This paper investigates the sandy desertification change between 1986 and 2000 in the western Jilin province, North China.
Land use and land cover data were obtained from Landsat TM data by using a supervised classification approach. We summarized
the total area of desertified land by each county, as well as the area for each of the four categories of desertified land.
The changes of different types of land use and land cover between 1986 and 2000 were calculated and analyzed. Taking Tongyu
and Qianan as examples, both human and natural driving forces of the sandy desertification were analyzed. Our analyses indicate
that the material sources and windy, warm and dry climate are the immanent causes of potential land desertification, while
the irrational human activities, such as deforestation, reclaiming and grazing in the grassland, are the external causes of
potential land desertification. However, rational human activities, such as planting trees and restoring grassland can reverse
the land desertification process. Furthermore, the countermeasures and suggestions for the sustainable development in ecotone
between agriculture and animal husbandry in North China are put forward. 相似文献
Coastal rivers contributed the majority of anthropogenic nitrogen (N) loads to coastal waters, often resulting in eutrophication and hypoxia zones. Accurate N source identification is critical for optimizing coastal river N pollution control strategies. Based on a 2-year seasonal record of dual stable isotopes (\({\updelta}^{15}\mathrm{N}-{\mathrm{NO}}_3^{\hbox{-} }\) and \({\updelta}^{18}\mathrm{O}-{\mathrm{NO}}_3^{\hbox{-} }\)) and water quality parameters, this study combined the dual stable isotope-based MixSIAR model and the absolute principal component score-multiple linear regression (APCS-MLR) model to elucidate N dynamics and sources in two coastal rivers of Hangzhou Bay. Water quality/trophic level indices indicated light-to-moderate eutrophication status for the studied rivers. Spatio-temporal variability of water quality was associated with seasonal agricultural, aquaculture, and domestic activities, as well as the seasonal precipitation pattern. The APCS-MLR model identified soil + domestic wastewater (69.5%) and aquaculture tailwater (22.2%) as the major nitrogen pollution sources. The dual stable isotope-based MixSIAR model identified soil N, aquaculture tailwater, domestic wastewater, and atmospheric deposition N contributions of 35.3 ±21.1%, 29.7 ±17.2%, 27.9 ±14.5%, and 7.2 ±11.4% to riverine \({\mathrm{NO}}_3^{\hbox{-} }\) in the Cao’e River (CER) and 34.4 ±21.3%, 29.5 ±17.2%, 27.4 ±14.7%, and 8.7 ±12.8% in the Jiantang River (JTR), respectively. The APCS-MLR model and the dual stable isotope-based MixSIAR model showed consistent results for riverine N source identification. Combining these two methods for riverine N source identifications effectively distinguished the mix-source components from the APCS-MLR method and alleviated the high cost of stable isotope analysis, thereby providing reliable N source apportionment results with low requirements for water quality sampling and isotope analysis costs. This study highlights the importance of soil N management and aquaculture tailwater treatment in coastal river N pollution control.
