A Critique of Estimating Future Costs Using Most Likely Value

ASTM E2137 (Standard Guide for Estimating Monetary Costs and Liability for Environmental Matters, or E2137) is the guidance for developing estimates of future environmental costs. E2137 provides a hierarchy of cost estimation approaches, and expresses an explicit preference for the use of probabilistic cost analysis to develop expected values for environmental costs. Dr. Ram and his colleagues have published an article (Remediation Journal, Autumn 2013) which rejects the use of EV analysis, arguing that while “good in principle” it has little practical value because it is nearly impossible to develop supportable probabilities. The E2137 principles and processes have been used for more than a decade in the context of addressing future environmental costs, yet their view of E2137 renders the standard meaningless. We conclude that the deficiency is not in the ASTM standard, and that when properly constructed, probabilistic analyses can be used to develop expected values with supportable probabilities. ©2015 Wiley Periodicals, Inc.     

Forest carbon management in the United States: 1600-2100

This paper reviews the effects of past forest management on carbon stocks in the United States, and the challenges for managing forest carbon resources in the 21st century. Forests in the United States were in approximate carbon balance with the atmosphere from 1600-1800. Utilization and land clearing caused a large pulse of forest carbon emissions during the 19th century, followed by regrowth and net forest carbon sequestration in the 20th century. Recent data and knowledge of the general behavior of forests after disturbance suggest that the rate of forest carbon sequestration is declining. A goal of an additional 100 to 200 Tg C/yr of forest carbon sequestration is achievable, but would require investment in inventory and monitoring, development of technology and practices, and assistance for land managers.     

Tillage and field scale controls on greenhouse gas emissions

There is a lack of understanding of how associations among soil properties and management-induced changes control the variability of greenhouse gas (GHG) emissions from soil. We performed a laboratory investigation to quantify relationships between GHG emissions and soil indicators in an irrigated agricultural field under standard tillage (ST) and a field recently converted (2 yr) to no-tillage (NT). Soil cores (15-cm depth) were incubated at 25 degrees C at field moisture content and 75% water holding capacity. Principal component analysis (PCA) identified that most of the variation of the measured soil properties was related to differences in soil C and N and soil water conditions under ST, but soil texture and bulk density under NT. This trend became more apparent after irrigation. However, principal component regression (PCR) suggested that soil physical properties or total C and N were less important in controlling GHG emissions across tillage systems. The CO2 flux was more strongly determined by microbial biomass under ST and inorganic N content under NT than soil physical properties. Similarly, N2O and CH4 fluxes were predominantly controlled by NO3- content and labile C and N availability in both ST and NT soils at field moisture content, and NH4+ content after irrigation. Our study indicates that the field-scale variability of GHG emissions is controlled primarily by biochemical parameters rather than physical parameters. Differences in the availability and type of C and N sources for microbial activity as affected by tillage and irrigation develop different levels and combinations of field-scale controls on GHG emissions.     

Multi-stage sampling for large scale natural resources surveys: a case study of rice and waterfowl

Large-scale sample surveys to estimate abundance and distribution of organisms and their habitats are increasingly important in ecological studies. Multi-stage sampling (MSS) is especially suited to large-scale surveys because of the natural clustering of resources. To illustrate an application, we: (1) designed a stratified MSS to estimate late autumn abundance (kg/ha) of rice seeds in harvested fields as food for waterfowl wintering in the Mississippi Alluvial Valley (MAV); (2) investigated options for improving the MSS design; and (3) compared statistical and cost efficiency of MSS to simulated simple random sampling (SRS). During 2000-2002, we sampled 25-35 landowners per year, 1 or 2 fields per landowner per year, and measured seed mass in 10 soil cores collected within each field. Analysis of variance components and costs for each stage of the survey design indicated that collecting 10 soil cores per field was near the optimum of 11-15, whereas sampling >1 field per landowner provided few benefits because data from fields within landowners were highly correlated. Coefficients of variation (CV) of annual estimates of rice abundance ranged from 0.23 to 0.31 and were limited by variation among landowners and the number of landowners sampled. Design effects representing the statistical efficiency of MSS relative to SRS ranged from 3.2 to 9.0, and simulations indicated SRS would cost, on average, 1.4 times more than MSS because clustering of sample units in MSS decreased travel costs. We recommend MSS as a potential sampling strategy for large-scale natural resource surveys and specifically for future surveys of the availability of rice as food for waterfowl in the MAV and similar areas.     

A comparative analysis of predictors of sense of place dimensions: attachment to, dependence on, and identification with lakeshore properties

Sense of place can be conceived as a multidimensional construct representing beliefs, emotions and behavioural commitments concerning a particular geographic setting. This view, grounded in attitude theory, can better reveal complex relationships between the experience of a place and attributes of that place than approaches that do not differentiate cognitive, affective and conative domains. Shoreline property owners (N=290) in northern Wisconsin were surveyed about their sense of place for their lakeshore properties. A predictive model comprising owners' age, length of ownership, participation in recreational activities, days spent on the property, extent of property development, and perceptions of environmental features, was employed to explain the variation in dimensions of sense of place. In general, the results supported a multidimensional approach to sense of place in a context where there were moderate to high correlations among the three place dimensions. Perceptions of environmental features were the biggest predictors of place dimensions, with owners' perceptions of lake importance varying in explanatory power across place dimensions.     

A Regional Classification Scheme for Estimating Reference Water Quality in Streams Using Land-Use-Adjusted Spatial Regression-Tree Analysis

Various approaches are used to subdivide large areas into regions containing streams that have similar reference or background water quality and that respond similarly to different factors. For many applications, such as establishing reference conditions, it is preferable to use physical characteristics that are not affected by human activities to delineate these regions. However, most approaches, such as ecoregion classifications, rely on land use to delineate regions or have difficulties compensating for the effects of land use. Land use not only directly affects water quality, but it is often correlated with the factors used to define the regions. In this article, we describe modifications to SPARTA (spatial regression-tree analysis), a relatively new approach applied to water-quality and environmental characteristic data to delineate zones with similar factors affecting water quality. In this modified approach, land-use-adjusted (residualized) water quality and environmental characteristics are computed for each site. Regression-tree analysis is applied to the residualized data to determine the most statistically important environmental characteristics describing the distribution of a specific water-quality constituent. Geographic information for small basins throughout the study area is then used to subdivide the area into relatively homogeneous environmental water-quality zones. For each zone, commonly used approaches are subsequently used to define its reference water quality and how its water quality responds to changes in land use. SPARTA is used to delineate zones of similar reference concentrations of total phosphorus and suspended sediment throughout the upper Midwestern part of the United States.     

Mapping Adolescents’ Sense of Place and Perceptions of Change in an Urban–Rural Transition Area

Environmental Management - Landscapes are changing, with rural areas becoming increasingly urbanized. Children and adolescents are underrepresented in the sense-of-place literature. Our study aimed...     

Circumpolar status of Arctic ptarmigan: Population dynamics and trends

Rock ptarmigan (Lagopus muta) and willow ptarmigan (L. lagopus) are Arctic birds with a circumpolar distribution but there is limited knowledge about their status and trends across their circumpolar distribution. Here, we compiled information from 90 ptarmigan study sites from 7 Arctic countries, where almost half of the sites are still monitored. Rock ptarmigan showed an overall negative trend on Iceland and Greenland, while Svalbard and Newfoundland had positive trends, and no significant trends in Alaska. For willow ptarmigan, there was a negative trend in mid-Sweden and eastern Russia, while northern Fennoscandia, North America and Newfoundland had no significant trends. Both species displayed some periods with population cycles (short 3–6 years and long 9–12 years), but cyclicity changed through time for both species. We propose that simple, cost-efficient systematic surveys that capture the main feature of ptarmigan population dynamics can form the basis for citizen science efforts in order to fill knowledge gaps for the many regions that lack systematic ptarmigan monitoring programs.

     

Bioaerosol sampling by a personal rotating cup sampler CIP 10-M

High concentrations of bioaerosols containing bacterial, fungal and biotoxinic matter are encountered in many workplaces, e.g. solid waste treatment plants, waste water treatment plants and sewage networks. A personal bioaerosol sampler, the CIP 10-M (M-microbiologic), has been developed to measure worker exposure to airborne biological agents. This sampler is battery operated; it is light and easy to wear and offers full work shift autonomy. It can sample much higher concentrations than biological impactors and limits the mechanical stress on the microorganisms. Biological particles are collected in 2 ml of liquid medium inside a rotating cup fitted with radial vanes to maintain an air flow rate of 10 l min(-1) at a rotational speed of approximately 7,000 rpm. The rotating cup is made of sterilisable material. The sampled particles follow a helicoidal trajectory as they are pushed to the surface of the liquid by centrifugal force, which creates a thin vertical liquid layer. Sterile water or another collecting liquid can be used. Three particle size selectors allow health-related aerosol fractions to be sampled according to international conventions. The sampled microbiological particles can be easily recovered for counting, incubation or further biochemical analysis, e.g., for airborne endotoxins. Its physical sampling efficiency was laboratory tested and field trials were carried out in industrial waste management conditions. The results indicate satisfactory collection efficiency, whilst experimental application has demonstrated the usefulness of the CIP 10-M personal sampler for individual bioaerosol exposure monitoring.     

Correction to: Opportunities to reduce nutrient inputs to the Baltic Sea by improving manure use efficiency in agriculture

While progress has been made in reducing external nutrient inputs to the Baltic Sea, further actions are needed to meet the goals of the Baltic Sea Action Plan (BSAP), especially for the Baltic Proper, Gulf of Finland, and Gulf of Riga sub-basins. We used the net anthropogenic nitrogen and phosphorus inputs (NANI and NAPI, respectively) nutrient accounting approach to construct three scenarios of reduced NANI-NAPI. Reductions assumed that manure nutrients were redistributed from areas with intense animal production to areas that focus on crop production and would otherwise import synthetic and mineral fertilizers. We also used the Simple as Necessary Baltic Long Term Large Scale (SANBALTS) model to compare eutrophication conditions for the scenarios to current and BSAP-target conditions. The scenarios suggest that reducing NANI-NAPI by redistributing manure nutrients, together with improving agronomic practices, could meet 54–82% of the N reductions targets (28–43 kt N reduction) and 38–64% P reduction targets (4–6.6 kt P reduction), depending on scenario. SANBALTS output showed that even partial fulfillment of nutrient reduction targets could have ameliorating effects on eutrophication conditions. Meeting BSAP targets will require addressing additional sources, such as sewage. A common approach to apportioning sources to external nutrients loads could enable further assessment of the feasibility of eutrophication management targets.