Study on the threshold relationship between landscape pattern and water quality considering spatial scale effect—a case study of Dianchi Lake Basin in China

Zhong, Xincheng; Xu, Qiqi; Yi, Junhua; Jin, Lijuan

doi:10.1007/s11356-022-18970-0

Cited by 25 publications

(5 citation statements)

References 40 publications

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“…Most previous studies focusing on the scale effect of landscape patterns considered dividing the study area using regular shapes rather than using a more scientific basis. Although some studies combined the buffer zone and watershed (Xu et al, 2020;Zhong et al, 2022), a few studies combined regional ecology and development planning. This study not only emphasizes the scale effect of landscape patterns on the microscale but also divides the study area by using EFRs on the macro scale.…”

Section: Discussion the Microspatials And Macrospatial Scale Dependen...mentioning

confidence: 99%

Spatiotemporal Evolution of Landscape Patterns and Their Driving Forces Under Optimal Granularity and the Extent at the County and the Environmental Functional Regional Scales

Nie

Yang

et al. 2022

Front. Ecol. Evol.

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Research on the evolution and driving forces of landscape patterns can provide important support for ecological governance decision-making. However, the heterogeneity of landscape patterns at the microscale (grain size and extent) and the enforceability of the zoning scale at the macroscale deserve more attention. The optimal grain size (30 ×30 m) and the extent (500 m) for landscape pattern research were obtained by analyzing the fluctuation of landscape metrics and semivariogram models in this study. The research area was divided into environmental functional regions (EFRs), which were defined according to the main ecological functions and protection objectives of each region. The analysis results of land use and land cover changes (LUCCs) showed that land use transfer in the past 20 years occurred mainly between woodland and cultivated land at the county scale, but this was not always the case in EFRs. The results of the landscape pattern analysis showed that landscape fragmentation, aggregation, and heterogeneity increased at the county scale during 1999–2020. Moreover, except within agricultural environmental protection areas (AEP) and living environment guaranteed areas (LEG), the degree and the speed of landscape damage decreased by 2020, and the turning point occurred in 2006–2013. The analysis results of geographical detectors showed that the digital elevation mode (DEM) and GDP were the main driving factors in most regions. At the county scale, the average explanatory power of the selected factors increased by 13.27% and 16.16% in 2006–2013 and 2013–2020, respectively. Furthermore, the study area was divided into three categories according to the intensity of human disturbance. The areas with high human disturbance need to focus on increasing land-use intensification and strengthening the development in low-slope hill regions. The areas of moderate human disturbance need to focus on improving the connectivity of ecological patches and optimizing industrial structures. Attention should be given to the monitoring of natural drivers and policy support for ecological governance in low human disturbance areas. The methods and findings in this study can provide a reference for decision-makers to formulate land-use policies, especially for integration into relevant urban planning, such as the spatial planning of national land that is being widely implemented in China.

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Section: Discussion the Microspatials And Macrospatial Scale Dependen...mentioning

confidence: 99%

Spatiotemporal Evolution of Landscape Patterns and Their Driving Forces Under Optimal Granularity and the Extent at the County and the Environmental Functional Regional Scales

Nie

Yang

et al. 2022

Front. Ecol. Evol.

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“…Death and Collier (2010), for instance, reported that catchments which retained 80-90% indigenous vegetation cover were associated with fauna indicative of "clean" water quality, while streams draining catchments with 40-60% vegetation cover retained 80% of the biodiversity found in pristine streams. Both Clément et al (2017) and Zhong et al (2022) reported thresholds of between 45 and 47% natural vegetation cover, below which water quality was found to decline. Finally, in a literature review published by the Open Space Institute, Morse et al (2018) concluded that water quality tends to deteriorate when natural vegetation cover falls below 60-90% of the catchment area, while observing that a threshold of at least 70% forest cover appears to represent the consensus.…”

Section: Modelling and Threshold Estimationmentioning

confidence: 99%

Estimating thresholds of natural vegetation for the protection of water quality in South African catchments

Locke,

Winter

2024

Science of The Total Environment

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“…Among the published studies, several have reported that aquatic systems may undergo sudden changes in water quality and/or ecosystem health in response to changes in their surrounding landscapes (Dodds et al, 2010;Capon et al, 2015;Tayyebi et al, 2015;D'Amario et al, 2019;Chen & Olden, 2020;Liu et al, 2021;Wang et al, 2022;Zhong et al, 2022;Xu et al, 2023a). However, as not all ecosystems experience nonlinear responses to external perturbations, it is also possible to identify regulatory thresholds that reflect balanced trade-offs between environmental protection and socioeconomic development (Antoniuk, 2006;Johnson, 2013;Guntenspergen & Gross, 2014;Kelly et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

“…By contrast, natural vegetation may provide an alternative land cover metric for which thresholds can be estimated. Based on the studies that have been published, it was hypothesised that metrics of natural vegetation may serve as superior predictors of water quality and that it may therefore be possible to estimate the minimum amount of natural vegetation cover required to protect water quality in a given region (see, for example, Brabec et al, 2002;Black et al, 2004;Death & Collier, 2010;Tran et al, 2010;Miller et al, 2011;Feld, 2013;Attua et al, 2014;Iñiguez-Armijos et al, 2014;Midway et al, 2015;Clément et al, 2017;de Mello et al, 2017;Morse et al, 2018;Hanna et al, 2021;Zhong et al, 2022). Reported thresholds have varied, however, and the precise extent of natural vegetation cover required to provide adequate levels of protection in different contexts remains uncertain.…”

Section: Introductionmentioning

confidence: 99%

Estimating Thresholds of Natural Vegetation for the Protection of Water Quality in South African Catchments

Locke

2024

Preprint

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Many of South Africa’s water quality problems are directly attributable to the negative impacts of anthropogenic land use transformations, including urban and agricultural expansion. To mitigate these impacts, the preservation of an adequate amount of natural vegetation within catchment areas is an important management strategy. However, it is unclear how much natural vegetation cover is required to provide adequate levels of protection, nor at which scale(s) this strategy would be most effective. Accordingly, regression analysis was used to model relationships between water quality (measured using Nemerow’s Pollution Index) and metrics of natural vegetation at multiple scales across a sample of sub-catchments located within South Africa’s Eastern and Western Cape provinces. With conspicuous outliers removed, the models were able to explain between 69 and 82% of variation in the sample. Moreover, a statistically significant, nonlinear, and inverse relationship was found between proportions of natural vegetation cover and pollution levels. This relationship was strongest when measured (1) across the whole catchment and (2) within a 200 m riparian buffer zone. The models further indicated that approximately 80 to 90% natural vegetation cover was necessary at these scales to maintain water quality at ecologically acceptable levels. Additional nonlinear thresholds estimated using breakpoint analysis suggested that if proportions of natural vegetation fall below 45% (across the whole catchment) and 60% (within a 200 m riparian buffer zone) a dramatic increase in pollution levels can be expected.

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Study on the threshold relationship between landscape pattern and water quality considering spatial scale effect—a case study of Dianchi Lake Basin in China

Cited by 25 publications

References 40 publications

Spatiotemporal Evolution of Landscape Patterns and Their Driving Forces Under Optimal Granularity and the Extent at the County and the Environmental Functional Regional Scales

Spatiotemporal Evolution of Landscape Patterns and Their Driving Forces Under Optimal Granularity and the Extent at the County and the Environmental Functional Regional Scales

Estimating thresholds of natural vegetation for the protection of water quality in South African catchments

Estimating Thresholds of Natural Vegetation for the Protection of Water Quality in South African Catchments

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