Science Enabled by Specimen Data
Chevalier, M. 2022. <i>crestr</i>: an R package to perform probabilistic climate reconstructions from palaeoecological datasets. Climate of the Past 18: 821–844. https://doi.org/10.5194/cp-18-821-2022
Abstract. Statistical climate reconstruction techniques are fundamental tools to study past climate variability from fossil proxy data. In particular, the methods based on probability density functions (or PDFs) can be used in various environments and with different climate proxies because they rely on elementary calibration data (i.e. modern geolocalised presence data). However, the difficulty of accessing and curating these calibration data and the complexity of interpreting probabilistic results have often limited their use in palaeoclimatological studies. Here, I introduce a new R package (crestr) to apply the PDF-based method CREST (Climate REconstruction SofTware) on diverse palaeoecological datasets and address these problems. crestr includes a globally curated calibration dataset for six common climate proxies (i.e. plants, beetles, chironomids, rodents, foraminifera, and dinoflagellate cysts) associated with an extensive range of climate variables (20 terrestrial and 19 marine variables) that enables its use in most terrestrial and marine environments. Private data collections can also be used instead of, or in combination with, the provided calibration dataset. The package includes a suite of graphical diagnostic tools to represent the data at each step of the reconstruction process and provide insights into the effect of the different modelling assumptions and external factors that underlie a reconstruction. With this R package, the CREST method can now be used in a scriptable environment and thus be more easily integrated with existing workflows. It is hoped that crestr will be used to produce the much-needed quantified climate reconstructions from the many regions where they are currently lacking, despite the availability of suitable fossil records. To support this development, the use of the package is illustrated with a step-by-step replication of a 790 000-year-long mean annual temperature reconstruction based on a pollen record from southeastern Africa.
Campbell, C., G. Granath, and H. Rydin. 2021. Climatic drivers of Sphagnum species distributions. Frontiers of Biogeography 13. https://doi.org/10.21425/f5fbg51146
Peatmosses(genus Sphagnum) dominate most Northern mires and show distinct distributional limits in Europe despite having efficient dispersal and few dispersal barriers. This pattern indicates that Sphagnum species distributions are strongly linked to climate. Sphagnumdominated mires have been the la…
Yi, S., C.-P. Jun, K. Jo, H. Lee, M.-S. Kim, S. D. Lee, X. Cao, and J. Lim. 2020. Asynchronous multi-decadal time-scale series of biotic and abiotic responses to precipitation during the last 1300 years. Scientific Reports 10. https://doi.org/10.1038/s41598-020-74994-x
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Chase, B. M., A. Boom, A. S. Carr, M. Chevalier, L. J. Quick, G. A. Verboom, and P. J. Reimer. 2019. Extreme hydroclimate response gradients within the western Cape Floristic region of South Africa since the Last Glacial Maximum. Quaternary Science Reviews 219: 297–307. https://doi.org/10.1016/j.quascirev.2019.07.006
The Cape Floristic Region (CFR) is one of the world's major biodiversity hotspots, and much work has gone into identifying the drivers of this diversity. Considered regionally in the context of Quaternary climate change, climate stability is generally accepted as being one of the major factors promo…
Chevalier, M., B. M. Chase, L. J. Quick, L. M. Dupont, and T. C. Johnson. 2020. Temperature change in subtropical southeastern Africa during the past 790,000 yr. Geology 49: 71–75. https://doi.org/10.1130/G47841.1
Across the glacial-interglacial cycles of the late Pleistocene (~700 k.y.), temperature variability at low latitudes is often considered to have been negligible compared to changes in precipitation. However, a paucity of quantified temperature records makes this difficult to reliably assess. In this…