The impact of climate change and human activities to vegetation carbon sequestration variation in Sichuan and Chongqing

Feng, Haopeng; Kang, Ping; Deng, Zhongci; Zhao, Wei; Hua, Ming; Zhu, Xinyue; Wang, Zhen

doi:10.1016/j.envres.2023.117138

Cited by 10 publications

(8 citation statements)

References 53 publications

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“…Temperature, a crucial climatic variable, wields considerable influence upon the phen logical and developmental processes of vegetation. In the hierarchy of explanatory variab affecting vegetative growth, it is acknowledged as the secondary determinant after precipi tion, as corroborated by multiple studies [1,4,12,19,23,28]. Climate and temperature have strong positive link in regions like the northern riparian zone, JDH, and CSH.…”

Section: Npp's Response To Climate-related Factorsmentioning

confidence: 87%

“…It is not only a key indicator for measuring the ecosystem's carbon sequestration capacity but also directly reflects the ecosystem's productivity and potential to sustain life activities [2][3][4]. Previous research on NPP contributes significantly to determining the carbon source and storage function of ecosystems, quantifying the Earth's carrying capacity, and analyzing the sustainable development of terrestrial ecosystems [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

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The Impact of Climate Change and Human Activities on the Spatial and Temporal Variations of Vegetation NPP in the Hilly-Plain Region of Shandong Province, China

Wu,

Yang,

et al. 2024

Forests

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Studying the spatio-temporal changes and driving mechanisms of vegetation’s net primary productivity (NPP) is critical for achieving green and low-carbon development, as well as the carbon peaking and carbon neutrality goals. This article employs various analytical approaches, including the Carnegie–Ames–Stanford approach (CASA) model, Theil–Sen median estimator, coefficient of variation, Hurst index, and land-use and land-cover change (LUCC) transition matrix, to conduct a thorough study of NPP variations in the Shandong Hilly Plain (SDHP) region. Furthermore, the geographic detector method was used to investigate the synergistic effects of meteorological changes and human activities on NPP in this region. Between 2000 and 2020, the vegetation NPP in the SDHP exhibited an average increase rate of 0.537 g C·m−2·a−1. However, the fluctuation in mean annual NPP, ranging from 203 to 230 g C·m−2·a−1, underscores an uneven growth pattern. Significant regional disparities are evident in vegetation NPP, gradually ascending from the southeast to the northwest and from the coastal areas to inland regions. The average Hurst index for the entire study area stands at 0.556, indicating an overall sustained growth trend in the time series of SDHP vegetation NPP. The vegetation NPP changes in SDHP can be well explained by climate variables (mean annual temperature, mean annual precipitation) and human activities (LUCC, night light index); of these, LUCC (q = 0.684) has the highest explanatory power on the impact of NPP and is a major influencing factor. This study deepens the understanding of the driving factors and patterns of vegetation’s dynamic response to climate change and human activities in the SDHP region. At the same time, it provides valuable scientific insights for improving ecosystem quality and promoting the carbon peaking and carbon neutrality goals.

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Section: Npp's Response To Climate-related Factorsmentioning

confidence: 87%

Section: Introductionmentioning

confidence: 99%

The Impact of Climate Change and Human Activities on the Spatial and Temporal Variations of Vegetation NPP in the Hilly-Plain Region of Shandong Province, China

Wu,

Yang,

et al. 2024

Forests

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“…Among them, precipitation and temperature are the main climate factors (Yan et al, 2022;Xu et al, 2024a), which are directly related to the hydrological cycle, soil evapotranspiration, and biological growth. Vegetation is crucial to ecosystems and is of great significance in climate regulation and water conservation (Zheng et al, 2020a;Feng et al, 2023). Population density, land use intensity, and GDP per land are the main anthropogenic factors.…”

Section: Driving Factorsmentioning

confidence: 99%

Spatio-temporal evolution and driving factors of regulating ecosystem service value: a case study of Poyang Lake Area, China

Liu,

Huang,

Liu

et al. 2024

Front. Ecol. Evol.

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Clarifying the driving mechanisms of spatial and temporal changes in the regulating ecosystem service value (RESV) is an important part of realizing the goal of sustainable development. Existing studies have focused on specific factors, ignoring the complex interactions between factors and their regional differences. In this regard, the spatial and temporal changes of RESV and its driving mechanisms in the different zones (core area, fringe area, and peripheral area) were explored in the Poyang Lake Area, China. The results showed that RESV spatially showed the distribution characteristics of fringe area > core area > peripheral area, while the lakes influenced the provision of regulating ecosystem services, showing that RESV per unit area was higher in the core area, and gradually declined with the increase of distance from the lakes, presenting the decreasing trend of fringe area > peripheral area. From 2000 to 2020, the study area lost 70.5988 billion CNY for RESV, in which the core area was the most affected. Further analysis of the driving mechanism of RESV in different areas found that there are regional differences in the paths of the driving factors: Population density mainly affects the core area, precipitation mainly affects the fringe area, and GDP per land mainly affects the peripheral area.

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“…The development of Remote Sensing and Geographic Information System technology has provided basic support for carbon sequestration accounting and monitoring [30]. Net ecosystem productivity (NEP) is a key indicator that directly describes the carbon sources/sequestration capacity of terrestrial ecosystems [21,31,32] and is widely used in regional carbon sequestration assessments [33,34]. The CASA (Carnegie Ames Stanford Approach) model is a representative model based on light use efficiency [35], and it can effectively support accounting for long time periods and a large regional NEP because of its data availability, its ability to reflect the distribution of carbon sequestration in large-scale regions, and the ease with which it can be used for long-term monitoring and estimation of carbon sequestration.…”

Section: Introductionmentioning

confidence: 99%

Spatial-Temporal Dynamics of Carbon Budgets and Carbon Balance Zoning: A Case Study of the Middle Reaches of the Yangtze River Urban Agglomerations, China

Fan,

Wang,

Han

et al. 2024

Land

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Analysis of the spatial variation characteristics of regional carbon sources/sinks is a prerequisite for clarifying the position of carbon balance zones and formulating measures to reduce emissions and increase sinks. Studies of carbon sinks have often used the coefficient method, which is limited by sample size, measurement error, and low spatial resolution. In this study, 31 cities in the middle reaches of the Yangtze River urban agglomerations (MRYRUA) were studied with the improved CASA (Carnegie Ames Stanford Approach) model to estimate the grid-scale net ecosystem productivity (NEP) and explore the spatial-temporal evolution of carbon budgets from 2005 to 2020. By calculating the carbon balance index (CBI), economic contribution coefficient (ECC), and ecological support coefficient (ESC), carbon balance zoning was conducted. Corresponding suggestions are based on the carbon balance zoning results. From 2005 to 2020, carbon budgets increased and were high in the north-central region and low in the south. In addition, carbon sink functional zones were distributed in cities with rich ecological resources. Low-carbon economic zones shifted from the Poyang Lake Urban Agglomeration to the Wuhan City Circle; low-carbon optimization zones occurred from the Wuhan City Circle to the Poyang Lake Urban Agglomeration. Carbon intensity control and high-carbon optimization zones were distributed in cities with rapid economic development. Our results support the MRYRUA in achieving “double carbon” targets and formulating regional collaborative emissions reduction policies.

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The impact of climate change and human activities to vegetation carbon sequestration variation in Sichuan and Chongqing

Cited by 10 publications

References 53 publications

The Impact of Climate Change and Human Activities on the Spatial and Temporal Variations of Vegetation NPP in the Hilly-Plain Region of Shandong Province, China

The Impact of Climate Change and Human Activities on the Spatial and Temporal Variations of Vegetation NPP in the Hilly-Plain Region of Shandong Province, China

Spatio-temporal evolution and driving factors of regulating ecosystem service value: a case study of Poyang Lake Area, China

Spatial-Temporal Dynamics of Carbon Budgets and Carbon Balance Zoning: A Case Study of the Middle Reaches of the Yangtze River Urban Agglomerations, China

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