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    Sustainable Agriculture in the “Belt and Road” Region in Conjunction with the Sustainable Development Goals
    CHEN Shaofeng, LIU Yang, SU Liyang
    Journal of Resources and Ecology    2019, 10 (6): 649-656.   DOI: 10.5814/j.issn.1674-764X.2019.06.010
    Abstract459)   HTML12)    PDF (497KB)(238)      

    The countries along the “Belt and Road” (B&R) should devote their efforts to top-level planning in the field of agriculture, so as to ensure the sustainable development of agriculture in the region. This will require a precise assessment of the sustainability of agriculture along the B&R. With a view to understanding the concept of sustainable agriculture along the B&R, combined with the interpretation of the agricultural objectives contained in the United Nation’s Sustainable Development Goals (SDGs), this study uses statistical regression analysis and trend prediction to predict the social and economic development trends in terms of economic growth and urbanization in the countries along the B&R up until 2030, and the corresponding impacts on agricultural resources and the environment. The results show that the future prospects for agricultural resources and the environment along the B&R are not promising, and meeting the future food security needs of the region will be difficult. Only by adopting innovative policies and implementing strategic planning can the goals of sustainable agricultural development and food security by 2030 be achieved in this region. Therefore, countries along the B&R should formulate agricultural development strategies from three aspects: building an agricultural cooperation platform, setting up special funds, and innovating the agricultural cooperation mode, so as to achieve the sustainable development of agriculture in the region.

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    Estimation of Travel Climate Comfort Degree in the Cross-border Region between China and Russia based on GIS
    ZHOU Yezhi, WANG Juanle, WANG Yi, Elena A. Grigorieva
    Journal of Resources and Ecology    2019, 10 (6): 657-666.   DOI: 10.5814/j.issn.1674-764X.2019.06.011
    Abstract478)   HTML7)    PDF (7312KB)(64)      

    The duration of travel climate comfort degree is an important factor that influences the length of the tourism season and the development of a tourism destination. In this study, we used the monthly average meteorological data for the last 10 years from 46 weather stations in Heilongjiang Province (China) and Primorsky Krai (Russia) to calculate the temperature-humidity index (THI) and wind chill index (WCI) based on ArcGIS software interpolation technology. We obtained the climate comfort charts of the study area with a grid size a 1 km 2 grid size, and analyzed the spatial distribution of comfort for each month. The results show the following: 1) The THI and WCI of the cross-border region gradually decrease from south to north and from low altitude to high altitude. The annual comfortable climate period is longer when analyzed in terms of the WCI rather \than the THI. 2) The travel climate comfortable period of the study area shows significant regional difference and the length of the comfortable period in Heilongjiang Province is 4 to 5 months. Meanwhile, the period in Primorsky Krai decreases from south to north and the length of the comfortable period length in its southern region can reach 7 months. 3) The predominant length of the climate comfortable period in the cross-border area is 5 months per year, and it covers 46.6% of the total area, while areas that have a climate comfortable period of 2 months are the most limited, covering less than 0.3% of the area. The results provide a scientific basis for the utilization and development of a meteorological tourism resources and touring arrangements for tourists in the cross-border region between China and Russia.

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    Temporal and Spatial Dynamics Analysis of Grassland Ecosystem Pressure in Kazakhstan
    WEN Xin, YAN Huimin, XIE Xiaoping, DU Wengpeng, LAI Chenxi, ZHEN Lin
    Journal of Resources and Ecology    2019, 10 (6): 667-675.   DOI: 10.5814/j.issn.1674-764X.2019.06.012
    Abstract224)   HTML6)    PDF (3719KB)(104)      

    Affected by climate change and policy factors, Kazakhstan is the country with the most severe ecological degradation and grassland conflicts in Central Asia. Therefore, studying the state of grassland carrying resources in Kazakhstan is particularly important for understanding the responses of grassland ecosystems to climate change and human activities. Based on Kazakhstan's remote sensing data and animal husbandry statistics, this study analyzes the patterns of changes in grassland ecosystems in Kazakhstan based on the supply and consumption of these ecosystems. The results show that: 1) From 2003 to 2017, the number of livestock raised in Kazakhstan showed a trend of sustained and steady growth. Due to freezing damage, the scale of livestock farming decreased in 2011, but a spatial difference in the livestock farming structure was not obvious. 2) The fluctuation of grassland supply in Kazakhstan has increased, while the consumption due to animal husbandry has also continued to increase, resulting in an increasing pressure on the grassland carrying capacity. 3) Between 2003 and 2017, the overall grassland carrying status of Kazakhstan have been abundant, but the grassland carrying pressure index has shown a steadily increasing trend, the grassland carrying pressure is growing, and it is mainly determined by grassland productivity. The greater pressure in lower Kyzylorda state, the southern Kazakhstan state of the cultivated land and the northern Kazakhstan state has gradually expanded to include the agro-pastoral zone and the semi-desert zone.

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    Estimation of Grassland Production in Central and Eastern Mongolia from 2006 to 2015 via Remote Sensing
    LI Ge, WANG Juanle, WANG Yanjie, WEI Haishuo
    Journal of Resources and Ecology    2019, 10 (6): 676-684.   DOI: 10.5814/j.issn.1674-764X.2019.06.013
    Abstract329)   HTML3)    PDF (1791KB)(65)      

    Mongolia is an important part of the Belt and Road Initiative “China-Mongolia-Russia Economic Corridor” and a region that has been severely affected by global climate change. Changes in grassland production have had a profound impact on the sustainable development of the region. Our study explored an optimal model for estimating grassland production in Mongolia and discovered its temporal and spatial distributions. Three estimation models were established using a statistical analysis method based on EVI, MSAVI, NDVI, and PsnNet from Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing data and measured data. A model evaluation and accuracy comparison showed that an exponential model based on MSAVI was the best simulation (model accuracy 78%). This was selected to estimate the grassland production in central and eastern Mongolia from 2006 to 2015. The results show that the grassland production in the study area had a significantly fluctuating trend for the decade study; a slight overall increasing trend was observed. For the first five years, the grassland production decreased slowly, whereas in the latter five years, significant fluctuations were observed. The grassland production (per unit yield) gradually increased from the southwest to northeast. In most provinces of the study area, the production was above 1000 kg ha -1, with the largest production in Hentiy, at 3944.35 kg ha -1. The grassland production (total yield) varied greatly among the provinces, with Kent showing the highest production, 2341.76×10 4 t. Results also indicate that the trend in grassland production along the China-Mongolia railway was generally consistent with that of the six provinces studied.

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    Measuring the Effect of Foreign Direct Investment on CO 2 Emissions in Laos
    XIONG Chenran, WANG Limao, YANG Chengjia, QU Qiushi, XIANG Ning
    Journal of Resources and Ecology    2019, 10 (6): 685-691.   DOI: 10.5814/j.issn.1674-764X.2019.06.014
    Abstract280)   HTML2)    PDF (450KB)(109)      

    This paper aims to explore the determinants of CO2 emissions in Laos by accounting for the significant role played by foreign direct investment (FDI) in influencing CO2 emissions during the period 1990-2017. We apply a Johansen co-integration testing approach to investigate the presence of co-integration, and the empirical findings underscore the presence of a long-run co-integration relationship between CO2 emissions, FDI, per capita GDP, and industrial structure. We also employ an error-correcting model to examine the short-term dynamic effect of FDI on CO2 emissions. The empirical results show that FDI has a significant short-term dynamic effect on changes in CO2 emissions, indicating that the relationship between FDI and CO2 emissions is an inverted U-shaped curve. This is a validation of the EKC. Changes of FDI, per capita GDP, and industrial structure increase CO2 emissions. Based on the analysis results, this paper puts forward policy suggestions emphasizing the need for both Laotian policymakers and Chinese investors to improve eco-environmental quality.

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