Improving the effectiveness of angular dispersion in plant neighbourhood models |
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| Authors: | MLA Richards MJ Aitkenhead AJS McDonald |
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| Institution: | 1. School of Biological Sciences, University of Aberdeen, Cruickshank Building, St Machar Drive, Aberdeen AB24 3UU, Scotland, UK;2. The Macaulay Institute, Craigiebuckler, Aberdeen AB15 8QH, Scotland, UK;1. School of Biological Sciences, University of Tasmania, Private Bag 55, Hobart, Tasmania 7001, Australia;2. Currency Creek Arboretum, PO Box 808, Melrose Park, South Australia 5039, Australia;1. Centre d’étude de la forêt, Département des sciences du bois et de la forêt, Pavillon Abitibi-Price, 2405 rue de la Terrasse, Université Laval, Québec, QC G1V 0A6, Canada;2. Département des sols et de génie agroalimentaire, Université Laval, Pavillon de l’Envirotron, 2480 boulevard Hochelaga, Québec, QC G1V 0A6, Canada;3. Direction de la recherche forestière, Ministère des Forêts, de la Faune et des Parcs du Québec 2700 rue Einstein, Québec, QC G1P 3W8, Canada;1. Department of Plant and Environmental Sciences, University of Copenhagen, Højbakkegaard Allé 13, DK-2630 Taastrup, Denmark;2. Department of Plant and Environmental Sciences, University of Copenhagen,Thorvaldsensvej 40, DK-1871 Frederiksberg, Denmark;1. Eskisehir Osmangazi University, Department of Statistics, 26480 Eskisehir, Turkey;2. Anadolu University, Department of Statistics, 26470 Eskisehir, Turkey;3. Ankara University, Department of Statistics, 06100 Ankara, Turkey;1. University of Minnesota, Department of Forest Resources, St. Paul, MN 55108, USA;2. University of Vermont, Rubenstein School of Environment and Natural Resources, Burlington, VT 05095, USA;3. USDA Forest Service, Northern Research Station, Grand Rapids, MN 55744, USA;4. University of Maine, School of Forest Resources, Orono, ME 04469, USA |
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| Abstract: | Spatial arrangement can be an important factor affecting competition among plants. We evaluated three ways to improve the effectiveness of angular dispersion (AD) for describing spatial arrangement in plant neighbourhood models. First, we modified Zar's (1974) AD formula by weighting each neighbour by its competitive influence. We calculated this using two different competition indices to derive an AD of competitive influence, rather than of equally weighted plant locations, around a subject plant. Secondly, we constrained the effect of AD on the neighbourhood model using an optimised parameter that defines the minimum value that AD can adopt. Thirdly, we included the direction in which competition is concentrated (the mean azimuth of the weighted AD) in the growth models. These developments were evaluated within a radial growth model of Scots pine and birch growing in semi-natural, spatially heterogeneous forest. Weighted AD resulted in significant improvements in predicted radial growth of target trees over the traditional measure of AD. The optimised parameter that defines the minimum value of AD consistently evolved values significantly higher than zero. This suggests that clumped and dispersed neighbourhoods do not differ in their negative effects on a subject tree as much as expected. The inclusion of directional components of the weighted AD did not improve the accuracy of the growth models. Weighting of the angular dispersion of neighbours improved the performance of local competition models. |
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