18 research outputs found

    BioTIME: A Database of Biodiversity Time Series for the Anthropocene

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    Motivation: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. Main types of variables included: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. Spatial location and grain: BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km(2) (158 cm(2)) to 100 km(2) (1,000,000,000,000 cm(2)). Time period and grainBio: TIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. Major taxa and level of measurement: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates

    Stabilization versus decomposition in alpine ecosystems of the Northwestern Caucasus: The results of a tea bag burial experiment

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    Mountainous areas exhibit highly variable decomposition rates as a result of strong local differences in climate and vegetation type. This paper describes the effect of these factors on two major determinants of the local carbon cycle: litter decomposition and carbon stabilization. In order to adequately reflect local heterogeneity, we have sampled 12 typical plant communities of the Russian Caucasus. In order to minimize confounding effects and encourage comparative studies, we have adapted the widely used tea bag index (TBI) that is typically used in areas with low decomposition. By incubating standardized tea litter for a year, we investigated whether (1) initial litter decomposition rate (k) is negatively correlated with litter stabilization (S) and (2) whether k or S exhibit correlations with altitude and other environmental conditions. Our results show that S and k are not correlated. Altitude, pH, and water content significantly influenced the stabilization factor S, while soil-freezing had no influence. In contrast, none of these factors predicted the decomposition rate k. Based on our data, we argue that collection of decomposition rates alone, as is now common practice, is not sufficient to understand carbon input to soils and can potentially lead to misleading results. Our data on community-specific decomposition and stabilization rates further constrain estimates of litter accumulation in subalpine communities and the potential effects of climate change

    Stabilization versus decomposition in alpine ecosystems of the Northwestern Caucasus : The results of a tea bag burial experiment

    No full text
    Mountainous areas exhibit highly variable decomposition rates as a result of strong local differences in climate and vegetation type. This paper describes the effect of these factors on two major determinants of the local carbon cycle: litter decomposition and carbon stabilization. In order to adequately reflect local heterogeneity, we have sampled 12 typical plant communities of the Russian Caucasus. In order to minimize confounding effects and encourage comparative studies, we have adapted the widely used tea bag index (TBI) that is typically used in areas with low decomposition. By incubating standardized tea litter for a year, we investigated whether (1) initial litter decomposition rate (k) is negatively correlated with litter stabilization (S) and (2) whether k or S exhibit correlations with altitude and other environmental conditions. Our results show that S and k are not correlated. Altitude, pH, and water content significantly influenced the stabilization factor S, while soil-freezing had no influence. In contrast, none of these factors predicted the decomposition rate k. Based on our data, we argue that collection of decomposition rates alone, as is now common practice, is not sufficient to understand carbon input to soils and can potentially lead to misleading results. Our data on community-specific decomposition and stabilization rates further constrain estimates of litter accumulation in subalpine communities and the potential effects of climate change

    Quantitative assessment of the differential impacts of arbuscular and ectomycorrhiza on soil carbon cycling

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    A significant fraction of carbon stored in the Earth's soil moves through arbuscular mycorrhiza (AM) and ectomycorrhiza (EM). The impacts of AM and EM on the soil carbon budget are poorly understood. We propose a method to quantify the mycorrhizal contribution to carbon cycling, explicitly accounting for the abundance of plant-associated and extraradical mycorrhizal mycelium. We discuss the need to acquire additional data to use our method, and present our new global database holding information on plant species-by-site intensity of root colonization by mycorrhizas. We demonstrate that the degree of mycorrhizal fungal colonization has globally consistent patterns across plant species. This suggests that the level of plant species-specific root colonization can be used as a plant trait. To exemplify our method, we assessed the differential impacts of AM : EM ratio and EM shrub encroachment on carbon stocks in sub-arctic tundra. AM and EM affect tundra carbon stocks at different magnitudes, and via partly distinct dominant pathways: via extraradical mycelium (both EM and AM) and via mycorrhizal impacts on above- and belowground biomass carbon (mostly AM). Our method provides a powerful tool for the quantitative assessment of mycorrhizal impact on local and global carbon cycling processes, paving the way towards an improved understanding of the role of mycorrhizas in the Earth's carbon cycle

    Quantitative assessment of the differential impacts of arbuscular and ectomycorrhiza on soil carbon cycling

    Get PDF
    A significant fraction of carbon stored in the Earth's soil moves through arbuscular mycorrhiza (AM) and ectomycorrhiza (EM). The impacts of AM and EM on the soil carbon budget are poorly understood. We propose a method to quantify the mycorrhizal contribution to carbon cycling, explicitly accounting for the abundance of plant-associated and extraradical mycorrhizal mycelium. We discuss the need to acquire additional data to use our method, and present our new global database holding information on plant species-by-site intensity of root colonization by mycorrhizas. We demonstrate that the degree of mycorrhizal fungal colonization has globally consistent patterns across plant species. This suggests that the level of plant species-specific root colonization can be used as a plant trait. To exemplify our method, we assessed the differential impacts of AM : EM ratio and EM shrub encroachment on carbon stocks in sub-arctic tundra. AM and EM affect tundra carbon stocks at different magnitudes, and via partly distinct dominant pathways: via extraradical mycelium (both EM and AM) and via mycorrhizal impacts on above- and belowground biomass carbon (mostly AM). Our method provides a powerful tool for the quantitative assessment of mycorrhizal impact on local and global carbon cycling processes, paving the way towards an improved understanding of the role of mycorrhizas in the Earth's carbon cycle

    Do patterns of intra-specific variability and community weighted-means of leaf traits correspond? An example from alpine plants

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    Intraspecific variability of the traits is usually less than interspecific, but directions of inter-and intraspecific variation along environmental gradients are not well studied. For 17 alpine species we test a hypothesis that the direction of intraspecific variation in leaf traits among different communities along an environmental gradient coincides consistently with community weighted mean (CWM) trait variation at the community level along the same gradient. We obtained two groups of leaf traits according to their response to CWM and topographic (snow depth and snow melt) gradients. For leaf mass and area intraspecific variation corresponded to CWM variation among communities. SLA, water content and leaf thickness patterns within species changed directly among communities according to the toposequence (snowmelt gradient). These results are well expressed for forbs, but mostly they were not significant for graminoids. For leaf area we obtained opposite response of forbs and graminoids to snowmelt gradient. Forbs increased, but graminoids decreased leaf area when snow depth increased. Intraspecific trait variation across natural gradients does not necessarily follow that for interspecific or community-level variation

    BioTIME: A Database of Biodiversity Time Series for the Anthropocene

    No full text
    Motivation: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community‐led open‐source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. Main types of variables included: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. Spatial location and grain: BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2). Time period and grain: BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. Major taxa and level of measurement: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates. Software format: .csv and .SQL
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