Modelling the third dimension: Incorporating topography into the movement rules of an individual-based spatially explicit population model |
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| Affiliation: | 1. Landscape and Biodiversity Research Group, School of Applied Sciences, University of Northampton, Park Campus, Northampton NN2 7AL, UK;2. Centre for Ecology and Hydrology, Monks Wood, Abbots Ripton, Huntingdon, Cambridgeshire PE28 2LS, UK;1. Division of Forestry and Natural Resources, West Virginia University, Morgantown, WV 26506, USA;2. Department of Civil and Environmental Engineering, Lafayette College, Easton, PA 18042, USA;1. Univ. Perpignan Via Domitia, CEntre de Formation et de Recherche sur les Environnements Méditerranéens, UMR 5110, 58 Avenue Paul Alduy, F-66860 Perpignan, France;2. CNRS, CEntre de Formation et de Recherche sur les Environnements Méditerranéens, UMR 5110, 58 Avenue Paul Alduy, F-66860 Perpignan, France;3. SEANEO, 7 rue de Turenne, F-66000 Perpignan, France;4. Réserve Naturelle Marine de Cerbère-Banyuls, Conseil Général des Pyrénées-Orientales, 5 rue Roger David, F-66650 Banyuls-sur-Mer, France;1. Department of Biology, University of Saskatchewan, Saskatoon, SK, Canada S7N 5E2;2. Department of Biology, Memorial University, St. John''s NL, Canada A1B 3X9;3. Department of Animal and Poultry Science & Indigenous Land Management Institute, College of Agriculture and Bioresources, University of Saskatchewan, Saskatoon, SK, Canada S7N 5A8;4. Department of Biological Sciences, University of Alberta, Edmonton AB, Canada T6G 2E9;1. University of Firenze, Dept. of AgriFood Production and Environmental Sciences, Laboratories of Applied and Environmental Botany, P.le Cascine 28, 50144 Firenze, Italy;2. Ghent University, Department of Forest and Water Management, Forest & Nature Lab (ForNaLab), Geraardsbergsesteenweg 267, B-9090 Gontrode, Belgium;3. University of Firenze, Department of Agricultural, Food and Forestry Systems, Via San Bonaventura, 13, Firenze 50145, Italy;4. University of Firenze, Department of Biology, Botanical Laboratories, Via G. La Pira 4, 50121 Firenze, Italy;1. Environmental Systems Analysis Group, Wageningen University, P.O. Box 47, 6700 AA Wageningen, the Netherlands;2. National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA Bilthoven, the Netherlands;3. Department Ecosystem Services, Helmholtz Centre for Environmental Research—UFZ, Permoserstr. 15, 04318 Leipzig, Germany;4. German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany |
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| Abstract: | A wide variety of topographical and environmental elements have been shown or proposed to influence the movement decisions of dispersing animals. Most real landscapes have topographical elements such as hills, valleys and urban developments, which can all act to modify a species’ perceptual range and directly influence movement behaviour. If a visual-based perceptual ability enables a dispersing individual to locate suitable habitat patches at a distance, then it is to be expected that topographical features would act to modify the overall success of this strategy. However, the majority of individual-based Spatially Explicit Population Models (SEPM) employ only two-dimensional landscapes.To investigate the effects of topographical elevation on dispersal patterns, a three-dimensional visual-based perceptual range algorithm was added to the dispersal rules of an individual-based SEPM. To explore the possible influences of a behavioural-based response to topography, an algorithm modelling valley-seeking behaviour was also developed. The performance of both algorithms was compared with that of a two-dimensional visual-based perceptual range algorithm. The overall consequences of dispersal under each algorithm were measured by recording population sizes in a target wood in the centre of a modelled, real landscape.The size of the population in the target wood, modelled using both of the three-dimensional algorithms, exhibited sensitivity to the direction of dispersal in interaction with perceptual range, which differed from that predicted by the two-dimensional approach. Population size was dependant on the spatial configuration of habitat patches and on the topography of the landscape, both of which could guide dispersers either towards or away from the target patch depending on the particular combinations of dispersal directions and perceptual ranges selected. Topography was found to have a greater effect on dispersal at shorter perceptual ranges, and thresholds in the results for all three algorithms suggested the existence of species and landscape dependant optimal perceptual ranges. It is recommended that both topography and topographical-based dispersal-altering algorithms, commensurate with the studied species’ behaviour, be incorporated into the movement rule-base of dispersal simulation models. The modelling of topography and its effects on movement in patchy landscapes are seen as essential ingredients in future landscape planning. |
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