Suitability of the boreal ecosystem simulator (BEPS) model for estimating gross primary productivity in hemi-boreal upland pine forest
By: Fariha Harun, Kaido Soosaar, Alisa Krasnova and Jan Pisek
References
- Beer, C., Reichstein, M., Tomelleri, E., Ciais, P., Jung, M., Carvalhais, N., Rödenbeck, C., Arain, M.A., Baldocchi, D., Bonan, G.B., Bondeau, A., Cescatti, A., Lasslop, G., Lindroth, A., Lomas, M., Luyssaert, S., Margolis, H., Oleson, K.W., Roupsard, O., Veenendaal, E., Viovy, N., Williams, C., Woodward, F.I., Papale, D. 2010. Terrestrial gross carbon dioxide uptake: Global distribution and covariation with climate. – Science, 329(5993), 834–838.
https://doi.org/10.1126/science.1184984 . - Bonan, G.B. 1995. Land-atmosphere CO2 exchange simulated by a land surface process model coupled to an atmospheric general circulation model. – Journal of Geophysical Research Atmospheres, 100(D2), 2817–2831.
https://doi.org/10.1029/94JD02961 . - Chen, J.M., Liu, J., Cihlar, J., Goulden, M.L. 1999. Daily canopy photosynthesis model through temporal and spatial scaling for remote sensing applications. – Ecological Modelling, 124(2–3), 99–119.
https://doi.org/10.1016/s0304-3800(99)00156-8 . - Estonian Environment Agency. 2020. Keskkonnaagentuur (KAUR). [WWW document]. – URL
https://www.keskkonnaagentuur.ee/en . [Accessed 26 December 2020]. - Estonian Weather Service. 2021. Ilmateenistus. [WWW document]. – URL
https://www.ilmateenistus.ee/?lang=en . [Accessed 17 April 2021]. - Feng, X., Liu, G., Chen, J.M., Chen, M., Liu, J., Ju, W.M., Sun, R., Zhou, W. 2007. Net primary productivity of China’s terrestrial ecosystems from a process model driven by remote sensing. – Journal of Environmental Management, 85(3), 563–573.
https://doi.org/10.1016/j.jenvman.2006.09.021 . - He, L., Chen, J.M., Pisek, J., Schaaf, C.B., Strahler, A.H. 2012. Global clumping index map derived from the MODIS BRDF product. – Remote Sensing of Environment, 119, 118–130.
https://doi.org/10.1016/j.rse.2011.12.008 . - Heiskanen, J., Rautiainen, M., Stenberg, P., Mõttus, M., Vesanto, V.-H., Korhonen, L., Majasalmi, T. 2012. Seasonal variation in MODIS LAI for a boreal forest area in Finland. – Remote Sensing of Environment, 126, 104–115.
https://doi.org/10.1016/j.rse.2012.08.001 . - Ju, W., Chen, J.M., Black, T.A., Barr, A.G., Liu, J., Chen, B., 2006. Modelling multi-year coupled carbon and water fluxes in a boreal aspen forest. – Agricultural and Forest Meteorology, 140(1–4), 136–151.
http://dx.doi.org/10.1016/j.agrformet.2006.08.008 . - Kljun, N., Calanca, P., Rotach, M.W., Schmid, H.P. 2015. A simple two-dimensional parameterisation for Flux Footprint Prediction (FFP). – Geoscientific Model Development, 8(11), 3695–3713.
- Li, X., Zhu, Z., Zeng, H., Piao, S. 2016. Estimation of gross primary production in China (1982–2010) with multiple ecosystem models. – Ecological Modelling, 324, 33–44.
https://doi.org/10.1016/j.ecolmodel.2015.12.019 . - Liang, S., Shuey, C.J., Russ, A.L., Fang, H., Chen, M., Walthall, C.L., Daughtry, C.S.T., Hunt, R. Jr. 2003. Narrowband to broadband conversions of land surface albedo: II. Validation. – Remote Sensing of Environment, 84(1), 25–41.
https://doi.org/10.1016/S0034-4257(02)00068-8 . - Liu, J., Chen, J.M., Cihlar, J., Chen, W. 1999. Net primary productivity distribution in the BOREAS region from a process model using satellite and surface data. – Journal of Geophysical Research Atmospheres, 104(D22), 27735–27754.
https://doi.org/10.1029/1999JD900768 . - Liu, J., Chen, J.M., Cihlar, J., Chen, W. 2002. Net primary productivity mapped for Canada at 1-km resolution. – Global Ecology and Biogeography, 11(2), 115–129.
https://doi.org/10.1046/j.1466-822X.2002.00278.x . - Liu, J., Chen, J.M., Cihlar, J., Park, W.M. 1997. A process-based boreal ecosystem productivity simulator using remote sensing inputs. – Remote Sensing of Environment, 62(2), 158–175.
https://doi.org/10.1016/S0034-4257(97)00089-8 . - Liu, S., Zhuang, Q., He, Y., Noormets, A., Chen, J., Gu, L. 2016. Evaluating atmospheric CO2 effects on gross primary productivity and net ecosystem exchanges of terrestrial ecosystems in the conterminous United States using the AmeriFlux data and an artificial neural network approach. – Agricultural and Forest Meteorology, 220, 38–49.
https://doi.org/10.1016/j.agrformet.2016.01.007 . - Lloyd, J., Taylor, J.A. 1994. On the temperature dependence of soil respiration. – Functional Ecology, 8(3), 315–323.
https://www.jstor.org/stable/2389824 . - Lõhmus, E. 2004. Forest site types in Estonia. (Eesti metsakasvukohatüübid). Tartu, Eesti Loodusfoto. 80 pp. (In Estonian).
- Luo, X., Croft, H., Chen, J.M., Bartlett, P., Staebler, R., Froelich, N. 2018. Incorporating leaf chlorophyll content into a two-leaf terrestrial biosphere model for estimating carbon and water fluxes at a forest site. – Agricultural and Forest Meteorology, 248, 156–168.
https://doi.org/10.1016/j.agrformet.2017.09.012 . - Ma, L., Bicking, S., Müller, F. 2019. Mapping and comparing ecosystem service indicators of global climate regulation in Schleswig-Holstein, Northern Germany. – Science of The Total Environment, 648, 1582–1597.
https://doi.org/10.1016/j.scitotenv.2018.08.274 . - Nilson, T. 1971. A theoretical analysis of the frequency of gaps in plant stands. – Agricultural Meteorology, 8, 25–38.
https://doi.org/10.1016/0002-1571(71)90092-6 . - Pisek, J., Lang, M., Nilson, T., Korhonen, L., Karu, H. 2011. Comparison of methods for measuring gap size distribution and canopy nonrandomness at Järvselja RAMI (RAdiation transfer Model Intercomparison) test sites. – Agricultural and Forest Meteorology, 151(3), 365–377.
https://doi.org/10.1016/j.agrformet.2010.11.009 . - 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., Valentini, R. 2005. On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm. – Global Change Biology, 11(9), 1424–1439.
https://doi.org/10.1111/j.1365-2486.2005.001002.x . - Román, M.O., Schaaf, C.B., Woodcock, C.E., Strahler, A.H., Yang, X., Braswell, R.H., Curtis, P.S., Davis, K.J., Dragoni, D., Goulden, M.L., Gu, L., Hollinger, D.Y., Kolb, T.E., Meyers, T.P., Munger, J.W., Privette, J.L., Richardson, A.D., Wilson, T.B., Wofsy, S.C. 2009. The MODIS (Collection V005) BRDF/albedo product: Assessment of spatial representativeness over forested landscapes. – Remote Sensing of Environment, 113(11), 2476–2498.
https://doi.org/10.1016/j.rse.2009.07.009 . - Shi, H., Li, L., Eamus, D., Huete, A., Cleverly, J., Tian, X., Yu, Q., Wang, S., Montagnani, L., Magliulo, V., Rotenberg, E., Pavelka, M., Carrara, A. 2017. Assessing the ability of MODIS EVI to estimate terrestrial ecosystem gross primary production of multiple land cover types. – Ecological Indicators, 72, 153–164.
https://doi.org/10.1016/j.ecolind.2016.08.022 . - Smith, R.B. 2010. The heat budget of the earth’s surface deduced from space. [WWW document]. – URL
https://yceo.yale.edu/sites/default/files/files/Surface_Heat_Budget_From_Space.pdf . [Accessed 31 October 2021]. - USGS. 2021. MCD15A3H product. [WWW document]. – URL
https://doi.org/10.5067/MODIS/MCD15A3H.006 . [Accessed 23 December 2021]. - Wang, Z., Schaaf, C.B., Chopping, M.J., Strahler, A.H., Wang, J., Román, M.O., Rocha, A.V., Woodcock, C.E., Shuai, Y. 2012. Evaluation of moderate-resolution imaging spectroradiometer (MODIS) snow albedo product (MCD43A) over tundra. – Remote Sensing of Environment, 117, 264–280.
https://doi.org/10.1016/j.rse.2011.10.002 . - Wang, Z., Schaaf, C.B., Strahler, A.H., Chopping, M.J., Román, M.O., Shuai, Y., Woodcock, C.E., Hollinger, D.Y., Fitzjarrald, D.R. 2014. Evaluation of MODIS albedo product (MCD43A) over grassland, agriculture and forest surface types during dormant and snow-covered periods. – Remote Sensing of Environment, 140, 60–77.
https://doi.org/10.1016/j.rse.2013.08.025 . - Wang, Z., Schaaf, C.B., Sun, Q., Kim, J., Erb, A.M., Gao, F., Román, M.O., Yang, Y., Petroy, S., Taylor, J.R., Masek, J.G., Morisette, J.T., Zhang, X., Papuga, S.A. 2017. Monitoring land surface albedo and vegetation dynamics using high spatial and temporal resolution synthetic time series from Landsat and the MODIS BRDF / NBAR / albedo product. – International Journal of Applied Earth Observations and Geoinformation, 59, 104–117.
https://doi.org/10.1016/j.jag.2017.03.008 . - Wu, C., Munger, J.W., Niu, Z., Kuang, D. 2010. Comparison of multiple models for estimating gross primary production using MODIS and eddy covariance data in Harvard Forest. – Remote Sensing of Environment, 114(12), 2925–2939.
https://doi.org/10.1016/j.rse.2010.07.012 . - Wutzler, T., Lucas-Moffat, A., Migliavacca, M., Knauer, J., Sickel, K., Šigut, L., Menzer, O., Reichstein, M. 2018. Basic and extensible post-processing of eddy covariance flux data with REddyProc. – Biogeosciences, 15(16), 5015–5030.
https://doi.org/10.5194/bg-15-5015-2018 . - Zhang, F., Chen, J.M., Chen, J., Gough, C.M., Martin, T.A., Dragoni, D. 2012. Evaluating spatial and temporal patterns of MODIS GPP over the conterminous U.S. against flux measurements and a process model. – Remote Sensing of Environment, 124, 717–729.
https://doi.org/10.1016/j.rse.2012.06.023 . - Zhu, X., Pei, Y., Zheng, Z., Dong, J., Zhang, Y., Wang, J., Chen, L., Doughty, R.B., Zhang, G., Xiao, X. 2018. Underestimates of grassland gross primary production in MODIS standard products. – Remote Sensing, 10(11), 1771.
https://doi.org/10.3390/rs10111771 .
Language: English
Page range: 1 - 14
Submitted on: Nov 8, 2021
Accepted on: Dec 25, 2021
Published on: Jun 4, 2022
Published by: Estonian University of Life Sciences
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year
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© 2022 Fariha Harun, Kaido Soosaar, Alisa Krasnova, Jan Pisek, published by Estonian University of Life Sciences
This work is licensed under the Creative Commons Attribution 4.0 License.