25 research outputs found

    暖温帯林の落葉層における水分の不均質性が落葉分解呼吸の時空間変動に与える影響

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    京都大学0048新制・課程博士博士(農学)甲第19032号農博第2110号新制||農||1031(附属図書館)学位論文||H27||N4914(農学部図書室)31983京都大学大学院農学研究科地域環境科学専攻(主査)教授 谷 誠, 教授 北山 兼弘, 教授 本田 与一学位規則第4条第1項該当Doctor of Agricultural ScienceKyoto UniversityDGA

    CO2 efflux from leaf litter focused on spatial and temporal heterogeneity of moisture

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    Leaf litter respiration (R [LL]) was directly measured in situ to evaluate relationships with the water content in leaf litter (WC), which is distributed heterogeneously under natural conditions. To do so, we developed a small, closed static chamber system using an infrared gas analyzer, which can measure instantaneous R [LL]. This study focuses on the measurement of CO2 effluxes from leaf litter using the chamber system in the field and examines the relationship between R [LL] and WC among seven broadleaf species in a temperate forest. The measurements focused on the position of leaves within the litter layer, finding that both R [LL] and WC were significantly higher in the lower layer. The value of R [LL] increased with increasing WC, and the response of R [LL] to WC was similar among all seven species. Moreover, the temporal variation in WC differed among three species and was associated with leaf litter thickness. The observed heterogeneity in WC induced by the physical environment (e.g., position and thickness of leaf litter) affects the variation in WC and, therefore, both R [LL] and the decomposition rates of organic matter in the litter layer

    One year of continuous measurements of soil CH4 and CO2 fluxes in a Japanese cypress forest: Temporal and spatial variations associated with Asian monsoon rainfall

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    We examined the effects of Asian monsoon rainfall on CH[4] absorption of water-unsaturated forest soil. We conducted a 1 year continuous measurement of soil CH[4] and CO[2] fluxes with automated chamber systems in three plots with different soil characteristics and water content to investigate how temporal variations in CH[4] fluxes vary with the soil environment. CH[4] absorption was reduced by the “Baiu” summer rainfall event and peaked during the subsequent hot, dry period. Although CH[4] absorption and CO[2] emission typically increased as soil temperature increased, the temperature dependence of CH[4] varied more than that of CO[2], possibly due to the changing balance of activities between methanotrophs and methanogens occurring over a wide temperature range, which was strongly affected by soil water content. In short time intervals (30 min), the responses of CH[4] and CO[2] fluxes to rainfall were different for each plot. In a dry soil plot with a thick humus layer, both fluxes decreased abruptly at the peak of rainfall intensity. After rainfall, CO[2] emission increased quickly, while CH[4] absorption increased gradually. Release of accumulated CO[2] underground and restriction and recovery of CH[4] and CO[2] exchange between soil and air determined flux responses to rainfall. In a wet soil plot and a dry soil plot with a thinner humus layer, abrupt decreases in CH[4]fluxes were not observed. Consequently, the Asian monsoon rainfall strongly influenced temporal variations in CH[4] fluxes, and the differences in flux responses to environmental factors among plots caused large variability in annual budgets of CH[4] fluxes

    COSORE: A community database for continuous soil respiration and other soil‐atmosphere greenhouse gas flux data

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    Globally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soil‐to‐atmosphere CO2 flux, commonly though imprecisely termed soil respiration (RS), is one of the largest carbon fluxes in the Earth system. An increasing number of high‐frequency RS measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, open‐source COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and long‐term GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured RS, the database design accommodates other soil‐atmosphere measurements (e.g. ecosystem respiration, chamber‐measured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package

    Using Capacitance Sensors for the Continuous Measurement of the Water Content in the Litter Layer of Forest Soil

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    Little is known about the wetting and drying processes of the litter layer (L layer), likely because of technical difficulties inherent in nondestructive water content (WC) monitoring. We developed a method for continuously measuring the WC of leaf litter (the “LWC method”) in situ using capacitance sensors. To test variants of this approach, five (for the LWC_5) or ten (for the LWC_10 method) Quercus serrata leaves were attached around capacitance sensors. The output voltage used for each LWC method was linearly correlated with the gravimetric WC (LWC_5: R2=0.940; LWC_10: R2=0.942), producing different slopes for each calibration line. For in situ continuous measurements of WC in the L layer, two sensors were used, one placed on top of the L layer and the other at the boundary between the L and mineral layers. The average continuous WC of the L layer was then calculated from the output voltage of the two sensors and the calibration function, and this value was linearly correlated with the gravimetric WC (R2=0.697). However, because the L layer characteristics (e.g., thickness, water-holding capacity, and species composition) may differ among study sites, appropriate approaches for measuring this layer’s moisture properties may be needed

    In situ CO2 efflux from leaf litter layer showed large temporal variation induced by rapid wetting and drying cycle.

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    We performed continuous and manual in situ measurements of CO2 efflux from the leaf litter layer (R(LL)) and water content of the leaf litter layer (LWC) in conjunction with measurements of soil respiration (RS) and soil water content (SWC) in a temperate forest; our objectives were to evaluate the response of R(LL) to rainfall events and to assess temporal variation in its contribution to R(S). We measured R(LL) in a treatment area from which all potential sources of CO2 except for the leaf litter layer were removed. Capacitance sensors were used to measure LWC. R(LL) increased immediately after wetting of the leaf litter layer; peak R(LL) values were observed during or one day after rainfall events and were up to 8.6-fold larger than R(LL) prior to rainfall. R(LL) declined to pre-wetting levels within 2-4 day after rainfall events and corresponded to decreasing LWC, indicating that annual R(LL) is strongly influenced by precipitation. Temporal variation in the observed contribution of R(LL) to RS varied from nearly zero to 51%. Continuous in situ measurements of LWC and CO2 efflux from leaf litter only, combined with measurements of RS, can provide robust data to clarify the response of R(LL) to rainfall events and its contribution to total R(S)

    CO[2] efflux from decomposing leaf litter stacks is influenced by the vertical distribution of leaf litter water content and its temporal variation

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    We evaluated the temporal changes in the vertical distribution of leaf litter respiration (RLL) due to changes of leaf lit- ter water content (WLL) within the leaf litter layer (L layer) using in situ direct measurements. To investigate the vertical distribution of RLL and WLL within the leaf litter layer over a time-series, we measured the RLL and WLL of 10 separate layers in vertical leaf litter stacks fixed to the forest floor using wire pins. Measurements were conducted for 30 stacks in a temperate broad-leaved secondary forest between May 2008 and January 2009. In the warm season, high RLL was ob- served at high WLL, while low RLL was observed at low WLL. RLL was comparatively lower during the cool season than during the warm season regardless of the magnitude of WLL. The temperature sensitivity of RLL differed depending on WLL; temperature increases under low-moisture conditions had small effects on RLL, while under higher-moisture condi- tions, RLL was more responsive to temperature increases. Small differences in position within the leaf litter stack affected the vertical variation of WLL and, consequently, there was large distribution in RLL during the wet period and small distri- bution in RLL (totally small values) during the dry period. Thus, CO2 efflux from the net L layer was strongly affected by RLL distribution induced by the local wetting within the L layer. In estimating CO2 efflux from the L layer using water content of the L layer, monitoring of the water content of the L layer, which takes into account the vertical distribution in WLL within the L layer, is necessary

    Relationship between observed and estimated CO<sub>2</sub> efflux rate from leaf litter respiration (<i>R</i><sub>LL</sub>) and soil respiration (<i>R</i><sub>S</sub>).

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    <p><i>R</i><sub>LL</sub> (A, B) and <i>R</i>s (C, D) show daily mean values. Estimated respiration rates were calculated using a function of temperature (A, C) from Eq. (5,6) and a function of temperature and water content (B, D) from Eq. (7,8) in the Results. Lines represent the 1∶1 ratio. RMSE: root mean square error.</p
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