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Stepping up to the thermogradient plate: a data framework for predicting seed germination under climate change

BACKGROUND AND AIMS: Seed germination is strongly influenced by environmental temperatures. With global temperatures predicted to rise, the timing of germination for thousands of plant species could change, leading to potential decreases in fitness and ecosystem-wide impacts. The thermogradient plat...

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Autores principales: Collette, Justin C, Sommerville, Karen D, Lyons, Mitchell B, Offord, Catherine A, Errington, Graeme, Newby, Zoe-Joy, von Richter, Lotte, Emery, Nathan J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9292609/
https://www.ncbi.nlm.nih.gov/pubmed/35212713
http://dx.doi.org/10.1093/aob/mcac026
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author Collette, Justin C
Sommerville, Karen D
Lyons, Mitchell B
Offord, Catherine A
Errington, Graeme
Newby, Zoe-Joy
von Richter, Lotte
Emery, Nathan J
author_facet Collette, Justin C
Sommerville, Karen D
Lyons, Mitchell B
Offord, Catherine A
Errington, Graeme
Newby, Zoe-Joy
von Richter, Lotte
Emery, Nathan J
author_sort Collette, Justin C
collection PubMed
description BACKGROUND AND AIMS: Seed germination is strongly influenced by environmental temperatures. With global temperatures predicted to rise, the timing of germination for thousands of plant species could change, leading to potential decreases in fitness and ecosystem-wide impacts. The thermogradient plate (TGP) is a powerful but underutilized research tool that tests germination under a broad range of constant and alternating temperatures, giving researchers the ability to predict germination characteristics using current and future climates. Previously, limitations surrounding experimental design and data analysis methods have discouraged its use in seed biology research. METHODS: Here, we have developed a freely available R script that uses TGP data to analyse seed germination responses to temperature. We illustrate this analysis framework using three example species: Wollemia nobilis, Callitris baileyi and Alectryon subdentatus. The script generates >40 germination indices including germination rates and final germination across each cell of the TGP. These indices are then used to populate generalized additive models and predict germination under current and future monthly maximum and minimum temperatures anywhere on the globe. KEY RESULTS: In our study species, modelled data were highly correlated with observed data, allowing confident predictions of monthly germination patterns for current and future climates. Wollemia nobilis germinated across a broad range of temperatures and was relatively unaffected by predicted future temperatures. In contrast, C. baileyi and A. subdentatus showed strong seasonal temperature responses, and the timing for peak germination was predicted to shift seasonally under future temperatures. CONCLUSIONS: Our experimental workflow is a leap forward in the analysis of TGP experiments, increasing its many potential benefits, thereby improving research predictions and providing substantial information to inform management and conservation of plant species globally.
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spelling pubmed-92926092022-07-19 Stepping up to the thermogradient plate: a data framework for predicting seed germination under climate change Collette, Justin C Sommerville, Karen D Lyons, Mitchell B Offord, Catherine A Errington, Graeme Newby, Zoe-Joy von Richter, Lotte Emery, Nathan J Ann Bot Technical Article BACKGROUND AND AIMS: Seed germination is strongly influenced by environmental temperatures. With global temperatures predicted to rise, the timing of germination for thousands of plant species could change, leading to potential decreases in fitness and ecosystem-wide impacts. The thermogradient plate (TGP) is a powerful but underutilized research tool that tests germination under a broad range of constant and alternating temperatures, giving researchers the ability to predict germination characteristics using current and future climates. Previously, limitations surrounding experimental design and data analysis methods have discouraged its use in seed biology research. METHODS: Here, we have developed a freely available R script that uses TGP data to analyse seed germination responses to temperature. We illustrate this analysis framework using three example species: Wollemia nobilis, Callitris baileyi and Alectryon subdentatus. The script generates >40 germination indices including germination rates and final germination across each cell of the TGP. These indices are then used to populate generalized additive models and predict germination under current and future monthly maximum and minimum temperatures anywhere on the globe. KEY RESULTS: In our study species, modelled data were highly correlated with observed data, allowing confident predictions of monthly germination patterns for current and future climates. Wollemia nobilis germinated across a broad range of temperatures and was relatively unaffected by predicted future temperatures. In contrast, C. baileyi and A. subdentatus showed strong seasonal temperature responses, and the timing for peak germination was predicted to shift seasonally under future temperatures. CONCLUSIONS: Our experimental workflow is a leap forward in the analysis of TGP experiments, increasing its many potential benefits, thereby improving research predictions and providing substantial information to inform management and conservation of plant species globally. Oxford University Press 2022-02-25 /pmc/articles/PMC9292609/ /pubmed/35212713 http://dx.doi.org/10.1093/aob/mcac026 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of the Annals of Botany Company. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Technical Article
Collette, Justin C
Sommerville, Karen D
Lyons, Mitchell B
Offord, Catherine A
Errington, Graeme
Newby, Zoe-Joy
von Richter, Lotte
Emery, Nathan J
Stepping up to the thermogradient plate: a data framework for predicting seed germination under climate change
title Stepping up to the thermogradient plate: a data framework for predicting seed germination under climate change
title_full Stepping up to the thermogradient plate: a data framework for predicting seed germination under climate change
title_fullStr Stepping up to the thermogradient plate: a data framework for predicting seed germination under climate change
title_full_unstemmed Stepping up to the thermogradient plate: a data framework for predicting seed germination under climate change
title_short Stepping up to the thermogradient plate: a data framework for predicting seed germination under climate change
title_sort stepping up to the thermogradient plate: a data framework for predicting seed germination under climate change
topic Technical Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9292609/
https://www.ncbi.nlm.nih.gov/pubmed/35212713
http://dx.doi.org/10.1093/aob/mcac026
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