Sub-dekahertz ultraviolet spectroscopy of 199Hg+

Using a laser that is frequency-locked to a Fabry-Perot etalon of high finesse and stability, we probe the 5d10 6s 2S_1/2 (F=0) - 5d9 6s 2D_5/2 (F=2) Delta-m_F = 0 electric-quadrupole transition of a single laser-cooled 199Hg+ ion stored in a cryogenic radio-frequency ion trap. We observe Fourier-transform limited linewidths as narrow as 6.7 Hz at 282 nm (1.06 X 10^15 Hz), yielding a line Q = 1.6 X 10^14. We perform a preliminary measurement of the 5d9 6s2 2D_5/2 electric-quadrupole shift due to interaction with the static fields of the trap, and discuss the implications for future trapped-ion optical frequency standards.Comment: 4 pages, 4 figures, submitted for publicatio

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

Carbon inputs from Miscanthus displace older soil organic carbon without inducing priming

The carbon (C) dynamics of a bioenergy system are key to correctly defining its viability as a sustainable alternative to conventional fossil fuel energy sources. Recent studies have quantified the greenhouse gas mitigation potential of these bioenergy crops, often concluding that C sequestration in soils plays a primary role in offsetting emissions through energy generation. Miscanthus is a particularly promising bioenergy crop and research has shown that soil C stocks can increase by more than 2 t C ha−1 yr−1. In this study, we use a stable isotope (13C) technique to trace the inputs and outputs from soils below a commercial Miscanthus plantation in Lincolnshire, UK, over the first 7 years of growth after conversion from a conventional arable crop. Results suggest that an unchanging total topsoil (0–30 cm) C stock is caused by Miscanthus additions displacing older soil organic matter. Further, using a comparison between bare soil plots (no new Miscanthus inputs) and undisturbed Miscanthus controls, soil respiration was seen to be unaffected through priming by fresh inputs or rhizosphere. The temperature sensitivity of old soil C was also seen to be very similar with and without the presence of live root biomass. Total soil respiration from control plots was dominated by Miscanthus-derived emissions with autotrophic respiration alone accounting for ∼50 % of CO2. Although total soil C stocks did not change significantly over time, the Miscanthus-derived soil C accumulated at a rate of 860 kg C ha−1 yr−1 over the top 30 cm. Ultimately, the results from this study indicate that soil C stocks below Miscanthus plantations do not necessarily increase during the first 7 years

COSORE: A community database for continuous soil respiration and other soil‐atmosphere greenhouse gas flux data

Globally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soil‐to‐atmosphere CO2 flux, commonly though imprecisely termed soil respiration (RS), is one of the largest carbon fluxes in the Earth system. An increasing number of high‐frequency RS measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, open‐source COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and long‐term GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured RS, the database design accommodates other soil‐atmosphere measurements (e.g. ecosystem respiration, chamber‐measured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package

Higher thermal acclimation potential of respiration but not photosynthesis in two alpine Picea taxa in contrast to two lowland congeners

The members of the genus Picea form a dominant component in many alpine and boreal forests which are the major sink for atmospheric CO2. However, little is known about the growth response and acclimation of CO2 exchange characteristics to high temperature stress in Picea taxa from different altitudes. Gas exchange parameters and growth characteristics were recorded from four year old seedlings of two alpine (Picea likiangensis vars. rubescens and linzhiensis) and two lowland (P. koraiensis and P. meyeri) taxa. Seedlings were grown at moderate (25°C/15°C) and high (35°C/25°C) day/night temperatures, for four months. The approximated biomass increment (ΔD2H) for all taxa decreased under high temperature stress, associated with decreased photosynthesis and increased respiration. However, the two alpine taxa exhibited lower photosynthetic acclimation and higher respiratory acclimation than either lowland taxon. Moreover, higher leaf dry mass per unit area (LMA) and leaf nitrogen content per unit area (Narea), and a smaller change in the nitrogen use efficiency of photosynthesis (PNUE) for lowland taxa indicated that these maintained higher homeostasis of photosynthesis than alpine taxa. The higher respiration rates produced more energy for repair and maintenance biomass, especially for higher photosynthetic activity for lowland taxa, which causes lower respiratory acclimation. Thus, the changes of ΔD2H for alpine spruces were larger than that for lowland spruces. These results indicate that long term heat stress negatively impact on the growth of Picea seedlings, and alpine taxa are more affected than low altitude ones by high temperature stress. Hence the altitude ranges of Picea taxa should be taken into account when predicting changes to carbon fluxes in warmer conditions

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant 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.Peer reviewe

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

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