Ectoparasite loads in free-ranging northern fence lizards, Sceloporus undulatus hyacinthinus: effects of testosterone and sex

More knowledge of the proximate factors that influence parasite loads would help us understand the selective pressures faced by hosts and host-parasite evolution. Testosterone has been associated with increased parasite loads in vertebrates. Here we asked whether experimentally elevated testosterone affected ectoparasite loads in free-ranging northern fence lizards (Sceloporus undulatus hyacinthinus). Males were captured, given testosterone or sham implants, and released. In 2 consecutive years, testosterone-implanted males had significantly more ectoparasites at recapture than did controls. Additionally, ectoparasite loads were positively correlated with testosterone concentrations in unmanipulated males, and males had significantly more ectoparasites than did females. The results are consistent with an effect of testosterone on parasite loads. However, rather than elevated testosterone increasing mite loads in experimental males, it appeared that high testosterone inhibited a natural seasonal decline in mite loads. Testosterone-implanted males also lost body mass whereas controls gained mass. Among controls, those retaining the most ectoparasites over the course of the experiment experienced the smallest gains in body mass, suggesting that the mites are costly.     

Phylogeographic structure of false clownfish, Amphiprion ocellaris, explained by sea level changes on the Sunda shelf

The phylogenetic structure of the anemonefish Amphiprion ocellaris was established based on sequence data generated for the 5′ end of the cytochrome b (cytb) gene at 11 sites throughout Southeast Asia. Considerable genetic structuring was observed throughout the range of A. ocellaris. The region has a complex geography, with the Sunda shelf having been exposed during the lower sea levels associated with periods of glaciation. The direction of subsequent flooding of the Sunda shelf, as a direct consequence of the retreating glacial sheets, can be predicted based on the major river drainage systems in the region. Much of the phylogeographic structure, including levels of intra-site genetic variation, can be explained in terms of the “seeding” of sites on the Sunda shelf, by those on the shelf rim, as sea levels rose. We often found surface ocean currents in the region, which should influence larval dispersal, to be poorly correlated with phylogeographic structure. Several geographically close sites, which appear to be connected by surface currents, showed significant genetic stratification. We hypothesise that the phylogeographic structure of A. ocellaris is more reminiscent of the Pleistocene sea level changes than surface currents. The high contribution of sea level changes to the phylogeographic structure was also supported by several missing haplotypes in the generated spanning network. Cytb DNA sequences generated for recently recruited A. ocellaris individuals sampled from Singapore indicate that, on a local scale, there is a directional inflow of recruits, which is dependent on the monsoon seasons. The nature of dispersal and genetic structure of reef fish species found on the Sunda shelf is clearly complex, and should take into consideration past phylogeographic events. Received: 13 November 1999 / Accepted: 12 July 2000     

How will Ocean Acidification Affect Baltic Sea Ecosystems? An Assessment of Plausible Impacts on Key Functional Groups

Increasing partial pressure of atmospheric CO₂ is causing ocean pH to fall—a process known as ‘ocean acidification’. Scenario modeling suggests that ocean acidification in the Baltic Sea may cause a ≤3 times increase in acidity (reduction of 0.2–0.4 pH units) by the year 2100. The responses of most Baltic Sea organisms to ocean acidification are poorly understood. Available data suggest that most species and ecologically important groups in the Baltic Sea food web (phytoplankton, zooplankton, macrozoobenthos, cod and sprat) will be robust to the expected changes in pH. These conclusions come from (mostly) single-species and single-factor studies. Determining the emergent effects of ocean acidification on the ecosystem from such studies is problematic, yet very few studies have used multiple stressors and/or multiple trophic levels. There is an urgent need for more data from Baltic Sea populations, particularly from environmentally diverse regions and from controlled mesocosm experiments. In the absence of such information it is difficult to envision the likely effects of future ocean acidification on Baltic Sea species and ecosystems.     

Novel Organisms: Comparing Invasive Species, GMOs, and Emerging Pathogens

Invasive species, range-expanding species, genetically modified organisms (GMOs), synthetic organisms, and emerging pathogens increasingly affect the human environment. We propose a framework that allows comparison of consecutive stages that such novel organisms go through. The framework provides a common terminology for novel organisms, facilitating knowledge exchange among researchers, managers, and policy makers that work on, or have to make effective decisions about, novel organisms. The framework also indicates that knowledge about the causes and consequences of stage transitions for the better studied novel organisms, such as invasive species, can be transferred to more poorly studied ones, such as GMOs and emerging pathogens. Finally, the framework advances understanding of how climate change can affect the establishment, spread, and impacts of novel organisms, and how biodiversity affects, and is affected by, novel organisms.     

A 13-Week Comparison of Passive and Continuous Ozone Monitors at Forested Sites in North-Central Pennsylvania

ABSTRACT

Ogawa passive O₃ samplers were used in a 13-week study (June 1-September 1, 1999) involving 11 forested and mountaintop sites in north-central Pennsylvania. Four of the sites were collocated with TECO model 49 O₃ analyzers. A significant correlation (p < 0.0001) was found for 24-hr average weekly O₃ concentrations between the two methodologies at the four sites with collocated monitors. As expected, there were positive relationships between increasing elevation of the sites and increasing O₃ concentrations. No O₃ exposure patterns were found on a west-to-east or south-to-north basis; however, the area known for lower O₃ exposures within a smaller subsection of the study area showed consistently lower O₃ exposures. Preliminary results regarding relationships of symptom responses within O₃-sensitive bioindicators are also presented with black cherry (Prunus serotina, Elirli.) and common milkweed (Asclepias syriaca, L.) showing clear evidence of increasing injury with increasing O₃ exposures. Due to the extremely dry conditions encountered in north-central Pennsylvania during the 1999 growing season, O₃-induced symptoms were sporadic and quite delayed until late-season rains during the latter portion of the observation period.     

Large and mesoscale meteo-oceanographic patterns in local responses of biogeochemical concentrations

Investigations surrounding the variability of productivity in upwelling regions are necessary for a better understanding the physical-biological coupling in these regions by monitoring systems of environmental impacts according to the needs of the regional coastal management. Using a spatial and temporal database from National Centers for Environmental Prediction (NCEP) and National Center for Atmospheric (NCAR) Research reanalysis, Quick Scatterometer vector wind, and surface stations from the Southeast coast of Brazil, we investigate the meteorological influences due to the large-scale systems in the variability of the nutrient and larvae concentration, and chlorophyll a, describing statistically relationships between them in upwelling regions. In addition, we used multivariate analysis, such as PCA and clustering to verify spatial and temporal variances and describe more clear the structure and composition of the ecosystem. Correlation matrix analyses were applied for different water masses present in the study area to identify the relations between physical and biogeochemical parameters in a region, where frequently upwelling occur. Statistical approaches and seasonal variability show that the period of November to March is more sensitive to nutrients (1.20?mg/m(3) for chlorophyll a, 2.20?μmol/l for total nitrogen and 5.5?ml/l for DO) and larvae concentrations (120 org/m(3) for most of the larvae, except for cirripedia that presented values around 370 org/m(3)) relating to the influence of large and mesoescale meteorological patterns. The spatial and temporal variables analyzed with multivariate approach show meaningful seasonality variance of the physical and biological samples, characterizing the principal components responsible for this variance in spring and summer (upwelling period), emphasizing the monitoring of species as crustaceans and mussels that are present in the local economy. Then, the spring and summer season are characterized by high productivity due to the occurrence of upwelling in this period.     

Examining intra-urban variation in fine particle mass constituents using GIS and constrained factor analysis

Recent studies have used land use regression (LUR) techniques to explain spatial variability in exposures to PM_2.5 and traffic-related pollutants. Factor analysis has been used to determine source contributions to measured concentrations. Few studies have combined these methods, however, to construct and explain latent source effects. In this study, we derive latent source factors using confirmatory factor analysis constrained to non-negative loadings, and develop LUR models to predict the influence of outdoor sources on latent source factors using GIS-based measures of traffic and other local sources, central site monitoring data, and meteorology. We collected 3–4 day samples of nitrogen dioxide (NO₂) and PM_2.5 outside of 44 homes in summer and winter, from 2003 to 2005 in and around Boston, Massachusetts. Reflectance analysis, X-ray fluorescence spectroscopy (XRF), and high-resolution inductively-coupled plasma mass spectrometry (ICP-MS) were performed on particle filters to estimate elemental carbon (EC), trace element, and water-soluble metals concentrations. Within our constrained factor analysis, a five-factor model was optimal, balancing statistical robustness and physical interpretability. This model produced loadings indicating long-range transport, brake wear/traffic exhaust, diesel exhaust, fuel oil combustion, and resuspended road dust. LUR models largely corroborated factor interpretations through covariate significance. For example, ‘long-range transport’ was predicted by central site PM_2.5 and season; ‘brake wear/traffic exhaust’ and ‘resuspended road dust’ by traffic and residential density; ‘diesel exhaust’ by percent diesel traffic on nearest major road; and ‘fuel oil combustion’ by population density. Results suggest that outdoor residential PM_2.5 source contributions can be partially predicted using GIS-based terms, and that LUR techniques can support factor interpretation for source apportionment. Together, LUR and factor analysis facilitate source identification, assessment of spatial and temporal variability, and more refined source exposure assignment for evaluation of source contributions to health outcomes in epidemiological studies.     

Further studies on the uptake of persistent organic pollutants (POPs) by polyurethane foam disk passive air samplers

Passive air samplers (PAS) can be used to monitor semi-volatile organic compounds in the atmosphere. Polyurethane foam (PUF) disks are a popular sampling medium because they have a high retention capacity for such compounds. This paper reports a highly time-resolved uptake study, to derive uptake rate data under field conditions, and investigate the effects of using different foam densities on the uptake rate. PUF disks were deployed alongside an active sampler, for periods of up to 12 weeks. The uptake rates were measured for a range of gas- and particle-bound persistent organic pollutants (polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs)), of different properties, to explore whether gas–particle partitioning affected uptake rate. Uptake rates for two different densities of foam (0.021 and 0.035 g cm^?3) were not statistically significantly different from each other. Uptake rates of light PCBs averaged ～6.5 m³ day^?1, somewhat higher than in previous studies; higher wind speeds and lower temperatures in this study are the likely reason for this difference. The study showed: i) the uptake rate of the compound with lowest K_OA considered in this study (PCB-28/31) declined in the later weeks, indicating an approach to equilibrium; ii) uptake rates of lighter BDEs and heavier PCBs (compounds of intermediate K_OA in this study) remain similar throughout the study period, indicating that they are not approaching equilibrium during the 12-week-study; iii) uptake rates were typically: ～8 m³ day^?1 for PCB-52; ～9.5 m³ day^?1 for PCB-95; ～11 m³ day^?1 for BDE-28 and ～2 m³ day^?1 BDE-99. The latter compound has an important particle-bound component and this lowers the sampling rate compared to predicted uptake rates for compounds which are in the gas phase only. It is shown that knowledge of gas–particle partitioning is needed to correct for this effect, and to improve predicted uptake rates.     

Using Spatial Pattern to Quantify Relationship Between Samples, Surroundings, and Populations

The need for accurate carbon budgeting, climate change modelling, and sustainable resource management has lead to an increase in the number of large area forest monitoring programs. Large area forest monitoring programs often utilize field and remotely sensed data sources. Sampling, via field or photo plots, enables the collection of data with the desired level of categorical detail in a timely and efficient manner. When sampling, the aim is to collect representative detailed data enabling the statistical reporting upon the characteristics of larger areas. As a consequence, approaches for investigating how well sample data represent larger areas (i.e., the sample neighbourhood and the population) are desired. Presented in this communication is a quantitative approach for assessing the nature of sampled areas in relation to surrounding areas and the overall population of interest. Classified Landsat data is converted to forest/non-forest categories to provide a consistent and uniform data set over a 130,000 km² study region in central British Columbia, Canada. From this larger study area 322 2 × 2 km photo plots on a 20 × 20 km systematic grid are populated with composition and configuration information for comparison to non-sampled areas. Results indicate that typically, within the study area, the spatial pattern of forest within a photo plot is representative of the forest patterns found within primary and secondary neighbourhoods and over the entire population of the study. These methods have implications for understanding the nature of data used in monitoring programs worldwide. The ability to audit photo and field plot information promotes an increased understanding of the results developed from sampling and provides tools identifying locations of possible bias.