Looking for TROLLing? Click here: https://trolling.uit.no/
Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Advanced Search

8,141 to 8,150 of 11,083 Results
MATLAB Data - 4.6 KB - MD5: 55b52905db25b87376ef51e68e2bef4a
Plain Text - 10.0 KB - MD5: 7965e7ae372a1802d79c6cd40baf7523
MATLAB Figure - 60.0 KB - MD5: 43d2aba9a87c29fe2f3d5d5120abd8dc
TIFF Image - 298.0 KB - MD5: 73459f782b32279098521784fb1e04c1
MATLAB Source Code - 1.9 KB - MD5: 2ab096c5ae0b58a98ca16f8c4df5315e
MATLAB Source Code - 1.6 KB - MD5: e87924c26903671c7e3648f4ef1ad147
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 abs...
Plain Text - 2.3 KB - MD5: 4aa538974b14d4222d16a741bf333125
CodeDataDocumentationNot available until 2020-04-30
ReadMe fie
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".
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?
Add Data

Log in to create a dataverse or add a dataset.

Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.