Exploring the Non-Stationary Effects of Forests and Developed Land within Watersheds on Biological Indicators of Streams Using Geographically-Weighted Regression

An, Alicia Kyoungjin; Lee, Sang‐Woo; Hwang, Soon‐Jin; Park, Se-Rin; Hwang, Sun-Ah

doi:10.3390/w8040120

Cited by 14 publications

(19 citation statements)

References 58 publications

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“…At present, most of the studies about the feedback of biomass or the community structure of algae on environmental factors are based on laboratory cultivation, ecological simulation or field sampling [31,32]. However, studies about the impact of land use change-induced water quality disturbances on the biomass and community structures of algae are still not adequate at the regional scale [33,34].…”

Section: Introductionmentioning

confidence: 99%

Effects of Land Use on Stream Water Quality in the Rapidly Urbanized Areas: A Multiscale Analysis

Song

Shao

et al. 2020

Water

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The land use and land cover changes in rapidly urbanized regions is one of the main causes of water quality deterioration. However, due to the heterogeneity of urban land use patterns and spatial scale effects, a clear understanding of the relationships between land use and water quality remains elusive. The primary purpose of this study is to investigate the effects of land use on water quality across multi scales in a rapidly urbanized region in Hangzhou City, China. The results showed that the response characteristics of stream water quality to land use were spatial scale-dependent. The total nitrogen (TN) was more closely related with land use at the circular buffer scale, whilst stronger correlations could be found between land use and algae biomass at the riparian buffer scales. Under the circular buffer scale, the forest and urban greenspace were more influential to the TN at small buffer scales, whilst significant positive or negative correlations could be found between the TN and the areas of industrial land or the wetland and river as the buffer scales increased. The redundancy analysis (RDA) showed that more than 40% variations in water quality could be explained by the landscape metrics at all circular and riparian buffer scales, and this suggests that land use pattern was an important factor influencing water quality. The variation in water quality explained by landscape metrics increased with the increase of buffer size, and this implies that land use pattern could have a closer correlation with water quality at larger spatial scales.

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Section: Introductionmentioning

confidence: 99%

Effects of Land Use on Stream Water Quality in the Rapidly Urbanized Areas: A Multiscale Analysis

Song

Shao

et al. 2020

Water

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“…When I is close to −1 or 1, the residuals of the estimated OLS and GWR models are strongly spatially dependent [66], which violates a fundamental assumption of statistical analysis. Lower AICc values indicate a closer approximation of the model to the actual nature of the relationships of dependent variables (i.e., percentage of Japanese red pine trees, elevation, and slope) with a dependent variable (i.e., burn severity) within a grid [37]. ArcMap GIS was used to compute Moran's I-values and visualize the localized variation in the effects of Japanese red pine on burn severity over the study area.…”

Section: Spatial Distribution Of Burn Severity and Percentage Of Japamentioning

confidence: 99%

“…The OLS model (Equation (1)) can be considered a special case of the GWR model (Equation (2)) in which the parameter surface is assumed to be constant over space [36][37][38][50][51][52]. Equation (2) is not a single equation; rather, it comprises an array of equations corresponding to different grid cells.…”

Section: Estimating the Global (Ols) And Local (Gwr) Modelsmentioning

confidence: 99%

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Examining Spatial Variation in the Effects of Japanese Red Pine (Pinus densiflora) on Burn Severity Using Geographically Weighted Regression

2017

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Abstract:Burn severity has profound impacts on the response of post-fire forest ecosystems to fire events. Numerous previous studies have reported that burn severity is determined by variables such as meteorological conditions, pre-fire forest structure, and fuel characteristics. An underlying assumption of these studies was the constant effects of environmental variables on burn severity over space, and these analyses therefore did not consider the spatial dimension. This study examined spatial variation in the effects of Japanese red pine (Pinus densiflora) on burn severity. Specifically, this study investigated the presence of spatially varying relationships between Japanese red pine and burn severity due to changes in slope and elevation. We estimated conventional ordinary least squares (OLS) and geographically weighted regression (GWR) models and compared them using three criteria; the coefficients of determination (R 2 ), Akaike information criterion for small samples (AICc), and Moran's I-value. The GWR model performed considerably better than the OLS model in explaining variation in burn severity. The results provided strong evidence that the effect of Japanese red pine on burn severity was not constant but varied spatially. Elevation was a significant factor in the variation in the effects of Japanese red pine on burn severity. The influence of red pine on burn severity was considerably higher in low-elevation areas but became less important than the other variables in high-elevation areas. The results of this study can be applied to location-specific strategies for forest managers and can be adopted to improve fire simulation models to more realistically mimic the nature of fire behavior.

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“…An et al [23] examined the non-stationary relationship between the ecological condition of streams and the proportions of forest and developed land in watersheds by using geographically weighted regression (GWR). They found that the GWR model had superior performance compared with the ordinary least squares method model.…”

Section: Contributionsmentioning

confidence: 99%

Ecological Monitoring, Assessment, and Management in Freshwater Systems

Park

Hwang

2016

Water

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Ecological monitoring and assessment is fundamental for effective management of ecosystems. As an introduction to this Special Issue, this editorial provides an overview of "Ecological Monitoring, Assessment, and Management in Freshwater Systems". This issue contains a review article on monitoring surface waters, and research papers on data management, biological assessment of aquatic ecosystems, water quality assessment, effects of land use on aquatic ecosystems, etc. The papers in this issue contribute to the existing scientific knowledge of freshwater ecology. They also contribute to the development of more reliable biological monitoring and assessment methods for sustainable freshwater ecosystems and ecologically acceptable decision-making policies, and establishment of practices for effective ecosystem management and conservation.

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Exploring the Non-Stationary Effects of Forests and Developed Land within Watersheds on Biological Indicators of Streams Using Geographically-Weighted Regression

Cited by 14 publications

References 58 publications

Effects of Land Use on Stream Water Quality in the Rapidly Urbanized Areas: A Multiscale Analysis

Effects of Land Use on Stream Water Quality in the Rapidly Urbanized Areas: A Multiscale Analysis

Examining Spatial Variation in the Effects of Japanese Red Pine (Pinus densiflora) on Burn Severity Using Geographically Weighted Regression

Ecological Monitoring, Assessment, and Management in Freshwater Systems

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