Isolation of polymorphic microsatellites in the stemless thistle (Cirsium acaule) and their utility in other Cirsium species

The genus Cirsium includes species with both widespread and restricted geographical distributions, several of which are serious weeds. Nine polymorphic microsatellite loci were isolated from the stemless thistle Cirsium acaule. Eight were polymorphic in C. acaule, six in C. arvense and seven in C. heterophyllum. One locus monomorphic in C. acaule showed polymorphism in C. heterophyllum. The mean number of alleles per locus was 4.1 in C. acaule, 6.2 in C. arvense and 2.9 in C. heterophyllum. These nine loci were also amplified in C. eriophorum and C. vulgare, suggesting that these markers may be of use throughout the genus

Intraspecfic variation in cold-temperature metabolic phenotypes of Arabidopsis lyrata ssp petraea

Atmospheric temperature is a key factor in determining the distribution of a plant species. Alongside this, plant populations growing at the margin of their range may exhibit traits that indicate genetic differentiation and adaptation to their local abiotic environment. We investigated whether geographically separated marginal populations of Arabidopsis lyrata ssp. petraea have distinct metabolic phenotypes associated with exposure to cold temperatures. Seeds of A. petraea were obtained from populations along a latitudinal gradient, namely Wales, Sweden and Iceland and grown in a controlled cabinet environment. Mannose, glucose, fructose, sucrose and raffinose concentrations were different between cold treatments and populations, especially in the Welsh population, but polyhydric alcohol concentrations were not. The free amino acid compositions were population specific, with fold differences in most amino acids, especially in the Icelandic populations, with gross changes in amino acids, particularly those associated with glutamine metabolism. Metabolic fingerprints and profiles were obtained. Principal component analysis (PCA) of metabolite fingerprints revealed metabolic characteristic phenotypes for each population and temperature. It is suggested that amino acids and carbohydrates were responsible for discriminating populations within the PCA. Metabolite fingerprinting and profiling has proved to be sufficiently sensitive to identify metabolic differences between plant populations at different atmospheric temperatures. These findings show that there is significant natural variation in cold metabolism among populations of A. l. petraea which may signify plant adaptation to local climates

The impact of alternative trait-scaling hypotheses for the maximum photosynthetic carboxylation rate (Vcmax) on global gross primary production

The maximum photosynthetic carboxylation rate (Vcmax) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global Vcmax distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 PgC yr−1, 65% of the range of a recent model intercomparison of global GPP. The variation in GPP propagated through to a 27% coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated (r = 0.85–0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand Vcmax variation in the field, particularly in northern latitudes

Cirsium species show disparity in patterns of genetic variation at their range-edge, despite similar patterns of reproduction and isolation

Genetic variation was assessed across the UK geographical range of Cirsium acaule and Cirsium heterophyllum. A decline in genetic diversity and increase in population divergence approaching the range edge of these species was predicted based on parallel declines in population density and seed production reported seperately. Patterns were compared with UK populations of the widespread Cirsium arvense.Populations were sampled along a latitudinal transect in the UK and genetic variation assessed using microsatellite markers. Cirsium acaule shows strong isolation by distance, a significant decline in diversity and an increase in divergence among range-edge populations. Geographical structure is also evident in C. arvense, whereas no such patterns are seen in C.heterophyllum. There is a major disparity between patterns of genetic variation in C. acaule and C. heterophyllum despite very similar patterns in seed production and population isolation in these species. This suggests it may be misleading to make assumptions about the geographical structure of genetic variation within species based solely on the present-day reproduction and distribution of populations

Carbon residence time dominates uncertainty in terrestrial vegetation responses to future climate and atmospheric CO2.

Future climate change and increasing atmospheric CO2 are expected to cause major changes in vegetation structure and function over large fractions of the global land surface. Seven global vegetation models are used to analyze possible responses to future climate simulated by a range of general circulation models run under all four representative concentration pathway scenarios of changing concentrations of greenhouse gases. All 110 simulations predict an increase in global vegetation carbon to 2100, but with substantial variation between vegetation models. For example, at 4 °C of global land surface warming (510-758 ppm of CO2), vegetation carbon increases by 52-477 Pg C (224 Pg C mean), mainly due to CO2 fertilization of photosynthesis. Simulations agree on large regional increases across much of the boreal forest, western Amazonia, central Africa, western China, and southeast Asia, with reductions across southwestern North America, central South America, southern Mediterranean areas, southwestern Africa, and southwestern Australia. Four vegetation models display discontinuities across 4 °C of warming, indicating global thresholds in the balance of positive and negative influences on productivity and biomass. In contrast to previous global vegetation model studies, we emphasize the importance of uncertainties in projected changes in carbon residence times. We find, when all seven models are considered for one representative concentration pathway × general circulation model combination, such uncertainties explain 30% more variation in modeled vegetation carbon change than responses of net primary productivity alone, increasing to 151% for non-HYBRID4 models. A change in research priorities away from production and toward structural dynamics and demographic processes is recommended.The research leading to these results has received funding from the European Community’s Seventh Framework Programme (FP7 2007-2013) under Grant 238366. R.B., R.K., R.D., A.W., and P.D.F. were supported by the Joint Department of Energy and Climate Change/Department for Environment, Food and Rural Affairs Met Office Hadley Centre Climate Programme (GA01101). A.I. and K.N. were supported by the Environment Research and Technology Development Fund (S-10) of the Ministry of the Environment, Japan. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for the Coupled Model Intercomparison Project (CMIP), and we thank the climate modeling groups responsible for the GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, and NorESM1-M models for producing and making available their model output. For CMIP, the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. This work has been conducted under the framework of the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). The ISI-MIP Fast Track project was funded by the German Federal Ministry of Education and Research (BMBF) with project funding Reference 01LS1201A.This is the author accepted manuscript. The final version is available from PNAS via http://dx.doi.org/10.1073/pnas.122247711

Training of Instrumentalists and Development of New Technologies on SOFIA

This white paper is submitted to the Astronomy and Astrophysics 2010 Decadal Survey (Astro2010)1 Committee on the State of the Profession to emphasize the potential of the Stratospheric Observatory for Infrared Astronomy (SOFIA) to contribute to the training of instrumentalists and observers, and to related technology developments. This potential goes beyond the primary mission of SOFIA, which is to carry out unique, high priority astronomical research. SOFIA is a Boeing 747SP aircraft with a 2.5 meter telescope. It will enable astronomical observations anywhere, any time, and at most wavelengths between 0.3 microns and 1.6 mm not accessible from ground-based observatories. These attributes, accruing from the mobility and flight altitude of SOFIA, guarantee a wealth of scientific return. Its instrument teams (nine in the first generation) and guest investigators will do suborbital astronomy in a shirt-sleeve environment. The project will invest $10M per year in science instrument development over a lifetime of 20 years. This, frequent flight opportunities, and operation that enables rapid changes of science instruments and hands-on in-flight access to the instruments, assure a unique and extensive potential - both for training young instrumentalists and for encouraging and deploying nascent technologies. Novel instruments covering optical, infrared, and submillimeter bands can be developed for and tested on SOFIA by their developers (including apprentices) for their own observations and for those of guest observers, to validate technologies and maximize observational effectiveness.Comment: 10 pages, no figures, White Paper for Astro 2010 Survey Committee on State of the Professio

Comprehensive ecosystem model-data synthesis using multiple data sets at two temperate forest free-air CO2 enrichment experiments: Model performance at ambient CO2 concentration

Free-air CO2 enrichment (FACE) experiments provide a remarkable wealth of data which can be used to evaluate and improve terrestrial ecosystem models (TEMs). In the FACE model-data synthesis project, 11 TEMs were applied to two decadelong FACE experiments in temperate forests of the southeastern U.S.—the evergreen Duke Forest and the deciduous Oak Ridge Forest. In this baseline paper, we demonstrate our approach to model-data synthesis by evaluating the models' ability to reproduce observed net primary productivity (NPP), transpiration, and leaf area index (LAI) in ambient CO2 treatments. Model outputs were compared against observations using a range of goodness-of-fit statistics. Many models simulated annual NPP and transpiration within observed uncertainty. We demonstrate, however, that high goodness-of-fit values do not necessarily indicate a successful model, because simulation accuracy may be achieved through compensating biases in component variables. For example, transpiration accuracy was sometimes achieved with compensating biases in leaf area index and transpiration per unit leaf area. Our approach to model-data synthesis therefore goes beyond goodness-of-fit to investigate the success of alternative representations of component processes. Here we demonstrate this approach by comparing competing model hypotheses determining peak LAI. Of three alternative hypotheses—(1) optimization to maximize carbon export, (2) increasing specific leaf area with canopy depth, and (3) the pipe model—the pipe model produced peak LAI closest to the observations. This example illustrates how data sets from intensive field experiments such as FACE can be used to reduce model uncertainty despite compensating biases by evaluating individual model assumptions

Trends in the sources and sinks of carbon dioxide

Efforts to control climate change require the stabilization of atmospheric CO2 concentrations. This can only be achieved through a drastic reduction of global CO2 emissions. Yet fossil fuel emissions increased by 29% between 2000 and 2008, in conjunction with increased contributions from emerging economies, from the production and international trade of goods and services, and from the use of coal as a fuel source. In contrast, emissions from land-use changes were nearly constant. Between 1959 and 2008, 43% of each year's CO2 emissions remained in the atmosphere on average; the rest was absorbed by carbon sinks on land and in the oceans. In the past 50 years, the fraction of CO2 emissions that remains in the atmosphere each year has likely increased, from about 40% to 45%, and models suggest that this trend was caused by a decrease in the uptake of CO2 by the carbon sinks in response to climate change and variability. Changes in the CO2 sinks are highly uncertain, but they could have a significant influence on future atmospheric CO2 levels. It is therefore crucial to reduce the uncertainties

Detecting Weak Spectral Lines in Interferometric Data through Matched Filtering

Modern radio interferometers enable observations of spectral lines with unprecedented spatial resolution and sensitivity. In spite of these technical advances, many lines of interest are still at best weakly detected and therefore necessitate detection and analysis techniques specialized for the low signal-to-noise ratio (S/N) regime. Matched filters can leverage knowledge of the source structure and kinematics to increase sensitivity of spectral line observations. Application of the filter in the native Fourier domain improves S/N while simultaneously avoiding the computational cost and ambiguities associated with imaging, making matched filtering a fast and robust method for weak spectral line detection. We demonstrate how an approximate matched filter can be constructed from a previously observed line or from a model of the source, and we show how this filter can be used to robustly infer a detection significance for weak spectral lines. When applied to ALMA Cycle 2 observations of CH3OH in the protoplanetary disk around TW Hya, the technique yields a ≈53% S/N boost over aperture-based spectral extraction methods, and we show that an even higher boost will be achieved for observations at higher spatial resolution. A Python-based open-source implementation of this technique is available under the MIT license at http://github.com/AstroChem/VISIBLE