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Simple Summary: Designing early warning systems for threats to food crops in Africa must respond to the needs of potential users of the system. This paper provides evidence from professional distributors, retailers, researchers, and agronomists in East Africa who may be able to use and communicate the results of the predictive modeling of pest outbreaks. Understanding the timing and spatial extent of required warnings will help guide research and engagement in these rapidly commercializing countries. Early warnings of the risks of pest and disease outbreaks are becoming more urgent, with substantial increases in threats to agriculture from invasive pests. With geospatial data improvements in quality and timeliness, models and analytical systems can be used to estimate potential areas at high risk of yield impacts. The development of decision support systems requires an understanding of what information is needed, when it is needed, and at what resolution and accuracy. Here, we report on a professional review conducted with 53 professional agronomists, retailers, distributors, and growers in East Africa working with the Syngenta Foundation for Sustainable Agriculture. The results showed that respondents reported fall armyworm, stemborers and aphids as being among the most common pests, and that crop diversification was a key strategy to reduce their impact. Chemical and cultural controls were the most common strategies for fall armyworm (FAW) control, and biological control was the least known and least used method. Of the cultural control methods, monitoring and scouting, early planting, and crop rotation with non-host crops were most used. Although pests reduced production, only 55% of respondents were familiar with early warning tools, showing the need for predictive systems that can improve farmer response. [ABSTRACT FROM AUTHOR]

Changing precipitation patterns caused by climate change are expected to have major impacts on food security and nutrition in agrarian areas in developing countries. However, the linkages between the duration and severity of precipitation shocks and their effects on child nutrition and household food security metrics remain underexplored. In this study, we used Feed the Future datasets from Ghana and Bangladesh to examine the impact of precipitation extremes on nutrition, measured by children's height-for-age and weight-for-height Z-scores, and food security, measured by the Household Hunger Scale. We used a spatial error regression to control for the effects of spatial autocorrelation, and we found an association between precipitation shocks and household hunger in both Ghana and Bangladesh, as well as an association between higher rainfall and worse child nutrition in Ghana. [ABSTRACT FROM AUTHOR]

As climate change continues, it is expected to have increasingly adverse impacts on child nutrition outcomes, and these impacts will be moderated by a variety of governmental, economic, infrastructural, and environmental factors. To date, attempts to map the vulnerability of food systems to climate change and drought have focused on mapping these factors but have not incorporated observations of historic climate shocks and nutrition outcomes. We significantly improve on these approaches by using over 580,000 observations of children from 53 countries to examine how precipitation extremes since 1990 have affected nutrition outcomes. We show that precipitation extremes and drought in particular are associated with worse child nutrition. We further show that the effects of drought on child undernutrition are mitigated or amplified by a variety of factors that affect both the adaptive capacity and sensitivity of local food systems with respect to shocks. Finally, we estimate a model drawing on historical observations of drought, geographic conditions, and nutrition outcomes to make a global map of where child stunting would be expected to increase under drought based on current conditions. As climate change makes drought more commonplace and more severe, these results will aid policymakers by highlighting which areas are most vulnerable as well as which factors contribute the most to creating resilient food systems. [ABSTRACT FROM AUTHOR]

Soil moisture reflects the amount of water available to crops in the top layer of soil. As such, considering soil moisture provides important insight into water availability and ultimately crop yields in agricultural settings. In studies of climate change, food security, and health, however, soil moisture is rarely empirically considered despite its connection to crop health and yields. In this project, we aim to advance understanding of climate impacts on food security by incorporating soil moisture into quantitative models of child health. Combining spatially referenced health survey data from the Demographic and Health Surveys for 2005 and 2010 in Senegal and 2007, 2011, and 2014 in Bangladesh, with soil moisture data from the Famine Early Warning System Network Land Data Assimilation System, we explore the linkages between sub-annual and sub-seasonal climate conditions and child malnutrition in two rainfed agriculture dependent countries—Bangladesh and Senegal. Results suggest that soil moisture, measured on very short time scales, may be associated with reductions in anthropometric weight-for-height z-scores, but the relationship is highly dependent upon geographic context. [ABSTRACT FROM AUTHOR]

Rapidly expanding global trade in the past three decades has lifted millions out of people out of poverty. Trade has also reduced manufacturing wages in high income countries and made entire industries uncompetitive in some communities, giving rise to nationalist politics that seek to stop or reverse further trade expansion in the United States and Europe. Given complex and uncertain political support for trade, how might changes in trade policy affect the global food system’s ability to adapt to climate change? Here we argue that we can best understand food security in a changing climate as a double exposure: the exposure of people and processes to both economic and climate-related shocks and stressors. Trade can help us adapt to climate change, or not. If trade restrictions proliferate, double exposure to both a rapidly changing climate and volatile markets will likely jeopardize the food security of millions. A changing climate will present both opportunities and challenges for the global food system, and adapting to its many impacts will affect food availability, food access, food utilization and food security stability for the poorest people across the world. Global trade can continue to play a central role in assuring that global food system adapts to a changing climate. This potential will only be realized, however, if trade is managed in ways that maximize the benefits of broadened access to new markets while minimizing the risks of increased exposure to international competition and market volatility. For regions like Africa, for example, enhanced transportation networks combined with greater national reserves of cash and enhanced social safety nets could reduce the impact of ‘double exposure’ on food security. [ABSTRACT FROM AUTHOR]

The Coordination Group for Meteorological Satellites (CGMS) provides an international forum for the exchange of technical information on geostationary and polar-orbiting meteorological satellite systems. In 2013, the CMGS established the Socioeconomic Benefits Tiger Team (SETT) to develop a credible methodology and common terminology for articulating the socioeconomic benefits of satellite observing systems, and to explore the most effective ways to communicate the benefits to decision makers and stakeholders. As part of its first years' activities, the SETT gathered examples of socioeconomic studies across all member organizations. This article describes key elements of these studies, and identified eight key themes that are presented. We welcome additional collaborations to identify opportunities to incorporate socioeconomic best practices, integrate these into additional or subsequent phases of work on new instruments and satellites, and develop recommendations for the way forward for the broader meteorological community. [ABSTRACT FROM AUTHOR]

As our climate changes through time there is an ever increasing need to quantify how and where it is changing so that mitigation strategies can be implemented. Urban areas have a disproportionate amount of warming due, in part, to the conductive properties of concrete and asphalt surfaces that make up an urban environment. The NASA Climate Adaptation Science Investigation working group at Goddard Space Flight Center in Greenbelt MD conducted a study to collect temperature and humidity data at 15 minute intervals from 12 sites on center. These sites represented the major surface types on center: asphalt, building roof, grass field, forest, and rain garden. The data show a strong distinction in the thermal properties of these surfaces on the center and the difference between the average value for the center compared to a local meteorological station. The data have been submitted to Oak Ridge National Laboratory Distributed Active Archive Center (ORNL-DAAC) for archival in comma separated value (csv) file format. [ABSTRACT FROM AUTHOR]

Much of the population in the developing world resides in rural areas, is dependent on local agriculture for survival, and thus directly subject to increasingly volatile and variable climatic patterns. Poverty limits options for adaptation to unpredictable weather and resultant food insecurity; these concerns are particularly salient in an era of climate change, which threatens to roll back years of development gains. Examining the association between the growing environment and child survival and nutrition is important in this context. Using NASA's satellite remote sensing data with Demographic and Health Surveys (DHS) data from four West African countries (Mali, Burkina Faso, Guinea and Benin), we assess the association between a climate-related environmental variable (vegetation index - NDVI) and child survival and nutrition. NDVI had a positive association with child survival and nutrition in countries with a wide distribution of NDVI values. NDVI was more likely to be positively associated with wasting rather than stunting. We find that environmental factors can be important for child survival and nutrition outcomes in specific contexts. Additional research is needed to further explore the ways NDVI can be used to inform our understanding of the environment's impact on child survival and nutrition. [ABSTRACT FROM AUTHOR]

The article reports on the initiation by the U.S. National Aeronautics & Space Administration (NASA) of the Soil Moisture Active Passive (SMAP) satellite mission, to address the need to measure soil moisture and freeze/thaw state with global coverage. The mission was recommended by the National Research Council in their 2007 report.

Research efforts for effectively and consistently monitoring terrestrial carbon are increasing in number. As such, there is a need to define carbon monitoring and how it relates to carbon cycle science and carbon management. There is also a need to identify capabilities of a carbon monitoring system and the system components needed to develop the capabilities. Capabilities that enable the effective application of a carbon monitoring system for monitoring and management purposes may include: reconciling carbon stocks and fluxes, developing consistency across spatial and temporal scales, tracking horizontal movement of carbon, attribution of emissions to originating sources, cross-sectoral accounting, uncertainty quantification, redundancy and policy relevance. Focused research is needed to integrate these capabilities for sustained estimates of carbon stocks and fluxes. Additionally, if monitoring is intended to inform management decisions, management priorities should be considered prior to development of a monitoring system. [ABSTRACT FROM AUTHOR]

Abstract: The World Bank has invested in infrastructure in developing countries for decades. This investment aims to reduce the isolation of markets, reducing both seasonality and variability in food availability and food prices. Here we combine city market price data, global distance to port, and country infrastructure data to create a new Isolation Index for countries and cities around the world. Our index quantifies the isolation of a city from the global market. We demonstrate that an index built at the country level can be applied at a sub-national level to quantify city isolation. In doing so, we offer policy makers with an alternative metric to assess food insecurity. We compare our isolation index with other indices and economic data found in the literature. We show that our Index measures economic isolation regardless of economic stability using correlation and analysis. [Copyright &y& Elsevier]

Abstract: Satellite remote sensing technology has contributed to the transformation of multiple earth science domains, putting space observations at the forefront of innovation in earth science. With new satellite missions being launched every year, new types of earth science data are being incorporated into science models and decision-making systems in a broad array of organizations. Policy guidance can influence the degree to which user needs influence mission design and when, and ensure that satellite missions serve both the scientific and user communities without becoming unfocused and overly expensive. By considering the needs of the user community early on in the mission-design process, agencies can ensure that satellites meet the needs of multiple constituencies. This paper describes the mission development process in NASA and ESA and compares and contrasts the successes and challenges faced by these agencies as they try to balance science and applications within their missions. [Copyright &y& Elsevier]

Abstract: Variations in agricultural production due to rainfall and temperature fluctuations are a primary cause of food insecurity on the African continent. Analysis of changes in phenology can provide quantitative information on the effect of climate variability on growing seasons in agricultural regions. Using a robust statistical methodology, we describe the relationship between phenology metrics derived from the 26year AVHRR NDVI record and the North Atlantic Oscillation index (NAO), the Indian Ocean Dipole (IOD), the Pacific Decadal Oscillation (PDO), and the Multivariate ENSO Index (MEI). We map the most significant positive and negative correlation for the four climate indices in Eastern, Western and Southern Africa between two phenological metrics and the climate indices. Our objective is to provide evidence of whether climate variability captured in the four indices has had a significant impact on the vegetative productivity of Africa during the past quarter century. We found that the start of season and cumulative NDVI were significantly affected by large scale variations in climate. The particular climate index and the timing showing highest correlation depended heavily on the region examined. In Western Africa the cumulative NDVI correlates with PDO in September–November. In Eastern Africa the start of the June–October season strongly correlates with PDO in March–May, while the PDO in December–February correlates with the start of the February–June season. The cumulative NDVI over this last season relates to the MEI of March–May. For Southern Africa, high correlations exist between SOS and NAO of September–November, and cumulative NDVI and MEI of March–May. The research shows that climate indices can be used to anticipate late start and variable vigor in the growing season of sensitive agricultural regions in Africa. [ABSTRACT FROM AUTHOR]

The article examines the relationship between markets, climate change, and food security in West Africa. The focus of the article is how the global fluctuations of food prices have made food security in West Africa tenuous. The article also discusses the role of technology in preventing food insecurity. According to the author, the use of technology has transformed agriculture and food production through advancements and improvements in irrigation, seed quality, and machinery; which has increased crop yields and the productivity of workers. Topics include an in-depth discussion of the agricultural systems in West Africa, including a welfare analysis of food prices in relation to sellers and buyers, the integration with global markets, and the use of technology to increase production.

Lek-breeding species are characterized by a negative association between territorial resource availability and male mating success; however, the impact of resources on the overall distribution patterns of the two sexes in lek systems is not clear. The normalized difference vegetation index (NDVI) has recently emerged as a powerful proxy measure for primary productivity, allowing the links between the distributions of animals and resources to be explored. Using NDVI at four spatial resolutions, we here investigate how the distribution of the two sexes in a lek-breeding population of topi antelopes relates to resource abundance before and during the rut. We found that in the dry season preceding the rut, topi density correlated positively with NDVI at the large, but not the fine, scale. This suggests that before the rut, when resources were relatively scant, topi preferred pastures where green grass was widely abundant. The pattern was less pronounced in males, suggesting that the need for territorial attendance prevents males from tracking resources as freely as females do. During the rut, which occurs in the wet season, both male and female densities correlated negatively with NDVI at the fine scale. At this time, resources were generally plentiful and the results suggest that, rather than by resource maximization, distribution during the rut was determined by benefits of aggregating on relatively resource-poor leks for mating, and possibly antipredator, purposes. At the large scale, no correlation between density and NDVI was found during the rut in either sex, which can be explained by leks covering areas too small to be reflected at this resolution. The study illustrates that when investigating spatial organization, it is important: (1) to choose the appropriate analytic scale, and (2) to consider behavioural as well as strictly ecological factors. [ABSTRACT FROM AUTHOR]

Abstract: Metrics that estimate the beginning of the growing season in semi-arid monsoonal ecosystems have become a central part of both crop models that are used to monitor crop production using satellite remote sensing and early warning indicators of possible future reductions in yield due to growing season length. This paper presents a new phenological model which is tuned to the semi-arid, monsoonal ecosystem of the West African Sahel and that uses humidity instead of calendar dates to identify the beginning of the season. We implement this model on vegetation index data from AVHRR, SPOT-Vegetation and MODIS data, and evaluate the results along with a rainfall-based start of season estimate for the region. Contributions of the paper include evaluating existing methods using ground observations of sowing date, comparing the same metric across multiple sensors and to rainfall-based SOS, and the development of a metric based on NDVI and relative humidity. [Copyright &y& Elsevier]

Systematic evaluation of food security throughout the Sahel has been attempted for nearly two decades. Food security analyses have used both food prices to determine the ability of the population to access food, and satellite-derived vegetation indices that measure vegetation production to establish how much food is available each year. The relationship between these two food security indicators is explored here using correspondence analysis and through the use of Markov chain models. Two sources of quantitative data were used: 8 km normalized difference vegetation index (NDVI) data from the Advanced Very High Resolution Radiometers (AVHRR) carried on the NOAA series of satellites, and monthly millet prices from 445 markets in Mali, Niger and Burkina Faso. The results show that the growing season vegetation production is related to the price of millet at the annual and the seasonal time scales. If the growing season was characterized by erratic, sparse rainfall, it resulted in higher prices, and well-distributed, abundant rainfall resulted in lower prices. The correspondence between vegetation production and millet prices is used to produce maps of millet prices for West Africa. [ABSTRACT FROM AUTHOR]

This paper evaluates the consistency of the Normalized Difference Vegetation Index (NDVI) records derived from Advanced Very High Resolution Radiometer (AVHRR), SPOT-Vegetation, SeaWiFS, Moderate Resolution Imaging Spectroradiometer, and Landsat ETM+. We used independently derived NDVI from atmospherically corrected ETM+ data at 13 Earth Observation System Land Validation core sites, eight locations of drought, and globally aggregated one-degree data from the four coarse resolution sensors to assess the NDVI records agreement. The objectives of this paper are to: 1) compare the absolute and relative differences of the vegetation signal across these sensors from a user perspective, and, to a lesser degree, 2) evaluate the possibility of merging the AVHRR historical data record with that of the more modern sensors in order to provide historical perspective on current vegetation activities. The statistical and correlation analyses demonstrate that due to the similarity in their overall variance, it is not necessary to choose between the longer time series of AVHRR and the higher quality of the more modern sensors. The long-term AVHRR-NDVI record provides a critical historical perspective on vegetation activities necessary for global change research and, thus, should be the basis of an intercalibrated, sensor-independent NDVI data record. This paper suggests that continuity is achievable given the similarity between these datasets. [ABSTRACT FROM AUTHOR]

Summary: This study demonstrates that there is a relationship between socioeconomic problems in parts of West Africa and remote-sensing-derived environmental information about the region (normalized difference vegetation index (NDVI), net primary production (NPP), and gridded rainfall data). Further, it finds that using both remotely sensed data and site-specific information from participatory rural appraisal (PRA) reports enables an improved understanding of natural resource management problems in the region. The study uses 100 PRA reports as sources of data on socioeconomic and natural resource management problems in Senegal and The Gambia. Utilizing a binary variable to extract semi-quantitative information from the reports, the study examines 10 PRA tools for their usefulness. [Copyright &y& Elsevier]

Abstract: Early warning systems (EWS) tend to focus on the identification of slow onset disasters such famine and epidemic disease. Since hazardous environmental conditions often precede disastrous outcomes by many months, effective monitoring via satellite and in situ observations can successfully guide mitigation activities. Accurate short term forecasts of NDVI could increase lead times, making early warning earlier. This paper presents a simple empirical model for making 1 to 4 month NDVI projections. These statistical projections are based on parameterized satellite rainfall estimates (RFE) and relative humidity demand (RHD). A quasi-global, 1 month ahead, 1° study demonstrates reasonable accuracies in many semi-arid regions. In Africa, a 0.1° cross-validated skill assessment quantifies the technique''s applicability at 1 to 4 month forecast intervals. These results suggest that useful projections can be made over many semi-arid, food insecure regions of Africa, with plausible extensions to drought prone areas of Asia, Australia and South America. [Copyright &y& Elsevier]

Since the advent of NASA's Earth Observing System, knowledge of the practical benefits of Earth science data has grown considerably. The community using NASA Earth science observations in applications has grown significantly, with increasing sophistication to serve national interests. Data latency, or how quickly communities receive science observations after acquisition, can have a direct impact on the applications and usability of the information. This study was conducted to determine how users are incorporating NASA data into applications and operational processes to benefit society beyond scientific research, as well as to determine the need for data latency of less than 12 h. The results of the analysis clearly show the significant benefit to society of serving the needs of the agricultural, emergency response, environmental monitoring and weather communities who use rapidly delivered, accurate Earth science data. The study also showed the potential of expanding the communities who use low latency NASA science data products to provide new ways of transforming data into information. These benefits can be achieved with a clear and consistent NASA policy on product latency. [ABSTRACT FROM AUTHOR]

As the cost of satellite missions grow, government agencies are working to increase the relevance and usefulness of the Earth science data that they produce. The US National Aeronautics and Space Administration's (NASA) early adopter program seeks to formalize partnerships with users of data early within the satellite planning process to ensure the greatest value of the mission. Scientists who are designing the satellite observing system, those who are developing mission data products, and the community who will use them need to work together to determine how satellite data can better inform decision making. NASA is working to initiate engagement with data users much earlier in the satellite program life so that the user needs can be prioritized, continue to engage with users throughout the development cycle, and then include analysis on societal impact after nominal mission life. The Early Adopter Program allows for broad and early engagement with decision makers by encouraging individuals and institutions with clear uses of data to engage with the mission. Early adopters facilitate feedback on mission products during pre-launch and accelerate the utilization of these products post-launch. This paper provides background and detail on how NASA is working to engage with early adopters, describes the partnership between early adopters and NASA missions, and connects the program to improved societal impacts of its satellite missions. [ABSTRACT FROM AUTHOR]

A response by Molly E. Brown, Christopher C. Funk and James Verdin to a letter to the editor about the article "FOOD SECURITY UNDER CLIMATE CHANGE" in the February 1, 2008 issue is presented.

The article focuses on the impact of climate change on agricultural and food systems. It is stated that increasing temperatures and declining precipitation over dry regions could potentially reduce yields for corn, wheat, rice, and other primary crops in the next two decades, affecting the global food security. It has been accounted since 1990s that the rising commodity prices and declining per capita cultivated area have led to decreases in food production, eroding food security in many communities. Information about the climatic change' impact on national revenue is included.

In this article we specify a model of millet prices in the three West African countries of Burkina Faso, Mali, and Niger. Using data obtained from USAID’s Famine Early Warning Systems Network (FEWS NET) we present a unique regional millet price forecasting model that takes advantage of the panel nature of our data and accounts for the distance of rural markets from capital cities. Another novel aspect of our analysis is our use of the Normalized Difference Vegetation Index (NDVI) to detect and control for variation in conditions for productivity. We find that including NDVI information significantly improves price forecasts. [ABSTRACT FROM AUTHOR]

Aim Global environmental change, through anthropogenic activities and climatic changes, is promoting broad-scale alterations to energy availability across the world's ecosystems. However, spatio-temporal variation in available energy is a key driver of animals' life histories, movement patterns and abundance, thus shaping the global distribution of individuals and species. As such, there is an increasing need to understand how and where changes to energy availability will produce the greatest impacts on animal ecology, and ultimately on the distribution of biodiversity. Location Global. Methods We compiled data from the published literature where attempts ( n = 171) have been made to find linkages between prevailing energy availability (primary productivity, indexed by the Normalized Difference Vegetation Index; NDVI) and ecological parameters (abundance, distribution and life histories) for bird and mammal species. We extracted information on trophic level (diet) and body mass for the species considered in these studies, as well as long-term site-specific average energy availability, and levels of seasonality and interannual stability (all indexed using NDVI-based metrics as proxies). We conducted a GLMM analysis to assess how these variables may structure the variability in the reported linkages between prevailing energy availability and the considered ecological parameters. Results Our analysis revealed that the strength of the reported relationships between metrics of prevailing energy availability and ecological parameters was highest in environments with high long-term interannual stability in available energy, and for larger, non-carnivorous animals. Importantly, we found no support for an influence of long-term site-specific average energy availability on the strength of these relationships. Main conclusions Overall, our results support the hypothesis that temporal stability in energy availability is a key factor controlling animal ecology over total available energy itself. These results may have some important implications for the future health and conservation requirements of currently largely stable regions under global environmental change. [ABSTRACT FROM AUTHOR]

The growth of human populations has many direct and indirect impacts on tropical forest ecosystems both locally and globally. This is particularly true in the Solomon Islands, where coastal rainforest cover still remains, but where climate change and a growing human population is putting increasing pressure on ecosystems. This study assessed recent primary productivity changes in the Kahua region (Makira, Solomon Islands) using remote sensing data (normalized difference vegetation index, NDVI). In this area, there has been no commercial logging and there is no existing information about the state of the forests. Results indicate that primary productivity has been decreasing in recent years, and that the recent changes are more marked near villages. Multiple factors may explain the reported pattern in primary productivity. The study highlights the need to (1) assess how accurately remote sensing data-based results match field data on the ground; (2) identify the relative contribution of the climatic, socioeconomic and political drivers of such changes; and (3) evaluate how primary productivity changes affect biodiversity level, ecosystem functioning and human livelihoods. [ABSTRACT FROM PUBLISHER]

Global NDVI data are routinely derived from the AVHRR, SPOT-VGT, and MODIS/Terra earth observation records for a range of applications from terrestrial vegetation monitoring to climate change modeling. This has led to a substantial interest in the harmonization of multisensor records. Most evaluations of the internal consistency and continuity of global multisensor NDVI products have focused on time-series harmonization in the spectral domain, often neglecting the spatial domain. We fill this void by applying variogram modeling (a) to evaluate the differences in spatial variability between 8-km AVHRR, 1-km SPOT-VGT, and 1-km, 500-m, and 250-m MODIS NDVI products over eight EOS (Earth Observing System) validation sites, and (b) to characterize the decay of spatial variability as a function of pixel size (i.e. data regularization) for spatially aggregated Landsat ETM+ NDVI products and a real multisensor dataset. First, we demonstrate that the conjunctive analysis of two variogram properties – the sill and the mean length scale metric – provides a robust assessment of the differences in spatial variability between multiscale NDVI products that are due to spatial (nominal pixel size, point spread function, and view angle) and non-spatial (sensor calibration, cloud clearing, atmospheric corrections, and length of multi-day compositing period) factors. Next, we show that as the nominal pixel size increases, the decay of spatial information content follows a logarithmic relationship with stronger fit value for the spatially aggregated NDVI products (R 2 =0.9321) than for the native-resolution AVHRR, SPOT-VGT, and MODIS NDVI products (R 2 =0.5064). This relationship serves as a reference for evaluation of the differences in spatial variability and length scales in multiscale datasets at native or aggregated spatial resolutions. The outcomes of this study suggest that multisensor NDVI records cannot be integrated into a long-term data record without proper consideration of all factors affecting their spatial consistency. Hence, we propose an approach for selecting the spatial resolution, at which differences in spatial variability between NDVI products from multiple sensors are minimized. This approach provides practical guidance for the harmonization of long-term multisensor datasets. [Copyright &y& Elsevier]

Global agriculture is under pressure to meet increasing demand for food and agricultural products. There are several global assessments of crop yields, but we know little about the uncertainties of their key findings, as the assessments are driven by the single best yield dataset available when each assessment was conducted. Recently, two different spatially explicit, global, historical yield datasets, one based on agricultural census and the other largely based on satellite remote sensing, became available. Using these datasets, we compare the similarities and differences in global yield gaps, trend patterns, growth rates and changes in year-to-year variability. We analyzed maize, rice, wheat and soybean for the period of 1981 to 2008 at four resolutions (0.083°, 0.5°, 1.0° and 2.0°). Although estimates varied by dataset and resolution, the global mean annual growth rates of 1.7–1.8%, 1.5–1.7%, 1.1–1.3% and 1.4–1.6% for maize, rice, wheat and soybean, respectively, are not on track to double crop production by 2050. Potential production increases that can be attributed to closing yield gaps estimated from the satellite-based dataset are almost twice those estimated from the census-based dataset. Detected yield variability changes in rice and wheat are sensitive to the choice of dataset and resolution, but they are relatively robust for maize and soybean. Estimates of yield gaps and variability changes are more uncertain than those of yield trend patterns and growth rates. These tendencies are consistent across crops. Efforts to reduce uncertainties are required to gain a better understanding of historical change and crop production potential to better inform agricultural policies and investments. [ABSTRACT FROM AUTHOR]

North Africa, the world's largest dust source, is non-uniform, consisting of a permanently arid region (Sahara), a semi-arid region (Sahel), and a relatively moist vegetated region (Savanna), each with very different rainfall patterns and surface conditions. This study aims to better understand the controlling factors that determine the variation of dust emission in North Africa over a 27-year period from 1982 to 2008, using observational data and model simulations. The results show that the model-derived Saharan dust emission is only correlated with the 10-m winds (W10m) obtained from reanalysis data, but the model-derived Sahel dust emission is correlated with both W10m and the Normalized Difference Vegetation Index (NDVI) that is obtained from satellite. While the Saharan dust accounts for 82% of the continental North Africa dust emission (1340–1570 Tg year −1 ) in the 27-year average, the Sahel accounts for 17% with a larger seasonal and inter-annual variation (230–380 Tg year −1 ), contributing about a quarter of the transatlantic dust transported to the northern part of South America. The decreasing dust emission trend over the 27-year period is highly correlated with W10m over the Sahara (R = 0.92). Over the Sahel, the dust emission is correlated with W10m (R = 0.69) but is also anti-correlated with the trend of NDVI (R = -0.65). W10m is decreasing over both the Sahara and the Sahel between 1982 and 2008, and the trends are correlated (R = 0.53), suggesting that Saharan/Sahelian surface winds are a coupled system, driving the inter-annual variation of dust emission. [ABSTRACT FROM AUTHOR]

The annual cycle of vegetation growth may be altered in response to climate changes affecting ecosystem dynamics. However, our understanding of vegetation seasonality is mostly limited to the mechanisms and attributes of phenological events, such as spring emergence and fall senescence. Here we have investigated the seasonal evolution of vegetation growth from winter dormancy to summer maturity of four forest types in the Northern Hemisphere (NH) temperate and boreal forests for 1982–2011. The present study assesses large-scale variations in the vegetation green-up rate ( VG rate ) and its connection to temperature variability using remotely sensed normalized difference vegetation index (NDVI) and surface air temperature. The average of the VG rate of the analysis period increases with latitude, which indicates that the canopy develops more rapidly from dormancy to maturity for vegetation in higher-latitude or colder climate zones. VG rate and precedent temperature also show a positive correlation (r) over temperate and boreal forests (67% of the forest area in the NH), indicating that increased temperatures lead to faster canopy development within the same climate zone or latitude band. Responsiveness of VG rate to temperature variability shows that despite the same magnitude of local temperature variability during extremely cold and warm years, the magnitude of VG rate acceleration in warm years (0.07 (15-day) − 1 ) is larger than the VG rate deceleration in cold years (− 0.03 (15-day) − 1 ), suggesting that the response of VG rate to temperature variability is nonlinear. Among the four forest types examined in this study, the nonlinear responses are most clearly observed in deciduous broadleaf forests indicating that forest composition may regulate the large-scale response of canopy development to temperature variability. Overall, our results suggest that anomalous seasonal warming will significantly affect canopy developments over wide deciduous forest areas. [ABSTRACT FROM AUTHOR]

The National Research Council (NRC) recently highlighted the dual role of NASA to support both science and applications in planning Earth observations. This article reports the efforts of the NASA Applied Sciences Program and NASA Soil Moisture Active Passive (SMAP) mission to integrate applications with science and engineering in prelaunch planning. The SMAP Early Adopter program supported the prelaunch applied research that comprises the SMAP Special Collection of the Journal of Hydrometeorology. This research, in turn, has resulted in unprecedented prelaunch preparation for SMAP applications and critical feedback to the mission to improve product specifications and distribution for postlaunch applications. These efforts have been a learning experience that should provide direction for upcoming missions and set some context for the next NRC decadal survey. [ABSTRACT FROM AUTHOR]

A partnership between Earth scientists and institutional stewards is helping the National Aeronautics and Space Administration (NASA) prepare for a changing climate and growing climate-related vulnerabilities. An important part of this partnership is an agency-wide Climate Adaptation Science Investigator (CASI) Workgroup. CASI has thus far initiated 1) local workshops to introduce and improve planning for climate risks, 2) analysis of climate data and projections for each NASA Center, 3) climate impact and adaptation toolsets, and 4) Center-specific research and engagement. Partnering scientists with managers aligns climate expertise with operations, leveraging research capabilities to improve decision-making and to tailor risk assessment at the local level. NASA has begun to institutionalize this ongoing process for climate risk management across the entire agency, and specific adaptation strategies are already being implemented. A case study from Kennedy Space Center illustrates the CASI and workshop process, highlighting the need to protect launch infrastructure of strategic importance to the United States, as well as critical natural habitat. Unique research capabilities and a culture of risk management at NASA may offer a pathway for other organizations facing climate risks, promoting their resilience as part of community, regional, and national strategies. [ABSTRACT FROM AUTHOR]

Host parasite diversity plays a fundamental role in ecological and evolutionary processes, yet the factors that drive it are still poorly understood. A variety of processes, operating across a range of spatial scales, are likely to influence both the probability of parasite encounter and subsequent infection. Here, we explored eight possible determinants of parasite richness, comprising rainfall and temperature at the population level, ranging behavior and home range productivity at the group level, and age, sex, body condition, and social rank at the individual level. We used a unique dataset describing gastrointestinal parasites in a terrestrial subtropical vertebrate (chacma baboons, Papio ursinus), comprising 662 fecal samples from 86 individuals representing all age-sex classes across two groups over two dry seasons in a desert population. Three mixed models were used to identify the most important factor at each of the three spatial scales (population, group, individual); these were then standardized and combined in a single, global, mixed model. Individual age had thestrongest influence on parasite richness, in a convex relationship. Parasite richness was also higher in females and animals in poor condition, albeit at a lower order of magnitude than age. Finally, with a further halving of effect size, parasite richness was positively correlated to day range and temperature. These findings indicate that a range of factors influence host parasite richness through both encounter and infection probabilities but that individual-level processes may be more important than those at the group or population level. Am J Phys Anthropol, 2012. © 2011 Wiley-Liss,Inc. [ABSTRACT FROM AUTHOR]

Changes in vegetative growing seasons are dominant indicators of the dynamic response of ecosystems to climate change. Therefore, knowledge of growing seasons over the past decades is essential to predict ecosystem changes. In this study, the long-term changes in the growing seasons of temperate vegetation over the Northern Hemisphere were examined by analyzing satellite-measured normalized difference vegetation index and reanalysis temperature during 1982-2008. Results showed that the length of the growing season (LOS) increased over the analysis period; however, the role of changes at the start of the growing season (SOS) and at the end of the growing season (EOS) differed depending on the time period. On a hemispheric scale, SOS advanced by 5.2 days in the early period (1982-1999) but advanced by only 0.2 days in the later period (2000-2008). EOS was delayed by 4.3 days in the early period, and it was further delayed by another 2.3 days in the later period. The difference between SOS and EOS in the later period was due to less warming during the preseason (January-April) before SOS compared with the magnitude of warming in the preseason (June-September) before EOS. At a regional scale, delayed EOS in later periods was shown. In North America, EOS was delayed by 8.1 days in the early period and delayed by another 1.3 days in the later period. In Europe, the delayed EOS by 8.2 days was more significant than the advanced SOS by 3.2 days in the later period. However, in East Asia, the overall increase in LOS during the early period was weakened in the later period. Admitting regional heterogeneity, changes in hemispheric features suggest that the longer-lasting vegetation growth in recent decades can be attributed to extended leaf senescence in autumn rather than earlier spring leaf-out. [ABSTRACT FROM AUTHOR]

Since 1980, the number of undernourished people in eastern and southern Africa has more than doubled. Rural development stalled and rural poverty expanded during the 1990s. Population growth remains very high, and declining per-capita agricultural capacity retards progress toward Millennium Development goals. Analyses of in situ station data and satellite observations of precipitation have identified another problematic trend: main growing-season rainfall receipts have diminished by ≈15% in food-insecure countries clustered along the western rim of the Indian Ocean. Occurring during the main growing seasons in poor countries dependent on rain-fed agriculture, these declines are societally dangerous. Will they persist or intensify? Tracing moisture deficits upstream to an anthropogenically warming Indian Ocean leads us to conclude that further rainfall declines are likely. We present analyses suggesting that warming in the central Indian Ocean disrupts onshore moisture transports, reducing continental rainfall. Thus, late 20th-century anthropogenic Indian Ocean warming has probably already produced societally dangerous climate change by creating drought and social disruption in some of the world's most fragile food economies. We quantify the potential impacts of the observed precipitation and agricultural capacity trends by modeling "millions of undernourished people" as a function of rainfall, population, cultivated area, seed, and fertilizer use. Persistence of current tendencies may result in a 50% increase in undernourished people by 2030. On the other hand, modest increases in per-capita agricultural productivity could more than offset the observed precipitation declines. Investing in agricultural development can help mitigate climate change while decreasing rural poverty and vulnerability. [ABSTRACT FROM AUTHOR]

Presents information on a study which aimed to evaluate the spatial coherence of satellite images using smoothness membership in Besov spaces. Methodology; Results and discussions; Conclusions.

A challenge in addressing climate risk in developing countries is that many regions have extremely limited formal data sets, so for these regions, people must rely on technologies like remote sensing for solutions. However, this means the necessary formal weather data to design and validate remote sensing solutions do not exist. Therefore, many projects use farmers' reported perceptions and recollections of climate risk events, such as drought. However, if these are used to design risk management interventions such as insurance, there may be biases and limitations which could potentially lead to a problematic product. To better understand the value and validity of farmer perceptions, this paper explores two related questions: (1) Is there evidence that farmers reporting data have any information about actual drought events, and (2) is there evidence that it is valuable to address recollection and perception issues when using farmer-reported data? We investigated these questions by analyzing index insurance, in which remote sensing products trigger payments to farmers during loss years. Our case study is perhaps the largest participatory farmer remote sensing insurance project in Ethiopia. We tested the cross-consistency of farmer-reported seasonal vulnerabilities against the years reported as droughts by independent satellite data sources. We found evidence that farmer-reported events are independently reflected in multiple remote sensing datasets, suggesting that there is legitimate information in farmer reporting. Repeated community-based meetings over time and aggregating independent village reports over space lead to improved predictions, suggesting that it may be important to utilize methods to address potential biases. [ABSTRACT FROM AUTHOR]