Carbon use efficiency variability from MODIS data
Submitted: 2017-01-09
|Accepted: 2017-03-24
|Published: 2017-06-20
Downloads
Keywords:
carbon use efficiency (CUE), GPP, NPP, MODIS
Supporting agencies:
Proyectos ERMES (FP7/2007-2013) y ESCENARIOS (MINECO/FEDER
CGL2016- 75239-R)
Abstract:
Carbon use efficiency (CUE) describes how efficiently plants incorporate the carbon fixed during photosynthesis into biomass gain and can be calculated as the ratio between net primary production (NPP) and gross primary production (GPP). In this work, annual CUE has been obtained from annual GPP and NPP MODIS products for the peninsular Spain study area throughout eight years. CUE is spatially and temporally analyzed in terms of the vegetation type and annual precipitation and annual average air temperature. Results show that dense vegetation areas with moderate to high levels of precipitation present lower CUE values, whereas more arid areas present the highest CUE values. However, the temperature effect on the spatial variation of CUE is not well characterized. On the other hand, inter-annual variations of CUE of different ecosystems are discussed in terms of inter-annual variations of temperature and precipitation. It is shown that CUE exhibited a positive correlation with precipitation and a negative correlation with temperature in most ecosystems. Thus, CUE decreases when the ecosystem conditions change towards aridity.
References:
Albrizio, R., Steduto, P. 2003. Photosynthesis, respiration and conservative carbon use efficiency of four field grown crops. Agricultural and Forest Meteorology, 116(1-2), 19-36. https://doi. org/10.1016/S0168-1923(02)00252-6
Alcaraz, D., Paruelo, J., Cabello, J. 2006. Identification of current ecosystem functional types in the Iberian Peninsula. Global Ecology and Biogeography, 15(2), 200-212.
https://doi.org/10.1111/j.1466- 822X.2006.00215.x
Atkin, O. K., Bloomfield, K. J., Reich, P. B., et al. 2015. Global variability in leaf respiration in relation to climate, plant functional types and leaf traits. New Phytologist, 206(2), 614-636. https://doi. org/10.1111/nph.13253
Baba, K., Shibata, R., Sibuya, M. 2004. Partial correlation and conditional correlation as measures of conditional independence. Australian & New Zealand Journal of Statistics, 46(4), 657-664. https://doi.org/10.1111/j.1467-842X.2004.00360.x
Bastos, A., Gouveia, C.M., Trigo, R.M., Running, S.W. 2014. Analysing the spatio-temporal impacts of the 2003 and 2010 extreme heatwaves on plant productivity in Europe. Biogeosciences, 11, 3421- 3435. https://doi.org/10.5194/bg-11-3421-2014
Bradford, M.A., Crowther, T.W. 2013. Carbon use efficiency and storage in terrestrial ecosystems (Commentary). New Phytologist, 199(1), 7-9. https://doi.org/10.1111/nph.12334
Campioli, M., Gielsen, B., Göckede, M., Papale, D., Bouriaud, O., Granier, A. 2011. Temporal variability of the NPP-GPP ratio at seasonal and interannual time scales in a temperate beech forest. Biogeosciences, 8, 2481-2492. https://doi.org/10.5194/bg-8-2481- 2011
Channan, S., K. Collins, Emanuel, W. R. 2014. Global mosaics of the standard MODIS land cover type data. University of Maryland and the Pacific Northwest National Laboratory, College Park, Maryland, USA.
Frantz, J.M., Bugbee, B. 2005. Acclimation of plant population to shade: Photosynthesis, respiration, and carbon use efficiency. Journal of the American Society for Horticultural Science, 130, 918-927.
Garbulsky, M. F., Peñuelas, J., Papale, D., Ardö, J., Goulden, M.L., Kiely, G., Richardson, A.D., Rotenberg, E., Veenendaal, E.M., Filella, I. 2010. Patterns and Controls of the Variability of Radiation Use Efficiency and Primary Productivity across Terrestrial Ecosystems. Global Ecology and Biogeography, 19(2), 253-267. https://doi. org/10.1111/j.1466-8238.2009.00504.x
Gilabert, M. A., Moreno, A., Maselli, F. Martínez, B., Chiesi, M., Sánchez-Ruis, S., García-Haro, F.J., Pérez-Hoyos, A., Campos-Taberner, M., PérezPriego, O., Serrano-Ortiz, P., Carrara, A. 2015. Daily GPP estimates in Mediterranean ecosystems by combining remote sensing and meteorological data, ISPRS J. Photogramm. Remote Sens., 102, 184-197. https://doi.org/10.1016/j.isprsjprs.2015.01.017
Golinkoff, J., 2010. Biome BGC version 4,2: The Theoretical Framework. Numerical Terradynamic Simulation Group, College of Forestry and Conservation, University of Montana, Missoula, MT, USA.
Immerzeel, W.W., Rutten, M.M., Droogers, P. 2009. Spatial downscaling of TRMM precipitation using vegetative response on the Iberian Peninsula. Remote Sensing of Environment, 113(2), 362-370. https://doi.org/10.1016/j.rse.2008.10.004
MAGRAMA. 2007. Tercer Inventario Forestal Nacional (IFN3) 1997-2007. Ministerio de Agricultura y Pesca, Alimentación y Medio Ambiente (http:// www.mapama.gob.es/).
Mäkelä, A., Valentine, H.T. 2001. The ratio of NPP to GPP: evidence of change over the course of stand development. Tree Phisiology, 21, 1015-1030. https://doi.org/10.1093/treephys/21.14.1015
Metcalfe, D. B., Meir, P., Aragão, L. E. O. C., Lobo-doVale, R., Galbraith, D., Fisher, R. A., et al., 2010. Shifts in plant respiration and carbon use efficiency at a large-scale drought experiment in the eastern Amazon. New Phytologist, 187, 608-621. https://doi. org/10.1111/j.1469-8137.2010.03319.x
Monteith, J.L. 1972. Solar radiation and productivity in tropical ecosystems. Journal of Applied Ecology, 9, 747-766. https://doi.org/10.2307/2401901
Moreno, A., Gilabert, M. A., Martínez, B. 2011. Mapping daily global solar irradiation over Spain: A comparative study of selected approaches. Solar Energy, 85(9), 2072-2084.
https://doi.org/10.1016/j. solener.2011.05.017
Myneni, R., Knyazikhin, Y., Park T. 2015. MYD15A2H MODIS/Aqua Leaf Area Index/FPAR 8-Day L4 Global 500m SIN Grid V006. NASA EOSDIS Land Processes DAAC. https://doi.org/10,5067/MODIS/ MYD15A2H.006
Reichstein, M., Falge, E., Baldocchi, D., Papale, D., Aubinet, M., Berbigier, P., et al. 2005. On the separation of net ecosystem exchange into assimilation and ecosystem respiration: Review and improved algorithm. Global Change Biology, 11, 1424-1439. https://doi.org/10.1111/j.1365- 2486.2005.001002.x
Röder, A., Udelhoven, Th., Hill, J., del Barrio, G., Tsiourlis, G. 2008. Trend analysis of Landsat-TM and -ETM+ imagery to monitor grazing impact in a rangeland ecosystem in Northern Greece. Remote Sensing of Environment, 112(6), 2863-2875. https:// doi.org/10.1016/j.rse.2008.01.018
Running, S.W., Nemani, R.R., Heinsch, F.A., Zhao, M., Reeves, M., Hashimoto, H. 2004. A Continuous Satellite-Derived Measure of Global Terrestrial Primary Production. BioScience, 54(6), 547-560. http://dx.doi.org/10.1641/0006-3568(2004)054[0547:ACSMOG]2.0.CO;2
Running, S. W., Zhao, M. 2015. Daily GPP and Annual NPP (MOD17A2/A3) Products NASA Earth Observing System MODIS Land Algorithm. MOD17 User’s Guide, 28 pp.
Tang, J., Luyssaert, S., Richardson, A.D., Kutsch, W., Janssens, I.A. 2014. Steeper declines in forest photosynthesis than respiration explain age-driven decreases in forest growth. PNAS, 111, 8856-8860. https://doi.org/10.1073/pnas.1320761111
Vicente-Serrano, S. M., Pérez-Cabello, F., Lasanta, T. 2008. Assessment of radiometric correction techniques in analyzing vegetation variability and change using time series of Landsat images. Remote Sensing of Environment, 112(10), 3916-3934. https://doi.org/10.1016/j.rse.2008.06.011
Wackernagel, H. 2013. Multivariate Geostatistics: An Introduction with Applications. Springer-Verlag, Berlin, 388 pp. Waring, R.H., Landsberg, J.J., Williams, M. 1998. Net primary production of forests: a constant fraction of gross primary production? Tree Physiology, 18, 129- 134.
Waring, R.H., Landsberg, J.J., Williams, M. 1998. Net primary production of forests: a constant fraction of gross primary production? Tree Physiology, 18, 129-134.
Waring, R.H., Running, S.W., 2007. Carbon cycle, en Forest Ecosystems. Analysis at multiple scales, Third edition, Elsevier Academic Press, pp. 59-98.
Zhang, Y., Xu, M., Chen, H., Adams, J. 2009. Global pattern of NPP to GPP ratio derived from MODIS data: effects of ecosystem type, geographical location and climate. Global Ecology and Biogeographie, 18, 280-290. https://doi.org/10.1111/j.1466- 8238.2008.00442.x
Zhang, Y., Yu, G., Yang, J., Wimberly, M.C., Zhang, X., Tao, J., Jiang, Y., Zhu, J., 2014. Climate-driven global changes in carbon use efficiency. Global Ecol. Biogeogr., 23, 144-155. http://doi.org/10.1111/ geb.12086
Zhao, M., Running, S.W. 2010. Drought-induced reduction in global terrestrial net primary production from 2000 through 2009. Science, 329(5994), 940- 943. https://doi.org/10.1126/science.1192666