Exploratory Analysis and a Stochastic Model for Humusdisintegration

Ulrich (1981) supposes in the hypothesis of humusdisintegrationthat the balance between polymerisation and breakdown of organicmaterial may be disturbed in chemically well buffered Europeanforest soils. This new aspect of aluminium toxicity may causenitrogen exceedance in forest ecosystems and subsequent seasonalnitrate output (Eichhorn and Hütterman, 1999).In a research program the substances in the seepage water aremonitored in a small woodland in central Germany. We explorethese multivariate data for examining possible influences on theprocess of humusdisintegration and its temporal evolution. As aresult, a regression model for carbon is developed, whichincludes covariables, i.e., other substances, as well as spatialand temporal terms describing systematic variability. Especiallyiron and aluminium turn out to be very influential in the model.So far our work is a basic step for monitoring the seepage waterdata by means of stochastic modelling.     

Gull eggs--food of high organic pollutant content?

A wide range and occasionally high levels of persistent organic pollutants (POPs) are reported in Arctic regions, especially among top predators. Polar bears (Ursus maritimus), arctic foxes (Alopex lagopus) and some gull species (Larus spp.) often have high levels of these fat-soluble pollutants. Gulls deposit significant levels of these contaminants in their eggs. In northern regions, gull eggs are part of the traditional human diet. In the present study we have investigated the levels of POPs in gull eggs in order to determine the tolerable weekly intake (TWI) for humans. Concentrations of polychlorinated biphenyls (PCBs), polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) were measured in 214 gull eggs collected in the spring of 2001-02. The eggs were collected from four gull species (herring gulls (Larus argentatus), great black-backed gulls (L. marinus), lesser black-backed gulls (L. fuscus) and glaucous gulls (L. hyperboreus)) at 12 different locations in Northern Norway, on the Faroe Islands and on Svalbard. The pollutant levels in gull eggs were found to be 65.5 +/- 26.9 pg toxic equivalent (TE) for dioxin and PCB g(-1) wet weight. Based on these findings and the TWI-value determined by the EU Scientific Committee on Food it is advised that children, young women and pregnant and nursing women should not eat gull eggs. Other people should limit their intake of eggs to an absolute minimum, considering the health risks associated with gull egg intake.     

A hybrid modeling approach to resolve pollutant concentrations in an urban area

A modeling tool that can resolve contributions from individual sources to the urban environment is critical for air-toxics exposure assessments. Air toxics are often chemically reactive and may have background concentrations originated from distant sources. Grid models are the best-suited tools to handle the regional features of these chemicals. However, these models are not designed to resolve pollutant concentrations on local scales. Moreover, for many species of interest, having reaction time scales that are longer than the travel time across an urban area, chemical reactions can be ignored in describing local dispersion from strong individual sources making Lagrangian and plume-dispersion models practical. In this study, we test the feasibility of developing an urban hybrid simulation system. In this combination, the Community Multi-scale Air Quality model (CMAQ) provides the regional background concentrations and urban-scale photochemistry, and local models such as Hybrid Single Particle Lagrangian Integrated Trajectory model (HYSPLIT) and AMS/EPA Regulatory Model (AERMOD) provide the more spatially resolved concentrations due to local emission sources. In the initial application, the HYSPLIT, AERMOD, and CMAQ models are used in combination to calculate high-resolution benzene concentrations in the Houston area. The study period is from 18 August to 4 September of 2000. The Mesoscale Model 5 (MM5) is used to create meteorological fields with a horizontal resolution of 1×1 km². In another variation to this approach, multiple HYSPLIT simulations are used to create a concentration ensemble to estimate the contribution to the concentration variability from point sources. HYSPLIT simulations are used to model two sources of concentration variability; one due to variability created by different particle trajectory pathways in the turbulent atmosphere and the other due to different flow regimes that might be introduced when using gridded data to represent meteorological data fields. The ensemble mean concentrations determined by HYSPLIT plus the concentrations estimated by AERMOD are added to the CMAQ calculated background to estimate the total mean benzene concentration. These estimated hourly mean concentrations are also compared with available field measurements.     

Postgraduale Weiterbildung, Nachwuchsf?rderpreis 2005, Jahrestagung 2006 in Landau

Ohne Zusammenfassung     

斯瓦尔巴特群岛--寒冷海岸的土地

威廉·巴伦支1596年登上斯瓦尔巴特群岛时.他发现岛上没有一座现代建筑,是他开启了这个群岛的现代史。荷兰的航海家门把这个群岛称为斯匹次卑尔根群岛。他们也并不知道古代著述中提到的斯瓦尔巴特群岛——寒冷海岸的土地.可能早在1194年就已被北欧的海盗们发现了。古代冰岛的文献中讲到”洋底北部”的土地有四天的航海路程.它是格陵兰群岛的一部分。     

Pulse emissions of N2O and CO2 from an arable field depending on fertilization and tillage practice

Nitrous oxide (N₂O) emissions from soil are characterized by strong emission pulses. Although several mechanisms are known to create them, pulses are difficult to predict. Currently there is no established systematic way to identify pulses from long-term static chamber measurement results. In this study we suggest a simple algorithm for pulse identification. The algorithm was applied on time series of N₂O and carbon dioxide (CO₂) fluxes from a field study on the long-term impact of fertilization and tillage practice. Between 4 and 9% of N₂O values were pulse values; 20-60% of total emission was emitted as pulses. Minimum tillage resulted in more pulses than plowing. In contrast, long-term averages of N₂O losses from nitrogen (N) fertilizer were similar (3-4%) for all management practices. N₂O emissions per crop yield for increased fertilization practice were double the values for reduced fertilization practice independent of tillage practice. CO₂ emission pulses were scarce and there was no significant effect of management practice on CO₂ pulse probability.     

Metalle und Stickstoff angereichert in Moosen Sachsens

Background, aim and scope Since 1990 the UN ECE Heavy Metals in Mosses Surveys provide data inventories of the atmospheric heavy metal bioaccumulation across Europe. In the survey 2005 the nitrogen (N) accumulation was measured for the first time in most of the participating countries. In Germany, the surveys were conducted in close cooperation of the relevant authorities of both the Federal Republic and the sixteen states. Therefore, statistical evaluations of the moss survey data with regard to the whole German territory and single federal states are of interest. This article concentrates on Saxony, dealing with the mapping of the spatiotemporal trends of metal accumulation from 1990 to 2005, the spatial patterns of nitrogen accumulation in 2005, and the spatial variability of bioaccumulation due to characteristics of the sampling sites and their surroundings. Exemplified for Cadmium (Cd), Mercury (Hg) and Lead (Pb) the metal loads in mosses are furthermore related to modelled deposition data provided from the European Monitoring and Evaluation Programme (EMEP). Materials and methods In Saxony Pleurozium schreberi (1990, 1995 most frequent moss species, thereafter second most), Hypnum cupressiforme (1990, 1995 second most, thereafter most frequent moss species), Scleropodium purum and Brachytecium rutabulum (1995, 2000) were sampled at up to 83 sites. All sampling sites were described with regard to topographical and ecological characteristics and several criteria to be fulfilled according to the guideline. Together with the measurements this metadata was combined with other information regarding land use in the surroundings of the sampling sites in the WebGIS MossMet. The spatial structure of the metal bioaccumulation was analysed and modelled by variogram analyses and then mapped by applying different kriging techniques. Furthermore, multi metal indices (MMI) were derived for both the sampling sites and raster maps with help of percentile statistics: The MMI_1990–2005 was calculated for arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), iron (Fe), nickel (Ni), lead (Pb), titanium (Ti), vanadium (V) and zinc (Zn). The statistical association of the metal bioaccumulation, site specific characteristics as well as information on land use and emissions was analysed by bivariate nonparametric correlation analysis, contingency tables and Classification and Regression Trees (CART). Results The results of the quality controlled chemical analyses show a decrease of the metal bioaccumulation in Saxony from 1990 to 2000. From 2000 to 2005?a significant increase can be stated for As, Cr, Cu, Fe, Ti and V. The element loads of Cd, Hg, Pb and Sb show a decreasing, although non significant, tendency. The MMI_1990–2005 decreased significantly from 1990 to 2000 and increased significantly from 2000 to 2005. The N concentration in mosses in Saxony reaches from 1.36 to 1.96?% in dry mass showing significant correlations to the agriculture density (+), the height of the surrounding trees (+), altitude (–) and the precipitation sum for the accumulation period (–). The ratios of forests around the monitoring sites show a negative correlation to all elements but for Pb, Sb and V. Unlike Cd the moss loads of As, Cr, Cu, Fe, Hg, Ni, Pb, Ti and V are positively correlated to the density of urban areas calculated from the Corine Landcover map 2000. The same holds true for Cr, Cu Fe and Ni regarding traffic density and Cd, Cu, Hg and Ni regarding agricultural density. The precipitation sum within the accumulation period is positively correlated with As, Cd, Cr (1990–2000), Ni, Pb, Sb und V, negatively with Cr (2005), Cu, Fe and Zn. Regarding altitude a similar tendency can be observed. The slope gradient shows significant association to Cd, Cu, Ni and Pb. Regarding the canopy effect negative correlation coefficients were calculated for As, Pb and Sb regarding the distance of the sampling site to the nearest tree crowns and positive correlations were calculated for Cd, Cr, Fe and Sb with respect to the height of the surrounding trees. The distance of the moss site to human settlements is significantly related to As, Cd, Cr, Hg, Ni, Pb and Sb. The impact of traffic becomes apparent for As, Cr, Cu, Ni, Pb, Sb, V and Zn which are all negatively correlated with the distance of the moss site to the nearest road. The multivariate statistical CART analysis identifies the urban land use density in a radius of 5?km around the sampling site as well as the height of surrounding trees as the statistically most significant factors for the Cu concentrations in mosses sampled in 2005. The modelled total deposition of Cd, Hg and Pb (EMEP) and the respective concentrations in Saxon mosses are correlated significantly (1995 Hg: r _s = 0.62, p = 0.004; 2005 Cd: r _s = 0.43, p = 0.07, Hg: r _s = 0.44, p = 0.06, Pb: r _s = 0.39, p = 0,099). Discussion Unlike in e.?g. Baden-Württemberg the metal accumulation in mosses in Saxony increased between 2000 and 2005, Cr thereby increased dramatically. For Cd, Hg and Pb it could be shown that the metal loads in mosses are significantly correlated to the modelled total deposition provided by EMEP. Nevertheless, this does not hold true for all elements in all campaigns. Taking this into account, it can be verified that positive relationships between the metal bioaccumulation and the deposition for Saxony exist. Conclusions Contrary to deposition measurements that exhibit a higher temporal resolution the moss surveys provide measurement data on a wide range of elements. Some of these elements are important with regard to human-toxicological aspects (e.?g. Al, As, Hg, Sb, V). The standardised biomonitoring of atmospheric pollution with mosses is an important link between the technical acquisition of depositions and the accumulation in biological material. To claim that the element concentrations in mosses and in the deposition should correlate to a high degree is not appropriate since both approaches are physically related but are not identical. The degree of correlation thereby depends on the boundary conditions of the physical processes, like regional and site-specific meteorological conditions within the accumulation period, the vertical and horizontal vegetation structure or land use conditions. Recommendations and perspectives The Heavy Metals in Mosses Surveys are a positive example for environmental monitoring activities reaching across three spatial and administrative levels: regional (e.?g. federal state or natural landscape), nation wide (e.?g. Germany) and continental (e.?g. Europe). It can therefore be claimed that the moss survey is the only environmental monitoring network that provides high density and surface covering information on the metal and N exposition of near-natural and agricultural ecosystems. The correlations of the metal bioaccumulation and the modelled deposition should therefore be used to complement the deposition measurement activities across Europe.     

Combined effects of life-history traits and human impact on extinction risk of freshwater megafauna

Megafauna species are intrinsically vulnerable to human impact. Freshwater megafauna (i.e., freshwater animals ≥30 kg, including fishes, mammals, reptiles, and amphibians) are subject to intensive and increasing threats. Thirty-four species are listed as critically endangered on the International Union for Conservation of Nature (IUCN). Red List of Threatened Species, the assessments for which are an important basis for conservation actions but remain incomplete for 49 (24%) freshwater megafauna species. Consequently, the window of opportunity for protecting these species could be missed. Identifying the factors that predispose freshwater megafauna to extinction can help predict their extinction risk and facilitate more effective and proactive conservation actions. Thus, we collated 8 life-history traits for 206 freshwater megafauna species. We used generalized linear mixed models to examine the relationships between extinction risk based on the IUCN Red List categories and the combined effect of multiple traits, as well as the effect of human impact on these relationships for 157 classified species. The most parsimonious model included human impact and traits related to species’ recovery potential including life span, age at maturity, and fecundity. Applying the most parsimonious model to 49 unclassified species predicted that 17 of them are threatened. Accounting for model predictions together with IUCN Red List assessments, 50% of all freshwater megafauna species are considered threatened. The Amazon and Yangtze basins emerged as global diversity hotspots of threatened freshwater megafauna, in addition to existing hotspots, including the Ganges-Brahmaputra and Mekong basins and the Caspian Sea region. Assessment and monitoring of those species predicted to be threatened are needed, especially in the Amazon and Yangtze basins. Investigation of life-history traits and trends in population and distribution, regulation of overexploitation, maintaining river connectivity, implementing protected areas focusing on freshwater ecosystems, and integrated basin management are required to protect threatened freshwater megafauna in diversity hotspots.     

Gradient forests: calculating importance gradients on physical predictors

In ecological analyses of species and community distributions there is interest in the nature of their responses to environmental gradients and in identifying the most important environmental variables, which may be used for predicting patterns of biodiversity. Methods such as random forests already exist to assess predictor importance for individual species and to indicate where along gradients abundance changes. However, there is a need to extend these methods to whole assemblages, to establish where along the range of these gradients the important compositional changes occur, and to identify any important thresholds or change points. We develop such a method, called "gradient forest," which is an extension of the random forest approach. By synthesizing the cross-validated R2 and accuracy importance measures from univariate random forest analyses across multiple species, sampling devices, and surveys, gradient forest obtains a monotonic function of each predictor that represents the compositional turnover along the gradient of the predictor. When applied to a synthetic data set, the method correctly identified the important predictors and delineated where the compositional change points occurred along these gradients. Application of gradient forest to a real data set from part of the Great Barrier Reef identified mud fraction of the sediment as the most important predictor, with highest compositional turnover occurring at mud fraction values around 25%, and provided similar information for other predictors. Such refined information allows for more accurate capturing of biodiversity patterns for the purposes of bioregionalization, delineation of protected areas, or designing of biodiversity surveys.