Journal of Ecology and Environment

pISSN 2287-8327 eISSN 2288-1220

Article

Home Article View

Research

Published online September 14, 2022
https://doi.org/10.5141/jee.22.036

Journal of Ecology and Environment (2022) 46:24

© The Ecological Society of Korea.

Carbon balance and net ecosystem production in Quercus glauca forest, Jeju Island in South Korea

Heon Mo Jeong1 , Young Han You2 and Seungbum Hong3*

1Climate Change and Carbon Research Team, National Institute of Ecology, Seocheon 33657, Republic of Korea
2Department of Biology, Kongju National University, Gongju 32588, Republic of Korea
3Ecological Adaptation Research Team, National Institute of Ecology, Seocheon 33657, Republic of Korea

Correspondence to:Seungbum Hong
E-mail sbhong@nie.re.kr

Received: May 4, 2022; Revised: August 4, 2022; Accepted: August 23, 2022

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Background: To assess the carbon sequestration capacity and net ecosystem productivity (NEP) of Quercus glauca forests, we analyzed the net primary productivity (NPP), carbon storage, and carbon emission of soil in a Q. glauca forest on Jeju Island (South Korea) from 2016 to 2018.
Results: The average carbon stock in the above- and below-ground plant biomass was 223.7 Mg C ha–1, while the average amount of organic carbon fixed by photosynthesis was 9.8 Mg C ha–1 yr–1, and the average NPP was 9.6 Mg C ha–1 yr–1. Stems and branches contributed to the majority of the above- and below-ground standing biomass and NPP. The average heterotrophic carbon emission from the soil was 8.7 Mg C ha–1 yr–1, while the average NEP was 1.1 Mg C ha–1 yr–1. Although the carbon stock, carbon absorption, and soil respiration values were higher than those reported in other oak forests in the world, the NEP was similar or lower.
Conclusions: These results indicator that Q. glauca forests perform the role of a large carbon sink through the CO2 absorption in the plants in terms of carbon balance. And it is judged to be helpful as data for assessment of carbon storage and flux in the forests and mitigation of elevated CO2 in the atmosphere.

Keywords: carbon budget, net ecosystem productivity, net primary productivity, soil respiration, standing biomass

Understanding the carbon cycle of terrestrial ecosystems is essential for evaluating an ecosystem’s ability to reduce atmospheric carbon dioxide (CO2) levels. Plants take up atmospheric CO2 through photosynthesis, releasing it into the atmosphere via respiration by plant metabolism or heterotrophic respiration by leaf decomposition. CO2 captured by plants is stored in vegetation and soil in the form of organic matter, and terrestrial ecosystems function as reservoirs for accumulated carbon. Houghton (2007) reported that terrestrial ecosystems contribute to the global carbon cycle, along with the atmosphere and oceans, by storing 550 Pg C year–1 in vegetation, 300 Pg C year–1 in litterfall, and 1,200 Pg C year–1 in soil. As such, terrestrial ecosystems play an important role in the global carbon cycle by absorbing and storing atmospheric carbon and releasing it through respiration. Nevertheless, the carbon budget of terrestrial ecosystems has not been studied in depth in South Korea, with most research examining forest productivity and carbon storage. Studies investigating carbon storage in forests in South Korea have been conducted in Seoraksan National Park (147 Mg C ha–1), Mudeungsan National Park (112 Mg C ha–1), Jirisan National Park (107 to 119 Mg C ha–1), the Quercus mongolica forest of Jeombongsan, Gangwon-do (140 Mg C ha–1), and the subalpine grasslands of Hallasan National Park (13.9 Mg C ha–1) (Jang et al. 2017; Jeong et al. 2016; Lee 2012a; Lee 2012b; Lee et al. 2015).

Increasing atmospheric CO2 concentrations and global warming are major environmental concerns worldwide. CO2 is widely known to be a major contributor to the greenhouse effect. Due to the influence of CO2, the average global temperature in 2019 was 1.1 ± 0.1°C higher than before industrialization, and the global mean sea level has risen 3.24 ± 0.33 mm per year since January 1993 (WMO 2020). One way to reduce greenhouse gases is to increase carbon sequestration by soil and plants in the forest, which can be realized through efficient forest management and conservation led by government policies. The Intergovernmental Panel on Climate Change (Shukla et al. 2019) mentioned that the land sink including forest ecosystem increased since 1900 and was a net sink of 11.7 Gt CO2 yr–1 (2008–2017), absorbing 29% of global anthropogenic emissions of CO2.

The forested area of South Korea covers 6,335,000 ha, accounting for 63.2% of the total land area (Korea Forest Service 2016). Approximately 0.15% of this forested area (9,669 ha) is covered by evergreen broad-leaved forests (Yoo et al. 2016), including Q. glauca, Q. acuta, Castanopsis sieboldii, Machilus thunbergii, and mixed forests mainly distributed in the southern regions, including Jeju Island, the lowlands, and islands. Although these forests are only distributed in the subtropical region of South Korea and occupy a small area, they maintain high biodiversity due to their diverse topographies and climates. The effects of global warming are predicted to cause the subtropical climate of South Korea to expand from the southern coast and the eastern coast of Korean peninsula, and then to the west coast and inland from 2071 to 2100 based on the A1B scenario (Kwon et al. 2007). Accordingly, the distribution of trees such as Q. glauca and Q. acuta is predicted to expand northward to the central region, causing major changes in the ecosystem of South Korea. Hence, there is a critical need for research on the ecological properties and functions of evergreen broad-leaved forests.

This study aimed to quantify the net primary production (NPP) and net ecosystem production (NEP) of a Q. glauca forest, one of the representative evergreen broad-leaved forests in South Korea, to estimate its productivity and carbon sequestration capacity. Tree diameter measurements were undertaken from 2016 to 2018 at a study site in the Q. glauca forest on Jeju Island, and the temperature and humidity of the soil were measured. The results of this study will be used to further understand the carbon sequestration capacity of Q. glauca forests in South Korea.

Study site

The Q. glauca forest study site was located in the Seonheul Gotjawal area, Seonheul-ri, Jocheon-eup, Jeju City, Jeju Island, South Korea (33° 31 09” N, 126° 42 57” E, Fig. 1). The Gotjawal ecosystem possesses a well-known and unique volcanic topography, with little soil or a relatively shallow layer of topsoil, and large and small rock masses of hardened lava from volcanic eruptions (Park et al. 2014). This uneven topography has been affected by collapse due to the cooling and cracking of lava, weathering, and vegetation growth (Koh et al. 2013), thereby forming various microhabitats for organisms, including endangered plants. The Seonheul Gotjawal area was continuously disturbed by tree cutting in the past, but has been designated as a protected area. The vegetation has been restored without human disturbance for about 30 years and is mostly composed of coppice sprout forests (Han et al. 2007). The Q. glauca forest in the Seonheul Gotjawal contains approximately 10% of the evergreen broad-leaved trees distributed on Jeju Island (Kwak et al. 2013). The Seonheul Gotjawal was registered as Wetland Protection Area (0.590 km2) in 2010, a Ramsar Site in 2011, and is rare wetland that the area 0.59 km2. This site is symbolic wetland that northern lineage and southern lineage plants co-exist with its special ecological environment. The Seonheul Gotjawal is home to many warm temperate evergreen trees such as Q. glauca, Q. salicina, Castanopsis cuspidata, Styrax japonica, Camellia japonica, and Eurya japonica (Han et al. 2007).

Figure 1. A map showing study site in Seonheul Gotjawal, Jeju Island (dotted line in figure appears boundary of Wetland protection area).

We had established the quadrat (10 × 10 m2) of Q. glauca forest to estimate the standing biomass, NPP and soil respiration in March, 2016. This study site is a place where NEP research has been conducted in the past (2011–2012, Han et al. 2018), and is meaningful in trend of NEP variations through the long-term and continuous research. This place is difficult for people to access, so there is no physical disturbance and the growth of trees is well.

The study site was located in a subtropical climate region (Kira 1991), with average annual temperatures of 14.3, 13.7, and 13.6°C in 2016, 2017, and 2018, respectively, which were within the average annual temperature range (10 to 15°C) of South Korea for the last 30 years (Fig. 2, Korea Meteorological Administration www.weather.go.kr). The average monthly maximum and minimum temperatures at the study site were 29.2, 29.8, and 28.7°C, and 0.5, –0.3, and –1.2°C, in 2016, 2017, and 2018, respectively. The average monthly maximum temperatures were higher than the average summer temperature in South Korea (23 to 26°C), whereas the average monthly minimum temperatures were within the range of the average winter temperature (–6 to 3°C), but on the higher side. The annual precipitation at the study site was 2,325.5, 1,034.0, and 2,289.0 mm in 2016, 2017, and 2018, respectively. The annual precipitation at the study site was higher than the average annual precipitation for the last 30 years on Jeju Island (1,500 to 1,900 mm) in 2016 and 2018, but much lower in 2017.

Figure 2. Monthly rainfall and atmospheric temperature (mean: TMean, maximum: TMax, and minimum: TMin temperature) from 2016 to 2018 in Seoheul Gotjzawal.

Standing biomass and NPP

The standing biomass and NPP of the Q. glauca forest were estimated by measuring the diameter at breast height (DBH) of all trees with DBH ≥ 3 cm within a 100 m² quadrat in the Q. glauca forest in April, 2016–2018. Although the best way to measure the biomass of trees is to harvest them, this was impossible in the Seonheul Gotjawal, as it is a protected wetland area. A well-known method for measuring the biomass of trees is to use allometric equations (Kang and Kwak 1998). In general, tree height and DBH have a positive correlation with the biomass of each organ, such as the stems, branches, and leaves of the tree (Kwon and Lee 2006). Therefore, the standing biomass of the above- ground Q. glauca forest was estimated by substituting DBH for the allometric equation suitable for each species (Table 1) (Jeong et al. 2014; Kwak et al. 2004; Mun 2006; Rodin and Bazilevich 1967; Son et al. 2014). And when there is no allometric equation relative to a specific tree species, we applied suitable equation considered classification group, height and shape type.

Table 1 . Regression models used estimation of standing biomass.

SpeicesAllometric equationReference
Quercus glauca Thunb.log Wstem = 2.4042logDBH-1.3045
log Wbranch = 2.6436logDBH-1.6232
log Wleaf = 1.5428logDBH-1.3692
Jeong et al. (2014)
Pinus thunbergii Parl.Wstem = 0.081(DBH)2.445
Wbranch = 0.028(DBH)2.327
Wleaf = 0.094(DBH)1.658
Son et al. (2014)
Castanopsis seiboldii Hatus.Wstem = 0.223(DBH)2.092
Wbranch = 0.004(DBH)3.050
Wleaf = 0.009(DBH)2.883
Styrax japonicus Siebold & Zucc.Wstem = 0.4505(D2H)-0.0943
Wbranch = 0.4505(D2H)-0.6943
Wleaf = 0.3455(D2H)-0.5943
Kwak et al. (2004)
Camellia japonica L.Wstem = 0.034(DBH)2.475
Wbranch = 0.002(DBH)3.738
Wleaf = 0.036(DBH)1.995
Son et al. (2014)
Eurya japonica Thunb.
Mallotus japonicus Müll. Arg.Wstem+branch = 0.6067(DBH)0.8355
Wleaf = 0.7318(DBH)0.6108
Mun (2006)

DBH: diameter at breast height.



The below-ground biomass is known to account for 15 to 35% of the plant body for perennials, and the below-ground biomass of Q. glauca reportedly accounts for 0.229 of the above-ground biomass as coefficient of Q. glauca root (Rodin and Bazilevich 1967; Son et al. 2014).

NPP is the net amount of carbon gained through photosynthesis by plants, which can be estimated by the difference between the gross primary production (GPP) and the amount of carbon released by plant respiration (Chapin III and Eviner 2014). The annual NPP of the Q. glauca forest (ΔW) was calculated by subtracting the standing biomass of the current year (W1) from the standing biomass of the following year (W2), during the study period from 2016 to 2018 (1).

ΔW=W2W1

Carbon storage and absorption

The carbon budget of a forest is affected by NPP and processes such as heterotrophic respiration in the soil (Cai et al. 2016). To estimate the amount of carbon storage and absorption of all trees in the Q. glauca forest, the above- and below-ground standing biomass and net production were used, estimating the organic carbon content to be 45% (Houghton 1983). The annual carbon absorption through CO2 assimilation was calculated by subtracting the carbon absorption of the year (C1) from the carbon absorption of the following year (C2), during the study period from 2016 to 2018 (2).

ΔC=C2C1

Heterotrophic respiration from soil and NEP

The soil respiration of the forest was estimated using a previously reported correlation equation between temperature and CO2 emission at a soil depth of 10 cm, measured using an infra-red CO2 gas analyzer (EGM-4; PP Systems, Haverhill, MA, USA) from August 2010 to December 2012 (Jeong et al. 2017). In general, the amount of CO2 emitted demonstrates a positive exponential relationship with the soil temperature. In the current study, an automatic weather system (Em50 data logger and Teros 11 Soil Moisture and Temperature Sensor; METER Group, Inc., Pullman, WA, USA) was installed in the study site in April, 2016. And soil temperature and humidity were measured at every 30 minutes in 2016 and 2017. Monthly and annual CO2 effluxes were calculated by substituting hourly soil temperatures into the relationship. CO2 efflux from forests can be largely divided into that caused by heterotrophs and that caused by tree roots. In previous studies, heterotrophic respiration caused 49% of the CO2 efflux from the Pinus densiflora forest (Nakane et al. 1983), 51% of the CO2 efflux from the Q. serrata forest (Nakane et al. 1996), 46% of the CO2 efflux from the Pinus koraiensis plantation (Pyo et al. 2003), 31% of the CO2 efflux from the Quercus-dominated forest, and 34% of the CO2 efflux from the Q. acutissima forest. In this study, heterotrophic respiration (Rh) was estimated to account for 56% of the total soil respiration, assuming that the root respiration of Q. glauca accounted for 46% of the total soil respiration (Wang et al. 2012). The annual NEP (3) was calculated by subtracting heterotrophic respiration from the amount of carbon increment each year (ΔC).

NEP=ΔCRh

Variations of average DBH and basal area in study site

The DBH and basal area of all trees in Q. glauca forest had steadily increased (Table 2). The mean breast height area was 110.4, 115.8, and 119.8 m2 ha–1 from 2016 to 2018, respectively. The tree species with the longest DBH was Castanopsis seiboldii. However, the trees species with the greatest basal area was Quercus glauca increased in order of P. thunbergii, C. japonica, C. seboldii, S. japonicas, C. japonica, E. japonica and M. japonicas. The basal area of S. japonicas was decreased by approximately 0.6 m2 ha–1. The reduction of basal area was caused by a decrease of individuals.

Table 2 . Average DBH and basal area of appearance tree species from 2016 to 2018.

Species201620172018
DBH (cm)Basal area
(m2 ha–1)
DBH (cm)Basal area
(m2 ha–1)
DBH (cm)Basal area
(m2 ha–1)
Quercus glauca8.7 ± 3.085.19.0 ± 3.190.09.1 ± 3.193.1
Pinus thunbergii14.8 ± 3.59.015.3 ± 3.59.615.5 ± 3.49.8
Castanopsis seiboldii28.2 ± 0.06.228.3 ± 0.06.328.9 ± 0.06.6
Styrax japonicus9.9 ± 2.05.511.0 ± 1.74.911.0 ± 1.84.9
Camellia japonica5.7 ± 0.83.15.7 ± 0.83.45.8 ± 0.83.6
Eurya japonica8.0 ± 3.81.28.2 ± 3.91.28.7 ± 3.51.5
Mallotus japonicus6.9 ± 0.00.47.1 ± 0.00.47.6 ± 0.00.5
Total110.4115.8119.8

DBH values are presented as mean ± standard deviation.

Standing biomass and organic carbon in plants.

DBH: diameter at breast height.



The basal area in this study site represented high value of about 115.3 m2 ha–1, which was about three times larger than 37.1 in Q. acuta forest as evergreen oak forest (Park 2012). The Q. glauca forest in Jeju island was continuously disturbed by thinning, but the vegetation has been restored as a sprout forest while human disturbance has been suspended for about 45 years. For this reason, sprouts of Q. glauca are very well developed, and the density of tree is high with 158 trees/100 m2 in 2018. High density of trees according to development of sprout contributed to the high basal area. However, It is necessary to increase the accuracy through the installation of sampling site, since small sampling site of this study can increase the variation of basal area.

The total standing biomass of the Q. glauca forest was 475.7, 496.4, and 519.0 Mg ha–1 in 2016, 2017, and 2018, respectively (Fig. 3). The biomasses of the stems, branches, leaves, and roots were 206.1, 142.2, 38.8, and 88.6 Mg ha–1, respectively, in 2016; 215.2, 149.6, 39.1, and 92.5 Mg ha–1, respectively, in 2017; and 224.3, 157.2, 40.7, and 96.7 Mg ha–1, respectively, in 2018. The stems generated the highest biomass in the Q. glauca forest, followed by the branches, roots, and leaves.

Figure 3. Standing biomass of Quercus glauca forest from 2016 to 2018.

The amount of organic carbon in the Q. glauca forest was 214.1, 223.4, and 233.6 Mg C ha–1 in 2016, 2017, and 2018, respectively. The amount of organic carbon in the stems, branches, leaves, and roots was 92.7, 64.0, 17.4, 39.9 Mg C ha–1, respectively, in 2016; 96.8, 67.3, 17.6, 41.6 Mg C ha–1, respectively, in 2017; and 101.0, 70.8, 18.3, 43.5 Mg C ha–1, respectively in 2018. Similar to the biomass, the stems contained the highest amount of stored organic carbon, followed by the branches, roots, and leaves.

Net primary production and carbon absorption

The NPP of the Q. glauca forest was 20.7 and 22.6 Mg ha–1 yr–1 in 2016 and 2017, respectively (Fig. 4). In 2016, NPP was highest in the stems (9.1 Mg ha–1 yr–1), followed by the branches (7.3 Mg ha–1 yr–1), roots (3.9 Mg ha–1 yr–1), and leaves (0.4 Mg ha–1 yr–1). Similar values were obtained in 2017, where NPP was highest in the stems (9.1 Mg ha–1 yr–1), followed by the branches (7.7 Mg ha–1 yr–1), roots (4.2 Mg ha–1 yr–1), and leaves (1.6 Mg ha–1 yr–1). Upon converting the NPP of the Q. glauca forest into the amount of organic carbon, the Q. glauca forest was estimated to have absorbed and stored 2.5 and 2.8 Mg ha–1 yr–1 of atmospheric carbon in 2016 and 2017, respectively.

Figure 4. Net primary production of Quercus glauca community from 2016 to 2017.

Heterotrophic respiration and net ecosystem production

The average soil temperatures in 2016 and 2017 of the Q. glauca forest were 14.9 and 14.8°C, respectively, demonstrating similar monthly soil temperature patterns (Fig. 5). In 2016, the soil temperature was highest in August (24.2°C) and lowest in February (6.5°C). Similarly, the soil temperature in 2017 was highest in August (24.6°C) and lowest in February (6.7°C). The soil respiration (CO2 efflux) of the Q. glauca forest was 59.6 and 58.2 Mg CO2 ha–1 yr–1 in 2016 and 2017, respectively, demonstrating similar monthly soil respiration patterns. In 2016, soil respiration was highest in August (12.6 Mg CO2 ha–1) and lowest in January and February (1.2 Mg CO2 ha–1). Similarly, soil respiration in 2017 was highest in August (13.3 Mg CO2 ha–1) and lowest in February (1.0 Mg CO2 ha–1).

Figure 5. Monthly dynamics of soil temperature and respiration of Quercus glauca forest from 2016 to 2017.

Estimating values based on the total soil respiration of the Q. glauca forest, the heterotrophic respiration and root respiration were 32.2 and 27.4 Mg CO2 ha–1, respectively, in 2016, and 31.4 and 26.8 Mg CO2 ha–1, respectively, in 2017. Thus, the CO2 efflux from the Q. glauca forest was estimated to be 8.8 and 8.6 Mg C ha–1 in 2016 and 2017, respectively. The NEP of the Q. glauca forest was calculated to be 0.5 and 1.6 Mg C ha–1 yr–1 in 2016 and 2017, respectively (Table 3).

Table 3 . Carbon stock and carbon absorption in the Q. glauca forest from 2016 to 2018.

Carbon storage and flux201620172018
Total biomass C stock (Mg C ha–1)214.1223.4233.6
Annual C absorption (Mg C ha–1 yr–1)9.310.2
Annual C efflux (Mg C ha–1 yr–1)8.88.6-
Net ecosystem production (Mg C ha–1 yr–1)0.51.6

Approximately 140 species of the genus Quercus are distributed in Asia, of which Q. glauca is distributed in the western Himalayas, the tropical and subtropical regions of China, and the central Honshu region of Japan (Menitsky 2009). In South Korea, Q. glauca dominates the low mountains of Jeju Island and the southwest region of the country (Kim and Kim 2012). Distributed in relatively diverse environments from alpine to subtropical areas, Q. glauca appears to have a variety of ecological niches.

During the study period from 2016 to 2018, the average standing biomass of the Q. glauca forest was 497.0 Mg ha–1 (Fig. 3), which was higher than that of Quercus forests in other areas. In previous studies, the standing biomass of Quercus forests varied from 10.3 to 1,130.8 Mg ha–1, due to environmental differences in Quercus habitats. On Jeju Island, the annual precipitation generally exceeded 2,000 mm (except in 2017), and the average annual temperature ranged from 13.6 to 14.3°C. In particular, the underground rock layer in the Gotjawal region of Jeju Island where the Q. glauca forest was located had a high water holding capacity (Jang and Lee 2009) and the temperature in the coldest month did not drop much below 0°C. This environment seems to have played a major role in maintaining the high productivity of the Q. glauca forest. Indeed, the Q. serrata forest in India, with a greater standing biomass than the Q. glauca forest in this study, is located in an area that is hot and humid in summer, but warm and humid in winter, with an average monthly maximum temperature as high as 21.7°C (January) to 29.5°C (August), as well as an average annual precipitation of 1,430 mm (Waikhom et al. 2018). The previously reported standing biomass of the Q. glauca forest was 345.9 Mg ha–1 in 2011 and 368.4 Mg ha–1 in 2012, indicating an increase in the standing biomass of this forest over time. The DBH of the trees in the forest ranged from 4.6 to 29.7 cm and the age of the Q. glauca trees was as high as 42 years (Jeong et al. 2017). Thus, the standing biomass of the protected Q. glauca forest is expected to continue to increase.

The amount of stored organic carbon was estimated to be 223.7 Mg C ha–1 during the study period, which was greater than that of the Q. brantii forest in Iran (22.1 Mg C ha–1) (Mahdavi et al. 2020), the evergreen Quercus forest in China (52.7 Mg C ha–1) (Wang et al. 2010), and the subtropical broad-leaved forest in China (32.8 Mg C ha–1) (Wang et al. 2010). The amount of organic carbon reportedly stored in the Q. serrata forest of India, with greater standing biomass than the forest in the current study, was 481.5 to 565.4 Mg C ha–1 (Waikhom et al. 2018). Meanwhile, the amount of stored organic carbon previously reported in the Q. glauca forest was 155.63 Mg C ha–1 in 2011 and 165.79 Mg C ha–1 in 2012 (Han et al. 2018), indicating an increase in the organic carbon stock of this forest over time.

The NPP of the Q. glauca forest was 20.7 and 22.6 Mg ha–1 in 2016 and 2017, respectively, which was higher than the NPP of the global temperate evergreen forest (13.0 Mg ha–1) (Whittaker and Likens 1973), the Q. robur forest in Europe (6.8 Mg ha–1) (Houghton 2007), and the Q. ilex forest (11.2 Mg ha–1) (Escarré et al. 1987). The NPP was also similar to that previously reported for the Q. glauca forest in 2011 (22.6 Mg ha–1) (Han 2018), indicating that the high productivity of the Q. glauca forest in Seonheul Gotjawal has remained stable over time.

Based on the NPP of the Q. glauca forest, carbon absorption by photosynthesis was calculated to be 9.3 and 10.2 Mg C ha–1 yr–1 in 2016 and 2017, respectively. This value was greater than the net carbon absorption of the evergreen Quercus forest in China (4.55 Mg C ha–1 yr–1), the subtropical broad-leaved forest (5.97 Mg C ha–1 yr–1 (Wang et al. 2010), and the deciduous Q. robur forest in Croatia (6.8 Mg C ha–1 yr–1) (Anić et al. 2018). On the other hand, the previously reported carbon absorption of the Q. glauca forest from 2011 to 2012 was approximately 14.2 Mg C ha–1 yr–1 (Han et al. 2018), which was greater than that found in this study.

Soil respiration is largely divided into heterotrophic respiration by soil microorganisms and root respiration (Lou and Zhou 2006), which needs to be analyzed to accurately estimate NEP. In this study, the carbon efflux was 8.8 and 8.6 Mg C ha–1 yr–1 in 2016 and 2017, respectively, which was similar to the average carbon efflux reported between 2011 and 2012 (8.85 Mg C ha–1 yr–1) (Wang et al. 2010). Moreover, the carbon efflux in the current study was greater than that of the evergreen Quercus forest in China (3.02 Mg C ha–1 yr–1) (Wang et al. 2010), the deciduous Q. robur forest in Croatia (5.0 Mg C ha–1 yr–1) (Anić et al. 2018). The soil respiration of forests tends to increase with increasing productivity. In the 80-year-old deciduous Quercus forest of the United Kingdom, GPP reportedly demonstrated a positive correlation with soil respiration (Wilkinson et al. 2012). Soil respiration is also known to be significantly affected by soil temperature and moisture (Davison et al. 1998; Inclán et al. 2010). The NPP and soil respiration in the current study were much greater than those of other Quercus forests, likely because the current study was conducted in a subtropical region with high average annual temperatures and precipitation, which may have affected the high CO2 efflux from the soil.

The NEP at the study site was 0.6 and 1.6 Mg C ha–1 yr–1 in 2016 and 2017, respectively, which was lower than that previously reported for the same Q. glauca forest (5 Mg C ha–1 yr–1) (Han et al. 2018). The NEP in 2016 was lower than that in 2017, as the NPP of the leaves in 2016 was as low as 25% that of the leaves in 2017, despite the increase in NPP of the stem, branches, and roots. Additionally, the carbon absorption was higher in 2011 and 2012 than in 2016 and 2017, which may have been due to differences in calculations for carbon absorption. The NEP of the Q. glauca forest was lower than or similar to that of the evergreen Quercus forest in China (1.53 Mg C ha–1 yr–1), the deciduous Q. cuspidata forest in Japan (3.47 Mg C ha–1 yr–1), and the NEE (net ecosystem exchange) of the deciduous Q. robur forest (3.19 Mg C ha–1 yr–1). In comparison with other Quercus forests in South Korea, the NEP of the Q. glauca forest was lower than or similar to that of the deciduous Q. acutissima forest (4.6 Mg C ha–1 yr–1) (Lee and Mun 2005) and the Q. mongolica forest (1.61 Mg C ha–1 yr–1) (Won et al. 2014).

The above results indicate that while the carbon stock and absorption of the Q. glauca forest were greater than those of other Quercus forests in South Korea and overseas, the NEP was lower than or similar to that of other Quercus forests, likely due to the high soil respiration. The productivity of trees is affected by abiotic environmental factors such as temperature and precipitation, as well as biotic environmental factors, such as biodiversity and structural diversity of the forest. Odum and Barrett (2005) reported a positive correlation between standing biomass and species diversity in a forest succession model. Studies have also reported that structural diversity, such as the thickness and height of trees, is associated with the above-ground biomass of forests (Con et al. 2013; Jeong et al. 2016). Due to the subtropical climate and growth of several species of arboreal and shrub plants as well as sprouts, trees of various sizes and ages were distributed in the Q. glauca forest, resulting in high productivity. Higher structural diversity and carbon stock were previously observed in older and more mature forests (Martínez-Sánchez et al. 2015). Thus, the Q. glauca forest is expected to function as a carbon sink for even more carbon at the climax of forest succession.

This study demonstrated the productivity and carbon absorption capacity of the Q. glauca forest on Jeju Island, a representative subtropical forest in South Korea. The average amount of carbon stored in the Q. glauca forest was 223.7 Mg C ha–1, with the highest carbon stock in the stems, followed by the branches, roots, and leaves. The annual average carbon absorption was 9.8 Mg C ha–1 yr–1, with the highest adsorption also in the stems, followed by the branches, roots, and leaves. The annual average carbon efflux by heterotrophic respiration was 8.7 Mg C ha–1 yr–1 and the NEP was approximately 1.1 Mg C ha–1 yr–1 during the study period. Compared with various Quercus forests in South Korea and overseas, the Q. glauca forest had higher carbon stock, productivity, and soil respiration, but lower NEP. Such characteristics may have been due to the forest’s location in a subtropical region with high annual temperatures and precipitation, as well as being populated with trees of various types and ages. As subtropical forests are expected to expand in the southern and coastal regions of South Korea due to global warming, which will likely be accompanied by changes in vegetation, the function of the Q. glauca forest as a carbon sink will become even more important.

HMJ did conceptualization, methodology, software, formal analysis, investigation, data curation, writing-original draft preparation and visualization. YHY did conceptualization, validation, review and editing, supervision. SH did conceptualization, investigation, review and editing, supervision, project administration.

This study was supported by a grant from the National Institute of Ecology (NIE), funded by the Ministry of Environment (MOE) of the Republic of Korea (NIE-B-2022-35).

  1. Anić M, Sever MGO, Alberti G, Balenović I, Paladinić E, Peressotti A, et al. Eddy Covariance vs. biometric based estimates of net primary productivity of pedunculate oak (Quercus robur L.) forest in croatia during ten years. Forests. 2018;9(12):764. https://doi.org/10.3390/f9120764.
    CrossRef
  2. Cai H, Di X, Chang SX, Wang C, Shi B, Geng P, et al. Carbon storage, net primary production, and net ecosystem production in four major temperate forest types in northeastern China. Can J For Res. 2016;46(2):143-51. https://doi.org/10.1139/cjfr-2015-0038.
    CrossRef
  3. Chapin III FS, Eviner VT. Biogeochemical interactions governing terrestrial net primary production. In: Holland HD, Turekian KK, editors. Treatise on geochemistry. 2nd ed. Oxford: Elsevier; 2014. p. 189-216.
    CrossRef
  4. Con TV, Thang NT, Ha DTT, Khiem CC, Quy TH, Lam VT, et al. Relationship between aboveground biomass and measures of structure and species diversity in tropical forests of Vietnam. For Ecol Manag. 2013;310:213-8. https://doi.org/10.1016/j.foreco.2013.08.034.
    CrossRef
  5. Davidson EA, Belk E, Boone RD. Soil water content and temperature as independent or confounded factors controlling soil respiration in a temperate mixed hardwood forest. Glob Change Biol. 1998;4(2):217-27. https://doi.org/10.1046/j.1365-2486.1998.00128.x.
    CrossRef
  6. Escarré A, Ferrés L, Lopez R, Martin J, Rodá F, Terrades J. Nutrient use strategy by evergreen-oak (Quercus ilex ssp. ilex) in NE Spain. In: Tenhunen JD, Catarino FM, Lange OL, Oechel WC, editors. Plant response to stress. Berlin: Springer; 1987. p. 429-35.
    CrossRef
  7. Han BH, Kim JY, Choi IT, Lee KJ. Vegetation structure of evergreen broad-leaved forest in Dongbaekdongsan(Mt.), Jeju-Do, Korea. Korean J Environ Ecol. 2007;21(4):336-46.
  8. Han YS, Lee EP, Park JH, Lee SY, Lee SI, You YH. Organic carbon distribution and cycling in the Quercus glauca forest at Gotjawal wetland, Jeju Island, Korea. J Ecol Environ. 2018;42:8. https://doi.org/10.1186/s41610-018-0068-1.
    CrossRef
  9. Houghton RA, Hobbie JE, Melillo JM, Moore B, Peterson BJ, Shaver GR, et al. Changes in the carbon content of terrestrial biota and soils between 1860 and 1980: a net release of CO2 to the atmosphere. Ecol Monogr. 1983;53(3):235-62. https://doi.org/10.2307/1942531.
    CrossRef
  10. Houghton RA. Balancing the global carbon budget. Ann Rev Earth Planet Sci. 2007;35(1):313-47. https://doi.org/10.1146/annurev.earth.35.031306.140057.
    CrossRef
  11. Inclán R, Uribe C, De La Torre D, Sánchez DM, Clavero MA, Fernández AM, et al. Carbon dioxide fluxes across the Sierra de Guadarrama, Spain. Eur J Forest Res. 2010;129:93. https://doi.org/10.1007/s10342-008-0247-1.
    CrossRef
  12. Jang RH, Jeong HM, Lee EP, Cho KT, You YH. Budget and distribution of organic carbon in Taxus cuspidata forest in subalpine zone of Mt. Halla. J Ecol Environ. 2017;41:4. https://doi.org/10.1186/s41610-017-0023-6.
    CrossRef
  13. Jang YC, Lee CW. Gotjawal forest in Jeju Island as an internationally important wetland. J Wetl Res. 2009;11(1):99-104.
  14. Jeong HM, Jang I, Hong S. Relationship between aboveground biomass and measures of structure and species diversity in Quercus mongolica-dominated forest, Mt. Jeombong. Korean J Environ Ecol. 2016;30(6):1022-31. https://doi.org/10.13047/KJEE.2016.30.6.1022.
    CrossRef
  15. Jeong HM, Jang RH, Kim HR, You YH. Soil CO2 efflux in a warm-temperature and sub-alpine forest in Jeju, South Korea. J Ecol Environ. 2017;41:23. https://doi.org/10.1186/s41610-017-0041-4.
    CrossRef
  16. Jeong HM, Kim HR, Cho KT, Lee SH, Han YS, You YH. Aboveground biomass estimation of Quercus glauca in evergreen forest, Kotzawal wetland, Cheju Island, Korea. J Wetl Res. 2014;16(2):245-50. https://doi.org/10.17663/JWR.2014.16.2.245.
    CrossRef
  17. Kim JS, Kim KY. [Woody plants of Korea peninsula]. Paju: Dolbegae; 2012. Korean.
  18. Kira T. Forest ecosystems of east and southeast Asia in a global perspective. Ecol Res. 1991;6:185-200. https://doi.org/10.1007/BF02347161.
    CrossRef
  19. Koh GW, Park JB, Kang BR, Kim GP, Moon DC. Volcanism in Jeju Island. J Geol Soc Korea. 2013;49(2):209-30. https://doi.org/10.14770/jgsk.2013.49.2.209.
    CrossRef
  20. Korea Forest Service. Basic forest statistics. Daejeon: Korea Forest Service; 2016.
  21. Kwak JI, Lee KJ, Han BH, Song JH, Jang JS. A study on the vegetation structure of evergreen broad-leaved forest Dongbaekdongsan(Mt.) in Jeju-do, Korea. Korean J Environ Ecol. 2013;27(2):241-52.
  22. Kwak YS, Hur YK, Song JH, Hwangbo JK. Quantification of atmospheric purification capacity by afforestation impact assessment of Kwangyang steel works. Res Inst Ind Sci Technol. 2004;18(4):334-40.
  23. Kwon KC, Lee DK. Above- and below-ground biomass and energy content of Quercus mongolica. J Korea For Energy. 2006;25(1):31-8.
  24. Kwon YA, Kwon WT, Boo KO, Choi YE. Future projections on subtropical climate regions over South Korea using SRES A1B data. J Korean Geogr Soc. 2007;42(3):355-67.
  25. Lee KJ, Mun HT. Organic carbon distribution in an oak forest. Korean J Ecol. 2005;28(5):265-70. https://doi.org/10.5141/JEFB.2005.28.5.265.
    CrossRef
  26. Lee NY, Na KT, Noh JM, Shim S. Estimation of carbon storage in a forest ecosystem at Mudeungsan Mt. National Park, Korea. J Natl Park Res. 2015;6(1):1-6.
  27. Luo Y, Zhou X. Soil respiration and the environment. Burlington: Elsevier; 2006.
  28. Mahdavi A, Saidi S, Iranmanesh Y, Naderi M. Biomass and carbon stocks in three types of Persian oak (Quercus brantii var. persica) of Zagros forests in a semi-arid area, Iran. J Arid Land. 2020;12:766-74. https://doi.org/10.1007/s40333-020-0027-4.
    CrossRef
  29. Martínez-Sánchez JL, Tigar BJ, Cámara L, Castillo O. Relationship between structural diversity and carbon stocks in humid and sub-humid tropical forest of Mexico. Ecoscience. 2015;22(2-4):125-31. https://doi.org/10.1080/11956860.2016.1169384.
    CrossRef
  30. Menitsky YL. Oaks of Asia. Enfield: Science Publishers; 2009.
  31. Mun HT. Biomass estimation of shrub Lindera obtusiloba by allometry. J Ecol Environ. 2006;29(5):485-8. https://doi.org/10.5141/JEFB.2006.29.5.485.
    CrossRef
  32. Nakane K, Kohno T, Horikoshi T. Root respiration rate before and just after clear-felling in a mature, deciduous, broad-leaved forest. Ecol Res. 1996;11(2):111-9. https://doi.org/10.1007/BF02347678.
    CrossRef
  33. Nakane K, Yamamoto M, Tsubota H. Estimation of root respiration rate in a mature forest ecosystem. Jpn J Ecol. 1983;33(4):397-408. https://doi.org/10.18960/seitai.33.4_397.
  34. Odum EP, Barrett GW. Fundamentals of ecology. 5th ed. Belmont: Thomson Brooks/Cole; 2005.
  35. Park JB, Kang BR, Koh GW, Kim GP. Geological characteristics of Gotjawal terrain in Jeju Island. J Geol Soc Korea. 2014;50(3):431-40. https://doi.org/10.14770/jgsk.2014.50.3.431.
    CrossRef
  36. Pyo JH, Kim SU, Mun HT. A study on the carbon budget in Pinus koreansis plantation. Korean J Ecol. 2003;26(3):129-34. https://doi.org/10.5141/JEFB.2003.26.3.129.
    CrossRef
  37. Rodin LE, Bazilevich NI. Production and mineral cycling in terrestrial vegetation. Edinburgh: Oliver & Boyd; 1967.
  38. Son YM, Kim RH, Lee KH, Pyo JK, Kim SW, Hwang JS, et al. Carbon emission factors and biomass allometric equations by species in Korea. Seoul: Korea Forest Research Institute; 2014.
  39. Waikhom AC, Nath AJ, Yadava PS. Aboveground biomass and carbon stock in the largest sacred grove of Manipur, Northeast India. J For Res. 2018;29(2):425-8. https://doi.org/10.1007/s11676-017-0439-y.
    CrossRef
  40. Wang B, Huang J, Yang X, Zhang B, Liu M. Estimation of biomass, net primary production and net ecosystem production of China's forests based on the 1999-2003 National Forest Inventory. Scand J For Res. 2010;25(6):544-53. https://doi.org/10.1080/02827581.2010.524891.
    CrossRef
  41. Wang X, Nakatsubo T, Nakane K. Impacts of elevated CO2 and temperature on soil respiration in warm temperate evergreen Quercus glauca stands: an open-top chamber experiment. Ecol Res. 2012;27(3):595-602. https://doi.org/10.1007/s11284-012-0932-x.
    CrossRef
  42. Whittaker RH, Likens GE. Primary production: the biosphere and man. Hum Ecol. 1973;1:357-69. https://doi.org/10.1007/BF01536732.
    CrossRef
  43. Wilkinson M, Eaton EL, Broadmeadow MSJ, Morison JIL. Inter-annual variation of carbon uptake by a plantation oak woodland in south-eastern England. Biogeosciences. 2012;9:5373-89. https://doi.org/10.5194/bg-9-5373-2012.
    CrossRef
  44. WMO (World Meteorological Organization). WMO statement on the state of the global climate in 2019. Geneva: WMO; 2020.
  45. Won HY, Shin CH, Mun HT. Valuation of ecosystem services through organic carbon distribution and cycling in the Quercus mongolica forest at Mt. Worak National Park. J Wetl Res. 2014;16(3):315-25. https://doi.org/10.17663/JWR.2014.16.3.315.
    CrossRef
  46. Yoo BO, Park JH, Park YB, Jung SY, Lee KS. Assessment of the distributional probability for evergreen broad-leaved forests (EBLFs) using a logistic regression model. J Korean Assoc Geogr Inf Stud. 2016;19(1):94-105. https://doi.org/10.11108/kagis.2016.19.1.094.
    CrossRef

Share this article on :

Related articles in JEE

  • There is No Related Article.
Close ✕

Journal of Ecology and Environment

pISSN 2287-8327 eISSN 2288-1220