Forestry Advance Access originally published online on January 12, 2006
Forestry 2006 79(2):231-239; doi:10.1093/forestry/cpl002
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Estimating net primary productivity of Chinese pine forests based on forest inventory data
1 Laboratory of Quantitative Vegetation Ecology, Institute of Botany, the Chinese Academy of Sciences, Beijing 100093, PR China
2 Urban Ecology and Environment Research Centre, Shanghai Normal University, Shanghai 200234, PR China
* Corresponding author. E-mail: zhougs{at}public2.bta.net.cn
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Summary |
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Forest inventory data (FID) include forest resources information at large spatial scale and long temporal scale. They are important data sources for estimating forest net primary productivity (NPP) and carbon budget at landscape and regional scales. In this study, more than 100 datasets of biomass, volume, NPP and stand age for Chinese pine forests (Pinus tabulaeformis) from the literature were synthesized to develop regression equations between biomass and volume, and between NPP and biomass as well as stand age. Using these regression equations and the fourth FID surveyed by the Forestry Ministry China from 1989 to 1993, NPP values of Chinese pine forests were estimated. The mean NPP of Chinese pine forests was 4.35 Mg ha–1 yr–1. NPP varied widely among provinces, ranging from 1.5 (Neimenggu) to 13.73 Mg ha–1 yr–1 (Guizhou). Total NPP of Chinese pine was 10.87 Tg yr–1 (1 Tg = 1012 g). NPP values of Chinese pine forests were not distributed evenly across different provinces in China. This study may be useful not only for estimating forest carbon of other forest types but also for evaluating terrestrial carbon balance at regional and global levels.
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Introduction |
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TopSummaryIntroductionData and methodsResultsDiscussionConclusionAcknowledgementsReferences |
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Net primary productivity (NPP) is generally defined as the balance between the light energy fixed through photosynthesis and lost through respiration and mortality, representing the net carbon input from the atmosphere to terrestrial vegetation (Mellilo et al., 1993). It is an important index in the evaluation of the patterns, processes and dynamics of carbon cycling in forest ecosystems at local, regional and global scales (Luo et al., 2002
). At the same time, it is also a basis for estimating the carbon budget of ecosystems. The study of NPP is a core task of the International Geosphere–Biosphere Program (IGBP) (IGBP Terrestrial Carbon Working Group, 1998). Therefore, a better understanding of forest NPP will improve the estimation of the global carbon budget and enhance our ability to manage forests under the changing global environment.
A wide variety of techniques have been applied to estimate forest NPP, and the results varied widely among the studies, often because of variability in the datasets (Scurlock et al., 1999; Zheng et al., 2003). Forest inventory data (FID) include information on forest type, volume and stand age at a large spatial scale and a long temporal scale, so they are important for evaluating forest carbon at landscape, regional and even global scales (Brown et al., 1999; Brown and Schroeder, 1999; Caspersen et al., 2000). Using continuous and systematic FID to evaluate the carbon dynamics has become a focus of those working to understand the impacts of climate change (Schroeder et al., 1997; Murillo, 1997; Fang et al., 2001).
Chinese pine (Pinus tabulaeformis) is a dominant species in the boreal forest of China where it accounts for 
70 per cent of the total boreal forest area. It is also a major species not only in reforestation and afforestation but also in wood production and erosion control (Xu, 1981). On the other hand, it is mainly distributed in the regions that are expected to be most sensitive to global climate change (Wang et al., 1995). Thus, studying the NPP of Chinese pine at country or regional scales is important in anticipating the impact of climate change. In fact, a lot of data on Chinese pine have been collected (Chen et al., 1984; Guan and Dong, 1986; Liu, 1987; Xiao, 1987; Zhang, 1992), but they were generally so sparse spatially that they did not reflect carbon storage at the regional scale. Based on the turnover rates of leaves, branches and roots, Ma (1988) estimated the NPP of Chinese pine at the regional scale. However, those parameters are difficult to obtain at a regional scale, and the method could not estimate the principles of NPP dynamics.
The objectives of the study are (1) to review and summarize the published data on volume, biomass, stand age and NPP of Chinese pine; (2) to develop regression equations between biomass and volume, and between NPP and biomass as well as stand age; and (3) to estimate Chinese pine NPP based on those regression equations and the FID from 1989 to 1993.
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Data and methods |
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TopSummaryIntroductionData and methodsResultsDiscussionConclusionAcknowledgementsReferences |
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Forest inventory data
Forest inventories of China have been conducted periodically in a 5-year cycle for more than 30 years using ground surveys and remote sensing. The fourth forest inventory (1989–1993) was compiled from 227 244 permanent and temporary plots distributed evenly across China. The inventory covered 5.78 x 106 km2 (about 61.2 per cent of Chinese area) and systematically designed as 4 km x 4 km or 8 km x 8 km regardless of forest or non-forest sites. All the investigations were carried out in accordance with technical standards formulated by the Ministry of Forestry. Tree height and diameter at breast height (d.b.h.) (1.3 m) were measured for all trees with d.b.h. >4 cm. The stem volume of each tree was obtained from a volume table compiled by species and regions. The stand volume of each plot was calculated by adding the volumes of all individual trees within the plot. In this inventory, forest area, volume and age class of Chinese pine forests were given for every province (Forest Ministry of China, 1994); there were five age classes (young forests of <30 years, middle-mature forests of 31–50 years, approximately mature forests of 51–60 years, mature forests of 61–80 years and over-mature forests of >80) following national guidelines for forest resource survey (Ministry of Forestry, 1982). The characteristics of the Chinese pine forests are listed in Table 1.
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Field measurement data
More than 100 datasets for Chinese pine forests were collected, including administrative site, stand age, volume, forest biomass, NPP and references from different sources (Tables 2 and 3). Here biomass is referred to the amount of living woody components including roots, stem, branches and leaves. NPP is the net increment of woody components including roots, stem, branches and leaves per unit ground area in 1 year. Forest volume is referred to as stem volume.
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Methods
Biomass estimation
Just as Zhou et al. (2002) had found that the relationship between biomass and volume of China's Larix forests could be expressed as hyperbolic curves, a hyperbolic relationship was also found between stand biomass and volume (equation (1)) for Chinese pine forests based on 14 sites summarized in Table 2.
 | (1) |
where B and V are stand biomass (Mg ha–1) and stand volume (m3 ha–1) respectively; a and b are constants.
NPP estimation
NPP is defined as the production of all tissues by photosynthesis after accounting for respiration by the plants themselves. Thus, forest NPP may have a close relationship with actual biomass increment (ABI = 
B/A), where B is the biomass increment, and A is the time interval. Considering FID, ABI would be replaced by mean annual biomass increment (MABI = B/A, where B is the forest biomass and A is the stand age), which includes the integrated effects of forest biomass and stand age. The relationship between NPP and MABI for the Larix forest could be given by a hyperbola curve, which indicates that the NPP of the Larix forest increases almost linearly with the increase in MABI when MABI is small, then the ratio of NPP to MABI decreases with the increase in stand age until NPP reaches the maximum value (Zhou et al., 2002). Following Zhou et al. (2002), the increasing rule of NPP with MABI could be described as
 | (2) |
 | (3) |
Thus, based on the observed data of NPP, biomass and stand age (sources as listed in Table 3), a and b in equation (2) could be determined. Equation (3) can also be changed into equation (4). The data of 64 sites from Table 3 were used to estimate the parameters a and b in equation (4).
 | (4) |
where NPP is in units of Mg ha–1 yr–1, and A is the stand age (year); a and b are constants. Based on equation (4) and the fourth FID, NPP (NPPi) of Chinese pine forests in i province could be calculated by equations (5)–(7):
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 | (6) |
 | (7) |
where Aij and Bij are middle stand age value and mean stand biomass for each age class (j = 1, 2, 3, 4, 5) of i province (i = 1, 2, 3,..., 17); a and b are defined in equation (4); Bij can be calculated by equation (1). Based on equations (5)–(7) and the fourth FID, the average NPP of Chinese pine forests (NPPave) was calculated by equation (8)
 | (8) |
where NPPi was defined by equations (5)–(7).
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Results |
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TopSummaryIntroductionData and methodsResultsDiscussionConclusionAcknowledgementsReferences |
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Relationships between biomass and volume, NPP and MABI
Based on the published data (Tables 2 and 3), the relationships between volume and biomass, and between NPP and MABI could be determined, which was the basis for calculating forest NPP at a large spatial scale. Using the field data of Chinese pine forests, correlations between volume and biomass could be described as equation (1) (Figure 1), and the relationship between NPP and MABI of the forest could be expressed as equation (2) (Figure 2).
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Model validation
The data which were not used to derive the parameters were used to validate the models (Table 2, numbers 15–21; Table 3, numbers 65–128) (Figure 3). The results showed that the correlative coefficients (R2) of the simulated values and the observed values were 0.79 (P < 0.01) and 0.68 (P < 0.01), respectively, suggesting that these models could be used for estimating the biomass and NPP of Chinese pine forests.
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Chinese pine forest NPP and its distribution in China
Based on equations (1)–(8) and the fourth FID, Chinese pine NPP could be evaluated. The mean NPP of Chinese pine was 4.35 Mg ha–1 yr–1; however, the values varied widely among provinces, ranging from 1.5 (Neimenggu) to 13.73 Mg ha–1 yr–1 (Guizhou). The NPP of Chinese pine in Guizhou, Qinghai and Xizang was higher than the average value, more than 6.5 Mg ha–1 yr–1; the NPP in Neimenggu, Hubei, Tianjin and Shangdong was less than 2 Mg ha–1 yr–1; while in concentrated main regions of Chinese pine (e.g. Shanxi, Shannxi), NPP was close to the average value, about 4 Mg ha–1 yr–1 or so (Table 4).
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The total NPP value of Chinese pine forest was 10.87 Tg yr–1, which is a major contribution to China's carbon storage. Since much of the NPP is associated with young forests, this implies that Chinese pine forests have the potential to accumulate significant quantities of additional carbon in living trees and will increasingly store atmospheric carbon in the future.
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Discussion |
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TopSummaryIntroductionData and methodsResultsDiscussionConclusionAcknowledgementsReferences |
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Explanation of the estimated Chinese pine NPP values
The mean estimated NPP (4.35 Mg ha–1 yr–1) of Chinese pine forest was lower than the observed average NPP (9.12 Mg ha–1 yr–1) which was calculated from Table 3; this may be explained in three ways. Firstly, about 75 per cent of Chinese pine forest area is occupied by pre-mature forest, and about 25 per cent is occupied by mature and post-mature forest. Secondly, most Chinese pine forests in China are of poor quality and consist of secondary forests, for many of those forests were planted in recent years. Thirdly, although FID has many advantages in estimating forest carbon (Grame et al., 2001), it only includes trees with a diameter of more than 4 cm (Fang et al., 1998). However, the parameters are easily obtained in this study.
Errors in estimating biomass and NPP based on FID
There are many advantages in estimating forest carbon from the FID, but there are biases or errors as well. The first type of biases and errors comes from the relationships between volume and biomass, and between NPP and biomass as well as stand age: (1) the field measured data may not be representative for the forest types as a whole; (2) one of the potential problems is that many studies are often done on well-managed sites and rarely conducted in a manner that fully captures the variability of an extensively managed forest estate. The second type of biases and errors comes from FID: (1) measurement errors in the estimation of the areas of different forest types. For example, area estimates derived from traditional two-dimensional map projections often underestimate the true surface area of the ground (Garnett et al., 2001); (2) litter and biomass losses to herbivores were not considered. Duvigneaud (1987) noted that the proportion of litter fall to total biomass in major biomes of the world is 2–7 per cent. Forest inventory monitoring programmes should be expanded with improved assessments covering deadwood, litter and ground vegetation, etc. For future projections, detailed work should be done.
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Conclusion |
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TopSummaryIntroductionData and methodsResultsDiscussionConclusionAcknowledgementsReferences |
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FID plays an important role in accurate estimation of NPP of forest at regional and global scales. Estimating the NPP of Chinese pine forests based on FID will improve the prediction of possible effects of climate change. The conclusion could be summarized as follows:
- 1 The relationships between biomass and volume, and between NPP and biomass as well as stand age could be expressed as hyperbola curves for Chinese pine forests.
- 2 The mean NPP value of Chinese pine forest was 4.35 Mg ha–1 yr–1 and was lower than that from other studies.
- 3 Chinese pine forest NPP varied widely among provinces, ranging from 1.5 (Neimenggu) to 13.73 Mg ha–1 yr–1 (Guizhou).
- 4 There were some errors and biases in estimating NPP based on FID. More researches should be done in the future in order to overcome those errors or biases.
- 2 The mean NPP value of Chinese pine forest was 4.35 Mg ha–1 yr–1 and was lower than that from other studies.
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Acknowledgements |
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TopSummaryIntroductionData and methodsResultsDiscussionConclusionAcknowledgementsReferences |
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This research was supported by the Chinese Academy of Sciences (KSCX2-SW-133), National Natural Science Foundation of China (Nos. 30070642, 40231018) and Shanghai Rising-Star Program (05QMX1443). We thank Xiang Feng for correcting the English of this manuscript.
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References |
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Brown, S.L. and Schroeder, P.E. 1999 Spatial patterns of aboveground production and mortality of woody biomass for eastern U.S. forest. Ecol. Appl. 9, 968–980.
Brown, S.L., Schroeder, P. and Kern J.S. 1999 Spatial distribution of biomass in forests of the eastern USA, For. Ecol. Manage. 123, 81–90.[CrossRef]
Caspersen, J.P., Pacala, S.W., Jenkins, J.C., Hurtt, G.C., Moorcroft, P.R. and Birdey, R.A. 2000 Contributions of land – use history to carbon accumulation in U.S. forests. Science 29, 2301–2309.[CrossRef]
Chen, L.Z., Ren, J.K., Bao, X.C., Chen, Q.L., Hu, S.H., Miao, Y.G. et al. 1984 Studies on the sociological characteristic and biomass of pine plantation on Xishan in Beiing. Acta Phytoecol. Geobot. Sin. 8, 173–181.
Dong, S.R. and Guan, X. 1980 Studies on productivity of Pinus tabulaeformis stands in Taiyue mountain. Shanxi province. J. Beijing For. Univ. 1, 1–20.
Duvigneaud, P. 1987 La Synthèse Ècologique (in Chinese, Y. Li, translator). Chinese Science Press, Beijing, China.
Fang, J.Y., Wang, G.G., Liu, G.H. and Xu, S.L., 1998 Forest biomass of China: an estimate based on the biomass – volume relationship. Ecol. Appl. 8, 1084–1091.
Fang, J.Y., Chen, A.P., Peng, C.H., Zhao, S.Q. and Ci, L.J. 2001 Changes in forest biomass carbon storage in China between 1949 and 1998. Science 292, 2320–2322.
Forest Ministry of China, 1994 Summary of Forest Resources in China (1989–1993). Chinese Forestry Publishers, Beijing, China.
Gao, J.R. 1987 Studies on the nutrient cycling of Pinus tabulaeformis in Huoditang, Qinling. J. Northwest For. Univ. 2, 23–35.
Garnett, M.H., Ineson, P., Stevenson, A.C. and Howard, D.C. 2001 Terrestrial organic carbon storage in a British moorland. Glob. Chang. Biol. 7, 375–388.[CrossRef]
Grame, M., Hall, J., Susank, W., Wiser, K., Allen, R.B., Beets, P.N. et al. 2001 Strategies to estimate national forest carbon stocks from inventory data: the 1990 New Zealand baseline. Glob. Chang. Biol. 7, 389–403.[CrossRef]
Guan, Y.X. and Dong, S.R. 1986 Studies on ecosystem of Pinus tabulaeformis plantations (II). A comparison of productivity between the stands in Taiyue, Shanxi province, and that in Chengde, Hebei province. J. Beijing For. Univ. 1, 1–10.
IGBP Terrestrial Carbon Working Group. 1998 The terrestrial carbon cycle: implication for the Koyoto Protocol. Science 280, 1393–1394.
Liu, C.J. 1987 Study on the biomass and nutrient cycling of the mixed plantation of Pinus tabulaeformis and Quercus variabilis in Xishan region, Beijing. J. Beijing For. Univ. 9, 1–10.
Luo, T.X., Li, W.H. and Zhu, H.Z. 2002 Estimated biomass and productivity of natural vegetation on the Tibetan Plateau. Ecol. Appl. 12, 980–997.
Ma, Q.Y. 1987 A study on the biomass of individual tree and stand of Pinus tabulaeformis in Inner Mongolia. J. Inner Mongolia For. Univ. 2, 13–22.
Ma, Q.Y. 1988 A study on biomass and primary productivity of Chinese Pine (Pinus tabulaeformis carr.). Ph.D. thesis. Beijing Forestry University.
Melillo, J.M., McGurie, A.D., Kicklighter, D.W., Moore, B. III, Vorosmarty, C.J. and Schloss, A.L. 1993 Global climate change and terrestrial net primary production. Nature 363, 234–240.[CrossRef]
Ministry of Forestry. 1982 Standards for Forestry Resource Survey. China Forestry Publisher, Beijing, China.
Murillo, J.C.R. 1997 Temporal variations in the carbon budget of forest ecosystems in Spain. Ecol. Appl. 7, 461–469.
Schroeder, P., Brown, S., Birdsey, J.M.R. and Cieszewski, C. 1997 Biomass estimation for temperate broadleaf forests of the US using inventory data. For. Sci. 43, 424–434.
Scurlock, J.M.O., Cramer, W., Olson, R.J., Parton, W.J., Prince, S.D. 1999 Terrestrial NPP: toward a consistent data set for global model evaluation. Ecol. Appl. 9, 913–919.
Wang, H.X. 1989 Study on P. Sylvestris and P. tabulaeformis in the western mountain of Liaoning province. J. Liaoning For. Sci. Technol. 1, 26–30.
Wang, H.M., Zhou, G.S., Wei, L. and Xing, X.R. 1995 NPP pattern of Chinese pine and its response to climate change. Chin. Bull. Botan. 12, 102–108.
Xiao, Y. 1987 Correlation analysis between productivity of Chinese Pinus tabulaeformis plantations and ecological factors in Shannxi province. Acta Bot. Sin. 29, 549–555.
Xiao, Y., Wu, B.S., Chen, B.Q., Zhang, J.C., Wang, M.H. and Wang, L.G. 1983 Study on aboveground biomass of Pinus tabulaeformis. Shanxi For. Sci. Technol. 2, 5–14.
Xu, H.C. 1993 Pinus tabulaeformis. Science Press, Beijing, 41–53.
Xu, H.C., Sun, Z.F., Guo, G.R. and Feng, L. 1981 Geographic distribution of Pinus tabulaeformis and classification of provenance regions. Sci. Silvae Sin. 3, 258–270.
Yao, Y.T. 1989 Study on the biomass and nutrient cycling of the mixed plantation of Pinus tabulaeformis and Platycladus oreentalis. J. Beijing For. Univ. 11(2), 38–46.
Zhang, B.L. 1992 Preliminary report on productivity of Pinus tabulaeformis plantation in Weibei region. J. Northwest For. Univ. 7(1), 64–67.
Zheng, D.L., Prince, S. and Wright, R. 2003 Terrestrial net primary production estimates for 0.5° grid cells from field observations-a contribution to global biogeochemical modeling. Glob. Chang. Biol. 9, 46–64.[CrossRef]
Zhou, G.S., Wang, Y.H., Jiang, Y.L. and Yang, Z.Y. 2002 Estimating biomass and net primary production from forest inventory data: a case study of China's Larix forests. For. Ecol. Manage. 169, 149–157.[CrossRef]
Received 9 September 2003.
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