Monitoring the Spatiotemporal Dynamics of Habitat Quality and Its Driving Factors Based on the Coupled NDVI-InVEST Model: A Case Study from the Tianshan Mountains in Xinjiang, China
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Sources
2.3. Methods
2.3.1. Habitat Quality Evaluation
2.3.2. Terrain Factors
2.3.3. Spatial Autocorrelation and Hot/Cold Spot Analysis
2.3.4. Selection of Driving Factors
2.3.5. Geographical Detector Model
3. Results
3.1. Validation of Habitat Quality
3.2. Land-Use Change from 1995–2015
3.3. Spatiotemporal Change in Habitat Quality
3.4. The Spatial Heterogeneity of the Habitat Quality
3.5. Habitat Quality in Relation to Different PAs
3.6. Habitat Quality Variation in Terrain Gradient
3.7. Driving Factors of Habitat Quality
3.7.1. Comparison of Driving Factors in the Different Sub-Regions
3.7.2. Spatial Interactions between Driving Factors
4. Discussion
4.1. Climate Change and Anthropogenic Activity Implications
4.2. The Gap between Conservation Expectations and Reality
4.3. Limitations and Future Work
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Threats | Maximum Influence Distance/km | Weight | Spatial Decay Type |
---|---|---|---|
Cropland | 8 | 0.7 | linear |
Urban land | 10 | 1 | linear |
Rural residential | 6 | 0.6 | linear |
Other construction land | 8 | 0.8 | linear |
Railway | 4 | 0.5 | linear |
Highway | 3 | 0.4 | linear |
Land-Use Code | Habitat | Cropland | Urban Land | Rural Residential | Other Construction Land | Railway | Highway |
---|---|---|---|---|---|---|---|
10 | 0.3 | 0.0 | 0.6 | 0.4 | 0.3 | 0.5 | 0.4 |
21 | 1 | 0.8 | 0.9 | 0.8 | 0.8 | 0.8 | 0.7 |
22 | 0.9 | 0.6 | 0.7 | 0.6 | 0.5 | 0.6 | 0.5 |
23 | 0.8 | 0.7 | 0.8 | 0.7 | 0.6 | 0.8 | 0.7 |
24 | 0.7 | 0.7 | 0.8 | 0.7 | 0.6 | 0.7 | 0.6 |
31 | 0.9 | 0.5 | 0.6 | 0.5 | 0.4 | 0.5 | 0.6 |
32 | 0.8 | 0.6 | 0.7 | 0.6 | 0.4 | 0.5 | 0.6 |
33 | 0.7 | 0.7 | 0.8 | 0.7 | 0.6 | 0.5 | 0.6 |
41 | 1 | 0.1 | 0.7 | 0.6 | 0.5 | 0.5 | 0.4 |
42 | 1 | 0.1 | 0.7 | 0.6 | 0.5 | 0.5 | 0.4 |
43 | 1 | 0.1 | 0.7 | 0.6 | 0.5 | 0.5 | 0.4 |
44 | 1 | 0.1 | 0.1 | 0.2 | 0.1 | 0.5 | 0.4 |
45 | 0.8 | 0.7 | 0.8 | 0.6 | 0.5 | 0.5 | 0.4 |
51 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
52 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
53 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
61 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
62 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
63 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.2 | 0.2 |
64 | 0.8 | 0.1 | 0.5 | 0.6 | 0.4 | 0.5 | 0.7 |
65 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.2 | 0.2 |
66 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
67 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Index | Code | Unit | Data Source and Calculation |
---|---|---|---|
Soil type | SOL | - | Data from RESDC |
Annual mean precipitation | PRE | mm | Data from RESDC |
Annual mean temperature | TEM | °C | Data from RESDC |
Elevation | ELE | m | Data from the Geospatial Data Cloud (http://www.gscloud.cn, accessed on 21 April 2022) |
Relief degree of land surface | RDLS | - | Extract from DEM |
Land-use type | LAND | - | Data from RESDC |
Gross domestic product | GPD | 104CNY/km2 | Data from RESDC |
Population density | PD | person/km2 | Data from RESDC |
Distance to tourism attractions | TOU | m | The tourism attractions were obtained from the Department of Culture and Tourism of the Xinjiang Uygur Autonomous Region. It was calculated by ArcGIS “Euclidean distance” tool. |
Grazing intensity | GI | heads/km2 | The livestock data was obtained from the XinJiang Statistical Yearbook. The grazing intensity was calculated based on literature (Li et al., 2014). |
Description | Interaction |
---|---|
q(X1∩X2) < Min(q(X1), q(X2)) | Weaken, nonlinear |
Min(q(X1), q(X2)) < q(X1∩X2) < Max(q(X1), q(X2)) | Weaken, univariate, nonlinear |
q(X1∩X2) > Max(q(X1), q(X2)) | Enhance, linear, bivariate |
q(X1∩X2) = q(X1) + q(X2) | Independent |
q(X1∩X2) > q(X1) + q(X2) | Enhance, nonlinear |
Classification | Level | Value | Area (%) | ||||
---|---|---|---|---|---|---|---|
1995 | 2000 | 2005 | 2010 | 2015 | |||
Very important habitat | L1 | 0.75~1.0 | 37.08 | 37.76 | 36.15 | 37.05 | 35.23 |
Important habitat | L2 | 0.5~0.75 | 10.65 | 9.60 | 11.78 | 10.87 | 10.69 |
Moderately important habitat | L3 | 0.25~0.5 | 16.86 | 15.76 | 16.47 | 15.29 | 14.98 |
General habitat | L4 | 0.0~0.25 | 35.41 | 36.88 | 35.61 | 36.78 | 39.10 |
Year | Zone | Main Interaction Detector |
---|---|---|
1995 | TTS | SOL∩LAND, GI∩LAND, GI∩SOL |
ETS | SOL∩LAND, GDP∩SOL, PRE∩LAND | |
NTS | SOL∩LAND, PRE∩LAND, GI∩LAND | |
MTS | SOL∩LAND, GI∩SOL, ELE∩SOL | |
2000 | TTS | SOL∩LAND, PRE∩LAND, GI∩SOL |
ETS | SOL∩LAND, GDP∩SOL, PD∩SOL | |
NTS | SOL∩LAND, PRE∩LAND, GI∩LAND | |
MTS | GI∩SOL, SOL∩LAND, ELE∩PRE | |
2005 | TTS | SOL∩LAND, GI∩SOL, GDP∩SOL |
ETS | GDP∩SOL, SOL∩LAND, PD∩SOL | |
NTS | SOL∩LAND, ELE∩LAND, GI∩LAND | |
MTS | SOL∩LAND, GI∩SOL, ELE∩SOL | |
2010 | TTS | SOL∩LAND, ELE∩SOL, GDP∩SOL |
ETS | SOL∩LAND, GDP∩SOL, PD∩SOL | |
NTS | SOL∩LAND, PRE∩LAND, GI∩LAND | |
MTS | ELE∩SOL, GI∩SOL, GDP∩SOL | |
2015 | TTS | SOL∩LAND, ELE∩SOL, GDP∩SOL |
ETS | SOL∩LAND, ELE∩SOL, PD∩SOL | |
NTS | SOL∩LAND, ELE∩LAND, TEM∩LAND | |
MTS | ELE∩SOL, GI∩SOL, ELE∩PRE |
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Lu, Y.; Zhao, J.; Qi, J.; Rong, T.; Wang, Z.; Yang, Z.; Han, F. Monitoring the Spatiotemporal Dynamics of Habitat Quality and Its Driving Factors Based on the Coupled NDVI-InVEST Model: A Case Study from the Tianshan Mountains in Xinjiang, China. Land 2022, 11, 1805. https://doi.org/10.3390/land11101805
Lu Y, Zhao J, Qi J, Rong T, Wang Z, Yang Z, Han F. Monitoring the Spatiotemporal Dynamics of Habitat Quality and Its Driving Factors Based on the Coupled NDVI-InVEST Model: A Case Study from the Tianshan Mountains in Xinjiang, China. Land. 2022; 11(10):1805. https://doi.org/10.3390/land11101805
Chicago/Turabian StyleLu, Yayan, Junhong Zhao, Jianwei Qi, Tianyu Rong, Zhi Wang, Zhaoping Yang, and Fang Han. 2022. "Monitoring the Spatiotemporal Dynamics of Habitat Quality and Its Driving Factors Based on the Coupled NDVI-InVEST Model: A Case Study from the Tianshan Mountains in Xinjiang, China" Land 11, no. 10: 1805. https://doi.org/10.3390/land11101805