Skip to main content

Advertisement

Log in

Eddy covariance measurements of CO2 exchange from agro-ecosystems located in subtropical (India) and boreal (Finland) climatic conditions

  • Published:
Journal of Earth System Science Aims and scope Submit manuscript

Abstract

Climate impacts agriculture in various complex ways at different levels and scales depending on the local natural crop growth limitations. Our objective in this study, therefore, is to understand how different is the atmosphere–biosphere exchange of CO2 under contrasting subtropical and boreal agricultural (an oilseed crop and a bioenergy crop, respectively) climates. The oilseed crop in subtropical climate continued to uptake CO2 from the atmosphere throughout the year, with maximum uptake occurring in the monsoon season, and drastically reduced uptake during drought. The boreal ecosystem, on the other hand, was a sustained, small source of CO2 to the atmosphere during the snow-covered winter season. Higher rates of CO2 uptake were observed owing to greater day-length in the growing season in the boreal ecosystem. The optimal temperature for photosynthesis by the subtropical ecosystem was close to the regional normal mean temperature. An enhanced photosynthetic response to the incident radiation was found for the boreal ecosystem implying the bioenergy crop to be more efficient than the oilseed crop in utilizing the available light. This comparison of the CO2 exchange patterns will help strategising the carbon management under different climatic conditions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6

Similar content being viewed by others

References

  • Alegbejo M D, Iwo G A, Abo M E and Idowu A A 2003 Sesame: A potential industrial and export oilseed crop in Nigeria; J. Sustain. Agric. 23 59–76, https://doi.org/10.1300/J064v23n01.

    Article  Google Scholar 

  • Aubinet M, Grelle A, Ibrom A, Rannik Ü, Moncrieff J, Foken T, Kowalski A S, Martin P H, Berbigier P, Bernhofer C, Clement R, Elbers J, Granier A, Grünwald T, Morgenstern K, Pilegaard K, Rebmann C, Snijders W, Valentini R and Vesala T 1999 Estimates of the annual net carbon and water exchange of forests: The EUROFLUX methodology; Adv. Ecol. Res. 30 113–175, https://doi.org/10.1016/S0065-2504(08)60018-5.

    Article  Google Scholar 

  • Baldocchi D, Falge E, Gu L, Olson R, Hollinger D, Running S, Anthoni P, Bernhofer C, Davis K, Evans R, Fuentes J, Goldstein A, Katul G, Law B, Lee X, Malhi Y, Meyers T, Munger W, Oechel W, Paw U K T, Pilegaard K, Schmid H P, Valentini R, Verma S, Vesala T, Wilson K and Wofsy S 2001 FLUXNET: A new tool to study the temporal and spatial variability of ecosystem-scale carbon dioxide, water vapor, and energy flux densities; Bull. Am. Meteorol. Soc. 82 2415–2434, https://doi.org/10.1175/1520-0477(2001)082%3c2415:FANTTS%3e2.3.CO;2.

    Article  Google Scholar 

  • Bhattacharyya P, Neogi S, Roy K S, Dash P K, Tripathi R and Rao K S 2013a Net ecosystem CO2 exchange and carbon cycling in tropical lowland flooded rice ecosystem; Nutr. Cycl. Agroecosyst. 95 133–144, https://doi.org/10.1007/s10705-013-9553-1.

    Article  Google Scholar 

  • Bhattacharyya P, Neogi S, Roy K S and Rao K S 2013b Gross primary production, ecosystem respiration and net ecosystem exchange in Asian rice paddy: An eddy covariance-based approach; Curr. Sci. 104 67–75.

    Google Scholar 

  • Bisht I S, Mahajan R K, Loknathan T R and Agrawal R C 1998 Diversity in Indian sesame collection and stratification of germplasm accessions in different diversity groups; Genet. Resour. Crop Evol. 45 325–335, https://doi.org/10.1023/A:1008652420477.

    Article  Google Scholar 

  • Boureima S, Oukarroum A, Diouf M, Cisse N and Damme P Van 2012 Screening for drought tolerance in mutant germplasm of sesame (Sesamum indicum) probing by chlorophyll a fluorescence; Environ. Exp. Bot. 81 37–43, https://doi.org/10.1016/j.envexpbot.2012.02.015.

    Article  Google Scholar 

  • Burba G 2013 Eddy Covariance Method for Scientific, Industrial, Agricultural and Regulatory Applications; Li-Cor Biosciences.

    Google Scholar 

  • Chatterjee A, Roy A, Chakraborty S, Karipot A K, Sarkar C, Singh S, Ghosh S K, Mitra A and Raha S 2018 Biosphere atmosphere exchange of CO2, H2O vapour and energy during spring over a high altitude Himalayan forest at eastern India; Aerosol Air Qual. Res. 18 2704–2719, https://doi.org/10.4209/aaqr.2017.12.0605.

    Article  Google Scholar 

  • Ciais P, Reichstein M, Viovy N, Granier A, Ogée J, Allard V, Aubinet M, Buchmann N, Bernhofer C, Carrara A, Chevallier F, De Noblet N, Friend A D, Friedlingstein P, Grünwald T, Heinesch B, Keronen P, Knohl A, Krinner G, Loustau D, Manca G, Matteucci G, Miglietta F, Ourcival J M, Papale D, Pilegaard K, Rambal S, Seufert G, Soussana J F, Sanz M J, Schulze E D, Vesala T and Valentini R 2005 Europe-wide reduction in primary productivity caused by the heat and drought in 2003; Nature 437 529–533, https://doi.org/10.1038/nature03972.

    Article  Google Scholar 

  • Ciais P, Sabine C, Bala G, Bopp L, Brovkin V, Canadell J, Chhabra A, DeFries R, Galloway J, Heimann M, Jones C, Quéré C Le Myneni R B, Piao S and Thornton P 2013 The physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change; In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, https://doi.org/10.1017/CBO9781107415324.015.

  • Deb Burman P K, Prabha T V Morrison R and Karipot A 2018 A case study of turbulence in the nocturnal boundary layer during the Indian summer monsoon; Bound.-Layer Meteorol. 169 115–138, https://doi.org/10.1007/s10546-018-0364-4.

    Article  Google Scholar 

  • Deb Burman P K, Sarma D, Morrison R, Karipot A and Chakraborty S 2019 Seasonal variation of evapotranspiration and its effect on the surface energy budget closure at a tropical forest over north-east India; J. Earth Syst. Sci. 128 1–21, https://doi.org/10.1007/s12040-019-1158-x.

    Article  Google Scholar 

  • Deb Burman P K, Sarma D, Williams M, Karipot A and Chakraborty S 2017 Estimating gross primary productivity of a tropical forest ecosystem over north-east India using LAI and meteorological variables; J. Earth Syst. Sci. 126 1–16, https://doi.org/10.1007/s12040-017-0874-3.

    Article  Google Scholar 

  • Escobedo J F, Gomes E N, Oliveira A P and Soares J 2009 Modeling hourly and daily fractions of UV, PAR and NIR to global solar radiation under various sky conditions at Botucatu, Brazil; Appl. Energy 86 299–309, https://doi.org/10.1016/j.apenergy.2008.04.013.

    Article  Google Scholar 

  • Field C B, Barros V R, Dokken D J, Mach K J, Mastrandrea M D, Bilir T E, Chatterjee M, Ebi K L, Estrada Y O, Genova R C, Girma B, Kissel E S, Levy A N, MacCracken S, Mastrandrea P R and White L L 2014 Climate change 2014 impacts, adaptation and vulnerability: Part A: Global and sectoral aspects: Working group II contribution to the fifth assessment report of the intergovernmental panel on climate change. Climate Change 2014 Impacts, Adaptation and Vulnerability: Part A: Global and Sectoral Aspects, https://doi.org/10.1017/CBO9781107415379.

  • Foken T 2008 The energy balance closure problem: An overview; Ecol. Appl. 18 1351–1367, https://doi.org/10.1890/06-0922.1.

    Article  Google Scholar 

  • Foken T, Göckede M, Mauder M, Mahrt L, Amiro B and Munger W 2004 Post-field data quality control; In: Handbook of Micrometeorology, https://doi.org/10.1007/1-4020-2265-4.

  • Foken T and Wichura B 1996 Tools for quality assessment of surface-based flux measurements; Agric. For. Meteorol, https://doi.org/10.1016/0168-1923(95)02248-1.

    Book  Google Scholar 

  • Fu Y L, Yu G R, Sun X M, Li Y N, Wen X F, Zhang L M, Li Z Q, Zhao L and Hao Y Bin 2006 Depression of net ecosystem CO2 exchange in semi-arid Leymus chinensis steppe and alpine shrub; Agric. For. Meteorol. 137 234–244, https://doi.org/10.1016/j.agrformet.2006.02.009.

    Article  Google Scholar 

  • Gelaro R, McCarty W, Suárez M J, Todling R, Molod A, Takacs L, Randles C A, Darmenov A, Bosilovich M G, Reichle R, Wargan K, Coy L, Cullather R, Draper C, Akella S, Buchard V, Conaty A, da Silva A M, Gu W, Kim G K, Koster R, Lucchesi R, Merkova D, Nielsen J E, Partyka G, Pawson S, Putman W, Rienecker M, Schubert S D, Sienkiewicz M and Zhao B 2017 The modern-era retrospective analysis for research and applications, version 2 (MERRA-2); J. Clim. 30 5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1.

    Article  Google Scholar 

  • Gnanamoorthy P, Selvam V, Ramasubramanian R, Nagarajan R, Chakraborty S, Deb Burman P K and Karipot A 2019 Diurnal and seasonal patterns of soil CO2 efflux from the Pichavaram mangroves, India; Environ. Monit. Assess. 191 1–12, https://doi.org/10.1007/s10661-019-7407-2.

    Article  Google Scholar 

  • Gu S, Tang Y, Du M, Cui X, Kato T, Li Y and Zhao X 2005 Effects of temperature on CO2 exchange between the atmosphere and an alpine meadow effects of temperature on CO2 exchange between the atmosphere and an Alpine Meadow; Phyton 45 361–370.

    Google Scholar 

  • Huxman T E, Turnipseed A A, Sparks J P, Harley P C and Monson R K 2003 Temperature as a control over ecosystem CO2 fluxes in a high-elevation, subalpine forest; Oecologia 134 537–546, https://doi.org/10.1007/s00442-002-1131-1.

    Article  Google Scholar 

  • Jain A K, Khanna M, Erickson M and Huang H 2010 An integrated biogeochemical and economic analysis of bioenergy crops in the Midwestern United States; GCB Bioenergy 2 217–234, https://doi.org/10.1111/j.1757-1707.2010.01041.x.

    Article  Google Scholar 

  • Järveoja J, Laht J, Maddison M, Soosaar K, Ostonen I and Mander Ü 2013 Mitigation of greenhouse gas emissions from an abandoned Baltic peat extraction area by growing reed canary grass: Life-cycle assessment; Reg. Environ. Change 13 781–795, https://doi.org/10.1007/s10113-012-0355-9.

    Article  Google Scholar 

  • Kaimal J C and Finnigan J J 1994 Atmospheric Boundary Layer Flows: Their Structure and Measurement; Oxford University Press, Oxford.

    Book  Google Scholar 

  • Kandel T P, Elsgaard L and Karki S 2016 Biomass yield and greenhouse gas emissions from a drained fen peatland cultivated with reed canary grass under different harvest and fertilizer regimes; BioEnergy Res. 6 883–895, https://doi.org/10.1007/s12155-013-9316-5.

    Article  Google Scholar 

  • Karki S, Elsgaard L, Kandel T P and Lærke P E 2015 Full GHG balance of a drained fen peatland cropped to spring barley and reed canary grass using comparative assessment of CO2 fluxes; Environ. Monit. Assess., https://doi.org/10.1007/s10661-014-4259-7.

    Article  Google Scholar 

  • Kashiwar S R, Nath T, Kumar D, Kundu M C, Dongarwa U R, Rajput B S, Pandey S K and Dongarwar L N 2018 Evaluation of soil fertility status of Rajiv Gandhi South Campus (Banaras Hindu University), Mirzapur, Uttar Pradesh by using GIS; Int. J. Curr. Microbiol. Appl. Sci., Spec. Issue, pp. 3825–3836.

  • Kottek M, Grieser J, Beck C, Rudolf B and Rubel F 2006 World map of the Köppen–Geiger climate classification updated; Meteorol. Zeitschrift 15 259–263, https://doi.org/10.1127/0941-2948/2006/0130.

    Article  Google Scholar 

  • Kumar V and Sharma S N 2011 Comparative potential of phenotypic, ISSR and SSR markers for characterization of sesame (Sesamum indicum L.) varieties from India; J. Crop Sci. Biotechnol. 14 163–171, https://doi.org/10.1007/s12892-010-0102-z.

    Article  Google Scholar 

  • Lal M, Singh K, Srinivasan G, Rathore L, Naidu D and Tripathi C 1999 Growth and yield responses of soybean in Madhya Pradesh, India to climate variability and change; Agric. For. Meteorol. 93 53–70, https://doi.org/10.1016/S0168-1923(98)00105-1.

    Article  Google Scholar 

  • Lal M, Singh K K, Rathore L S, Srinivasan G and Saseendran S A 1998 Vulnerability of rice and wheat yields in NW India to future changes in climate; Agric. For. Meteorol. 89 101–114, https://doi.org/10.1016/S0168-1923(97)00064-6.

    Article  Google Scholar 

  • Lasslop G, Reichstein M, Papale D, Richardson A D, Arneth A, Barr A, Stoy P and Wohlfahrt G 2010 Separation of net ecosystem exchange into assimilation and respiration using a light response curve approach: critical issues and global evaluation; Glob. Chang. Biol. 16 187–208, https://doi.org/10.1111/j.1365-2486.2009.02041.x.

    Article  Google Scholar 

  • Le Quéré C, Andrew R M, Canadell J G, Sitch S, Ivar Korsbakken J, Peters G P, Manning A C, Boden T A, Tans P P, Houghton R A, Keeling R F, Alin S, Andrews O D, Anthoni P, Barbero L, Bopp L, Chevallier F, Chini L P, Ciais P, Currie K, Delire C, Doney S C, Friedlingstein P, Gkritzalis T, Harris I, Hauck J, Haverd V, Hoppema M, Klein Goldewijk K, Jain A K, Kato E, Kortzinger A, Landschutzer P, Lefevre N, Lenton A, Lienert S, Lombardozzi D, Melton J R, Metzl N, Millero F, Monteiro P M S, Munro D R, Nabel J E M S, Nakaoka S I, O’Brien K, Olsen A, Omar A M, Ono T, Pierrot D, Poulter B, Rodenbeck C, Salisbury J, Schuster U, Schwinger J, Seferian R, Skjelvan I, Stocker B D, Sutton A J, Takahashi T, Tian H, Tilbrook B, Van Der Laan-Luijkx I T, Van Der Werf G R, Viovy N, Walker A P, Wiltshire A J and Zaehle S 2016 Global Carbon Budget 2016; Earth Syst. Sci. Data 8 605–649, https://doi.org/10.5194/essd-8-605-2016.

    Article  Google Scholar 

  • Lind S E, Shurpali N J, Peltola O, Mammarella I, Hyvönen N, Maljanen M, Räty M, Virkajärvi P and Martikainen P J 2016 Carbon dioxide exchange of a perennial bioenergy crop cultivation on a mineral soil; Biogeoscience 13 1255–1268, https://doi.org/10.5194/bg-13-1255-2016.

    Article  Google Scholar 

  • Mall R K and Aggarwal P K 2002 Climate change and rice yields in diverse agro-environments of India. I: Evaluation of impact assessment models; Clim. Change 52 315–330, https://doi.org/10.1023/A:1013702105870.

    Article  Google Scholar 

  • Mammarella I, Peltola O, Nordbo A, Järvi L and Rannik Ü 2016 EddyUH: An advanced software package for eddy covariance flux calculation for a wide range of instrumentation and ecosystems; Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2015-323.

    Article  Google Scholar 

  • Mander Ü, Järveoja J, Maddison M, Soosaar K, Aavola R, Ostonen I and Salm J O 2012 Reed canary grass cultivation mitigates greenhouse gas emissions from abandoned peat extraction areas; GCB Bioenergy 4 462–474, https://doi.org/10.1111/j.1757-1707.2011.01138.x.

    Article  Google Scholar 

  • Matin S and Behera M D 2017 Alarming rise in aridity in the Ganga river basin, India, in past 3.5 decades; Curr. Sci, https://doi.org/10.1038/srep20716.

    Article  Google Scholar 

  • Mauder M, Cuntz M, Drüe C, Graf A, Rebmann C, Schmid H P, Schmidt M and Steinbrecher R 2013 A strategy for quality and uncertainty assessment of long-term eddy-covariance measurements; Agric. For. Meteorol. 169 122–135, https://doi.org/10.1016/j.agrformet.2012.09.006.

    Article  Google Scholar 

  • McCaughey J H, Pejam M R, Arain M A and Cameron D A 2006 Carbon dioxide and energy fluxes from a boreal mixedwood forest ecosystem in Ontario, Canada; Agric. For. Meteorol. 140 79–96, https://doi.org/10.1016/j.agrformet.2006.08.010.

    Article  Google Scholar 

  • Mishra V, Aadhar S, Akarsh A, Pai S and Kumar R 2016 On the frequency of the 2015 monsoon season drought in the Indo-Gangetic Plain; Geophys. Res. Lett., https://doi.org/10.1002/2016GL071407.

    Article  Google Scholar 

  • Moncrieff J B, Massheder J M, de Bruin H, Elbers J, Friborg T, Heusinkveld B, Kabat P, Scott S, Soegaard H and Verhoef A 1997 A system to measure surface fluxes of momentum, sensible heat, water vapour and carbon dioxide; J. Hydrol. 188189 589–611, https://doi.org/10.1016/S0022-1694(96)03194-0.

    Article  Google Scholar 

  • Moncrieff J, Clement R, Finnigan J and Meyers T 2004 Averaging, detrending and filtering of Eddy covariance time series; In: Handbook of Micrometeorology, https://doi.org/10.1007/1-4020-2265-4_2.

  • Myneni R Y K and Park T 2015 MCD15A3H MODIS/Terra+Aqua Leaf Area Index/FPAR 4-day L4 Global 500m SIN Grid V006; NASA EOSDIS Land Processes DAAC, https://doi.org/10.5067/MODIS/MCD15A3H.006.

  • Nakai T, Van Der Molen M K, Gash J H C and Kodama Y 2006 Correction of sonic anemometer angle of attack errors; Agric. For. Meteorol. 136 19–30, https://doi.org/10.1016/j.agrformet.2006.01.006.

    Article  Google Scholar 

  • Nath R, Chakraborty P K and Chakraborty A 2001 Effect of climatic variation on yield of sesame (Sesamum indicum L.) at different dates of sowing; J. Agron. Crop Sci. 186 97–102.

    Article  Google Scholar 

  • ORNL DAAC 2018 MODIS and VIIRS land products global subsetting and visualization tool; ORNL DAAC, Oak Ridge, Tennessee, USA. Subset obtained for MCD15A3H product at 25.06N, 82.59E, time period: 2014-01-01 to 2016-12-30 and subset size: 0.5×0.5 km, https://doi.org/10.3334/ORNLDAAC/1379.

  • Pai D S and Bhan S C 2014 Monsoon 2014. A Report (Vol. 01). Pune; http://www.imd.gov.in/section/nhac/monsoon_report_2014.pdf.

  • Papale D, Reichstein M, Aubinet M, Canfora E, Bernhofer C, Kutsch W, Longdoz B, Rambal S, Valentini R, Vesala T and others 2006 Towards a standardized processing of net ecosystem exchange measured with eddy covariance technique: Algorithms and uncertainty estimation; Biogeoscience 3 571–583, https://doi.org/10.5194/bg-3-571-2006.

    Article  Google Scholar 

  • Patel N R, Dadhwal V K and Saha S K 2011 measurement and scaling of carbon dioxide (CO2) exchanges in wheat using flux-tower and remote sensing; J. Indian Soc. Remote Sens. 39 383, https://doi.org/10.1007/s12524-011-0107-1.

    Article  Google Scholar 

  • Patra P K, Canadell J G, Houghton R A, Piao S L, Oh N H, Ciais P, Manjunath K R, Chhabra A, Wang T, Bhattacharya T, Bousquet P, Hartman J, Ito A, Mayorga E, Niwa Y, Raymond P A, Sarma V V S and Lasco R 2013 The carbon budget of South Asia; Biogeoscience 10 513–527, https://doi.org/10.5194/bg-10-513-2013.

    Article  Google Scholar 

  • Pinker R and Laszlo I 1992 Global distribution of photosynthetically active radiation as observed from satellites; J. Clim., https://doi.org/10.1175/1520-0442(1992)005%3c0056:GDOPAR%3e2.0.CO;2.

    Article  Google Scholar 

  • Prabha T V, Khain A, Maheskumar R S, Pandithurai G, Kulkarni J R and Goswami B N 2011 Microphysics of premonsoon and monsoon clouds as seen from in situ measurements during the cloud aerosol interaction and precipitation enhancement experiment (CAIPEEX); J. Atmos. Sci. 68 1882–1901, https://doi.org/10.1175/2011JAS3707.1.

    Article  Google Scholar 

  • Ramarao M V S, Sanjay J, Krishnan R, Mujumdar M, Bazaz A and Revi A 2018 On observed aridity changes over the semiarid regions of India in a warming climate; Theor. Appl. Climatol., https://doi.org/10.1007/s00704-018-2513-6.

    Article  Google Scholar 

  • Rannik Ü and Vesala T 1999 Autoregressive filtering versus linear detrending in estimation of fluxes by the eddy covariance method; Bound.-Layer Meteorol. 91 259–280, https://doi.org/10.1023/A:1001840416858.

    Article  Google Scholar 

  • Reichstein M, Falge E, Baldocchi D, Papale D, Aubinet M, Berbigier P, Bernhofer C, Buchmann N, Gilmanov T, Granier A, Grünwald T, Havránková K, Ilvesniemi H, Janous D, Knohl A, Laurila T, Lohila A, Loustau D, Matteucci G, Meyers T, Miglietta F, Ourcival J M, Pumpanen J, Rambal S, Rotenberg E, Sanz M, Tenhunen J, Seufert G, Vaccari F, Vesala T, Yakir D and Valentini R 2005 On the separation of net ecosystem exchange into assimilation and ecosystem respiration: Review and improved algorithm; Glob. Change Biol. 11 1424–1439, https://doi.org/10.1111/j.1365-2486.2005.001002.x.

    Article  Google Scholar 

  • Restaino C M, Peterson D L and Littell J 2016 Increased water deficit decreases Douglas fir growth throughout western US forests; Proc. Nat. Acad. Sci. 113 9557–9562, https://doi.org/10.1073/pnas.1602384113.

    Article  Google Scholar 

  • Rodda S, Thumaty K, Jha C and Dadhwal V 2016 Seasonal variations of carbon dioxide, water vapor and energy fluxes in tropical Indian mangroves; Forests 7 35, https://doi.org/10.3390/f7020035.

    Article  Google Scholar 

  • Sarma D, Kumar Baruah K, Baruah R, Gogoi N, Bora A, Chakraborty S and Karipot A 2018 Carbon dioxide, water vapour and energy fluxes over a semi-evergreen forest in Assam, northeast India; J. Earth Syst. Sci. 127 94, https://doi.org/10.1007/s12040-018-0993-5.

    Article  Google Scholar 

  • Sathyanadh A, Prabha T V, Balaji B, Resmi E A and Karipot A 2017 Evaluation of WRF PBL parameterization schemes against direct observations during a dry event over the Ganges valley; Atmos. Res. 193 125–141, https://doi.org/10.1016/j.atmosres.2017.02.016.

    Article  Google Scholar 

  • Schotanus P, Nieuwstadt F T M and De Bruin H A R 1983 Temperature measurement with a sonic anemometer and its application to heat and moisture fluxes; Bound.-Layer Meteorol. 26 81–93, https://doi.org/10.1007/BF00164332.

    Article  Google Scholar 

  • Shurpali N J, Hyvönen N P, Huttunen J T, Clement R J, Reichstein M, Nykänen H, Biasi C and Martikainen P J 2009 Cultivation of a perennial grass for bioenergy on a boreal organic soil-carbon sink or source? GCB Bioenergy 1 35–50, https://doi.org/10.1111/j.1757-1707.2009.01003.x.

    Article  Google Scholar 

  • Shurpali N J, Strandman H, Kilpeläinen A, Huttunen J, Hyvönen N, Biasi C, Kellomäki S and Martikainen P J 2010 Atmospheric impact of bioenergy based on perennial crop (reed canary grass, Phalaris arundinaceae, L) Cultivation on a drained boreal organic soil; GCB Bioenergy 2 130–138, https://doi.org/10.1111/j.1757-1707.2010.01048.x.

    Article  Google Scholar 

  • Solantie, R 2006 Temporal variation of evapotranspiration and growth in Finnish forest in relation to climate; Geophysica 42 35–54.

    Google Scholar 

  • Wagle P and Kakani V G 2014 Agriculture, ecosystems and environment environmental control of daytime net ecosystem exchange of carbon dioxide in switchgrass; Agric. Ecosyst. Environ. 186 170–177, https://doi.org/10.1016/j.agee.2014.01.028.

    Article  Google Scholar 

  • Wang B, Jin H, Li Q, Chen D, Zhao L, Tang Y, Kato T and Gu S 2017 Diurnal and seasonal variations in the net ecosystem CO2 exchange of a pasture in the three-river source region of the Qinghai–Tibetan Plateau; PLoS ONE 12 1–23, https://doi.org/10.1371/journal.pone.0170963.

    Article  Google Scholar 

  • Wang K and Dickinson R E 2012 A review of global terrestrial evapotranspiration: Observation, modelling, climatology and climatic variability; Rev. Geophys. 50 1–54, https://doi.org/10.1029/2011RG000373.

    Article  Google Scholar 

  • Watham T, Kushwaha S P, Patel N R and Dadhwal V K 2014 Monitoring of carbon dioxide and water vapour exchange over a young mixed forest plantation using eddy covariance technique; Curr. Sci. 107 858–866.

    Google Scholar 

  • Watson D J 1947 Comparative physiological studies on the growth of field crops: I. Variation in net assimilation rate and leaf area between species and varieties and within and between years; Ann. Bot. 11 41–76, https://doi.org/10.1093/oxfordjournals.aob.a083148.

    Article  Google Scholar 

  • Webb E K, Pearman G I and Leuning R 1980 Correction of flux measurements for density effects due to heat and water vapour transfer; Q. J. R. Meteorol. Soc. 106 85–100, https://doi.org/10.1002/qj.49710644707.

    Article  Google Scholar 

  • Wutzler T, Lucas-Moffat A, Migliavacca M, Knauer J, Sickel K, Šigut L, Menzer O and Reichstein M 2018 Basic and extensible post-processing of eddy covariance flux data with REddyProc; Biogeosci. Discuss. 15 1–39, https://doi.org/10.5194/bg-2018-56.

    Article  Google Scholar 

Download references

Acknowledgements

We thank the National Data Centre, India Meteorological Department, Pune for providing the long term temperature and rainfall measurements at Varanasi. We also acknowledge the partial funding support for this work from the Academy of Finland (311970—INDO-NORDEN, 296423—CAPTURE), Ministry of Forestry and Agriculture, Finland and the Niemi Foundation, Helsinki, Finland. We thank 3TIER Inc. (https://www.solarpowerworldonline.com/suppliers/3tier/) for making available the solar radiation data at Varanasi for research purpose. The surface measurement data used in this work can be obtained for research purpose by contacting Dr Narasinha J Shurpali at narasinha.shurpali@uef.fi and Dr. Thara V Prabha at thara@tropmet.res.in.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Pramit Kumar Deb Burman.

Additional information

Communicated by Kavirajan Rajendran

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Deb Burman, P.K., Shurpali, N.J., Chowdhuri, S. et al. Eddy covariance measurements of CO2 exchange from agro-ecosystems located in subtropical (India) and boreal (Finland) climatic conditions. J Earth Syst Sci 129, 43 (2020). https://doi.org/10.1007/s12040-019-1305-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12040-019-1305-4

Keywords

Navigation