Morphology-based model for predicting osteocyte-like cell line (MLO-Y4) growth process

This work has led to the development of empirical mathematical models to quantitatively predicate the changes of morphology in osteocyte-like cell lines (MLO-Y4) in culture. MLO-Y4 cells were cultured at low density and the changes in morphology recorded over 11 hours. Cell area and three dimensional shape features including aspect ratio, circularity and solidity were then determined using widely accepted image analysis software (ImageJTM). Based on the data obtained from the imaging analysis, mathematical models were developed using the non-linear regression method. The developed mathematical models accurately predict the morphology of MLO-Y4 cells for different culture times and can, therefore, be used as a reference model for analyzing MLO-Y4 cell morphology changes within various biological/mechanical studies, as necessary.

Mapping of multiple quantitative trait loci affecting bovine spongiform encephalopathy

A whole-genome scan was conducted to map quantitative trait loci (QTL) for BSE resistance or susceptibility. Cows from four half-sib families were included and 173 microsatellite markers were used to construct a 2835-cM (Kosambi) linkage map covering 29 autosomes and the pseudoautosomal region of the sex chromosome. Interval mapping by linear regression was applied and extended to a multiple-QTL analysis approach that used identified QTL on other chromosomes as cofactors to increase mapping power. In the multiple-QTL analysis, two genome-wide significant QTL (BTA17 and X/Y ps) and four genome-wide suggestive QTL (BTA1, 6, 13, and 19) were revealed. The QTL identified here using linkage analysis do not overlap with regions previously identified using TDT analysis. One factor that may explain the disparity between the results is that a more extensive data set was used in the present study. Furthermore, methodological differences between TDT and linkage analyses may affect the power of these approaches.

Caring efficacy and job satisfaction in Australian registered nurses

Purpose: The purpose of the study was to examine relationships between socio-demographic variables, job satisfaction and nurses’ caring experiences in a registered nurse population, as measured by the caring efficacy scale (CES) which was developed from Bandura’s social cognitive theory and Watson’s transpersonal caring theory. Methods: A cross-sectional survey was undertaken of nurses representing a variety of nursing specialties. A stratified random sample of registered nurses, who were members of a professional nursing organisation, was invited to participate in this study. Descriptive analyses, correlation analyses, one- way ANOVA tests, simple linear regression and multivariable analyses were conducted to examine if any relationships existed between these variables. Results: There were a total of 639 respondents to the national survey. The respondents (100%) showed positive perceived CES scores and 80.8% showed positive job satisfaction scores. Correlation analysis found age, years experience as a registered nurse and years in current job, all positively correlated with each other, (r >0.40: p < 0.001). CES scores were found to be positively correlated with age, years of experience as a registered nurse (r>0.1: p < 0.001) and job satisfaction (r>0.1: p < 0.001). An ANOVA found significant positive relationships between CES scores and age (p=0.05). Conclusion: Results from this study have identified that relationships between age, years of experience, job satisfaction and the perceived caring experiences of nurses’ exist. Organisational leaders may develop strategies for professional development and orientation programmes that enhance the caring experiences of nurses to provide quality patient care. The development of programmes that provide role modelling, emotional support or use verbal persuasion are needed where encouragement is required for nurses to master new skills. This may also improve job satisfaction and retention of nurses in the workplace in the current economically focussed healthcare system.

A longitudinal study of grieving in family caregivers of people with dementia

A longitudinal study of grieving in family caregivers of people with dementia Recent research into dementia has identified the long term impact that the role of care giving for a relative with dementia has on family members This is largely due to the cognitive decline that characterises dementia and the losses that can be directly attributed to this. These losses include loss of memories, relationships and intimacy, and are often ambiguous so that the grief that accompanies them is commonly not recognised or acknowledged. The role and impact of pre-death or anticipatory grief has not previously been widely considered as a factor influencing health and well-being of family caregivers. Studies of grief in caregivers of a relative with dementia have concluded that grief is one of the greatest barriers to care giving and is a primary determinant of caregiver well-being. The accumulation of losses, in conjunction with experiences unique to dementia care giving, place family caregivers at risk of complicated grief. This occurs when integration of the death does not take place following bereavement and has been associated with a range of negative health outcomes. The aim of this research was to determine the influence of grief, in addition to other factors representing both positive and negative aspects of the role, on the health related quality of life of family caregivers of people with dementia, prior to and following the death of their relative with dementia. An exploratory research project underpinned by a conceptual framework of caregivers’ adaptation in the context of subjective appraisal of the strains and gains in their role was undertaken. The research comprised three studies. Study 1 was a scoping study that involved a series of semi-structured interviews with thirteen participants who were family caregivers of people with severe dementia or whose relative with dementia had died in the previous twelve months. The results of this study in conjunction with factors identified in the literature informed data collection for the further studies. Study 2 was a cross sectional survey of fifty caregivers recruited when their relative was in the moderate to severe stage of dementia. This study provided the baseline data for Study 3, a prospective cohort follow up study. Study 3 consisted of seventeen participants followed up at two time points after the death of their relative with dementia: six weeks and then six months following the death of the relative with dementia. The scoping study indicated that differences in appraisal of the care giving role and encounters with health professionals were related to levels of grief of caregivers prior to and following the death of the relative with dementia. This was supported in the baseline and follow up studies. In the baseline study, after adjusting for all variables in multivariate regression models, subjective appraisal of burden was found to make a significant contribution (p<.05) to mental health related quality of life. The two dependent variables, anticipatory grief and mental health related quality of life, were significantly (p<.01) correlated at a bivariate level. In the follow up study, linear mixed modelling and multiple regression analysis of data found that subjective appraisal of burden and resilience were significantly associated (p<.05 and p<.01, respectively) with mental health related quality of life over time. In addition, bereavement and complicated grief were significantly associated (p<.05) with mental health following the death of the relative. In this study social support and satisfaction with end of life care were found to be statistically associated (p<.05) with physical health related quality of life over time. The strong relationship between grief of caregivers and their health related quality of life over the entire care giving trajectory and period following the death of their relative highlights the urgent need for further research and interventions in this area. Overall results indicate that addressing the risk and protective factors including subjective appraisal of their care giving role, resilience, social support and satisfaction with end of life care of their relative, has the potential to both ameliorate negative health outcomes and to promote improved health for these caregivers. This research provides important information for development of targeted and appropriate interventions that aim to promote resilience and reduce the personal burden on caregivers of people with dementia.

Morphology of osteocyte cells in normal and hyper-gravity

Osteocyte cells are the most abundant cells in human bone tissue. Due to their unique morphology and location, osteocyte cells are thought to act as regulators in the bone remodelling process, and are believed to play an important role in astronauts’ bone mass loss after long-term space missions. There is increasing evidence showing that an osteocyte’s functions are highly affected by its morphology. However, changes in an osteocyte’s morphology under an altered gravity environment are still not well documented. Several in vitro studies have been recently conducted to investigate the morphological response of osteocyte cells to the microgravity environment, where osteocyte cells were cultured on a two-dimensional flat surface for at least 24 hours before microgravity experiments. Morphology changes of osteocyte cells in microgravity were then studied by comparing the cell area to 1g control cells. However, osteocyte cells found in vivo are with a more 3D morphology, and both cell body and dendritic processes are found sensitive to mechanical loadings. A round shape osteocyte’s cells support a less stiff cytoskeleton and are more sensitive to mechanical stimulations compared with flat cellular morphology. Thus, the relative flat and spread shape of isolated osteocytes in 2D culture may greatly hamper their sensitivity to a mechanical stimulus, and the lack of knowledge on the osteocyte’s morphological characteristics in culture may lead to subjective and noncomprehensive conclusions of how altered gravity impacts on an osteocyte’s morphology. Through this work empirical models were developed to quantitatively predicate the changes of morphology in osteocyte cell lines (MLO-Y4) in culture, and the response of osteocyte cells, which are relatively round in shape, to hyper-gravity stimulation has also been investigated. The morphology changes of MLO-Y4 cells in culture were quantified by measuring cell area and three dimensionless shape features including aspect ratio, circularity and solidity by using widely accepted image analysis software (ImageJTM). MLO-Y4 cells were cultured at low density (5×103 per well) and the changes in morphology were recorded over 10 hours. Based on the data obtained from the imaging analysis, empirical models were developed using the non-linear regression method. The developed empirical models accurately predict the morphology of MLO-Y4 cells for different culture times and can, therefore, be used as a reference model for analysing MLO-Y4 cell morphology changes within various biological/mechanical studies, as necessary. The morphological response of MLO-Y4 cells with a relatively round morphology to hyper-gravity environment has been investigated using a centrifuge. After 2 hours culture, MLO-Y4 cells were exposed to 20g for 30mins. Changes in the morphology of MLO-Y4 cells are quantitatively analysed by measuring the average value of cell area and dimensionless shape factors such as aspect ratio, solidity and circularity. In this study, no significant morphology changes were detected in MLO-Y4 cells under a hyper-gravity environment (20g for 30 mins) compared with 1g control cells.

Postnatal depression in Central Vietnam

Postnatal depression (PND) is a significant global health issue, which not only impacts maternal wellbeing, but also infant development and family structures. Mental health disorders represent approximately 14% of global burden of disease and disability, including low and middle-income countries (LMIC), and PND has direct relevance to the Millennium Development Goals of reducing child mortality, improving maternal health, and creating global partnerships (United Nations, 2012; Guiseppe, Becker & Farmer, 2011). Emerging evidence suggests that PND in LMIC is similar to, or higher than in high-income countries (HIC), however, less than 10% of LMIC have prevalence data available (Fisher, Cabral de Mello, & Izutsu 2009; Lund et al., 2011). Whilst a small number of studies on maternal mental disorders have been published in Vietnam, only one specifically focuses on PND in a hospital-based sample. Also, community based mental health studies and information on mental health in rural areas of Vietnam is still scarce. The purpose of this study was to determine the prevalence of PND, and its associated social determinants in postnatal women in Thua Thien Hue Province, Central Vietnam. In order to identify social determinants relevant to the Central Vietnamese context, two qualitative studies and one community survey were undertaken. Associations between maternal mental health and infant health outcomes were also explored. The study was comprised of three phases. Firstly, iterative, qualitative interviews with Vietnamese health professionals (n = 17) and postpartum women (n = 15) were conducted and analysed using Kleinman's theory of explanatory models to identify narratives surrounding PND in the Vietnamese context (Kleinman, 1978). Secondly, a participatory concept mapping exercise was undertaken with two groups of health professionals (n = 12) to explore perceived risk and protective factors for postnatal mental health. Qualitative phases of the research elucidated narratives surrounding maternal mental health in the Vietnamese context such as son preference, use of traditional medicines, and the popularity of confinement practices such as having one to three months of complete rest. The qualitative research also revealed the construct of depression was not widely recognised. Rather, postpartum changes in mood were conceptualised as a loss of 'vital strength' following childbirth or 'disappointment'. Most women managed postpartum changes in mood within the family although some sought help from traditional medicine practitioners or biomedical doctors. Thirdly, a cross-sectional study of twelve randomly selected communes (six urban, six rural) in Thua Thien Hue Province was then conducted. Overall, 465 women with infants between 4 weeks and six months old participated, and 431 questionnaires were analysed. Women from urban (n = 216) and rural (n = 215) areas participated. All eligible women completed a structured interview about their health, basic demographics, and social circumstances. Maternal depression was measured using the Edinburgh Postnatal Depression Scale (EPDS) as a continuous variable. Multivariate generalised linear regression was conducted using PASW Statistics version 18.0 (2009). When using the conventional EPDS threshold for probable depression (EPDS score ~ 13) 18.1% (n = 78) of women were depressed (Gibson, McKenzie-McHarg, Shakespeare, Price & Gray, 2009). Interestingly, 20.4% of urban women (n = 44) had EPDS scores~ 13, which was a higher proportion than rural women, where 15.8% (n = 34) had EPDS scores ~ 13, although this difference was not statistically significant: t(429) = -0.689, p = 0.491. Whilst qualitative narratives identified infant gender and family composition, and traditional confinement practices as relevant to postnatal mood, these were not statistically significant in multivariate analysis. Rather, poverty, food security, being frightened of your husband or family members, experiences of intimate partner violence and breastfeeding difficulties had strong statistical associations. PND was also associated with having an infant with diarrhoea in the past two weeks, but not infant malnutrition or acute respiratory infections. This study is the first to explore maternal mental health in Central Vietnam, and provides further evidence that PND is a universally experienced phenomenon. The independent social risk factors of depressive symptoms identified such as poverty, food insecurity, experiences of violence and powerlessness, and relationship adversity points to women in a context of social suffering which is relevant throughout the world (Kleinman, Das & Lock, 1997). The culturally specific risk factors explored such as infant gender were not statistically significant when included in a multivariable model. However, they feature prominently in qualitative narratives surrounding PND in Vietnam, both in this study and previous literature. It appears that whilst infant gender may not be associated with PND per se, the reactions of close relatives to the gender of the baby can adversely affect maternal wellbeing. This study used a community based participatory research approach (CBPR) (Israel.2005). This approach encourages the knowledge produced to be used for public health interventions and workforce training in the community in which the research was conducted, and such work has commenced. These results suggest that packages of interventions for LMIC devised to address maternal mental health and infant wellbeing could be applied in Central Vietnam. Such interventions could include training lay workers to follow up postpartum women, and incorporating mental health screening and referral into primary maternal and child health care (Pate! et al., 2011; Rahman, Malik, Sikander & Roberts, 2008). Addressing the underlying social determinants of PND through poverty reduction and violence elimination programs is also recommended.

Vulnerability and damage analysis of reinforced concrete framed buildings subjected to near field blast events

Terrorists usually target high occupancy iconic and public buildings using vehicle borne incendiary devices in order to claim a maximum number of lives and cause extensive damage to public property. While initial casualties are due to direct shock by the explosion, collapse of structural elements may extensively increase the total figure. Most of these buildings have been or are built without consideration of their vulnerability to such events. Therefore, the vulnerability and residual capacity assessment of buildings to deliberately exploded bombs is important to provide mitigation strategies to protect the buildings' occupants and the property. Explosive loads and their effects on a building have therefore attracted significant attention in the recent past. Comprehensive and economical design strategies must be developed for future construction. This research investigates the response and damage of reinforced concrete (RC) framed buildings together with their load bearing key structural components to a near field blast event. Finite element method (FEM) based analysis was used to investigate the structural framing system and components for global stability, followed by a rigorous analysis of key structural components for damage evaluation using the codes SAP2000 and LS DYNA respectively. The research involved four important areas in structural engineering. They are blast load determination, numerical modelling with FEM techniques, material performance under high strain rate and non-linear dynamic structural analysis. The response and damage of a RC framed building for different blast load scenarios were investigated. The blast influence region for a two dimensional RC frame was investigated for different load conditions and identified the critical region for each loading case. Two types of design methods are recommended for RC columns to provide superior residual capacities. They are RC columns detailing with multi-layer steel reinforcement cages and a composite columns including a central structural steel core. These are to provide post blast gravity load resisting capacity compared to typical RC column against a catastrophic collapse. Overall, this research broadens the current knowledge of blast and residual capacity analysis of RC framed structures and recommends methods to evaluate and mitigate blast impact on key elements of multi-storey buildings.

Retinal nerve fibre layer thickness is associated with higher risk of foot ulceration in diabetic peripheral neuropathy

Purpose To evaluate the association between retinal nerve fibre layer (RNFL) thickness and diabetic peripheral neuropathy in people with type 2 diabetes, and specifically those at higher risk of foot ulceration. Methods RNFL thicknesses was measured globally and in four quadrants (temporal, superior, nasal and inferior) at 3.45 mm diameter around the optic nerve head using optical coherence tomography (OCT). Severity of neuropathy was assessed using the Neuropathy Disability Score (NDS). Eighty-two participants with type 2 diabetes were stratified according to NDS scores (0-10) as: none, mild, moderate, and severe neuropathy. A control group was additionally included (n=17). Individuals with NDS≥ 6 (moderate and severe neuropathy) have been shown to be at higher risk of foot ulceration. A linear regression model was used to determine the association between RNFL and severity of neuropathy. Age, disease duration and diabetic retinopathy levels were fitted in the models. Independent t-test was employed for comparison between controls and the group without neuropathy, as well as for comparison between groups with higher and lower risk of foot ulceration. Analysis of variance was used to compare across all NDS groups. Results RNFL thickness was significantly associated with NDS in the inferior quadrant (b= -1.46, p=0.03). RNFL thicknesses globally and in superior, temporal and nasal quadrants did not show significant associations with NDS (all p>0.51). These findings were independent of the effect of age, disease duration and retinopathy. RNFL was thinner for the group with NDS ≥ 6 in all quadrants but was significant only inferiorly (p<0.005). RNFL for control participants was not significantly different from the group with diabetes and no neuropathy (superior p=0.07, global and all other quadrants: p>0.23). Mean RNFL thickness was not significantly different between the four NDS groups globally and in all quadrants (p=0.08 for inferior, P>0.14 for all other comparisons). Conclusions Retinal nerve fibre layer thinning is associated with neuropathy in people with type 2 diabetes. This relationship is strongest in the inferior retina and in individuals at higher risk of foot ulceration.

Australian baby boomers switched to more environment friendly modes of transport during the global financial crisis

The global financial crisis (GFC) in 2008 rocked local, regional, and state economies throughout the world. Several intermediate outcomes of the GFC have been well documented in the literature including loss of jobs and reduced income. Relatively little research has, however, examined the impacts of the GFC on individual level travel behaviour change. To address this shortcoming, HABITAT panel data were employed to estimate a multinomial logit model to examine mode switching behaviour between 2007 (pre-GFC) and 2009 (post-GFC) of a baby boomers cohort in Brisbane, Australia—a city within a developed country that has been on many metrics the least affected by the GFC. In addition, a Poisson regression model was estimated to model the number of trips made by individuals in 2007, 2008, and 2009. The South East Queensland Travel Survey datasets were used to develop this model. Four linear regression models were estimated to assess the effects of the GFC on time allocated to travel during a day: one for each of the three travel modes including public transport, active transport, less environmentally friendly transport; and an overall travel time model irrespective of mode. The results reveal that individuals were more likely to switch to public transport who lost their job or whose income reduced between 2007 and 2009. Individuals also made significantly fewer trips in 2008 and 2009 compared to 2007. Individuals spent significantly less time using less environmentally friendly transport but more time using public transport in 2009. Baby boomers switched to more environmentally friendly travel modes during the GFC.

Spatially-explicit modelling of grassland classes - an improved method of integrating a climate-based classification model with interpolated climate surfaces

Spatially-explicit modelling of grassland classes is important to site-specific planning for improving grassland and environmental management over large areas. In this study, a climate-based grassland classification model, the Comprehensive and Sequential Classification System (CSCS) was integrated with spatially interpolated climate data to classify grassland in Gansu province, China. The study area is characterized by complex topographic features imposed by plateaus, high mountains, basins and deserts. To improve the quality of the interpolated climate data and the quality of the spatial classification over this complex topography, three linear regression methods, namely an analytic method based on multiple regression and residues (AMMRR), a modification of the AMMRR method through adding the effect of slope and aspect to the interpolation analysis (M-AMMRR) and a method which replaces the IDW approach for residue interpolation in M-AMMRR with an ordinary kriging approach (I-AMMRR), for interpolating climate variables were evaluated. The interpolation outcomes from the best interpolation method were then used in the CSCS model to classify the grassland in the study area. Climate variables interpolated included the annual cumulative temperature and annual total precipitation. The results indicated that the AMMRR and M-AMMRR methods generated acceptable climate surfaces but the best model fit and cross validation result were achieved by the I-AMMRR method. Twenty-six grassland classes were classified for the study area. The four grassland vegetation classes that covered more than half of the total study area were "cool temperate-arid temperate zonal semi-desert", "cool temperate-humid forest steppe and deciduous broad-leaved forest", "temperate-extra-arid temperate zonal desert", and "frigid per-humid rain tundra and alpine meadow". The vegetation classification map generated in this study provides spatial information on the locations and extents of the different grassland classes. This information can be used to facilitate government agencies' decision-making in land-use planning and environmental management, and for vegetation and biodiversity conservation. The information can also be used to assist land managers in the estimation of safe carrying capacities which will help to prevent overgrazing and land degradation.

Damping structure selection in nonlinear ship manoeuvring models

This paper presents the application of a statistical method for model structure selection of lift-drag and viscous damping components in ship manoeuvring models. The damping model is posed as a family of linear stochastic models, which is postulated based on previous work in the literature. Then a nested test of hypothesis problem is considered. The testing reduces to a recursive comparison of two competing models, for which optimal tests in the Neyman sense exist. The method yields a preferred model structure and its initial parameter estimates. Alternatively, the method can give a reduced set of likely models. Using simulated data we study how the selection method performs when there is both uncorrelated and correlated noise in the measurements. The first case is related to instrumentation noise, whereas the second case is related to spurious wave-induced motion often present during sea trials. We then consider the model structure selection of a modern high-speed trimaran ferry from full scale trial data.

Parameter estimation of structural commodity price models

Commodity price modeling is normally approached in terms of structural time-series models, in which the different components (states) have a financial interpretation. The parameters of these models can be estimated using maximum likelihood. This approach results in a non-linear parameter estimation problem and thus a key issue is how to obtain reliable initial estimates. In this paper, we focus on the initial parameter estimation problem for the Schwartz-Smith two-factor model commonly used in asset valuation. We propose the use of a two-step method. The first step considers a univariate model based only on the spot price and uses a transfer function model to obtain initial estimates of the fundamental parameters. The second step uses the estimates obtained in the first step to initialize a re-parameterized state-space-innovations based estimator, which includes information related to future prices. The second step refines the estimates obtained in the first step and also gives estimates of the remaining parameters in the model. This paper is part tutorial in nature and gives an introduction to aspects of commodity price modeling and the associated parameter estimation problem.

Calculate excess mortality during heatwaves using Hilbert-Huang transform algorithm

Background Heatwaves could cause the population excess death numbers to be ranged from tens to thousands within a couple of weeks in a local area. An excess mortality due to a special event (e.g., a heatwave or an epidemic outbreak) is estimated by subtracting the mortality figure under ‘normal’ conditions from the historical daily mortality records. The calculation of the excess mortality is a scientific challenge because of the stochastic temporal pattern of the daily mortality data which is characterised by (a) the long-term changing mean levels (i.e., non-stationarity); (b) the non-linear temperature-mortality association. The Hilbert-Huang Transform (HHT) algorithm is a novel method originally developed for analysing the non-linear and non-stationary time series data in the field of signal processing, however, it has not been applied in public health research. This paper aimed to demonstrate the applicability and strength of the HHT algorithm in analysing health data. Methods Special R functions were developed to implement the HHT algorithm to decompose the daily mortality time series into trend and non-trend components in terms of the underlying physical mechanism. The excess mortality is calculated directly from the resulting non-trend component series. Results The Brisbane (Queensland, Australia) and the Chicago (United States) daily mortality time series data were utilized for calculating the excess mortality associated with heatwaves. The HHT algorithm estimated 62 excess deaths related to the February 2004 Brisbane heatwave. To calculate the excess mortality associated with the July 1995 Chicago heatwave, the HHT algorithm needed to handle the mode mixing issue. The HHT algorithm estimated 510 excess deaths for the 1995 Chicago heatwave event. To exemplify potential applications, the HHT decomposition results were used as the input data for a subsequent regression analysis, using the Brisbane data, to investigate the association between excess mortality and different risk factors. Conclusions The HHT algorithm is a novel and powerful analytical tool in time series data analysis. It has a real potential to have a wide range of applications in public health research because of its ability to decompose a nonlinear and non-stationary time series into trend and non-trend components consistently and efficiently.

A broad-scale analysis of links between coastal fisheries production and mangrove extent : a case-study for northeastern Australia

The paradigm that mangroves are critical for sustaining production in coastal fisheries is widely accepted, but empirical evidence has been tenuous. This study showed that links between mangrove extent and coastal fisheries production could be detected for some species at a broad regional scale (1000s of kilometres) on the east coast of Queensland, Australia. The relationships between catch-per-unit-effort for different commercially caught species in four fisheries (trawl, line, net and pot fisheries) and mangrove characteristics, estimated from Landsat images were examined using multiple regression analyses. The species were categorised into three groups based on information on their life history characteristics, namely mangrove-related species (banana prawns Penaeus merguiensis, mud crabs Scylla serrata and barramundi Lates calcarifer), estuarine species (tiger prawns Penaeus esculentus and Penaeus semisulcatus, blue swimmer crabs Portunus pelagicus and blue threadfin Eleutheronema tetradactylum) and offshore species (coral trout Plectropomus spp.). For the mangrove-related species, mangrove characteristics such as area and perimeter accounted for most of the variation in the model; for the non-mangrove estuarine species, latitude was the dominant parameter but some mangrove characteristics (e.g. mangrove perimeter) also made significant contributions to the models. In contrast, for the offshore species, latitude was the dominant variable, with no contribution from mangrove characteristics. This study also identified that finer scale spatial data for the fisheries, to enable catch information to be attributed to a particular catchment, would help to improve our understanding of relationships between mangroves and fisheries production.

Benthic metabolism as an indicator of stream ecosystem health

We tested direct and indirect measures of benthic metabolism as indicators of stream ecosystem health across a known agricultural land-use disturbance gradient in southeast Queensland, Australia. Gross primary production (GPP) and respiration (R24) in benthic chambers in cobble and sediment habitats, algal biomass (as chlorophyll a) from cobbles and sediment cores, algal biomass accrual on artificial substrates and stable carbon isotope ratios of aquatic plants and benthic sediments were measured at 53 stream sites, ranging from undisturbed subtropical rainforest to catchments where improved pasture and intensive cropping are major land-uses. Rates of benthic GPP and R24 varied by more than two orders of magnitude across the study gradient. Generalised linear regression modelling explained 80% or more of the variation in these two indicators when sediment and cobble substrate dominated sites were considered separately, and both catchment and reach scale descriptors of the disturbance gradient were important in explaining this variation. Model fits were poor for net daily benthic metabolism (NDM) and production to respiration ratio (P/R). Algal biomass accrual on artificial substrate and stable carbon isotope ratios of aquatic plants and benthic sediment were the best of the indirect indicators, with regression model R2 values of 50% or greater. Model fits were poor for algal biomass on natural substrates for cobble sites and all sites. None of these indirect measures of benthic metabolism was a good surrogate for measured GPP. Direct measures of benthic metabolism, GPP and R24, and several indirect measures were good indicators of stream ecosystem health and are recommended in assessing process-related responses to riparian and catchment land use change and the success of ecosystem rehabilitation actions.