Terrestrial Ecosystem Model (TEM) Dataset - data from 16 vegetation types worldwide

The Terrestrial Ecosystem Model (TEM) is a process-based model developed by staff at the Ecosystems Center, Marine Biological Laboratory, Woods Hole, Massachusetts, U.S.A. Data on pool sizes and fluxes of carbon (C) and nitrogen (N) from 16 field study sites in a wide range of biomes were used to ca...

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Bibliographic Details
Main Authors: Kicklighter, David, National Center For Ecological Analysis And Synthesis, NCEAS 2017 Prince Global Primary Production Data Initiative
Format: Dataset
Language:English
Published: KNB Data Repository 2004
Subjects:
carbon
nitrogen
net primary production
vegetation
soil
Tundra
Online Access:https://dx.doi.org/10.5063/aa/nceas.149.4
https://knb.ecoinformatics.org/view/doi:10.5063/AA/nceas.149.4
id ftdatacite:10.5063/aa/nceas.149.4
record_format openpolar
spelling ftdatacite:10.5063/aa/nceas.149.4 2023-05-15T18:40:11+02:00 Terrestrial Ecosystem Model (TEM) Dataset - data from 16 vegetation types worldwide Kicklighter, David National Center For Ecological Analysis And Synthesis NCEAS 2017 Prince Global Primary Production Data Initiative 2004 text/xml https://dx.doi.org/10.5063/aa/nceas.149.4 https://knb.ecoinformatics.org/view/doi:10.5063/AA/nceas.149.4 en eng KNB Data Repository carbon nitrogen net primary production vegetation soil dataset Dataset 2004 ftdatacite https://doi.org/10.5063/aa/nceas.149.4 2021-11-05T12:55:41Z The Terrestrial Ecosystem Model (TEM) is a process-based model developed by staff at the Ecosystems Center, Marine Biological Laboratory, Woods Hole, Massachusetts, U.S.A. Data on pool sizes and fluxes of carbon (C) and nitrogen (N) from 16 field study sites in a wide range of biomes were used to calibrate the model. Ranging from tundra to tropical forest, but excluding wetlands, these data are collectively known as the Dataset Tundra DataCite Metadata Store (German National Library of Science and Technology)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
topic carbon
nitrogen
net primary production
vegetation
soil
spellingShingle carbon
nitrogen
net primary production
vegetation
soil
Kicklighter, David
National Center For Ecological Analysis And Synthesis
NCEAS 2017 Prince Global Primary Production Data Initiative
Terrestrial Ecosystem Model (TEM) Dataset - data from 16 vegetation types worldwide
topic_facet carbon
nitrogen
net primary production
vegetation
soil
description The Terrestrial Ecosystem Model (TEM) is a process-based model developed by staff at the Ecosystems Center, Marine Biological Laboratory, Woods Hole, Massachusetts, U.S.A. Data on pool sizes and fluxes of carbon (C) and nitrogen (N) from 16 field study sites in a wide range of biomes were used to calibrate the model. Ranging from tundra to tropical forest, but excluding wetlands, these data are collectively known as the
format Dataset
author Kicklighter, David
National Center For Ecological Analysis And Synthesis
NCEAS 2017 Prince Global Primary Production Data Initiative
author_facet Kicklighter, David
National Center For Ecological Analysis And Synthesis
NCEAS 2017 Prince Global Primary Production Data Initiative
author_sort Kicklighter, David
title Terrestrial Ecosystem Model (TEM) Dataset - data from 16 vegetation types worldwide
title_short Terrestrial Ecosystem Model (TEM) Dataset - data from 16 vegetation types worldwide
title_full Terrestrial Ecosystem Model (TEM) Dataset - data from 16 vegetation types worldwide
title_fullStr Terrestrial Ecosystem Model (TEM) Dataset - data from 16 vegetation types worldwide
title_full_unstemmed Terrestrial Ecosystem Model (TEM) Dataset - data from 16 vegetation types worldwide
title_sort terrestrial ecosystem model (tem) dataset - data from 16 vegetation types worldwide
publisher KNB Data Repository
publishDate 2004
url https://dx.doi.org/10.5063/aa/nceas.149.4
https://knb.ecoinformatics.org/view/doi:10.5063/AA/nceas.149.4
genre Tundra
genre_facet Tundra
op_doi https://doi.org/10.5063/aa/nceas.149.4
_version_ 1766229425837309952

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