Crop models and their use in assessing crop production and food security: A review

Agriculture is directly related to food security as it determines the global food supply. Research in agriculture to predict crop productivity and losses helps avoid high food demand with little supply and price spikes. Here, we review ten crop models and one intercomparison project used for simulating crop growth and productivity under various impacts from soil–crop–atmosphere interactions. The review outlines food security and production assessments using numerical models for maize, wheat, and rice production. A summary of reviewed studies shows the following: (1) model ensembles provide smaller modeling errors compared to single models, (2) single models show better results when coupled with other types of models, (3) the ten reviewed crop models had improvements over the years and can accurately predict crop growth and yield for most of the locations, management conditions, and genotypes tested, (4) APSIM and DSSAT are fast and reliable in assessing broader output variables, (5) AquaCrop is indicated to investigate water footprint, quality and use efficiency in rainfed and irrigated systems, (6) all models assess nitrogen dynamics and use efficiency efficiently, excluding AquaCrop and WOFOST, (7) JULES specifies in evaluating food security vulnerability, (8) ORYZA is the main crop model used to evaluate paddy rice production, (9) grain filling is usually assessed with APSIM, DAISY, and DSSAT, and (10) the ten crop models can be used as tools to evaluate food production, availability, and security

The impact of the North Atlantic Oscillation on the uptake and accumulation of anthropogenic CO2 by North Atlantic Ocean mode waters

Author Posting. © American Geophysical Union, 2011. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Global Biogeochemical Cycles 25 (2011): GB3022, doi:10.1029/2010GB003892.The North Atlantic Ocean accounts for about 25% of the global oceanic anthropogenic carbon sink. This basin experiences significant interannual variability primarily driven by the North Atlantic Oscillation (NAO). A suite of biogeochemical model simulations is used to analyze the impact of interannual variability on the uptake and storage of contemporary and anthropogenic carbon (Canthro) in the North Atlantic Ocean. Greater winter mixing during positive NAO years results in increased mode water formation and subsequent increases in subtropical and subpolar Canthro inventories. Our analysis suggests that changes in mode water Canthro inventories are primarily due to changes in water mass volumes driven by variations in water mass transformation rates rather than local air-sea CO2 exchange. This suggests that a significant portion of anthropogenic carbon found in the ocean interior may be derived from surface waters advected into water formation regions rather than from local gas exchange. Therefore, changes in climate modes, such as the NAO, may alter the residence time of anthropogenic carbon in the ocean by altering the rate of water mass transformation. In addition, interannual variability in Canthro storage increases the difficulty of Canthro detection and attribution through hydrographic observations, which are limited by sparse sampling of subsurface waters in time and space.We would like to acknowledge funding from the NOAA Climate Program under the Office of Climate Observations and Global Carbon Cycle Program (NOAA‐NA07OAR4310098), NSF (OCE‐0623034), NCAR, the WHOI Ocean Climate Institute, a National Defense Science and Engineering Graduate Fellowship and an Environmental Protection Agency STAR graduate fellowship. NCAR is sponsored by the National Science Foundation

Using the Theoretical Domains Framework (TDF) to understand adherence to multiple evidence-based indicators in primary care : a qualitative study

BACKGROUND: There are recognised gaps between evidence and practice in general practice, a setting posing particular implementation challenges. We earlier screened clinical guideline recommendations to derive a set of 'high-impact' indicators based upon criteria including potential for significant patient benefit, scope for improved practice and amenability to measurement using routinely collected data. Here, we explore health professionals' perceived determinants of adherence to these indicators, examining the degree to which determinants were indicator-specific or potentially generalisable across indicators. METHODS: We interviewed 60 general practitioners, practice nurses and practice managers in West Yorkshire, the UK, about adherence to four indicators: avoidance of risky prescribing; treatment targets in type 2 diabetes; blood pressure targets in treated hypertension; and anticoagulation in atrial fibrillation. Interview questions drew upon the Theoretical Domains Framework (TDF). Data were analysed using framework analysis. RESULTS: Professional role and identity and environmental context and resources featured prominently across all indicators whilst the importance of other domains, for example, beliefs about consequences, social influences and knowledge varied across indicators. We identified five meta-themes representing more general organisational and contextual factors common to all indicators. CONCLUSIONS: The TDF helped elicit a wide range of reported determinants of adherence to 'high-impact' indicators in primary care. It was more difficult to pinpoint which determinants, if targeted by an implementation strategy, would maximise change. The meta-themes broadly underline the need to align the design of interventions targeting general practices with higher level supports and broader contextual considerations. However, our findings suggest that it is feasible to develop interventions to promote the uptake of different evidence-based indicators which share common features whilst also including content-specific adaptations

Estimating the monthly pCO2 distribution in the north Atlantic using a self-organizing neural network

Here we present monthly, basin-wide maps of the partial pressure of carbon dioxide (pCO2) for the North Atlantic on a 1° latitude by 1° longitude grid for years 2004 through 2006 inclusive. The maps have been computed using a neural network technique which reconstructs the non-linear relationships between three biogeochemical parameters and marine pCO 2. A self organizing map (SOM) neural network has been trained using 389 000 triplets of the SeaWiFS-MODIS chlorophyll-a concentration, the NCEP/NCAR reanalysis sea surface temperature, and the FOAM mixed layer depth. The trained SOM was labelled with 137 000 underway pCO2 measurements collected in situ during 2004, 2005 and 2006 in the North Atlantic, spanning the range of 208 to 437 µatm. The root mean square error (RMSE) of the neural network fit to the data is 11.6 µatm, which equals to just above 3 per cent of an average pCO2 value in the in situ dataset. The seasonal pCO2 cycle as well as estimates of the interannual variability in the major biogeochemical provinces are presented and discussed. High resolution combined with basin-wide coverage makes the maps a useful tool for several applications such as the monitoring of basin-wide air-sea CO2 fluxes or improvement of seasonal and interannual marine CO2 cycles in future model predictions. The method itself is a valuable alternative to traditional statistical modelling techniques used in geosciences

Mapping autism risk loci using genetic linkage and chromosomal rearrangements.

International audienceAutism spectrum disorders (ASDs) are common, heritable neurodevelopmental conditions. The genetic architecture of ASDs is complex, requiring large samples to overcome heterogeneity. Here we broaden coverage and sample size relative to other studies of ASDs by using Affymetrix 10K SNP arrays and 1,181 [corrected] families with at least two affected individuals, performing the largest linkage scan to date while also analyzing copy number variation in these families. Linkage and copy number variation analyses implicate chromosome 11p12-p13 and neurexins, respectively, among other candidate loci. Neurexins team with previously implicated neuroligins for glutamatergic synaptogenesis, highlighting glutamate-related genes as promising candidates for contributing to ASDs

An update to the Surface Ocean CO₂ Atlas (SOCAT version 2)

The Surface Ocean CO₂ Atlas (SOCAT), an activity of the international marine carbon research community, provides access to synthesis and gridded fCO₂ (fugacity of carbon dioxide) products for the surface oceans. Version 2 of SOCAT is an update of the previous release (version 1) with more data (increased from 6.3 million to 10.1 million surface water fCO₂ values) and extended data coverage (from 1968–2007 to 1968–2011). The quality control criteria, while identical in both versions, have been applied more strictly in version 2 than in version 1. The SOCAT website (http://www.socat.info/) has links to quality control comments, metadata, individual data set files, and synthesis and gridded data products. Interactive online tools allow visitors to explore the richness of the data. Applications of SOCAT include process studies, quantification of the ocean carbon sink and its spatial, seasonal, year-to-year and longerterm variation, as well as initialisation or validation of ocean carbon models and coupled climate-carbon models

An ecological quantification of the relationships between water, sanitation and infant, child, and maternal mortality

<p>Abstract</p> <p>Background</p> <p>Water and sanitation access are known to be related to newborn, child, and maternal health. Our study attempts to quantify these relationships globally using country-level data: How much does improving access to water and sanitation influence infant, child, and maternal mortality?</p> <p>Methods</p> <p>Data for 193 countries were abstracted from global databases (World Bank, WHO, and UNICEF). Linear regression was used for the outcomes of under-five mortality rate and infant mortality rate (IMR). These results are presented as events per 1000 live births. Ordinal logistic regression was used to compute odds ratios for the outcome of maternal mortality ratio (MMR).</p> <p>Results</p> <p>Under-five mortality rate decreased by 1.17 (95%CI 1.08-1.26) deaths per 1000, <it>p </it>< 0.001, for every quartile increase in population water access after adjustments for confounders. There was a similar relationship between quartile increase of sanitation access and under-five mortality rate, with a decrease of 1.66 (95%CI 1.11-1.32) deaths per 1000, <it>p </it>< 0.001. Improved water access was also related to IMR, with the IMR decreasing by 1.14 (95%CI 1.05-1.23) deaths per 1000, <it>p </it>< 0.001, with increasing quartile of access to improved water source. The significance of this relationship was retained with quartile improvement in sanitation access, where the decrease in IMR was 1.66 (95%CI 1.11-1.32) deaths per 1000, <it>p </it>< 0.001. The estimated odds ratio that increased quartile of water access was significantly associated with increased quartile of MMR was 0.58 (95%CI 0.39-0.86), <it>p </it>= 0.008. The corresponding odds ratio for sanitation was 0.52 (95%CI 0.32-0.85), <it>p </it>= 0.009, both suggesting that better water and sanitation were associated with decreased MMR.</p> <p>Conclusions</p> <p>Our analyses suggest that access to water and sanitation independently contribute to child and maternal mortality outcomes. If the world is to seriously address the Millennium Development Goals of reducing child and maternal mortality, then improved water and sanitation accesses are key strategies.</p

An update to the Surface Ocean CO2 Atlas (SOCAT version 2)

The Surface Ocean CO2 Atlas (SOCAT), an activity of the international marine carbon research community, provides access to synthesis and gridded fCO(2) (fugacity of carbon dioxide) products for the surface oceans. Version 2 of SOCAT is an update of the previous release (version 1) with more data (increased from 6.3 million to 10.1 million surface water fCO(2) values) and extended data coverage (from 1968-2007 to 1968-2011). The quality control criteria, while identical in both versions, have been applied more strictly in version 2 than in version 1. The SOCAT website (http://www.socat.info/) has links to quality control comments, metadata, individual data set files, and synthesis and gridded data products. Interactive online tools allow visitors to explore the richness of the data. Applications of SOCAT include process studies, quantification of the ocean carbon sink and its spatial, seasonal, year-to-year and longer-term variation, as well as initialisation or validation of ocean carbon models and coupled climate-carbon models.</p

Ethical and legal implications of whole genome and whole exome sequencing in African populations

BACKGROUND: Rapid advances in high throughput genomic technologies and next generation sequencing are making medical genomic research more readily accessible and affordable, including the sequencing of patient and control whole genomes and exomes in order to elucidate genetic factors underlying disease. Over the next five years, the Human Heredity and Health in Africa (H3Africa) Initiative, funded by the Wellcome Trust (United Kingdom) and the National Institutes of Health (United States of America), will contribute greatly towards sequencing of numerous African samples for biomedical research. DISCUSSION: Funding agencies and journals often require submission of genomic data from research participants to databases that allow open or controlled data access for all investigators. Access to such genotype-phenotype and pedigree data, however, needs careful control in order to prevent identification of individuals or families. This is particularly the case in Africa, where many researchers and their patients are inexperienced in the ethical issues accompanying whole genome and exome research; and where an historical unidirectional flow of samples and data out of Africa has created a sense of exploitation and distrust. In the current study, we analysed the implications of the anticipated surge of next generation sequencing data in Africa and the subsequent data sharing concepts on the protection of privacy of research subjects. We performed a retrospective analysis of the informed consent process for the continent and the rest-of-the-world and examined relevant legislation, both current and proposed. We investigated the following issues: (i) informed consent, including guidelines for performing culturally-sensitive next generation sequencing research in Africa and availability of suitable informed consent documents; (ii) data security and subject privacy whilst practicing data sharing; (iii) conveying the implications of such concepts to research participants in resource limited settings. SUMMARY: We conclude that, in order to meet the unique requirements of performing next generation sequencing-related research in African populations, novel approaches to the informed consent process are required. This will help to avoid infringement of privacy of individual subjects as well as to ensure that informed consent adheres to acceptable data protection levels with regard to use and transfer of such information

Synchronous chaos and broad band gamma rhythm in a minimal multi-layer model of primary visual cortex

Visually induced neuronal activity in V1 displays a marked gamma-band component which is modulated by stimulus properties. It has been argued that synchronized oscillations contribute to these gamma-band activity [... however,] even when oscillations are observed, they undergo temporal decorrelation over very few cycles. This is not easily accounted for in previous network modeling of gamma oscillations. We argue here that interactions between cortical layers can be responsible for this fast decorrelation. We study a model of a V1 hypercolumn, embedding a simplified description of the multi-layered structure of the cortex. When the stimulus contrast is low, the induced activity is only weakly synchronous and the network resonates transiently without developing collective oscillations. When the contrast is high, on the other hand, the induced activity undergoes synchronous oscillations with an irregular spatiotemporal structure expressing a synchronous chaotic state. As a consequence the population activity undergoes fast temporal decorrelation, with concomitant rapid damping of the oscillations in LFPs autocorrelograms and peak broadening in LFPs power spectra. [...] Finally, we argue that the mechanism underlying the emergence of synchronous chaos in our model is in fact very general. It stems from the fact that gamma oscillations induced by local delayed inhibition tend to develop chaos when coupled by sufficiently strong excitation.Comment: 49 pages, 11 figures, 7 table