Coastal Pine-Oak Glacial Refugia in the Mediterranean Basin: A Biogeographic Approach Based on Charcoal Analysis and Spatial Modelling

Abstract

During the glacial episodes of the Quaternary, European forests were restricted to small favourable spots, namely refugia, acting as biodiversity reservoirs. the Iberian, Italian and Balkan peninsulas have been considered as the main glacial refugia of trees in Europe. In this study, we estimate the composition of the last glacial forest in a coastal cave of the Cilento area (SW Italy) in seven time frames, spanning from the last Pleniglacial to the Late Glacial. Charcoal analyses were performed in seven archaeological layers. Furthermore, a paleoclimate modelling (Maxent) approach was used to complement the taxonomic identification of charcoal fragments to estimate the past potential distribution of tree species in Europe. Our results showed that the mesothermophilous forest survived in this region in the core of the Mediterranean basin during the Last Glacial Period (LGP, since ~36 ka cal BP), indicating that this area played an important role as a reservoir of woodland biodiversity. Here, Quercus pubescens was the most abundant component, followed by a wide variety of deciduous trees and Pinus nigra. Charcoal data also pointed at the crucial role of this coastal area, acting as a reservoir for warm temperate trees of genera Tilia, Carpinus and Sambucus, in LGP, in the Mediterranean region. Our modelling results showed that P. nigra might be the main candidate as a “Pinus sylvestris type” in the study site in the Last Glacial Maximum (LGM). Furthermore, we found that P. nigra might coexist with Q. pubescens in several European territories both currently and in the LGM. All models showed high levels of predictive performances. Our results highlight the advantage of combining different approaches such as charcoal analysis and ecological niche models to explore biogeographic questions about past and current forest distribution, with important implications to inform today’s forest management and conservation.

The Relict Ecosystem of Maytenus senegalensis subsp. europaea in an Agricultural Landscape: Past, Present and Future Scenarios

“…Said software has been used in many fields of science which proved its validity [81][82][83][84][85], being widely recognized as the most used tool, even for small sample sizes and poorly known species' distributions [71]. The modelling process is able to indicate suitable conditions for species in areas where their presence has not been registered or evidenced; several studies supported the reliability of SDMs [67,86,87]. Since this process is iterative, the modelling outcomes can highlight other factors related to the physical environment, anthropogenic influences or conditions of growth and reproduction of the species [88][89][90].…”

“…Hence, several models from different communities may be obtained, and thus their spatial-temporal dynamics In order to achieve higher accuracy in establishing the influence of bioclimatic scenarios, models of singular thermophilic and xerophilous species that coexist with M. europaea could be compared in equal space-time conditions [113]. Hence, several models from different communities may be obtained, and thus their spatial-temporal dynamics analyzed [86,87]. In addition, indirect gradient variables corresponding to the physical characteristics of the territory (elevation, orientation, slope, geology, etc.)…”

A Disjunctive Marginal Edge of Evergreen Broad-Leaved Oak (Quercus gilva) in East Asia: The High Genetic Distinctiveness and Unusual Diversity of Jeju Island Populations and Insight into a Massive, Independent Postglacial Colonization

“…We found that the Jeju populations harbor a level of allele richness ( A R ) and private allele rate ( P riv ) comparable to those of Kyushu populations. Although, such indicators provide a strong possibility for the existence of refugia in this area [ 77 , 78 , 79 ], we are convinced that Jeju Island did not serve as the glacial refuge of Q. gilva . In agreement with our assumption, ENM showed that the probability values for the distribution of the trees on Jeju Island during the LGM converged at zero.…”

Planning priority conservation areas for biodiversity under climate change in topographically complex areas: A case study in Sichuan province, China

“…The maxent model ran 1, 000 iterations of the processes or set the value of threshold to 0.00001. Meanwhile, the Receiver Operating Characteristic plot, the Area Under Curve (AUC) values, and the True Skill Statistics (TSS) were used to measure the accuracy of the Maxent model [ 30 , 31 ]. The greater value of AUC represented the better performer [ 32 ].…”