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Study On Restoration Of Broad-leaved Korean Pine Forest Based On Spatial Structure Optimization

Posted on:2019-09-22Degree:MasterType:Thesis
Country:ChinaCandidate:L L CaoFull Text:PDF
GTID:2393330572954076Subject:Ecology
Abstract/Summary:PDF Full Text Request
In this study,we used field survey data to classify the broad-leaved Korean pine forest of Changbai Mountain after disturbed by harvesting.Taking the original broad-leaved Korean pine forest as the control,the spatial distribution pattern and spatial correlation of the main tree species in different forest types were analyzed by point pattern analysis method.And then the spatial structure optimization simulation of different types of secondary forests was carried out.Major results were as follows:1.The fixed plots of Lushuihe Forest Bureau could be divided into 6 forest types,namely,which were the original broad-leaved Korean pine forest(BKPF),the larch forest(LF),the birch forest(BF),the selective cutting forest in the early restoration stage(ESF),the selective cutting forest in the middle restoration stage(MSF),the selective cutting forest in the later stage restoration(LSF).2.The order from high to low of main tree species important values in BKPF were Pinus koraiensis,Tilia amurensis,Quercus mongolica,Fraxinus mandshurica and Ulmus japonica.Pinus koraiensis was in an absolute dominant position.Compared with BKPF,the species composition of three selective cutting forests had changed,slightly.Pinus koraiensis was still dominant.The species composition of BF and LF was obviously different from that of BKPF and selective cutting forests.The average DBH of Pinus koraiensis and timber species was not significantly different from that of BKPF in MSF and LSF.While the average DBH of Pinus koraiensis and timber species was significantly lower than that of BKPF in LF,BF and ESF.3.The age structure of the main tree species in different forest types was different.The density of large diameter Pinus koraiensis,Tilia amurensis and Quercus mongolica in BKPF was higher than other forest types.While the density of young trees was extremely low.Compared with BKPF,the density of large diameter Pinus koraiensis increased,that of young trees was extremely low in LSF.The density of Pinus koraiensis and timber species decreased,while that of young trees increased in MSF,LSF,LF and BF.The regeneration of undergrowth improved in MSF,LSF,LF and BF.4.In different forest types,the spatial distribution pattern of main tree species were different.The main tree species in BKPF,except Tilia amurensis,showed a significant aggregation distribution on small scale,while Pinus koraiensis,Quercus mongolica,Fraxinus mandshurica and Ulmus japonica were randomly distributed in the scale of study.The spatial distribution pattern of the same species in other community types were different significantly,especially in BF,LF and ESF.However,most of them showed significant aggregation distribution on small scale,while the degree of aggregation decreased or showed randomly distributed as the scale increased.5.Interspecific spatial association was different among different forest types.It was uncorrelated between most of main species in the scale of study in BKPF.There was no interspecific spatial association between most main tree species in MSF and LSF in the scale of study,either.While only the interspecific spatial association between Fraxinus mandshurica and other tree species changed in MSF.It was negatively correlated between main tree species in BF.Only a few species in LF were uncorrelated.6.In the study,Pinus koraiensis and timber species were selected as reserved tree species.Most cutting tree species were associated tree species,such as Syringa reticulate var.Mandshurica,A.mono,A.ukurunduense,Malus baccata.Spatial structure optimization improved the dominant position and competitive ability of the reserved tree species,which adjusted the tree species composition to a certain extent,thus the stability of the stand structure was improved and the expected purpose was achieved.
Keywords/Search Tags:Forest type division, spatial pattern, interspecific correlation, spatial structure optimization
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