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      Pathways of Leymus chinensis Individual Aboveground Biomass Decline in Natural Semiarid Grassland Induced by Overgrazing: A Study at the Plant Functional Trait Scale

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          Abstract

          Natural grassland productivity, which is based on an individual plant’s aboveground biomass (AB) and its interaction with herbivores, can obviously affect terrestrial ecosystem services and the grassland’s agricultural production. As plant traits have been linked to both AB and ecosystem success, they may provide a useful approach to understand the changes in individual plants and grassland productivity in response to grazing on a generic level. Unfortunately, the current lack of studies on how plant traits affect AB affected by herbivores leaves a major gap in our understanding of the mechanism of grassland productivity decline. This study, therefore, aims to analyze the paths of overgrazing-induced decline in the individual AB of Leymus chinensis (the dominant species of meadow-steppe grassland in northern China) on a plant functional trait scale. Using a paired-sampling approach, we compared the differences in the functional traits of L. chinensis in long-term grazing-excluded and experimental grazing grassland plots over a continuous period of approximately 20 years (located in meadow steppe lands in Hailar, Inner Mongolia, China). We found a highly significant decline in the individual height and biomass (leaf, stem, and the whole plant) of L. chinensis as a result of overgrazing. Biomass allocation and leaf mass per unit area were significantly affected by the variation in individual size. Grazing clearly enhanced the sensitivity of the leaf-to-stem biomass ratio in response to variation in individual size. Moreover, using a method of standardized major axis estimation, we found that the biomass in the leaves, stems, and the plant as a whole had highly significant allometric scaling with various functional traits. Also, the slopes of the allometric equations of these relationships were significantly altered by grazing. Therefore, a clear implication of this is that grazing promotes an asymmetrical response of different plant functional traits to variation in individual plant size, which influences biomass indirectly. Furthermore, we detected paths of individual AB decline in L. chinensis induced by grazing by fitting to a structural equation model. These results indicate that grazing causes AB decline primarily through a ‘bottom-up’ effect on plant height and stem traits. However, leaf traits, via the process of allometric scaling, affect plant AB indirectly.

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          Functional and phylogenetic diversity as predictors of biodiversity--ecosystem-function relationships.

          How closely does variability in ecologically important traits reflect evolutionary divergence? The use of phylogenetic diversity (PD) to predict biodiversity effects on ecosystem functioning, and more generally the use of phylogenetic information in community ecology, depends in part on the answer to this question. However, comparisons of the predictive power of phylogenetic diversity and functional diversity (FD) have not been conducted across a range of experiments. To address how phylogenetic diversity and functional trait variation control biodiversity effects on biomass production, we summarized the results of 29 grassland plant experiments where both the phylogeny of plant species used in the experiments is well described and where extensive trait data are available. Functional trait variation was only partially related to phylogenetic distances between species, and the resulting FD values therefore correlate only partially with PD. Despite these differences, FD and PD predicted biodiversity effects across all experiments with similar strength, including in subsets that excluded plots with legumes and that focused on fertilization experiments. Two- and three-trait combinations of the five traits used here (leaf nitrogen percentage, height, specific root length, leaf mass per unit area, and nitrogen fixation) resulted in the FD values with the greatest predictive power. Both PD and FD can be valuable predictors of the effect of biodiversity on ecosystem functioning, which suggests that a focus on both community trait diversity and evolutionary history can improve understanding of the consequences of biodiversity loss.
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            Plant diversity and productivity experiments in european grasslands

            At eight European field sites, the impact of loss of plant diversity on primary productivity was simulated by synthesizing grassland communities with different numbers of plant species. Results differed in detail at each location, but there was an overall log-linear reduction of average aboveground biomass with loss of species. For a given number of species, communities with fewer functional groups were less productive. These diversity effects occurred along with differences associated with species composition and geographic location. Niche complementarity and positive species interactions appear to play a role in generating diversity-productivity relationships within sites in addition to sampling from the species pool.
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              Functional traits explain phytoplankton community structure and seasonal dynamics in a marine ecosystem.

              A fundamental yet elusive goal of ecology is to predict the structure of communities from the environmental conditions they experience. Trait-based approaches to terrestrial plant communities have shown that functional traits can help reveal the mechanisms underlying community assembly, but such approaches have not been tested on the microbes that dominate ecosystem processes in the ocean. Here, we test whether functional traits can explain community responses to seasonal environmental fluctuation, using a time series of the phytoplankton of the English Channel. We show that interspecific variation in response to major limiting resources, light and nitrate, can be well-predicted by lab-measured traits characterising light utilisation, nitrate utilisation and maximum growth rate. As these relationships were predicted a priori, using independently measured traits, our results show that functional traits provide a strong mechanistic foundation for understanding the structure and dynamics of ecological communities. © 2012 Blackwell Publishing Ltd/CNRS.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                5 May 2015
                2015
                : 10
                : 5
                : e0124443
                Affiliations
                [1 ]Institute of Grassland Research, Chinese Academy of Agricultural Sciences, Ministry of Agriculture Key Laboratory of Grassland Resources and Utilization, Hohhot, China
                [2 ]Graduate School of Chinese Academy of Agricultural Sciences, Beijing, China
                [3 ]Experimental Center of Desert Forestry, China Academy of Forestry, Dengkou, China
                Henan Agricultural University, CHINA
                Author notes

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

                Conceived and designed the experiments: XLL ZL ZW XW JH XH. Performed the experiments: XLL ZW HS YZ FG. Analyzed the data: XLL ZL YZ XH XEL. Contributed reagents/materials/analysis tools: XLL ZL. Wrote the paper: XLL ZL XH.

                Article
                PONE-D-15-00211
                10.1371/journal.pone.0124443
                4420280
                25942588
                4ea63912-bd32-4be7-8019-aa607c5725fc
                Copyright @ 2015

                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

                History
                : 12 January 2015
                : 14 March 2015
                Page count
                Figures: 8, Tables: 4, Pages: 17
                Funding
                This study was financially supported by the National Key Basic Research Development Program of China (2014CB138800), the International Science and Technology Cooperation Project of China (2012DFA31290), Central Non-profit Research Institutes Fundamental Research Funds of China (1610332015020) and Natural Science Foundation of Inner Mongolia Autonomous Region of china (2014BS0328). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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