Exploring Spatial Non-Stationarity and Scale Effects of Natural and Anthropogenic Factors on Net Primary Productivity of Vegetation in the Yellow River Basin
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Sources
- (1)
- The MOD17A3HGF v006 NPP data from Google Earth Engine (https://code.earthengine.google.com/, accessed on 26 August 2024).
- (2)
- Influencing factor data includes 8 natural and 4 anthropogenic factors (Table 1).
2.3. Methods
2.3.1. Theil–Sen Median Analysis and Mann–Kendall Test
2.3.2. Hurst Index
2.3.3. Multi-Scale Geographically Weighted Regression
3. Results
3.1. Spatiotemporal Variation in Vegetation NPP
3.2. Trend of Change in NPP
3.3. Regression Coefficients of Influencing Factors
3.4. Spatial Interactions between NPP and Influencing Factors
3.5. Scale Differences in Influencing Factors
4. Discussion
4.1. Increased Trend in Vegetation NPP and Its Persistence
4.2. Spatial Non-Stationarity of Natural and Anthropogenic Effects on NPP
4.2.1. The Effect of Natural Factors on NPP
4.2.2. The Effect of Anthropogenic Factors on NPP
4.3. Scale Effect Analysis
4.4. Policy Suggestion
4.5. Limitations and Uncertainties
5. Conclusions
- (1)
- From 2000 to 2020, the overall trend in NPP for YRB is increasing. The future trend indicates that the NPP in southern Qinghai, Shaanxi and Inner Mongolia will show a change from increasing to decreasing, and the vegetation is at risk of degradation. Therefore, the focus of future management should be on the region for the improvement of its ecosystem stability.
- (2)
- The reaction of NPP to influencing factors exhibits significant spatial non-stationarity. Most of the effects of natural factors show east-west gradual distribution, and individuals show north-south distribution. This is due to the fact that NPP originates from the natural environment and is related to the spatial distribution of natural factors in the YRB. In contrast, there is no similar law of spatial non-stationarity between anthropogenic factors and NPP.
- (3)
- The impact scale of different factors on vegetation NPP varied significantly. The bandwidths of factors were negatively correlated with the regression coefficient, that is, the greater the effect intensity, the stronger the spatial non-stationary relationship of vegetation NPP. Due to the YRB being semi-arid, the impact size and scale of RH are both large. The study of such scale effects can allow governments to set the scope of policy implementation according to the size of the impact scale.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Factor | Code | Unit | Resolution | Data Source | |
---|---|---|---|---|---|
Natural factors | Digital elevation model | DEM | m | 30 m | United States Geological Survey (https://www.usgs.gov/, accessed on 26 August 2024) |
Slope | Slope | ° | 30 m | ||
Topographic relief | TR | m | 30 m | ||
Mean annual temperature | TEM | °C | 1 km | National Earth System Science Data Center (http://www.geodata.cn, accessed on 26 August 2024) | |
Annual precipitation | PRE | mm | 1 km | ||
Potential evapotranspiration | PET | mm | 1 km | ||
Relative humidity | RH | % | 1 km | ||
Sunshine hours | SH | h | 1 km | ||
Anthropogenic factors | Human footprint | HF | / | 1 km | https://doi.org/10.6084/m9.figshare.16571064, accessed on 26 August 2024 |
Greenhouse gases | CO2 | 0.1° | Emissions Database for Global Atmospheric Research (EDGAR) (https://edgar.jrc.ec.europa.eu/, accessed on 26 August 2024) | ||
CH4 | ton | 0.1° | |||
N2O | 0.1° |
SNPP | Z Value | NPP Change Trend | Area Proportion/% |
---|---|---|---|
<0 | <−1.96 | Significantly degrade | 0.16 |
−1.96–1.96 | Slightly degrade | 0.26 | |
=0 | −1.96–1.96 | Stable | 13.17 |
>0 | −1.96–1.96 | Slightly improve | 16.39 |
>1.96 | Significantly improve | 70.02 |
SNPP | Hurst Index | NPP Future Trend Change | Area Proportion/% |
---|---|---|---|
>0 | >0.5 | Continuous increase | 17.58 |
<0 | >0.5 | Continuous decrease | 0.68 |
>0 | <0.5 | Increase to decrease | 80.57 |
<0 | <0.5 | Decrease to increase | 1.17 |
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Wang, X.; He, W.; Huang, Y.; Wu, X.; Zhang, X.; Zhang, B. Exploring Spatial Non-Stationarity and Scale Effects of Natural and Anthropogenic Factors on Net Primary Productivity of Vegetation in the Yellow River Basin. Remote Sens. 2024, 16, 3156. https://doi.org/10.3390/rs16173156
Wang X, He W, Huang Y, Wu X, Zhang X, Zhang B. Exploring Spatial Non-Stationarity and Scale Effects of Natural and Anthropogenic Factors on Net Primary Productivity of Vegetation in the Yellow River Basin. Remote Sensing. 2024; 16(17):3156. https://doi.org/10.3390/rs16173156
Chicago/Turabian StyleWang, Xiaolei, Wenxiang He, Yilong Huang, Xing Wu, Xiang Zhang, and Baowei Zhang. 2024. "Exploring Spatial Non-Stationarity and Scale Effects of Natural and Anthropogenic Factors on Net Primary Productivity of Vegetation in the Yellow River Basin" Remote Sensing 16, no. 17: 3156. https://doi.org/10.3390/rs16173156