The canopy net photosynthesis rate of Mongolian oak (
Quercus mongolica
) tree species that are dominant in East Asia and Korea is estimated with empirical models derived from field experimental data obtained from the Nam-San site in Seoul, Korea for the growing period from early May to late October in 2010. The empirical models include the attenuation function of photosynthetic photon flux density (PPFD) (
r
2
= 0.98
-0.99, p < 0.001) and the photosynthetic light response function (r2 = 0.99, p < 0.001) derived from the measured data at several levels within the canopy. The incident PPFD at each level within canopy significantly varies diurnally and seasonally due to the seasonal variation of the total plant area index (TPAI = leaf area index + wood silhouette area index) and the light shielding effect of light path-length through the canopy in association with the variation of solar elevation angle. Consequently, a remarkable seasonal variation of the total canopy net photosynthesis rate of Q. mongolica forest stand is found for its growing period. The PPFD exceeding 1000 μmol m-2·s-1 is found to cause the decrease of net photosynthesis rate due to the thermal stress in the early (May) and late (September) growing period. During the whole growing season, the estimated total canopy net photosynthesis rate is found to be about 3.3 kg CO2 m-2.
Mongolian Oak (Quercus mongolica) Canopy Net Photosynthesis Rate PPFD TPAI Solar Elevation Angle1. Introduction
A better understanding on the response of forest against current environmental factors is prerequisite for an accurate estimation of the potential global carbon cycle in association with future climate changes [1] [2] [3] . Therefore, much attention has been given to the subject of quantifying and identifying the carbon budget of forest ecosystems in the regional and global scales, whether the forest ecosystem is a sink or a source for atmospheric CO2 [4] [5] .
The net carbon acquisition of forest ecosystem, as well as the net primary pro- ductivity (NPP) depends principally on the photosynthetic capacity and respiration of the ecosystem in the growing season of a given forest [6] [7] . The rate of instantaneous photosynthetic assimilation is one of the most important factors in determining the rate of CO2 exchange between the atmosphere and forest eco- systems [8] [9] .
Many studies have been extensively focused on photosynthetic characteristics at the leaf level, including comparisons of different functional types, biochemistry and eco-physiology of plant species, and leaf morphologies [10] [11] . However, the structural distribution of plant’s organs has rarely been studied even though it affects significantly the canopy photosynthesis rate at the stand level through the changes of the transmittance and interception patterns of the incident light within the canopy [12] [13] .
The forest canopy photosynthesis depends upon its own eco-physiological and architectural properties [14] , and meteorological factors such as light incidence, air temperature and humidity, atmospheric CO2 concentration and wind speed [15] . Among all these parameters, the light condition that is measured by the photosynthetic photon flux density (PPFD) is a main driving parameter in determining photosynthetic characteristics, and other biological and environmental conditions within the canopy [16] [17] [18] . The light response of photosynthesis of an individual leaf and the attenuation of PPFD in the canopy largely depend on the distribution of leaf area within the canopy [19] so that the detailed distribution of PPFD at different levels of the forest canopy is a prerequisite for the accurate estimation of the photosynthesis rate [20] [21] .
Eco-physiological measurements in the processes of the forest ecosystem can provide crucial parameters for the canopy photosynthesis modeling [22] [23] . For example, the leaf area index (LAI), defined as the projected area of foliage per unit ground surface area (m2∙m−2), is a very useful quantitative measure for the quantity of forest foliages [24] [25] and regulates the spatial and temporal distribution patterns of PPFD [26] . Thus, accurate measurements of seasonal variations of LAI and the leaf-level photosynthetic capacity that is affected by environment conditions (light, temperature, humidity and precipitation etc.) are required for estimating eco-physiological ecosystem processes (photosynthesis and respiration) [27] [28] .
Cool-temperate deciduous forests are widely distributed in East Asia including southeastern Siberia, northern China, central and northern Japan and the Korean Peninsula [11] [29] . These forests are regarded as significant sinks for atmospheric CO2 [30] . In Korea, the forested region is located within the complex terrain of mountainous regions, which occupies about 65 % (6.3 × 106 hectare) of the whole territorial area. Deciduous and mixed forests of broad-leaved species are predominant with the area of 1.7 × 106 hectare and 1.9 × 106 hectare, respectively. They account for about 56 % of all Korean forests. In particular, Mongolian oak (Quercus mongolica) forest stand is one of the typical deciduous broad-leaved forest types in the Korean Peninsula [31] .
However, photosynthetic assimilation mechanisms, as well as biological pro- cesses and modeling at the forest stand level of Q. mongolica species in Korea have rarely been studied due to the lack of observed eco-physiological and phenological parameters for this forest, even though the CO2 sequestration behaviors in Q. mongolica forest stands may have a great effect on the balance of carbon budgets [32] .
The purpose of this study is to estimate the canopy net photosynthesis rate of Q. mongolica forest stand for the growing period at the Nam-San ecological- experimental site with optimally derived photosynthetic light response curves and LAIs at several layers within the canopy with the use of the measured photosynthesis rates and the modified PPFDs by total plant area index (TPAI).
2. Materials and Methods2.1. Field Experimental Site
Field experiments were conducted in a secondary Mongolian oak (Quercus mongolica) forest at the Nam-San Ecological Experimental site located in central Seoul city surrounded by urban complexes having various CO2 sources in the west-central part of the Korean Peninsula (Figure 1). The experimental site is located at 126˚59'E and 37˚33'N with a northeastern aspect, a gentle slope and an elevation of 220 m in a cool-temperate zone under the influence of Asian monsoon climate with a mild in springs and autumns, hot and humid in summers, and cold and snowy in winters. The climate data from Seoul Weather Station (belonging to Korea Meteorological Administration) close to the experimental site indicate that the annual mean air temperature and annual total precipitation are 11.8˚C (minimum of −3.4˚C in January and maximum of 25.4˚C in August) and 1369.8 mm , respectively. A tower-based continuous measurement of CO2 flux between the forest and atmosphere, soil CO2 effluxes with automatic opening/closing chamber systems and various meteorological elements in the forest ecosystem have been made continuously since 2008 [33] .
The vegetation at the site is classified as an approximately 49 - 55 years old deciduous broad-leaved forest, composed mainly of Q. mongolica. The predominant tree stand of Q. mongolica has an average diameter at breast height (DBH) of 23.2 cm and a total basal area of 22.1 m2∙ha−1. The continuous canopy height and density in Q. mongolica trees are about 15.1 m and 482 ha−1, respectively. The mid- and understory vegetation under the dominant tree canopy of this site is rarely composed of few trees with Sorbus alnifolia, Styrax japonica, Acer pseudo-sieboldianum species. All leaves of these deciduous species at the site usually begin to flush in late April, and to fall in November. The starting times of leaf unfolding and shedding of Q. mongolica trees were, respectively 27 April and 30 October in 2010. More detailed descriptions of the Nam-San eco-
The geographical location of (a) Seoul, Korea. The topography of (b) Mt. Nam in Seoul with the indication of the ecological-experimental site ( ) in the Q. mongolica forest stand during the whole growing season (May-October) in 2010
maximum value is about 0.87 kg CO2 m−2 month−1 (1.02 kg CO2 m−2 month−1) in June. However, in spite of the mid growing period of August, the canopy net photosynthesis rate is as low as 0.43 kg CO2 m−2 month−1 due to the cloudy weather in August and the monthly total daylight hour was about 60% of that in June (Figure 10). During the whole growing period (May to October) of 2010 at the site, the estimated total canopy net photosynthesis rate with (PPFD)t (PPFD) is found to be about 3.3 kg CO2 m−2 (3.9 kg CO2 m−2) that is within the range of 3.3 - 4.3 kg CO2 m−2 yr−1 for various cool-temperate deciduous forests estimated by Falge et al. [9] and Muraoka et al. [13] .
In the whole growing season, the estimated total canopy net photosynthesis rate with (PPFD)t is approximately 14% (0.6 kg CO2 m−2) lower than that estimated with PPFD, suggesting the total canopy net photosynthesis rate being significantly affected by the seasonal variations of the effective TPAI and the relative (PPFD)t within different canopy layers. This also suggests that the present method has a great potential for more accurate estimation of the photosynthesis rate in the forest stand.
5. Conclusions
Field measurements have been conducted throughout the growing season of the Q. mongolica forest at the Nam-San ecological experimental site in Seoul, Korea from May to October in 2010. An empirical model for the estimation of canopy net photosynthesis rate of Q. mongolica forest stand has been developed using the field experimental data by constructing the photosynthetic light response curve, vertical distributions of the leaf area index (LAI) and the photosynthetic photon flux density (PPFD) measured at around noon within the canopy of five levels (0.5, 9, 12, 14 and 15 m heights).
It is found that LAIs within the canopy layers of the Q. mongolica forest stand show distinct seasonal variations with a maximum of 4.6 m2∙m−2 at the lowest canopy level (0.5 m above the ground) in July. The increasing rate of LAI is rather large during the leaf expansion period (late April to May) at all levels within the canopy compared to the decreasing rate during the leaf-litter fall period (late October to November). It is also found that the observed PPFD within the canopy can be properly regressed by the Beer-Lambert’s law with the observed total plant area index (TPAI) within the canopy. The estimated light extinction coefficients (β) are found to be a maximum value of 0.92 - 0.97 in the early growing season (May) and the late growing season (October) with a near constant value of 0.57 - 0.59 during the peak growing season (June to August), suggesting a significant amount of PPFD being extinguished by the branch and stem (wood silhouette area index) during the early and late growing seasons.
The photosynthetic light response curve for the leaves of Q. mongolica is found to show a great increase of the net photosynthesis rate with the increase of PPFD in the peak growing seasons of June and July in 2010. However, in the early growing period of May and the late growing period of September the PPFD exceeding 1000 μmol∙m−2∙s−1 is founded to cause the decrease of the net photosynthesis rate due to the thermal stress probably caused by higher temperature than that at LSP which varies with the growth of the leaf.
The total canopy net photosynthesis rate for the growing period of Q. mongolica forest (May to October) at this site is found to be about 3.3 kg CO2 m−2 that is about 1.3 times larger than the total soil respiration of 2.5 kg CO2 m−2 measured at the same site for the same period [33] . The presently estimated canopy net photosynthesis rate is comparable to those estimated by Falge et al. [9] and Muraoka et al. [13] , suggesting the potential usefulness of the present model for the estimation of the canopy net photosynthesis rate of Q. mongolica forest stand.
This study is mainly pertained to the estimation of the canopy net photosynthesis rate in the Q. mongolica forest stand with empirically derived the photosynthetic light response curve using limited measurement data. Some important parameters affecting the net photosynthesis rate are not evaluated independently. This is now on hand at the Nam-San ecological-experimental site based on direct measurements of photosynthesis rates, respirations and environmental conditions continuously with the automatic chamber systems.
Acknowledgements
This work was funded by the Korea Meteorological Administration Research and Development Program under Grant KMIPA 2015-6040.
Cite this paper
Joo, S.J. and Park, S.-U. (2017) Canopy Net Photosynthesis Rate of a Mongolian Oak (Quercus mongolica) Forest Estimated by Field Experimental Data. American Journal of Plant Scien- ces, 8, 390-411. https://doi.org/10.4236/ajps.2017.83027
ReferencesCanadell, J.G., Mooney, H.A., Baldocchi, D.D., Berry, J.A., Ehleringer, J.R., Field, C.B., Gower, S.T., Hollinger, D.Y., Hunt, J.E., Jackson, R.B., Running, S.W., Shaver, G.R., Steffen, W., Trumbore, S.E., Valentini, R. and Bond, B.Y. (2000) Carbon Metabolism of the Terrestrial Biosphere: A Multi-Technique Approach for Improved Understanding. Ecosystems, 3, 115-130. https://doi.org/10.1007/s100210000014Cox, P.M., Betts, R.A., Jones, C.D., Spall, S.A. and Totterdell, I.J. (2000) Acceleration of Global Warming Due to Carbon-Cycle Feedbacks in a Coupled Climate Model. Nature, 408, 184-187. https://doi.org/10.1038/35041539Davidson, E.A., Janssens, I.A. and Luo, Y. (2006) On the Variability of Respiration in Terrestrial Ecosystems: Moving Beyond Q10. Global Change Biology, 12, 154-164.
https://doi.org/10.1111/j.1365-2486.2005.01065.xOhtsuka, T., Mo, W., Satomura, T., Inatomi, M. and Koizumi, H. (2007) Biometric Based Carbon Flux Measurements and Net Ecosystem Production (NEP) in a Temperate Deciduous Broad-Leaved Forest Beneath a Flux Tower. Ecosystems, 10, 324-334. https://doi.org/10.1007/s10021-007-9017-zKwak, Y.S. and Kim, J.H. (1992) Secular Changes of Density, Litterfall, Phytomass and Primary Productivity in Mongolian Oak (Quercus mongolica) Forest. The Korean Journal of Ecology, 15, 19-33.Kim, W.S., Cho, J.I., Myong, G.M., Mano, M., Komori, D. and Kim, S.D. (2008) Quality Assessment of Data from the Daegwallyeong Flux Measurement Station (DFMS) Based on Short-Term Experiments. Journal of Agricultural Meteorology, 64, 111-120. https://doi.org/10.2480/agrmet.64.3.3Joo, S.J., Park, S.U., Park, M.S. and Lee, C.S. (2012) Estimation of Soil Respiration Using Automated Chamber Systems in an Oak (Quercus mongolica) Forest at the Nam-San Site in Seoul, Korea. Science of the Total Environment, 416, 400-409.
https://doi.org/10.1016/j.scitotenv.2011.11.025Norman, J.M. and Campbell, G.S. (1989) Canopy Structure. In: Pearcy, R.W., Ehlringer, J., Mooney, H.A. and Eundel, P.W., Eds., Plant Physiological Ecology: Field Methods and Instrumentation, Chapman and Hall, London and New York, 301-325. https://doi.org/10.1007/978-94-009-2221-1_14Welles, J.M. and Norman, J.M. (1991) Instrument for Indirect Measurement of Canopy Architecture. Agronomy Journal, 83, 818-825.
https://doi.org/10.2134/agronj1991.00021962008300050009xKucharik, C.J., Norman, J.M. and Gower, S.T. (1998) Measurement of Branch Area and Adjusting Leaf Area Index Indirect Measurements. Agricultural and Forest Meteorology, 91, 69-88. https://doi.org/10.1016/S0168-1923(98)00064-1Monsi, M. and Saeki, T. (1953) über den Lichtfaktor in den Pflanzengesellschaften und seine Bedeutung für die Stoffproduktion. Japanese Journal of Botany, 14, 22-52. (In German)Monsi, M. and Saeki, T. (2005) On the Factor Light in Plant Communities and Its Importance for Matter Production. Annals of Botany, 95, 549-567.
https://doi.org/10.1093/aob/mci052Suwa, R., Khan, M.N.I. and Hagihara, A. (2006) Canopy Photosynthesis, Canopy Respiration and Surplus Production in a Subtropical Mangrove Kandelia candel forest, Okinawa Island, Japan. Marine Ecology Progress Series, 320, 131-139.
https://doi.org/10.3354/meps320131Koyama, K. and Kikuzawa, K. (2011) Reduction of Photosynthesis before Midday Depression Occurred: Leaf Photosynthesis of Fagus crenata in a Temperate Forest in Relation to Canopy Position and a Number of Days after Rainfall. Ecological Research, 26, 999-1006. https://doi.org/10.1007/s11284-011-0859-7Noilhan, J. and Planton, S. (1989) A Simple Parameterization of Land Surface Processes for Meteorological Models. Monthly Weather Review, 117, 536-549.
https://doi.org/10.1175/1520-0493(1989)117<0536:ASPOLS>2.0.CO;2Aber, J.D. and Melillo, J.M. (2001) Terrestrial Ecosystem. 2nd Edition, Academic Press, Cambridge.Bassow, S.L. and Bazzaz, F.A. (1998) How Environmental Conditions Affect Canopy Leaf-Level Photosynthesis in Four Deciduous Tree Species. Ecology, 79, 2660-2675. https://doi.org/10.1890/0012-9658(1998)079[2660:HECACL]2.0.CO;2Chazdon, R.L. and Pearcy, R.W. (1991) The Importance of Sunflecks for Forest Understory Plants. BioScience, 41, 760-766. https://doi.org/10.2307/1311725Nasahara, K.N., Muraoka, H., Nagai, S. and Mikami, H. (2008) Vertical Integration of Leaf Area Index in a Japanese Deciduous Broad-Leaved Forest. Agricultural and Forest Meteorology, 148, 1136-1146.
https://doi.org/10.1016/j.agrformet.2008.02.011Itano, S., Akiyama, T., Ishida, H., Okubo, T. and Watanabe, N. (2000) Spectral Characteristics of Aboveground Biomass, Plant Coverage, and Plant Height in Italian Ryegrass (Lolium multiiflorum L.) Meadows. Japanese Society of Grassland Science, 46, 1-9.Lefsky, M.A., Cohen, W.B., Acker, S.A., Parker, G.G., Spies, T.A. and Harding, D. (1999) Lidar Remote Sensing of the Canopy Structure and Biophysical Properties of Douglas-Fir Western Hemlock Forests. Remote Sensing of Environment, 70, 339-361. https://doi.org/10.1016/S0034-4257(99)00052-8Kimball, J.S., Thornton, P.E., White, M.A. and Running, S.W. (1997) Simulating Forest Productivity and Surface-Atmosphere Carbon Exchange in the BOREAS Study Region. Tree Physiology, 17, 589-599.
https://doi.org/10.1093/treephys/17.8-9.589Wang, Y.P. and Jarvis, P.G. (1990) Description and Validation of an Array Model-MAESTRO. Agricultural and Forest Meteorology, 51, 257-280.
https://doi.org/10.1016/0168-1923(90)90112-JSakai, T., Saigusa, N., Yamamoto, S. and Akiyama, T. (2005) Microsite Variation in Light Availability and Photosynthesis in a Cool-Temperate Deciduous Broadleaf Forest in Central Japan. Ecological Research, 20, 537-545.
https://doi.org/10.1007/s11284-005-0067-4Koike, T., Kitao, M., Maruyama, Y., Mori, S. and Lei, T.T. (2001) Leaf Morphology and Photosynthetic Adjustments among Deciduous Broad-Leaved Trees within the Vertical Canopy Profile. Tree Physiology, 21, 951-958.
https://doi.org/10.1093/treephys/21.12-13.951Leuning, R., Kelliher, F.M., de Pury, D.G.G. and Schulze, E.D. (1995) Leaf Nitrogen, Photosynthesis, Conductance and Transpiration: Scaling from Leaves to Canopies. Plant, Cell & Environment, 18, 1183-1200.
https://doi.org/10.1111/j.1365-3040.1995.tb00628.xRocha, A.V., Su, H.B., Vogel, C.S., Schmid, H.P. and Curtis, P.S. (2004) Photosynthetic and Water Use Efficiency Responses to Diffuse Radiation by an Aspen-Dominated Northern Hardwood Forest. Forest Science, 50, 793-801.Clark, D.B., Clark, A.C., Rich, P.M., Weiss, S. and Oberbauer, S.F. (1996) Landscape-Scale Evaluation of Understory Light and Canopy Structure: Methods and Application in a Neotropical Lowland Rain Forest. Canadian Journal of Forest Research, 26, 747-757. https://doi.org/10.1139/x26-084Ellsworth, D.S. and Reich, P.B. (1993) Canopy Structure and Vertical Patterns of Photosynthesis and Related Leaf Traits in Deciduous Forest. Oecologia, 96, 169-178.
https://doi.org/10.1007/BF00317729Ito, A., Saigusa, N., Murayama, S. and Yamamoto, S. (2005) Modeling of Gross and Net Carbon Dioxide Exchange over a Cool-Temperate Deciduous Broad-Leaved Forest in Japan: Analysis of Seasonal and Interannual Change. Agricultural and Forest Meteorology, 134, 122-134. https://doi.org/10.1016/j.agrformet.2005.11.002Norman, J.M. (1993) Scaling Processes between Leaf and Canopy Levels. In: Ehlringer, J. and Field, C.B., Eds., Scaling Physiological Processes: Leaf to Global, Academic Press, London, 41-76.
https://doi.org/10.1016/B978-0-12-233440-5.50010-5Muraoka, H., Saigusa, N., Nasahara, K.N., Noda, H., Yoshino, J., Saitoh, T.M., Nagai, S., Murayama, S. and Koizumi, H. (2010) Effects of Seasonal and Interannual Variations in Leaf Photosynthesis and Canopy Leaf Area Index on Gross Primary Production of a Coo-Temperate Deciduous Broadleaf Forest in Takayama, Japan. Journal of Plant Research, 123, 563-576. https://doi.org/10.1007/s10265-009-0270-4Arkebauer, T.J., Walter-Shea, E.A., Mesarch, M.A., Suyker, A.E. and Verma, S.B. (2009) Scaling up of CO2 Fluxes from Leaf to Canopy in Maize-Based Agroecosystems. Agricultural and Forest Meteorology, 149, 2110-2119.
https://doi.org/10.1016/j.agrformet.2009.04.013Wu, J., Guan, D., Sun, X., Zhang, M., Shi, T., Han, S. and Jin, C. (2006) Photosynthetic Characteristics of Dominant Tree Species and Canopy in the Broadleaved Korean Pine Forest of Changbai Mountains. Science in China. Series D, Earth Sciences, 49, 89-98. https://doi.org/10.1007/s11430-006-8089-5Farquhar, G.D., von Caemmerer, S. and Berry, J.A. (1980) A Biochemical Model of Photosynthetic CO2 Assimilation in Leaves of C3 Species. Planta, 149, 78-90.
https://doi.org/10.1007/BF00386231Falge, E., Baldocchi, D., Tenhunen, J., Aubinet, M., Bakwind, P., Berbigier, P., Bernhofer, C., Burba, G., Clement, R., Davis, K.J., Elbers, J.A., Goldstein, A.H., Grelle, A., Granier, A., Guemundssonm, J., Hollinger, D., Kowalski, A.S., Katul, G., Law, B.E., Malhi, Y., Meyers, T., Monson, R.K., Munger, J.W., Oechel, W., Paw, U.K.T., Pilegaard, K., Rannik, ü., Rebmann, C., Suyker, A., Valentini, R., Wilson, K. and Wofsy, S. (2002) Seasonality of Ecosystem Respiration and Gross Primary Production as Derived from FLUXNET Measurements. Agricultural and Forest Meteorology, 113, 53-74. https://doi.org/10.1016/S0168-1923(02)00102-8Luo, Y., Hui, D., Cheng, W., Coleman, J.S., Johnson, D.W. and Sims, D.A. (2000) Canopy Quantum Yield in a Mesocosm Study. Agricultural and Forest Meteorology, 100, 35-48. https://doi.org/10.1016/S0168-1923(99)00085-4Muraoka, H. and Koizumi, H. (2009) Satellite Ecology (SATECO)-Linking Ecology, Remote Sensing and Micrometeorology, from Plot to Regional Scale, for the Study of Ecosystem Structure and Function. Journal of Plant Research, 122, 3-20.
https://doi.org/10.1007/s10265-008-0188-2Bondeau, A., Kicklighter, D.W., Kaduk, J. and The Participants of the Potsdam NPP Model Intercomparison (1999) Comparison Global Models of Terrestrial Net Primary Productivity (NPP): Importance of Vegetation Structure on Seasonal NPP Estimates. Global Change Biology, 5, 35-45.
https://doi.org/10.1046/j.1365-2486.1999.00005.xSasai, T., Okamoto, K., Hiyama, T. and Yamagucchi, Y. (2007) Comparing Terrestrial Carbon Fluxes from the Scale of a Flux Tower to the Global Scale. Ecological Modelling, 208, 135-144. https://doi.org/10.1016/j.ecolmodel.2007.05.014Sitch, S., Smith, B., Prentice, I.C., Arneth, A., Bondeau, A., Cramer, W., Kaplan, J.O., Levis, S., Lucht, W., Sykes, M.T., Thonicke, K. and Venevsky, S. (2003) Evaluation of Ecosystem Dynamics, Plant Geography and Terrestrial Carbon Cycling in the LJP Dynamic Global Vegetation Model. Global Change Biology, 9, 161-185.
https://doi.org/10.1046/j.1365-2486.2003.00569.x