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| Titel |
CREST (Climate REconstruction SofTware): a probability density function (PDF)-based quantitative climate reconstruction method |
| VerfasserIn |
M. Chevalier, R. Cheddadi, B. M. Chase |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1814-9324
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| Digitales Dokument |
URL |
| Erschienen |
In: Climate of the Past ; 10, no. 6 ; Nr. 10, no. 6 (2014-11-28), S.2081-2098 |
| Datensatznummer |
250117080
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| Publikation (Nr.) |
 copernicus.org/cp-10-2081-2014.pdf |
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| Zusammenfassung |
| 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. |
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