Uncertainty in a cellular automata model for vegetation change

REFERENCES

• Adamatzky, A. (1994) Identification of Cellular Automata, Taylor & Francis, London.
   Google Scholar
• Alonso, D., & Solé, R.V. (2000) The DivGame simulator: a stochastic cellular automata model of rainforest dynamics. Ecological Modelling, vol. 133, no. 1–2, pp. 131–141.
   Web of Science ®Google Scholar
• Antos, M.J., & Bennett, A.F. (2005) How important are different types of temperate woodlands for ground-foraging birds?Wildlife Research, vol. 32, no. 6, pp. 557–572.
   Web of Science ®Google Scholar
• Antos, M.J., Bennett, A.F., & White, J.G. (2008) Where exactly do ground-foraging woodland birds forage? Foraging sites and microhabitat selection in temperate woodlands of southern Australia. Emu, vol. 108, no. 3, pp. 201–211.
   Web of Science ®Google Scholar
• Baetens, J.M., Van der Weeën, P., & De Baets, B. (2012) Effect of asynchronous updating on the stability of cellular automata. Chaos, Solitons and Fractals, vol. 45, no. 4, pp. 383–394.
   Web of Science ®Google Scholar
• Balzter, H., Braun, P.W., & Köhler, W. (1998) Cellular automata models for vegetation dynamics. Ecological Modelling, vol. 107, no. 2–3, pp. 113–125.
   Web of Science ®Google Scholar
• Barrett, G.W., Ford, H.A., & Recher, H.F. (1994) Conservation of woodland birds in a fragmented rural landscape. Pacific Conservation Biology, vol. 1, no. 3, pp. 245–256.
   Google Scholar
• Batty, M., & Xie, Y. (2005) Urban growth using cellular automata models. In: Maguire, D.J., Batty, M., & Goodchild, M.F., eds. GIS, Spatial Analysis and Modelling, ESRI Press, Redlands, CA, pp. 151–172.
   Google Scholar
• Bolt, W., Baetens, J.M., & De Baets, B. (2013) Identifying CAs with evolutionary algorithms. In: Kari, J., Kutrib, M., & Malcher, A., eds. 19th International Workshop on Cellular Automata and Discrete Complex Systems, Sep 17–19Giessen, Germany, pp. 11–20.
   Google Scholar
• Bone, C., Dragicevic, S., & Roberts, A. (2006) A fuzzy-constrained cellular automata model of forest insect infestations. Ecological Modelling, vol. 192, no. 1–2, pp. 107–125.
   Web of Science ®Google Scholar
• Bowen, M.E., McAlpine, C.A., House, A.P.N., & Smith, G.C. (2007) Regrowth forests on abandoned agricultural land: a review of their habitat values for recovering forest fauna. Biological Conservation, vol. 140, no. 3–4, pp. 273–296.
   Web of Science ®Google Scholar
• Breckling, B., Pe'er, G., & Matsinos, Y.G. (2011) Cellular automata in ecological modelling. In: Jopp, F., Reuter, H., & Breckling, B., eds. Modelling Complex Ecological Dynamics, Springer, Berlin, pp. 105–117.
   Google Scholar
• Bureau of Meteorology (2013) Climate data online. Available from: http://www.bom.gov.au/climate/data/, Commonwealth of Australia.
   Google Scholar
• Carey, P.D. (1996) DISPERSE: a cellular automaton for predicting the distribution of species in a changed climate. Global Ecology and Biogeography Letters, vol. 5, no. 4/5, pp. 217–226.
   Web of Science ®Google Scholar
• Cariboni, J., Gatelli, D., Liska, R., & Saltelli, A. (2007) The role of sensitivity analysis in ecological modelling. Ecological Modelling, vol. 203, no. 1–2, pp. 167–182.
   Web of Science ®Google Scholar
• Caswell, H., & Etter, R. (1999) Cellular automaton models for competition in patchy environments: facilitation, inhibition, and tolerance. Bulletin of Mathematical Biology, vol. 61, no. 4, pp. 625–649.
   PubMed Web of Science ®Google Scholar
• Childress, W.M., Rykiel, E.J.Jr, Forsythe, W., Li, B.L., & Wu, H.I. (1996) Transition rule complexity in grid-based automata models. Landscape Ecology, vol. 11, no. 5, pp. 257–266.
   Web of Science ®Google Scholar
• Cohen, J. (1960) A coefficient of agreement for nominal scales. Educational Psychological Measurement, vol. 20, no. 1, pp. 37–46.
   Web of Science ®Google Scholar
• Couclelis, H. (1985) Cellular worlds: a framework for modeling micro – macro dynamics. Environment and Planning A, vol. 17, no. 5, pp. 585–596.
   Web of Science ®Google Scholar
• Couto, P. (2003) Assessing the accuracy of spatial simulation models. Ecological Modelling, vol. 167, no. 1–2, pp. 181–198.
   Web of Science ®Google Scholar
• Cremer, K.W. (1977) Distance of seed dispersal in eucalypts estimated from seed weights. Australian Forest Research, vol. 7, pp. 225–228.
   Web of Science ®Google Scholar
• CSIRO (2007) Climate change in Australia: technical report, CSIRO and Bureau of Meteorology, Australia. Available from: http://www.climatechangeinaustralia.gov.au/technical_report.php.
   Google Scholar
• Czaran, T., & Bartha, S. (1992) Spatiotemporal dynamic models of plant populations and communities. Trends in Ecology Evolution, vol. 7, no. 2, pp. 38–42.
   PubMed Web of Science ®Google Scholar
• Di Traglia, M., Attorre, F., Francesconi, F., Valenti, R., & Vitale, M. (2011) Is cellular automata algorithm able to predict the future dynamical shifts of tree species in Italy under climate change scenarios? A methodological approach. Ecological Modelling, vol. 222, no. 4, pp. 925–934.
   Web of Science ®Google Scholar
• Dorrough, J., & Moxham, C. (2005) Eucalypt establishment in agricultural landscapes and implications for landscape-scale restoration. Biological Conservation, vol. 123, no. 1, pp. 55–66.
   Web of Science ®Google Scholar
• Dragićević, S. (2010) Modeling the dynamics of complex spatial systems using GIS, cellular automata and fuzzy sets applied to invasive plant species propagation. Geography Compass, vol. 4, no. 6, pp. 599–615.
   Google Scholar
• Durrett, R. (2009) Coexistence in stochastic spatial models. The Annals of Applied Probability, vol. 19, no. 2, pp. 477–496.
   Web of Science ®Google Scholar
• Durrett, R., & Levin, S. (1994) Stochastic spatial models: a user's guide to ecological applications. Philosophical Transactions of the Royal Society B: Biological Sciences, vol. 343, no. 1305, pp. 329–350.
   Web of Science ®Google Scholar
• Florence, R.G. (1996) Ecology and Silviculture of Eucalypt Forests, CSIRO Publishing, Melbourne.
   Google Scholar
• Gardner, M. (1970) Mathematical games: the fantastic combinations of John Conway's new solitaire game ‘Life’. Scientific American, vol. 223, no. 4, pp. 120–123.
   Web of Science ®Google Scholar
• Geddes, L.S., Lunt, I.D., Smallbone, L.T., & Morgan, J.W. (2011) Old field colonization by native trees and shrubs following land use change: could this be Victoria's largest example of landscape recovery?Ecological Management and Restoration, vol. 12, no. 1, pp. 31–36.
   Google Scholar
• Graniero, P.A. (2007) The influence of landscape heterogeneity and local habitat effects on the response to competitive pressures in metapopulations. Ecological Modelling, vol. 203, no. 3–4, pp. 349–362.
   Web of Science ®Google Scholar
• Hamby, D.M. (1994) A review of techniques for parameter sensitivity analysis of environmental models. Environmental Monitoring and Assessment, vol. 32, no. 2, pp. 135–154.
   PubMed Web of Science ®Google Scholar
• Hasbani, J.G., Wijesekara, N., & Marceau, D.J. (2011) An interactive method to dynamically create transition rules in a land-use cellular automata model. In: Salcido, A., ed. Cellular Automata: Simplicity behind Complexity, InTech, New York.
   Google Scholar
• Hobbs, R.J., & Cramer, V.A. (2007) Why old fields? Socioeconomic and ecological causes and consequences of land abandonment. In: Cramer, V.A., & Hobbs, R.J., eds. Old Fields: Dynamics and Restoration of Abandoned Farmland, Island Press, Washington, DC, pp. 1–14.
   Google Scholar
• Itami, R.M. (1994) Simulating spatial dynamics: cellular automata theory. Landscape and Urban Planning, vol. 30, no. 1–2, pp. 27–47.
   Web of Science ®Google Scholar
• Kocabas, V., & Dragicevic, S. (2006) Assessing cellular automata model behaviour using a sensitivity analysis approach. Computers, Environment and Urban Systems, vol. 30, no. 6, pp. 921–953.
   Web of Science ®Google Scholar
• Lai, T., Dragićević, S., & Schmidt, M. (2013) Integration of multicriteria evaluation and cellular automata methods for landslide simulation modelling. Geomatics, Natural Hazards and Risk, vol. 4, no. 4, pp. 355–375.
   Web of Science ®Google Scholar
• Levins, R. (1966) The strategy of model building in population biology. American Scientist, vol. 54, no. 4, pp. 421–431.
   Web of Science ®Google Scholar
• Li, X., Lin, J., Chen, Y., Liu, X., & Ai, B. (2013) Calibrating cellular automata based on landscape metrics by using genetic algorithms. International Journal of Geographical Information Science, vol. 27, no. 3, pp. 594–613.
   Web of Science ®Google Scholar
• Li, X., & Yeh, A.G.-O. (2000) Modelling sustainable urban development by the integration of constrained cellular automata and GIS. International Journal of Geographical Information Science, vol. 14, no. 2, pp. 131–152.
   Web of Science ®Google Scholar
• Liu, Y., & Phinn, S.R. (2003) Modelling urban development with cellular automata incorporating fuzzy-set approaches. Computers, Environment and Urban Systems, vol. 27, no. 6, pp. 637–658.
   Google Scholar
• Ma, Z., & Redmund, R.L. (1995) Tau coefficients for accuracy assessment of classification of remote sensing data. Photogrammetric Engineering and Remote Sensing, vol. 61, no. 4, pp. 435–439.
   Web of Science ®Google Scholar
• Maeda, K., & Sakama, C. (2007) Identifying cellular automata rules. Journal of Cellular Automata, vol. 2, no. 1, pp. 1–20.
   Web of Science ®Google Scholar
• Manning, A.D., Fischer, J., & Lindenmayer, D.B. (2006) Scattered trees are keystone structures – implications for conservation. Biological Conservation, vol. 132, no. 3, pp. 311–321.
   Web of Science ®Google Scholar
• Matsinos, Y.G., & Troumbis, A.Y. (2002) Modeling competition, dispersal and effects of disturbance in the dynamics of a grassland community using a cellular automaton model. Ecological Modelling, vol. 149, no. 1–2, pp. 71–83.
   Web of Science ®Google Scholar
• Ménard, A., & Marceau, D.J. (2005) Exploration of spatial scale sensitivity in geographic cellular automata. Environment and Planning B: Planning and Design, vol. 32, no. 5, pp. 693–714.
   Web of Science ®Google Scholar
• Ménard, A., & Marceau, D.J. (2007) Simulating the impact of forest management scenarios in an agricultural landscape of southern Quebec, Canada, using a geographic cellular automata. Landscape and Urban Planning, vol. 79, no. 3–4, pp. 253–265.
   Web of Science ®Google Scholar
• Montague-Drake, R.M., Lindenmayer, D.B., & Cunningham, R.B. (2009) Factors affecting site occupancy by woodland bird species of conservation concern. Biological Conservation, vol. 142, no. 12, pp. 2896–2903.
   Web of Science ®Google Scholar
• Moreno, N., Ménard, A., & Marceau, D.J. (2008) VecGCA: a vector-based geographic cellular automata model allowing geometric transformations of objects. Environment and Planning B: Planning and Design, vol. 35, no. 4, pp. 647–665.
   Web of Science ®Google Scholar
• Moreno, N., Wang, F., & Marceau, D.J. (2009) Implementation of a dynamic neighborhood in a land-use vector-based cellular automata model. Computers, Environment and Urban Systems, vol. 33, no. 1, pp. 44–54.
   Web of Science ®Google Scholar
• Pan, Y., Roth, A., Yu, Z., & Doluschitz, R. (2010) The impact of variation in scale on the behavior of a cellular automata used for land use change modeling. Computers, Environment and Urban Systems, vol. 34, no. 5, pp. 400–408.
   Web of Science ®Google Scholar
• Rey Benayas, J.M., Martins, A., Nicolau, J.M., & Schulz, J.J. (2007) Abandonment of agricultural land: an overview of drivers and consequences. CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources, vol. 2, no. 57, pp. 1–14.
   Google Scholar
• Ruxton, G.D., & Saravia, L.A. (1998) The need for biological realism in the updating of cellular automata models. Ecological Modelling, vol. 107, no. 2–3, pp. 105–112.
   Web of Science ®Google Scholar
• Soares-Filho, B.S., Coutinho Cerqueira, G., & Lopes Pennachin, C. (2002) DINAMICA—a stochastic cellular automata model designed to simulate the landscape dynamics in an Amazonian colonization frontier. Ecological Modelling, vol. 154, no. 3, pp. 217–235.
   Web of Science ®Google Scholar
• Story, M., & Congalton, R.G. (1986) Accuracy assessment: a user's perspective. Photogrammetric Engineering and Remote Sensing, vol. 52, no. 3, pp. 397–399.
   Web of Science ®Google Scholar
• Sun, X., Rosin, P.L., & Martin, R.R. (2011) Fast rule identification and neighborhood selection for cellular automata. IEEE Transactions on Systems, Man, Cybernetics, Part B (Cybernetics), vol. 41, no. 3, pp. 749–760.
   PubMed Web of Science ®Google Scholar
• van Wijk, M.T., & Rodriguez-Iturbe, I. (2002) Tree-grass competition in space and time: insights from a simple cellular automata model based on ecohydrological dynamics. Water Resources Research, vol. 38, no. 9, pp. 18-1–18-15.
   Web of Science ®Google Scholar
• Vega, E., & Montaña, C. (2011) Effects of overgrazing and rainfall variability on the dynamics of semiarid banded vegetation patterns: a simulation study with cellular automata. Journal of Arid Environments, vol. 75, no. 1, pp. 70–77.
   Web of Science ®Google Scholar
• Vesk, P.A., & Dorrough, J.W. (2006) Getting trees on farms the easy way? Lessons from a model of eucalypt regeneration on pastures. Australian Journal of Botany, vol. 54, no. 6, pp. 509–519.
   Web of Science ®Google Scholar
• Watson, D.M. (2011) A productivity-based explanation for woodland bird declines: poorer soils yield less food. Emu, vol. 111, no. 1, pp. 10–18.
   Web of Science ®Google Scholar
• White, R., & Engelen, G. (2000) High-resolution integrated modelling of the spatial dynamics of urban and regional systems. Computers, Environment and Urban Systems, vol. 24, no. 5, pp. 383–400.
   Google Scholar
• Wiens, J.A. (1989) The Ecology of Bird Communities: Volume One, Foundations and Pattern, Cambridge University Press, Cambridge.
   Google Scholar
• Wolfram, S. (1984) Cellular automata as models of complexity. Nature, vol. 311, no. 5985, pp. 419–424.
   Web of Science ®Google Scholar
• Wrigley, J.W., & Fagg, M. (1991). 3rd ed.Australian Native Plants, Harper Collins, London.
   Google Scholar
• Yang, Y., & Billings, S.A. (2000) Neighborhood detection and rule selection from cellular automata patterns. IEEE Transactions on Systems, Man, Cybernetics – Part A: Systems Humans, vol. 30, no. 6, pp. 840–847.
   Web of Science ®Google Scholar
• Yassemi, S., Dragićević, S., & Schmidt, M. (2008) Design and implementation of an integrated GIS-based cellular automata model to characterize forest fire behaviour. Ecological Modelling, vol. 210, no. 1–2, pp. 71–84.
   Web of Science ®Google Scholar