IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v15y2018i10p2103-d171877.html
   My bibliography  Save this article

Distribution and Driving Factors of Forest Swamp Conversions in a Cold Temperate Region

Author

Listed:
  • Dandan Zhao

    (School of Geographical Sciences, Northeast Normal University, Changchun 130024, China)

  • Hong S. He

    (School of Geographical Sciences, Northeast Normal University, Changchun 130024, China
    School of Natural Resources, University of Missouri, Columbia, MO 65211, USA)

  • Wen J. Wang

    (Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China)

  • Jiping Liu

    (School of Tourism and Geography Science, Jilin Normal University, Siping 136000, China)

  • Haibo Du

    (School of Geographical Sciences, Northeast Normal University, Changchun 130024, China)

  • Miaomiao Wu

    (School of Geographical Sciences, Northeast Normal University, Changchun 130024, China)

  • Xinyuan Tan

    (School of Geographical Sciences, Northeast Normal University, Changchun 130024, China)

Abstract

Forest swamps are widely distributed in cold temperate regions, with important landscape and ecological functions. They are prone to conversion caused by complex factors. Forest swamp conversions involve forest swamping, meadow swamping, water body swamping, and conversion to farmland. An understanding of the landscape characteristics and primary environmental factors driving forest swamp conversions is imperative for exploring the mechanism of forest swamp conversions. We investigated the landscape characteristics of forest swamp conversions and quantified the relative importance of environmental factors driving these conversions for the period from 1990 to 2015 in the Great Xing’an Mountains of China. We found that forest swamping displayed high patch numbers (34,916) and density (8.51/100 ha), commonly occurring at the edge of large areas of forests. Meadow swamping was localized with low patch numbers (3613) and density (0.88/100 ha) due to lack of water recharge from ground water. Water body swamping had complex shapes (perimeter area ratio mean = 348.32) because of water table fluctuations and helophyte growth during this conversion process. Conversions to farmland presented fairly regular (perimeter area ratio mean = 289.91) and aggregated (aggregation index = 67.82) characteristics affected by agricultural irrigation and management. We found that climatic and geomorphic factors were relatively important compared to topographic factors for forest swamp conversions. Negative geomorphic conditions provided the waterlogging environment as a precondition of swamp formation. Sufficient precipitation was an important source of water recharge due to the existence of permafrost regions and long-term low temperature reduced the evaporation of swamps water and the decomposition rate of organisms. These wet and cold climatic conditions promoted forest swamp development in cold temperate regions. Humans exerted a relatively important role in forest swamping and conversions to farmland. Fire disturbance and logging accelerated the conversion from forest to swamp. This study provides scientific information necessary for the management and conservation of forest swamp resources in cold temperate regions.

Suggested Citation

  • Dandan Zhao & Hong S. He & Wen J. Wang & Jiping Liu & Haibo Du & Miaomiao Wu & Xinyuan Tan, 2018. "Distribution and Driving Factors of Forest Swamp Conversions in a Cold Temperate Region," IJERPH, MDPI, vol. 15(10), pages 1-14, September.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:10:p:2103-:d:171877
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/15/10/2103/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/15/10/2103/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Heimlich, Ralph E. & Langner, Linda L., 1986. "Swampbusting: Wetland Conversion and Farm Programs," Agricultural Economic Reports 308005, United States Department of Agriculture, Economic Research Service.
    2. Dandan Zhao & Hong S. He & Wen J. Wang & Lei Wang & Haibo Du & Kai Liu & Shengwei Zong, 2018. "Predicting Wetland Distribution Changes under Climate Change and Human Activities in a Mid- and High-Latitude Region," Sustainability, MDPI, vol. 10(3), pages 1-14, March.
    3. Jianling Xu & Hanxi Wang & Lianxi Sheng & Xuejun Liu & Xiaoxue Zheng, 2017. "Distribution Characteristics and Risk Assessment of Polycyclic Aromatic Hydrocarbons in the Momoge Wetland, China," IJERPH, MDPI, vol. 14(1), pages 1-15, January.
    4. Vincenzi, Simone & Zucchetta, Matteo & Franzoi, Piero & Pellizzato, Michele & Pranovi, Fabio & De Leo, Giulio A. & Torricelli, Patrizia, 2011. "Application of a Random Forest algorithm to predict spatial distribution of the potential yield of Ruditapes philippinarum in the Venice lagoon, Italy," Ecological Modelling, Elsevier, vol. 222(8), pages 1471-1478.
    5. Sam Moore & Chris D. Evans & Susan E. Page & Mark H. Garnett & Tim G. Jones & Chris Freeman & Aljosja Hooijer & Andrew J. Wiltshire & Suwido H. Limin & Vincent Gauci, 2013. "Deep instability of deforested tropical peatlands revealed by fluvial organic carbon fluxes," Nature, Nature, vol. 493(7434), pages 660-663, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wiltshire, Kathryn H & Tanner, Jason E, 2020. "Comparing maximum entropy modelling methods to inform aquaculture site selection for novel seaweed species," Ecological Modelling, Elsevier, vol. 429(C).
    2. Greta C. Dargie & Ian T. Lawson & Tim J. Rayden & Lera Miles & Edward T. A. Mitchard & Susan E. Page & Yannick E. Bocko & Suspense A. Ifo & Simon L. Lewis, 2019. "Congo Basin peatlands: threats and conservation priorities," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 24(4), pages 669-686, April.
    3. K. Hergoualc’h & L. Verchot, 2014. "Greenhouse gas emission factors for land use and land-use change in Southeast Asian peatlands," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 19(6), pages 789-807, August.
    4. H. Oğuz Çoban & Ömer K. Örücü & E. Seda Arslan, 2020. "MaxEnt Modeling for Predicting the Current and Future Potential Geographical Distribution of Quercus libani Olivier," Sustainability, MDPI, vol. 12(7), pages 1-17, March.
    5. Erika Berenguer & Toby A Gardner & Joice Ferreira & Luiz E O C Aragão & Plínio B Camargo & Carlos E Cerri & Mariana Durigan & Raimundo C Oliveira Junior & Ima C G Vieira & Jos Barlow, 2015. "Developing Cost-Effective Field Assessments of Carbon Stocks in Human-Modified Tropical Forests," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-19, August.
    6. Dandan Zhao & Hong S. He & Wen J. Wang & Lei Wang & Haibo Du & Kai Liu & Shengwei Zong, 2018. "Predicting Wetland Distribution Changes under Climate Change and Human Activities in a Mid- and High-Latitude Region," Sustainability, MDPI, vol. 10(3), pages 1-14, March.
    7. Denis J. Murphy, 2024. "Carbon Sequestration by Tropical Trees and Crops: A Case Study of Oil Palm," Agriculture, MDPI, vol. 14(7), pages 1-31, July.
    8. Jig Han Jeong & Jonathan P Resop & Nathaniel D Mueller & David H Fleisher & Kyungdahm Yun & Ethan E Butler & Dennis J Timlin & Kyo-Moon Shim & James S Gerber & Vangimalla R Reddy & Soo-Hyung Kim, 2016. "Random Forests for Global and Regional Crop Yield Predictions," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-15, June.
    9. Jenny E Goldstein, 2016. "Knowing the subterranean: Land grabbing, oil palm, and divergent expertise in Indonesia’s peat soil," Environment and Planning A, , vol. 48(4), pages 754-770, April.
    10. So Young Woo & Chung Gil Jung & Ji Wan Lee & Seong Joon Kim, 2019. "Evaluation of Watershed Scale Aquatic Ecosystem Health by SWAT Modeling and Random Forest Technique," Sustainability, MDPI, vol. 11(12), pages 1-15, June.
    11. V. Kohestani & M. Hassanlourad & A. Ardakani, 2015. "Evaluation of liquefaction potential based on CPT data using random forest," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 79(2), pages 1079-1089, November.
    12. das Neves, Patricia Bittencourt Tavares & Blanco, Claudio José Cavalcante & Montenegro Duarte, André Augusto Azevedo & das Neves, Filipe Bittencourt Souza & das Neves, Isabela Bittencourt Souza & de P, 2021. "Amazon rainforest deforestation influenced by clandestine and regular roadway network," Land Use Policy, Elsevier, vol. 108(C).
    13. Dislich, Claudia & Keyel, Alexander C. & Salecker, Jan & Kisel, Yael & Meyer, Katrin M. & Corre, Marife D. & Faust, Heiko & Hess, Bastian & Knohl, Alexander & Kreft, Holger & Meijide, Ana & Nurdiansya, 2015. "Ecosystem functions of oil palm plantations - a review," EFForTS Discussion Paper Series 16, University of Goettingen, Collaborative Research Centre 990 "EFForTS, Ecological and Socioeconomic Functions of Tropical Lowland Rainforest Transformation Systems (Sumatra, Indonesia)".
    14. Nielsen, Elizabeth G. & Miranowski, John A. & Morehart, Mitchell J, 1989. "Investments in Soil Conservation and Land Improvements: Factors Explaining Farmers' Decisions," Agricultural Economic Reports 308064, United States Department of Agriculture, Economic Research Service.
    15. Wiebe, Keith & Tegene, Abebayehu & Kuhn, Betsey, 1996. "Partial Interests in Land: Policy Tools for Resource Use and Conservation," Agricultural Economic Reports 262040, United States Department of Agriculture, Economic Research Service.
    16. Erqi Xu & Yimeng Chen, 2019. "Modeling Intersecting Processes of Wetland Shrinkage and Urban Expansion by a Time-Varying Methodology," Sustainability, MDPI, vol. 11(18), pages 1-24, September.
    17. Grimmett, Liam & Whitsed, Rachel & Horta, Ana, 2020. "Presence-only species distribution models are sensitive to sample prevalence: Evaluating models using spatial prediction stability and accuracy metrics," Ecological Modelling, Elsevier, vol. 431(C).
    18. Di Wang & Shilei Zhu & Lijing Wang & Qing Zhen & Fengpeng Han & Xingchang Zhang, 2020. "Distribution, Origins and Hazardous Effects of Polycyclic Aromatic Hydrocarbons in Topsoil Surrounding Oil Fields: A Case Study on the Loess Plateau, China," IJERPH, MDPI, vol. 17(4), pages 1-14, February.
    19. Netrananda Sahu & Pritiranjan Das & Atul Saini & Ayush Varun & Suraj Kumar Mallick & Rajiv Nayan & S. P. Aggarwal & Balaram Pani & Ravi Kesharwani & Anil Kumar, 2023. "Analysis of Tea Plantation Suitability Using Geostatistical and Machine Learning Techniques: A Case of Darjeeling Himalaya, India," Sustainability, MDPI, vol. 15(13), pages 1-21, June.
    20. Di Wang & Jing Ma & Hao Li & Xingchang Zhang, 2018. "Concentration and Potential Ecological Risk of PAHs in Different Layers of Soil in the Petroleum-Contaminated Areas of the Loess Plateau, China," IJERPH, MDPI, vol. 15(8), pages 1-15, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:15:y:2018:i:10:p:2103-:d:171877. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.