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ISSN : 1598-5504(Print)
ISSN : 2383-8272(Online)
Journal of Agriculture & Life Science Vol.50 No.6 pp.45-54
DOI : https://doi.org/10.14397/jals.2016.50.6.45

Basal Area Effects on Soil Respiration Rates of a Pinus densiflora Stand

Jaeyeob Jeong1, Choonsig Kim2*
1Forest Practice Research Center of the National Institute of Forest Science, Pocheon, 11186, Korea
2Department of Forest Resources, Gyeongnam National University of Science and Technology, Jinju, 52725, Korea
Corresponding author : Choonsig Kim +82-55-751-3247Fax: +82-55-751-3247ckim@gntech.ac.kr
August 8, 2016 November 1, 2016 November 2, 2016

Abstract

This study was conducted to determine the relationship between stand and soil environmental factors, and soil respiration rates at various levels of basal area in a 40-year-old natural red pine(Pinus densiflora S. et Z.) stand in southern Korea. Soil respiration rates were measured monthly using an infrared gas analyzer system from six basal area treatments between 21.4 m2 ha-1 and 46.7 m2 ha-1 for one year. Soil respiration at various levels of basal area showed a clear monthly variation, which had a similar pattern to soil temperature. The mean annual soil respiration rates were positively correlated with increasing basal area(r=0.86, p<0.05), aboveground tree carbon (C) storage(r=0.85, p<0.05) and needle litter C fluxes(r=0.88, p<0.05), but the rates were not correlated by the soil environmental factors(p>0.05) such as the mean annual soil temperature, soil water content, soil pH, and soil organic C content during the study period. The results indicate that it is important to understand the role of stand attributes in the mean annual soil respiration rates in a stand level.


초록


    Gyeongnam National University of Science and Technology

    Introduction

    The quantitative evaluation of soil respiration is a key process for understanding carbon (C) dynamics in forest ecosystems(Gough et al., 2004; Kim et al., 2009). Changes in soil respiration within a forest stand could be attributed to variations in stand and soil environmental factors. For example, soil respiration responded differently to changes in soil environmental factors such as nutrient availability, soil water content, and soil temperature(Raich & Tufekcioglu, 2000), and stand environmental factors such as tree density, litter fall production and litter decomposition(Søe & Buchmann 2005; Davisson & Janssens, 2006; Noh et al., 2010).

    Understanding of soil respiration following forest thinning practice(Laporte et al., 2003; Kim et al., 2009) is important because the different levels of basal area following the thinning practice can alter soil respiration processes with spatial and temporal variations of stand and soil environmental factors which is related to soil respiration in a stand level(Søe & Buchmann, 2005; Kim et al., 2009). In addition, a better understanding of the impacts on soil respiration can allow forest managers to select the most appropriate forest management strategies because the potential for temporary and long-term soil respiration may be affected by stand and soil environmental factors induced by tree removal such as thinning practices. However, experimental data in relation to various levels of basal areas following thinning practice are limited(Kim, 2016).

    The objective of this study was to determine the relationships between soil respiration rates and stand environmental factors(stem density, DBH, basal area, tree C storage and increment, litter fall C, litter decomposition) or soil environmental factors(soil temperature, soil water content, soil pH, soil organic C concentration) induced by various levels of basal area in a red pine.

    Materials and methods

    1.Study area

    This study was conducted in the Hwangmaesan mountain national forest(35° 29' N, 127° 57' E), which is located in Sancheong-gun, Gyeongsangnam-do and administered by the Hamyang National Forest Station, Korea Forest Service(Fig. 1). Mean annual precipitation and temperature over the past 30 years in the study area is 1,556 mm year-1 and 12.8°C, respectively. The study site consisted of an approximately 40-year-old natural red pine pure stand. The soil is a well-drained, slightly wet, brown forest soil originating from granite, with a loamy texture and a pH of 4.6-5.1. Dominant understory species in the study site included Carpinus laxiflora, Rhododendron mucronulatum, Lindera glauca, L. erythrocarpa, Lespedeza spp., and Quercus serrata etc.

    The study area was divided into six 20 m × 20 m plots at varying degrees of basal area under similar environmental conditions to minimize spatial variations in the soil properties in adjacent, natural red pine stands such that there was a small distance(< 20 m) between treatment plots(Fig. 1, Table 1). The difference in basal area was due to thinning practice conducted in 2005, which is the most common forest management practice in Korea(Kim et al., 2009). The mean tree density was ranged from 500 trees ha-1 to 1,525 trees ha-1 and the basal area was approximately ranged from 21.36 m2 ha-1 to 46.47 m2 ha-1, respectively(Table 1).

    2.Tree C and soil respiration measurements

    Tree biomass in each plot was estimated with allometric equations developed for aboveground tree component in this site(Kim et al., 2011), while the coarse root biomass was estimated for each measured tree by the basal area ratio method. Tree C storage values were then calculated, assuming a C concentration of 50% of the biomass(Power et al., 2012).

    Soil respiration rates were measured using an infrared gas analyzer system(Model EGM-4 environmental gas monitor systems, PP systems, Hitchin, UK) equipped with a flow-through closed soil respiration chamber (Model SRC-2, PP systems, Hitchin, UK). Five replicate measurements in each plot were performed monthly between 10:00 and 12:30 h for one year, from January to December, 2008. Soil temperature was measured at 20 cm depth adjacent to the soil respiration chamber using a soil temperature probe (Model STP-1, PP systems, Hitchin, UK) attached with EGM-4. In addition, adjacent to each chamber, five soil core samples were collected at 20 cm depth using an Oakfield sampler. The soil samples were placed in plastic bags, transported to a laboratory and dried in an oven for 48 h at 105°C to quantify the soil gravimetric water content. The organic C concentration of the soils was determined by the loss during combustion at 550°C for 4 h, while the soil pH(1:5 soil to water suspension) was determined by glass electrode.

    3.Litter fall and litter decomposition

    To measure litter fall at various levels of basal area, five circular litter traps with a surface area of 0.25 m2 were installed 60 cm above the forest floor at each plot. Litter was collected at monthly intervals between January and December, 2008. The litter from each trap was transported to a laboratory and then oven-dried at 65°C for 48 h. All dried samples were separated into needles, bark, cones, branches, and miscellaneous components, and each portion was then weighed. The litter samples were ground in a Wiley mill to pass through a 40-mesh(0.425 mm) stainless steel sieve. Carbon concentrations of the ground materials were determined using an elemental analyzer (CE Instruments EA1110, Thermo Quest Italia S.P.A. Italy). Needle litter decomposition at various levels of basal area was measured using the litterbag technique. Fresh needle litter from each treatment was collected from the forest floor during late November, 2007. After collection, the litter was air-dried at room temperature for 14 days, and a sample of approximately 10 g was weighed to the nearest 0.01 g and placed in 30 cm × 30 cm nylon net bag with a mesh size of 0.1 mm. Sub-samples from the litter were also taken to determine the oven-dried mass after heating at 65°C for 48 hours. Five litterbags for each treatment plot(a total of 30 bags) were randomly placed on the forest floor on December 10th, 2007 and collected from each plot after one year(on December 11th, 2008). After collection, each litterbag sample was oven-dried at 65°C for 48 h, weighed, and the rates of mass loss were determined. Nutrient of littter fall and litter decomposition in this study site was found elsewhere(Kim, 2016).

    4.Data analyses

    The data were analyzed to determine the treatment effects at a significance level of p<0.05 using the General Linear Models procedure in SAS(SAS institute 2003). Where statistical differences occurred, the treatment means were compared using Tukey's test. Correlation coefficient was used to measure associations between mean annual soil respiration rates and stand or soil environmental factors. Soil respiration data collected over a one-year period were used to test exponential relations between the soil respiration rates and soil temperature at various levels of the basal area. The Q10 values were calculated for soil respiration rates, given an increase of 10℃ in soil temperature.

    Results

    Monthly rates of soil respiration were not significantly affected(p>0.05) by various levels of basal area, but the rates during some months(April or November) were significantly higher in high basal area(42.1 or 46.7 m2 ha-1) stands than in low basal area(27.0 or 30.8 m2 ha-1) stands. Monthly soil respiration rates at various levels of basal area showed a clear monthly variation, which had a similar monthly pattern to soil temperature, regardless of the different levels of basal area(Fig. 2).

    The mean annual soil respiration rates were positively correlated(p<0.05) with the basal area, while the stand environmental factors(stem density, DBH, annual increment of basal area, needle litter decomposition) and soil environmental factors(mean annual soil temperature, mean annual soil pH, mean annual soil water content, mean annual soil organic C concentration) were not correlated(p>0.05) with the mean annual soil respiration rates(Fig. 3) except for roots, aboveground and total tree C storage, and needle litter C fluxes(Fig. 4). The exponential relationship that exists between soil respiration rates and soil temperature at a depth of 20 cm was statistically significant(R2=0.68-0.84, p<0.05) at all basal area treatments(Fig. 5). Q10 values in soil respiration rates were 6.49 in the highest basal area(46.7 m2 ha-1) stand and 4.05 in the lowest basal area(21.4 m2 ha-1) stand.

    Discussion

    Monthly rates of soil respiration were influenced by basal area treatments. For example, high soil respiration rates in the high basal area stands during some months could be associated with the difference of soil temperature(April: 46.7 m2 ha-1, 9.0℃; 27.0 m2 ha-1, 7.8℃) and soil pH(April: 42.1 m2 ha-1, pH 4.85; 30.8 m2 ha-1, pH 4.50). The soil respiration rates at various levels of basal area could be attributed to environmental conditions for microbial growth activity, soil organic matter decomposition, and root growth activity(Lee & Jose 2003; Davidson & Janssens, 2006) induced by the difference of soil temperature and soil pH. In addition, the mean annual soil respiration rates were significantly affected(p<0.05) by the parameters related to stand environmental variables. Similarly, soil respiration rates in a forest stand was most likely explained by variations to forest structure parameters, such as the DBH and basal area(Søe & Buchmann, 2005). However, there was no correlation between soil environmental factors and soil respiration rates due to high temporal and spatial variations in these factors(Kim et al., 2009).

    The mean annual soil respiration rates were higher in the high basal area(0.30 g CO2 m-2 h-1) stands than in the low basal area(0.27 g CO2 m-2 h-1) stands. The low soil respiration rates in the low basal area stands could be attributed to the decrease in autotrophic respiration rates due to the difference in live root biomass(Table 1) because soil environmental variables(soil temperature, soil water content, soil pH, and soil organic C concentration), which are regarded as the main factors influencing soil respiration, were not significantly correlated with the basal area(Fig. 2). Autotrophic respiration rates by living roots in the red pine stands of Korea accounted for approximately 38% of the total soil respiration(Kim et al., 2012). Additionally, the reduction in soil respiration rates in the low basal area stands could be due to a reduction of the litter fall C fluxes(Fig. 4, Table 1), which are a significant food source for microorganisms and contribute to the fine root respiration in the humus layer in forest ecosystems(Scheafer et al., 2009). Many researchers have found a significant relationship between soil respiration rates and litter fall C fluxes in coniferous forests(Davidson et al., 2002; Noh et al., 2010).

    An exponential regression has been widely used to describe the relationship between soil respiration rates and soil temperature in tree density treatments in forest stands(Litton et al., 2003; Noh et al., 2010). In this study, the exponential relationship between soil respiration rate and the corresponding soil temperature at a depth of 20 cm(Fig. 4) were significant(R2 = 0.68-0.84, p<0.05) at various levels of basal area. Soil temperature at various level of basal area explained the majority of the variance in soil respiration rates in a red pine stand because of the temperature dependency of microbial decay and root growth(Søe & Buchmann, 2005; Davidson & Janssens, 2006).

    Q10 values in soil respiration were independent by basal area treatments(Fig. 5), although the high Q10 values in the highest basal area stands could be due to increased root respiration. The variation of Q10 values in this pine stand could be attributed to different stand factors rather than soil environmental factors because no significant correlation on soil environmental factors was observed with increased basal area(Fig. 3). Q10 values of soil respiration rates in this study were higher than those of other red pine forests in Korea, which are 3.45-3.77 at 12 cm soil depth in red pine stands(Noh et al., 2010). The range of Q10 values may have partly resulted from the differences in the soil depth at which the temperature was measured. For example, the Q10 values increased from 1.9 to 3.5 with increasing soil depth in European beech, Norway spruce and Scots pine forests(Borken et al., 2002).

    In summary, the mean annual soil respiration rates showed high sensitivity to stand environmental variables, such as basal area, tree and root C storage, and needle litter C fluxes, but were not affected by soil environmental variables in the small plot based level. These results suggest that the mean annual soil respiration rates can be controlled by stand environmental variables induced by various levels of basal area in a red pine stand level.

    Acknowledgement

    This work was partially supported by a grant from the Gyeongnam National University of Science and Technology(2016).

    Figure

    JALS-50-45_F1.gif

    Location and basal area treatments(a: 21.4 m2 ha-1, b: 27.0 m2 ha-1, c: 30.8 m2 ha-1, d: 37.0 m2 ha-1, e: 42.1 m2 ha-1, f: 46.7 m2 ha-1) in a red pine stand of Hwangmaesan mountain forest in Sancheong-gun.

    JALS-50-45_F2.gif

    Monthly variation of soil respiration rates, soil temperature, soil water content, soil pH and soil organic carbon content at various levels of basal area(m2 ha-1) in a red pine stand. Vertical bars indicate standard errors. Different letters for each month denote significant differences at p<0.05. n.s.: non-significance.

    JALS-50-45_F3.gif

    Correlation between mean annual soil respiration rates or mean annual soil environmental factors and various levels of basal area in a red pine stand. Vertical bars indicate standard errors. *: p<0.05, n.s.: non-significance.

    JALS-50-45_F4.gif

    Correlation between mean annual soil respiration rates(soil CO2 efflux) and stand variables or mean annual soil environmental variables in a red pine stand. *: p<0.05, n.s.: non-significance.

    JALS-50-45_F5.gif

    Exponential regressions between soil respiration rates and soil temperature at various levels of basal area(BA) in a red pine stand.

    Table

    Stand attributes at various levels of basal area in a red pine stand

    *The values in parentheses are the basal area, DBH and C(Mg C ha-1 yr-1) increments for one year(Dec. 2007 - Dec. 2008).

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