Estimation of spatio-temporal distribution of 137Cs concentrations in litter layer of forest ecosystems in Fukushima using FoRothCs model.

The nuclear power plant accident in Fukushima had led to pollution of forest ecosystems with 137Cs in 2011. In this study, we simulated the spatiotemporal distribution of 137Cs concentrations of litter layer in the contaminated forest ecosystems in two decades from 2011, which is one of the key environmental components of 137Cs migration in the environment due to the high bioavailability of 137Cs in the litter. Our simulations showed that 137Cs deposition is the most important factor in the degree of contamination of the litter layer but vegetation type (evergreen coniferous/deciduous broadleaf) and mean annual temperature are also important for changes over time. Deciduous broadleaf trees had higher initial concentrations in the litter layer due to the direct initial deposition on the forest floor. However, the concentrations remained higher than those in evergreen conifers after 10 years due to redistribution of 137Cs by vegetation. Moreover, areas with lower average annual temperatures and lower litter decomposition activity retained higher 137Cs concentrations in the litter layer. The results of the spatiotemporal distribution estimation of the radioecological model suggest that, in addition to 137Cs deposition, elevation and vegetation distribution should also be considered in the long-term management of contaminated watersheds, which can be informative in identifying hotspots of 137Cs contamination on a long-term scale.

Dissolved N2O concentrations in oil palm plantation drainage in a peat swamp of Malaysia.

Oil palm plantations in Southeast Asia are the largest supplier of palm oil products and have been rapidly expanding in the last three decades even in peat-swamp areas. Oil palm plantations on peat ecosystems have a unique water management system that lowers the water table and, thus, may yield indirect N2O emissions from the peat drainage system. We conducted two seasons of spatial monitoring for the dissolved N2O concentrations in the drainage and adjacent rivers of palm oil plantations on peat swamps in Sarawak, Malaysia, to evaluate the magnitude of indirect N2O emissions from this ecosystem. In both the dry and wet seasons, the mean and median dissolved N2O concentrations exhibited over-saturation in the drainage water, i.e., the oil palm plantation drainage may be a source of N2O to the atmosphere. In the wet season, the spatial distribution of dissolved N2O showed bimodal peaks in both the unsaturated and over-saturated concentrations. The bulk δ15N of dissolved N2O was higher than the source of inorganic N in the oil palm plantation (i.e., N fertilizer and soil organic nitrogen) during both seasons. An isotopocule analysis of the dissolved N2O suggested that denitrification was a major source of N2O, followed by N2O reduction processes that occurred in the drainage water. The δ15N and site preference mapping analysis in dissolved N2O revealed that a significant proportion of the N2O produced in peat and drainage is reduced to N2 before being released into the atmosphere.

N2O emission factors for organic amendments in Japan from measurement campaign and systematic review.

Organic amendments are important sources of nitrous oxide (N2O) emissions from agricultural soils. In 2020, the total amount of N in organic amendments applied to Japanese agricultural soils (440 ktN) was larger than that of synthetic fertilizer (374 ktN). However, N2O emissions from organic amendments were estimated by using the country-specific N2O emission factor (EF) for synthetic fertilizer (0.31 % for rice paddy, 2.9 % for tea, and 0.62 % for other crops) in the National Greenhouse Gas Inventory Report of Japan. Thus, we conducted a N2O flux measurement campaign at 12 different experimental sites across Japan to estimate fertilizer-induced N2O EFs for major organic amendments in Japan, that is, poultry manure compost, swine manure compost, cattle manure compost, and organic fertilizer pellets. In addition, we conducted systematic review of N2O emissions and EFs for organic amendments, including data from our measurement campaign and published data from peer-reviewed papers in Japan. The final dataset, including the field measurement campaign and published data, resulted in 404 observations (including synthetic fertilizer and zero-N control) in 29 sites. Results showed that soil type affected EFs, that is, the mean EF of Andosols was lower than that of non-Andosols, which is similar to the case of EFs for synthetic fertilizer. Mean EFs for poultry manure compost, swine manure compost, cattle manure (compost and slurry), and non-animal manure organic fertilizers were 0.83 % (uncertainty range of 2.5th and 97.5th percentile: 0.09 % to 3.46 %), 0.70 % (0.02 % to 2.45 %), 0.39 % (0.00 % to 1.62 %), and 1.16 % (0.41 % to 3.03 %), respectively, when weighted by area of soil types. The mean EF of all organic amendments was 0.84 % (0.00 % to 2.91 %), when the area of soil type and amount of organic amendment used in Japan were considered. Our study provides country-specific EFs to estimate N2O emission from organic amendments in Japan.

Dynamics of radiocaesium within forests in Fukushima-results and analysis of a model inter-comparison.

Forests cover approximately 70% of the area contaminated by the Fukushima Daiichi Nuclear Power Plant accident in 2011. Following this severe contamination event, radiocaesium (137Cs) is anticipated to circulate within these forest ecosystems for several decades. Since the accident, a number of models have been constructed to evaluate the past and future dynamics of 137Cs in these forests. To explore the performance and uncertainties of these models we conducted a model inter-comparison exercise using Fukushima data. The main scenario addressed an evergreen needleleaf forest (cedar/cypress), which is the most common and commercially important forest type in Japan. We also tested the models with two forest management scenarios (decontamination by removal of soil surface litter and forest regeneration) and, furthermore, a deciduous broadleaf forest (konara oak) scenario as a preliminary modelling study of this type of forest. After appropriate calibration, the models reproduced the observed data reliably and the ranges of calculated trajectories were narrow in the early phase after the fallout. Successful model performances in the early phase were probably attributable to the availability of comprehensive data characterizing radiocaesium partitioning in the early phase. However, the envelope of the calculated model end points enlarged in long-term simulations over 50 years after the fallout. It is essential to continue repetitive verification/validation processes using decadal data for various forest types to improve the models and to update the forecasting capacity of the models.

Nitrogen budgets in Japan from 2000 to 2015: Decreasing trend of nitrogen loss to the environment and the challenge to further reduce nitrogen waste.

The benefits of the artificial fixation of reactive nitrogen (Nr, nitrogen [N] compounds other than dinitrogen), in the form of N fertilizers and materials are huge, while at the same time posing substantial threats to human and ecosystem health by the release of Nr to the environment. To achieve sustainable N use, Nr loss to the environment must be reduced. An N-budget approach at the national level would allow us to fully grasp the whole picture of Nr loss to the environment through the quantification of important N flows in the country. In this study, the N budgets in Japan were estimated from 2000 to 2015 using available statistics, datasets, and literature. The net N inflow to Japanese human sectors in 2010 was 6180 Gg N yr-1 in total. With 420 Gg N yr-1 accumulating in human settlements, 5760 Gg N yr-1 was released from the human sector, of which 1960 Gg N yr-1 was lost to the environment as Nr (64% to air and 36% to waters), and the remainder assumed as dinitrogen. Nr loss decreased in both atmospheric emissions and loss to terrestrial water over time. The distinct reduction in the atmospheric emissions of nitrogen oxides from transportation, at -4.3% yr-1, was attributed to both emission controls and a decrease in energy consumption. Reductions in runoff and leaching from land as well as the discharge of treated water were found, at -1.0% yr-1 for both. The aging of Japan's population coincided with the reductions in the per capita supply and consumption of food and energy. Future challenges for Japan lie in further reducing N waste and adapting its N flows in international trade to adopt more sustainable options considering the reduced demand due to the aging population.

Tree manipulation experiment for the short-term effect of tree cutting on N2O emission: A evaluation using Bayesian hierarchical modeling.

Considerable uncertainty exists with regard to the effects of thinning and harvesting on N2O emissions as a result of changes caused in the belowground environment by tree cutting. To evaluate on the effects of changes in the belowground environment on N2O emissions from soils, we conducted a tree manipulation experiment in a Japanese cedar (Cryptomeria japonica) stand without soil compaction or slash falling near measurement chambers and measured N2O emission at distances of 50 and 150 cm from the tree stem (stump) before and after cutting. In addition, we inferred the effects of logging on the emission using a hierarchical Bayesian (HB) model. Our results showed that tree cutting stimulated N2O emission from soil and that the increase in N2O emission depended on the distance from the stem (stump); increase in N2O emission was greater at 50 than at 150 cm from the stem. Tree cutting caused the estimated N2O emission at 0-40 cm from the stem to double (the % increase in N2O emission by tree cutting was 54%-213%, 95% predictive credible interval) when soil temperature was 25 °C and WFPS was 60%. Posterior simulation of the HB model predicted that 30% logging would cause a 57% (47%-67%) increase in N2O emission at our study site (2000 trees ha-1) considering only the effects of belowground changes by tree cutting during the measurement period.

Quantification of global and national nitrogen budgets for crop production.

Input-output estimates of nitrogen on cropland are essential for improving nitrogen management and better understanding the global nitrogen cycle. Here, we compare 13 nitrogen budget datasets covering 115 countries and regions over 1961-2015. Although most datasets showed similar spatiotemporal patterns, some annual estimates varied widely among them, resulting in large ranges and uncertainty. In 2010, global medians (in TgN yr-1) and associated minimum-maximum ranges were 73 (64-84) for global harvested crop nitrogen; 161 (139-192) for total nitrogen inputs; 86 (68-97) for nitrogen surplus; and 46% (40-53%) for nitrogen use efficiency. Some of the most uncertain nitrogen budget terms by country showed ranges as large as their medians, revealing areas for improvement. A benchmark nitrogen budget dataset, derived from central tendencies of the original datasets, can be used in model comparisons and inform sustainable nitrogen management in food systems.

Influence of δ18 O of water on measurements of δ18 O of nitrite and nitrate.

RATIONALE: Oxygen isotope ratio measurements of NO2 - and NO3 - by the azide method and denitrifier method are sensitive to the δ18 O value of the sample water. However, the influence of δ18 OH2O on those measurements has not been quantitatively evaluated and documented so far. Therefore, we investigated the influence of δ18 OH2O of a sample on the δ18 O analysis of NO2 - and NO3 - . METHODS: We prepared NO2 - and NO3 - standards (with known δ18 ONO2- and δ18 ONO3- values) dissolved in waters having different δ18 OH2O values (δ18 OH2O = -12.6, 25.9, 56.7, and 110.1‰). Nitrite and nitrate were converted into N2 O using the azide method and the denitrifier method, respectively. The isotope ratios of the generated N2 O were measured with a Sercon purge-and-trap gas chromatography/isotope ratio mass spectrometry (PT-GC/IRMS) system. The measured δ18 O values of the produced N2 O were plotted against known δ18 ONO2- and δ18 ONO3- values to evaluate the influence of exchange of an oxygen atom with H2 O during the conversion of NO2 - into N2 O and NO3 - into N2 O, respectively. RESULTS: The degree of oxygen isotope exchange was 10.8 ± 0.3% in the azide method and 5.5 ± 1.0% in the denitrifier method, indicating that the azide method is more susceptible to artifacts arising from differences in the δ18 OH2O value of water than the denitrifier method. Thus, the intercept of the standard calibration curve must be corrected to account for differences in δ18 OH2O . Abiotic NO2 -H2 O equilibrium isotope effect experiments yielded a rate constant of (1.13 ± 007) × 10-2 (h-1 ) and an equilibrium isotope effect of 11.9 ± 0.1‰ under the condition of pH = 7.5, 30°C, and 2.5% salinity. CONCLUSIONS: Oxygen isotope ratio measurements of NO2 - by the azide method are highly sensitive to δ18 OH2O as a result of significant oxygen isotope exchange between NO2 - and H2 O. Therefore, to obtain the most accurate measurements water with the same δ18 OH2O value as that of the sample must be used to make the NO2 - and NO3 - standards.

A dataset of 137Cs activity concentration and inventory in forests contaminated by the Fukushima accident.

The majority of the area contaminated by the Fukushima Daiichi Nuclear Power Plant accident is covered with forests. We developed a dataset for radiocaesium (137Cs) in trees, soil, and mushrooms measured at numerous forest sites. The 137Cs activity concentration and inventory data reported in scientific journal papers written in English and Japanese, governmental reports, and governmental monitoring data on the web were collated. The ancillary information describing the forest stands were also collated, and further environmental information (e.g. climate) was derived from the other databases using longitude and latitude coordinates of the sampling locations. The database contains 8593, 4105, and 3189 entries of activity concentration data for trees, soil, and mushrooms, and 471 and 3521 entries of inventory data for trees and soil, respectively, which were collected from 2011 to 2017, and covers the entire Fukushima prefecture. The data can be used to document and understand the spatio-temporal dynamics of radiocaesium in the affected region and to aid the development and validation of models of radiocaesium dynamics in contaminated forests.

Nitrogen and Oxygen Isotope Signatures of Nitrogen Compounds during Anammox in the Laboratory and a Wastewater Treatment Plant.

Isotopic fractionation factors against 15N and 18O during anammox (anaerobic ammonia oxidization by nitrite) are critical for evaluating the importance of this process in natural environments. We performed batch incubation experiments with an anammox-dominated biomass to investigate nitrogen (N) and oxygen (O) isotopic fractionation factors during anammox and also examined apparent isotope fractionation factors during anammox in an actual wastewater treatment plant. We conducted one incubation experiment with high δ18O of water to investigate the effects of water δ18O. The N isotopic fractionation factors estimated from incubation experiments and the wastewater treatment plant were similar to previous values. We also found that the N isotopic effect (15εNXR of -77.8 to -65.9‰ and 15ΔNXR of -31.3 to -30.4‰) and possibly O isotopic effect (18εNXR of -20.6‰) for anaerobic nitrite oxidation to nitrate were inverse. We applied the estimated isotopic fractionation factors to the ordinary differential equation model to clarify whether anammox induces deviations in the δ18O vs δ15N of nitrate from a linear trajectory of 1, similar to heterotrophic denitrification. Although this deviation has been attributed to nitrite oxidation, the O isotopic fractionation factor for anammox is crucial for obtaining a more detailed understanding of the mechanisms controlling this deviation. In our model, anammox induced the trajectory of the δ18O vs δ15N of nitrate during denitrification to less than one, which strongly indicates that this deviation is evidence of nitrite oxidation by anammox under denitrifying conditions.

New predictions of 137Cs dynamics in forests after the Fukushima nuclear accident.

Most of the area contaminated by the Fukushima Daiichi Nuclear Power Plant accident is covered by forest. In this paper, we updated model predictions of temporal changes in the 137Cs dynamics using the latest observation data and newly provided maps of the predicted 137Cs activity concentration for wood, which is the most commercially important part of the tree body. Overall, the previous prediction and latest observation data were in very good agreement. However, further validation revealed that the migration from the soil surface organic layer to the mineral soil was overestimated for evergreen needleleaf forests. The new prediction of the 137Cs inventory showed that although the 137Cs distribution within forests differed among forest types in the first 5 years, the difference diminished in the later phase. Besides, the prediction of the wood 137Cs activity concentrations reproduced the different trends of the 137Cs activity concentrations for cedar, oak, and pine trees. Our simulation suggests that the changes of the wood 137Cs activity concentration over time will slow down after 5-10 years. Although the model uncertainty should be considered and monitoring and model updating must continue, the study provides helpful information on the 137Cs dynamics within forest ecosystems and the changes in wood contamination.

Extensive analysis of radiocesium concentrations in wild mushrooms in eastern Japan affected by the Fukushima nuclear accident: Use of open accessible monitoring data.

After the Fukushima Daiichi Nuclear Power Plant accident, there has been an increasing concern regarding the contamination of wild mushrooms with radiocesium (134Cs and 137Cs) in eastern Japan. In this study, we analyzed the radioactivity monitoring data of 3189 wild edible mushrooms of 107 species collected by the 265 local municipalities in eastern Japan to investigate the radiocesium levels in wild mushrooms. Results of the analysis showed that radiocesium concentrations in mushrooms were normalized with radioactivity deposition data from aircraft monitoring, and then we evaluated the effects of species, sampled location, sampling year and regional deviation between 134Cs and 137Cs activity of specimens using a hierarchical Bayesian approach considering spatial autocorrelation (an intrinsic CAR model). Normalized activity concentration by species ranged from 1.1×10-4 to 2.3×10-2 (m2 kg-1, fresh weight). As reported in previous studies, the mycorrhizal species tended to have higher radiocesium concentrations. Some saprophytic species (e.g. Pholiota lubrica) also had high concentrations. For the mushroom species that were also evaluated in the post-Chernobyl studies, we found that the same species had similar trends of absorption capacities. Our results indicate the extensive analysis of public monitoring data is helpful to understand the situation of mushroom contamination and evaluate the internal dose by ingestion of wild mushrooms according to species and areas.

Calibration of forest 137Cs cycling model "FoRothCs" via approximate Bayesian computation based on 6-year observations from plantation forests in Fukushima.

Predicting the environmental fate of 137Cs in forest ecosystems along with the concentrations of 137Cs in tree parts are important for the managements of radioactively contaminated forests. In this study, we calibrate the Forest RothC and Cs model (FoRothCs), a forest ecosystem 137Cs dynamics model, using observational data obtained over six years from four forest sites with different levels of 137Cs contamination from Fukushima Prefecture. To this end, we applied an approximate Bayesian computation (ABC) technique based on the observed 137Cs concentrations (Bq kg-1) of five compartments (leaf, branch, stem, litter, and soil) in a Japanese cedar plantation. The environmental decay (increment) constants of the five compartments were used as the summary statistics (i.e., the metric for model performance) to infer the five parameters related to 137Cs transfer processes in FoRothCs. The ABC technique successfully reconciled the model outputs with the observed trends in 137Cs concentrations at all sites during the study period. Furthermore, the estimated parameters are in agreement with the literature values (e.g., the root uptake rates of 137Cs). Our study demonstrates that model calibration with ABC based on the trends in 137Cs concentrations of multi compartments is useful for reducing the prediction uncertainty of 137Cs dynamics in forest ecosystems.

Varying sensitivity of mountainous streamwater base-flow [Formula: see text]concentrations to N deposition in the northern suburbs of Tokyo.

Ecosystems of suburban landscapes (i.e., forest, inland water ecosystem) are threatened by high nitrogen (N) loadings derived from urban air pollutants. Forest ecosystems under high chronic N loadings tend to leach more N via streams. In the northern suburbs of Tokyo, N deposition loading on terrestrial ecosystems has increased over the past 30 years. In this region, we investigated nitrate concentrations in 608 independent small forested catchment water samples from northeastern suburbs of Tokyo. The nitrate concentrations varied from 0.07 to 3.31 mg-N L-1 in this region. We evaluated the effects of N deposition and catchment properties (e.g., meteorological and topographic factors, vegetation and soil types) on nitrate concentrations. In the random forest model, simulated N deposition rates from an atmospheric chemistry transportation model explained most of the variance of nitrate concentration. To evaluate the effects of afforestation management in the catchment, we followed a model-based recursive partitioning method (MOB). MOB succeeded in data-driven identification of subgroups with varying sensitivities to N deposition rate by vegetation composition in the catchment. According to MOB, the catchment with dominant coniferous coverage that mostly consisted of plantation with old tree age tended to have strong sensitivity of nitrate concentrations to N deposition loading.

A meta-analysis of leaf nitrogen distribution within plant canopies.

BACKGROUND AND AIMS: Leaf nitrogen distribution in the plant canopy is an important determinant for canopy photosynthesis. Although the gradient of leaf nitrogen is formed along light gradients in the canopy, its quantitative variations among species and environmental responses remain unknown. Here, we conducted a global meta-analysis of leaf nitrogen distribution in plant canopies. METHODS: We collected data on the nitrogen distribution and environmental variables from 393 plant canopies (100, 241 and 52 canopies for wheat, other herbaceous and woody species, respectively). KEY RESULTS: The trends were clearly different between wheat and other species; the photosynthetic nitrogen distribution coefficient (Kb) was mainly determined by leaf area index (LAI) in wheat, whereas it was correlated with the light extinction coefficient (KL) and LAI in other species. Some other variables were also found to influence Kb We present the best equations for Kb as a function of environmental variables and canopy characteristics. As a more simple function, Kb = 0·5KL can be used for canopies of species other than wheat. Sensitivity analyses using a terrestrial carbon flux model showed that gross primary production tended to be more sensitive to the Kb value especially when nitrogen content of the uppermost leaf was fixed. CONCLUSION: Our results reveal that nitrogen distribution is mainly driven by the vertical light gradient but other factors such as LAI also have significant effects. Our equations contribute to an improvement in the projection of plant productivity and cycling of carbon and nitrogen in terrestrial ecosystems.

Carbon residence time dominates uncertainty in terrestrial vegetation responses to future climate and atmospheric CO2.

Future climate change and increasing atmospheric CO2 are expected to cause major changes in vegetation structure and function over large fractions of the global land surface. Seven global vegetation models are used to analyze possible responses to future climate simulated by a range of general circulation models run under all four representative concentration pathway scenarios of changing concentrations of greenhouse gases. All 110 simulations predict an increase in global vegetation carbon to 2100, but with substantial variation between vegetation models. For example, at 4 °C of global land surface warming (510-758 ppm of CO2), vegetation carbon increases by 52-477 Pg C (224 Pg C mean), mainly due to CO2 fertilization of photosynthesis. Simulations agree on large regional increases across much of the boreal forest, western Amazonia, central Africa, western China, and southeast Asia, with reductions across southwestern North America, central South America, southern Mediterranean areas, southwestern Africa, and southwestern Australia. Four vegetation models display discontinuities across 4 °C of warming, indicating global thresholds in the balance of positive and negative influences on productivity and biomass. In contrast to previous global vegetation model studies, we emphasize the importance of uncertainties in projected changes in carbon residence times. We find, when all seven models are considered for one representative concentration pathway × general circulation model combination, such uncertainties explain 30% more variation in modeled vegetation carbon change than responses of net primary productivity alone, increasing to 151% for non-HYBRID4 models. A change in research priorities away from production and toward structural dynamics and demographic processes is recommended.

Multisectoral climate impact hotspots in a warming world.

The impacts of global climate change on different aspects of humanity's diverse life-support systems are complex and often difficult to predict. To facilitate policy decisions on mitigation and adaptation strategies, it is necessary to understand, quantify, and synthesize these climate-change impacts, taking into account their uncertainties. Crucial to these decisions is an understanding of how impacts in different sectors overlap, as overlapping impacts increase exposure, lead to interactions of impacts, and are likely to raise adaptation pressure. As a first step we develop herein a framework to study coinciding impacts and identify regional exposure hotspots. This framework can then be used as a starting point for regional case studies on vulnerability and multifaceted adaptation strategies. We consider impacts related to water, agriculture, ecosystems, and malaria at different levels of global warming. Multisectoral overlap starts to be seen robustly at a mean global warming of 3 °C above the 1980-2010 mean, with 11% of the world population subject to severe impacts in at least two of the four impact sectors at 4 °C. Despite these general conclusions, we find that uncertainty arising from the impact models is considerable, and larger than that from the climate models. In a low probability-high impact worst-case assessment, almost the whole inhabited world is at risk for multisectoral pressures. Hence, there is a pressing need for an increased research effort to develop a more comprehensive understanding of impacts, as well as for the development of policy measures under existing uncertainty.

In vitro selection of a peptide antagonist of growth hormone secretagogue receptor using cDNA display.

G protein-coupled receptors (GPCRs) are major drug targets, and their ligands are currently being explored and developed by many pharmaceutical companies and independent researchers. Class A (rhodopsin-like) GPCRs compose a predominant GPCR family; therefore, class A GPCR ligands are in demand. Growth hormone secretagogue receptor (GHS-R) is a class A GPCR that stimulates food intake by binding to its peptide ligand, ghrelin. Therefore, antagonists of GHS-R are expected to exert antiobesity function. In this article, we describe the use of cDNA display to screen for successfully and identify an antagonistic peptide of GHS-R. The antagonistic peptide inhibited the ghrelin-induced increase in intracellular Ca(2+) in vitro (IC(50) = approximately 10 µM) and repressed the contraction of isolated animal stomach in response to ghrelin. Furthermore, peripheral administration of the peptide inhibited the food intake of mice. This work provides new insight into the development of antiobesity drugs and describes a method for the discovery of unique peptide ligands for class A GPCRs.