MODELING LIGHT ATTENUATION,SECCHI DISK,AND EFFECTS OF TRIPTON IN SENACA RIVER,NEW YORK,USA1

The development, testing, and application of a probabilistic model framework for the light attenuation coefficient for downwelling irradiance (K_d) and Secchi disc transparency (SD) that resolves the effects of several light attenuating constituents, including phytoplankton and nonliving particles (tripton), is documented. The model is consistent with optical theory, partitioning the magnitudes of the light attenuating processes of absorption and scattering according to the contributions of attenuating constituents as simple summations. The probabilistic framework accommodates variations in the character and concentrations of these constituents and ambient conditions during measurements, and recognizes a linear relationship between the magnitudes of absorption and scattering by tripton. The model is tested and applied for a 21 km reach of the Seneca River, New York, that features optical gradients caused by an intervening hypereutrophic lake and dam, and a severe infestation of the exotic zebra mussel. The model is applied to resolve the roles of phytoplankton and tripton in regulating measured longitudinal patterns of SD along the study reach of the river and increases in SD since the zebra mussel invasion, and to predict decreases in K_d since the invasion.     

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.     

BASE FLOW TRENDS IN URBANIZING WATERSHEDS OF THE DELAWARE RIVER BASIN1

Rapid land development is raising concern regarding the ability of urbanizing watersheds to sustain adequate base flow during periods of drought. Long term streamflow records from unregulated watersheds of the lower to middle Delaware River basin are examined to evaluate the impact of urbanization and imperviousness on base flow. Trends in annual base flow volumes, seven‐day low flows, and runoff ratios are determined for six urbanizing watersheds and four reference watersheds across three distinct physiographic regions. Hydrograph separation is used to determine annual base flow and stormflow volumes, and nonparametric trend tests are conducted on the resulting time series. Of the watersheds examined, the expected effects of declining base flow volumes and seven‐day low flows and increasing stormflows are seen in only one watershed that is approximately 20 percent impervious and has been subject to a net water export over the past 15 years. Both interbasin transfers and hydrologic mechanisms are invoked to explain these results. The results show that increases in impervious area may not result in measurable reductions in base flow at the watershed scale.     

Science in the public process of ecosystem management: lessons from Hawaii, Southeast Asia, Africa and the US Mainland

Partnerships and co-operative environmental management are increasing worldwide as is the call for scientific input in the public process of ecosystem management. In Hawaii, private landowners, non-governmental organizations, and state and federal agencies have formed watershed partnerships to conserve and better manage upland forested watersheds. In this paper, findings of an international workshop convened in Hawaii to explore the strengths of approaches used to assess stakeholder values of environmental resources and foster consensus in the public process of ecosystem management are presented. Authors draw upon field experience in projects throughout Hawaii, Southeast Asia, Africa and the US mainland to derive a set of lessons learned that can be applied to Hawaiian and other watershed partnerships in an effort to promote consensus and sustainable ecosystem management. Interdisciplinary science-based models can serve as effective tools to identify areas of potential consensus in the process of ecosystem management. Effective integration of scientific input in co-operative ecosystem management depends on the role of science, the stakeholders and decision-makers involved, and the common language utilized to compare tradeoffs. Trust is essential to consensus building and the integration of scientific input must be transparent and inclusive of public feedback. Consideration of all relevant stakeholders and the actual benefits and costs of management activities to each stakeholder is essential. Perceptions and intuitive responses of people can be as influential as analytical processes in decision-making and must be addressed. Deliberative, dynamic and iterative decision-making processes all influence the level of stakeholder achievement of consensus. In Hawaii, application of lessons learned can promote more informed and democratic decision processes, quality scientific analysis that is relevant, and legitimacy and public acceptance of ecosystem management.     

Estimating the economic burden from illnesses associated with recreational coastal water pollution--a case study in Orange County, California

A cost-of-illness framework was applied to health and income data to quantify the health burden from illnesses associated with exposure to polluted recreational marine waters. Using data on illness severity due to exposure to polluted coastal water and estimates of mean annual salaries and medical costs (adjusted to 2001 values) for residents of Orange County, California, we estimated that the economic burden per gastrointestinal illness (GI) amounts to 36.58 dollars, the burden per acute respiratory disease is 76.76 dollars, the burden per ear ailment is 37.86 dollars, and the burden per eye ailment is 27.31 dollars. These costs can become a substantial public health burden when millions of exposures per year to polluted coastal waters result in hundreds of thousands of illnesses. For example, exposures to polluted waters at Orange County's Newport and Huntington Beaches were estimated to generate an average of 36,778 GI episodes per year. At this GI illness rate, one can also expect that approximately 38,000 more illness episodes occurred per year of other types, including respiratory, eye, and ear infections. The combination of excess illnesses associated with coastal water pollution resulted in a cumulative public health burden of 3.3 million dollars per year for these two beaches. This paper introduces a public health cost variable that can be applied in cost-benefit analyses when evaluating pollution abatement strategies.     

Increased bioavailability of metals in two contrasting agricultural soils treated with waste wood-derived biochar and ash

Recycled waste wood is being increasingly used for energy production; however, organic and metal contaminants in by-products produced from the combustion/pyrolysis residue may pose a significant environmental risk if they are disposed of to land. Here we conducted a study to evaluate if highly polluted biochar (from pyrolysis) and ash (from incineration) derived from Cu-based preservative-treated wood led to different metal (e.g., Cu, As, Ni, Cd, Pb, and Zn) bioavailability and accumulation in sunflower (Helianthus annuus L.). In a pot experiment, biochar at a common rate of 2 % w/w, corresponding to ～50 t ha^?1, and an equivalent pre-combustion dose of wood ash (0.2 % w/w) were added to a Eutric Cambisol (pH 6.02) and a Haplic Podzol (pH 4.95), respectively. Both amendments initially raised soil pH, although this effect was relatively short-term, with pH returning close to the unamended control within about 7 weeks. The addition of both amendments resulted in an exceedance of soil Cu statutory limit, together with a significant increase of Cu and plant nutrient (e.g., K) bioavailability. The metal-sorbing capacity of the biochar, and the temporary increase in soil pH caused by adding the ash and biochar were insufficient to offset the amount of free metal released into solution. Sunflower plants were negatively affected by the addition of metal-treated wood-derived biochar and led to elevated concentration of metals in plant tissue, and reduced above- and below-ground biomass, while sunflower did not grow at all in the Haplic Podzol. Biochar and ash derived from wood treated with Cu-based preservatives can lead to extremely high Cu concentrations in soil and negatively affect plant growth. Identifying sources of contaminated wood in waste stream feedstocks is crucial before large-scale application of biochar or wood ash to soil is considered.     

Toward reassessing data‐deficient species

One in 6 species (13,465 species) on the International Union for Conservation of Nature (IUCN) Red List is classified as data deficient due to lack of information on their taxonomy, population status, or impact of threats. Despite the chance that many are at high risk of extinction, data‐deficient species are typically excluded from global and local conservation priorities, as well as funding schemes. The number of data‐deficient species will greatly increase as the IUCN Red List becomes more inclusive of poorly known and speciose groups. A strategic approach is urgently needed to enhance the conservation value of data‐deficient assessments. To develop this, we reviewed 2879 data‐deficient assessments in 6 animal groups and identified 8 main justifications for assigning data‐deficient status (type series, few records, old records, uncertain provenance, uncertain population status or distribution, uncertain threats, taxonomic uncertainty, and new species). Assigning a consistent set of justification tags (i.e., consistent assignment to assessment justifications) to species classified as data deficient is a simple way to achieve more strategic assessments. Such tags would clarify the causes of data deficiency; facilitate the prediction of extinction risk; facilitate comparisons of data deficiency among taxonomic groups; and help prioritize species for reassessment. With renewed efforts, it could be straightforward to prevent thousands of data‐deficient species slipping unnoticed toward extinction.