Past, present and future distributions of Oriental beech (Fagus orientalis) under climate change projections

Conclusions In this study, we investigated the late Quaternary history of F. orientalis utilizing palynological data and past reconstructions and estimated the future distribution of the species in response to global climate change. We compared model outputs to the observed present distribution of F. orientalis and palynological records from LGM and MH. Based on these empirical data, the RF algorithm, among five algorithms in the R-package ‘biomod2’, performed best with more plausible results for both past and future distributions. As in previous studies using F. sylvatica and Quercus robur as focal species, models tend to overestimate occurrence probabilities. For LGM and MH, the results were roughly in accord with palynological data for the Sea of Mar- mara and the Black Sea region, while palynological data did not support potential refugia south of the Caspian Sea during LGM. However, genetically long isolated populations of Ori- ental beech south of the Caspian Sea strongly suggest that they survived the LGM in-situ. For future projections, with continuing climate change, F. orientalis populations in the western Eurasian region will be decreasing with increasing drought; the geographical range will con- tract leaving only two possible refugia, the southern Caspian Sea region (northern Iran) and the Caucasus. This study shows, albeit they can be improved by including other environmental data (e.g. aspect, soil), that our models provide crucial information on the effect of climate change on F.

orientalis in Asia Minor even when only considering the climate. In addition, these results emphasize the importance of combining evidence from modelling with real-world data, such as the rich Quaternary pollen record of Fagus, to understand species-specific responses to changing environments. Hence, these results should be taken into account in order to improve conservation and management plans for this important forest species in western Eurasia. Supporting information S1 Table. 19 bioclimatic variables obtained from WorldClim version 1.4. (PDF) S1 File. R code sheet for biomod2 package to perform SDM. (PDF) S1 Fig. Probability distributions of F. orientalis predicted for the present, MH, LGM, pessi- mistic (RCP 8.5) 2050 and 2070, moderate (RCP 4.5) 2050 and 2070, and optimistic (RCP 2.6) 2050 and 2070 with MaxEnt algorithm and MIROC–ESM GCM. (TIF) S2 Fig. Probability distributions of F. orientalis predicted for the present, MH, LGM, pessi- mistic (RCP 8.5) 2050 and 2070, moderate (RCP 4.5) 2050 and 2070, and optimistic (RCP 2.6) 2050 and 2070 with MaxEnt algorithm and CCSM4 GCM. (TIF) S3 Fig. Probability distributions of F. orientalis predicted for the present, MH, LGM, pessi- mistic (RCP 8.5) 2050 and 2070, moderate (RCP 4.5) 2050 and 2070, and optimistic (RCP 2.6) 2050 and 2070 with GLM algorithm and MIROC–ESM GCM. (TIF) S4 Fig. Probability distributions of F. orientalis predicted for the present, MH, LGM, pessi- mistic (RCP 8.5) 2050 and 2070, moderate (RCP 4.5) 2050 and 2070, and optimistic (RCP 2.6) 2050 and 2070 with GLM algorithm and CCSM4 GCM. (TIF) PLOS ONE

Species distribution modeling of Oriental beech (Fagus orientalis) PLOS ONE | https://doi.org/10.1371/journal.pone.0242280 November 17, 2020 13 / 19