Carbon sequestration in soils of SW-Germany as affected by agricultural management—Calibration of the EPIC model for regional simulations

Global emissions trading allows for agricultural measures to be accounted for the carbon sequestration in soils. The Environmental Policy Integrated Climate (EPIC) model was tested for central European site conditions by means of agricultural extensification scenarios. Results of soil and management analyses of different management systems (cultivation with mouldboard plough, reduced tillage, and grassland/fallow establishment) on 13 representative sites in the German State Baden-Württemberg were used to calibrate the EPIC model. Calibration results were compared to those of the Intergovernmental Panel on Climate Change (IPCC) prognosis tool. The first calibration step included adjustments in (a) N depositions, (b) N₂-fixation by bacteria during fallow, and (c) nutrient content of organic fertilisers according to regional values. The mixing efficiency of implements used for reduced tillage and four crop parameters were adapted to site conditions as a second step of the iterative calibration process, which should optimise the agreement between measured and simulated humus changes. Thus, general rules were obtained for the calibration of EPIC for different criteria and regions. EPIC simulated an average increase of +0.341 Mg humus-C ha⁻¹ a⁻¹ for on average 11.3 years of reduced tillage compared to land cultivated with mouldboard plough during the same time scale. Field measurements revealed an average increase of +0.343 Mg C ha⁻¹ a⁻¹ and the IPCC prognosis tool +0.345 Mg C ha⁻¹ a⁻¹. EPIC simulated an average increase of +1.253 Mg C ha⁻¹ a⁻¹ for on average 10.6 years of grassland/fallow establishment compared to an average increase of +1.342 Mg humus-C ha⁻¹ a⁻¹ measured by field measurements and +1.254 Mg C ha⁻¹ a⁻¹ according to the IPCC prognosis tool. The comparison of simulated and measured humus C stocks was r² ≥ 0.825 for all treatments. However, on some sites deviations between simulated and measured results were considerable. The result for the simulation of yields was similar. In 49% of the cases the simulated yields differed from the surveyed ones by more than 20%. Some explanations could be found by qualitative cause analyses. Yet, for quantitative analyses the available information from farmers was not sufficient. Altogether EPIC is able to represent the expected changes by reduced tillage or grassland/fallow establishment acceptably under central European site conditions of south-western Germany.     

Inferring linear feature use in the presence of GPS measurement error

Global Positioning System (GPS) collars are increasingly used to study animal movement and habitat use. Measurement error is defined as the difference between the observed and true value being measured. In GPS data measurement error is referred to as location error and leads to misclassification of observed locations into habitat types. This is particularily true when studying habitats of small spatial extent with large amounts of edge, such as linear features (e.g. roads and seismic lines). However, no consistent framework exists to address the effect of measurement error on habitat classification of observed locations and resulting biological inference. We developed a mechanistic, empirically-based method for buffering linear features that minimizes the underestimation of animal use introduced by GPS measurement error. To do this we quantified the distribution of measurement error and derived an explicit formula for buffer radius which incorporated the error distribution, the width of the linear feature, and a predefined amount of acceptable type I error in location classification. In our empirical study we found the GPS measurement error of the Lotek GPS_3300 collar followed a bivariate Laplace distribution with parameter ρ = 0.1123. When we applied our method to a simulated landscape, type I error was reduced by 57%. This study highlights the need to address the effect of GPS measurement error in animal location classification, particularily for habitats of small spatial extent.     

Effects of sampling error and temporal correlations in population growth on process variance estimators

Estimates of a population’s growth rate and process variance from time-series data are often used to calculate risk metrics such as the probability of quasi-extinction, but temporal correlations in the data from sampling error, intrinsic population factors, or environmental conditions can bias process variance estimators and detrimentally affect risk predictions. It has been claimed (McNamara and Harding, Ecol Lett 7:16–20, 2004) that estimates of the long-term variance that incorporate observed temporal correlations in population growth are unaffected by sampling error; however, no estimation procedures were proposed for time-series data. We develop a suite of such long-term variance estimators, and use simulated data with temporally autocorrelated population growth and sampling error to evaluate their performance. In some cases, we get nearly unbiased long-term variance estimates despite ignoring sampling error, but the utility of these estimators is questionable because of large estimation uncertainty and difficulties in estimating correlation structure in practice. Process variance estimators that ignored temporal correlations generally gave more precise estimates of the variability in population growth and of the probability of quasi-extinction. We also found that the estimation of probability of quasi-extinction was greatly improved when quasi-extinction thresholds were set relatively close to population levels. Because of precision concerns, we recommend using simple models for risk estimates despite potential biases, and limiting inference to quantifying relative risk; e.g., changes in risk over time for a single population or comparative risk among populations.     

Recruitment and attrition of associated plants under a shading crop canopy: Model selection and calibration

Associated plant and animal diversity provides ecosystem services within crop production systems. The importance of the maintenance or restoration of diversity is therefore increasingly acknowledged. Here we study the population dynamics of associated annual plants (‘weeds’) during the growth of a crop in a season and introduce a minimal model to characterize the recruitment and attrition of the associated plants under the influence of shading by the crop. A mechanistically based, logistic, light interception model was parameterized with light interception measurements in two single crops (barley and rye) and in mixtures of these cereals with peas. Population dynamics data were collected for the annuals Papaver rhoeas, Centaurea cyanus, Chrysanthemum segetum, and Misopates orontium. A minimal population dynamics model was identified for each annual plant species, using system identification techniques as model selection and calibration.     

On reducing the windfall profits in environmental subsidy programs

Investment subsidies are widely used to induce adoption of new technologies that can lower the (marginal) cost of reducing emissions. To economize on these subsidies, governments would like to distinguish between firms that need to receive a subsidy to adopt a new technology, and firms that would adopt that technology even without subsidies. We show that policies consisting of a menu of emission taxes and investment subsidies can potentially induce firms to self-select.     

Challenges of simulating complex environmental systems at the landscape scale: A controversial dialogue between two cups of espresso

With the advancement of computational systems and the development of model integration concepts, complexity of environmental model systems increased. In contrast to that, theory and knowledge about > environmental systems as well as the capability for environmental systems analyses remained, to a large extent, unchanged. As a consequence, model conceptualization, data gathering, and validation, have faced new challenges that hardly can be tackled by modellers alone. In this discourse-like review, we argue that modelling with reliable simulations of human-environmental interactions necessitate linking modelling and simulation research much stronger to science fields such as landscape ecology, community ecology, eco-hydrology, etc. It thus becomes more and more important to identify the adequate degree of complexity in environmental models (which is not only a technical or methodological question), to ensure data availability, and to test model performance. Even equally important, providing problem specific answers to environmental problems using simulation tools requires addressing end-user and stakeholder requirements during early stages of problem development. In doing so, we avoid modelling and simulation as an end of its own.     

Heavy metals in potable groundwater of mining-affected river catchments,northwestern Romania

Groundwater, accessed using wells and municipal springs, represents the major source of potable water for the human population outside of major urban areas in northwestern Romania, a region with a long history of metal mining and metallurgy. The magnitude and spatial distribution of metal contamination in private-supply groundwater was investigated in four mining-affected river catchments in Maramureş and Satu Mare Counties through the collection of 144 groundwater samples. Bedrock geology, pH and Eh were found to be important controls on the solubility of metals in groundwater. Peak metal concentrations were found to occur in the Lapuş catchment, where metal levels exceed Dutch target and intervention values in up to 49% and 14% of samples, respectively. A 700 m wide corridor in the Lapuş catchment on either side of the main river channel was identified in which peak Cd (31 μg l⁻¹), Cu (50 μg l⁻¹), Pb (50 μg l⁻¹) and Zn (3,000 μg l⁻¹) concentrations were found to occur. Given the generally similar bedrock geologies, lower metal levels in other catchments are believed to reflect differences in the magnitude of metal loading to the local environment from both metal mining and other industrial and municipal sources. Sampling of groundwater in northwestern Romania has indicated areas of potential concern for human health, where heavy metal concentrations exceed accepted environmental quality guidelines. The presence of elevated metal levels in groundwater also has implications for the implementation of the EU Water Framework Directive (WFD) and achieving ‘good’ status for groundwater in this part of the Danube River Basin District (RBD).     

Großräumige Regionalisierung der Kohlenstoffbindung in Wäldern Nordrhein-Westfalens

Background, aim and scope The United Nations Framework Convention on Climate Change understands carbon fixation in forests as an important contribution for the reduction of atmospheric pollution in terms of greenhouse gases. According to the German forest inventory on carbon in biomass an amount of 191?t C/ha was roughly estimated, without any spatial differentiation. Therefore, the aim of this investigation was to statistically identify factors that are significant for the carbon fixation and to map the spatial patterns of C sequestration in the federal state North Rhine-Westphalia. Materials and methods Together with information on climate, elevation, vegetation, and deposition, data from two forest monitoring networks were analysed statistically. Geostatistics and the decision tree algorithms Classification and Regression Trees (CART) and Chi-Square Automatic Interaction Detection (CHAID) were applied to calculate surface maps from punctual data on C in vegetation, in dead wood and in soil. Whereas spatial autocorrelation could be detected for the C loads in the humus layers, no surface maps could be calculated for the C contents of the mineral soils and for the forest trees/dead wood. Here, CART and CHAID were used to derive decision trees that were applied on available surface data to predict C loads for the entire study area. Results About 19?t C/ha could be predicted for the humus layer, 67?t C/ha for forest trees/dead wood and 90.7?t C/ha for the soil. An overall mean of 177?t C/ha was calculated for North Rhine-Westphalia lying 14?t C/ha below the German wide mean. Discussion Compared to the calculated results in another investigation a total of 68?mio. t C for the above ground dendromass was estimated. This is 11?mio. t C/ha higher than the amount calculated in this study and may be due to the fact that this value includes the C-pools in both, the brushwood and herbaceous layer in their estimations. The average C concentration in the humus layer all over Germany was found to amount for 20.7?t C/ha which is slightly above the C storage calculated for North Rhine-Westphalia. In the same study a Germany wide C average of 87.9?t C/ha was calculated which is very close to the 90.7?t C/ha calculated in this study. Conclusions The surface estimations of the C-pools in the above-ground biomass, the humus layer and the mineral soil enable to map the efficiency of the C-bounding capacity regarding the fixation of the greenhouse gas CO₂. The mean values derived in this study are in good accordance with estimations based on other techniques. Recommendations and perspectives The approach presented should be verified by application to Germany wide inventory data and by means of Regression Kriging. Furthermore, the C-fixation under climate change should be calculated by combining statistical methods and the dynamic modelling tool WASMOD.     

Eine Weight-of-Evidence-Studie zur Bewertung der Sedimentbelastung und des Fischrückgangs in der Oberen Donau

Background and aim Despite intensive and continuous stocking and improvement of water quality since the 1970s, fish populations, especially those of the grayling (Thymallus thymallus), have declined over the last two decades in the upper Danube River (Germany). In order to assess 1) possible links between molecular/biochemical responses and ecologically relevant effects, and 2) if ecotoxicological effects might be related to the decline in fish catches in the upper Danube river, sediment samples and fish were collected at different locations and analyzed using a weight-of-evidence (WOE) approach with several lines of evidence. The objective of the presentation is to introduce the conceptual framework and to review results of the ongoing study. As previously addressed by Chapman and Hollert (2006) a variety of lines of evidence can be used in WOE studies. Briefly, 1) a comprehensive battery of acute and mechanism-specific bioassays was used to characterize the ecotoxicological hazard potential. 2) Histopathological investigations and the micronucleus assay with erythrocytes were applied, analyzing in situ parameters. 3) Diversity and abundance of benthic macroinvertebrates and fish as well as 4) persistent organic pollutants, endocrine disrupting substances, limnochemical parameters and the concentration of heavy metals were recorded. To identify organic contaminants a spotential causes of sediment toxicity assays, 5) effect directed analysis was applied.