Methodology for Mapping the Ecological Security Pattern and Ecological Network in the Arid Region of Xinjiang, China
Abstract
:1. Introduction
2. Data Sources and Research Methods
2.1. Study Area
2.2. Data Sources
2.3. Methods
2.3.1. Construction of Ecological Security Pattern
- (1)
- Habitat quality
- (2)
- Ecosystem service value
- (3)
- Water-soil retention
- (4)
- Construction of a comprehensive ecological security pattern
2.3.2. Construction of Ecological Network
- (1)
- Source identification
- (2)
- Corridor extraction and screening
- (3)
- Identification of ecological nodes
3. Result and Analysis
3.1. Construction of Ecological Security Pattern
3.2. Construction of Ecological Network
3.2.1. Source Identification
3.2.2. Corridor Recognition and Screening
3.2.3. Ecological Node Identification
3.2.4. Results of Ecological Network
4. Discussion
4.1. The Development of Ecological Network Construction in Xinjiang
4.2. Applicability of Research Methods
4.3. Limitations and Prospects
5. Conclusions and Recommendations
- (1)
- The spatial differentiation of the ecological security pattern of a single element is basically consistent with the comprehensive ecological security pattern. The ecological security level of the study area is mainly ecological fringe, and the overall ecological conditions are bad, mostly in a continuous large area of desert, showing very obvious characteristics of arid areas. The ecological land is extremely fragmented and mainly distributed in the mountains and waters which are far away from human activities, with obvious spatial differences and low ecological security level.
- (2)
- The ecological network framework in Xinjiang has the structural characteristics of an uneven distribution of “source”, broken corridor structure, and a low degree of networking. The ecological corridor is spatially oriented from north to south and runs through the whole study area. Based on the prominent contradiction between humans and land, this study combines the regional physical and geographical characteristics and the overall development plan. The ecological space layout system of “7 ecological subsystems, 51 source areas, 87 ecological corridors, and 33 ecological nodes” has been constructed.
- (1)
- Protect the core source area. The core source areas in Xinjiang’s ecological network are mainly composed of forest land and water bodies, and they are concentrated in mountainous areas and large water bodies. The mountainous areas have large terrain undulations and precipitation, and thus often have a greater risk of soil erosion. These areas are closer to the dense areas of human activities. Thus, these ecological networks face a greater risk of destruction. Therefore, proper maintenance of the ecological land around the source area is essential. Management should convert more farmland to forest and grassland, strengthen the protection of existing forest land, and promote tree planting in risk areas. In addition, decision makers should reduce the interference of human activities in the source area by restricting the development of national land space or opening up the edge buffer zone of the source area. Moreover, management should prevent urban sprawl and cultivated land occupation around the ecological source area to improve the landscape conditions of other ecological land, and to artificially cultivate and optimize ecological patches with great potential. By doing so, they should be able to increase the number of potential sources, and, at the same time, promote the improvement of the landscape conditions of existing sources.
- (2)
- Build ecological corridors. The construction of ecological corridors should be divided into different levels and focused. The focus of management and control should be concentrated on the four subsystems on both sides of the Tianshan Mountains. The construction of corridors should make full use of the current land types, and ensure that all sources can be directly or indirectly connected.
- (3)
- Improve the layout of ecological nodes. The current ecological nodes mainly involve maintenance, and the control nodes, such as the ecological stepping-stones at the intersection of corridors or near the source, should be strengthened. The stability should be enhanced by planting drought-tolerant vegetation, expanding the area, and improving the status of land use. The graded ecological stepping-stones adopt different construction strategies, which can be appropriately increased or decreased by judging the economic benefits of node construction.
- (4)
- Regulate the ecological subsystem. From the perspective of the current ecological subsystem, the ecological source areas of Altay, Altun Mountain, and West Kunlun Glacier are far away from the spaces for human activities. So, the risk of damage is low. Since other ecological source areas are clustered around the human activity space with a greater risk of damage, they must be protected. Different administrative strategies should be adopted to realize the linkage between different ecological source areas. For example, the Altay ecological source area is mainly forestland, so it is necessary to pay attention to water and soil conservation and strengthen the stability of the forest ecosystem through vegetation restoration and controlled development. The Bosten Lake ecological source area is dominated by large water bodies, so attention should be paid to water source protection and controlled agricultural irrigation. In terms of ecological network governance, Yin et al. [77] conducted in-depth research on the status quo of the ecological network in Hunan Province from the perspective of territorial and spatial planning and provincial cooperation. Gu et al. [78] put forward the supervision of ecological element cybernetics theory for the ecological network of nature reserves in Fujian Province. In actual ecological management, we must fully consider the regional ecological background and ecological needs and then formulate targeted protection strategies.
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Li, H.; Chen, W.; He, W. Planning of Green Space Ecological Network in Urban Areas: An Example of Nanchang, China. Int. J. Environ. Res. Public Health 2015, 12, 12889–12904. [Google Scholar] [CrossRef] [PubMed]
- Su, Y.; Chen, X.; Liao, J.; Zhang, H.; Wang, C.; Ye, Y.; Wang, Y. Modeling the optimal ecological security pattern for guiding the urban constructed land expansions. Urban For. Urban Green. 2016, 19, 35–46. [Google Scholar] [CrossRef]
- Baloch, M.A.; Zhang, J.J.; Iqbal, K.; Iqbal, Z. The effect of financial development on ecological footprint in BRI countries: Evidence from panel data estimation. Environ. Sci. Pollut. Res. 2019, 26, 6199–6208. [Google Scholar] [CrossRef] [PubMed]
- Pravalie, R.; Bandoc, G.; Patriche, C.; Sternberg, T. Recent changes in global drylands: Evidences from two major aridity databases. Catena 2019, 178, 209–231. [Google Scholar] [CrossRef]
- Zhang, Y.; Yang, Z.; Yu, X. Ecological network and energy analysis of urban metabolic systems: Model development, and a case study of four Chinese cities. Ecol. Model. 2009, 220, 1431–1442. [Google Scholar] [CrossRef]
- Wu, Y.; Han, Z.; Meng, J.; Zhu, L. Circuit theory-based ecological security pattern could promote ecological protection in the Heihe River Basin of China. Environ. Sci. Pollut. Res. 2022, 30, 27340–27356. [Google Scholar] [CrossRef]
- Peng, J.; Pan, Y.; Liu, Y.; Zhao, H.; Wang, Y. Linking ecological degradation risk to identify ecological security patterns in a rapidly urbanizing landscape. Habitat Int. 2018, 71, 110–124. [Google Scholar] [CrossRef]
- Chen, J.; Wang, S.; Zou, Y. Construction of an ecological security pattern based on ecosystem sensitivity and the importance of ecological services: A case study of the Guanzhong Plain urban agglomeration, China. Ecol. Indic. 2022, 136, 108688. [Google Scholar] [CrossRef]
- Saura, S.; Pascual-Hortal, L. A new habitat availability index to integrate connectivity in landscape conservation planning: Comparison with existing indices and application to a case study. Landsc. Urban Plan. 2007, 83, 91–103. [Google Scholar] [CrossRef]
- Ma, L.; Bo, J.; Li, X.; Fang, F.; Cheng, W. Identifying key landscape pattern indices influencing the ecological security of inland river basin: The middle and lower reaches of Shule River Basin as an example. Sci. Total Environ. 2019, 674, 424–438. [Google Scholar] [CrossRef]
- Zhang, C.; Jia, C.; Gao, H.; Shen, S. Ecological Security Pattern Construction in Hilly Areas Based on SPCA and MCR: A Case Study of Nanchong City, China. Sustainability 2022, 14, 11368. [Google Scholar] [CrossRef]
- Liu, S.H.; Wang, D.Y.; Li, H.; Li, W.B.; Wu, W.J.; Zhu, Y.L. The Ecological Security Pattern and Its Constraint on Urban Expansion of a Black Soil Farming Area in Northeast China. ISPRS Int. J. Geo-Inf. 2017, 6, 263. [Google Scholar] [CrossRef]
- Peng, J.; Yang, Y.; Liu, Y.; Hu, Y.N.; Du, Y.; Meersmans, J.; Qiu, S.J. Linking ecosystem services and circuit theory to identify ecological security patterns. Sci. Total Environ. 2018, 644, 781–790. [Google Scholar] [CrossRef]
- Li, Y.; Zhao, J.; Yuan, J.; Ji, P.; Deng, X.; Yang, Y. Constructing the Ecological Security Pattern of Nujiang Prefecture Based on the Framework of “Importance-Sensitivity-Connectivity”. Int. J. Environ. Res. Public Health 2022, 19, 10869. [Google Scholar] [CrossRef]
- Zhang, H.; Li, S.; Liu, Y.; Xu, M. Assessment of the Habitat Quality of Offshore Area in Tongzhou Bay, China: Using Benthic Habitat Suitability and the InVEST Model. Water 2022, 14, 1574. [Google Scholar] [CrossRef]
- Cui, X.; Deng, W.; Yang, J.; Huang, W.; de Vries, W.T. Construction and optimization of ecological security patterns based on social equity perspective: A case study in Wuhan, China. Ecol. Indic. 2022, 136, 108714. [Google Scholar] [CrossRef]
- Sun, H.Y.; Wu, D.D.; Mao, Q.G.; Wei, X.F.; Zhang, H.Q.; Xi, Y.Z. Soil heavy metal pollution and ecological risk assessment in a copper mining area in East Tianshan, Xinjiang. Environ. Chem. 2019, 38, 2690–2699. (In Chinese) [Google Scholar]
- Li, F.; Ye, Y.; Song, B.; Wang, R. Evaluation of urban suitable ecological land based on the minimum cumulative resistance model: A case study from Changzhou, China. Ecol. Model. 2015, 318, 194–203. [Google Scholar] [CrossRef]
- Yilmaz, R.; Yilmaz, O. Determination of the vital ecological networks: The case of European side of Turkey. J. Environ. Prot. Ecol. 2016, 17, 1603–1611. [Google Scholar]
- Loro, M.; Ortega, E.; Arce, R.M.; Geneletti, D. Ecological connectivity analysis to reduce the barrier effect of roads. An innovative graph-theory approach to define wildlife corridors with multiple paths and without bottlenecks. Landsc. Urban Plan. 2015, 139, 149–162. [Google Scholar] [CrossRef]
- Li, J.; Deng, W.; Zhang, J.F. Evaluating Mountain water scarcity on the county scale: A case study of Dongchuan District, Kunming, China. J. Mt. Sci. 2019, 16, 744–754. [Google Scholar] [CrossRef]
- Shi, F.; Liu, S.; Sun, Y.; An, Y.; Zhao, S.; Liu, Y.; Li, M. Ecological network construction of the heterogeneous agro-pastoral areas in the upper Yellow River basin. Agric. Ecosyst. Environ. 2020, 302, 107069. [Google Scholar] [CrossRef]
- Zhu, Z.Y.; Kasimu, A. Spatial-temporal evolution of habitat quality in Yili Valley based on geographical detector and its influencing factors. Chin. J. Ecol. 2020, 39, 3408–3420. [Google Scholar]
- Cook, E.A. Landscape structure indices for assessing urban ecological networks. Landsc. Urban Plan. 2002, 58, 269–280. [Google Scholar] [CrossRef]
- Ulanowicz, R.E. Quantitative methods for ecological network analysis—ScienceDirect. Comput. Biol. Chem. 2004, 28, 321–339. [Google Scholar] [CrossRef] [PubMed]
- Fu, B.J. Chinese ecosystem research network: Progress and perspectives. Ecol. Complex. 2010, 7, 225–233. [Google Scholar] [CrossRef]
- Chen, Y.; Li, B.; Fan, Y.; Sun, C.; Fang, G. Hydrological and water cycle processes of inland river basins in the arid region of Northwest China. J. Arid. Land 2019, 11, 161–179. [Google Scholar] [CrossRef]
- Liu, S.; Xu, L.; Zhang, J. Spatiotemporal change of land ecological security in Xinjiang. Acta Ecol. Sin. 2019, 39, 3871–3884. [Google Scholar]
- Zhang, H.; Zhang, C.; Hu, T.; Zhang, M.; Ren, X.; Hou, L. Exploration of roadway factors and habitat quality using InVEST. Transp. Res. Part D Transp. Environ. 2020, 87, 102551. [Google Scholar] [CrossRef]
- Wang, Y.Y.; Jing, X.P.; Sheng, C.Z.; Bao, G.Y.; Liu, J.; Zhou, Y.G. Study on the Construction of Ecological Security pattern in Eastern developed areas—A case study of Southern Jiangsu. Acta Ecol. Sin. 2019, 7, 1–22. (In Chinese) [Google Scholar]
- Yeernaer, H.; Xu, X.H.; Dilinuer, T. Response of Vegetation Coverage to Climate Change in Altai Mountain Forest and Grassland Ecological Function Area in Xinjiang, China. J. Ecol. Rural. Environ. 2019, 35, 307–315. [Google Scholar]
- You, Y.; Wang, Y.; Lei, J. Xinjiang Uyghur’s local knowledge of ecological protection: The case of water resources protection in Hotan, China. Desalination Water Treat. 2019, 163, 409–414. [Google Scholar] [CrossRef]
- Zhou, Y.; Zhang, Q.N. Impacts of road networks on species migration and landscape connectivity. Chin. J. Appl. Ecol. 2014, 33, 440–446. [Google Scholar]
- Liu, Y.; Hu, W.; Wang, S.; Sun, L. Eco-environmental effects of urban expansion in Xinjiang and the corresponding mechanisms. Eur. J. Remote Sens. 2021, 54, 132–144. [Google Scholar] [CrossRef]
- Ye, X.; Wang, T.; Skidmore, A.K. Spatial pattern of habitat quality modulates population persistence in fragmented landscapes. Ecol. Res. 2013, 28, 949–958. [Google Scholar] [CrossRef]
- Xu, H.; Dong, B.; Gao, X.; Xu, Z.; Ren, C.; Fang, L.; Wei, Z.; Liu, X.; Lu, Z. Habitat quality assessment of wintering migratory birds in Poyang Lake National Nature Reserve based on InVEST model. Environ. Sci. Pollut. Res. 2022, 30, 28847–28862. [Google Scholar] [CrossRef]
- Zhang, J.; Cao, Y.; Ding, F.; Wu, J.; Chang, I.S. Regional Ecological Security Pattern Construction Based on Ecological Barriers: A Case Study of the Bohai Bay Terrestrial Ecosystem. Sustainability 2022, 14, 5384. [Google Scholar] [CrossRef]
- Chen, C.; Liu, J.; Bi, L. Spatial and Temporal Changes of Habitat Quality and Its Influential Factors in China Based on the InVEST Model. Forests 2023, 14, 374. [Google Scholar] [CrossRef]
- Jia, H.; Wang, X.; Sun, W.; Mu, X.; Gao, P.; Zhao, G.; Li, Z. Estimation of Soil Erosion and Evaluation of Soil and Water Conservation Benefit in Terraces under Extreme Precipitation. Water 2022, 14, 1675. [Google Scholar] [CrossRef]
- Singh, M.C.; Sur, K.; Al-Ansari, N.; Arya, P.K.; Verma, V.K.; Malik, A. GIS integrated RUSLE model-based soil loss estimation and watershed prioritization for land and water conservation aspects. Front. Environ. Sci. 2023, 11, 1136243. [Google Scholar] [CrossRef]
- Behera, D.K.; Jamal, S.; Ahmad, W.S.; Taqi, M.; Kumar, R. Estimation of Soil Erosion Using RUSLE Model and GIS Tools: A Study of Chilika Lake, Odisha. J. Geol. Soc. India 2023, 99, 406–414. [Google Scholar] [CrossRef]
- Huang, L.; He, C.; Wang, B. Study on the spatial changes concerning ecosystem services value in Lhasa River Basin, China. Environ. Sci. Pollut. Res. 2022, 29, 7827–7843. [Google Scholar] [CrossRef] [PubMed]
- Choudhary, A.; Deval, K.; Joshi, P.K. Study of habitat quality assessment using geospatial techniques in Keoladeo National Park, India. Environ. Sci. Pollut. Res. 2020, 28, 14105–14114. [Google Scholar] [CrossRef]
- Zhang, Y.; Song, W. Identify Ecological Corridors and Build Potential Ecological Networks in Response to Recent Land Cover Changes in Xinjiang, China. Sustainability 2020, 12, 8960. [Google Scholar] [CrossRef]
- Zhu, F.; Yang, B.D.; Yang, Y.J.; Zhang, S.L.; Li, G.; Chen, F. Research on the Ecological Network Reconstruction of Traditional Mining City in East China. J. Ecol. Rural. Environ. 2020, 36, 26–33. [Google Scholar]
- Aneseyee, A.B.; Noszczyk, T.; Soromessa, T.; Elias, E. The InVEST Habitat Quality Model Associated with Land Use/Cover Changes: A Qualitative Case Study of the Winike Watershed in the Omo-Gibe Basin, Southwest Ethiopia. Remote Sens. 2020, 12, 1103. [Google Scholar] [CrossRef]
- Nematollahi, S.; Fakheran, S.; Kienast, F.; Jafari, A. Application of InVEST habitat quality module in spatially vulnerability assessment of natural habitats (case study: Chaharmahal and Bakhtiari province, Iran). Environ. Monit. Assess. 2020, 192, 487. [Google Scholar] [CrossRef] [PubMed]
- Costanza, R.; d’Arge, R.; de Groot, R.; Farber, S.; Grasso, M.; Hannon, B.; Limburg, K.; Naeem, S.; O’Neill, R.V.; Paruelo, J.; et al. The value of the world’s ecosystem services and natural capital. Nature 1997, 387, 253–260. [Google Scholar] [CrossRef]
- Pan, D.; Jia, H.; Yuan, Y. A GIS-Based Ecological Safety Assessment of Wushen Banner, China. Hum. Ecol. Risk Assess. 2015, 21, 297–306. [Google Scholar] [CrossRef]
- Yushanjiang, A.; Zhang, F.; Yu, H.; Kung, H.-t. Quantifying the spatial correlations between landscape pattern and ecosystem service value: A case study in Ebinur Lake Basin, Xinjiang, China. Ecol. Eng. 2018, 113, 94–104. [Google Scholar] [CrossRef]
- Yushanjiang, A.; Zhang, F.; Kung, H.-t.; Li, Z. Spatial-temporal variation of ecosystem service values in Ebinur Lake Wetland National Natural Reserve from 1972 to 2016, Xinjiang, arid region of China. Environ. Earth Sci. 2018, 77, 586. [Google Scholar] [CrossRef]
- Teng, H.; Rossel, R.A.V.; Shi, Z.; Behrens, T.; Chappell, A.; Bui, E. Assimilating satellite imagery and visible-near infrared spectroscopy to model and map soil loss by water erosion in Australia. Environ. Model. Softw. 2016, 77, 156–167. [Google Scholar] [CrossRef]
- Renard, K.G.; Foster, G.R.; Weesies, G.A.; McCool, D.K.; Yoder, D.C. Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE); Agricultural Handbook; U.S. Department of Agriculture, Agricultural Research Service: Washington, DC, USA, 1997. [Google Scholar]
- Naipal, V.; Reick, C.; Pongratz, J.; Van Oost, K. Improving the global applicability of the RUSLE model—Adjustment of the topographical and rainfall erosivity factors. Geosci. Model Dev. 2015, 8, 2893–2913. [Google Scholar] [CrossRef]
- Guo, Y.; Peng, C.; Zhu, Q.; Wang, M.; Wang, H.; Peng, S.; He, H. Modelling the impacts of climate and land use changes on soil water erosion: Model applications, limitations and future challenges. J. Environ. Manag. 2019, 250, 109403. [Google Scholar] [CrossRef] [PubMed]
- Vadas, P.A.; Krogstad, T.; Sharpley, A.N. Modeling phosphorus transfer between labile and nonlabile soil pools: Updating the EPIC model. Soil Sci. Soc. Am. J. 2006, 70, 736–743. [Google Scholar] [CrossRef]
- Wischmeier, W.H. Predicting Rainfall Erosion Losses—A Guide to Conservation Planning; Agriculture Handbook; Department of Agriculture, Science and Education Administration: Charlottesville, VR, USA, 1978; Volume 537. [Google Scholar]
- Xiong, M.; Sun, R.; Chen, L. Effects of soil conservation techniques on water erosion control: A global analysis. Sci. Total Environ. 2018, 645, 753–760. [Google Scholar] [CrossRef]
- Qiu, S.; Wang, Y.X.; Wang, P.Z.; Lin, C. Construction of Urban Ecological Security pattern and Development Model of Construction Land based on MCR Model. Trans. Chin. Soc. Agric. Eng. 2018, 17, 257–266. (In Chinese) [Google Scholar]
- Liu, X.Y.; Zeng, J.; Jia, M.Y.; Zhang, S. Construction of Ecological Security pattern and Simulation of Urban expansion in Fujian Triangle Urban agglomeration. Acta Ecol. Sin. 2020, 21, 1–13. (In Chinese) [Google Scholar]
- Wang, L.C.; Jiao, L.; Lai, F.B. Study on Evaluation and Driving Forces of Ecological Changes in Jinghe County 0067, Xinjiang. J. Ecol. Rural. Environ. 2019, 35, 316–323. [Google Scholar]
- Taylor, P.D.; Fahrig, L.; Merriam, H.G.J.O. Connectivity Is a Vital Element of Landscape Structure. Oikos 1993, 68, 571–573. [Google Scholar] [CrossRef]
- Saura, S.; Torne, J. Conefor Sensinode 2.2: A software package for quantifying the importance of habitat patches for landscape connectivity. Environ. Model. Softw. 2009, 24, 135–139. [Google Scholar] [CrossRef]
- Dai, L.; Liu, Y.; Luo, X. Integrating the MCR and DOI models to construct an ecological security network for the urban agglomeration around Poyang Lake, China. Sci. Total Environ. 2021, 754, 141868. [Google Scholar] [CrossRef] [PubMed]
- Chen, C.; Shi, L.; Lu, Y.; Yang, S.; Liu, S. The Optimization of Urban Ecological Network Planning Based on the Minimum Cumulative Resistance Model and Granularity Reverse Method: A Case Study of Haikou, China. IEEE Access 2020, 8, 43592–43605. [Google Scholar] [CrossRef]
- Yu, K.J. Ecological strategic points in landscape and surface model. Acta Geogr. Sin. 1998, 53, 11–20. (In Chinese) [Google Scholar]
- Herrera, L.P.; Sabatino, M.C.; Jaimes, F.R.; Saura, S. Landscape connectivity and the role of small habitat patches as stepping stones: An assessment of the grassland biome in South America. Biodivers. Conserv. 2017, 26, 3465–3479. [Google Scholar] [CrossRef]
- Xu, W.J.; Chen, C.; Zhang, Z. Ecological corridor construction based on important ecological nodes in Duliujian River Basin. Res. Environ. Sci. 2018, 31, 805–813. [Google Scholar]
- Pan, B.R.; Zhang, Y.M. Characteristics and conservation of biodiversity in Xinjiang. Sci. China Ser. D-Earth Sci. 2002, 45, 174–179. [Google Scholar] [CrossRef]
- Huang, J.; Wang, R.; Zhang, H. Analysis of patterns and ecological security trend of modern oasis landscapes in Xinjiang, China. Environ. Monit. Assess. 2007, 134, 411–419. [Google Scholar] [CrossRef]
- Gao, J.; Liu, X.; Wang, C.; Wang, Y.; Fu, Z.; Hou, P.; Lyu, N. Evaluating changes in ecological land and effect of protecting important ecological spaces in China. J. Geogr. Sci. 2021, 31, 1245–1260. [Google Scholar] [CrossRef]
- Zagas, T.D.; Raptis, D.I.; Zagas, D.T. Identifying and mapping the protective forests of southeast Mt. Olympus as a tool for sustainable ecological and silvicultural planning, in a multi-purpose forest management framework. Ecol. Eng. 2011, 37, 286–293. [Google Scholar] [CrossRef]
- Cunha, N.S.; Magalhaes, M.R. Methodology for mapping the national ecological network to mainland Portugal: A planning tool towards a green infrastructure. Ecol. Indic. 2019, 104, 802–818. [Google Scholar] [CrossRef]
- Sun, J.; Li, Y.P.; Gao, P.P.; Xia, B.C. A Mamdani fuzzy inference approach for assessing ecological security in the Pearl River Delta urban agglomeration, China. Ecol. Indic. 2018, 94, 386–396. [Google Scholar] [CrossRef]
- Miao, Z.; Pan, L.; Wang, Q.; Chen, P.; Yan, C.; Liu, L. Research on Urban Ecological Network Under the Threat of Road Networks-A Case Study of Wuhan. ISPRS Int. J. Geo-Inf. 2019, 8, 342. [Google Scholar] [CrossRef]
- Song, S.; Xu, D.; Hu, S.; Shi, M. Ecological Network Optimization in Urban Central District Based on Complex Network Theory: A Case Study with the Urban Central District of Harbin. Int. J. Environ. Res. Public Health 2021, 18, 1427. [Google Scholar] [CrossRef] [PubMed]
- Yin, H.W.; Kong, F.H.; Qi, Y.; Wang, H.Y.; Zhou, Y.N.; Qin, Y.M. Developing and optimizing ecological networks in urban agglomeration of Hunan Province, China. Acta Ecol. Sin. 2011, 31, 2863–2874. [Google Scholar]
- Gu, F.; Huang, Y.X.; Chen, C.M.; Chen, D.L.; Guo, J.L. Construction and optimization of ecological network for nature reserves in Fujian Province, China. Chin. J. Appl. Ecol. 2017, 28, 1013–1020. [Google Scholar]
Data | Resolution | Time (Year) | Source | Application |
---|---|---|---|---|
Land use/cover type | 30 m | 2018 | REDCP (http://www.resdc.cn, 15 March 2022) | InVEST mode data/ESV model data |
Normalized difference vegetation index | 250 m | 2018 | NASA (https://www.nasa.gov, 15 March 2022) | ESV correction |
Night-time light data | 1 km | 2018 | NASA (http://reverb.echo.nasa.gov, 15 March 2022) | InVEST mode data |
Road vector | 1 km | 2018 | OSM (http://www.openstreetmap.org, 1 May 2022) | RUSLE model data |
Population density | 1 km | 2018 | ORNL (https://www.satpalda.com, 1 May 2022) | InVEST mode data |
Soil properties | 1 km | - | HWSD (http://webarchive.iiasa.ac.at, 1 May 2022) | RUSLE model data |
National administrative boundary | 1:1,000,000 | 2017 | NGCC (https://www.tianditu.gov.cn, 15 March 2022) | Basic data |
Meteorological data | - | 2018 | CIMISS (http://data.cma.cn/, 1 May 2022) | RUSLE model data |
Threat | Maximun Impact Distance/km | Weight | Recession Type |
---|---|---|---|
Farmland | 4 | 0.6 | Linear |
Urban | 8 | 0.8 | Linear |
Village | 6 | 0.6 | Exponential |
Other construction land | 7 | 0.7 | Exponential |
Bare land | 4 | 0.4 | Exponential |
Night-time light | 7 | 0.8 | Linear |
Population | 6 | 0.8 | Linear |
Land Use Type | Habitat Suitability | Farmland | Urban | Village | Other Construction Land | Unused Land | Population | Night-Time Light |
---|---|---|---|---|---|---|---|---|
Farmland | 0.5 | 0 | 0.8 | 0.6 | 0.7 | 0.4 | 0 | 0 |
Forest land | 1 | 0.7 | 0.9 | 0.8 | 0.8 | 0.5 | 0.7 | 0.8 |
Shrub land | 1 | 0.6 | 0.8 | 0.7 | 0.7 | 0.4 | 0.7 | 0.8 |
Sparse forest land | 0.9 | 0.7 | 0.9 | 0.8 | 0.8 | 0.5 | 0.7 | 0.8 |
Other forest land | 1 | 0.7 | 0.9 | 0.8 | 0.8 | 0.5 | 0.7 | 0.8 |
High coverage land | 0.9 | 0.6 | 0.7 | 0.7 | 0.7 | 0.7 | 0.7 | 0.8 |
Medium coverage land | 0.8 | 0.7 | 0.8 | 0.8 | 0.8 | 0.7 | 0.7 | 0.8 |
Low coverage land | 0.7 | 0.7 | 0.8 | 0.8 | 0.8 | 0.7 | 0.7 | 0.8 |
Water | 0.9 | 0.4 | 0.7 | 0.6 | 0.7 | 0.4 | 0.6 | 0.6 |
Urban land | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Rural resident land | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Other construction land | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Bare land | 0.3 | 0.4 | 0.6 | 0.5 | 0.6 | 0 | 0.2 | 0.2 |
Land Use Types | Farmland | Woodland | Grassland | Water | Construction Land | Bare Land |
---|---|---|---|---|---|---|
Unit value | 4.37 × 103 | 19.95 × 103 | 2.15 × 103 | 24.06 × 103 | 0.30 × 103 | 0.22 × 103 |
Farmland | Woodland | Grassland | Water | Construction Land | Bare Land | |
---|---|---|---|---|---|---|
C | 0.2 | 0.05 | 0.3 | 0 | 0 | 1.0 |
p | 0.15 | 1.0 | 1.0 | 0 | 0 | 0 |
Resistance Factor | Weight | Indicator | Resistance Coefficient | |
---|---|---|---|---|
Landscape types | 0.40 | Woodland | 10 | |
Water | 15 | |||
Farmland | 25 | |||
Grassland | 30 | |||
Bare land | 80 | |||
Construction | 100 | |||
Geomorphological factors | Slope | 0.30 | <8° | 1 |
8~15° | 10 | |||
15~25° | 50 | |||
25~35° | 75 | |||
>35° | 100 | |||
RDLS | 0.30 | <25° | 1 | |
25~50° | 10 | |||
50~70° | 50 | |||
70~100° | 75 | |||
>100° | 100 |
Landscape Type | Area/km2 | Proportion of Prospects/% | Proportion of Total Area/% |
---|---|---|---|
Core | 1.86 × 104 | 18.51 | 1.14 |
Islet | 2.52 × 104 | 25.12 | 1.54 |
Perforation | 0.02 × 104 | 0.18 | 0.01 |
Edge | 1.94 × 104 | 19.29 | 1.19 |
Loop | 0.38 × 104 | 3.81 | 0.23 |
Bridge | 1.53 × 104 | 15.18 | 0.93 |
Branch | 1.80 × 104 | 17.91 | 1.10 |
Total | 10.1 × 104 | 100.00 | 6.15 |
Ecological Source Area | Source | Corridor | Ecological Node | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
The Main Corridor | Bridge Corridor | Planning Auxiliary Corridor | Stepping-Stone | Ecological Fracture Point | ||||||||||
Number | Area/km2 | Number | Length/km | Number | Length/km | Number | Length/km | Level 1 | Level 2 | Level 3 | Level 1 | Level 2 | Level 3 | |
1. Altay ecological source area | 13 | 3031.23 | 16 | 696.69 | 0 | 0.00 | 1 | 558.01 | 5 | 0 | 5 | 6 | 0 | 0 |
2. Yili River Valley ecological source area | 11 | 2008.83 | 11 | 771.53 | 1 | 145.47 | 3 | 519.33 | 5 | 4 | 3 | 8 | 3 | 0 |
3. Tianshan North Slope ecological source area | 13 | 1401.18 | 23 | 728.75 | 5 | 1012.46 | 0 | 0.00 | 11 | 2 | 1 | 8 | 6 | 0 |
4. Weiku Oasis ecological source area | 3 | 688.60 | 5 | 216.25 | 2 | 694.86 | 1 | 133.54 | 3 | 3 | 0 | 1 | 5 | 0 |
5. Bosten Lake ecological source area | 1 | 737.57 | 0 | 0.00 | 2 | 319.19 | 1 | 656.88 | 0 | 4 | 1 | 0 | 4 | 0 |
6. West Kunlun glacier ecological source area | 5 | 1324.23 | 5 | 242.04 | 3 | 1138.70 | 1 | 265.33 | 4 | 6 | 2 | 0 | 5 | 0 |
7. Altun Mountain ecological source area | 5 | 1625.05 | 6 | 577.74 | 0 | 0.00 | 1 | 68.94 | 5 | 1 | 8 | 0 | 0 | 1 |
Total | 51 | 10,816.68 | 66 | 3233.01 | 13 | 3310.68 | 8 | 2202.04 | 33 | 20 | 20 | 23 | 23 | 1 |
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Wang, Y.; Zhang, F.; Li, X.; Johnson, V.C.; Tan, M.L.; Kung, H.-T.; Shi, J.; Bahtebay, J.; He, X. Methodology for Mapping the Ecological Security Pattern and Ecological Network in the Arid Region of Xinjiang, China. Remote Sens. 2023, 15, 2836. https://doi.org/10.3390/rs15112836
Wang Y, Zhang F, Li X, Johnson VC, Tan ML, Kung H-T, Shi J, Bahtebay J, He X. Methodology for Mapping the Ecological Security Pattern and Ecological Network in the Arid Region of Xinjiang, China. Remote Sensing. 2023; 15(11):2836. https://doi.org/10.3390/rs15112836
Chicago/Turabian StyleWang, Yishan, Fei Zhang, Xingyou Li, Verner Carl Johnson, Mou Leong Tan, Hsiang-Te Kung, Jingchao Shi, Jupar Bahtebay, and Xin He. 2023. "Methodology for Mapping the Ecological Security Pattern and Ecological Network in the Arid Region of Xinjiang, China" Remote Sensing 15, no. 11: 2836. https://doi.org/10.3390/rs15112836
APA StyleWang, Y., Zhang, F., Li, X., Johnson, V. C., Tan, M. L., Kung, H. -T., Shi, J., Bahtebay, J., & He, X. (2023). Methodology for Mapping the Ecological Security Pattern and Ecological Network in the Arid Region of Xinjiang, China. Remote Sensing, 15(11), 2836. https://doi.org/10.3390/rs15112836