Risk Mitigation through Diversified Farm Production Strategies: The Case in Northern Mozambique

Mozambique, like many other parts of the low-income world, faces perennial challenges with food security. With a rapidly growing population and arable land on the decline, sustainable agriculture is vital to managing the already depleted natural resources of Sub-Saharan Africa more effectively while increasing food security. Food security issues for subsistence farmers in most low-income countries are a product of endogenous (crop yields) and exogenous (currency fluctuations as many agricultural inputs are imported) factors. In Mozambique the value of the local currency, meticals, has decreased by approximately 50% since January 2015 compared to the U.S. dollar. While this makes exporting products out of Mozambique more attractive in a relative sense, it negatively effects those industries which rely on imported inputs such as animal feed and inorganic fertilizer. In response to this exogenous currency crisis, research was conducted in Nampula, Mozambique during the summer of 2016 on a method for implementing crop diversification to reduce the risk that accompanies the devaluation of the metical. This research was undertaken on a poultry operation which is heavily dependent on imported maize and soya. Similar to the market structure of the poultry industry in the United States, all birds are grown by individual out growers who typically also have small plots of land to farm. Objectives for the project included 1) perform on-site crop production evaluations, 2) determine profitability for various row crops, and 3) simulate alternative production practices to increase crop profitability. Of the crops grown (tomatoes, maize, and cabbage), maize required the least labor, lowest initial investment, and the highest probability of breaking even. This research concluded that if poultry producers in Mozambique who rely on imported feed grew maize simultaneously it would reduce the dependency on imported maize and reduce income variability associated with exogenous currency fluctuations. Implementing a program such as this could increase revenue streams as well as reduce variability, thereby enhancing regional food securit

Risk Mitigation through Diversified Farm Production Strategies: The Case in Northern Mozambique

Mozambique, like many other parts of the low-income world, faces perennial challenges with food security. With a rapidly growing population and arable land on the decline, sustainable agriculture is vital to managing the already depleted natural resources of Sub-Saharan Africa more effectively while increasing food security. Food security issues for subsistence farmers in most low-income countries are a product of endogenous (crop yields) and exogenous (currency fluctuations as many agricultural inputs are imported) factors. In Mozambique the value of the local currency, meticals, has decreased by approximately 50% since January 2015 compared to the U.S. dollar. While this makes exporting products out of Mozambique more attractive in a relative sense, it negatively effects those industries which rely on imported inputs such as animal feed and inorganic fertilizer. In response to this exogenous currency crisis, research was conducted in Nampula, Mozambique during the summer of 2016 on a method for implementing crop diversification to reduce the risk that accompanies the devaluation of the metical. This research was undertaken on a poultry operation which is heavily dependent on imported maize and soya. Similar to the market structure of the poultry industry in the United States, all birds are grown by individual out growers who typically also have small plots of land to farm. Objectives for the project included 1) perform on-site crop production evaluations, 2) determine profitability for various row crops, and 3) simulate alternative production practices to increase crop profitability. Of the crops grown (tomatoes, maize, and cabbage), maize required the least labor, lowest initial investment, and the highest probability of breaking even. This research concluded that if poultry producers in Mozambique who rely on imported feed grew maize simultaneously it would reduce the dependency on imported maize and reduce income variability associated with exogenous currency fluctuations. Implementing a program such as this could increase revenue streams as well as reduce variability, thereby enhancing regional food securit

Reconstruction d'ensemble des événements spatio-temporels d'étiage extrême en France depuis 1871

International audienceThe length of streamflow observations is generally limited to the last 50 years even in data-rich countries like France. It therefore offers too small a sample of extreme low-flow events to properly explore the long-term evolution of their characteristics and associated impacts. To overcome this limit, this work first presents a daily 140-year ensemble reconstructed streamflow dataset for a reference network of near-natural catchments in France. This dataset, called SCOPE Hydro (Spatially COherent Probabilistic Extended Hydrological dataset), is based on (1) a probabilistic precipitation, temperature, and reference evapotranspiration downscaling of the Twentieth Century Reanalysis over France, called SCOPE Climate, and (2) continuous hydrological modelling using SCOPE Climate as forcings over the whole period. This work then introduces tools for defining spatio-temporal extreme low-flow events. Extreme low-flow events are first locally defined through the sequent peak algorithm using a novel combination of a fixed threshold and a daily variable threshold. A dedicated spatial matching procedure is then established to identify spatio-temporal events across France. This procedure is furthermore adapted to the SCOPE Hydro 25-member ensemble to characterize in a probabilistic way unrecorded historical events at the national scale. Extreme low-flow events are described and compared in a spatially and temporally homogeneous way over 140 years on a large set of catchments. Results highlight well-known recent events like 1976 or 1989-1990, but also older and relatively forgotten ones like the 1878 and 1893 events. These results contribute to improving our knowledge of historical events and provide a selection of benchmark events for climate change adaptation purposes. Moreover, this study allows for further detailed analyses of the effect of climate variability and anthropogenic climate change on low-flow hydrology at the scale of France

SCOPE Climate: a 142-year daily high-resolution ensemble meteorological reconstruction dataset over France

SCOPE Climate (Spatially COherent Probabilistic Extended Climate dataset) is a 25-member ensemble of 142-year daily high-resolution reconstructions of precipitation, temperature, and Penman–Monteith reference evapotranspiration over France, from 1 January 1871 to 29 December 2012. SCOPE Climate provides an ensemble of 25 spatially coherent gridded multivariate time series. It is derived from the statistical downscaling of the Twentieth Century Reanalysis (20CR) by the SCOPE method, which is based on the analogue approach. SCOPE Climate performs well in comparison to both dependent and independent data for precipitation and temperature. The ensemble aspect corresponds to the uncertainty related to the SCOPE method. SCOPE Climate is the first century-long gridded high-resolution homogeneous dataset available over France and thus has paved the way for improving knowledge on specific past meteorological events or for improving knowledge on climate variability, since the end of the 19th century. This dataset has also been designed as a forcing dataset for long-term hydrological applications and studies of the hydrological consequences of climate variability over France. SCOPE Climate is freely available for any non-commercial use and can be downloaded as NetCDF files from https://doi.org/10.5281/zenodo.1299760 for precipitation, https://doi.org/10.5281/zenodo.1299712 for temperature, and https://doi.org/10.5281/zenodo.1251843 for reference evapotranspiration.</p

Use of temperature to improve West Nile virus forecasts

Ecological and laboratory studies have demonstrated that temperature modulates West Nile virus (WNV) transmission dynamics and spillover infection to humans. Here we explore whether inclusion of temperature forcing in a model depicting WNV transmission improves WNV forecast accuracy relative to a baseline model depicting WNV transmission without temperature forcing. Both models are optimized using a data assimilation method and two observed data streams: mosquito infection rates and reported human WNV cases. Each coupled model-inference framework is then used to generate retrospective ensemble forecasts of WNV for 110 outbreak years from among 12 geographically diverse United States counties. The temperature-forced model improves forecast accuracy for much of the outbreak season. From the end of July until the beginning of October, a timespan during which 70% of human cases are reported, the temperature-forced model generated forecasts of the total number of human cases over the next 3 weeks, total number of human cases over the season, the week with the highest percentage of infectious mosquitoes, and the peak percentage of infectious mosquitoes that on average increased absolute forecast accuracy 5%, 10%, 12%, and 6%, respectively, over the non-temperature forced baseline model. These results indicate that use of temperature forcing improves WNV forecast accuracy and provide further evidence that temperature influences rates of WNV transmission. The findings provide a foundation for implementation of a statistically rigorous system for real-time forecast of seasonal WNV outbreaks and their use as a quantitative decision support tool for public health officials and mosquito control programs

Dry weather induces outbreaks of human West Nile virus infections

<p>Abstract</p> <p>Background</p> <p>Since its first occurrence in the New York City area during 1999, West Nile virus (WNV) has spread rapidly across North America and has become a major public health concern in North America. By 2002, WNV was reported in 40 states and the District of Columbia with 4,156 human and 14,539 equine cases of infection. Mississippi had the highest human incidence rate of WNV during the 2002 epidemic in the United States. Epidemics of WNV can impose enormous impacts on local economies. Therefore, it is advantageous to predict human WNV risks for cost-effective controls of the disease and optimal allocations of limited resources. Understanding relationships between precipitation and WNV transmission is crucial for predicting the risk of the human WNV disease outbreaks under predicted global climate change scenarios.</p> <p>Methods</p> <p>We analyzed data on the human WNV incidences in the 82 counties of Mississippi in 2002, using standard morbidity ratio (SMR) and Bayesian hierarchical models, to determine relationships between precipitation and human WNV risks. We also entertained spatial autocorrelations of human WNV risks with conditional autocorrelative (CAR) models, implemented in WinBUGS 1.4.3.</p> <p>Results</p> <p>We observed an inverse relationship between county-level human WNV incidence risk and total annual rainfall during the previous year. Parameters representing spatial heterogeneity in the risk of human exposure to WNV improved model fit. Annual precipitation of the previous year was a predictor of spatial variation of WNV risk.</p> <p>Conclusions</p> <p>Our results have broad implications for risk assessment of WNV and forecasting WNV outbreaks. Assessing risk of vector-born infectious diseases will require understanding of complex ecological relationships. Based on the climatologically characteristic drought occurrence in the past and on climate model predictions for climate change and potentially greater drought occurrence in the future, we suggest that the frequency and relative risk of WNV outbreaks could increase.</p

The European 2015 drought from a hydrological perspective

In 2015 large parts of Europe were affected by drought. In this paper, we analyze the hydrological footprint (dynamic development over space and time) of the drought of 2015 in terms of both severity (magnitude) and spatial extent and compare it to the extreme drought of 2003. Analyses are based on a range of low flow and hydrological drought indices derived for about 800 streamflow records across Europe, collected in a community effort based on a common protocol. We compare the hydrological footprints of both events with the meteorological footprints, in order to learn from similarities and differences of both perspectives and to draw conclusions for drought management. The region affected by hydrological drought in 2015 differed somewhat from the drought of 2003, with its center located more towards eastern Europe. In terms of low flow magnitude, a region surrounding the Czech Republic was the most affected, with summer low flows that exhibited return intervals of 100 years and more. In terms of deficit volumes, the geographical center of the event was in southern Germany, where the drought lasted a particularly long time. A detailed spatial and temporal assessment of the 2015 event showed that the particular behavior in these regions was partly a result of diverging wetness preconditions in the studied catchments. Extreme droughts emerged where preconditions were particularly dry. In regions with wet preconditions, low flow events developed later and tended to be less severe. For both the 2003 and 2015 events, the onset of the hydrological drought was well correlated with the lowest flow recorded during the event (low flow magnitude), pointing towards a potential for early warning of the severity of streamflow drought. Time series of monthly drought indices (both streamflow- and climate-based indices) showed that meteorological and hydrological events developed differently in space and time, both in terms of extent and severity (magnitude). These results emphasize that drought is a hazard which leaves different footprints on the various components of the water cycle at different spatial and temporal scales. The difference in the dynamic development of meteorological and hydrological drought also implies that impacts on various water-use sectors and river ecology cannot be informed by climate indices alone. Thus, an assessment of drought impacts on water resources requires hydrological data in addition to drought indices based solely on climate data. The transboundary scale of the event also suggests that additional efforts need to be undertaken to make timely pan-European hydrological assessments more operational in the future

Development of a Kemp\u27s Ridley Sea Turtle Stock Assessment Model

We developed a Kemp’s ridley (Lepidochelys kempii) stock assessment model to evaluate the relative contributions of conservation efforts and other factors toward this critically endangered species’ recovery. The Kemp’s ridley demographic model developed by the Turtle Expert Working Group (TEWG) in 1998 and 2000 and updated for the binational recovery plan in 2011 was modified for use as our base model. The TEWG model uses indices of the annual reproductive population (number of nests) and hatchling recruitment to predict future annual numbers of nests on the basis of a series of assumptions regarding age and maturity, remigration interval, sex ratios, nests per female, juvenile mortality, and a putative ‘‘turtle excluder device effect’’ multiplier starting in 1990. This multiplier was necessary to fit the number of nests observed in 1990 and later. We added the effects of shrimping effort directly, modified by habitat weightings, as a proxy for all sources of anthropogenic mortality. Additional data included in our model were incremental growth of Kemp’s ridleys marked and recaptured in the Gulf of Mexico, and the length frequency of stranded Kemp’s ridleys. We also added a 2010 mortality factor that was necessary to fit the number of nests for 2010 and later (2011 and 2012). Last, we used an empirical basis for estimating natural mortality, on the basis of a Lorenzen mortality curve and growth estimates. Although our model generated reasonable estimates of annual total turtle deaths attributable to shrimp trawling, as well as additional deaths due to undetermined anthropogenic causes in 2010, we were unable to provide a clear explanation for the observed increase in the number of stranded Kemp’s ridleys in recent years, and subsequent disruption of the species’ exponential growth since the 2009 nesting season. Our consensus is that expanded data collection at the nesting beaches is needed and of high priority, and that 2015 be targeted for the next stock assessment to evaluate the 2010 event using more recent nesting and in-water data

An Integrated Approach to the Design of Fault Tolerant Computing Systems

This paper offers an introduction to a research effort in fault tolerant computer architecture which has been organized at the University of Southwestern Louisiana (USL). It is intended as an overview of several topics which have been isolated for study, and as an indication of preliminary undertakings with regards to one particular topic. This first area of concentration lnvolves the systematic design of fault tolerant computing systems via a multi-level approach. Efforts are being initiated also in the areas of diagnosis of microprogrammable processors via firmware, fault data management across levels of virtual machines, development of a methodology for realizing a firmware hardcore on a variety of hosts, and delineation of a minimal set of resources for the design of a practical host for a multi-level fault tolerant computing system. The research is being conducted under the auspices of Project Beta at USL