Fine-scale genetic structure in short-beaked common dolphins (<Emphasis Type="Italic">Delphinus</Emphasis><Emphasis Type="Italic">delphis</Emphasis>) along the East Australian Current

Oceanographic processes play a significant role in shaping the genetic structure of marine populations, but it is less clear whether they affect genetic differentiation of highly mobile vertebrates. We used microsatellite markers and mtDNA control region sequences to investigate the spatial genetic structure of short-beaked common dolphins (Delphinus delphis) in southeastern Australia, a region characterised by complex oceanographic conditions associated with the East Australian Current (EAC). A total of 115 biopsy samples of dolphins were collected from six localities spanning approximately 1,000 km of the New South Wales (NSW) coastline. We found evidence for contrasting genetic diversity and fine-scale genetic structure, characterised by three genetically differentiated populations with varying levels of admixture. Spatial genetic structure was not explained by a model of isolation by distance, instead it coincides with main patterns of oceanographic variation along the EAC. We propose that common dolphins along the EAC may be adapted to three water masses recently characterised in this region.     

溶剂萃取法再生废机油的研究

用溶剂萃取-白土精制法对4种废机油进行了再生研究,萃取过程剂油质量比为3∶1,萃取温度为60℃,减压蒸馏回收溶剂。白土精制过程中白土质量为油质量的10%,精制温度为185℃。精制后4种废机油的密度、凝点、黏度、闪点、酸值等都有不同程度的改善。     

Sociopolitical ideology and the morality of green behaviour

Combating climate change and protecting the environment is a significant topic amongst political leaders and concerned citizens across the globe. The degree to which individuals perceive green issues as important is connected to their politics, those subscribing to conservative ideologies being less supportive of pro-environmental initiatives and less concerned about climate change than those endsorsing liberal ideologies. Examining political ideology as a uni- and bi-dimensional construct, the present research investigated whether political liberals (vs. conservatives), those higher (vs. lower) in right-wing authoritarianism, and those higher (vs. lower) in social dominance orientation differ in their perceptions of the morality of green behaviours. In Studies 1 (n = 200) and 2 (n = 150), liberal (vs. conservative) ideologies related to perceiving pro-environmental behaviours as more moral. Further, in Study 2, the relation between ideology and perceptions of green behaviours as moral was explained by positive feelings associated with the self engaging in green behaviours.     

Does process fairness affect job performance? It only matters if they plan to stay

Incorporating a social exchange perspective, we examined the joint impact of process fairness and turnover intentions on job performance. Results from two independent samples suggest that employee turnover intentions moderate relations between process fairness perceptions and employee job performance. Specifically, the positive effects of the two types of process fairness on performance were stronger for employees who planned to stay with the organization than for those who intended to leave. Copyright © 2012 John Wiley & Sons, Ltd.     

Social dimensions of science–humanitarian collaboration: lessons from Padang,Sumatra, Indonesia

This paper contains a critical exploration of the social dimensions of the science–humanitarian relationship. Drawing on literature on the social role of science and on the social dimensions of humanitarian practice, it analyses a science–humanitarian partnership for disaster risk reduction (DRR) in Padang, Sumatra, Indonesia, an area threatened by tsunamigenic earthquakes. The paper draws on findings from case study research that was conducted between 2010 and 2011. The case study illustrates the social processes that enabled and hindered collaboration between the two spheres, including the informal partnership of local people and scientists that led to the co‐production of earthquake and tsunami DRR and limited organisational capacity and support in relation to knowledge exchange. The paper reflects on the implications of these findings for science–humanitarian partnering in general, and it assesses the value of using a social dimensions approach to understand scientific and humanitarian dialogue.     

Nitrate removal in a riparian wetland of the Appalachian Valley and Ridge physiographic province

Riparian zones within the Appalachian Valley and Ridge physiographic province are often characterized by localized variability in soil moisture and organic carbon content, as well as variability in the distribution of soils formed from alluvial and colluvial processes. These sources of variability may significantly influence denitrification rates. This investigation studied the attenuation of nitrate (NO3- -N) as wastewater effluent flowed through the shallow ground water of a forested headwater riparian zone within the Appalachian Valley and Ridge physiographic province. Ground water flow and NO3- -N measurements indicated that NO3- -N discharged to the riparian zone preferentially flowed through the A and B horizons of depressional wetlands located in relic meander scars, with NO3- -N decreasing from > 12 to < 0.5 mg L(-1). Denitrification enzyme activity (DEA) attributable to riparian zone location, soil horizon, and NO3- -N amendments was also determined. Mean DEA in saturated soils attained values as high as 210 microg N kg(-1) h(-1), and was significantly higher than in unsaturated soils, regardless of horizon (p < 0.001). Denitrification enzyme activity in the shallow A horizon of wetland soils was significantly higher (p < 0.001) than in deeper soils. Significant stimulation of DEA (p = 0.027) by N03- -N amendments occurred only in the meander scar soils receiving low NO3- -N (<3.6 mg L(-1)) concentrations. Significant denitrification of high NO3- -N ground water can occur in riparian wetland soils, but DEA is dependent upon localized differences in the degree of soil saturation and organic carbon content.     

Ion partitioning among soil and plant components under drip,furrow, and sprinkler irrigation regimes: field and modeling assessments

Soil and water resources can be severely degraded by salinity when total salt input exceeds output in irrigated agriculture. This study was conducted to examine partitioning of Ca2+, Na+, and Cl- between soil and soybean [Glycine max (L.) Merr.] plants under different irrigation regimes with both field and modeling assessments. In drip and sprinkler treatments, the irrigation water was salinized with NaCl and CaCl2 salts to simulate a Cl- and Na+ dominant saline drainage water. In the furrow irrigation treatment, the soil was salinized, prior to planting, with NaCl and CaCl2 salts to simulate a Cl- and Na+ dominant saline soil. A total of 756 soil and 864 plant samples were collected and analyzed for the salt ions to obtain ion partitioning and mass balance assessments. Modeling of salt ion uptake by plants and distribution in the soil profile was performed with a two-dimensional solute transport model for the three irrigation regimes. Results indicated that about 20% of the applied Ca2+ was recovered in harvested soybean biomass in all treatments. Plant uptake of either Na+ or Cl- was less than 0.5% in the drip and furrow, and about 2% in the sprinkler irrigation treatment. Significant increases in soil salinity were found in the sprinkler plot that received the highest cumulative amount of salts. Simulated ion distributions in the soil were comparable with the measurements. Compared with the total seasonal salt input, mass balances between 65 and 108% were obtained. Most salt inputs accumulate in the soil, and need to be removed periodically to prevent soil salinization.     

Effects of seismic intensity and socioeconomic status on injury and displacement after the 2007 Peru earthquake

Earthquakes are a major cause of displacement, particularly in developing countries. Models of injury and displacement can be applied to assist governments and aid organisations in effectively targeting preparedness and relief efforts. A stratified cluster survey was conducted in January 2008 to evaluate risk factors for injury and displacement following the 15 August 2007 earthquake in southern Peru. In statistical modelling, seismic intensity, distance to rupture, living conditions, and educational attainment collectively explained 54.9 per cent of the variability in displacement rates across clusters. Living conditions was a particularly significant predictor of injury and displacement, indicating a strong relationship between risk and socioeconomic status. Contrary to expectations, urban, periurban, and rural clusters did not exhibit significantly different injury and displacement rates. Proxies of socioeconomic status, particularly the living conditions index score, proved relevant in explaining displacement, likely due to unmeasured aspects of housing construction practices and building materials.     

Tree growth inference and prediction from diameter censuses and ring widths.

Estimation of tree growth is based on sparse observations of tree diameter, ring widths, or increments read from a dendrometer. From annual measurements on a few trees (e.g., increment cores) or sporadic measurements from many trees (e.g., diameter censuses on mapped plots), relationships with resources, tree size, and climate are extrapolated to whole stands. There has been no way to formally integrate different types of data and problems of estimation that result from (1) multiple sources of observation error, which frequently result in impossible estimates of negative growth, (2) the fact that data are typically sparse (a few trees or a few years), whereas inference is needed broadly (many trees over many years), (3) the fact that some unknown fraction of the variance is shared across the population, and (4) the fact that growth rates of trees within competing stands are not independent. We develop a hierarchical Bayes state space model for tree growth that addresses all of these challenges, allowing for formal inference that is consistent with the available data and the assumption that growth is nonnegative. Prediction follows directly, incorporating the full uncertainty from inference with scenarios for "filling the gaps" for past growth rates and for future conditions affecting growth. An example involving multiple species and multiple stands with tree-ring data and up to 14 years of tree census data illustrates how different levels of information at the tree and stand level contribute to inference and prediction.