Towards a statistically robust determination of minimum water potential and hydraulic risk in plants
Summary Minimum water potential (Ψmin) is a key variable for characterizing dehydration tolerance and hydraulic safety margins (HSMs) in plants. Ψmin is usually estimated as the absolute minimum tissue Ψ experienced by a species, but this is problematic because sample extremes are affected by sample...
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Veröffentlicht in: | The New phytologist 2021-10, Vol.232 (1), p.404-417 |
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creator | Martínez‐Vilalta, Jordi Santiago, Louis S. Poyatos, Rafael Badiella, Llorenç Cáceres, Miquel Aranda, Ismael Delzon, Sylvain Vilagrosa, Alberto Mencuccini, Maurizio |
description | Summary
Minimum water potential (Ψmin) is a key variable for characterizing dehydration tolerance and hydraulic safety margins (HSMs) in plants. Ψmin is usually estimated as the absolute minimum tissue Ψ experienced by a species, but this is problematic because sample extremes are affected by sample size and the underlying probability distribution.
We compare alternative approaches to estimate Ψmin and assess the corresponding uncertainties and biases; propose statistically robust estimation methods based on extreme value theory (EVT); and assess the implications of our results for the characterization of hydraulic risk.
Our results show that current estimates of Ψmin and HSMs are biased, as they are strongly affected by sample size. Because sampling effort is generally higher for species living in dry environments, the differences in current Ψmin estimates between these species and those living under milder conditions are partly artefactual. When this bias is corrected using EVT methods, resulting HSMs tend to increase substantially with resistance to embolism across species.
Although data availability and representativeness remain the main challenges for proper determination of Ψmin, a closer look at Ψ distributions and the use of statistically robust methods to estimate Ψmin opens new ground for characterizing plant hydraulic risks. |
doi_str_mv | 10.1111/nph.17571 |
format | Article |
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Minimum water potential (Ψmin) is a key variable for characterizing dehydration tolerance and hydraulic safety margins (HSMs) in plants. Ψmin is usually estimated as the absolute minimum tissue Ψ experienced by a species, but this is problematic because sample extremes are affected by sample size and the underlying probability distribution.
We compare alternative approaches to estimate Ψmin and assess the corresponding uncertainties and biases; propose statistically robust estimation methods based on extreme value theory (EVT); and assess the implications of our results for the characterization of hydraulic risk.
Our results show that current estimates of Ψmin and HSMs are biased, as they are strongly affected by sample size. Because sampling effort is generally higher for species living in dry environments, the differences in current Ψmin estimates between these species and those living under milder conditions are partly artefactual. When this bias is corrected using EVT methods, resulting HSMs tend to increase substantially with resistance to embolism across species.
Although data availability and representativeness remain the main challenges for proper determination of Ψmin, a closer look at Ψ distributions and the use of statistically robust methods to estimate Ψmin opens new ground for characterizing plant hydraulic risks.</description><identifier>ISSN: 0028-646X</identifier><identifier>EISSN: 1469-8137</identifier><identifier>DOI: 10.1111/nph.17571</identifier><language>eng</language><publisher>Lancaster: Wiley Subscription Services, Inc</publisher><subject>Dehydration ; drought resistance ; drought tolerance ; Embolism ; Environmental Sciences ; Estimates ; Extreme value theory ; Extreme values ; hydraulic risk ; hydraulic safety margin ; Hydraulics ; minimum water potential ; physiological limits ; Probability distribution ; Probability theory ; Robustness ; Safety margins ; Species ; Statistical methods ; Water potential</subject><ispartof>The New phytologist, 2021-10, Vol.232 (1), p.404-417</ispartof><rights>2021 The Authors. © 2021 New Phytologist Foundation</rights><rights>2021. 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><rights>Attribution - NonCommercial - NoDerivatives</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4651-5e1f95e9f0de7a9d361b84e132c3190ee639de9c8302364324e06f0c1dcbaa2e3</citedby><cites>FETCH-LOGICAL-c4651-5e1f95e9f0de7a9d361b84e132c3190ee639de9c8302364324e06f0c1dcbaa2e3</cites><orcidid>0000-0001-7132-2080 ; 0000-0001-9086-7940 ; 0000-0003-3442-1711 ; 0000-0003-0840-1477 ; 0000-0001-5994-6122 ; 0000-0002-1432-1214 ; 0000-0002-9653-7421 ; 0000-0002-2332-7298 ; 0000-0003-0521-2523</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fnph.17571$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fnph.17571$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>230,314,780,784,885,1417,1433,27924,27925,45574,45575,46409,46833</link.rule.ids><backlink>$$Uhttps://hal.inrae.fr/hal-03610717$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Martínez‐Vilalta, Jordi</creatorcontrib><creatorcontrib>Santiago, Louis S.</creatorcontrib><creatorcontrib>Poyatos, Rafael</creatorcontrib><creatorcontrib>Badiella, Llorenç</creatorcontrib><creatorcontrib>Cáceres, Miquel</creatorcontrib><creatorcontrib>Aranda, Ismael</creatorcontrib><creatorcontrib>Delzon, Sylvain</creatorcontrib><creatorcontrib>Vilagrosa, Alberto</creatorcontrib><creatorcontrib>Mencuccini, Maurizio</creatorcontrib><title>Towards a statistically robust determination of minimum water potential and hydraulic risk in plants</title><title>The New phytologist</title><description>Summary
Minimum water potential (Ψmin) is a key variable for characterizing dehydration tolerance and hydraulic safety margins (HSMs) in plants. Ψmin is usually estimated as the absolute minimum tissue Ψ experienced by a species, but this is problematic because sample extremes are affected by sample size and the underlying probability distribution.
We compare alternative approaches to estimate Ψmin and assess the corresponding uncertainties and biases; propose statistically robust estimation methods based on extreme value theory (EVT); and assess the implications of our results for the characterization of hydraulic risk.
Our results show that current estimates of Ψmin and HSMs are biased, as they are strongly affected by sample size. Because sampling effort is generally higher for species living in dry environments, the differences in current Ψmin estimates between these species and those living under milder conditions are partly artefactual. When this bias is corrected using EVT methods, resulting HSMs tend to increase substantially with resistance to embolism across species.
Although data availability and representativeness remain the main challenges for proper determination of Ψmin, a closer look at Ψ distributions and the use of statistically robust methods to estimate Ψmin opens new ground for characterizing plant hydraulic risks.</description><subject>Dehydration</subject><subject>drought resistance</subject><subject>drought tolerance</subject><subject>Embolism</subject><subject>Environmental Sciences</subject><subject>Estimates</subject><subject>Extreme value theory</subject><subject>Extreme values</subject><subject>hydraulic risk</subject><subject>hydraulic safety margin</subject><subject>Hydraulics</subject><subject>minimum water potential</subject><subject>physiological limits</subject><subject>Probability distribution</subject><subject>Probability theory</subject><subject>Robustness</subject><subject>Safety margins</subject><subject>Species</subject><subject>Statistical methods</subject><subject>Water potential</subject><issn>0028-646X</issn><issn>1469-8137</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><recordid>eNp1kDFPwzAQhS0EEqUw8A8sMTGktePEScaqAopUAUOR2CzXdlSXxA62Q5V_j0sQTNxyp3vfPZ0eANcYzXCsuel2M1zkBT4BE5zRKikxKU7BBKG0TGhG387Bhfd7hFCV03QC5MYeuJMecugDD9oHLXjTDNDZbe8DlCoo12oTJWugrWGcddu38MCjADsblAmaN5AbCXeDdLxvtIBO-3eoDewaboK_BGc1b7y6-ulT8Hp_t1mukvXzw-NysU5ERnOc5ArXVa6qGklV8EoSirdlpjBJBcEVUoqSSqpKlASlhGYkzRSiNRJYii3nqSJTcDv67njDOqdb7gZmuWarxZoddyhaogIXnziyNyPbOfvRKx_Y3vbOxPdYmtNjOJjQP0fhrPdO1b-2GLFj4CwGzr4Dj-x8ZA-6UcP_IHt6WY0XX6y_gto</recordid><startdate>202110</startdate><enddate>202110</enddate><creator>Martínez‐Vilalta, Jordi</creator><creator>Santiago, Louis S.</creator><creator>Poyatos, Rafael</creator><creator>Badiella, Llorenç</creator><creator>Cáceres, Miquel</creator><creator>Aranda, Ismael</creator><creator>Delzon, Sylvain</creator><creator>Vilagrosa, Alberto</creator><creator>Mencuccini, Maurizio</creator><general>Wiley Subscription Services, Inc</general><general>Wiley</general><scope>24P</scope><scope>WIN</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>7SN</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H95</scope><scope>L.G</scope><scope>M7N</scope><scope>P64</scope><scope>RC3</scope><scope>1XC</scope><scope>VOOES</scope><orcidid>https://orcid.org/0000-0001-7132-2080</orcidid><orcidid>https://orcid.org/0000-0001-9086-7940</orcidid><orcidid>https://orcid.org/0000-0003-3442-1711</orcidid><orcidid>https://orcid.org/0000-0003-0840-1477</orcidid><orcidid>https://orcid.org/0000-0001-5994-6122</orcidid><orcidid>https://orcid.org/0000-0002-1432-1214</orcidid><orcidid>https://orcid.org/0000-0002-9653-7421</orcidid><orcidid>https://orcid.org/0000-0002-2332-7298</orcidid><orcidid>https://orcid.org/0000-0003-0521-2523</orcidid></search><sort><creationdate>202110</creationdate><title>Towards a statistically robust determination of minimum water potential and hydraulic risk in plants</title><author>Martínez‐Vilalta, Jordi ; Santiago, Louis S. ; Poyatos, Rafael ; Badiella, Llorenç ; Cáceres, Miquel ; Aranda, Ismael ; Delzon, Sylvain ; Vilagrosa, Alberto ; Mencuccini, Maurizio</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4651-5e1f95e9f0de7a9d361b84e132c3190ee639de9c8302364324e06f0c1dcbaa2e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Dehydration</topic><topic>drought resistance</topic><topic>drought tolerance</topic><topic>Embolism</topic><topic>Environmental Sciences</topic><topic>Estimates</topic><topic>Extreme value theory</topic><topic>Extreme values</topic><topic>hydraulic risk</topic><topic>hydraulic safety margin</topic><topic>Hydraulics</topic><topic>minimum water potential</topic><topic>physiological limits</topic><topic>Probability distribution</topic><topic>Probability theory</topic><topic>Robustness</topic><topic>Safety margins</topic><topic>Species</topic><topic>Statistical methods</topic><topic>Water potential</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Martínez‐Vilalta, Jordi</creatorcontrib><creatorcontrib>Santiago, Louis S.</creatorcontrib><creatorcontrib>Poyatos, Rafael</creatorcontrib><creatorcontrib>Badiella, Llorenç</creatorcontrib><creatorcontrib>Cáceres, Miquel</creatorcontrib><creatorcontrib>Aranda, Ismael</creatorcontrib><creatorcontrib>Delzon, Sylvain</creatorcontrib><creatorcontrib>Vilagrosa, Alberto</creatorcontrib><creatorcontrib>Mencuccini, Maurizio</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>Wiley Online Library (Open Access Collection)</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Ecology Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 1: Biological Sciences & Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>The New phytologist</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Martínez‐Vilalta, Jordi</au><au>Santiago, Louis S.</au><au>Poyatos, Rafael</au><au>Badiella, Llorenç</au><au>Cáceres, Miquel</au><au>Aranda, Ismael</au><au>Delzon, Sylvain</au><au>Vilagrosa, Alberto</au><au>Mencuccini, Maurizio</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Towards a statistically robust determination of minimum water potential and hydraulic risk in plants</atitle><jtitle>The New phytologist</jtitle><date>2021-10</date><risdate>2021</risdate><volume>232</volume><issue>1</issue><spage>404</spage><epage>417</epage><pages>404-417</pages><issn>0028-646X</issn><eissn>1469-8137</eissn><abstract>Summary
Minimum water potential (Ψmin) is a key variable for characterizing dehydration tolerance and hydraulic safety margins (HSMs) in plants. Ψmin is usually estimated as the absolute minimum tissue Ψ experienced by a species, but this is problematic because sample extremes are affected by sample size and the underlying probability distribution.
We compare alternative approaches to estimate Ψmin and assess the corresponding uncertainties and biases; propose statistically robust estimation methods based on extreme value theory (EVT); and assess the implications of our results for the characterization of hydraulic risk.
Our results show that current estimates of Ψmin and HSMs are biased, as they are strongly affected by sample size. Because sampling effort is generally higher for species living in dry environments, the differences in current Ψmin estimates between these species and those living under milder conditions are partly artefactual. When this bias is corrected using EVT methods, resulting HSMs tend to increase substantially with resistance to embolism across species.
Although data availability and representativeness remain the main challenges for proper determination of Ψmin, a closer look at Ψ distributions and the use of statistically robust methods to estimate Ψmin opens new ground for characterizing plant hydraulic risks.</abstract><cop>Lancaster</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1111/nph.17571</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0001-7132-2080</orcidid><orcidid>https://orcid.org/0000-0001-9086-7940</orcidid><orcidid>https://orcid.org/0000-0003-3442-1711</orcidid><orcidid>https://orcid.org/0000-0003-0840-1477</orcidid><orcidid>https://orcid.org/0000-0001-5994-6122</orcidid><orcidid>https://orcid.org/0000-0002-1432-1214</orcidid><orcidid>https://orcid.org/0000-0002-9653-7421</orcidid><orcidid>https://orcid.org/0000-0002-2332-7298</orcidid><orcidid>https://orcid.org/0000-0003-0521-2523</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Dehydration drought resistance drought tolerance Embolism Environmental Sciences Estimates Extreme value theory Extreme values hydraulic risk hydraulic safety margin Hydraulics minimum water potential physiological limits Probability distribution Probability theory Robustness Safety margins Species Statistical methods Water potential |
title | Towards a statistically robust determination of minimum water potential and hydraulic risk in plants |
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