• Energy Research
• 2016-2025close
• Open Access close
• Embargo close
• 15. Life on land close

A successful rice production on swampland would require a planting material from high yielding varieties adaptated to the swampy ecosystem. This study was carried out to compare the growth and yield characteristics of five rice lines and a check variety as grown on non-tidal swampland. The lines were F4 generation of bulk selection from the crosses involving Bengkulu swamp rice landraces (Hanafi Putih, Tigo-tigo, Harum Curup, and Lubuk Durian) and high yielding varieties for the irrigated field (Sidenuk and Bestari). The trial was conducted on a shallow non-tidal swampland with stagnant inundation no more than 50 cm in depth often occurred during the plant life cycle. The lines and the check variety (Inpara 4) were arranged in a randomized complete block design with three replications. Observations were made for the agronomic performances of the plant, including plant height, total tiller number clump-1, effective tiller number clump-1, heading date, maturity date, panicle length, grain number panicle-1, 100-grain weight, and grain yield clump-1. Significant variation among the genotypes was found for all observed traits. On average, the evaluated lines showed comparable growth and yield performances to the check variety. Tigo-tigo × Bestari was the tallest line and potential for medium depth swampland. This line showed good overall agronomic performances and yielded relatively higher than the check variety, but delayed in attaining maturity. For shallow swampland, Hanafi Putih x Sidenuk exhibited the most potent line by having good overall agronomic and yield performances, except late in maturity. For early maturing line, Lubuk Durian x Hanafi Putih showed its potential for shallow swampland. Although this line was not the best, it showed better overall agronomic performances than the check variety. Keywords: F4 lines, growth and yield performance, rice landrace, swampland, plant maturity

Abstract Levee systems are an important part of California’s water infrastructure, engineered to provide resilience against flooding and reduce flood losses. The growth in California is partly associated with costly infrastructure developments that led to population expansion in the levee protected areas. Therefore, potential changes in the flood hazard could have significant socioeconomic consequences over levee protected areas, especially in the face of a changing climate. In this study, we examine the possible impacts of a warming climate on flood hazard over levee protected land in California. We use gridded maximum daily runoff from global circulation models (GCMs) that represent a wide range of variability among the climate projections, and are recommended by the California’s Fourth Climate Change Assessment Report, to investigate possible climate-induced changes. We also quantify the exposure of several critical infrastructure protected by the levee systems (e.g. roads, electric power transmission lines, natural gas pipelines, petroleum pipelines, and railroads) to flooding. Our results provide a detailed picture of change in flood risk for different levees and the potential societal consequences (e.g. exposure of people and critical infrastructure). Levee systems in the northern part of the Central Valley and coastal counties of Southern California are likely to observe the highest increase in flood hazard relative to the past. The most evident change is projected for the northern region of the Central Valley, including Butte, Glenn, Yuba, Sutter, Sacramento, and San Joaquin counties. In the leveed regions of these counties, based on the model simulations of the future, the historical 100-year runoff can potentially increase up to threefold under RCP8.5. We argue that levee operation and maintenance along with emergency preparation plans should take into account the changes in frequencies and intensities of flood hazard in a changing climate to ensure safety of levee systems and their protected infrastructure.

AbstractElevated CO2 concentration has been reported to decrease grain nutrient concentrations and thus worsen nutritional deficiency and hidden hunger. One nutritional aspect is mineral content, yet mineral bioavailability can be limited by the presence of phytic acid. Given that future climate scenarios predict elevated global temperature driven by elevated atmospheric CO2 concentrations, we used Temperature by Free‐Air CO2 Enrichment (T‐FACE) field experiments to investigate whether elevated temperature alters the effects of elevated CO2 on grain mineral concentrations, grain mineral yields, and their bioavailability in a range of wheat and rice genotypes. We found that the negative effects of elevated CO2 were compensated for by positive effects of elevated temperature. As a result, the combined elevated CO2 and elevated temperature increased concentrations of some minerals by up to ~15% in both rice and wheat relative to control conditions. Moreover, the combined elevated CO2 and elevated temperature did not significantly change total yields of some minerals despite lower grain yields. The combined CO2 and temperature elevation increased phytic acid concentration in rice by 18.1% but decreased it in wheat by 3.5%. The mineral bioavailability, estimated as the mole ratio of phytic acid to minerals in rice and wheat grains, was limited by the combined CO2 and temperature elevation in only a few cases. Our results indicate that under future climate conditions of elevated temperature and CO2, the nutritional quality of rice and wheat with respect to minerals may remain unchanged.

Abstract. Flooding in the Amazon basin is frequently attributed to modes of large-scale climate variability, but little attention is paid to how these modes influence the timing and duration of floods despite their importance to early warning systems and the significant impacts that these flood characteristics can have on communities. In this study, river discharge data from the Global Flood Awareness System (GloFAS 2.1) and observed data at 58 gauging stations are used to examine whether positive or negative phases of several Pacific and Atlantic indices significantly alter the characteristics of river flows throughout the Amazon basin (1979–2015). Results show significant changes in both flood magnitude and duration, particularly in the north-eastern Amazon for negative El Niño–Southern Oscillation (ENSO) phases when the sea surface temperature (SST) anomaly is positioned in the central tropical Pacific. This response is not identified for the eastern Pacific index, highlighting how the response can differ between ENSO types. Although flood magnitude and duration were found to be highly correlated, the impacts of large-scale climate variability on these characteristics are non-linear; some increases in annual flood maxima coincide with decreases in flood duration. The impact of flood timing, however, does not follow any notable pattern for all indices analysed. Finally, observed and simulated changes are found to be much more highly correlated for negative ENSO phases compared to the positive phase, meaning that GloFAS struggles to accurately simulate the differences in flood characteristics between El Niño and neutral years. These results have important implications for both the social and physical sectors working towards the improvement of early warning action systems for floods.

AbstractClimate change poses new and unique challenges that threaten lives and livelihoods. Given the increasing risks and looming uncertainty of climate change, increasing attention has been directed towards adaptation, or the strategies that enable humanity to persist and thrive through climate change the best it can. Though climate change is a global problem often discussed at the national scale, urban areas are increasingly seen as having a distinct role, and distinctive motivation and capacity, for adaptation. The 12 articles in this special issue explore ways of understanding and addressing climate change impacts on urban areas. Together they reveal young but rapidly growing scholarship on how to measure, and then overcome, challenges of climate change. Two key themes emerge in this issue: 1) that we must identify and then overcome current barriers to urban adaptation and 2) frameworks/metrics are necessary to identify and track adaptation progress in urban settings. Both of these themes point to the power of indicators and other quantitative information to inform priorities and illuminate the pathway forward for adaptation. As climate change is an entirely new challenge, careful measurement that enables investment by private and public parties is necessary to provide efficient outcomes that benefit the greatest number of people.

Different species within the same community may exhibit distinct phenological responses to climate change, so it is necessary to study species differences in the green-up date among abundant species within a wide area, and a suitable phenology model should be introduced to explain the associated climate-driven mechanism. Although various models have been developed, very few studies have aimed to compare their efficiency and robustness, and the relative contributions of climate driving factors have not been sufficiently examined. We analyzed phenology data for 12 species across 17 stations in Inner Mongolia and found that essential spatiotemporal and interspecies differences existed in the green-up date. Five process-based models were established for each species and their performance was comprehensively evaluated. The two-phase models (sequential model, parallel model, unified model and unified model combined with precipitation driving) generally performed better than the one-phase model (thermal time model), and the model considering precipitation performed the best, which indicates that it is necessary to introduce the chilling effect and precipitation driving effect to improve the model accuracy in arid environments. We proposed a method to estimate the contribution rates of various climate driving factors, and significant differences in the relative demand for the various climate driving factors among different species were clearly revealed. The results indicated that for natural vegetation in Inner Mongolia, the need for the chilling and temperature driving is relatively high, and the precipitation driving is very important for herbaceous vegetation, which leads to considerable spatial and interspecies differences in green-up date. We demonstrated the feasibility of quantitatively evaluating the contributions of different climate driving factors with a process-based model, and the contradiction in phenological changes among different studies may eventually be clarified.

Scarcity of water resources in the entire country is more serious in the northern provinces like Golestan. Therefore, farmers have to use saline water or waste waters. One way to adapt to this condition is to use unconventional water such as Caspian Sea water, with lower salinity as compared with water from free seas, for common crops like soybean. Thus feasibility of using Caspian Sea water that has integrated with narrow common water and the calibration of Aquacrop model under the effect of salinity and water stress for soybean crop in Golestan province are more important. The Aquacrop model assumes a linear relationship between the biomass yield (BY) and crop transpiration one one hand and water productivity (WP) value on the other (Steduto and Albrizio, 2005). This model, as compared to other crop models, requires minimal input data and its new version 4.0 (June, 2012) has a salinity module which was used in this research to simulate the grain yield (GY) and WP of soybean under deficit and saline water irrigation. Furthermore, the AquaCrop model has not often been tested to simulate the yield of soybean under saline conditions in the semi-arid climate of Golestan province. This study aims at evaluating the efficiency of AquaCrop model in soybean yield simulation. The results are to be used for optimizing water consumption under water and saline stress. To this end, an experiment was carried out at the research farm of Gorgan University of Agricultural Sciences and Natural Resources.