Competition indices at the individual tree level in a mixed ombrophylous forest

被引:0
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作者
Schons C.T. [1 ]
Filho A.F. [1 ,2 ]
Santos T.L. [1 ]
Nascimento R.G.M. [3 ]
机构
[1] Universidade Federal do Paraná - UFPR, Curitiba, PR
[2] Universidade Estadual do Centro-Oeste - UNICENTRO, Irati, PR
[3] Universidade Federal Rural da Amazônia - UFRA, Belém, PA
来源
Scientia Forestalis/Forest Sciences | 2021年 / 48卷 / 128期
关键词
Araucaria forest; Distance-independent indices; Forest management; Periodic increment;
D O I
10.18671/SCIFOR.V48N128.13
中图分类号
学科分类号
摘要
This study aimed to investigate competitive interactions which influence the growth in individual basal area for individual trees of four species in a Montane Mixed Ombrophilous Forest (FOM) in southern Brazil, seeking to identify an index that best represents the competition for these species. The data came from permanent plots installed and monitored since 2002 in the Irati National Forest (FLONA de Irati), Paraná state, Brazil. Seven distance-independent competition indices were evaluated, based on graphical analysis and the linear correlation coefficient between each index and the periodic annual increment in individual basal area. The best performance competition index was selected to predict growth rates related to competition indices of the species Araucaria angustifolia, Cedrela fissilis, Ocotea puberula and Ocotea odorifera and analyze the dynamics of competition. In general, all indices evaluated showed a good correlation with the growth of individual trees, especially for the Lorimer, Glover and Holl and Stage indices. The competition-growth relationship showed differences between species, suggesting that there are species with more and less sensitive growth to the competition variation, probably related to their ecological characteristics. The distance-independent competition indices tested in this study are recommended to represent competition in Mixed Ombrophilous Forest and contribute with subsidies in the context of increment sub-models in individual tree level modeling. © 2020 University of Sao Paolo. All rights reserved.
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