Multiple-scale spatial analysis of community structure in a mountainous mixed evergreen-deciduous broad-leaved forest, southwest China

doi:10.3724/SP.J.1003.2009.08148

Abstract

Abstract:

To investigate the spatial-dependence of heterogeneity at multiple scales for a community, we selected a representative plot of 100 m × 100 m in the mountainous evergreen and deciduous mixed broad-leaved forest in Sichuan, southwest China (102°50´E, 30°02´N). The location of every tree was mapped by compass, and all-scale analysis of spatial structure of forest community was conducted by the method of PCNM (principal coordinates of neighbor matrices). The results showed that Pielou evenness index, gap-fraction, openness, stand basal area, and stand density were influenced by spatial structure of the community at a broad scale. At the same time Pielou evenness index was impacted significantly by stand density, direct radiation, and leaf area index at all scales, while soil organic matter contents were markedly influenced by stand density, biomass, direct radiation, and gap-fraction at each scale. It could be concluded that community structure and environmental factors are markedly influenced by spatial sampling procedures. Our results highlighted that PCNM analysis could achieve a spectral decomposition vector of the spatial relationships among sampling sites, and that the significant PCNM variables could be directly interpreted in terms of spatial scales, or including variation decomposition with respect to spatial and environmental components. Canonical correlation analysis also indicated that forest community structure variables were correlated significantly with light factors, and both were interacted with each other and correlated well with PCNM variables. Therefore, the method of PCNM could help to understand the scale-dependence of heterogeneity at the community level.

Key words: ecological community, spatial patterns, principal coordinates of neighbor matrices (PCNM), scale, spatial model

Anjiu Zhao, Tingxing Hu, Xiaohong Chen. Multiple-scale spatial analysis of community structure in a mountainous mixed evergreen-deciduous broad-leaved forest, southwest China[J]. Biodiv Sci, 2009, 17(1): 43-50.

Add to citation manager EndNote|Ris|BibTeX

URL: https://www.biodiversity-science.net/EN/10.3724/SP.J.1003.2009.08148

https://www.biodiversity-science.net/EN/Y2009/V17/I1/43

Figures/Tables 5

References 38

[1]	Blackburn TM, Gaston KJ (1996) Spatial patterns in the geographic range sizes of bird species in the New World. Philosophical Transactions of the Royal Society of London B, 351, 897-912.
[2]	Blackburn TM, Gaston KJ (1996) Spatial patterns in the species richness of birds in the New World. Ecography, 19, 369-376.
[3]	Borcard D, Legendre P (1994) Environmental control and spatial structure in ecological communities: an example using oribatid mites (Acari, Oribatei). Environmental and Ecological Statistics, 1, 37-61.
[4]	Borcard D, Legendre P (2002) All-scale spatial analysis of ecological data by means of principal coordinates of neighbour matrices. Ecological Modelling, 153, 51-68.
[5]	Borcard D, Legendre P, Avois-Jacquet C, Tuomisto H (2004) Dissecting the spatial structure of ecological data at multiple scales. Ecology, 85, 1826-1832.
[6]	Borcard D, Legendre P, Drapeau P (1992) Partialling out the spatial component of ecological variation. Ecology, 73, 1045-1055.
[7]	Brown MJ, Parker GC (1994) Canopy light transmittance in a chronosequence of mixed-species deciduous forests. Canadian Journal of Forest Research, 24, 1694-1703.
[8]	Chen J, Song B, Mark R, Moeur M, Bible K (2004) Spatial relationship of biomass and species distribution in an old-growth Pseudotauga-Tsuga forest. Forest Science, 50, 364-376.
[9]	Chen J, Bradshaw GA (1999) Forest structure in space: a case study of an old growth spruce-fir forest in Changbaishan Natural Reserve, PR China. Forest Ecology and Management, 120, 205-215.
[10]	Clark DB, Clark DA, Rich PM, Weiss S (1996) Landscape-scale analyses of forest structure and understory light environments in a neotropical lowland rain forest. Canadian Journal of Forest Research, 26, 747-757.
[11]	Cormack RM, Ord JK (1979) Spatial and Temporal Analysis in Ecology. International Co-operative Publishing House, Fairland.
[12]	Gimaret-Carpentier C, Dray S, Pascal JP (2003) Broad-scale biodiversity pattern of the endemic tree flora of the Western Ghats (India) using canonical correlation analysis of herbarium records. Ecography, 26, 429-444.
[13]	Gittins R (1968) Trend-surface analysis of ecological data. Journal of Ecology, 56, 845-869.
[14]	Gittins R (1985) Canonical Analysis, A Review with Applications in Ecology. Springer-Verlag, Berlin.
[15]	Legendre P (1993) Spatial autocorrelation: trouble or new paradigm? Ecology, 74, 1659-1673.
[16]	Legendre P, Fortin MJ (1989) Spatial pattern and ecological analysis. Vegetatio, 80, 107-138.
[17]	Legendre P, Legendre L (1998) Numerical Ecology, 2nd edn. Elsevier Science, Amsterdam.
[18]	Méot A, Legendre P, Borcard D (1998) Partialling out the spatial component of ecological variation: questions and propositions in the linear modelling framework. Environmental and Ecological Statistics, 5, 1-27.
[19]	Michael AB, Robert JM, Paul PM, Stephen DP (2003) Light transmittance estimates in a longleaf pine woodland. Forest Science, 49, 752-762.
[20]	Norcliffe GB (1969) On the use and limitations of trend surface models. Canadian Geographer, 13, 338-348.
[21]	O’Neill RV, King AW(1998) Why are there so many books on scale? In: Ecological Scale—Theory and Applications (eds Peterson DL, Parker VT), pp. 3-15. Columbia University Press, New York.
[22]	Olden JD, Jackson DA, Peres-Neto PR (2001) Spatial isolation and fish communities in drainage lakes. Oecologia, 127, 572-585. DOI URL PMID
[23]	Pélissier R (1998) Tree spatial patterns in three contrasting plots in a southern Indian tropical moist evergreen forest. Journal of Tropical Ecology, 14, 1-16.
[24]	Pélissier R, Dray S, Sabatier D (2002) Within-plot relationships between tree species occurrences and hydrological soil constraints: an example in French Guiana investigated through canonical correlation analysis. Plant Ecology, 162, 143-156.
[25]	Peres-Neto PR (2004) Patterns in the co-occurrence of fish species in streams: the role of site suitability, morphology and phylogeny versus species interactions. Oecologia, 140, 352-360.
[26]	Roxburgh SH, Matsuki M (1999) The statistical validation of null models used in spatial association analyses. Oikos, 85, 68-78.
[27]	Scarlett MJ (1972) Problems of analysis of spatial distribution. In: Congrès International de Géographie (eds Adams WP, Helleiner FM), pp. 928-931, University of Toronto Press, Montréal.
[28]	Selmi S, Boulinier T (2001) Ecological biogeography of southern ocean islands: the importance of considering spatial issues. The American Naturalist, 158, 426-437. URL PMID
[29]	Shi HJ, Zhang LJ, Liu JG (2006) A new spatial-attribute weighting function for geographically weighted regression. Canadian Journal of Forest Research, 36, 996-1006.
[30]	Smith EP (2002) Ecological statistics. In: Encyclopedia of Environmetrics (eds El-Shaarawi AH, Piergorsch WW), pp. 589-602, John Wiley and Sons, Chichester.
[31]	Smith TM, Urban DL (1988) Scale and resolution of forest structural pattern. Vegetatio, 74, 143-150.
[32]	Sokal RR (1979) Testing statistical significance of geographic variation patterns. Systematic Zoology, 28, 227-232.
[33]	Student (1914) The elimination of spurious correlation due to position in time or space. Biometrika, 10, 179-180.
[34]	Wagner HH (2003) Spatial covariance in plant communities: integrating ordination, geostatistics, and variance testing. Ecology, 84, 1045-1057.
[35]	Wagner HH (2004) Direct multi-scale ordination with canonical correspondence analysis. Ecology, 85, 342-351.
[36]	Wartenberg D (1985) Canonical trend surface analysis: a method for describing geographic pattern. Systematic Zoology, 34, 259-279.
[37]	White PS, Miller RI (1988) Topographic models of vascular plant richness in the southern Appalachian peaks. Journal of Ecology, 76, 192-199.
[38]	Xiao DN (肖笃宁), Bu RC (布仁仓), Li XZ (李秀珍) (1997) Spatial ecology and landscape heterogeneity. Acta Ecologica Sinica (生态学报), 17, 453-461. (in Chinese with English abstract)

	均匀度指数 Pielou evenness index	大尺度 Broad scale	中尺度Medium scale	小尺度 Fine scale
R² of environments	0.674	0.964	0.575	0.757
胸径 Diameter at breast height	0.018	0.023		0.017
树高 Height		0.038		0.042
冠层高 Canopy height	0.021	0.007		0.070
林分密度 Stand density	0.011	0.010	0.0001	0.012
空隙度 GapFraction	0.075			0.077
叶面积指数 Leaf area index	0.066	0.098	0.001
聚集指数 Index of clumping leaves	0.036	0.100		0.031
林下地表直接辐射 Direct radiation		0.032	0.012	0.033
有机质 Organic matters contents	0.045	0.041		0.052
开度 Openness		0.039
冠层下散射的光通量密度 Diffuse photosynthetic photon flux density under canopy	0.086

	均匀度指数 Pielou evenness index	大尺度 Broad scale	中尺度Medium scale	小尺度 Fine scale
R² of environments	0.674	0.964	0.575	0.757
胸径 Diameter at breast height	0.018	0.023		0.017
树高 Height		0.038		0.042
冠层高 Canopy height	0.021	0.007		0.070
林分密度 Stand density	0.011	0.010	0.0001	0.012
空隙度 GapFraction	0.075			0.077
叶面积指数 Leaf area index	0.066	0.098	0.001
聚集指数 Index of clumping leaves	0.036	0.100		0.031
林下地表直接辐射 Direct radiation		0.032	0.012	0.033
有机质 Organic matters contents	0.045	0.041		0.052
开度 Openness		0.039
冠层下散射的光通量密度 Diffuse photosynthetic photon flux density under canopy	0.086

	有机质 Organic matter content	大尺度 Broad scale	中尺度Medium scale	小尺度 Fine scale
R² of environment	0.701	0.967	0.856	0.944
胸径 Diameter at breast height	0.002	0.015	0.004	0.008
冠层高 Canopy height	0.033	0.005	0.001	0.091
林分密度 Stand density	0.003	0.008
生长速率 Growth ratio of BA	0.005	0.017	0.002
生物量 Biomass	0.0001	0.055	0.006	0.068
空隙度 GapFraction	0.010	0.002	0.018	0.071
叶面积指数 Leaf area index	0.042	0.029		0.040
聚集指数 Index of clumping leaves	0.007		0.008	0.033
林下地表直接辐射 Direct radiation	0.001	0.030	0.004	0.085
林下地表散射 Diffuse radiation	0.015	0.012	0.003
冠层下散射的光通量密度 Diffuse photosynthetic photon flux density under canopy	0.022			0.043
开度 Openness	0.011

	有机质 Organic matter content	大尺度 Broad scale	中尺度Medium scale	小尺度 Fine scale
R² of environment	0.701	0.967	0.856	0.944
胸径 Diameter at breast height	0.002	0.015	0.004	0.008
冠层高 Canopy height	0.033	0.005	0.001	0.091
林分密度 Stand density	0.003	0.008
生长速率 Growth ratio of BA	0.005	0.017	0.002
生物量 Biomass	0.0001	0.055	0.006	0.068
空隙度 GapFraction	0.010	0.002	0.018	0.071
叶面积指数 Leaf area index	0.042	0.029		0.040
聚集指数 Index of clumping leaves	0.007		0.008	0.033
林下地表直接辐射 Direct radiation	0.001	0.030	0.004	0.085
林下地表散射 Diffuse radiation	0.015	0.012	0.003
冠层下散射的光通量密度 Diffuse photosynthetic photon flux density under canopy	0.022			0.043
开度 Openness	0.011

第一组变量 First group variables	第二组变量 Second group variables	典型相关系数 Canonical correlation coefficients	典型变量 Canonical variables
结构因子 Structure variables	光因子 Light variables	λ₁ = 0.940634	V₁= -2.8062DBH+1.1367Height+0.5801BRHH+2.7372BA-2.3781DEN -0.1896GRBA+0.179biomass-1.6385 volume W₁ = -21.68 GF+22.62Openness-0.47LAI-0.81 ClumpFact-798.89DSF-48.90ISF+ 826.07TSF-218.08PPFDDirU+19.22PPFDDifU+201.94 PPFDTU
		λ₂ = 0.64406
		λ₃ = 0.493505
		λ₄= 0.432535
结构因子 Structure variables	空间因子(PCNM)	λ₁ = 0.9998	V₁= 2.1582 DBH+0.5098 Height-1.4834 BRHH-0.2816 BA+1.585 DEN+0.0917 biomass+0.1322 volume W₁ = 0.449 PCNM1+1.525 PCNM3 +0.627 PCNM4+2.632 PCNM5-1.531 PCNM7+0.093 PCNM8+1.344 PCNM9+1.497 PCNM10+0.152 PCNM11 +0.345 PCNM12-0.121 PCNM13-1.254 PCNM14+0.988 PCNM15-1.764 PCNM18+2.150 PCNM19+0.318 PCNM21-0.253 PCNM22 +1.199 PCNM24+3.262 PCNM25
		λ₂= 0.992
		λ₃ = 0.954633
		λ₄ = 0.940490
光因子 Light variables	空间因子(PCNM)	λ₁ = 0.999	V₁ = 25.551GF-27.189Openness-0.591LAI-0.222ClumpFac+1213.001DSF+34.911ISF -698.782TSF-756.670PPFDDirU-19.734 PPFDDifU+238.120 PPFDTU W₁ = 0.1105 PCNM2+0.1245 PCNM3+0.3092 PCNM5+0.3640 PCNM6+0.2677 PCNM7+0.2772 PCNM8+0.2036 PCNM9+0.3604 PCNM10+0.2052 PCNM13-0.0062 PCNM14+0.0635 PCNM17+0.2569 PCNM19+0.1649 PCNM21+0.6269 PCNM23+0.1094 PCNM25
		λ₂ = 0.998333
		λ₃ = 0.968076
		λ₄ = 0.897069