Browsing by Subject "Transfer function"
Now showing items 1-2 of 2
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(2019)Understanding local patterns and large-scale processes in past climate necessitates a detailed network of temperature reconstructions. In this study, a merged temperature inference model using fossil chironomid (Diptera: Chironomidae) datasets from Finland and Poland was constructed to fill the lack of an applicable training set for East European sites. The developed weighted averaging partial least squares (WA-PLS) inference model showed favorable performance statistics, suggesting that the model can be useful for downcore reconstructions. The combined calibration model includes 212 sites, 142 taxa, and a temperature gradient of 11.3-20.1 degrees C. The 2-component WA-PLS model has a cross-validated coefficient of determination of 0.88 and a root mean squared prediction error of 0.88 degrees C. We tested the new East European temperature transfer function in chironomid stratigraphies from a Finnish high-resolution short-core sediment record and a Polish paleolake (Zabieniec) covering the past similar to 20 000 yr. In the Finnish site, the chironomid-inferred temperatures correlated closely with the observed instrumental temperatures, showing improved accuracy compared to estimates by the original Finnish calibration model. In addition, the long-core reconstruction from the Polish site showed logical results in its general trends compared to existing knowledge on the past regional climate trends; however, it had distinct differences when compared with hemispheric climate oscillations. Hence, based on these findings, the new temperature model will enable more detailed examination of long-term temperature variability in Eastern Europe, and consequently, reliable identification of local and regional climate variability of the past.
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(2018)Fossil testate amoeba assemblages have been used to reconstruct peatland palaeohydrology for more than two decades. While transfer function training sets are typically of local-to regional-scale in extent, combining those data to cover broad ecohydrological gradients, from the regional-to continental- and hemispheric-scales, is useful to assess if ecological optima of species vary geographically and therefore may have also varied over time. Continental-scale transfer functions can also maximise modern analogue quality without losing reconstructive skill, providing the opportunity to contextualise understanding of purely statistical outputs with greater insight into the biogeography of organisms. Here, we compiled, at moderate taxonomic resolution, a dataset of nearly 2000 modern surface peatland testate amoeba samples from 137 peatlands throughout North America. We developed transfer functions using four model types, tested them statistically and applied them to independent palaeoenvironmental data. By subdividing the dataset into eco-regions, we examined biogeographical patterns of hydrological optima and species distribution across North America. We combined our new dataset with data from Europe to create a combined transfer function. The performance of our North-American transfer function was equivalent to published models and reconstructions were comparable to those developed using regional training sets. The new model can therefore be used as an effective tool to reconstruct peatland palaeohydrology throughout the North American continent. Some eco-regions exhibited lower taxonomic diversity and some key indicator taxa had restricted ranges. However, these patterns occurred against a background of general cosmopolitanism, at the moderate taxonomic resolution used. Likely biogeographical patterns at higher taxonomic resolution therefore do not affect transfer function performance. Output from the combined North American and European model suggested that any geographical limit of scale beyond which further compilation of peatland testate amoeba data would not be valid has not yet been reached, therefore advocating the potential for a Holarctic synthesis of peatland testate amoeba data. Extending data synthesis to the tropics and the Southern Hemisphere would be more challenging due to higher regional endemism in those areas. (C) 2018 The Authors. Published by Elsevier Ltd.
