Integrating Future Land Use Scenarios to Evaluate the Spatio-Temporal Dynamics of Landscape Ecological Security
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Processing
2.3. Methods
2.3.1. Scenario Assumptions
2.3.2. Specific Settings in the CLUE-S Model
2.3.3. Spatial Evaluation of Landscape Ecological Security
3. Results
3.1. Retrospective Analysis of Historic Land Use Change
3.2. Spatial and Temporal Analysis of Land Use Simulation under Different Scenarios
3.3. Spatial and Temporal Changes in Landscape Ecological Security Based on the P-S-R Framework
3.3.1. Analysis of the Pressure, State, and Response of Ecological Security
3.3.2. Spatial and Temporal Analyses of Landscape Ecological Security under Different Scenarios
4. Discussion
4.1. The Integrated Method of Ecological Security Evaluation
4.2. Implications of the Spatio-Temporal Dynamics of Ecological Security under Different Scenarios
5. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
Appendix A
Ecological Function Zoning | Change in the Implementation Degree Index | |||
---|---|---|---|---|
2000 | 2010 | 2020 NTS | 2020 EPS | |
Ecological headwater protection zone | 0.7 | 0.8 | 0.9 | 1 |
Ecological environmental resilience zone | 0 | 0.5 | 0.7 | 0.9 |
Ecological tourism development zone | 0.3 | 0.4 | 0.5 | 0.6 |
Ecological economic development zone | 0 | 0.3 | 0.4 | 0.5 |
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Variable | Description | Resolution | Source |
---|---|---|---|
DEM | Spatial data used to generate the elevation, aspect, and slope | 30 m | The Geospatial Data Cloud of the Chinese Academy of Science [49] |
Administrative boundaries | Spatial data at the national, provincial, and city levels used to generate the administrative map of Huangshan City | Cartographic scale of 1:400,000 at the national and provincial levels | The National Geometrics Center of China (NGCC) [50] |
Cartographic scale of 1:200,000 at the city level | The Department of Urban-Rural Planning, Huangshan City | ||
Roads | Level 1–2 traffic network distribution (highway and railway) | Cartographic scale of 1:200,000 | Same as above |
Rivers | River network distribution | Same as above | Same as above |
Administrative center | Level 1–3 administrative center distribution (urban, town, and rural settlement centers) | Same as above | Same as above |
Population | Seven counties and towns from 2000–2010 | / | Huangshan City Statistical Yearbooks |
GDP | Seven counties and towns from 2000–2010 | / | Same as above |
Ecological function zones | Map used to determine the implementation degree | Cartographic scale of 1:10,000 | The Department of Environmental Protection, Huangshan City |
Scenarios | Shrubland | Forest | Construction Land | Farmland | Grassland | Wetland | Bareland |
---|---|---|---|---|---|---|---|
NTS | 0.6 | 0.7 | 1 | 0.5 | 0.4 | 0.4 | 0.7 |
EPS | 0.7 | 0.8 | 0.9 | 0.5 | 0.5 | 0.9 | 0.3 |
Dimension (Weight) | Indicator (Weight) (±) | Equation | Description | |
---|---|---|---|---|
P-Pressure of landscape change (0.4) | P1-Development intensity of construction land (0.6) (−) | is the construction land area and is the total area of the evaluation unit . | ||
P2-Population density (0.4) (−) | is the total population and is the total area of the i-th county. The value of each evaluation unit is obtained by interpolating the value of counties into the entire study area. | |||
S-State of the landscape ecological system (0.5) | S1-Structure state (0.6) (−) | Landscape disturbance degree and vulnerability degree | is the area of the i-th landscape in the kth unit, is the area of the kth unit, is the index of the landscape disturbance degree of the i-th landscape, and is the vulnerability index of the i-th landscape. | |
S2-Function state (0.4) (+) | Ecological service value | Xi is the area of the i-th type of land use and Vi is the ecosystem service value of the i-th type of land use. | ||
R-Human response (0.1) | R-Implementation degree of the ecological function zoning (1.0) (+) | This index is based on the eco-functional zoning in Huangshan City and values recommended by researchers, urban administrators, and local residents using the Delphi method (see Appendix A). |
Name | Equation | Introduction |
---|---|---|
Landscape disturbance degree | ni is the number of patches in the i-th landscape, Ai is the area of the i-th landscape, A is the area of all the landscapes, Pi is the proportion of the landscape occupied by the i-th landscape patch, and m is the number of landscape classes. The weights of the landscape indices are 0.5, 0.3, and 0.2 for , , and , respectively [65]. | |
Landscape fragmentation index | ||
Landscape isolation index | ||
Landscape dominance index | ||
Landscape vulnerability degree | The associated values are as follows: Shrubland (0.2), Forest (0.1), Construction land (0.6), Farmland (0.4), Grassland (0.3), Wetland (0.5), and Bareland (0.7) [70,71]. |
2010 | Shrubland | Forestland | Construction Land | Farmland | Grassland | Wetland | Bareland | |
---|---|---|---|---|---|---|---|---|
2000 | ||||||||
Shrubland | 32,342.02 | 71.35 | 4.01 | 1.28 | 0 | 0.07 | 0 | |
Forestland | 3.26 | 784,250.68 | 32.88 | 12.27 | 0 | 4.06 | 0 | |
Construction land | 0 | 0.09 | 7199.08 | 0.46 | 0 | 0.79 | 0 | |
Farmland | 81.25 | 288.07 | 4166.04 | 115,252.74 | 0.17 | 732.50 | 0 | |
Grassland | 1127.67 | 0.22 | 0.01 | 0.75 | 15,654.83 | 0.46 | 0 | |
Wetland | 0.00 | 0.15 | 17.04 | 896.00 | 0.01 | 14,123.65 | 0 | |
Bareland | 0 | 0 | 0.02 | 0 | 0 | 0 | 1392.63 | |
Net gain/loss | 1135.46 | 307.42 | 4218.65 | −4357.27 | −1128.92 | −175.33 | −0.02 | |
Change rate | 3.50% | 0.04% | 58.59% | −3.62% | −6.73% | −1.17% | −0.00% |
Shrubland | Forestland | Construction Land | Farmland | Grassland | Wetland | Bareland | |
---|---|---|---|---|---|---|---|
ROC | 0.837 | 0.783 | 0.876 | 0.868 | 0.788 | 0.950 | 0.977 |
Year Land Use Type | 2010 | 2020 | Change Rate | ||
---|---|---|---|---|---|
NTS | EPS | NTS | EPS | ||
Shrubland | 33,512 | 34,580 | 35,180 | 3.22% | 5.0% |
Forestland | 784,423 | 784,709 | 790,637 | 0.032% | 0.8% |
Construction land | 11,385 | 15,490 | 12,523 | 36.11% | 10.0% |
Farmland | 116,338 | 112,113 | 109,357 | −3.64% | −6.0% |
Grassland | 15,712 | 14,653 | 14,924 | −6.71% | −5.0% |
Wetland | 14,842 | 14,665 | 14,842 | −1.23% | 0.0% |
Bareland | 1389 | 1389 | 138 | 0.0% | −90.0% |
Year | Scenario | Average Value (No Units) | Area Percentage (Unit: %) | ||||
---|---|---|---|---|---|---|---|
Extremely Low | Low | Medium | High | Extremely High | |||
2000 | 0.760 | 0 | 2.34 | 5.35 | 49.32 | 42.99 | |
2010 | 0.751 | 0.1 | 3.58 | 5.92 | 49.27 | 41.13 | |
2020 | NTS | 0.748 | 0.73 | 3.92 | 5.43 | 44.51 | 45.40 |
EPS | 0.767 | 0.07 | 3.79 | 5.06 | 36.25 | 54.84 |
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Lu, Y.; Wang, X.; Xie, Y.; Li, K.; Xu, Y. Integrating Future Land Use Scenarios to Evaluate the Spatio-Temporal Dynamics of Landscape Ecological Security. Sustainability 2016, 8, 1242. https://doi.org/10.3390/su8121242
Lu Y, Wang X, Xie Y, Li K, Xu Y. Integrating Future Land Use Scenarios to Evaluate the Spatio-Temporal Dynamics of Landscape Ecological Security. Sustainability. 2016; 8(12):1242. https://doi.org/10.3390/su8121242
Chicago/Turabian StyleLu, Yi, Xiangrong Wang, Yujing Xie, Kun Li, and Yiyang Xu. 2016. "Integrating Future Land Use Scenarios to Evaluate the Spatio-Temporal Dynamics of Landscape Ecological Security" Sustainability 8, no. 12: 1242. https://doi.org/10.3390/su8121242