RCRA Cleanup Reforms

The Environmental Protection Agency's (EPA's) administrative reforms offer results‐oriented cleanup guidance that emphasizes flexibility and practical approaches. © 2001 John Wiley & Sons, Inc.     

Improved estimates of certainty in stable-isotope-based methods for tracking migratory animals.

The use of stable-hydrogen isotopes (deltaD) has become a common tool for estimating geographic patterns of movement in migratory animals. This method relies on broad and relatively predictable geographic patterning in deltaD values of precipitation, but these patterns are not estimated without error. In addition, deltaD measurements are relatively imprecise, particularly for organic tissue. Most models for estimating geographic locations have ignored these sources of error. Common modeling approaches include regression, range-matching, and likelihood-based assignment tests (including discriminant analysis). Here, we show the benefits of a simple stochastic extension to likelihood-based assignment tests that incorporates two estimable sources of error and describe the resulting influence on the certainty of assigning breeding origins for wintering American Redstarts (Setophaga ruticilla), a small Nearctic-Neotropical migratory bird. Through simulation, we incorporated both spatial interpolation error associated with models of deltaD in precipitation and analytical error associated with the measurement of deltaD in tissue samples. In general, assignments that did not include these sources of error fell within the ranges of the stochastic results, but the difference in proportion of birds assigned to any one breeding region varied by as much as 54%. To explore how the distribution of assignments generated from error models influenced the application of these results, we developed a simple model of winter habitat loss. We removed the proportion of Redstarts wintering at a particular site from the global population and then used the isotope-based assignments to predict the resulting population declines for each breeding region. This gave distributions of change in population sizes, some of which included no change or even a population increase. The sources of error we modeled may challenge the degree of certainty in the use of stable-isotope-based data on connectivity to predict population dynamics of migratory animals. We suggest that stronger inference will result from incorporating these sources of error into future studies that use deltaD or other stable isotopes to infer the geographic origin of individuals.     

A genoscape-network model for conservation prioritization in a migratory bird

Migratory animals are declining worldwide and coordinated conservation efforts are needed to reverse current trends. We devised a novel genoscape-network model that combines genetic analyses with species distribution modeling and demographic data to overcome challenges with conceptualizing alternative risk factors in migratory species across their full annual cycle. We applied our method to the long distance, Neotropical migratory bird, Wilson's Warbler (Cardellina pusilla). Despite a lack of data from some wintering locations, we demonstrated how the results can be used to help prioritize conservation of breeding and wintering areas. For example, we showed that when genetic, demographic, and network modeling results were considered together it became clear that conservation recommendations will differ depending on whether the goal is to preserve unique genetic lineages or the largest number of birds per unit area. More specifically, if preservation of genetic lineages is the goal, then limited resources should be focused on preserving habitat in the California Sierra, Basin Rockies, or Coastal California, where the 3 most vulnerable genetic lineages breed, or in western Mexico, where 2 of the 3 most vulnerable lineages overwinter. Alternatively, if preservation of the largest number of individuals per unit area is the goal, then limited conservation dollars should be placed in the Pacific Northwest or Central America, where densities are estimated to be the highest. Overall, our results demonstrated the utility of adopting a genetically based network model for integrating multiple types of data across vast geographic scales and better inform conservation decision-making for migratory animals.     

Extinction rate of discovered and undiscovered plants in Singapore

Extinction is a key issue in the assessment of global biodiversity. However, many extinction rate measures do not account for species that went extinct before they could be discovered. The highly developed island city–state of Singapore has one of the best-documented tropical floras in the world. This allowed us to estimate the total rate of floristic extinctions in Singapore since 1822 after accounting for sampling effort and crypto extinctions by collating herbaria records. Our database comprised 34,224 specimens from 2076 native species, of which 464 species (22%) were considered nationally extinct. We assumed that undiscovered species had the same annual per-species extinction rates as discovered species and that no undiscovered species remained extant. With classical and Bayesian algorithms, we estimated that 304 (95% confidence interval, 213–414) and 412 (95% credible interval, 313–534) additional species went extinct before they could be discovered, respectively; corresponding total extinction rate estimates were 32% and 35% (range 30–38%). We detected violations of our 2 assumptions that could cause our extinction estimates, particularly the absolute numbers, to be biased downward. Thus, our estimates should be treated as lower bounds. Our results illustrate the possible magnitudes of plant extirpations that can be expected in the tropics as development continues.     

Park isolation in anthropogenic landscapes: land change and livelihoods at park boundaries in the African Albertine Rift

Regional Environmental Change - Landscapes are changing rapidly in regions where rural people live adjacent to protected parks and reserves. This is the case in highland East Africa, where many...     

Systematic comparison of ILWAS, MAGIC, and ETD watershed acidification models: 3. Mass balance budgets for acid neutralizing capacity

Three watershed acidification models-ILWAS, MAGIC, and ETD-were quantitatively compared to determine model structural differences by using a combination of input mapping and ANC mass balance budgets. Input mapping is a set of rules and algorithms to ensure that consistent input values were simultaneously derived for all three models. ANC budget analysis under current SO4(2-) deposition and a 70% reduction in SO4(2-) deposition allows examination of the relative importance of biogeochemical processes in affecting predictions of ANC or predicted changes in ANC. Model inputs were based on two dissimilar watersheds having characteristics typical of watersheds in the northeastern US. After mapping inputs, the three models predicted values of outflow ANC fluxes that were similar among the models for each watershed and deposition scenario. Within each watershed, the changes in outflow ANC fluxes between the scenarios were similar for the three models. Terrestrial weathering was the major source of ANC for all three models for both watersheds and deposition scenarios. The contributions of other processes to the ANC of the two watersheds were, under certain conditions, model-specific. Cation exchange was responsible for changes in ANC when deposition decreased for the three models. Other processes responsible for changes in ANC between scenarios were SO4(2-) sorption (for MAGIC) and in-lake weathering (for ETD). The processes responsible for the change in ANC from a change in deposition (cation exchange, SO4(2-) sorption, and in-lake weathering) were different from the processes contributing to the absolute ANC for a given deposition scenario (terrestrial weathering). The budget analysis complements an earlier Monte Carlo analysis that showed that the three models are structurally different and that predictions viewed on a relative scale are more similar than absolute scale predictions.     

The prognostic factors in the prenatal diagnosis of the echogenic fetal lung

The prenatal diagnosis of an echogenic fetal lung (EFL) is now often made in the early second trimester using high-resolution ultrasound. This ultrasound appearance is usually caused by a congenital cystic adenomatoid lung malformation (CCAM), an intrapulmonary lung sequestration or obstruction of a major airway. In order to provide prognostic guidelines to parents who may be considering termination of a fetus with these findings, we have analysed a series of 11 cases diagnosed in our centre over the past 2 years in conjunction with 60 cases from major published series. The data suggest that in the absence of non-immune hydrops fetalis (NIHF) or other anomalies, the outcome for the fetuses is excellent, with over 90 per cent survival. Neither early diagnosis (24 weeks) nor the presence of mediastinal shift is a poor prognostic indicator. In addition, it appears that if NIHF is absent at diagnosis, the chance that it will develop as the pregnancy continues is small (6 per cent). Furthermore, there is a significant (up to 30 per cent) chance that this ultrasound finding will resolve in utero. The development of in utero fetal surgical techniques may be the only hope for those hydropic fetuses who appear to have a dismal prognosis.     

Phytoremediation of petroleum hydrocarbons in tropical coastal soils II. microbial response to plant roots and contaminant

GOAL, SCOPE AND BACKGROUND: The goal of this study was to understand the interaction between plants and microorganisms during petroleum-hydrocarbon bioremediation in Pacific Islands coastal soils. Total bacteria and hydrocarbon-degrading microorganisms population dyanamics were examined in the rhizospheres of tropical trees and shrubs, which were evaluated for their phytoremediation potential in a greenhouse experiment. The respective and combined effects of plant roots and diesel contaminant on the microbial populations were determined in relation to diesel fuel depletion. An increase in the grading populations size of the hydrocarbon-degrading populations of microbes, elicited by rhizodeposition, is generally regarded as conducive to an enhanced degradation of petroleum hydrocarbon pollutants in vegetated soil. METHODS: The soil was a coastal sandy loam (pH 7.8) which was artificially contaminated with 10 g of No. 2 diesel fuel/kg soil or left uncontaminated. The pots were irrigated with fertilizer and 1% NaCl. The enumerations were carried out in the contaminated and uncontaminated rhizospheres of three trees, kiawe (Prosopis pallida), milo (Thespesia populnea), and kou (Cordia subcordata) and three shrubs, beach naupaka (Scaevola sericea), false sandalwood (Myoporum sandwicense), and oleander (Nerium oleander). Unplanted control soils were included in the experiment. Total bacteria and phenanthrene-degrading bacteria were enumerated on plates. Diesel- and pristane-degrading microorganisms were enumerated by the most-probable-number technique in tissue-culture plates. RESULTS AND DISCUSSION: All four types of microorganisms responded to the rhizosphere of the 6 plants in uncontaminated soil and to the diesel contaminant in unplanted soil. In contaminated rhizospheres, no effect of the plant on the hydrocarbon-degrader numbers was visible. Total bacteria responded more to the plant roots than to the contaminant. The phenanthrene-degrading bacteria and pristane-degrading microorganisms were more influenced by the contaminant than by the plants. The diesel-degrading microorganisms were equally stimulated by the plants and the contaminant. The numbers of hydrocarbon degraders were similar in the contaminated rhizospheres of the three effective plants (kiawe, kou, and milo) and in those of the three ineffective shrubs. CONCLUSION: The results suggest the quality of the rhizodeposition is plant-dependent and governs the type of diesel-degrader populations that will be enhanced by a given plant. RECOMMENDATIONS AND OUTLOOK: In the proposed phytoremediation-benefit model plant roots maintain high levels of hydrocaron degraders in uncontaminated soil. When the root enters a contaminated zone of soil, those hydrocarbon degraders that prefer the contaminant would switch to the contaminant as a carbon source, effectively removing the hydrocarbons. If the root exudates and the contaminant are equally attractive to the hydrocarbon degraders, the contaminant degradaton would be less effective.     

Partitioning of dioxins and dibenzofurans: Whole blood, blood plasma and adipose tissue

It has become relatively common to estimate human dioxin body burden and to document dioxin exposures by measuring dioxin and dibenzofuran congeners in adipose tissue, whole blood or blood plasma, and reporting these values on a lipid basis. It has not been determined whether these three types of specimens contain identical dioxin and dibenzofuran levels. This paper compares paired plasma and adipose tissue and paired whole blood and adipose tissue in analyses from two groups of patients. The first group consists of twenty U.S. veterans with paired plasma and adipose specimens. The second group consists of four German adults with whole blood compared to adipose tissue. Forty-eight analyses were performed. The results suggest that for some higher chlorinated compounds, such as OCDD, plasma lipid values may be higher than adipose lipid values, but whole blood lipid values for the higher as well as lower chlorinated PCDD/Fs may be relatively similar. On the other hand, the values for the lower chlorinated PCDD/Fs, such as TCDD, are similar in blood plasma, adipose tissue and whole blood. Total PCDD/F dioxin “toxic equivalents” are similar within each of the two series reported here, using the current “International Dioxin Toxic Equivalent” system.     

Improved light extinction reconstruction in interagency monitoring of protected visual environments

The U.S. Environmental Protection Agency (EPA) published the Regional Haze Rule (RHR) in 1999. The RHR default goal is to reduce haze linearly from the baseline period of 2000 through 2004 to natural background in 2064. EPA-recommended method for estimating baseline and natural haze uses the Interagency Monitoring of Protected Visual Environments (IMPROVE) light extinction formula. The IMPROVE formula predicts light extinction from measured aerosol chemical concentrations and estimates of the relative humidity multiplier. On average, the IMPROVE formula overpredicts 6156 nephelometer days (24-hr average measured particle light scattering, bsp) of data by 25%. A new IMPROVED method that reconstructs light extinction using a concentration power law model overpredicts these nephelometer days of data by just 2%. Ignoring the 20% lowest light scattering days, this new IMPROVED formula has a 3% underprediction bias over the 4925 highest nephelometer days with light scattering > or =8 inverse megameters. For comparison, the IMPROVE formula has a 12% overprediction bias for the same days. The IMPROVE formula overprediction averages 77%, 27%, 17%, 9%, and -5% broken down by quintile from lowest to highest nephelometer measured light scattering days. The new IMPROVED formula average overprediction is 21%, -5%, -5%, -2%, and 0%. So, agreement between measured and predicted light scattering improves by modifying the current IMPROVE light extinction formula.