Increase or decrease? Integrating the CLUMondo and InVEST models to assess the impact of the implementation of the Major Function Oriented Zone planning on carbon storage

Nie, Xin; Lu, Bo; Chen, Zhoupeng; Yang, Yiwei; Chen, Shuo; Chen, Zhenghua; Wang, Han

doi:10.1016/j.ecolind.2020.106708

Cited by 71 publications

(30 citation statements)

References 57 publications

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“…The InVEST(version 3.7.0) carbon storage and sequestration model quantifies the amount of carbon stored based on the different land uses and carbon densities [37,38]. Carbon storage generally consists of two parts: vegetation carbon storage (aboveground biomass, underground biomass, and dead organic matter) and soil carbon storage.…”

Section: Carbon Storagementioning

confidence: 99%

Spatial-Temporal Variation and Tradeoffs/Synergies Analysis on Multiple Ecosystem Services: A Case Study in Fujian

Peng

Wei

2022

Sustainability

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The rapid urbanization process has severely affected the ecological security and ecosystem services (ESs) in China’s southern province of Fujian, and threated the sustainable development of the local economy and society in the last two decades. This study mapped the spatial-temporal variation of four types of ESs and evaluated the tradeoffs/synergies among the ESs in Fujian Province from 2000 to 2020 on the three scales of the province, city and county. The results showed that: (1) From 2000 to 2020, the three ESs functions of soil conservation service, carbon storage service, and habitat quality decreased, while the function of food supply service increased. (2) At the provincial scale, soil conservation services, carbon storage services, and habitat quality were in a synergistic relationship, and food supply service was always in tradeoffs relationships with soil conservation services, carbon storage services, and habitat quality. At the prefecture-level scale, the tradeoffs/synergies among ESs vary among prefecture-level cities. At the county scale, the Moran’s I index of bivariate spatial autocorrelation was consistent with the correlation coefficient, and the tradeoffs/synergies between ESs showed significant spatial heterogeneity. (3) Based on the correlation analysis method, the Ecosystem Service Tradeoff-synergy Degree (ESTD) model and bivariate spatial autocorrelation analysis can clearly show the relationship between various ESs, and the research results are relatively consistent. The spatial distribution of four ecosystem services in Fujian province showed a specific aggregation pattern. High—high concentrations and low—low concentrations are strong. Low—high agglomeration and high—low agglomeration are weak.

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Section: Carbon Storagementioning

confidence: 99%

Spatial-Temporal Variation and Tradeoffs/Synergies Analysis on Multiple Ecosystem Services: A Case Study in Fujian

Peng

Wei

2022

Sustainability

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“…The InVEST (Integrated Valuation of Ecosystem Services and Trade-offs) model was jointly developed by Stanford University, the World Wide Fund for Nature (WWF), and the Nature Conservancy (TNC) in 2007 (Yang et al 2020). The model was quickly favored by researchers and widely used in water yield (Cong et al 2020;Hu et al 2020;Wang & Han 2020), water purification (Srichaichana et al 2019), carbon storage (Maanan et al 2019;Li et al 2020;Nie et al 2020), soil and water conservation (Qi et al 2019;Hu et al 2020), and the evaluation of other ecological functions.…”

Section: Calculating Water Yield In the Invest Modelmentioning

confidence: 99%

“…National and international research has made many useful explorations (Nie et al 2020;Wang & Han 2020;Wang et al 2020a), but the research has mostly stayed at the stage of conceptual framework analysis, and there are relatively few studies that draw specific service flow path diagrams (Báldi & Vári 2020;Gao et al 2020;Tong & Shi 2020). The University of Vermont in the United States proposed the Service Path Attribution Networks (SPANs) model within the Artificial Intelligence for Ecosystem Services (ARIES) project (Bagstad et al 2013).…”

Section: Introductionmentioning

confidence: 99%

Analysis of water yield service of Lianshui River Basin in China based on ecosystem services flow model

Mao

2021

Water Supply

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Water security assessment is very important to social development. However, most studies only focus on the status quo of water security in a static state and ignore the flow characteristics of water resources into the water security assessment. This paper integrates multi-source data to construct a water supply and service supply-demand balance and spatial flow model in the Lianshui River Basin, simulates the spatial pattern of the service flow of the aquatic water ecosystem in the Lianshui River Basin from 1990 to 2018, and quantifies the service flow. Results show that (1) From 1990 to 2018, the water supply in the Lianshui River Basin first decreased, then increased, and finally decreased. Water yield was the highest in 2010 and lowest in 2000. (2) Water demand increased year by year, and the amount of area with a poor water resource security index increased, indicating that water security was deteriorating. (3) The four main beneficiary areas in the basin are the urban area of Lianyuan City, the county seat of Shuangfeng County, the Louxing District of Loudi City, and the urban area of Xiangxiang City and nearby towns. The service flow showed the same changing trend as the water yield. In 2018, the water resource gap in the beneficiary area was as high as 4.49 billion m3. Local governments should actively build a water-saving society, improve the efficiency of industrial and agricultural water-saving and residents' awareness of water-saving, and improve the water resources in the river basin. The research can provide a scientific basis for realizing the sustainable development of water resources in the Lianshui River Basin and improving the ecological compensation mechanism, and can also provide references for water resources management in other river basins.

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“…However, spatiotemporal changes in CS at the provincial scale and future changes in CS have not been thoroughly studied, especially with regard to the development needs of different cities. Analyzing the demands of different cities could help policymakers choose an optimal urbanization model and land use pattern for improving CS ( Gao & Wang, 2019 ; Nie et al, 2020 ). Scenario settings are useful tools for predicting the future impacts of LULC changes on CS and can be used to produce critical information for urban development and planning ( Sun & Shi, 2020 ; Tang et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Exploring the spatiotemporal changes in carbon storage under different development scenarios in Jiangsu Province, China

Zhang

Wang

ChunLei

et al. 2022

PeerJ

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Carbon storage (CS) is closely linked to the global challenge of climate change. Land use/cover (LULC) change is the main factor driving changes in CS, and evaluating the impact of LULC changes on CS is important for carbon balance. Taking Jiangsu Province as an example, we used the Integrated Valuation of Ecosystem Services and Trade-offs model to analyze the spatiotemporal changes in CS during 2000–2015. Then we coupled it with the patch-generating land use simulation model to simulate and predict LULC and CS in 2050 under four different development plans. The results showed that LULC change in Jiangsu Province was manifested mainly as transformation of cropland to construction land (3,485 km2) and cropland to water body (470 km2). The high value area for CS was concentrated mainly in forest land, water body and grassland, whereas the low value area was concentrated mainly in construction land. During 2000–2015, CS decreased by 0.23 Tg, and during 2015–2050, CS was predicted to decrease by 0.16, 1.69, 0.02, and 0.10 Tg under the baseline, fast, slow and harmonious development scenarios. The conversion of a large amount of cropland to construction land was the main cause of CS loss. In all scenarios, the carbon loss was the largest in southern Jiangsu and lowest in central Jiangsu. It is necessary to balance the conflict between economic development and ecological protection during the process of urbanization. This study can provide an important reference for decision makers during the formulation of regional development models and ecological management strategies.

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Increase or decrease? Integrating the CLUMondo and InVEST models to assess the impact of the implementation of the Major Function Oriented Zone planning on carbon storage

Cited by 71 publications

References 57 publications

Spatial-Temporal Variation and Tradeoffs/Synergies Analysis on Multiple Ecosystem Services: A Case Study in Fujian

Spatial-Temporal Variation and Tradeoffs/Synergies Analysis on Multiple Ecosystem Services: A Case Study in Fujian

Analysis of water yield service of Lianshui River Basin in China based on ecosystem services flow model

Exploring the spatiotemporal changes in carbon storage under different development scenarios in Jiangsu Province, China

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