IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v259y2013icp16-23.html
   My bibliography  Save this article

Global sensitivity analysis of a modified CENTURY model for simulating impacts of harvesting fine woody biomass for bioenergy

Author

Listed:
  • Wang, Fugui
  • Mladenoff, David J.
  • Forrester, Jodi A.
  • Keough, Cindy
  • Parton, William J.

Abstract

Modeling the long-term effects of intensive forest biomass harvesting scenarios over time, including the more complete removal of tree tops and branches, is a scientific and policy need. Yet, due to our incomplete understanding about complex forest ecosystems, model simulations are to various degrees uncertain. In this study we first modified a well-evaluated and widely used ecosystem model – CENTURY 4.5 – to model management scenarios that retain various sizes and quantities of small-diameter woody material after intensive biomass harvests. Second, we used a global sensitivity analysis approach to evaluate the sensitivity of nine model outputs to 55 parameters, grouped into 17 factors. The values of the parameters were generated with a normal distribution and sampled with the extended Fourier amplitude sensitivity test. Our analysis indicated that within a harvest rotation, the model output sensitivity varied over years in response to different factors. The model was most sensitive to factors consisting of temperature effects on potential production as well as N deposition and non-symbiotic N fixation. In response to the uncertain parameter values, the model simulation revealed that outputs of net N mineralization rates in slow and passive soil organic matter pools had the highest uncertainties. However, due to the very low fraction of the N supplied from these two pools, forest production and other simulations were not strongly affected, ending with overall variations less than 6%. Ultimately, this study exhibits a novel approach in modeling the effects of harvesting fine woody debris for bioenergy on long-term ecosystem C and N cycles, and illustrates that sensitivity testing the most uncertain parameters is crucial for minimizing model uncertainty.

Suggested Citation

  • Wang, Fugui & Mladenoff, David J. & Forrester, Jodi A. & Keough, Cindy & Parton, William J., 2013. "Global sensitivity analysis of a modified CENTURY model for simulating impacts of harvesting fine woody biomass for bioenergy," Ecological Modelling, Elsevier, vol. 259(C), pages 16-23.
    • Handle: RePEc:eee:ecomod:v:259:y:2013:i:c:p:16-23
    DOI: 10.1016/j.ecolmodel.2013.03.008
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380013001579
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2013.03.008?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. Cariboni, J. & Gatelli, D. & Liska, R. & Saltelli, A., 2007. "The role of sensitivity analysis in ecological modelling," Ecological Modelling, Elsevier, vol. 203(1), pages 167-182.
    2. Saloranta, Tuomo M. & Andersen, Tom, 2007. "MyLake—A multi-year lake simulation model code suitable for uncertainty and sensitivity analysis simulations," Ecological Modelling, Elsevier, vol. 207(1), pages 45-60.
    3. Scheller, Robert M. & Hua, Dong & Bolstad, Paul V. & Birdsey, Richard A. & Mladenoff, David J., 2011. "The effects of forest harvest intensity in combination with wind disturbance on carbon dynamics in Lake States Mesic Forests," Ecological Modelling, Elsevier, vol. 222(1), pages 144-153.
    4. Saltelli, Andrea & Bolado, Ricardo, 1998. "An alternative way to compute Fourier amplitude sensitivity test (FAST)," Computational Statistics & Data Analysis, Elsevier, vol. 26(4), pages 445-460, February.
    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. Simons-Legaard, Erin & Legaard, Kasey & Weiskittel, Aaron, 2015. "Predicting aboveground biomass with LANDIS-II: A global and temporal analysis of parameter sensitivity," Ecological Modelling, Elsevier, vol. 313(C), pages 325-332.
    2. Juhua Ding & Qiuan Zhu & Hanwei Li & Xiaolu Zhou & Weiguo Liu & Changhui Peng, 2022. "Contribution of Incorporating the Phosphorus Cycle into TRIPLEX-CNP to Improve the Quantification of Land Carbon Cycle," Land, MDPI, vol. 11(6), pages 1-22, May.
    3. Morris, David J. & Speirs, Douglas C. & Cameron, Angus I. & Heath, Michael R., 2014. "Global sensitivity analysis of an end-to-end marine ecosystem model of the North Sea: Factors affecting the biomass of fish and benthos," Ecological Modelling, Elsevier, vol. 273(C), pages 251-263.
    4. Kai Yin & Dengsheng Lu & Yichen Tian & Qianjun Zhao & Chao Yuan, 2014. "Evaluation of Carbon and Oxygen Balances in Urban Ecosystems Using Land Use/Land Cover and Statistical Data," Sustainability, MDPI, vol. 7(1), pages 1-27, December.
    5. Huber, Nica & Bugmann, Harald & Lafond, Valentine, 2018. "Global sensitivity analysis of a dynamic vegetation model: Model sensitivity depends on successional time, climate and competitive interactions," Ecological Modelling, Elsevier, vol. 368(C), pages 377-390.
    6. Ma, Haijiao & Wang, Jianliang & Liu, Tao & Guo, Yahui & Zhou, Yang & Yang, Tianle & Zhang, Weijun & Sun, Chengming, 2023. "Time series global sensitivity analysis of genetic parameters of CERES-maize model under water stresses at different growth stages," Agricultural Water Management, Elsevier, vol. 275(C).
    7. Zhao, Gang & Bryan, Brett A. & Song, Xiaodong, 2014. "Sensitivity and uncertainty analysis of the APSIM-wheat model: Interactions between cultivar, environmental, and management parameters," Ecological Modelling, Elsevier, vol. 279(C), pages 1-11.

    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. Francisco A. Buendia-Hernandez & Maria J. Ortiz Bevia & Francisco J. Alvarez-Garcia & Antonio Ruizde Elvira, 2022. "Sensitivity of a Dynamic Model of Air Traffic Emissions to Technological and Environmental Factors," IJERPH, MDPI, vol. 19(22), pages 1-17, November.
    2. Imron, Muhammad Ali & Gergs, Andre & Berger, Uta, 2012. "Structure and sensitivity analysis of individual-based predator–prey models," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 71-81.
    3. Pelletier, Dominique & Mahevas, Stéphanie & Drouineau, Hilaire & Vermard, Youen & Thebaud, Olivier & Guyader, Olivier & Poussin, Benjamin, 2009. "Evaluation of the bioeconomic sustainability of multi-species multi-fleet fisheries under a wide range of policy options using ISIS-Fish," Ecological Modelling, Elsevier, vol. 220(7), pages 1013-1033.
    4. Frank H. Koch & Denys Yemshanov & Daniel W. McKenney & William D. Smith, 2009. "Evaluating Critical Uncertainty Thresholds in a Spatial Model of Forest Pest Invasion Risk," Risk Analysis, John Wiley & Sons, vol. 29(9), pages 1227-1241, September.
    5. Scheller, Robert & Kretchun, Alec & Hawbaker, Todd J. & Henne, Paul D., 2019. "A landscape model of variable social-ecological fire regimes," Ecological Modelling, Elsevier, vol. 401(C), pages 85-93.
    6. Lorscheid, Iris & Meyer, Matthias, 2016. "Divide and conquer: Configuring submodels for valid and efficient analyses of complex simulation models," Ecological Modelling, Elsevier, vol. 326(C), pages 152-161.
    7. Kanapaux, William & Kiker, Gregory A., 2013. "Development and testing of an object-oriented model for adaptively managing human disturbance of least tern (Sternula antillarum) nesting habitat," Ecological Modelling, Elsevier, vol. 268(C), pages 64-77.
    8. Chu-Agor, M.L. & Muñoz-Carpena, R. & Kiker, G.A. & Aiello-Lammens, M.E. & Akçakaya, H.R. & Convertino, M. & Linkov, I., 2012. "Simulating the fate of Florida Snowy Plovers with sea-level rise: Exploring research and management priorities with a global uncertainty and sensitivity analysis perspective," Ecological Modelling, Elsevier, vol. 224(1), pages 33-47.
    9. 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.
    10. R. Iestyn Woolway & Pille Meinson & Peeter Nõges & Ian D. Jones & Alo Laas, 2017. "Atmospheric stilling leads to prolonged thermal stratification in a large shallow polymictic lake," Climatic Change, Springer, vol. 141(4), pages 759-773, April.
    11. Petropoulos, G. & Wooster, M.J. & Carlson, T.N. & Kennedy, M.C. & Scholze, M., 2009. "A global Bayesian sensitivity analysis of the 1d SimSphere soil–vegetation–atmospheric transfer (SVAT) model using Gaussian model emulation," Ecological Modelling, Elsevier, vol. 220(19), pages 2427-2440.
    12. H. Christopher Frey & Sumeet R. Patil, 2002. "Identification and Review of Sensitivity Analysis Methods," Risk Analysis, John Wiley & Sons, vol. 22(3), pages 553-578, June.
    13. Gregory Hill & Steven Kolmes & Michael Humphreys & Rebecca McLain & Eric T. Jones, 2019. "Using decision support tools in multistakeholder environmental planning: restorative justice and subbasin planning in the Columbia River Basin," Journal of Environmental Studies and Sciences, Springer;Association of Environmental Studies and Sciences, vol. 9(2), pages 170-186, June.
    14. Wernsdörfer, H. & Rossi, V. & Cornu, G. & Oddou-Muratorio, S. & Gourlet-Fleury, S., 2008. "Impact of uncertainty in tree mortality on the predictions of a tropical forest dynamics model," Ecological Modelling, Elsevier, vol. 218(3), pages 290-306.
    15. Rougier, Thibaud & Drouineau, Hilaire & Dumoulin, Nicolas & Faure, Thierry & Deffuant, Guillaume & Rochard, Eric & Lambert, Patrick, 2014. "The GR3D model, a tool to explore the Global Repositioning Dynamics of Diadromous fish Distribution," Ecological Modelling, Elsevier, vol. 283(C), pages 31-44.
    16. Lola Gilbert & Tiphaine Jeanniard-du-Dot & Matthieu Authier & Tiphaine Chouvelon & Jérôme Spitz, 2023. "Composition of cetacean communities worldwide shapes their contribution to ocean nutrient cycling," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    17. Wu, Qiong-Li & Cournède, Paul-Henry & Mathieu, Amélie, 2012. "An efficient computational method for global sensitivity analysis and its application to tree growth modelling," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 35-43.
    18. Song, Xiaodong & Bryan, Brett A. & Almeida, Auro C. & Paul, Keryn I. & Zhao, Gang & Ren, Yin, 2013. "Time-dependent sensitivity of a process-based ecological model," Ecological Modelling, Elsevier, vol. 265(C), pages 114-123.
    19. López-Benito, Alfredo & Bolado-Lavín, Ricardo, 2017. "A case study on global sensitivity analysis with dependent inputs: The natural gas transmission model," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 11-21.
    20. Brown, S. & Beck, J. & Mahgerefteh, H. & Fraga, E.S., 2013. "Global sensitivity analysis of the impact of impurities on CO2 pipeline failure," Reliability Engineering and System Safety, Elsevier, vol. 115(C), pages 43-54.

    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:259:y:2013:i:c:p:16-23. 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.