Temporal and spatial variation of gross primary productivity and its response to extreme climate in Mongolia
Монгол орны ургамлын нийт анхдагч бүтээгдэхүүний орон зай, цаг хугацааны өөрчлөлт, эрс тэс уур амьсгалын үзүүлэх нөлөө
DOI:
https://doi.org/10.22353/gi.2026.26.06Keywords:
GPP, extreme climate events, extreme climate indices, Mongolia, Structural Equation Modeling (SEM)Abstract
Mongolia has extremely fragile ecosystems and rich vegetation resources in arid and semi-arid zones. It is highly affected by extreme climatic events and is important in the global carbon cycle. In global warming, it is important to study its vegetation changes for ecological security. In this paper, based on the gross primary productivity (GPP) data with daily maximum temperature, daily minimum temperature and daily precipitation data of Mongolia from 2000 to 2023, the characteristics of spatial and temporal changes in GPP and its response to climate extremes were analyzed by using Sen Slope + Mann-Kendall trend analysis, MK mutation test, Pearson's correlation analysis method, and structural equation modeling (SEM). The main findings of the study are as follows: (1) GPP shows an overall increasing trend, especially in the northern Mongolia, with 61% of the study area experiencing significant growth. (2) Extreme temperature indices (SU, TNx, TNn) and precipitation index R20 are increasing at most stations, while R95P and SDII are declining. (3) Extreme precipitation indices generally support GPP, though they suppress it in Western Mongolia. R20 is identified as the primary driver of vegetation growth. (4) TNx and SU inhibit GPP, except in North Mongolia, where warmer summers enhance productivity. R20 and R95P have opposing effects on GPP, highlighting the dual role of precipitation type and intensity.
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