CREST (Climate REconstruction SofTware): a probability density function (PDF)-based quantitative climate reconstruction method
Several methods currently exist to quantitatively reconstruct palaeoclimatic variables from fossil botanical data. Of these, probability density function (PDF)-based methods have proven valuable as they can be applied to a wide range of plant assemblages. Most commonly applied to fossil pollen data,...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2014-11-01
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| Series: | Climate of the Past |
| Online Access: | http://www.clim-past.net/10/2081/2014/cp-10-2081-2014.pdf |
| _version_ | 1811306380457410560 |
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| author | M. Chevalier R. Cheddadi B. M. Chase |
| author_facet | M. Chevalier R. Cheddadi B. M. Chase |
| author_sort | M. Chevalier |
| collection | DOAJ |
| description | Several methods currently exist to quantitatively reconstruct
palaeoclimatic variables from fossil botanical data. Of these, probability
density function (PDF)-based methods have proven
valuable as they can be applied to a wide range of plant
assemblages. Most commonly applied to fossil pollen data, their
performance, however, can be limited by the taxonomic resolution of
the pollen data, as many species may belong to a given
pollen type. Consequently, the climate information associated with
different species cannot always be precisely identified,
resulting in less-accurate reconstructions. This can become
particularly problematic in regions of high biodiversity. In this
paper, we propose a novel PDF-based method that takes into account
the different climatic requirements of each species constituting the
broader pollen type. PDFs are fitted in two successive steps, with
parametric PDFs fitted first for each species and then
a combination of those individual species PDFs into a broader
single PDF to represent the pollen type as a unit. A climate value
for the pollen assemblage is estimated from the likelihood function
obtained after the multiplication of the pollen-type PDFs, with
each being weighted according to its pollen percentage.
To test its performance, we have applied the method to southern Africa as a
regional case study and reconstructed a suite of climatic variables (e.g.
winter and summer temperature and precipitation, mean annual aridity,
rainfall seasonality). The reconstructions are shown to be accurate for
both temperature and precipitation. Predictable exceptions were areas that
experience conditions at the extremes of the regional climatic spectra.
Importantly, the accuracy of the reconstructed values is independent of the
vegetation type where the method is applied or the number of species used.
The method used in this study is publicly available in a software package
entitled CREST (Climate REconstruction SofTware) and will provide the opportunity to reconstruct quantitative
estimates of climatic variables even in areas with high geographical and
botanical diversity. |
| first_indexed | 2024-04-13T08:44:19Z |
| format | Article |
| id | doaj.art-6bb7de0209cc45a5b4d7cbe281856a51 |
| institution | Directory Open Access Journal |
| issn | 1814-9324 1814-9332 |
| language | English |
| last_indexed | 2024-04-13T08:44:19Z |
| publishDate | 2014-11-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Climate of the Past |
| spelling | doaj.art-6bb7de0209cc45a5b4d7cbe281856a512022-12-22T02:53:46ZengCopernicus PublicationsClimate of the Past1814-93241814-93322014-11-011062081209810.5194/cp-10-2081-2014CREST (Climate REconstruction SofTware): a probability density function (PDF)-based quantitative climate reconstruction methodM. Chevalier0R. Cheddadi1B. M. Chase2Institut des Sciences de l'Évolution de Montpellier, UMR 5554, Centre National de Recherche Scientifique/Université Montpellier 2, Bat. 22, CC061, Place Eugène Bataillon, 34095 Montpellier, CEDEX 5, FranceInstitut des Sciences de l'Évolution de Montpellier, UMR 5554, Centre National de Recherche Scientifique/Université Montpellier 2, Bat. 22, CC061, Place Eugène Bataillon, 34095 Montpellier, CEDEX 5, FranceInstitut des Sciences de l'Évolution de Montpellier, UMR 5554, Centre National de Recherche Scientifique/Université Montpellier 2, Bat. 22, CC061, Place Eugène Bataillon, 34095 Montpellier, CEDEX 5, FranceSeveral methods currently exist to quantitatively reconstruct palaeoclimatic variables from fossil botanical data. Of these, probability density function (PDF)-based methods have proven valuable as they can be applied to a wide range of plant assemblages. Most commonly applied to fossil pollen data, their performance, however, can be limited by the taxonomic resolution of the pollen data, as many species may belong to a given pollen type. Consequently, the climate information associated with different species cannot always be precisely identified, resulting in less-accurate reconstructions. This can become particularly problematic in regions of high biodiversity. In this paper, we propose a novel PDF-based method that takes into account the different climatic requirements of each species constituting the broader pollen type. PDFs are fitted in two successive steps, with parametric PDFs fitted first for each species and then a combination of those individual species PDFs into a broader single PDF to represent the pollen type as a unit. A climate value for the pollen assemblage is estimated from the likelihood function obtained after the multiplication of the pollen-type PDFs, with each being weighted according to its pollen percentage. To test its performance, we have applied the method to southern Africa as a regional case study and reconstructed a suite of climatic variables (e.g. winter and summer temperature and precipitation, mean annual aridity, rainfall seasonality). The reconstructions are shown to be accurate for both temperature and precipitation. Predictable exceptions were areas that experience conditions at the extremes of the regional climatic spectra. Importantly, the accuracy of the reconstructed values is independent of the vegetation type where the method is applied or the number of species used. The method used in this study is publicly available in a software package entitled CREST (Climate REconstruction SofTware) and will provide the opportunity to reconstruct quantitative estimates of climatic variables even in areas with high geographical and botanical diversity.http://www.clim-past.net/10/2081/2014/cp-10-2081-2014.pdf |
| spellingShingle | M. Chevalier R. Cheddadi B. M. Chase CREST (Climate REconstruction SofTware): a probability density function (PDF)-based quantitative climate reconstruction method Climate of the Past |
| title | CREST (Climate REconstruction SofTware): a probability density function (PDF)-based quantitative climate reconstruction method |
| title_full | CREST (Climate REconstruction SofTware): a probability density function (PDF)-based quantitative climate reconstruction method |
| title_fullStr | CREST (Climate REconstruction SofTware): a probability density function (PDF)-based quantitative climate reconstruction method |
| title_full_unstemmed | CREST (Climate REconstruction SofTware): a probability density function (PDF)-based quantitative climate reconstruction method |
| title_short | CREST (Climate REconstruction SofTware): a probability density function (PDF)-based quantitative climate reconstruction method |
| title_sort | crest climate reconstruction software a probability density function pdf based quantitative climate reconstruction method |
| url | http://www.clim-past.net/10/2081/2014/cp-10-2081-2014.pdf |
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