Analysis Of Second-order Characteristics Of Stand Spatial Structure Of Natural Forests

Spatial structure is an important feature of forest stands.It is considered the reflection of the spatial organization relationships between trees in a forest community.The current structure state is not only the traces leaved by natural ecological processes(such as inter-tree competition,regeneration,growth,death,etc.)and human activities in past,but also acts as the initial state determining interactions and competition among plants,affecting the growth and survival of seedlings and the formation of tree canopy.Thus,forest structure is an important determinant for the future development of forest stands.For researches regarding forest management and ecology,proper and effective characterization of forest structure using mathematical and statistical methods depends on the scientific interpretation of forest spatial structure.Proper modelling methods of forest structure will assist us to understand and infer the natural ecological processes that determine the development of forest stands,and can provide theoretical knowledge for sustainable forest management as well.Structure indexes based on the relationship description between a reference tree and its four nearest neighbors expressed different aspects of forest structure,and these structure indexes have been applied to describe the structure of various forest types worldwide.It provides a novel method for forest management and ecology researches,and revealed many interesting structure characteristics of natural forests.In the construction of this set of structure indexes,the selection of fixed four nearest neighbors around a reference tree has been widely used and recognized to be effective,but some studies argued that,similar to single tree competition analysis,other potential methods of nearest neighbor identification may provide useful alternatives for more reasonable quantification of forest spatial structure.However,for this set of structure indexes,if other nearest neighbor identification methods that are used for constructing competition indexes can be simply applied,or how the application of unfixed number of neighboring trees influences the expression of these structure indexes,remains unclear.Hence,these disputes need to be solved urgently.Structure indexes based on nearest neighbor analysis simply quantify spatial correlations between nearest neighbors at a certain scale,while second order characteristics of forest stand structure can express spatial patterns of trees at varying scales.Null models can also be used to examine if second order functions of observed forests deviate from independent spatial dispersal patterns at different scales and the degree of deviation.Many forest ecology researches used second order functions,especially the unmarked point process(Ripley's K function,O-ring statistics,pair correlation functions and etc.),to analyze spatial distribution patterns of forest trees,spatial correlations between tree species and etc.However,most of these studies were only descriptive analysis but did not build a link between structure and forest natural ecologic processes,i.e.,trying to infer some important ecological processes that structure forest communities from the observed spatial patterns of trees.Especially statistics of marked point processes are less used,which considers spatial dispersal patterns of tree attributes,such as species,size,etc.While forest spatial structure not only contains information of distribution patterns of tree positions but the spatial arrangement of tree natural attributes,the application of marked second order functions can characterize different aspects of forest structure and quantify the diversity of forest spatial structure.These marked point processes statistics can also be used to understand and infer some interesting ecological processes in natural forests in which the structure is mainly a result of long term effects of ecological processes.This study firstly clarified the connections and differences between the two point pattern statistical approaches of nearest neighbor analysis and second order spatial pattern statistics,and then by using both nearest neighbor analysis and second order statistics,we analyzed forest stands spatial structure characteristics of two Mongolian Scots pine stands and four Korean pine broad-leaved stands(each stand has an area of 1 ha).By analyzing the spatial structure of these forest stands,we studied the prevalence of inter-tree competition and its importance in shaping the structure of Mongolian Scots pine forests,and identified the effects of negative conspecific density dependence in affecting neighborhood species segregation of Korean pine broad-leaved natural forests.When analyzing how sampling unit size influenceneighborhood-based spatial structure indexes,we simulated stands with different spatial structural characteristics and systematically compared their structure indexes(Uniform angle index,mingling and dominance)when two to eight neighboring trees were selected.In order to test the effects of inter-tree competition on shaping community structure,we used the nearest neighbour method to determine the presence of competition,and unmarked and marked spatial point pattern analyses to test the density-dependent mortality effects and the spatial autocorrelation of tree size.Mingling index and mark mingling second order function were both used to examine if large trees are surrounded by more heterospecific trees in Korean pine broad-leaved forests.If large size trees have significantly greater mingling levels than small trees,the ecological processes behind these special observed patterns in long-term undisturbed forests can be inferred as strong intraspecific interactions.The main findings of this study are listed in the following:(1)Although the fixed number structure unit(e.g.four-tree structure unit)has been successfully applied in the structure attributes analysis,our results showed the neighborhood-based structure analyses can be influenced by the structure unit size.For the estimation of the patterns of tree locations,we found that selecting different numbers of neighboring trees strongly influenced the uniform angle index.Its values obtained from different sizes of structure units under complete spatial randomness differed and were not always ~0.5.The influence of structure unit size on mingling and dominance structural indices depended on tree species and size spatial arrangement patterns to a great extent.When tree species and sizes were completely randomly interspersed,different numbers of neighbors had little influence on mingling and dominance indices.Changes of mingling or dominance indexes caused by different numbers of neighbors occurred when the tree species or size classes were not randomly interspersed and their changing characteristics can be detected according to the spatial arrangement patterns of tree species and sizes.The number of neighboring trees selected for analyzing stand spatial structure parameters should be fixed.We found that we may have biased assessment of distribution patterns of trees locations with respect to non-random patterns that were very close to random distribution patterns when two or three neighboringtrees were used.We proposed that the four-tree structure unit is the best compromise between sampling accuracy and costs for practical forest management.(2)We collected two observational plot data from a natural Mongolian Scots pine forest and used spatial point pattern analysis to detect the contribution of competition to tree growth,mortality,and size inequality.The nearest neighbour analysis of the correlation between the combined distances of the nearest neighbours to a focal tree and the combined crown length showed significant positive correlations in both plots,suggesting that competition was an important factor in reducing individual tree growth.The pair correlation functions of both plots exhibited regular distribution patterns of all trees including dead and living trees and of living trees at small scales.The random labelling null model clearly rejected the random mortality hypothesis in both plots,indicating trees living in more crowded environments were more likely to die.However,the mark differentiation characteristics showed weak evidence of a negative spatial autocorrelation in tree size,particularly in the high-density plot.We suggest that the high mortality rate of suppressed trees and weak asymmetric competition may have accounted for the lack of dissimilarity in tree size.This study showed that inter-tree competition is an important determinant of the development of Mongolian Scots pine forests.Regulating competition is necessary for enhancing the stability and species diversity in young or middle-aged natural P.sylvestris var.mongolica forests.(3)According to the negative conspecific density dependent effects,we expect that neighborhood species segregation increases with increasing tree sizes,and therefore larger trees are surrounded by more heterospecific neighbors than smaller trees due to negative density dependent effects.Our results show that bigger trees(DBH > 25)generally have higher species mingling levels and low mingling levels are specifically associated with small trees(DBH < 25).Under heterogeneous Poisson null model tests,mark mingling functions of different tree size classes showed that neighborhood species segregation ranged from lower than expected levels to random or close to random patterns at small scales as tree size classes increased.Bigger trees(DBH > 25)generally have more heterospecific neighbors than smalltrees at a range of 15 m.This study provides some evidence in support of negative density dependent effects in temperate forests.