Personality and job performance: the importance of narrow traits

In a recent discussion of the bandwidth–fidelity dilemma in personality measurement for personnel selection, Ones and Viswesvaran (1996) concluded that ‘broader and richer personality traits will have higher predictive validity than narrower traits’. In this paper, the arguments made by Ones and Viswesvaran in favor of the exclusive use of broad personality dimensions are discussed. New data are presented that contradict Ones and Viswesvaran's claim of the existence of a general, integrity-related personality factor, and that show two narrow measures—the Responsibility and Risk Taking scales of the Jackson Personality Inventory—to have higher validities than the Big Five dimensions with respect to job performance criteria based on self-reported workplace delinquency in a sample of 127 entry-level employees. © 1998 John Wiley & Sons, Ltd.     

Wetland Flowpaths Mediate Nitrogen and Phosphorus Concentrations across the Upper Mississippi River Basin

Eutrophication, harmful algal blooms, and human health impacts are critical environmental challenges resulting from excess nitrogen and phosphorus in surface waters. Yet we have limited information regarding how wetland characteristics mediate water quality across watershed scales. We developed a large, novel set of spatial variables characterizing hydrological flowpaths from wetlands to streams, that is, “wetland hydrological transport variables,” to explore how wetlands statistically explain the variability in total nitrogen (TN) and total phosphorus (TP) concentrations across the Upper Mississippi River Basin (UMRB) in the United States. We found that wetland flowpath variables improved landscape-to-aquatic nutrient multilinear regression models (from R² = 0.89 to 0.91 for TN; R² = 0.53 to 0.84 for TP) and provided insights into potential processes governing how wetlands influence watershed-scale TN and TP concentrations. Specifically, flowpath variables describing flow-attenuating environments, for example, subsurface transport compared to overland flowpaths, were related to lower TN and TP concentrations. Frequent hydrological connections from wetlands to streams were also linked to low TP concentrations, which likely suggests a nutrient source limitation in some areas of the UMRB. Consideration of wetland flowpaths could inform management and conservation activities designed to reduce nutrient export to downstream waters.     

Enhancing perspectives on lake impairments using satellite observations: A case study on High Rock Lake,North Carolina

Stakeholders developing water quality improvement plans for lakes and reservoirs are challenged by the sparsity of in-situ data and the uncertainty ingrained in management decisions. This study explores how satellite images can fill gaps in water quality databases and provide more holistic assessments of impairments. The study site is an impaired water body that is serving as a pilot for improving state-wide nutrient management planning processes. An existing in-situ database was used to calibrate semi-analytical models that relate satellite reflectance values to turbidity and total suspended solids (TSS). Landsat-7 images from 1999 to 2020 that overpass High Rock Lake, North Carolina were downloaded and processed, providing 42 turbidity and 39 TSS satellite and in-situ match-ups for model calibration and validation. Model r-squared values for the fitted turbidity and TSS models are 0.72 and 0.74, and the mean absolute errors are 14.6 NTU and 3.2 mg/L. The satellite estimates were compared to the in-situ data and simulated TSS values produced by a calibrated hydrologic-hydrodynamic model. The process-based model is considered less accurate than the satellite model based on statistical performance metrics. Comparisons between data sources are illustrated with time series plots, frequency curves, and aggregate decision metrics to highlight the dependence of lake impairment assessments on the spatial and temporal frequency of available data and model accuracy.     

Model‐Based Nitrogen and Phosphorus (Nutrient) Criteria for Large Temperate Rivers: 2. Criteria Derivation

Nitrogen and phosphorus criteria were developed for 233 km of the Yellowstone River, one of the first cases where a mechanistic model has been used to derive large river numeric nutrient criteria. A water quality model and a companion model which simulates lateral algal biomass across transects were used to simulate effects of increasing nutrients on five variables (dissolved oxygen, total organic carbon, total dissolved gas, pH, and benthic algal biomass in depths ≤1 m). Incremental increases in nutrients were evaluated relative to their impact on predefined thresholds for each variable; the first variable to exceed a threshold set the nutrient criteria. Simulations were made at a low flow, the 14Q5 (lowest average 14 consecutive day flow, July‐September, recurring one in five years), which was derived using benthic algae growth curves and EPA guidance on excursion frequency. An extant climate dataset with an annual recurrence was used, and tributary water quality and flows were coincident with the river's 10 lowest flow years. The river had different sensitivities to nutrients longitudinally, pH being the most sensitive variable in the upstream reach and algal biomass in the lower. Model‐based criteria for the Yellowstone River are as follows: between the Bighorn and Powder river confluences, 55 μg TP/l and 655 μg TN/l; from the Powder River confluence to Montana state line, 95 μg TP/l and 815 μg TN/l. Pros and cons of using steady‐state models to derive river nutrient criteria are discussed.     

A strategy for the next decade to address data deficiency in neglected biodiversity

Measuring progress toward international biodiversity targets requires robust information on the conservation status of species, which the International Union for Conservation of Nature (IUCN) Red List of Threatened Species provides. However, data and capacity are lacking for most hyperdiverse groups, such as invertebrates, plants, and fungi, particularly in megadiverse or high-endemism regions. Conservation policies and biodiversity strategies aimed at halting biodiversity loss by 2020 need to be adapted to tackle these information shortfalls after 2020. We devised an 8-point strategy to close existing data gaps by reviving explorative field research on the distribution, abundance, and ecology of species; linking taxonomic research more closely with conservation; improving global biodiversity databases by making the submission of spatially explicit data mandatory for scientific publications; developing a global spatial database on threats to biodiversity to facilitate IUCN Red List assessments; automating preassessments by integrating distribution data and spatial threat data; building capacity in taxonomy, ecology, and biodiversity monitoring in countries with high species richness or endemism; creating species monitoring programs for lesser-known taxa; and developing sufficient funding mechanisms to reduce reliance on voluntary efforts. Implementing these strategies in the post-2020 biodiversity framework will help to overcome the lack of capacity and data regarding the conservation status of biodiversity. This will require a collaborative effort among scientists, policy makers, and conservation practitioners.     

Environmental modeling of uranium interstitial compositions of non-stoichiometric oxides: experimental and theoretical analysis

Study of uranium interstitial compositions of non-stoichiometric oxides UO_2+x (x ∈ 0.1–0.02) in gas and condense phases has been presented, using various soft-ionization mass spectrometric methods such as ESI-, APCI-, and MALDI-MS at a wide dynamic temperature gradient (∈ 25–300 °C). Linearly polarized vibrational spectroscopy has been utilized in order to assign unambiguously, the vibrational frequencies of uranium non-stoichiometric oxides. Experimental design has involved xUO_2.66·yUO_2.33, xUO_2.66·yUO_2.33/SiO₂, xUO_2.66·yUO_2.33/SiO₂ (NaOH) and SiO₂/x′NaOH·y′UO₂(NO₃)₂·6H₂O, multicomponent systems (x = 1, y ∈ 0.1–1.0 and x′ = 1, y′ ∈ 0.1–0.6) as well as phase transitions UO₂(NO₃)₂·6H₂O → {U₄O₉(UO_2.25)} → U₃O₇(UO_2.33) → U₃O₈(UO_2.66) → {UO₃}, thus ensuring a maximal representativeness to real environmental conditions, where diverse chemical, geochemical and biochemical reactions, including complexation and sorption onto minerals have occurred. Experimental factors such as UV-irradiation, pH, temperature, concentration levels, solvent types and ion strength have been taken into consideration, too. As far as uranium speciation represents a challenging analytical task in terms of chemical identification diverse coordination species, mechanistic aspects relating incorporation of oxygen into UO _2+x form the shown full methods validation significantly impacts the field of environmental radioanalytical chemistry. UO₂ is the most commonly used fuel in nuclear reactors around the globe; however, a large non-stoichiometric range ∈ UO_1.65–UO_2.25 has occurred due to radiolysis of water on UO₂ surface yielding to H₂O₂, OH^·, and more. Each of those compositions has different oxygen diffusion. And in this respect enormous effort has been concentrated to study the potential impact of hazardous radionuclide on the environment, encompassing from the reprocessing to the disposal stages of the fuel waste, including the waste itself, the processes in the waste containers, the clay around the containers, and geological processes. In a broader sense, thereby, this study contributes to field of environmental analysis highlighting the great ability of various soft-ionization MS methods, particularly, MALDI-MS one, for direct assay of complex multicomponent heterogeneous mixtures at fmol–attomol concentration ranges, along with it the great instrumental features allowing, not only meaningful quantitative, but also structural information of the analytes, thus making the method indispensable for environmental speciation of radionuclides, generally.