Free Access
Issue
Ann. For. Sci.
Volume 67, Number 5, July-August 2010
Article Number 502
Number of page(s) 11
DOI https://doi.org/10.1051/forest/2010004
Published online 29 April 2010
  • Begon M., Harper J.L., and Townsend C.R., 1996. Ecology: individuals, populations and communities. Blackwell Publishing, Oxford, 1068 p. [Google Scholar]
  • Biging G.S., and Dobbertin M., 1992. A comparison of distance-dependent competition measures for height and basal area growth of individual conifer trees. For. Sci. 38: 695–720. [Google Scholar]
  • Biondi F., Klemmedson J.O., and Kuehl R.O., 1992. Dendrochronological analysis of single-tree interactions in mixed pine oak stands of central Arizona, USA. For. Ecol. Manage. 48: 321–333. [CrossRef] [Google Scholar]
  • Canham C.D., LePage P.T., and Coates K.D., 2004. A neighborhood analysis of canopy tree competition: effects of shading versus crowding. Can. J. For. Res. 34: 778–787. [CrossRef] [Google Scholar]
  • Canham C.D., Papaik M.J., Uriarte M., McWilliams W.H., Jenkins J.C., and Twery M.J., 2006. Neighborhood analyses of canopy tree competition along environmental gradients in New England forests. Ecol. Appl. 16: 540–554. [CrossRef] [PubMed] [Google Scholar]
  • Coligny F.D., Ancelin P., Cornu G., Courbaud B., Dreyfus P., Goreaud F., Gourlet-Fleury S., Meredieu C., and Saint-André L., 2003. CAPSIS: computer-aided projection for strategies in silviculture: advantages of a shared forest-modelling platform. International Workshop of IUFRO working party 4.01 “Reality, models and parameter estimation”. Sesimbra, Portugal, June 2–5, 2002. Modelling Forest Systems. CABI Publishing, Wallingford, UK, pp. 319–323. [Google Scholar]
  • Comas C., and Mateu J., 2007. Modelling forest dynamics: a perspective from point process methods. Biom. J. 49: 176–196. [CrossRef] [MathSciNet] [PubMed] [Google Scholar]
  • Goreaud F., 2000. Apports de l’analyse de la structure spatiale en forêt tempérée à l’étude et la modélisation des peuplements complexes. M.S. thesis, ENGREF, 362 p. [Google Scholar]
  • Goreaud F., Loreau M., and Millier C., 2002. Spatial structure and the survival of an inferior competitor: a theoretical model of neighbourhood competition in plants. Ecol. Model. 158: 1–19. [CrossRef] [Google Scholar]
  • Goreaud F., Loussier B., Ngo Bieng M.A., and Allain R., 2004. Simulating realistic spatial structure for forest stands: a mimetic point process. Interdisciplinary Spatial Statistics Workshop, Paris. 22 p. [Google Scholar]
  • Grissino-Mayer H.D., 2002. Research report evaluating crossdating accuracy: a manual and tutorial for the computer program COFECHA. Tree-Ring Res. 57: 205–221. [Google Scholar]
  • Illian J., Penttinen A., Stoyan H., and Stoyan D., 2008. Statistical analysis and modelling of spatial point patterns, Wiley, Chichester, 560 p. [Google Scholar]
  • Kokkila T., Makela A., and Nikinmaa E., 2002. A method for generating stand structures using Gibbs marked point process. Silva Fenn. 36: 265–277. [Google Scholar]
  • Lotwick H.W., and Silverman B.W., 1982. Methods for analysing spatial processes of several types of points. J. R. Stat. Soc. B 44: 406–413. [Google Scholar]
  • Morneau F., Duprez C., and Hervé J.C., 2008. Les forêts mélangées en France métropolotaine. Caractérisation à partir des résultats de l’Inventaire Forestier National. Rev. For. Fr. LX: 107–120. [Google Scholar]
  • Munro D.D., 1974. Forest growth models – a prognosis. Growth models for tree and stand simulation. Proceedings of the IUFRO congress S4-01-4, Stockholm, Department of forest yield research, Royal College of Forestry pp. 7–21. [Google Scholar]
  • Ngo Bieng M.A., 2007. Construction de modèles de structure spatiale permettant de simuler des peuplements virtuels réalistes. Application aux peuplements mélangés chêne sessile – pin sylvestre de la région Centre. M.S. Thesis, ENGREF-Cemagref, Nogent-sur-Vernisson, 183 p. [Google Scholar]
  • Ngo Bieng M.A., Ginisty C., Goreaud F., and Perot T., 2006. A first typology of oak and Scots pine mixed stands in the Orléans forest (France), based on the canopy spatial structure. N. Z. J. For. Sci. 36: 325–346. [Google Scholar]
  • Phillips P.D., Thompson I.S., Silva J.N.M., van Gardingen P.R., and Degen B., 2004. Scaling up models of tree competition for tropical forest population genetics simulation. Ecol. Model. 180: 419–434. [CrossRef] [Google Scholar]
  • Pommerening A., 2006. Evaluating structural indices by reversing forest structural analysis. For. Ecol. Manage. 224: 266–277. [CrossRef] [Google Scholar]
  • Pommerening A., and Stoyan D., 2008. Reconstructing spatial tree point patterns from nearest neighbour summary statistics measured in small subwindows. Can. J. For. Res. 38: 1110–1122. [CrossRef] [Google Scholar]
  • Porté A., and Bartelink H.H., 2002. Modelling mixed forest growth: a review of models for forest management. Ecol. Model. 150: 141–188. [CrossRef] [Google Scholar]
  • Pretzsch H., 1997. Analysis and modeling of spatial stand structures. Methodological considerations based on mixed beech-larch stands in Lower Saxony. For. Ecol. Manage. 97: 237–253. [Google Scholar]
  • Pukkala T., 1989. Methods to describe the competition process in a tree stand. Scan. J. For. Res. 4: 187–202. [CrossRef] [Google Scholar]
  • Regent I., 2005. Windendro 2005a: manual for tree-ring analysis. Université du Québec à Chicoutimi, 132 p. [Google Scholar]
  • Rio M. and Sterba H., 2009. Comparing volume growth in pure and mixed stands of Pinus sylvestris and Quercus pyrenaica. Ann. For. Sci. 66: 502. [CrossRef] [EDP Sciences] [Google Scholar]
  • Ripley B.D., 1977. Modelling spatial patterns. J. R. Stat. Soc. B 39: 172–212. [Google Scholar]
  • Ripley B.D., 1981. Spatial statistics. Wiley, New York, 250 p. [Google Scholar]
  • Stadt K.J., Huston C., Coates K.D., Feng Z., Dale M.R.T., and Lieffers V.J., 2007. Evaluation of competition and light estimation indices for predicting diameter growth in mature boreal mixed forests. Ann. For. Sci. 64: 477–490. [CrossRef] [EDP Sciences] [Google Scholar]
  • Stoyan D., and Penttinen A., 2000. Recent applications of point process methods in forestry statistics. Stat. Sci. 15: 61–78. [Google Scholar]
  • Tilman D., 1988. Plant strategies and the dynamics and structure of plant communities. Princeton University Press, Princeton, USA. [Google Scholar]
  • Ulrich E., Renaud J.P., Nageleisen L.M., Flot J.L., Dumé G., Bilger I., Colin E., Ferrand P., Peyron J.L., and Hamza N., 2006. Les indicateurs de gestion durable des forêts française – édition 2005. Ministère de l’Agriculture et de la Pêche, IFN, 148 p. [Google Scholar]
  • Uriarte M., Canham C.D., Thompson J., and Zimmerman J.K. 2004a. A neighborhood analysis of tree growth and survival in a hurricane-driven tropical forest. Ecol. Monogr. 74: 591–614. [CrossRef] [Google Scholar]
  • Uriarte M., Condit R., Canham C.D., and Hubbell S.P. 2004b. A spatially explicit model of sapling growth in a tropical forest: does the identity of neighbours matter? J. Ecol. 92: 348–360. [CrossRef] [Google Scholar]
  • Wimberly M.C., and Bare B.B., 1996. Distance-dependent and distance-independent models of Douglas-fir and western hemlock basal area growth following silvicultural treatment. For. Ecol. Manage. 89: 1–11. [CrossRef] [Google Scholar]
  • Wyckoff P.H., and Clark J.S., 2000. Predicting tree mortality from diameter growth: a comparison of maximum likelihood and Bayesian approaches. Can. J. For. Res. 30: 156–167. [CrossRef] [Google Scholar]
  • Wykoff W.R., 1990. A basal area increment model for individual conifers in the northern Rocky Mountains. For. Sci. 36: 1077–1104. [Google Scholar]
  • Zhao D., Borders B., Wilson M., and Rathbun S.L., 2006. Modeling neighborhood effects on the growth and survival of individual trees in a natural temperate species-rich forest. Ecol. Model. 196: 90–102. [CrossRef] [Google Scholar]