understanding of the role of agricultural phenology dynamic in land surface process and climate feedback.

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References

  • Aisawi K A B, Reynolds M P, Singh R P et al., 2015. The physiological basis of the genetic progress in yield potential of CIMMYT spring wheat cultivars from 1966 to 2009. Crop Science, 55(4): 1749–1764.

    Article  Google Scholar 

  • Asseng S, Ewert F, Rosenzweig C et al., 2013. Uncertainty in simulating wheat yields under climate change. Nature Climate Change, 3(9): 827–832.

    Article  Google Scholar 

  • Bagley J E, Desai A R, Dirmeyer P A et al., 2012. Effects of land cover change on moisture availability and potential crop yield in the world’s breadbaskets. Environmental Research Letters, 7(1): 014009. doi: 10.1088/1748-9326/1087/1081/014009.

    Article  Google Scholar 

  • Bagley J E, Miller J, Bernacchi C J, 2015. Biophysical impacts of climate-smart agriculture in the Midwest United States. Plant Cell and Environment, 38(9): 1913–1930.

    Article  Google Scholar 

  • Bali M, Collins D, 2015. Contribution of phenology and soil moisture to atmospheric variability in ECHAM5/JSBACH model. Climate Dynamics, 45(9): 2329–2336.

    Article  Google Scholar 

  • Balota M, William A P, Evett S R et al., 2008. Morphological and physiological traits associated with canopy temperature depression in three closely related wheat lines. Crop Science, 48(5): 1897–1910.

    Article  Google Scholar 

  • Betts R A, 2005. Integrated approaches to climate-crop modelling: Needs and challenges. Philosophical Transactions of the Royal Society B: Biological Sciences, 360(1463): 2049–2065.

    Article  Google Scholar 

  • Bondeau A, Smith P C, Zaehle S et al., 2007. Modelling the role of agriculture for the 20th century global terrestrial carbon balance. Global Change Biology, 13(3): 679–706.

    Article  Google Scholar 

  • Bright R M, Zhao K, Jackson R B et al., 2015. Quantifying surface albedo and other direct biogeophysical climate forcings of forestry activities. Global Change Biology, 21(9): 3246–3266.

    Article  Google Scholar 

  • Chang K H, Warland J S, Bartlett P A et al., 2014. A simple crop phenology algorithm in the land surface model CN-CLASS. Agronomy Journal, 106(1): 297–308.

    Article  Google Scholar 

  • Chen F, Xie Z, 2011. Effects of crop growth and development on land surface fluxes. Advances in Atmospheric Sciences, 28(4): 927–944.

    Article  Google Scholar 

  • Chen M, Griffis T J, Baker J et al., 2015. Simulating crop phenology in the Community Land Model and its impact on energy and carbon fluxes. Journal of Geophysical Research: Biogeosciences, 120(2): 310–325.

    Google Scholar 

  • Chen Xiaoqiu, Wang Linhai, 2009. Progress in remote sensing phenological research. Progress in Geography, 28(1): 33–40. (in Chinese)

    Google Scholar 

  • Chmielewski F M, Müller A, Bruns E, 2004. Climate changes and trends in phenology of fruit trees and field crops in Germany, 1961–2000. Agricultural and Forest Meteorology, 121(1/2): 69–78.

    Article  Google Scholar 

  • Dai Junhu, Wang Huanjiong, Ge Quansheng, 2013. Changes of spring frost risks during the flowering period of woody plants in temperate monsoon area of China over the past 50 years. Acta Geographica Sinica, 68(5): 593–601. (in Chinese)

    Google Scholar 

  • de Beurs K M, Henebry G M, 2004. Land surface phenology, climatic variation, and institutional change: Analyzing agricultural land cover change in Kazakhstan. Remote Sensing of Environment, 89(4): 497–509.

    Article  Google Scholar 

  • de Noblet-Ducoudre N, Gervois S, Ciais P et al., 2004. Coupling the Soil-Vegetation-Atmosphere-Transfer Scheme ORCHIDEE to the agronomy model STICS to study the influence of croplands on the European carbon and water budgets. Agronomie, 24(6/7): 397–407.

    Article  Google Scholar 

  • Erb K H, Luyssaert S, Meyfroidt P et al., 2016. Land management: Data availability and process understanding for global change studies. Global Change Biology, 23(2): 512–533.

    Article  Google Scholar 

  • Eyshi Rezaei E, Siebert S, Ewert F, 2017. Climate and management interaction cause diverse crop phenology trends. Agricultural and Forest Meteorology, 233: 55–70.

    Article  Google Scholar 

  • Fan Deqin, Zhao Xuesheng, Zhu Wenquan et al., 2016. Review of influencing factors of accuracy of plant phenology monitoring based on remote sensing data. Progress in Geography, 35(3): 304–319. (in Chinese)

    Article  Google Scholar 

  • Garnaud C, Sushama L, 2015. Biosphere-climate interactions in a changing climate over North America. Journal of Geophysical Research: Atmospheres, 120(3): 1091–1108.

    Google Scholar 

  • Ge Q S, Wang H J, Zheng J Y et al., 2014. A 170 year spring phenology index of plants in eastern China. Journal of Geophysical Research: Biogeosciences, 119(3): 301–311.

    Google Scholar 

  • Ge Quanshen, Dai Junhu, Zheng Jingyun, 2010. The Progress of phenology studies and challenges to modern phenology research in China. Bulletin of Chinese Academy of Sciences, 25(3): 310–316. (in Chinese)

    Google Scholar 

  • Gervois S, de Noblet-Ducoudre N, Viovy N et al., 2004. Including croplands in a global biosphere model: Methodology and evaluation at specific sites. Earth Interactions, 18: GB1009. doi: 10.1029/2003GB002108.

    Google Scholar 

  • Gilmore E C, Rogers J S, 1958. Heat units as a method of measuring maturity in corn. Agronomy Journal, 50(10): 611–615.

    Article  Google Scholar 

  • Guillevic P, Koster R D, Suarez M J et al., 2002. Influence of the interannual variability of vegetation on the surface energy balance: A global sensitivity study. Journal of Hydrometeorology, 3(6): 617–629.

    Article  Google Scholar 

  • Hammerle A, Haslwanter A, Tappeiner U et al., 2008. Leaf area controls on energy partitioning of a temperate mountain grassland. Biogeosciences, 5(2): 421–431.

    Article  Google Scholar 

  • Jackson B M, Wheater H S, Mcintyre N R et al., 2008. The impact of upland land management on flooding: Insights from a multiscale experimental and modelling programme. Journal of Flood Risk Management, 1(2): 71–80.

    Article  Google Scholar 

  • Jeong S J, Ho C H, Jeong J H, 2009. Increase in vegetation greenness and decrease in springtime warming over east Asia. Geophysical Research Letters, 36(2): L02710. doi: 10.1029/2008GL036583.

    Article  Google Scholar 

  • Jeong S J, Ho C H, Piao S et al., 2014. Effects of double cropping on summer climate of the North China Plain and neighbouring regions. Nature Clim. Change, 4(7): 615–619.

    Article  Google Scholar 

  • Koester R P, Nohl B M, Diers B W et al., 2016. Has photosynthetic capacity increased with 80 years of soybean breeding? An examination of historical soybean cultivars. Plant Cell and Environment, 39(5): 1058–1067.

    Article  Google Scholar 

  • Korner C, Basler D, 2010. Phenology under global warming. Science, 327(5972): 1461–1462.

    Article  Google Scholar 

  • Kowalczyk E A, Stevens L E, Law R M et al., 2016. The impact of changing the land surface scheme in ACCESS(v1.0/1.1) on the surface climatology. Geoscientific Model Development, 9(8): 2771–2791.

    Article  Google Scholar 

  • Kumudini S, Andrade F H, Boote K J et al., 2014. Predicting maize phenology: Intercomparison of functions for developmental response to temperature. Agronomy Journal, 106(6): 2087–2097.

    Article  Google Scholar 

  • Leff B, Ramankutty N, Foley J A, 2004. Geographic distribution of major crops across the world. Global Biogeochemical Cycles, 18(1): GB1009. doi: 10.1029/2003GB002108

    Article  Google Scholar 

  • Lei H, Yang D, Lokupitiya E et al., 2010. Coupling land surface and crop growth models for predicting evapotranspiration and carbon exchange in wheat-maize rotation croplands. Biogeosciences, 7(10): 3363–3375.

    Article  Google Scholar 

  • Levis S, Bonan G B, Kluzek E et al., 2012. Interactive crop management in the Community Earth System Model (CESM1): Seasonal influences on land-atmosphere fluxes. Journal of Climate, 25(14): 4839–4859.

    Article  Google Scholar 

  • Liu F S, Tao F L, Liu J Y et al., 2016. Effects of land use/cover change on land surface energy partitioning and climate in Northeast China. Theoretical and Applied Climatology, 123(1/2): 141–150.

    Article  Google Scholar 

  • Liu J Y, Shao Q Q, Yan X D et al., 2016. The climatic impacts of land use and land cover change compared among countries. Journal of Geographical Sciences, 26(7): 889–903.

    Article  Google Scholar 

  • Lobell D B, Bala G, Duffy P B, 2006. Biogeophysical impacts of cropland management changes on climate. Geophysical Research Letters, 33(6): L06708. doi: 10.1029/2005GL025492.

    Article  Google Scholar 

  • Lokupitiya E, Denning S, Paustian K et al., 2009. Incorporation of crop phenology in Simple Biosphere Model (SiBcrop) to improve land-atmosphere carbon exchanges from croplands. Biogeosciences, 6(6): 969–986.

    Article  Google Scholar 

  • Luyssaert S, Jammet M, Stoy P C et al., 2014. Land management and land-cover change have impacts of similar magnitude on surface temperature. Nature Climate Change, 4(5): 389–393.

    Article  Google Scholar 

  • McGuire A D, Chapin F S, Walsh J E et al., 2006. Integrated regional changes in arctic climate feedbacks: Implications for the global climate system. Annual Review of Environment and Resources, 31: 61–91.

    Article  Google Scholar 

  • Mirschel W, Wenkel K O, Schultz A et al., 2005. Dynamic phenological model for winter rye and winter barley. European Journal of Agronomy, 23(2): 123–135.

    Article  Google Scholar 

  • Morin X, Lechowicz M J, Augspurger C et al., 2009. Leaf phenology in 22 North American tree species during the 21st century. Global Change Biology, 15(4): 961–975.

    Article  Google Scholar 

  • Mueller N D, Butler E E, McKinnon K A et al., 2016. Cooling of US Midwest summer temperature extremes from cropland intensification. Nature Climate Change, 6(3): 317–324.

    Article  Google Scholar 

  • Oguntunde P G, van de Giesen N, 2004. Crop growth and development effects on surface albedo for maize and cowpea fields in Ghana, West Africa. International Journal of Biometeorology, 49(2): 106–112.

    Article  Google Scholar 

  • Olesen J E, Borgesen C D, Elsgaard L et al., 2012. Changes in time of sowing, flowering and maturity of cereals in Europe under climate change. Food Additives and Contaminants Part A: Chemistry Analysis Control Exposure & Risk Assessment, 29(10): 1527–1542.

    Article  Google Scholar 

  • Osborne T M, Lawrence D M, Challinor A J et al., 2007. Development and assessment of a coupled crop-climate model. Global Change Biology, 13(1): 169–183.

    Article  Google Scholar 

  • Oteros J, Garcia-Mozo H, Botey R et al., 2015. Variations in cereal crop phenology in Spain over the last twenty-six years (1986–2012). Climatic Change, 130(4): 545–558.

    Article  Google Scholar 

  • Parent B, Tardieu F, 2012. Temperature responses of development processes have not been affected by breeding in different ecological areas for 17 crop species. New Phytologist, 194(3): 760–774.

    Article  Google Scholar 

  • Penuelas J, Rutishauser T, Filella I, 2009. Phenology feedbacks on climate change. Science, 324(5929): 887–888.

    Article  Google Scholar 

  • Pielke R A, Adegoke J, Beltran-Przekurat A et al., 2007. An overview of regional land-use and land-cover impacts on rainfall. Tellus Series B: Chemical and Physical Meteorology, 59(3): 587–601.

    Article  Google Scholar 

  • Raddatz R L, Cummine J D, 2003. Inter-annual variability of moisture flux from the prairie agro-ecosystem: Impact of crop phenology on the seasonal pattern of Tornado Days. Boundary-Layer Meteorology, 106(2): 283–295.

    Article  Google Scholar 

  • Richardson A D, Keenan T F, Migliavacca M et al., 2013. Climate change, phenology, and phenological control of vegetation feedbacks to the climate system. Agricultural and Forest Meteorology, 169: 156–173.

    Article  Google Scholar 

  • Sacks W J, Kucharik C J, 2011. Crop management and phenology trends in the US Corn Belt: Impacts on yields, evapotranspiration and energy balance. Agricultural and Forest Meteorology, 151(7): 882–894.

    Article  Google Scholar 

  • Schwartz M D, Ahas R, Aasa A, 2006. Onset of spring starting earlier across the Northern Hemisphere. Global Change Biology, 12(2): 343–351.

    Article  Google Scholar 

  • Sharma K D, Pannu R K, 2008. Physiological response of wheat (Triticum durum L.) to limited irrigation. Journal of Agrometeorology, 10(2): 113–117.

    Google Scholar 

  • Shi Wenjiao, Tao Fulu, Zhang Zhao, 2012. Identifying contributions of climate change to crop yields based on statistical models: A review. Acta Geographica Sinica, 67(9): 1213–1222. (in Chinese)

    Google Scholar 

  • Song Y, Jain A K, McIsaac G F, 2013. Implementation of dynamic crop growth processes into a land surface model: Evaluation of energy, water and carbon fluxes under corn and soybean rotation. Biogeosciences, 10(12): 8201–8201.

    Article  Google Scholar 

  • Tao F L, Zhang S A, Zhang Z, 2012. Spatiotemporal changes of wheat phenology in China under the effects of temperature, day length and cultivar thermal characteristics. European Journal of Agronomy, 43: 201–212.

    Article  Google Scholar 

  • Tao F L, Zhang S, Zhang Z et al., 2014. Maize growing duration was prolonged across China in the past three decades under the combined effects of temperature, agronomic management, and cultivar shift. Global Change Biology, 20(12): 3686–3699.

    Article  Google Scholar 

  • Tsarouchi G M, Buytaert W, Mijic A, 2014. Coupling a land-surface model with a crop growth model to improve ET flux estimations in the Upper Ganges basin, India. Hydrology and Earth System Sciences, 18(10): 4223–4238.

    Article  Google Scholar 

  • Tsvetsinskaya E A, Mearns L O, Easterling W E, 2001. Investigating the effect of seasonal plant growth and development in three-dimensional atmospheric simulations. Part I: Simulation of surface fluxes over the growing season. Journal of Climate, 14(5): 692–709.

    Article  Google Scholar 

  • Van den Hoof C, Hanert E, Vidale P L, 2011. Simulating dynamic crop growth with an adapted land surface model–JULES-SUCROS: Model development and validation. Agricultural and Forest Meteorology, 151(2): 137–153.

    Article  Google Scholar 

  • Wang E, Engel T, 1998. Simulation of phenological development of wheat crops. Agricultural Systems, 58(1): 1–24.

    Article  Google Scholar 

  • Wang Z, Chen J, Li Y et al., 2016. Effects of climate change and cultivar on summer maize phenology. International Journal of Plant Production, 10(4): 509–525.

    Google Scholar 

  • Wilson D R, Muchow R C, Murgatroyd C J, 1995. Model analysis of temperature and solar radiation limitations to maize potential productivity in a cool climate. Field Crops Research, 43(1): 1–18.

    Article  Google Scholar 

  • Xiao D P, Moiwo J P, Tao F L et al., 2015. Spatiotemporal variability of winter wheat phenology in response to weather and climate variability in China. Mitigation and Adaptation Strategies for Global Change, 20(7): 1191–1202.

    Article  Google Scholar 

  • Xiao D P, Qi Y Q, Shen Y J et al., 2016. Impact of warming climate and cultivar change on maize phenology in the last three decades in North China Plain. Theoretical and Applied Climatology, 124(3/4): 653–661.

    Article  Google Scholar 

  • Xiao D P, Tao F L, Liu Y J et al., 2013. Observed changes in winter wheat phenology in the North China Plain for 1981–2009. International Journal of Biometeorology, 57(2): 275–285.

    Article  Google Scholar 

  • Xiao Y G, Qian Z G, Wu K et al., 2012. Genetic gains in grain yield and physiological traits of winter wheat in Shandong Province, China, from 1969 to 2006. Crop Science, 52(1): 44–56.

    Article  Google Scholar 

  • Yuan Zaijian, Shen Yanjun, Chu Yingmin et al., 2010. Characteristics and simulation of heat and CO2 fluxes over a typical cropland during the winter wheat growing in the North China Plain. Environmental Science, 31(1): 41–48. (in Chinese)

    Google Scholar 

  • Zhang X, Tang Q, Zheng J et al., 2013. Warming/cooling effects of cropland greenness changes during 1982–2006 in the North China Plain. Environmental Research Letters, 8(2): 024038.

    Article  Google Scholar 

  • Zheng Jingyun, Liu Yand, Ge Quansheng et al., 2015. Spring phenodate records derived from historical documents and reconstruction on temperature change in Central China during 1850–2008. Acta Geographica Sinica, 70(5): 696–704. (in Chinese)

    Google Scholar 

  • Zhou Guangsheng, 2015. Research prospect on impact of climate change on agricultural production in China. Meteorological and Environmental Sciences, 38(1): 80–94. (in Chinese)

    Google Scholar 

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Correspondence to Fulu Tao or Quansheng Ge.

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Foundation China Postdoctoral Science Foundation, No.2016M601115; National Natural Science Foundation of China, No.41571088, No.41371002

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Liu, F., Chen, Y., Shi, W. et al. Influences of agricultural phenology dynamic on land surface biophysical process and climate feedback. J. Geogr. Sci. 27, 1085–1099 (2017). https://doi.org/10.1007/s11442-017-1423-3

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