IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v228y2012icp123-129.html
   My bibliography  Save this article

The belief index: An empirical measure for evaluating outcomes in Bayesian belief network modelling

Author

Listed:
  • Vilizzi, L.
  • Price, A.
  • Beesley, L.
  • Gawne, B.
  • King, A.J.
  • Koehn, J.D.
  • Meredith, S.N.
  • Nielsen, D.L.
  • Sharpe, C.P.

Abstract

Bayesian belief networks (BBNs) are a widespread tool for modelling the effects of management decisions and activities on a variety of environmental and ecological responses. Parameterisation of BBNs is often achieved by elicitation involving multiple experts, and this may result in different conditional probability distribution tables for the nodes in a BBN. Another common use of BBNs is in the comparison of alternative management scenarios. This paper describes and implements the ‘belief index’ (BI), an empirical measure for evaluating outcomes in BBN modelling that summarises the probabilities (or beliefs) of any one node in a BBN. A set of four species-specific BBNs for managing watering events for wetland fish is outlined and used to statistically assess between-expert and between-species variability in parameter estimates by means of the BI. Different scenarios for management decisions are also compared using the % improvement measure, a derivative of the BI.

Suggested Citation

  • Vilizzi, L. & Price, A. & Beesley, L. & Gawne, B. & King, A.J. & Koehn, J.D. & Meredith, S.N. & Nielsen, D.L. & Sharpe, C.P., 2012. "The belief index: An empirical measure for evaluating outcomes in Bayesian belief network modelling," Ecological Modelling, Elsevier, vol. 228(C), pages 123-129.
    • Handle: RePEc:eee:ecomod:v:228:y:2012:i:c:p:123-129
    DOI: 10.1016/j.ecolmodel.2012.01.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380012000166
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2012.01.005?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. Nicholson, Ann E. & Flores, M. Julia, 2011. "Combining state and transition models with dynamic Bayesian networks," Ecological Modelling, Elsevier, vol. 222(3), pages 555-566.
    2. Pollino, Carmel A. & White, Andrea K. & Hart, Barry T., 2007. "Examination of conflicts and improved strategies for the management of an endangered Eucalypt species using Bayesian networks," Ecological Modelling, Elsevier, vol. 201(1), pages 37-59.
    3. Renken, Henk & Mumby, Peter J., 2009. "Modelling the dynamics of coral reef macroalgae using a Bayesian belief network approach," Ecological Modelling, Elsevier, vol. 220(9), pages 1305-1314.
    4. Marti J. Anderson, 2006. "Distance-Based Tests for Homogeneity of Multivariate Dispersions," Biometrics, The International Biometric Society, vol. 62(1), pages 245-253, March.
    5. Uusitalo, Laura, 2007. "Advantages and challenges of Bayesian networks in environmental modelling," Ecological Modelling, Elsevier, vol. 203(3), pages 312-318.
    6. Johnson, Sandra & Mengersen, Kerrie & de Waal, Alta & Marnewick, Kelly & Cilliers, Deon & Houser, Ann Marie & Boast, Lorraine, 2010. "Modelling cheetah relocation success in southern Africa using an Iterative Bayesian Network Development Cycle," Ecological Modelling, Elsevier, vol. 221(4), pages 641-651.
    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. Liedloff, Adam C. & Smith, Carl S., 2010. "Predicting a ‘tree change’ in Australia's tropical savannas: Combining different types of models to understand complex ecosystem behaviour," Ecological Modelling, Elsevier, vol. 221(21), pages 2565-2575.
    2. Guo, Kai & Zhang, Xinchang & Kuai, Xi & Wu, Zhifeng & Chen, Yiyun & Liu, Yi, 2020. "A spatial bayesian-network approach as a decision-making tool for ecological-risk prevention in land ecosystems," Ecological Modelling, Elsevier, vol. 419(C).
    3. Nicholson, Ann E. & Flores, M. Julia, 2011. "Combining state and transition models with dynamic Bayesian networks," Ecological Modelling, Elsevier, vol. 222(3), pages 555-566.
    4. Moe, S. Jannicke & Haande, Sigrid & Couture, Raoul-Marie, 2016. "Climate change, cyanobacteria blooms and ecological status of lakes: A Bayesian network approach," Ecological Modelling, Elsevier, vol. 337(C), pages 330-347.
    5. Hamilton, Serena H. & Pollino, Carmel A. & Jakeman, Anthony J., 2015. "Habitat suitability modelling of rare species using Bayesian networks: Model evaluation under limited data," Ecological Modelling, Elsevier, vol. 299(C), pages 64-78.
    6. Jim Lewis & Kerrie Mengersen & Laurie Buys & Desley Vine & John Bell & Peter Morris & Gerard Ledwich, 2015. "Systems Modelling of the Socio-Technical Aspects of Residential Electricity Use and Network Peak Demand," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-21, July.
    7. Ropero, R.F. & Aguilera, P.A. & Rumí, R., 2015. "Analysis of the socioecological structure and dynamics of the territory using a hybrid Bayesian network classifier," Ecological Modelling, Elsevier, vol. 311(C), pages 73-87.
    8. Johnson, Sandra & Mengersen, Kerrie & de Waal, Alta & Marnewick, Kelly & Cilliers, Deon & Houser, Ann Marie & Boast, Lorraine, 2010. "Modelling cheetah relocation success in southern Africa using an Iterative Bayesian Network Development Cycle," Ecological Modelling, Elsevier, vol. 221(4), pages 641-651.
    9. Ropero, R.F. & Renooij, S. & van der Gaag, L.C., 2018. "Discretizing environmental data for learning Bayesian-network classifiers," Ecological Modelling, Elsevier, vol. 368(C), pages 391-403.
    10. Maldonado, A.D. & Aguilera, P.A. & Salmerón, A. & Nicholson, A.E., 2018. "Probabilistic modeling of the relationship between socioeconomy and ecosystem services in cultural landscapes," Ecosystem Services, Elsevier, vol. 33(PB), pages 146-164.
    11. Di Zhang & Xinping Yan & Zaili Yang & Jin Wang, 2014. "An accident data–based approach for congestion risk assessment of inland waterways: A Yangtze River case," Journal of Risk and Reliability, , vol. 228(2), pages 176-188, April.
    12. Meineri, Eric & Dahlberg, C. Johan & Hylander, Kristoffer, 2015. "Using Gaussian Bayesian Networks to disentangle direct and indirect associations between landscape physiography, environmental variables and species distribution," Ecological Modelling, Elsevier, vol. 313(C), pages 127-136.
    13. De Iuliis, Melissa & Kammouh, Omar & Cimellaro, Gian Paolo & Tesfamariam, Solomon, 2021. "Quantifying restoration time of power and telecommunication lifelines after earthquakes using Bayesian belief network model," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    14. Radomír Němec & Marie Vymazalová & Hana Skokanová, 2022. "The Impact of Fine-Scale Present and Historical Land Cover on Plant Diversity in Central European National Parks with Heterogeneous Landscapes," Land, MDPI, vol. 11(6), pages 1-18, May.
    15. Isabel Fuentes-Santos & Uxío Labarta & María José Fernández-Reiriz, 2018. "Characterizing individual variability in mussel (Mytilus galloprovincialis) growth and testing its physiological drivers using Functional Data Analysis," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-13, October.
    16. Antonio Bracale & Pasquale De Falco, 2015. "An Advanced Bayesian Method for Short-Term Probabilistic Forecasting of the Generation of Wind Power," Energies, MDPI, vol. 8(9), pages 1-22, September.
    17. Renken, Henk & Mumby, Peter J., 2009. "Modelling the dynamics of coral reef macroalgae using a Bayesian belief network approach," Ecological Modelling, Elsevier, vol. 220(9), pages 1305-1314.
    18. Stewart-Koster, Ben & Dieu Anh, Nguyen & Burford, Michele A. & Condon, Jason & Qui, Nguyen Van & Hiep, Le Huu & Bay, Doan Van & Sammut, Jesmond, 2017. "Expert based model building to quantify risk factors in a combined aquaculture-agriculture system," Agricultural Systems, Elsevier, vol. 157(C), pages 230-240.
    19. repec:osf:osfxxx:qabhj_v1 is not listed on IDEAS
    20. Halder, Kaushik & Panda, Deepak Kumar & Das, Saptarshi & Das, Sourav & Gupta, Amitava, 2022. "Specified QoS based networked observer and PI controller design with disturbance and noise rejection under random packet dropout," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    21. Verda Kocabas & Suzana Dragicevic, 2013. "Bayesian networks and agent-based modeling approach for urban land-use and population density change: a BNAS model," Journal of Geographical Systems, Springer, vol. 15(4), pages 403-426, October.

    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:ecomod:v:228:y:2012:i:c:p:123-129. 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.journals.elsevier.com/ecological-modelling .

    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.