The inf l uence of selective cutting of mixed Korean pine(Pinus koraiensis Sieb.et Zucc.)and broad-leaf forest on rare species distribution patterns and spatial correlation in Northeast China

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ORIGINAL PAPER

The inf l uence of selective cutting of mixed Korean pine(Pinus koraiensis Sieb.et Zucc.)and broad-leaf forest on rare species distribution patterns and spatial correlation in Northeast China

Binbin Kan1•Qingcheng Wang1•Wenjuan Wu1

©Northeast Forestry University and Springer-Verlag Berlin Heidelberg 2015

This study aimed to demonstrate change in spatial correlation between Korean pine(Pinus koraiensis Sieb.et Zucc.)and three rare species,and change in spatial distribution of four species in response to a range of selective cutting intensities.We sampled three plots of mixed Korean pine and broad-leaf forest in Lushuihe Forestry Bureau of Jilin province,China.Plot 1,a control, was unlogged Korean pine broad-leaf forest.In plots 2 and 3,Korean pine was selectively cut at 15 and 30%intensity,respectively,in the 1970s.Other species were rarely cut.We used point-pattern analysis to research the spatial distributions of four tree species and quantify spatial correlations between Korean pine and the other three species, Amur linden(Tilia amurensis Rupr.),Manchurian ash (Fraxinus mandshurica Rupr.),and Mongolian oak (Quercus mongolica Fisch.)in all three plots.The results of the study show that selective cutting at 15%intensity did not signif i cantly change either the species spatial patterns or the spatial correlation between Korean pine and broadleaf species.Selective cutting at 30%intensity slightly affected the growth of Korean pine and valuable species in forest communities,and the effect was considered nondestructive and recoverable.

Korean pine broad-leaf forest⋅Cutting intensity⋅Rare species⋅Spatial pattern⋅Spatial correlation

Introduction

Population spatial patterns and spatial correlations are critical to population study(Borchsenius et al.2004;Daz et al.2000).Population spatial pattern is studied to quantitatively describe stable population structures and understand their genesis(Condit et al.2000;Druckenbrod et al. 2005).Such studies contribute to understanding species growth,reproduction,death,regeneration,and resource utilization,as well as ecological processes(such as seed dispersal,intra-or inter-species competition,and interference),the biological characteristics of population(such as life history,phototaxis,and tolerance of shade)and environmental factors(e.g.,plant adaptations to environments, environmental heterogeneity)(Nathan 2006).Population distribution patterns change over time(Chen and Bradshaw 1999;Schurr et al.2004;Wiegand and Moloney 2004)due to environmental adaptation and natural selection(Masaki et al.2004).Environment often inf l uences the progress of population growth.Human activity is an important factor, especially harvesting,which affects ecosystem structure in ways different from the direction and speed of natural succession.Under the inf l uence of disturbance,different species have different mechanisms to adapt,thereby affecting the competition of plants for limited resources and resulting in differentiation of spatial patterns of populations(He and Duncan 2000).

Large areas of original forest in China were cut between the 1950s and 1980s.After 30 years of protection,natural secondary forests formed with varying patterns resultingfrom natural succession.Questions for forest managers include:which pattern is more conducive to population development and what kind of cutting intensity yields a productive pattern.Study of distribution pattern aids understanding of the structure and of forest succession processes.This provides a guide for complementary planting and harvesting during forest regeneration.Many researchers in China have focused on the study of the spatial patterns or spatial correlations of forest species(Ge et al.2008;Tang et al.2003;Yu et al.2009).However,the inf l uence of cutting intensities on spatial patterns and spatial correlation analysis of rare species in northeast China has been little studied.In this study,we researched spatial distributions of four tree species and spatial correlation between Korean pine and three other species,Amur linden,Manchurian ash,and Mongolian oak.

Materials and methods

Study area

The study was conducted at Dongsheng tree farm of Lushuihe Forestry Bureau in Jilin Province,China,west of the Changbai Mountains.Average elevation of the study site was 600–800 m,rarely above 1000 m,and the aspect mainly faced northwest.The climate is temperate continental.The combination of low temperature,low evaporation,and moist atmosphere benef i ts the formation of thick deciduous broad-leaf and coniferous mixed forests. Mixed Korean pine and broad-leaf forest was the typical vegetation type,where coniferous tree vegetation included Korean pine and Larch(Larix gmelinii(Rupr.)Kuzen.). Broad-leaf vegetation included Manchurian ash(Fraxinus mandshurica),Amur linden(Tilia amurensis),Amur phellodendron(Phellodendron amurense Rupr),Mongolian oak(Quercus mongolica),White birch(Betula platyphylla Suk),Manchurian walnut(Juglans mandshurica Maxim),Poplar(Populus spp.),Elm(U.Pumila L.)and Mono maple(Acer mono Maxim.).

Field investigation and data collection

Three sampling plots on similar aspects,slope gradients, and forest stands were demarcated in 2011 based on a longterm f i eld investigation and historical data from the local forestry bureau in Lushuihe area(Table 1).Plot 1 was original Korean pine and broad-leaf forest.Korean pine and other species had not been cut and human disturbance was uncommon.In plots 2 and 3,Korean pine was selective cut in the 1970s at 15 and 30%intensity,respectively, while other species were rarely cut.Study plot 1 was used as a control.The size of each sampling plot was 100×100 m,divided into 25 squares with dimensions of 20×20 m using a compass.A basis point was set up every 20 m.All trees of diameter at breast height(DBH)＞1 cm were tagged,and species,height,crown dimensions (east–west direction=crown length,north–south= crown length)and the tree location coordinates were recorded.

Statistical analysis

We used Ripley’s K function-based approach for spatial point pattern analysis(Ripley 1978).This method is commonly used to analyze spatial patterns at arbitrary scales because results are not inf l uenced by population density(Duncan and Stewart 1991;Zhan 1998;Rebertus and Moser 1989;Wang et al.1998).Ripley’s K function assigns individual trees a two-dimensional point and analyzes the spatial pattern and spatial correlation at multiple scales based on a two-point picture that includes all individuals.The method is widely used in the analysis of spatial patterns in plant populations.Besag(1977)optimized Ripley’s K function and proposed the evolutive function-L(t)(Besag 1977).In this study,L(t)functions were used for data analysis and processed using Programit software,in which the‘r’range of spatial scale was 0–50 m,and step length was 1 m with 98%conf i dence intervals bounded by upper and lower envelopes.These functions were calculated 100 times using the Monte-Carlo approach.In analyzing patterns of spatial distribution,if the function curve was above the upper envelope,under the lower envelope,or between these two envelopes,such pattern was considered an aggregated distribution,uniform distribution,or random distribution,respectively.For spatial correlation study,function L12(t)deformed from Ripley’s function k12(t)was adopted to calculate the spatial correlation of bivariate point patterns.If the function curve was above the upper envelope,under the lower envelope,or between these two envelopes,the relationship was considered positive,negative,or neutral correlation, respectively(Xin 2009).

Results

Structural analysis of diameter class

Korean pine was the dominant species in all three plots based on its highest percentile of large diameter trees (DBH＞50 cm)and largest breast-height basal area.The total breast-height basal area of broad-leaf species was signif i cantly less than that of Korean pine(Table 2;Fig.1). Because of selective cutting,the number of Korean pine trees left in plot 1 was more than that of plot 2,and plot 2was more than plot 3.The diameters of most Mongolian oak,Amur linden,and Manchurian ash ranged from 10 to 40 cm.

Table 1 Characteristics of three sample plots

Table 2 Basal area of four tree species and number of trees in three plots

Spatial distribution of Korean pine and three associated species

The distribution of Korean pine in three plots is presented in Fig.2.In the three plots,the density of Korean pine followed the order from high to low,of plot 1,plot 2,and plot 3.Aggregated distribution of Korean pine was shown in plot 1.Selective cutting in plot 3 resulted in a lack of Korean pine in some areas,and aggregated distribution was infrequently observed.Korean pine was aggregated at 0–23 m scale and randomly distributed at 23–50 m scale in plot 1(Fig.3,a-1),Korean pine showed an overall random distribution with an aggregation trend in plot 2(Fig.3, a-2).In plot 3,the distribution of Korean pine was aggregated,random,and uniform on 0–7 m,7–25 m,and 25–50 m scales,respectively(Fig.3,a-3).Mongolian oak was randomly distributed in plots 1 and 2(Fig.3,b-1,b-2). Aggregated distribution of Mongolian oak was recorded in plot 3 at both 5–10 m and 15–37 m scales,but random distribution was recorded at other scales(Fig.3,b-3). Amur linden was randomly distributed at 20–33 m and 37–48 m scales,or aggregated on other scales in plot 1 (Fig.3,c-1),randomly distributed at 0–50 m scale in plot 2 (Fig.3,c-2),and aggregated at 0–50 m scale in plot 3 (Fig.3,c-3).Manchurian ash was randomly distributed in plots 1 and 2,but aggregated at 17–28 m scale in plot 2, (Fig.3,d-1,d-2)and aggregated at all scales in plot 3 (Fig.3,d-3).

Analysis of spatial correlation between Korean pine and rare trees

Korean pine and Mongolian oak showed overall neutral correlation in all three plots,but positive correlation at 10–20 m scale in plot 1(Fig.4,e-1)and at a 0–12 m scale in plot 3(Fig.4,e-3).Korean pine and Amur linden showed neutral correlation at 0–25 m scale or negative correlation at 25-50 m scale in plot 1(Fig.4,f-1).Neutral correlation was recorded at 0–10 m scale or a tendency to negative correlation at 10-40 m scale in plot 2(Fig.4,f-2), and positive correlation,neutral,and negative correlation at 3–18 m,18–30 m,and 30-50 m scales in plot 3(Fig.4, f-3).Korean pine and Manchurian ash were neutrally correlated in all three plots,but negatively correlated at 37–42 and 44-50 m scales in plot 1(Fig.4,g-1),negatively correlated at 5–11 m scale in plot 2(Fig.4,g-2),and negatively correlated at 11–16 m scale in plot 3(Fig.4,g-3).

Discussion

Effects of selective cutting on spatial pattern of trees

Numerous studies have demonstrated that most natural populations,including conifer species,follow a cluster pattern as a result of the combined actions of arboreal growth,survival,intra-or inter-species competition,and interaction between species and habitat,thus ref l ecting adaptive mechanism of populations(Taylor et al.1996; Manabe and Yamamoto 1997;Zheng 1997;Manabe et al. 2000).Tree harvest inf l uences resource availability andalters the resource utilization eff i ciency of plant populations,thereby affecting changes in spatial relationships of plants.In this study,Korean pine showed superiority in all three plots based on its percentile of basal area in all species,although two of the plots had been selectively harvested at different cutting intensities.More Korean pines of large diameter and fewer saplings were observed,and most broad-leaf species were located in renewal and succession layers.Korean pine was aggregated at small scale(0–23 m) or randomly distributed at large scale(＞23 m)in plot 1, which could be explained by the number of saplings showing aggregated distribution around the parent trees that were randomly distributed.In previous studies of structural change in populations at different developmental stages,a similar phenomenon was observed(Li et al.2005; Xu et al.2005;Zhang et al.2009).This could be related to seed dispersal methods,renewal modes,and intra-or interspecies competition.Gravity is essential in the seed dispersal of Korean pine,in which seeds are scattered around the seed tree,resulting in aggregated distribution at small scales(Smith 1983).Otherwise,some scholars believe that the aggregate distribution of Korean pines is mainly due to action of squirrels(Lu 2003)Intra-specif i c competition for light,moisture,and nutrients causes large-scale mortality of Korean pine trees,resulting in a tendency toward random distribution of Korean pine in the population.Species tend to be aggregated at lower canopy layers,but randomly or evenly distributed in upper layers,the aggregation degree decreasing with canopy height(Zhang et al.2007). The severe selective cutting(30%intensity)caused a uniform distribution of Korean pines at broader scales as a result of human disturbance.Amur linden,Manchurian ash,and Mongolian oak all showed random distribution in plot 2,comparable to that in plot 1 and aggregated distribution in plot 3.Severe cutting produced large forest gaps that differed from the gaps formed by natural disturbance.This can inf l uence the structure and dynamic process of populations,thereby leading to the differentiation of distribution(Li and Wang 2009).Forest gaps increase ground temperatures and accelerate the decomposition of litter,this enables some light-tolerant species to accelerate growth,which increases population aggregation(Bai 2012 and Wan 2005).In plots 1 and 2,most broad-leaf species were recorded in succession and renewal layers.These species consume more resources,including light,moisture, and limited nutrients in the microenvironment.Competition results in natural forest thinning,which could explain why aggregated distribution is relatively uncommon and eventually manifests as uniform or random distribution.

Fig.1 Diameter class of the four species,a–c is four species in plot 1–3

Selective cutting effects on spatial relationships of trees

Fig.2 Spatial distribution of Pinus koraiensi s(dbh≥1 cm)in three plots(100×100 m),a–c is Pinus koraiensi s in plot 1–3

Fig.3 Spatial distribution of four species in each sample plot,X—scale/m,Y—L(t),black lines for L(t);the grey lines are the upper and lower envelopes;a1–a3 is the Pinus koraiensis spatial pattern in plots 1–3;b1–b3 is the Quercus mongolica spatial pattern in plots 1–3;c1–c3 is the Tilia amurensis spatial pattern in plot 1–3;and d1–d3 is the Fraxinus mandshurica spatial pattern in plots 1–3

Korean pine and Amur linden were negatively correlated at large spatial scale in all three plots(Fig.4,f1–f3).This suggested that Korean pine inhibited the growth of Amur linden at large spatial scale.This is consistent with results of Zhao et al.(2011).Korean pine was dominant in space and widely distributed in the overstory layer of the three plots,whereas Amur linden grew in the forest gaps,mostlylocated in the lower layer.Both Korean pine and Amur linden are light-tolerant species.(Song 2007;Xu 2001) Korean pine blocked sunlight required by Amur linden, resulting in a negative correlation or a tendency to be negatively correlated at large spatial scales.In contrast, Korean pine and Amur linden were positively correlated at small spatial scales under severe cutting because the selective cutting released the space occupied by Korean pine so that it enabled Amur linden to consume more sunlight and nutrients(Chen et al.2008).

Fig.4 Spatial correlations of Pinus koraiensis and three species in each sample plot,X—scale/m,Y—L12(t),black lines for L12(t);the grey lines are the upper and lower envelopes;e1–e3 is the Pinus koraiensis and Quercus mongolica spatial correlation in plot 1–3;f1–f3 is the Pinus koraiensis and Tilia amurensis spatial correlation in plot 1–3;g1–g3 is the Pinus koraiensis and Fraxinus mandshurica spatial correlation in plot 1–3

Korean pine and Manchurian ash were neutrally correlated in the three plots,with a tendency toward positive correlation as cutting intensity increased.This f i nding indicated that these two species could coexist in one community with minimal interplay.Most Manchurian ash grew in the midstory layers,where the requirements of growth space and nutrients were slightly limited by Korean pine.However,these two species were located in different growth layers.Manchurian ash grew well in the gaps of Korean pine,Han et al.(2004)found that sunlight penetration is critical to the regeneration of Manchurian Ash (Han et al.2004).Brokaw(1987)reported that some species are restricted by the size of canopy gaps.However, spatial distribution of saplings of most species is unrelated to canopy gaps(Milton Lieberman and Rodolfo 1995; Hubbell et al.1999).So it is necessary to further study the relationship between the canopy gap size and spatial distribution of Korean pine broad-leaf forest with respect to the distribution pattern of lower species.

Korean pine and Mongolian oak were neutrally associated in three plots.But a positive correlation was recorded between them at 0–12 m scale in plot 3 where excessive partial cutting released suff i cient sunlight,moisture,and nutrients to the broad-leaf species in the midstory andunderstory layers.This result is different from that of Zhang et al.(2006),which showed a positive correlation between Korean pine and Mongolian oak at 48–50 m scale, Zhang et al.(2006)has doubts about this result,he thinks because of Korean pine and Mongolian oak from 48 to 50 m scales are randomly distributed,so although the two species showed positive spatial correlation,there may be no interaction between them.Such spatial correlation may not have been caused by the effects of interspecif i c relationships(Zhang et al.2006).

Conclusions

The control plot without cutting was observed to have stable structureatthe top levelofsuccession.Thecutting ofKorean pine atthe overstory layerbenef i ted the growth ofbroad-leaf species.Large Korean pines and few seedlings or saplings were recorded in the three sampling plots.Such a pattern is not conducive to regeneration of Korean pine populations. Therefore,appropriate selective cutting of Korean pine is a good alternative to facilitate itsregeneration and promote the growth ofothervaluable broad-leafspecies.Korean pine and Amur linden compete with each other at large scales.Thus, complementary planting of Amur linden is not suggested. Selective cutting of either species could be considered according to demand to reduce interspecif i c competition and accelerate species growth.

AcknowledgmentsThe study was funded by China National Science and Technology Support Program(Grant No.2012BAD21B02). We are grateful to Wang Shuli,Gao Qunzong,Wang Haiyang for fi eld investigation assistance,and the Lushuihe Forestry Bureau of Jilin Province of China for logistical support.We also would like to thank two anonymous reviewers for their invaluable suggestions.

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28 June 2014/Accepted:12 January 2015/Published online:2 July 2015

Project funding:The study was funded by China National Science and Technology Support Program(Grant No.2012BAD21B02).

The online version is available at http://www.springerlink.com

Corresponding editor:Chai Ruihai

✉Qingcheng Wang

wqcnefu@163.com

1Forestry College of Northeast Forestry University,26 Hexing Rd,Harbin 150040,People’s Republic of China