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.
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•Radioactivity data of 3189 wild edible mushrooms of 107 species were analyzed.•A hierarchical Bayesian analysis considering spatial autocorrelation worked well.•Mycorrhizal and some saprophytic species tended to have higher radioactivity.•Species-wise radioactivities were positively correlated with those in Chernobyl.
We provided reliable species characteristics of radiocesium in wild mushrooms which could be utilized for current and future contamination issues.
•A new satellite-based algorithm for detecting rice phenology is proposed.•Feature-based VH, EVI, and NDYI predict rice planting, heading, and harvest dates.•Robustness was confirmed for multiple ...scales and cropping systems in monsoon Asia.•Algorithm is promising in mapping large-scale high resolution rice phenology map.
Knowledge of rice phenology is essential for understanding the agricultural practices and studying its impact on ecosystem services. However, so far, available global-scale rice phenology maps do not provide fine spatiotemporal details of rice phenology in a consistent framework because they rely on the compilation of statistical data. Thus, this paper proposes an algorithm that combines the complementary advantages of Sentinel-1 and Sentinel-2 satellite images to produce large-scale maps that depict rice phenology dynamics. The novelty of this algorithm lies in the correlation with rice phenology features, i.e., rice in water condition and rice color change. The time series of backscattering at Vertical-Horizontal (VH) polarization and Enhanced Vegetation Index (EVI) are proposed to recognize rice planting and heading dates, respectively. For the same time, the Normalized Difference Yellow Index (NDYI) is utilized to detect the rice harvest date for the first time. The proposed algorithm is applied to multiple spatial scales (prefecture, 0.5° gridcell, and site scales) and to multiple rice cropping systems (single, double, and triple croppings) in monsoon Asia. Results reveal that the algorithm is able to accurately detect the rice planting and harvest dates across two rice paddy field distribution maps with moderate-to-high spatial resolution, different validation data, and different rice cropping systems. The bias values of detected planting dates are 2, 0, and 4 days, while that of harvest dates are -2, -5, and -13 days at the prefecture, 0.5° gridcell, and site scales, respectively. These results highlight the potential of this algorithm to generate national, continental, or even global maps of rice phenology dynamics in an efficient manner, which can facilitate research on the impact of rice phenology on rice ecosystem services that echoes environmental and climate change.
Abstract
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
137
Cs ...dynamics using the latest observation data and newly provided maps of the predicted
137
Cs 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
137
Cs inventory showed that although the
137
Cs 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
137
Cs activity concentrations reproduced the different trends of the
137
Cs activity concentrations for cedar, oak, and pine trees. Our simulation suggests that the changes of the wood
137
Cs 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
137
Cs dynamics within forest ecosystems and the changes in wood contamination.
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.
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•Nitrogen budgets in Japan from 2000 to 2015 were estimated for all sectors.•Reactive nitrogen loss to the environment in 2010 was 1960 Gg N yr−1.•Another 3800 Gg N yr−1 was rendered useless by conversion to dinitrogen.•Reactive nitrogen loss to air and water decreased from 2000 to 2015.•There is room for further reductions in nitrogen waste in Japan.
Abstract
The release of carbon dioxide from the soil to the atmosphere, known as soil respiration, is the second largest terrestrial carbon flux after photosynthesis, but the convergence of the ...data-driven estimates is unclear. Here we collate all historical data-driven estimates of global soil respiration to analyze convergence and uncertainty in the estimates. Despite the development of a dataset and advanced scaling techniques in the last two decades, we find that inter-model variability has increased. Reducing inter-model variability of global soil respiration is not an easy task, but when the puzzle pieces of the carbon cycle fit together perfectly, climate change prediction will be more reliable.
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.
The length of time that carbon remains in forest biomass
is one of the largest uncertainties in the global carbon cycle, with both
recent historical baselines and future responses to environmental ...change
poorly constrained by available observations. In the absence of large-scale
observations, models used for global assessments tend to fall back on
simplified assumptions of the turnover rates of biomass and soil carbon
pools. In this study, the biomass carbon turnover times calculated by an
ensemble of contemporary terrestrial biosphere models (TBMs) are analysed to
assess their current capability to accurately estimate biomass carbon
turnover times in forests and how these times are anticipated to change in
the future. Modelled baseline 1985–2014 global average forest biomass
turnover times vary from 12.2 to 23.5 years between TBMs. TBM differences in
phenological processes, which control allocation to, and turnover rate of,
leaves and fine roots, are as important as tree mortality with regard to
explaining the variation in total turnover among TBMs. The different
governing mechanisms exhibited by each TBM result in a wide range of
plausible turnover time projections for the end of the century. Based on
these simulations, it is not possible to draw robust conclusions regarding
likely future changes in turnover time, and thus biomass change, for
different regions. Both spatial and temporal uncertainty in turnover time
are strongly linked to model assumptions concerning plant functional type
distributions and their controls. Thirteen model-based hypotheses of
controls on turnover time are identified, along with recommendations for
pragmatic steps to test them using existing and novel observations. Efforts
to resolve uncertainty in turnover time, and thus its impacts on the future
evolution of biomass carbon stocks across the world's forests, will need to
address both mortality and establishment components of forest demography, as
well as allocation of carbon to woody versus non-woody biomass growth.
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.
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).
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.
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.
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.
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•This study observed dissolved N2O in oil palm plantations established on peat swamps.•We found that dissolved N2O exhibits seasonal variations.•Isotopocule analysis revealed a high N2O reduction before reaching drainage surface.
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