8 citations as recorded by crossref.

1. Can machine-learning algorithms improve upon classical palaeoenvironmental reconstruction models? P. Sun et al. https://doi.org/10.5194/cp-20-2373-2024
2. An improved statistical approach for reconstructing past climates from biotic assemblages M. Liu et al. https://doi.org/10.1098/rspa.2020.0346
3. Revising Estimates of Spatially Variable Subsidence during the A.D. 1700 Cascadia Earthquake Using a Bayesian Foraminiferal Transfer Function A. Kemp et al. https://doi.org/10.1785/0120170269
4. Combining a pollen and macrofossil synthesis with climate simulations for spatial reconstructions of European climate using Bayesian filtering N. Weitzel et al. https://doi.org/10.5194/cp-15-1275-2019
5. Holocene climates of the Iberian Peninsula: pollen-based reconstructions of changes in the west–east gradient of temperature and moisture M. Liu et al. https://doi.org/10.5194/cp-19-803-2023
6. Temperature reconstructions for the last 1.74-Ma on the eastern Tibetan Plateau based on a novel pollen-based quantitative method Y. Zhao et al. https://doi.org/10.1016/j.gloplacha.2021.103433
7. Timing and amount of southern Cascadia earthquake subsidence over the past 1700 years at northern Humboldt Bay, California, USA J. Padgett et al. https://doi.org/10.1130/B35701.1
8. Statistical challenges in estimating past climate changes J. Sweeney et al. https://doi.org/10.1002/wics.1437