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Palm oil accounts for about 40% of the global demand of vegetable oil. To meet the demand, oil palm plantations have expanded in the humid tropics at the expense of tropical forests. Land conversion begins with clear cutting and generates much woody debris, which was stacked in rows. Woody debris decomposes and emits carbon dioxide (CO2), but the time course of the decomposition is not well understood, especially at the early stage. Thus, we measured carbon (C) stock in woody debris in a newly established plantation after clear cutting of a secondary peat swamp forest in Sarawak, Malaysia. A litter bag method was applied to examine the decomposition of woody debris scattered on the ground. Also, we periodically measured apparent cross-sectional area (ACSA) of a stacking row (about 5 m wide and 90 m long) assuming that the cross-sectional form was triangular. The C stock of the stacking row was estimated from ACSA and measured C fractions using a significant sigmoidal relationship. The decomposition rate constants (k) for C content were determined to be 0.231-0.313 yr-1 for ground woody debris and 0.459 yr-1 for stacked woody debris. In addition, the total decomposition of the aboveground woody debris proceeded according to another k of 0.440 yr-1 during the experimental period of 740 days. The total C stock of aboveground woody debris was 48.4 Mg C ha-1 at the beginning of the field experiment, about 16 months after clear cutting. The C stock accounted for 63% of the C of forest aboveground biomass. Despite the uncertainty in the spatial representativeness, we think that simply measurable ACSA is useful to quantify the C stock of stacked woody debris. The technique could be applicable to large-area estimation using drone technology.

Emissions from biomass burning (BB) are a key source of atmospheric tracer gases that affect the atmospheric carbon cycle. We developed four sets of global BB emissions estimates (named GlcGlob, GlcGeoc, McdGlob, and McdGeoc) using a bottom-up approach and by combining the remote sensing products related to fire distribution with two aboveground biomass (AGB) and two land cover classification (LCC) distributions. The sensitivity of the estimates of BB emissions to the AGB and LCC data was evaluated using the carbon monoxide (CO) emissions associated with each BB estimate. Using the AGB and/or LCC data led to substantially different spatial estimates of CO emissions, with a large (factor of approximately 3) spread of estimates for the mean annual CO emissions: 526±53, 219±35, 624±57, and 293±44 Tg CO yr−1 for GlcGlob, GlcGeoc, McdGlob, and McdGeoc, respectively, and 415±47 Tg CO yr−1 for their ensemble average (EsmAve). We simulated atmospheric CO variability at an approximately 2.5∘ grid using an atmospheric tracer transport model and the BB emissions estimates and compared it with ground-based and satellite observations. At ground-based observation sites during fire seasons, the impact of intermittent fire events was poorly defined in our simulations due to the coarse resolution, which obscured temporal and spatial variability in the simulated atmospheric CO concentration. However, when compared at the regional and global scales, the distribution of atmospheric CO concentrations in the simulations shows substantial differences among the estimates of BB emissions. These results indicate that the estimates of BB emissions are highly sensitive to the AGB and LCC data.

In 2015, El Niño contributed to severe droughts in equatorial Asia (EA). The severe droughts enhanced fire activity in the dry season (June–November), leading to massive fire emissions of CO2 and aerosols. Based on large event attribution ensembles of the MIROC5 atmospheric global climate model, we suggest that historical anthropogenic warming increased the chances of meteorological droughts exceeding the 2015 observations in the EA area. We also investigate changes in drought in future climate simulations, in which prescribed sea surface temperature data have the same spatial patterns as the 2015 El Niño with long-term warming trends. Large probability increases of stronger droughts than the 2015 event are projected when events like the 2015 El Niño occur in the 1.5 and 2.0 ∘C warmed climate ensembles according to the Paris Agreement goals. Further drying is projected in the 3.0 ∘C ensemble according to the current mitigation policies of nations. We use observation-based empirical functions to estimate burned area, fire CO2 emissions and fine (

Global warming has become worse and worse as the increasing greenhouse gas (GHG) emissions especially by the main contributor carbon dioxide (CO2). Thus, clarifying the spatiotemporal patterns of CO2 emissions from residential sector is very important for policy makers. To support the GHG mitigation in local area, this study provides a bottom-up framework that could count the monthly residential CO2 emissions at community level, demonstrated for Japan. A map-based population census is utilized to count the monthly and yearly emissions by combining the statistics data on households with detailed emission intensities. The residential emissions from each census area are estimated and mapped by Geographic Information System. Through the analysis, we proposed the solutions on GHG mitigation and reported the spatiotemporal patterns for residential emissions.

The regional budget of methane (CH4) emissions for East Asia, a crucial region in the global greenhouse gas budget, was quantified for 1990–2015 with a bottom-up method based on inventories and emission model simulations. Anthropogenic emissions associated with fossil fuel extraction, industrial activities, waste management, and agricultural activities were derived from the Emission Database for Global Atmospheric Research version 4.3.2 and compared with other inventories. Emissions from natural wetlands and CH4 uptake by upland soil oxidation were estimated using the Vegetation Integrative SImulator for Trace gases (VISIT), a biogeochemical model that considers historical land use and climatic conditions. Emissions from biomass burning and termites were calculated using satellite and land-use data combined with empirical emission factors. The resulting average annual estimated CH4 budget for 2000–2012 indicated that East Asia was a net source of 67.3 Tg CH4 yr−1, of which 88.8% was associated with anthropogenic emissions. The uncertainty (±standard deviation) of this estimate, ±14 Tg CH4 yr−1, stemmed from data and model inconsistencies. The increase of the net flux from 60.2 Tg CH4 yr−1 in 1990 to 78.0 Tg CH4 yr−1 in 2012 was due mainly to increased emissions by the fossil fuel extraction and livestock sectors. Our results showed that CH4 was a crucial component of the regional greenhouse gas budget. A spatial analysis using 0.25° × 0.25° grid cells revealed emission hotspots in urban areas, agricultural areas, and wetlands. These hotspots were surrounded by weak sinks in upland areas. The estimated natural and anthropogenic emissions fell within the range of independent estimates, including top-down estimates from atmospheric inversion models. Such a regional accounting is an effective way to elucidate climatic forcings and to develop mitigation policies. Further studies, however, are required to reduce the uncertainties in the budget.

This study investigates the factors controlling the soil CO2 and CH4 fluxes and quantifies annual cumulative soil respiration (RS), heterotrophic respiration (RH), and soil CH4 emission in an undrained forest on tropical peat by continuous measurement using an automated chamber system for 2 years. Daily mean soil CO2 flux was increased by lowering groundwater level (GWL), which indicates oxidative peat decomposition is promoted by the enhancement of aeration. On the other hand, soil CH4 flux showed a bell-shaped relationship with GWL, which suggested that the development of anaerobic conditions promoted CH4 production by the rise in GWL, whereas hydrostatic pressure suppressed CH4 diffusion when the GWL was above the peat surface. Mean annual gap-filled CO2 emissions were 926 ± 610 and 891 ± 476 g C m−2 y−1 (mean ± 1 SD) for RS (n = 10) and RH (n = 6), respectively, and were not significantly different from each other. The annual RH in this study was similar to that of previous studies despite the higher annual mean GWL in this study, possibly due to the inclusion of litter decomposition in contrast to most of the previous studies in tropical peatland. Mean annual gap-filled CH4 emission was 4.32 ± 3.95 g C m−2 y−1 (n = 9), which was the high end of the previous studies in tropical peatland due to higher annual mean GWL in this study. In conclusion, RS was lower and CH4 emission was higher in the undrained peat swamp forest than those previously reported for drained and disturbed forests on tropical peat.

As the increasing concern for climate change, quantification on greenhouse gas (GHG) emissions in urban scale has been a key component for local climate actions. To explore an approach on estimating the GHG emissions closely to the real-world condition, in this paper, we make efforts on counting the carbon dioxide (CO2) emissions from road traffic in Tokyo. The road traffic emissions mapping is achieved by linking spatial road line data with detailed activity data (traffic census). Through the data processing by Geographic Information System technique, the emissions of each road segment are estimated basing on the daily average traffic amount and speed of vehicles on each road segment. As our estimation, the CO2 emissions from road traffic of Tokyo in 2015 are about 16,323 Gg. The highlight points mainly refer to linking the traffic census information for the observed road segments on map and allocation efforts for unserved ones. As the limited amount of observation points in traffic census, accurate estimation for unobserved road segments is a challenge. Our approach overcomes it by assumption of a familiar traffic condition for all road segments in the same sub-city area. This approach could simulate the traffic patterns closely to the real traffic condition so that it will more effectively support the emission mitigation policies on road traffic for local climate.

Background: The quantification of urban greenhouse gas (GHG) emissions is an important task in combating climate change. Emission inventories that include spatially explicit emission estimates facilitate the accurate tracking of emission changes, identification of emission sources, and formulation of policies for climate-change mitigation. Many currently available gridded emission estimates are based on the disaggregation of country- or state-wide emission estimates, which may be useful in describing city-wide emissions but are of limited value in tracking changes at subnational levels. Urban GHG emissions should therefore be quantified with a true bottom-up approach. Results: Multi-resolution, spatially explicit estimates of fossil-fuel carbon dioxide (FFCO2) emissions from the Tokyo Metropolis, Japan, were derived. Spatially explicit emission data were collected for point (e.g., power plants and waste incinerators), line (mostly traffic), and area (e.g., residential and commercial areas) sources. Emissions were mapped on the basis of emission rates calculated for source locations. Activity, emissions, and spatial data were integrated, and the results were visualized using a geographic information system approach. Conclusions: The annual total FFCO2 emissions from the Tokyo Metropolis in 2014 were 44,855 Gg CO2, with the road-transportation sector (16,323 Gg CO2) accounting for 36.4% of the total. Spatial emission patterns were verified via a comparison with the East Asian Air Pollutant Emission Grid Database for Japan (EAGrid-Japan), which demonstrated the applicability of this methodology to other prefectures and therefore the entire country.

Methane ( $$\mathrm {CH}_{4}$$ ) is known to be emitted from lakes to the atmosphere via processes such as diffusion and ebullition (i.e., bubble emission). We developed a practical method for partitioning eddy-covariance $$\mathrm {CH}_{4}$$ fluxes from a shallow lake into diffusive and ebullitive fluxes using a wavelet analysis based on local scalar similarity between the $$\mathrm {CH}_{4}$$ concentration and other reference scalars, such as the air temperature or water vapour concentration, in the wavelet time-scale domain, with the hypothesis that similar and dissimilar fluctuation components are related to diffusive and ebullitive $$\mathrm {CH}_{4}$$ fluxes, respectively. Our method is applied to approximately two weeks of data obtained at a shallow mid-latitude lake. The partitioned diffusive flux has a physically sound relationship with wind speed, supporting the validity of the method. The ratio of the diffusive flux to the total flux is typically 0.11 with flow from an area of steady bubble emission, but otherwise 0.36. Further validation is required using a larger dataset and data from other lakes. The proposed method can be easily applied to historical data because it requires only 10-Hz data of $$\mathrm {CH}_{4}$$ concentration and other reference scalars, along with an empirical parameter.

Tropical peat forests are a globally important reservoir of carbon, but little is known about CO2 exchange on an annual basis. We measured CO2 exchange between the atmosphere and tropical peat swamp forest in Sarawak, Malaysia using the eddy covariance technique over 4 years from 2011 to 2014. The CO2 fluxes varied between seasons and years. A small carbon uptake took place during the rainy season at the beginning of 2011, while a substantial net efflux of >600 g C/m2 occurred over a 2 month period in the middle of the dry season. Conversely, the peat ecosystem was a source of carbon during both the dry and rainy seasons in subsequent years and more carbon was lost during the rainy season relative to the dry season. Our results demonstrate that the forest was a net source of CO2 to the atmosphere during every year of measurement with annual efflux ranging from 183 to 632 g C m-2 year-1 , noting that annual flux values were sensitive to gap filling methodology. This is in contrast to the typical view of tropical peat forests which must have acted as net C sinks over time scales of centuries to millennia to create the peat deposits. Path analyses revealed that the gross primary productivity (GPP) and ecosystem respiration (RE) were primarily affected by vapour pressure deficit (VPD). Results suggest that future increases in VPD could further reduce the C sink strength and result in additional net CO2 losses from this tropical peat swamp forest in the absence of plant acclimation to such changes in atmospheric dryness.

Tropical peat swamp forest is a unique ecosystem, in which both swamp forest and peat soil have coexisted over millennia and accumulated a significant amount of soil carbon as peat. Owing to the huge soil carbon stock and high groundwater level (GWL), tropical peatlands potentially represent a significant source of methane (CH4) to the atmosphere. However, a few studies of CH4 flux by the soil chamber technique have reported that annual CH4 emissions from tropical peat swamp forest were very low as compared to mid- and high-latitude peatlands. Recently, it has been reported that some tree species growing in peat swamp forest emit CH4 from their stems. It is impossible to continuously measure ecosystem-scale CH4 flux including both soil and plant-mediated CH4 emissions by the chamber technique. Thus, we have measured net ecosystem CH4 exchange (FCH4) above a tropical peat swamp forest in Sarawak, Malaysia using the eddy covariance technique from February 2014 to July 2015 (18 months). The mean (±1 standard deviation) of half-hourly measured FCH4 was 24.0 ± 42.2 nmol m–2 s–1. Monthly mean FCH4 was always positive during the 18 months, even in the driest month with mean GWL of –30 cm. FCH4 was positively associated with GWL or soil moisture in a quadratic form. Annual FCH4 from March 2014 through February 2015 was 7.5–10.8 g C m–2 yr–1. The annual FCH4 was much higher than annual soil CH4 emissions from tropical peatlands, because the FCH4 included aboveground CH4 emissions mainly from tree stems. However, the annual FCH4 was relatively low in comparison with those measured by the eddy covariance technique in mid- and high-latitude peatlands.

Sarawak State Government and the Federal Government of Malaysia; National Science Foundation Division of Environmental Biology. Grant Number: 1552976

Soil carbon dioxide (CO₂) efflux was measured continuously for two years using an automated chamber system in an oil palm plantation on tropical peat. This study investigated the factors controlling the CO₂ efflux and quantified the annual cumulative CO₂ emissions through soil respiration and heterotrophic respiration, which is equivalent to oxidative peat decomposition. Soil respiration was measured in close-to-tree (< 2.5 m, CT) and far from-tree (> 3 m, FT) plots, and heterotrophic respiration was measured in root-cut (RC) plots by a trenching method. The daily mean CO2 efflux values (mean ±1 standard deviation) were 2.80±2.18, 1.59±1.18, and 1.94±1.581 μmol m⁻² s⁻¹ in the CT, FT, and RC plots, respectively. Daily mean CO₂ efflux increased exponentially as the groundwater level or water-filled pore space decreased, indicating that oxidative peat decomposition and gas diffusion in the soil increased due to enhanced aeration resulting from lower groundwater levels. Mean annual gap-filled CO₂ emissions were 1.03 ± 0.53, 0.59 ± 0.26, and 0.69 ± 0.21 kg C m⁻² yr⁻¹ in the CT, FT, and RC plots, respectively. Soil CO₂ emissions were significantly higher in the CT plots (P < 0.05), but did not differ significantly between the FT and RC plots. This implies that root respiration was negligible in the FT plots. Heterotrophic respiration accounted for 66% of soil respiration. Annual CO₂ emissions through both soil and heterotrophic respiration were smaller than those of other oil palm plantations on tropical peat, possibly due to the higher groundwater levels, land compaction, and continuous measurement of soil CO₂ efflux in this study. Mean annual total subsidence was 1.55 to 1.62 cm yr⁻¹, of which oxidative peat decomposition accounted for 72 to 74%. In conclusion, water management to raise groundwater levels would mitigate soil CO₂ emissions from oil palm plantations on tropical peatland.

Tropical peat swamp forest (PSF) has accumulated a huge amount of carbon as peat over millennia, though the carbon rich ecosystem is now threatened with disturbances due to land-use change to industrial plantations of oil palm and pulp woods. Through the land conversion, peat carbon has become vulnerable and potentially changes to a great carbon dioxide (CO2) source to the atmosphere. It is essential to quantify the CO2 balance of the ecosystem and understand how the CO2 balance responds to environmental changes to predict the role of PSF in global carbon cycles. However, filed studies based on the ecosystem-scale monitoring of CO2 flux are quite limited. Thus, we began CO2 flux monitoring over a secondary PSF in Sarawak, Malaysia, by the eddy covariance technique in 2010. Daily NEE and RE were significantly different between the dry and wet periods (p

Larch, a deciduous needle-leaf gymnosperm, is widely distributed in cool temperate and boreal forests of the Northern Hemisphere. Thus, evaluating evapotranspiration (ET) in larch forests is important to elucidate energy and water cycles on a global scale. In addition, severe forest disturbance is expected to change ET and energy balance through a drastic change in the canopy structure. However, knowledge related to the environmental functions of larch forests in cool temperate regions remains lacking compared with Siberian larch forests. Furthermore, few reports describe quantified changes in ET and energy balance before and after forest disturbance. Therefore, for more than a decade, we measured sensible and latent heat fluxes using the eddy covariance technique above a larch forest in northern Japan and its succeeding ex-forest after a stand-replacing disturbance caused by windthrow. In general, the larch forest’s ET was not limited by water in contrast to that of a Siberian larch forest. Although the aboveground biomass decreased by 97% through the disturbance, both cumulative ET and latent heat flux normalized by incident solar radiation (lE/Rg) during the snow-free period of about seven months were decreased by only 24% in the second year after disturbance. The 24% decrease was caused by 17% decrease in the partition of incident solar radiation to net radiation (Rg/Rn) and 9% decrease in the partition of net radiation to ET (lE/Rn). The former resulted from increased albedo and decreased net longwave radiation, and the latter was mainly due to decrease in surface conductance. According to the vegetation recovery of shrubs and herbaceous plants, cumulative ET during the snow-free period increased gradually and almost reached pre-disturbance levels in six years. However, normalized ET by solar radiation (lE/Rg) decreased in the 11th and 12th years after reaching the pre-disturbance level. Positive relationship between cumulative ET and vegetation indices indicates that the ET recovery was due to vegetation recovery.

In 2015, El Niño caused severe droughts in equatorial Asia (EA). The severe droughts enhanced fire activities in the dry seasons, leading to massive fire emissions of CO2 and aerosols. Using large event attribution ensembles of the MIROC5 atmospheric global climate model, we suggest that historical anthropogenic warming increased the chances of meteorological droughts exceeding the 2015 observations in the EA area. Large probability increases in stronger droughts than the 2015 event are found in the ensemble simulations of 1.5 °C and 2.0 °C global warming according to the Paris Agreement goals. Further drying is projected in the 3.0 °C ensemble. We combine these experiments and empirical functions between precipitation, burned area, and fire emissions of CO2 and PM2.5. Increases in the chances of the burned area and the emissions of CO2 and PM2.5 exceeding the 2015 observations due to anthropogenic climate change in the past are not significant. In contrast, there are significant increases in the burned area and CO2 and PM2.5 emissions even if the 1.5 °C and 2.0 °C goals are achieved. If global warming reaches 3.0 °C, as is expected from the current mitigation policies of nations, the chances of the burned area, CO2 and PM2.5 emissions exceeding the 2015 observed values become approximately 100 %, at least in the single model ensembles. We also compare changes in fire CO2 emissions due to climate changes and the land-use CO2 emission scenarios of five shared socio-economic pathways, where the climate change effects on fire are not considered. There are two main implications. First, in a national policy context, future EA climate policy will need to consider these climate change effects regarding both mitigation and adaptation aspects. Second, the consideration of fire increases would change global CO2 emissions and the mitigation strategy, which suggests that future climate change mitigation studies should take these factors into account.

Tropical rainforests control the exchange of water and energy between the land surface and the atmosphere near the equator and thus play an important role in the global climate system. Measurements of latent (LE) and sensible heat exchange (H) have not been synthesized across global tropical rainforests to date, which can help place observations from individual tropical forests in a global context. We measured LE and H for four years in a tropical peat forest ecosystem in Sarawak, Malaysian Borneo using eddy covariance, and hypothesize that the study ecosystem will exhibit less seasonal variability in turbulent fluxes than other tropical ecosystems as soil water is not expected to be limiting in a tropical forested wetland. LE and H show little variability across seasons in the study ecosystem, with LE values on the order of 11 MJ m−2 day and H on the order of 3 MJ m−2 day−1. Annual evapotranspiration (ET) did not differ among years and averaged 1579 ± 47 mm year−1. LE exceeded characteristic values from other tropical rainforest ecosystems in the FLUXNET2015 database with the exception of GF-Guy near coastal French Guyana, which averaged 8–11 MJ m−2 day−1. The Bowen ratio (Bo) in tropical rainforests in the FLUXNET2015 database either exhibited little seasonal trend, one seasonal peak, or two peaks. Volumetric water content (VWC) and VPD explained a trivial amount of the variability of LE and Bo in some of the tropical rainforests including the study ecosystem, but were strong controls in others, suggesting differences in stomatal regulation and/or the partitioning between evaporation and transpiration. Results demonstrate important differences in the seasonal patterns in water and energy exchange across different tropical rainforest ecosystems that need to be understood to quantify how ongoing changes in tropical rainforest extent will impact the global climate system.

We evaluated the long-term (52-year) effect of climate, disturbance, and subsequent recovery on the carbon balance of cool temperate forests by using the process-based ecosystem model VISIT. The study sites were artificial larch forests planted after clear-cutting of mixed forest in Hokkaido, Japan. The model was validated, scenarios were computed, and a sensitivity analysis was performed. First, we performed a baseline simulation of carbon dynamics and compared these values with those observed across a wide range of stand ages (old mixed forest and young and middle-aged larch forests). Second, we ran scenarios to investigate how disturbance and several climate factors affect long-term carbon fluxes. Third, we analyzed the sensitivity of carbon balance to the amount of disturbance-generated tree biomass residues. By taking into account seasonal variation in the understory leaf area index, which played an important role, especially in the initial stage of recovery, the simulated net ecosystem production (NEP), gross primary production, ecosystem respiration, and biomass for the three types of forest were consistent with observed values (mean ± SD of R2 of monthly NEP, GPP and RE for the three types of forest were 0.63 ± 0.26, 0.93 ± 0.07, 0.94 ± 0.2, respectively). The effect of disturbances such as clear-cutting, land-use conversion, and thinning on the long-term trend of NEP was larger than that of climate variation, even 50 years after clear-cutting. In contrast, interannual variation in the carbon balance was primarily driven by climate variation. These findings indicate that disturbance controlled the long-term trend of the carbon balance, whereas climate factors controlled yearly variation in the carbon balance. Among the meteorological factors considered, temperature and precipitation were the main ones that affected NEP and its interannual variation. The carbon balance in the initial post-disturbance period, which is strongly affected by the amount of residues, influenced the subsequent long-term carbon budget, implying the importance of residue management. Consequently, carbon release just after disturbance and the length of the recovery period required to balance the carbon budget are controlled by the amount of residues.

Oil palm plantations have been expanding in recent decades in Indonesia and Malaysia. Carbon-rich tropical peat swamp forest has not been excluded from this expansion, because it was the last frontier suitable for industrial agriculture and more accessible than other undeveloped areas. Carbon dioxide (CO2) emission through accelerated peat decomposition is one of the main environmental concerns in the conversion of peatlands into plantations, which undergo drainage to increase palm growth rates and production. Changes in aboveground biomass might also significantly alter the CO2 exchange dynamics of the ecosystem. Despite the potential changes in CO2 balance due to land conversion, so far no study has been conducted using the eddy covariance technique about the CO2 balance of oil palm plantations established on peat. We have monitored the eddy CO2 flux above an oil palm plantation on peat in Sarawak, Malaysia since 2011. During the period from 2011 to 2014 (four years), the plantation at 7–10 years of age was a large stable CO2 source with an annual net ecosystem CO2 exchange (NEE) of 994 ± 158 g C m−2 yr−1. The NEE was much more positive than that of a peat swamp forest (-136 ± 51 g C m−2 yr−1) in the same region during the same period. The large positive NEE was caused mainly by its relatively small gross primary production (GPP) (2529 ± 125 g C m−2 yr−1) due to low leaf area index resulting from high palm mortality. In addition, a large amount of plant debris left in the plantation probably contributed to the large NEE through decomposition, especially under the many canopy gaps due to high palm mortality mainly caused by toppling on poorly compacted peat. Adequate peat compaction is essential to reduce the mortality rate.

Wetlands in Southeast Asia are thought to be one of the greatest sources of methane (CH4) to the atmosphere. Tropical peatlands are typical in Southeast Asia, and store an enormous amount of soil organic carbon. However, chamber studies of soil CH4 flux have reported that CH4 emissions from tropical peatlands in Southeast Asia are almost negligible. Recently, it was reported that some tree species growing in peat swamp forests emit considerable CH4 from their stems. Thus, ecosystem-scale flux measurement is essential to quantify the CH4 balance of tropical peat ecosystems. In this 3-year study (February 2014 to January 2017), using the eddy covariance technique, we measured the net ecosystem exchange of CH4 (FCH4) above three different tropical peat ecosystems in Sarawak, Malaysia. The three sites were an undrained peat swamp forest (UF), a relatively disturbed secondary peat swamp forest (DF) and an oil palm plantation (OP). The weekly mean FCH4 was positively correlated to the groundwater level (GWL) in the UF and DF. In contrast, the FCH4 was independent of GWL in the OP, in which GWL was lowered by drainage. The monthly mean FCH4 was always positive, even in the drained OP. Mean annual CH4 emissions (± 1 SD) were 8.46 ± 0.51, 4.17 ± 0.69, and 2.19 ± 0.21 g C m–2 year–1 in the UF, DF, and OP, respectively. The inter-site differences in emissions were explained by a significant positive exponential relationship (P

Temporal and spatial variations in methane (CH4) emissions from the littoral zone of a shallow mid-latitude lake, Lake Suwa, were examined using the eddy covariance technique. The observation data were supplemented with dissolved CH4 measurement and incubation experiments of lake sediment and water. This lake had areas with steady bubble CH4 emissions, shaping the spatial variation in CH4 flux with strong spot emissions. In the other areas, CH4 was emitted via diffusion and episodic ebullition. CH4 emissions from this area had a clear seasonal variation, reflecting temperature variations, with a maximum monthly mean emission of 0.39 µ mol m − 2 s − 1 in August. The higher emission in summer was due to higher CH4 production in the sediment and the resulting higher dissolved CH4 concentration in the surface water. The steady bubble CH4 emission was seasonally controlled by the total hydrostatic pressure, with higher emission under lower pressure, suggesting regulation of the amount of bubbles emitted from the lake bottom by pressure. Isotope analysis revealed that this CH4 was produced biologically. This natural gas seepage was estimated to emit 1.9 Mg of CH4 annually. Compared with other eddy covariance studies over inland waters, CH4 emissions from Lake Suwa may be large for the latitude. This may be related to eutrophication, which enhances CH4 production.

Larch (Larix spp.) forests are predominantly distributed across high latitudes of Eurasia. They potentially have a strong influence on the terrestrial carbon and energy cycles, because of their vast area and the large carbon stocks in their peat soils in the permafrost. In this study, we elucidated intersite variation of ecosystem photosynthetic and respiratory parameters of eight larch forests in East Asia using the CarboEastAsia carbon flux and micrometeorology dataset. These parameters were determined using the empirical relationship between the carbon fluxes (photosynthesis and respiration) and micrometeorological variables (light and temperature). In addition, we examined leaf area index (LAI) determined by Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing data to explain the intersite variation. Linear or exponential relationships with annual mean temperature or seasonal maximum LAI at the study sites were found for the annual carbon fluxes (gross primary production [GPP] and total ecosystem respiration [RE]) as well as for four of the five seasonal maximum values of determined photosynthetic and respiratory parameters (maximum GPP at light saturation, initial slope of the light-response curve, daytime respiration, and RE at the reference temperature of 10 degrees C). Phenological indices, such as start day of the growing season, growing season length and growing season degree days explained much of the intersite variation of GPP and RE of the studied larch forests; however, the relationship between MODIS LAI and photosynthetic or respiratory parameters implies that the intersite variation in GPP and RE was caused not only by the temperature variation (abiotic factor), but also by the variation in the photosynthetic and respiration activity by vegetation (biotic factor) through the change in leaf (or whole vegetation) biomass. Our analysis shows that MODIS LAI serves as a good index to explain the variation of the ecosystem photosynthetic and respiratory characteristics of East Asian larch forests.

The datasets of net ecosystem CO2 exchange (NEE) were acquired from 21 forests, 3 grasslands, and 3 croplands in the eastern part of Asia based on the eddy covariance measurements of the international joint program, CarboEastAsia. The program was conducted by three networks in Asia, ChinaFLUX, JapanFlux, and KoFlux, to quantify, synthesize, and understand the carbon budget of the eastern part of Asia. An intercomparison was conducted for NEE estimated by three gap-filling procedures adopted by ChinaFLUX, JapanFlux, and KoFlux to test the range of uncertainty in the estimation of NEE. The overall comparison indicated good agreement among the procedures in the seasonal patterns of NEE, although a bias was observed in dormant seasons depending on the different criteria of data screening. Based on the gap-filled datasets, the magnitude and seasonality of the carbon budget were compared among various biome types, phenology, and stress conditions throughout Asia. The annual values of gross primary production and ecosystem respiration were almost proportional to the annual air temperature. Forest management, including clear-cutting, plantation, and artificial drainage, was significant and obviously affected the annual carbon uptake within the forests. Agricultural management resulted in notable seasonal patterns in the crop sites. The dataset obtained from a variety of biome types would be an essential source of knowledge for ecosystem science as well as a valuable validation dataset for modeling and remote sensing to upscale the carbon budget estimations in Asia.

The relaxed eddy accumulation (REA) method is an attractive alternative to the eddy covariance method to measure trace-gas flux, because it allows the use of analyzers with an optimal integration time to reduce the noise. However, the use of an empirical coefficient b results in uncertainties in the REA method. The consistency of b for temperature was investigated using a 1 year dataset obtained at three forest sites in East Asia: a temperate evergreen coniferous forest, a tropical evergreen broadleaf forest, and a cool-temperate deciduous coniferous forest. The observational b ranged from 0.54 to 0.57 under unstable conditions. Although the values for observational b were within narrow ranges among the sites, there were slight site-specific differences. We introduced new expression of b, similarity b, based on scalar similarity using the integral turbulence characteristics to investigate the nature of b. Both the observational and similarity b increased with increasing atmospheric stability under stable conditions, when lower values for the standard deviation of the vertical wind velocity resulted in higher values for b. The variations in b under stable conditions differed among sites. There were no seasonal variations in the observational b at all sites. Consequently, the present study recommends determining the coefficient b for unstable conditions for each site and considering changes in b associated with atmospheric stability in order to minimize errors in the REA method.

The process of confining unnecessary freedom is a step toward advanced ecosystem modeling. This study demonstrates the importance of carbon flux and biometric observation in constraining a terrestrial ecosystem model with a simple optimization scheme. At the selected sites from AsiaFlux network, a simultaneous optimization scheme for both carbon flux and biomass was compared with carbon flux-oriented and biomass-oriented optimization schemes using the Biome-BGC model. The optimization scheme oriented to either carbon flux or biomass provided simulation results that were consistent with observations, but with reduced performance in unconstrained variables. The simultaneous optimization scheme yielded results that were consistent with observations for both carbon flux and biomass. By comparing long-term projections simulated by three schemes, it was found that the optimization oriented only to carbon flux has limited performance because misrepresented biomass significantly affected a projection of carbon exchange through heterotrophic respiration. From these experiments, we found that (1) a process model like Biome-BGC is capable of reproducing both carbon flux and biomass within acceptable proximity, (2) constraining biomass is importance not just because it is one of carbon cycle components, but also it significantly affects simulations of carbon flux. Thus, it is important to invest more effort to improve simulation of biomass as well as carbon flux.

Gross primary productivity (GPP) is a major component of carbon exchange between the atmosphere and terrestrial ecosystems and a key component of the terrestrial carbon cycle. Because of the large spatial heterogeneity and temporal dynamics of ecosystems, it is a challenge to estimate GPP accurately at global or regional scales. The 8-day MODerate resolution Imaging Spectroradiometer (MODIS) GPP product provides a near real time estimate of global GPP. However, previous studies indicated that MODIS GPP has large uncertainties, partly caused by biases in parameterization and forcing data. In this study, MODIS GPP was validated using GPP derived from the eddy covariance flux measurements at five typical forest sites in East Asia. The validation indicated that MODIS GPP was seriously underestimated in these forest ecosystems of East Asia, especially at northern sites. With observed meteorological data, fraction of photosynthetically active radiation absorbed by the plant canopy (fPAR) calculated using smoothed MODIS leaf area index, and optimized maximum light use efficiency (e max) to force the MOD17 algorithm, the agreement between predicted GPP and tower-based GPP was significantly improved. The errors of MODIS GPP in these forest ecosystems of East Asia were mainly caused by uncertainties in e max, followed by those in fPAR and meteorological data. The separation of canopy into sunlit and shaded leaves, for which GPP is individually calculated, can improve GPP simulation significantly.

We summarize the current status of carbon and GHG budget estimates in tropical ecosystems at different spatial scales by using a process-based terrestrial ecosystem model. First, carbon balances of tropical peatland forest were simulated at the site scale. Second, we evaluated changes in carbon budgets of Borneo Island taking land-use changes into account. Third, we evaluated methane emissions from wetlands on a global scale.

Evapotranspiration (ET), the sum of evaporation from soil and transpiration from vegetation, is of vital importance in the hydrologic cycle and must be taken into consideration in assessments of the water resources of any region. The MODerate resolution Imaging Spectroradiometer (MODIS) sensor offers a promising opportunity for estimating daily ET with a 1 km spatial resolution, but is hampered by frequent cloud contamination or data gaps from other factors. In this study, 1) a stand-alone ET model was applied and tested during clear or partial cloudy sky conditions using MODIS-based inputs of land surface and atmospheric data and 2) meteorological simulations by using Four-Dimensional Data Assimilation (FDDA) system between MODIS and the 5th Generation Meso-scale Meteorological Model (MM5) was used in cloudy conditions to facilitate continuous daily ET estimates. The MODIS ET algorithm modified from Mu et al. (2007) is based on the Penman–Monteith equation and was applied to predict ET at flux measurement sites. This algorithm considers both the effects of surface energy partitioning processes and environmental constraints on ET. We devised gap-filling approaches for MODIS aerosol and albedo data that were identified as bottlenecks to determine retrieval rates of insolation and ET. MODIS-derived input variables (i.e., meteorological variables and radiation components) for estimating ET showed a good agreement with flux tower observations at each site. The retrieval rate of MODIS ET doubled at four flux measurement sites after gap-filling with negligible compensation was undertaken for accuracy. In spite of the high accuracy of MODIS-derived input variables, MODIS ET showed meaningful errors at the four flux measurement sites. These errors were mainly associated with errors in the estimated canopy conductance. During clear sky conditions, MODIS was used to calculate ET, while the MODIS-MM5 FDDA system provided input variables for the calculation of ET under cloudy sky conditions. The performance of the MODIS-MM5 FDDA system was evaluated by comparing ET based on MODIS, which showed a good agreement with the MODIS ET for various land cover types. Our results indicate that MODIS can be applied to monitor the land surface energy budget and ET with reasonable accuracy and that MODIS-MM5 FDDA has the potential to provide reasonable input data of ET estimation under cloudy conditions.

Aggregating and sharing the metadata of flux observation sites results in a strong collaboration among various fields of study. Such data sharing will also be a part of the future design of a tower flux observation network in Asia. The aim of this review is to comprehend the state of tower flux observation sites in Asia. There are 109 tower flux observation sites in Asia including 51 forest sites. There are more new sites under construction in Asia than in America and Europe. These sites range from the taiga in Siberia to the rainforest in Southeast Asia, and from the equatorial to polar Koeppen climate zones. There are many highly humid areas in Asia, not only at low latitudes but also at middle latitudes. This climate condition has developed unique vegetation such as lucidophyllous (evergreen broadleaf) forest, which is distributed in warm areas with high precipitation in the growing season. However, there are only a few observations taking place in lucidophyllous forest. Rice paddy fields are also unique land cover in Asia. It is important to accumulate long-term data for rice fields with their management records, because plant activity depends highly on both climate conditions and land-use management. Flux data, especially net ecosystem exchange and related elements, are used for widespread studies not only within the flux-research community but also in other fields of study, for example remote sensing. At present, however, both the quantity and quality of the data are not sufficient for these studies. Regarding the quantity, there are many recently established sites that have not published data yet; regarding quality, flux data include uncertainties caused by methodological problems. Flux researchers are required not only to obtain flux data but also to improve their quality. Meanwhile, data users must understand there are still uncertainties in flux data.

Measurements of net ecosystem production (NEP) over forest stands were conducted from 11 flux towers in sub-arctic, temperate, and tropical regions in East Asia between 2000 and 2005. The sites extend over a wide latitude, ranging from 3 to 64 degrees N, and include sub-arctic and temperate needle-leaf deciduous forests (larch) (central Siberia, Mongolia, China, and northern Japan), temperate mixed, broadleaf deciduous, needle-leaf evergreen forests (northern and central japan), and seasonal and tropical rain forests (Thailand and Malaysia). The sub-arctic larch forests had short growing periods of 3-4 months. The temperate deciduous forests showed the greatest positive NEP after leaf expansion in early summer. Among the 11 sites, the maximum gross primary production (GPP) was observed in a temperate larch forest during the early stages of the growing period due to the high productivity of the larch species. The temperate evergreen sites displayed positive NEP earlier in the spring than the deciduous sites and had long growing periods (>10 months). The tropical seasonal forests showed negative NEP during the dry period from February to April, and turned positive after the rainy season started. The tropical rain forest showed a small flux (

The objective of this paper is to clarify what kind of environmental factors that regulate net ecosystem production (NEP), gross primary production (GPP), and ecosystem respiration (RE) in forest ecosystems across East Asia. Study sites were widely distributed and included diverse ecosystems, such as evergreen and deciduous, coniferous and broadleaf, planted and natural forests, from subarctic to tropical zones. We measured NEP using the eddy covariance technique at 13 forest sites in East Asia. Annual values of GPP and RE are simply regulated by annual mean air temperature across East Asia. There is a clear linear relationship between annual GPP and annual mean air temperature because the air temperature influences both growing period length and the seasonal variation of the maximum photosynthetic capacity, which, together, regulate the annual GPP. On the other hand, there is a strong exponential relationship between annual RE and annual mean air temperature on an East Asia scale, which is quite similar to the relation obtained on a canopy scale. The dependency of annual RE on air temperature on the East Asia scale was similar to that of monthly RE on air temperature on an individual site scale excepting for temperate larch and mixed forests in northern Japan. The reason why the relation is simple is that severe stress, which affects GPP or RE, is small in East Asia. The present study suggests that RE is sensitive to non-climate environmental factors when compared to GPP, thus the annual RE-air temperature relationship is more scattered than the annual GPP-air temperature relationship. The NEP is small at high latitude, relatively large at mid-latitude, and scattered at low latitude. As a whole, the NEP is more influenced by RE than GPP in East Asia. Compared to North America and Europe, the increase in the ratio of GPP to air temperature is slightly higher in East Asia. One of the possible reasons for this is that GPP in East Asia is not exposed to severe environmental stresses, such as summer drought.

This paper reports 3-year measurements (2001–2003) of the net ecosystem CO2 exchange (NEE) over a northern Japan larch plantation forest, using an eddy covariance technique with both open- and closed-path systems. The study evaluates interannual variations in the seasonal patterns of NEE, the annual NEE, clarifying the factors controlling the carbon balance. NEE for both open- and closed-path systems look equivalent from the half-hourly mean values; however, there is a small systematic bias in the annual cumulative totals. In this study, we used closed-path data because open-path data during winter are doubtful and the annual NEE from closed-path data was closer to the biometric NEP than that from open-path data. The 3-year averages of annual NEE, gross primary production (GPP), and ecosystem respiration (RE) were −212 ± 43 (standard deviation), −1673 ± 59, and 1462 ± 42 gC m−2 y−1, respectively. The larch plantation forest absorbed large amounts of CO2 during just 1 month, June. During that period, photosynthetic photon flux density (PPFD) was large while the temperature was not high. These meteorological conditions were suitable for CO2 absorption before the leaf area index (LAI) reached its peak. Maximum GPP at light saturation (Pmax) was also large. During the 3-year measurement period, PPFD in summer, and temperatures in spring and summer engendered remarkable interannual differences of GPP, RE, and NEE. In spring, snowmelt and larch foliation occurred about 2 weeks earlier in 2002 than in either 2001 or 2003 because of higher temperatures; consequently, the ecosystem began to photosynthesize earlier. In July, NEE was more negative in 2003 than in other years. The GPP became larger because of higher PPFD, larger Pmax; while the RE became smaller because of lower temperatures. Compared with similar forests, the amounts of GPP and RE measured here were large, but NEE was similar. The reason is that the photosynthetic capacity of larch is naturally large: the ample PPFD, and the lack of environmental stresses from dry air or soil, consequently allows high photosynthesis rates to be maintained. Moreover, it can be inferred that RE values are enhanced by the high photosynthetic activity of larch forest during the growing season.

Since both open- and closed-path eddy covariance techniques have been used in ecosystem observation networks such as AsiaFlux, estimating the random and systematic differences in CO2 fluxes observed by the two techniques is important. In the present study, CO2 fluxes measured by open- and closed-path eddy covariance systems were compared using year-round data obtained in a single-cropping rice paddy and in a larch forest. The two sites were similar in eddy covariance instrumentation and data processing, but dissimilar in canopy height and structure, phenology, and climate. For both sites, differences in half-hourly CO2 fluxes measured by the open- and closed-path systems followed a Laplace distribution, but were significantly biased, resulting in the open-path system measuring lower values than the closed-path system and in a larger carbon sequestration by vegetation being estimated with the open-path system. The systematic difference between the two systems mainly arose from an inconsistency between the open-path CO2 flux and the WPL correction for the effect of air density fluctuations, and increased with the magnitude of the WPL correction. During the growing season, the systematic difference at the paddy site was consistently smaller than that at the larch site because of the much low Bowen ratio and the resulting small WPL correction term caused by standing water in the paddy field. The WPL correction term was large and thus, the systematic difference became apparent in late winter because of the high Bowen ratios at the paddy and larch site, each covered with dried soil and snowpack, respectively. The year-round, half-hourly data accumulated after quality control tests showed that, between the two systems, relative differences existed of 9.9% (N=6074) for the paddy site and 15.8% (N=4591) for the larch site.