Analysis of Spatiotemporal Evolution and Influencing Factors of Vegetation Net Primary Productivity in the Yellow River Basin from 2000 to 2022
Abstract
:1. Introduction
2. Data and Method
2.1. Study Area
2.2. Data
2.2.1. NPP
2.2.2. Static Factors Data
2.2.3. Dynamic Factors Data
- Meteorological data
- 2.
- TWS data
- 3.
- Human activity data
2.3. Method
2.3.1. Miami Model
2.3.2. Trend Analysis
2.3.3. Stability Analysis
2.3.4. Geographical Detector
2.3.5. Transfer Matrix
3. Results and Analysis
3.1. Spatiotemporal Distribution Characteristics of Vegetation NPP in the Yellow River Basin
3.1.1. Spatiotemporal Changes in Vegetation NPP in the Yellow River Basin from 2000 to 2022
3.1.2. Change Rate and Stability Analysis
3.2. Static Factors Analysis on Vegetation NPP in the YRB
3.2.1. Geographical Location Analysis on Vegetation NPP in the YRB
3.2.2. Altitude Analysis on Vegetation NPP in the YRB
3.2.3. Slope Analysis on Vegetation NPP in the YRB
3.3. Dynamic Factors Analysis Analysis on Vegetation NPP in the YRB
3.3.1. Correlation Analysis on Vegetation NPP in the YRB
3.3.2. Single Factor Analysis on Vegetation NPP in the YRB
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Data | Period | Spatial Resolution | Website (Access Data: 30 December 2023) | |
---|---|---|---|---|
NPP | 2000–2022 | 500 m | https://ladsweb.nascom.nasa.gov/ | |
Static factors | Geographical location | 1 km | http://www.Gscloud.cn | |
Elevation | ||||
Slope | ||||
Soil type | ||||
Dynamic factors | Accumulated temperature | 2000–2019 | 1 km | http://data.cma.cn/data |
Sunshine duration | ||||
Temperature | ||||
Precipitation | ||||
TWS | 2003–2019 | 0.25° | http://data.tpdc.ac.cn/data | |
Land use | 2000, 2005, 2010, 2015, 2019 | 1 km | http://www.resdc.cn | |
Population density | ||||
GDP |
NPP (gC·m−2·a−1) | NPP Categories | Area Ratio (2000) | Area Ratio (2022) | Area Ratio Change (2000–2022) |
---|---|---|---|---|
<200 | Low | 53.42% | 27.98% | −25.44% |
200~400 | Lower | 41.62% | 35.49% | −6.13% |
400~600 | Median | 2.60% | 30.84% | 28.24% |
600~800 | Higher | 2.35% | 5.59% | 3.24% |
>800 | High | 0.01% | 0.10% | 0.09% |
Spatial (m) | Spatial Proportion (%) | Unit NPP (gC·m−2·a−1) | RMS (gC·m−2·a−1) | Unit NPP Proportion (%) | Total NPP (gC·m−2·a−1) | Total NPP Proportion (%) |
---|---|---|---|---|---|---|
<1000 | 16.49% | 344.37 | 122.68 | 23.96% | 56.79 | 20.48% |
1000~2000 | 53.01% | 255.14 | 152.37 | 17.75% | 135.25 | 48.78% |
2000~3000 | 8.34% | 327.68 | 148.4 | 22.80% | 27.33 | 9.86% |
3000~4000 | 11.88% | 342.62 | 77.33 | 23.84% | 40.70 | 14.68% |
>4000 | 10.28% | 167.55 | 75.94 | 11.66% | 17.22 | 6.21% |
Slope (°) | Slope Proportion (%) | Unit NPP (gC·m−2·a−1) | RMS (gC·m−2·a−1) | Unit NPP Proportion (%) | Total NPP (gC·m−2·a−1) | Total NPP Proportion (%) |
---|---|---|---|---|---|---|
<3 | 66.68% | 250.46 | 138.1 | 15.49% | 167.01 | 60.22% |
3~6 | 22.06% | 326.39 | 136.12 | 20.18% | 72.00 | 25.96% |
6~9 | 7.11% | 334.43 | 146.67 | 20.68% | 23.78 | 8.57% |
9~12 | 2.71% | 341.94 | 156.84 | 21.14% | 9.27 | 3.34% |
>12 | 1.45% | 364.02 | 170.83 | 22.51% | 5.28 | 1.90% |
Correlation Coefficient | Correlation | Area Proportion | ||||
---|---|---|---|---|---|---|
Accumulated Temperature | Sunshine | Precipitation | Air Temperature | TWS | ||
−1~−0.8 | Negative extremely strong | 0% | 0% | 0% | 0% | 16% |
−0.8~−0.6 | Negative strong | 0% | 6% | 0% | 0% | 19% |
−0.6~−0.4 | Negative moderate | 1% | 15% | 1% | 1% | 13% |
−0.4~−0.2 | Negative weak | 2% | 20% | 4% | 2% | 8% |
−0.2~−0 | Negative extremely weak | 11% | 23% | 14% | 9% | 11% |
0~0.2 | Positive extremely weak | 18% | 17% | 15% | 13% | 7% |
0.2~0.4 | Positive weak | 32% | 12% | 18% | 28% | 9% |
0.4~0.6 | Positive moderate | 20% | 6% | 25% | 36% | 10% |
0.6~0.8 | Positive strong | 15% | 1% | 20% | 12% | 5% |
0.8~1 | Positive extremely strong | 2% | 0% | 3% | 0% | 1% |
Average proportion | 31% | 17% | 35% | 34% | 39% | |
Significance proportion (>95%) | 76.42% | 85.75% | 50.95% | 87.21% | 52.48% | |
Linear trend (npp:6.617) | 16.874 | −7.2665 | 2.9609 | 0.0721 | −0.7512 | |
Linear correlation coefficient with NPP | 0.58 | −0.27 | 0.45 | 0.55 | −0.89 |
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Tian, K.; Liu, X.; Zhang, B.; Wang, Z.; Xu, G.; Chang, K.; Xu, P.; Han, B. Analysis of Spatiotemporal Evolution and Influencing Factors of Vegetation Net Primary Productivity in the Yellow River Basin from 2000 to 2022. Sustainability 2024, 16, 381. https://doi.org/10.3390/su16010381
Tian K, Liu X, Zhang B, Wang Z, Xu G, Chang K, Xu P, Han B. Analysis of Spatiotemporal Evolution and Influencing Factors of Vegetation Net Primary Productivity in the Yellow River Basin from 2000 to 2022. Sustainability. 2024; 16(1):381. https://doi.org/10.3390/su16010381
Chicago/Turabian StyleTian, Kunjun, Xing Liu, Bingbing Zhang, Zhengtao Wang, Gong Xu, Kai Chang, Pengfei Xu, and Baomin Han. 2024. "Analysis of Spatiotemporal Evolution and Influencing Factors of Vegetation Net Primary Productivity in the Yellow River Basin from 2000 to 2022" Sustainability 16, no. 1: 381. https://doi.org/10.3390/su16010381
APA StyleTian, K., Liu, X., Zhang, B., Wang, Z., Xu, G., Chang, K., Xu, P., & Han, B. (2024). Analysis of Spatiotemporal Evolution and Influencing Factors of Vegetation Net Primary Productivity in the Yellow River Basin from 2000 to 2022. Sustainability, 16(1), 381. https://doi.org/10.3390/su16010381