Analysis on spatial distribution characteristics and geographical factors of Chinese National Geoparks

Abstract

This study presents the Pearson correlation analyses of the various factors influencing the Chinese NationalGeoparks. The aim of this contribution is to offer insights on the Chinese National Geoparks by describing its relations with geoheritage and their intrinsic linkages with geological, climatic controls. The results suggest that: 1) Geomorphologic landscape and palaeontology National Geoparks contribute to 81.65% of Chinese National Geoparks.2) The NNI of geoparks is 0.97 and it belongs to causal distributional patternwhose regional distributional characteristics may be best characterized as 'dispersion in overall and aggregation in local'. 3) Spatial distribution of National Geoparks is wide. The geographic imbalance in their distribution across regions and types of National Geoparks is obvious, with 13 clustered belts, including Tianshan-Altaishan Mountain, Lesser HiggnanChangbai, Western Bohai Sea,Taihangshan Mountain, Shandong, Qilianshan-Qinling Mountain, Annulus Tibetan Plateau, Dabashan Mountain, Dabieshan Mountain, Chongqing-Western Hunan, Nanling Mountain, Wuyishan Mountain, Southeastern Coastal, of which the National Geoparks number is 180, accounting for 82.57%. 4) Spatial distribution of National Geoparks coincide with latitudinal tectonic zone and longitude tectonic zone of geological structure features, which is consistent with the areas around the Pacific Rim of volcanic tectonic zones. The coupling relationships are obvious between the spatial distributional pattern and the natural and geological conditions.

Factors affecting distribution patterns of organic carbon in sediments at regional and national scales in China

“…(2013) and Wang et al . (2014) 16 , 74 , were involved to analyze OC storage in this study. The significant different OC distribution across among precipitation regions and the non-significant OC distribution across the sampled four wetlands suggested that precipitation is one important factor affecting carbon storage in large scale.…”

“…2 . In addition, data on precipitations, climate zones and land-sea differences were also obtained to assess the distribution trend of OC across China 16 .…”

“…At large scale, Mitsch et al . (2014) reported that tropical wetlands have significantly higher OC than boreal wetlands 15 , and variation in precipitation, climate and landscape can also influence the C distribution and storage 16 , 17 . Therefore, the regional and large-scale factors such like wetland types, soil depths, seasons, climate and precipitation, etc.…”

Geoparks and Geotourism in China: A Sustainable Approach to Geoheritage Conservation and Local Development—A Review

“…Zouros and Martini (2001) studied the relationship between European geoparks, geoconservation, geotourism and the sustainable development of the local economy [10]. Some scholars in China consider related studies on geoheritage and geoparks as important [73][74][75][76][77]. These authors have attempted to extend such studies to include the geological background of national geoparks [75][76][77][78], geoheritage assessment [79][80][81][82], geoconservation [83][84][85][86], geoheritage development [86][87][88], relationship between geoheritage conservation and economic development [89][90][91][92][93][94], and the sustainable development of geoparks [95][96][97][98].…”

Spatial distribution characteristics of national protected areas in China

“…Previous studies have largely focused on specific areas, and the few national-level studies have focused on overall policy, legal system, or international experience, rather than spatial perspectives. The studies have concentrated on national wetland parks (Duan et al, 2017), forest parks (Luo et al, 2016), scenic spots (Notar, 2010), geological parks (Wang et al, 2014), nature areas (Liu, 2008), water recreation areas (Qiu et al, 2009); and A-grade tourist attractions (Pan et al, 2015), only occasionally comparing distribution characteristics of national parks. The methods mainly included rank methods, spatial autocorrelation, point pattern analysis, hot clustering, and fractal methods, but rarely combined natural and cultural regionalization with NPAs.…”