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Relationships between Riparian Forest Fragmentation and Biological Indicators of Streams

Author

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  • Yirigui Yirigui

    (Graduate Program, Department of Environmental Science, Konkuk University, Gwangjin-gu, Seoul 05029, Korea)

  • Sang-Woo Lee

    (Department of Forestry and Landscape Architecture, Konkuk University, Gwangjin-gu, Seoul 05029, Korea)

  • A. Pouyan Nejadhashemi

    (Department of Biosystems and Agricultural Engineering, Michigan State University, East Lansing, MI 48824, USA)

  • Matthew R. Herman

    (Department of Biosystems and Agricultural Engineering, Michigan State University, East Lansing, MI 48824, USA)

  • Jong-Won Lee

    (Graduate Program, Department of Environmental Science, Konkuk University, Gwangjin-gu, Seoul 05029, Korea)

Abstract

Anthropogenic activities, such as land use and land cover modifications in riparian areas, can alter the degree of fragmentation of riparian vegetation, lead to the degradation of stream habitats, and affect biological communities in the streams. The characteristics of the riparian forests can modify the condition of stream environments and the transporting mechanisms of materials, sediments, nutrients, and pollutants loaded from the watersheds. This study aimed to examine the relationships between forest fragmentation and three biological indicators of trophic diatom, benthic macroinvertebrate, and the fish assessment in the Nakdong River, Korea. Eighty-nine biological assessment sampling sites in the National Aquatic Ecological Monitoring Program of South Korea were identified. For each sampling site, riparian forest data within a 500 m radius were extracted from national LULC using GIS to compute fragmentation metrics using FRAGSTATS software. Four fragmentation metrics—number of forest patches, percentage of riparian forest cover (PLAND), largest riparian forest patch index (LPI), and riparian forest division index (DIVISION)—were correlated with the biological indicators. Also, due to severe spatial autocorrelation among observations, the fragmentation metrics and stream environmental variables were regressed to biological indicators using regression tree analysis. Our results indicate that the biological indicators were significantly associated with most forest fragmentation metrics. We found positive correlations of PLAND and LPI with biological indicators, whereas DIVISION was negatively correlated with biological indicators. Both correlation and regression tree analyses revealed that the biological conditions of streams were likely to be better if riparian forests are less fragmented. Particularly, stronger relationships were revealed between macroinvertebrates and fish with the fragmentation metrics of riparian forests than with benthic diatoms. However, these relationships varied with elevation, stream size, and slope conditions. The results of this study reinforced the importance of including riparian forests in the planning, restoration, and management of stream environments. These results also suggested that planners and managers may need to consider different strategies for different stream environments and topographic characteristics in managing riparian forests.

Suggested Citation

  • Yirigui Yirigui & Sang-Woo Lee & A. Pouyan Nejadhashemi & Matthew R. Herman & Jong-Won Lee, 2019. "Relationships between Riparian Forest Fragmentation and Biological Indicators of Streams," Sustainability, MDPI, vol. 11(10), pages 1-24, May.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:10:p:2870-:d:232800
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    References listed on IDEAS

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    1. Miller, Jennifer & Franklin, Janet & Aspinall, Richard, 2007. "Incorporating spatial dependence in predictive vegetation models," Ecological Modelling, Elsevier, vol. 202(3), pages 225-242.
    2. Polterovich, Victor & Popov, Vladimir, 2006. "Эволюционная Теория Экономической Политики: Часть I: Опыт Быстрого Развития [An Evolutionary Theory of Economic Policy: Part I: The Experience of Fast Development]," MPRA Paper 22168, University Library of Munich, Germany.
    3. Peterson, Erin & Ver Hoef, Jay, 2014. "STARS: An ArcGIS Toolset Used to Calculate the Spatial Information Needed to Fit Spatial Statistical Models to Stream Network Data," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 56(i02).
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    Cited by:

    1. Yirigui Yirigui & Sang-Woo Lee & A. Pouyan Nejadhashemi, 2019. "Multi-Scale Assessment of Relationships between Fragmentation of Riparian Forests and Biological Conditions in Streams," Sustainability, MDPI, vol. 11(18), pages 1-24, September.
    2. Lisu Chen & Qiong Wei & Qiang Fu & Daolun Feng, 2021. "Spatiotemporal Evolution Analysis of Habitat Quality under High-Speed Urbanization: A Case Study of Urban Core Area of China Lin-Gang Free Trade Zone (2002–2019)," Land, MDPI, vol. 10(2), pages 1-21, February.
    3. Mi-Young Kim & Sang-Woo Lee, 2021. "Regression Tree Analysis for Stream Biological Indicators Considering Spatial Autocorrelation," IJERPH, MDPI, vol. 18(10), pages 1-19, May.
    4. Se-Rin Park & Suyeon Kim & Sang-Woo Lee, 2021. "Evaluating the Relationships between Riparian Land Cover Characteristics and Biological Integrity of Streams Using Random Forest Algorithms," IJERPH, MDPI, vol. 18(6), pages 1-14, March.
    5. Se-Rin Park & Sang-Woo Lee, 2020. "Spatially Varying and Scale-Dependent Relationships of Land Use Types with Stream Water Quality," IJERPH, MDPI, vol. 17(5), pages 1-22, March.
    6. Se-Rin Park & Soon-Jin Hwang & Kyungjin An & Sang-Woo Lee, 2021. "Identifying Key Watershed Characteristics That Affect the Biological Integrity of Streams in the Han River Watershed, Korea," Sustainability, MDPI, vol. 13(6), pages 1-15, March.

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