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Structural equation-based latent growth curve modeling of watershed attribute-regulated stream sensitivity to reduced acidic deposition

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  • Chen, Yushun
  • Lin, Lian-Shin

Abstract

Little information is available about the effects of watershed attributes on long-term stream chemical responses to reduced acidic deposition. Long-term chemical data (1980–2006) for 21 stream sites from the Appalachian Mountain region and data of 8 watershed attributes of the corresponding watersheds were analyzed to study such effects. Latent growth curve modeling (LGM), a structural equation modeling (SEM) approach, was conducted to quantify stream sensitivity to reduced acidic deposition in the region, and to model the initial chemical conditions (intercepts) and changing rates (slopes) in three time periods: 1980s, 1990s, and 2000s. The modeled chemical trends were generally consistent with those trends which were detected by trend analyses in a previous study. Watershed attributes including area, mean elevation, percentage of developed land, percentage of grassland, percentages of shale and sandstone, percentage of barren land, and percentage of soil type Gilpin-Upshur-Vandalia (GUV) were found to affect stream sensitivity to the reduced acidic deposition with their importance in the respective order. The stream sensitivity in turn regulated streams’ chemical initial conditions and their changing rates in the studied watersheds. This innovative application of LGM for modeling long-term chemical trends advanced our understanding of the role of watershed attributes in regulating streams’ responses to reduced acidic deposition. This approach can be applied for evaluating streams’ responses to acidic deposition in other regions and, more broadly, for studying causal effects on long-term behaviors in other ecological and environmental science subjects.

Suggested Citation

  • Chen, Yushun & Lin, Lian-Shin, 2010. "Structural equation-based latent growth curve modeling of watershed attribute-regulated stream sensitivity to reduced acidic deposition," Ecological Modelling, Elsevier, vol. 221(17), pages 2086-2094.
    • Handle: RePEc:eee:ecomod:v:221:y:2010:i:17:p:2086-2094
    DOI: 10.1016/j.ecolmodel.2010.05.010
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    References listed on IDEAS

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    2. Yun Wang & Xuedong Yan & Yu Zhou & Qingwan Xue, 2017. "Influencing Mechanism of Potential Factors on Passengers’ Long-Distance Travel Mode Choices Based on Structural Equation Modeling," Sustainability, MDPI, vol. 9(11), pages 1-22, October.

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