| Literature DB >> 35886349 |
Yiting Zhu1, Xueru Pang1, Chunshan Zhou1,2, Xiong He2.
Abstract
The rapid economic growth of geoparks has put pressure on their ecological environments. Therefore, to ensure the sustainable development of geoparks, we must explore the coupling relationship between their socioeconomic benefits (SEBs) and eco-environmental benefits (EEBs). Based on coupling coordination theory and using statistical data from 2005 to 2018, in this study, we aimed to establish an indicator system for evaluating the coupling coordination degree (CCD) between the SEBs and EEBs of the Koktokay Global Geopark in China, which is both theoretically and practically relevant for research on the sustainable development of geoparks. As a result, we found the following: First, the comprehensive development level of the SEBs of the Koktokay Global Geopark showed a fluctuating upward trend during the study period. Second, the comprehensive development level of the EEBs of the geopark remained stable but fluctuated slightly: it declined from 2009 to 2012, affected by the deterioration of the eco-environment, and fell to its lowest point in 2012. By strengthening the protection of the eco-environment of geoparks, the EEBs gradually improved and became stable. Finally, we found that the CCD between the SEBs and EEBs of the Koktokay Global Geopark improved from mildly disordered to basically coordinated, indicating that the CCD is developing toward an increasingly higher level. The purpose of this study was to promote the reasonable development of geotourism while focusing on a sound eco-environment and to provide recommendations for the sustainable development of the Koktokay Global Geopark and a reference for the development of other similar geoparks.Entities:
Keywords: Koktokay Global Geopark; coupling coordination degree; eco-environmental benefits; socioeconomic benefits
Mesh:
Year: 2022 PMID: 35886349 PMCID: PMC9317884 DOI: 10.3390/ijerph19148498
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 4.614
Figure 1Map of Koktokay Global Geopark showing geological and heritage resources and elevation changes, indicating its location within northwestern China.
Figure 2The representative scenic spots of the Koktokay Global Geopark. (a) Eremu Lake; (b) Cocosuri; (c) the No. 3 Mine Pit; (d) Betula forest; (e,f) Shenzhong Canyon.
Figure 3Complex system of SEBs and EEBs of Global Geoparks.
The indicator system of SEBs and EEBs.
| Subsystem | First-Level Indicator | Second-Level Indicator | Type |
|---|---|---|---|
| SEB system | Tourism development A1 | Total tourism revenue A11 | + |
| Number of residents participating in tourism development A12 | + | ||
| Local economic development A2 | Engel coefficient of residents A21 | − | |
| Investment in planning and construction projects A22 | + | ||
| Per capita disposable income A23 | + | ||
| Transformation of scientific research achievements A24 | + | ||
| Popularizing geoscience knowledge A3 | Number of popularization activities of geoscience knowledge A31 | + | |
| EEB system | Environmental protection B1 | Water cleanliness B11 | + |
| Degree of air cleanliness B12 | + | ||
| Noise level B13 | − | ||
| Per capita water resources B14 | + | ||
| Ecological protection B2 | Species richness B21 | + | |
| Forest coverage rate B22 | + | ||
| Landscape protection B3 | Landscape fragmentation B31 | − |
Note: “+” indicates a positive indicator; “−” indicates a negative indicator.
Information entropy and weight of each indicator of SEBs.
| Year | A1 (0.0316) | A2 (0.0434) | A3 (0.0122) | ||||
|---|---|---|---|---|---|---|---|
| A11 | A12 | A21 | A22 | A23 | A24 | ||
| 2005 | 0.0229 | 0.0000 | 0.0362 | 0.0323 | 0.0031 | 0.0000 | 0.0000 |
| 2006 | 0.0163 | 0.0000 | 0.0371 | 0.0203 | 0.0029 | 0.0060 | 0.0000 |
| 2007 | 0.0248 | 0.0000 | 0.0375 | 0.0236 | 0.0033 | 0.0109 | 0.0000 |
| 2008 | 0.0202 | 0.0000 | 0.0283 | 0.0184 | 0.0035 | 0.0308 | 0.0003 |
| 2009 | 0.0261 | 0.0031 | 0.0317 | 0.0205 | 0.0031 | 0.1327 | 0.0005 |
| 2010 | 0.0183 | 0.0000 | 0.0238 | 0.0176 | 0.0041 | 0.0217 | 0.0004 |
| 2011 | 0.0287 | 0.0104 | 0.0204 | 0.0146 | 0.0051 | 0.1149 | 0.0026 |
| 2012 | 0.0161 | 0.1275 | 0.0316 | 0.0155 | 0.0059 | 0.1325 | 0.0135 |
| 2013 | 0.0218 | 0.0036 | 0.0274 | 0.0304 | 0.0051 | 0.1475 | 0.0108 |
| 2014 | 0.0676 | 0.0310 | 0.0251 | 0.0185 | 0.0043 | 0.1155 | 0.0232 |
| 2015 | 0.0318 | 0.0290 | 0.0284 | 0.0244 | 0.0052 | 0.2283 | 0.0183 |
| 2016 | 0.0612 | 0.0349 | 0.0241 | 0.0296 | 0.0073 | 0.2010 | 0.0308 |
| 2017 | 0.0915 | 0.0361 | 0.0221 | 0.0282 | 0.0064 | 0.2134 | 0.0347 |
| 2018 | 0.1242 | 0.0384 | 0.0236 | 0.1104 | 0.0069 | 0.2078 | 0.0358 |
|
| 0.2937 | 0.1614 | 0.2042 | 0.2078 | 0.0340 | 0.8033 | 0.0878 |
|
| 0.1312 | 0.1558 | 0.1478 | 0.1472 | 0.1795 | 0.0365 | 0.1695 |
Information entropy and weight of each indicator of EEBs.
| Year | B1 (0.0450) | B2 (0.0057) | B3 (0.0273) | ||||
|---|---|---|---|---|---|---|---|
| B11 | B12 | B13 | B14 | B21 | B22 | ||
| 2005 | 0.0608 | 0.0039 | 0.0302 | 0.0202 | 0.0042 | 0.0073 | 0.0260 |
| 2006 | 0.0614 | 0.0042 | 0.0308 | 0.0192 | 0.0042 | 0.0080 | 0.0262 |
| 2007 | 0.0687 | 0.0055 | 0.0316 | 0.0247 | 0.0039 | 0.0076 | 0.0285 |
| 2008 | 0.0684 | 0.0054 | 0.0296 | 0.0166 | 0.0044 | 0.0070 | 0.0281 |
| 2009 | 0.0501 | 0.0068 | 0.0304 | 0.0239 | 0.0043 | 0.0070 | 0.0270 |
| 2010 | 0.0473 | 0.0073 | 0.0314 | 0.0263 | 0.0037 | 0.0069 | 0.0278 |
| 2011 | 0.0515 | 0.0113 | 0.0321 | 0.0460 | 0.0037 | 0.0067 | 0.0261 |
| 2012 | 0.0460 | 0.0253 | 0.0308 | 0.0348 | 0.0038 | 0.0070 | 0.0296 |
| 2013 | 0.0629 | 0.0476 | 0.3029 | 0.0616 | 0.0043 | 0.0068 | 0.0280 |
| 2014 | 0.0490 | 0.0236 | 0.0285 | 0.1105 | 0.0042 | 0.0068 | 0.0266 |
| 2015 | 0.0478 | 0.0192 | 0.0307 | 0.1134 | 0.0039 | 0.0070 | 0.0278 |
| 2016 | 0.0419 | 0.0201 | 0.0314 | 0.0701 | 0.0044 | 0.0070 | 0.0262 |
| 2017 | 0.0483 | 0.0337 | 0.0297 | 0.1362 | 0.0044 | 0.0074 | 0.0273 |
| 2018 | 0.0507 | 0.0413 | 0.0310 | 0.1078 | 0.0043 | 0.0081 | 0.0264 |
|
| 0.3880 | 0.1312 | 0.3603 | 0.4170 | 0.0297 | 0.0517 | 0.1961 |
|
| 0.1137 | 0.1614 | 0.1188 | 0.1083 | 0.1802 | 0.1762 | 0.1493 |
Classification of CCD of SEBs and EEBs systems of geoparks.
| Category | CCD | Subclass | Type | Characteristic |
|---|---|---|---|---|
| Disorder | 0.00–0.09 | Extreme disorder | Extreme disorder with EEBs lagging | |
| Extreme disorder with SEBs and EEBs synchronized | ||||
| Extreme disorder with SEBs lagging | ||||
| 0.1–0.19 | Serious disorder | Serious disorder with EEBs lagging | ||
| Serious disorder with SEBs and EEBs synchronized | ||||
| Serious disorder with SEBs lagging | ||||
| 0.2–0.29 | Moderate disorder | Moderate disorder with EEBs lagging | ||
| Moderate disorder with SEBs and EEBs synchronized | ||||
| Moderate disorder with SEBs lagging | ||||
| 0.3–0.39 | Mild disorder | Mild disorder with EEBs lagging | ||
| Mild disorder with SEBs and EEBs synchronized | ||||
| Mild disorder with SEBs lagging | ||||
| 0.4–0.49 | Near disorder | Near disorder with EEBs lagging | ||
| Near disorder with SEBs and EEBs synchronized | ||||
| Near disorder with SEBs lagging | ||||
| Coordination | 0.5–0.59 | Bare coordination | Bare coordination with EEBs lagging | |
| Bare coordination with SEBs and EEBs synchronized | ||||
| Bare coordination with SEBs lagging | ||||
| 0.6–0.69 | Primary coordination | Primary coordination with EEBs lagging | ||
| Primary coordination with SEBs and EEBs synchronized | ||||
| Primary coordination with SEBs lagging | ||||
| 0.7–0.79 | Intermediate coordination | Intermediate coordination with EEBs lagging | ||
| Intermediate coordination with SEBs and EEBs synchronized | ||||
| Intermediate coordination with SEBs lagging | ||||
| 0.8–0.89 | Good coordination | Good coordination with EEBs lagging | ||
| Good coordination with SEBs and EEBs synchronized | ||||
| Good coordination with SEBs lagging | ||||
| 0.9–1.00 | High-quality coordination | High-quality coordination with EEBs lagging | ||
| High-quality coordination with SEBs and EEBs synchronized | ||||
| High-quality coordination with SEBs lagging |
Figure 4Evolution of comprehensive evaluation index of SEBs and EEBs of Koktokay Global Geopark from 2005 to 2018.
CCD of the SEBs and EEBs systems for the Koktokay Global Geopark from 2005 to 2018.
| Year |
|
|
| Type | Characteristic | ||
|---|---|---|---|---|---|---|---|
| 2005 | 0.1989 | 0.3081 | 0.5739 | 0.2535 | 0.3814 | Mild disorder with SEBs lagging | |
| 2006 | 0.2350 | 0.3182 | 0.5790 | 0.2766 | 0.4002 | Near disorder with SEBs lagging | |
| 2007 | 0.2912 | 0.3036 | 0.5107 | 0.2974 | 0.3897 | Mild disorder with SEBs lagging | |
| 2008 | 0.4590 | 0.3240 | 0.5504 | 0.3915 | 0.4642 | Near disorder with EEBs lagging | |
| 2009 | 0.4170 | 0.3023 | 0.5696 | 0.3596 | 0.4526 | Near disorder with EEBs lagging | |
| 2010 | 0.4906 | 0.2438 | 0.5151 | 0.3672 | 0.4349 | Near disorder with EEBs lagging | |
| 2011 | 0.5317 | 0.2453 | 0.5061 | 0.3885 | 0.4434 | Near disorder with EEBs lagging | |
| 2012 | 0.5698 | 0.2119 | 0.4868 | 0.3909 | 0.4362 | Near disorder with EEBs lagging | |
| 2013 | 0.5406 | 0.2618 | 0.5323 | 0.4012 | 0.4621 | Near disorder with EEBs lagging | |
| 2014 | 0.5460 | 0.3191 | 0.5722 | 0.4326 | 0.4975 | Near disorder with EEBs lagging | |
| 2015 | 0.6074 | 0.3045 | 0.5474 | 0.4559 | 0.4996 | Near disorder with EEBs lagging | |
| 2016 | 0.6134 | 0.3691 | 0.5874 | 0.4913 | 0.5372 | Bare coordination with EEBs lagging | |
| 2017 | 0.6439 | 0.3210 | 0.5986 | 0.4824 | 0.5374 | Bare coordination with EEBs lagging | |
| 2018 | 0.6645 | 0.3219 | 0.5378 | 0.4932 | 0.5150 | Bare coordination with EEBs lagging |
Figure 5Evolving curve of the CCD of the SEBs and EEBs systems for the Koktokay Global Geopark from 2005 to 2018.
Figure 6CCD type between the SEBs and EEBs systems of Koktokay Global Geopark.