Measuring climate for work group innovation: development and validation of the team climate inventory

This paper reports the development and psychometric validation of a multi-dimensional measure of facet-specific climate for innovation within groups at work: the Team Climate Inventory (TCI). Brief reviews of the organizational climate and work group innovation literatures are presented initially, and the need for measures of facet-specific climate at the level of the proximal work group asserted. The four-factor theory of facet-specific climate for innovation, which was derived from these reviews, is described, and the procedures used to operationalize this model into the original version measure described. Data attesting to underlying factor structure, internal homogeneity, predictive validity and factor replicability across groups of the summarized measure are presented. An initial sample of 155 individuals from 27 hospital management teams provided data for the exploratory factor analysis of this measure. Responses from 121 further groups in four occupations (35 primary health care teams, 42 social services teams, 20 psychiatric teams and 24 oil company teams; total N=971) were used to apply confirmatory factor analysis techniques. This five-factor, 38-item summarized version demonstrates robust psychometric properties, with acceptable levels of reliability and validity. Potential applications of this measure are described and the implication of these findings for the measurement of proximal work group climate are discussed. © 1998 John Wiley & Sons, Ltd.     

Status and trends of circumpolar peregrine falcon and gyrfalcon populations

Ambio - The peregrine falcon (Falco peregrinus) and the gyrfalcon (Falco rusticolus) are top avian predators of Arctic ecosystems. Although existing monitoring efforts are well established for both...     

Horizon scanning for South African biodiversity: A need for social engagement as well as science

Ambio - A horizon scan was conducted to identify emerging and intensifying issues for biodiversity conservation in South Africa over the next 5–10 years. South African biodiversity...     

Spatial and covariate-varying relationships among dominant tree species in Utah

Environmental and Ecological Statistics - The presence and establishment of a tree species at a particular spatial location is influenced by multiple physiological and environmental filters such as...     

Partitioning species variability from soil property effects on phytotoxicity: ECx normalization using a plant contaminant sensitivity index

Soil properties mitigate hazardous effects of contaminants through soil chemical sequestration and should be considered when evaluating ecological risk from terrestrial contamination. Empirical models that quantify relationships between soil properties and toxicity to ecological receptors are necessary for site-specific adjustments to ecological risk assessments. However, differential sensitivities of test organisms in dose-response studies may limit the utility of such models. We present a novel approach to toxicity estimation that partitions the effect of differential sensitivities of test organisms from that of soil chemical/physical properties. Five soils that ranged in selected properties were spiked with five concentrations of sodium arsenate. Bioassays were conducted where above ground dry matter growth and the corresponding tissue arsenic concentrations were evaluated for three terrestrial plants (Alfalfa, Medicago sativa L.; Perennial ryegrass, Lolium perrene L.; and Japanese millet, Echinochloa crusgalli L.). Estimates were combined into a plant contaminant sensitivity index (PCSI) and used to normalize phytotoxicity parameters to the most sensitive species (i.e., alfalfa) where necessary. Simple linear regression and ANCOVA indicated a 36.5% increase in the explanatory power of the modifying effects of soil properties on phytotoxicity when differential arsenate sensitivities were accounted for by PCSI (r(2) = 0.477-0.833). Normalization of ecotoxicity parameters by PCSI is a seemingly effective approach to quantify the modifying effects of soil properties on phytotoxicity endpoints when it is of interest to consider multiple plant species (or varieties within a species) with differential sensitivities to experimental contaminants.     

Optimal spatial resolution for collection of ground data and multi-sensor image mapping of a soil erosion cover factor

Military training activities disturb ground and vegetation cover of landscapes and increases potential soil erosion. To monitor the dynamics of soil erosion, there is an important need for an optimal sampling design in which determining the optimal spatial resolutions in terms of size of sample plots used for the collection of ground data and the size of pixels for mapping. Given a sample size, an optimal spatial resolution should be cost-efficient in both sampling costs and map accuracy. This study presents a spatial variability-based method for that purpose and compared it with the traditional methods in a study area in which a soil erosion cover factor was sampled and mapped with multiple plot sizes and multi-sensor images. The results showed that the optimal spatial resolutions obtained using the spatial variability-based method were 12 and 20m for years 1999 and 2000, respectively, and were consistent with those using the traditional methods. Moreover, the most appropriate spatial resolutions using the high-resolution images were also consistent with those using ground sample data, which provides a potential to use the high-resolution images instead of ground data to determine the optimal spatial resolutions before sampling. The most appropriate spatial resolutions above were then verified in terms of cost-efficiency which was defined as the product of sampling cost and map error using ordinary kriging without images and sequential Gaussian co-simulation with images to generate maps.     

Polybrominated diphenyl ethers (PBDE) in serum: findings from a US cohort of consumers of sport-caught fish

Polybrominated diphenyl ethers (PBDEs) have been used as flame retardants in foams, fabrics and plastics, and are common contaminants of household air and dust and bioaccumulate in wildlife, and are detectable in human tissues and in fish and animal food products. In the Great Lakes Basin sport fish consumption has been demonstrated to be an important source of PCB and DDE exposure. PBDEs are present in the same sport fish but prior to our study the contribution to human PBDE body burdens from Great Lakes sport fish consumption had not been investigated. This study was designed to assess PBDE, PCB and 1,1-bis(4-chlorophenyl)-2,2-dichloroethene (DDE) serum concentrations in an existing cohort of 508 frequent and infrequent consumers of sport-caught fish living in five Great Lake states. BDE congeners 47 and 99 were identified in the majority of blood samples, 98% and 62% respectively. summation operatorPBDE levels were positively associated with age, hours spent outdoors, DDE, summation operatorPCB, years of sportfish consumption, and catfish and shellfish intake, and negatively associated with income and recent weight loss. Other dietary components collected were not predictive of measured summation operatorPBDE levels. In multivariate models, summation operatorPBDE levels were positively associated with age, years consuming sport fish, shellfish meals, and computer use and negatively associated with recent weight loss. Having summation operatorPBDE levels in the highest quintile was independently associated with older age, male gender, consumption of catfish and shellfish, computer use and spending less time indoors. summation operatorPCB and DDE were strongly associated suggesting common exposure routes. The association between summation operatorPBDE and summation operatorPCB or DDE was much weaker and modeling suggested more diverse PBDE sources with few identified multi-contaminant-shared exposure routes. In our cohort Great Lakes sport fish consumption does not contribute strongly to PBDE exposure.     

Vegetative buffers for fan emissions from poultry farms: 2. ammonia, dust and foliar nitrogen

This study evaluated the potential of trees planted around commercial poultry farms to trap ammonia (NH(3)) and dust or particulate matter (PM). Norway spruce, Spike hybrid poplar, hybrid willow, and Streamco purpleosier willow were planted on five commercial farms from 2003 to 2004. Plant foliage was sampled in front of the exhaust fans and at a control distance away from the fans on one turkey, two laying hen, and two broiler chicken farms between June and July 2006. Samples were analyzed for dry matter (DM), nitrogen (N), and PM content. In addition, NH(3) concentrations were measured downwind of the exhaust fans among the trees and at a control distance using NH(3) passive dosi-tubes. Foliage samples were taken and analyzed separately based on plant species. The two layer farms had both spruce and poplar plantings whereas the two broiler farms had hybrid willow and Streamco willow plantings which allowed sampling and species comparisons with the effect of plant location (control vs. fan). The results showed that NH(3) concentration h(- 1) was reduced by distance from housing fans (P < or = 0.0001), especially between 0 m (12.01 ppm), 11.4 m (2.59 ppm), 15 m (2.03 ppm), and 30 m (0.31 ppm). Foliar N of plants near the fans was greater than those sampled away from the fans for poplar (3.87 vs. 2.56%; P < or = 0.0005) and hybrid willow (3.41 vs. 3.02%; P < or = 0.05). The trends for foliar N in spruce (1.91 vs. 1.77%; P = 0.26) and Streamco willow (3.85 vs. 3.33; P = 0.07) were not significant. Pooling results of the four plant species indicated greater N concentration from foliage sampled near the fans than of that away from the fans (3.27 vs. 2.67%; P < or = 0.0001). Foliar DM concentration was not affected by plant location, and when pooled the foliar DM of the four plant species near the fans was 51.3% in comparison with 48.5% at a control distance. There was a significant effect of plant location on foliar N and DM on the two layer farms with greater N and DM adjacent to fans than at a control distance (2.95 vs. 2.15% N and 45.4 vs. 38.2% DM, respectively). There were also significant plant species effects on foliar N and DM with poplar retaining greater N (3.22 vs. 1.88%) and DM (43.7 vs. 39.9%) than spruce. The interaction of location by species (P < or = 0.005) indicated that poplar was more responsive in terms of foliar N, but less responsive for DM than spruce. The effect of location and species on foliar N and DM were not clear among the two willow species on the broiler farms. Plant location had no effect on plant foliar PM weight, but plant species significantly influenced the ability of the plant foliage to trap PM with spruce and hybrid willow showing greater potential than poplar and Streamco willow for PM(2.5)(0.0054, 0.0054, 0.0005, and 0.0016 mg cm(- 2); P < or = 0.05) and total PM (0.0309, 0.0102, 0.0038, and 0.0046 mg cm(- 2), respectively; P < or = 0.001). Spruce trapped more dust compared to the other three species (hybrid willow, poplar, and Streamco willow) for PM(10) (0.0248 vs. 0.0036 mg cm(- 2); P < or = 0.0001) and PM(> 10) (0.0033 vs. 0.0003 mg cm(- 2); P = 0.052). This study indicates that poplar, hybrid willow, and Streamco willow are appropriate species to absorb poultry house aerial NH(3)-N, whereas spruce and hybrid willow are effective traps for dust and its associated odors.     

Apportionment of ambient primary and secondary fine particulate matter at the Pittsburgh National Energy Laboratory particulate matter characterization site using positive matrix factorization and a potential source contributions function analysis

Fine particulate matter (PM2.5) concentrations associated with 202 24-hr samples collected at the National Energy Technology Laboratory (NETL) particulate matter (PM) characterization site in south Pittsburgh from October 1999 through September 2001 were used to apportion PM2.5 into primary and secondary contributions using Positive Matrix Factorization (PMF2). Input included the concentrations of PM2.5 mass determined with a Federal Reference Method (FRM) sampler, semi-volatile PM2.5 organic material, elemental carbon (EC), and trace element components of PM2.5. A total of 11 factors were identified. The results of potential source contributions function (PSCF) analysis using PMF2 factors and HYSPLIT-calculated back-trajectories were used to identify those factors associated with specific meteorological transport conditions. The 11 factors were identified as being associated with emissions from various specific regions and facilities including crustal material, gasoline combustion, diesel combustion, and three nearby sources high in trace metals. Three sources associated with transport from coal-fired power plants to the southeast, a combination of point sources to the northwest, and a steel mill and associated sources to the west were identified. In addition, two secondary-material-dominated sources were identified, one was associated with secondary products of local emissions and one was dominated by secondary ammonium sulfate transported to the NETL site from the west and southwest. Of these 11 factors, the four largest contributors to PM2.5 were the secondary transported material (dominated by ammonium sulfate) (47%), local secondary material (19%), diesel combustion emissions (10%), and gasoline combustion emissions (8%). The other seven factors accounted for the remaining 16% of the PM2.5 mass. The findings are consistent with the major source of PM2.5 in the Pittsburgh area being dominated by ammonium sulfate from distant transport and so decoupled from local activity emitting organic pollutants in the metropolitan area. In contrast, the major local secondary sources are dominated by organic material.