BIOECONOMIC ANALYSIS OF SELECTED CONSERVATION PRACTICES ON SOIL EROSION AND FRESHWATER FISHERIES1

ABSTRACT: Farmers can generate environmental benefits (improved water quality and fisheries and wildlife habitat), but they may not be able to quantify them. Furthermore, farmers may reduce their incomes from managing lands to produce these positive externalities but receive little monetary compensation in return. This study simulated the relationship between agricultural practices, water quality, fish responses to suspended sediment and farm income within two small watersheds, one of a cool water stream and one of a warm water stream. Using the Agricultural Drainage and Pesticide Transport (ADAPT) model, this study related best management practices (BMPs) to calculated instream suspended sediment concentrations by estimating sediment delivery, runoff, base flow, and streambank erosion to quantify the effects of suspended sediment exposure on fish communities. By implementing selected BMPs in each watershed, annual net farm income declined $18,000 to $28,000 (1 to 3 percent) from previous levels. “Lethal” fish events from suspended sediments in the cool water watershed decreased by 60 percent as conservation tillage and riparian buffers increased. Despite reducing suspended sediments by 25 percent, BMPs in the warm water watershed did not reduce the negative response of the fisheries. Differences in responses (physical and biological) between watersheds highlight potential gains in economic efficiency by targeting BMPs or by offering performance based “green payments.”     

DRY AND WET WEATHER FLOW NUTRIENT LOADS FROM A LOS ANGELES WATERSHED1

Effective watershed management requires an accurate assessment of the pollutant loads from the associated point and nonpoint sources. The importance of wet weather flow (WWF) pollutant loads is well known, but in semi‐arid regions where urbanization is significant the pollutant load in dry weather flow (DWF) may also be important. This research compares the relative contributions of potential contaminants discharged in DWF and WWF from the Ballona Creek Watershed in Los Angeles, California. Models to predict DWF and WWF loads of total suspended solids, biochemical oxygen demand, nitrate‐nitrogen, nitrite‐nitrogen, ammonia‐nitrogen, total Kjeldahl nitrogen, and total phosphorus from the Ballona Creek Watershed for six water years dating from 1991 to 1996 were developed. The contaminants studied were selected based on data availability and their potential importance in the degradation of Ballona Creek and Santa Monica Bay beneficial uses. Wet weather flow was found to contribute approximately 75 percent to 90 percent of the total annual flow volume discharged by the Ballona Creek Watershed. Pollutant loads are also predominantly due to WWF, but during the dry season, DWF is a more significant contributor. Wet weather flow accounts for 67 to 98 percent of the annual load of the constituents studied. During the dry season, however, the portion attributable to DWF increases to greater than 40 percent for all constituents except biochemical oxygen demand and total suspended solids. When individual catchments within the watershed are considered, the DWF pollutant load from the largest catchment is similar to the WWF pollutant load in two other major catchments. This research indicates WWF is the most significant source of nonpoint source pollution load on an annual basis, but management of the effects of the nonpoint source pollutant load should consider the seasonal importance of DWF.     

MODELING THE DISTRIBUTION OF DIFFUSE NITROGEN SOURCES AND SINKS IN THE NEUSE RIVER BASIN OF NORTH CAROLINA,USA1

This study quantified nonpoint source nitrogen (NPS‐N) sources and sinks across the 14,582 km² Neuse River Basin (NRB) located in North Carolina, to provide tabular data summaries and graphic overlay products to support the development of management approaches to best achieve established N reduction goals. First, a remote sensor derived, land cover classification was performed to support modeling needs. Modeling efforts included the development of a mass balance model to quantify potential N sources and sinks, followed by a precipitation event driven hydrologic model to effectively transport excess N across the landscape to individual stream reaches to support subsequent labeling of transported N values corresponding to source origin. Results indicated that agricultural land contributed 55 percent of the total annual NPS‐N loadings, followed by forested land at 23 percent (background), and urban areas at 21 percent. Average annual N source contributions were quantified for agricultural (1.4 kg/ha), urban (1.2 kg/ha), and forested cover types (0.5 kg/ha). Nonpoint source‐N contributions were greatest during the winter (40 percent), followed by spring (32 percent), summer (28 percent), and fall (0.3 percent). Seasonal total N loadings shifted from urban dominated and forest dominated sources during the winter, to agricultural sources in the spring and summer. A quantitative assessment of the significant NRB land use activities indicated that high (greater than 70 percent impervious) and medium (greater than 35 percent impervious) density urban development were the greatest contributors of NPS‐N on a unit area basis (1.9 and 1.6 kg/ha/yr, respectively), followed by row crops and pasture/hay cover types (1.4 kg/ha/yr).     

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.     

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.     

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.