Adopting higher-yielding varieties to ensure Chinese food security under climate change in 2050

AbstractChallenges of ensuring food security under climate change require urgent and substantial increase in the focus of research, innovation, transformation of knowledge, and rapid adoption of available technologies. Here we simulate the effects of the adoption of higher-yielding varieties of rice, wheat and maize crops into the food production systems on China's food security index (FSI, or relative food surplus per capita) in 2050, using the CERES crop models, climate change and a range of socio- economic and agronomic scenarios which were developed following two contrasting development pathways in line with the IPCC A2 and B2 emission scenarios, respectively. The obtained results predict a slightly positive effect of climate change on the FSI, but the magnitude of this positive effect cannot compensate the negative effects of population growth, urbanization rate and the rising affluence on the future trends of the FSI. The outcomes of the adoption of higher-yielding varieties show that a systematic adoption of higher-yielding varieties can raise the average FSI values by a margin of 16 and 27 units under the A2 and B2 scenarios, respectively, during the 2030-2050 period, compared to the average predicted FSI values of -2 and 8 percentage points under A2 and B2 during the same period. This suggests that systematic adoption of higher-yield varieties is an effective measure for Chinese agriculture not only to ensure food security but also to build adaptive capacity to climate change in 2050

Time-series modeling and prediction of global monthly absolute temperature for environmental decision making

A generalized, structural, time series modeling framework was developed to analyze the monthly records of absolute surface temperature, one of the most important environmental parameters, using a deterministicstochastic combined (DSC) approach. Although the development of the framework was based on the characterization of the variation patterns of a global dataset, the methodology could be applied to any monthly absolute temperature record. Deterministic processes were used to characterize the variation patterns of the global trend and the cyclic oscillations of the temperature signal, involving polynomial functions and the Fourier method, respectively, while stochastic processes were employed to account for any remaining patterns in the temperature signal, involving seasonal autoregressive integrated moving average (SARIMA) models. A prediction of the monthly global surface temperature during the second decade of the 21st century using the DSC model shows that the global temperature will likely continue to rise at twice the average rate of the past 150 years. The evaluation of prediction accuracy shows that DSC models perform systematically well against selected models of other authors, suggesting that DSC models, when coupled with other ecoenvironmental models, can be used as a supplemental tool for short-term (similar to 10-year) environmental planning and decision making

Climate change impact on China food security in 2050

Climate change is now affecting global agriculture and food production worldwide. Nonetheless the direct link between climate change and food security at the national scale is poorly understood. Here we simulated the effect of climate change on food security in China using the CERES crop models and the IPCC SRES A2 and B2 scenarios including CO2 fertilization effect. Models took into account population size, urbanization rate, cropland area, cropping intensity and technology development. Our results predict that food crop yield will increase +3-11 % under A2 scenario and +4 % under B2 scenario during 2030-2050, despite disparities among individual crops. As a consequence China will be able to achieve a production of 572 and 615 MT in 2030, then 635 and 646 MT in 2050 under A2 and B2 scenarios, respectively. In 2030 the food security index (FSI) will drop from +24 % in 2009 to -4.5 % and +10.2 % under A2 and B2 scenarios, respectively. In 2050, however, the FSI is predicted to increase to +7.1 % and +20.0 % under A2 and B2 scenarios, respectively, but this increase will be achieved only with the projected decrease of Chinese population. We conclude that 1) the proposed food security index is a simple yet powerful tool for food security analysis; (2) yield growth rate is a much better indicator of food security than yield per se; and (3) climate change only has a moderate positive effect on food security as compared to other factors such as cropland area, population growth, socio-economic pathway and technology development. Relevant policy options and research topics are suggested accordingly

Effects of fence enclosure on vegetation community characteristics and productivity of a degraded temperate meadow steppe in Northern China

Species composition and biomass are two important indicators in assessing the effects of restoration measures of degraded grasslands. In this paper, we present a field study on the temporal changes in plant community characteristics, species diversity and biomass production in a degraded temperate meadow steppe in response to an enclosure measure in Hulunbuir in Northern China. Our results showed that the plant community responded positively to the fence enclosure in terms of vegetation coverage, height, above- and belowground biomass. A year-to-year increase in aboveground biomass was observed, and this increase plateaued at the ninth year of the enclosure. Our results also showed that the existing dominant and foundation species gained predominance against other species. The sum of the biomass of these two species was more than doubled after the ninth year of the enclosure. However, belowground biomass only briefly increased until the fifth year of the enclosure and then decreased until the end of the experimental period. Plant diversity, evenness, and richness indices showed similar trends to that of belowground biomass. Overall, we found that the degraded temperate meadow steppe responded significantly positively to the enclosure treatment, but an optimal condition was only reached after approximately 5-7 years of continuous protection, providing a solid use case for grassland conservation and management at regional scales

A new perspective of hypothalamic disease: Shapiro's syndrome

Shapiro's syndrome (SS) is characterized by spontaneous periodic hypothermia. It occurs to patients regardless of age or sex. To date, <60 cases have been reported worldwide. Current knowledge of the disease is limited to clinical feature since the pathogenesis and etiology are still controversial. In this review, the clinical characteristics, pathological mechanism, and possible etiology of the syndrome were reviewed to improve the clinical understanding of the disease

Association between behavioral patterns and depression symptoms: dyadic interaction between couples

BackgroundBehavioral patterns are sometimes associated with depression symptoms; however, few studies have considered the intra-couple effects. This study examined the effect of a spouses’ behavioral patterns on depression symptoms within themself and in their spouse.MethodsA total of 61,118 childbearing age participants (30,559 husband-wife dyads) were surveyed. The depression symptoms were assessed using the nine-item Patient Health Questionnaire (PHQ-9). The behavioral patterns were identified by the latent class analysis. The effects of behavioral patterns on the couple’s own depression symptoms (actor effect) and their partner’s depression symptoms (partner effect) were analyzed using the Actor-Partner Interdependence Model (APIM).ResultsThree behavioral patterns were identified: low-risk group, moderate-risk group, and high-risk group. The high risk of these behavior patterns would be associated with a higher score on the PHQ-9; for both husbands and wives, their behavioral patterns were positively associated with PHQ-9 scores (βhusband = 0.53, P < 0.01; βwife = 0.58, P < 0.01). Wives’ behavioral patterns were also positively associated with their husbands’ PHQ-9 scores (β = 0.14, P < 0.01), but husbands’ behavioral patterns were not associated with their wives’ PHQ-9 scores.ConclusionsWives’ depression symptoms were affected only by their own behavioral patterns, whereas husbands’ depression symptoms were influenced by both their own and their spouses’ behavioral patterns

Prediction of Drug-Target Interactions and Drug Repositioning via Network-Based Inference

Drug-target interaction (DTI) is the basis of drug discovery and design. It is time consuming and costly to determine DTI experimentally. Hence, it is necessary to develop computational methods for the prediction of potential DTI. Based on complex network theory, three supervised inference methods were developed here to predict DTI and used for drug repositioning, namely drug-based similarity inference (DBSI), target-based similarity inference (TBSI) and network-based inference (NBI). Among them, NBI performed best on four benchmark data sets. Then a drug-target network was created with NBI based on 12,483 FDA-approved and experimental drug-target binary links, and some new DTIs were further predicted. In vitro assays confirmed that five old drugs, namely montelukast, diclofenac, simvastatin, ketoconazole, and itraconazole, showed polypharmacological features on estrogen receptors or dipeptidyl peptidase-IV with half maximal inhibitory or effective concentration ranged from 0.2 to 10 µM. Moreover, simvastatin and ketoconazole showed potent antiproliferative activities on human MDA-MB-231 breast cancer cell line in MTT assays. The results indicated that these methods could be powerful tools in prediction of DTIs and drug repositioning