CREST (Climate REconstruction SofTware): a probability density function (PDF)-based quantitative climate reconstruction method

Abstract

Abstract. 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.

Fallacies and fantasies: the theoretical underpinnings of the Coexistence Approach for palaeoclimate reconstruction

“…Greenwood et al, 2005;Boyle et al, 2008;Thompson et al, 2012;Chevalier et al, 2014;Harbert and Nixon, 2015), and there are avenues ripe for exploration (see, e.g., Broennimann et al, 2012;Denk et al, 2013). However, all of these methods require (further) testing and then careful, well-documented usage when reconstructing palaeoclimates.…”

“…Therefore, we suggest that any current or future taxon-based method be 1. tested against the modern flora (e.g. Boyle et al, 2008;Thompson et al, 2012;Chevalier et al, 2014;Harbert and Nixon, 2015).…”

“…5). This includes methods such as the weighted mutual climate range approach (Thompson et al, 2012), the probability density function method (Chevalier et al, 2014) and the coexistence likelihood estimation method (Harbert and Nixon, 2015). However, these methods will probably begin to break down when the nearest-living-relative principle is needed to link fossils with extant lineages (Thompson et al, 2012;Harbert and Nixon, 2015), and this may explain why their application has been limited to Quaternary assemblages.…”

50,000 years of vegetation and climate change in the southern Namib Desert, Pella, South Africa

“…To derive more specific palaeoclimatic information, we used the CREST software package (Climate REconstruction SofTware; Chevalier et al, 2014) to analyse the fossil pollen data from Pella. In this paper, we focus on the reconstruction of an aridity index (AI) and mean annual temperature (MAT).…”

Climate change and ecosystems dynamics over the last 6000 years in the Middle Atlas, Morocco

“…The monthly mean precipitation and T jan were obtained using the probability density function of modern plant species (pdf method). This method is described in Chevalier et al (2014). In order to apply it to a fossil pollen record collected in the Mediterranean area, it required a modern database of Mediterranean plant species distributions and their corresponding modern climate variables.…”