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      Identifying the microbial taxa that consistently respond to soil warming across time and space.

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          Abstract

          Soil microbial communities are the key drivers of many terrestrial biogeochemical processes. However, we currently lack a generalizable understanding of how these soil communities will change in response to predicted increases in global temperatures and which microbial lineages will be most impacted. Here, using high-throughput marker gene sequencing of soils collected from 18 sites throughout North America included in a 100-day laboratory incubation experiment, we identified a core group of abundant and nearly ubiquitous soil microbes that shift in relative abundance with elevated soil temperatures. We then validated and narrowed our list of temperature-sensitive microbes by comparing the results from this laboratory experiment with data compiled from 210 soils representing multiple, independent global field studies sampled across spatial gradients with a wide range in mean annual temperatures. Our results reveal predictable and consistent responses to temperature for a core group of 189 ubiquitous soil bacterial and archaeal taxa, with these taxa exhibiting similar temperature responses across a broad range of soil types. These microbial 'bioindicators' are useful for understanding how soil microbial communities respond to warming and to discriminate between the direct and indirect effects of soil warming on microbial communities. Those taxa that were found to be sensitive to temperature represented a wide range of lineages and the direction of the temperature responses were not predictable from phylogeny alone, indicating that temperature responses are difficult to predict from simply describing soil microbial communities at broad taxonomic or phylogenetic levels of resolution. Together, these results lay the foundation for a more predictive understanding of how soil microbial communities respond to soil warming and how warming may ultimately lead to changes in soil biogeochemical processes.

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          Most cited references34

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          Testing for phylogenetic signal in comparative data: behavioral traits are more labile.

          The primary rationale for the use of phylogenetically based statistical methods is that phylogenetic signal, the tendency for related species to resemble each other, is ubiquitous. Whether this assertion is true for a given trait in a given lineage is an empirical question, but general tools for detecting and quantifying phylogenetic signal are inadequately developed. We present new methods for continuous-valued characters that can be implemented with either phylogenetically independent contrasts or generalized least-squares models. First, a simple randomization procedure allows one to test the null hypothesis of no pattern of similarity among relatives. The test demonstrates correct Type I error rate at a nominal alpha = 0.05 and good power (0.8) for simulated datasets with 20 or more species. Second, we derive a descriptive statistic, K, which allows valid comparisons of the amount of phylogenetic signal across traits and trees. Third, we provide two biologically motivated branch-length transformations, one based on the Ornstein-Uhlenbeck (OU) model of stabilizing selection, the other based on a new model in which character evolution can accelerate or decelerate (ACDC) in rate (e.g., as may occur during or after an adaptive radiation). Maximum likelihood estimation of the OU (d) and ACDC (g) parameters can serve as tests for phylogenetic signal because an estimate of d or g near zero implies that a phylogeny with little hierarchical structure (a star) offers a good fit to the data. Transformations that improve the fit of a tree to comparative data will increase power to detect phylogenetic signal and may also be preferable for further comparative analyses, such as of correlated character evolution. Application of the methods to data from the literature revealed that, for trees with 20 or more species, 92% of traits exhibited significant phylogenetic signal (randomization test), including behavioral and ecological ones that are thought to be relatively evolutionarily malleable (e.g., highly adaptive) and/or subject to relatively strong environmental (nongenetic) effects or high levels of measurement error. Irrespective of sample size, most traits (but not body size, on average) showed less signal than expected given the topology, branch lengths, and a Brownian motion model of evolution (i.e., K was less than one), which may be attributed to adaptation and/or measurement error in the broad sense (including errors in estimates of phenotypes, branch lengths, and topology). Analysis of variance of log K for all 121 traits (from 35 trees) indicated that behavioral traits exhibit lower signal than body size, morphological, life-history, or physiological traits. In addition, physiological traits (corrected for body size) showed less signal than did body size itself. For trees with 20 or more species, the estimated OU (25% of traits) and/or ACDC (40%) transformation parameter differed significantly from both zero and unity, indicating that a hierarchical tree with less (or occasionally more) structure than the original better fit the data and so could be preferred for comparative analyses.
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            Soil-carbon response to warming dependent on microbial physiology

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              Will plant movements keep up with climate change?

              In the face of anthropogenic climate change, species must acclimate, adapt, move, or die. Although some species are moving already, their ability to keep up with the faster changes expected in the future is unclear. 'Migration lag' is a particular concern with plants, because it could threaten both biodiversity and carbon storage. Plant movements are not realistically represented in models currently used to predict future vegetation and carbon-cycle feedbacks, so there is an urgent need to understand how much of a problem failure to track climate change is likely to be. Therefore, in this review, we compare how fast plants need to move with how fast they can move; that is, the velocity of climate change with the velocity of plant movement. Copyright © 2013 Elsevier Ltd. All rights reserved.
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                Author and article information

                Journal
                Glob Chang Biol
                Global change biology
                Wiley-Blackwell
                1365-2486
                1354-1013
                May 2017
                : 23
                : 5
                Affiliations
                [1 ] Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, CO, 80309, USA.
                [2 ] Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, 80309, USA.
                [3 ] School of Forestry and Environmental Studies, Yale University, New Haven, CT, 06511, USA.
                Article
                10.1111/gcb.13557
                27891711
                f6929ba5-7421-4190-8bc2-a15997b2a021
                History

                bacteria,microbial bioindicators,soil,temperature,warming
                bacteria, microbial bioindicators, soil, temperature, warming

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