Modeling carbon cycles in a Cryptomeria japonica planted forest. Tsukuba, Ibaraki, Japan ;

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1 Modeling carbon cycles in a Cryptomeria japonica planted forest Y. Mitsuda 1, K. Hosoda 1, T. Iehara 1, and M. Matsumoto 2 1 Forest Management Division, Forestry and Forest Products Research Institute, 1 Matsunosato, Tsukuba, Ibaraki, Japan ; mitsuda@ffpri.affrc.go.jp 2 Bureau of Climate Change, Forestry and Forest Products Research Institute, 1 Matsunosato, Tsukuba, Ibaraki, Japan. Introduction Forest managers, policy-makers, and governments require a tool to estimate the carbon dynamics of forests under various types of forest management (e.g. Kurz et al. 2009). One such tool is a stand-level process-based carbon cycle model. Japanese cedar (Cryptomeria japonica) is the dominant planting species in Japan, therefore there is an urgent requirement to develop a carbon cycle model for this species. The objective of this study was to develop a stand-level process-based carbon cycle model for Japanese cedar planted forest using long-term permanent plot data. Using this model, we show how to make better use of traditional forest monitoring data. Materials and Methods Our model is based on the 3-PG (Physiological Principles Predicting Growth) model developed by Landsberg and Waring (1997). This model consists of four biomass pools (i.e., foliage, stem, branch, and root) and uses dry matter weight per unit area as the basis for calculating carbon balance. We simplified the original version to have only six processes: (1) photosynthetically active radiation absorption; (2) conversion to gross primary production; (3) constraints on photosynthesis by environmental factors; (4) respiration; (5) litterfall and root turnover; and (6) biomass partitioning (Figure 1). Photosynthetically active radiation absorbed by stand (APAR) is calculated by Beer s law. We adopted a 5-layer canopy structure to substitute for the single-layer canopy structure used in the original version. We also modified the process of conversion to gross primary production (GPP). APAR is converted to GPP by a light-response curve (e.g. Hirose and Werger 1987). The efficiency of this conversion is also constrained by environmental factors,

2 which were temperature and vapor pressure deficit (VPD) in this study. The respiration of each biomass pool is calculated in proportion to its biomass. Litterfall and root turnover are calculated as well. Net primary production (NPP) is calculated as GPP minus respiration and total biomass growth is calculated as NPP minus litterfall and root turnover. Total biomass growth is partitioned into four biomass pools using a biomass proportion function for Japanese cedar developed by Fukuda et al. (2003). We used a monthly time-step for processes 1 to 3, and a yearly time-step for processes 4 to 6. Temperature VPD Solar Radiation Radiation absorption Foliage Constraints Light-response curve Branch Stem GPP Root Respiration NPP Litterfall Turnover Growth Biomass partitioning Figure 1. Flow diagram of a simplified version of the 3-PG model. We used field measurement data derived from long-term permanent plots and time-series of climatic data. The Forestry and Forest Products Research Institute and National Forest of Japan have maintained permanent plots to investigate the growth of Japanese cedar planted forest since the early 1930 s. Trees in these plots have been identified and their diameter and height have been measured. We calculated the stand-level biomass of each biomass pool from tree-level field measurement data, and obtained 136 stand-level observations derived from 20 permanent plots for parameterization. The 1-km resolution 30-year average climatic data published by the Japan Meteorological Agency with time-series fluctuations was used as climatic data of radiation, temperature and VPD. Thus, we prepared time-series stand biomass and climatic data for each plot (Figure 2). Using these data, we parameterized the simplified version of the 3-PG by Bayesian calibration

3 (e.g. Van Oijen et al. 2005). Parameters of respiration and litterfall and turnover processes were fixed to the values used in Chiba (1998). Parameters of Beer s law, light-response curve, and the constraint functions for temperature and VPD were estimated by Bayesian calibration. a) Stem biomass Stem biomass [ton/ha] b) Monthly mean temperature Mean temperature [ C] c) Monthly photosynthetically active radiation PAR [MJ m 2 ] d) Monthly mean vapor pressure deficit VPD [kpa] Calendar Year Figure 2. An example of time-series data of model parameterization. Field measurements were conducted at the years indicated by the dotted line.

4 Results All parameters converged in the Bayesian calibration. Posterior distributions of some parameters showed sharp peakes, which indicated that these parameters were well conditioned by the data through Bayesian calibration; however, others were not so informative. The comparison of measured and predicted stem biomass is shown in Figure 3. We used medians of the posterior distribution of each parameter for simulating stem biomass. Model calculations reproduced the observed stand stem biomass to some degree, but there were large errors in some cases. Measured Stem Biomass [ton ha] Predicted Stem Biomass [ton ha] Figure 3. Comparison of measured stem biomass and predicted stem biomass. Discussion A simplified version of the 3-PG model for Japanese cedar was parameterized by Bayesian calibration using tree measurement data derived from long-term permanent plots and monthly climatic data of radiation, temperature, and VPD. Although our model is relatively simple and uses only three climatic factors, it can represent the growth patterns of various stands with various climatic conditions to some degree. Because 1-km resolution grid climatic data as used in this study is available for the whole of Japan, this model offers broad applicability. It would also be possible to assess the long-term effects of climate change on Japanese cedar planted forest using the carbon cycle model developed in this study.

5 Process-based models usually require ecophysiological experiments for parameterization, whereas we parameterized this kind of model using tree measurement data, which did not contain any ecophysiological values. The recently-developed Bayesian approach may allow us to use a large amount of accumulated field survey data for various applications. Conclusion The stand-level process-based carbon cycle model for Japanese cedar planted forest developed in this study could help forest managers and policy-makers to make decisions on forest management. This success in parameterization of a stand-level process-based model using Bayesian calibration also shows the way to make better use of traditional forest monitoring data. Literature Cited Chiba, Y Simulation of CO 2 budget and ecological implications of sugi (Cryptomeria japonica) man-made forests in Japan. Ecol. Model. 111(2-3): Fukuda, M., T. Iehara, and M. Matsumoto Carbon stock estimates for sugi and hinoki forests in Japan. For.Ecol. Manage. 184(1-3): Hirose, T. and M.J.A. Werger Maximizing daily canopy photosynthesis with respect to the leaf nitrogen allocation pattern in the canopy. Oecologia 72(4): Kurz, W., C. Dymond, T. White, G. Stinson, C.H. Shaw G. Rampley, C. Smyth, B.N. Simpson, E.T. Neilson J.A. Trofymow, J. Metsaranta, and M.J. Apps CBM-CFS3: A model of carbon-dynamics in forestry and land-use change implementing IPCC standards. Ecol. Model. 220(4): Landsberg, J. and R. Waring A generalised model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning. For. Ecol. Manage. 95(3): Van Oijen, M., J. Rougier, and R. Smith Bayesian calibration of process-based forest models: bridging the gap between models and data. Tree Physiol. 25: