Modelling changes in vegetation productivity and carbon balance under future climate scenarios in southeastern Australia

Australia, characterized by extensive and heterogeneous terrestrial ecosystems, plays a critical role in the global carbon cycle and in efforts to mitigate climate change. Prior research has quantified vegetation productivity and carbon balance within the Australian context over preceding decades. Nonetheless, the responses of vegetation and carbon dynamics to the evolving phenomena of climate change and escalating concentrations of atmospheric carbon dioxide remain ambiguous within the Australian landscape. Here, we used LPJ-GUESS model to assess the impacts of climate change on Gross Primary Productivity (GPP) and Net Biome Productivity (NBP) of carbon for the state of New South Wales (NSW) in southeastern Australia. LPJ-GUESS simulations were driven by an ensemble of 27 global climate models under different emission scenarios. We investigated the change of GPP for different vegetation types and whether NSW ecosystems will be a net sink or source of carbon under climate change. We found that LPJ-GUESS successfully simulated GPP for the period 2003-2021, demonstrating a comparative performance with GPP derived from upscaled eddy covariance fluxes (R2 = 0.58, nRMSE = 14.2 %). The simulated NBP showed a larger interannual variation compared with flux data and other inversion products but could capture the timing of rainfall-driven carbon sink and source variations in 2015-2020. GPP would increase by 10.3-19.5 % under a medium emission scenario and 19.7-46.8 % under a high emission scenario. The mean probability of NSW acting as a carbon sink in the future showed a small decrease with a large uncertainty with >8 of the 27 climate models indicating an increased potential for carbon sink. These findings emphasize the significance of emission scenarios in shaping future carbon dynamics but also highlight considerable uncertainties stemming from different climate projections. Our study represents a baseline for understanding natural ecosystem dynamics and their key role in governing land carbon uptake and storage in Australia.

The use of predator tags to explain reversal movement patterns in Atlantic salmon smolts (Salmo salar L.)

Acoustic telemetry has seen a rapid increase in utility and sophistication in recent years and is now used extensively to assess the behavior and survival rates of many aquatic animals, including the Atlantic salmon. As part of the salmon's complex life cycle, salmon smolts are thought to make a unidirectional migration from fresh water to the sea, which is initiated by changes in their physiology. However, some tag movement patterns do not conform with this and can be difficult to explain, particularly if the tagged fish has been eaten by a predator. This study combines the use of predator tags with machine learning techniques to understand the fate of migrating salmon smolts and thereby improve estimates for migration success. Over 3 years between 2020 and 2022, 217 salmon smolts (including wild and hatchery-reared ranched fish) were acoustically tagged and released into an embayment on the west coast of Ireland. Some tagged smolts were observed to return from the estuary back into a saline lagoon through which they had already migrated. To distinguish between the movement of a salmon smolt and that of a predator, predator tags were deployed in migrating smolts in 2021 and 2022. The addition of a temperature sensor in 2022 enabled the determination of predator type causing the returning movement. A significant number of predator tags were triggered, and the patterns of movement associated with these triggered tags were then used with two types of machine learning algorithms (hierarchical cluster analysis and random forest) to identify and validate the behavior of smolts tagged without extra sensors. Both models produced the same outputs, grouping smolts tagged with predator tags with smolts tagged without the additional sensors but showing similar movements. A mammalian predator was identified as the cause of most reversal movement, and hatchery-reared ranched smolts were found to be more likely predated upon by this predator than wild smolts within the lake and the estuary. However, overall migration success estimates were similar for both wild and hatchery-reared ranched fish. This study highlights the value of predator tags as an essential tool in the overall validation of detection data.

Deficit Irrigation at Pre-Anthesis Can Balance Wheat Yield and Water Use Efficiency under Future Climate Change in North China Plain

Background. Deficit irrigation (DI) is a feasible strategy to enhance crop WUE and also has significant compensation effects on yield. Previous studies have found that DI has great potential to maintain crop production as full irrigation (FI) does. Therefore, adopting DI to improve crop production and safeguard groundwater resources is of great importance in water scarce regions, e.g., the North China Plain (NCP). Under the background of global warming, it is worth investigating whether DI continues to play such a key role under future climate scenarios. Methods. We studied the response of winter wheat yield and WUE to different DI levels at pre-anthesis under two Shared Socioeconomic Pathways (SSPs) scenarios (SSP245 and SSP585) using the Agricultural Production Systems Simulator (APSIM) model driven by 21 general circulation models (GCMs) from the Coupled Model Inter-Comparison Project phase 6 (CMIP6). Additionally, we explored the effects of different nitrogen (N) fertilizer application rates on DI. Results. We found that simulated wheat yield would increase by 3.5–45.0%, with WUE increasing by 8.8–46.4% across all treatments under future climate change. Moderate deficit irrigation (DI3, ≤0.4 PAWC at the sowing to flowering stage) under the N3 (150 kg N ha−1) condition was identified as the optimum irrigation schedule for the study site under future climate change. However, compensation effects of DI3 on yield and WUE became weak in the future, which was mainly due to increased growing season rainfall projected by GCMs. In addition, we found that N fertilizer application could mitigate the effect of DI3. Conclusions. We highlight that in water scarce regions of NCP, DI remains an effective strategy to maintain higher yield and enhance water use under future climate scenarios. Results strongly suggest that moderate deficit irrigation under a 150 kg N ha−1 condition could mitigate the contradiction between production and water consumption and ensure food safety in the NCP.

Extreme fire weather is the major driver of severe bushfires in southeast Australia

In Australia, the proportion of forest area that burns in a typical fire season is less than for other vegetation types. However, the 2019-2020 austral spring-summer was an exception, with over four times the previous maximum area burnt in southeast Australian temperate forests. Temperate forest fires have extensive socio-economic, human health, greenhouse gas emissions, and biodiversity impacts due to high fire intensities. A robust model that identifies driving factors of forest fires and relates impact thresholds to fire activity at regional scales would help land managers and fire-fighting agencies prepare for potentially hazardous fire in Australia. Here, we developed a machine-learning diagnostic model to quantify nonlinear relationships between monthly burnt area and biophysical factors in southeast Australian forests for 2001-2020 on a 0.25° grid based on several biophysical parameters, notably fire weather and vegetation productivity. Our model explained over 80% of the variation in the burnt area. We identified that burnt area dynamics in southeast Australian forest were primarily controlled by extreme fire weather, which mainly linked to fluctuations in the Southern Annular Mode (SAM) and Indian Ocean Dipole (IOD), with a relatively smaller contribution from the central Pacific El Niño Southern Oscillation (ENSO). Our fire diagnostic model and the non-linear relationships between burnt area and environmental covariates can provide useful guidance to decision-makers who manage preparations for an upcoming fire season, and model developers working on improved early warning systems for forest fires.

Future climate impacts on forest growth and implications for carbon sequestration through reforestation in southeast Australia

Reforestation is identified as one of the key nature-based solutions to deliver carbon dioxide removal, which will be required to achieve the net zero ambition of the Paris Agreement. However, the potential for sequestration through reforestation is uncertain because climate change is expected to affect the drivers of forest growth. This study used the process-based 3-PG model to investigate the effects of climate change on development of above-ground biomass (AGB), as an indicator of forest growth, in regenerating native forests in southeast Australia. We investigated how changing climate affects AGB, by combining historical data and future climate projections based on 25 global climate models (GCMs) for the Coupled Model Intercomparison Project Phase 6 (CMIP6) under two Shared Socioeconomic Pathways. We found that the ensemble means of 25 GCMs indicated an increase in temperature with large variations in projected rainfall. When these changes were applied in 3-PG, we found an increase in the simulated AGB by as much as 25% under a moderate emission scenario. This estimate rose to 51% under a high emission scenario by the end of the 21st century across nine selected sites in southeast Australia. However, when CO₂ response was excluded, we found a large decrease in AGB at the nine sites. Our modelling results showed that the modelled response to elevated atmospheric CO₂ (the CO₂ fertilization effect) was largely responsible for the simulated increase of AGB (%). We found that the estimates of future changes in the AGB were subject to uncertainties originating from climate projections, future emission scenarios, and the assumed response to CO₂ fertilization. Such modelling simulation improves understanding of possible climate change impacts on forest growth and the inherent uncertainties in estimating mitigation potential through reforestation, with implications for climate policy in Australia.

1505 EASiE: ENT and Airway Simulation in Emergencies

Aim

A literature review of undergraduate ENT teaching found that most final year medical students and junior doctors did not feel adequately prepared for clinical practice in ENT. Other surveys found junior doctors lack confidence in recognising or initiating management in patients with blocked tracheostomies. To improve this, we ran a simulation session designed to replicate airway emergencies that junior doctors should be able to manage. The aim was to improve confidence in and knowledge of basic management of airway emergencies, including tracheostomies.

Method

Groups of 4-6 final year medical students participated in 3 scenarios: 2 tracheostomy-related and 1 partially compromised airway. The students had attended a session introducing tracheostomies and the algorithms produced by the National Tracheostomy Safety Project for tracheostomy emergencies. A semi-structured debrief followed each scenario, highlighting key learning points. The students completed a pre- and post-session questionnaire, rating confidence in several domains related to the scenarios.

Results

Of 24 participants, the percentage of students who felt confident or very confident in the following domains were compared pre- and post-simulation respectively: recognising a potential airway problem (0% vs 71%); identifying an altered airway (0% vs 75%); managing a potentially compromised surgical airway (4% vs 71%); initially managing a compromised airway (8% vs 67%); and identifying when to escalate with a potential airway problem (25% vs 96%).

Conclusions

Simulation is a valuable tool that can be used to improve both knowledge and confidence in managing potential airway problems in final year medical students. This supports findings from other studies.

1617 SOCS: Surgical On-Call Simulation

Introduction

Simulation is a well-known method of effectively teaching Medical students. The majority of the simulation scenarios are related to Medicine. Surgical simulation is a gap within the curriculum, especially Surgical on-call simulations. To improve this, we ran simulation sessions designed to replicate a General Surgery themed on-call shift that junior doctors should be able to manage. We aimed to improve confidence in clinical prioritisation and confidence in being an on-call Junior doctor, managing the most common on-call surgical tasks.

Method

Groups of 3-4 final year Medical students participated in a 2 hour-long simulated “on-call” shift, throughout the hospital. There were 8 scenarios, which ranged from prescribing to acute clinical scenarios. Students were given bleeps and were called at set times. They had to receive/give handovers and prioritise tasks according to clinical importance. A debrief following the session focussed on prioritisation and highlighted key learning points. The students completed a pre- and post-session questionnaire as assessment.

Results

The percentage of students who felt confident or very confident in the following domains were compared pre- and post-simulation respectively: confidence in clinical prioritisation (17% vs 86%); confidence in prescribing medication (0% vs 14%); confidence in escalation to seniors (33% vs 71%). 87.5% of the participants felt the session was an effective way to learn how to prioritise clinical tasks, and 100% felt this an effective way to learn about common General Surgical queries whilst on-call.

Conclusions

This project demonstrates how simulation is effective in improving confidence in prioritisation and knowledge within clinical practice, especially surgery.

1438 The Past, Present and Future Management of Complex Chyle Fistulae

Background

Chyle leak/fistula is a rare complication of oesophageal surgery, usually consequent on an unintended breach of the thoracic duct, its tributaries, or the cisterna chyli. For high volume persistent leaks further surgery has been the traditional approach, however two cases have resulted in a new management approach at this Centre.

Case Series

The first patient, a 49-year-old, developed high volume drain output post three stage oesophagectomy. His jejunostomy feeding was discontinued, total parenteral nutrition and a somatostatin analogue, were commenced. Despite these measures, the drain output remained >1.5litres per day and an exploratory thoracotomy was performed. The second patient, an 81-year-old underwent a transhiatal-oesophagectomy. On postoperative day 10 he developed acute onset shortness of breath, CXR demonstrated a large left sided pleural effusion. CT thorax demonstrated multiloculated complex pleural effusions. US guided pig tail drain was placed in the largest targetable effusion. The fluid was chylous in appearance. In both cases, an interventional radiological approach, not previously performed at this centre, provided definitive management. Lymphangiography was performed via injection of 1mL of Lipoidol® every 5 minutes into the inguinal lymph nodes to identify the cisterna chyli. A guidewire was advanced via the cisterna chyli with coils and glue used to embolize the leaking tracts.

Discussion

The lessons from this experience provide an algorithm for the management of chyle leaks, that will change practice at this centre. Embolization or disruption of thoracic duct and cisterna chyli leaks will be first line therapy for complex chyle leaks, with surgery reserved for where this fails.

Sources of uncertainty for wheat yield projections under future climate are site-specific

Understanding sources of uncertainty in climate-crop modelling is critical for informing adaptation strategies for cropping systems. An understanding of the major sources of uncertainty in yield change is needed to develop strategies to reduce the total uncertainty. Here, we simulated rain-fed wheat cropping at four representative locations in China and Australia using eight crop models, 32 global climate models (GCMs) and two climate downscaling methods, to investigate sources of uncertainty in yield response to climate change. We partitioned the total uncertainty into sources caused by GCMs, crop models, climate scenarios and the interactions between these three. Generally, the contributions to uncertainty were broadly similar in the two downscaling methods. The dominant source of uncertainty is GCMs in Australia, whereas in China it is crop models. This difference is largely due to uncertainty in GCM-projected future rainfall change across locations. Our findings highlight the site-specific sources of uncertainty, which should be one step towards understanding uncertainties for more robust climate-crop modelling.

Using large-scale climate drivers to forecast meteorological drought condition in growing season across the Australian wheatbelt

Recurring drought has caused large crop yield losses in Australia during past decades. Long-term drought forecasting is of great importance for the development of risk management strategies. Recently, large-scale climate drivers (e.g. El Niño-Southern Oscillation) have been demonstrated as useful in the application of drought forecasting. Machine learning-based models that use climate drivers as input are commonly adopted to provide drought forecasts as these models are easy to develop and require less information compared to physical-based models. However, few machine learning-based models have been developed to forecast drought conditions during growing season across all Australian cropping areas. In this study, we developed a growing season (Apr.-Nov.) meteorological drought forecasting model for each climate gauging location across the Australian wheatbelt based on multiple lagged (past) large-scale climate indices and the Random Forest (RF) algorithm. The Standardized Precipitation Index (SPI) was used as the response variable to measure the degree of meteorological drought. Results showed that the RF model could provide satisfactory drought forecasts in the eastern areas of the wheatbelt with Pearson's correlation coefficient r > 0.5 and normalized Root Mean Square Error (nRMSE) < 23%. Forecasted drought maps matched well with observed drought maps for three representative periods. We identified NINO3.4 sea surface temperature and Multivariate ENSO Index as the most influential indices dominating growing season drought conditions across the wheatbelt. In addition, lagged impacts of large-scale climate drivers on growing season drought conditions were long-lasting and the indices in previous year could also potentially affect drought conditions during current year. As large-scale climate indices are readily available and can be rapidly used to feed data driven models, we believe the proposed meteorological drought forecasting models can be easily extended to other regions to provide drought outlooks which can help mitigate adverse drought impacts.

Late planting has great potential to mitigate the effects of future climate change on Australian rain-fed cotton

The rain-fed cotton industry in Australia is vulnerable to climate change due to its high dependence on seasonal climate and summer rainfall. The rain-fed cotton in eastern Australia is increasingly being incorporated into cereal crop rotations due to government regulation of water resources, restricting opportunities for irrigated cotton. The accurate quantification of future climate impacts on exposed cropping systems such as rain-fed cotton is required to identify effective agronomic practices and inform strategic industry planning for the expansion of Australian cotton industry. Our study utilized 32 General Circulation Model (GCMs) for four cotton-growing regions representing the geographic range of cotton production in eastern Australia. We assessed the climate impacts on rain-fed cotton yield for two future periods (2040s and 2080s) under the RCP4.5 (low) and RCP8.5 (high) emissions scenarios employing the processed-based APSIM-Cotton model. Our results showed that current cotton yields varied with planting date, and the magnitude of yield change was consistent with regional climate variations at four locations representing the current geographic distribution of rain-fed cotton production. Means from multi-GCM ensemble showed growth period temperature increased more under RCP8.5 in the longer-term (2080s). Growth period rainfall changes had significantly positive effects on yield at all planting dates over each site. The projected increases in rainfall were more evident at later planting dates for dry sites than early planting dates at wet sites. In addition, we found planting date had the greatest influence on cotton yield at wet sites, while GCMs accounted for a large portion of variation in cotton yield at dry sites. We conclude that later planting has a great potential to increase rain-fed cotton yields. This provides important insights for regional-specific adaptation strategies for the rain-fed cotton industry in eastern Australia.

Carbon farming for resilient rangelands: people, paddocks and policy

Carbon farming is a new land use option over extensive areas of the Australian rangelands. This land use change has been promoted by government incentives to mitigate climate change, with most of Australia’s land sector abatement to date being delivered in rangelands. Aside from these mitigation benefits, carbon farming has also demonstrated potential co-benefits that enhance socio-ecological resilience by diversifying land uses and income streams, providing opportunities for sustainable land management to enhance soil and vegetation and creating opportunities for self-organisation and collaboration. However, factors such as policy uncertainty, perceived loss of future land use flexibility and the potential for carbon farming eligibility to create social divisions may negatively affect resilience. In this paper we weigh up these risks, opportunities and co-benefits and propose indicators for measuring the impact of carbon farming on the resilience of rangeland systems. A set of land policy principles for enhancing resilience through carbon farming are also identified.

Self-rated health of Middle Eastern immigrants in the US: a national study

OBJECTIVES

The aim of the study was to examine self-rated health (SRH) of Middle Eastern immigrants in the US compared with US-born non-Hispanic whites and to examine factors associated with fair/poor SRH among Middle Eastern immigrants in the US.

STUDY DESIGN

We used a cross-sectional design to analyze the National Health Interview Survey from 2001 to 2015.

METHODS

Secondary survey analysis procedures were conducted using the SAS program, with a total of 3,966 Middle Eastern and 731,285 US-born non-Hispanic whites. Descriptive statistics and regression analyses were used.

RESULTS

Middle Eastern immigrants had significantly higher rates of fair/poor SRH than US-born whites across the three survey waves. Reporting symptoms of serious psychological distress, older age (60+ years), current alcohol-drinking status, and having a family member with disability were the factors associated significantly with higher odds of reporting fair/poor SRH in Middle Eastern immigrants, whereas education was a protecting factor of fair/poor SRH.

CONCLUSIONS

This study indicates that Middle Eastern immigrants are one of the US immigrant populations that report poor health status, which reveals the need for health policy attention to reduce health disparities.

Future climate change likely to reduce the Australian plague locust (Chortoicetes terminifera) seasonal outbreaks

Climate is a major limiting factor for insect distributions and it is expected that a changing climate will likely alter spatial patterns of pest outbreaks. The Australian plague locust (APL) Chortoicetes terminifera, is the most economically important locust species in Australia. Invasions cause large scale economic damage to agricultural crops and pastures. Understanding the regional-scale and long-term dynamics is a prerequisite to develop effective control and preventive management strategies. In this study, we used a 32-year locust survey database to uncover the relationship between historical bioclimatic variables and spatial seasonal outbreaks by developing two machine learning species distribution models (SDMs), random forest and boosted regression trees. The explanatory variables were ranked by contribution to the generated models. The bio-climate models were then projected into a future climate change scenario (RCP8.5) using downscaled 34 global climate models (GCMs) to assess how climate change may alter APL seasonal distribution patterns in eastern Australia. Our results show that the model for the distribution of spring outbreaks performed better than those for summer and autumn, based on statistical evaluation criteria. The spatial models of seasonal outbreaks indicate that the areas subject to APL outbreaks were likely to decrease in all seasons. Multi-GCM ensemble means show the largest decrease in area was for spring outbreaks, reduced by 93-94% by 2071-2090, while the area of summer outbreaks decreased by 78-90%, and 67-74% for autumn outbreaks. The bioclimatic variables could explain 78-98% outbreak areas change. This study represents an important step toward the assessment of the effects of the changing climate on locust outbreaks and can help inform future priorities for regional mitigation efforts in the context of global climate change in eastern Australia.

Evaluating the potential financial contributions of carbon farming to grazing enterprises in Western NSW

This article reports on modelling of the farm-level financial implications of changing land use from rangelands grazing to ‘carbon farming’ (vegetation-based carbon sequestration) in north-western New South Wales, Australia. Four model farm businesses were created by combining information from existing carbon projects funded under the Australian Government’s Emissions Reduction Fund (ERF), data from surveys of farm businesses in the study regions and biomass estimations from the pasture growth model, GRASP. Scenarios for each of the businesses were: baseline (current grazing system); clearing vegetation to increase carrying capacity; establishing a carbon project; and establishing a carbon project and reinvesting some of the additional income in exclusion fencing to increase carrying capacity on non-project areas. The carbon project scenarios were based on either of two approved carbon sequestration methodologies within the ERF: avoided deforestation; and human-induced regeneration. In comparing the financial outcomes of these scenarios across the modelled businesses, we found potential advantages for landholders in having projects where livestock carrying capacity was at medium to low levels for the study region and where woody vegetation biomass potential was medium to high for the region. The case for sequestration projects on land with higher carrying capacity and therefore higher opportunity cost was much less compelling. In most cases, reinvestment in exclusion fencing resulted in similar financial returns to just having a carbon project but farm business income increased in later years.

High resolution mapping of soil organic carbon stocks using remote sensing variables in the semi-arid rangelands of eastern Australia

Efficient and effective modelling methods to assess soil organic carbon (SOC) stock are central in understanding the global carbon cycle and informing related land management decisions. However, mapping SOC stocks in semi-arid rangelands is challenging due to the lack of data and poor spatial coverage. The use of remote sensing data to provide an indirect measurement of SOC to inform digital soil mapping has the potential to provide more reliable and cost-effective estimates of SOC compared with field-based, direct measurement. Despite this potential, the role of remote sensing data in improving the knowledge of soil information in semi-arid rangelands has not been fully explored. This study firstly investigated the use of high spatial resolution satellite data (seasonal fractional cover data; SFC) together with elevation, lithology, climatic data and observed soil data to map the spatial distribution of SOC at two soil depths (0-5cm and 0-30cm) in semi-arid rangelands of eastern Australia. Overall, model performance statistics showed that random forest (RF) and boosted regression trees (BRT) models performed better than support vector machine (SVM). The models obtained moderate results with R² of 0.32 for SOC stock at 0-5cm and 0.44 at 0-30cm, RMSE of 3.51MgCha^-1 at 0-5cm and 9.16MgCha^-1 at 0-30cm without considering SFC covariates. In contrast, by including SFC, the model accuracy for predicting SOC stock improved by 7.4-12.7% at 0-5cm, and by 2.8-5.9% at 0-30cm, highlighting the importance of including SFC to enhance the performance of the three modelling techniques. Furthermore, our models produced a more accurate and higher resolution digital SOC stock map compared with other available mapping products for the region. The data and high-resolution maps from this study can be used for future soil carbon assessment and monitoring.

Alpha galactosidase A activity in Parkinson's disease

Glucocerebrosidase (GCase, deficient in Gaucher disease) enzymatic activity measured in dried blood spots of Parkinson's Disease (PD) cases is within healthy range but reduced compared to controls. It is not known whether activities of additional lysosomal enzymes are reduced in dried blood spots in PD. To test whether reduction in lysosomal enzymatic activity in PD is specific to GCase, we measured GCase, acid sphingomyelinase (deficient in Niemann-Pick disease types A and B), alpha galactosidase A (deficient in Fabry), acid alpha-glucosidase (deficient in Pompe) and galactosylceramidase (deficient in Krabbe) enzymatic activities in dried blood spots of PD patients (n = 648) and controls (n = 317) recruited from Columbia University. Full sequencing of glucocerebrosidase (GBA) and the LRRK2 G2019S mutation was performed. Enzymatic activities were compared between PD cases and controls using t-test and regression models adjusted for age, gender, and GBA and LRRK2 G2019S mutation status. Alpha galactosidase A activity was lower in PD cases compared to controls both when only non-carriers were included (excluding all GBA and LRRK2 G2019S carriers and PD cases with age-at-onset below 40) [2.85 μmol/l/h versus 3.12 μmol/l/h, p = 0.018; after controlling for batch effect, p = 0.006 (468 PD cases and 296 controls)], and when including the entire cohort (2.89 μmol/l/h versus 3.10 μmol/l/h, p = 0.040; after controlling for batch effect, p = 0.011). Because the alpha galactosidase A gene is X-linked, we stratified the analyses by sex. Among women who were non-carriers of GBA and LRRK2 G2019S mutations (PD, n = 155; control, n = 194), alpha galactosidase A activity was lower in PD compared to controls (2.77 μmol/l/h versus 3.10 μmol/l/h, p = 0.044; after controlling for a batch effect, p = 0.001). The enzymatic activity of acid sphingomyelinase, acid alpha-glucosidase and galactosylceramidase was not significantly different between PD and controls. In non-carriers, most lysosomal enzyme activities were correlated, with the strongest association in GCase, acid alpha-glucosidase, and alpha galactosidase A (Pearson correlation coefficient between 0.382 and 0.532). In a regression model with all five enzymes among non-carriers (adjusted for sex and age), higher alpha galactosidase A activity was associated with lower odds of PD status (OR = 0.54; 95% CI:0.31-0.95; p = 0.032). When LRRK2 G2019S PD carriers (n = 37) were compared to non-carriers with PD, carriers had higher GCase, acid sphingomyelinase and alpha galactosidase A activity. We conclude that alpha galactosidase A may have a potential independent role in PD, in addition to GCase.

Estimating chronic disease rates in Canada: which population-wide denominator to use?

INTRODUCTION

Chronic disease rates are produced from the Public Health Agency of Canada's Canadian Chronic Disease Surveillance System (CCDSS) using administrative health data from provincial/territorial health ministries. Denominators for these rates are based on estimates of populations derived from health insurance files. However, these data may not be accessible to all researchers. Another source for population size estimates is the Statistics Canada census. The purpose of our study was to calculate the major differences between the CCDSS and Statistics Canada's population denominators and to identify the sources or reasons for the potential differences between these data sources.

METHODS

We compared the 2009 denominators from the CCDSS and Statistics Canada. The CCDSS denominator was adjusted for the growth components (births, deaths, emigration and immigration) from Statistics Canada's census data.

RESULTS

The unadjusted CCDSS denominator was 34 429 804, 3.2% higher than Statistics Canada's estimate of population in 2009. After the CCDSS denominator was adjusted for the growth components, the difference between the two estimates was reduced to 431 323 people, a difference of 1.3%. The CCDSS overestimates the population relative to Statistics Canada overall. The largest difference between the two estimates was from the migrant growth component, while the smallest was from the emigrant component.

CONCLUSION

By using data descriptions by data source, researchers can make decisions about which population to use in their calculations of disease frequency.

Native seed for restoration: a discussion of key issues using examples from the flora of southern Australia

Land clearing across southern Australia since European settlement has fundamentally changed the amount and distribution of native vegetation; it has also substantially reduced genetic diversity in plant species throughout Australia, especially in agricultural regions. The most recent State of the Environment report indicates that Australian biodiversity continues to decline. Many approaches to restoration are used in Australia including re-establishing plant populations using tube stock or by direct seeding. Native seed for these projects is often assumed to be plentiful and available for the majority of species we wish to restore but these assumptions are rarely true. We also rely on a small number of species for the majority of restoration projects despite the vast number of species required to fully restore complex plant communities. The majority of seed for restoration is still primarily collected from native vegetation despite longstanding concerns regarding the sustainability of this practice and the globally recognised impacts of vegetation fragmentation on seed production and genetic diversity. Climate change is also expected to challenge seed production as temperatures rise and water availability becomes more limited; changes to current planting practices may also be required. Until now native seed collection has relied on market forces to build a strong and efficient industry sector, but in reality the Australian native seed market is primarily driven by Federal, State and Territory funding. In addition, unlike other seed-based agri-businesses native seed collection lacks national industry standards. A new approach is required to support development of the native seed collection and use sector into an innovative industry.

Stellar dynamics. The fastest unbound star in our Galaxy ejected by a thermonuclear supernova

Hypervelocity stars (HVSs) travel with velocities so high that they exceed the escape velocity of the Galaxy. Several acceleration mechanisms have been discussed. Only one HVS (US 708, HVS 2) is a compact helium star. Here we present a spectroscopic and kinematic analysis of US 708. Traveling with a velocity of ~1200 kilometers per second, it is the fastest unbound star in our Galaxy. In reconstructing its trajectory, the Galactic center becomes very unlikely as an origin, which is hardly consistent with the most favored ejection mechanism for the other HVSs. Furthermore, we detected that US 708 is a fast rotator. According to our binary evolution model, it was spun-up by tidal interaction in a close binary and is likely to be the ejected donor remnant of a thermonuclear supernova.

Increased Rate of Sporadic and Recurrent Rare Genic Copy Number Variants in Parkinson's Disease Among Ashkenazi Jews

To date, only one genome-wide study has assessed the contribution of copy number variants (CNVs) to Parkinson's disease (PD). We conducted a genome-wide scan for CNVs in a case–control dataset of Ashkenazi Jewish (AJ) origin (268 PD cases and 178 controls). Using high-confidence CNVs, we examined the global genome wide burden of large (≥100 kb) and rare (≤1% in the dataset) CNVs between cases and controls. A total of 986 such CNVs were observed in our dataset of 432 subjects. Overall global burden analyses did not reveal significant differences between cases and controls in CNV rate, distribution of deletions or duplications or number of genes affected by CNVs. Overall deletions (total CNV size and ≥2× frequency) were found 1.4 times more often in cases than in controls (P = 0.019). The large CNVs (≥500 kb) were also significantly associated with PD (P = 0.046, 1.24-fold higher in cases than in controls). Global burden was elevated for rare CNV regions. Specifically, for OVOS2 on Chr12p11.21, CNVs were observed only in PD cases (n = 7) but not in controls (P = 0.028) and this was experimentally validated. A total of 81 PD cases carried a rare genic CNV that was absent in controls. Ingenuity pathway analysis (IPA) identified ATXN3, FBXW7, CHCHD3, HSF1, KLC1, and MBD3 in the same disease pathway with known PD genes.

Pathology and temporal onset of visual hallucinations, misperceptions and family misidentification distinguishes dementia with Lewy bodies from Alzheimer's disease

OBJECTIVE

To determine whether the temporal onset of visual phenomena distinguishes Lewy body disease (LBD) from Alzheimer's disease (AD), and to characterize the extent Lewy bodies and neurofibrillary tangles are associated with these clinical features.

METHODS

Consecutive cases of autopsy-confirmed LBD (n = 41), AD (n = 70), and AD with amygdala-predominant Lewy bodies (AD-ALB) (n = 14) with a documented clinical history of dementia were included. We mailed questionnaires to next-of-kin asking about symptoms during life. Lewy pathology and neurofibrillary tangle pathology were assessed.

RESULTS

The occurrence of visual hallucinations, misperceptions and family misidentification did not distinguish LBD from AD or AD-ALB, but the onset was earlier in LBD compared to AD and AD-ALB. When visual hallucinations developed within the first 5 years of dementia, the odds were 4-5 times greater for autopsy-confirmed LBD (or intermediate/high likelihood dementia with Lewy bodies) and not AD or AD-ALB. In LBD, limbic but not cortical Lewy body pathology was related to an earlier onset of visual hallucinations, while limbic and cortical Lewy body pathology were associated with visual misperceptions and misidentification. Cortical neurofibrillary tangle burden was associated with an earlier onset of misidentification and misperceptions in LBD and AD, but only with earlier visual hallucinations in AD/AD-ALB.

CONCLUSION

When visual hallucinations occur within the first 5 years of the dementia, a diagnosis of LBD was more likely than AD. Visual hallucinations in LBD were associated with limbic Lewy body pathology. Visual misperceptions and misidentification delusions were related to cortical Lewy body and neurofibrillary tangle burden in LBD and AD/AD-ALB.

Cognitive performance of GBA mutation carriers with early-onset PD: the CORE-PD study

OBJECTIVE

To assess the cognitive phenotype of glucocerebrosidase (GBA) mutation carriers with early-onset Parkinson disease (PD).

METHODS

We administered a neuropsychological battery and the University of Pennsylvania Smell Identification Test (UPSIT) to participants in the CORE-PD study who were tested for mutations in PARKIN, LRRK2, and GBA. Participants included 33 GBA mutation carriers and 60 noncarriers of any genetic mutation. Primary analyses were performed on 26 GBA heterozygous mutation carriers without additional mutations and 39 age- and PD duration-matched noncarriers. Five cognitive domains, psychomotor speed, attention, memory, visuospatial function, and executive function, were created from transformed z scores of individual neuropsychological tests. Clinical diagnoses (normal, mild cognitive impairment [MCI], dementia) were assigned blind to genotype based on neuropsychological performance and functional impairment as assessed by the Clinical Dementia Rating (CDR) score. The association between GBA mutation status and neuropsychological performance, CDR, and clinical diagnoses was assessed.

RESULTS

Demographics, UPSIT, and Unified Parkinson's Disease Rating Scale-III performance did not differ between GBA carriers and noncarriers. GBA mutation carriers performed more poorly than noncarriers on the Mini-Mental State Examination (p = 0.035), and on the memory (p = 0.017) and visuospatial (p = 0.028) domains. The most prominent differences were observed in nonverbal memory performance (p < 0.001). Carriers were more likely to receive scores of 0.5 or higher on the CDR (p < 0.001), and a clinical diagnosis of either MCI or dementia (p = 0.004).

CONCLUSION

GBA mutation status may be an independent risk factor for cognitive impairment in patients with PD.

The relation between depression and parkin genotype: the CORE-PD study

BACKGROUND

Mutations in parkin are a known genetic risk factor for early onset Parkinson's disease (EOPD) but their role in non-motor manifestations is not well established. Genetic factors for depression are similarly not well characterized. We investigate the role of parkin mutations in depression among those with EOPD and their relatives.

METHODS

We collected psychiatric information using the Patient Health Questionnaire and Beck Depression Inventory II on 328 genotyped individuals including 88 probands with early onset PD (41 with parkin mutations, 47 without) and 240 first and second-degree relatives without PD.

RESULTS

Genotype was not associated with depression risk among probands. Among unaffected relatives of EOPD cases, only compound heterozygotes (n = 4), and not heterozygotes, had significantly increased risk of depressed mood (OR = 14.1; 95% CI 1.2-163.4), moderate to severe depression (OR = 17.8; 95% CI 1.0-332.0), depression (score ≥ 15) on the Beck Depression Inventory II (BDI-II) (OR = 51.9; 95% CI 4.1-657.4), and BDI-II total depression score (β = 8.4; 95% CI 2.4-11.3) compared to those without parkin mutations.

CONCLUSIONS

Relatives of EOPD cases with compound heterozygous mutations and without diagnosed PD may have a higher risk of depression compared to relatives without parkin mutations. These findings support evidence of a genetic contribution to depression and may extend the phenotypic spectrum of parkin mutations to include non-motor manifestations that precede the development of PD.

Spatial inhibition and the visual cortex: a magnetic resonance spectroscopy imaging study

INTRODUCTION

Deficits in processing spatial information have been observed in clinical populations who have abnormalities within the dopamine (DA) system. As psychostimulants such as methamphetamine (MA) are particularly neurotoxic to the dopaminergic system it was of interest to examine the performance of MA-dependent individuals on a task of spatial attention.

METHOD

51 MA-dependent subjects and 22 age-matched non-substance abusing control subjects were tested on a Spatial Stroop attention test. MR Spectroscopy (MRS) imaging data were analyzed from 32 MA abusers and 13 controls.

RESULTS

No group differences in response time or accuracy emerged on the behavioral task with both groups exhibiting equivalent slowing when the word meaning and the spatial location of the word were in conflict. MRS imaging data from the MA abusers revealed a strong inverse correlation between NAA/Cr ratios in the Primary Visual Cortex (PVC) and spatial interference (p=0.0001). Moderate inverse correlations were also seen in the Anterior Cingulate Cortex (ACC) (p=0.02). No significant correlations were observed in the controls, perhaps due to the small sample of imaging data available (n=13).

DISCUSSION

The strong correlation between spatial conflict suppression and NAA/Cr levels within the PVC in the MA-dependent individuals suggests that preserved neuronal integrity within the PVC of stimulant abusers may modulate cognitive mechanisms that process implicit spatial information.

Olfaction in Parkin heterozygotes and compound heterozygotes: the CORE-PD study

BACKGROUND

While Parkinson disease (PD) is consistently associated with impaired olfaction, one study reported better olfaction among Parkin mutation carriers than noncarriers. Whether olfaction differs between Parkin mutation heterozygotes and carriers of 2 Parkin mutations (compound heterozygotes) is unknown.

OBJECTIVE

To assess the relationship between Parkin genotype and olfaction in PD probands and their unaffected relatives.

METHODS

We administered the University of Pennsylvania Smell Identification Test (UPSIT) to 44 probands in the Consortium on Risk for Early-Onset Parkinson Disease study with PD onset ≤50 years (10 Parkin mutation heterozygotes, 9 compound heterozygotes, 25 noncarriers) and 80 of their family members (18 heterozygotes, 2 compound heterozygotes, 60 noncarriers). In the probands, linear regression was used to assess the association between UPSIT score (outcome) and Parkin genotype (predictor), adjusting for covariates. Among family members without PD, we compared UPSIT performance in heterozygotes vs noncarriers using generalized estimating equations, adjusting for family membership, age, gender, and smoking.

RESULTS

Among probands with PD, compound heterozygotes had higher UPSIT scores (31.9) than heterozygotes (20.1) or noncarriers (19.9) (p < 0.001). These differences persisted after adjustment for age, gender, disease duration, and smoking. Among relatives without PD, UPSIT performance was similar in heterozygotes (32.5) vs noncarriers (32.4), and better than in heterozygotes with PD (p = 0.001).

CONCLUSION

Olfaction is significantly reduced among Parkin mutation heterozygotes with PD but not among their heterozygous relatives without PD. Compound heterozygotes with PD have olfaction within the normal range. Further research is required to assess whether these findings reflect different neuropathology in Parkin mutation heterozygotes and compound heterozygotes.