Agronomic and Economic Performance Characteristics of Conventional and Low-External-Input Cropping Systems in the Central Corn Belt

We conducted a 9-ha field experiment near Boone, IA, to test the hypothesis that yield, weed suppression, and profit characteristics of low-external-input (LEI) cropping systems can match or exceed those of conventional systems. Over a 4-yr period, we compared a conventionally managed 2-yr rotation system {corn (Zea mays L.)/soybean [Glycine max (L.) Merr.]} with two LEI systems: a 3-yr corn/soybean/small grain + red clover (Trifolium pratense L.) rotation, and a 4-yr corn/soybean/small grain + alfalfa (Medicago sativa L.)/alfalfa rotation. Synthetic N fertilizer use was 59 and 74% lower in the 3- and 4-yr systems, respectively, than in the 2-yr system; similarly, herbicide use was reduced 76 and 82% in the 3- and 4-yr systems. Corn and soybean yields were as high or higher in the LEI systems as in the conventional system, and weed biomass in corn and soybean was low (≤4.2 g m−2) in all systems. Experimentally supplemented giant foxtail (Setaria faberi Herrm.) seed densities in the surface 20 cm of soil declined in all systems; supplemented velvetleaf (Abutilon theophrasti Medik.) seed densities declined in the 2- and 4-yr systems and remained unchanged in the 3-yr system. Without subsidy payments, net returns were highest for the 4-yr system ($540 ha−1 yr−1), lowest for the 3-yr system ($475 ha−1 yr−1), and intermediate for the 2-yr system ($504 ha−1 yr−1). With subsidies, differences among systems in net returns were smaller, as subsidies favored the 2-yr system, but rank order of the systems was maintained

Detecting Foci of Malaria Transmission with School Surveys: A Pilot Study in the Gambia.

BACKGROUND: In areas of declining malaria transmission such as in The Gambia, the identification of malaria infected individuals becomes increasingly harder. School surveys may be used to identify foci of malaria transmission in the community. METHODS: The survey was carried out in May-June 2011, before the beginning of the malaria transmission season. Thirty two schools in the Upper River Region of The Gambia were selected with probability proportional to size; in each school approximately 100 children were randomly chosen for inclusion in the study. Each child had a finger prick blood sample collected for the determination of antimalarial antibodies by ELISA, malaria infection by microscopy and PCR, and for haemoglobin measurement. In addition, a simple questionnaire on socio-demographic variables and the use of insecticide-treated bed nets was completed. The cut-off for positivity for antimalarial antibodies was obtained using finite mixture models. The clustered nature of the data was taken into account in the analyses. RESULTS: A total of 3,277 children were included in the survey. The mean age was 10 years (SD = 2.7) [range 4-21], with males and females evenly distributed. The prevalence of malaria infection as determined by PCR was 13.6% (426/3124) [95% CI = 12.2-16.3] with marked variation between schools (range 3-25%, p<0.001), while the seroprevalence was 7.8% (234/2994) [95%CI = 6.4-9.8] for MSP119, 11.6% (364/2997) [95%CI = 9.4-14.5] for MSP2, and 20.0% (593/2973) [95% CI = 16.5-23.2) for AMA1. The prevalence of all the three antimalarial antibodies positive was 2.7% (79/2920). CONCLUSIONS: This survey shows that malaria prevalence and seroprevalence before the transmission season were highly heterogeneous

The roles of nearest neighbor methods in imputing missing data in forest inventory and monitoring databases

Almost universally, forest inventory and monitoring databases are incomplete, ranging from missing data for only a few records and a few variables, common for small land areas, to missing data for many observations and many variables, common for large land areas. For a wide variety of applications, nearest neighbor (NN) imputation methods have been developed to fill in observations of variables that are missing on some records (Y-variables), using related variables that are available for all records (X-variables). This review attempts to summarize the advantages and weaknesses of NN imputation methods and to give an overview of the NN approaches that have most commonly been used. It also discusses some of the challenges of NN imputation methods. The inclusion of NN imputation methods into standard software packages and the use of consistent notation may improve further development of NN imputation methods. Using X-variables from different data sources provides promising results, but raises the issue of spatial and temporal registration errors. Quantitative measures of the contribution of individual X-variables to the accuracy of imputing the Y-variables are needed. In addition, further research is warranted to verify statistical properties, modify methods to improve statistical properties, and provide variance estimators

Factors associated with cognitive achievement in late childhood and adolescence: The Young Lives cohort study of children in Ethiopia, India, Peru, and Vietnam

Background: There is a well-established link between various measures of socioeconomic status and the schooling achievement and cognition of children. However, less is known about how cognitive development is impacted by childhood improvements in growth, a common indicator of child nutritional status. This study examines the relationship between socioeconomic status and child growth and changes in cognitive achievement scores in adolescents from resource-poor settings. Methods: Using an observational cohort of more than 3000 children from four low- and middle-income countries, this study examines the association between cognitive achievement scores and household economic, educational, and nutritional resources to give a more accurate assessment of the influence of families on cognitive development. A composite measure of cognition when children were approximately 8, 12, and 15 years of age was constructed. Household factors included maternal schooling, wealth, and children’s growth. Results: A positive and statistically significant relationship between household factors and child cognition was found for each country. If parents have more schooling, household wealth increases, or child growth improves, then children’s cognitive scores improve over time. Results for control variables are less consistent. Conclusion: Our findings suggest there is a consistent and strong association between parental schooling, wealth, and child growth with child cognitive achievement. Further, these findings demonstrate that a household’s ability to provide adequate nutrition is as important as economic and education resources even into late childhood and adolescence. Hence, efforts to improve household resources, both early in a child’s life and into adolescence, and to continue to promote child growth beyond the first few years of life have the potential to help children over the life course by improving cognition.This study is supported by the Bill and Melinda Gates Foundation (Global Health Grant OPP10327313), Eunice Shriver Kennedy National Institute of Child Health and Development (Grant R01 HD070993), and Grand Challenges Canada (Grant 0072-03 to the Grantee, The Trustees of the University of Pennsylvania). The data used in this study come from Young Lives, an international study of childhood poverty, following the lives of 12,000 children in four countries – Ethiopia, India, Peru and Vietnam – over 15 years (www.younglives.org.uk). Young Lives is core-funded by UK aid from the Department for International Development (DFID) and co-funded from 2010-2014 by the Netherlands Ministry of Foreign Affairs, and by Irish Aid from 2014 to 2015. Findings and conclusions in this article are those of the authors and do not necessarily reflect positions or policies of the Bill and Melinda Gates Foundation, the Eunice Kennedy Shriver National Institute of Child Health and Human Development, Grand Challenges Canada, Young Lives, DFID or other funders