Correlated variability in the blazar 3C 454.3

The blazar 3C 454.3 was revealed by the Fermi Gamma-ray Space Telescope to be in an exceptionally high flux state in July 2008. Accordingly, we performed a multi-wavelength monitoring campaign on this blazar using IR and optical observations from the SMARTS telescopes, optical, UV and X-ray data from the Swift satellite, and public-release gamma-ray data from Fermi. We find an excellent correlation between the IR, optical, UV and gamma-ray light curves, with a time lag of less than one day. The amplitude of the infrared variability is comparable to that in gamma-rays, and larger than at optical or UV wavelengths. The X-ray flux is not strongly correlated with either the gamma-rays or longer wavelength data. These variability characteristics find a natural explanation in the external Compton model, in which electrons with Lorentz factor gamma~10^(3-4) radiate synchrotron emission in the infrared-optical and also scatter accretion disk or emission line photons to gamma-ray energies, while much cooler electrons (gamma~10^(1-2)) produce X-rays by scattering synchrotron or other ambient photons.Comment: 7 pages, 3 figures, submitted to ApJ Letter

Interactive Effects of Time, CO\u3csub\u3e2\u3c/sub\u3e, N, and Diversity on Total Belowground Carbon Allocation and Ecosystem Carbon Storage in a Grassland Community

Predicting if ecosystems will mitigate or exacerbate rising CO2 requires understanding how elevated CO2 will interact with coincident changes in diversity and nitrogen (N) availability to affect ecosystem carbon (C) storage. Yet achieving such understanding has been hampered by the difficulty of quantifying belowground C pools and fluxes. Thus, we used mass balance calculations to quantify the effects of diversity, CO2, and N on both the total amount of C allocated belowground by plants (total belowground C allocation, TBCA) and ecosystem C storage in a periodically burned, 8-year Minnesota grassland biodiversity, CO2, and N experiment (BioCON). Annual TBCA increased in response to elevated CO2, enriched N, and increasing diversity. TBCA was positively related to standing root biomass. After removing the influence of root biomass, the effect of elevated CO2 remained positive, suggesting additional drivers of TBCA apart from those that maintain high root biomass. Removing root biomass effects resulted in the effects of N and diversity becoming neutral or negative (depending on year), suggesting that the positive effects of diversity and N on TBCA were related to treatmentdriven differences in root biomass. Greater litter production in high diversity, elevated CO2, and enhanced N treatments increased annual ecosystem C loss in fire years and C gain in non-fire years, resulting in overall neutral C storage rates. Our results suggest that frequently burned grasslands are unlikely to exhibit enhanced C sequestration with increasing atmospheric CO2 levels or N deposition

Convergence Of Soil Nitrogen Isotopes Across Global Climate Gradients

Quantifying global patterns of terrestrial nitrogen (N) cycling is central to predicting future patterns of primary productivity, carbon sequestration, nutrient fluxes to aquatic systems, and climate forcing. With limited direct measures of soil N cycling at the global scale, syntheses of the N-15 : N-14 ratio of soil organic matter across climate gradients provide key insights into understanding global patterns of N cycling. In synthesizing data from over 6000 soil samples, we show strong global relationships among soil N isotopes, mean annual temperature (MAT), mean annual precipitation (MAP), and the concentrations of organic carbon and clay in soil. In both hot ecosystems and dry ecosystems, soil organic matter was more enriched in N-15 than in corresponding cold ecosystems or wet ecosystems. Below a MAT of 9.8 degrees C, soil delta N-15 was invariant with MAT. At the global scale, soil organic C concentrations also declined with increasing MAT and decreasing MAP. After standardizing for variation among mineral soils in soil C and clay concentrations, soil delta N-15 showed no consistent trends across global climate and latitudinal gradients. Our analyses could place new constraints on interpretations of patterns of ecosystem N cycling and global budgets of gaseous N loss.

TRY plant trait database - enhanced coverage and open access

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

Litter mixture interactions at the level of plant functional types are additive.

It is very difficult to estimate litter decomposition rates in natural ecosystems because litters of many species are mixed and idiosyncratic interactions occur among those litters. A way to tackle this problem is to investigate litter mixing effects not at the species level but at the level of Plant Functional Types (PFTs). We tested the hypothesis that at the PFT level positive and negative interactions balance each other, causing an overall additive effect (no significant interactions among PFTs). Thereto, we used litter of four PFTs from a temperate peatland in which random draws were taken from the litter species pool of each PFT for every combination of 2, 3, and 4 PFTs. Decomposition rates clearly differed among the 4 PFTs (Sphagnum spp. < graminoids = N-fixing tree < forbs) and showed little variation within the PFTs (notably for the Sphagnum mosses and the graminoids). Significant positive interactions (4 out of 11) in the PFT mixtures were only found after 20 weeks and in all these combinations Sphagnum was involved. After 36 and 56 weeks of incubation interactions were not significantly different from zero. However, standard deviations were larger than the means, indicating that positive and negative interactions balanced each other. Thus, when litter mixture interactions are considered at the PFT level the interactions are additive. From this we conclude that for estimating litter decomposition rates at the ecosystem level, it is sufficient to use the weighted (by litter production) average decomposition rates of the contributing PFTs. © 2009 The Author(s)

Quinoa Phenotyping Methodologies: An International Consensus

Quinoa is a crop originating in the Andes but grown more widely and with the genetic potential for significant further expansion. Due to the phenotypic plasticity of quinoa, varieties need to be assessed across years and multiple locations. To improve comparability among field trials across the globe and to facilitate collaborations, components of the trials need to be kept consistent, including the type and methods of data collected. Here, an internationally open-access framework for phenotyping a wide range of quinoa features is proposed to facilitate the systematic agronomic, physiological and genetic characterization of quinoa for crop adaptation and improvement. Mature plant phenotyping is a central aspect of this paper, including detailed descriptions and the provision of phenotyping cards to facilitate consistency in data collection. High-throughput methods for multi-temporal phenotyping based on remote sensing technologies are described. Tools for higher throughput post-harvest phenotyping of seeds are presented. A guideline for approaching quinoa field trials including the collection of environmental data and designing layouts with statistical robustness is suggested. To move towards developing resources for quinoa in line with major cereal crops, a database was created. The Quinoa Germinate Platform will serve as a central repository of data for quinoa researchers globally

Variation in Soil Respiration across Soil and Vegetation Types in an Alpine Valley.

BACKGROUND AND AIMS: Soils of mountain regions and their associated plant communities are highly diverse over short spatial scales due to the heterogeneity of geological substrates and highly dynamic geomorphic processes. The consequences of this heterogeneity for biogeochemical transfers, however, remain poorly documented. The objective of this study was to quantify the variability of soil-surface carbon dioxide efflux, known as soil respiration (Rs), across soil and vegetation types in an Alpine valley. To this aim, we measured Rs rates during the peak and late growing season (July-October) in 48 plots located in pastoral areas of a small valley of the Swiss Alps. FINDINGS: Four herbaceous vegetation types were identified, three corresponding to different stages of primary succession (Petasition paradoxi in pioneer conditions, Seslerion in more advanced stages and Poion alpinae replacing the climactic forests), as well as one (Rumicion alpinae) corresponding to eutrophic grasslands in intensively grazed areas. Soils were developed on calcareous alluvial and colluvial fan deposits and were classified into six types including three Fluvisols grades and three Cambisols grades. Plant and soil types had a high level of co-occurrence. The strongest predictor of Rs was soil temperature, yet we detected additional explanatory power of sampling month, showing that temporal variation was not entirely reducible to variations in temperature. Vegetation and soil types were also major determinants of Rs. During the warmest month (August), Rs rates varied by over a factor three between soil and vegetation types, ranging from 2.5 μmol m-2 s-1 in pioneer environments (Petasition on Very Young Fluvisols) to 8.5 μmol m-2 s-1 in differentiated soils supporting nitrophilous species (Rumicion on Calcaric Cambisols). CONCLUSIONS: Overall, this study provides quantitative estimates of spatial and temporal variability in Rs in the mountain environment, and demonstrates that estimations of soil carbon efflux at the watershed scale in complex geomorphic terrain have to account for soil and vegetation heterogeneity

Root traits explain plant species distributions along climatic gradients yet challenge the nature of ecological trade-offs

Ecological theory is built on trade-offs, where trait differences among species evolved as adaptations to different environments. Trade-offs are often assumed to be bidirectional, where opposite ends of a gradient in trait values confer advantages in different environments. However, unidirectional benefits could be widespread if extreme trait values confer advantages at one end of an environmental gradient, whereas a wide range of trait values are equally beneficial at the other end. Here, we show that root traits explain species occurrences along broad gradients of temperature and water availability, but model predictions only resembled trade-offs in two out of 24 models. Forest species with low specific root length and high root tissue density (RTD) were more likely to occur in warm climates but species with high specific root length and low RTD were more likely to occur in cold climates. Unidirectional benefits were more prevalent than trade-offs: for example, species with large-diameter roots and high RTD were more commonly associated with dry climates, but species with the opposite trait values were not associated with wet climates. Directional selection for traits consistently occurred in cold or dry climates, whereas a diversity of root trait values were equally viable in warm or wet climates. Explicit integration of unidirectional benefits into ecological theory is needed to advance our understanding of the consequences of trait variation on species responses to environmental change.</p