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8,501 to 8,510 of 11,437 Results

Supplementary data for: Using mathematical modelling to investigate the adaptive divergence of whitefish in Fennoscandia Apr 1, 2020 Thibert-Plante, Xavier; Præbel, Kim; Østbye, Kjartan; Kahilainen, Kimmo K; Amundsen, Per-Arne; Gavrilets, Sergey, 2020, "Supplementary data for: Using mathematical modelling to investigate the adaptive divergence of whitefish in Fennoscandia", https://doi.org/10.18710/PI8PJQ, DataverseNO, V1 These data constitute the supplementary material for the publication "Using mathematical modelling to investigate the adaptive divergence of whitefish in Fennoscandia". The dataset forms the results for the entire parameter space used in simulations. Please read the following abstract from publication for more detail about the nature of the project...
00_README.txt Apr 1, 2020 - Supplementary data for: Using mathematical modelling to investigate the adaptive divergence of whitefish in Fennoscandia Plain Text - 2.3 KB - MD5: 4aa538974b14d4222d16a741bf333125 CodeDataDocumentationNot available until 2020-04-30 ReadMe fie
adaptive_divergence_whitefish.zip.gz Apr 1, 2020 - Supplementary data for: Using mathematical modelling to investigate the adaptive divergence of whitefish in Fennoscandia Gzip Archive - 261.8 MB - MD5: 5143c32974d3f36e5cfedb4b10d73008 CodeDataDocumentationNot available until 2020-04-30 This folder contains supplementary material for the paper "Using mathematical modelling to investigate the adaptive divergence of whitefish in Fennoscandia".
Replication Data for: How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes? Mar 9, 2020 Ancin-Murguzur, Francisco Javier; Brown, Antony G.; Clarke, Charlotte; Sjøgren, Per; Svendsen, John Inge; Alsos, Inger Greve, 2020, "Replication Data for: How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes?", https://doi.org/10.18710/OJC4TH, DataverseNO, V1 This dataset contains the reference data and script to develop a predictive NIRS model to measure LOI in lacustrine sediments, as described in the article: How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes?
00_ReadMe_file_LOI.txt Mar 9, 2020 - Replication Data for: How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes? Plain Text - 1.6 KB - MD5: 2e7d26cc64217682a47be9689c048baa README file
LOI_Modeling_Script.R Mar 9, 2020 - Replication Data for: How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes? R Syntax - 3.2 KB - MD5: 22498b95800e905b07643382b720afeb Script to develop the LOI predictive model based on lacustrine samples scanned by means of near infra-red reflectance spectroscopy
LOI_Reference_Dataset.txt Mar 9, 2020 - Replication Data for: How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes? Plain Text - 13.1 MB - MD5: 5875ab1e2b7614cb30e0b23be2e4439b Reference dataset containing the spectral values, LOI values and lake ID
001_ALL_GEOMETRIES.xyz Mar 9, 2020 - Replication Data for: Static polarizabilities at the basis set limit: A benchmark of 124 species Co-Ordinate Animation - 15.9 KB - MD5: bebea36982e2503a70b350114e4fae26 File containing cartesian coordinates, charges, and spin multiplicities of all species studied. Coordinates specified in the standard XYZ file format, each species separated by a newline character.
Replication data for: Quantifying tourism booms and the increasing footprint in the Arctic with social media data Feb 6, 2020 Runge, Claire A.; Daigle, Remi M.; Hausner, Vera H., 2020, "Replication data for: Quantifying tourism booms and the increasing footprint in the Arctic with social media data", https://doi.org/10.18710/QEOFPY, DataverseNO, V1, UNF:6:czqP04pzsqnMiDPqDgKLpg== [fileUNF] Arctic tourism has rapidly increased in the past two decades. We used social media data to examine localized tourism booms and quantify the spatial expansion of the Arctic tourism footprint. We extracted geotagged locations from over 800,000 photos on Flickr and mapped these across space and time. We critically examine the use of social media as a...
00_Readme.txt Feb 6, 2020 - Replication data for: Quantifying tourism booms and the increasing footprint in the Arctic with social media data Plain Text - 4.9 KB - MD5: 0d6900643e1817f2d46f22d0751b619c Contains descriptions of data files and column headers

Supplementary data for: Using mathematical modelling to investigate the adaptive divergence of whitefish in Fennoscandia

Apr 1, 2020

Thibert-Plante, Xavier; Præbel, Kim; Østbye, Kjartan; Kahilainen, Kimmo K; Amundsen, Per-Arne; Gavrilets, Sergey, 2020, "Supplementary data for: Using mathematical modelling to investigate the adaptive divergence of whitefish in Fennoscandia", https://doi.org/10.18710/PI8PJQ, DataverseNO, V1

These data constitute the supplementary material for the publication "Using mathematical modelling to investigate the adaptive divergence of whitefish in Fennoscandia". The dataset forms the results for the entire parameter space used in simulations. Please read the following abstract from publication for more detail about the nature of the project...

00_README.txt

Apr 1, 2020 - Supplementary data for: Using mathematical modelling to investigate the adaptive divergence of whitefish in Fennoscandia

Plain Text - 2.3 KB -

CodeDataDocumentationNot available until 2020-04-30

ReadMe fie

adaptive_divergence_whitefish.zip.gz

Apr 1, 2020 - Supplementary data for: Using mathematical modelling to investigate the adaptive divergence of whitefish in Fennoscandia

Gzip Archive - 261.8 MB -

CodeDataDocumentationNot available until 2020-04-30

This folder contains supplementary material for the paper "Using mathematical modelling to investigate the adaptive divergence of whitefish in Fennoscandia".

Replication Data for: How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes?

Mar 9, 2020

Ancin-Murguzur, Francisco Javier; Brown, Antony G.; Clarke, Charlotte; Sjøgren, Per; Svendsen, John Inge; Alsos, Inger Greve, 2020, "Replication Data for: How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes?", https://doi.org/10.18710/OJC4TH, DataverseNO, V1

This dataset contains the reference data and script to develop a predictive NIRS model to measure LOI in lacustrine sediments, as described in the article: How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes?

00_ReadMe_file_LOI.txt

Mar 9, 2020 - Replication Data for: How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes?

Plain Text - 1.6 KB -

README file

LOI_Modeling_Script.R

Mar 9, 2020 - Replication Data for: How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes?

R Syntax - 3.2 KB -

Script to develop the LOI predictive model based on lacustrine samples scanned by means of near infra-red reflectance spectroscopy

LOI_Reference_Dataset.txt

Mar 9, 2020 - Replication Data for: How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes?

Plain Text - 13.1 MB -

Reference dataset containing the spectral values, LOI values and lake ID

001_ALL_GEOMETRIES.xyz

Mar 9, 2020 - Replication Data for: Static polarizabilities at the basis set limit: A benchmark of 124 species

Co-Ordinate Animation - 15.9 KB -

File containing cartesian coordinates, charges, and spin multiplicities of all species studied. Coordinates specified in the standard XYZ file format, each species separated by a newline character.

Replication data for: Quantifying tourism booms and the increasing footprint in the Arctic with social media data

Feb 6, 2020

Runge, Claire A.; Daigle, Remi M.; Hausner, Vera H., 2020, "Replication data for: Quantifying tourism booms and the increasing footprint in the Arctic with social media data", https://doi.org/10.18710/QEOFPY, DataverseNO, V1, UNF:6:czqP04pzsqnMiDPqDgKLpg== [fileUNF]

Arctic tourism has rapidly increased in the past two decades. We used social media data to examine localized tourism booms and quantify the spatial expansion of the Arctic tourism footprint. We extracted geotagged locations from over 800,000 photos on Flickr and mapped these across space and time. We critically examine the use of social media as a...

00_Readme.txt

Feb 6, 2020 - Replication data for: Quantifying tourism booms and the increasing footprint in the Arctic with social media data

Plain Text - 4.9 KB -

Contains descriptions of data files and column headers

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