[Spatiotemporal Patterns and Driving Forces Analysis of Ecological Carbon Sink from 2001 to 2022 in Qinling-Daba Mountains,China].

Huan Jing Ke Xue

Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an 710127, China.

Published: January 2025

The Qinling-Daba Mountain area, an essential ecological conservation zone in China, occupies a pivotal position in the pursuit of carbon neutrality. Using diverse data sources, including temperature, precipitation, solar radiation, and the Normalized Difference Vegetation Index, we refined the CASA model by replacing model indicators. This enhanced model simulated the net primary productivity of vegetation in the Qinling-Daba Mountain area from 2001 to 2022. Additionally, we employed a method that subtracts soil respiration (Rh) from the simulated vegetation net primary productivity to calculate the regional net ecosystem productivity (NEP), thereby characterizing the ecological carbon sink. Employing techniques such as linear regression analysis, MK trend testing, partial correlation analysis, and composite correlation analysis, we examined the spatiotemporal evolution characteristics of NEP over the past 22 years in the Qinling-Daba Mountain area and assessed the degree of influence of various factors. Our findings revealed that: ① Over the past 22 years, the vegetation NEP in the Qinling-Daba Mountain area displayed a fluctuating upward trend, with an average annual increase of 168 g·m·a, resulting in a total increase of 52.2 Tg in regional vegetation NEP (in terms of C) over the 22-year period. ② Spatially, the Qinling-Daba Mountain area predominantly functioned as a carbon sink, with only 0.3% of the area serving as a carbon source, primarily concentrated in a punctate pattern on the eastern side of the Qinling-Daba Mountain area. ③ Changes in the carbon sink in the Qinling-Daba Mountain area were the consequence of the interaction of multiple factors, with 60% of the contribution stemming from climatic factors. The combined weak driving force of temperature, precipitation, and solar radiation accounted for as much as 29%, distributed in a scattered manner across the central and eastern regions of the Qinling-Daba Mountain area.

Download full-text PDF

Source
http://dx.doi.org/10.13227/j.hjkx.202401064DOI Listing

Publication Analysis

Top Keywords

qinling-daba mountain
32
mountain area
32
carbon sink
16
qinling-daba
9
area
9
ecological carbon
8
2001 2022
8
mountain
8
temperature precipitation
8
precipitation solar
8

Similar Publications

[Spatiotemporal Patterns and Driving Forces Analysis of Ecological Carbon Sink from 2001 to 2022 in Qinling-Daba Mountains,China].

Huan Jing Ke Xue

January 2025

Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an 710127, China.

The Qinling-Daba Mountain area, an essential ecological conservation zone in China, occupies a pivotal position in the pursuit of carbon neutrality. Using diverse data sources, including temperature, precipitation, solar radiation, and the Normalized Difference Vegetation Index, we refined the CASA model by replacing model indicators. This enhanced model simulated the net primary productivity of vegetation in the Qinling-Daba Mountain area from 2001 to 2022.

View Article and Find Full Text PDF

In this paper, we examined the elevation-dependent warming (EDW) patterns of MODIS LST across different seasons in the Qinling-Daba Mountains, further investigate the connections between the EDW patterns of Land surface temperature (LST) and land surface albedo (ALB) as well as aerosol optical depth (AOD). The key findings include: (1) Our study reveals a robust correlation between LST and air temperature in the Qinling-Daba Mountains, suggesting the feasibility of using MODIS LST to predict the temperature trends (2) During the period from 2001 to 2010, MODIS LST shows a significant EDW trend, primarily in the spring season. In contrast, a negative EDW is observed in the period during 2011-2021, which is contrary to the earlier decade, particularly during the autumn and winter seasons.

View Article and Find Full Text PDF

Pine wilt disease (PWD), caused by , severely threatens global pine forests. is the primary vector of in East Asia. Understanding the population structure and evolutionary forces of vector insects is critical for establishing effective PWD management strategies.

View Article and Find Full Text PDF

Accurate estimation of forest aboveground biomass (AGB) is crucial for understanding and managing forest ecosystems in the context of global environmental change, and also provides a scientific basis for national and regional ecological planning and carbon emission reduction policies. In order to investigate the regional pattern of forest AGB and its influencing factors in central China, a total of 469 sample plots were measured along four sample transects and on six mountains in field survey. The results showed that: 1) Two longitudinal distribution patterns of forest AGB were found, and one was that the AGB in the Qinling Mountains and the Daba Moutains gradually decreased from east to west, and the other was that the AGB in the areas between the two mountains gradually increased from east to west.

View Article and Find Full Text PDF

Understanding the impact of climate change on the geographical distribution of species is a fundamental requirement for biodiversity conservation and resource management. , an evergreen oak endemic to China, plays a crucial role in maintaining the ecological stability in subtropical regions and high economic value attributed to its dark and high-density heartwood, but the existing resources are close to endangered. Currently, limited knowledge exists regarding its distribution and potential influences of climate change on suitable areas.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!