The tree species composition can influence the dynamics of herbaceous species and enhance the spatial heterogeneity of the soil. But there is very little evidence on how both overstorey structure and soil properties affect the spatial variation of the herb layer. The aim of this study is to evaluate the factors of the soil and overstorey structure by which it is possible to explain the fine-scale variation of herbaceous layer communities in an Eastern European poplar-willow forest. The research was conducted in the “Dnipro-Orils’kiy” Nature Reserve (Ukraine). The research polygon (48°30′51″N, 34°49″02″E) was laid in an Eastern European poplar-willow forest in the floodplain of the River Protich, which is a left inflow of the River Dnipro. The site consists of 7 transects. Each transect was made up of 15 test points. The distance between rows in the site was 3 m. At the site, we established a plot of 45×21 m, with 105 subplots of 3×3 m organized in a regular grid. The adjacent subplots were in close proximity. Vascular plant species lists were recorded at each 3×3 m subplot along with visual estimates of species cover using the nine-degree Braun-Blanquet scale. Within the plot, all woody stems ≥ 1 cm in diameter at breast height were measured and mapped. Dixon’s segregation index was calculated for tree species to quantify their relative spatial mixing. Based on geobotanical descriptions, a phytoindicative assessment of environmental factors according to the Didukh scale was made. The redundancy analysis was used for the analysis of variance in the herbaceous layer species composition. The geographic coordinates of sampling locations were used to generate a set of orthogonal eigenvector-based spatial variables. Two measurements of the overstorey spatial structure were applied: the distances from the nearest tree of each species and the distance based on the evaluation of spatial density of point objects, which are separate trees. In both cases, the distance matrix of sampling locations was calculated, which provided the opportunity to generate eigenvector-based spatial variables. A kernel smoothed intensity function was used to compute the density of the trees’ spatial distribution from the point patterns’ data. Gaussian kernel functions with various bandwidths were used. The coordinates of sampling locations in the space obtained after the conversion of the trees’ spatial distribution densities were used to generate a set of orthogonal eigenvector-based spatial variables, each of them representing a pattern of particular scale within the extent of the bandwidth area structured according to distance and reciprocal placement of the trees. An overall test of random labelling reveals the total nonrandom distribution of the tree stems within the site. The unexplained variation consists of 43.8%. The variation explained solely by soil variables is equal to 15.5%, while the variation explained both by spatial and soil variables is 18.0%. The measure of the overstorey spatial structure, which is based on the evaluation of its density enables us to obtain different estimations depending on the bandwidth. The bandwidth affects the explanatory capacity of the tree stand. A considerable part of the plant community variation explained by soil factors was spatially structured. The orthogonal eigenvector-based spatial variables (dbMEMs) approach can be extended to quantifying the effect of forest structures on the herbaceous layer community. The measure of the overstorey spatial structure, which is based on the evaluation of its density, was very useful in explaining herbaceous layer community variation.
If the inline PDF is not rendering correctly, you can download the PDF file here.
Aiba, M., Takafumi, H. & Hiura T. (2012). Interspecific differences in determinants of plant species distribution and the relationships with functional traits. J. Ecol., 100. 950−957. DOI: 10.1111/j.1365-2745.2012.01959.x.
Aitchison, J. (1986). The statistical analysis of compositional data. London: Chapman and Hall.
Aitchison, J. & Greenacre M. (2002). Biplots of Compositional Data. Journal of the Royal Statistical Society: Series C (Applied Statistics), 51, 375–392. DOI: 10.1111/1467-9876.00275.
Andivia, E., Fernández, M., Alejano, R. & Vázquez-Piqué J. (2015). Tree patch distribution drives spatial heterogeneity of soil traits in cork oak woodlands. Ann. For. Sci., 72, 549–559. DOI: 10.1007/s13595-015-0475-8.
Angers, D.A. & Caron J. (1998). Plant-induced Changes in Soil Structure: Processes and Feedbacks. Biogeochemistry, 42(1–2), 55–72. DOI: 10.1023/A:1005944025343.
Baddeley, A. & Turner R. (2005). Spatstat: an R package for analyzing spatial point patterns. Journal of Statistical Software, 12, 1–42. DOI: 10.18637/jss.v012.i06.
Barthes, B. & Roose E. (2002). Aggregate stability as an indicator of soil susceptibility to runoff and erosion; validation at several levels. Catena, 47(2), 133–149. DOI: 10.1016/S0341-8162(01)00180-1.
Binkley, D. & Giardina C. (1998). Why do tree species affect soils? The warp and woof of tree-soil interactions. Biogeochemistry, 42(1–2), 89–106. DOI: 10.1023/A:1005948126251.
Blanchet, F.G., Legendre, P. & Borcard D. (2008). Forward selection of explanatory variables. Ecology, 89(9), 2623–2632. DOI: 10.1890/07-0986.1.
Blank, L. & Carmel Y. (2012). Woody vegetation patch type determines herbaceous species richness and composition in Mediterranean ecosystem. Community Ecol., 13, 72–81. DOI: 10.1556/ComEc.13.2012.1.9.
Borcard, D. & Legendre P. (2002). All-scale spatial analysis of ecological data by means of principal coordinates of neighbour matrices. Ecol. Model., 153, 51–68. DOI: 10.1016/S0304-3800(01)00501-4.
Bratton, S. (1976). Resource division in an understory herb community: responses to temporal and microtopographic gradients. Am. Nat., 110(974), 679–693. www.jstor.org/stable/2459584.
Breshears, D., Rich, P., Barnes, F. & Campbell K. (1997). Overstorey-imposed heterogeneity in solar radiation and soil moisture in a semiarid woodland. Ecol. Appl., 7(4), 1201–1215. DOI: 10.2307/2641208.
Buzuk, G.N. (2017). Phytoindication with ecological scales and regression analysis: environmental index. Bulletin of Pharmacy, 2 (76), 31–37.
Canton, Y., Sole-Benet, A., Asensio, C., Chamizo, S. & Puigdefabregas J. (2009). Aggregate stability in range sandy loam soils Relationships with runoff and erosion. Catena, 77, 192–199. DOI: 10.1016/j.catena.2008.12.011.
Chang, L.-W., Zelený, D., Li, C.-F., Chiu, S.-T. & Hsieh C.-F. (2013). Better environmental data may reverse conclusions about niche-and dispersal-based processes in community assembly. Ecology, 94, 2145–2151. DOI: 10.1890/12-2053.1.
Chase, J.M. (2014). Spatial scale resolves the niche versus neutral theory debate. J. Veg. Sci., 25, 319–322. DOI: 10.1111/jvs.12159.
Chudomelová, M., Zelený, D. & Li Ch.-F. (2017). Contrasting patterns of fine-scale herb layer species composition in temperate forests. Acta Oecol., 80, 24–31. DOI: 10.1016/j.actao.2017.02.003.
Cottenie, K. (2005). Integrating environmental and spatial processes in ecological community dynamics. Ecol. Lett., 8, 1175–1182. DOI: 10.1111/j.1461-0248.2005.00820.x.
Dallas, T. & Drake J.M. (2014). Relative importance of environmental, geographic, and spatial variables on zooplankton metacommunities. Ecosphere, 5(9), 104. DOI: 10.1890/ES14-00071.1.
De la Cruz, M. (2008). Metodos para analizar datos puntuales. In F.T. Maestre, A. Escudero & A. Bonet (Eds.), Introduccion al Analisis Espacial de Datos en Ecologia y Ciencias Ambientales: Metodos y Aplicaciones (pp. 76−127). Madrid: Asociacion Espanola de Ecologia Terrestre, Universidad Rey Juan Carlos y Caja de Ahorros del Mediterraneo.
Didukh, Ya.P. (2011). The ecological scales for the species of Ukrainian flora and their use in synphytoindication. Kyiv: Phytosociocentre.
Dray, S., Bauman, D., Blanchet, G., Borcard, D., Clappe, S., Guenard, G., Jombart, T., Larocque, G., Legendre, P., Madi, N. & Wagner H.H. (2018). adespatial: Multivariate multiscale spatial analysis. R package version 0.3-2. https://CRAN.R-project.org/package=adespatial.
Egozcue, J.J., Pawlowsky–Glahn, V., Mateu–Figueras, G. & Barcel’o–Vidal C. (2003). Isometric logratio transformations for compositional data analysis. Mathematical Geology, 35(3), 279–300. DOI: 10.1023/A:1023818214614.
Elliott, K.J., Vose, J.M., Knoepp, L.D., Clinton, B.D. & Kloeppel B.D. (2015). Functional role of the herbaceous layer in eastern deciduous forest ecosystems. Ecosystems, 18(2), 221–236. DOI: 10.1007/s10021-014-9825-x.
Fekete, I., Varga, C., Biró, B., Tóth, J.A., Várbíró, G., Lajtha, K., Szabó, S. & Kotroczó Z. (2016). The effects of litter production and litter depth on soil microclimate in a Central European deciduous forest. Plant Soil, 398 (1–2), 291–300. DOI: 10.1007/s11104-015-2664-5.
Fortin, M.-J. & Dale M. (2005). Spatial analysis: Guide for ecologists. Cambridge: Cambridge University Press. Frelich, L.E., Machado, J.L. & Reich P.B. (2003). Fine scale environmental variation and structure of understorey plant communities in two old growth pine forests. J. Ecol., 91, 283–293. DOI: 10.1046/j.1365-2745.2003.00765.x.
Gazol, A. & Ibanez R. (2010). Plant species composition in a temperate forest: Multi-scale patterns and determinants. Acta Oecol., 36, 634–644. DOI: 10.1016/j.actao.2010.09.009.
Gilbert, B. & Lechowicz M.J. (2004). Neutrality, niches, and dispersal in a temperate forest understory. Proc. Nat. Acad. Sci. USA, 101(20), 7651–7656. DOI: 10.1073/pnas.0400814101.
Gilliam, F.S., Turrill, N.L. & Adams M.B. (1995). Herbaceous-layer and overstorey species in clear-cut and mature central Appalachian hardwood forests. Ecol. Appl., 5, 947–955. DOI: 10.2307/2269345.
Gilliam, F.S. (2007). The ecological significance of the herbaceous layer in temperate forest ecosystems. Bioscience, 57, 845–858. DOI: 10.1641/B571007.
Griffith, D.A. (1992). What is spatial autocorrelation? Reflections on the past 25 years of spatial statistics. L’Espace Géographique, 21, 265–280.
Hurlbert, S.H. (1984). Pseudoreplication and the design of ecological field experiments. Ecol. Monogr., 54(2), 187–211. DOI: 10.2307/1942661.
Jones, C.G., Lawton, J.H. & Shachak M. (1994). Organisms as ecosystem engineers. Oikos, 69, 373–386. DOI: 10.2307/3545850.
Jones, M.M., Tuomisto, H., Clark, D.B. & Olivas P. (2006). Effects of mesoscale environmental heterogeneity and dispersal limitation on floristic variation in rainforest ferns. J. Ecol., 94, 181–195. DOI: 10.1111/j.1365-2745.2005.01071.x.
Jones, M.M., Tuomisto, H., Borcard, D., Legendre, P., Clark, D.B. & Olivas P.C. (2008). Explaining variation in tropical plant community composition: influence of environmental and spatial data quality. Oecologia, 155, 593–604. DOI: 10.1007/s00442-007-0923-8.
Karst, J., Gilbert, B. & Lechowicz M.J. (2005). Fern community assembly: the roles of chance and the environment at local and intermediate scales. Ecology, 86, 2473–2486. DOI: 10.1890/04-1420.
King, A.W. & With K.A. (2002). Dispersal success on spatially structured landscapes: when do spatial pattern and dispersal behavior really matter? Ecol. Model., 147(1), 23−39. DOI: 10.1016/S0304-3800(01)00400-8.
Laliberte, A.S., Rango, A., Herrick, J.E., Fredrickson, E.L. & Burkett L. (2009). An object–based image analysis approach for determining fractional cover of senescent and green vegetation with digital plot photography. J. Arid Environ., 69, 1–14. DOI: 10.1016/j.jaridenv.2006.08.016.
Legendre, P. & Fortin M.J. (1989). Spatial pattern and ecological analysis. Vegetatio, 80(2), 107–138. DOI: 10.1007/BF00048036.
Legendre, P. (1993). Spatial autocorrelation: trouble or new paradigm? Ecology, 74, 1659–1673. DOI: 10.2307/1939924.
Legendre, P. & Gallagher E.D. (2001). Ecologically meaningful transformations for ordination of species. Oecologia, 129(2), 271–280. DOI: 10.1007/s004420100716.
Legendre, P., Mi, X., Ren, H., Ma, K., Yu, M., Sun, I.–F. & He F. (2009). Partitioning beta diversity in a subtropical broadleaved forest of China. Ecology, 90, 663–674. DOI: 10.1890/07-1880.1.
Legendre, P. & Legendre L. (2012.) Numerical ecology. Amsterdam: Elsevier Science.
Legendre, P. & Gauthier O. (2014). Statistical methods for temporal and space-time analysis of community composition data. Proc. R. Soc. B, 281(1778), 20132728. DOI: 10.1098/rspb.2013.2728.
Lennon, J.J. (2000). Red-shifts and red herrings in geographical ecology. Ecography, 23, 101−113. DOI: 10.1111/j.1600-0587.2000.tb00265.x.
Levin, D.A. & Wilson A.C. (1976). Rates of evolution in seed plants: Net increase in diversity of chromosome numbers and species numbers through time. Proc. Nat. Acad. Sci., 73(6), 2086–2090. DOI: 10.1073/pnas.73.6.2086.
Lososová, Z., Šmarda, P., Chytrý, M., Purschke, O., Pyšek, P., Sádlo, J., Tichý, L. & Winter M. (2015). Phylogenetic structure of plant species pools reflects habitat age on the geological time scale. J. Veg. Sci., 26, 1080–1089. DOI: 10.1111/jvs.12308.
Lyon, J. & Sharpe W.E. (2003). Impacts of hay-scented fern on nutrition of northern red oak seedlings. J. Plant Nutr., 26(3), 487–502. DOI: 10.1081/PLN-120017661.
MacKinney, A.L. (1929). Effects of forest litter on soil temperature and soil freezing in autumn and winter. Ecology, 10(3), 312–321. DOI: 10.2307/1929507.
Mölder, A., Bernhardt-Römermann, M. & Schmidt W. (2008). Herb-layer diversity in deciduous forests: raised by tree richness or beaten by beech? For. Ecol. Manag., 256(3), 272–281. DOI: 10.1016/j.foreco.2008.04.012.
Nettesheim, F.C., Garbin, M.L., Rajão, P.H.M., Araujo, D.S.D. & Grelle C.E.V. (2018). Environment is more relevant than spatial structure as a driver of regional variation in tropical tree community richness and composition. Plant Ecology & Diversity, DOI: 10.1080/17550874.2018.1473520.
Oijen, D., Feijen, M., Hommel, P., Ouden, J. & Waal R. (2005). Effects of tree species composition on within-forest distribution of understorey species. Appl. Veg. Sci., 8(2), 155–166. DOI: 10.1111/j.1654-109X.2005.tb00641.x.
Oksanen, J., Blanchet, F.G., Kindt, R., Legendre, P., Minchin, P.R., O’Hara, R.B., Simpson, G.L., Solymos, P., Stevens, M.H.H. & Wagner H. (2018). Community ecology package. R package version 2.5-2. https://CRAN.R-project.org/package=vegan
Paluch, J.G. & Gruba P. (2012). Effect of local species composition on topsoil properties in mixed stands with silver fir (Abies alba Mill.). Forestry: An International Journal of Forest Research, 85(3), 413–426. DOI: 10.1093/forestry/cps040.
Parent, L., de Almeida, C., Hernandes, A., Egozcue, J.J., Gülser, C., Bolinder, M.A., Kätterer, T., Andrén, O., Parent, S.E., Anctil, F., Centurion, J.F. & Natale W. (2012). Compositional analysis for an unbiased measure of soil aggregation. Geoderma, 179–180, 123–131. DOI: 10.1016/j.geoderma.2012.02.022.
Pennisi, B.V. & van Iersel M. (2002). Three ways to measure medium EC. GMPro, 22(1), 46–48.
Rao, C.R. (1964). The use and interpretation of principal component analysis in applied research. Sankhyā: The Indian Journal of Statistics, Series A, 26, 329–358. https://www.jstor.org/stable/25049339
Siefert, A., Ravenscroft, C., Althoff, D., Alvarez-Y Epiz, J.C., Carter, B.E., Glennon, K.L., Heberling, J.M., Jo, I.S., Pontes, A., Sauer, A., Willis, A. & Fridley J.D. (2012). Scale dependence of vegetation-environment relationships: a meta-analysis of multivariate data. J. Veg. Sci., 23, 942–951. DOI: 10.1111/j.1654-1103.2012.01401.x.
Silvertown, J., McConway, K., Gowing, D., Dodd, M., Fay, M.F., Joseph, J.A. & Dolphin K. (2006). Absence of phylogenetic signal in the niche structure of meadow plant communities. Proc. R. Soc. B, 273, 39–44. DOI: 10.1098/rspb.2005.3288.
Smith, T.W. & Lundholm J.T. (2010). Variation partitioning as a tool to distinguish between niche and neutral processes. Ecography, 33, 648–655. DOI: 10.1111/j.1600-0587.2009.06105.x.
Standovár, T., Ódor, P., Aszalós, R. & Gálhidy L. (2006). Sensitivity of ground layer vegetation diversity descriptors in indicating forest naturalness. Community Ecol., 7(2), 199–209. DOI: 10.1556/ComEc.7.2006.2.7.
Stohlgren, T.J., Owen, A.J. & Lee M. (2000). Monitoring shifts in plant diversity in response to climate change: a method for landscapes. Biodivers. Conserv., 9(1), 65–86. DOI: 10.1023/A:1008995726486.
Teng, S.N., Xu, C., Sandel, B. & Svenning J-C. (2018). Effects of intrinsic sources of spatial autocorrelation on spatial regression modelling. Methods in Ecology and Evolution, 9, 363–372. DOI: 10.1111/2041-210X.12866.
Tobler, W. (1970). A computer movie simulating urban growth in the Detroit region. Economic Geography, 46(1), 234–240. DOI: 10.2307/143141.
Vadunina, A.F. & Korchagin S.A. (1986). Methods for research of physical properties of the soil. Moscow: Agropromizdat.
von Oheimb, G. & Härdtle W. (2009). Selection harvest in temperate deciduous forest: impact on herb layer richness and composition. Biodivers. Conserv., 18(2), 271–287. DOI: 10.1007/s10531-008-9475-4.
Weiher, E., Freund, D., Bunton, T., Stefanski, A., Lee, T. & Bentivenga S. (2011). Advances, challenges and a developing synthesis of ecological community assembly theory. Philos. Trans. R. Soc. Lond. B, 366, 2403–2413. DOI: 10.1098/rstb.2011.0056.
Westhoff, V. & van der Maarel E. (1978). The Braun-Blanquet approach. In R.H. Whittaker (Ed.), Classification of plant communities (pp. 289−399). Hague: W. Junk.
Whigham, D.F. (2004). The ecology of woodland herbs in temperate deciduous forests. Annual Review of Ecology, Evolution, and Systematics, 35, 583–621. DOI: 10.1146/annurev.ecolsys.35.021103.105708.
Xing, Z., Yan, D., Wang, D., Liu, Sh. & Dong G. (2018). Experimental analysis of the effect of forest litter cover on surface soil water dynamics under continuous rainless condition in North China. Kuwait Journal of Science, 45(2), 75–83.
Yoon, T. K., Noh, N. J., Han, S., Lee, J. & Son Y. (2014). Soil moisture effects on leaf litter decomposition and soil carbon dioxide efflux in wetland and upland forests. Soil Sci. Soc. Am. J., 78, 1804–1816. DOI: 10.2136/sssaj2014.03.0094.
Zhukov, A. & Gadorozhnaya G. (2016). Spatial heterogeneity of mechanical impedance of a typical chernozem: the ecological approach. Ekológia (Bratislava), 35, 263–278. DOI: 10.1515/eko-2016-0021.
Zhukov, A.V. & Zadorozhnaya G.A. (2016). Ecomorphes of the sod-lithogenic soils on reddish-brown clays. Issues of Steppe Forestry and Forest Reclamation of Soils, 45, 91–103.
Zhukov, O., Kunah, O., Dubinina, Y. & Novikova V. (2018). The role of edaphic and vegetation factors in structuring beta diversity of the soil macrofauna community of the Dnipro river arena terrace. Ekológia (Bratislava), 37(3), 301–327. DOI: 10.2478/eko-2018-0023.
Zinke, P. (1962). The pattern of influence of individual forest trees on soil properties. Ecology, 43(1), 130–133. DOI: 10.2307/1932049.