Quantifying the human disturbance intensity of ecosystems and its natural and socioeconomic driving factors in urban agglomeration in South China

Author(s):  
Xiaojun Wang ◽  
Guangxu Liu ◽  
Aicun Xiang ◽  
Salman Qureshi ◽  
Tianhang Li ◽  
...  
Author(s):  
Xiaoyan Sun ◽  
Yali Luo ◽  
Xiaoyu Gao ◽  
Mengwen Wu ◽  
Mingxin Li ◽  
...  

AbstractIn this study, high-resolution surface and radar observations are used to analyze 24 localized extreme hourly rainfall (EXHR, > 60mm/h) events with strong urban heat island (UHI) effects over the Great Bay Area (GBA) in South China during 2011-2016 warm seasons. Quasi-idealized, convection-permitting ensemble simulations driven by diurnally varying lateral boundary conditions, which are extracted from the composite global analysis of 3-5 June 2013, are then conducted with a multi-layer urban canopy model to unravel the influences of the UHI and various surface properties nearby on the EXHR generation in a complex geographical environment with sea-land contrast, topography, and vegetation variation. Results show that EXHR is mostly distributed over the urban agglomeration and within about 40 km on its downwind side, and produced during the afternoon-to-evening hours by short-lived meso-γ to β-scale storms. On the EXHR days, the GBA is featured by a weak-gradient environment with abundant moisture, and a weak southwesterly flow prevailing in the boundary layer (BL). The UHI effects lead to the development of a deep mixed layer with “warm bubbles” over the urban agglomeration, in which the lower-BL convergence and BL-top divergence is developed, assisting in convective initiation. Such urban BL processes and associated convective development with moisture supply by the synoptic low-level southwesterly flow are enhanced by orographically increased horizontal winds and sea breezes under the influence of the herringbone coastline, thereby increasing the inhomogeneity and intensity of rainfall production over the “Π-shaped” urban clusters. Vegetation variations are not found to be an important factor in determining the EXHR production over the region.


2018 ◽  
Vol 10 (9) ◽  
pp. 3346 ◽  
Author(s):  
Xianzhe Zhang ◽  
Yanming Chen ◽  
Manchun Li

Studying the geospatial association within the urban agglomeration around the South China Sea can provide a basis for understanding the internal development of the China-Association of Southeast Asian Nations (ASEAN) Free Trade Area (CAFTA) and provide ideas for promoting economic and trade cooperation among cities in the region. The purpose of this paper was to reflect the characteristics of the urban agglomeration association network based on big traffic data. Based on trajectory data mining and complex network analysis methods, the automatic identification system (AIS) data was used to construct the traffic flow association network of the urban agglomeration around the South China Sea and then analysis and evaluation were carried out in three aspects: Spatial distribution characteristics of marine traffic flow, analysis of spatial hierarchy and internal difference analysis of the urban agglomeration. The results show the following: (1) The distribution of marine traffic flow within the urban agglomeration around the South China Sea is characterized by polarization and localization and shows a specific power-law distribution; (2) there is a close relationship within the urban agglomeration and the core urban and the marginal urban agglomerations were apparent; (3) subgroup division of urban agglomeration around the South China Sea shows an evident geographic agglomeration phenomenon and there were significant differences between the level of economic development among subgroups; and (4) relative to static factors such as population size and economic aggregate, dynamic flow of information and capital traffic flow plays a more important role in the spatial correlation between cities. Strengthening the links among the three layers of core-intermediate-edge cities through trade and investment means enhancing cooperation among cities within the urban agglomeration and ultimately promoting sustainable regional development.


2016 ◽  
Vol 36 (6) ◽  
Author(s):  
王军星 WANG Junxing ◽  
谭烨辉 TAN Yehui ◽  
黄良民 HUANG Liangmin ◽  
柯志新 KE Zhixin ◽  
周林滨 ZHOU Linbin

2020 ◽  
Vol 256 ◽  
pp. 120692 ◽  
Author(s):  
Chao Cheng ◽  
Yaolin Liu ◽  
Yanfang Liu ◽  
Renfei Yang ◽  
Yongsheng Hong ◽  
...  

2019 ◽  
Vol 11 (23) ◽  
pp. 6623 ◽  
Author(s):  
Peng ◽  
Huang ◽  
Elahi ◽  
Wei

The vulnerability of ecological environment threatens social and economic development. Recent studies failed to reveal the driving mechanism behind it, and there is little analysis on the spatial clustering characteristics of the vulnerability of urban agglomerations. Therefore, this article estimates ecological environment vulnerability in 2005, 2011, and 2017, determines Moran Index (MI) with spatial autocorrelation model, analyzes the spatial-temporal difference characteristics of ecological environment vulnerability of Yangtze River Urban Agglomeration and the spatial aggregation effect, and discusses its driving factors. The study results estimate that the overall vulnerability index of the Yangtze River Urban Agglomeration is in a mild fragile state. However, most fragile and slightly fragile cities are developing in the direction of moderate to severe vulnerability. The spatial agglomeration effect of the ecological environment vulnerability of the Yangtze River Urban Agglomeration is not obvious, and the effect of mutual ecological environment influence among cities is not obvious. Moreover, the driving factors of ecological environment vulnerability of Yangtze River city group changed from natural factors to social economic factors and then to policy factors. It is necessary to develop an ecological economy, coordinate the spatial agglomeration of urban agglomerations, and make balance the internal differences of urban agglomerations.


2021 ◽  
Author(s):  
Sindre Eftestøl ◽  
Diress Tsegaye ◽  
Kjetil Flydal ◽  
Jonathan E. Colman

Abstract Context Within Rangifer ranges, many studies focus on expanding infrastructure and human activity negatively influencing habitat use. Little documentation exists on how disturbances act in synergy (i.e. cumulative effects), nor methods to test such effects. Objectives (1) Investigate how cumulative disturbance at different distances affects reindeer habitat use and (2) at what disturbance levels and distances loss of habitat functionality occurs. Methods Disturbance intensity levels for trails and infrastructure were based on expected amount of human activity, on a scale from 1 to 6. To test cumulative disturbance, we adapted the multi-grain method and summed-up disturbance intensity levels within “disturbance distance intervals” (0–0.25, 0.25–1, 1–2 km, etc. instead of 0–0.25, 0–1, 0–2 km, etc.), and tested reindeers’ avoidance using GPS data for 2011–2018. Results We found decreased habitat use within 0.25 km with increasing cumulative disturbance for snow free and winter seasons. For spring, a similar effect occurred up to 1 km. Reductions in use in areas with highest cumulative disturbance within these zones were between 92 and 98%. Strongest avoidance during spring supports previous studies. Comparatively, the multi-grain approach showed negative effects up to 3 km. Conclusions Our approach provides novel results and precisely estimates where cumulative effects actually occur. Reindeer in our study tolerate low intensities of human disturbance, while further increase in disturbance intensity reduces habitat functionality. We suggest clustering future human developments within areas of high disturbance, i.e. where functional habitat use is already lost or highly reduced. Our method can be used for other areas and species.


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