Population carrying capacity and sustainable agricultural use of land resources in Caoxian County (North China)

In this study, an attempt is made to assess the potential sustainable agricultural use of the land resources in Caoxian County in north China. Based on a land resources inventory (physiography, climate, soil, land use and management), the rotation of winter wheat-summer maize was selected as the major land utilization type of grain production in the study area. Land use requirements were adapted to the local conditions and hierarchical production potentials were estimated using the collected data. Satisfactory results have been achieved for six scenarios combining local management practices and input levels. The population carrying capacity has been obtained and guidelines for a sustainable use of land resources were formulated. Conclusions were drawn with regard to the methodologies applied

Development of a Web-based land evaluation system and its application to population carrying capacity assessment using .Net technology

The multi-disciplinary approach used in this study combines the state-of-the-art IT technology with an elaborated land evaluation methodology and results in a Web-based land evaluation system (WLES). The WLES is designed in such a way that the system operates both as a Web Application and as a Web Service. Implemented on top of the .NET platform, the WLES has a loosely coupled multi-layer structure which seamlessly integrates the domain knowledge of land evaluation and the soil database. The Web Service feature makes the WLES suitable to act as a building block of a larger system such as that of the population carrying capacity (PCC) assessment. As a reference application, a framework is made to assess the PCC on the basis of the production potential calculations which are available through the WLES Web Service interface

Simulating long-term food producing capacities in China using a Web-based land evaluation system

This dissertation presents a modeling approach to assess the long-term food producing capacities, and consequently food security, in China using a Web-based land evaluation system (WLES, http://weble.ugent.be). WLES implements a 3-step quantitative land evaluation model which evaluates the realistic yield of a field crop by considering the effects of (a) radiation and temperature regimes, (b) water stress, (c) limited soil fertility and (d) insufficient crop management. Homogeneous 5 km by 5 km grid datasets of climatic, soil, crop and management parameters were created. Food productions in 2030 and 2050 were simulated using production scenarios involving population growth, urbanization rate, cropland area, cropping intensity, management level and soil degradation. The model predicted that food crops may experience a 9.7% productivity loss by 2030 if the soil is degraded at the current rate (“business-as-usual” scenario, BAU); productivity loss will increase to an unbearable level of 36.7% by 2050, should the soil be twice more degraded than it is now (“double degradation” scenario, 2xSD). China's food producing capacity tends to decline in the long run if the general trend of soil degradation will not be reverted. China will be able to achieve a production of 430 million tons from food crops in 2030 and 410 million tons in 2050 under the BAU scenario, which are 11.5% and 15.5% lower than the 2005 level, respectively. In per capita terms, China will experience a food shortage of 9.8% in 2030 and 7.5% in 2050 even under the “zero-degradation” scenario (0xSD), compared to a 12.7% food surplus in 2005. Per capita food shortage in 2050 will be as high as 22.6% under the BAU scenario and 38.3% under the 2xSD scenario. The results suggest the present-day producing capacity (2005 level) will not be able to sustain the long-term needs under the current management level even if soil degradation is not becoming more limiting. The detrimental effect of soil degradation on food security is so evident that technical measures and policy levers must be activated today in order to avoid, or at least mitigate, the risks of food insecurity tomorrow

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

Dynamics of Manganese and Cerium Enrichments in Arctic Ocean Sediments: A Case Study From the Alpha Ridge

Manganese (Mn) and cerium (Ce) are known as reactive metals sensitive to marine redox conditions, and can therefore serve as useful proxies for paleoceanographic environments. Quaternary sedimentary records in the Arctic Ocean show a consistent cyclicity of Mn enrichments, but Mn sources, transportation and deposition patterns, and relationship to paleoclimatic conditions are not well understood. Sediment core ARC3-B85D from the Alpha Ridge with the estimated stratigraphy covering ∼350 kyr is used to investigate a coupled distribution of Mn and Ce in Quaternary Arctic Ocean sediments. By analyzing Mn and Ce distribution patterns in the core and surface sediments from the western Arctic Ocean and adjacent shelves, we investigate the conditions and dynamics of concurrent metal enrichments. Stratigraphic Ce and Mn patterns follow inferred glacial-interglacial cycles, with enrichments generally occurring during interglacial-type conditions with high sea levels. However, the relationships involved are not straightforward as highest Mn and Ce enrichments seem to occur closer to the end of interglacial/major interstadial periods, when sea levels were lowering from their highest positions. We conclude that the enrichment patterns are primarily defined by sediment dynamics controlling resuspension and transportation of reactive metals and their deposition in the central Arctic Ocean after diagenetic preconditioning on the shelves. We further infer that major transportation agents are sea-level affected cross-shelf and mid-depth ocean currents rather than sea ice as has been proposed earlier. Comprehending this coupled geochemical and sedimentary system is important for improving the chronostratigraphic framework for Quaternary deposits in the Arctic Ocean

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

AKConv: Convolutional Kernel with Arbitrary Sampled Shapes and Arbitrary Number of Parameters

Neural networks based on convolutional operations have achieved remarkable results in the field of deep learning, but there are two inherent flaws in standard convolutional operations. On the one hand, the convolution operation be confined to a local window and cannot capture information from other locations, and its sampled shapes is fixed. On the other hand, the size of the convolutional kernel is fixed to k $\times$ k, which is a fixed square shape, and the number of parameters tends to grow squarely with size. It is obvious that the shape and size of targets are various in different datasets and at different locations. Convolutional kernels with fixed sample shapes and squares do not adapt well to changing targets. In response to the above questions, the Alterable Kernel Convolution (AKConv) is explored in this work, which gives the convolution kernel an arbitrary number of parameters and arbitrary sampled shapes to provide richer options for the trade-off between network overhead and performance. In AKConv, we define initial positions for convolutional kernels of arbitrary size by means of a new coordinate generation algorithm. To adapt to changes for targets, we introduce offsets to adjust the shape of the samples at each position. Moreover, we explore the effect of the neural network by using the AKConv with the same size and different initial sampled shapes. AKConv completes the process of efficient feature extraction by irregular convolutional operations and brings more exploration options for convolutional sampling shapes. Object detection experiments on representative datasets COCO2017, VOC 7+12 and VisDrone-DET2021 fully demonstrate the advantages of AKConv. AKConv can be used as a plug-and-play convolutional operation to replace convolutional operations to improve network performance. The code for the relevant tasks can be found at https://github.com/CV-ZhangXin/AKConv.Comment: 10 pages, 5 figure