Dating groundwater in the Bohemian Cretaceous Basin: Understanding tracer variations in the subsurface

The northern section of the Bohemian Cretaceous Basin has been the site of intensive U exploitation with harmful impacts on groundwater quality. The understanding of groundwater flow and age distribution is crucial for the prediction of the future dispersion and impact of the contamination. State of the art tracer methods (3H, 3He, 4He, 85Kr, 39Ar and 14C) were, therefore, used to obtain insights to ageing and mixing processes of groundwater along a north–south flow line in the centre of the two most important aquifers of Cenomanian and middle Turonian age. Dating of groundwater is particularly complex in this area as: (i) groundwater in the Cenomanian aquifer is locally affected by fluxes of geogenic and biogenic gases (e.g. CO2, CH4, He) and by fossil brines in basement rocks rich in Cl and SO4; (ii) a thick unsaturated zone overlays the Turonian aquifer; (iii) a periglacial climate and permafrost conditions prevailed during the Last Glacial Maximum (LGM), and iv) the wells are mostly screened over large depth intervals. Large disagreements in 85Kr and 3H/3He ages indicate that processes other than ageing have affected the tracer data in the Turonian aquifer. Mixing with older waters (>50 a) was confirmed by 39Ar activities. An inverse modelling approach, which included time lags for tracer transport throughout the unsaturated zone and degassing of 3He, was used to estimate the age of groundwater. Best fits between model and field results were obtained for mean residence times varying from modern up to a few hundred years. The presence of modern water in this aquifer is correlated with the occurrence of elevated pollution (e.g. nitrates). An increase of reactive geochemical indicators (e.g. Na) and radiogenic 4He, and a decrease in 14C along the flow direction confirmed groundwater ageing in the deeper confined Cenomanian aquifer. Radiocarbon ages varied from a few hundred years to more than 20 ka. Initial 14C activity for radiocarbon dating was calibrated by means of 39Ar measurements. The 14C age of a sample recharged during the LGM was further confirmed by depleted stable isotope signatures and near freezing point noble gas temperature. Radiogenic 4He accumulated in groundwater with concentrations increasing linearly with 14C ages. This enabled the use of 4He to validate the dating range of 14C and extend it to other parts of this aquifer. In the proximity of faults, 39Ar in excess of modern concentrations and 14C dead CO2 sources, elevated 3He/4He ratios and volcanic activity in Oligocene to Quaternary demonstrate the influence of gas of deeper origin and impeded the application of 4He, 39Ar and 14C for groundwater dating.

Iron fluxes to Talos Dome, Antarctica, over the past 200 kyr

Atmospheric fluxes of iron (Fe) over the past 200 kyr are reported for the coastal Antarctic Talos Dome ice core, based on acid leachable Fe concentrations. Fluxes of Fe to Talos Dome were consistently greater than those at Dome C, with the greatest difference observed during interglacial climates. We observe different Fe flux trends at Dome C and Talos Dome during the deglaciation and early Holocene, attributed to a combination of deglacial activation of dust sources local to Talos Dome and the reorganisation of atmospheric transport pathways with the retreat of the Ross Sea ice shelf. This supports similar findings based on dust particle sizes and fluxes and Rare Earth Element fluxes. We show that Ca and Fe should not be used as quantitative proxies for mineral dust, as they all demonstrate different deglacial trends at Talos Dome and Dome C. Considering that a 20 ppmv decrease in atmospheric CO2 at the coldest part of the last glacial maximum occurs contemporaneously with the period of greatest Fe and dust flux to Antarctica, we confirm that the maximum contribution of aeolian dust deposition to Southern Ocean sequestration of atmospheric CO2 is approximately 20 ppmv.�

Methane emissions from floodplains in the Amazon Basin: challenges in developing a process-based model for global applications

Tropical wetlands are estimated to represent about 50% of the natural wetland methane (CH4) emissions and explain a large fraction of the observed CH4 variability on timescales ranging from glacial–interglacial cycles to the currently observed year-to-year variability. Despite their importance, however, tropical wetlands are poorly represented in global models aiming to predict global CH4 emissions. This publication documents a first step in the development of a process-based model of CH4 emissions from tropical floodplains for global applications. For this purpose, the LPX-Bern Dynamic Global Vegetation Model (LPX hereafter) was slightly modified to represent floodplain hydrology, vegetation and associated CH4 emissions. The extent of tropical floodplains was prescribed using output from the spatially explicit hydrology model PCR-GLOBWB. We introduced new plant functional types (PFTs) that explicitly represent floodplain vegetation. The PFT parameterizations were evaluated against available remote-sensing data sets (GLC2000 land cover and MODIS Net Primary Productivity). Simulated CH4 flux densities were evaluated against field observations and regional flux inventories. Simulated CH4 emissions at Amazon Basin scale were compared to model simulations performed in the WETCHIMP intercomparison project. We found that LPX reproduces the average magnitude of observed net CH4 flux densities for the Amazon Basin. However, the model does not reproduce the variability between sites or between years within a site. Unfortunately, site information is too limited to attest or disprove some model features. At the Amazon Basin scale, our results underline the large uncertainty in the magnitude of wetland CH4 emissions. Sensitivity analyses gave insights into the main drivers of floodplain CH4 emission and their associated uncertainties. In particular, uncertainties in floodplain extent (i.e., difference between GLC2000 and PCR-GLOBWB output) modulate the simulated emissions by a factor of about 2. Our best estimates, using PCR-GLOBWB in combination with GLC2000, lead to simulated Amazon-integrated emissions of 44.4 ± 4.8 Tg yr−1. Additionally, the LPX emissions are highly sensitive to vegetation distribution. Two simulations with the same mean PFT cover, but different spatial distributions of grasslands within the basin, modulated emissions by about 20%. Correcting the LPX-simulated NPP using MODIS reduces the Amazon emissions by 11.3%. Finally, due to an intrinsic limitation of LPX to account for seasonality in floodplain extent, the model failed to reproduce the full dynamics in CH4 emissions but we proposed solutions to this issue. The interannual variability (IAV) of the emissions increases by 90% if the IAV in floodplain extent is accounted for, but still remains lower than in most of the WETCHIMP models. While our model includes more mechanisms specific to tropical floodplains, we were unable to reduce the uncertainty in the magnitude of wetland CH4 emissions of the Amazon Basin. Our results helped identify and prioritize directions towards more accurate estimates of tropical CH4 emissions, and they stress the need for more research to constrain floodplain CH4 emissions and their temporal variability, even before including other fundamental mechanisms such as floating macrophytes or lateral water fluxes.

Past and future carbon fluxes from land use change, shifting cultivation and wood harvest

Carbon emissions from anthropogenic land use (LU) and land use change (LUC) are quantified with a Dynamic Global Vegetation Model for the past and the 21st century following Representative Concentration Pathways (RCPs). Wood harvesting and parallel abandonment and expansion of agricultural land in areas of shifting cultivation are explicitly simulated (gross LUC) based on the Land Use Harmonization (LUH) dataset and a proposed alternative method that relies on minimum input data and generically accounts for gross LUC. Cumulative global LUC emissions are 72 GtC by 1850 and 243 GtC by 2004 and 27–151 GtC for the next 95 yr following the different RCP scenarios. The alternative method reproduces results based on LUH data with full transition information within <0.1 GtC/yr over the last decades and bears potential for applications in combination with other LU scenarios. In the last decade, shifting cultivation and wood harvest within remaining forests including slash each contributed 19% to the mean annual emissions of 1.2 GtC/yr. These factors, in combination with amplification effects under elevated CO2, contribute substantially to future emissions from LUC in all RCPs.

Seasonal Variation in the Capacity for Plant Trait Measures to Predict Grassland Carbon and Water Fluxes

There is a need for accurate predictions of ecosystem carbon (C) and water fluxes in field conditions. Previous research has shown that ecosystem properties can be predicted from community abundance-weighted means (CWM) of plant functional traits and measures of trait variability within a community (FDvar). The capacity for traits to predict carbon (C) and water fluxes, and the seasonal dependency of these trait-function relationships has not been fully explored. Here we measured daytime C and water fluxes over four seasons in grasslands of a range of successional ages in southern England. In a model selection procedure, we related these fluxes to environmental covariates and plant biomass measures before adding CWM and FDvar plant trait measures that were scaled up from measures of individual plants grown in greenhouse conditions. Models describing fluxes in periods of low biological activity contained few predictors, which were usually abiotic factors. In more biologically active periods, models contained more predictors, including plant trait measures. Field-based plant biomass measures were generally better predictors of fluxes than CWM and FDvar traits. However, when these measures were used in combination traits accounted for additional variation. Where traits were significant predictors their identity often reflected seasonal vegetation dynamics. These results suggest that database derived trait measures can improve the prediction of ecosystem C and water fluxes. Controlled studies and those involving more detailed flux measurements are required to validate and explore these findings, a worthwhile effort given the potential for using simple vegetation measures to help predict landscape-scale fluxes.

Anthropogenic perturbation of the carbon fluxes from land to ocean

A substantial amount of the atmospheric carbon taken up on land through photosynthesis and chemical weathering is transported laterally along the aquatic continuum from upland terrestrial ecosystems to the ocean. So far, global carbon budget estimates have implicitly assumed that the transformation and lateral transport of carbon along this aquatic continuum has remained unchanged since pre-industrial times. A synthesis of published work reveals the magnitude of present-day lateral carbon fluxes from land to ocean, and the extent to which human activities have altered these fluxes. We show that anthropogenic perturbation may have increased the flux of carbon to inland waters by as much as 1.0 Pg C yr(-1) since pre-industrial times, mainly owing to enhanced carbon export from soils. Most of this additional carbon input to upstream rivers is either emitted back to the atmosphere as carbon dioxide (similar to 0.4 Pg C yr(-1)) or sequestered in sediments (similar to 0.5 Pg C yr(-1)) along the continuum of freshwater bodies, estuaries and coastal waters, leaving only a perturbation carbon input of similar to 0.1 Pg C yr(-1) to the open ocean. According to our analysis, terrestrial ecosystems store similar to 0.9 Pg C yr(-1) at present, which is in agreement with results from forest inventories but significantly differs from the figure of 1.5 Pg C yr(-1) previously estimated when ignoring changes in lateral carbon fluxes. We suggest that carbon fluxes along the land-ocean aquatic continuum need to be included in global carbon dioxide budgets.

A second look at gauged supergravities from fluxes in M-theory

We investigate reductions of M-theory beyond twisted tori by allowing the presence of KK6 monopoles (KKO6-planes) compatible with N = 4 supersymmetry in four dimensions. The presence of KKO6-planes proves crucial to achieve full moduli stabilisation as they generate new universal moduli powers in the scalar potential. The resulting gauged supergravities turn out to be compatible with a weak G2 holonomy at N = 1 as well as at some non-supersymmetric AdS4 vacua. The M-theory flux vacua we present here cannot be obtained from ordinary type IIA orientifold reductions including background fluxes, D6-branes (O6-planes) and/or KK5 (KKO5) sources. However, from a four-dimensional point of view, they still admit a description in terms of so-called non-geometric fluxes. In this sense we provide the M-theory interpretation for such non-geometric type IIA flux vacua.

Simulating Carbon Stocks and Fluxes of an African Tropical Montane Forest with an Individual-Based Forest Model

Tropical forests are carbon-dense and highly productive ecosystems. Consequently, they play an important role in the global carbon cycle. In the present study we used an individual-based forest model (FORMIND) to analyze the carbon balances of a tropical forest. The main processes of this model are tree growth, mortality, regeneration, and competition. Model parameters were calibrated using forest inventory data from a tropical forest at Mt. Kilimanjaro. The simulation results showed that the model successfully reproduces important characteristics of tropical forests (aboveground biomass, stem size distribution and leaf area index). The estimated aboveground biomass (385 t/ha) is comparable to biomass values in the Amazon and other tropical forests in Africa. The simulated forest reveals a gross primary production of 24 tcha-1yr-1. Modeling above- and belowground carbon stocks, we analyzed the carbon balance of the investigated tropical forest. The simulated carbon balance of this old-growth forest is zero on average. This study provides an example of how forest models can be used in combination with forest inventory data to investigate forest structure and local carbon balances.