Use of landscape and land use parameters for classification and characterization of watersheds in the mid-Atlantic across five physiographic provinces

The Atlantic Slope Consortium (ASC) is a project designed to develop and test a set of indicators in coastal systems that are ecologically appropriate, economically reasonable, and relevant to society. The suite of indicators will produce integrated assessments of the condition, health and sustainability of aquatic ecosystems based on ecological and socioeconomic information compiled at the scale of estuarine segments and small watersheds. The research mandate of the ASC project is the following:

Using a universe of watersheds, covering a range of social choices, we ask two questions:

• ? How “good” can the environment be, given those social choices?
• ? What is the intellectual model of condition within those choices, i.e., what are the causes of condition and what are the steps for improvement?

As a basis for compiling ecological indicators, a watershed classification system was required for the experimental design. The goal was to develop approximately five categories of watersheds for each physiographic province, utilizing landscape and land use parameters that would be predictive of aquatic resource condition. All 14-digit Hydrologic Unit Code (HUC) watersheds in the Mid-Atlantic region would then be classified according to the regime. Five parameters were utilized for the classification: three land cover categories, consisting of forested, agricultural, and urban, median slope or median elevation, and total variance of land covers in 1-km-radius circles positioned on all stream convergence points in a specified 14-digit?HUC watershed. Cluster analysis utilizing these five parameters resulted in approximately five well-defined watershed classes per physiographic province. The distribution of all watersheds in the Mid-Atlantic region across these categories provides a unique report on the probable condition of watersheds in the region.     

Geospatial indicators of emerging water stress: an application to Africa

This study demonstrates the use of globally available Earth system science data sets for water assessment in otherwise information-poor regions of the world. Geospatial analysis at 8 km resolution shows that 64% of Africans rely on water resources that are limited and highly variable. Where available, river corridor flow is critical in augmenting local runoff, reducing impacts of climate variability, and improving access to freshwater. A significant fraction of cropland resides in Africa's driest regions, with 39% of the irrigation nonsustainable. Chronic overuse and water stress is high for 25% of the population with an additional 13% experiencing drought-related stress once each generation. Paradoxically, water stress for the vast majority of Africans typically remains low, reflecting poor water infrastructure and service, and low levels of use. Modest increases in water use could reduce constraints on economic development, pollution, and challenges to human health. Developing explicit geospatial indicators that link biogeophysical, socioeconomic, and engineering perspectives constitutes an important next step in global water assessment.     

Source of musty odor associated with mucidone

The musty odor previously ascribed to mucidone is due to the presence of a trace contaminant, suspected to be 2-methylisoborneol. Pure mucidone has a sweet, low intensity odor that was overwhelmed by the seemingly insignificant, but highly odoriferous musty-smelling contaminant. This led to the erroneous classification of mucidone among the musty-earthy odorants that have plagued water supplies.     

Satellite telemetry and prey sampling reveal contaminant sources to Pacific Northwest Ospreys.

Migratory behavior can be an important factor in determining contaminant exposure in avian populations. Accumulation of organochlorine (OC) pesticides while birds are wintering in tropical regions has been cited often as the reason for high concentrations in migrant populations. To explore this issue, we satellite tracked 16 Ospreys (Pandion haliaetus) over the period 1996-2003 from breeding sites in British Columbia, Canada, and integrated the results into a database on 15 Ospreys that were satellite tracked over the period 1995-1999, from breeding locations in Washington and Oregon, USA. Data on wintering sites of 31 Ospreys in Mexico and Central America were used for spatially targeted sampling of prey fish. Concentrations of the main organochlorine contaminant, p,p'-dichloro-diphenyl-dichloroethylene (DDE), in fish composites from Mexico ranged from 0.005 to 0.115 nicrog/g wet mass. Significant differences existed among fish families in p,p'-DDE, total dichloro-diphenyl-trichloroethane (sigmaDDT), sigmachlordanes, and total polychlorinated biphenyls (sigmaPCBs). Catfish (family Ariidae) generally had significantly higher levels of DDT metabolites and other organochlorine contaminants compared to other fish families collected. Differences in prey contaminant levels were detected among the collection sites around coastal Mexico, with fish from Veracruz State generally having higher levels of DDT metabolites, sigmachlordanes, sigmaPCBs, and hexachlorobenzene. Eggs collected from 16 nests throughout the Pacific Northwest (nine from British Columbia, seven from Oregon and Washington) where Ospreys had been satellite tagged, showed marked variation in levels of DDT metabolites (p,p'-DDE; range 0.02-10.14 microg/g). Wintering site had no significant effect on contaminant concentrations in sample eggs from those specific Ospreys; rather concentrations of p,p'-DDE, were predicted by breeding sites with highest levels in eggs of Ospreys breeding in the lower Columbia River, consistent with published reports of continued high concentrations of DDT and related compounds in that system.     

Mercury cycling in litter and soil in different forest types in the Adirondack region, New York, USA.

The fate of mercury in decomposing leaf litter and soil is key to understanding the biogeochemistry of mercury in forested ecosystems. We quantified mercury dynamics in decomposing leaf litter and measured fluxes and pools of mercury in litterfall, throughfall, and soil in two forest types of the Adirondack region, New York, USA. The mean content of total mercury in leaf litter increased to 134% of its original mass during two years of decomposition. The accumulation pattern was seasonal, with significant increases in mercury mass during the growing season (+4.9% per month). Litterfall dominated mercury fluxes into the soil in the deciduous forest, whereas throughfall dominated fluxes into the coniferous forest. The increase in mercury mass in decomposing deciduous litter during the growing season was greater than could be accounted for by throughfall inputs during the growing season (P < 0.05), suggesting translocation of mercury from the soil to the decomposing deciduous litter. This internal recycling mechanism concentrates mercury in the organic horizons and retards transport through the soil, thereby increasing the residence time of mercury in the forest floor. A mass balance assessment suggests that the ultimate fate of mercury in the landscape depends upon forest type and associated differences in the delivery and incorporation of mercury into the soil. Our results show that incorporation of mercury into decaying leaf litter increases its residence time in the landscape and may further delay the recovery of surface waters, fish, and associated biota following control of mercury emissions to the atmosphere.     

Comparative tests of reproductive skew in male primates: the roles of demographic factors and incomplete control

Reproductive skew models have been proposed as a unifying framework for understanding animal social systems, but few studies have investigated reproductive skew in a broad evolutionary context. We compiled data on the distribution of mating among males for 31 species of primates and calculated skew indices for each study. We analyzed the determinants of mating skew with phylogenetic comparative methods to investigate two models from reproductive skew theory, the concession model and the tug-of-war model. Mating skew decreased as the number of males increased in multimale groups, suggesting that monopolization of females becomes more difficult when there are more rivals, and therefore supporting the tug-of-war model. We predicted that single males are unable to monopolize receptive females as overlap in female receptivity increases (estrous synchrony) and, as a result, that mating skew decreases. However, we did not find any evidence for a link between female estrous synchrony and male mating skew. Finally, the concession model predicts high skew in male philopatric species relative to species in which males disperse, yet our measures of mating skew showed no significant associations with qualitative scores of male dispersal. More definitive tests of the concession model will require more quantitative measures of relatedness, which are presently unavailable for most primate species in our study. Overall, our results provide support for the tug-of-war model in primates, and the approach developed here can be applied to study comparative patterns of skew in other biological systems.Electronic supplementary material Supplementary material is available in the online version of this article at and is accessible to authorized users.     

Continuous dose-response modeling and risk analysis with the gamma and reciprocal gamma distributions

Kodell and West (1993) describe two methods for calculating pointwise upper confidence limits on the risk function with normally distributed responses and using a certain definition of adverse quantitative effect. But Banga et al. (2000) have shown that these normal theory methods break down when applied to skew data. We accordingly develop a risk analysis model and associated likelihood-based methodology when the response follows either a gamma or reciprocal gamma distribution. The model supposes that the shape (index) parameter k of the response distribution is held fixed while the logarithm of the scale parameter is a linear model in terms of the dose level. Existence and uniqueness of the maximum likelihood estimates is established. Asymptotic likelihood-based upper and lower confidence limits on the risk are solutions of the Lagrange equations associated with a constrained optimization problem. Starting values for an iterative solution are obtained by replacing the Lagrange equations by the lowest order terms in their asymptotic expansions. Three methods are then compared for calculating confidence limits on the risk: (i) the aforementioned starting values (LRAL method), (ii) full iterative solution of the Lagrange equations (LREL method), and (iii) bounds obtained using approximate normality of the maximum likelihood estimates with standard errors derived from the information matrix (MLE method). Simulation is used to assess coverage probabilities for the resulting upper confidence limits when the log of the scale parameter is quadratic in the dose level. Results indicate that coverage for the MLE method can be off by as much as 15% points and converges very slowly to nominal coverage levels as the sample size increases. Coverage for the LRAL and LREL methods, on the other hand, is close to nominal levels unless (a) the sample size is small, say N < 25, (b) the index parameter is small, say k 1, and (c) the direction of adversity is to the left for the gamma distribution or to the right for the reciprocal gamma distribution.     

Direct calculation of likelihood-based benchmark dose levels for quantitative responses

A benchmark dose (BMD) for quantitative responses is a lower confidence limit (LCL) on the effective dose corresponding to a specified risk level r. A commonly adopted method for calculating the BMD is to obtain a pointwise upper confidence curve U(d) on the risk function and then invert this relationship by solving the equation U(d)=r. The solution d is taken to be the BMD. Sciullo et al. (2000) have shown that the coverage achieved by this inversion method is at least as great as the coverage achieved by U (·) but that there is otherwise no general relationship between the two coverage probabilities. The present paper develops a method for direct calculation of the BMD based on the asymptotic distribution of the likelihood ratio statistic. It is further shown that the direct method and the inversion method are equivalent when U (·) is also based on the likelihood ratio. Since the direct method is known to be asymptotically correct, it follows that the LR-based inversion method is also asymptotically correct. However, the direct method is computationally faster and easier to program. Finally, some simulation studies are conducted to assess the small sample coverage probabilities of the direct method when responses follow either a normal or a gamma distribution.