The Effect of Agricultural Growing Season Change on Market Prices in Africa

Local agricultural production is a key element of food security in many agricultural countries in Africa. Climate change and variability is likely to adversely affect these countries, particularly as they affect the ability of smallholder farmers to raise enough food to feed themselves. Seasonality influences farmers' decisions about when to sow and harvest, and ultimately the success or failure of their crops. At a 2009 conference in the United Kingdom hosted by the Institute of Development Studies, Jennings and Magrath (2009) described farmer reports from East Asia, South Asia, Southern Africa, East Africa and Latin America. Farmers indicate significant changes in the timing of rainy seasons and the pattern of rains within seasons, including: More erratic rainfall, coming at unexpected times in and out of season; Extreme storms and unusually intense rainfall are punctuated by longer dry spells within the rainy season; Increasing uncertainty as to the start of rainy seasons in many areas; Short or transitional second rainy seasons are becoming stronger than normal or are disappearing altogether. These farmer perceptions of change are striking in that they are geographically widespread and are remarkably consistent across diverse regions (Jennings and Magrath, 2009). The impact of these changes on farmers with small plots and few resources is large. Farming is becoming riskier because of heat stress, lack of water, pests and diseases that interact with ongoing pressures on natural resources. Lack of predictability in the start and length of the growing season affects the ability of farmers to invest in appropriate fertilizer levels or improved, high yielding varieties. These changes occur at the same time as the demand for food is rising and is projected to continue to rise for the next fifty years (IAASTD, 2008). Long-term data records derived from satellite remote sensing can be used to verify these reports, providing necessary analysis and documentation required to plan effective adaptation strategies. Remote sensing data can also provide some understanding of the spatial extent of these changes and whether they are likely to continue. Given the agricultural nature of most economies on the African continent, agricultural production continues to be a critical determinant of both food security and economic growth (Funk and Brown, 2009). Crop phenological parameters, such as the start and end of the growing season, the total length of the growing season, and the rate of greening and senescence are important for planning crop management, crop diversification, and intensification. The World Food Summit of 1996 defined food security as: "when all people at all times have access to sufficient, safe, nutritious food to maintain a healthy and active life". Food security roughly depends on three factors: 1) availability of food; 2) access to food and 3) appropriate use of food, as well as adequate water and sanitation. The first factor is dependent on growing conditions and weather and climate. In a previous paper we have investigated this factor by evaluating the effect of large scale climate oscillation on land surface phenology (Brown et al., 2010). We found that all areas in Africa are significantly affected by at least one type of large scale climate oscillations and concluded that these somewhat predictable oscillations could perhaps be used to forecast agricultural production. In addition, we have evaluated changes in agricultural land surface phenology over time (Brown et al., 2012). We found that land surface phenology models, which link large-scale vegetation indices with accumulated humidity, could successfully predict agricultural productivity in several countries around the world. In this chapter we are interested in the effect of variability in peak timing of the growing season, or phenology, on the second factor of food security, food access. In this chapter we want to determine if there is a link between market prices and land surface phenology and to determine which markets are vulnerable to land surface phenology changes and variability and which market prices are not correlated

Dual Scale Trend Analysis Distinguishes Climatic from Anthropogenic Effects on the Vegetated Land Surface

We present a dual scale trend analysis for characterizing and comparing two contrasting areas of change in Russia and Kazakhstan that lie less than 800 km apart. We selected a global NASA MODIS (moderate resolution imaging spectroradiometer) product (MCD43C4 and MCD43A4) at a 0.05◦ (∼5.6 km) and 500 m spatial resolution and a 16-day temporal resolution from 2000 to 2008. We applied a refinement of the seasonal Kendall trend method to the normalized difference vegetation index (NDVI) image series at both scales. We only incorporated composites during the vegetative growing season which was delineated by start of season and end of season estimates based on analysis of normalized difference infrared index data. Trend patterns on two scales pointed to drought as the proximal cause of significant declines in NDVI in Kazakhstan. In contrast, the area of increasing NDVI trend in Russia was linked through the dual scale analysis with agricultural land cover change. The coarser scale analysis was relevant to atmospheric boundary layer processes, while the finer scale data revealed trends that were more relevant to human decision-making and regional economics

What proportion of initially prescribed antidepressants is still being prescribed chronically after 5 years in general practice? A longitudinal cohort analysis

Objectives Antidepressant prescribing almost doubled in the Netherlands between 1996 and 2012, which could be accounted for by longer continuation after the first prescription. This might be problematic given a growing concern of large-scale antidepressant dependence. We aimed to assess the extent and determinants of chronic antidepressant prescribing among patient aged 18 years and older. We hypothesise a relatively large prevalence of chronic (&gt;2 years) prescription.Design A longitudinal observational study based on routinely registered prescription data from general practice.Setting 189 general practices in the Netherlands.Participants 326 025 patients with valid prescription data for all 5 years of the study.Outcome measures Primary outcome measure: the number of patients (N) receiving at least four antidepressant prescriptions in 2011, as well as during each of the four subsequent years. Secondary outcome measure: the above, but specified for selective serotonin reuptake inhibitors and for tricyclic antidepressants.Results Antidepressants were prescribed to almost 7% of our 326 025 participants each year. They were prescribed for depression (38%), anxiety (17%), other psychological disorders (20%) and non-psychological indications (25%). Antidepressants were prescribed in all 5 years to the 42% of the population who had at least four prescriptions dispensed in 2011. Chronic prescribing was higher among women than men, for those aged 45-64 years than for those aged &gt; 65 years and for those treated for depression or anxiety than for non-psychological indications (eg, neuropathic pain). Chronic prescribing also varied markedly among general practices.Conclusion Chronic antidepressant use is common for depression and for anxiety and non-psychological diagnoses. Once antidepressants have been prescribed, general practitioners and other prescribers should be aware of the risks associated with long-term use and should provide annual monitoring of the continued need for therapy.</p

Land Surface Anomalies Preceding the 2010 Russian Heat Wave and a Link to the North Atlantic Oscillation

The Eurasian wheat belt (EWB) spans a region across Eastern Ukraine, Southern Russia, and Northern Kazakhstan; accounting for nearly 15% of global wheat production. We assessed land surface conditions across the EWB during the early growing season (April–May–June; AMJ) leading up to the 2010 Russian heat wave, and over a longer-term period from 2000 to 2010. A substantial reduction in early season values of the normalized difference vegetation index occurred prior to the Russian heat wave, continuing a decadal decline in early season primary production in the region. In 2010, an anomalously cold winter followed by an abrupt shift to a warmer-than-normal early growing season was consistent with a persistently negative phase of the North Atlantic oscillation (NAO). Regression analyses showed that early season vegetation productivity in the EWB is a function of both the winter (December–January–February; DJF) and AMJ phases of the NAO. Land surface anomalies preceding the heat wave were thus consistent with highly negative values of both the DJF NAO and AMJ NAO in 2010

Identifying priority sites for low impact development (LID) in a mixed-use watershed

AbstractLow impact development (LID), a comprehensive land use planning and design approach with the goal of mitigating land development impacts to the environment, is increasingly being touted as an effective approach to lessen runoff and pollutant loadings to streams. Broad-scale approaches for siting LID have been developed for agricultural watersheds, but are rare for urban watersheds, largely due to greater land use complexity. Here, we introduce a spatially-explicit approach to assist landscape architects, urban planners, and water managers in identifying priority sites for LID based exclusively on freely available data. We use a large, mixed-use watershed in central Oklahoma, the United States of America, as a case-study to demonstrate our approach. Our results indicate that for one sub-catchment of the Lake Thunderbird Watershed, LID placed in 11 priority locations can facilitate reductions in nutrient and sediment loading to receiving waters by as much as 16% and 17%, respectively. We had a high rate of correctly identified sites (94±5.7%). Our systematic and transferable approach for prioritizing LID sites has the potential to facilitate effective implementation of LID to lessen the effects of urban land use on stream ecosystems

Diffractive shear interferometry for extreme ultraviolet high-resolution lensless imaging

We demonstrate a novel imaging approach and associated reconstruction algorithm for far-field coherent diffractive imaging, based on the measurement of a pair of laterally sheared diffraction patterns. The differential phase profile retrieved from such a measurement leads to improved reconstruction accuracy, increased robustness against noise, and faster convergence compared to traditional coherent diffractive imaging methods. We measure laterally sheared diffraction patterns using Fourier-transform spectroscopy with two phase-locked pulse pairs from a high harmonic source. Using this approach, we demonstrate spectrally resolved imaging at extreme ultraviolet wavelengths between 28 and 35 nm

The bittersweet effects of COVID-19 on mental health:Results of an online survey among a sample of the Dutch population five weeks after relaxation of lockdown restriction

Previous research shows that crises can have both negative and positive mental health effects on the population. The current study explored these effects in the context of the COVID-19 pandemic after relaxation of governmental measures. An online survey was administered among a representative sample of the Dutch population (n = 1519) in June 2020, ten weeks after the peak of COVID-19 had passed, and five weeks after restrictions were relaxed. Participants were asked about mental health, adverse events during COVID-19, and about any positive effects of the pandemic. Most participants (80%, n = 1207) reported no change in mental health since the COVID-19 pandemic. This was also the case among respondents who had experienced an adverse event. Protective factors of mental health were being male and high levels of positive mental well-being. Risk factors were emotional loneliness and the experience of adverse life events. Social loneliness was positively associated with stable mental health, stressing the importance of meaningful relationships. Note that 58% of participants reported positive effects of the pandemic, the most common of which were rest, working from home, and feeling more socially connected. In summary, 10 weeks after the start of the crisis, and 5 weeks after relaxation of the restrictions, most people remained stable during the crisis, and were even able to report positive effects

Correlates of eating disorder pathology in Saudi Arabia: BMI and body dissatisfaction.

BACKGROUND\nMETHOD\nRESULTS\nDISCUSSION\nSaudi Arabia is undergoing rapid sociocultural changes, which may have led to an increase of body mass index and eating disorder pathology. The aim of this study is to investigate whether body dissatisfaction, self-esteem, having lived abroad, cultural orientation, perceived stress, media use, and socioeconomic status are correlates of eating disorder pathology with body mass index as a covariate. Additional aims are to investigate if cultural orientation is associated with symptomatology and if stress is a covariate in the association between eating disorder pathology and Western orientation.\nSelf-report measures were administered in a convenience Saudi community sample (N = 1225) between April 2017 and May 2018. Hierarchical multiple linear regression analyses with eating disorder pathology as dependent variable were performed to establish the associations among the variables.\nAfter adjusting for the effect of BMI, only body dissatisfaction and eating disorder pathology were moderately associated. Eating disorder pathology and body dissatisfaction were more severe among Saudi citizens with a higher BMI.\nSeveral explanations for the lack of associations of westernization, self-esteem, and stress with eating disorder pathology are reviewed and discussed. The majority of this convenience sample existed of young unmarried Saudi females of high socioeconomic status. Of the total sample, 35% displayed eating disorder pathology which may be a reflection of the high rates of excess weight.Stress and Psychopatholog