Modelling predicts positive and negative interactions between three Australian tropical tree species in monoculture and binary mixture


Autoria(s): Manson, D.G.; Hanan, J.; Hunt, M.; Bristow, M.; Erskine, P.D.; Lamb, D.; Schmidt, S.
Data(s)

01/09/2006

Resumo

Computer modelling promises to be an important tool for analysing and predicting interactions between trees within mixed species forest plantations. This study explored the use of an individual-based mechanistic model as a predictive tool for designing mixed species plantations of Australian tropical trees. The `spatially explicit individually based-forest simulator' (SeXI-FS) modelling system was used to describe the spatial interaction of individual tree crowns within a binary mixed-species experiment. The three-dimensional model was developed and verified with field data from three forest tree species grown in tropical Australia. The model predicted the interactions within monocultures and binary mixtures of Flindersia brayleyana, Eucalyptus pellita and Elaeocarpus grandis, accounting for an average of 42% of the growth variation exhibited by species in different treatments. The model requires only structural dimensions and shade tolerance as species parameters. By modelling interactions in existing tree mixtures, the model predicted both increases and reductions in the growth of mixtures (up to +/-50% of stem volume at 7 years) compared to monocultures. This modelling approach may be useful for designing mixed tree plantations.

Identificador

Manson, D.G. and Hanan, J. and Hunt, M. and Bristow, M. and Erskine, P.D. and Lamb, D. and Schmidt, S. (2006) Modelling predicts positive and negative interactions between three Australian tropical tree species in monoculture and binary mixture. Forest Ecology and Management, 233 (2-3). pp. 315-323.

http://era.daf.qld.gov.au/1223/

Publicador

Elsevier B.V.

Relação

http://dx.doi.org/10.1016/j.foreco.2006.05.028

http://era.daf.qld.gov.au/1223/

Palavras-Chave #Sylviculture #Simulation modelling
Tipo

Article

PeerReviewed