Effects of land use patterns on the interannual variations of carbon sinks of terrestrial ecosystems in China

Liu, Jiaxiang; Wang, Zheng; Duan, Yafeng; Li, Xinrui; Zhang, Mingyang; Liu, Huiyu; Xue, Peng; Gong, Haibo; Wang, Xing; Chen, Yu; Geng, Yinuo

doi:10.1016/j.ecolind.2023.109914

Cited by 11 publications

(4 citation statements)

References 51 publications

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“…City's leading carbon sinks come from non-construction land and crops, such as forest land, grassland, and water areas. Considering that it is difficult to obtain relevant vegetation survey data, this paper uses the carbon absorption per unit area of land use to calculate the carbon sink of forest land [43], water areas [44], and unused land [45]. Based on the carbon absorption rate, economic yield, water content, and economic coefficient of each crop in the city, the carbon sink of agricultural activities can be calculated [46].…”

Section: Carbon Emission Measurement Of Urban Sectorsmentioning

confidence: 99%

Carbon Emission Patterns and Carbon Balance Zoning in Urban Territorial Spaces Based on Multisource Data: A Case Study of Suzhou City, China

Zhang,

Yu,

Hou

et al. 2023

IJGI

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The concept of green and low-carbon development is integrated into territorial spatial planning and district control research. It is one of the systematic policy tools for emission reduction and carbon sequestration, greatly contributing to achieving the double carbon goal. This paper presents a method for measuring the carbon emissions of urban territorial spaces using multisource big data, aiming to identify the spatial patterns and levels of carbon emissions at microspatial scales. The spatial patterns of carbon emissions were used to construct a carbon balance zoning method to evaluate the regional differences in the spatial distribution of carbon emissions, taking Suzhou as an example to achieve carbon balance zoning at the micro scale of the city. Based on our research, the following was determined: (1) Suzhou’s total carbon emissions in 2020 was approximately 240.3 million tons, with the industrial sector accounting for 81.32% of these emissions. The total carbon sink was about 0.025 million tons. (2) In Suzhou City, the high-value plots of carbon emissions are mainly located in industrial agglomeration areas. By contrast, low-value plots are primarily located in suburban areas and various carbon sink functional areas, exhibiting a scattered distribution. (3) The territorial space unit was divided into four functional areas of carbon balance, with 36 low-carbon economic zone units accounting for 37.11%, 29 carbon-source control zone units accounting for 29.90%, 14 carbon-sink functional zone units accounting for 14.43%, and 18 high-carbon optimization zone units accounting for 18.56%. As a result of this study, carbon balance zoning was achieved at the grassroots space level, which will assist the city in low-carbon and refined urban governance. Some ideas and references are also provided to formulate policies for low-carbon development at the micro scale of a city.

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Section: Carbon Emission Measurement Of Urban Sectorsmentioning

confidence: 99%

Carbon Emission Patterns and Carbon Balance Zoning in Urban Territorial Spaces Based on Multisource Data: A Case Study of Suzhou City, China

Zhang,

Yu,

Hou

et al. 2023

IJGI

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“…China is located in the southeastern part of Eurasia, along the western coast of the Pacific Ocean, and is characterized by a strong thermal contrast between land and sea [26,27] (Figure 1). China possesses the world's most typical monsoon climate zone, with high temperatures and heavy precipitation in summer and cold and poor precipitation in winter, when the high-temperature period coincides with the rainy period [28]. China is home to a rich diversity of vegetation types, ranging from cold boreal coniferous forests to warm subtropical broadleaf evergreen forests and tropical rainforests.…”

Section: Research Regionmentioning

confidence: 99%

Net Primary Productivity Estimation of Terrestrial Ecosystems in China with Regard to Saturation Effects and Its Spatiotemporal Evolutionary Impact Factors

Zhang

2023

Remote Sensing

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The net primary productivity (NPP) of vegetation holds a pivotal character for the global carbon balance as a key parameter for characterizing terrestrial ecological processes. The most commonly used indices for estimating vegetation NPP, for instance, the normalized difference vegetation index (NDVI), often suffer from saturation issues that can compromise the accuracy of NPP estimation. This research utilizes a new vegetation index based on the radial basis function (RBF) to estimate vegetation NPP in Chinese terrestrial ecosystems over the past two decades (2001–2020) and investigates the spatiotemporal variation characteristics of NPP and the driving mechanisms. The results indicate that the kernel vegetation index (kNDVI) can effectively alleviate the saturation problem and significantly improve the accuracy of NPP estimation compared to NDVI. Over the past two decades, the NPP of Chinese terrestrial vegetation ranged from 64.13 to 79.72 g C/m2, with a mean value of 72.75 g C/m2, showing a fluctuating upward trend. Changes in the NPP of terrestrial ecosystems in China are mainly affected by precipitation. The dominant factors influencing NPP changes varied over time and had different impacts. For instance, in the period of 2001–2005 the climate had a positive effect on NPP changes, with the dominant factors being evaporation and precipitation. However, in the period of 2010–2015 the dominant climate factors shifted to evaporation and temperature, and their effect on NPP changes became negative. The outcomes of this research aim to serve as a foundation for carbon cycle research and ecosystem environment construction in China.

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“…Overlooking the nonlinear features of NEP may mask the ongoing phenomena of NEP intensification and declining trend transitions [20]. Thus, understanding the nonlinear changes in NEP can help identify the key states and inflection points of ecosystems, facilitating the formulation of appropriate conservation strategies and management measures, which is crucial for guiding ecosystem management and preservation [21]. However, Empirical Mode Decomposition Ensemble (EEMD), as a nonlinear trend analysis method, possesses advantages such as adaptability, effective noise reduction, independence from prior knowledge, natural decomposition, a non-parametric nature, and multi-level decomposition integration.…”

Section: Introductionmentioning

confidence: 99%

Characteristic Analysis of Carbon Sink Capacity Changes in Xinjiang’s Terrestrial Ecosystem Based on EEMD

Zhang,

Zheng,

Zhang

et al. 2024

Sustainability

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Net Ecosystem Productivity (NEP) is an important measure to assess the carbon balance and dynamics of ecosystems, providing a direct measure of carbon source–sink dynamics in terrestrial ecosystems and finding widespread applications in carbon cycle research. However, the nonlinear characteristics of NEP in Xinjiang’s terrestrial ecosystems remain unclear. Additionally, the influence of land use patterns, temperature, and precipitation variations on carbon sink capacity remains unclear. Ensemble Empirical Mode Decomposition (EEMD) is used to investigate the nonlinear variation of NEP in Xinjiang. Landscape pattern analysis of Xinjiang’s land use patterns from 1981 to 2019 is conducted using a 30 km moving window, and the interannual relationships between NEP, land use patterns, and meteorological factors are investigated through EEMD detrending analysis and Pearson correlation. The findings indicate that: (1) NEP exhibits interannual variations, primarily concentrated in the foothills of the Tianshan Mountains, with a three-year cycle. (2) Although NEP changes in most regions are not significant, urban clusters on the northern slopes of the Tianshan Mountains show noteworthy trends, with initial decrease followed by an increase, covering around 34.87% of the total area. Areas at risk of NEP decline constitute approximately 7.32% of the total area. (3) Across Xinjiang, we observe a widespread rise in patch fragmentation and complexity, coupled with a decline in patch connectivity and the size of the dominant patch. Additionally, there is a notable increase in both the diversity and evenness of land use types. However, the correlation between land use patterns and NEP is generally found to be insignificant in the majority of areas, with a percentage exceeding 85%. (4) Approximately 62% of regions in Xinjiang have NEP that is positively correlated with temperature, with significance observed in 33% of these areas. Furthermore, almost 95% of regions demonstrate that NEP is positively correlated with precipitation, with significance noted in 83% of these regions. It appears that precipitation exerts a more pronounced influence on NEP fluctuations in Xinjiang when compared to temperature.

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Effects of land use patterns on the interannual variations of carbon sinks of terrestrial ecosystems in China

Cited by 11 publications

References 51 publications

Carbon Emission Patterns and Carbon Balance Zoning in Urban Territorial Spaces Based on Multisource Data: A Case Study of Suzhou City, China

Carbon Emission Patterns and Carbon Balance Zoning in Urban Territorial Spaces Based on Multisource Data: A Case Study of Suzhou City, China

Net Primary Productivity Estimation of Terrestrial Ecosystems in China with Regard to Saturation Effects and Its Spatiotemporal Evolutionary Impact Factors

Characteristic Analysis of Carbon Sink Capacity Changes in Xinjiang’s Terrestrial Ecosystem Based on EEMD

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