Abstract
In the context of climate change, the climatic factors in the environment in which vegetation grows have changed significantly, with profound effects on the terrestrial carbon uptake process of photosynthesis. The total amount of carbon absorbed by photosynthesis is known as terrestrial carbon uptake, that is, the total primary productivity (GPP). It is of great significance to clarify the effects of climate factors on terrestrial carbon uptake and to analyze the characteristics of GPP changes in response to changes in temperature and precipitation in order to actively respond to climate change. This study proposes an integrated modeling approach to assess the impacts of temperature and precipitation changes on terrestrial carbon uptake. Firstly, the degree of influence of climate factors on GPP was analyzed. After analyzing historical trends in temperature and precipitation, we used a land surface model to simulate GPP under a range of projected warming and precipitation scenarios. It was found that temperature, precipitation, longwave radiation, shortwave radiation, and wind speed affected the vegetation GPP by 40.13%, of which temperature contributed 16.61% and precipitation 8.04% to the GPP. Over the last 20 years, temperature and precipitation have changed significantly, with both temperature and precipitation showing an increasing trend. As the temperature increased, GPP showed a decreasing trend from April to September, while showed an increasing trend from January to March and October to December. For every 0.1°C increase in temperature, the GPP of forests decreased by 1.68 gC/m2, while the GPP of grasslands was the least affected, with a 0.1°C increase in temperature resulting in a 1.01 gC/m2 decrease in the GPP of grasslands. Changes in precipitation had the greatest effect on grass, with a 10% increase in precipitation increasing the grass GPP by 6.44 gC/m2, while the least effect was on impervious surfaces, with a 10% increase in precipitation increasing the GPP by 2.42 gC/m2. This research contributes to understanding and predicting the impact of climate change on vegetation growth in southwestern China.
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