Multimodel evaluation of longitudinal stream temperature gradient and dominant influencing factors in Michigan streams
Stream temperature is an important determinant of fish growth, migration, and survival and can thus impact the structure and function of stream ecosystems. Many streams in Michigan and elsewhere in North America receive groundwater inputs that help regulate instream conditions by stabilizing dischar...
Gespeichert in:
Veröffentlicht in: | River research and applications 2022-12, Vol.38 (10), p.1829-1842 |
---|---|
Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 1842 |
---|---|
container_issue | 10 |
container_start_page | 1829 |
container_title | River research and applications |
container_volume | 38 |
creator | Andrews, Ryan M. Hayes, Daniel B. Zorn, Troy G. |
description | Stream temperature is an important determinant of fish growth, migration, and survival and can thus impact the structure and function of stream ecosystems. Many streams in Michigan and elsewhere in North America receive groundwater inputs that help regulate instream conditions by stabilizing discharge as well as stream temperature. However, groundwater withdrawal can cause reductions in streamflow which typically results in increased summer stream temperatures. Other atmospheric and hydrologic variables (i.e., overland discharge) also impact the rate at which stream temperature changes as it flows downstream. We deployed paired up‐ and downstream water pressure and temperature loggers within 21 stream reaches throughout the state of Michigan to quantify and model relationships between stream discharge, air temperature, and longitudinal change in stream temperature (i.e., temperature gradient). Using multimodel selection criteria, we evaluated the performance of a hierarchical suite of models that predict temperature gradient as a function of potential driving variables. The multimodel selection criteria identified a best‐fitting model that was able to model the diurnal, seasonal, and annual variations in rates of longitudinal temperature fluctuations across most sample streams. Partial regression analysis indicated that proxy variables representing solar radiation at the stream surface were generally the most influential predictors of longitudinal changes in stream temperature, but air temperature and components of streamflow including groundwater input were significant predictors and important in many streams. |
doi_str_mv | 10.1002/rra.4054 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_3153175235</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3153175235</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3604-8ea4fff48b727ce1d0fc865cd0f70a601d9f3faad4adb301a5d71f1eef72e50c3</originalsourceid><addsrcrecordid>eNp1kVtLJDEQhRtxwcsu-BMCvvjSY9KddHoeRbyBsiC7z6EmqYyRdDImacV_v9ERBWGfTlXxcaDOaZojRheM0u40JVhwKvhOs89EL1rGB7n7OYvlXnOQ8yOlTI7Lcb95vpt9cVM06Ak-g5-huBhItMTHsHZlNi6AJ7kkhIkUnDaYoMwJyTqBcRgKgWCIiVPl6uKC9TMG7cKaWNAlplxv5M7pB7eG8GGUfzY_LPiMvz70sPl7efHn_Lq9_X11c3522-p-oLwdEbi1lo8r2UmNzFCrx0HoqpLCQJlZ2t4CGA5m1VMGwkhmGaKVHQqq-8PmZOu7SfFpxlzU5LJG7yFgnLPqay5Miq4XFT3-hj7GOdXns-ok51yOA11-GeoUc05o1Sa5CdKrYlS9FaBqAeqtgIq2W_TFeXz9L6fu78_e-X_UvIpS</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2744478609</pqid></control><display><type>article</type><title>Multimodel evaluation of longitudinal stream temperature gradient and dominant influencing factors in Michigan streams</title><source>Wiley Online Library Journals Frontfile Complete</source><creator>Andrews, Ryan M. ; Hayes, Daniel B. ; Zorn, Troy G.</creator><creatorcontrib>Andrews, Ryan M. ; Hayes, Daniel B. ; Zorn, Troy G.</creatorcontrib><description>Stream temperature is an important determinant of fish growth, migration, and survival and can thus impact the structure and function of stream ecosystems. Many streams in Michigan and elsewhere in North America receive groundwater inputs that help regulate instream conditions by stabilizing discharge as well as stream temperature. However, groundwater withdrawal can cause reductions in streamflow which typically results in increased summer stream temperatures. Other atmospheric and hydrologic variables (i.e., overland discharge) also impact the rate at which stream temperature changes as it flows downstream. We deployed paired up‐ and downstream water pressure and temperature loggers within 21 stream reaches throughout the state of Michigan to quantify and model relationships between stream discharge, air temperature, and longitudinal change in stream temperature (i.e., temperature gradient). Using multimodel selection criteria, we evaluated the performance of a hierarchical suite of models that predict temperature gradient as a function of potential driving variables. The multimodel selection criteria identified a best‐fitting model that was able to model the diurnal, seasonal, and annual variations in rates of longitudinal temperature fluctuations across most sample streams. Partial regression analysis indicated that proxy variables representing solar radiation at the stream surface were generally the most influential predictors of longitudinal changes in stream temperature, but air temperature and components of streamflow including groundwater input were significant predictors and important in many streams.</description><identifier>ISSN: 1535-1459</identifier><identifier>EISSN: 1535-1467</identifier><identifier>DOI: 10.1002/rra.4054</identifier><language>eng</language><publisher>Chichester, UK: John Wiley & Sons, Ltd</publisher><subject>Air temperature ; animal growth ; Annual variations ; Atmospheric models ; Criteria ; Discharge ; Downstream ; Fish ; Groundwater ; groundwater extraction ; Hydrology ; Hydrostatic pressure ; longitudinal temperature gradient ; Michigan ; Migrations ; multimodel selection ; overland discharge ; partial regression ; Performance evaluation ; Regression analysis ; Rivers ; Solar radiation ; Stabilizing ; Stream discharge ; Stream flow ; stream temperature ; Streams ; Structure-function relationships ; summer ; Survival ; Temperature ; Temperature gradients ; Water pressure ; water temperature</subject><ispartof>River research and applications, 2022-12, Vol.38 (10), p.1829-1842</ispartof><rights>2022 The Authors. published by John Wiley & Sons Ltd.</rights><rights>2022. This article is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3604-8ea4fff48b727ce1d0fc865cd0f70a601d9f3faad4adb301a5d71f1eef72e50c3</citedby><cites>FETCH-LOGICAL-c3604-8ea4fff48b727ce1d0fc865cd0f70a601d9f3faad4adb301a5d71f1eef72e50c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Frra.4054$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Frra.4054$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids></links><search><creatorcontrib>Andrews, Ryan M.</creatorcontrib><creatorcontrib>Hayes, Daniel B.</creatorcontrib><creatorcontrib>Zorn, Troy G.</creatorcontrib><title>Multimodel evaluation of longitudinal stream temperature gradient and dominant influencing factors in Michigan streams</title><title>River research and applications</title><description>Stream temperature is an important determinant of fish growth, migration, and survival and can thus impact the structure and function of stream ecosystems. Many streams in Michigan and elsewhere in North America receive groundwater inputs that help regulate instream conditions by stabilizing discharge as well as stream temperature. However, groundwater withdrawal can cause reductions in streamflow which typically results in increased summer stream temperatures. Other atmospheric and hydrologic variables (i.e., overland discharge) also impact the rate at which stream temperature changes as it flows downstream. We deployed paired up‐ and downstream water pressure and temperature loggers within 21 stream reaches throughout the state of Michigan to quantify and model relationships between stream discharge, air temperature, and longitudinal change in stream temperature (i.e., temperature gradient). Using multimodel selection criteria, we evaluated the performance of a hierarchical suite of models that predict temperature gradient as a function of potential driving variables. The multimodel selection criteria identified a best‐fitting model that was able to model the diurnal, seasonal, and annual variations in rates of longitudinal temperature fluctuations across most sample streams. Partial regression analysis indicated that proxy variables representing solar radiation at the stream surface were generally the most influential predictors of longitudinal changes in stream temperature, but air temperature and components of streamflow including groundwater input were significant predictors and important in many streams.</description><subject>Air temperature</subject><subject>animal growth</subject><subject>Annual variations</subject><subject>Atmospheric models</subject><subject>Criteria</subject><subject>Discharge</subject><subject>Downstream</subject><subject>Fish</subject><subject>Groundwater</subject><subject>groundwater extraction</subject><subject>Hydrology</subject><subject>Hydrostatic pressure</subject><subject>longitudinal temperature gradient</subject><subject>Michigan</subject><subject>Migrations</subject><subject>multimodel selection</subject><subject>overland discharge</subject><subject>partial regression</subject><subject>Performance evaluation</subject><subject>Regression analysis</subject><subject>Rivers</subject><subject>Solar radiation</subject><subject>Stabilizing</subject><subject>Stream discharge</subject><subject>Stream flow</subject><subject>stream temperature</subject><subject>Streams</subject><subject>Structure-function relationships</subject><subject>summer</subject><subject>Survival</subject><subject>Temperature</subject><subject>Temperature gradients</subject><subject>Water pressure</subject><subject>water temperature</subject><issn>1535-1459</issn><issn>1535-1467</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><recordid>eNp1kVtLJDEQhRtxwcsu-BMCvvjSY9KddHoeRbyBsiC7z6EmqYyRdDImacV_v9ERBWGfTlXxcaDOaZojRheM0u40JVhwKvhOs89EL1rGB7n7OYvlXnOQ8yOlTI7Lcb95vpt9cVM06Ak-g5-huBhItMTHsHZlNi6AJ7kkhIkUnDaYoMwJyTqBcRgKgWCIiVPl6uKC9TMG7cKaWNAlplxv5M7pB7eG8GGUfzY_LPiMvz70sPl7efHn_Lq9_X11c3522-p-oLwdEbi1lo8r2UmNzFCrx0HoqpLCQJlZ2t4CGA5m1VMGwkhmGaKVHQqq-8PmZOu7SfFpxlzU5LJG7yFgnLPqay5Miq4XFT3-hj7GOdXns-ok51yOA11-GeoUc05o1Sa5CdKrYlS9FaBqAeqtgIq2W_TFeXz9L6fu78_e-X_UvIpS</recordid><startdate>202212</startdate><enddate>202212</enddate><creator>Andrews, Ryan M.</creator><creator>Hayes, Daniel B.</creator><creator>Zorn, Troy G.</creator><general>John Wiley & Sons, Ltd</general><general>Wiley Subscription Services, Inc</general><scope>24P</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7SN</scope><scope>7SS</scope><scope>7ST</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H95</scope><scope>H96</scope><scope>L.G</scope><scope>SOI</scope><scope>7S9</scope><scope>L.6</scope></search><sort><creationdate>202212</creationdate><title>Multimodel evaluation of longitudinal stream temperature gradient and dominant influencing factors in Michigan streams</title><author>Andrews, Ryan M. ; Hayes, Daniel B. ; Zorn, Troy G.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3604-8ea4fff48b727ce1d0fc865cd0f70a601d9f3faad4adb301a5d71f1eef72e50c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Air temperature</topic><topic>animal growth</topic><topic>Annual variations</topic><topic>Atmospheric models</topic><topic>Criteria</topic><topic>Discharge</topic><topic>Downstream</topic><topic>Fish</topic><topic>Groundwater</topic><topic>groundwater extraction</topic><topic>Hydrology</topic><topic>Hydrostatic pressure</topic><topic>longitudinal temperature gradient</topic><topic>Michigan</topic><topic>Migrations</topic><topic>multimodel selection</topic><topic>overland discharge</topic><topic>partial regression</topic><topic>Performance evaluation</topic><topic>Regression analysis</topic><topic>Rivers</topic><topic>Solar radiation</topic><topic>Stabilizing</topic><topic>Stream discharge</topic><topic>Stream flow</topic><topic>stream temperature</topic><topic>Streams</topic><topic>Structure-function relationships</topic><topic>summer</topic><topic>Survival</topic><topic>Temperature</topic><topic>Temperature gradients</topic><topic>Water pressure</topic><topic>water temperature</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Andrews, Ryan M.</creatorcontrib><creatorcontrib>Hayes, Daniel B.</creatorcontrib><creatorcontrib>Zorn, Troy G.</creatorcontrib><collection>Wiley-Blackwell Open Access Titles</collection><collection>CrossRef</collection><collection>Aqualine</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Environment Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 1: Biological Sciences & Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Environment Abstracts</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>River research and applications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Andrews, Ryan M.</au><au>Hayes, Daniel B.</au><au>Zorn, Troy G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Multimodel evaluation of longitudinal stream temperature gradient and dominant influencing factors in Michigan streams</atitle><jtitle>River research and applications</jtitle><date>2022-12</date><risdate>2022</risdate><volume>38</volume><issue>10</issue><spage>1829</spage><epage>1842</epage><pages>1829-1842</pages><issn>1535-1459</issn><eissn>1535-1467</eissn><abstract>Stream temperature is an important determinant of fish growth, migration, and survival and can thus impact the structure and function of stream ecosystems. Many streams in Michigan and elsewhere in North America receive groundwater inputs that help regulate instream conditions by stabilizing discharge as well as stream temperature. However, groundwater withdrawal can cause reductions in streamflow which typically results in increased summer stream temperatures. Other atmospheric and hydrologic variables (i.e., overland discharge) also impact the rate at which stream temperature changes as it flows downstream. We deployed paired up‐ and downstream water pressure and temperature loggers within 21 stream reaches throughout the state of Michigan to quantify and model relationships between stream discharge, air temperature, and longitudinal change in stream temperature (i.e., temperature gradient). Using multimodel selection criteria, we evaluated the performance of a hierarchical suite of models that predict temperature gradient as a function of potential driving variables. The multimodel selection criteria identified a best‐fitting model that was able to model the diurnal, seasonal, and annual variations in rates of longitudinal temperature fluctuations across most sample streams. Partial regression analysis indicated that proxy variables representing solar radiation at the stream surface were generally the most influential predictors of longitudinal changes in stream temperature, but air temperature and components of streamflow including groundwater input were significant predictors and important in many streams.</abstract><cop>Chichester, UK</cop><pub>John Wiley & Sons, Ltd</pub><doi>10.1002/rra.4054</doi><tpages>14</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1535-1459 |
ispartof | River research and applications, 2022-12, Vol.38 (10), p.1829-1842 |
issn | 1535-1459 1535-1467 |
language | eng |
recordid | cdi_proquest_miscellaneous_3153175235 |
source | Wiley Online Library Journals Frontfile Complete |
subjects | Air temperature animal growth Annual variations Atmospheric models Criteria Discharge Downstream Fish Groundwater groundwater extraction Hydrology Hydrostatic pressure longitudinal temperature gradient Michigan Migrations multimodel selection overland discharge partial regression Performance evaluation Regression analysis Rivers Solar radiation Stabilizing Stream discharge Stream flow stream temperature Streams Structure-function relationships summer Survival Temperature Temperature gradients Water pressure water temperature |
title | Multimodel evaluation of longitudinal stream temperature gradient and dominant influencing factors in Michigan streams |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-13T20%3A00%3A03IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Multimodel%20evaluation%20of%20longitudinal%20stream%20temperature%20gradient%20and%20dominant%20influencing%20factors%20in%20Michigan%20streams&rft.jtitle=River%20research%20and%20applications&rft.au=Andrews,%20Ryan%20M.&rft.date=2022-12&rft.volume=38&rft.issue=10&rft.spage=1829&rft.epage=1842&rft.pages=1829-1842&rft.issn=1535-1459&rft.eissn=1535-1467&rft_id=info:doi/10.1002/rra.4054&rft_dat=%3Cproquest_cross%3E3153175235%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2744478609&rft_id=info:pmid/&rfr_iscdi=true |