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Which climate change path are we following? Bad news from Scots pine
Current expectations on future climate derive from coordinated experiments, which compile many climate models for sampling the entire uncertainty related to emission scenarios, initial conditions, and modelling process. Quantifying this uncertainty is important for taking decisions that are robust u...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5734685/ https://www.ncbi.nlm.nih.gov/pubmed/29252985 http://dx.doi.org/10.1371/journal.pone.0189468 |
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author | Bombi, Pierluigi D’Andrea, Ettore Rezaie, Negar Cammarano, Mario Matteucci, Giorgio |
author_facet | Bombi, Pierluigi D’Andrea, Ettore Rezaie, Negar Cammarano, Mario Matteucci, Giorgio |
author_sort | Bombi, Pierluigi |
collection | PubMed |
description | Current expectations on future climate derive from coordinated experiments, which compile many climate models for sampling the entire uncertainty related to emission scenarios, initial conditions, and modelling process. Quantifying this uncertainty is important for taking decisions that are robust under a wide range of possible future conditions. Nevertheless, if uncertainty is too large, it can prevent from planning specific and effective measures. For this reason, reducing the spectrum of the possible scenarios to a small number of one or a few models that actually represent the climate pathway influencing natural ecosystems would substantially increase our planning capacity. Here we adopt a multidisciplinary approach based on the comparison of observed and expected spatial patterns of response to climate change in order to identify which specific models, among those included in the CMIP5, catch the real climate variation driving the response of natural ecosystems. We used dendrochronological analyses for determining the geographic pattern of recent growth trends for three European species of trees. At the same time, we modelled the climatic niche for the same species and forecasted the suitability variation expected across Europe under each different GCM. Finally, we estimated how well each GCM explains the real response of ecosystems, by comparing the expected variation with the observed growth trends. Doing this, we identified four climatic models that are coherent with the observed trends. These models are close to the highest range limit of the climatic variations expected by the ensemble of the CMIP5 models, suggesting that current predictions of climate change impacts on ecosystems could be underestimated. |
format | Online Article Text |
id | pubmed-5734685 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-57346852017-12-22 Which climate change path are we following? Bad news from Scots pine Bombi, Pierluigi D’Andrea, Ettore Rezaie, Negar Cammarano, Mario Matteucci, Giorgio PLoS One Research Article Current expectations on future climate derive from coordinated experiments, which compile many climate models for sampling the entire uncertainty related to emission scenarios, initial conditions, and modelling process. Quantifying this uncertainty is important for taking decisions that are robust under a wide range of possible future conditions. Nevertheless, if uncertainty is too large, it can prevent from planning specific and effective measures. For this reason, reducing the spectrum of the possible scenarios to a small number of one or a few models that actually represent the climate pathway influencing natural ecosystems would substantially increase our planning capacity. Here we adopt a multidisciplinary approach based on the comparison of observed and expected spatial patterns of response to climate change in order to identify which specific models, among those included in the CMIP5, catch the real climate variation driving the response of natural ecosystems. We used dendrochronological analyses for determining the geographic pattern of recent growth trends for three European species of trees. At the same time, we modelled the climatic niche for the same species and forecasted the suitability variation expected across Europe under each different GCM. Finally, we estimated how well each GCM explains the real response of ecosystems, by comparing the expected variation with the observed growth trends. Doing this, we identified four climatic models that are coherent with the observed trends. These models are close to the highest range limit of the climatic variations expected by the ensemble of the CMIP5 models, suggesting that current predictions of climate change impacts on ecosystems could be underestimated. Public Library of Science 2017-12-18 /pmc/articles/PMC5734685/ /pubmed/29252985 http://dx.doi.org/10.1371/journal.pone.0189468 Text en © 2017 Bombi et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Bombi, Pierluigi D’Andrea, Ettore Rezaie, Negar Cammarano, Mario Matteucci, Giorgio Which climate change path are we following? Bad news from Scots pine |
title | Which climate change path are we following? Bad news from Scots pine |
title_full | Which climate change path are we following? Bad news from Scots pine |
title_fullStr | Which climate change path are we following? Bad news from Scots pine |
title_full_unstemmed | Which climate change path are we following? Bad news from Scots pine |
title_short | Which climate change path are we following? Bad news from Scots pine |
title_sort | which climate change path are we following? bad news from scots pine |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5734685/ https://www.ncbi.nlm.nih.gov/pubmed/29252985 http://dx.doi.org/10.1371/journal.pone.0189468 |
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