Front. For. China (2006) 1: 28–32DOI 10.1007/s11461-005-0022-0

RESEARCH ARTICLE

Zhang Zhi, Sun Yujun

Distribution of Landscape Elements Along EnvironmentalGradients in Over-Cut Forests

# Higher Education Press and Springer-Verlag 2006

Abstract The method of trend surface analysis was usedto analyze the distribution of landscape elements alongenvironmental gradients in Jingouling forest farm, north-east China’s Jilin Province. Results showed that topograph-ic characteristics and disturbance pattern have much moreimpacts on the distribution of landscape elements thando horizontal geographical position in the study area. Theelevation, slope aspect, and slope degree were found to bedominant features controlling landscape pattern. At differ-ent altitudinal ranges, the effects of slope aspect and slopedegree on the distribution of landscape elements vary mark-edly in orientation and intensity. These differences wereanalyzed and discussed, and some basic rules of spatialdistribution of landscape elements were proposed.

Keywords landscape ecology, landscape pattern,trend surface analysis, forest landscape, spatial distribution

JEL Classification X144

1 Introduction

How to command exactly the general spatial distributiontrend and rules of landscape elements is a problem that wehave to face in the study of landscape ecology [1,2]. Thetrend surface analysis was adopted as a special tactic meth-od to study the geographical distribution trend of plant com-munities or populations in a specific scope [3], which wasalso called large-scale pattern analysis [4]. The geographi-cal spatial distribution rules of communities or populationsare not always clear because of the complicated environ-mental factors. The variational trend of the geographicaldistribution of communities or populations controlled by

environmental factors can be determined by building atrend surface model to eliminate the effects of some factors.Therefore, it is an effective method of quantitative analysisin community or population ecology [5]. This method wasonce proposed to analyze landscape pattern and its mechan-ics [6], but how to apply it and how to reveal the basiccharacteristics and variational trend of the spatial distribu-tion of these landscape elements from real landscape stillneed further study.

The Jingouling forest farm is located at the Changbai-shan forest area in Jilin Province, whose forest coveragerate reaches 94% and nature forest area accounts for 84% ofthe total forest area. The mixed forest of spruce, fir, andbroad-leaved trees is originally the dominant forest typeand belongs to climax community in the forest ecologicalsuccession. It exhibits enormous productivity and stabilityand plays a very important role in keeping landscape hetero-geneity and stability. At the same time, it offers numerousforest products and other services for the society. However,the current ecosystem of spruce and fir forms after severaltimes of intensive selection cutting, with an intensity of30%–50%, and recovers after tens of years. Now, the forestlandscape exhibits a complicated mosaic pattern due tovaried landforms and frequent human activities. Under thejoint control of ecosuccession and disturbance, ecologicalprocess is very active, and the change of landscape patternis also complicated. Hence, it is very difficult to graspintuitively the spatial distribution trend and rules. Thestudy attempts to reveal the basic characteristics andchanging rules of the spatial pattern of forest landscape,which will be helpful to promote sustainable managementof forest resources and sustainable economic developmentin this area.

2 General situation of the study area

The experimental field is located at Jingouling farm (43°22′N, 130°10′E) in Jilin Province. It has a hilly geomor-phology, with an elevation of 300–1,200 m and a slope of10–25°. This area has a monsoon climate, with mean annual

Translated from Scientia Silvae Sinicae, 2004, 41(1) (in Chinese)

Zhang Zhi (*), Sun YujunKey Laboratory for Silviculture and Conservation,Ministry of Education, Beijing Forestry University,Beijing 100083, ChinaE-mail: zhangzhibjfu@yahoo.com.cn

temperature of 4°C for the whole year, the lowest temper-ature of −32°C in January, and the highest temperature of22°C in July. The annual precipitation is 600–700 mm,mainly concentrated in July. The soil is podzolic gray brownearth in the middle and low mountain areas, coniferousgray brown earth between 800 and 1,000 m above sealevel, and meadow soil, muddy soil, bog soil, or warpedsoil in ravines. The soil is grainy and loose clay, with anaverage thickness of 40 cm.

3 Methods

3.1 Basic information

A classification system of landscape elements according totree species was established, which was based on a landformand forest map (1:50,000 in scale, not shown) of Jingoulingforest farm with a reference to local forest inventory datamanagement (Table 1). We can deal with the map men-tioned above through GIS software. Landform map andthe digital landscape layout of this area were built bymean of GIS software after a series of steps (scanning,specifying, editing, building topological relation, datainput).

3.2 Determination of succession state

To discover the spatial distribution trend of landscape ele-ments along environmental gradients, the authors used com-

munity continuum index (CI) to determine the successionstate of the community [7]:

CI ¼X

IV � CAV

where IV is the importance value of arbor species and CAVis the climax adaptive value. Because the value of CI is verysmall, which is not convenient to simulate and compare, wedivide further the classification unit of the environmentalelements and add the first classification code to the formula.

SI ¼X

IV � CAV þ n� 10

where SI is the succession index and n is the first classi-fication code.

3.3 Building of the grid layout

A set of uniform grid layouts were established based on thesame TIC points by using the software ArcInfo. A squaregrid with a size of 12 hm2 was used in this study. First, thecenter point of the grid was determined, and then the mar-ginal layout was used to cut and delete the grids out of thegrid layout. A total of 1,986 grid points were used in thisstudy.

3.4 Sampling of grid points and building of database

The grid layout and landform layout were piled up, and thegeographical attribute data of every sample point were ob-tained with the help of TIN functions of ArcInfo; the gridlayout and landscape layout were piled up and the land-scape attribute data were obtained. Databases of the setupof the landscape element distribution were prepared, includ-ing the sample code, abscissa, Y-coordinate, slope aspect,slope degree, elevation and succession index, etc.

3.5 Building and analysis of trend surface model

A binary multinomial was used to analyze the trend surfaceusing SI as the trend value of the simulated model. The geo-graphical location, elevation, slope aspect, and slope degreeof the south–north and east–west directions were regardedas independent variables. To analyze conveniently and setup a three-dimensional model of trend surface, we selectedeach two elements mentioned above to set up the models.

The model can be expressed as SI = a0 + a1X + a2Y +a3X

2 + a4XY + a5Y2 + a6X

3 + a7X2Y + a8XY

2 + a9Y3,

where a0 – a9 are multinomial coefficients and X and Y aresimulated variables of the model.

The least square method was used to estimate the modelparameters. Using the software MatLab, the normal equa-tion was set up on the computer based on the database ofsample points. Then, the parameters of the coefficient model

Table 1 Classification system of landscape elements

First class Code Secondary class Code SI

Pure forest 1 Pinus koraiensis 11 19Picea jezoensis 12 17Pinus sylvestris 13 15Larix olgensis var. changpaiensis 14 16Ulmus propinqua 15 13Betula platyphylla 16 12

Relativelypure forest

2 P. koraiensis 21 29P. jezoensis 22 27P. sylvestris 23 26L.olgensis var. changpaiensis 24 25Abies nephrolepis 25 28U. propinqua 26 24B. platyphylla 27 23Populus ussuriensis 28 21Shaw 29 22

Mixed forest 3 Spruce and fir mixed forest 31 39Larch, maple, basswood, spruce,and fir mixed forest

32 36

Maple, basswood, poplar, birch,spruce, and fir mixed forest

33 34

Broad-leaved mixed forest 34 32

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of normal equation were obtained, and the map of trendsurface model was drawn.

4 Results and analysis

4.1 Horizontal spatial distribution patternof landscape elements

Taking the abscissa and y-axis of sample point as inde-pendent variables and the succession index of landscapeelements as dependent variable, the spatial model of thepresent horizontal distribution was set up (Fig. 1). At thesame time, the trend surface model of the present horizontaldistribution was set up based on the succession index oflandscape elements (Fig. 2).

Comparing Fig. 1 with Fig. 2, the trend surface modelreflects the distribution pattern of landscape elements inJingouling forest farm, but there exists a marked differencebetween them, which shows that the landscape heteroge-neity is obvious and part landform plays an important rolein controlling the spatial distribution of landscape elements.Therefore, as a determinant of spatial pattern of landscapeelements, horizontal geographical position has no signif-icant impact on the spatial pattern of complicated secondaryforest mosaics. The horizontal distribution trend of environ-mental elements reflects, in essence, the controlling roles oflandform and topography in the study area. It is necessaryto further analyze the impacts of landform on the environ-mental pattern.

4.2 The controlling roles of elevation and slope aspectto distribution pattern of landscape elements

Taking elevation and slope as independent variables andthe succession index as the dependent variable, the trendsurface model along the gradient of elevation and aspect

was set up (Fig. 3). To analyze conveniently, the distribu-tion trend maps along the gradient at different elevations insunny and shady slopes were drawn (Fig. 4).

From Figs. 3 and 4, an obvious general trend of zonaldistribution along the gradient of elevation can be observed.Such a trend weakens among different elevations and slopeaspects with the increase in elevation above 1,000 m. Never-theless, the difference enlarges with the increase in eleva-tion below 1,000 m, and the difference between differentslope aspects is more marked than that among elevations.Obviously, it is because of human activities in low elevations.

It can be observed that the succession index of the shadyslope is low in the low altitude zone and the change ismarked. The main reason is that the forest farm mainly

Fig. 1 Spatial model of present horizontal distribution

Fig. 2 Trend surface model of present horizontal distribution

Fig. 3 Trend surface model along the gradient of elevation andslope aspect

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adopts a clear cutting model during the period of 1954–1958. Since then, larch was the main tree species planted inthe deforested lands. At present, the major forest types arepure larch forest and relatively pure larch forest. The changein sunny slopes is smaller than that in sunny slopes, andmixed tree species are planted. The forest type at elevationsbelow 400 m is mixed forest composed of maple, bass, pop-lar, birch, spruce, and fir, and at 400–1,000 m, it is spruceand fir mixed forest, or coniferous and broad-leaved mixedforest. In higher elevations, the succession indexes at differ-ent aspects vary gently, with the same forest type as that at400 –1,000 m.

Succession indexes at eight different aspects were se-lected for comparison, and it can be found that the indexesdiffer markedly, with the highest in the northwest aspectand lowest in the north aspect. Landscape elements have anobvious general distribution trend along slope aspects. Thesuccession indexes at different slope aspects follow anorder of northwest > west > southwest > south > southeast >east > northeast > north.

4.3 Effect of slope degree on the spatial distributionpattern of landscape elements

From Figs. 5 and 6, it can be observed that when the slopedegree is below 18°, the succession index is low, and theforest types are mainly coniferous and broad-leaved mixedforest and broad-leaved mixed forest; when the slope degreeis above 18°, the forest type is mainly mixed forest. Thepattern is restricted by two facts: firstly, the gentle slopesare often located at the mountain ridge or ravine bottom, soforest distribution is restricted due to special landform andhuman activities; secondly, with the decrease in elevation,the succession index is low due to cutting intensity in gentleslopes.

Generally, the effect of slope on the spatial distributionof landscape elements exhibits through enhancing the roleof slope aspect in improving the water conditions. There-fore, the changes of site conditions because of differentslope degrees is not the crucial factor determining the spatialdistribution trend of forest type in the study area, but afactor in part area.

5 Conclusion

Trend surface analysis is a method commonly used incommunity and population ecology. It can effectively an-alyze the general spatial distribution trend of landscapeelements, by which we can grasp the general characteristicsof landscape pattern and discover the spatial distributiontrend of landscape elements and controlling factors.

Horizontal geographical position has no significant im-pact on the spatial pattern of secondary forest mosaics inthe Jingouling forest farm.

The spatial pattern of landscape elements is mostly con-trolled by landform characteristics and interference pattern,and the elevation, slope aspect and slope degree are leadingfactors controlling the spatial distribution pattern of land-scape elements.

Fig. 4 Comparison of distribution trend along the elevation inshady and sunny slopes

Fig. 5 Trend surface model along the gradient of slope aspect andslope degree

Fig. 6 Comparison of distribution trend along the slope degree inshady and sunny slopes

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At different altitudinal ranges, the effects of slope aspectand slope degree on the distribution of landscape elementsvary markedly in orientation and intensity.

Acknowledgement This study was financially supported by “theTenth 5-Year Plan” National Key Research Project of Environ-mentally Sound Forest Management Techniques & Models in theNortheastern China (Grant No. 2001BA510B0703).

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