Past, present, and future geographic range of the relict Mediterranean and Macaronesian Juniperus phoenicea complex

Distribution patterns of Quercus ilex from the last interglacial period to the future by ecological niche modeling

The plants' geographic distribution is affected by natural or human-induced climate change. Numerous studies at both the global and regional levels currently focus on the potential changes in plant distribution areas. Ecological niche modeling can help predict the likely distribution of species according to environmental variables under different climate scenarios. In this study, we predicted the potential geographic distributions of Quercus ilex L. (holm oak), a keystone species of the Mediterranean ecosystem, for the Last Interglacial period (LIG: ~130 Ka), the Last Glacial Maximum (LGM: ~22 Ka), mid-Holocene (MH: ~6 Ka), and future climate scenarios (Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios) for 2050-2070 obtained from CCSM4 and MIROC-ESM global climate scenarios respectively. The models were produced with algorithms from the R-package "biomod2" and assessed by AUC of the receiver operating characteristic plot and true skill statistics. Aside from BIOCLIM (SRE), all model algorithms performed similarly and produced projections that are supported by good evaluation scores, although random forest (RF) slightly outperformed all the others. Additionally, distribution maps generated for the past period were validated through a comparison with pollen data acquired from the Neotoma Pollen Database. The results revealed that southern areas of the Mediterranean Basin, particularly coastal regions, served as long-term refugia for Q. ilex, which was supported by fossil pollen data. Furthermore, the models suggest long-term refugia role for Anatolia and we argue that Anatolia may have served as a founding population for the species. Future climate scenarios indicated that Q. ilex distribution varied by region, with some areas experiencing range contractions and others range expands. This study provides significant insights into the vulnerability of the Q. ilex to future climate change in the Mediterranean ecosystem and highlights the crucial role of Anatolia in the species' historical distribution.

The Perspective of Arctic-Alpine Species in Southernmost Localities: The Example of Kalmia procumbens in the Pyrenees and Carpathians

High-mountain and arctic plants are considered especially sensitive to climate change because of their close adaptation to the cold environment. Kalmia procumbens, a typical arctic-alpine species, reaches southernmost European localities in the Pyrenees and Carpathians. The aim of this study was the assessment and comparison of the current potential niche areas of K. procumbens in the Pyrenees and Carpathians and their possible reduction due to climate change, depending on the scenario. The realized niches of K. procumbens in the Pyrenees are compact, while those in the Carpathians are dispersed. In both mountain chains, the species occurs in the alpine and subalpine vegetation belts, going down to elevations of about 1500-1600 m, while the most elevated localities in the Pyrenees are at ca. 3000 m, about 500 m higher than those in the Carpathians. The localities of K. procumbens in the Carpathians have a more continental climate than those in the Pyrenees, with lower precipitation and temperatures but higher seasonality of temperature and precipitation. The species covered a larger area of geographic range during the Last Glacial Maximum, but its geographic range was reduced during the mid-Holocene. Due to climate warming, a reduction in the potential area of occurrence could be expected in 2100; this reduction is expected to be strong in the Carpathians and moderate in the Pyrenees.

Clay and climatic variability explain the global potential distribution of Juniperus phoenicea toward restoration planning

Juniperus phoenicea is a medicinal conifer tree species distributed mainly in the Mediterranean region, and it is IUCN Red Listed species, locally threatened due to arid conditions and seed over-collection for medicinal purposes, particularly in the East-Mediterranean region. Several studies have addressed the potential distribution of J. phoenicea using bioclimatic and topographic variables at a local or global scale, but little is known about the role of soil and human influences as potential drivers. Therefore, our objectives were to determine the most influential predictor factors and their relative importance that might be limiting the regeneration of J. phoenicea, in addition, identifying the most suitable areas which could be assumed as priority conservation areas. We used ensemble models for species distribution modelling. Our findings revealed that aridity, temperature seasonality, and clay content are the most important factors limiting the potential distribution of J. phoenicea. Potentially suitable areas of the output maps, in which J. phoenicea populations degraded, could be assumed as decision-support tool reforestation planning. Other suitable areas, where there was no previous tree cover are a promising tool for afforestation and conservation planning. Finally, conservation actions are needed for natural habitats, particularly in the arid and semi-arid regions, which are highly threatened by global warming.

Phenotypic Comparison of Three Populations of Juniperus turbinata Guss. in North-Eastern Morocco

Juniperus turbinata Guss. is a native species of Morocco; however, an exhaustive taxonomic description based on phenotypical characterization of north-eastern Moroccan population species is lacking, which might lead to taxonomic confusion. In order to expound the phenotypic description of J. turbinata of the north-eastern Moroccan population and to examine the taxonomic differences within it; a comparative analysis of cones, leaves, and seeds was performed between three populations. A total of 280 samples were compared on the basis of nine measured and eight calculated traits. The results reveal significant interpopulation changes in the studied characteristics of cones, leaves, and seeds. The most discriminating traits were associated with the proportion between cone diameter and number of seeds. We detected the lowest number of seeds in coastal population when compared to other localities, but at the same time, the seeds from the littoral were the longest and the widest. In addition, the semi-continental population had the highest quantity of seeds, and leaves had intermediate values for the majority of the assessed traits. The phenotypical difference between populations demonstrates a certain adaptability of the species in a biogeographical pattern. This study is a contribution to completing the description of patterns of phenotypical differences of the Phoenician juniper in the Mediterranean region, and confirms its evolutionary plasticity linked to adaptation to local environmental conditions.

Predicting the Potential Global Distribution of Amblyomma americanum (Acari: Ixodidae) under Near Current and Future Climatic Conditions, Using the Maximum Entropy Model

Amblyomma americanum (the lone star tick) is a pathogen vector, mainly from eastern North America, that bites humans. With global integration and climate change, some ticks that are currently confined to a certain place may begin to spread out; some reports have shown that they are undergoing rapid range expansion. The difference in the potential geographic distribution of A. americanum under current and future climatic conditions is dependent on environment variables such as temperature and precipitation, which can affect their survival. In this study, we used a maximum entropy (MaxEnt) model to predict the potential geographic distribution of A. americanum. The MaxEnt model was calibrated at the native range of A. americanum using occurrence data and the current climatic conditions. Seven WorldClim climatic variables were selected by the jackknife method and tested in MaxEnt using different combinations of model feature class functions and regularization multiplier values. The best model was chosen based on the omission rate and the lowest Akaike information criterion. The resulting model was then projected onto the global scale using the current and future climate conditions modeled under four greenhouse gas emission scenarios.