Storm versus calm : Variation in fauna associated with drifting macrophytes in sandy beach surf zones

New insights about nearshore dynamics came from studying the effects of regular storms in South Australia on drifting marine macrophytes, consequent wrack accumulation and associated fauna in beach surf zones across three different regions. This study examined whether the influence of storms may be more pronounced in sheltered coastal waters compared to more exposed coastlines where biota could have adaptations to persist in larger swell conditions. There were obvious regional differences for wrack species richness, abundances and assemblages that matched the attached floral subtidal landscape in each region. Consequently, invertebrates also differed amongst regions, which highlight the close affinity that some invertebrates have with drifting macrophytes. Fish were not so closely aligned to the regional patterns identified for wrack or invertebrates suggesting that many fish are using wrack accumulations as habitat but, being highly mobile, they may actively and constantly move into, out of and within these habitat features. Well-known beach-type models focused upon beach morphology may be more pertinent to the ecology of the surf zones offshore than previously thought, being the most consistent indicator of wrack accumulations and their fauna. This new evidence on the ecology of nearshore waters during storm versus calm weather in multiple regions and the subsequent influence on wrack-fauna associations in sandy-beach surf zones are important for future beach management, particularly when and where large wrack accumulations occur.

Zinc and zinc transporters in macrophages and their roles in efferocytosis in COPD

Our previous studies have shown that nutritional zinc restriction exacerbates airway inflammation accompanied by an increase in caspase-3 activation and an accumulation of apoptotic epithelial cells in the bronchioles of the mice. Normally, apoptotic cells are rapidly cleared by macrophage efferocytosis, limiting any secondary necrosis and inflammation. We therefore hypothesized that zinc deficiency is not only pro-apoptotic but also impairs macrophage efferocytosis. Impaired efferocytic clearance of apoptotic epithelial cells by alveolar macrophages occurs in chronic obstructive pulmonary disease (COPD), cigarette-smoking and other lung inflammatory diseases. We now show that zinc is a factor in impaired macrophage efferocytosis in COPD. Concentrations of zinc were significantly reduced in the supernatant of bronchoalveolar lavage fluid of patients with COPD who were current smokers, compared to healthy controls, smokers or COPD patients not actively smoking. Lavage zinc was positively correlated with AM efferocytosis and there was decreased efferocytosis in macrophages depleted of Zn in vitro by treatment with the membrane-permeable zinc chelator TPEN. Organ and cell Zn homeostasis are mediated by two families of membrane ZIP and ZnT proteins. Macrophages of mice null for ZIP1 had significantly lower intracellular zinc and efferocytosis capability, suggesting ZIP1 may play an important role. We investigated further using the human THP-1 derived macrophage cell line, with and without zinc chelation by TPEN to mimic zinc deficiency. There was no change in ZIP1 mRNA levels by TPEN but a significant 3-fold increase in expression of another influx transporter ZIP2, consistent with a role for ZIP2 in maintaining macrophage Zn levels. Both ZIP1 and ZIP2 proteins were localized to the plasma membrane and cytoplasm in normal human lung alveolar macrophages. We propose that zinc homeostasis in macrophages involves the coordinated action of ZIP1 and ZIP2 transporters responding differently to zinc deficiency signals and that these play important roles in macrophage efferocytosis.

Hydrologic landscape regionalisation using deductive classification and random forests

Landscape classification and hydrological regionalisation studies are being increasingly used in ecohydrology to aid in the management and research of aquatic resources. We present a methodology for classifying hydrologic landscapes based on spatial environmental variables by employing non-parametric statistics and hybrid image classification. Our approach differed from previous classifications which have required the use of an a priori spatial unit (e.g. a catchment) which necessarily results in the loss of variability that is known to exist within those units. The use of a simple statistical approach to identify an appropriate number of classes eliminated the need for large amounts of post-hoc testing with different number of groups, or the selection and justification of an arbitrary number. Using statistical clustering, we identified 23 distinct groups within our training dataset. The use of a hybrid classification employing random forests extended this statistical clustering to an area of approximately 228,000 km2 of south-eastern Australia without the need to rely on catchments, landscape units or stream sections. This extension resulted in a highly accurate regionalisation at both 30-m and 2.5-km resolution, and a less-accurate 10-km classification that would be more appropriate for use at a continental scale. A smaller case study, of an area covering 27,000 km2, demonstrated that the method preserved the intra- and inter-catchment variability that is known to exist in local hydrology, based on previous research. Preliminary analysis linking the regionalisation to streamflow indices is promising suggesting that the method could be used to predict streamflow behaviour in ungauged catchments. Our work therefore simplifies current classification frameworks that are becoming more popular in ecohydrology, while better retaining small-scale variability in hydrology, thus enabling future attempts to explain and visualise broad-scale hydrologic trends at the scale of catchments and continents.

Predicting the likely response of data-poor ecosystems to climate change using space-for-time substitution across domains

Predicting ecological response to climate change is often limited by a lack of relevant local data from which directly applicable mechanistic models can be developed. This limits predictions to qualitative assessments or simplistic rules of thumb in data-poor regions, making management of the relevant systems difficult. We demonstrate a method for developing quantitative predictions of ecological response in data-poor ecosystems based on a space-for-time substitution, using distant, well-studied systems across an inherent climatic gradient to predict ecological response. Changes in biophysical data across the spatial gradient are used to generate quantitative hypotheses of temporal ecological responses that are then tested in a target region. Transferability of predictions among distant locations, the novel outcome of this method, is demonstrated via simple quantitative relationships that identify direct and indirect impacts of climate change on physical, chemical and ecological variables using commonly available data sources. Based on a limited subset of data, these relationships were demonstrably plausible in similar yet distant (>2000 km) ecosystems. Quantitative forecasts of ecological change based on climate-ecosystem relationships from distant regions provides a basis for research planning and informed management decisions, especially in the many ecosystems for which there are few data. This application of gradient studies across domains - to investigate ecological response to climate change - allows for the quantification of effects on potentially numerous, interacting and complex ecosystem components and how they may vary, especially over long time periods (e.g. decades). These quantitative and integrated long-term predictions will be of significant value to natural resource practitioners attempting to manage data-poor ecosystems to prevent or limit the loss of ecological value. The method is likely to be applicable to many ecosystem types, providing a robust scientific basis for estimating likely impacts of future climate change in ecosystems where no such method currently exists.

Population genetic structure of the Australian caddisfly Lectrides varians Mosely (Trichoptera: Leptoceridae) and the identification of cryptic species in south-eastern Australia

Lectrides varians (Mosely) is a large, ecologically-important, caddisfly found in perennial and intermittent streams throughout much of eastern Australia. We conducted a population genetic analysis to investigate the dispersal potential of L. varians, building on previous works that have assessed life-history traits associated with drought resistance. Genetic analyses of L. varians from the Grampians region of Victoria, based on mitochondrial DNA sequence data, revealed extensive gene flow and a lack of genetic structure across the sample range (ΦST = 0.04). This suggests that the species is a strong disperser and is likely to be resilient to increased drying and habitat fragmentation under climate change considering other known resistance traits. However, during this study, two divergent genotypes were identified, indicating a potential species complex. A comprehensive phylogenetic analysis of L. varians across its current range was subsequently performed, confirming the species is indeed paraphyletic, consisting of one lineage that is restricted to the Grampians National Park and the other being widespread throughout south-eastern Australia. Further analyses revealed consistent morphological differences between these lineages supporting the notion that L. varians is a species complex. We discuss the implications of these findings with regard to conservation and taxonomy of this important invertebrate group.

Individual differences in intention to fake job interviews: Personality, self-monitoring, and the theory of planned behaviour

When job applicants lie in job interviews, they can deprive a more honest candidate of a job and deprive an organisation of the best employees. To better understand job interview faking, the present study examined the effect of general dispositions and domain-specific beliefs on the intention to fake job interviews. A community sample of 313 participants completed measures of personality (i.e., extraversion, neuroticism, conscientiousness) and self-monitoring, and a domain-specific measure of beliefs about faking job interviews based on the theory of planned behaviour, which measured attitudes, subjective norms, and perceived behavioural control. Results indicated that the measure of attitudes was the strongest predictor of intention to fake. In line with the compatibility principle, the domain-specific measures based on the theory of planned behaviour correlated much more strongly with intentions to fake job interviews than did the general measures of personality or self-monitoring. Of the dispositional measures, lower conscientiousness, higher neuroticism, and higher self-monitoring was associated with greater intention to fake job interviews. The findings support a model whereby the effect of personality on intentions is partially mediated by domain-specific beliefs.

Assessing spatio-temporal hydrologic variability: a case-study in western Victoria

This research explored spatial and temporal variability in the relationships between land cover, topography, and climate on streamflows and wetland extents in western Victoria.