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2,731 to 2,740 of 11,643 Results

01_ReadMe.txt Dec 20, 2019 - Replication Data for: Data on European seafood biomass production by country, sectors and species in 1951-2014 Plain Text - 1.6 KB - MD5: c352b97078ba20ad83b9d5db968aaa67 Description of the dataset
EU_Fish_Prod_1950_2014_upload.tab Dec 20, 2019 - Replication Data for: Data on European seafood biomass production by country, sectors and species in 1951-2014 Tabular Data - 164 B - 1 Variables, 4 Observations - UNF:6:p4oswtPhPvaiY+Apu1jpOQ==
EU_Fish_Prod_1950_2014_upload.txt Dec 20, 2019 - Replication Data for: Data on European seafood biomass production by country, sectors and species in 1951-2014 Plain Text - 1.8 MB - MD5: 85e5d75e5c8116021ea84e394ff7d1f9
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
Replication data for: Modelling Silicate – Nitrate - Ammonium co-limitation of algal growth and the importance of bacterial remineralisation based on an experimental Arctic coastal spring bloom culture study Aug 19, 2020 Vonnahme, Tobias R; Leroy, Martial; Thoms, Silke; van Oevelen, Dick; Harvey, Rodger; Kristiansen, Svein; Dietrich, Ulrike; Gradinger, Rolf R; Völker, Christoph, 2020, "Replication data for: Modelling Silicate – Nitrate - Ammonium co-limitation of algal growth and the importance of bacterial remineralisation based on an experimental Arctic coastal spring bloom culture study", https://doi.org/10.18710/VA4IU9, DataverseNO, V1 Phytoplankton spring blooms in Arctic coastal ecosystems are affected by a drastically changing climate; making modelling their responses to these changes an important challenge to model ecosystem responses. These spring blooms are mostly dominated by diatoms growing exponentially in spring until the nutrients silicon or nitrogen are depleted and t...
00_README.txt Aug 19, 2020 - Replication data for: Modelling Silicate – Nitrate - Ammonium co-limitation of algal growth and the importance of bacterial remineralisation based on an experimental Arctic coastal spring bloom culture study Plain Text - 7.6 KB - MD5: aaf3ce7245936865a782823b96544278
ModExpData_archived.txt Aug 19, 2020 - Replication data for: Modelling Silicate – Nitrate - Ammonium co-limitation of algal growth and the importance of bacterial remineralisation based on an experimental Arctic coastal spring bloom culture study Plain Text - 8.3 KB - MD5: a27cea2d3340049a1bf17808da0bd6d1

01_ReadMe.txt

Dec 20, 2019 - Replication Data for: Data on European seafood biomass production by country, sectors and species in 1951-2014

Plain Text - 1.6 KB -

Description of the dataset

EU_Fish_Prod_1950_2014_upload.tab

Dec 20, 2019 - Replication Data for: Data on European seafood biomass production by country, sectors and species in 1951-2014

Tabular Data - 164 B - 1 Variables, 4 Observations -

EU_Fish_Prod_1950_2014_upload.txt

Dec 20, 2019 - Replication Data for: Data on European seafood biomass production by country, sectors and species in 1951-2014

Plain Text - 1.8 MB -

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

Replication data for: Modelling Silicate – Nitrate - Ammonium co-limitation of algal growth and the importance of bacterial remineralisation based on an experimental Arctic coastal spring bloom culture study

Aug 19, 2020

Vonnahme, Tobias R; Leroy, Martial; Thoms, Silke; van Oevelen, Dick; Harvey, Rodger; Kristiansen, Svein; Dietrich, Ulrike; Gradinger, Rolf R; Völker, Christoph, 2020, "Replication data for: Modelling Silicate – Nitrate - Ammonium co-limitation of algal growth and the importance of bacterial remineralisation based on an experimental Arctic coastal spring bloom culture study", https://doi.org/10.18710/VA4IU9, DataverseNO, V1

Phytoplankton spring blooms in Arctic coastal ecosystems are affected by a drastically changing climate; making modelling their responses to these changes an important challenge to model ecosystem responses. These spring blooms are mostly dominated by diatoms growing exponentially in spring until the nutrients silicon or nitrogen are depleted and t...

00_README.txt

Aug 19, 2020 - Replication data for: Modelling Silicate – Nitrate - Ammonium co-limitation of algal growth and the importance of bacterial remineralisation based on an experimental Arctic coastal spring bloom culture study

Plain Text - 7.6 KB -

ModExpData_archived.txt

Plain Text - 8.3 KB -

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