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      Phenotypic plasticity vs. local adaptation in quantitative traits differences of Stipa grandis in semi-arid steppe, China

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          Abstract

          Whether plants are able to adapt to environmental changes depends on their genetic characteristics and phenotypic plastic responses. We investigated the phenotypic responses of 7 populations of an important dominant species in semi-arid steppe of China - Stipa grandis, and then distinguished which adaptive mechanism(s), phenotypic plasticity or local adaptation, was/were involved in this species to adapt to environmental changes. (1) All traits were significantly influenced by the interaction of population and growth condition and by population in each condition, and inter-population variability (CV inter) was larger in the field than in the common garden for 8/9 traits, indicating that both phenotypic plasticity and genetic differentiation controlled the phenotypic differences of S. grandis. (2) From a functional standpoint, the significant relationships between the values of traits in the common garden and the environmental variables in their original habitats couldn’t support local habitat adaptation of these traits. (3) Low CV intra, low quantitative differentiation among populations ( Q ST ), and low plasticity shown in the western populations indicated the very low adaptive potential of S. grandis to environmental changes. (4) From the original habitats to the common garden which is far away from S. grandis distribution region, positive phenotypic responses were found in several populations, indicating that some original habitats have become unfavorable for S. grandis.

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          Climate change, adaptation, and phenotypic plasticity: the problem and the evidence

          Many studies have recorded phenotypic changes in natural populations and attributed them to climate change. However, controversy and uncertainty has arisen around three levels of inference in such studies. First, it has proven difficult to conclusively distinguish whether phenotypic changes are genetically based or the result of phenotypic plasticity. Second, whether or not the change is adaptive is usually assumed rather than tested. Third, inferences that climate change is the specific causal agent have rarely involved the testing – and exclusion – of other potential drivers. We here review the various ways in which the above inferences have been attempted, and evaluate the strength of support that each approach can provide. This methodological assessment sets the stage for 11 accompanying review articles that attempt comprehensive syntheses of what is currently known – and not known – about responses to climate change in a variety of taxa and in theory. Summarizing and relying on the results of these reviews, we arrive at the conclusion that evidence for genetic adaptation to climate change has been found in some systems, but is still relatively scarce. Most importantly, it is clear that more studies are needed – and these must employ better inferential methods – before general conclusions can be drawn. Overall, we hope that the present paper and special issue provide inspiration for future research and guidelines on best practices for its execution.
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            Rapid shifts in plant distribution with recent climate change.

            A change in climate would be expected to shift plant distribution as species expand in newly favorable areas and decline in increasingly hostile locations. We compared surveys of plant cover that were made in 1977 and 2006-2007 along a 2,314-m elevation gradient in Southern California's Santa Rosa Mountains. Southern California's climate warmed at the surface, the precipitation variability increased, and the amount of snow decreased during the 30-year period preceding the second survey. We found that the average elevation of the dominant plant species rose by approximately 65 m between the surveys. This shift cannot be attributed to changes in air pollution or fire frequency and appears to be a consequence of changes in regional climate.
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              Genetics of climate change adaptation.

              The rapid rate of current global climate change is having strong effects on many species and, at least in some cases, is driving evolution, particularly when changes in conditions alter patterns of selection. Climate change thus provides an opportunity for the study of the genetic basis of adaptation. Such studies include a variety of observational and experimental approaches, such as sampling across clines, artificial evolution experiments, and resurrection studies. These approaches can be combined with a number of techniques in genetics and genomics, including association and mapping analyses, genome scans, and transcription profiling. Recent research has revealed a number of candidate genes potentially involved in climate change adaptation and has also illustrated that genetic regulatory networks and epigenetic effects may be particularly relevant for evolution driven by climate change. Although genetic and genomic data are rapidly accumulating, we still have much to learn about the genetic architecture of climate change adaptation.
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                Author and article information

                Contributors
                zhaonianxi@nankai.edu.cn
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                16 February 2018
                16 February 2018
                2018
                : 8
                : 3148
                Affiliations
                [1 ]ISNI 0000 0000 9878 7032, GRID grid.216938.7, Department of Plant Biology and Ecology, College of Life Science, , Nankai University, ; Tianjin, 300071 P.R. China
                [2 ]ISNI 0000 0004 1808 3510, GRID grid.412728.a, College of Agronomy & Resources and Environment, , Tianjin Agricultural University, ; Tianjin, 300384 P.R. China
                Author information
                http://orcid.org/0000-0002-0473-6782
                Article
                21557
                10.1038/s41598-018-21557-w
                5816645
                29453378
                e51d2fca-ac70-4323-96d7-0d1c815d0426
                © The Author(s) 2018

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 15 August 2017
                : 6 February 2018
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