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Sommerfeltia 32 Innmat 20081031 Fargeredigert.Indd SOMMERFELTIA 32 (2008) 3 Liu, H.Y., Økland, T., Halvorsen, R., Gao, J.X., Liu, Q.R., Eilertsen, O. & Bratli, H. 2008. Gradients analyses of forests ground vegetation and its relationships to environmental variables in five subtropical forest areas, S and SW China. – Sommerfeltia 32: 1 – 196. Oslo. ISBN 82-7420-046-2. ISSN 0800- 6865. Monitoring of ground vegetation and environmental variables in subtropical forests in China was initiated in 1999 as part of the “Integrated Monitoring Programme of Acidification of Chinese Ter- restrial Systems”. The study areas were selected to span regional gradients, in deposition of airborne pollutants and climatic conditions. All five study areas are located in the southern and south-western parts of China and consist of subtropical forests. In each study area 50 1-m2 plots were randomly chosen within each of ten 10×10 m macro plots, each in turn positioned in the centre of 30×30 m extended macro plot. All 250 1-m2 plots were subjected to vegetation analysis, using frequency in subplots as measure of species abundance. A total of 33 environmental variables were recorded for 1-m2 plots as well as 10×10 m macro plots. A major objective of this study is to identify the environ- mental variables that are most strongly related to the species composition of ground vegetation in S and SW Chinese subtropical forests, as a basis for future monitoring. Comparison among DCA, LNMDS and GNMDS ordination methods, an additional objective of the study, was achieved by using a set of different techniques: calculation of pair-wise correlation coefficients between corresponding ordination axes, Procrustes comparison, assessment of outlier influence, and split-plot GLM analysis between environmental variables and ordination axes. LNMDS and GNMDS consistently produce very similar ordinations. GNMDS ordinations are generally more similar to DCA than LNMDS to DCA. In most cases DCA, LNMDS and GNMDS extract the same main ground vegetation compositional gradients and the choice of LNMDS or GNMDS is therefore hardly decisive for the results. GNMDS was chosen for interpretation and presentation of vegetation- environment relationships. The dimensionality of GNMDS (number of reliable axes) was decided by demanding high correspondence of all axes with DCA and LNMDS axes. Three dimensions were needed to describe the variation in vegetation in two of the areas (TSP and LXH), two dimensions in the other three areas (LCG, LGS and CJT). Environmental interpretation of ordinations (identification of ecoclines; gradients in species composition and the environment) was made by split-plot GLM analysis and non-parametric cor- relation analysis. Plexus diagrams and PCA ordination were used to visualize correlations between environmental variables. Several graphical means were used to aid interpretation. Complex gradients in litter-layer depth, topography, soil pH/soil nutrient, and tree density/crown cover were found to be most strongly related to vegetation gradients. However, the five study areas differed somewhat with respect to which of the environmental variables that were most strongly related to the vegetation gradients (ordination axes). Litter-layer depth was related to vegetation gradients in four areas (TSP, LCG, CJT and LXH); topography in four study areas (TSP, LGS, CJT and LXH); soil pH in three areas (LCG, LGS and CJT); soil nutrients in one area (LGS); and tree density/crown cover in one area (LCG). The ecological processes involved in relationships between vegetation and main complex-gradi- ents in litter-layer depth, topography, soil pH/soil nutrient, and tree density/crown cover, in subtropical forests, are discussed. We find that gradient relationships of subtropical forests are complex, and that heavy pollution may increase this complexity. Furthermore, our results suggest that better knowledge of vegetation-environment relationships has potential for enhancing our understanding of subtropical forests that occupy vast areas of the S and SW China. Keywords: China, DCA, Environmental variables, Gradient, GNMDS, LNMDS, Monitoring, Ordina- tion, Subtropical forests, Ground vegetation. Hai-Ying Liu, Department of Botany, Natural History Museum, University of Oslo, P.O. Box 1172 Blindern, N-0318 Oslo, Norway and Institute of Ecology, Chinese Research Academy of Environ- mental Science, Beiyuan, Anwai, 100012, Beijing, P.R. China; Tonje Økland, Norwegian Forest and Landscape Institute, P.O. Box 115, N-1431, Ås, Norway; Rune Halvorsen, Department of Botany, Natural History Museum, University of Oslo, P.O. Box 1172 Blindern, N-0318 Oslo, Norway; Ji-Xi Gao, Institute of Ecology, Chinese Research Academy of Environmental Science, Beiyuan, Anwai, 100012, Beijing, P.R. China; Quan-Ru Liu, College of Life Science, Beijing Normal University, No 19, Xinjiekouwai Avenue, 100875, Beijing, P.R. China; Harald Bratli, Norwegian Forest and Landscape Institute, P.O. Box 115, N-1431, Ås, Norway;and Odd Eilertsen, Norwegian Forest and Landscape Institute, P.O. Box 115, N-1431, Ås, Norway and Institute of Ecology, Chinese Research Academy of Environmental Science, Beiyuan, Anwai, 100012, Beijing, P.R. China. Current address: Hai-Ying Liu Norweigan Institute for Air Research P.O.Box 100, NO-2027 Kjeller, Norway Phone: +47 63898040 E-mail: [email protected] SOMMERFELTIA 32 (2008) 9 INTRODUCTION The rapid economic growth in China has been accompanied by a corresponding increase in pollu- tion. During the last decades Chinese energy consumption increased more than 5% annually (Byrne et al. 1996, World Bank 1999). Coal accounts for about 75% of the commercial energy production and it is likely that coal will be the major energy carrier in the coming decades (Seip et al. 1999). Acid rain was recognized as a potential environmental problem in China in the late 1970s and early 1980s (Zhao & Sun 1986, Zhao et al. 1988, Wang et al. 1997), but it was not until mid 1990s Chinese research projects provided relevant information needed for implementing adequate control measures. There are still big gaps in the scientific knowledge of air pollution effects in China, particularly re- garding quantification of effects. In order to provide a sound scientific basis for cost-effective control measures to reduce emissions of acidifying substances, China found it beneficial to exploit foreign experience, methodologies and “State of the art” equipment through cooperation with bilateral and multilateral development agencies. One of this activities was the Sino-Norwegian project IMPACTS (The Integrated Monitoring Program on Acidification of Chinese Terrestrial System), launched in 1999 and running for five-year (Larssen et al. 2006). It included five forest monitoring areas that receive significant amounts of long-distance airborne acidifying compounds. Motivated by the sensitivity of ground vegetation to acid rain (Falkengren-Grerup 1986, Nieppola 1992, R. Økland 1995a, R. Økland & Eilertsen 1996, T. Økland et al. 2004) and the high conservation value of ground vegetation in Chi- nese subtropical forests, a ground vegetation module was included in the IMPACTS project together with monitoring of the quality of air, precipitation, soil water, surface water, and forests health. These forests represent species-rich ecosystems with many important species (endemic species, key stone species, threatened species, etc.), and the forests are also important as resource (biodiversity, food, building material, etc.) for individual residents and thus for local and national economy (Tang et al. 2004). Ground vegetation monitoring in the IMPACTS project is based upon the basic principles of monitoring developed for use in Norway, highlighting detailed studies of ground vegetation and environmental conditions in permanent plots, in ways that facilitate statistical analyses (R. Økland & Eilertsen 1993, T. Økland 1996, Lawesson et al. 2000). Five monitoring areas were selected to span local environmental gradients and regional gradients in air pollution, while other human influences were as far as possible kept at a low level. Acidification pollution has been and continues to be of major concern for management of the region (Tang et al. 2004). In order to control acidification and to better manage the ecosystems of subtropical forests, a better knowledge of relationships between environmental variables and species composition in the region is needed. The species composition in an area is known to vary along with differences in environmental conditions (Gleason 1926, Whittaker 1967). A gradual change in environmental conditions will most often produce a gradual shift in species composition. The identification of major coenoclines (gra- dients in species composition; Whittaker 1967) and the complex-gradients responsible for them are fundamental tasks of vegetation ecological research (R. Økland & Eilertsen 1993, Antoine & Niklaus 2000). For more than a century, ecologists have attempted to determine the factors that control plant species distribution and variation in vegetation composition (Glenn et al. 2002). The importance of climate for plant distributions was recognized already in the early 19th century (Humboldt & Bonpland 1807). Later, climate in combination with other environmental factors has been used to explain vegetation patterns around the world (Stott 1981, Woodward 1987, Cook & Irwin 1992). To explain relationships between species composition (variation in species abundances) and the environ- ment on finer scales, large sets of corresponding vegetation and soil data sets (i.e. data recorded
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