Determinants of distribution of six Pinus species in Catalonia, Spain

Authors

  • Mathieu Rouget,

    Corresponding author
    1. Institute for Plant Conservation, Botany Department, University of Cape Town, Rondebosch, 7701, South Africa
      *Corresponding author; Fax +27216504046; E-mail mrouget@botzoo.uct.ac.za
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  • David M. Richardson,

    1. Institute for Plant Conservation, Botany Department, University of Cape Town, Rondebosch, 7701, South Africa
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  • Sandra Lavorel,

    1. Centre d'Ecologie Fonctionnelle et Evolutive, CNRS UPR 9056, 1919 Route de Mende, F-34293 Montpellier Cedex 05, France
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  • Jordi Vayreda,

    1. Center for Ecological Research and Applied Forestry, CREAF, Autonomous University of Barcelona (UAB), E-08193 Bellaterra, Barcelona, Spain
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  • Carles Gracia,

    1. Center for Ecological Research and Applied Forestry, CREAF, Autonomous University of Barcelona (UAB), E-08193 Bellaterra, Barcelona, Spain
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  • Suzanne J. Milton

    1. Department of Nature Conservation, Faculty of Agricultural and Forestry Science, University of Stellenbosch, Private Bag XI, Matieland 7602, South Africa
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*Corresponding author; Fax +27216504046; E-mail mrouget@botzoo.uct.ac.za

Abstract

Abstract. This study explores the determinants of distribution, abundance and regeneration of six Pinus species (P. halepensis, P. nigra, P. pinaster, P. pinea, P. sylvestris and P. uncinata) that occur naturally in Catalonia, northeastern Spain. The aim of this study was to generate accurate predictions of the distribution of each species using simple and readily available environmental variables. We used recursive partitioning and GIS analyses to relate the data base of 10 600 field plots from the Forestry Inventory of Catalonia with abiotic and biotic characteristics of each plot. We present general patterns of distribution, dominance and regeneration for the six species and then focus on P. halepensis, the most abundant pine species in the western Mediterranean Basin. For all six species, the models correctly classified more than 80% of the distribution using abiotic factors, mainly altitude and rainfall variability. Biotic factors such as the basal area of other pine species were necessary to accurately predict patterns of pine species dominance. Biotic factors, especially the basal area of evergreen species (mainly Quercus ilex), were of overriding importance when predicting patterns of seedling occurrence. Potentially important factors such as land use and fire history were of little significance for predicting distribution at the scale of our study. Our models failed to predict accurately which species (and in which numbers) co-occur with P. halepensis. Factors not included in this study, such as stand age, disturbance (cutting, clearing) and other human-induced factors, are probably the main determinants of co-existence patterns.

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