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      Idiosyncratic responses of evergreen broad-leaved forest constituents in China to the late Quaternary climate changes

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          Abstract

          Subtropical evergreen broad-leaved forest (EBLF) is one of the most important vegetation types in China. Inferences from palaeo-biome reconstruction (PBR) and phylogeography regarding range shift history of EBLF during the late Quaternary are controversial and should be reconciled. We compared phylogeographic patterns of three EBLF constituents in China, Castanopsis tibetana, Machilus thunbergii and Schima superba. Contrary to a chorus of previous phylogeographic studies and the results of species distribution modelling (SDM) of this study ( in situ survival during the LGM), the three species displayed three different phylogeographic patterns that conform to either an in situ survival model or an expansion-contraction model. These results are partially congruent with the inference of PBR that EBLF was absent to the north of 24° N at the LGM. This study suggests that the constituents of EBLF could have responded idiosyncratically to climate changes during the Late Quaternary. The community assemblages of EBLF could have been changing over time, resulting in no palaeo-analogs to modern-day EBLF, which may be the main reason responsible for the failure of PBR to detect the occurrence of EBLF north of 24° N at the LGM.

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          Most cited references15

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          Niches, models, and climate change: assessing the assumptions and uncertainties.

          As the rate and magnitude of climate change accelerate, understanding the consequences becomes increasingly important. Species distribution models (SDMs) based on current ecological niche constraints are used to project future species distributions. These models contain assumptions that add to the uncertainty in model projections stemming from the structure of the models, the algorithms used to translate niche associations into distributional probabilities, the quality and quantity of data, and mismatches between the scales of modeling and data. We illustrate the application of SDMs using two climate models and two distributional algorithms, together with information on distributional shifts in vegetation types, to project fine-scale future distributions of 60 California landbird species. Most species are projected to decrease in distribution by 2070. Changes in total species richness vary over the state, with large losses of species in some "hotspots" of vulnerability. Differences in distributional shifts among species will change species co-occurrences, creating spatial variation in similarities between current and future assemblages. We use these analyses to consider how assumptions can be addressed and uncertainties reduced. SDMs can provide a useful way to incorporate future conditions into conservation and management practices and decisions, but the uncertainties of model projections must be balanced with the risks of taking the wrong actions or the costs of inaction. Doing this will require that the sources and magnitudes of uncertainty are documented, and that conservationists and resource managers be willing to act despite the uncertainties. The alternative, of ignoring the future, is not an option.
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            Measuring and testing genetic differentiation with ordered versus unordered alleles.

            Estimates and variances of diversity and differentiation measures in subdivided populations are proposed that can be applied to haplotypes (ordered alleles such as DNA sequences, which may contain a record of their own histories). Hence, two measures of differentiation can be compared for a single data set: one (GST) that makes use only of the allelic frequencies and the other (NST) for which similarities between the haplotypes are taken into account in addition. Tests are proposed to compare NST and GST with zero and with each other. The difference between NST and GST can be caused by several factors, including sampling artefacts, unequal effect of mutation rates and phylogeographic structure. The method presented is applied to a published data set where a nuclear DNA sequence had been determined from individuals of a grasshopper distributed in 24 regions of Europe. Additional insights into the genetic subdivision of these populations are obtained by progressively combining related haplotypes and reanalyzing the data each time.
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              A simulated annealing approach to define the genetic structure of populations.

              We present a new approach for defining groups of populations that are geographically homogeneous and maximally differentiated from each other. As a by-product, it also leads to the identification of genetic barriers between these groups. The method is based on a simulated annealing procedure that aims to maximize the proportion of total genetic variance due to differences between groups of populations (spatial analysis of molecular variance; samova). Monte Carlo simulations were used to study the performance of our approach and, for comparison, the behaviour of the Monmonier algorithm, a procedure commonly used to identify zones of sharp genetic changes in a geographical area. Simulations showed that the samova algorithm indeed finds maximally differentiated groups, which do not always correspond to the simulated group structure in the presence of isolation by distance, especially when data from a single locus are available. In this case, the Monmonier algorithm seems slightly better at finding predefined genetic barriers, but can often lead to the definition of groups of populations not differentiated genetically. The samova algorithm was then applied to a set of European roe deer populations examined for their mitochondrial DNA (mtDNA) HVRI diversity. The inferred genetic structure seemed to confirm the hypothesis that some Italian populations were recently reintroduced from a Balkanic stock, as well as the differentiation of groups of populations possibly due to the postglacial recolonization of Europe or the action of a specific barrier to gene flow.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                18 August 2016
                2016
                : 6
                : 31044
                Affiliations
                [1 ]Laboratory of Subtropical Biodiversity, Jiangxi Agricultural University , Nanchang, Jiangxi, 330045, China
                [2 ]Department of Biology, Middle Tennessee State University , Murfreesboro, TN 37132, Tennessee, USA
                [3 ]Department of Biology, University of Florida , Gainesville, FL 17 32611, USA
                [4 ]Florida Museum of Natural History, University of Florida , Gainesville, FL 17 32611, USA
                Author notes
                [*]

                These authors contributed equally to this work.

                Article
                srep31044
                10.1038/srep31044
                4989166
                27534981
                7f5369a9-5695-4be0-9437-437516447308
                Copyright © 2016, The Author(s)

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 06 May 2016
                : 06 July 2016
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