Model studies on the response of the terrestrial carbon cycle to climate change and variability

The first part of this thesis describes the further development of a dynamic global vegetation model, LPJ, and its application to selected scientific questions. LPJ has been extended to include isotopic fractionation of 13C at the leaf level during assimilation and includes a full isotopic terrestrial carbon cycle. Hence, it simulates the isotopic signature of the heterotrophic respiration fluxes. The model thus allows a quantitative analysis of the net biosphere exchange of CO2 and 13CO2 with the atmosphere as a function of changes in climate, land cover, atmospheric CO2, and the isotope ratio of CO2. The extended version of LPJ has been used to study the response of the global vegetation distribution to an abrupt climate change event (Younger Dryas) and the thereby incurred changes in the terrestrial carbon pools and fluxes and their isotopic 13C/12ratio. Climate data from a 850-year-long coupled ocean-atmosphere general circulation model (ECHAM3/LSG) is used for these simulations. The comparison of the modelled vegetation distribution and shifts during this idealized Younger Dryas event with reconstructed vegetation maps for North America and Europe based on pollen records shows a reasonable agreement. The impact of the terrestrial carbon release during the Younger Dryas on the atmospheric CO2 and δ 13C is analyzed using a simplified ocean model and compared to ice core measurements. In the standard case the simulation exhibits a significant change in global total terrestrial carbon stocks of about 180 Pg C leading to an atmospheric CO2 increase of approx. 28 ppmv as a consequence of the climate change event. The robustness of the terrestrial signal during the Younger Dryas is studied by several sensitivity experiments concerning the initial values of the carbon pool sizes as well as the CO2 fertilization effect and the temperature dependency of the carbon decomposition rates. The resulting increase of atmospheric CO2 concentrations for the cold event varies between 16 to 33 ppmv among the different experiments. The simulated atmospheric δ 13C values which are about 0.4 per mil lower during the cold phase reflect major findings from ice core measurements and are fairly robust against the sensitivity experiments. The isotope version of LPJ has also been used to study the effects of climate variability, fire, and changes in land use on the exchange fluxes of CO2 and 13CO2 between the terrestrial biosphere and atmosphere for the last 100 years in greater detail. A transient, spatially explicit dataset of C4 crops and tropical C4 pastures has been compiled which, in combination with a land use scheme, allows the analysis of the impact of land use and C4 cultivation on the terrestrial stable isotope composition. LPJ simulates a global mean isotopic fractionation of 17.7 per mil at the leaf level with interannual variations of ca. 0.3 per mil in the case without land use for the years 1950 to 1998. In this case, interannual variability in the net 13CO2 flux between atmosphere and terrestrial biosphere is of the order of 15 Pg C per mil yr-1. It is reduced to 4 Pg C per mil yr-1 if the leaf-level fractionation factor is held constant at the long term mean. Depending on the chosen land use scheme modelled values of leaf discrimination vary between 17.9 per mil and 17.0 per mil with results from the experiment specifying C4 crops and C4 pastures being the lowest. Modelled values of isotopic disequilibrium similarly depend on the amount of prescribed C4 vegetation (crops and pastures) and vary between 37.9 Pg C per mil yr-1 and 23.9 Pg C per mil yr-1 averaged over the years 1985 to 1995. In addition, the effect of fire on the isotopic disequilibrium has been estimated to lead to a reduction of approx. 10 Pg C per mil yr-1. The second part of the thesis describes the construction and application of a terrestrial Carbon Cycle Data Assimilation System (CCDAS). In the assimilation step parameters of a terrestrial biosphere model, BETHY, are constrained subject to observations. The technique is demonstrated by using atmospheric CO2 concentration observations from 1979 to 1999 and satellite remote sensing data (identifying vegetation activity) for the years 1989 and 1990 to optimize the tunable parameters in the model (some spatially explicit, some global) and also give an estimate of their uncertainties. Quantities (global and spatially explicit carbon fluxes) derived from the prognostic step of CCDAS are then analyzed with respect to climate anomalies. Processes responsible for the mean terrestrial fluxes and their variability are identified. A highly significant correlation between El Nino/Southern Oscillation and terrestrial CO2 fluxes, with CO2 lagging by a few months was found. Net CO2 outgasing during El Nino events is caused mainly by a reduction of photosynthesis in large parts of the tropics, notably the Amazon basin and Central Africa. The most important deviation of this pattern is found after the eruption of Mount Pinatubo in 1991

Mixture effects at very low doses with combinations of anti-androgenic pesticides, antioxidants, industrial pollutant and chemicals used in personal care products

This article has been made available through the Brunel Open Access Publishing Fund.Many xenobiotics have been identified as in vitro androgen receptor (AR) antagonists, but information about their ability to produce combined effects at low concentrations ismissing. Such data can reveal whether joint effects at the receptor are induced at low levels andmay support the prioritisation of in vivo evaluations and provide orientations for the grouping of anti-androgens in cumulative risk assessment. Combinations of 30 AR antagonists from a wide range of sources and exposure routes (pesticides, antioxidants, parabens, UV-filters, synthetic musks, bisphenol-A, benzo(a)pyrene, perfluorooctane sulfonate and pentabromodiphenyl ether) were tested using a reporter gene assay (MDA-kb2). Chemicalswere combined at threemixture ratios, equivalent to single components' effect concentrations that inhibit the action of dihydrotesterone by 1%, 10% or 20%. Concentration addition (CA) and independent action were used to calculate additivity expectations. We observed complete suppression of dihydrotestosterone effects when chemicals were combined at individual concentrations eliciting 1%, 10% or 20% AR antagonistic effect. Due to the large number of mixture components, the combined AR antagonistic effects occurred at very low concentrations of individual mixture components. CA slightly underestimated the combined effects at all mixture ratios. In conclusion, large numbers of AR antagonists froma wide variety of sources and exposure routes have the ability of acting together at the receptor to produce joint effects at very low concentrations. Significant mixture effects are observed when chemicals are combined at concentrations that individually do not induce observable AR antagonistic effects. Cumulative risk assessment for AR antagonists should apply grouping criteria based on effects where data are available, rather than on criteria of chemical similarity

Environmental concentrations of anti-androgenic pharmaceuticals do not impact sexual disruption in fish alone or in combination with steroid oestrogens

This article has been made available through the Brunel Open Access Publishing Fund.Sexual disruption in wild fish has been linked to the contamination of river systems with steroid oestrogens, including the pharmaceutical 17α-ethinylestradiol, originating from domestic wastewaters. As analytical chemistry has advanced, more compounds derived from the human usage of pharmaceuticals have been identified in the environment and questions have arisen as to whether these additional pharmaceuticals may also impact sexual disruption in fish. Indeed, pharmaceutical anti-androgens have been shown to induce such effects under laboratory conditions. These are of particular interest since anti-androgenic biological activity has been identified in the aquatic environment and is potentially implicated in sexual disruption alone and in combination with steroid oestrogens. Consequently, predictive modelling was employed to determine the concentrations of two anti-androgenic human pharmaceuticals, bicalutamide and cyproterone acetate, in UK sewage effluents and river catchments and their combined impacts on sexual disruption were then assessed in two fish models. Crucially, fish were also exposed to the anti-androgens in combination with steroid oestrogens to determine whether they had any additional impact on oestrogen induced feminisation. Modelling predicted that the anti-androgenic pharmaceuticals were likely to be widespread in UK river catchments. However, their concentrations were not sufficient to induce significant responses in plasma vitellogenin concentrations, secondary sexual characteristics or gross indices in male fathead minnow or intersex in Japanese medaka alone or in combination with steroid oestrogens. However, environmentally relevant mixtures of oestrone, 17β-oestradiol and 17α-ethinylestradiol did induce vitellogenin and intersex, supporting their role in sexual disruption in wild fish populations. Unexpectedly, a male dominated sex ratio (100% in controls) was induced in medaka and the potential cause and implications are briefly discussed, highlighting the potential of non-chemical modes of action on this endpoint

Evidence of estrogenic mixture effects on the reproductive performance of fish

The official published version can be obtained from the link below - Copyright @ 2007 American Chemical SocietyRecent research into the effects of mixtures of estrogenic chemicals has revealed the capacity for similarly acting chemicals to act in combination, according to the principles of concentration addition. This means that, collectively, they may pose a significant environmental risk, even when each component is present at a low and individually ineffective concentration. The aim of this study was to investigate the ecological significance of mixture effects at low-effect concentrations by assessing the combined effect of estrogenic chemicals on the reproductive performance of fish. Pairs of fathead minnows were exposed to five estrogenic chemicals. Endpoints analyzed included fecundity, the expression of male secondary sexual characteristics, somatic indices, and vitellogenin induction. In the first phase of the study, a concentration-response analysis was performed to investigate the relative sensitivity of these endpoints. In the second phase, mixture effects at low-effect concentrations were explored by exposing fish to each of the mixture components, individually and in combination. Data from these experiments provide evidence of mixture effects on fitness and fecundity, demonstrating the capacity for chemicals to act together to affect reproductive performance, even when each component is present belowthe threshold of detectable effects. This has important implications for hazard assessment and contributes to our understanding of mixture effects at increasing levels of biological complexity.This work was funded by the European Commission, under contract EVK1-2001-00091

Reviews and syntheses: Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems

The global carbon cycle is an important component of the Earth system and it interacts with the hydrology, energy and nutrient cycles as well as ecosystem dynamics. A better understanding of the global carbon cycle is required for improved projections of climate change including corresponding changes in water and food resources and for the verification of measures to reduce anthropogenic greenhouse gas emissions. An improved understanding of the carbon cycle can be achieved by data assimilation systems, which integrate observations relevant to the carbon cycle into coupled carbon, water, energy and nutrient models. Hence, the ingredients for such systems are a carbon cycle model, an algorithm for the assimilation and systematic and well error-characterised observations relevant to the carbon cycle. Relevant observations for assimilation include various in situ measurements in the atmosphere (e.g. concentrations of CO2 and other gases) and on land (e.g. fluxes of carbon water and energy, carbon stocks) as well as remote sensing observations (e.g. atmospheric composition, vegetation and surface properties). We briefly review the different existing data assimilation techniques and contrast them to model benchmarking and evaluation efforts (which also rely on observations). A common requirement for all assimilation techniques is a full description of the observational data properties. Uncertainty estimates of the observations are as important as the observations themselves because they similarly determine the outcome of such assimilation systems. Hence, this article reviews the requirements of data assimilation systems on observations and provides a non-exhaustive overview of current observations and their uncertainties for use in terrestrial carbon cycle data assimilation. We report on progress since the review of model-data synthesis in terrestrial carbon observations by Raupach et al.(2005), emphasising the rapid advance in relevant space-based observations

Extending the applicability of the dose addition model to the assessment of chemical mixtures of partial agonists by using a novel toxic unit extrapolation method

This article has been made available through the Brunel Open Access Publishing Fund.Dose addition, a commonly used concept in toxicology for the prediction of chemical mixture effects, cannot readily be applied to mixtures of partial agonists with differing maximal effects. Due to its mathematical features, effect levels that exceed the maximal effect of the least efficacious compound present in the mixture, cannot be calculated. This poses problems when dealing with mixtures likely to be encountered in realistic assessment situations where chemicals often show differing maximal effects. To overcome this limitation, we developed a pragmatic solution that extrapolates the toxic units of partial agonists to effect levels beyond their maximal efficacy. We extrapolated different additivity expectations that reflect theoretically possible extremes and validated this approach with a mixture of 21 estrogenic chemicals in the E-Screen. This assay measures the proliferation of human epithelial breast cancers. We found that the dose-response curves of the estrogenic agents exhibited widely varying shapes, slopes and maximal effects, which made it necessary to extrapolate mixture responses above 14% proliferation. Our toxic unit extrapolation approach predicted all mixture responses accurately. It extends the applicability of dose addition to combinations of agents with differing saturating effects and removes an important bottleneck that has severely hampered the use of dose addition in the past. © 2014 Scholze et al

Combining ASTER multispectral imagery analysis and support vector machines for rapid and cost-effective post-fire assessment: a case study from the Greek wildland fires of 2007

Remote sensing is increasingly being used as a cost-effective and practical solution for the rapid evaluation of impacts from wildland fires. The present study investigates the use of the support vector machine (SVM) classification method with multispectral data from the Advanced Spectral Emission and Reflection Radiometer (ASTER) for obtaining a rapid and cost effective post-fire assessment in a Mediterranean setting. A further objective is to perform a detailed intercomparison of available burnt area datasets for one of the most catastrophic forest fire events that occurred near the Greek capital during the summer of 2007. For this purpose, two ASTER scenes were acquired, one before and one closely after the fire episode. Cartography of the burnt area was obtained by classifying each multi-band ASTER image into a number of discrete classes using the SVM classifier supported by land use/cover information from the CORINE 2000 land nomenclature. Overall verification of the derived thematic maps based on the classification statistics yielded results with a mean overall accuracy of 94.6% and a mean Kappa coefficient of 0.93. In addition, the burnt area estimate derived from the post-fire ASTER image was found to have an average difference of 9.63% from those reported by other operationally-offered burnt area datasets available for the test region

Genotoxic mixtures and dissimilar action: Concepts for prediction and assessment

This article has been made available through the Brunel Open Access Publishing Fund. This article is distributed under the terms of the creative commons Attribution license which permits any use, distribution, and reproduction in any medium, provided the original author(s)and the source are credited.Combinations of genotoxic agents have frequently been assessed without clear assumptions regarding their expected (additive) mixture effects, often leading to claims of synergisms that might in fact be compatible with additivity. We have shown earlier that the combined effects of chemicals, which induce micronuclei (MN) in the cytokinesis-block micronucleus assay in Chinese hamster ovary-K1 cells by a similar mechanism, were additive according to the concept of concentration addition (CA). Here, we extended these studies and investigated for the first time whether valid additivity expectations can be formulated for MN-inducing chemicals that operate through a variety of mechanisms, including aneugens and clastogens (DNA cross-linkers, topoisomerase II inhibitors, minor groove binders). We expected that their effects should follow the additivity principles of independent action (IA). With two mixtures, one composed of various aneugens (colchicine, flubendazole, vinblastine sulphate, griseofulvin, paclitaxel), and another composed of aneugens and clastogens (flubendazole, doxorubicin, etoposide, melphalan and mitomycin C), we observed mixture effects that fell between the additivity predictions derived from CA and IA. We achieved better agreement between observation and prediction by grouping the chemicals into common assessment groups and using hybrid CA/IA prediction models. The combined effects of four dissimilarly acting compounds (flubendazole, paclitaxel, doxorubicin and melphalan) also fell within CA and IA. Two binary mixtures (flubendazole/paclitaxel and flubendazole/doxorubicin) showed effects in reasonable agreement with IA additivity. Our studies provide a systematic basis for the investigation of mixtures that affect endpoints of relevance to genotoxicity and show that their effects are largely additive.UK Food Standards Agenc

The benefits of investing into improved carbon flux monitoring

Operationalizing a Global Carbon Observing and Analysis System (www.geocarbon.net) would provide a sound basis for monitoring actual carbon fluxes and thus getting quantities right when pricing carbon – be it in a cap-and-trade scheme or under a tax regime. However, such monitoring systems are expensive and—especially in times of economic weakness—budgets for science and environmental policy are under particular scrutiny. In this study, we attempt to demonstrate the magnitude of benefits of improved information about actual carbon fluxes. Such information enables better-informed policy-making and thus paves the way for a more secure investment environment when decarbonizing the energy sector. The numerical results provide a robust indication of a positive social value of improving carbon monitoring systems when compared to their cost, especially for the more ambitious climate policies