EFFECTS OF BEST MANAGEMENT PRACTICES ON FOREST STREAMWATER QUALITY IN EASTERN KENTUCKY1

ABSTRACT: Forest land managers are concerned about the effects of logging on soil erosion, streamflow, and water quality and are promoting the use of Best Management Practices (BMPs) to control impacts. To compare the effects of BMP implementation on streamwater quality, two of three small watersheds in Kentucky were harvested in 1983 and 1984, one with BMPs, the other without BMPs. There was no effect of clearcutting on stream temperatures. Streamflow increased by 17.8 cm (123 percent) on the BMP watershed during the first 17 months after cutting and by 20.6 cm (138 percent) on the Non-BMP watershed. Water yields remained significantly elevated compared to the uncut watershed 8 years after harvesting. Suspended sediment flux was 14 and 30 times higher on the BMP and Non-BMP Watersheds, respectively, than on the uncut watershed during treatment, and 4 and 6.5 times higher in the 17 months after treatment was complete. Clearcutting resulted in increased concentrations of nitrate, and other nutrients compared to the uncut watershed, and concentrations were highest on the non-BMP watershed. Recovery of biotic control over nutrient losses occurred within three years of clearcutting. The streamside buffer strip was effective in reducing the impact of clearcutting on water yield and sediment flux.     

Baselines for land-use change in the tropics: application to avoided deforestation projects

Although forest conservation activities, particularly in the tropics, offer significant potential for mitigating carbon (C) emissions, these types of activities have faced obstacles in the policy arena caused by the difficulty in determining key elements of the project cycle, particularly the baseline. A baseline for forest conservation has two main components: the projected land-use change and the corresponding carbon stocks in applicable pools in vegetation and soil, with land-use change being the most difficult to address analytically. In this paper we focus on developing and comparing three models, ranging from relatively simple extrapolations of past trends in land use based on simple drivers such as population growth to more complex extrapolations of past trends using spatially explicit models of land-use change driven by biophysical and socioeconomic factors. The three models used for making baseline projections of tropical deforestation at the regional scale are: the Forest Area Change (FAC) model, the Land Use and Carbon Sequestration (LUCS) model, and the Geographical Modeling (GEOMOD) model. The models were used to project deforestation in six tropical regions that featured different ecological and socioeconomic conditions, population dynamics, and uses of the land: (1) northern Belize; (2) Santa Cruz State, Bolivia; (3) Paraná State, Brazil; (4) Campeche, Mexico; (5) Chiapas, Mexico; and (6) Michoacán, Mexico. A comparison of all model outputs across all six regions shows that each model produced quite different deforestation baselines. In general, the simplest FAC model, applied at the national administrative-unit scale, projected the highest amount of forest loss (four out of six regions) and the LUCS model the least amount of loss (four out of five regions). Based on simulations of GEOMOD, we found that readily observable physical and biological factors as well as distance to areas of past disturbance were each about twice as important as either sociological/demographic or economic/infrastructure factors (less observable) in explaining empirical land-use patterns. We propose from the lessons learned, a methodology comprised of three main steps and six tasks can be used to begin developing credible baselines. We also propose that the baselines be projected over a 10-year period because, although projections beyond 10 years are feasible, they are likely to be unrealistic for policy purposes. In the first step, an historic land-use change and deforestation estimate is made by determining the analytic domain (size of the region relative to the size of proposed project), obtaining historic data, analyzing candidate baseline drivers, and identifying three to four major drivers. In the second step, a baseline of where deforestation is likely to occur–a potential land-use change (PLUC) map—is produced using a spatial model such as GEOMOD that uses the key drivers from step one. Then rates of deforestation are projected over a 10-year baseline period based on one of the three models. Using the PLUC maps, projected rates of deforestation, and carbon stock estimates, baseline projections are developed that can be used for project GHG accounting and crediting purposes: The final step proposes that, at agreed interval (e.g., about 10 years), the baseline assumptions about baseline drivers be re-assessed. This step reviews the viability of the 10-year baseline in light of changes in one or more key baseline drivers (e.g., new roads, new communities, new protected area, etc.). The potential land-use change map and estimates of rates of deforestation could be re-done at the agreed interval, allowing the deforestation rates and changes in spatial drivers to be incorporated into a defense of the existing baseline, or the derivation of a new baseline projection.     

Soybean production and conversion of tropical forest in the Brazilian Amazon: the case of Vilhena, Rondônia

The recent rise in Brazilian soybean production has generated concern among the environmental community and some authors that natural tropical environments of the Amazon Basin are being converted to soybean fields. Proponents of soybean production counter that soybeans represent a viable agricultural commodity for the region; environmental concern is unwarranted, because new soybean fields are replacing already deforested or otherwise transformed lands. Both arguments have been made without comprehensive study and measure of land-use/land-cover (LULC) in areas undergoing expansion of soybean production. This case study, conducted in the municipality of Vilhena, Rond?nia, Brazil, in the southwestern Amazon Basin, uses remote sensing to evaluate the LULC accompanying this municipality's large growth in soybean production from 1996 to 2001. Forests are being converted for soybean production, but most of the production increase appears attributable to slight expansion of already existing fields, conversion of already deforested land, and higher yields.     

The transformation of outdoor ammonium nitrate aerosols in the indoor environment

Recent studies associate particulate air pollution with adverse health effects; however, the exposure to indoor particles of outdoor origin is not well characterized, particularly for individual chemical species. We conducted a field study in an unoccupied, single-story residence in Clovis, California to provide data and analyses to address issues important for assessing exposure. We used real-time particle monitors both outdoors and indoors to quantify nitrate, sulfate, and carbon particulate matter of particle size 2.5 μm or less in diameter (PM-2.5). The results show that measured indoor ammonium nitrate concentrations were significantly lower than would be expected based solely on penetration and deposition losses. The additional reduction can be attributed to the transformation indoors of ammonium nitrate into ammonia and nitric acid gases, which are subsequently lost by deposition and sorption to indoor surfaces. A mass balance model that accounts for the kinetics of ammonium nitrate evaporation was able to reproduce measured indoor ammonium nitrate and nitric acid concentrations, resulting in a fitted value of the deposition velocity for nitric acid of 0.56 cm s⁻¹. The results indicate that indoor exposure to outdoor ammonium nitrate in Central Valley of California are small, and suggest that exposure assessments based on total particle mass measured outdoors may obscure the actual causal relationships for indoor exposure to particles of outdoor origin.     

Pesticides in rainfall in Europe

Papers and published reports investigating the presence of pesticides in rainfall in Europe were reviewed. Approximately half of the compounds that were analysed for were detected. For those detected, most concentrations were below about 100 ng/l, but larger concentrations, up to a few thousand nanograms per litre, were detected occasionally at most monitoring sites. The most frequently detected compounds were lindane (gamma-HCH) and its isomer (alpha-HCH), which were detected on 90-100% of sampling occasions at most of the sites where they were monitored. For compounds developed more recently, detection was usually limited to the spraying season. A classification of pesticides according to their deposition pattern is proposed.     

Power models and average ship parameter effects on marine emissions inventories

Maritime greenhouse gas emissions are projected to increase significantly by 2050, highlighting the need for reliable inventories as a first step in analyzing ship emission control policies. The impact of ship power models on marine emissions inventories has garnered little attention, with most inventories employing simple, load-factor-based models to estimate ship power consumption. The availability of more expansive ship activity data provides the opportunity to investigate the inventory impacts of adopting complex power models. Furthermore, ship parameter fields can be sparsely populated in ship registries, making gap-filling techniques and averaging processes necessary. Therefore, it is important to understand of the impact of averaged ship parameters on ship power and emission estimations. This paper examines power estimation differences between results from two complex, resistance-based and two simple, load-factor-based power models on a baseline inventory with unique ship parameters. These models are additionally analyzed according to their sensitivities toward average ship parameters. Automated Identification System (AIS) data from a fleet of commercial marine vessels operating over a 6-month period off the coast of the southwestern United States form the basis of the analysis. To assess the inventory impacts of using averaged ship parameters, fleet-level carbon dioxide (CO₂) emissions are calculated using ship parameter data averaged across ship types and their subtype size classes. Each of the four ship power models are used to generate four CO₂ emissions inventories, and results are compared with baseline estimates for the same sample fleet where no averaged values were used. The results suggest that a change in power model has a relatively high impact on emission estimates. They also indicate relatively little sensitivity, by all power models, to the use of ship characteristics averaged by ship and subtype.

Implications: Commercial marine vessel emissions inventories were calculated using four different models for ship engine power. The calculations used 6 months of Automated Identification System (AIS) data from a sample of 248 vessels as input data. The results show that more detailed, resistance-based models tend to estimate a lower propulsive power, and thus lower emissions, for ships than traditional load-factor-based models. Additionally, it was observed that emission calculations using averaged values for physical ship parameters had a minimal impact on the resulting emissions inventories.     

Rapporteurs' report on discussions at the workshop on excess nitrogen deposition, Leatherhead, September 1987

This paper reports major points from the discussions which took place during the Workshop on Excess Nitrogen Deposition.     

An inter-laboratory study to test the ability of amendments to reduce the availability of Cd, Pb, and Zn in situ

An international inter-laboratory research program investigated the effectiveness of in situ remediation of soils contaminated by cadmium, lead and zinc, measuring changes in soil and soil solution chemistry, plants and soil microbiota. A common soil, from mine wastes in Jasper County MO, was used. The soil was pH 5.9, had low organic matter (1.2 g kg(-1) C) and total Cd, Pb, and Zn concentrations of 92, 5022, and 18 532 mg kg(-1), respectively. Amendments included lime, phosphorus (P), red mud (RM), cyclonic ashes (CA), biosolids (BIO), and water treatment residuals (WTR). Both soil solution and NH4NO3 extractable metals were decreased by all treatments. Phytotoxicity of metals was reduced, with plants grown in P treatments having the highest yields and lowest metal concentration (0.5, 7.2 and 406 mg kg(-1) Cd, Pb, and Zn). Response of soil micro-organisms was similar to plant responses. Phosphorus addition reduced the physiologically based extraction test Pb from 84% of total Pb extracted in the untreated soil to 34.1%.     

Improved recovery of repeat intoxicated drivers using fingernails and blood spots to monitor alcohol and other substance abuse

Objectives: This study reports the results of a pilot program in Kenosha County that used a combination of direct biomarkers extracted from blood spots and nails to monitor repeat intoxicated drivers for their use of alcohol and drugs with a detection window spanning from 3 weeks to several months. The objectives were to test whether the direct biomarkers phosphatidylethanol (PEth), ethylglucuronide (EtG), and 5 drug metabolites would (1) help assessors obtain a more objective evaluation of repeat offenders during the assessment interview, (2) allow for timely identification of relapses and improve classification of drivers into risk categories, and (3) predict recidivism by identifying offenders most likely to obtain a subsequent operating while intoxicated (OWI) offense within 4 years of enrollment in the program.

Methods: All (N = 261) repeat offenders were tested using PEth obtained from blood spots and EtG obtained from fingernails; 159 participants were also tested for a 5 drugs of abuse nail panel. Drivers were tested immediately after the assessment interview (baseline) and at 3, 6, 9, and 12 months after baseline. Based on biomarker results and self-reports of abstinence, offenders were classified into different risk categories and required to follow specific testing timelines based on the program's decision tree.

Results: The baseline analysis shows that 60% of drivers tested positive for alcohol biomarkers (EtG, PEth, or both) at the assessment interview, with lower detection rates (0–11%) for the 5 drug metabolites. The comparison of biomarkers results to self-reports of abstinence identified 28% of all offenders as high risk and assigned them to more frequent testing and more intense monitoring. The longitudinal analysis shows that 56% (completers) of participants completed the program successfully and the remaining 44% (noncompliant) terminated prematurely. Two thirds (68%) of the completers were able to reduce or control their drinking and one third relapsed at least one time during their mandated monitoring periods. After a brief intervention by the assessors, 79% of relapsers tested negative for biomarkers in their repeat tests. The rearrest analysis showed that offenders classified in the noncompliant and relapsers groups were 7 times more likely to receive a new OWI 4 years after enrollment compared to drivers classified as abstainers or controllers. Refractory drivers were monitored the longest and reported no subsequent rearrests.

Conclusion: These findings demonstrate the benefits of more individualized interventions with repeat OWI offenders and calls for further development of multimodal approaches in traffic medicine including those that use direct alcohol biomarkers as evidence-based practices to reduce recidivism.     

Achieving forest carbon information with higher certainty: A five-part plan

International negotiations on the inclusion of land use activities into an emissions reduction system for the UN Framework Convention on Climate Change (UNFCCC) have been partially hindered by the technical challenges of measuring, reporting, and verifying greenhouse gas (GHG) emissions and the policy issues of leakage, additionality, and permanence. This paper outlines a five-part plan for estimating forest carbon stocks and emissions with the accuracy and certainty needed to support a policy for Reducing Emissions from Deforestation and forest Degradation, forest conservation, sustainable management of forests, and enhancement of forest carbon stocks (the REDD-plus framework considered at the UNFCCC COP-15) in developing countries. The plan is aimed at UNFCCC non-Annex 1 developing countries, but the principles outlined are also applicable to developed (Annex 1) countries. The parts of the plan are: (1) Expand the number of national forest carbon Measuring, Reporting, and Verification (MRV) systems with a priority on tropical developing countries; (2) Implement continuous global forest carbon assessments through the network of national systems; (3) Achieve commitments from national space agencies for the necessary satellite data; (4) Establish agreed-on standards and independent verification processes to ensure robust reporting; and (5) Enhance coordination among international and multilateral organizations.