Northern Arizona University

DNA sequencing continues to decrease in cost with the Illumina HiSeq2000 generating up to 600 Gb of paired-end 100 base reads in a ten-day run. Here we present a protocol for community amplicon sequencing on the HiSeq2000 and MiSeq Illumina platforms, and apply that protocol to sequence 24 microbial communities from host-associated and free-living environments. A critical question as more sequencing platforms become available is whether biological conclusions derived on one platform are consistent with what would be derived on a different platform. We show that the protocol developed for these instruments successfully recaptures known biological results, and additionally that biological conclusions are consistent across sequencing platforms (the HiSeq2000 versus the MiSeq) and across the sequenced regions of amplicons.

Gut microbial communities represent one source of human genetic and metabolic diversity. To examine how gut microbiomes differ among human populations, here we characterize bacterial species in fecal samples from 531 individuals, plus the gene content of 110 of them. The cohort encompassed healthy children and adults from the Amazonas of Venezuela, rural Malawi and US metropolitan areas and included mono- and dizygotic twins. Shared features of the functional maturation of the gut microbiome were identified during the first three years of life in all three populations, including age-associated changes in the genes involved in vitamin biosynthesis and metabolism. Pronounced differences in bacterial assemblages and functional gene repertoires were noted between US residents and those in the other two countries. These distinctive features are evident in early infancy as well as adulthood. Our findings underscore the need to consider the microbiome when evaluating human development, nutritional needs, physiological variations and the impact of westernization. The human gut microbiome from a large cohort of more than 500 indivduals living on three continents with three distinct cultures is analysed, emphasizing the effect of host age, diet and environment on the composition and functional repertoire of fecal microbiota. The human gut microbiome is thought to be shaped by both host diet and genetics. Using a sample set of more than 500 individuals belonging to around 150 families from three different countries, Yatsunenko et al. analyse the impact of both factors on the composition and functional repertoire of the fecal microbiota.

BACKGROUND: Taxonomic classification of marker-gene sequences is an important step in microbiome analysis. RESULTS: We present q2-feature-classifier ( https://github.com/qiime2/q2-feature-classifier ), a QIIME 2 plugin containing several novel machine-learning and alignment-based methods for taxonomy classification. We evaluated and optimized several commonly used classification methods implemented in QIIME 1 (RDP, BLAST, UCLUST, and SortMeRNA) and several new methods implemented in QIIME 2 (a scikit-learn naive Bayes machine-learning classifier, and alignment-based taxonomy consensus methods based on VSEARCH, and BLAST+) for classification of bacterial 16S rRNA and fungal ITS marker-gene amplicon sequence data. The naive-Bayes, BLAST+-based, and VSEARCH-based classifiers implemented in QIIME 2 meet or exceed the species-level accuracy of other commonly used methods designed for classification of marker gene sequences that were evaluated in this work. These evaluations, based on 19 mock communities and error-free sequence simulations, including classification of simulated "novel" marker-gene sequences, are available in our extensible benchmarking framework, tax-credit ( https://github.com/caporaso-lab/tax-credit-data ). CONCLUSIONS: Our results illustrate the importance of parameter tuning for optimizing classifier performance, and we make recommendations regarding parameter choices for these classifiers under a range of standard operating conditions. q2-feature-classifier and tax-credit are both free, open-source, BSD-licensed packages available on GitHub.

Severe droughts have been associated with regional-scale forest mortality worldwide. Climate change is expected to exacerbate regional mortality events; however, prediction remains difficult because the physiological mechanisms underlying drought survival and mortality are poorly understood. We developed a hydraulically based theory considering carbon balance and insect resistance that allowed development and examination of hypotheses regarding survival and mortality. Multiple mechanisms may cause mortality during drought. A common mechanism for plants with isohydric regulation of water status results from avoidance of drought-induced hydraulic failure via stomatal closure, resulting in carbon starvation and a cascade of downstream effects such as reduced resistance to biotic agents. Mortality by hydraulic failure per se may occur for isohydric seedlings or trees near their maximum height. Although anisohydric plants are relatively drought-tolerant, they are predisposed to hydraulic failure because they operate with narrower hydraulic safety margins during drought. Elevated temperatures should exacerbate carbon starvation and hydraulic failure. Biotic agents may amplify and be amplified by drought-induced plant stress. Wet multidecadal climate oscillations may increase plant susceptibility to drought-induced mortality by stimulating shifts in hydraulic architecture, effectively predisposing plants to water stress. Climate warming and increased frequency of extreme events will probably cause increased regional mortality episodes. Isohydric and anisohydric water potential regulation may partition species between survival and mortality, and, as such, incorporating this hydraulic framework may be effective for modeling plant survival and mortality under future climate conditions.

Acknowledgements Preface Introduction 1. Comprehension and production strategies in language learning 2. The role of memory and lexical learning 3. Psycholinguistic processes in language use and language learning 4. Models of language learning 5. A rationale for task-based instruction 6. Implementing task-based instruction 7. Processing perspectives on testing 8. Research into language aptitude 9. Issues in aptitude theory: exceptional learners and modularity 10. Learning style 11. Learners, learning, and pedagogy 12. Conclusions Bibliography Index

Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth's microbial diversity.

PURPOSE: The number of cancer survivors worldwide is growing, with over 15.5 million cancer survivors in the United States alone-a figure expected to double in the coming decades. Cancer survivors face unique health challenges as a result of their cancer diagnosis and the impact of treatments on their physical and mental well-being. For example, cancer survivors often experience declines in physical functioning and quality of life while facing an increased risk of cancer recurrence and all-cause mortality compared with persons without cancer. The 2010 American College of Sports Medicine Roundtable was among the first reports to conclude that cancer survivors could safely engage in enough exercise training to improve physical fitness and restore physical functioning, enhance quality of life, and mitigate cancer-related fatigue. METHODS: A second Roundtable was convened in 2018 to advance exercise recommendations beyond public health guidelines and toward prescriptive programs specific to cancer type, treatments, and/or outcomes. RESULTS: Overall findings retained the conclusions that exercise training and testing were generally safe for cancer survivors and that every survivor should "avoid inactivity." Enough evidence was available to conclude that specific doses of aerobic, combined aerobic plus resistance training, and/or resistance training could improve common cancer-related health outcomes, including anxiety, depressive symptoms, fatigue, physical functioning, and health-related quality of life. Implications for other outcomes, such as peripheral neuropathy and cognitive functioning, remain uncertain. CONCLUSIONS: The proposed recommendations should serve as a guide for the fitness and health care professional working with cancer survivors. More research is needed to fill remaining gaps in knowledge to better serve cancer survivors, as well as fitness and health care professionals, to improve clinical practice.

Abstract Plant traits – the morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs – determine how primary producers respond to environmental factors, affect other trophic levels, influence ecosystem processes and services and provide a link from species richness to ecosystem functional diversity. Trait data thus represent the raw material for a wide range of research from evolutionary biology, community and functional ecology to biogeography. Here we present the global database initiative named TRY, which has united a wide range of the plant trait research community worldwide and gained an unprecedented buy‐in of trait data: so far 93 trait databases have been contributed. The data repository currently contains almost three million trait entries for 69 000 out of the world's 300 000 plant species, with a focus on 52 groups of traits characterizing the vegetative and regeneration stages of the plant life cycle, including growth, dispersal, establishment and persistence. A first data analysis shows that most plant traits are approximately log‐normally distributed, with widely differing ranges of variation across traits. Most trait variation is between species (interspecific), but significant intraspecific variation is also documented, up to 40% of the overall variation. Plant functional types (PFTs), as commonly used in vegetation models, capture a substantial fraction of the observed variation – but for several traits most variation occurs within PFTs, up to 75% of the overall variation. In the context of vegetation models these traits would better be represented by state variables rather than fixed parameter values. The improved availability of plant trait data in the unified global database is expected to support a paradigm shift from species to trait‐based ecology, offer new opportunities for synthetic plant trait research and enable a more realistic and empirically grounded representation of terrestrial vegetation in Earth system models.

We continue to uncover a wealth of information connecting microbes in important ways to human and environmental ecology. As our scientific knowledge and technical abilities improve, the tools used for microbiome surveys can be modified to improve the accuracy of our techniques, ensuring that we can continue to identify groundbreaking connections between microbes and the ecosystems they populate, from ice caps to the human body. It is important to confirm that modifications to these tools do not cause new, detrimental biases that would inhibit the field rather than continue to move it forward. We therefore demonstrated that two recently modified primer pairs that target taxonomically discriminatory regions of bacterial and fungal genomic DNA do not introduce new biases when used on a variety of sample types, from soil to human skin. This confirms the utility of these primers for maintaining currently recommended microbiome research techniques as the state of the art.

Future drought is projected to occur under warmer temperature conditions as climate change progresses, referred to here as global-change-type drought, yet quantitative assessments of the triggers and potential extent of drought-induced vegetation die-off remain pivotal uncertainties in assessing climate-change impacts. Of particular concern is regional-scale mortality of overstory trees, which rapidly alters ecosystem type, associated ecosystem properties, and land surface conditions for decades. Here, we quantify regional-scale vegetation die-off across southwestern North American woodlands in 2002-2003 in response to drought and associated bark beetle infestations. At an intensively studied site within the region, we quantified that after 15 months of depleted soil water content, >90% of the dominant, overstory tree species (Pinus edulis, a piñon) died. The die-off was reflected in changes in a remotely sensed index of vegetation greenness (Normalized Difference Vegetation Index), not only at the intensively studied site but also across the region, extending over 12,000 km2 or more; aerial and field surveys confirmed the general extent of the die-off. Notably, the recent drought was warmer than the previous subcontinental drought of the 1950s. The limited, available observations suggest that die-off from the recent drought was more extensive than that from the previous drought, extending into wetter sites within the tree species' distribution. Our results quantify a trigger leading to rapid, drought-induced die-off of overstory woody plants at subcontinental scale and highlight the potential for such die-off to be more severe and extensive for future global-change-type drought under warmer conditions.

Connectivity among populations and habitats is important for a wide range of ecological processes. Understanding, preserving, and restoring connectivity in complex landscapes requires connectivity models and metrics that are reliable, efficient, and process based. We introduce a new class of ecological connectivity models based in electrical circuit theory. Although they have been applied in other disciplines, circuit-theoretic connectivity models are new to ecology. They offer distinct advantages over common analytic connectivity models, including a theoretical basis in random walk theory and an ability to evaluate contributions of multiple dispersal pathways. Resistance, current, and voltage calculated across graphs or raster grids can be related to ecological processes (such as individual movement and gene flow) that occur across large population networks or landscapes. Efficient algorithms can quickly solve networks with millions of nodes, or landscapes with millions of raster cells. Here we review basic circuit theory, discuss relationships between circuit and random walk theories, and describe applications in ecology, evolution, and conservation. We provide examples of how circuit models can be used to predict movement patterns and fates of random walkers in complex landscapes and to identify important habitat patches and movement corridors for conservation planning.

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

Contaminated soils and waters pose a major environmental and human health problem, which may be partially solved by the emerging phytoremediation technology. This cost-effective plant-based approach to remediation takes advantage of the remarkable ability of plants to concentrate elements and compounds from the environment and to metabolize various molecules in their tissues. Toxic heavy metals and organic pollutants are the major targets for phytoremediation. In recent years, knowledge of the physiological and molecular mechanisms of phytoremediation began to emerge together with biological and engineering strategies designed to optimize and improve phytoremediation. In addition, several field trials confirmed the feasibility of using plants for environmental cleanup. This review concentrates on the most developed subsets of phytoremediation technology and on the biological mechanisms that make phytoremediation work.

SUMMARY A great diversity of plants and fungi engage in mycorrhizal associations. In natural habitats, and in an ecologically meaningful time span, these associations have evolved to improve the fitness of both plant and fungal symbionts. In systems managed by humans, mycorrhizal associations often improve plant productivity, but this is not always the case. Mycorrhizal fungi might be considered to be parasitic on plants when net cost of the symbiosis exceeds net benefits. Parasitism can be developmentally induced, environmentally induced, or possibly genotypically induced. Morphological, phenological, and physiological characteristics of the symbionts influence the functioning of mycorrhizas at an individual scale. Biotic and abiotic factors at the rhizosphere, community, and ecosystem scales further mediate mycorrhizal functioning. Despite the complexity of mycorrhizal associations, it might be possible to construct predictive models of mycorrhizal functioning. These models will need to incorporate variables and parameters that account for differences in plant responses to, and control of, mycorrhizal fungi, and differences in fungal effects on, and responses to the plant. Developing and testing quantitative models of mycorrhizal functioning in the real world requires creative experimental manipulations and measurements. This work will be facilitated by recent advances in molecular and biochemical techniques. A greater understanding of how mycorrhizas function in complex natural systems is a prerequisite to managing them in agriculture, forestry, and restoration.

This book describes the most important kinds of texts in English and introduces the methodological techniques used to analyse them. Three analytical approaches are introduced and compared, describing a wide range of texts from the perspectives of register, genre and style. The primary focus of the book is on the analysis of registers. Part 1 introduces an analytical framework for studying registers, genre conventions, and styles. Part 2 provides detailed descriptions of particular text varieties in English, including spoken interpersonal varieties (conversation, university office hours, service encounters), written varieties (newspapers, academic prose, fiction), and emerging electronic varieties (e-mail, internet forums, text messages). Finally, Part 3 introduces advanced analytical approaches using corpora, and discusses theoretical concerns, such as the place of register studies in linguistics, and practical applications of register analysis. Each chapter ends with three types of activities: reflection and review activities, analysis activities, and larger project ideas.

The calculation and use of effect sizes—such as d for mean differences and r for correlations—has increased dramatically in second language (L2) research in the last decade. Interpretations of these effects, however, have been rare and, when present, have largely defaulted to Cohen's levels of small ( d = .2, r = .1), medium (.5, .3), and large (.8, .5), which were never intended as prescriptions but rather as a general guide. As Cohen himself and many others have argued, effect sizes are best understood when interpreted within a particular discipline or domain. This article seeks to promote more informed and field‐specific interpretations of d and r by presenting a description of L2 effects from 346 primary studies and 91 meta‐analyses ( N > 604,000). Results reveal that Cohen's benchmarks generally underestimate the effects obtained in L2 research. Based on our analysis, we propose a field‐specific scale for interpreting effect sizes, and we outline eight key considerations for gauging relative magnitude and practical significance in primary and secondary studies, such as theoretical maturity in the domain, the degree of experimental manipulation, and the presence of publication bias.

Persistent changes in tree mortality rates can alter forest structure, composition, and ecosystem services such as carbon sequestration. Our analyses of longitudinal data from unmanaged old forests in the western United States showed that background (noncatastrophic) mortality rates have increased rapidly in recent decades, with doubling periods ranging from 17 to 29 years among regions. Increases were also pervasive across elevations, tree sizes, dominant genera, and past fire histories. Forest density and basal area declined slightly, which suggests that increasing mortality was not caused by endogenous increases in competition. Because mortality increased in small trees, the overall increase in mortality rates cannot be attributed solely to aging of large trees. Regional warming and consequent increases in water deficits are likely contributors to the increases in tree mortality rates.

Functional profiles of microbial communities are typically generated using comprehensive metagenomic or metatranscriptomic sequence read searches, which are time-consuming, prone to spurious mapping, and often limited to community-level quantification. We developed HUMAnN2, a tiered search strategy that enables fast, accurate, and species-resolved functional profiling of host-associated and environmental communities. HUMAnN2 identifies a community's known species, aligns reads to their pangenomes, performs translated search on unclassified reads, and finally quantifies gene families and pathways. Relative to pure translated search, HUMAnN2 is faster and produces more accurate gene family profiles. We applied HUMAnN2 to study clinal variation in marine metabolism, ecological contribution patterns among human microbiome pathways, variation in species' genomic versus transcriptional contributions, and strain profiling. Further, we introduce 'contributional diversity' to explain patterns of ecological assembly across different microbial community types.

Abstract. Soils and other unconsolidated deposits in the northern circumpolar permafrost region store large amounts of soil organic carbon (SOC). This SOC is potentially vulnerable to remobilization following soil warming and permafrost thaw, but SOC stock estimates were poorly constrained and quantitative error estimates were lacking. This study presents revised estimates of permafrost SOC stocks, including quantitative uncertainty estimates, in the 0–3 m depth range in soils as well as for sediments deeper than 3 m in deltaic deposits of major rivers and in the Yedoma region of Siberia and Alaska. Revised estimates are based on significantly larger databases compared to previous studies. Despite this there is evidence of significant remaining regional data gaps. Estimates remain particularly poorly constrained for soils in the High Arctic region and physiographic regions with thin sedimentary overburden (mountains, highlands and plateaus) as well as for deposits below 3 m depth in deltas and the Yedoma region. While some components of the revised SOC stocks are similar in magnitude to those previously reported for this region, there are substantial differences in other components, including the fraction of perennially frozen SOC. Upscaled based on regional soil maps, estimated permafrost region SOC stocks are 217 ± 12 and 472 ± 27 Pg for the 0–0.3 and 0–1 m soil depths, respectively (±95% confidence intervals). Storage of SOC in 0–3 m of soils is estimated to 1035 ± 150 Pg. Of this, 34 ± 16 Pg C is stored in poorly developed soils of the High Arctic. Based on generalized calculations, storage of SOC below 3 m of surface soils in deltaic alluvium of major Arctic rivers is estimated as 91 ± 52 Pg. In the Yedoma region, estimated SOC stocks below 3 m depth are 181 ± 54 Pg, of which 74 ± 20 Pg is stored in intact Yedoma (late Pleistocene ice- and organic-rich silty sediments) with the remainder in refrozen thermokarst deposits. Total estimated SOC storage for the permafrost region is ∼1300 Pg with an uncertainty range of ∼1100 to 1500 Pg. Of this, ∼500 Pg is in non-permafrost soils, seasonally thawed in the active layer or in deeper taliks, while ∼800 Pg is perennially frozen. This represents a substantial ∼300 Pg lowering of the estimated perennially frozen SOC stock compared to previous estimates.

The c2d Spitzer Legacy project obtained images and photometry with both IRAC and MIPS instruments for five large, nearby molecular clouds. Three of the clouds were also mapped in dust continuum emission at 1.1 mm, and optical spectroscopy has been obtained for some clouds. This paper combines information drawn from studies of individual clouds into a combined and updated statistical analysis of star-formation rates and efficiencies, numbers and lifetimes for spectral energy distribution (SED) classes, and clustering properties. Current star-formation efficiencies range from 3% to 6%; if star formation continues at current rates for 10 Myr, efficiencies could reach 15-30%. Star-formation rates and rates per unit area vary from cloud to cloud; taken together, the five clouds are producing about 260 M of stars per Myr. The star-formation surface density is more than an order of magnitude larger than would be predicted from the Kennicutt relation used in extragalactic studies, reflecting the fact that those relations apply to larger scales, where more diffuse matter is included in the gas surface density. Measured against the dense gas probed by the maps of dust continuum emission, the efficiencies are much higher, with stellar masses similar to masses of dense gas, and the current stock of dense cores would be exhausted in 1.8 Myr on average. Nonetheless, star formation is still slow compared to that expected in a free-fall time, even in the dense cores. The derived lifetime for the Class I phase is 0.54 Myr, considerably longer than some estimates. Similarly, the lifetime for the Class 0 SED class, 0.16 Myr, with the notable exception of the Ophiuchus cloud, is longer than early estimates. If photometry is corrected for estimated extinction before calculating class indicators, the lifetimes drop to 0.44 Myr for Class I and to 0.10 for Class 0. These lifetimes assume a continuous flow through the Class II phase and should be considered median lifetimes or half-lives. Star formation is highly concentrated to regions of high extinction, and the youngest objects are very strongly associated with dense cores. The great majority (90%) of young stars lie within loose clusters with at least 35 members and a stellar density of 1 M pc^(–3). Accretion at the sound speed from an isothermal sphere over the lifetime derived for the Class I phase could build a star of about 0.25 M , given an efficiency of 0.3. Building larger mass stars by using higher mass accretion rates could be problematic, as our data confirm and aggravate the "luminosity problem" for protostars. At a given T bol, the values for L bol are mostly less than predicted by standard infall models and scatter over several orders of magnitude. These results strongly suggest that accretion is time variable, with prolonged periods of very low accretion. Based on a very simple model and this sample of sources, half the mass of a star would be accreted during only 7% of the Class I lifetime, as represented by the eight most luminous objects.