Plant water potential improves prediction of empirical stomatal models.
Climate change is expected to lead to increases in drought frequency and severity, with deleterious effects on many ecosystems. Stomatal responses to changing environmental conditions form the backbone of all ecosystem models, but are based on empirical relationships and are not well-tested during d...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2017-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC5638234?pdf=render |
| _version_ | 1819065495796580352 |
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| author | William R L Anderegg Adam Wolf Adriana Arango-Velez Brendan Choat Daniel J Chmura Steven Jansen Thomas Kolb Shan Li Frederick Meinzer Pilar Pita Víctor Resco de Dios John S Sperry Brett T Wolfe Stephen Pacala |
| author_facet | William R L Anderegg Adam Wolf Adriana Arango-Velez Brendan Choat Daniel J Chmura Steven Jansen Thomas Kolb Shan Li Frederick Meinzer Pilar Pita Víctor Resco de Dios John S Sperry Brett T Wolfe Stephen Pacala |
| author_sort | William R L Anderegg |
| collection | DOAJ |
| description | Climate change is expected to lead to increases in drought frequency and severity, with deleterious effects on many ecosystems. Stomatal responses to changing environmental conditions form the backbone of all ecosystem models, but are based on empirical relationships and are not well-tested during drought conditions. Here, we use a dataset of 34 woody plant species spanning global forest biomes to examine the effect of leaf water potential on stomatal conductance and test the predictive accuracy of three major stomatal models and a recently proposed model. We find that current leaf-level empirical models have consistent biases of over-prediction of stomatal conductance during dry conditions, particularly at low soil water potentials. Furthermore, the recently proposed stomatal conductance model yields increases in predictive capability compared to current models, and with particular improvement during drought conditions. Our results reveal that including stomatal sensitivity to declining water potential and consequent impairment of plant water transport will improve predictions during drought conditions and show that many biomes contain a diversity of plant stomatal strategies that range from risky to conservative stomatal regulation during water stress. Such improvements in stomatal simulation are greatly needed to help unravel and predict the response of ecosystems to future climate extremes. |
| first_indexed | 2024-12-21T15:47:23Z |
| format | Article |
| id | doaj.art-2743945e863d4cea8ff729dacc612ca4 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-21T15:47:23Z |
| publishDate | 2017-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-2743945e863d4cea8ff729dacc612ca42022-12-21T18:58:19ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-011210e018548110.1371/journal.pone.0185481Plant water potential improves prediction of empirical stomatal models.William R L AndereggAdam WolfAdriana Arango-VelezBrendan ChoatDaniel J ChmuraSteven JansenThomas KolbShan LiFrederick MeinzerPilar PitaVíctor Resco de DiosJohn S SperryBrett T WolfeStephen PacalaClimate change is expected to lead to increases in drought frequency and severity, with deleterious effects on many ecosystems. Stomatal responses to changing environmental conditions form the backbone of all ecosystem models, but are based on empirical relationships and are not well-tested during drought conditions. Here, we use a dataset of 34 woody plant species spanning global forest biomes to examine the effect of leaf water potential on stomatal conductance and test the predictive accuracy of three major stomatal models and a recently proposed model. We find that current leaf-level empirical models have consistent biases of over-prediction of stomatal conductance during dry conditions, particularly at low soil water potentials. Furthermore, the recently proposed stomatal conductance model yields increases in predictive capability compared to current models, and with particular improvement during drought conditions. Our results reveal that including stomatal sensitivity to declining water potential and consequent impairment of plant water transport will improve predictions during drought conditions and show that many biomes contain a diversity of plant stomatal strategies that range from risky to conservative stomatal regulation during water stress. Such improvements in stomatal simulation are greatly needed to help unravel and predict the response of ecosystems to future climate extremes.http://europepmc.org/articles/PMC5638234?pdf=render |
| spellingShingle | William R L Anderegg Adam Wolf Adriana Arango-Velez Brendan Choat Daniel J Chmura Steven Jansen Thomas Kolb Shan Li Frederick Meinzer Pilar Pita Víctor Resco de Dios John S Sperry Brett T Wolfe Stephen Pacala Plant water potential improves prediction of empirical stomatal models. PLoS ONE |
| title | Plant water potential improves prediction of empirical stomatal models. |
| title_full | Plant water potential improves prediction of empirical stomatal models. |
| title_fullStr | Plant water potential improves prediction of empirical stomatal models. |
| title_full_unstemmed | Plant water potential improves prediction of empirical stomatal models. |
| title_short | Plant water potential improves prediction of empirical stomatal models. |
| title_sort | plant water potential improves prediction of empirical stomatal models |
| url | http://europepmc.org/articles/PMC5638234?pdf=render |
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