Linking canopy reflectance to crop structure and photosynthesis to capture and interpret spatiotemporal dimensions of per-field photosynthetic productivity

Biogeosciences - Tập 14 Số 5 - Trang 1315-1332
Wei Xue1, Seungtaek Jeong1, Jonghan Ko1, John Tenhunen2
1Department of Applied Plant Science, Chonnam National University, 500757 Gwangju, South Korea
2Department of Plant Ecology, BayCEER, University of Bayreuth, 95440, Bayreuth, Germany

Tóm tắt

Abstract. Nitrogen and water availability alter canopy structure and physiology, and thus crop growth, yielding large impacts on ecosystem-regulating/production provisions. However, to date, explicitly quantifying such impacts remains challenging partially due to lack of adequate methodology to capture spatial dimensions of ecosystem changes associated with nitrogen and water effects. A data fitting, where close-range remote-sensing measurements of vegetation indices derived from a handheld instrument and an unmanned aerial vehicle (UAV) system are linked to in situ leaf and canopy photosynthetic traits, was applied to capture and interpret inter- and intra-field variations in gross primary productivity (GPP) in lowland rice grown under flooded conditions (paddy rice, PD) subject to three nitrogen application rates and under rainfed conditions (RF) in an East Asian monsoon region of South Korea. Spatial variations (SVs) in both GPP and light use efficiency (LUEcabs) early in the growing season were enlarged by nitrogen addition. The nutritional effects narrowed over time. A shift in planting culture from flooded to rainfed conditions strengthened SVs in GPP and LUEcabs. Intervention of prolonged drought late in the growing season dramatically intensified SVs that were supposed to seasonally decrease. Nevertheless, nitrogen addition effects on SV of LUEcabs at the early growth stage made PD fields exert greater SVs than RF fields. SVs of GPP across PD and RF rice fields were likely related to leaf area index (LAI) development less than to LUEcabs, while numerical analysis suggested that considering strength in LUEcabs and its spatial variation for the same crop type tends to be vital for better evaluation in landscape/regional patterns of ecosystem photosynthetic productivity at critical phenology stages.

Từ khóa


Tài liệu tham khảo

Adiku, S., Reichstein, M., Lohila, A., Dinh, N., Aurela, M., Laurila, T., Lueers, J., and Tenhunen, J.: PIXGRO: a model for simulating the ecosystem CO2 exchange and growth of spring barley, Ecol. Model., 190, 260–276, 2006.

Alton, P. B.: Retrieval of seasonal Rubisco-limited photosynthetic capacity at global FLUXNET sites from hyperspectral satellite remote sensing: impact on carbon modelling, Agr. Forest Meteorol., 232, 74–88, 2017.

Bausch, W. and Khosla, R.: QuickBird satellite versus ground-based multi-spectral data for estimating nitrogen status of irrigated maize, Precis. Agric., 11, 274–290, 2010.

Cao, Q., Cui, Z., Chen, X., Khosla, R., Dao, T. H., and Miao, Y.: Quantifying spatial variability of indigenous nitrogen supply for precision nitrogen management in small scale farming, Precis. Agric., 13, 45–61, 2012.

Devendra, C.: Small farm system to feed hungry Asia, Outlook Agric., 36, 17–20, 2007.

Dow, G. J. and Bergmann, D. C.: Patterning and processes: how stomatal development defines physiological potential, Curr. Opin Plant Biol., 21, 67–74, 2014.

Fisher, P., Abuzar, M., Rab, M., Best, F., and Chandra, S.: Advances in precision agriculture in south-eastern Australia, I. A regression methodology to simulate spatial variation in cereal yields using farmers' historical paddock yields and normalised difference vegetation index, Crop Pasture Sci., 60, 844–858, 2009.

Forkel, M., Carvalhais, N., Rödenbeck, C., Keeling, R., Heimann, M., Thonicke, K., Zaehle, S., and Reichstein, M.: Enhanced seasonal CO2 exchange caused by amplified plant productivity in northern ecosystems, Science, 351, 696–699, 2016.

Inoue, Y., Peñuelas, J., Miyata, A., and Mano, M.: Normalized difference spectral indices for estimating photosynthetic efficiency and capacity at a canopy scale derived from hyperspectral and CO2 flux measurements in rice, Remote Sens. Environ., 112, 156–172, 2008.

Jeong, S., Ko, J., Kim, M., and Kim, J.: Construction of an unmanned aerial vehicle remote sensing system for crop monitoring, J. Appl. Remote Sens., 10, https://doi.org/10.1117/1.JRS.10.026027, 2016.

Jo, S. H. and Ko, J. H.: Determining canopy growth conditions of paddy rice via ground-based remote sensing, Korea J. Remote Sens., 31, 11–20, 2015.

Karaba, A., Dixit, S., Greco, R., Aharoni, A., Trijatmiko, K. R., Marsch-Martinez, N., Krishnan, A., Nataraja, K. N., Udayakumar, M., and Pereira, A.: Improvement of water use ef?ciency in rice by expression of HARDY, an Arabidopsis drought and salt tolerance gene, P. Natl. Acad. Sci. USA, 104, 15270–15275, 2007.

Kato, Y., Tajima, R., Toriumi, A., Homma, K., Moritsuka, N., Shiraiwa, T., Yamagishi, J., Mekwatanakern, P., Chamarerk, V., and Jongdee, B.: Grain yield and phosphorus uptake of rainfed lowland rice under unsubmerged soil stress, Field Crop. Res., 190, 54–59, 2016.

Kim, K. Y., Ha, K. Y., Ko, J. C., Choung, J. I., Lee, J. K., Ko, J. K., Kim, B. K., Nam, J. K., Shin, M. S., and Choi, Y. H.,: A new early maturity rice cultivar, ”Unkwang” with high grain quality and cold tolerance, Korea J. Breed., 38, 261–262, 2006.

Ko, J., Jeong, S., Yeom, J., Kim, H., Ban, J. O., and Kim, H. Y.: Simulation and mapping of rice growth and yield based on remote sensing, J. Appl. Remote Sens., 9, 096067, https://doi.org/10.1117/1.JRS.9.096067, 2015.

Kwon, H., Kim, J., Hong, J., and Lim, J.-H.: Influence of the Asian monsoon on net ecosystem carbon exchange in two major ecosystems in Korea, Biogeosciences, 7, 1493–1504, https://doi.org/10.5194/bg-7-1493-2010, 2010.

Lausch, A., Bannehr, L., Beckmann, M., Boehm, C., Feilhauer, H., Hacker, J., Heurich, M., Jung, A., Klenke, R., and Neumann, C.: Linking earth observation and taxonomic, structural and functional biodiversity: local to ecosystem perspectives, Ecol. Indic., 70, 317–339, 2016.

Lee, B.: Remote sensing-based assessment of gross primary production in agricultural ecosystems, in: Ph.D Thesis, University of Bayreuth, 134 pp., 2014.

Lindner, S., Otieno, D., Lee, B., Xue, W., Arnhold, S., Kwon, H., Huwe, B., and Tenhunen, J.: Carbon dioxide exchange and its regulation in the main agro-ecosystems of Haean catchment in South Korea, Agr. Ecosyst. Environ., 199, 132–145, 2015.

Lindner, S., Xue, W., Nay-Htoon, B., Choi, J., Ege, Y., Lichtenwald, N., Fischer, F., Ko, J., Tenhunen, J., and Otieno, D.: Canopy scale CO2 exchange and productivity of transplanted paddy and direct seeded rainfed rice production systems in S. Korea, Agr. Forest Meteorol., 228, 229–238, 2016.

Loescher, H., Ayres, E., Duffy, P., Luo, H., and Brunke, M.: Spatial variation in soil properties among North American ecosystems and guidelines for sampling designs, Plos One, 9, e83216, https://doi.org/10.1371/journal.pone.0083216, 2014.

Masek, J. G., Hayes, D. J., Hughes, M. J., Healey, S. P., and Turner, D. P.: The role of remote sensing in process-scaling studies of managed forest ecosystems, Forest Ecol. Manag., 355, 109–123, 2015.

Niinemets, Ü. and Tenhunen, J.: A model separating leaf structural and physiological effects on carbon gain along light gradients for the shade-tolerant species Acer saccharum, Plant Cell Environ., 20, 845–866, 1997.

Pause, M., Schweitzer, C., Rosenthal, M., Keuck, V., Bumberger, J., Dietrich, P., Heurich, M., Jung, A., and Lausch, A.: In situ/remote sensing integration to assess forest health-a review, Remote Sens., 8, 471, https://doi.org/10.3390/rs8060471, 2016.

Pierson, F. B. and Wight, J. R.: Variability of near-surface soil temperature on sagebrush rangeland, J. Range Manage., 44, 491–497, 1991.

Richardson, A. D., Keenan, T. F., Migliavacca, M., Ryu, Y., Sonnentag, O., and Toomey, M.: Climate change, phenology, and phenological control of vegetation feedbacks to the climate system, Agr. Forest Meteorol., 169, 156–173, 2013.

Swain, K. C., Thomson, S. J., and Jayasuriya, H. P.: Adoption of an unmanned helicopter for low-altitude remote sensing to estimate yield and total biomass of a rice crop, T. ASABE, 53, 21–27, 2010.

Seo, B., Bogner, C., Poppenborg, P., Martin, E., Hoffmeister, M., Jun, M., Koellner, T., Reineking, B., Shope, C. L., and Tenhunen, J.: Deriving a per-field land use and land cover map in an agricultural mosaic catchment, Earth Syst. Sci. Data, 6, 339–352, https://doi.org/10.5194/essd-6-339-2014, 2014.

Serraj, R., Bennett, J., and Hardy, B.: Drought frontiers in rice: crop improvement for increased rainfed production, International Rice Research Institute, Manila, Philippines, 385 pp., 2008.

Sinclair, T. and Horie, T.: Leaf nitrogen, photosynthesis, and crop radiation use efficiency: a review, Crop Sci., 29, 90–98, 1989.

Steudle, E.: Water uptake by roots: effects of water deficit, J. Exp. Bot., 51, 1531–1542, 2000.

Tanaka, Y., Sugano, S. S., Shimada, T., and Hara-Nishimura, I.: Enhancement of leaf photosynthetic capacity through increased stomatal density in Arabidopsis, New Phytol., 198, 757–764, 2013.

Tenhunen, J., Geyer, R., Adiku, S., Reichstein, M., Tappeiner, U., Bahn, M., Cernusca, A., Dinh, N., Kolcun, O., and Lohila, A.: Influences of changing land use and CO2 concentration on ecosystem and landscape level carbon and water balances in mountainous terrain of the Stubai Valley, Austria, Glob. Planet. Change, 67, 29–43, 2009.

Tubaña, B., Harrell, D., Walker, T., Teboh, J., Lofton, J., and Kanke, Y.: In-season canopy reflectance-based estimation of rice yield response to nitrogen, Agron. J., 104, 1604–1611, 2012.

Van Genuchten, M. T.: A closed-form equation for predicting the hydraulic conductivity of unsaturated soils, Soil Sci. Soc. Am. J., 44, 892–898, 1980.

Vieira, S., Hatfield, J., Nielsen, D., and Biggar, J.: Geostatistical theory and application to variability of some agronomical properties, Hilgardia, 51, 1–75, 1983.

Wang, Y., Noguchi, K., Ono, N., Inoue, S., Terashima, I., and Kinoshita, T.: Overexpression of plasma membrane H+-ATPase in guard cells promoteslight-induced stomatal opening and enhances plant growth, P. Natl. Acad. Sci. USA, 111, 533–538, 2014.

Wehrhan, M., Rauneker, P., and Sommer, M.: UAV-based estimation of carbon exports from heterogeneous soil landscapes-a case study from the CarboZALF experimental area, Sensors, 16, 255, https://doi.org/10.3390/s16020255, 2016.

Xue, W., Lindner, S., Nay-Htoon, B., Dubbert, M., Otieno, D., Ko, J., Muraoka, H., Werner, C., Tenhunen, J., and Harley, P.: Nutritional and developmental influences on components of rice crop light use efficiency, Agr. Forest Meteorol., 223, 1–16, 2016a.

Xue, W., Nay-Htoon, B., Lindner, S., Dubbert, M., Otieno, D., Ko, J., Werner, C., and Tenhunen, J.: Soil water availability and capacity of nitrogen accumulation influence variations of intrinsic water use efficiency in rice, J. Plant Physiol., 193, 26–36, 2016b.

Xue, W., Otieno, D., Ko, J., Werner, C., and Tenhunen, J.: Conditional variations in temperature response of photosynthesis, mesophyll and stomatal control of water use in rice and winter wheat, Field Crop. Res., 199, 77–88, 2016c.

Xue, W., Lindner, S., Dubbert, M., Otieno, D., Ko, J., Muraoka, H., Werner, C., and Tenhunen, J.: Supplement understanding of the relative importance of biophysical factors in determination of photosynthetic capacity and photosynthetic productivity in rice ecosystems, Agr. Forest Meteorol., 232, 550–565, 2017.

Yoshida, S.: Fundamentals of rice crop science, International Rice Research Institute, Manila, Philippines, 279 pp., 1981.

Zhang, C. and Kovacs, J. M.: The application of small unmanned aerial systems for precision agriculture: a review, Precis. Agric., 13, 693–712, 2012.