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Analyzing the sustainable development of a given region can provide an important reference and guide for future orientation. The study selects Turpan (including Gaochang District, Shanshan County, and Toksun County) in Xinjiang Uygur Autonomous Region of Northwest China as the study area and first investigates the essence of regional sustainable development. Based on the relevant data of the population, economy, and environment of Turpan from 2002 to 2018, we constructed an evaluation index system for three dimensions, namely, the population, economy, and environment, and analyzed them systematically. Specifically, we quantitatively calculated the comprehensive evaluation index, coupling degree, and coupling coordination degree of the sustainable development system of the study area. The study finds that Turpan has on some dimensions become increasingly sustainable, especially the economic development level has improved. The results show that the coupling coordination degree has increased from 0.3692 to 0.8894 during the period 2002–2018, which reflects the actual situation of Turpan and indicates that the proposed analysis method can effectively measure and evaluate the level of sustainable development in this region. Moreover, the study also puts forward main functional zoning of Turpan (i.e., Gaochang District as an optimized development zone, Shanshan County as a major agricultural production zone, and Toksun County as a key ecological function zone) and regional planning principles based on the population, economic, and environmental coupling analysis for the three jurisdictions in Turpan.
The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers.