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...
| Main Authors: | , , , , |
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| Format: | Audio |
| Language: | English |
| Published: |
Friedrich-Schiller-Universität Jena
2018
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| Subjects: | |
| Online Access: | https://dx.doi.org/10.22032/dbt.37842 https://www.db-thueringen.de/receive/dbt_mods_00037842 |
| Summary: | 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 ... |
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