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Spatial and temporal variation in soil respiration in a seasonally dry tropical forest, Thailand

Published online by Cambridge University Press:  01 September 2009

Minaco Adachi*
Affiliation:
Agro-Meteorology Division, National Institute for Agro-Environmental Science, 3-1-3 Kannondai, Tsukuba 305-8604, Japan
Atsushi Ishida
Affiliation:
Department of Plant Ecology, Forestry and Forest Products Research Institute, 1 Matsuno-sato, Tsukuba 305-8687, Japan
Sarayudh Bunyavejchewin
Affiliation:
Research Office, National Parks Wildlife and Plant Conservation Department, Chatuchak, Bangkok, 10900, Thailand
Toshinori Okuda
Affiliation:
Graduate School of Integrated Arts and Sciences, Hiroshima University, 1-7-1 Kagamiyama Higashi-Hiroshima, 739-8521, Japan
Hiroshi Koizumi
Affiliation:
River Basin Research Center, Gifu University, 1-1 Yanagido, Gifu 501-1193, Japan
*
1Corresponding author. Email: adachi.minaco@nies.go.jp
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Abstract:

Spatial and seasonal variation in soil respiration rates were investigated in a tropical dry forest in Thailand. The spatial variation was examined at 50 points within a 2-ha plot in the forest floor during the dry and wet seasons. The seasonal and diurnal variations in soil respiration were measured at 16 and 5 points, respectively. The mean soil respiration rate during the wet season was 1041 ± 542 mg CO2 m−2 h−1 (mean ± SD), which is about twice that during the dry season. Soil respiration rate was negatively correlated with soil water content during the wet season. A polynomial equation using seasonal data describes soil respiration and water content: soil respiration rate increased with soil water content, but started to drop when soil water content exceeded 21%. The diurnal variation in soil respiration rate during the wet season was positively correlated with soil temperature, whereas during the wet season it was not correlated with soil temperature. The diurnal variation in soil respiration rate during the dry season showed a midday depression. The estimation of soil carbon flux with polynomial equations should incorporate different functions for the wet and dry seasons in tropical dry forests.

Information

Type
Research Article
Copyright
Copyright © Cambridge University Press 2009
Figure 0

Figure 1. Climatic data at the Huai Kha Khaeng wildlife sanctuary, in a seasonally dry tropical forest, Thailand (original data are from Bunyavejchewin et al. 2004). Bars indicate total monthly rainfall (1992–1995); open and closed circles represent maximum and minimum diurnal air temperatures (1992–1994). Broken lines represent the monthly mean soil temperature at 5 cm (June 2003–September 2005).

Figure 1

Table 1. Descriptive statistics (mean ± SD) for soil respiration and soil environmental factors in a 2-ha plot. * differs significantly from the dry season at P < 0.0001.

Figure 2

Figure 2. Seasonal variation in soil temperature (solid line) at 5-cm depth, and soil water contents (broken line) in the small plot in a seasonally dry tropical forest, Thailand. Soil temperature and soil water content were measured by data loggers.

Figure 3

Figure 3. Relationship between soil respiration rates and soil temperature at 5-cm depth (a), soil water contents for the wet and dry seasons in the 2-ha plot (b) in a seasonally dry tropical forest, Thailand. Closed and open circles represent data for the wet and dry seasons, respectively. The line in (b) indicates a linear regression (r = −0.415, P = 0.0028) as determined by the single regression between soil respiration and soil water content in the wet season.

Figure 4

Figure 4. Diurnal variation in soil respiration rates and soil temperatures (1-cm depth) at the small plot during 2 d in the wet season (a, b), and in the dry season (c, d) in a seasonally dry tropical forest, Thailand. Soil respiration and soil temperatures are represented as closed and open circles, respectively. The error bar shows 1 SD (n = 5).

Figure 5

Table 2. Seasonal variation in soil respiration and soil environmental factors (mean ± SD) in the small plot (n = 16). Means followed by different letters within a row are significantly different (Scheffé's test, P < 0.05).

Figure 6

Figure 5. The relationship between the soil respiration rate and soil temperature at 5-cm depth (a) and soil water content (b) from seasonal variation in the small plot in a seasonally dry tropical forest, Thailand. Open and closed squares in (a) represent data obtained under the condition of low (below 21%) and high (above 21%) soil water content, respectively. The lines on the graph were regression equations at each relationship. Soil respiration = 0.498 exp(0.318 × soil temperature), R2 = 0.346, P = 0.0001 (a) and Soil respiration = −3.05(soil water content)2 + 131(soil water content) + 43.6, R2 = 0.531, P = 0.0001(b).

Figure 7

Table 3. Fitted semivariogram model parameters for soil respiration and environmental factors in wet and dry season, and elevation at each measuring point. NA means not applicable.