Eier der Flußseeschwalbe (Sterna hirundo) als Indikator für die aktuelle Belastung von Rhein, Weser und Elbe mit Umweltchemikalien

In 1995, common tern (Sterna hirundo) eggs from the big German rivers, the Rhine, Weser and Elbe were collected to study the contamination with organochlorines and mercury. We found distinct differences between the rivers: common tern eggs from the Rhine had higher concentrations of PCBs and HCHs, while eggs from the Elbe had higher residues of DDT, HCB and mercury. Also toxic PCB congeners had higher residue levels in the Rhine. Considering all organochlorines, samples from the Rhine also had the highest concentrations, while those from the Elbe were the lowest. With 5.7 μg×g^?1 fresh weight, the ΖCBs had a level endangering breeding success. Fish eating birds should be used as indicators of the contamination of the rivers with environmental chemicals and should be included in monitoring programmes.     

Modelling and assessment of South African elephant Loxodonta africana population persistence

The use of a quantitative population growth model to investigate the persistence of South African elephant populations is explored. The model provides quantitative assessments of population persistence and confidence intervals for estimated parameters based purely on population size estimates. The analysis supports the view that most of the larger populations in the region are secure. This view is further supported by a lack of density dependent effects in most of the recovering populations and the high population rates of increase observed. This predominantly positive prognosis is in contrast with that emerging from most of the rest of the African continent where the populations are under greater threat because of habitat restriction and direct human conflict. This preliminary assessment of elephant population persistence suggests that “viable” populations may lie between 400 and 6000 individuals. Although not inconsistent with information-greedy genetic and demographic models, the relationship between population growth versus genetic and demographic models should be further investigated. The implementation of a metapopulation management strategy towards these smaller populations is advocated. In addition, as all of the populations included in this analysis have been afforded some degree of protection since the 1920s, continued protection would be a prerequisite for their continued survival.     

METHODOLOGIES FOR CALIBRATION AND PREDICTIVE ANALYSIS OF A WATERSHED MODEL1

ABSTRACT: The use of a fitted parameter watershed model to address water quantity and quality management issues requires that it be calibrated under a wide range of hydrologic conditions. However, rarely does model calibration result in a unique parameter set. Parameter nonuniqueness can lead to predictive nonuniqueness. The extent of model predictive uncertainty should be investigated if management decisions are to be based on model projections. Using models built for four neighboring watersheds in the Neuse River Basin of North Carolina, the application of the automated parameter optimization software PEST in conjunction with the Hydrologic Simulation Program Fortran (HSPF) is demonstrated. Parameter nonuniqueness is illustrated, and a method is presented for calculating many different sets of parameters, all of which acceptably calibrate a watershed model. A regularization methodology is discussed in which models for similar watersheds can be calibrated simultaneously. Using this method, parameter differences between watershed models can be minimized while maintaining fit between model outputs and field observations. In recognition of the fact that parameter nonuniqueness and predictive uncertainty are inherent to the modeling process, PEST's nonlinear predictive analysis functionality is then used to explore the extent of model predictive uncertainty.     

THE VULNERABILITY OF WETLANDS TO CLIMATE CHANGE: A HYDROLOGIC LANDSCAPE PERSPECTIVE1

ABSTRACT: The vulnerability of wetlands to changes in climate depends on their position within hydrologic landscapes. Hydrologic landscapes are defined by the flow characteristics of ground water and surface water and by the interaction of atmospheric water, surface water, and ground water for any given locality or region. Six general hydrologic landscapes are defined; mountainous, plateau and high plain, broad basins of interior drainage, riverine, flat coastal, and hummocky glacial and dune. Assessment of these landscapes indicate that the vulnerability of all wetlands to climate change fall between two extremes: those dependent primarily on precipitation for their water supply are highly vulnerable, and those dependent primarily on discharge from regional ground water flow systems are the least vulnerable, because of the great buffering capacity of large ground water flow systems to climate change.     

Reverse logistics in the Brazilian construction industry

In Brazil most Construction and Demolition Waste (C&D waste) is not recycled. This situation is expected to change significantly, since new federal regulations oblige municipalities to create and implement sustainable C&D waste management plans which assign an important role to recycling activities. The recycling organizational network and its flows and components are fundamental to C&D waste recycling feasibility. Organizational networks, flows and components involve reverse logistics. The aim of this work is to introduce the concepts of reverse logistics and reverse distribution channel networks and to study the Brazilian C&D waste case.     

Respiration and lipid content of the Arctic copepod<Emphasis Type="Italic"> Calanus hyperboreus</Emphasis> overwintering 1 m above the seafloor at 2,300 m water depth in the Fram Strait

In August 2000 high concentrations of the dominant herbivorous copepod Calanus hyperboreus were detected in the Arctic Fram Strait, west of Spitsbergen, 1 m above the seafloor at 2,290 m water depth. Individuals from that layer were sampled by a hyper-benthic net attached to the frame of an epi-benthic sledge. For comparison, the vertical distribution of C. hyperboreus in the water column was studied simultaneously by a multiple opening/closing net haul from 2,250 m depth to the surface. Maximum abundance was found close to the surface with 6.6 and 10.0 ind. m^?3 at 0–50 m and 50–100 m depth, respectively. However, the major fraction of the population (>40%) occurred between 1,000 and 1,500 m depth. In the deepest layer (2,000–2,250 m) abundance measured 2.2 ind. m^?3 and was twice as high as between 100 and 1,000 m depth. In comparison to individuals from surface waters, copepods from the hyper-benthic layer were torpid and did not react to mechanical stimuli. Stage CV copepodids and females from the deep sample contained 4–10% less lipid and showed significantly reduced respiration rates of 0.24 and 0.26 ml O₂ h^?1 g^?1 dry mass (DM) as compared to surface samples (0.49 and 0.43 ml O₂ h^?1 g^?1 DM). All these observations indicate that the hyper-benthic part of the population had already started a dormant overwintering phase at great depth. Based on the lipid deposits and energy demands, the potential maximum duration of the non-feeding dormant phase was estimated at 76–110 days for females and at 98–137 days for CV copepodids, depending on what indispensable minimum lipid content was assumed. In any case, the estimated times could not meet the necessary requirements for a starvation period of >6 months until the next phytoplankton bloom in the following spring. The ecological implications of these results are discussed with respect to the life cycle and eco-physiological adaptations of C. hyperboreus to its high-Arctic habitat.     

Global sensitivity analysis of a process-based model for ammonia emissions from manure storage and treatment structures

The development of process-based models to estimate ammonia emissions from animal feeding operations (AFOSs) is sought to replace costly and time-consuming direct measurements. Critical to process-based model development is conducting sensitivity analysis to determine the input parameters and their interactions that contribute most to the variance of the model output. Global and relative sensitivity analyses were applied to a process-based model for predicting ammonia emissions from the surface of anaerobic lagoons for treating and storing manure. The objectives were to compare global sensitivity analysis (GSA) to relative (local) sensitivity analysis (RSA) on a process-based model for ammonia emissions. Based on the first-order coefficient, both GSA and RSA showed the model input parameters in order of importance in process model for ammonia emissions from lagoon surfaces were: (i) pH, (ii) lagoon liquid temperature, (iii) wind speed above the lagoon surface, and (iv) the concentration of ammoniacal nitrogen in the lagoon. The GSA revealed that interactions between model parameters accounted for over two-thirds of the model variance, a result that cannot be achieved using traditional RSA. Also, the GSA showed that parameter interactions involving liquid pH had more impact on the model output variance than the single parameters: (i) temperature, (ii) wind speed, or (iii) total ammoniacal nitrogen. This study demonstrates that GSA provides a more complete analysis of model input parameters and their interactions on the model output compared to RSA. A comprehensive tutorial regarding the application of GSA to a process model is presented.