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.
Objective: Integrated assessment and energy-economy models have become central tools for informing long-term global and regional climate mitigation strategies. There is a large demand for improved representations of complex system interactions and thorough validation of model behaviour in order to increase user confidence in climate policy assessments. ADVANCE aims to respond to this demand by facilitating the development of a new generation of integrated assessment models. This will be achieved by substantial progress in key areas where model improvements are greatly needed: end use and energy service demand; representation of heterogeneity, behaviour, innovation and consumer choices; technical change and uncertainty; system integration, path dependencies and resource constraints; and economic impacts of mitigation policies. In the past, methodological innovations and improvements were hindered by the unavailability of suitable input data. The ADVANCE project will make a large and coordinated effort to generate relevant datasets. These datasets, along with newly developed methodologies, will be made available to the broader scientific community as open-access resources. ADVANCE will also put a focus on improved model transparency, model validation, and data handling. A central objective of ADVANCE is to evaluate and to improve the suitability of models for climate policy impact assessments. The improved models will be applied to an assessment of long-term EU climate policy in a global context, and disseminated to the wider community. The ADVANCE consortium brings together long-standing expertise in integrated assessment and energy-economy modelling with a strong expertise in material flows, energy system integration, and energy service demand.
Farm households, whose living standard largely depend on the successful management of natural resources, have a low per capita income and are in danger of further impoverishment due to unsustainable resource management. Investigations in the first phase confirmed the hypothesis. A great number of farms were analyzed and clustered in representative types in both countries. Sustainability was measured using a sustainability index, which indicates tremendous environmental effects and variation between individual farms and ethnic groups.Sub-project G1.1 will follow three major tasks. The first is to evaluate sustainability strategies on the farm and farming system level, as it was done in the previous phase, but on the basis of a significantly extended data base. The second is to aggregate farm household data to the regional level. For this, a comparative-static approach is chosen. The third is to develop a multi-agent-based simulation model. Multi-agent simulation models (MAS) as well as GIS-tools are gaining increasing importance as tools for simulating future agriculture resource use, since they allow the integration of a wide range of different stakeholder's perceptions. It becomes possible to simulate the dynamic effects of changing land use patterns, environmental policy options, and technical innovation together with environmental constraints and structural change issues. The MAS approach is used to model heterogeneous farm-household and political decision makers perspectives by capturing their socio-economic, environmental, and spatial interactions explicitly. The integration of economic and spatial processes facilitates the consideration of feedback effects and the efficient use of scarce land resources. The simulation runs of the model will be carried out with a socio-economic and GIS data set, which is provided by the previous project phase in the attempt to generate effective ways of land use resource management. Land use efficiency is strongly influenced by the overall land allocation policy analyzed in project F1. Therefore, this is an important area further integrated research using MAS in combination with GIS as modeling tools.To achieve a continuous integration of results in the best possible way, a computer-based discussion/communication platform is developed. This serves as the conceptual basis for the development of the final multi-agent simulation model. Results of the discussion/communication platform and the agent-based simulation model will continuously be passed on to downstream sub-projects to be integrated into the ongoing research activities.
The research is carried out in cooperation with KU Leuven, Forschungszentrum Jülich and Kasetsart University in Bangkok, Thailand, and aims at improving our understanding of how spatial variability in soil properties and vegetation characteristics control water flow and transport processes in the soil at the field scale, and how it determines resource use efficiency of agro-ecosystems. It focuses on the spatio-temporal dynamics of water contents and competition for water uptake in mixed cropping systems. The emphasis is on spatial variation that is caused by the cropping pattern and landscape. To this end, a set of monitoring techniques will be used with which spatial patterns of crop status and subsurface soil water contents can be imaged in a non-invasive manner. Soil water content distributions will be determined using geophysical methods: electrical resistivity tomography and time domain reflectometry. The state of the crop and its spatial pattern will be monitored using leaf area index (LAI) sensors and an infrared camera. These techniques will be complemented with 13C stable isotope analysis of plants, which is a measure of the integrated stress of the plant over the growing season. In order to interpret the obtained datasets, a soil-crop model will be developed which considers light interception, photosynthesis and stomatal control, water flow within the plant, root growth and root water uptake, and heat fluxes within the canopy in more detail than in currently available crop growth models.
The goal of the proposal is to explore the structure and functioning of metacommunities in ecological compensation areas at a multi-trophic level. First, we will assess the effect of plant diversity and herbivore and/or predator exclusion on metacommunity functioning in sown wildflower strips. We will document the communities inhabiting these experimental plots, paying attention at interactions between species, and with consideration of larger consumers linking these habitats with the surrounding matrix. Second, we will explore the relationship between various measures of the environment (isolation, habitat size) and descriptors of the metacommunities (diversity, composition, abundances, and productivity of various taxonomic groups, food-web structure, temporal variability, local invasions and extinctions). Third, using a high-quality dataset on quantitative food webs and the present data, we will conduct meta-analyses to test various models of community organisation (neutral models of biodiversity, species-area relationship in trophic levels, regional similarity hypothesis, food-web structure). Fourth, we will develop various models describing food-web structure and metacommunities dynamics. We will synthesize our results to develop a theory of 'meta food-webs'. Fifth, we will apply the gained knowledge to improve current agri-environment schemes. The study of species interactions in spatially structured metacommunities is comprehensive and global. As such, this project has a strong potential to provide fundamental insight into conservation biology. This project is multidisciplinary, putting together practitioners, ecologists and mathematicians, and is expected to yield important results both of fundamental and conservation relevance. We will use various methodologies to reach our goals. For the first part, we will set up an experiment with replicated sown wildflower strips where plant species richness and the abundance of major predators (foxes and birds of prey) and/or of major herbivores (voles and slugs) will be controlled (balanced incomplete block design). The other parts will rely on classical meta-analyses, multivariate statistics, and mathematical modelling. For the latter part, we will develop stochastic models to explore the dynamics of communities.
One unsolved problem of the micrometeorological community is the unclosed energy balance when its components are independently measured in the field. This so-called energy balance closure gap was investigated with focus on sinks and sources (storage change terms) and on the uncertainties involved in the estimation of the available energy. The second main topic was the assessment of the non-turbulent fluxes of sensible heat and latent heat as well as the horizontal turbulent flux in case of sensible heat. These fluxes are commonly neglected as their assessment is difficult. The third main point was the comparison of advective fluxes of sensible heat and carbon dioxide with the aim to facilitate an easier assessment of the advective fluxes of carbon dioxide. Analyses were based on the ADVEX- and the MORE II-dataset. For the investigated sites it could be shown that the energy balance closure improved when the storage terms were carefully considered. An inspection of the uncertainties involved in the available energy revealed that these uncertainties cannot explain the lack of energy balance closure alone. An inclusion of the non-turbulent advective fluxes of latent heat and sensible heat changed the corresponding budgets and improved the energy balance closure partly. However, residuals did not vanish. The horizontal turbulent flux divergence of sensible heat turned out to be negligible for the investigated site and time period. The comparison of the non-turbulent advective fluxes of sensible heat and carbon dioxide showed that advective fluxes of both scalars are larger during night than during day and that they both share a considerable scatter. On a mean diurnal basis, the advective fluxes of sensible heat and carbon dioxide turned out to be of opposite sign especially during night.
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.