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  • Authors: Crowther, Claudia; Adams, Clare; Fondren, Andy; Janzen, Fredric;

    # Adult sex-ratio bias does not lead to detectable adaptive offspring sex allocation via nest-site choice in a turtle with temperature-dependent sex determination [https://doi.org/10.5061/dryad.vt4b8gv20](https://doi.org/10.5061/dryad.vt4b8gv20) ## Description of the data and file structure Data and code required to reproduce the analyses in "Adult sex-ratio bias does not lead to detectable adaptive offspring sex allocation via nest-site choice in a turtle with temperature-dependent sex determination" Data was collected to compare the nesting behaviour (timing, depth, and shade cover) of painted turtles (*Chrysemys picta*) in three outdoor enclosures with experimentally manipulated adult sex ratios (ASR). The purpose of the experiment was to ascertain whether species with temperature-dependent sex determination (TSD, incubation temperature determines the sex of embryos) could adaptively manipulate offspring sex via nest-site choice in response to the ASR. ### Files and variables #### File: ASR\_Data\_Crowther\_2023.csv **Description:** csv file containing nest characteristics for all the nests laid in the experimental enclosures. Missing values are indicated by "NA" (not available). ##### Variables * Date: The date that the nest was laid, format: M/DD/YYYY. * Jdate: The day of the year that the nest was laid (e.g. Jdate 152 = the 31st of May). * Pond: The letter identifier for the experimental pond that the nest was laid in. The adult sex ratio of the ponds varied, B = male-biased, C = equal sex ratio, and D = female-biased. * MomID: The unique identifier for the mother that laid the nest. * SCL: The straight carapace (dorsal side of the shell) length of the mother in millimeters. * NestDepthCM: The depth of the nest in centimeters. * HemiPhoto: The file name of the hemispherical canopy cover photo. * SexRatio: The proportion male offspring in the clutch associated with the nest (hatchlings were incubated in a laboratory environment). NA values for this variable indicate that the data is not available because we did not determine the sex of hatchlings in those clutches. * Clutch.Size: The number of eggs in the clutch. * Clutch.no: The order the mother laid the clutch, 1 = mother's 1st clutch in season, 2 = mother's second clutch. * SW.Open: The percentage of sky area over the South West half of the nest not covered by vegetation or other shade. ### **File Folder: Nest Photos** **Description:** Hemispherical photographs of the sky area above nests, used to calculate nest canopy cover. The nests were photographed using a Nikon Coolpix S3600 camera equipped with a Zykkor fish eye lens (0.2x180°). The photographs are stored in a .jpeg format. Nest photographs are linked to the corresponding nest data by their file name, which is recorded in the 'HemiPhoto' column of ASR_Data_Crowther_2023.csv ## Code/software #### Nest\_trait\_analysis\_V3.R ##### Description: An R file containing code to repeat the analyses presented in '*Adult sex-ratio bias does not lead to detectable adaptive offspring sex allocation via nest-site choice in a turtle with temperature-dependent sex determination*' a manuscript submitted to Ecology and Evolution. The script also contains code for publication and supplementary graphs. The script requires the data file 'ASR_Data_Crowther_2023.csv' to perform the analyses. Code was compiled in R version 4.3.2 and uses the following packages: 'tidyverse', 'showtext', 'DHARMa', 'patchwork', 'lme4', 'glmmTMB', and 'emmeans'. Sex-ratio theory predicts that parents can optimize their fitness by producing offspring of the rarer sex, yet there is a dearth of empirical evidence for adaptive sex allocation in response to the adult sex ratio (ASR). This is concerning, as anthropogenic disruption of the sex ratios of reproductive individuals threatens to cause demographic collapse in animal populations. Species with environmental sex determination (ESD) are especially at risk, but may possess the capacity to adaptively influence offspring sex via control over the developmental environment. For example, reptiles with temperature-dependent sex determination (TSD) could conceivably choose nest sites with thermal characteristics that produce offspring of the rarer sex. To test this hypothesis, we seeded three secure outdoor ponds with different sex ratios (~ 3:1, 1:1, and 1:3) of adult painted turtles (Chrysemys picta), a reptile species with TSD. We then quantified nesting traits that could influence nest temperature, and thus offspring sex ratio, including nesting date, nest depth, and nest canopy cover. We found no directional relationship between the ASR treatments and any measured nest traits, and thus reject our hypothesis. Interestingly, increased maternal body size was associated with reduced nest canopy cover, and this trend was more pronounced in the biased ASR treatments. If adaptive sex allocation occurs in this system, it instead may manifest via maternal epigenetic predisposition of offspring sex or in response to a phenomenon other than the ASR.

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    DRYAD
    Dataset . 2024
    License: CC 0
    Data sources: Datacite
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      DRYAD
      Dataset . 2024
      License: CC 0
      Data sources: Datacite
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    Authors: Zweifel, Roman; Sterck, Frank J; Braun, Sabine; Buchmann, Nina; +8 Authors

    The timing of diel stem growth of mature forest trees is still largely unknown, as empirical data with high temporal resolution have not been available so far. Consequently, the effects of day-night conditions on tree growth remained uncertain. Here we present the first comprehensive field study of hourly-resolved radial stem growth of seven temperate tree species, based on 57 million underlying data points over a period of up to 8 years. We show that trees grow mainly at night, with a peak after midnight, when the vapour pressure deficit (VPD) is among the lowest. A high VPD strictly limits radial stem growth and allows little growth during daylight hours, except in the early morning. Surprisingly, trees also grow in moderately dry soil when the VPD is low. Species-specific differences in diel growth dynamics show that species able to grow earlier during the night are associated with the highest number of hours with growth per year and the largest annual growth increment. We conclude that species with the ability to overcome daily water deficits faster have greater growth potential. Furthermore, we conclude that growth is more sensitive than carbon uptake to dry air, as growth stops before stomata are known to close.

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    B2FIND
    Dataset . 2021
    Data sources: B2FIND
    PANGAEA
    Dataset . 2021
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2021
      Data sources: B2FIND
      PANGAEA
      Dataset . 2021
      Data sources: PANGAEA
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    Authors: T Ya Churilova; G P Berseneva; L V Georgieva;
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    B2FIND
    Dataset . 2004
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2004
    License: CC BY
    Data sources: PANGAEA
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    PANGAEA
    Dataset . 2004
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2004
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2004
      License: CC BY
      Data sources: PANGAEA
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      PANGAEA
      Dataset . 2004
      Data sources: PANGAEA
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    Authors: K L Smith;
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    B2FIND
    Dataset . 2002
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2002
    License: CC BY
    Data sources: PANGAEA
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    PANGAEA
    Dataset . 2002
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2002
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2002
      License: CC BY
      Data sources: PANGAEA
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      PANGAEA
      Dataset . 2002
      Data sources: PANGAEA
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  • Authors: Mooney, Meghan; Waechter, Katy;

    The National Renewable Energy Laboratory's (NREL) PV Rooftop Database for Puerto Rico (PVRDB-PR) is a lidar-derived, geospatially-resolved dataset of suitable roof surfaces and their PV technical potential for virtually all buildings in Puerto Rico. The dataset can be downloaded at the AWS S3 explorer page. The GitHub documentation page provides a description of the dataset with methods and assumptions. The Puerto Rico Solar-For-All dataset provides Census Tract level estimates of residential low-to-moderate income (LMI) PV rooftop technical potential as well as solar electric bill savings potential for LMI communities at the municipality level.

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    Authors: Metsaranta, Juha; Mamet, Steven; Maillet, Jay; Barr, Alan;

    These datasets are associated with the following paper: Metsaranta, J.M., Mamet, S.D., Maillett, J., Barr, A.G. (2021). Comparison of tree-ring and eddy covariance derived annual ecosystem production estimates for jack pine and trembling aspen forests in Saskatchewan, Canada. Agricultural and Forest Meteorology. There are two files: (1) CBMOutput.zip. This contains the hybrid biometric modelled ecosystem C stock and flux estimates. (2) StandReconstructionData.zip. This contains the field measurement data and the tree level biomass and wood volume data for the Stand Reconstruction plots used to develop the hybrid biometric modelled estimates. The data are formatted as .csv files, and an associated Microsoft Excel spreadsheet explains the data columns and provides information on the associated units of measure.

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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
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    Smithsonian figshare
    Dataset . 2021
    License: CC BY
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO
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      Smithsonian figshare
      Dataset . 2021
      License: CC BY
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    Authors: PowerTAC;

    Log and boot files of games 101 - 105

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    ZENODO
    Dataset . 2015
    License: CC 0
    Data sources: ZENODO
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    ZENODO
    Dataset . 2015
    License: CC 0
    Data sources: Datacite
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      ZENODO
      Dataset . 2015
      License: CC 0
      Data sources: ZENODO
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      ZENODO
      Dataset . 2015
      License: CC 0
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Fischer, Andrea; Fickert, Thomas; Schwaizer, Gabriele; Patzelt, Gernot; +1 Authors

    Monitoring of plant succession in glacier forelands so far has been restricted to field sampling. In this study, in situ vegetation sampling along a chronosequence between Little Ice Age (LIA) maximum extent and the recent glacier terminus at Jamtalferner/Silvretta (ferner is a Tyrolian toponym for glacier) is compared to time series of the Normalized Difference Vegetation Index (NDVI) calculated from 13 Landsat scenes (1985-2016). The glacier terminus positions at 16 dates between the LIA maximum and 2015 were analysed from historical maps, orthophotos and LiDAR images and used for site age determination. We sampled plots of different time since deglaciation, from very recent to approx. 150 years: after 100 years, roughly 80% of the ground is covered by plants and ground cover did not increase essentially thereafter. Species number increases from 10-20 species on young sites to 40-50 species after 100 years. The NDVI increases for all plots between 1985 and 2016, from a mean of 0.11 for 1985-1991 to 0.2 in 2009 and 0.27 in 2016. For the plots deglaciated between 1 and about 150 years, the NDVI increases with the time of exposure. As the increase in ground cover is clearly reproduced by the NDVI (R² ground cover/NDVI 0.84) - even for sparsely vegetated areas -, we see a high potential of satellite-borne NDVI to perform regional characterizations of glacier forelands for hydrological, ecological and hazard management related applications. This data collection comprises the galcier outlines, NDVIs and chronosequencing locations with diversity and ground cover data.

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    B2FIND
    Dataset . 2019
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2019
    License: CC BY
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2019
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2019
      License: CC BY
      Data sources: PANGAEA
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  • Providing the source code and case settings for the simulations used in "Numerical Investigation of Regenerative Wind Farms Featuring Enhanced Vertical Energy Entrainment".####################################################### Source codeSource code for "flyingActuationDiskSource" is in the directory "src". Please compile it by executing the file "Allwmake". Version of the OpenFOAM used in this work is "OpenFOAM v2106". Note that in the file "./src/Make/files", token "yourPATH" should be changed to the path where one would like to store the .so file. For convenience, .so file is provided in directory "platform".## Case filesEach case is stored in separate directories. Names of the directories should be self explainable. Note that the file "system/controlDict" of each case also contain a token "yourPATH", which should be changed to where the .so file is stored.Notice: when decomposing the domain, make sure that all the actuator elements of one MRSL are included in a single processor. This should be done since while smearing the body force, an actuator element in a processor cannot spread the information to another processor, making some of the forces "missing".Notice: Not all the fields in "constant/fvOptions" are used. Some of them are completely useless and removable, while some of them should not be removed even they are not used (used in the constructor). Please check the source code for further details.## Case submitting"fullrunDiskActuator.sh" is an example of the job file used for this work.## Computing resources estimationA case took up about 80GB at most, and took around 48 hr on 144 cores when using "2x Intel Xeon E5-6248R 24C 3.0GHz" (computaional resources provided by Delft High Performance Computing Centre, https://doc.dhpc.tudelft.nl/delftblue/DHPC-hardware/).

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  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao

    The enclosed files provide the Stata scripts and data to replicate the results from the study.

    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Mendeley Dataarrow_drop_down
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    Mendeley Data
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Mendeley Data
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      Mendeley Data
      Dataset . 2019
      License: CC BY
      Data sources: Datacite
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      Mendeley Data
      Dataset . 2019
      License: CC BY
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  • Authors: Crowther, Claudia; Adams, Clare; Fondren, Andy; Janzen, Fredric;

    # Adult sex-ratio bias does not lead to detectable adaptive offspring sex allocation via nest-site choice in a turtle with temperature-dependent sex determination [https://doi.org/10.5061/dryad.vt4b8gv20](https://doi.org/10.5061/dryad.vt4b8gv20) ## Description of the data and file structure Data and code required to reproduce the analyses in "Adult sex-ratio bias does not lead to detectable adaptive offspring sex allocation via nest-site choice in a turtle with temperature-dependent sex determination" Data was collected to compare the nesting behaviour (timing, depth, and shade cover) of painted turtles (*Chrysemys picta*) in three outdoor enclosures with experimentally manipulated adult sex ratios (ASR). The purpose of the experiment was to ascertain whether species with temperature-dependent sex determination (TSD, incubation temperature determines the sex of embryos) could adaptively manipulate offspring sex via nest-site choice in response to the ASR. ### Files and variables #### File: ASR\_Data\_Crowther\_2023.csv **Description:** csv file containing nest characteristics for all the nests laid in the experimental enclosures. Missing values are indicated by "NA" (not available). ##### Variables * Date: The date that the nest was laid, format: M/DD/YYYY. * Jdate: The day of the year that the nest was laid (e.g. Jdate 152 = the 31st of May). * Pond: The letter identifier for the experimental pond that the nest was laid in. The adult sex ratio of the ponds varied, B = male-biased, C = equal sex ratio, and D = female-biased. * MomID: The unique identifier for the mother that laid the nest. * SCL: The straight carapace (dorsal side of the shell) length of the mother in millimeters. * NestDepthCM: The depth of the nest in centimeters. * HemiPhoto: The file name of the hemispherical canopy cover photo. * SexRatio: The proportion male offspring in the clutch associated with the nest (hatchlings were incubated in a laboratory environment). NA values for this variable indicate that the data is not available because we did not determine the sex of hatchlings in those clutches. * Clutch.Size: The number of eggs in the clutch. * Clutch.no: The order the mother laid the clutch, 1 = mother's 1st clutch in season, 2 = mother's second clutch. * SW.Open: The percentage of sky area over the South West half of the nest not covered by vegetation or other shade. ### **File Folder: Nest Photos** **Description:** Hemispherical photographs of the sky area above nests, used to calculate nest canopy cover. The nests were photographed using a Nikon Coolpix S3600 camera equipped with a Zykkor fish eye lens (0.2x180°). The photographs are stored in a .jpeg format. Nest photographs are linked to the corresponding nest data by their file name, which is recorded in the 'HemiPhoto' column of ASR_Data_Crowther_2023.csv ## Code/software #### Nest\_trait\_analysis\_V3.R ##### Description: An R file containing code to repeat the analyses presented in '*Adult sex-ratio bias does not lead to detectable adaptive offspring sex allocation via nest-site choice in a turtle with temperature-dependent sex determination*' a manuscript submitted to Ecology and Evolution. The script also contains code for publication and supplementary graphs. The script requires the data file 'ASR_Data_Crowther_2023.csv' to perform the analyses. Code was compiled in R version 4.3.2 and uses the following packages: 'tidyverse', 'showtext', 'DHARMa', 'patchwork', 'lme4', 'glmmTMB', and 'emmeans'. Sex-ratio theory predicts that parents can optimize their fitness by producing offspring of the rarer sex, yet there is a dearth of empirical evidence for adaptive sex allocation in response to the adult sex ratio (ASR). This is concerning, as anthropogenic disruption of the sex ratios of reproductive individuals threatens to cause demographic collapse in animal populations. Species with environmental sex determination (ESD) are especially at risk, but may possess the capacity to adaptively influence offspring sex via control over the developmental environment. For example, reptiles with temperature-dependent sex determination (TSD) could conceivably choose nest sites with thermal characteristics that produce offspring of the rarer sex. To test this hypothesis, we seeded three secure outdoor ponds with different sex ratios (~ 3:1, 1:1, and 1:3) of adult painted turtles (Chrysemys picta), a reptile species with TSD. We then quantified nesting traits that could influence nest temperature, and thus offspring sex ratio, including nesting date, nest depth, and nest canopy cover. We found no directional relationship between the ASR treatments and any measured nest traits, and thus reject our hypothesis. Interestingly, increased maternal body size was associated with reduced nest canopy cover, and this trend was more pronounced in the biased ASR treatments. If adaptive sex allocation occurs in this system, it instead may manifest via maternal epigenetic predisposition of offspring sex or in response to a phenomenon other than the ASR.

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    DRYAD
    Dataset . 2024
    License: CC 0
    Data sources: Datacite
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      DRYAD
      Dataset . 2024
      License: CC 0
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Zweifel, Roman; Sterck, Frank J; Braun, Sabine; Buchmann, Nina; +8 Authors

    The timing of diel stem growth of mature forest trees is still largely unknown, as empirical data with high temporal resolution have not been available so far. Consequently, the effects of day-night conditions on tree growth remained uncertain. Here we present the first comprehensive field study of hourly-resolved radial stem growth of seven temperate tree species, based on 57 million underlying data points over a period of up to 8 years. We show that trees grow mainly at night, with a peak after midnight, when the vapour pressure deficit (VPD) is among the lowest. A high VPD strictly limits radial stem growth and allows little growth during daylight hours, except in the early morning. Surprisingly, trees also grow in moderately dry soil when the VPD is low. Species-specific differences in diel growth dynamics show that species able to grow earlier during the night are associated with the highest number of hours with growth per year and the largest annual growth increment. We conclude that species with the ability to overcome daily water deficits faster have greater growth potential. Furthermore, we conclude that growth is more sensitive than carbon uptake to dry air, as growth stops before stomata are known to close.

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    B2FIND
    Dataset . 2021
    Data sources: B2FIND
    PANGAEA
    Dataset . 2021
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2021
      Data sources: B2FIND
      PANGAEA
      Dataset . 2021
      Data sources: PANGAEA
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: T Ya Churilova; G P Berseneva; L V Georgieva;
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ B2FINDarrow_drop_down
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    B2FIND
    Dataset . 2004
    Data sources: B2FIND
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    PANGAEA
    Dataset . 2004
    License: CC BY
    Data sources: PANGAEA
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    PANGAEA
    Dataset . 2004
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2004
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2004
      License: CC BY
      Data sources: PANGAEA
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      PANGAEA
      Dataset . 2004
      Data sources: PANGAEA
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: K L Smith;
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ B2FINDarrow_drop_down
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    B2FIND
    Dataset . 2002
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2002
    License: CC BY
    Data sources: PANGAEA
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    PANGAEA
    Dataset . 2002
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2002
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2002
      License: CC BY
      Data sources: PANGAEA
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      PANGAEA
      Dataset . 2002
      Data sources: PANGAEA
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  • Authors: Mooney, Meghan; Waechter, Katy;

    The National Renewable Energy Laboratory's (NREL) PV Rooftop Database for Puerto Rico (PVRDB-PR) is a lidar-derived, geospatially-resolved dataset of suitable roof surfaces and their PV technical potential for virtually all buildings in Puerto Rico. The dataset can be downloaded at the AWS S3 explorer page. The GitHub documentation page provides a description of the dataset with methods and assumptions. The Puerto Rico Solar-For-All dataset provides Census Tract level estimates of residential low-to-moderate income (LMI) PV rooftop technical potential as well as solar electric bill savings potential for LMI communities at the municipality level.

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    Authors: Metsaranta, Juha; Mamet, Steven; Maillet, Jay; Barr, Alan;

    These datasets are associated with the following paper: Metsaranta, J.M., Mamet, S.D., Maillett, J., Barr, A.G. (2021). Comparison of tree-ring and eddy covariance derived annual ecosystem production estimates for jack pine and trembling aspen forests in Saskatchewan, Canada. Agricultural and Forest Meteorology. There are two files: (1) CBMOutput.zip. This contains the hybrid biometric modelled ecosystem C stock and flux estimates. (2) StandReconstructionData.zip. This contains the field measurement data and the tree level biomass and wood volume data for the Stand Reconstruction plots used to develop the hybrid biometric modelled estimates. The data are formatted as .csv files, and an associated Microsoft Excel spreadsheet explains the data columns and provides information on the associated units of measure.

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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
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    Smithsonian figshare
    Dataset . 2021
    License: CC BY
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Smithsonian figshare
      Dataset . 2021
      License: CC BY
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: PowerTAC;

    Log and boot files of games 101 - 105

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    ZENODO
    Dataset . 2015
    License: CC 0
    Data sources: ZENODO
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    ZENODO
    Dataset . 2015
    License: CC 0
    Data sources: Datacite
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      ZENODO
      Dataset . 2015
      License: CC 0
      Data sources: ZENODO
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      ZENODO
      Dataset . 2015
      License: CC 0
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Fischer, Andrea; Fickert, Thomas; Schwaizer, Gabriele; Patzelt, Gernot; +1 Authors

    Monitoring of plant succession in glacier forelands so far has been restricted to field sampling. In this study, in situ vegetation sampling along a chronosequence between Little Ice Age (LIA) maximum extent and the recent glacier terminus at Jamtalferner/Silvretta (ferner is a Tyrolian toponym for glacier) is compared to time series of the Normalized Difference Vegetation Index (NDVI) calculated from 13 Landsat scenes (1985-2016). The glacier terminus positions at 16 dates between the LIA maximum and 2015 were analysed from historical maps, orthophotos and LiDAR images and used for site age determination. We sampled plots of different time since deglaciation, from very recent to approx. 150 years: after 100 years, roughly 80% of the ground is covered by plants and ground cover did not increase essentially thereafter. Species number increases from 10-20 species on young sites to 40-50 species after 100 years. The NDVI increases for all plots between 1985 and 2016, from a mean of 0.11 for 1985-1991 to 0.2 in 2009 and 0.27 in 2016. For the plots deglaciated between 1 and about 150 years, the NDVI increases with the time of exposure. As the increase in ground cover is clearly reproduced by the NDVI (R² ground cover/NDVI 0.84) - even for sparsely vegetated areas -, we see a high potential of satellite-borne NDVI to perform regional characterizations of glacier forelands for hydrological, ecological and hazard management related applications. This data collection comprises the galcier outlines, NDVIs and chronosequencing locations with diversity and ground cover data.

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    B2FIND
    Dataset . 2019
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2019
    License: CC BY
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2019
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2019
      License: CC BY
      Data sources: PANGAEA
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  • Providing the source code and case settings for the simulations used in "Numerical Investigation of Regenerative Wind Farms Featuring Enhanced Vertical Energy Entrainment".####################################################### Source codeSource code for "flyingActuationDiskSource" is in the directory "src". Please compile it by executing the file "Allwmake". Version of the OpenFOAM used in this work is "OpenFOAM v2106". Note that in the file "./src/Make/files", token "yourPATH" should be changed to the path where one would like to store the .so file. For convenience, .so file is provided in directory "platform".## Case filesEach case is stored in separate directories. Names of the directories should be self explainable. Note that the file "system/controlDict" of each case also contain a token "yourPATH", which should be changed to where the .so file is stored.Notice: when decomposing the domain, make sure that all the actuator elements of one MRSL are included in a single processor. This should be done since while smearing the body force, an actuator element in a processor cannot spread the information to another processor, making some of the forces "missing".Notice: Not all the fields in "constant/fvOptions" are used. Some of them are completely useless and removable, while some of them should not be removed even they are not used (used in the constructor). Please check the source code for further details.## Case submitting"fullrunDiskActuator.sh" is an example of the job file used for this work.## Computing resources estimationA case took up about 80GB at most, and took around 48 hr on 144 cores when using "2x Intel Xeon E5-6248R 24C 3.0GHz" (computaional resources provided by Delft High Performance Computing Centre, https://doc.dhpc.tudelft.nl/delftblue/DHPC-hardware/).

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  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao

    The enclosed files provide the Stata scripts and data to replicate the results from the study.

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    Mendeley Data
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
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    Dataset . 2019
    License: CC BY
    Data sources: Datacite
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      Mendeley Data
      Dataset . 2019
      License: CC BY
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      Dataset . 2019
      License: CC BY
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