IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i11p6542-d825430.html
   My bibliography  Save this article

Multiscale Spatial Distribution Pattern and Influencing Factors on Inland Fishing Gardens in China

Author

Listed:
  • Yong Huang

    (College of Nature Resources and Environment, Northwest A&F University, Xianyang 712100, China)

  • Qinjun Kang

    (College of Nature Resources and Environment, Northwest A&F University, Xianyang 712100, China)

  • Qi Wang

    (College of Nature Resources and Environment, Northwest A&F University, Xianyang 712100, China)

  • Lili Luo

    (College of Nature Resources and Environment, Northwest A&F University, Xianyang 712100, China)

  • Tingting Wang

    (Yellow River’s Soil and Water Conservation, Xifeng Governance Bureau, Qingyang 745000, China)

  • Qingrui Chang

    (College of Nature Resources and Environment, Northwest A&F University, Xianyang 712100, China)

Abstract

Recently, a significant number of freshwater fishing gardens have sprouted up across mainland China. These recreational facilities are an important component in promoting the upgrading of the fishing industry and rural revitalization, and they are a key component in the high-quality development of rural tourism. This paper uses fishing gardens points of interest (POI) in China as data sources and employs kernel density estimation and geographical detectors to systematically uncover the multiscale spatial distribution pattern of these gardens, as well as the factors influencing their distribution. The results show that: (1) There are 15,090 fishing gardens in inland China. The spatial distribution of Chinese fishing gardens corresponds well with the “Hu-Line”, with a greater number of gardens clustered in the southeast and few in the northwest. The density distribution exhibits a polarized pattern with multiple high-density centers. (2) The number of fishing gardens varies significantly across regions, with the eastern > central > western > northeastern; Guangdong has the most fishing gardens. The top five provinces have 43.4% of the total number of fishing gardens in the country. Large-scale fishing gardens are common in developed cities such as the Pearl River Delta, Beijing-Tianjin-Hebei, and the Yangtze River economic belt. (3) In natural environmental factors, land altitude and contour are negatively correlated with the distribution of fishing gardens, whereas winter temperature is positively correlated with the distribution. More than 50% of fishing gardens are located within 6 km of urban built-up areas. (4) GDP, population, and tourism revenue are the most important social development factors influencing the distribution of fishing gardens. The moderate factors are per capita income and the rate of urbanization; the weak factors are fishery output value and freshwater products production. In the discussion, suggestions on how to guide the rational layout and healthy development of the fishing garden industry in the region are put forward. We believe that these suggestions could be part of the pursuit to improve the fishing garden industrial policy in China.

Suggested Citation

  • Yong Huang & Qinjun Kang & Qi Wang & Lili Luo & Tingting Wang & Qingrui Chang, 2022. "Multiscale Spatial Distribution Pattern and Influencing Factors on Inland Fishing Gardens in China," Sustainability, MDPI, vol. 14(11), pages 1-17, May.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:11:p:6542-:d:825430
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/11/6542/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/11/6542/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. John Rolfe & Prabha Prayaga, 2007. "Estimating values for recreational fishing at freshwater dams in Queensland ," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 51(2), pages 157-174, June.
    2. Ruomu Miao & Yuxia Wang & Shuang Li, 2021. "Analyzing Urban Spatial Patterns and Functional Zones Using Sina Weibo POI Data: A Case Study of Beijing," Sustainability, MDPI, vol. 13(2), pages 1-15, January.
    3. Anton Paulrud & Thomas Laitila, 2013. "A cost-benefit analysis of restoring the Em River in Sweden: valuation of angling site characteristics and visitation frequency," Applied Economics, Taylor & Francis Journals, vol. 45(16), pages 2255-2266, June.
    4. Christos Polykretis & Manolis G. Grillakis & Athanasios V. Argyriou & Nikos Papadopoulos & Dimitrios D. Alexakis, 2021. "Integrating Multivariate (GeoDetector) and Bivariate (IV) Statistics for Hybrid Landslide Susceptibility Modeling: A Case of the Vicinity of Pinios Artificial Lake, Ilia, Greece," Land, MDPI, vol. 10(9), pages 1-23, September.
    5. Rolfe, John & Prayaga, Prabha, 2007. "Estimating values for recreational fishing at freshwater dams in Queensland," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 51(2), pages 1-18.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wenxin Wang & Xia Yang & Xia Gan & Chang Yang & Xiangwen Gong & Si Chen, 2023. "The Differences in the Impact of Economic Structure Adjustment on the Ecological Carrying Capacity of County Education—A Case Study of Chongqing, China," Sustainability, MDPI, vol. 15(2), pages 1-17, January.
    2. Qiuyu Zou & Jianwei Sun & Jing Luo & Jiaxing Cui & Xuesong Kong, 2023. "Spatial Patterns of Key Villages and Towns of Rural Tourism in China and Their Influencing Factors," Sustainability, MDPI, vol. 15(18), pages 1-16, September.

    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. Raguragavan, Jananee & Hailu, Atakelty & Burton, Michael, 2013. "Economic Valuation of Recreational Fishing in Western Australia: Statewide Random Utility Modelling of Fishing Site Choice Behaviour," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 57(4), pages 1-20.
    2. Jegnie, Alemken & Hailu, Atakelty & Burton, Michael P., 2017. "Boat-based and other recreational fishing in Western Australia: Analysis of site choice, access values and bag limit effects," Working Papers 257167, University of Western Australia, School of Agricultural and Resource Economics.
    3. Zhang, Fan & Fogarty, James, 2015. "Nonmarket Valuation of Water Sensitive Cities: Current Knowledge and Issues," Working Papers 207694, University of Western Australia, School of Agricultural and Resource Economics.
    4. Pascoe, Sean, 2019. "Recreational beach use values with multiple activities," Ecological Economics, Elsevier, vol. 160(C), pages 137-144.
    5. He, Xiaoyang & Poe, Gregory L., 2021. "Exploring the shelf-life of travel cost methods of valuing recreation for benefits transfer," Resource and Energy Economics, Elsevier, vol. 63(C).
    6. Zhang, Fan & Wang, Xiao Hua & Nunes, Paulo A.L.D. & Ma, Chunbo, 2015. "The recreational value of gold coast beaches, Australia: An application of the travel cost method," Ecosystem Services, Elsevier, vol. 11(C), pages 106-114.
    7. Windle, Jill & Rolfe, John & Pascoe, Sean, 2017. "Assessing recreational benefits as an economic indicator for the Gladstone Harbour Report Card," 2017 Conference (61st), February 7-10, 2017, Brisbane, Australia 258681, Australian Agricultural and Resource Economics Society.
    8. Sascha Samadi, 2017. "The Social Costs of Electricity Generation—Categorising Different Types of Costs and Evaluating Their Respective Relevance," Energies, MDPI, vol. 10(3), pages 1-37, March.
    9. Farr, Marina & Stoeckl, Natalie, 2018. "Overoptimism and the undervaluation of ecosystem services: A case-study of recreational fishing in Townsville, adjacent to the Great Barrier Reef," Ecosystem Services, Elsevier, vol. 31(PC), pages 433-444.
    10. Pascoe, Sean & Doshi, Amar & Dell, Quentin & Tonks, Mark & Kenyon, Rob, 2014. "Economic value of recreational fishing in Moreton Bay and the potential impact of the marine park rezoning," Tourism Management, Elsevier, vol. 41(C), pages 53-63.
    11. Shelley Burgin, 2017. "Indirect Consequences of Recreational Fishing in Freshwater Ecosystems: An Exploration from an Australian Perspective," Sustainability, MDPI, vol. 9(2), pages 1-18, February.
    12. Star, Megan & Rolfe, John & Brown, Julia, 2020. "From farm to fork: Is food tourism a sustainable form of economic development?," Economic Analysis and Policy, Elsevier, vol. 66(C), pages 325-334.
    13. Zander, Kerstin K. & Straton, Anna, 2010. "An economic assessment of the value of tropical river ecosystem services: Heterogeneous preferences among Aboriginal and non-Aboriginal Australians," Ecological Economics, Elsevier, vol. 69(12), pages 2417-2426, October.
    14. Farr, Marina & Stoeckl, Natalie & Sutton, Stephen, 2014. "Recreational fishing and boating: Are the determinants the same?," Marine Policy, Elsevier, vol. 47(C), pages 126-137.
    15. Jiaxin Zhang & Zhilin Yu & Yunqin Li & Xueqiang Wang, 2023. "Uncovering Bias in Objective Mapping and Subjective Perception of Urban Building Functionality: A Machine Learning Approach to Urban Spatial Perception," Land, MDPI, vol. 12(7), pages 1-20, June.
    16. Yuewen Yang & Dongyan Wang & Zhuoran Yan & Shuwen Zhang, 2021. "Delineating Urban Functional Zones Using U-Net Deep Learning: Case Study of Kuancheng District, Changchun, China," Land, MDPI, vol. 10(11), pages 1-21, November.
    17. Oliveira, Renata Lúcia Magalhães de & Dablanc, Laetitia & Schorung, Matthieu, 2022. "Changes in warehouse spatial patterns and rental prices: Are they related? Exploring the case of US metropolitan areas," Journal of Transport Geography, Elsevier, vol. 104(C).
    18. Satoshi Yamazaki & Steven Rust & Sarah Jennings & Jeremy Lyle & Sven Frijlink, 2013. "Valuing recreational fishing in Tasmania and assessment of response bias in contingent valuation," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 57(2), pages 193-213, April.
    19. Marit E. Kragt & Jeff Bennett, 2008. "Developing a Questionnaire for Valuing Changes in Natural Resource Management in the George Catchment, Tasmania," Environmental Economics Research Hub Research Reports 0808, Environmental Economics Research Hub, Crawford School of Public Policy, The Australian National University.
    20. Bo Cao & Qingyi Li & Yuhang Zhu, 2022. "Comparison of Effects between Different Weight Calculation Methods for Improving Regional Landslide Susceptibility—A Case Study from Xingshan County of China," Sustainability, MDPI, vol. 14(17), pages 1-15, September.

    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:jsusta:v:14:y:2022:i:11:p:6542-:d:825430. 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.