Multimodal signals increase active space of communication by wolf spiders in a complex litter environment

Multimodal signals may compensate for environmental constraints on communication, as signals in different modalities vary in efficacy. We examined the influence of complex microhabitats on transmission of vibratory and visual signals of courting male Schizocosa ocreata wolf spiders (Araneae: Lycosidae) with laser Doppler vibrometry (LDV) and behavioral observations in lab and field. We measured maximum potential detection distance of visual and vibratory signals by females in laboratory mesocosms, recorded vibration signal attenuation on different substrates, and estimated transmission distances for male vibration signals in the field. We also determined effective line-of-sight visual detection distances in the field with laser distance measures. Together, these data were used to estimate the potential and effective active space of multimodal signals. LDV measures show leaves are highly conductive substrates for wolf spider vibratory signals compared to others (soil, wood, rock). For both visual and vibratory modes, lab estimates of maximum potential distance for signal transmission and detection (behavior studies) exceeded estimates of effective active space (signal attenuation, “vanishing point,” and “line-of-sight” measures). Field estimates of transmission distance for signal modes overlap, such that in close range (<20 cm), vibratory signals are more likely to be detected, while farther away, visual signals are more likely to be seen. These findings thus support current hypotheses regarding how multimodal communication might extend the range of overall signal active space or compensate for environmental constraints.     

A composite measure of habitat loss for entire assemblages of species

Habitat destruction is among the greatest threats facing biodiversity, and it affects common and threatened species alike. However, metrics for communicating its impacts typically overlook the nonthreatened component of assemblages. This risks the loss of habitat going unreported for species that comprise the majority of assemblages. We adapted a widely used measure for summarizing researcher output (the h index) to provide a metric that describes natural habitat loss for entire assemblages, inclusive of threatened and nonthreatened species. For each of 447 Australian native terrestrial bird species, we combined information on their association with broad vegetation groups with distributional range maps to identify the difference between the estimated pre-European and current extents of potential habitat, defined as vegetation groups most closely associated with each species. From this, we calculated the loss index (LI), which revealed that 30% of native birds have each lost at least 30% of their potential natural habitat (LI = 30). At the subcontinental scale, LIs ranged from 15 in arid Australia to 61 in the highly transformed southeastern part of the country. Different subcomponents of the assemblage had different LI values. For example, Australia's parrots (n = 52 species) had an LI of 38, whereas raptors (n = 32 species) had an LI of 25. The LI is simple to calculate and can be determined using readily available spatial information on species distributions, native vegetation associations, and human impacts on natural land cover. This metric, including the curves used to deduce it, could complement other biodiversity indices if it is used for regional and global biodiversity assessments that compare the status of natural habitat extent for assemblages within and among nations, monitor changes through time, and forecast future changes to guide strategic land-use planning. The LI is an intuitive tool that can be used to summarize and communicate how human actions affect whole assemblages, not just threatened species.     

Predictive mapping of air pollution involving sparse spatial observations

A limited number of sample points greatly reduces the availability of appropriate spatial interpolation methods. This is a common problem when one attempts to accurately predict air pollution levels across a metropolitan area. Using ground-level ozone concentrations in the Tucson, Arizona, region as an example, this paper discusses the above problem and its solution, which involves the use of linear regression. A large range of temporal variability is used to compensate for sparse spatial observations (i.e. few ozone monitors). Gridded estimates of emissions of ozone precursor chemicals, which are developed, stored, and manipulated within a geographic information system, are the core predictor variables in multiple linear regression models. Cross-validation of the pooled models reveals an overall R2 of 0.90 and approximately 7% error. Composite ozone maps predict that the highest ozone concentrations occur in a monitor-less area on the eastern edge of Tucson. The maps also reveal the need for ozone monitors in industrialized areas and in rural, forested areas.     

Climate change and mining in Canada

Climate is an important component of the operating environment for the Canadian mining sector. However, in recent years mines across Canada have been affected by significant climatic hazards, several which are regarded to be symptomatic of climate change. For the mining sector, climate change is a pressing environmental threat and a significant business risk. The extent to which the mining sector is able to mitigate its own impact and adapt to climate change will affect its long-term success and prosperity, and have profound economic consequences for host communities. This paper draws upon case studies conducted with mining operations in Canada involving in-depth interviews with mining professionals and analysis of secondary sources to characterize the vulnerability of the Canadian mining industry to climate change. Five key findings are discussed: i) mines in the case studies are affected by climate events that are indicative of climate change, with examples of negative impacts over the past decade; ii) most mine infrastructure has been designed assuming that the climate is not changing; iii) most industry stakeholders interviewed view climate change as a minor concern; iv) limited adaption planning for future climate change is underway; v) significant vulnerabilities exist in the post-operational phase of mines. This paper argues for greater collaboration among mining companies, regulators, scientists and other industry stakeholders to develop practical adaptation strategies that can be integrated into existing and new mine operations, including in the post-operational phase.     

Development and Preliminary Evaluation of a Particulate Matter Emission Factor Model for European Motor Vehicles

ABSTRACT

Although modeling of gaseous emissions from motor vehicles is now quite advanced, prediction of particulate emissions is still at an unsophisticated stage. Emission factors for gasoline vehicles are not reliably available, since gasoline vehicles are not included in the European Union (EU) emission test procedure. Regarding diesel vehicles, emission factors are available for different driving cycles but give little information about change of emissions with speed or engine load. We have developed size-specific speed-dependent emission factors for gasoline and diesel vehicles. Other vehicle-generated emission factors are also considered and the empirical equation for re-entrained road dust is modified to include humidity effects. A methodology is proposed to calculate modal (accelerating, cruising, or idling) emission factors. The emission factors cover particle size ranges up to 10 um, either from published data or from user-defined size distributions.

A particulate matter emission factor model (PMFAC), which incorporates virtually all the available information on particulate emissions for European motor vehicles, has been developed. PMFAC calculates the emission factors for five particle size ranges [i.e., total suspended particulates (TSP), PM₁₀, PM₅, PM₂₅, and PM₁] from both vehicle exhaust and nonexhaust emissions, such as tire wear, brake wear, and re-entrained road dust. The model can be used for an unlimited number of roads and lanes, and to calculate emission factors near an intersection in user-defined elements of the lane. PMFAC can be used for a variety of fleet structures. Hot emission factors at the user-defined speed can be calculated for individual vehicles, along with relative cold-to-hot emission factors. The model accounts for the proportions of distance driven with cold engines as a function of ambient temperature and road type (i.e., urban, rural, or motorway).

A preliminary evaluation of PMFAC with an available dispersion model to predict the airborne concentration in the urban environment is presented. The trial was on the A6 trunk road where it passes through Loughborough, a medium-size town in the English East Midlands. This evaluation for TSP and PM₁₀ was carried out for a range of traffic fleet compositions, speeds, and meteorological conditions. Given the limited basis of the evaluation, encouraging agreement was shown between predicted and measured concentrations.     

地下水脆弱性评价方法研究

地下水脆弱性评价是区域进行地下水资源保护和管理的重要依据。本文回顾了现有地下水脆弱性评价的方法,提出了应用地理信息系统平台和模糊逻辑与神经网络对地下水进行脆弱性评价的模型,并实际应用于美国与中国选定区域,创新并拓展了地下水脆弱性评价方法。     

Biotechnology: the ultimate cleaner production technology for agriculture?

There has been much discussion regarding the potential environmental benefits and hazards associated with agricultural biotechnology. Some argue that it can eliminate the need for a wide range of material inputs such as pesticides and herbicides. Others argue that it will increase the demand for non-sustainable and potentially hazardous ‘agri-business' practices. We test these claims against the cleaner production approach. Although we found that pressures to accept this technology are strong enough to overcome initial resistance, we also found that biotechnology, as it applies to agriculture, is not consistent with a cleaner production approach due to the high level of risk. We suggest that this type of technology adds an additional dimension to the cleaner production argument.     

Wetland cultivation and hydrological management in eastern Africa: Matching community and hydrological needs through sustainable wetland use

Wetlands are critical natural resources in developing countries where they perform a range of environmental functions and provide numerous socio-economic benefits to local communities and a wider population. In recent years, however, many wetlands throughout eastern Africa have come under extreme pressure as government policies, socio-economic change and population pressure have stimulated a need for more agriculturally productive land. Although wetland drainage and cultivation can make a key contribution to food and livelihood security in the short term, in the long term there are concerns over the sustainability of this utilization and the maintenance of wetland benefits. This article draws upon recent research carried out in western Ethiopia, which addressed the sustainability of wetland agriculture in an area of increasing food insecurity and population pressure. It discusses the impacts of drainage and cultivation on wetland hydrology and draws attention to local wetland management strategies, particularly those characterized by multiple use of wetlands, where agriculture exists alongside other wetland uses. The article suggests that where multiple wetland uses exist, a range of benefits can be sustained with little evidence of environmental degradation. Ways of promoting and empowering such sustainable wetland management systems are discussed in the context of the wider need for water security throughout the region.     

Measurements of atmospheric aerosol size distributions by co-located optical particle counters

Ambient aerosol number concentrations and size distributions were measured in both indoor and outdoor environments using two identical co-located and concurrently operated optical particle counters (OPCs). Indoor measurements were performed in a research laboratory, whereas two different locations were used for outdoor measurements; the sampling duration exceeded 12 hours and one hour respectively. Results from the two OPCs have been presented for eight size classes between 0.5 and 20 [micro sign]m, represented by central value diameters 0.875, 1.5, 2.75, 4.25, 6.25, 8.75, 12.5 and 15 microm. Overall, for the six indoor and outdoor experiments conducted at different times of day, the mean particle count ratios from the two OPCs for the individual samples showed +/-20% variation for indoor experiments and +/-50% variations for outdoor experiments. Significant random departures of the mean ratios from unity at all size classes were noticed even for indoor sample periods exceeding 20 hours. However, the coefficient of determination (R(2)) for the plots of readings from the two OPCs indicated higher consistency for "fine" particles (0.5-3.5 microm) than for "coarse" particles (10-20 microm), with average R(2) > 0.8 and R(2) < 0.5 respectively. Poisson counting statistics help to explain the divergence in the latter case where number concentrations were very low for the outdoor experiments. However, it cannot explain the divergence for indoor measurements where the concentrations were much higher. Increasing the averaging period reduced the scatter, especially in size classes with low number concentration. However, this procedure may lead to over-smoothing of data for environments with rapidly changing number concentration. These results indicate that, when two such analysers are used for comparative studies, the divergence between their responses may generate significant values of source contribution or deposition flux, even for nominally similar aerosol populations.     

Assessing the Relationship between Personal Particulate and Gaseous Exposures of Senior Citizens Living in Baltimore,MD

ABSTRACT

We conducted a multi-pollutant exposure study in Baltimore, MD, in which 15 non-smoking older adult subjects (>64 years old) wore a multi-pollutant sampler for 12 days during the summer of 1998 and the winter of 1999. The sampler measured simultaneous 24-hr integrated personal exposures to PM₂₅, PM₁₀, SO₄ ^2-, O₃, NO₂, SO₂, and exhaust-related VOCs.

Results of this study showed that longitudinal associations between ambient PM_2.5 concentrations and corresponding personal exposures tended to be high in the summer (median Spearman's r = 0.74) and low in the winter (median Spearman's r = 0.25). Indoor ventilation was an important determinant of personal PM_2.5 exposures and resulting personal-ambient associations. Associations between personal PM₂₅ exposures and corresponding ambient concentrations were strongest for well-ventilated indoor environments and decreased with ventilation. This decrease was attributed to the increasing influence of indoor PM_{2 5} sources. Evidence for this was provided by SO₄ ^2-measurements, which can be thought of as a tracer for ambient PM₂₅. For SO₄ ^2-, personal-ambient associations were strong even in poorly ventilated indoor environments, suggesting that personal exposures to PM_2.5 of ambient origin are strongly associated with corresponding ambient concentrations. The results also indicated that the contribution of indoor PM_2.5 sources to personal PM_2.5 exposures was lowest when individuals spent the majority of their time in well-ventilated indoor environments.

Results also indicate that the potential for confounding by PM_2.5 co-pollutants is limited, despite significant correlations among ambient pollutant concentrations. In contrast to ambient concentrations, PM_2.5 exposures were not significantly correlated with personal exposures to PM_2.5-10, PM_2.5 of non-ambient origin, O₃, NO₂, and SO₂. Since a confounder must be associated with the exposure of interest, these results provide evidence that the effects observed in the PM_2.5 epidemiologic studies are unlikely to be due to confounding by the PM_2.5 co-pollutants measured in this study.