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      Species-Specific Effects on Throughfall Kinetic Energy in Subtropical Forest Plantations Are Related to Leaf Traits and Tree Architecture

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          Soil erosion is a key threat to many ecosystems, especially in subtropical China where high erosion rates occur. While the mechanisms that induce soil erosion on agricultural land are well understood, soil erosion processes in forests have rarely been studied. Throughfall kinetic energy (TKE) is influenced in manifold ways and often determined by the tree’s leaf and architectural traits. We investigated the role of species identity in mono-specific stands on TKE by asking to what extent TKE is species-specific and which leaf and architectural traits account for variation in TKE. We measured TKE of 11 different tree species planted in monocultures in a biodiversity-ecosystem-functioning experiment in subtropical China, using sand-filled splash cups during five natural rainfall events in summer 2013. In addition, 14 leaf and tree architectural traits were measured and linked to TKE. Our results showed that TKE was highly species-specific. Highest TKE was found below Choerospondias axillaris and Sapindus saponaria, while Schima superba showed lowest TKE. These species-specific effects were mediated by leaf habit, leaf area (LA), leaf pinnation, leaf margin, stem diameter at ground level (GD), crown base height (CBH), tree height, number of branches and leaf area index (LAI) as biotic factors and throughfall as abiotic factor. Among these, leaf habit, tree height and LA showed the highest effect sizes on TKE and can be considered as major drivers of TKE. TKE was positively influenced by LA, GD, CBH, tree height, LAI, and throughfall amount while it was negatively influenced by the number of branches. TKE was lower in evergreen, simple leaved and dentate leaved than in deciduous, pinnated or entire leaved species. Our results clearly showed that soil erosion in forest plantations can be mitigated by the appropriate choice of tree species.

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          The advantages of being evergreen.

           Rien Aerts (1995)
          Recent research shows that the dominance of evergreen species in nutrient-poor environments can be explained by their low nutrient loss rates. From this work It appears that the plant traits that are associated with low nutrient loss rates lead to low maximum-dry-matter production and to low rates of litter decomposition. This suggests a positive feedback between the evergreen habit and low nutrient availability. The growth characteristics of evergreens lead to a low responsiveness to environmental changes. As a result, global warming may lead to changes in the distribution of evergreens.
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            Leaf Trait-Environment Relationships in a Subtropical Broadleaved Forest in South-East China

            Although trait analyses have become more important in community ecology, trait-environment correlations have rarely been studied along successional gradients. We asked which environmental variables had the strongest impact on intraspecific and interspecific trait variation in the community and which traits were most responsive to the environment. We established a series of plots in a secondary forest in the Chinese subtropics, stratified by successional stages that were defined by the time elapsed since the last logging activities. On a total of 27 plots all woody plants were recorded and a set of individuals of every species was analysed for leaf traits, resulting in a trait matrix of 26 leaf traits for 122 species. A Fourth Corner Analysis revealed that the mean values of many leaf traits were tightly related to the successional gradient. Most shifts in traits followed the leaf economics spectrum with decreasing specific leaf area and leaf nutrient contents with successional time. Beside succession, few additional environmental variables resulted in significant trait relationships, such as soil moisture and soil C and N content as well as topographical variables. Not all traits were related to the leaf economics spectrum, and thus, to the successional gradient, such as stomata size and density. By comparing different permutation models in the Fourth Corner Analysis, we found that the trait-environment link was based more on the association of species with the environment than of the communities with species traits. The strong species-environment association was brought about by a clear gradient in species composition along the succession series, while communities were not well differentiated in mean trait composition. In contrast, intraspecific trait variation did not show close environmental relationships. The study confirmed the role of environmental trait filtering in subtropical forests, with traits associated with the leaf economics spectrum being the most responsive ones.
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              China's forest policy for the 21st century.

              A half-century policy of forest exploitation and monoculture in China has led to disastrous consequences, including degradation of forests and landscapes, loss of biodiversity, unacceptable levels of soil erosion, and catastrophic flooding. A new forest policy had been adopted in China called the Natural Forest conservation Program (NFCP), which emphasizes expansion of natural forests and increasing the productivity of forest plantations. Through locally focused management strategies, biodiversity and forest resources will be sustained, and downstream regions will be better protected from flooding. This new policy is being implemented with a new combination of policy tools, including technical training and education, land management planning, mandatory conversion of marginal farmlands to forest, resettlement and retaining of forest dwellers, share in private ownership, and expanded research. These policy tools may have wider relevance for other countries, particularly developing countries.

                Author and article information

                Role: Academic Editor
                PLoS One
                PLoS ONE
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                16 June 2015
                : 10
                : 6
                [1 ]University of Tübingen, Department of Geosciences, Institute of Geography, Chair of Soil Science and Geomorphology, Rümelinstraße 19–23, 72070, Tübingen, Germany
                [2 ]Martin-Luther-University Halle Wittenberg, Geobotany, am Kirchtor 1, 06108, Halle, Germany
                [3 ]German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103, Leipzig, Germany
                [4 ]Leuphana University Lüneburg, Faculty of Sustainability, Institute of Ecology, Scharnhorststraße 1, 21335, Lüneburg, Germany
                [5 ]Technische Universität Dresden, Institute of General Ecology and Environmental Protection, Pienner Str. 7, 01737, Tharandt, Germany
                DOE Pacific Northwest National Laboratory, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: PG HB PK GVO TS. Performed the experiments: PG SS WK YL. Analyzed the data: PG HB. Wrote the paper: PG HB WH WK PK YL SS GVO TS.

                ‡ These authors also contributed equally to this work.


                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

                Page count
                Figures: 2, Tables: 2, Pages: 13
                The authors gratefully acknowledge funding by the German Research Foundation, (DFG FOR 891/1 and 2). Travel grants and summer schools were granted through the Sino-German Centre for Research Promotion in Beijing, (GZ 524,592,698,699 and 785). Support was also received from the Open Access Publishing Fund of the University of Tübingen.
                Research Article
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                All relevant data are from the BEF-China experiment and may be found at the BEF-China data portal, (URL: http://china.befdata.biow.uni-leipzig.de/) or upon request from the author.



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