BASE FLOW RECESSION RATES,LOW FLOWS,AND HYDROLOGIC FEATURES OF SMALL WATERSHEDS IN PENNSYLVANIA,USA1

This paper examines the relationships between measurable watershed hydrologic features, base flow recession rates, and the Q_7,10 low flow statistic (the annual minimum seven‐day average streamflow occurring once every 10 years on average). Base flow recession constants were determined by analyzing hydrograph recession data from 24 small (>130 km²), unregulated watersheds across five major physiographic provinces of Pennsylvania, providing a highly variable dataset. Geomorphic, hydrogeologic, and land use parameters were determined for each watershed. The base flow recession constant was found to be most strongly correlated to drainage density, geologic index, and ruggedness number (watershed slope); however, these three parameters are intercorrelated. Multiple regression models were developed for predicting the recession rate, and it was found that only two parameters, drainage density and hydrologic soil group, were required to obtain good estimates of the recession constant. Equations were also developed to relate the recession rates to Q_7,10 per unit area, and to the Q_7,10/Q₅₀ ratio. Using these equations, estimates of base flow recession rates, Q_7,10, and streamflow reduction under drought conditions can be made for small, ungaged basins across a wide range of physiography.     

PREDICTING FECAL COLIFORM BACTERIA LEVELS IN THE CHARLES RIVER,MASSACHUSETTS, USA1

In Massachusetts, the Charles River Watershed Association conducts a regular water quality monitoring and public notification program in the Charles River Basin during the recreational season to inform users of the river's health. This program has relied on laboratory analyses of river samples for fecal coliform bacteria levels, however, results are not available until at least 24 hours after sampling. To avoid the need for laboratory analyses, ordinary least squares (OLS) and logistic regression models were developed to predict fecal coliform bacteria concentrations and the probabilities of exceeding the Massachusetts secondary contact recreation standard for bacteria based on meteorological conditions and streamflow. The OLS models resulted in adjusted R²s ranging from 50 to 60 percent. An uncertainty analysis reveals that of the total variability of fecal coliform bacteria concentrations, 45 percent is explained by the OLS regression model, 15 percent is explained by both measurement and space sampling error, and 40 percent is explained by time sampling error. Higher accuracy in future bacteria forecasting models would likely result from reductions in laboratory measurement errors and improved sampling designs.     

On measuring wealth: a case study on the state of Queensland

In order for policy makers to plan effectively for sustainable development, there is a need for measures of welfare that consider changes in the natural capital stock. Current measures based on conventional national accounting are flawed because they are based solely on flow measures and do not account for environmental effects. In this paper, we use an expanded measure of wealth to estimate the value of natural capital for Queensland. The state's stock of natural capital is valued at A dollar 355.6 billion, of which non-timber forest resources account for 45.3%, ecosystem services 20.0%, and mineral resources 17.6%. This figure is a conservative estimate of the true value since some significant components such as the ecological and life-support functions of the environment are excluded. The estimates highlight the relative importance of different forms of natural capital and can be used to draw the attention of policymakers to the need to give adequate weight to the value of such services in decision-making processes.     

Erratum to: Accumulation of Cr,Cd, Pb,Cu, and Zn by plants in tanning sludge storage sites: opportunities for contamination bioindication and phytoremediation

Environmental Science and Pollution Research -     

Pyrolysis and catalytic pyrolysis as a recycling method of waste CDs originating from polycarbonate and HIPS

Pyrolysis appears to be a promising recycling process since it could convert the disposed polymers to hydrocarbon based fuels or various useful chemicals. In the current study, two model polymers found in WEEEs, namely polycarbonate (PC) and high impact polystyrene (HIPS) and their counterparts found in waste commercial Compact Discs (CDs) were pyrolysed in a bench scale reactor. Both, thermal pyrolysis and pyrolysis in the presence of two catalytic materials (basic MgO and acidic ZSM-5 zeolite) was performed for all four types of polymers. Results have shown significant recovery of the monomers and valuable chemicals (phenols in the case of PC and aromatic hydrocarbons in the case of HIPS), while catalysts seem to decrease the selectivity towards the monomers and enhance the selectivity towards other desirable compounds.     

Pollutant concentration profile reconstruction using digital soft sensors for biodegradation and exposure assessment in the presence of model uncertainty

A new approach to the problem of environmental hazard assessment and monitoring for pollutant biodegradation reaction systems in the presence of uncertainty is proposed using soft sensor-based pollutant concentration dynamic profile reconstruction techniques. In particular, a robust reduced-order soft sensor is proposed that can be digitally implemented in the presence of inherent complexity and the inevitable model uncertainty. The proposed method explicitly incorporates all the available information associated with a process model characterized by varying degrees of uncertainty, as well as available sensor measurements of certain physicochemical quantities. Based on the above information, a reduced-order soft sensor is designed enabling the reliable reconstruction of pollutant concentration profiles in complex biodegradation systems that can not be always achieved due to physical and/or technical limitations associated with current sensor technology. The option of using the aforementioned approach to compute toxic load and persistence indexes on the basis of the reconstructed concentration profiles is also pursued. Finally, the performance of the proposed method is evaluated in two illustrative environmental hazard assessment case studies.     

An interdisciplinary review of current and future approaches to improving human–predator relations

In a world of shrinking habitats and increasing competition for natural resources, potentially dangerous predators bring the challenges of coexisting with wildlife sharply into focus. Through interdisciplinary collaboration among authors trained in the humanities, social sciences, and natural sciences, we reviewed current approaches to mitigating adverse human–predator encounters and devised a vision for future approaches to understanding and mitigating such encounters. Limitations to current approaches to mitigation include too much focus on negative impacts; oversimplified equating of levels of damage with levels of conflict; and unsuccessful technical fixes resulting from failure to engage locals, address hidden costs, or understand cultural (nonscientific) explanations of the causality of attacks. An emerging interdisciplinary literature suggests that to better frame and successfully mitigate negative human–predator relations conservation professionals need to consider dispensing with conflict as the dominant framework for thinking about human–predator encounters; work out what conflicts are really about (they may be human–human conflicts); unravel the historical contexts of particular conflicts; and explore different cultural ways of thinking about animals. The idea of cosmopolitan natures may help conservation professionals think more clearly about human–predator relations in both local and global context. These new perspectives for future research practice include a recommendation for focused interdisciplinary research and the use of new approaches, including human‐animal geography, multispecies ethnography, and approaches from the environmental humanities notably environmental history. Managers should think carefully about how they engage with local cultural beliefs about wildlife, work with all parties to agree on what constitutes good evidence, develop processes and methods to mitigate conflicts, and decide how to monitor and evaluate these. Demand for immediate solutions that benefit both conservation and development favors dispute resolution and technical fixes, which obscures important underlying drivers of conflicts. If these drivers are not considered, well‐intentioned efforts focused on human–wildlife conflicts will fail.     

Trait space of rare plants in a fire‐dependent ecosystem

The causes of species rarity are of critical concern because of the high extinction risk associated with rarity. Studies examining individual rare species have limited generality, whereas trait‐based approaches offer a means to identify functional causes of rarity that can be applied to communities with disparate species pools. Differences in functional traits between rare and common species may be indicative of the functional causes of species rarity and may therefore be useful in crafting species conservation strategies. However, there is a conspicuous lack of studies comparing the functional traits of rare species and co‐occurring common species. We measured 18 important functional traits for 19 rare and 134 common understory plant species from North Carolina's Sandhills region and compared their trait distributions to determine whether there are significant functional differences that may explain species rarity. Flowering, fire, and tissue‐chemistry traits differed significantly between rare and common, co‐occurring species. Differences in specific traits suggest that fire suppression has driven rarity in this system and that changes to the timing and severity of prescribed fire may improve conservation success. Our method provides a useful tool to prioritize conservation efforts in other systems based on the likelihood that rare species are functionally capable of persisting.     

Review of Italian experience on automotive shredder residue characterization and management

Automotive Shredder Residue (ASR) is a special waste that can be classified as either hazardous or non hazardous depending on the amount of hazardous substances and on the features of leachate gathered from EN12457/2 test. However both the strict regulation concerning landfills and the EU targets related to End-of-Life Vehicles (ELVs) recovery and recycling rate to achieve by 2015 (Directive 2000/53/EC), will limit current landfilling practice and will impose an increased efficiency of ELVs valorization. The present paper considers ELVs context in Italy, taking into account ASRs physical–chemical features and current processing practice, focusing on the enhancement of secondary materials recovery. The application in waste-to-energy plants, cement kilns or metallurgical processes is also analyzed, with a particular attention to the possible connected environmental impacts. Pyrolysis and gasification are considered as emerging technologies although the only use of ASR is debatable; its mixing with other waste streams is gradually being applied in commercial processes. The environmental impacts of the processes are acceptable, but more supporting data are needed and the advantage over (co-)incineration remains to be proven.     

Using long-term data for a reintroduced population to empirically estimate future consequences of inbreeding

Inbreeding depression is an important long-term threat to reintroduced populations. However, the strength of inbreeding depression is difficult to estimate in wild populations because pedigree data are inevitably incomplete and because good data are needed on survival and reproduction. Predicting future population consequences is especially difficult because this also requires projecting future inbreeding levels and their impacts on long-term population dynamics, which are subject to many uncertainties. We illustrate how such projections can be derived through Bayesian state-space modeling methods based on a 26-year data set for North Island Robins (Petroica longipes) reintroduced to Tiritiri Matangi Island in 1992. We used pedigree data to model increases in the average inbreeding level (F ) over time based on kinship of possible breeding pairs and to estimate empirically N_e/N (effective/census population size). We used multiple imputation to model the unknown components of inbreeding coefficients, which allowed us to estimate effects of inbreeding on survival for all 1458 birds in the data set while modeling density dependence and environmental stochasticity. This modeling indicated that inbreeding reduced juvenile survival (1.83 lethal equivalents [SE 0.81]) and may have reduced subsequent adult survival (0.44 lethal equivalents [0.81]) but had no apparent effect on numbers of fledglings produced. Average inbreeding level increased to 0.10 (SE 0.001) as the population grew from 33 (0.3) to 160 (6) individuals over the 25 years, giving a ratio of 0.56 (0.01). Based on a model that also incorporated habitat regeneration, the population was projected to reach a maximum of 331–1144 birds (median 726) in 2130, then to begin a slow decline. Without inbreeding, the population would be expected stabilize at 887–1465 birds (median 1131). Such analysis, therefore, makes it possible to empirically derive the information needed for rational decisions about inbreeding management while accounting for multiple sources of uncertainty.