Abstract

Understanding the ecology of populations located in the rear edge of their distribution is key to assessing the response of the species to changing environmental conditions. Here, we focus on rear-edge populations of Quercus pyrenaica in Sierra Nevada (southern Iberian Peninsula) to analyze their ecological and floristic diversity. We perform multivariate analyses using high-resolution environmental information and forest inventories to determine how environmental variables differ among oak populations, and to identify population groups based on environmental and floristic composition. We find that water availability is a key variable in explaining the distribution of Q. pyrenaica and the floristic diversity of their accompanying communities within its rear edge. Three cluster of oak populations were identified based on environmental variables. We found differences among these clusters regarding plant diversity, but not for forest attributes. A remarkable match between the populations clustering derived from analysis of environmental variables and the ordination of the populations according to species composition was found. The diversity of ecological behaviors for Q. pyrenaica populations in this rear edge are consistent with the high genetic diversity shown by populations of this oak in the Sierra Nevada. The identification of differences between oak populations within the rear-edge with respect to environmental variables can aid with planning the forest management and restoration actions, particularly considering the importance of some environmental factors in key ecological aspects.

Highlights

  • The study of ecological dynamics within the rear-edge populations is considered essential to establish proper management guidelines under current climate uncertainties [1]

  • Considering that the conservation strategies for tree species need to take into account the peculiarities of the rear-edge populations [1,2,37], and the high vulnerability to climate change of Q. pyrenaica [30], we focus here on the rear-edge populations of this species in the mountains of southern Iberian Peninsula to answer the question: Are the environmental conditions of the rear-edge populations of Q. pyrenaica in Sierra Nevada homogeneous? The answer to this question may be useful to analyze how the predicted climate changes would impact the rear-edge population, providing valuable information for the development of efficient forest management and restoration plans

  • The objectives of the work were: (i) to determine the most important environmental variables for the distribution of Pyrenean oak populations in Sierra Nevada; (ii) to identify groups of Pyrenean oak populations based on floristic composition and environmental conditions; and (iii) to unveil whether the rear-edge populations clustering according to environmental variables coincides with their grouping based on their floristic composition

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Summary

Introduction

The study of ecological dynamics within the rear-edge populations is considered essential to establish proper management guidelines under current climate uncertainties [1]. The heterogeneity in the response to climate change observed across ecological and geographical gradients [8,9,10,11], justifies the need to incorporate fine-scale variation of environment variables throughout species ranges to better understand species responses to global change [12,13] This is important for mountain landscapes, where the topographic complexity may cause a decoupling between the climate and the geographic spaces [14,15]. The environmental heterogeneity (microclimate, geomorphology, topography, etc.) found in mountains allows the existence of a diverse plethora of ecological conditions at very fine spatial scales [16,17], offering an excellent opportunity to study ecological responses to future environmental changes [18,19,20,21] Some tree species, such as Pinus sylvestris and Quercus pyrenaica, have their rear-edge populations located in mountainous areas of southern Europe. If the environmental conditions are heterogeneous, we expect a variety of responses, which forces us to consider different future scenarios at a very fine spatial scale, since climate change sensitivities could strongly vary at local scales [5,26,27]

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