66 research outputs found
Ionic-electronic halide perovskite memdiodes enabling neuromorphic computing with a second-order complexity
Full text linkISSN:2375-254
Eco-geographic Environment and Regional Development in Xinjiang of China
No full textThe study on relationship between eco-geographic environment (EGE) and regional development (RD) is of theoretical and practical significance to promote the comprehensive study on nature and human factors and regional coordination development. Based on the evaluation index system and models of EGE and RD, Quadrant Analysis Method (QAM) and the Coordination Degree and Coordinated Development Degree Model (CDCDDM) were applied to studying the relationship between EGE and RD in Xinjiang in this paper. The results show that Xinjiang can be divided into four type regions according to the relationship between EGE and RD, namely high coordination region (HCR), overloading development region (ODR), low coordination region (LCR) and potential development region (PDR). Most areas of Xinjiang belong to LCR which can not bear a larger population and support large-scale economic development. HCR, ODR and PDR, which are mainly distributed in piedmont oases and take basin as unit, should be focused on in the development of Xinjiang. The EGE has great influence on RD, and there is serious contradiction between them. Relevant suggestions on development strategies were put forward according to the character of different type regions, and the key regions of macro-layout of RD in Xinjiang were pointed out
Pre-assessment on the loss and impact caused by large-scale flood disasters
No full textThrough intensive studies, we have established an index system for evaluating the loss and impact caused by large-scale flood disasters, and constructed a methodological system for pre-assessing the loss and impact caused by large-scale flood disasters. Through numerical simulation, submerged characteristics of large-scale flood can be determined. According to the characteristics of spatial corresponding distribution between land-use types and types of disaster-affecting subjects, we have realized spatialization for social and economic statistic data, and have completed spatialization evaluation on the loss and social impact caused by large-scale flood disasters using the spatial analytical function of GIS software. It is possible that large-scale flood can occur in the lower Yellow River. Flood management requires pre-assessment on the loss and impact caused by flood disasters. Nevertheless, there is no appropriate pre-assessment method for the lower Yellow River at present. By imitating the flood happened in Yuanyang, the north bank of the lower reach of Yellow River in 1958, we did pre-assessment on the loss and social impact caused by the overflow flood. We found that this method can be used to predict the types,. quantity and spatial distribution of economic loss caused by large-scale flood disasters. This method can determine population affected by disasters and degree and spatial distribution of disasters. Indirect loss can be predicted as well using this method. In general, this method can meet the needs of regions affected by flood for planning and making decisions in fighting floods and reducing loss
Determining factors in potential evapotranspiration changes over China in the period 1971-2008
No full textNational Natural Science Foundation of China [40701010, 40771016
Hotspots of Yield Loss for Four Crops of the Belt and Road Terrestrial Countries under 1.5 °C Global Warming
No full textThe Fifth Assessment Report of the Intergovernmental Panel on Climate change (IPCC) shows that climate change poses severe risks to the Belt and Road region and could cut future crop production. Identifying the positions and features of hotspots, which refer to regions with severe yield loss at 1.5 °C global warming, is the key to developing proper mitigation and adaptation policies to ensure regional food security. This study examined yield loss hotspots of four crops (maize, rice, soybean and wheat) at 1.5 °C global warming under RCP8.5. Yield data were derived from simulations of multiple climate-crop model ensembles from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). Hotspots were identified by setting a threshold of the 10th percentile of crop yields during the reference period (1986–2005). To quantify the likelihood of crop yield loss hotspots within multi-model ensembles, the agreement of model combinations for hotspots was calculated for each crop at the grid scale with 0.5° × 0.5° spatial resolution. Results revealed spatial heterogeneity of cultivation structure and hotspot likelihood for four crops. The four crops’ production of SA (South Asia) and SEA (Southeast Asia) accounts for more than 40% of the total production in the Belt and Road region, roughly four times the amount produced in CEE (Central and Eastern Europe) and NEA (Northeast Asia). Besides, the hotspots likelihood of maize, rice and soybean is generally larger in SA/SEA than that in CEE/NEA which means the risk of yield reduction is higher in the current main agricultural area. According to IPCC’s classification rules for likelihood, four crops’ hotspot patterns were displayed under the 1.5 °C global warming. As the highest-yielding crop, maize shows the largest proportion of “likely” hotspots (hotspot likelihood > 66%), which is about 6.48%, accounting for more than four times that of the other three crops. In addition, four crops’ hotspots are mainly distributed in SEA and SA. Overall, SEA and SA are vulnerable subregions and maize is the vulnerable crop of the Belt and Road region. Our results could provide information on target areas where mitigation or adaptations are needed to reduce the adverse influence of climate change in the agricultural system
Modeling Subtropical Forest Changes under Climate Change and Close-to-Nature Silviculture: Is There a Tipping Point in an Uncertain Future in Southern China?
No full textSubtropical forests face pressure from both rapidly changing climate and increasing harvest activity in southern China. However, the interactive effects of various spatial processes on forests are not well known. The objective of the present study was to answer the question of how forest aboveground biomass (AGB) changes under alternative climate change and harvesting scenarios and to determine whether there will be a tipping point for forest AGB before 2300. Our simulation results show that, although total forest AGB did not reach a tipping point before 2300 under possible climate change and harvesting scenarios, the slope of the total forest AGB showed a decreasing trend around 2100 and 2200. Moderate climate warming was conducive to AGB accumulation, except for in the high emissions Representative Concentration Pathway (RCP8.5) scenario. Our results also indicate that timber harvesting is adaptable to the accumulation of biomass under climate change scenarios. Harvesting intensity was a key variable affecting forest AGB more than harvesting frequency. Our findings will help develop more sustainable forest management strategies that can adapt to potential climate change scenarios, as well as determining the effectiveness of implementing alternative forest harvesting policies
Modeling the Relative Contributions of Land Use Change and Harvest to Forest Landscape Change in the Taihe County, China
No full textForests are under pressure from land use change due to anthropogenic activities. Land use change and harvest are the main disturbances of forest landscape changes. Few studies have focused on the relative contributions of different disturbances. In this study, we used the CA-Markov model, a land-use change model, coupled with a forest landscape model, LANDIS-II, to simulate dynamic change in Taihe County, China, from 2010 to 2050. Scenarios analysis was conducted to quantify the relative contributions of land use change and harvest. Our results show that forestland and arable land will remain the primary land-use types in 2050, whereas the built-up land will sprawl drastically. Land use change and harvest may result in the significant loss of forest area and changes in landscape structure. The simulated forest area will increase by 16.2% under the no disturbance scenario. However, under harvest, forest conversion, and integrated scenario, the area will be reduced by 5.2%, 16.5%, and 34.9%, respectively. The effect of harvest is gradually enhanced. The land use change will account for 60% and harvest will account for 40% of forest landscape change in 2050, respectively. Our results may benefit from the integration of regional forest management and land-use policy-making, and help to achieve a trade-off between economy and ecological environment
PS123 crop growth model based method to calculate potential maize productivity in Hailun, Heilongjiang
No full textThis paper analyses potential maize productivity in Hailun, Heilongjiang by combining PS123 crop growth model with ordinary methods. Data from 1999 to 2001 were adopted to calculate the potential maize productivity and get the average as the final result. The estimates of photosynthesis potential productivity (PPP), the temperature potential productivity (TPP), climate potential productivity (CPP) and land potential productivity (LPP) of maize are 54008, 11998, 9531, 8006 kg/hm<sup>2</sup>, respectively. Compared with the reality on maize productivity in Hailun, the use efficiencies of PPP, TPP, CPP and LPP are 10.7%, 48.3%, 60.9%, 72.4%, respectively, which means that there is still great potential in Hailun
A gradient analysis on urban sprawl and urban landscape pattern between 1985 and 2000 in the Pearl River Delta, China
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