IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v274y2022ics0378377422005005.html
   My bibliography  Save this article

Effects of environmental and agronomic factors on pond water quality within an intensive agricultural landscape in subtropical southern China

Author

Listed:
  • Meng, Cen
  • Liu, Huanyao
  • Li, Yuyuan
  • Shen, Jianlin
  • Li, Xi
  • Wu, Jinshui

Abstract

Water quality deterioration, such as eutrophication, can contribute to the degradation of farm pond ecosystems, threatening numerous ecological services and socioeconomic benefits. However, the variability of water quality and the complexity of influencing variables pose large uncertainties for pond management practices and watershed planning. This study integrated a self-organizing map (SOM) and partial least squares structural equation modeling (PLS-SEM) to evaluate the nitrogen (N) and phosphorus (P) variations in 39 typical farm ponds in the Dongting Lake basin, and related the variations to pond internal factors, external environment, and agronomic management. The results indicated that 39 monitored farm ponds faced a high risk of eutrophication owing to high N and P levels, and that total N (TN), total P (TP), and particulate P (PP) generally exceeded the threshold of level V surface water quality standards in China (2.0 mg N L−1 and 0.2 mg P L−1). Simultaneously, pond water quality showed high spatiotemporal variability, and pollution hotspots occurred mostly during the overlapping periods of fallow-dry-winter and planting-rainy-spring. Based on the constructed SEM model, external environmental factors (meteorology, catchment landscape composition, configuration, topography, and soil chemical properties), pond internal characteristics, and agronomic management combined explained 60.2 ± 2.9 % and 54.2 ± 3.1 % of the N and P variations, respectively. There were intricate interactions among the above latent variables, including such meteorology positively moderated the paths of soil chemical properties→pond P and landscape composition→pond N and P; landscape composition, soil, and pond internal characteristics mediated the effects of other variables on variations of N and P. The total effects (indirect effects + direct effects) of landscape composition on the variations of pond N and P were higher than those of other variables. Among all the indicators composing latent variables, agricultural and residential land area percentage, rainfall, water depth, and fish farming were relatively important in pond water quality variations. The constructed model and analytical results offer essential information for the accurate management and restoration of pond water quality.

Suggested Citation

  • Meng, Cen & Liu, Huanyao & Li, Yuyuan & Shen, Jianlin & Li, Xi & Wu, Jinshui, 2022. "Effects of environmental and agronomic factors on pond water quality within an intensive agricultural landscape in subtropical southern China," Agricultural Water Management, Elsevier, vol. 274(C).
    • Handle: RePEc:eee:agiwat:v:274:y:2022:i:c:s0378377422005005
    DOI: 10.1016/j.agwat.2022.107953
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377422005005
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2022.107953?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhang, Wangshou & Li, Hengpeng & Pueppke, Steven G & Diao, Yaqin & Nie, Xiaofei & Geng, Jianwei & Chen, Dongqiang & Pang, Jiaping, 2020. "Nutrient loss is sensitive to land cover changes and slope gradients of agricultural hillsides: Evidence from four contrasting pond systems in a hilly catchment," Agricultural Water Management, Elsevier, vol. 237(C).
    2. Arnold Wollenberg, 1977. "Redundancy analysis an alternative for canonical correlation analysis," Psychometrika, Springer;The Psychometric Society, vol. 42(2), pages 207-219, June.
    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. Vittadini, Giorgio & Minotti, Simona C. & Fattore, Marco & Lovaglio, Pietro G., 2007. "On the relationships among latent variables and residuals in PLS path modeling: The formative-reflective scheme," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5828-5846, August.
    2. Hanafi, Mohamed & Kiers, Henk A.L., 2006. "Analysis of K sets of data, with differential emphasis on agreement between and within sets," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1491-1508, December.
    3. Kazi-Aoual, Frederique & Hitier, Simon & Sabatier, Robert & Lebreton, Jean-Dominique, 1995. "Refined approximations to permutation tests for multivariate inference," Computational Statistics & Data Analysis, Elsevier, vol. 20(6), pages 643-656, December.
    4. Cook, Judith A. & Razzano, Lisa & Cappelleri, Joseph C., 1996. "Canonical correlation analysis of residential and vocational outcomes following psychiatric rehabilitation," Evaluation and Program Planning, Elsevier, vol. 19(4), pages 351-363, November.
    5. Kargin, V. & Onatski, A., 2008. "Curve forecasting by functional autoregression," Journal of Multivariate Analysis, Elsevier, vol. 99(10), pages 2508-2526, November.
    6. Minjung Kyung & Ju-Hyun Park & Ji Yeh Choi, 2022. "Bayesian Mixture Model of Extended Redundancy Analysis," Psychometrika, Springer;The Psychometric Society, vol. 87(3), pages 946-966, September.
    7. Miaomiao Yang & Keli Zhang & Chenlu Huang & Qinke Yang, 2022. "Effects of Content of Soil Rock Fragments on Soil Erodibility in China," IJERPH, MDPI, vol. 19(2), pages 1-19, January.
    8. Wayne DeSarbo & Heungsun Hwang & Ashley Stadler Blank & Eelco Kappe, 2015. "Constrained Stochastic Extended Redundancy Analysis," Psychometrika, Springer;The Psychometric Society, vol. 80(2), pages 516-534, June.
    9. Abby Israëls, 1986. "Reviews," Psychometrika, Springer;The Psychometric Society, vol. 51(3), pages 495-497, September.
    10. Takane, Yoshio & Jung, Sunho, 2009. "Regularized nonsymmetric correspondence analysis," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3159-3170, June.
    11. Martínez-Ventura, Constanza & Mariño-Martínez, Ricardo & Miguélez-Márquez, Javier, 2023. "Redundancy of Centrality Measures in Financial Market Infrastructures," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(4).
    12. John Zilvinskis & Anthony A. Masseria & Gary R. Pike, 2017. "Student Engagement and Student Learning: Examining the Convergent and Discriminant Validity of the Revised National Survey of Student Engagement," Research in Higher Education, Springer;Association for Institutional Research, vol. 58(8), pages 880-903, December.
    13. Ariyawardana, A. & Bailey, W.C, 2002. "The Relationship between Core Resources and Strategies of Firms: The Case of Sri Lankan Value-Added Tea Producers," Sri Lankan Journal of Agricultural Economics, Sri Lanka Agricultural Economics Association (SAEA), vol. 4, pages 1-19.
    14. Lazraq, Aziz & Cléroux, Robert, 2001. "Statistical Inference Concerning Several Redundancy Indices," Journal of Multivariate Analysis, Elsevier, vol. 79(1), pages 71-88, October.
    15. Dray, Stephane, 2008. "On the number of principal components: A test of dimensionality based on measurements of similarity between matrices," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 2228-2237, January.
    16. Jos Berge, 1985. "On the relationship between Fortier's simultaneous linear prediction and van den Wollenberg's redundancy analysis," Psychometrika, Springer;The Psychometric Society, vol. 50(1), pages 121-122, March.
    17. Susana Mendes & M. Jos� Fernández-Gómez & Mário Jorge Pereira & Ulisses Miranda Azeiteiro & M. Purificación Galindo-Villardón, 2012. "An empirical comparison of Canonical Correspondence Analysis and STATICO in the identification of spatio-temporal ecological relationships," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(5), pages 979-994, October.
    18. Michel Tenenhaus & Arthur Tenenhaus & Patrick J. F. Groenen, 2017. "Regularized Generalized Canonical Correlation Analysis: A Framework for Sequential Multiblock Component Methods," Psychometrika, Springer;The Psychometric Society, vol. 82(3), pages 737-777, September.
    19. Pietro Giorgio Lovaglio & Gianmarco Vacca & Stefano Verzillo, 2016. "Human capital estimation in higher education," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 10(4), pages 465-489, December.
    20. Yvonne Milker & Manuel F G Weinkauf & Jürgen Titschack & Andre Freiwald & Stefan Krüger & Frans J Jorissen & Gerhard Schmiedl, 2017. "Testing the applicability of a benthic foraminiferal-based transfer function for the reconstruction of paleowater depth changes in Rhodes (Greece) during the early Pleistocene," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-30, November.

    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:eee:agiwat:v:274:y:2022:i:c:s0378377422005005. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agwat .

    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.