Quantitative PCR analysis of house dust can reveal abnormal mold conditions

Indoor mold concentrations were measured in the dust of moldy homes (MH) and reference homes (RH) by quantitative PCR (QPCR) assays for 82 species or related groups of species (assay groups). About 70% of the species and groups were never or only rarely detected. The ratios (MH geometric mean : RH geometric mean) for 6 commonly detected species (Aspergillus ochraceus, A. penicillioides, A. unguis, A. versicolor, Eurotium group, and Cladosporium sphaerospermum) were >1 (Group I). Logistic regression analysis of the sum of the logs of the concentrations of Group I species resulted in a 95% probability for separating MH from RH. These results suggest that it may be possible to evaluate whether a home has an abnormal mold condition by quantifying a limited number of mold species in a dust sample. Also, four common species of Aspergillus were quantified by standard culturing procedures and their concentrations compared to QPCR results. Culturing underestimated the concentrations of these four species by 2 to 3 orders of magnitude compared to QPCR.     

Using Ion-Exchange Resins to Study Soil Response to Experimental Watershed Acidification

Ion-exchange resins (IER) offer alternative approaches to measuring ionic movement in soils that may have advantages over traditional approaches in some settings, but more information is needed to understand how IER compare with traditional methods of measurement in forested ecosystems. At the Bear Brook Watershed in Maine (BBWM), one of two paired, forested watersheds is treated bi-monthly with S and N (28.8 and 25.2kgha⁻¹yr⁻¹ of S and N, respectively). Both IER and ceramic cup tension lysimeters were used to study soil solution responses after ∼11 years of treatment. Results from both methods showed treatments resulted in the mobilization of base cations and Al, and higher SO₄—S and inorganic N in the treated watershed. Both methods indicated similar differences in results associated with forest type (hardwoods versus softwoods), a result of differences in litter quality and atmospheric aerosol interception capacity. The correlation between lysimeter and IER data for individual analytes varied greatly. Significant correlations were evident for Na (r=0.75), Al (r=0.65), Mn (r=0.61), Fe (r=0.57), Ca (r=0.49), K (r=0.41) and NO₃—N (r=0.59). No correlation was evident between IER and soil solution data for NH₄—N and Pb. Both IER and soil solution techniques suggested similar interpretations of biogeochemical behavior in the watershed.     

Selecting Species for Marine Assessment of Radionuclides Around Amchitka: Planning for Diverse Goals and Interests

Considerable attention has been devoted to selecting bioindicator species as part of monitoring programs for exposure and effects from contaminants in the environment. Yet the rationale for selection of bioindicators is often literature-based, rather than developed with a firm site-specific base of data on contaminant levels in a diverse range of organisms at different trophic levels in the same ecosystem. We suggest that this latter step is an important phase in the environmental assessment process that is often missing. In this paper we address the problem of how to select a wide range of species representing different trophic levels that serve as a basis for selecting a few species suitable as bioindicators. We illustrate this with our assessment of radionuclides on Amchitka Island, Alaska. We propose a multi-stage process for arriving at the list of available species that includes review of literature, review by experts experienced in the area, review by interested and affected parties, selection of trophic levels or groups for analysis, arraying of possible species, and selection of species within each trophic level group for sample collection. We first had to identify all likely species, then narrow our focus to those we could collect and analyze. In all cases, review includes suggestions for possible target species with justifications. While this method increases the up-front costs of developing bioindicators for an ecosystem, it has the advantage of providing information for selection of species that will be most informative in the long run, including those that are the best bioaccumulators, thus providing the earliest warning of any potential environmental consequences. Further, the recognition that a range of stakeholder's needs and interests should be included increases the utility for public-policy makers, and the potential for continued usage to establish long-term trends.     

Inorganic nitrogen transformations in the treatment of landfill leachate with a high ammonium load: A case study

The inorganic nitrogen transformations occurring at a municipal waste leachate treatment facility were investigated. The treatment facility consisted of a collection well and an artificial wetland between two aeration ponds. The first aeration pond showed a decrease in ammonium (from 3480 (± 120) to 630(± 90) mg ⋅ L⁻¹), a reduction in inorganic nitrogen load (3480 to 1680 mg N ⋅ L⁻¹), and an accumulation of nitrite (< 1.3 mg-N ⋅ L⁻¹ in the collection well, to 1030 mg-N ⋅ L⁻¹). Incomplete ammonium oxidation was presumably the result of the low concentration of carbonate alkalinity (∼2 mg ⋅ L⁻¹), which may cause a limitation in the ammonium oxidation rate of nitrifiers. Low carbonate alkalinity levels may have been the result of stripping of CO₂ from the first aeration pond at the high aeration rates and low pH. Various chemodenitrification mechanisms are discussed as the reason for the reduction in the inorganic nitrogen load, including; the reduction of nitrite by iron (II) (producing various forms of gaseous nitrogen); and reactions involving nitrous acid. It is suggested that the accumulation of nitrite may be the result of inhibition of nitrite oxidizers by nitrous acid and low temperatures. Relative to the first aeration pond, the speciation and concentration of inorganic nitrogen was stable in the wetlands and 2nd aeration pond. The limited denitrification in the wetlands most probably occurred due to low concentrations of organic carbon, and short retention times.     

Sensitivity to assumptions in models of generalist predation on a cyclic prey

Ecological theory predicts that generalist predators should damp or suppress long-term periodic fluctuations (cycles) in their prey populations and depress their average densities. However, the magnitude of these impacts is likely to vary depending on the availability of alternative prey species and the nature of ecological mechanisms driving the prey cycles. These multispecies effects can be modeled explicitly if parameterized functions relating prey consumption to prey abundance, and realistic population dynamical models for the prey, are available. These requirements are met by the interaction between the Hen Harrier (Circus cyaneus) and three of its prey species in the United Kingdom, the Meadow Pipit (Anthus pratensis), the field vole (Microtus agrestis), and the Red Grouse (Lagopus lagopus scoticus). We used this system to investigate how the availability of alternative prey and the way in which prey dynamics are modeled might affect the behavior of simple trophic networks. We generated cycles in one of the prey species (Red Grouse) in three different ways: through (1) the interaction between grouse density and macroparasites, (2) the interaction between grouse density and male grouse aggressiveness, and (3) a generic, delayed density-dependent mechanism. Our results confirm that generalist predation can damp or suppress grouse cycles, but only when the densities of alternative prey are low. They also demonstrate that diametrically opposite indirect effects between pairs of prey species can occur together in simple systems. In this case, pipits and grouse are apparent competitors, whereas voles and grouse are apparent facilitators. Finally, we found that the quantitative impacts of the predator on prey density differed among the three models of prey dynamics, and these differences were robust to uncertainty in parameter estimation and environmental stochasticity.     

Sardine (Sardina pilchardus) spawning seasonality in European waters of the northeast Atlantic

Egg data from ichthyoplankton monitoring sites in the western English Channel (1988–2003) and northern Spain (1990–2000) and macroscopic maturity data from biological samples of purse seine landings in western and southern Iberia (1980–2004) are used to describe the spawning seasonality of sardine (Sardina pilchardus) in European waters of the northeast Atlantic using generalised additive models. The fitted models reveal a double peak in spawning activity during early summer and autumn in the western Channel, a wider spring peak off northern Spain and a broad winter season in the western and southern Iberian Peninsula. At all sites, a high probability of spawning activity was observed over at least 3 months of the year, with the duration of the season increasing with both decreasing latitude and increasing fish size. Off western and southern Iberia there are indications that the spawning season has been of longer duration in recent years for all size classes (reaching in some cases 8 months of the year for large fish). These patterns are in general agreement with existing literature and theoretical expectations of sardine spawning being driven locally by the seasonal cycle of water temperature, assuming preferences for spawning at 14 –15°C and avoidance for temperatures below 12°C and above 16°C. Regional quotient plots indicated that spawning tolerance to higher temperatures increases progressively with decreasing latitude. Despite the weak evidence for geographical differences in temperature tolerance that may have some genetic origin, the degree of spatio-temporal overlap in sardine-spawning activity within Atlantic European waters is unlikely to promote any reproductive isolation in that area.     

Multiple sources of predictive uncertainty in modeled estimates of net ecosystem CO2 exchange

Net ecosystem CO₂ exchange (NEE) is typically measured directly by eddy covariance towers or is estimated by ecosystem process models, yet comparisons between the data obtained by these two methods can show poor correspondence. There are three potential explanations for this discrepancy. First, estimates of NEE as measured by the eddy-covariance technique are laden with uncertainty and can potentially provide a poor baseline for models to be tested against. Second, there could be fundamental problems in model structure that prevent an accurate simulation of NEE. Third, ecosystem process models are dependent on ecophysiological parameter sets derived from field measurements in which a single parameter for a given species can vary considerably. The latter problem suggests that with such broad variation among multiple inputs, any ecosystem modeling scheme must account for the possibility that many combinations of apparently feasible parameter values might not allow the model to emulate the observed NEE dynamics of a terrestrial ecosystem, as well as the possibility that there may be many parameter sets within a particular model structure that can successfully reproduce the observed data. We examined the extent to which these three issues influence estimates of NEE in a widely used ecosystem process model, Biome-BGC, by adapting the generalized likelihood uncertainty estimation (GLUE) methodology. This procedure involved 400,000 model runs, each with randomly generated parameter values from a uniform distribution based on published parameter ranges, resulting in estimates of NEE that were compared to daily NEE data from young and mature Ponderosa pine stands at Metolius, Oregon. Of the 400,000 simulations run with different parameter sets for each age class (800,000 total), over 99% of the simulations underestimated the magnitude of net ecosystem CO₂ exchange, with only 4.07% and 0.045% of all simulations providing satisfactory simulations of the field data for the young and mature stands, even when uncertainties in eddy-covariance measurements are accounted for. Results indicate fundamental shortcomings in the ability of this model to produce realistic carbon flux data over the course of forest development, and we suspect that much of the mismatch derives from an inability to realistically model ecosystem respiration. However, difficulties in estimating historic climate data are also a cause for model-data mismatch, particularly in a highly ecotonal region such as central Oregon. This latter difficulty may be less prevalent in other ecosystems, but it nonetheless highlights a challenge in trying to develop a dynamic representation of the terrestrial biosphere.     

Reproductive status of Octopus pallidus, and its relationship to age and size

Age-specific information on individual octopus reproductive development and investment from wild populations has until recently been unobtainable. Using daily-formed increments within stylets (internal shells) the individual ages of 503 wild Octopus pallidus were determined. In addition, detailed reproductive information was collected for each of the aged octopus, along with reproductive data for an additional 925 octopus. All of the octopus were collected from Bass Strait waters in south-eastern Australia from November 2004 to November 2006. This information was used to investigate seasonal trends in reproductive scheduling and investment, fecundity and egg size. Maturation in O. pallidus primarily depends on size with little relationship to age and is highly variable between genders, with females >350 days still maturing in comparison to all males >142 days being mature. Size at 50% maturity for females was approximately 473 g, which is considerably larger than male 100% maturity at <250 g. This indicates that for females at least, maturity does not necessarily come with age. Seasonal scheduling in reproductive investment between genders revealed an optimal spawning period between late summer and early autumn. These results reinforce the view that individual growth and maturity is highly variable in cephalopods.     

Scale-dependent responses of plant biodiversity to nitrogen enrichment

Experimental studies demonstrating that nitrogen (N) enrichment reduces plant diversity within individual plots have led to the conclusion that anthropogenic N enrichment is a threat to global biodiversity. These conclusions overlook the influence of spatial scale, however, as N enrichment may alter beta diversity (i.e., how similar plots are in their species composition), which would likely alter the degree to which N-induced changes in diversity within localities translate to changes in diversity at larger scales that are relevant to policy and management. Currently, it is unclear how N enrichment affects biodiversity at scales larger than a small plot. We synthesized data from 18 N-enrichment experiments across North America to examine the effects of N enrichment on plant species diversity at three spatial scales: small (within plots), intermediate (among plots), and large (within and among plots). We found that N enrichment reduced plant diversity within plots by an average of 25% (ranging from a reduction of 61% to an increase of 5%) and frequently enhanced beta diversity. The extent to which N enrichment altered beta diversity, however, varied substantially among sites (from a 22% increase to an 18% reduction) and was contingent on site productivity. Specifically, N enrichment enhanced beta diversity at low-productivity sites but reduced beta diversity at high-productivity sites. N-induced changes in beta diversity generally reduced the extent of species loss at larger scales to an average of 22% (ranging from a reduction of 54% to an increase of 18%). Our results demonstrate that N enrichment often reduces biodiversity at both local and regional scales, but that a focus on the effects of N enrichment on biodiversity at small spatial scales may often overestimate (and sometimes underestimate) declines in regional biodiversity by failing to recognize the effects of N on beta diversity.