Progress toward Sustainable Development Goals and interlinkages between them in Arctic countries.

The adoption of the 2030 Agenda and its 17 Sustainable Development Goals (SDGs) contribute to addressing the multiple and complex challenges faced by humankind. In particular, the increasing impact of climate change and globalization represent a great challenge for the sustainable development of Arctic countries and efforts are needed to measure, assess, and compare the progress toward SDGs and the trends in this region. This study used 69 indicators closely related to Arctic countries and a composite indicator approach to assess their sustainability performance. SDG interlinkages were also assessed through Spearman's rank order correlation. The results showed that the sustainable development of Arctic countries gradually improved from 2000 to 2020, with increasing scores recorded for 82% of the goals and 73% of the indicators. Overall, significant progress was observed in the SDG 10 (reduction of inequality), SDG 3 (health improvement), and SDG 4 (quality of education). The highest-ranking scores were obtained for poverty reduction (SDG 1), SDG 3, and climate actions (SDG 13) in 2020. Over the 21-year period, Sweden reached the highest overall score for sustainable development, and Russia showed the greatest improvement. Synergies dominated over trade-offs among and within SDGs. SDGs 1, 3, 9, 10, and 11 presented a relatively higher proportion of synergies, while higher proportions of trade-offs were observed for the 8-9, 8-11, 3-12, and 10-12 SDG pairs. The associations of industry development with clean energy use and environmental conservation were strengthened during the study period. However, the performance varied greatly for different indicators, goals, and their correlations among Arctic countries. The results indicate that the main challenges for these countries in relation to SDGs consist in promoting an inclusive economic model as well as sustainable consumption and production patterns.

Spatial quantification method of grassland utilization intensity on the Qinghai-Tibetan Plateau: A case study on the Selinco basin.

Existing methods for spatial quantification of grassland utilization intensity cannot meet the demand for accurate detection of the spatial distribution of grassland utilization intensity in the Qinghai-Tibetan Plateau with high spatial resolution. In this paper, a method based on remote-sensing observations and simulations of grassland growth dynamics is proposed. The grassland enhanced vegetation index (EVI) time-series curve during the growing season characterizes the growth of grassland in the corresponding pixel; The deviation between the observed and potential EVI curves indicates the disturbance on grassland growth imposed by human activities, and it can characterize the grassland utilization intensity during the growing season. Based on the main idea described above, absolute and relative disturbances are calculated and used as quantitative indicators of grassland utilization intensity defined from different perspectives. Livestock amount at the pixel scale is obtained by pixel-by-pixel calculations based on the function relationship at the township scale between absolute disturbance and livestock density, which is specific quantitative indicator that considers the mode of grassland utilization. In simulating the potential EVI of grassland, the lag and accumulation effects of meteorological factors are investigated at the daily scale using a multi-objective genetic algorithm. Further, the nonlinear functions between multiple environmental factors (e.g., grassland type, topography, soil, meteorology) and the grassland EVI are established using an error back-propagation feedforward artificial neural network (ANN-BP) with parameter optimization. Finally, the potential EVIs of all grassland pixels are simulated on the basis of this model. The method is applied to the Selinco basin on the Qinghai-Tibetan Plateau and validated by examining the spatial consistency of the results with township-scale livestock density and grazing pressure. The final results indicate that the proposed method can accurately detect the spatial distribution of grassland utilization intensity which is appliable in the similar regions.

The constraints and driving forces of oasis development in arid region: a case study of the Hexi Corridor in northwest China.

The oasis, a special landscape with the integration of nature and humanity in the arid region, has undergone an enormous transformation during the past decades. To gain a better understanding of the tradeoff between economic growth and oases stability in the arid land, we took the oases in the Hexi Corridor as a case to explore the constraints of oases development and the driving factors of oases expansion. The dynamic changes and spatial distribution patterns underwent by the oases were examined using multispectral remote sensing imagery. The constraints of oasis development in arid land were investigated by the grid-transformed model, as well as the index system of driving forces was analyzed using the grey incidence model based on the data from statistics yearbooks. The oasis area in the Hexi Corridor had tremendous changes expanded 40% from 1986 to 2015, the stable oasis area was 9062 km2, while the maximum area reached 16,374 km2. The constraints for oases of topography, hydrology and heat condition are as follow: The elevation of oasis ranged from 1000 to 1800 m, peaked in 1500 m; the slope of oasis distribution was flatter than 3 degrees; the aspect of oases on slope land concentrated in northeast and north, accounting for more than 60%. The main driving forces of oasis spatial expansion in the arid region were population, water resource, economy, policies, and other factors. These results are expected to (1) improve the rationality of oasis development, and (2) promote the sustainable planning and management of oases in the arid land.