Estimating carbon stocks in Korean forests between 2010 and 2110: a prediction based on forest volume–age relationships

Abstract

This study was focused on attempting to estimate the potential change in forest carbon stocks between 2010 and 2110 in South Korea, using forest cover maps and National Forest Inventory (NFI) data. Allometric functions (logistic regression models) of volume–age relationships were developed to estimate carbon stock change during the next 100 years for Pinus densiflora, P. koraiensis, P. rigida, Larix kaempferi and Quercus spp. As a result, we found that the average forest volume would increase from 126.89 m³/ha to 246.61 m³/ha and the average carbon stocks would increase from 50.51 Mg C/ha to 99.76 Mg C/ha during the next 100 years. The carbon stocks would increase by approximately 0.5 Mg C/(ha·yr), a high value if other northern countries’ (Canada, Russia, China, etc.) rates of increase are considered, as these are −0.10 to 0.28 Mg C/(ha·yr) as determined in a previous study. This can probably be attributed to the fact that the change in carbon stocks was estimated without the consideration of mortality, thinning, and tree species’ change in this study, which is may lead to somewhat overestimation of carbon sequestration. However, this study is meaningful, as the estimated carbon stocks were based on the data from NFI and forest cover maps.

Keywords:

• forest volume–age relationships
• National Forest Inventory
• forest cover map
• carbon stocks

Introduction

It is undeniable that recent phenomena such as global warming have been experienced throughout Earth's long history and will probably continue to be experienced irrespective of human contribution towards increasing greenhouse-gas concentrations (Florides & Christodoulides 2008). The Kyoto Protocol was agreed upon in 1997 and came into force in 2005 (Groenleer & van Schaik 2007). It obliges participating developed countries to reduce their emissions to 5.2% below the 1990 levels, averaged over the period from 2008 to 2012 (Pajot 2011). The Intergovernmental Panel on Climate Change (IPCC) found that the atmospheric concentrations of greenhouse gases (GHGs) such as carbon dioxide, methane, and nitrous oxide have grown significantly since pre-industrial times (about 1750). Among all the gases that cause the greenhouse effect, is the main contributor to this effect because it is the most important anthropogenic greenhouse gas (Lazare 2001; IPCC 2007). Therefore, the reduction of GHGs such as and the acquisition of emission rights have become serious social issues in today's world.

Forests have been considered one of the most important land areas for the storage and sequestration of GHGs that lead to global warming. Temperate and boreal forests in particular function as an important terrestrial sink (Johnston et al. 1996; Fang et al. 1998; Goodale et al. 2002).

The development of afforestation and reforestation under the clean development mechanism (A/R CDM), reducing emissions from deforestation and forest degradation in developing countries (REDD), and other initiatives which are related to carbon stocks and sequestration have been increasingly active since the 1990s (Thenkabail et al. 2004; Park et al. 2011). South Korea has a large forest area covering approximately 64% of the country, and thus it has a high potential for carbon sinks in the future.

The evaluation and monitoring of carbon stocks and sequestration in South Korea have been performed by the estimation of forest volume because volume is an essential element for predicting forest biomass and carbon storage (Kwak et al. 2012). The volume information can be converted into biomass and carbon storage simply by using the biomass expansion factors (BEF) developed by the Korea Forest Research Institute (KFRI) and the carbon fraction (CF) suggested by the IPCC (Son et al. 2008).

In Korea, previous studies on estimating volume have been carried out; for instance, one approach involves using the diameter at breast height (DBH) and height (H) as independent variations for estimating tree volume (v = f(DBH, H)) (Kwak et al. 2012). In Korea, this model is generally used (Kim 1966; Lee et al. 2001; Han et al. 2010). However, volume estimation using this equation is lacking in comparison with other approaches for further improvement of the model. Nevertheless, trying many kinds of methods is necessary for improving the accuracy of this model.

This study, therefore, applied another approach for estimating volume. This approach uses volume–age relationships to estimate changes in volume and carbon stocks from 2010 to 2110. As the main purpose of the present study was to verify whether the new approach could be used for estimating carbon stocks in South Korea, this study did not focus on the process of comparison between methods for volume estimation.

Materials and method

Study area

The study area comprised the entirety of South Korea, located at longitude of 124°54′–131°06′ and latitude of 33°09′–38°45′ (Figure 1). Currently, the forest occupies approximately 64% (6368,844 ha) of the total land area in South Korea. The forest area in South Korea is composed of coniferous (40.5%), deciduous (27%), mixed (29.3%), and other forests (3.2%) (Korea Forest Service 2011). According to the Korea Forest Service (2011), the forest composition in South Korea is being changed gradually into deciduous broad-leaved forest because of the rise in mean temperature due to climate change.

Figure 1 Geographical location and elevation distribution (digital elevation model [DEM]) of study area

National Forest Inventory (NFI) data

In South Korea, the NFI for only-forest areas has been conducted annually since 2006. Here, we used the fifth NFI (Korea Forest Service 2010). The survey consists of systematic sampling with intervals of 4 km (longitude) × 4 km (latitude). In all sites for the NFI, many kinds of measurements have already been done. NFI data (species, age, height, and DBH of individual trees) were used to develop forest growth models for estimating present and future forest volumes in accordance with changes in forest cover.

Forest cover map

A forest cover map has been produced every 10 years through the visual interpretation of aerial photographs and field surveys of forest attributes all over South Korea from the 1960s using a scale of 1:25,000 (Korea Forest Research Institute 2009). The maps are composed of stands that have information on tree species, DBH class, age class, and crown density of only-forested areas. In this study, we used the fourth forest cover map, which was the most recently produced (from 1996 to 2005), to estimate the present forest volume using the forest growth model developed based on NFI data.

We selected five main forests (Pinus densiflora, P. koraiensis, P. rigida, Larix kaempferi, and Quercus spp.) from the forest cover map, which are the main tree species in South Korea. Both age and DBH data were converted into the median value of each class for relating approximate units (year and centimeter) to actual estimates.

Relationships between volume density and forest age

The volume data provided by NFI are individual data; therefore, we had to know how many trees appear in a unit area. Hence, we used an equation estimating the number of trees per hectare using independent variations of relative spacing index (RSI) and free height (H) (Zhao et al. 2010).

where Nha denotes the number of trees per hectare; H, the average tree height; and RSI, the relative spacing index.

Using the site index that provided a yield table (Korea Forest Service 2009), we estimated tree density in each stand and classified the values into three classes (scatter, moderate, and dense). The range of the site index is 10–24, and from the average of these values we estimated the moderate tree density, which has a value of 0.29. Using the same process, the range 20–24 was used as scatter (0.24) and 10–14 was used as dense (0.32).

Then, we used the individual tree volume data from NFI and Nha with a simple mathematic equation to calculate the volume per hectare:

where V denotes the volume per hectare; v_i , the volume of an individual tree i; and Nha, the number of trees per hectare.

Xu et al. (2010) developed a biomass–age relationship regression model for calculating China's carbon stocks. The model's equation was based on the study by Fang and Wang (2001), in which biomass was estimated from the relationship of BEF and timber volume. Then, the biomass and tree age were used to develop a regression model. However, for using the available data, in this study, the biomass–age relationship model was converted to a volume–age relationship model, and the equation changes to

where V denotes the volume density, t denotes the forest age, and w, a, and k are constants for a specific forest type.

DBH and tree height have been used as basic elements for estimating tree volume (Lee 1995), and both DBH and tree height could be estimated by age (Huang & Titus 1994; Barton 1999). Therefore, volume can be estimated using just forest age.

Prediction of future carbon stocks

Assuming that no clear-cuts, die-offs, species change, or forest area change would occur in the next 100 years and using the fourth forest cover map, we calculated the total forest carbon stocks in Korea for a particular year using the following equation:

where C _Δt denotes the total carbon stock of Korea's existing forests Δt years after 2010, i and j indicate the forest type and the age class, respectively, c denotes the conversion factor between biomass and carbon storage (0.5 in this study), A_ij denotes the forest area for forest type i and age class j, V_ij denotes the volume per hectare volume for type i and age class j (eq. (4)), BEF is the biomass expansion factor for forest type i, and BWD is basic wood density for forest type i.

The BEF values (average) used in this study were fixed for each tree species (KFRI 2010) (Table 1).

Table 1 Biomass expansion factor and wood density for five tree species (KFRI 2010)

Species	Pinus densiflora	P. koraiensis	P. rigida	Larix kaempferi	Quercus spp.
BEF	1.42	1.85	1.39	1.32	1.43
BWD	0.446	0.411	0.504	0.453	0.692

Results and discussion

Relationships between volume density and forest age and uncertainties in predicting forest volume

The relationships between the volume per hectare and the forest age for the five main forest types are summarized in Table 2. The determination coefficients (R ²) of relationships between the forest age and the volume per hectare range from 0.68 to 0.83. This relatively low R² reflects that the diverse topographic and climatic conditions of the Korean peninsula can lead to a variety of forest growth. In fact, climate is the strongest driver of spatial variation in tree growth, and climate change may therefore have large consequences for forest productivity and carbon sequestration (Toledo et al. 2011).

Table 2 Parameters of logistic curves fitting the relationships between volume density and forest age

Forest type	w	k	a	R ^2
Pinus densiflora	275.5	8.2171	0.0626	0.778
P. koraiensis	183.7	128.1	0.2036	0.826
P. rigida	195.4	27.5741	0.1416	0.744
Larix kaempferi	363.2	13.771	0.0763	0.722
Quercus spp.	227.7	4.3953	0.0427	0.680

To test the reliability of this prediction, we compared the actual average volumes with the volumes we estimated for these forests (Figure 2). Statistical analysis suggests that there is no significant difference between these two values. The range of differences, from −7.7% to +5.4%, suggests that the prediction of forest volume used in this study is reasonable. Nevertheless, large uncertainties still exist in this prediction because several assumptions were used. First, the prediction assumed that clear-cuts, die-offs, species change, and forest area change will not occur in the next 100 years. Therefore, the value is somewhat overestimated. Second, carbon accumulation in forests can be influenced by climate change, elevation of atmospheric CO₂, and nitrogen deposition (Hyvönen et al. 2007; Luyssaert et al. 2007), which were not taken into account in this study. Third, human beings are the main factor, and because of economic reasons and the impact humans have on biodiversity, as well as other human-related effects, human impact can influence tree distribution significantly. Their further action may influence the accuracy of the prediction in this study as well. Actually, in Korea, forest tending works (FTW) were a public employment project organized by the Korean government. An area of 4.3 million ha was managed by FTW between 1998 and 2010 (Korea Forest Service 2011). In addition, the equation for volume–age relationship also has limitations, as the volume could not be larger than the constant w. However, since tree volume will be different even in the same tree species, the maximum tree volume would be different as well, and actual volume may even exceed the value of w.

Figure 2 Comparison between actual and predicted values of average volume (m³) for the five main forest types (from left to right: Pinus densiflora, P. koraiensis, P. rigida, Larix kaempferi, and Quercus spp.)

Predicting forest volume and carbon stock

This study was focused on attempting to estimate the change in forest volume from 2010 to 2110 for five forest types. As a result, the average volume per hectare is predicted to increase from 126.89 m³/ha in 2010 to 246.61 m³/ha by 2110. The distribution of the volume in 2060 was assessed for observing increasing trends over 100 years. The total volume and per hectare volume will be 1,347,122,701 m³ and 226.81 m³/ha, respectively (Table 3). Based on the changes in the volume of each forest, we estimated the change in carbon stocks for the current five main forest types of Korea for the next 100 years (Table 4). In 2110, the total carbon stock of Korea's forests will be 592.53 Tg, which is 292.54 Tg higher than that in 2010. According to this, the carbon stock will increase to2.93 Tg C/yr and 0.5 Mg C/(ha·yr) during the period from 2010 to 2110. As is shown in Table 3, the carbon stocks increased by almost twice as much from the current situation to 2060 (Figure 3). However, for 50 more years after 2060, our predictions show that this increase will slow down. This is because the present forest is occupied mainly by young trees. Therefore, the volume will increase more rapidly while the trees are young and growing at a fast rate, and the volume and thus the rate of growth will slow down when the trees are in their mature period.

Table 3 Estimated volume change for each forest type and in total from 2010 to 2110

		Present			After 50 years			After 100 years
Species	Forest area (ha)*	m^3	m^3/ha	Percentage (%)	m^3	m^3/ha	Percentage (%)	m^3	m^3/ha	Percentage (%)
Pinus densiflora	1,716,488	289,575,383	168.70	38.42	441,685,550	257.32	32.79	471,410,394	274.64	32.18
P. koraiensis	203,876	22,616,706	110.93	3.00	37,449,770	183.69	2.78	37,452,068	183.70	2.56
P. rigida	351,618	42,382,794	120.54	5.62	68,651,200	195.24	5.10	68,706,109	195.40	4.69
Larix kaempferi	478,454	64,397,186	134.59	8.54	166,147,333	347.25	12.33	173,596,314	362.83	11.85
Quercus spp.	3,188,869	334,684,954	104.95	44.41	633,188,848	198.56	47.00	713,538,380	223.76	48.72
Total	5,939,305	753,657,023		100	1,347,122,701		100	1,464,703,265		100

Table 4 Estimated carbon stock change for each forest type and in total from 2010 to 2110

	Present			After 50 years			After 100 years
Species	Mg C	Mg C/ha	Percentage (%)	Mg C	Mg C/ha	Percentage (%)	Mg C	Mg C/ha	Percentage (%)
Pinus densiflora	91,696,941	53.42	30.57	139,864,146	81.48	25.85	149,276,815	86.97	25.19
P. koraiensis	8,598,306	42.17	2.87	14,237,466	69.83	2.63	14,238,340	69.84	2.40
P. rigida	14,845,845	42.22	4.95	24,047,142	68.39	4.44	24,066,376	68.44	4.06
Larix kaempferi	19,253,471	40.24	6.42	49,674,730	103.82	9.18	51,901,826	108.48	8.76
Quercus spp.	165,595,422	51.93	55.20	313,289,178	98.24	57.90	353,044,520	110.71	59.58
Total	299,989,984		100	541,112,663		100	592,527,877		100

Li et al. (2010) estimated carbon stocks in Korea from 1954 to 2007. Their paper shows that the forest area possessed 196.45 Tg C in 2007. We calculated almost 300 Tg C (above 95% of forest area) in 2010, which is almost 1.5 times higher than their estimation of carbon stocks in 2007. This kind of difference may be caused by the difference in the models used. Li et al.'s (2010) study was based on a linear model to estimate carbon stocks; however, we used a non-linear model, which fitted to the general tree growth trend.

The carbon stocks will increase at a rate of 0.5 Mg C/(ha·yr) during the period from 2010 to 2110, and, although this estimation is probably different from the actual rate of increase, the disparity between the estimated and actual values would not be very large. Moreover, the rate of increase in carbon stock in Korea would still be higher than that in Canada (−0.10 Mg C/(ha·yr)), Russia (0.08 Mg C/(ha·yr)),or China (0.28 Mg C/(ha·yr))(Fang et al. 2005). This remarkable value shows that the Korean forest has a great potential for the sequestration of carbon. However, again, on comparing the carbon sequestration between the first 50 years (0.81 Mg C/(ha·yr)) and the second 50 years (0.17 Mg C/(ha·yr)) of our 100-year prediction, we find that the first increase in carbon sequestration in the first 50 years is almost five times that for the next 50 years. This illustrates that many trees will have achieved a mature state after 50 years, and, thus, preparing and formulating effective forest management is necessary so that the decrease in the rate of carbon sequestration after 50 years is prepared for and accounted for in future studies.

Conclusion

In this study, we attempted to estimate carbon stocks at the present time and 100 years into the future in Korea, using forest cover and NFI data. According to the regression model (volume–age relationships) that we applied to estimate the present and future tree volumes, we found that the five main forest types in South Korea have a high potential to store and sequestrate carbon. Our results show that tree volume will double from 2010 (126.89 m³/ha) to 2110 (246.61 m³/ha), and a similar trend will be followed for carbon stocks during the same period (50.51–99.76 Mg C/ha). More specifically, the sequestration of carbon from 2010 to 2050 (241,122,678 Mg C) will be five times higher than that from 2050 to2100 (51,415,214 Mg C).

However, it should be noted that in this study the change in forest carbon stocks was estimated without considering the influence of forest management practices (such as thinning and forest tending works) and climate change, which can cause changes in tree species and mortality, or disasters by forest fires, pests, and disease. In future studies, more reliable results can be obtained if these factors are considered. Nevertheless, this study is meaningful, as the estimated carbon stocks were based on the data from NFI and forest cover maps. This research will be helpful as fundamental data to be used for decision-making and forest management or for the development of a more accurate model for the estimation of forest carbon stocks into the future.

Acknowledgements

The authors would like to thank J.Y. Fang and J.L. Zhu for their invaluable comments about the biomass–age relationship model for estimating carbon stocks in forests. This study was carried out with the support of “Developing Forest Management Model for Climate Change Adaptation (Project No. FE0100-2009-01)” provided by the Korea Forest Research Institute and the “A3 Foresight Program” (Grant No A307-K005) provided by the National Research Foundation of Korea.

Notes

*We assumed that forest area would not be changed from 2010 to 2110.

Figure 3 Estimated change in carbon stock (Mg C) and carbon distribution from left to right, 2010, 2060 and 2110, respectively