Time-dependent sensitivity of a process-based ecological model

Ecological Modelling

Volumn 265, Issue , 2013, Pages 114-123

  Song, Xiaodong ^a,b   Bryan, Brett A ^b   Almeida, Auro C ^b   Paul, Keryn I ^b   Zhao, Gang ^b,c   Ren, Yin ^d  

^a ZHEJIANG UNIVERSITY   (China)

^b CSIRO   (Australia)

^c UNIVERSITY OF BONN   (Germany)

^d INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

Author keywords

3 PG; Forest growth model; Fourier amplitude sensitivity test; Process based model; Sensitivity analysis; Temporal

Indexed keywords

3-PG; FOREST GROWTH MODEL; FOURIER AMPLITUDE SENSITIVITY TESTS; PROCESS-BASED MODELS; TEMPORAL;

COMPUTER SIMULATION; ECOLOGY; FORESTRY; PHYSIOLOGICAL MODELS;

SENSITIVITY ANALYSIS;

BIOMASS; FOLIAGE; FOREST ECOSYSTEM; FOURIER TRANSFORM; GROWTH MODELING; MODEL VALIDATION; SENSITIVITY ANALYSIS; TIME DEPENDENT BEHAVIOR;

ECOLOGY; FORESTRY; FOURIER ANALYSIS; PHYSIOLOGY; SENSITIVITY;

EID: 84880357848     PISSN: 03043800     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ecolmodel.2013.06.013     Document Type: Article

References (56)

1. Almeida A.C., Landsberg J.J., Sands P.J. Parameterisation of 3-PG model for fast-growing Eucalyptus grandis plantations. Forest Ecology and Management 2004, 193:179-195.
2. Almeida A.C., Paul K.I., Siggins A., Sands P.J., Polglase P., Marcar N.E., Jovanovic T., Theiveyanathan S., Crawford D.F., England J.R., Falkiner R., Hawkins C., White D. Development, Calibration and Validation of the Forest Growth Model 3-PG with an Improved Water Balance, Client Report No. 1786 2007.
3. Almeida A.C., Siggins A., Batista T.R., Beadle C., Fonseca S., Loos R. Mapping the effect of spatial and temporal variation in climate and soils on Eucalyptus plantation production with 3-PG, a process-based growth model. Forest Ecology and Management 2010, 259:1730-1740.
4. Almeida A.C., Soares J.V., Landsberg J.J., Rezende G.D. Growth and water balance of Eucalyptus grandis hybrid plantations in Brazil during a rotation for pulp production. Forest Ecology and Management 2007, 251:10-21.
5. Borgonovo E. A new uncertainty importance measure. Reliability Engineering and System Safety 2007, 92:771-784.
6. Bryan B.A., Crossman N.D. Impact of multiple interacting financial incentives on land use change and the supply of ecosystem services. Ecosystem Services 2013, 4:60-72.
7. Bryan B.A., King D., Wang E. Potential of woody biomass production for motivating widespread natural resource management under climate change. Land Use Policy 2010, 27:713-725.
8. Cairns M.A., Brown S., Helmer E.H., Baumgardner G.A. Root biomass allocation in the world's upland forests. Oecologia 1997, 111:1-11.
9. Campolongo F., Cariboni J., Saltelli A. An effective screening design for sensitivity analysis of large models. Environmental Modelling & Software 2007, 22:1509-1518.
10. Cariboni J., Gatelli D., Liska R., Saltelli A. The role of sensitivity analysis in ecological modelling. Ecological Modelling 2007, 203:167-182.
11. Coops N.C., Hember R.A., Waring R.H. Assessing the impact of current and projected climates on Douglas-Fir productivity in British Columbia, Canada, using a process-based model (3-PG). Canadian Journal of Forest Research: Revue Canadienne de Recherche Forestiere 2010, 40:511-524.
12. Coops N.C., Waring R.H., Landsberg J.J. Assessing forest productivity in Australia and New Zealand using a physiologically-based model driven with averaged monthly weather data and satellite-derived estimates of canopy photosynthetic capacity. Forest Ecology and Management 1998, 104:113-127.
13. Crossman N.D., Bryan B.A., Summers D.M. Carbon payments and low-cost conservation. Conservation Biology 2011, 25:835-845.
14. Cukier R.I., Fortuin C.M., Shuler K.E., Petschek A.G., Schaibly J.H. Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. I Theory. The Journal of Chemical Physics 1973, 59:3873-3878.
15. Cukier R.I., Levine H.B., Shuler K.E. Nonlinear sensitivity analysis of multiparameter model systems. Journal of Computational Physics 1978, 26:1-42.
16. Cukier R.I., Schaibly J.H., Shuler K.E. Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. III Analysis of the approximations. The Journal of Chemical Physics 1975, 63:1140-1149.
17. Efron B., Tibshirani R. An Introduction to the Bootstrap 1993, Chapman Hall, New York.
18. Esprey L.J., Sands P.J., Smith C.W. Understanding 3-PG using a sensitivity analysis. Forest Ecology and Management 2004, 193:235-250.
19. Friedl M.A., Davis F.W., Michaelsen J., Moritz M.A. Scaling and uncertainty in the relationship between the NDVI and land surface biophysical variables: an analysis using a scene simulation model and data from FIFE. Remote Sensing of Environment 1995, 54:233-246.
20. Fuentes M., Kittel T.G.F., Nychka D. Sensitivity of ecological models to their climate drivers: statistical ensembles for forcing. Ecological Application 2006, 16:99-116.
21. Helton J.C. Uncertainty and sensitivity analysis for models of complex systems. Computational Methods in Transport: Verification and Validation, vol. 62 of Lecture Notes in Computational Science and Engineering 2008, 207-228.
22. Helton J.C., Johnson J.D., Sallaberry C.J., Storlie C.B. Survey of sampling-based methods for uncertainty and sensitivity analysis. Reliability Engineering and System Safety 2006, 91:1175-1209.
23. Iman R.L., Conover W. A measure of top-down correlation. Technometrics 1987, 29:351-357.
24. Kioutsioukis I., Tarantola S., Saltelli A., Gatelli D. Uncertainty and global sensitivity analysis of road transport emission estimates. Atmospheric Environment 2004, 38:6609-6620.
25. Landsberg J.J., Johnsen K.H., Albaugh T.J., Allen H.L., McKeand S.E. Applying 3-PG, a simple process-based model designed to produce practical results, to data from loblolly pine experiments. Forest Science 2001, 47:43-51.
26. Landsberg J.J., Waring R.H. A generalised model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning. Forest Ecology and Management 1997, 95:209-228.
27. Lu Y.C., Mohanty S. Sensitivity analysis of a complex proposed geologic waste disposal system using the Fourier amplitude sensitivity test method. Reliability Engineering and System Safety 2001, 72:275-291.
28. Makler-Pick V., Gal G., Gorfine M., Hipsey M.R., Carmel Y. Sensitivity analysis for complex ecological models - a new approach. Environmental Modelling & Software 2011, 26:124-134.
29. Marino S., Hogue I.B., Ray C.J., Kirschner D.E. A methodology for performing global uncertainty and sensitivity analysis in systems biology. Journal of Theoretical Biology 2008, 254:178-196.
30. Moradkhani H., Hsu K.L., Gupta H., Sorooshian S. Uncertainty assessment of hydrologic model states and parameters: sequential data assimilation using the particle filter. Water Resources Research 2005, 41:W05012.
31. Morris M.D. Factorial sampling plans for preliminary computational experiments. Technometrics 1991, 33:161-174.
32. Paterson S., Bryan B.A. Food-carbon trade-offs between agriculture and reforestation land uses under alternate market-based policies. Ecology and Society 2012, 17.
33. Paul K.I., Booth T.H., Jovanovic T., Sands P.J., Morris J.D. Calibration of the forest growth model 3-PG to eucalypt plantations growing in low rainfall regions of Australia. Forest Ecology and Management 2007, 243:237-247.
34. Plischke E., Borgonovo E., Smith C.L. Global sensitivity measures from given data. European Journal of Operational Research 2013, 226:536-550.
35. Ryan M.G., Yoder B.J. Hydraulic limits to tree height and tree growth. Bioscience 1997, 47:235-242.
36. Saltelli A. Sensitivity analysis as an ingredient of modeling. Statistical Science 2000, 15:377-395.
37. Saltelli A., Annoni P., Azzini I., Campolongo F., Ratto M., Tarantola S. Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index. Computer Physics Communications 2010, 181:259-270.
38. Saltelli A., Ratto M., Andres T., Campolongo F., Cariboni J., Gatelli D., Saisana M., Tarantola S. Global Sensitivity Analysis: The Primer 2008, John Wiley & Sons, Ltd.
39. Saltelli A., Tarantola S., Chan K.P.S. A quantitative model-independent method for global sensitivity analysis of model output. Technometrics 1999, 41:39-56.
40. Sands P.J. Adaptation of 3-PG to Novel Species: Guidelines for Data Collection and Parameter Assignment, Technical Report. No. 141 2004.
41. Sands P.J., Landsberg J.J. Parameterisation of 3-PG for plantation grown Eucalyptus globulus. Forest Ecology and Management 2002, 163:273-292.
42. Sobol' I.M. On sensitivity estimation for nonlinear mathematical models. Matematicheskoe Modelirovanie 1990, 2:112-118.
43. Song X., Bryan B.A., Paul K.I., Zhao G. Variance-based sensitivity analysis of a forest growth model. Ecological Modelling 2012, 247:135-143.
44. Spadavecchia L., Williams M., Law B.E. Uncertainty in predictions of forest carbon dynamics: separating driver error from model error. Ecological Applications 2011, 21:1506-1522.
45. Tarantola S., Gatelli D., Mara T.A. Random balance designs for the estimation of first order global sensitivity indices. Reliability Engineering and System Safety 2006, 91:717-727.
46. Thogmartin W.E. Sensitivity analysis of North American bird population estimates. Ecological Modelling 2010, 221:173-177.
47. Thornton P.E., Law B.E., Gholz H.L., Clark K.L., Falge E., Ellsworth D.S., Goldstein A.H., Monson R.K., Hollinger D., Falk M., Chen J., Sparks J.P. Modeling and measuring the effects of disturbance history and climate on carbon and water budgets in evergreen needleleaf forests. Agricultural and Forest Meteorology 2002, 113:185-222.
48. Tickle P.K., Coops N.C., Hafner S.D., Bago Sci T. Assessing forest productivity at local scales across a native eucalypt forest using a process model, 3PG-SPATIAL. Forest Ecology and Management 2001, 152:275-291.
49. van Oijen M., Cameron D.R., Butterbach-Bahl K., Farahbakhshazad N., Jansson P.E., Kiese R., Rahn K.H., Werner C., Yeluripati J.B. A Bayesian framework for model calibration, comparison and analysis: application to four models for the biogeochemistry of a Norway spruce forest. Agricultural and Forest Meteorology 2011, 151:1609-1621.
50. van Oijen M., Rougier J., Smith R. Bayesian calibration of process-based forest models: bridging the gap between models and data. Tree Physiol 2005, 25:915-927.
51. Vrugt J.A., Robinson B.A. Treatment of uncertainty using ensemble methods: comparison of sequential data assimilation and Bayesian model averaging. Water Resources Research 2007, 43.
52. Wang W., Ichii K., Hashimoto H., Michaelis A.R., Thornton P.E., Law B.E., Nemani R.R. A hierarchical analysis of terrestrial ecosystem model Biome-BGC: equilibrium analysis and model calibration. Ecological Modelling 2009, 220:2009-2023.
53. Xu C., Gertner G. Extending a global sensitivity analysis technique to models with correlated parameters. Computational Statistics & Data Analysis 2007, 51:5579-5590.
54. Xu C., Gertner G.Z., Scheller R.M. Uncertainties in the response of a forest landscape to global climatic change. Global Change Biology 2009, 15:116-131.
55. Xu C.G., Gertner G. Understanding and comparisons of different sampling approaches for the Fourier amplitudes sensitivity test (FAST). Computational Statistics & Data Analysis 2011, 55:184-198.
56. Yang J. Convergence and uncertainty analyses in Monte-Carlo based sensitivity analysis. Environmental Modelling & Software 2011, 26:444-457.