Solid-phase extraction using hierarchical organosilicates for enhanced detection of nitroenergetic targets

A novel porous organosilicate material was evaluated for application as a solid phase extraction sorbent for preconcentration of nitroenergetic targets from aqueous solution prior to HPLC analysis. The performance of the sorbent in spiked deionized water, groundwater, and surface water was evaluated. Targets considered included 2,4,6-trinitrotoluene, 2,4-dinitrotoluene, RDX, HMX, and nitroglycerin. The sorbent was shown to provide improved performance over Sep-Pak RDX. The impact of complex matrices on target preconcentration by the sorbent was also found to be less dramatic than that observed for LiChrolut EN. The impact of changes in pH on target preconcentration was considered. Aqueous soil extracts generated from samples collected at sites of ordnance testing were also used to evaluate the materials. The results presented here demonstrate the potential of this novel sorbent for application as a solid phase extraction material for the preconcentration of nitroenergetic targets from aqueous solutions.     

Use of a low‐cost substrate in a continuous recirculation process to stimulate plumewide anaerobic dechlorination of chlorinated solvents

Over the past 20 years, significant time and money have been spent on better understanding and successfully applying bioremediation in the field. The results of these efforts provide a deeper un‐derstanding of aerobic and anaerobic microbial processes, the microbial species and environ‐mental conditions that are desirable for specific degradation pathways, and the limitations that may prevent full‐scale bioremediation from being successfully applied in heterogeneous subsur‐face environments. Numerous substrates have been identified as effective electron donors to stimulate anaerobic dechlorination of chlorinated ethenes, but methods of delivering these sub‐strates for in situ bioremediation (direct‐push injections, slug injections, high‐pressure injections, fracture wells, etc.) have yet to overcome the main limitation of achieving contact between these substrates and the contaminants. Therefore, although it is important (from a full‐scale remedia‐tion standpoint) to select an appropriate, low‐cost substrate that can be supplied in sufficient quantity to promote remediation of a large source area and its associated plume, it is equally im‐portant to ensure that the substrate can be delivered throughout the impacted plume zone. Failure to achieve substrate delivery and contact within the chlorinated solvent plume usually re‐sults in wasted money and limited remediation benefit. Bioremediation is a contact technology that cannot be effectively implemented on a large scale unless a method for rapidly delivering the low‐cost substrate across the entire source and plume areas is utilized. Unfortunately, many cur‐rent substrate delivery methods are not achieving sitewide distribution or treatment of the sorbed contaminant mass that exists in the organic fraction of a soil matrix. The following discussion sum‐marizes substrate delivery using an aggressive groundwater recirculation approach that can achieve plumewide contact between the contaminants and substrate, thus accelerating dechlori‐nation rates and shortening the overall remediation time frame. © 2006 Wiley Periodicals, Inc.     

Anticoagulant rodenticide exposure in raptors from Ontario,Canada

Environmental Science and Pollution Research - Anticoagulant rodenticides (ARs) are used globally to control rodent pest infestations in both urban and agricultural settings. It is well documented...     

On estimating the exponent of power-law frequency distributions

Power-law frequency distributions characterize a wide array of natural phenomena. In ecology, biology, and many physical and social sciences, the exponents of these power laws are estimated to draw inference about the processes underlying the phenomenon, to test theoretical models, and to scale up from local observations to global patterns. Therefore, it is essential that these exponents be estimated accurately. Unfortunately, the binning-based methods traditionally used in ecology and other disciplines perform quite poorly. Here we discuss more sophisticated methods for fitting these exponents based on cumulative distribution functions and maximum likelihood estimation. We illustrate their superior performance at estimating known exponents and provide details on how and when ecologists should use them. Our results confirm that maximum likelihood estimation outperforms other methods in both accuracy and precision. Because of the use of biased statistical methods for estimating the exponent, the conclusions of several recently published papers should be revisited.     

Glucosinolates and trichomes track tissue value in two sympatric mustards

Glucosinolates, trichomes, nitrogen, and carbon are not distributed uniformly through the canopies of mustards. In this study, we asked whether glucosinolate concentrations and trichome densities in two sympatric mustards, Brassica kaber and B. nigra, are highest in tissues of greatest value to the plant. We also asked whether nitrogen or carbon content is the stronger predictor of tissue value, and what fraction of each resource is incorporated in glucosinolates. To quantify tissue values, we removed three equal-area fractions (lower, middle, and upper) from the canopies of B. kaber and B. nigra in the greenhouse, as well as whole canopies of naturally growing B. nigra in the field, at two times during growth and measured reductions in their performance relative to controls. We also measured trichome density in both experiments, as well as glucosinolate, nitrogen, and carbon concentrations for the equal-area fractions in the greenhouse. We found that upper leaves had the highest glucosinolate concentrations, trichome densities, and tissue values. Furthermore, young plants in the field had higher trichome densities and tissue values than did older plants. Collectively, these data provide strong support for optimal defense theory and are among the first such evidence for glucosinolates and for physical defenses. The positive relationship between trichome density and tissue value was strong even after we accounted for the effects of leaf expansion. While nitrogen and carbon have both received attention as currencies for trade-offs, our data suggest that nitrogen concentration is a significantly better predictor of tissue value in these two mustard species. Interestingly, <1% of the nitrogen or carbon in leaves was incorporated in glucosinolates, which may explain why glucosinolates lack a consistent response to nitrogen fertilization.     

Estimating survival rates of uncatchable animals: the myth of high juvenile mortality in reptiles

Survival rates of juvenile reptiles are critical population parameters but are difficult to obtain through mark-recapture programs because these small, secretive animals are rarely caught. This scarcity has encouraged speculation that survival rates of juveniles are very low, and we test this prediction by estimating juvenile survival rates indirectly. A simple mathematical model calculates the annual juvenile survival rate needed to maintain a stable population size, using published data on adult survival rates, reproductive output, and ages at maturity in 109 reptile populations encompassing 57 species. Counter to prediction, estimated juvenile survival rates were relatively high (on average, only about 13% less than those of conspecific adults) and highly correlated with adult survival rates. Overall, survival rates during both juvenile and adult life were higher in turtles than in snakes, and higher in snakes than in lizards. As predicted from life history theory, rates of juvenile survival were higher in species that produce large offspring, and higher in viviparous squamates than in oviparous species. Our analyses challenge the widely held belief that juvenile reptiles have low rates of annual survival and suggest instead that sampling problems and the elusive biology of juvenile reptiles have misled researchers in this respect.     

Habitat-mediated foraging limitations drive survival bottlenecks for juvenile salmon

Realistic population models and effective conservation strategies require a thorough understanding of mechanisms driving stage-specific mortality. Mortality bottlenecks for many species occur in the juvenile stage and are thought to result from limitation on food or foraging habitat during a "critical period" for growth and survival. Without a way to account for maternal effects or to measure integrated consumption rates in the field, it has been virtually impossible to test these relationships directly. Hence uncertainties about mechanisms underlying such bottlenecks remain. In this study we randomize maternal effects across sites and apply a new method for measuring consumption integrated over weeks to months to test the hypothesis that food limitation drives early-season juvenile mortality bottlenecks in Atlantic salmon (Salmo salar). Using natural signatures of geologically derived cesium (133Cs), we estimated consumption rates of >400 fry stocked into six streams. Two to four weeks after stocking, consumption was extremely low across sites (0.005 g x g(-1) x d(-1)) and was predicted to be below maintenance rations (i.e., yielding negative energy balances) for the majority of individuals from five of six sites. However, consumption during this time was positively correlated with growth rates and survival (measured at the end of the growing season). In contrast, consumption rates increased in mid- (0.030 g x g(-1) x d(-1)) and late (0.035 g x g(-1) x d(-1)) seasons, but juvenile survival and consumption were not correlated, and correlations between growth and consumption were weak. These findings are consistent with predictions of a habitat-based bioenergetic model constructed using the actual stream positions of the individual fish in the present study, which indicates that habitat-based models capture important environmental determinants of juvenile growth and survival. Hence, by combining approaches, reducing maternal effects and controlling initial conditions, we offer a general framework for linking foraging with juvenile survival and present the first direct consumption-based evidence for the early season bottleneck hypothesis.     

Southern Ocean biogeography and taxonomic resolution: what’s in the name?

We examined the taxonomic resolution of zooplankton data required to identify ocean basin scale biogeographic zonation in the Southern Ocean. A 2,154 km transect was completed south of Australia. Sea surface temperature (SST) measured at 1 min intervals showed that seven physical zones were sampled. Zooplankton were collected at a spatial resolution of ~9.2 km with a continuous plankton recorder, identified to the highest possible taxonomic resolution and enumerated. Zooplankton assemblage similarity between samples was calculated using the Bray–Curtis index for the taxonomic levels of species, genus, family, order and class after first log₁₀(x + 1) (LA) and then presence/absence (PA) transformation of abundance data. Although within and between zone sample similarity increased with decreasing taxonomic resolution, for both data transformations, cluster analysis demonstrated that the biogeographic separation of zones remained at all taxonomic levels when using LA data. ANOSIM confirmed this, detecting significant differences in zooplankton assemblage structure between all seven a priori determined physical zones for all taxonomic levels when using the LA data. In the case of the PA data for the complete data set, and both LA and PA data for a crustacean only data set, no significant differences were detected between zooplankton assemblages in the Polar frontal zone (PFZ) and inter-PFZ at any taxonomic level. Loss of information at resolutions below the species level, particularly in the PA data, prevented the separation of some zones. However, the majority of physical zones were biogeographically distinct from species level to class using both LA and PA transformations. Significant relationships between SST and zooplankton community structure, summarised as NMDS scores, at all taxonomic levels, for both LA and PA transformations, and complete and crustacean only data sets, highlighted the biogeographic relevance of low resolution taxonomic data. The retention of biogeographic information in low taxonomic resolution data shows that data sets collected with different taxonomic resolutions may be meaningfully merged for the post hoc generation of Southern Ocean time series.     

Effects of sampling error and temporal correlations in population growth on process variance estimators

Estimates of a population’s growth rate and process variance from time-series data are often used to calculate risk metrics such as the probability of quasi-extinction, but temporal correlations in the data from sampling error, intrinsic population factors, or environmental conditions can bias process variance estimators and detrimentally affect risk predictions. It has been claimed (McNamara and Harding, Ecol Lett 7:16–20, 2004) that estimates of the long-term variance that incorporate observed temporal correlations in population growth are unaffected by sampling error; however, no estimation procedures were proposed for time-series data. We develop a suite of such long-term variance estimators, and use simulated data with temporally autocorrelated population growth and sampling error to evaluate their performance. In some cases, we get nearly unbiased long-term variance estimates despite ignoring sampling error, but the utility of these estimators is questionable because of large estimation uncertainty and difficulties in estimating correlation structure in practice. Process variance estimators that ignored temporal correlations generally gave more precise estimates of the variability in population growth and of the probability of quasi-extinction. We also found that the estimation of probability of quasi-extinction was greatly improved when quasi-extinction thresholds were set relatively close to population levels. Because of precision concerns, we recommend using simple models for risk estimates despite potential biases, and limiting inference to quantifying relative risk; e.g., changes in risk over time for a single population or comparative risk among populations.     

Simulating dynamic and mixed-severity fire regimes: A process-based fire extension for LANDIS-II

Fire regimes result from reciprocal interactions between vegetation and fire that may be further affected by other disturbances, including climate, landform, and terrain. In this paper, we describe fire and fuel extensions for the forest landscape simulation model, LANDIS-II, that allow dynamic interactions among fire, vegetation, climate, and landscape structure, and incorporate realistic fire characteristics (shapes, distributions, and effects) that can vary within and between fire events. We demonstrate the capabilities of the new extensions using two case study examples with very different ecosystem characteristics: a boreal forest system from central Labrador, Canada, and a mixed conifer system from the Sierra Nevada Mountains (California, USA). In Labrador, comparison between the more complex dynamic fire extension and a classic fire simulator based on a simple fire size distribution showed little difference in terms of mean fire rotation and potential severity, but cumulative burn patterns created by the dynamic fire extension were more heterogeneous due to feedback between fuel types and fire behavior. Simulations in the Sierra Nevada indicated that burn patterns were responsive to topographic features, fuel types, and an extreme weather scenario, although the magnitude of responses depended on elevation. In both study areas, simulated fire size and resulting fire rotation intervals were moderately sensitive to parameters controlling the curvilinear response between fire spread and weather, as well as to the assumptions underlying the correlation between weather conditions and fire duration. Potential fire severity was more variable within the Sierra Nevada landscape and also was more sensitive to the correlation between weather conditions and fire duration. The fire modeling approach described here should be applicable to questions related to climate change and disturbance interactions, particularly within locations characterized by steep topography, where temporally or spatially dynamic vegetation significantly influences spread rates, where fire severity is variable, and where multiple disturbance types of varying severities are common.