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Atmospheric methane (CH4) is a potent greenhouse gas, and its mole fraction has more than doubled since the preindustrial era. Fossil fuel extraction and use are among the largest anthropogenic sources of CH4 emissions, but the precise magnitude of these contributions is a subject of debate. Carbon-14 in CH4 (14CH4) can be used to distinguish between fossil (14C-free) CH4 emissions and contemporaneous biogenic sources; however, poorly constrained direct 14CH4 emissions from nuclear reactors have complicated this approach since the middle of the 20th century. Moreover, the partitioning of total fossil CH4 emissions (presently 172 to 195 teragrams CH4 per year) between anthropogenic and natural geological sources (such as seeps and mud volcanoes) is under debate; emission inventories suggest that the latter account for about 40 to 60 teragrams CH4 per year. Geological emissions were less than 15.4 teragrams CH4 per year at the end of the Pleistocene, about 11,600 years ago, but that period is an imperfect analogue for present-day emissions owing to the large terrestrial ice sheet cover, lower sea level and extensive permafrost. Here we use preindustrial-era ice core 14CH4 measurements to show that natural geological CH4 emissions to the atmosphere were about 1.6 teragrams CH4 per year, with a maximum of 5.4 teragrams CH4 per year (95 per cent confidence limit)—an order of magnitude lower than the currently used estimates. This result indicates that anthropogenic fossil CH4 emissions are underestimated by about 38 to 58 teragrams CH4 per year, or about 25 to 40 per cent of recent estimates. Our record highlights the human impact on the atmosphere and climate, provides a firm target for inventories of the global CH4 budget, and will help to inform strategies for targeted emission reductions.

Analyses of ancient food webs reveal important paleoecological processes and responses to a range of perturbations throughout Earth’s history, such as climate change. These responses can inform our forecasts of future biotic responses to similar perturbations. However, previous analyses of ancient food webs rarely accounted for key differences between modern and ancient community data, particularly selective loss of soft-bodied taxa during fossilization. To consider how fossilization impacts inferences of ancient community structure we (1) analyzed node-level attributes to identify correlations between ecological roles and fossilization potential and (2) applied selective information loss procedures to food web data for extant systems. We found that selective loss of soft-bodied organisms has predictable effects on the trophic structure of “artificially fossilized” food webs, because these organisms occupy unique, consistent food web positions. Fossilized food webs misleadingly appear less stable (i.e., more prone to trophic cascades), with less predation and an overrepresentation of generalist consumers. We also found that ecological differences between soft- and hard-bodied taxa—indicated by distinct positions in modern food webs—are recorded in an Early Eocene web, but not in Cambrian webs. This suggests that ecological differences between the groups have existed for ≥ 48 million years. Our results indicate that accounting for soft-bodied taxa is vital for accurate depictions of ancient food webs. However, the consistency of information loss trends across the analyzed food webs means it is possible to predict how the selective loss of soft-bodied taxa affects food web metrics, which can permit better modeling of ancient communities. Repository Contents: Supplementary Information: Containing Supplementary Text, Figures, Tables, and Data descriptions. Supplementary Data 1: Food web data (adjacency matrices and metadata; see publication; see Related Works). Supplementary Data 2: Additional references consulted for preservation group assignments. Supplementary Data 3: Data and R scripts to recreate analyses from this study. S3_AllWebTaxonomy_updated_200903.csv: Taxonomy data for all food web nodes. S3_AnalysisOfTaxonomicRanks.csv: Lowest taxonomic rank for each node. S3_MainFigures_CaimanComparison.R: Compare the three food webs contained in (Roopnarine and Hertog 2013). S3_MainFigures_ComparisonFunctions.R: Functions for calculating metrics and generating trophic species webs. S3_MainFigures_FossilizationFunctions.R: Functions for artificially fossilizing networks. S3_MainFigures_Setup_200826.R: Setup to import food webs. S3_MainFigures_Code.R: Code to apply functions. S3_pbdb_data_200504.csv: Data from the Paleobiology Database, excluding Lagerstätten (see publication). S3_PresGrAssignments_updated_200902.csv: Preservation group assignments for all nodes. Fossil faunal lists were downloaded from the PBDB on 17th January 2020. Any data processing steps are shown in R Scripts and described in publication. Paleobiology Database is licensed under a CC BY 4.0 International License. https://creativecommons.org/licenses/by/4.0/. We analyzed food webs for four modern marine systems, one modern freshwater system, two ancient marine systems, and one ancient lake system from previous publications. All webs have similar, broad higher-rank taxonomic compositions and contain at least 85 nodes (the size of the smallest ancient network considered). For comparisons with ancient diversity, we downloaded fossil occurrences from the Paleobiology Database (PBDB) on 17th January 2020. 

The detected variety in chemistry and circumstellar shell morphology of the limited sample of Galactic post-AGB stars is so large that there is no consensus yet on how the different objects are linked by evolutionary channels. The evaluation is complicated by the fact that their distances and hence luminosities remain largely unknown. Via cross-correlation of the Spitzer SAGE catalogue with optical catalogues we selected a sample of LMC post-AGB candidates based on their [8]-[24] colour index and estimated luminosity. We determined the fundamental properties of the central stars of 105 of these objects using low-resolution, optical spectra that we obtained at Siding Spring Observatory and SAAO, and constructed a catalogue of 70 high probability and 1337 candidate post-AGB stars that is available at the CDS. The sample forms an ideal testbed for stellar evolution theory predictions of the final phase of low- and intermediate-mass stars, because the distance and hence luminosity and also the current and initial mass of these objects is well constrained. About half of the objects in our sample of post-AGB candidates show a spectral energy distribution (SED) that is indicative of a disc rather than an expanding and cooling AGB remnant. Like in the Galaxy, the disc sources are likely associated with binary evolution. Important side products of this research are catalogues of candidate young stellar objects, candidate supergiants with circumstellar dust, and discarded objects for which a spectrum was obtained. These too are available at the CDS.

Symmetric flow cell cycling of a soluble phenothiazine.

Abstract. This paper aims to assess the spatial variability in the response of CO2 exchange to irradiance across the Arctic tundra during peak season using light response curve (LRC) parameters. This investigation allows us to better understand the future response of Arctic tundra under climatic change. Peak season data were collected during different years (between 1998 and 2010) using the micrometeorological eddy covariance technique from 12 circumpolar Arctic tundra sites, in the range of 64–74° N. The LRCs were generated for 14 days with peak net ecosystem exchange (NEE) using an NEE–irradiance model. Parameters from LRCs represent site-specific traits and characteristics describing the following: (a) NEE at light saturation (Fcsat), (b) dark respiration (Rd), (c) light use efficiency (α), (d) NEE when light is at 1000 μmol m−2 s−1 (Fc1000), (e) potential photosynthesis at light saturation (Psat) and (f) the light compensation point (LCP). Parameterization of LRCs was successful in predicting CO2 flux dynamics across the Arctic tundra. We did not find any trends in LRC parameters across the whole Arctic tundra but there were indications for temperature and latitudinal differences within sub-regions like Russia and Greenland. Together, leaf area index (LAI) and July temperature had a high explanatory power of the variance in assimilation parameters (Fcsat, Fc1000 and Psat, thus illustrating the potential for upscaling CO2 exchange for the whole Arctic tundra. Dark respiration was more variable and less correlated to environmental drivers than were assimilation parameters. This indicates the inherent need to include other parameters such as nutrient availability, substrate quantity and quality in flux monitoring activities.

AbstractIndirect climate effects on tree fecundity that come through variation in size and growth (climate-condition interactions) are not currently part of models used to predict future forests. Trends in species abundances predicted from meta-analyses and species distribution models will be misleading if they depend on the conditions of individuals. Here we find from a synthesis of tree species in North America that climate-condition interactions dominate responses through two pathways, i) effects of growth that depend on climate, and ii) effects of climate that depend on tree size. Because tree fecundity first increases and then declines with size, climate change that stimulates growth promotes a shift of small trees to more fecund sizes, but the opposite can be true for large sizes. Change the depresses growth also affects fecundity. We find a biogeographic divide, with these interactions reducing fecundity in the West and increasing it in the East. Continental-scale responses of these forests are thus driven largely by indirect effects, recommending management for climate change that considers multiple demographic rates.