α1-Microglobulin levels and correlation with cadmium and other metals in urine of non-smoking women among general populations in Japan

The present study was initiated to examine urinary α₁-microglobulin (α₁-MG-U) levels among non-smoking women in the general population in Japan. A previously established database on spot urine samples from adult woman volunteers in 10 non-polluted areas all over Japan was re-examined. The data examined were on α₁-MG-U, cadmium, calcium, magnesium and zinc levels in urine (Cd-U, Ca-U, Mg-U and Zn-U, respectively), urinary creatinine (CR or cr), urine specific gravity (SG or sg), smoking habits and age. Thus, 8975 never-smoking women were selected for statistical analyses. The grand geometric mean (GM) for α₁-MG-U among the population was 2.1?mg/L or 2.5?mg/g?cr, depending on the correction for urine density. It was 1.1?µg/L or 1.3?µg/g?cr for GM Cd-U. The inter-area difference in α₁-MG-U was <1.5?mg/g?cr or <0.7?mg/L; the area with the highest or lowest GM Cd-U was not always highest or lowest in GM α₁-MG-U. The correlation coefficient (0.53) between log?Cd-U and log?α₁-MG-U (both without urine density correction) became substantially smaller when the analyte levels were corrected for CR (0.25) or SG (0.26). In multiple regression analysis, the power of influence of the five independent variables (log?Cd-U, Ca-U, Mg-U, Zn-U and age) in combination was small (R ²?≦?0.13). In contrast, logistic regression analysis suggested that α₁-MG-U might be elevated as a function of an increase in Cd-U, depending on the cut-off values. Discussion was made on dose (Cd-U_cr) and response (α₁-MG-U_cr) relationship based on information available in literatures to show that the increment in α₁-MG-U_cr per Cd-U_cr was much greater when Cd-U_cr was large, e.g., in excess of 10?µg/g?cr.     

Combining Measures of Dispersal to Identify Conservation Strategies in Fragmented Landscapes

Abstract: Understanding the way in which habitat fragmentation disrupts animal dispersal is key to identifying effective and efficient conservation strategies. To differentiate the potential effectiveness of 2 frequently used strategies for increasing the connectivity of populations in fragmented landscapes—corridors and stepping stones—we combined 3 complimentary methods: behavioral studies at habitat edges, mark‐recapture, and genetic analyses. Each of these methods addresses different steps in the dispersal process that a single intensive study could not address. We applied the 3 methods to the case study of Atrytonopsis new species 1, a rare butterfly endemic to a partially urbanized stretch of barrier islands in North Carolina (U.S.A.). Results of behavioral analyses showed the butterfly flew into urban and forested areas, but not over open beach; mark‐recapture showed that the butterfly dispersed successfully through short stretches of urban areas (<500 m); and genetic studies showed that longer stretches of forest (>5 km) were a dispersal barrier, but shorter stretches of urban areas (≤5 km) were not. Although results from all 3 methods indicated natural features in the landscape, not urbanization, were barriers to dispersal, when we combined the results we could determine where barriers might arise: forests restricted dispersal for the butterfly only when there were long stretches with no habitat. Therefore, urban areas have the potential to become a dispersal barrier if their extent increases, a finding that may have gone unnoticed if we had used a single approach. Protection of stepping stones should be sufficient to maintain connectivity for Atrytonopsis new species 1 at current levels of urbanization. Our research highlights how the use of complementary approaches for studying animal dispersal in fragmented landscapes can help identify conservation strategies.     

Projected Climate Impacts for the Amphibians of the Western Hemisphere

Abstract: Given their physiological requirements, limited dispersal abilities, and hydrologically sensitive habitats, amphibians are likely to be highly sensitive to future climatic changes. We used three approaches to map areas in the western hemisphere where amphibians are particularly likely to be affected by climate change. First, we used bioclimatic models to project potential climate‐driven shifts in the distribution of 413 amphibian species based on 20 climate simulations for 2071–2100. We summarized these projections to produce estimates of species turnover. Second, we mapped the distribution of 1099 species with restricted geographic ranges. Finally, using the 20 future climate‐change simulations, we mapped areas that were consistently projected to receive less seasonal precipitation in the coming century and thus were likely to have altered microclimates and local hydrologies. Species turnover was projected to be highest in the Andes Mountains and parts of Central America and Mexico, where, on average, turnover rates exceeded 60% under the lower of two emissions scenarios. Many of the restricted‐range species not included in our range‐shift analyses were concentrated in parts of the Andes and Central America and in Brazil's Atlantic Forest. Much of Central America, southwestern North America, and parts of South America were consistently projected to experience decreased precipitation by the end of the century. Combining the results of the three analyses highlighted several areas in which amphibians are likely to be significantly affected by climate change for multiple reasons. Portions of southern Central America were simultaneously projected to experience high species turnover, have many additional restricted‐range species, and were consistently projected to receive less precipitation. Together, our three analyses form one potential assessment of the geographic vulnerability of amphibians to climate change and as such provide broad‐scale guidance for directing conservation efforts.     

Temporal Analysis of Genetic Structure to Assess Population Dynamics of Reintroduced Swift Foxes

Reintroductions are increasingly used to reestablish species, but a paucity of long‐term postrelease monitoring has limited understanding of whether and when viable populations subsequently persist. We conducted temporal genetic analyses of reintroduced populations of swift foxes (Vulpes velox) in Canada (Alberta and Saskatchewan) and the United States (Montana). We used samples collected 4 years apart, 17 years from the initiation of the reintroduction, and 3 years after the conclusion of releases. To assess program success, we genotyped 304 hair samples, subsampled from the known range in 2000 and 2001, and 2005 and 2006, at 7 microsatellite loci. We compared diversity, effective population size, and genetic connectivity over time in each population. Diversity remained stable over time and there was evidence of increasing effective population size. We determined population structure in both periods after correcting for differences in sample sizes. The geographic distribution of these populations roughly corresponded with the original release locations, which suggests the release sites had residual effects on the population structure. However, given that both reintroduction sites had similar source populations, habitat fragmentation, due to cropland, may be associated with the population structure we found. Although our results indicate growing, stable populations, future connectivity analyses are warranted to ensure both populations are not subject to negative small‐population effects. Our results demonstrate the importance of multiple sampling years to fully capture population dynamics of reintroduced populations. Análisis Temporal de la Estructura Genética para Evaluar la Dinámica Poblacional de Zorros (Vulpes velox) Reintroducidos     

Paradigms for parasite conservation

Parasitic species, which depend directly on host species for their survival, represent a major regulatory force in ecosystems and a significant component of Earth's biodiversity. Yet the negative impacts of parasites observed at the host level have motivated a conservation paradigm of eradication, moving us farther from attainment of taxonomically unbiased conservation goals. Despite a growing body of literature highlighting the importance of parasite‐inclusive conservation, most parasite species remain understudied, underfunded, and underappreciated. We argue the protection of parasitic biodiversity requires a paradigm shift in the perception and valuation of their role as consumer species, similar to that of apex predators in the mid‐20th century. Beyond recognizing parasites as vital trophic regulators, existing tools available to conservation practitioners should explicitly account for the unique threats facing dependent species. We built upon concepts from epidemiology and economics (e.g., host‐density threshold and cost‐benefit analysis) to devise novel metrics of margin of error and minimum investment for parasite conservation. We define margin of error as the risk of accidental host extinction from misestimating equilibrium population sizes and predicted oscillations, while minimum investment represents the cost associated with conserving the additional hosts required to maintain viable parasite populations. This framework will aid in the identification of readily conserved parasites that present minimal health risks. To establish parasite conservation, we propose an extension of population viability analysis for host–parasite assemblages to assess extinction risk. In the direst cases, ex situ breeding programs for parasites should be evaluated to maximize success without undermining host protection. Though parasitic species pose a considerable conservation challenge, adaptations to conservation tools will help protect parasite biodiversity in the face of an uncertain environmental future.     

Bayesian Small Area Models for Assessing Wildlife Conservation Risk in Patchy Populations

Abstract:  Species conservation risk assessments require accurate, probabilistic, and biologically meaningful maps of population distribution. In patchy populations, the reasons for discontinuities are not often well understood. We tested a novel approach to habitat modeling in which methods of small area estimation were used within a hierarchical Bayesian framework. Amphibian occurrence was modeled with logistic regression that included third-order drainages as hierarchical effects to account for patchy populations. Models including the random drainage effects adequately represented species occurrences in patchy populations of 4 amphibian species in the Oregon Coast Range (U.S.A.). Amphibian surveys from other locations within the same drainage were used to calibrate local drainage-scale effects. Cross-validation showed that prediction errors for calibrated models were 77% to 86% lower than comparable regionally constructed models, depending on species. When calibration data were unavailable, small area and regional models performed similarly, although poorly. Small area estimation models complement wildlife ecology and habitat studies, and can help managers develop a regional picture of the conservation status for relatively rare species.     

An assessment methodology for successional systems. I. Null models and the regulatory framework

Standard procedures for evaluating environmental impact involve comparison between before and after conditions or scenarios or between treatment and control site pairs. In many cases, however, endogenous directional change (natural succession) is expected to occur at a significant rate over the period of concern, particularly for manmade systems such as impoundments. Static evaluations do not provide an adequate approach to such problems. A new evaluation frame is proposed. Nominal system behavior over time is characterized by a stochastic envelope around a nominal trajectory. We show that both the state variance and the sampling variance can change over time. In this context, environmental regulations can be framed as constraints, targets, or conformance to ideal trajectories. Statistical tests for determining noncompliance are explored relative to process variance, sample error, and sample size. Criteria are elucidated for choosing properties to monitor, sample size, and sampling interval.     

Differences among model simulations of climate change on the scale of resource regions

The climate simulations from atmospheric general circulation models (GCMs) are often used to analyze the potential effects of climate change on environmental resources. It has been demonstrated that there are differences among the simulations from various GCMs, on spatial scales ranging from global to regional. This paper quantifies the differences in temperature and precipitation simulated by three major GCMs for four specific regions: an agricultural region (the North American winter wheat belt), a hydrologic region (the Great Basin), a demographic region (the high-density population corridor of the northeast United States), and a political region (the state of Texas). Both the current (control) climate and the climatic response to a doubling of atmospheric carbon dioxide (CO₂) are consideredIn each region, even when the data are averaged on a seasonal basis, marked differences occurred in the areal average climate simulated by the different GCMs for both the control climate and the doubled-CO₂ climate. Thus, climate impact studies based on the simulations of more than one GCM could easily yield a range of possible results     

COMPARISON OF REGRESSION AND TIME-SERIES METHODS FOR SYNTHESIZING MISSING STREAMFLOW RECORDS1

ABSTRACT: Regression and time-series techniques have been used to synthesize and predict the stream flow at the Foresta Bridge gage from information at the upstream Pohono Bridge gage on the Merced River near Yosemite National Park. Using the available data from two time periods (calendar year 1979 and water year 1986), we evaluated the two techniques in their ability to model the variation in the observed flows and in their ability to predict stream flow at the Foresta Bridge gage for the 1979 time period with data from the 1986 time period. Both techniques produced reasonably good estimates and forecasts of the flow at the downstream gage. However, the regression model was found to have a significant amount of autocorrelation in the residuals, which the time-series model was able to eliminate. The time-series technique presented can be of great assistance in arriving at reasonable estimates of flow in data sets that have large missing portions of data.