Grassland Phenology’s Sensitivity to Extreme Climate Indices in the Sichuan Province, Western China
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Source
2.3. Methods
2.3.1. Phenological Extraction Method
2.3.2. Trend Analysis
2.3.3. Temperature Vegetation Dryness Index (TVDI)
2.3.4. Analysis of the Persistence of Phenological Changes Using Hurst Exponent and Rescaled Range (R/S) Analysis
2.3.5. Sensitivity Analysis
3. Results
3.1. Assessment of the MOD13A1 Data
3.2. Spatial Distribution Patterns of Grassland Vegetation Phenology
3.3. Analysis of Interannual Phenological Variation
3.4. Analysis of the Future Viability of the Phenological Period
3.5. The Significant Influence of Extreme Climate Indices on Phenological Variables
3.6. Analysis of Phenology Sensitivity to Extreme Climate Indices
4. Discussion
4.1. The Relationship between Grassland SOS and EOS, and Ground Observation and Remote Sensing Inversion Methods
4.2. Trends in Grassland SOS and EOS
4.3. The Relationship between Grassland Phenology and Extreme Climate Indices
4.4. Limitations
5. Conclusions
- The SOS vegetation in Sichuan Province gradually evolves with the geography of the slopes from west to east and from the surrounding mountains to the core basin. Climatic changes are strongly dependent on elevation, with most vegetation in the study area showing a trend of advancing SOS. Phenological EOS values of the different vegetation types differed and showed a trend towards delayed EOS. The development of grassland vegetation SOS was gradually delayed from mid to high altitudes, while it advanced at EOS. The tendency towards delayed SOS could be caused by insufficient cooling due to the warming climate in late autumn and winter.
- The future viability of grassland based on Hurst exponents showed that the changing trend of SOS and the changing trend between 2001 and 2020 were generally weak and opposite; i.e., grassland SOS could be delayed, which means that future trends are more random and have no clear direction. Pixels with a Hurst exponent greater than 0.5 in the Sichuan Basin indicate that the sustainability of vegetation EOS in the future will continue the same trend as the average level of change over the past 20 years, and there will be a shifting trend. To avoid the risk of ecological degradation, we need to take a series of measures to protect the plateau ecosystem: environmental protection projects should be further promoted, natural ecological reserves should be established, local people’s awareness of environmental protection and nature conservation should be raised, afforestation and artificial grassland construction should take place, and excessive development should be avoided. In addition, reasonable resource planning and allocation will help to better manage environmental security problems in the province.
- Grassland SOS was mainly influenced by the yearly maximum consecutive five-day precipitation, diurnal temperature, and temperature-vegetation dryness index, while EOS was mainly influenced by yearly minimum daily temperature, yearly mean temperature, and temperature-vegetation dryness index. Vegetation phenology in Sichuan province showed heterogeneous regional differentiation in response to different climate indices, with positive sensitivity coefficients between SOS and the climate indices compared to negative sensitivity coefficients between EOS and the climate indices. This suggests that extreme climate change leading to an advance in vegetation SOS may indirectly leads to an advance in vegetation EOS. SOS and EOS were strongly influenced by extreme climate and drought, implying that high temperatures lead to evaporation of moisture from the soil, resulting in a lack of rainfall leading to drought. SOS correlated positively with the yearly maximum consecutive five-day precipitation and temperature-vegetation dryness index, implying that precipitation and drought had a strong influence on vegetation growth.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Indicators | Description |
---|---|
DEM | Digital elevation model |
RS | Solar radiation |
ET | Evapotranspiration |
TVDI | Temperature vegetation dryness index |
PER | Yearly mean accumulated precipitation |
RX1 | Yearly maximum consecutive one-day precipitation |
RX5 | Yearly maximum consecutive five-day precipitation |
DTR | Diurnal temperature range |
TEMP_MEAN | Yearly mean value of temperature |
TEMP_MAX | Yearly mean value of daily maximum temperature |
TEMP_MIN | Yearly mean value of daily minimum temperature |
TNN | Yearly minimum value of daily minimum temperature |
TNX | Yearly maximum value of daily minimum temperature |
TXN | Yearly minimum value of daily maximum temperature |
TXX | Yearly maximum value of daily maximum temperature |
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Adu, B.; Qin, G.; Li, C.; Wu, J. Grassland Phenology’s Sensitivity to Extreme Climate Indices in the Sichuan Province, Western China. Atmosphere 2021, 12, 1650. https://doi.org/10.3390/atmos12121650
Adu B, Qin G, Li C, Wu J. Grassland Phenology’s Sensitivity to Extreme Climate Indices in the Sichuan Province, Western China. Atmosphere. 2021; 12(12):1650. https://doi.org/10.3390/atmos12121650
Chicago/Turabian StyleAdu, Benjamin, Gexia Qin, Chunbin Li, and Jing Wu. 2021. "Grassland Phenology’s Sensitivity to Extreme Climate Indices in the Sichuan Province, Western China" Atmosphere 12, no. 12: 1650. https://doi.org/10.3390/atmos12121650