Towards stability of food production and farm income in a variable climate

Stable food production is vital for food security. Stability of farm income is also necessary to ensure the sustainability of food production and to protect livelihoods, in a changing climate. We analyse the relative effects of climate variability, subsidies and farming practices on the stability of food production and farm income. We examine farms in England and Wales between 2005 and 2017, and link farms to climate data at a sub-regional scale. Our results show that variability in temperature and rainfall reduces the stability of farm income and food production. While variability in climate can be largely outside of the farmers control our findings indicate that, under current conditions, farm management can have a larger effect on stability than climate. We identified three key aspects of farm management and policy that improve stability: i) increasing agricultural diversity, ii) increasing the efficiency of agrochemical use and iii) agri-environmental management. These management practices have previously been associated with benefits to natural ecosystems and may therefore increase the stability of agriculture whilst reducing negative impacts of farming on the environment. We also found differences in effect size of climate impacts and adaptation options between farm types, emphasising the need for flexible agricultural policies

Prioritising surveillance for alien organisms transported as stowaways on ships travelling to South Africa

The global shipping network facilitates the transportation and introduction of marine and terrestrial organisms to regions where they are not native, and some of these organisms become invasive. South Africa was used as a case study to evaluate the potential for shipping to contribute to the introduction and establishment of marine and terrestrial alien species (i.e. establishment debt) and to assess how this varies across shipping routes and seasons. As a proxy for the number of species introduced (i.e. 'colonisation pressure') shipping movement data were used to determine, for each season, the number of ships that visited South African ports from foreign ports and the number of days travelled between ports. Seasonal marine and terrestrial environmental similarity between South African and foreign ports was then used to estimate the likelihood that introduced species would establish. These data were used to determine the seasonal relative contribution of shipping routes to South Africa's marine and terrestrial establishment debt. Additionally, distribution data were used to identify marine and terrestrial species that are known to be invasive elsewhere and which might be introduced to each South African port through shipping routes that have a high relative contribution to establishment debt. Shipping routes from Asian ports, especially Singapore, have a particularly high relative contribution to South Africa's establishment debt, while among South African ports, Durban has the highest risk of being invaded. There was seasonal variation in the shipping routes that have a high relative contribution to the establishment debt of the South African ports. The presented method provides a simple way to prioritise surveillance effort and our results indicate that, for South Africa, port-specific prevention strategies should be developed, a large portion of the available resources should be allocated to Durban, and seasonal variations and their consequences for prevention strategies should be explored further. (Résumé d'auteur

Asymmetry, realised volatility and stock return risk estimates

In this paper we estimate minimum capital risk requirements for short and long positions with three investment horizons, using the traditional GARCH model and two other GARCH-type models that incorporate the possibility of asymmetric responses of volatility to price changes. We also address the problem of the extremely high estimated persistence of the GARCH model to generate observed volatility patterns by including realised volatility as an explanatory variable into the model’s variance equation. The results suggest that the inclusion of realised volatility improves the GARCH forecastability as well as its ability to calculate accurate minimum capital risk requirements and makes it quite competitive when compared with asymmetric conditional heteroscedastic models such as the GJR and the EGARCH.info:eu-repo/semantics/publishedVersio

Forecasting Daily Variability of the S and P 100 Stock Index using Historical, Realised and Implied Volatility Measurements

The increasing availability of financial market data at intraday frequencies has not only led to the development of improved volatility measurements but has also inspired research into their potential value as an information source for volatility forecasting. In this paper we explore the forecasting value of historical volatility (extracted from daily return series), of implied volatility (extracted from option pricing data) and of realised volatility (computed as the sum of squared high frequency returns within a day). First we consider unobserved components and long memory models for realised volatility which is regarded as an accurate estimator of volatility. The predictive abilities of realised volatility models are compared with those of stochastic volatility models and generalised autoregressive conditional heteroskedasticity models for daily return series. These historical volatility models are extended to include realised and implied volatility measures as explanatory variables for volatility. The main focus is on forecasting the daily variability of the Standard and Poor's 100 stock index series for which trading data (tick by tick) of almost seven years is analysed. The forecast assessment is based on the hypothesis of whether a forecast model is outperformed by alternative models. In particular, we will use superior predictive ability tests to investigate the relative forecast performances of some models. Since volatilities are not observed, realised volatility is taken as a proxy for actual volatility and is used for computing the forecast error. A stationary bootstrap procedure is required for computing the test statistic and its $p$-value. The empirical results show convincingly that realised volatility models produce far more accurate volatility forecasts compared to models based on daily returns. Long memory models seem to provide the most accurate forecasts

Toxoplasma gondii seropositivity and risk factors in pregnant women followed up by the Family Health Strategy

INTRODUCTION : Toxoplasmosis is a zoonotic infection caused by Toxoplasma gondii. It is transmitted by the ingestion of contaminated water and foods, by soil contaminated with cat feces, especially while handling it, and congenitally via the placenta. The diagnosis of maternal infection is made by serological detection of either IgM or IgG antibodies. This study assessed the seropositivity in pregnant women followed up by the Family Health Strategy (FHS) in Lages, Santa Catarina, Brazil. METHODS: The study was performed in 19 FHS units and included 148 childbearing women. The outcomes evaluated were IgM and IgG seropositivity and behavioral variables. RESULTS: IgG yielded positive results in 16% of the pregnant women, whereas IgM was positive in only 1%. CONCLUSIONS: The 1% IgM positivity rate for T. gondii indicates congenital toxoplasmosis is not common in Lages

Susceptibility of Human Lymphoid Tissue Cultured ex vivo to Xenotropic Murine Leukemia Virus-Related Virus (XMRV) Infection

BACKGROUND: Xenotropic murine leukemia virus-related virus (XMRV) was generated after a recombination event between two endogenous murine leukemia viruses during the production of a prostate cancer cell line. Although the associations of the XMRV infection with human diseases appear unlikely, the XMRV is a retrovirus of undefined pathogenic potential, able to replicate in human cells in vitro. Since recent studies using animal models for infection have yielded conflicting results, we set out an ex vivo model for XMRV infection of human tonsillar tissue to determine whether XMRV produced by 22Rv1 cells is able to replicate in human lymphoid organs. Tonsil blocks were infected and infection kinetics and its pathogenic effects were monitored RESULTS: XMRV, though restricted by APOBEC, enters and integrates into the tissue cells. The infection did not result in changes of T or B-cells, immune activation, nor inflammatory chemokines. Infectious viruses could be recovered from supernatants of infected tonsils by reinfecting DERSE XMRV indicator cell line, although these supernatants could not establish a new infection in fresh tonsil culture, indicating that in our model, the viral replication is controlled by innate antiviral restriction factors. CONCLUSIONS: Overall, the replication-competent retrovirus XMRV, present in a high number of laboratories, is able to infect human lymphoid tissue and produce infectious viruses, even though they were unable to establish a new infection in fresh tonsillar tissue. Hereby, laboratories working with cell lines producing XMRV should have knowledge and understanding of the potential biological biohazardous risks of this virus