Detecting Fauna Habitat in Semi-Arid Grasslands Using Satellite Imagery

Managing grasslands for biodiversity conservation is a relatively recent phenomenon and there is uncertainty over the most effective strategy. Past research has found that intermediate levels of disturbance (e.g. burning or grazing) may be required to maintain the natural mosaic of small-scale patterning required for a diverse range of flora and fauna species. For sustainable grassland management, appropriate methods of spatial assessment and temporal monitoring are required, to facilitate understanding of how past and present climate, land management and landscape features influence vegetation structure. Due to the expense and time-consuming nature of conventional ground-based monitoring, satellite remote-sensing techniques offer a feasible approach

Integrating plant- and animal-based perspectives for more effective restoration of biodiversity

Ecological restoration of modified and degraded landscapes is an important challenge for the 21st century, with potential for major gains in the recovery of biodiversity. However, there is a general lack of agreement between plant- and animal-based approaches to restoration, both in theory and practice. Here, we review these approaches, identify limitations from failing to effectively integrate their different perspectives, and suggest ways to improve outcomes for biodiversity recovery in agricultural landscapes. We highlight the need to strengthen collaboration between plant and animal ecologists, to overcome disciplinary and cultural differences, and to achieve a more unified approach to restoration ecology. Explicit consideration of key ecosystem functions, the need to plan at multiple spatial and temporal scales, and the importance of plant–animal interactions can provide a bridge between plant- and animal-based methods. A systematic approach to restoration planning is critical to achieving effective biodiversity outcomes while meeting long-term social and economic needs

Risk of major cardiovascular events in patients with psoriasis receiving biologic therapies: a prospective cohort study

Background: The cardiovascular safety profile of biologic therapies used for psoriasis is unclear. Objectives: To compare the risk of major cardiovascular events (CVEs; acute coronary syndrome, unstable angina, myocardial infarction and stroke) in patients with chronic plaque psoriasis treated with adalimumab, etanercept or ustekinumab in a large prospective cohort. Methods: Prospective cohort study examining the comparative risk of major CVEs was conducted using the British Association of Dermatologists Biologics and Immunomodulators Register. The main analysis compared adults with chronic plaque psoriasis receiving ustekinumab with tumour necrosis‐α inhibitors (TNFi: etanercept and adalimumab), whilst the secondary analyses compared ustekinumab, etanercept or methotrexate against adalimumab. Hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated using overlap weights by propensity score to balance baseline covariates among comparison groups. Results: We included 5468 biologic‐naïve patients subsequently exposed (951 ustekinumab; 1313 etanercept; and 3204 adalimumab) in the main analysis. The secondary analyses also included 2189 patients receiving methotrexate. The median (p25–p75) follow‐up times for patients using ustekinumab, TNFi, adalimumab, etanercept and methotrexate were as follows: 2.01 (1.16–3.21), 1.93 (1.05–3.34), 1.94 (1.09–3.32), 1.92 (0.93–3.45) and 1.43 (0.84–2.53) years, respectively. Ustekinumab, TNFi, adalimumab, etanercept and methotrexate groups had 7, 29, 23, 6 and 9 patients experiencing major CVEs, respectively. No differences in the risk of major CVEs were observed between biologic therapies [adjusted HR for ustekinumab vs. TNFi: 0.96 (95% CI 0.41–2.22); ustekinumab vs. adalimumab: 0.81 (0.30–2.17); etanercept vs. adalimumab: 0.81 (0.28–2.30)] and methotrexate against adalimumab [1.05 (0.34–3.28)]. Conclusions: In this large prospective cohort study, we found no significant differences in the risk of major CVEs between three different biologic therapies and methotrexate. Additional studies, with longer term follow‐up, are needed to investigate the potential effects of biologic therapies on incidence of major CVEs

Development and validation of a multivariable risk prediction model for serious infection in patients with psoriasis receiving systemic therapy

BACKGROUND: Patients with psoriasis are often concerned about the risk of serious infection associated with systemic psoriasis treatments. OBJECTIVES: To develop and externally validate a prediction model for serious infection in patients with psoriasis within 1 year of starting systemic therapies. METHODS: The risk prediction model was developed using the British Association of Dermatologists Biologic Interventions Register (BADBIR), and the German Psoriasis Registry PsoBest was used as the validation dataset. Model discrimination and calibration were assessed internally and externally using the C-statistic, the calibration slope and the calibration in the large. RESULTS: Overall 175 (1·7%) out of 10 033 participants from BADBIR and 41 (1·7%) out of 2423 participants from PsoBest developed a serious infection within 1 year of therapy initiation. Selected predictors in a multiple logistic regression model included nine baseline covariates, and starting infliximab was the strongest predictor. Evaluation of model performance showed a bootstrap optimism-corrected C-statistic of 0·64 [95% confidence interval (CI) 0·60-0·69], calibration in the large of 0·02 (95% CI -0·14 to 0·17) and a calibration slope of 0·88 (95% CI 0·70-1·07), while external validation performance was poor, with C-statistic 0·52 (95% CI 0·42-0·62), calibration in the large 0·06 (95% CI -0·25 to 0·37) and calibration slope 0·36 (95% CI -0·24 to 0·97). CONCLUSIONS: We present the first results of the development of a multivariable prediction model. This model may help patients and dermatologists in the U.K. and the Republic of Ireland to identify modifiable risk factors and inform therapy choice in a shared decision-making process

Crop Updates 2005 - Farming Systems

This session covers forty four papers from different authors: PLENARY 1. 2005 Outlook, David Stephens and Nicola Telcik, Department of Agriculture FERTILITY AND NUTRITION 2. The effect of higher nitrogen fertiliser prices on rotation and fertiliser strategies in cropping systems, Ross Kingwell, Department of Agriculture and University of Western Australia 3. Stubble management: The short and long term implications for crop nutrition and soil fertility, Wayne Pluske, Nutrient Management Systems and Bill Bowden, Department of Agriculture 4. Stubble management: The pros and cons of different methods, Bill Bowden, Department of Agriculture, Western Australia and Mike Collins, WANTFA 5. Effect of stubble burning and seasonality on microbial processes and nutrient recycling, Frances Hoyle, The University of Western Australia 6. Soil biology and crop production in Western Australian farming systems, D.V. Murphy, N. Milton, M. Osman, F.C. Hoyle, L.K Abbott, W.R. Cookson and S. Darmawanto, The University of Western Australia 7. Urea is as effective as CAN when no rain for 10 days, Bill Crabtree, Crabtree Agricultural Consulting 8. Fertiliser (N,P,S,K) and lime requirements for wheat production in the Merredin district, Geoff Anderson, Department of Agriculture and Darren Kidson, Summit Fertilizers 9. Trace element applications: Up-front verses foliar? Bill Bowden and Ross Brennan, Department of Agriculture 10. Fertcare®, Environmental Product Stewardship and Advisor Standards for thee Fertiliser Industry, Nick Drew, Fertilizer Industry Federation of Australia (FIFA) SOIL AND LAND MANAGEMENT 11. Species response to row spacing, density and nutrition, Bill Bowden, Craig Scanlan, Lisa Sherriff, Bob French and Reg Lunt, Department of Agriculture 12. Investigation into the influence of row orientation in lupin crops, Jeff Russell, Department of Agriculture and Angie Roe, Farm Focus Consultants 13. Deriving variable rate management zones for crops, Ian Maling, Silverfox Solutions and Matthew Adams, DLI 14. In a world of Precision Agriculture, weigh trailers are not passé, Jeff Russell, Department of Agriculture 15. Cover crop management to combat ryegrass resistance and improve yields, Jeff Russell, Department of Agriculture and Angie Roe, Farm Focus Consultants 16. ARGT home page, the place to find information on annual ryegrass toxicity on the web, Dr George Yan, BART Pty Ltd 17. Shallow leading tine (SLT) ripper significantly reduces draft force, improves soil tilth and allows even distribution of subsoil ameliorants, Mohammad Hamza, Glen Riethmuller and Wal Anderson, Department of Agriculture PASTURE ANS SUMMER CROP SYSTEMS 18. New annual pasture legumes for Mediteranean farming systems, Angelo Loi, Phil Nichols, Clinton Revell and David Ferris, Department of Agriculture 19. How sustainable are phase rotations with Lucerne? Phil Ward, CSIRO Plant Industry 20. Management practicalities of summer cropping, Andrea Hills and Sally-Anne Penny, Department of Agriculture 21. Rainfall zone determines the effect of summer crops on winter yields, Andrea Hills, Sally-Anne Penny and David Hall, Department of Agriculture 22. Summer crops and water use, Andrea Hills, Sally-Anne Penny and David Hall, Department of Agriculture, and Michael Robertson and Don Gaydon, CSIRO Brisbane 23. Risk analysis of sorgum cropping, Andrea Hills and Sally-Anne Penny, Department of Agriculture, and Dr Michael Robertson and Don Gaydon, CSIRO Brisbane FARMER DECISION SUPPORT AND ADOPTION 24. Variety release and End Point Royalties – a new system? Tress Walmsley, Department of Agriculture 25. Farming system analaysis using the STEP Tool, Caroline Peek and Megan Abrahams, Department of Agriculture 26. The Leakage Calculator: A simple tool for groundwater recharge assessment, Paul Raper, Department of Agriculture 27. The cost of Salinity Calculator – your tool to assessing the profitability of salinity management options, Richard O’Donnell and Trevor Lacey, Department of Agriculture 28. Climate decision support tools, Meredith Fairbanks and David Tennant, Department of Agriculture 29. Horses for courses – using the best tools to manage climate risk, Cameron Weeks, Mingenew-Irwin Group/Planfarm and Richard Quinlan, Planfarm Agronomy 30. Use of seasonal outlook for making N decisions in Merredin, Meredith Fairbanks and Alexandra Edward, Department of Agriculture 31. Forecasts and profits, Benefits or bulldust? Chris Carter and Doug Hamilton, Department of Agriculture 32. A tool to estimate fixed and variable header and tractor depreciation costs, Peter Tozer, Department of Agriculture 33. Partners in grain: ‘Putting new faces in new places’, Renaye Horne, Department of Agriculture 34. Results from the Grower group Alliance, Tracey Gianatti, Grower Group Alliance 35. Local Farmer Group Network – farming systems research opportunities through local groups, Paul Carmody, Local Farmer Group Network GREENHOUSE GAS AND CLIMATE CHANGE 36. Changing rainfall patterns in the grainbelt, Ian Foster, Department of Agriculture 37. Vulnerability of broadscale agriculture to the impacts of climate change, Michele John, CSIRO (formerly Department of Agriculture) and Ross George, Department of Agriculture 38. Impacts of climate change on wheat yield at Merredin, Imma Farré and Ian Foster, Department of Agriculture 39. Climate change, land use suitability and water security, Ian Kininmonth, Dennis van Gool and Neil Coles, Department of Agriculture 40. Nitrous oxide emissions from cropping systems, Bill Porter, Department of Agriculture, Louise Barton, University of Western Australia 41. The potential of greenhouse sinks to underwrite improved land management in Western Australia, Richard Harper and Peter Ritson, CRC for Greenhouse Accounting and Forest Products Commission, Tony Beck, Tony Beck Consulting Services, Chris Mitchell and Michael Hill, CRC for Greenhouse Accounting 42. Removing uncertainty from greenhouse emissions, Fiona Barker-Reid, Will Gates, Ken Wilson and Rob Baigent, Department of Primary Industries - Victoria and CRC for Greenhouse Accounting (CRCGA), and Ian Galbally, Mick Meyer and Ian Weeks, CSIRO Atmospheric Research and CRCGA 43. Greenhouse in Agriculture Program (GIA), Traci Griffin, CRC for Greenhouse Accounting 44. Grains Greenhouse Accounting framework, D. Rodriguez, M. Probust, M. Meyers, D. Chen, A. Bennett, W. Strong, R. Nussey, I. Galbally and M. Howden CONTACT DETAILS FOR PRINCIPAL AUTHOR

Impact of early disease factors on metabolic syndrome in systemic lupus erythematosus: data from an international inception cohort.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked Files. This article is open access.The metabolic syndrome (MetS) may contribute to the increased cardiovascular risk in systemic lupus erythematosus (SLE). We examined the association between MetS and disease activity, disease phenotype and corticosteroid exposure over time in patients with SLE.Recently diagnosed (1, higher disease activity, increasing age and Hispanic or Black African race/ethnicity were independently associated with MetS over the first 2 years of follow-up in the cohort.MetS is a persistent phenotype in a significant proportion of patients with SLE. Renal lupus, active inflammatory disease and damage are SLE-related factors that drive MetS development while antimalarial agents appear to be protective from early in the disease course.Canadian Institutes of Health Research 93695 86526 Arthritis Research UK (Arthritis Research UK Epidemiology Unit Core Support Programme Grant) National Institute for Health Research (NIHR) Biomedical Research Unit Funding Scheme NIHR Manchester Biomedical Research Centre Arthritis Research UK Manchester Academic Health Science Centre NIHR Biomedical Research Unit Funding Scheme NIHR Manchester Wellcome Trust Clinical Research Facility Arthritis Research Clinical Research Fellowship 18845 Ministry for Health and Welfare, Republic of Korea A120404 Lupus UK NIHR/Wellcome Trust Clinical Research Facility at University Hospital Birmingham NHS Foundation Trust and City Hospital Sandwell and West Birmingham Hospitals NHS Trust, UK NIH UL1 RR025741 P60AR 30692 K24 AR 002138 RR00046 Hopkins Lupus Cohort NIH RD-1 43727 Department of Education, Universities and Research, Basque Government Singer Family Fund for Lupus Research tier 1 Canada Research Chair on Systemic Autoimmune Rheumatic Diseases, Universite Lava