Representativeness-Based Sampling Network Design for the Arctic ...
Resource and logistical constraints limit the frequency and extent of environmental observations, particularly in the Arctic, necessitating the development of a systematic sampling strategy to maximize coverage and objectively represent environmental variability at desired scales. Required is a quan...
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Friedrich-Schiller-Universität Jena
2018
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Online Access: | https://dx.doi.org/10.22032/dbt.37842 https://www.db-thueringen.de/receive/dbt_mods_00037842 |
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ftdatacite:10.22032/dbt.37842 2023-12-31T10:03:23+01:00 Representativeness-Based Sampling Network Design for the Arctic ... Hoffman, Forrest Kumar, Jitendra Hargrove, William Pallandt, Martijn Goeckedei, Mathias 2018 https://dx.doi.org/10.22032/dbt.37842 https://www.db-thueringen.de/receive/dbt_mods_00037842 en eng Friedrich-Schiller-Universität Jena https://www.db-thueringen.de/receive/dbt_mods_00037842?XSL.Transformer=mods https://www.db-thueringen.de/receive/dbt_mods_00037820 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 spatiotemporal, network analysis, representativeness, ecoregions 004 570 580 590 600 630 ScholarlyArticle Text article-journal speech 2018 ftdatacite https://doi.org/10.22032/dbt.37842 2023-12-01T11:25:54Z Resource and logistical constraints limit the frequency and extent of environmental observations, particularly in the Arctic, necessitating the development of a systematic sampling strategy to maximize coverage and objectively represent environmental variability at desired scales. Required is a quantitative methodology for stratifying sampling domains, informing site selection, and determining the representativeness of measurement sites and networks. Multivariate spatiotemporal clustering was applied to down-scaled general circulation model results and data for the State of Alaska at 2 km ✕ 2 km resolution to define multiple sets of bioclimatic ecoregions across two decadal time periods. Maps of ecoregions for the present (2000–2009) and future (2090–2099) were produced, showing how combinations of 37 bioclimatic and permafrost characteristics are distributed and how they may shift in the future. Representative sampling locations are identified on present and future ecoregion maps. A representativeness ... : ICEI 2018 : 10th International Conference on Ecological Informatics- Translating Ecological Data into Knowledge and Decisions in a Rapidly Changing World ... Audio Arctic permafrost Alaska DataCite Metadata Store (German National Library of Science and Technology) |
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Open Polar |
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DataCite Metadata Store (German National Library of Science and Technology) |
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ftdatacite |
language |
English |
topic |
spatiotemporal, network analysis, representativeness, ecoregions 004 570 580 590 600 630 |
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spatiotemporal, network analysis, representativeness, ecoregions 004 570 580 590 600 630 Hoffman, Forrest Kumar, Jitendra Hargrove, William Pallandt, Martijn Goeckedei, Mathias Representativeness-Based Sampling Network Design for the Arctic ... |
topic_facet |
spatiotemporal, network analysis, representativeness, ecoregions 004 570 580 590 600 630 |
description |
Resource and logistical constraints limit the frequency and extent of environmental observations, particularly in the Arctic, necessitating the development of a systematic sampling strategy to maximize coverage and objectively represent environmental variability at desired scales. Required is a quantitative methodology for stratifying sampling domains, informing site selection, and determining the representativeness of measurement sites and networks. Multivariate spatiotemporal clustering was applied to down-scaled general circulation model results and data for the State of Alaska at 2 km ✕ 2 km resolution to define multiple sets of bioclimatic ecoregions across two decadal time periods. Maps of ecoregions for the present (2000–2009) and future (2090–2099) were produced, showing how combinations of 37 bioclimatic and permafrost characteristics are distributed and how they may shift in the future. Representative sampling locations are identified on present and future ecoregion maps. A representativeness ... : ICEI 2018 : 10th International Conference on Ecological Informatics- Translating Ecological Data into Knowledge and Decisions in a Rapidly Changing World ... |
format |
Audio |
author |
Hoffman, Forrest Kumar, Jitendra Hargrove, William Pallandt, Martijn Goeckedei, Mathias |
author_facet |
Hoffman, Forrest Kumar, Jitendra Hargrove, William Pallandt, Martijn Goeckedei, Mathias |
author_sort |
Hoffman, Forrest |
title |
Representativeness-Based Sampling Network Design for the Arctic ... |
title_short |
Representativeness-Based Sampling Network Design for the Arctic ... |
title_full |
Representativeness-Based Sampling Network Design for the Arctic ... |
title_fullStr |
Representativeness-Based Sampling Network Design for the Arctic ... |
title_full_unstemmed |
Representativeness-Based Sampling Network Design for the Arctic ... |
title_sort |
representativeness-based sampling network design for the arctic ... |
publisher |
Friedrich-Schiller-Universität Jena |
publishDate |
2018 |
url |
https://dx.doi.org/10.22032/dbt.37842 https://www.db-thueringen.de/receive/dbt_mods_00037842 |
genre |
Arctic permafrost Alaska |
genre_facet |
Arctic permafrost Alaska |
op_relation |
https://www.db-thueringen.de/receive/dbt_mods_00037842?XSL.Transformer=mods https://www.db-thueringen.de/receive/dbt_mods_00037820 |
op_rights |
Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 |
op_doi |
https://doi.org/10.22032/dbt.37842 |
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1786821242999799808 |