CGIAR

The focus of the great majority of climate change impact studies is on changes in mean climate. In terms of climate model output, these changes are more robust than changes in climate variability. By concentrating on changes in climate means, the full impacts of climate change on biological and human systems are probably being seriously underestimated. Here, we briefly review the possible impacts of changes in climate variability and the frequency of extreme events on biological and food systems, with a focus on the developing world. We present new analysis that tentatively links increases in climate variability with increasing food insecurity in the future. We consider the ways in which people deal with climate variability and extremes and how they may adapt in the future. Key knowledge and data gaps are highlighted. These include the timing and interactions of different climatic stresses on plant growth and development, particularly at higher temperatures, and the impacts on crops, livestock and farming systems of changes in climate variability and extreme events on pest-weed-disease complexes. We highlight the need to reframe research questions in such a way that they can provide decision makers throughout the food system with actionable answers, and the need for investment in climate and environmental monitoring. Improved understanding of the full range of impacts of climate change on biological and food systems is a critical step in being able to address effectively the effects of climate variability and extreme events on human vulnerability and food security, particularly in agriculturally based developing countries facing the challenge of having to feed rapidly growing populations in the coming decades.

Functional traits offer a rich quantitative framework for developing and testing theories in evolutionary biology, ecology and ecosystem science. However, the potential of functional traits to drive theoretical advances and refine models of global change can only be fully realised when species-level information is complete. Here we present the AVONET dataset containing comprehensive functional trait data for all birds, including six ecological variables, 11 continuous morphological traits, and information on range size and location. Raw morphological measurements are presented from 90,020 individuals of 11,009 extant bird species sampled from 181 countries. These data are also summarised as species averages in three taxonomic formats, allowing integration with a global phylogeny, geographical range maps, IUCN Red List data and the eBird citizen science database. The AVONET dataset provides the most detailed picture of continuous trait variation for any major radiation of organisms, offering a global template for testing hypotheses and exploring the evolutionary origins, structure and functioning of biodiversity.

The narrowing of diversity in crop species contributing to the world's food supplies has been considered a potential threat to food security. However, changes in this diversity have not been quantified globally. We assess trends over the past 50 y in the richness, abundance, and composition of crop species in national food supplies worldwide. Over this period, national per capita food supplies expanded in total quantities of food calories, protein, fat, and weight, with increased proportions of those quantities sourcing from energy-dense foods. At the same time the number of measured crop commodities contributing to national food supplies increased, the relative contribution of these commodities within these supplies became more even, and the dominance of the most significant commodities decreased. As a consequence, national food supplies worldwide became more similar in composition, correlated particularly with an increased supply of a number of globally important cereal and oil crops, and a decline of other cereal, oil, and starchy root species. The increase in homogeneity worldwide portends the establishment of a global standard food supply, which is relatively species-rich in regard to measured crops at the national level, but species-poor globally. These changes in food supplies heighten interdependence among countries in regard to availability and access to these food sources and the genetic resources supporting their production, and give further urgency to nutrition development priorities aimed at bolstering food security.

Farmers in mixed crop-livestock systems produce about half of the world's food. In small holdings around the world, livestock are reared mostly on grass, browse, and nonfood biomass from maize, millet, rice, and sorghum crops and in their turn supply manure and traction for future crops. Animals act as insurance against hard times and supply farmers with a source of regular income from sales of milk, eggs, and other products. Thus, faced with population growth and climate change, small-holder farmers should be the first target for policies to intensify production by carefully managed inputs of fertilizer, water, and feed to minimize waste and environmental impact, supported by improved access to markets, new varieties, and technologies.

OBJECTIVE: This literature review assessed the burden of treatment-resistant depression in the United States by compiling published data about the clinical, societal, and economic outcomes associated with failure to respond to one or more adequate trials of drug therapy. METHODS: PubMed and the Tufts Cost-Effectiveness Analyses Registry were searched for English-language articles published between January 1996 and August 2013 that collected primary data about treatment-resistant depression. Two researchers independently assessed study quality and extracted data. RESULTS: Sixty-two articles were included (N=59,462 patients). Patients with treatment-resistant depression had 3.8±2.1 prior depressive episodes and illness duration of 4.4±3.3 years and had completed 4.7±2.7 unsuccessful drug trials involving 2.1±.3 drug classes. Response rates for treatment-resistant depression were 36%±1%. A total of 17%±6% of patients had prior suicide attempts (1.1±.2 attempts per patient). Quality-of-life scores (scale of 0-1, with 0 indicating death and 1 indicating perfect health) for patients with treatment-resistant depression were .41±.8 and .26±.8 points lower, respectively, than for patients who experienced remission or response. Annual costs for health care and lost productivity were $5,481 and $4,048 higher, respectively, for patients with treatment-resistant versus treatment-responsive depression. CONCLUSIONS: Treatment-resistant depression exacts a substantial toll on patients' quality of life. At current rates of 12%-20% among all depressed patients, treatment-resistant depression may present an annual added societal cost of $29-$48 billion, pushing up the total societal costs of major depression by as much as $106-$118 billion. These findings underscore the need for research on the mechanisms of depression, new therapeutic targets, existing and new treatment combinations, and tests to improve the efficacy of and adherence to treatments for treatment-resistant depression.

The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1◦C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries China, India, USA and France, but less so for Russia. Point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in projecting that warmer regions are likely to suffer more yield loss with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify ‘method uncertainty’ in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security.

Genotype-by-environment interaction (GEI) is an important phenomenon in plant breeding. This paper presents a series of models for describing, exploring, understanding, and predicting GEI. All models depart from a two-way table of genotype by environment means. First, a series of descriptive and explorative models/approaches are presented: Finlay-Wilkinson model, AMMI model, GGE biplot. All of these approaches have in common that they merely try to group genotypes and environments and do not use other information than the two-way table of means. Next, factorial regression is introduced as an approach to explicitly introduce genotypic and environmental covariates for describing and explaining GEI. Finally, QTL modeling is presented as a natural extension of factorial regression, where marker information is translated into genetic predictors. Tests for regression coefficients corresponding to these genetic predictors are tests for main effect QTL expression and QTL by environment interaction (QEI). QTL models for which QEI depends on environmental covariables form an interesting model class for predicting GEI for new genotypes and new environments. For realistic modeling of genotypic differences across multiple environments, sophisticated mixed models are necessary to allow for heterogeneity of genetic variances and correlations across environments. The use and interpretation of all models is illustrated by an example data set from the CIMMYT maize breeding program, containing environments differing in drought and nitrogen stress. To help readers to carry out the statistical analyses, GenStat® programs, 15th Edition and Discovery® version, are presented as "Appendix."

Protein from forest wildlife is crucial to rural food security and livelihoods across the tropics. The harvest of animals such as tapir, duikers, deer, pigs, peccaries, primates and larger rodents, birds and reptiles provides benefits to local people worth millions of US$ annually and represents around 6 million tonnes of animals extracted yearly. Vulnerability to hunting varies, with some species sustaining populations in heavily hunted secondary habitats, while others require intact forests with minimal harvesting to maintain healthy populations. Some species or groups have been characterized as ecosystem engineers and ecological keystone species. They affect plant distribution and structure ecosystems, through seed dispersal and predation, grazing, browsing, rooting and other mechanisms. Global attention has been drawn to their loss through debates regarding bushmeat, the "empty forest" syndrome and their ecological importance. However, information on the harvest remains fragmentary, along with understanding of ecological, socioeconomic and cultural dimensions. Here we assess the consequences, both for ecosystems and local livelihoods, of the loss of these species in the Amazon and Congo basins.

The water crisis is threatening the sustainability of the irrigated rice system and food security in Asia. Our challenge is to develop novel technologies and production systems that allow rice production to be maintained or increased in the face of declining water availability. This paper introduces principles that govern technologies and systems for reducing water inputs and increasing water productivity, and assesses the opportunities of such technologies and systems at spatial scale levels from plant to field, to irrigation system, and to agro-ecological zones. We concluded that, while increasing the productivity of irrigated rice with transpired water may require breakthroughs in breeding, many technologies can reduce water inputs at the field level and increase field-level water productivity with respect to irrigation and total water inputs. Most of them, however, come at the cost of decreased yield. More rice with less water can only be achieved when water management is integrated with (i) germplasm selection and other crop and resource management practices to increase yield, and (ii) system-level management such that the water saved at the field level is used more effectively to irrigate previously un-irrigated or low-productivity lands. The amount of water that can be saved at the system level could be far less than assumed from computations of field-level water savings because there is already a high degree of recycling and conjunctive use of water in many rice areas. The impact of reducing water inputs for rice production on weeds, nutrients, sustainability, and environmental services of rice ecosystems warrants further investigation.

Dehydration avoidance through cooler canopy temperature (CT) has been shown to explain over 60% yield variation in a random progeny derived from a Seri/Babax cross. A near ‘isomorphic’ subset of Seri/Babax progeny and parents encompassing a restricted range of height and phenology were used for detailed characterisation of drought-adaptive trait expression under contrasting water regimes. Under drought, five of the six progeny out yielded the best parent Babax by up to 35%. The main physiological attributes associated with drought adaptation were increased root dry weight at depth, transpiration rate – evidenced by grain carbon isotope discrimination (?13C) – grain filling duration and decreased CT during grain filling. Furthermore, increased root mass at depth was associated with reduced levels of stem water soluble carbohydrates (WSC) when comparing genotypes. It is concluded that differences in rooting depth expressed among iso-morphic wheat sister lines explains superior adaptation to drought. These effects can be detected in season using remote sensing. In addition, the data suggest that accumulation of stem carbohydrates and deep rooting may be two alternative strategies for adapting to drought stress, the latter being beneficial where water is available at depth.

Projections of climate change are available at coarse scales (70-400 km). But agricultural and species models typically require finer scale climate data to model climate change impacts. Here, we present a global database of future climates developed by applying the delta method -a method for climate model bias correction. We performed a technical evaluation of the bias-correction method using a 'perfect sibling' framework and show that it reduces climate model bias by 50-70%. The data include monthly maximum and minimum temperatures and monthly total precipitation, and a set of bioclimatic indices, and can be used for assessing impacts of climate change on agriculture and biodiversity. The data are publicly available in the World Data Center for Climate (WDCC; cera-www.dkrz.de), as well as in the CCAFS-Climate data portal (http://ccafs-climate.org). The database has been used up to date in more than 350 studies of ecosystem and agricultural impact assessment.

KEY MESSAGE: The integration of new technologies into public plant breeding programs can make a powerful step change in agricultural productivity when aligned with principles of quantitative and Mendelian genetics. The breeder's equation is the foundational application of quantitative genetics to crop improvement. Guided by the variables that describe response to selection, emerging breeding technologies can make a powerful step change in the effectiveness of public breeding programs. The most promising innovations for increasing the rate of genetic gain without greatly increasing program size appear to be related to reducing breeding cycle time, which is likely to require the implementation of parent selection on non-inbred progeny, rapid generation advance, and genomic selection. These are complex processes and will require breeding organizations to adopt a culture of continuous optimization and improvement. To enable this, research managers will need to consider and proactively manage the, accountability, strategy, and resource allocations of breeding teams. This must be combined with thoughtful management of elite genetic variation and a clear separation between the parental selection process and product development and advancement process. With an abundance of new technologies available, breeding teams need to evaluate carefully the impact of any new technology on selection intensity, selection accuracy, and breeding cycle length relative to its cost of deployment. Finally breeding data management systems need to be well designed to support selection decisions and novel approaches to accelerate breeding cycles need to be routinely evaluated and deployed.

In Uganda, Ghana and Bangladesh, participatory tools were used for a socio-economic and gender analysis of three topics: climate-smart agriculture (CSA), climate analogue approaches, and climate and weather forecasting. Policy and programme-relevant results were obtained. Smallholders are changing agricultural practices due to observations of climatic and environmental change. Women appear to be less adaptive because of financial or resource constraints, because of male domination in receiving information and extension services and because available adaptation strategies tend to create higher labour loads for women. The climate analogue approach (identifying places resembling your future climate so as to identify potential adaptations) is a promising tool for increasing farmer-to-farmer learning, where a high degree of climatic variability means that analogue villages that have successfully adopted new CSA practices exist nearby. Institutional issues related to forecast production limit their credibility and salience, particularly in terms of women's ability to access and understand them. The participatory tools used in this study provided some insights into women's adaptive capacity in the villages studied, but not to the depth necessary to address women's specific vulnerabilities in CSA programmes. Further research is necessary to move the discourse related to gender and climate change beyond the conceptualization of women as a homogenously vulnerable group in CSA programmes.

Abstract Addressing the global challenges of climate change, food security, and poverty alleviation requires enhancing the adaptive capacity and mitigation potential of agricultural landscapes across the tropics. However, adaptation and mitigation activities tend to be approached separately due to a variety of technical, political, financial, and socioeconomic constraints. Here, we demonstrate that many tropical agricultural systems can provide both mitigation and adaptation benefits if they are designed and managed appropriately and if the larger landscape context is considered. Many of the activities needed for adaptation and mitigation in tropical agricultural landscapes are the same needed for sustainable agriculture more generally, but thinking at the landscape scale opens a new dimension for achieving synergies. Intentional integration of adaptation and mitigation activities in agricultural landscapes offers significant benefits that go beyond the scope of climate change to food security, biodiversity conservation, and poverty alleviation. However, achieving these objectives will require transformative changes in current policies, institutional arrangements, and funding mechanisms to foster broad‐scale adoption of climate‐smart approaches in agricultural landscapes.

The completion of the genome sequences of both rice and Magnaporthe oryzae has strengthened the position of rice blast disease as a model to study plant-pathogen interactions in monocotyledons. Genetic studies of blast resistance in rice were established in Japan as early as 1917. Despite such long-term study, examples of cultivars with durable resistance are rare, partly due to our limited knowledge of resistance mechanisms. A rising number of blast resistance genes and quantitative trait loci (QTL) have been genetically described, and some have been characterized during the last 20 years. Using the rice genome sequence, can we now go a step further toward a better understanding of the genetics of blast resistance by combining all these results? Is such knowledge appropriate and sufficient to improve breeding for durable resistance? A review of bibliographic references identified 85 blast resistance genes and approximately 350 QTL, which we mapped on the rice genome. These data provide a useful update on blast resistance genes as well as new insights to help formulate hypotheses about the molecular function of blast QTL, with special emphasis on QTL for partial resistance. All these data are available from the OrygenesDB database.

We compute and investigate four types of imprint of a stochastic background of primordial magnetic fields (PMFs) on the cosmic microwave background (CMB) anisotropies: the impact of PMFs on the CMB temperature and polarization spectra, which is related to their contribution to cosmological perturbations; the effect on CMB polarization induced by Faraday rotation; the impact of PMFs on the ionization history; magnetically-induced non-Gaussianities and related non-zero bispectra; and the magnetically-induced breaking of statistical isotropy. We present constraints on the amplitude of PMFs that are derived from different Planck data products, depending on the specific effect that is being analysed. Overall, Planck data constrain the amplitude of PMFs to less than a few nanoGauss, with different bounds that depend on the considered model. In particular, individual limits coming from the analysis of the CMB angular power spectra, using the Planck likelihood, are B 1 Mpc < 4.4 nG (where B 1 Mpc is the comoving field amplitude at a scale of 1 Mpc) at 95% confidence level, assuming zero helicity. By considering the Planck likelihood, based only on parity-even angular power spectra, we obtain B 1 Mpc < 5.6 nG for a maximally helical field. For nearly scale-invariant PMFs we obtain B 1 Mpc < 2.0 nG and B 1 Mpc < 0.9 nG if the impact of PMFs on the ionization history of the Universe is included in the analysis. From the analysis of magnetically-induced non-Gaussianity, we obtain three different values, corresponding to three applied methods, all below 5 nG. The constraint from the magnetically-induced passive-tensor bispectrum is B 1 Mpc < 2.8 nG. A search for preferred directions in the magneticallyinduced passive bispectrum yields B 1 Mpc < 4.5 nG, whereas the compensated-scalar bispectrum gives B 1 Mpc < 3 nG. The analysis of the Faraday rotation of CMB polarization by PMFs uses the Planck power spectra in EE and BB at 70 GHz and gives B 1 Mpc < 1380 nG. In our final analysis, we consider the harmonic-space correlations produced by Alfvn waves, finding no significant evidence for the presence of these waves. Together, these results comprise a comprehensive set of constraints on possible PMFs with Planck data.

Summary Barley ( H ordeum vulgare ssp. vulgare ) is an excellent model for understanding agricultural responses to climate change. Its initial domestication over 10 millennia ago and subsequent wide migration provide striking evidence of adaptation to different environments, agro‐ecologies and uses. A bottleneck in the selection of modern varieties has resulted in a reduction in total genetic diversity and a loss of specific alleles relevant to climate‐smart agriculture. However, extensive and well‐curated collections of landraces, wild barley accessions ( H . vulgare ssp. spontaneum ) and other H ordeum species exist and are important new allele sources. A wide range of genomic and analytical tools have entered the public domain for exploring and capturing this variation, and specialized populations, mutant stocks and transgenics facilitate the connection between genetic diversity and heritable phenotypes. These lay the biological, technological and informational foundations for developing climate‐resilient crops tailored to specific environments that are supported by extensive environmental and geographical databases, new methods for climate modelling and trait/environment association analyses, and decentralized participatory improvement methods. Case studies of important climate‐related traits and their constituent genes – including examples that are indicative of the complexities involved in designing appropriate responses – are presented, and key developments for the future highlighted. Contents Summary 913 I. Introduction 913 II. Barley resources for climate change interventions 915 III. Predictions for barley production and genetic resources based on environmental modelling 917 IV. Examples of important genes and traits under climate change 919 V. Practical approaches for responding to climate change 922 VI. Looking to the future 926 Acknowledgements 927 References 927

Food system innovations will be instrumental to achieving multiple Sustainable Development Goals (SDGs). However, major innovation breakthroughs can trigger profound and disruptive changes, leading to simultaneous and interlinked reconfigurations of multiple parts of the global food system. The emergence of new technologies or social solutions, therefore, have very different impact profiles, with favourable consequences for some SDGs and unintended adverse side-effects for others. Stand-alone innovations seldom achieve positive outcomes over multiple sustainability dimensions. Instead, they should be embedded as part of systemic changes that facilitate the implementation of the SDGs. Emerging trade-offs need to be intentionally addressed to achieve true sustainability, particularly those involving social aspects like inequality in its many forms, social justice, and strong institutions, which remain challenging. Trade-offs with undesirable consequences are manageable through the development of well planned transition pathways, careful monitoring of key indicators, and through the implementation of transparent science targets at the local level.

OBJECTIVE: To compare the behavioral features and to investigate the neuroanatomic correlates of behavioral dysfunction in anatomically defined temporal and frontal variants of frontotemporal dementia (tvFTD and fvFTD). METHODS: Volumetric measurements of the frontal, anterior temporal, ventromedial frontal cortical (VMFC), and amygdala regions were made in 51 patients with FTD and 20 normal control subjects, as well as 22 patients with Alzheimer disease (AD) who were used as dementia controls. FTD patients were classified as fvFTD or tvFTD based on the relative degree of frontal and anterior temporal volume loss compared with controls. Behavioral symptoms, cerebral volumes, and the relationship between them were examined across groups. RESULTS: Both variants of FTD showed significant increases in rates of elation, disinhibition, and aberrant motor behavior compared with AD. The fvFTD group also showed more anxiety, apathy, and eating disorders, and tvFTD showed a higher prevalence of sleep disturbances than AD. The only behaviors that differed significantly between fvFTD and tvFTD were apathy, greater in fvFTD, and sleep disorders, more frequent in tvFTD. FvFTD was associated with greater frontal atrophy and tvFTD was associated with more temporal and amygdala atrophy compared with AD, but both groups showed significant atrophy in the VMFC compared with AD, which was not associated with VMFC atrophy. In FTD, the presence of many of the behavioral disorders was associated with decreased volume in right-hemispheric regions. CONCLUSION: FvFTD and tvFTD show many similarities in behavior, which appear to be associated with damage to right frontal and temporal structures.

Focused ultrasound surgery (FUS) is a noninvasive image-guided therapy and an alternative to surgical interventions. It presents an opportunity to revolutionize cancer therapy and to affect or change drug delivery of therapeutic agents in new focally targeted ways. In this article the background, principles, technical devices, and clinical cancer applications of image-guided FUS are reviewed.