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http://dx.doi.org/10.5532/KJAFM.2018.20.1.57

Assessment of Ecosystem Productivity and Efficiency using Flux Measurement over Haenam Farmland Site in Korea (HFK)  

Indrawati, Yohana Maria (Interdisciplinary Program in Agricultural & Forest Meteorology, Seoul National University)
Kim, Joon (Interdisciplinary Program in Agricultural & Forest Meteorology, Seoul National University)
Kang, Minseok (National Center for AgroMeteorology)
Publication Information
Korean Journal of Agricultural and Forest Meteorology / v.20, no.1, 2018 , pp. 57-72 More about this Journal
Abstract
Time series analysis of tower flux measurement can be used to build quantitative evidence for the achievement of climate-smart agriculture (CSA). In this study, we have assessed the first objective of CSA (regarding ecosystem productivity and efficiency) for rice paddy-dominated heterogeneous farmland. A set of quantitative indicators were evaluated by analysing the time series data of carbon, water and energy fluxes over the Haenam farmland site in Korea (HFK) during the rice growing seasons from 2003 to 2015. Four different varieties of rice were cultivated during the study period in chronological order of Dongjin No. 1 (2003-2008), Nampyung (2009), Onnuri (2010-2011), and Saenuri (2012-2015). Overall at HFK, gross primary productivity (GPP) ranged from 800 to $944g\;C\;m^{-2}$, water use efficiency (WUE) ranged from 1.91 to $2.80g\;C\;kg\;H_2O^{-1}$, carbon uptake efficiency (CUE) ranged from 1.06 to 1.34, and light use efficiency (LUE) ranged from 0.99 to $1.55g\;C\;MJ^{-1}$. Among the four rice varieties, Dongjin No. 1-dominated HFK showed the highest productivity with higher WUE and LUE, but comparable CUE. Considering the heterogeneous vegetation cover at HFK, a rule of thumb comparison suggested that the productivity of Dongjin No1-dominated HFK was comparable to those of monoculture rice paddies in Asia, whereas HFK was more efficient in water use and less efficient in carbon uptake. Saenuri-dominated HFK also produced high productivity but with the growing season length longer than Dongjin No.1. Although the latter showed better traits for CSA, farmers cultivate Saenuri because of higher pest resistance (associated with adaptability and resilience). This emphasizes the need for the evaluation of other two objectives of CSA (i.e. system resilience and greenhouse gas mitigation) for complete assessment at HFK, which is currently in progress.
Keywords
Climate-smart agriculture; Productivity; Efficiency; Eddy covariance; Rice paddy; Farmland;
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1 Kang, M., B. L. Ruddell, C. Cho, J. Chun, and J. Kim, 2017: Identifying CO 2 advection on a hill slope using information flow. Agricultural and Forest Meteorology 232, 265-278.   DOI
2 Keenan, T. F., D. Y. Hollinger, G. Bohrer, D. Dragoni, J. W. Munger, H. P. Schmid, and A. D. Richardson, 2013: Increase in forest water-use efficiency as atmospheric carbon dioxide concentrations rise. Nature 499(7458), 324-327.   DOI
3 Kim, Y., and J. Kim, 2018: Application of spectrum and wavelet analyses for the fields of agriculture, forestry and ecohydrology. (in preparation)
4 Kim, Y., M. S. A. Talucder, M. Kang, K. M. Shim, N. Kang, and J. Kim, 2016: Interannual variations in methane emission from an irrigated rice paddy caused by rainfalls during the aeration period. Agriculture, Ecosystems & Environment 223, 67-75.   DOI
5 KOSIS, 2015: Korean Statistical database 2015, Korea.
6 Kuglitsch, F. G., M. Reichstein, C. Beer, A. Carrara, R. Ceulemans, A. Granier, I. A. Janssens, B. Koestner, A. Lindroth, D. Loustau, and G. Matteucci, 2008: Characterisation of ecosystem water-use efficiency of european forests from eddy covariance measurements. Biogeosciences Discussions 5(6), 4481-4519.   DOI
7 Zurlini, G., I. Petrosillo, K. B. Jones, and N. Zaccarelli, 2013: Highlighting order and disorder in social-ecological landscapes to foster adaptive capacity and sustainability. Landscape Ecology 28(6), 1161-1173.   DOI
8 Ciais, P., M. Reichstein, N. Viovy, A. Granier, J. Ogee, V. Allard, M. Aubinet, N. Buchmann, C. Bernhofer, A. Carrara, and F. Chevallier, 2005: Europe-wide reduction in primary productivity caused by the heat and drought in 2003. Nature 437(7058), 529.   DOI
9 Choi, S.-W., J. Kim, M. Kang, S. H. Lee, N. Kang, Y. Ryu, K-M. Shim, 2018: Estimation and Mapping of Methane Emissions from Rice Paddies in Korea: Analysis of Regional Differences and Characteristics. Korean Journal of Agricultural and Forest Meteorology. (in Korean with English abstract)
10 Churkina, G., D. Schimel, B. H. Braswell, and X. Xiao, 2005: Spatial analysis of growing season length control over net ecosystem exchange. Global Change Biology 11(10), 1777-1787.   DOI
11 Farquhar, G., and R. Richards, 1984: Isotopic composition of plant carbon correlates with water-use efficiency of wheat genotypes. Functional Plant Biology 11(6), 539-552.
12 Kwon, H., J. Kim, J. Hong, and J. Lim, 2010: Influence of the Asian monsoon on net ecosystem carbon exchange in two major ecosystems in Korea. Biogeosciences 7(5), 1493-1504.   DOI
13 Kwon, H., T.-Y. Park, J. Hong, J.-H. Lim, and J. Kim, 2009: Seasonality of Net Ecosystem Carbon Exchange in Two Major Plant Functional Types in Korea. Asia-Pacific Journal of Atmospheric Sciences 45(2), 149-163.
14 Law, B. E., E. Falge, L. V. Gu, D. D. Baldocchi, P. Bakwin, P. Berbigier, K. Davis, A. J. Dolman, M. Falk, J. D. Fuentes, and A. Goldstein, 2002: Environmental controls over carbon dioxide and water vapor exchange of terrestrial vegetation. Agricultural and Forest Meteorology 113(1), 97-120.   DOI
15 Cochran, F. V., N. A. Brunsell, and A. E. Suyker, 2016: A thermodynamic approach for assessing agroecosystem sustainability. Ecological Indicators 67, 204-214.
16 Falge, E., D. Baldocchi, J. Tenhunen, M. Aubinet, P. Bakwin, P. Berbigier, C. Bernhofer, G. Burba, R. Clement, K. J. Davis, and J. A. Elbers, 2002: Seasonality of ecosystem respiration and gross primary production as derived from FLUXNET measurements. Agricultural and Forest Meteorology 113(1), 53-74.   DOI
17 Gitelson, A. A., and J. A. Gamon, 2015: The need for a common basis for defining light-use efficiency: Implications for productivity estimation. Remote Sensing of Environment 156, 196-201.
18 Gitelson, A. A., A. Vina, S. B. Verma, D. C. Rundquist, T. J. Arkebauer, G. Keydan, B. Leavitt, V. Ciganda, G. G. Burba, and A. E. Suyker, 2006: Relationship between gross primary production and chlorophyll content in crops: Implications for the synoptic monitoring of vegetation productivity. Journal of Geophysical Research: Atmospheres, 111(D8).
19 Lee, H. C., J. Hong, C.-H. Cho, B.-C. Choi, S.-N. Oh, and J. Kim, 2003: Surface exchange of energy and carbon dioxide between the atmosphere and a farmland in Haenam, Korea. Korean Journal of Agricultural and Forest Meteorology 5(2), 61-69.
20 Lee, C. K., J. Kim, J. Shon, W. H. Yang, Y. H. Yoon, K. J. Choi, and K. S. Kim, 2012: Impacts of climate change on rice production and adaptation method in Korea as evaluated by simulation study. Korean Journal of Agricultural and Forest Meteorology 14(4), 207-221. (in Korean with English abstract)   DOI
21 Lee, Y.-H., J. Kim, and J. Hong, 2008: The Simulation of Water Vapor and Carbon Dioxide Fluxes over a Rice Paddy Field by Modified Soil-Plant-Atmosphere Model (mSPA). Asia-Pacific Journal of Atmospheric Sciences 44(1), 69-83.
22 Mizoguchi, Y., A. Miyata, Y. Ohtani, R. Hirata, and S. Yuta, 2009: A review of tower flux observation sites in Asia. Journal of forest research, 14(1), 1-9.   DOI
23 Hong, J. K., H. J. Kwon, J. H. Lim, Y. H. Byun, J. H. Lee, and J. Kim, 2009: Standardization of KoFlux eddy-covariance data processing. Korean Journal of Agricultural and Forest Meteorology 11(1), 19-26. (in Korean with English abstract)   DOI
24 Lin, H., M. Cao, P. C. Stoy, and Y. Zhang, 2009: Assessing self-organization of plant communities-a thermodynamic approach. Ecological Modelling 220(6), 784-790.   DOI
25 Lin, H., M. Cao, and Y. Zhang, 2011: Self-organization of tropical seasonal rain forest in southwest China. Ecological Modelling 222(15), 2812-2816.   DOI
26 Lipper, L., P. Thornton, B. M. Campbell, T. Baedeker, A. Braimoh, M. Bwalya, P. Caron, A. Cattaneo, D. Garrity, K. Henry, and R. Hottle, 2014: Climate-smart agriculture for food security. Nature Climate Change 4(12), 1068-1072.   DOI
27 McMillen, R. T., 1988: An eddy correlation technique with extended applicability to non-simple terrain. Boundary-Layer Meteorology 43(3), 231-245.   DOI
28 Monteith, J.L. and C. Moss,, 1977: Climate and the efficiency of crop production in Britain [and discussion]. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 281(980), 277-294.   DOI
29 http://asiaflux.net/index.php?page_id=60 (2017.11.1).
30 Hsieh, C. I., G. Katul, and T. W. Chi, 2000: An approximate analytical model for footprint estimation of scalar fluxes in thermally stratified atmospheric flows. Advances in Water Resources 23, 765-772.   DOI
31 https://egis.me.go.kr/main.do (2007.12.10).
32 http://www.haenam.go.kr/planweb/board/list.9is?boardUid=4a94e38a4830deca0148e83ce61d14d2&contentUid=18e3368f5281ef400152b037a5fe4007&layoutUid=4a94e38a478f462d01479f3dd2820253 (2017.08.23).
33 Ikawa, H., K. Ono, M. Mano, K. Kobayashi, T. Takimoto, T. Kuwagata, and A. Miyata, 2017: Evapotranspiration in a rice paddy field over 13 crop years. Journal of Agricultural Meteorology 73(3), 109-118.   DOI
34 IRRI, 2013: Rice Knowledge Bank, Step-by-step production: Crop calendar. IRRI.
35 Jang, T., S.-B. Lee, C.-H. Sung, H.-P. Lee, and S.-W. Park, 2010: Safe application of reclaimed water reuse for agriculture in Korea. Paddy and Water Environment 8(3), 227-233.   DOI
36 Kang, M., 2013: Understanding the evapotranspiration dynamics in East Asian forest ecosystems for resilient water management. dissertation Thesis, Yonsei University, Seoul Korea, 263.
37 Kang, M., J. Kim, H.-S. Kim, B. M. Thakuri, and J.-H. Chun, 2014: On the nighttime correction of $CO_2$ flux measured by eddy covariance over temperate forests in complex terrain. Korean Journal of Agricultural and Forest Meteorology 16(3), 233-245.   DOI
38 Neufeldt, H., M. Jahn, B. M. Campbell, J. R. Beddington, F. DeClerck, A. De Pinto, J. Gulledge, J. Hellin, M. Herrero, A. Jarvis, and D. LeZaks, 2013: Beyond climate-smart agriculture: toward safe operating spaces for global food systems. Agriculture & Food Security, 2(1), 12.   DOI
39 NCAM, 2013: Advancement in urban, agricultural and forest land surface model (II): Designing land surface model for agricultural management using long-term flux data, Seoul, South Korea, 69pp.
40 NCIS., 2017: 2017 Explanatory Notes on Major Crops (Rice) Varieties (2017주요 식랑작물(벼) 품종해설서), National Institute of Crop Science, Korea.
41 Nielsen, S., and S. Jorgensen, 2013: Goal functions, orientors and indicators (GoFOrIt's) in ecology. Application and functional aspects-Strengths and weaknesses. Ecological Indicators, 28, 31-47.
42 Odum, E., 1969: The strategy of ecosystem development. Science (New York, NY), 164(3877), 262.   DOI
43 Palombi, L., and R. Sessa, 2013: Climate-smart agriculture: sourcebook. Food and Agriculture Organization of the United Nations(FAO).
44 Papale, D., M. Reichstein, M. Aubinet, E. Canfora, C. Bernhofer, W. Kutsch, B. Longdoz, S. Rambal, R. Valentini, T. Vesala, and D. Yakir, 2006: Towards a standardized processing of Net Ecosystem Exchange measured with eddy covariance technique: algorithms and uncertainty estimation. Biogeosciences 3(4), 571-583.   DOI
45 Ponton, S., L. B. Flanagan, K. P. Alstad, B. G. Johnson, K. A. I. Morgenstern, N. Kljun, T. A. Black, and A. G. Barr, 2006: Comparison of ecosystem water-use efficiency among Douglas-fir forest, aspen forest and grassland using eddy covariance and carbon isotope techniques. Global Change Biology 12(2), 294-310.   DOI
46 Prokopenko, M., F. Boschetti, and A. J. Ryan, 2009: An information-theoretic primer on complexity, self-organization, and emergence. Complexity 15(1), 11-28.   DOI
47 Saito, M., A. Miyata, H. Nagai, and T. Yamada, 2005: Seasonal variation of carbon dioxide exchange in rice paddy field in Japan. Agricultural and forest meteorology 135(1-4), 93-109.   DOI
48 Reichstein, M., P. Ciais, D. Papale, R. Valentini, S. Running, N. Viovy, W. Cramer, A. Granier, J. Ogee, V. Allard, and M. Aubinet, 2007: Reduction of ecosystem productivity and respiration during the European summer 2003 climate anomaly: a joint flux tower, remote sensing and modelling analysis. Global Change Biology 13(3), 634-651.   DOI
49 Reichstein, M., E. Falge, D. Baldocchi, D. Papale, M. Aubinet, P. Berbigier, . . ., and A. Granier, 2005: On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm. Global Change Biology 11(9), 1424-1439.   DOI
50 Rosenstock, T. S., C. Lamanna, S. Chesterman, P. Bell, A. Arslan, M. Richards, J. Rioux, A. O. Akinleye, C. Champalle, Z. Cheng, and C. Corner-Dolloff, 2016: The scientific basis of climate-smart agriculture: A systematic review protocol.
51 Schneider, E. D., and J. J. Kay, 1994: Life as a manifestation of the second law of thermodynamics. Mathematical and computer modelling 19(6), 25-48.   DOI
52 Svirezhev, Y., 2010: Entropy and Entropy Flows in the Biosphere. Global Ecology 154.
53 Van Gorsel, E., N. Delpierre, R. Leuning, A. Black, J. W. Munger, S. Wofsy, M. Aubinet, C. Feigenwinter, J. Beringer, D. Bonal, and B. Chen, 2009: Estimating nocturnal ecosystem respiration from the vertical turbulent flux and change in storage of CO 2. Agricultural and forest meteorology 149(11), 1919-1930.   DOI
54 Yu, G., X. Song, Q. Wang, Y. Liu, D. Guan, J. Yan, X. Sun, L. Zhang, and X. Wen, 2008: Water-use efficiency of forest ecosystems in eastern China and its relations to climatic variables. New Phytologist 177(4), 927-937.   DOI
55 Wang, E., C. J. Smith, W. J. Bond, and K. Verburg, 2005: Estimations of vapor pressure deficit and crop water demand in APSIM and their implications for prediction of crop yield, water use, and deep drainage. Crop and Pasture Science 55(12), 1227-1240.
56 Wang, Y., L. Zhou, Q. Jia, and W. Yu, 2017: Water use efficiency of a rice paddy field in Liaohe Delta, Northeast China. Agricultural Water Management 187, 222-231.   DOI
57 Webb, E. K., G. I. Pearman, and R. Leuning, 1980: Correction of flux measurements for density effects due to heat and water vapor transfer. Quarterly Journal of the Royal Meteorological Society 106(447), 85-100.   DOI
58 Xin, F., X. Xiao, B. Zhao, A. Miyata, D. Baldocchi, S. Knox, M. Kang, K. M. Shim, S. Min, B. Chen, and X. Li, 2017: Modeling gross primary production of paddy rice cropland through analyses of data from $CO_2$ eddy flux tower sites and MODIS images. Remote sensing of environment 190, 42-55.
59 Yoo, G., and J. Kim, 2007: Development of a methodology assessing rice production vulnerabilities to climate change. RE-14. Korea Environment Institute.
60 Alberto, M. C. R., R. Wassmann, T. Hirano, A. Miyata, R. Hatano, A. Kumar, A. Padre, and M. Amante, 2011: Comparisons of energy balance and evapotranspiration between flooded and aerobic rice fields in the Philippines. Agricultural Water Management 98(9), 1417-1430.   DOI
61 Aubinet, M., B. Chermanne, M. Vandenhaute, B. Longdoz, M. Yernaux, and E. Laitat, 2001: Long term carbon dioxide exchange above a mixed forest in the Belgian Ardennes. Agricultural and Forest Meteorology 108(4), 293-315.   DOI
62 Baldocchi, D., E. Falge, L. Gu, and R. Olson, 2001: FLUXNET: A new tool to study the temporal and spatial variability of ecosystem-scale carbon dioxide, water vapor, and energy flux densities. Bulletin of the American Meteorological Society 82(11), 2415.   DOI
63 Beer, C., M. Reichstein, P. Ciais, G. Farquhar, and D. Papale, 2007: Mean annual GPP of Europe derived from its water balance. Geophysical Research Letters 34(5).
64 Yun, J., M. Kang, S. Kim, J. H. Chun, C. H. Cho, and J. Kim, 2014: How is the Process Network Organized and When Does it Show Emergent Properties in a Forest Ecosystem? In ISCS 2013: Interdisciplinary Symposium on Complex Systems, 307-317. Springer Berlin Heidelberg.
65 Zaccarelli, N., B.-L. Li, I. Petrosillo, and G. Zurlini, 2013: Order and disorder in ecological time-series: introducing normalized spectral entropy. Ecological Indicators 28, 22-30.   DOI
66 Zhang, Y., M. Xu, H. Chen, and J. Adams, 2009: Global pattern of NPP to GPP ratio derived from MODIS data: effects of ecosystem type, geographical location and climate. Global Ecology and Biogeography 18(3), 280-290.   DOI
67 Baldocchi, D. D., S. B. Verma, and N. J. Rosenberg, 1985: Water use efficiency in a soybean field: influence of plant water stress. Agricultural and forest meteorology 34(1), 53-65.   DOI
68 Beer, C., P. Ciais, M. Reichstein, D. Baldocchi, B. E. Law, D. Papale, J. F. Soussana, C. Ammann, N. Buchmann, D. Frank, and D. Gianelle, 2009: Temporal and among-site variability of inherent water use efficiency at the ecosystem level. Global biogeochemical cycles 23(2).
69 Brunsell, N. A., S. J. Schymanski, and A. Kleidon, 2011: Quantifying the thermodynamic entropy budget of the land surface: is this useful? Earth System Dynamics 2(1), 87-103.   DOI