Estimating the Density of Honeybee Colonies across Their Natural Range to Fill the Gap in Pollinator Decline Censuses

Abstract: Although pollinator declines are a global biodiversity threat, the demography of the western honeybee (Apis mellifera) has not been considered by conservationists because it is biased by the activity of beekeepers. To fill this gap in pollinator decline censuses and to provide a broad picture of the current status of honeybees across their natural range, we used microsatellite genetic markers to estimate colony densities and genetic diversity at different locations in Europe, Africa, and central Asia that had different patterns of land use. Genetic diversity and colony densities were highest in South Africa and lowest in Northern Europe and were correlated with mean annual temperature. Confounding factors not related to climate, however, are also likely to influence genetic diversity and colony densities in honeybee populations. Land use showed a significantly negative influence over genetic diversity and the density of honeybee colonies over all sampling locations. In Europe honeybees sampled in nature reserves had genetic diversity and colony densities similar to those sampled in agricultural landscapes, which suggests that the former are not wild but may have come from managed hives. Other results also support this idea: putative wild bees were rare in our European samples, and the mean estimated density of honeybee colonies on the continent closely resembled the reported mean number of managed hives. Current densities of European honeybee populations are in the same range as those found in the adverse climatic conditions of the Kalahari and Saharan deserts, which suggests that beekeeping activities do not compensate for the loss of wild colonies. Our findings highlight the importance of reconsidering the conservation status of honeybees in Europe and of regarding beekeeping not only as a profitable business for producing honey, but also as an essential component of biodiversity conservation.     

总硬度的测量不确定度评定

通过对总硬度浓度的测定过程分析,找出影响结果的各个分量,进行测量不确定度的评定,按照计量技术规范,给出标准的表示法。     

Water Quality and Land Use Changes in the Alafia and Hillsborough River Watersheds,Florida, USA1

Abstract: Spatial distribution of land use can have a substantial effect on surface and groundwater quality. Our objective was to test for trends in flow components and water quality related to changes in land use in the Alafia and Hillsborough River watersheds in Florida, USA, over the period 1974‐2007. In addition, water quality statistics were evaluated in the perspective of numeric water quality criteria and proposed reclassification of segments of the Alafia River. Trends in 10 water quality parameters and three discharge variables were evaluated using a nonparametric trend detection test. Results of land use analysis indicated substantial urbanization and loss of agricultural land in the study area. Discharge variables did not exhibit significant trends, whereas trends in the majority of water quality concentrations were negative or nonsignificant with total nitrogen and total Kjeldahl nitrogen as exceptions showing positive trends. Changes in nutrient pathways could not be clearly identified. Considering recently promulgated numeric nutrient criteria and standards for dissolved fluoride, much of the Alafia River was found to be out of compliance. While there were land use changes and changes in water quality over the study period, it was difficult to identify a direct cause‐effect relationship. Responses to regulatory efforts, such as the Clean Water Act and improvements in phosphate mining practices, may have had greater impacts on water quality than changes in land use.     

Organic matter determination for street dust in Delhi

The organic matter of street dust is considered as one of the causes for high human mortality rate. To understand the association, the street dust samples were collected from four different localities (industrial, residential, residential–commercial, and commercial) situated in the greater Delhi area of India. The loss-on-ignition method was used to determine the organic matter (OM) content in street dust. The OM content, potassium, calcium, sulfate, and nitrate concentrations of street dust in Delhi, India is measured to understand the spatial variation. Correlation analysis, analysis of variance, and factor analysis were performed to define the sources. The dust OM level ranges from 2.63 to 10.22 %. It is found through correlation and factor analysis that OM is primarily contributed from secondary aerosol and vehicular exhaust. The OM levels suggest that the use of a residential–commercial site for commercial purposes is polluting the street dust and creating the environmental and human health problems.     

Identifying Determinants of Nations' Wetland Management Programs Using Structural Equation Modeling: An Exploratory Analysis

Integrated management and policy models suggest that solutions to environmental issues may be linked to the socioeconomic and political characteristics of a nation. In this study, we empirically explore these suggestions by applying them to the wetland management activities of nations. Structural equation modeling was used to evaluate a model of national wetland management effort and one of national wetland protection. Using five predictor variables of social capital, economic capital, environmental and political characteristics, and land-use pressure, the multivariate models were able to explain 60% of the variation in nations' wetland protection efforts based on data from 90 nations, as defined by level of participation in the international wetland convention. Social capital had the largest direct effect on wetland protection efforts, suggesting that increased social development may eventually lead to better wetland protection. In contrast, increasing economic development had a negative linear relationship with wetland protection efforts, suggesting the need for explicit wetland protection programs as nations continue to focus on economic development. Government, environmental characteristics, and land-use pressure also had a positive direct effect on wetland protection, and mediated the effect of social capital on wetland protection. Explicit wetland protection policies, combined with a focus on social development, would lead to better wetland protection at the national level.     

Indoor air quality modeling for PM10, PM2.5, and PM1.0 in naturally ventilated classrooms of an urban Indian school building

Assessment of indoor air quality (IAQ) in classrooms of school buildings is of prime concern due to its potential effects on student??s health and performance as they spend a substantial amount of their time (6?C7 h per day) in schools. A number of airborne contaminants may be present in urban school environment. However, respirable suspended particulate matter (RSPM) is of great significance as they may significantly affect occupants?? health. The objectives of the present study are twofold, one, to measure the concentrations of PM₁₀ (<10  $\upmu $ m), PM_2.5 (<2.5  $\upmu $ m), and PM_1.0 (<1.0  $\upmu $ m) in naturally ventilated classrooms of a school building located near a heavy-traffic roadway (9,755 and 4,296 vehicles/hour during weekdays and weekends, respectively); and second, to develop single compartment mass balance-based IAQ models for PM₁₀ (NVIAQM_pm10), PM_2.5 (NVIAQM_pm2.5), and PM_1.0 (NVIAQM_pm1.0) for predicting their indoor concentrations. Outdoor RSPM levels and classroom characteristics, such as size, occupancy level, temperature, relative humidity, and CO₂ concentrations have also been monitored during school hours. Predicted indoor PM₁₀ concentrations show poor correlations with observed indoor PM₁₀ concentrations (R ² = 0.028 for weekdays, and 0.47 for weekends). However, a fair degree of agreement (d) has been found between observed and predicted concentrations, i.e., 0.42 for weekdays and 0.59 for weekends. Furthermore, NVIAQM_pm2.5 and NVIAQM_pm1.0 results show good correlations with observed concentrations of PM_2.5 (R ² = 0.87 for weekdays and 0.9 for weekends) and PM_1.0 (R ² = 0.86 for weekdays and 0.87 for weekends). NVIAQM_pm10 shows the tendency to underpredict indoor PM₁₀ concentrations during weekdays as it does not take into account the occupant??s activities and its effects on the indoor concentrations during the class hours. Intense occupant??s activities cause resuspension or delayed deposition of PM₁₀. The model results further suggests conductance of experimental and physical simulation studies on dispersion of particulates indoors to investigate their resuspension and settling behavior due to occupant??s activities/movements. The models have been validated at three different classroom locations of the school site. Sensitivity analysis of the models has been performed by varying the values of mixing factor (k) and newly introduced parameter R _c. The results indicate that the change in values of k (0.33 to 1.00) does not significantly affect the model performance. However, change in value of R _c (0.001 to 0.500) significantly affects the model performance.