What signals does procedural justice climate convey? The roles of group status,and organizational benevolence and integrity

We propose and test a theoretical framework to explore why and how procedural justice climate influences individual behaviors after controlling for the influence of individual justice perception. Two types of symbolic information conveyed by procedural justice climate are considered. We argue that procedural justice climate reflects the status of or respect for a justice recipient, a work unit within an organization in our context, which then influences the identification of its members with the work unit. Procedural justice climate also reflects the moral attributes of a justice actor, herein an organization, which then influences organizational identification and perceived job security. Consistent with these arguments, results showed that perceived respect for the work unit mediated the relationship between procedural justice climate and identification with the work unit, and both perceived organizational benevolence and integrity mediated the relationship of procedural justice climate with organizational identification and job security. The two types of social identification and perceived job security were related to several outcome variables differently. Copyright © 2013 John Wiley & Sons, Ltd.     

Elevated CO2 alters larval proteome and its phosphorylation status in the commercial oyster, Crassostrea hongkongensis

Ocean acidification (OA) is beginning to have noticeable negative impact on calcification rate, shell structure and physiological energy budgeting of several marine organisms; these alter the growth of many economically important shellfish including oysters. Early life stages of oysters may be particularly vulnerable to OA-driven low pH conditions because their shell is made up of the highly soluble form of calcium carbonate (CaCO₃) mineral, aragonite. Our long-term CO₂ perturbation experiment showed that larval shell growth rate of the oyster species Crassostrea hongkongensis was significantly reduced at pH < 7.9 compared to the control (8.2). To gain new insights into the underlying mechanisms of low-pH-induced delays in larval growth, we have examined the effect of pH on the protein expression pattern, including protein phosphorylation status at the pediveliger larval stage. Using two-dimensional electrophoresis and mass spectrometry, we demonstrated that the larval proteome was significantly altered by the two low pH treatments (7.9 and 7.6) compared to the control pH (8.2). Generally, the number of expressed proteins and their phosphorylation level decreased with low pH. Proteins involved in larval energy metabolism and calcification appeared to be down-regulated in response to low pH, whereas cell motility and production of cytoskeletal proteins were increased. This study on larval growth coupled with proteome change is the first step toward the search for novel Protein Expression Signatures indicative of low pH, which may help in understanding the mechanisms involved in low pH tolerance.     

Residues of fluoroquinolones in marine aquaculture environment of the Pearl River Delta, South China

Concentrations and distributions of selected fluoroquinolones (norfloxacin, ciprofloxacin and enrofloxacin) in water, sediments and nine kinds of fish species collected from 6 sites in two marine aquaculture regions of the Pearl River Delta, China, were analyzed by using high-performance liquid chromatography with fluorescence detector (HPLC). The results showed that the concentrations of ciprofloxacin and enrofloxacin were below the limits of quantification (LOQ) in all water samples except for norfloxacin. Norfloxacin and ciprofloxacin concentrations ranged from 1.88 to 11.20 ng g⁻¹ dry wt, 0.76–2.42 ng g⁻¹ dry wt in sediments collected from the Dapeng’ao region (sites 1–3) and ranged from 2.31 to 4.75 ng g⁻¹ dry wt, 1.26–1.76 ng g⁻¹ dry wt in sediments collected from the Hailing Island region (sites 4–6), respectively. However, no enrofloxacin was found in all sediment samples. The three fluoroquinolones (FQs) were detected in all fish samples, and the concentrations were higher in liver tissues than those in muscle tissues. The levels of norfloxacin were higher than ciprofloxacin and enrofloxacin in both liver and muscle tissues. Among the nine marine fish species, Siganus fuscescens from Hailing Island had a significantly high level of norfloxacin in liver tissue (254.58 ng g⁻¹ wet wt), followed by Sparus macrocephalus (133.15 ng g⁻¹ wet wt) from Dapeng’ao, and the lowest value was Lutianus argentimaculatus (5.18 ng g⁻¹ wet wt) from Hailing Island. The obtained results of FQs in present study do not represent a risk to the human health in Guangdong coastal area, based on the maximum residue limits (MRLs) established by Chinese Government and the acceptable daily intake (ADI) recommended by the Food and Agriculture Organization and World Health Organization (FAO/WHO).     

Predicting regional spread of non-native species using oceanographic models: validation and identification of gaps

Predicting spread is a central goal of invasion ecology. Within marine systems, researchers have increasingly made use of oceanographic circulation models to estimate currents and track species dispersal. However, the accuracy of these models for predicting biological patterns, particularly for non-native species, has generally not been validated. Particularly, we wished to examine the ability of models to predict physical and biological processes, which jointly determine the spread of marine larval organisms. We conducted two empirical studies—a recruitment study and a drift card study—along the coast of New England, USA, focusing on two invaders of concern—the European green crab (Carcinus maenas) and the Asian shore crab (Hemigrapsus sanguineus), to explicitly evaluate the ability of oceanographic models to predict patterns of spread. We used data from the large-scale drift card study to validate our ability to capture dispersal patterns driven purely by physical processes. Next, we conducted a recruitment study to evaluate our ability to reproduce patterns of biological dispersal. We were generally capable of reproducing drift cards patterns—suggesting that the physical mechanics in the model were predictive. However, predicted biological patterns were inconsistent—we were able to predict dispersal patterns for H. sanguineus but not for C. maenas. Our results highlight the importance of validating models and suggest that more work is necessary before we can reliably use oceanographic models to predict biological spread of intertidal organisms.