Attribution and driving force of nitrogen losses from the Taihu Lake Basin by the InVEST and GeoDetector models

He, Xinghua; Tian, Jiaming; Zhang, Yanqin; Zhao, Zihan; Cai, Zucong; Wang, Yanhua

doi:10.1038/s41598-023-34184-x

Cited by 6 publications

(2 citation statements)

References 65 publications

(74 reference statements)

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“…Even though biogeochemical modeling and biomass approaches are highly accurate in estimating carbon stocks, it is challenging to depict changes in carbon stocks over extended time periods, and the sheer amount of factors needed restricts the application scenarios [18,19]. The InVEST (Integrated Valuation of Environmental Services and Tradeoffs) model can simulate the changes in ecosystem services under different LUCC scenarios [20]. The model's terrestrial module can precisely evaluate how LUCC affects carbon storage [21].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Evolution and Prediction of Land Use and Carbon Stock in Shanghai

Xu,

Yu,

Lin

et al. 2024

Land

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Soil organic carbon (SOC) constitutes a critical component of carbon reservoirs within terrestrial ecosystems. The ramifications of urban land use transitions on SOC dynamics, particularly in rapidly urbanizing regions such as Shanghai, remain insufficiently elucidated. This investigation synergizes a predictive land use change model (Logistic-CA-Markov) with an ecosystem service quantification framework (InVEST), aiming to delineate the interplay between SOC variability and Land Use and Land Cover Change (LUCC) under natural development and ecological protection scenarios. Empirical observations from 2010 to 2020 reveal a contraction in Shanghai’s agricultural land of 34,912.76 hectares, juxtaposed with an expansion of urban built-up areas of 36,048.24 hectares. Projections for 2030 under an ecological protection scenario indicate a moderated urban sprawl, reducing built-up area expansion by 13,518 hectares relative to the natural development scenario. Notably, the net carbon sequestration capacity of Shanghai is anticipated to diminish by approximately 0.418 million tons between 2020 and 2030. This trend is observed under both considered scenarios, forecasting a cumulative reduction in SOC stocks exceeding 1 million tons by 2030. The natural development pathway portends a more pronounced and accelerated depletion of SOC reserves. Although ecological conservation measures show the potential to decelerate this loss, they appear insufficient to reverse the ongoing decline in SOC stocks. This study advocates for strategic urban planning interventions focused on constraining the growth of building densities and augmenting the preservation and management of eco-lands. Such measures are imperative for bolstering Shanghai’s carbon sequestration capacity.

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Section: Introductionmentioning

confidence: 99%

Spatiotemporal Evolution and Prediction of Land Use and Carbon Stock in Shanghai

Xu,

Yu,

Lin

et al. 2024

Land

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“…Yang et al [46] also applied Geodetector to detect the specific relationship between urban vitality and urban carbon emissions. He et al [47] combined InVEST and Geodetector models to estimate Nr losses in the Taihu Lake Basin from 1990 to 2020, as well as explore the driving forces. Recent attempts have been made to quantitatively explore the driving factors of soil salinity.…”

Section: Introductionmentioning

confidence: 99%

Analyzing Driving Factors of Soil Alkalinization Based on Geodetector—A Case in Northeast China

et al. 2023

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The Songnen Plain of Northeast China is one of the three largest soda saline–alkaline regions in the world. To better understand soil alkalinization in this important agricultural region of China, it is vital to explore the driving factors of soil alkalinity. Combined with prior research on the Wuyu’er–Shuangyang River Basin, this study examined the driving factors of soil alkalinity using the Geodetector method. First, the analysis results of the risk detector, the factor detector, and the ecological detector revealed the primary driving factors of soil alkalinity in the study area. Next, the analysis results of the interaction detector determined how combinations of driving factors impacted soil alkalinity in the study area. In general, the natural driving factors of altitude and spring temperature, especially altitude, played a key role in soil alkalinization. These results indicated that the closed terrain and warming trends were the main causes of soil alkalinization in the study area. In addition, there were significant enhance-nonlinear and enhance-bivariate relationships among the driving factors, which indicated that combined driving factors contributed more to soil alkalinization than individual driving factors.

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Biochar mediated carbon and nutrient dynamics under arable land

Abbas,

Hameed,

Shahani

et al. 2024

Biochar Production for Green Economy

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Attribution and driving force of nitrogen losses from the Taihu Lake Basin by the InVEST and GeoDetector models

Cited by 6 publications

References 65 publications

Spatiotemporal Evolution and Prediction of Land Use and Carbon Stock in Shanghai

Spatiotemporal Evolution and Prediction of Land Use and Carbon Stock in Shanghai

Analyzing Driving Factors of Soil Alkalinization Based on Geodetector—A Case in Northeast China

Biochar mediated carbon and nutrient dynamics under arable land

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