28 research outputs found

    Growth rates of interface-feeding spionid polychaetes in simulated tidal currents

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    Most spionid polychaetes switch from surface deposit feeding to suspension feeding as current speed and the flux of suspended food increase. Previous experiments testing the effects of flow on the growth of facultative, interface feeders have been limited to very simplified flow regimes such as constant, unidirectional currents. To measure the growth of interface-feeding spionids in more realistic currents, we programmed two identical counter-rotating annular flumes to simulate two different semidiurnal tidal currents. Each regime included four speeds that varied in hourly steps. At 5 mm above bottom, speeds in the slower flow regime were 0, 2.5, 5, and 7.5 cm s−1. Speeds in the faster regime were 0, 4, 8, and 12 cm s−11. Every 6 h, after each hour at 0 cm s−11, the flume rotation was reversed to simulate the directional shift between ebb and flood currents. The 12-h periods were repeated over 96 h. The experiment included eight 4-d runs of paired slow- and fast-flow flumes. Field-collected sediment and a nonliving algal slurry were added to control deposited and suspended food. Individuals of four species were measured for body volumes before and after each 4-d run: Polydora cornuta, Streblospio benedicti, Pygospio elegans, and Spio setosa. Each species except S. setosa was divided a priori into two size classes. Both small and large P. cornuta grew significantly faster in the fast-flow regime. Large P. elegans grew significantly faster in the fast-flow regime, but the growth rates of small P. elegans did not differ between regimes. Neither size class of S. benedicti grew at significantly different rates between flow regimes, and the broad size class of S. setosa did not show significant flow-dependent growth. The significant growth responses of two of the four species to moderate differences in tidal flow over a short time period underscore the impact flow can have on the population dynamics of some interface-feeding spionids. The differences among species suggest that variability in tidal currents can influence the structure and dynamics of communities in which spionids are often important and abundant

    TRY plant trait database – enhanced coverage and open access

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    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

    Author correction : roadmap for naming uncultivated archaea and bacteria

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    Correction to: Nature Microbiology https://doi.org/10.1038/s41564-020-0733-x , published online 8 June 2020. In the version of this Consensus Statement originally published, Pablo Yarza was mistakenly not included in the author list. Also, in Supplementary Table 1, Alexander Jaffe was missing from the list of endorsees. These errors have now been corrected and the updated Supplementary Table 1 is available online

    Roadmap for naming uncultivated Archaea and Bacteria

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    The assembly of single-amplified genomes (SAGs) and metagenome-assembled genomes (MAGs) has led to a surge in genome-based discoveries of members affiliated with Archaea and Bacteria, bringing with it a need to develop guidelines for nomenclature of uncultivated microorganisms. The International Code of Nomenclature of Prokaryotes (ICNP) only recognizes cultures as ‘type material’, thereby preventing the naming of uncultivated organisms. In this Consensus Statement, we propose two potential paths to solve this nomenclatural conundrum. One option is the adoption of previously proposed modifications to the ICNP to recognize DNA sequences as acceptable type material; the other option creates a nomenclatural code for uncultivated Archaea and Bacteria that could eventually be merged with the ICNP in the future. Regardless of the path taken, we believe that action is needed now within the scientific community to develop consistent rules for nomenclature of uncultivated taxa in order to provide clarity and stability, and to effectively communicate microbial diversity

    Long-Term Sorption of Metals Is Similar among Plastic Types: Implications for Plastic Debris in Aquatic Environments

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    <div><p>Concerns regarding plastic debris and its ability to accumulate large concentrations of priority pollutants in the aquatic environment led us to quantify relationships between different types of mass-produced plastic and metals in seawater. At three locations in San Diego Bay, we measured the accumulation of nine targeted metals (aluminum, chromium, manganese, iron, cobalt, nickel, zinc, cadmium and lead) sampling at 1, 3, 6, 9 and 12 months, to five plastic types: polyethylene terephthalate (PET), high-density polyethylene (HDPE), polyvinyl chloride (PVC), low-density polyethylene (LDPE), and polypropylene (PP). Accumulation patterns were not consistent over space and time, and in general all types of plastic tended to accumulate similar concentrations of metals. When we did observe significant differences among concentrations of metals at a single sampling period or location in San Diego Bay, we found that HDPE typically accumulated lesser concentrations of metals than the other four polymers. Furthermore, over the 12-month study period, concentrations of all metals increased over time, and chromium, manganese, cobalt, nickel, zinc and lead did not reach saturation on at least one plastic type during the entire 12-month exposure. This suggests that plastic debris may accumulate greater concentrations of metals the longer it remains at sea. Overall, our work shows that a complex mixture of metals, including those listed as priority pollutants by the US EPA (Cd, Ni, Zn and Pb), can be found on plastic debris composed of various plastic types.</p></div

    Map of San Diego Bay.

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    <p>The map shows the three study locations: Coronado Cays, Shelter Island and Nimitz Marine Facility. Figure generated with ArcGIS version 9.3.</p

    Concentrations of Mn, Co, Ni, Zn and Cd over time.

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    <p>Concentrations of Mn, Co, Ni, Zn and Cd (ng/g of pellets) vs time for each type of plastic at Coronado Cays (CC) where contamination was greatest. Rows represent plastic types PET, HDPE, PVC, LDPE and PP (in order from top to bottom). Columns represent metals ordered from left to right according to molecular weight. Note that vertical axes differ among graphs. Data were fit to the first-order approach to equilibrium model <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0085433#pone.0085433-Mato1" target="_blank">[26]</a> using the exponential rise to maximum equation C<sub>t</sub>  =  C<sub>eq</sub> (1 − e<sup>−kt</sup>), where C<sub>t</sub> is the concentration at time t, C<sub>eq</sub> is the predicted equilibrium concentration, and k is the rate constant. The horizontal dotted line denotes the predicted C<sub>eq</sub> for each plastic type. Where no equation is given, the model could not be fit to the data and where no horizontal line is given the non-linear regression was not statistically significant (p>0.05).</p
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