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    Temperature and salinity preferences of endangered Delta Smelt (Hypomesus transpacificus, Actinopterygii, Osmeridae)

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    Author Correction: Protect European green agricultural policies for future food security

    Departamento de Ecología, Universidad Autónoma de Madrid, Madrid, SpainManuel B. Morales & Juan TrabaCentro de Investigación en Biodiversidad y Cambio Global, Universidad Autónoma de Madrid, Madrid, SpainManuel B. Morales, Juan Traba & Elena D. ConcepciónMuseo Nacional de Ciencias Naturales, CSIC, Madrid, SpainMario Díaz & Elena D. ConcepciónConservation Biology Group, Landscape Dynamics and Biodiversity Program, Conservation Biology Group (GBiC), Forest Science and Technology Centre of Catalonia (CTFC), Solsona, SpainDavid Giralt, Francesc Sardà-Palomera & Gerard BotaInstituto de Investigación en Recursos Cinegéticos (CSIC-UCLM-JCCM), Ciudad Real, SpainFrançois Mougeot & Beatriz ArroyoEstación Biológica de Doñana, CSIC, Sevilla, SpainDavid SerranoDepartament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia, Universitat de Barcelona, Barcelona, SpainSanti MañosaInstitut de Recerca de la Biodiversitat (IRBio), Universitat de Barcelona, Barcelona, SpainSanti MañosaUSC 1339 Centre d’Etudes Biologiques de Chizé, INRAE, CNRS & Université de La Rochelle, F-79360, Villiers-en-Bois, FranceSabrina GabaUMR 7372 Centre d’Etudes Biologiques de Chizé, CNRS & Université de La Rochelle, F-79360, Villiers-en-Bois, FranceSabrina GabaCIBIO/InBio–University of Porto and Institute of Agronomy–University of Lisbon, Lisbon, PortugalFrancisco MoreiraSwedish University of Agricultural Sciences, Uppsala, SwedenTomas PärtSustainable Forest Management Research Institute (iuFOR), Universidad de Valladolid & INIA, Valladolid, SpainRocío Tarjuelo More

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    A tripartite model system for Southern Ocean diatom-bacterial interactions reveals the coexistence of competing symbiotic strategies

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    Ancient marine sediment DNA reveals diatom transition in Antarctica

    Sampling location and sediment coringSamples were collected during IODP Exp. 382 ‘Iceberg Alley and Subantarctic Ice and Ocean Dynamics’ on-board RV Joides Resolution between 20 March and 20 May 2019. Specifically, we collected samples at Site U1534 (Falkland Plateau, 606 m water depth), U1536 (Dove Basin, Scotia Sea, 3220 m water depth), and Site U1538 (Pirie Basin, Scotia Sea, 3130 m water depth) (Fig. 1). Site U1534 is located at the Subantarctic Front on a contourite drift at the northern limit of the Scotia Sea. This setting is ideal to study the poorly understood role of Antarctic Intermediate Water (AAIC) and its impact on the Atlantic Meridional Overturning Circulation (AMOC) along the so-called ‘cold water route’ that connects to the Pacific Ocean through the Drake Passage, as opposed to the ‘warm water route’ that connects to the Indian Ocean via the Agulhas Current42. Sites U1536 and U1538 are located in the southern and central Scotia Sea, respectively, and were drilled to study the Neogene flux of icebergs through ‘Iceberg Alley’, the main pathway along which icebergs calved from the margin of the AIS travel as they move equatorward into the warmer waters of the Antarctic Circumpolar Current (ACC)23. sedaDNA samples collected at Site U1534 were from Hole C, at Site U1536 from Hole B, and at Site U1538 from Holes C and D (Table 1), and in the following we refer to site names only. IODP Expedition proposals undergo a rigorous environmental protection and safety review, which is approved by the IODP’s Environmental Protection and Safety Panel (EPSP) and/or the Safety Panel. The same procedure was applied to IODP Exp. 382 and approval was provided by the EPSP. Sediment samples for sedaDNA analyses were imported to Australia under Import Permit number 0002658554 provided by the Australian Government Department for Agriculture and Water Resources (date of issue: 19 September 2018), and were stored and extracted at a quarantine approved facility (AA Site No. S1253, Australian Centre for Ancient DNA). No ethical approval was required for this study.Table 1 Sampling location and sample detailsFull size tableSample age determinationAge control for Site U1534 is based on tuning of benthic foraminifera δ18O to the LR04 stack43. Wherever present specimens of Uvigerina bifurcata were picked from samples at 10 cm intervals. During warmer periods when U. bifurcata was not present, Melonis affinis and/or Hoeglundina elegans were analysed. Sedimentation rates over the intervals sampled for sedaDNA typically range between 6 and 30 cm/kyr, with rates exceeding 100 cm/kyr during the Last Glacial Maximum ~20,000 years ago (20 ka). For our deepest sample, U1534C-10H-6_115cm (90.95 mbsf), we only have biostratigraphically assigned ages available (shipboard data), which date this sample as early Pleistocene (~2.5–0.7 million years ago, Ma44).Low-resolution age control for both Sites U1536 and U1538 was established using shipboard magneto- and biostratigraphy21,23. Average sedimentation rates are ~10 cm/kyr for Site U1536, with elevated values (up to 20 cm/kyr) in the upper ~80 mbsf (the last ~400 ka). Site U1538 average sedimentation rates are twice as high, averaging ~20 cm/kyr. Especially in the upper ~430 mbsf (the last 1.8 Ma), rates are up to 40 cm/kyr. Higher resolution age models are based on dust climate couplings, correlating sedimentary dust proxy records such as magnetic susceptibility and sedimentary Ca and Fe records to ice-core dust proxy records over the last 800 ka45 and to a benthic isotopic stack26 before that. These age models were established for Site U1537 (adjacent to Site U1536) and provide orbital to millennial scale resolution. For this study we correlated sedimentary cycles of Sites U1536 and U1538 to U1537 to achieve similar resolution and to be able to determine if a sample originates from a glacial or interglacial period (Table 1).Sampling of sedaDNAA detailed description of sedaDNA sampling methods can be found in ref. 24. In brief, we used advanced piston coring (APC) to acquire sediment cores, which recovers the least disturbed sediments46,47,48 and is thus the preferred technique for sedaDNA sampling. All samples were taken on the ship’s ‘catwalk’, where, once the core was on deck, the core liners were wiped clean twice (3% sodium hypochlorite, ‘bleach’) at each cutting point. Core cutting tools were sterilised before each cut (3% bleach and 80% ethanol) of the core in 1 m sections. The outer ~3 mm of surface material were removed from the bottom of each core section to be sampled, using sterilised scrapers (~4 cm wide; bleach and ethanol treated). A cylindrical sample was taken from the core centre using a sterile (autoclaved) 10 mL cut-tip syringe, providing ~5 cm3 of sediment material. The syringe was placed in a sterile plastic bag (Whirl-Pak) and immediately frozen at −80 °C. The mudline (sediment/seawater interface) was transferred from the core liner into a sterile bucket (3% bleach treated), and 10 mL sample was retained in a sterile 15 mL centrifuge tube (Falcon) and frozen at −80 °C. Samples were collected at various depth intervals depending on the site to span the Holocene up to ~1 million years (Table 1). This lower depth/age limit was determined by switching coring system from APC to the extended core barrel (XCB) system.To test for potential airborne contamination, at least one air control was taken during the sedaDNA sampling process per site. For this, an empty syringe was held for a few seconds in the sampling area and then transferred into a sterile plastic bag and frozen at −80 °C. The air controls were processed, sequenced and analysed alongside the sediment samples.Contamination control using perfluoromethyldecalin tracersAs part of the APC process, drill fluid (basically, seawater) is pumped into the borehole to trigger the hydraulic coring system, therefore, the potential for contamination exists due to drill fluid making contact with the core liner. To assess the latter, we added the non-toxic chemical tracer perfluoromethyldecalin (PFMD) to the drill fluid at a rate of ~0.55 mL min−1 for cores collected at Sites U1534 and U153649. As we found that PFMD concentrations were very low at these sites (Results section), the infusion rate was doubled prior to sedaDNA sampling at Site U1538 to ensure low PFMD concentrations represent low contamination and not delivery failure of PFMD to the core. At each sedaDNA sampling depth, one PFMD sample was taken from the periphery of the core (prior to scraping, to test whether drill fluid reached the core pipe), and one next to the sedaDNA sample in the centre of the core (after scraping, to minimise differences to the sedaDNA sample, and testing if drill fluid had reached the core centre). We transferred ~3 cm3 of sediment using a disposable, autoclaved 5 mL cut-tip syringe into a 20 mL headspace vial with metal caps and Teflon seals. We also collected a sample of the tracer-infused drill fluid at each site, by transferring ~10 mL of the fluid collected at the injection pipe on the rig floor via a sterile plastic bottle into a 15 mL centrifuge tube (inside a sterile plastic bag) and freezing it at −80 °C. These drill fluid controls were processed and analysed in the same way as the sedaDNA samples including sequencing. Samples were analysed using gas chromatography (GC-µECD; Hewlett-Packard 6890).A detailed description of the PFMD GC measurements is provided in ref. 24. Briefly, PFMD measurements were undertaken in batches per site for U1534, U1536 and U1538. This included the analyses of PFMD samples collected at two additional holes at these sites, U1534D and U1536C, from which we also collected sedaDNA samples but that are not part of this study. PFMD is categorised as the stereoisomers of PFMD (C11F20), which add up to 87-88% (and with the remaining 12% being additional perfluoro compounds unable to be separated by the manufacturer). We exclusively refer to the first and measurable PFMD category, calibrating for the 88% in bottle concentrations during concentration calculations. Each GC analysis run included the measurement of duplicate blanks and duplicate PFMD standards. Due to a large sample number, PFMD at Site U1538 was measured in three separate runs, with the first and last run including triplicate blank and triplicate PFMD standards (duplicates in the second run), and the last run also containing a drill-fluid sample. To blank-correct PFMD concentrations, we subtracted the average PFMD concentration of all blanks per run from PFMD measurements in that run. To determine the detection limit of PFMD, we used three times the standard deviation of the average blank PFMD values per run; due to all blank values for the U1538 runs being 0, we used three times the standard deviation of the lowest PFMD standard for this site in this calculation. This provided us with a PFMD detection limit of 0.2338 ng mL−1. Any PFMD measurements of samples below this limit were rejected.
    sedaDNA extractions and metagenomic library preparationsA total of 80 sedaDNA extracts and metagenomic shotgun libraries (Table 1) were prepared following8,10. For the sedaDNA extractions, we randomised our samples and controls and extracted sedaDNA in batches of 16 extracts/libraries at a time, with each batch including at least one air control and one extraction blank control (EBC), and the last batch including mudline and PFMD samples to avoid contamination of the sedaDNA samples. In brief, we used 20 µL sedaDNA extracts in a repair reaction (using T4 DNA polymerase, New England Biolabs, USA; 15 min, 25 °C), then purified the sedaDNA (MinElute Reaction Cleanup Kit, Qiagen, Germany), ligated adaptors (T4 DNA ligase, Fermentas, USA, where truncated Illumina-adaptor sequences containing two unique 7 base-pair (bp) barcodes were attached to the double-stranded DNA; 60 min, 22 °C), purified the sedaDNA again (MinElute Reaction Cleanup Kit, Qiagen), and then added a fill-in reaction with adaptor sequences (Bst DNA polymerase, New England Biolabs, USA; 30 min, 37 °C, with polymerase deactivation for 10 min, 80 °C). We amplified the barcoded libraries using IS7/IS8 primers50 (8 replicates per sample, where each replicate was a 25 µL reaction containing 3 µL DNA template; using 22 cycles), purified (AxyPrep magnetic beads, Axygen Biosciences, USA; 1:1.8 library:beads) and quantified them (Qubit dsDNA HS Assay, Invitrogen, Molecular Probes, USA). We amplified the libraries (8 replicates per sample, 13 amplification cycles) using IS4 and GAII Indexing Primers50, purified (AxyPrep magnetic beads, at a ratio of 1:1.1 library:beads), quantified and quality-checked using Qubit (dsDNA HS Assay, Invitrogen, USA) and TapeStation (Agilent Technologies, USA). We combined the libraries into an equimolar pool (volume of 68 µL in total), diluted this pool with nuclease-free H2O to 100 µL, and performed a ‘reverse’ AxyPrep clean-up to retain only the small DNA fragments typical for ancient DNA (≤ 500 bp; initial library:beads ratio of 1:0.6, followed by 1:1.1, and double-eluted in 30 µL nuclease-free H2O8,51). We added one more AxyPrep clean-up to remove primer-dimer (library:beads ratio of 1:1.05) and checked sedaDNA quantity and quality via TapeStation and qPCR (QuantStudio, Applied Biosystems, USA). The libraries sequenced at the Garvan Institute for Medical Research, Sydney, Australia (Illumina NovaSeq 2 × 100 bp).
    sedaDNA data processingThe sequencing data was processed and filtered as described in detail in refs. 8, 10. Briefly, data filtering involved the removal of sequences More

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    Revealing the uncharacterised diversity of amphibian and reptile viruses

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    Device for automatic measurement of light pollution of the night sky

    For several years, systematic research has been carried out on the pollution of the night sky by artificial light in the city of Toruń11,36,38. The main objective is to monitor this phenomenon, including its spatial and temporal variability and the most important factors affecting it. Based on previous experience, an in-house measurement device was constructed to automate the process of data acquisition.Genesis of the projectThe first measurements pertaining to the phenomenon of night sky pollution in Toruń were made in autumn 2017, followed by regular observations using a handheld SQM photometer (Unihedron, Canada) as part of a project implemented in 2017–2018. To this end, a permanent measurement network distributed throughout the city was established, consisting of 24 locations. During a one night measurement session taking place during the astronomical night (there is no such period at the latitude of Toruń in the summer), sky brightness was measured at all sites. The results of spot monitoring were plotted using interpolation methods and visualisation tools available in GIS systems11,39, which helped to determine the spatial distribution and extent of night sky light pollution. The intensity of this phenomenon at each of the surveyed points was also explored in relation to the distinguished landcover categories and types of urban development.Repeatable measurements performed regularly over such a long period of time were characterised by significant limitations. One measurement session was very time-consuming, as it lasted about two hours, during which time all measurement locations were visited, covering a distance of almost 50 km each night by car. Despite the observance of all time frames and sticking to the plan of fieldwork, measurements were not carried out simultaneously at all the locations, which affected the results, especially during the night with changing cloud cover. Although the measurements were carried out with great consistency and care, they were performed in a spatial buffer of about 5 m, which could unintentionally slightly affect the obtained results. An additional limitation was also a one-time night measurement at one point, instead of a whole series of measurements at specific time intervals. Inaccuracies in the readings within a single session could have been caused by sudden changes in meteorological parameters. In the adopted procedure, it was not possible to carry out simultaneous measurements in identical time and weather conditions at all the locations, not to mention the involvement of the personnel in each tour of the measurement network points.Using the experience gained and after an analysis of the identified constraints and the technical capabilities at hand, work began in 2019 on developing a network for automatic remote monitoring of light pollution of the night sky in Toruń, based on designed in-house recording devices.Design, functional and utility features of the deviceTo enhance the research on light pollution in urban space, work has begun on the construction of a device that would perform automatic measurements, would be mobile, battery-powered and use long-range wireless communication. All the aforementioned features are in line with the strategy of Industry 4.0 and modern solutions proposed as part of the Smart City concept.The concept of Industry 4.0 assumes the more and more common use of process automation as well as the processing and exchange of data with the use of new transmission technologies26. LoRaWAN is one of the solutions used for communication of Internet of Things (IoT) devices, which supports the development of Smart Cities in the Smart Environment area. As a result, the interactivity, frequency, and scope of measurements carried out in urbanized areas are increased40,41.According to the developed project, the device was to serve as a meter of very low intensity light observed in the night sky. In this respect, it was necessary to use a sensor with technical parameters suitable for very accurate measurements of light intensity. To locally verify the weather conditions occurring during the operation of the device, it was decided to carry out additional simultaneous measurements of other environmental parameters—temperature and moisture content. The analysis of the spatial coverage of the study area indicated that 36 measurement devices should be deployed to provide full coverage of Toruń. The concept of creating an urban measurement network assumes the selection of points covering the whole city relatively evenly and representing different types of housing development and elements of land cover. It was assumed that measurements will be made only at night, between 21 p.m. and 6 a.m. on the following day, at 15 min intervals, and in addition, weather conditions will be recorded twice a day.Construction and technical parameters of the device, and selected characteristics of its componentsA prototype device meeting all the predefined functionalities was constructed based on available electronic modules. The B-L072Z-LRWAN Discovery developmental board from STMicroelectronics42 was selected as the main electronic component providing wireless communication. This board has an integrated LoRa communication module, enabling low-power wireless messaging, and also allows the board to enter a low-power state during hibernation, and thus target long-term battery-powered operation. This module is fully programmable, which enables future expansion of the set with other functionalities. The TSL2591 light sensor from AMS, which has high sensitivity and registration accuracy, was selected as a component implementing the light intensity measurement. Its great advantage is a wide measurement range of 188 μlx to 88 000 lx, sensitivity reaching 0.000377 lx, and a wide dynamic range (WDR) of 600 M:143. The sensor used has two diodes with different spectral properties. One of them registers visible light together with infrared (in the range from 400 to 1 100 nm), while the other is responsible for the registration of infrared light (between 500 and 1 100 nm). Thanks to this solution, we can use the results in various ways. The use of the formula provided by the manufacturer allows us to obtain spectral characteristics similar to the human eye. The presence of a compensating diode makes a difference compared to the sensor used in the SQM device, so the results obtained in the measurements may be slightly different.To measure additional environmental parameters, the X-NUCLEO-IKS01A2 development board from STMicroelectronics was used, which is connected to the STM32 microcontroller via the I2C interface44. This board enables the recording of a number of parameters, however, in the constructed device it is only responsible for reading the temperature and humidity of the environment. This results from the necessity to limit the size of the message packets sent, while at the same time improving the operating range and reducing the power consumption of the device.Once all the components had been selected, tested and integrated, the process of final connection and programming was carried out. The base of the device, i.e. the B-L072Z-LRWAN development board was connected to the X-NUCLEO-IKS01A2 environmental sensor board, using Arduino connectors. Using standard wires, a TSL2591 light sensor was added by connecting the corresponding I2C (SCL and SDA), power supply (VIN), sensor ground (GND) pins and the X-NUCLEO-IKS01A2 board.All components used were placed in a standard external casing with dimensions of 8.0 × 5.4 × 15.8 cm. In its lower part an opening was made for an external antenna, while in the upper part a specifically selected opening was cut out, protected with a glass pane, through which measurements are performed by the light sensor (Fig. 2).Figure 2(photo by Dominika Karpińska).Constructed device viewFull size imageFollowing the above steps, an automatic device was constructed to record light intensity in the lower troposphere, i.e. to measure the pollution of the night sky by artificial light coming from the Earth’s surface. Selected technical parameters of the device are presented in Table 1.Table 1 Selected technical parameters of the device for measuring light pollution of the night sky.Full size tableFlowchart of the system operationAfter constructing the device and writing the control software, the construction of the entire measurement system was started. Each of the measuring instruments is ultimately connected to the communication gateway using LoRa technology. A MultiTech communication gateway with a LoRaWAN module was used as an access device. To successfully connect the gateway to the measuring device, it was necessary to configure the communication gateway software. To this end, the information about the unique device number (Dev EUI) and the application key and its number (App EUI and App Key) was used. Once the unit is configured, it is possible to send data to the communication gateway and read them using NodeRED, a programming tool where data are redirected to a selected server, which stores all measurement results. Figure 3 shows a schematic representation of the constructed measurement system.Figure 3Schematic diagram of the measurement system.Full size image More

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    Wolf risk fails to inspire fear in two mesocarnivores suggesting facilitation prevails

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