研究目的
To provide insight into the responses of diverse vegetation biomes to ongoing recent climate warming by exploring vegetation behavior in representative warming places across global vegetation biomes.
研究成果
Climate warming relaxes heat constraints on vegetation activity in high-latitude areas (>60° N), promoting growth, but imposes negative impacts through drought and heat stress in mid to low latitude areas. Forest biomes are more resistant than crops to elevated temperatures. Further studies should systematically consider other factors like water availability and CO2 fertilization.
研究不足
The study focuses on temperature effects and may not fully account for other influential factors such as water availability, radiation, CO2 fertilization, and human disturbance, which synergistically impact vegetation biome activity. The data resolution and time period (1982–2013) might limit the generalizability of findings.
1：Experimental Design and Method Selection:
The study used a two-step procedure to identify representative warming places with significant positive mean annual temperature (MAT) trends (p <
2：01) and selected study sites from the 90th percentile of MAT increments to amplify the effect of climate warming on vegetation activity. Sample Selection and Data Sources:
Global gridded temperature data (
3：5° resolution, 1982–2013) from the University of Delaware, and remote sensing data including NDVI3g (8 km resolution, 1982–2013) from NASA's AVHRR instruments and MODIS land cover data (1 km resolution) for vegetation biomes classification. List of Experimental Equipment and Materials:
Not specified beyond data sources; no physical equipment mentioned.
4：Experimental Procedures and Operational Workflow:
Summarized 15-day MVC NDVI values to monthly and then yearly NDVI, calculated MAT from monthly air temperatures, identified warming sites, and analyzed heat responses using linear and quadratic functions.
5：Data Analysis Methods:
Statistical analysis including trend significance (p-values) for NDVI responses to temperature changes, using methods like linear and quadratic regression.
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