Although global pesticide use increases steadily, our field-data based knowledge regarding exposure of non-target ecosystems is very restricted. Consequently, this meta-analysis will for the first time evaluate the worldwide available peer-reviewed information on agricultural insecticide concentrations in surface water or sediment and test the following two hypotheses: I) Insecticide concentrations in the field largely exceed regulatory threshold levels and II) Additional factors important for threshold level exceedances can be quantified using retrospective meta-analysis. A feasibility study using a restricted dataset (n = 377) suggested the significance of the expected results, i.e. an threshold level exceedance rate of more than 50Prozent of the detected concentrations. Subsequent to a comprehensive database search in the peer-reviewed literature of the past 60 years, analysis of covariance with the relevant threshold level exceedance as the continuous dependent variable (about 10,000 cases) will be performed and the impact of significant predictor variables will be quantified. Parameters not yet considered in pesticide exposure assessment will be included as independent variables, such as compound class, environmental regulatory quality, and sampling design. The simultaneous presence of several insecticide compounds as a well as their metabolites will also be considered in the evaluation. The present approach may provide an innovative and integrated view on the potential environmental side effects of global high-intensity agriculture and in particular of pesticides use.
In hydrology, the relationship between water storage and flow is still fundamental in characterizing and modeling hydrological systems. However, this simplification neglects important aspects of the variability of the hydrological system, such as stable or instable states, tipping points, connectivity, etc. and influences the predictability of hydrological systems, both for extreme events as well as long-term changes. We still lack appropriate data to develop theory linking internal pattern dynamics and integral responses and therefore to identify functionally similar hydrological areas and link this to structural features. We plan to investigate the similarities and differences of the dynamic patterns of state variables and the integral response in replicas of distinct landscape units. A strategic and systematic monitoring network is planned in this project, which contributes the essential dynamic datasets to the research group to characterize EFUs and DFUs and thus significantly improving the usual approach of subdividing the landscape into static entities such as the traditional HRUs. The planned monitoring network is unique and highly innovative in its linkage of surface and subsurface observations and its spatial and temporal resolution and the centerpiece of CAOS.
The formation of biogeochemical interfaces in soils is controlled, among other factors, by the type of particle surfaces present and the assemblage of organic matter and mineral particles. Therefore, the formation and maturation of interfaces is studied with artificial soils which are produced in long-term biogeochemical laboratory incubation experiments (3, 6, 12, 18 months. Clay minerals, iron oxides and charcoal are used as major model components controlling the formation of interfaces because they exhibit high surface area and microporosity. Soil interface characteristics have been analyzed by several groups involved in the priority program for formation of organo-mineral interfaces, sorptive and thermal interface properties, microbial community structure and function. Already after 6 months of incubation, the artificial soils exhibited different properties in relation to their composition. A unique dataset evolves on the development and the dynamics of interfaces in soil in the different projects contributing to this experiment. An integrated analysis based on a conceptual model and multivariate statistics will help to understand overall processes leading to the biogeochemical properties of interfaces in soil, that are the basis for their functions in ecosystems. Therefore, we propose to establish an integrative project for the evaluation of data obtained and for publication of synergistic work, which will bring the results to a higher level of understanding.
Landscape and soil changes are strongly coupled to chemical and physical (erosion) weathering and soil production. The erosion rate is preserved in the signal of cosmogenic nuclides (e.g., 10Be) in stream sediments or even directly in a soil profile. The genesis of clastic sediments and soils has been investigated to quantify processes occurring within source areas and catchments, including chemical and physical weathering, and textural and compositional modification of detritus during transition from bedrock to grus and thereafter to soil or a fluvial environment. Well-defined (or -controlled) settings are however needed to calculate mass balances for a given (tectonically active) catchment. Measurements of mid- to long-term erosion rates have recently become more widely available through cosmogenic nuclide techniques. Still, new approaches can be developed to improve our understanding of weathering processes and their rates. Ideal settings and a considerable dataset about mineral weathering are given for the Sila massif in southern Italy (and consequently in a Mediterranean environment). It represents a tectonically active area. The upland plateaus consist of old planation surfaces, bordered by steep slopes, and are characterised by granitic spheroidal boulders which form wide boulder fields. The combination of the major tectonic and relief features with typical upland Mediterranean climate conditions promoted the triggering of severe erosion, that led to the exhumation of the boulders. Data about soil erosion amounts and rates related to the soil formation period would complete the puzzle of the driving forces and enable a more detailed interpretation of landscape and soil evolution. These boulders seemed to 'grow' out of the surface with time. Consequently, by measuring the 10Be content at different levels along a rock boulder (from the soil surface to the top of boulders), the age(s) of exposure could be derived and subsequent total denudation rates will be obtained. This would be an elegant way to calculate erosion rates for different time-steps that cover almost the entire period of soil evolution. Such an approach would give insight into a) the overall denudation and erosion rates over the whole (potential) soil formation period and b) erosion and denudation rates during time segments and would allow for the distinction of different erosion phases during the Pleistocene and Holocene c) volumes of loose material that were removed from the uplands and entered the drainage river system in this time span. (...)
The goal of this study was to enable a prognosis on the future rainfall conditions of the Nile Equatorial Lakes regions by delivering time-series of monthly rainfall sums for the time-period from 2021 to 2050 that can be used for all kinds of applications. One example might be the dimensioning of hydraulic structures. In these very long lasting investments, future climatic conditions have to be considered during present planning and construction.The principal sources of information on future climate conditions are General Circulation Models (GCMs). These are physically based atmospheric models that resemble a numerical weather prediction system but on a much coarser scale. This forecast cannot be perfect. Especially, it cannot predict single values, e. g. if January 2050 will be rather wet or dry, but only climatic references, i.e. state, if Januaries in general will become wetter or dryer in the future. Even if the predictions of a GCM were perfect, its output could not be used directly for hydrological purposes, due to its coarse resolution. The monthly precipitation values that are provided by the GCM present the spatially averaged precipitation over a grid cell of several thousand square kilometres. This 'block rainfall' can differ significantly from rainfall measured at the ground. Rain gauges are influenced by local effects like micro climatic conditions or orographic effects of mountain ranges that GCMs are not able to resolve.This study combined the information from different data sources. As global trend information, monthly precipitation values from two GCMs (ECHAM5 and HadCM3) were used. Three CO2-emission scenarios (A1b, A2 and B1) were considered in this data. As local ground reference observed monthly rainfall sums from several rain gauges in East Africa as well as from three reanalysis projects (Climate Research Unit, University of Delaware and GPCC) were used.At each rain gauge or observation point in the reanalysis a technique called 'Quantile-Quantile-Transformation' was applied to establish a relationship between the Cumulative Distribution Function (CDF) of the GCMs and that of the ground references during the calibration period from 1961-1990. The CDFs were fitted by non-parametric Kernel-Smoothing. To account for potential shifts in the annual cycles of GCMs and ground references, the transformations was done separately for each month.Assuming that the relation between Global Model and local response will be constant in the future, the global predictions of the GCM can be downscaled to local scale, leading to future rainfall scenarios that are coherent with observed past rainfall.Combining the data from three CO2-emission scenarios of two GCM with three reanalysis data sets, an ensemble of 18 different rainfall time-series was created for each observation point. The range of this ensemble helps to estimate the possible uncertainties in the prognosis of future monthly precipitation sums from 2021 to 2050.
We intend to investigate the molecular mechanisms of mineral nutrient dependent poplar physiology with special focus on potassium. This will be accomplished using two different approaches. 1. Molecular biology: We will study the regulation of ion channels and transporters by different environmental conditions, such as the effect of nutrition, salt, hormonal action, cold and drought during wood production and the dormancy-growth transitions. Phenotype analysis of transporter sense/antisense plants will be used to gain insights into the role of the transporters in tree physiology. On the basis of a laser-micro-dissection system, we will be able to prepare cDNA of distinct cell types and generate subtractive cDNAs to determine genes, specific for the differentiation of vessels and bast fibers. 2. Electrophysiological investigations: We will compare the functional properties of the transporters. Ion-fluxes and transporters, involved in cambial activation will be characterized in vivo and in vitro. The response to changes in e.g. the extracellular medium in vitro, will provide a measure for the regulation of ion transport by apoplastic factors in vivo. Based on this data sets we should be able to establish a model on the seasonal fluxes of potassium in relation to the transporter properties and dynamics in the context of tree physiology in general and xylogenesis in particular.
The Earth's climate is changing as a response to anthropogenic emissions of fossil fuels, and is very likely to do so over the next decades to centuries. The projected changes from multiple numerical climate models differ significantly, because some feedbacks and processes are poorly understood or cannot be resolved in the models. Yet a quantitative picture of the uncertainty associated with the expected changes on regional and global scales is crucial, in order to quantify impacts, and decide on adaptation and mitigation measures. The objective of this project is to assess the uncertainty in large-scale regional to global climate change projections based on the CMIP3 dataset, a collection of simulations of about twenty global climate models coordinated for the recent IPCC report. While the amount of data produced by climate models and the desire for ever more detailed projections and probabilistic information is growing rapidly, there is a lack of understanding on how to define the skill of a climate model for a forecast that in practice cannot be verified. So far, models are often averaged regardless of their ability to satisfy even basic requirements, and the community is reluctant to define a set of metrics that would seem important for a model to be credible. Also, a consensus of uncertainty in climate change projections on regional to global scales is missing. We propose to develop a framework to evaluate climate models for their suitability in predicting changes by a set of metrics that are important to be simulated correctly from a physical point of view, rather than comparing present day simulations to observations. In addition, by treating one model M as observations, statistical methods can be used to find optimal predictors and to define model weight, such that a weighted mean or a probabilistic method using the rest of the models can best predict M. The issue of common model error and model dependence will be addressed. We also propose novel methods to aggregate results in regional averages using clustering techniques, and a more flexible approach to communicating results using climate change indices. As milestones of the project, we will attempt to answer the following questions: How large are the uncertainties of model projections on different spatial and temporal scales? On what spatial scale can the current models provide robust information? How can we quantify model performance for projections, and use that to define model weight? Is a small set of 'good' models more useful than a large number of 'good' and 'bad' models? How do model dependence, common biases, and overconfidence affect projection uncertainties? How can we attach confidence to climate change indices? The proposed work combines efforts in climate research and statistics. The results will be used in improving a Bayesian hierarchical model to generate probabilistic climate change information for the spatial scales on which .
A lysimeter is a vessel containing soil placed with its top edge to the ground surface. Lysimeter are used to study phases of the hydrological cycle in terms of water content and dynamics, e.g. infiltration, evapotranspiration or runoff. Lysimeter provide a good alternative to carry out and test various methods or theoretical theories under relative undisturbed circumstances. In cooperation with the Institute of Chemistry and Dynamics of the Geosphere, IV Agrosphere (ICG-IV) of the Forschungszentrum Jülich GmbH, the solute transport inside a lysimeter ought to be investigated.To avoid the inevitable problem of the boundary conditions for electromagnetic geophysical methods of a normal lysimeter with its metal wall, an alternative had to be found. Therefore PVC-cylinders were chosen with 1.5 m height and 1.2 m diameter. The dielectric permittivity of soils depends strongly on the water content. Therefore, GPR was used as it can provide non-invasive high-resolution information regarding the distribution of the dielectric permittivity of a heterogeneous medium. Because the used lysimeter has PVC walls tomographic measurements can be performed. Considering the relatively small dimensions of the lysimeter (1.2m diameter, 1.5m height) and the armament with sensors for other methods, a pair of shielded antennas was chosen with centre frequencies of approx. 750 MHz. In April and September 2002 first measurements were carried out on a filled but unequipped lysimeter to check signal quality, feasibility as well as the needed time to gather a dataset under ideal conditions. Furthermore pot irrigation tests were made in 2002 and 2004 to estimate the actual resolution with the available equipment. To derive the volumetric water content, the calculated dielectric permittivity values have to be transformed. Based on the soil inside the lysimeter (approx. 80% sand, 15% silt and 5% clay with approx. 40% porosity) appropriate mixing formulas for bulk dielectric permittivity have to be chosen and compared to the results gathered from alternative methods.
Satellite measurements strongly contribute to the understanding of the processes related to stratospheric ozone loss, e.g. by global and long term monitoring of ozone and its depleting substances. For instance, measurements performed in limb geometry by SCIAMACHY on ENVISAT largely improved the knowledge about the vertical distribution of species like BrO and OClO only recently. However, there are still important open questions, like e.g. the chlorine activation processes on different kinds of aerosols and polar stratospheric clouds. Also, the role of very short lived species in the stratospheric bromine budget or the effects of a possible enhancement of the Brewer-Dobson circulation are not fully understood.Globally, the vertical distribution of ozone depleting species varies significantly in space and time due to solar illumination, atmospheric chemistry and transport. Especially strong gradients occur near the twilight zone or across stratospheric transport barriers (polar vortex boundary, subtropical transport barriers). These regions are of particular importance for chemistry and transport of the lower stratosphere and upper troposphere, since they separate air masses on large scales but also enable exchange between them.Standard 1-D profile retrievals, which assume horizontal homogeneity, result in large systematic biases due to neglecting the effect of horizontal gradients on the measurement. We propose to develop, improve and apply a tomographic profile retrieval algorithm, which optimally combines the information provided by the SCIAMACHY limb and nadir measurements. An improved global dataset of 3D stratospheric profiles for NO2, BrO and OClO for the 10 years of the SCIAMACHY mission (2002-2012) will be developed, compared to atmospheric chemistry simulations and applied to selected questions of atmospheric science. The dataset developed in this project will be very useful for investigating the complex interplay of stratospheric chemistry and transport processes, and will help to reduce the uncertainties in the distribution of ozone depleting species, in particular for regions with large horizontal inhomogeneity.
The HGF Alliance 'Remote Sensing and Earth System Dynamics' aims at the development and evaluation of novel bio/geo-physical information products derived from data acquired by a new generation of remote sensing satellites; and their integration in Earth system models for improving understanding and modelling ability of global environmental processes and ecosystem change. The Earth system comprises a multitude of processes that are intimately meshed through complex interactions. In times of accelerated global change, the understanding and quantification of these processes is of primary importance. Spaceborne remote sensing sensors are predestined to produce bio-geo-information products on a global scale. The upcoming generation of spaceborne remote sensing configurations will be able to provide global data sets and products with unprecedented spatial and temporal resolution in the context of a consistent and systematic observation strategy. The integration of these data sets in existing environmental and climate science components will allow a new global view of the Earth system and its dynamics, initiating a performance leap in ecosystem and climate change modelling.
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