Loading…
Assessing dynamic vegetation model parameter uncertainty across Alaskan arctic tundra plant communities
As the Arctic region moves into uncharted territory under a warming climate, it is important to refine the terrestrial biosphere models (TBMs) that help us understand and predict change. One fundamental uncertainty in TBMs relates to model parameters, configuration variables internal to the model wh...
Saved in:
Published in: | Ecological applications 2021-12, Vol.32 (2) |
---|---|
Main Authors: | , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | |
---|---|
cites | |
container_end_page | |
container_issue | 2 |
container_start_page | |
container_title | Ecological applications |
container_volume | 32 |
creator | Euskirchen, Eugénie S. Serbin, Shawn P. Carman, Tobey B. Fraterrigo, Jennifer M. Genet, Hélène Iversen, Colleen M. Salmon, Verity McGuire, A. David |
description | As the Arctic region moves into uncharted territory under a warming climate, it is important to refine the terrestrial biosphere models (TBMs) that help us understand and predict change. One fundamental uncertainty in TBMs relates to model parameters, configuration variables internal to the model whose value can be estimated from data. We incorporate a version of the Terrestrial Ecosystem Model (TEM) developed for arctic ecosystems into the Predictive Ecosystem Analyzer (PEcAn) framework. PEcAn treats model parameters as probability distributions, estimates parameters based on a synthesis of available field data, and then quantifies both model sensitivity and uncertainty to a given parameter or suite of parameters. We examined how variation in 21 parameters in the equation for gross primary production influenced model sensitivity and uncertainty in terms of two carbon fluxes (net primary productivity and heterotrophic respiration) and two carbon (C) pools (vegetation C and soil C). We set up different parameterizations of TEM across a range of tundra types (tussock tundra, heath tundra, wet sedge tundra, and shrub tundra) in northern Alaska, along a latitudinal transect extending from the coastal plain near $Utqia\dot{g}ik$ to the southern foothills of the Brooks Range, to the Seward Peninsula. TEM was most sensitive to parameters related to the temperature regulation of photosynthesis. Model uncertainty was mostly due to parameters related to leaf area, temperature regulation of photosynthesis, and the stomatal responses to ambient light conditions. Our analysis also showed that sensitivity and uncertainty to a given parameter varied spatially. At some sites, model sensitivity and uncertainty tended to be connected to a wider range of parameters, underlining the importance of assessing tundra community processes across environmental gradients or geographic locations. Generally, across sites, the flux of net primary productivity (NPP) and pool of vegetation C had about equal uncertainty, while heterotrophic respiration had higher uncertainty than the pool of soil C. Our study illustrates the complexity inherent in evaluating parameter uncertainty across highly heterogeneous arctic tundra plant communities. It also provides a framework for iteratively testing how newly collected field data related to key parameters may result in more effective forecasting of Arctic change. |
format | article |
fullrecord | <record><control><sourceid>osti</sourceid><recordid>TN_cdi_osti_scitechconnect_1835373</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1835373</sourcerecordid><originalsourceid>FETCH-osti_scitechconnect_18353733</originalsourceid><addsrcrecordid>eNqNi0GKwkAQRZthhHHUOxTuA0maGF2KKHOA2UtRKWPPpKulqyJ4e7PwAP7Ne4v3P9y82vld0TTb-nPysqmKst1UX-5b9a-cVtf13PV7VVYN0kP3EIyB4M49G1pIAjF1PMANM0Y2zjAKcTYMYg9AykkV9gPqPwpgJpvONkqXEW4DigGlGEcJFliXbnbBQXn14sKtT8ffw0-R1MJZKRjTlZIIk52rrW986_1b0RN0oEo6</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Assessing dynamic vegetation model parameter uncertainty across Alaskan arctic tundra plant communities</title><source>JSTOR Archival Journals and Primary Sources Collection【Remote access available】</source><source>Wiley-Blackwell Read & Publish Collection</source><creator>Euskirchen, Eugénie S. ; Serbin, Shawn P. ; Carman, Tobey B. ; Fraterrigo, Jennifer M. ; Genet, Hélène ; Iversen, Colleen M. ; Salmon, Verity ; McGuire, A. David</creator><creatorcontrib>Euskirchen, Eugénie S. ; Serbin, Shawn P. ; Carman, Tobey B. ; Fraterrigo, Jennifer M. ; Genet, Hélène ; Iversen, Colleen M. ; Salmon, Verity ; McGuire, A. David ; Brookhaven National Laboratory (BNL), Upton, NY (United States) ; Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)</creatorcontrib><description>As the Arctic region moves into uncharted territory under a warming climate, it is important to refine the terrestrial biosphere models (TBMs) that help us understand and predict change. One fundamental uncertainty in TBMs relates to model parameters, configuration variables internal to the model whose value can be estimated from data. We incorporate a version of the Terrestrial Ecosystem Model (TEM) developed for arctic ecosystems into the Predictive Ecosystem Analyzer (PEcAn) framework. PEcAn treats model parameters as probability distributions, estimates parameters based on a synthesis of available field data, and then quantifies both model sensitivity and uncertainty to a given parameter or suite of parameters. We examined how variation in 21 parameters in the equation for gross primary production influenced model sensitivity and uncertainty in terms of two carbon fluxes (net primary productivity and heterotrophic respiration) and two carbon (C) pools (vegetation C and soil C). We set up different parameterizations of TEM across a range of tundra types (tussock tundra, heath tundra, wet sedge tundra, and shrub tundra) in northern Alaska, along a latitudinal transect extending from the coastal plain near $Utqia\dot{g}ik$ to the southern foothills of the Brooks Range, to the Seward Peninsula. TEM was most sensitive to parameters related to the temperature regulation of photosynthesis. Model uncertainty was mostly due to parameters related to leaf area, temperature regulation of photosynthesis, and the stomatal responses to ambient light conditions. Our analysis also showed that sensitivity and uncertainty to a given parameter varied spatially. At some sites, model sensitivity and uncertainty tended to be connected to a wider range of parameters, underlining the importance of assessing tundra community processes across environmental gradients or geographic locations. Generally, across sites, the flux of net primary productivity (NPP) and pool of vegetation C had about equal uncertainty, while heterotrophic respiration had higher uncertainty than the pool of soil C. Our study illustrates the complexity inherent in evaluating parameter uncertainty across highly heterogeneous arctic tundra plant communities. It also provides a framework for iteratively testing how newly collected field data related to key parameters may result in more effective forecasting of Arctic change.</description><identifier>ISSN: 1051-0761</identifier><identifier>EISSN: 1939-5582</identifier><language>eng</language><publisher>United States: Wiley Blackwell (John Wiley & Sons)</publisher><subject>arctic carbon budget ; arctic tundra ; ENVIRONMENTAL SCIENCES ; landscape heterogeneity ; model uncertainty ; parameter sensitivity ; terrestrial biosphere model</subject><ispartof>Ecological applications, 2021-12, Vol.32 (2)</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000000341368971 ; 0000000203571007 ; 0000000345379563 ; 0000000182933450 ; 0000000208484295 ; 0000000346460750 ; 000000022188551X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,776,780,881</link.rule.ids><backlink>$$Uhttps://www.osti.gov/biblio/1835373$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Euskirchen, Eugénie S.</creatorcontrib><creatorcontrib>Serbin, Shawn P.</creatorcontrib><creatorcontrib>Carman, Tobey B.</creatorcontrib><creatorcontrib>Fraterrigo, Jennifer M.</creatorcontrib><creatorcontrib>Genet, Hélène</creatorcontrib><creatorcontrib>Iversen, Colleen M.</creatorcontrib><creatorcontrib>Salmon, Verity</creatorcontrib><creatorcontrib>McGuire, A. David</creatorcontrib><creatorcontrib>Brookhaven National Laboratory (BNL), Upton, NY (United States)</creatorcontrib><creatorcontrib>Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)</creatorcontrib><title>Assessing dynamic vegetation model parameter uncertainty across Alaskan arctic tundra plant communities</title><title>Ecological applications</title><description>As the Arctic region moves into uncharted territory under a warming climate, it is important to refine the terrestrial biosphere models (TBMs) that help us understand and predict change. One fundamental uncertainty in TBMs relates to model parameters, configuration variables internal to the model whose value can be estimated from data. We incorporate a version of the Terrestrial Ecosystem Model (TEM) developed for arctic ecosystems into the Predictive Ecosystem Analyzer (PEcAn) framework. PEcAn treats model parameters as probability distributions, estimates parameters based on a synthesis of available field data, and then quantifies both model sensitivity and uncertainty to a given parameter or suite of parameters. We examined how variation in 21 parameters in the equation for gross primary production influenced model sensitivity and uncertainty in terms of two carbon fluxes (net primary productivity and heterotrophic respiration) and two carbon (C) pools (vegetation C and soil C). We set up different parameterizations of TEM across a range of tundra types (tussock tundra, heath tundra, wet sedge tundra, and shrub tundra) in northern Alaska, along a latitudinal transect extending from the coastal plain near $Utqia\dot{g}ik$ to the southern foothills of the Brooks Range, to the Seward Peninsula. TEM was most sensitive to parameters related to the temperature regulation of photosynthesis. Model uncertainty was mostly due to parameters related to leaf area, temperature regulation of photosynthesis, and the stomatal responses to ambient light conditions. Our analysis also showed that sensitivity and uncertainty to a given parameter varied spatially. At some sites, model sensitivity and uncertainty tended to be connected to a wider range of parameters, underlining the importance of assessing tundra community processes across environmental gradients or geographic locations. Generally, across sites, the flux of net primary productivity (NPP) and pool of vegetation C had about equal uncertainty, while heterotrophic respiration had higher uncertainty than the pool of soil C. Our study illustrates the complexity inherent in evaluating parameter uncertainty across highly heterogeneous arctic tundra plant communities. It also provides a framework for iteratively testing how newly collected field data related to key parameters may result in more effective forecasting of Arctic change.</description><subject>arctic carbon budget</subject><subject>arctic tundra</subject><subject>ENVIRONMENTAL SCIENCES</subject><subject>landscape heterogeneity</subject><subject>model uncertainty</subject><subject>parameter sensitivity</subject><subject>terrestrial biosphere model</subject><issn>1051-0761</issn><issn>1939-5582</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNqNi0GKwkAQRZthhHHUOxTuA0maGF2KKHOA2UtRKWPPpKulqyJ4e7PwAP7Ne4v3P9y82vld0TTb-nPysqmKst1UX-5b9a-cVtf13PV7VVYN0kP3EIyB4M49G1pIAjF1PMANM0Y2zjAKcTYMYg9AykkV9gPqPwpgJpvONkqXEW4DigGlGEcJFliXbnbBQXn14sKtT8ffw0-R1MJZKRjTlZIIk52rrW986_1b0RN0oEo6</recordid><startdate>20211213</startdate><enddate>20211213</enddate><creator>Euskirchen, Eugénie S.</creator><creator>Serbin, Shawn P.</creator><creator>Carman, Tobey B.</creator><creator>Fraterrigo, Jennifer M.</creator><creator>Genet, Hélène</creator><creator>Iversen, Colleen M.</creator><creator>Salmon, Verity</creator><creator>McGuire, A. David</creator><general>Wiley Blackwell (John Wiley & Sons)</general><scope>OTOTI</scope><orcidid>https://orcid.org/0000000341368971</orcidid><orcidid>https://orcid.org/0000000203571007</orcidid><orcidid>https://orcid.org/0000000345379563</orcidid><orcidid>https://orcid.org/0000000182933450</orcidid><orcidid>https://orcid.org/0000000208484295</orcidid><orcidid>https://orcid.org/0000000346460750</orcidid><orcidid>https://orcid.org/000000022188551X</orcidid></search><sort><creationdate>20211213</creationdate><title>Assessing dynamic vegetation model parameter uncertainty across Alaskan arctic tundra plant communities</title><author>Euskirchen, Eugénie S. ; Serbin, Shawn P. ; Carman, Tobey B. ; Fraterrigo, Jennifer M. ; Genet, Hélène ; Iversen, Colleen M. ; Salmon, Verity ; McGuire, A. David</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-osti_scitechconnect_18353733</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>arctic carbon budget</topic><topic>arctic tundra</topic><topic>ENVIRONMENTAL SCIENCES</topic><topic>landscape heterogeneity</topic><topic>model uncertainty</topic><topic>parameter sensitivity</topic><topic>terrestrial biosphere model</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Euskirchen, Eugénie S.</creatorcontrib><creatorcontrib>Serbin, Shawn P.</creatorcontrib><creatorcontrib>Carman, Tobey B.</creatorcontrib><creatorcontrib>Fraterrigo, Jennifer M.</creatorcontrib><creatorcontrib>Genet, Hélène</creatorcontrib><creatorcontrib>Iversen, Colleen M.</creatorcontrib><creatorcontrib>Salmon, Verity</creatorcontrib><creatorcontrib>McGuire, A. David</creatorcontrib><creatorcontrib>Brookhaven National Laboratory (BNL), Upton, NY (United States)</creatorcontrib><creatorcontrib>Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)</creatorcontrib><collection>OSTI.GOV</collection><jtitle>Ecological applications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Euskirchen, Eugénie S.</au><au>Serbin, Shawn P.</au><au>Carman, Tobey B.</au><au>Fraterrigo, Jennifer M.</au><au>Genet, Hélène</au><au>Iversen, Colleen M.</au><au>Salmon, Verity</au><au>McGuire, A. David</au><aucorp>Brookhaven National Laboratory (BNL), Upton, NY (United States)</aucorp><aucorp>Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Assessing dynamic vegetation model parameter uncertainty across Alaskan arctic tundra plant communities</atitle><jtitle>Ecological applications</jtitle><date>2021-12-13</date><risdate>2021</risdate><volume>32</volume><issue>2</issue><issn>1051-0761</issn><eissn>1939-5582</eissn><abstract>As the Arctic region moves into uncharted territory under a warming climate, it is important to refine the terrestrial biosphere models (TBMs) that help us understand and predict change. One fundamental uncertainty in TBMs relates to model parameters, configuration variables internal to the model whose value can be estimated from data. We incorporate a version of the Terrestrial Ecosystem Model (TEM) developed for arctic ecosystems into the Predictive Ecosystem Analyzer (PEcAn) framework. PEcAn treats model parameters as probability distributions, estimates parameters based on a synthesis of available field data, and then quantifies both model sensitivity and uncertainty to a given parameter or suite of parameters. We examined how variation in 21 parameters in the equation for gross primary production influenced model sensitivity and uncertainty in terms of two carbon fluxes (net primary productivity and heterotrophic respiration) and two carbon (C) pools (vegetation C and soil C). We set up different parameterizations of TEM across a range of tundra types (tussock tundra, heath tundra, wet sedge tundra, and shrub tundra) in northern Alaska, along a latitudinal transect extending from the coastal plain near $Utqia\dot{g}ik$ to the southern foothills of the Brooks Range, to the Seward Peninsula. TEM was most sensitive to parameters related to the temperature regulation of photosynthesis. Model uncertainty was mostly due to parameters related to leaf area, temperature regulation of photosynthesis, and the stomatal responses to ambient light conditions. Our analysis also showed that sensitivity and uncertainty to a given parameter varied spatially. At some sites, model sensitivity and uncertainty tended to be connected to a wider range of parameters, underlining the importance of assessing tundra community processes across environmental gradients or geographic locations. Generally, across sites, the flux of net primary productivity (NPP) and pool of vegetation C had about equal uncertainty, while heterotrophic respiration had higher uncertainty than the pool of soil C. Our study illustrates the complexity inherent in evaluating parameter uncertainty across highly heterogeneous arctic tundra plant communities. It also provides a framework for iteratively testing how newly collected field data related to key parameters may result in more effective forecasting of Arctic change.</abstract><cop>United States</cop><pub>Wiley Blackwell (John Wiley & Sons)</pub><orcidid>https://orcid.org/0000000341368971</orcidid><orcidid>https://orcid.org/0000000203571007</orcidid><orcidid>https://orcid.org/0000000345379563</orcidid><orcidid>https://orcid.org/0000000182933450</orcidid><orcidid>https://orcid.org/0000000208484295</orcidid><orcidid>https://orcid.org/0000000346460750</orcidid><orcidid>https://orcid.org/000000022188551X</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1051-0761 |
ispartof | Ecological applications, 2021-12, Vol.32 (2) |
issn | 1051-0761 1939-5582 |
language | eng |
recordid | cdi_osti_scitechconnect_1835373 |
source | JSTOR Archival Journals and Primary Sources Collection【Remote access available】; Wiley-Blackwell Read & Publish Collection |
subjects | arctic carbon budget arctic tundra ENVIRONMENTAL SCIENCES landscape heterogeneity model uncertainty parameter sensitivity terrestrial biosphere model |
title | Assessing dynamic vegetation model parameter uncertainty across Alaskan arctic tundra plant communities |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-23T08%3A03%3A23IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-osti&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Assessing%20dynamic%20vegetation%20model%20parameter%20uncertainty%20across%20Alaskan%20arctic%20tundra%20plant%20communities&rft.jtitle=Ecological%20applications&rft.au=Euskirchen,%20Eug%C3%A9nie%20S.&rft.aucorp=Brookhaven%20National%20Laboratory%20(BNL),%20Upton,%20NY%20(United%20States)&rft.date=2021-12-13&rft.volume=32&rft.issue=2&rft.issn=1051-0761&rft.eissn=1939-5582&rft_id=info:doi/&rft_dat=%3Costi%3E1835373%3C/osti%3E%3Cgrp_id%3Ecdi_FETCH-osti_scitechconnect_18353733%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |