多変量状態空間モデルを用いたリター分解実験のためのパラメータ推定

要旨あり生態学における統計モデリング研究ノー

Novel method to rescue a lethal phenotype through integration of target gene onto the X-chromosome.

The loss-of-function mutations of serine protease inhibitor, Kazal type 1 (SPINK1) gene are associated with human chronic pancreatitis, but the underlying mechanisms remain unknown. We previously reported that mice lacking Spink3, the murine homologue of human SPINK1, die perinatally due to massive pancreatic acinar cell death, precluding investigation of the effects of SPINK1 deficiency. To circumvent perinatal lethality, we have developed a novel method to integrate human SPINK1 gene on the X chromosome using Cre-loxP technology and thus generated transgenic mice termed "X-SPINK1". Consistent with the fact that one of the two X chromosomes is randomly inactivated, X-SPINK1 mice exhibit mosaic pattern of SPINK1 expression. Crossing of X-SPINK1 mice with Spink3+/- mice rescued perinatal lethality, but the resulting Spink3-/-;XXSPINK1 mice developed spontaneous pancreatitis characterized by chronic inflammation and fibrosis. The results show that mice lacking a gene essential for cell survival can be rescued by expressing this gene on the X chromosome. The Spink3-/-;XXSPINK1 mice, in which this method has been applied to partially restore SPINK1 function, present a novel genetic model of chronic pancreatitis

Understanding the uncertainty in global forest carbon turnover

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\u27s 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

Prevalence and Outcomes of Acute Hepatitis B in Okayama, Japan, 2006-2010

Hepatitis B virus (HBV) is one of the major viruses causing acute hepatitis. Recently, the incidence of acute hepatitis with genotype A has been increasing in Japan. The aim of this study was to investigate acute hepatitis B (AHB) in Okayama prefecture, with special attention to HBV genotype A. AHB patients who visited one of 12 general hospitals in Okayama prefecture between 2006 and 2010 were retrospectively analyzed. Over the course of the study period, 128 patients were diagnosed with AHB. Sexual transmission was supposed in the majority of patients (78 patients, 61%), including 59 (76%) having sex with heterosexual partners. The genotypes of HBV were assessed in 90 patients (70%), of whom 27 patients were infected with genotype A, 5 with genotype B, and 58 with genotype C. The prevalence of genotype A was significantly higher among male patients (28.7%), aged 20-29 (35.6%, p＜0.01), among men who had sex with men (100%, p＜0.005), and among patients having sex with unspecified partners (44.8%, p＜0.005). Genotype A was not a significant factor associated with delayed HBsAg disappearance. Caution should be exercised with regard to sexually transmissible diseases in order to slow the pandemic spread of AHB due to genotype A

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.The research leading to these results has received funding from the European Community’s Seventh Framework Programme (FP7 2007-2013) under Grant 238366. R.B., R.K., R.D., A.W., and P.D.F. were supported by the Joint Department of Energy and Climate Change/Department for Environment, Food and Rural Affairs Met Office Hadley Centre Climate Programme (GA01101). A.I. and K.N. were supported by the Environment Research and Technology Development Fund (S-10) of the Ministry of the Environment, Japan. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for the Coupled Model Intercomparison Project (CMIP), and we thank the climate modeling groups responsible for the GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, and NorESM1-M models for producing and making available their model output. For CMIP, the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. This work has been conducted under the framework of the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). The ISI-MIP Fast Track project was funded by the German Federal Ministry of Education and Research (BMBF) with project funding Reference 01LS1201A.This is the author accepted manuscript. The final version is available from PNAS via http://dx.doi.org/10.1073/pnas.122247711

Benchmarking carbon fluxes of the ISIMIP2a biome models

The purpose of this study is to evaluate the eight ISIMIP2a biome models against independent estimates of long-term net carbon fluxes (i.e. Net Biome Productivity, NBP) over terrestrial ecosystems for the recent four decades (1971–2010). We evaluate modeled global NBP against 1) the updated global residual land sink (RLS) plus land use emissions (E LUC) from the Global Carbon Project (GCP), presented as R + L in this study by Le Quéré et al (2015), and 2) the land CO2 fluxes from two atmospheric inversion systems: Jena CarboScope s81_v3.8 and CAMS v15r2, referred to as F Jena and F CAMS respectively. The model ensemble-mean NBP (that includes seven models with land-use change) is higher than but within the uncertainty of R + L, while the simulated positive NBP trend over the last 30 yr is lower than that from R + L and from the two inversion systems. ISIMIP2a biome models well capture the interannual variation of global net terrestrial ecosystem carbon fluxes. Tropical NBP represents 31 ± 17% of global total NBP during the past decades, and the year-to-year variation of tropical NBP contributes most of the interannual variation of global NBP. According to the models, increasing Net Primary Productivity (NPP) was the main cause for the generally increasing NBP. Significant global NBP anomalies from the long-term mean between the two phases of El Niño Southern Oscillation (ENSO) events are simulated by all models (p < 0.05), which is consistent with the R + L estimate (p = 0.06), also mainly attributed to NPP anomalies, rather than to changes in heterotrophic respiration (Rh). The global NPP and NBP anomalies during ENSO events are dominated by their anomalies in tropical regions impacted by tropical climate variability. Multiple regressions between R + L, F Jena and F CAMS interannual variations and tropical climate variations reveal a significant negative response of global net terrestrial ecosystem carbon fluxes to tropical mean annual temperature variation, and a non-significant response to tropical annual precipitation variation. According to the models, tropical precipitation is a more important driver, suggesting that some models do not capture the roles of precipitation and temperature changes adequately

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 degC 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 degC. 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

Concealed nitrogen footprint in protein-free foods: an empirical example using oil palm products

The agro-food system satisfying human food demand releases heavy nitrogen (N) loads into the environment. The N footprint is an indicator of N loads from individual consumption of food as well as energy. A bottom-up approach called the ‘N-calculator method’ calculates the food N footprint using the N content in consumed foods, such that the N footprint of protein-free foods is treated as zero. This method underestimates the N footprint of protein-free foods, such as oil and sugar, when the source crops require N input in production. In this study, we propose a substitution factor, the virtual nitrogen factor for protein-free foods (VNFree), defined as the potential N load per unit weight of consumed food, to explicitly calculate the production N footprint. Oil palm and its products, palm oil (PO) and palm kernel oil (PKO), were chosen for this case study of protein-free foods. Global mean VNFree values of PO and PKO obtained by averaging national-scale data of the three countries with the largest production (Indonesia, Malaysia, and Thailand) were 0.0241 and 0.0037 kg N kg ^–1 oil, respectively. The 6.5-times difference in VNFree values was attributed to the difference in oil yield. The food N footprint of PO and PKO calculated here represented less than 2% of the previously reported total food N footprints of several countries. However, oil palm products are also used for industry, and the chemical fertilizer consumption for oil palm accounted for only 8%–12% of that of all oil and sugar crops. The protein-free N footprint of all these products will be much larger. We expect that the current N-calculator method as a bottom-up approach will be improved by expanding the VNFree concept, which enables the calculation of the concealed N footprint in protein-free products, including all uses of oil and sugar crops

Divergent data-driven estimates of global soil respiration

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

Historical global map of NH4+ and NO3- application in synthetic nitrogen fertilizer, link to NetCDF files

This paper provides a method for constructing a new historical global nitrogen fertilizer application map (0.5° × 0.5° resolution) for the period 1961-2010 based on country-specific information from Food and Agriculture Organization statistics (FAOSTAT) and various global datasets. This new map incorporates the fraction of NH+4 (and NONO-3) in N fertilizer inputs by utilizing fertilizer species information in FAOSTAT, in which species can be categorized as NH+4 and/or NO-3-forming N fertilizers. During data processing, we applied a statistical data imputation method for the missing data (19 % of national N fertilizer consumption) in FAOSTAT. The multiple imputation method enabled us to fill gaps in the time-series data using plausible values using covariates information (year, population, GDP, and crop area). After the imputation, we downscaled the national consumption data to a gridded cropland map. Also, we applied the multiple imputation method to the available chemical fertilizer species consumption, allowing for the estimation of the NH+4/NO-3 ratio in national fertilizer consumption. In this study, the synthetic N fertilizer inputs in 2000 showed a general consistency with the existing N fertilizer map (Potter et al., 2010, doi:10.1175/2009EI288.1) in relation to the ranges of N fertilizer inputs. Globally, the estimated N fertilizer inputs based on the sum of filled data increased from 15 Tg-N to 110 Tg-N during 1961-2010. On the other hand, the global NO-3 input started to decline after the late 1980s and the fraction of NO-3 in global N fertilizer decreased consistently from 35 % to 13 % over a 50-year period. NH+4 based fertilizers are dominant in most countries; however, the NH+4/NO-3 ratio in N fertilizer inputs shows clear differences temporally and geographically. This new map can be utilized as an input data to global model studies and bring new insights for the assessment of historical terrestrial N cycling changes