Sequential sampling designs for catching the tail of dispersal kernels |
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| Institution: | 1. Departamento de Ciencias del Medio Natural, Universidad Pública de Navarra, Campus Arrosadía S/N, E-31006 Pamplona, Spain;2. Departamento de Ecología, Facultad de Ciencias, Universidad Autónoma de Madrid, C/Darwin 2, E-28049 Madrid, Spain;3. ARAID-Instituto Pirenaico de Ecología (IPE-CSIC), Avda. Montañana 1005, Apdo. 202, E-50192 Zaragoza, Spain;4. Departament of Ecology, Fac. Biology, University of Barcelona, Avda. Diagonal 645, E-08028 Barcelona, Spain;5. Departament of Conservation Biology, Estación Biológica de Doñana (EBD-CSIC), C/Américo Vespucio s/n, E-41092 Sevilla, Spain;6. Forest Sciences Center of Catalonia (CTFC), Ctra. Sant Llorenç de Morunys km. 2, E-25280 Solsona, Spain;7. CREAF, Centre for Ecological Research and Forestry Applications, Autonomous University of Barcelona, Bellaterra E-08193, Catalonia, Spain;1. Chilean Forest Institute (INFOR), Metropolitan Office, Sucre 2397, Santiago, Chile;2. Universidad Nacional de Córdoba, College of Agriculture, CONICET Biometry Unit, Córdoba, Argentina;1. Universidade de Lisboa, Instituto Superior de Agronomia, Centro de Estudos Florestais, Tapada da Ajuda, 1349-017 Lisboa, Portugal;2. Instituto de Investigação Agrária e Veterinária, I.P, Unidade Estratégica de Sistemas Agrários e Florestais e Sanidade Vegetal, Av. da Républica, Quinta do Marquês, 2780-159 Oeiras, Portugal;3. INRA UR633 Unité de Zoologie Forestière (URZF), Centre de recherche d''Orléans, 2163 avenue de la pomme de pin, CS40001 Ardon 45075 ORLEANS CEDEX 2, France;1. Eawag: Swiss Federal Institute of Aquatic Science and Technology, Department of Aquatic Ecology, Überlandstrasse 133, CH-8600 Dübendorf, Switzerland;2. Field Station Fabrikschleichach, University of Würzburg, Glashüttenstr. 5, D-96181 Rauhenebrach, Germany;3. Evolution and Ecology Program, International Institute for Applied Systems Analysis, Schlossplatz 1, A-2361 Laxenburg, Austria;1. Department of Biogeography and Global Change, National Museum of Natural Sciences, CSIC, C/ José Gutiérrez Abascal, 28006 Madrid, Spain;2. Forest Ecology and Restoration Group, Department of Life Sciences, Science Building, University of Alcala, 28871 Alcalá de Henares, Madrid, Spain;3. CEFE UMR 5175, CNRS - Université de Montpellier - Université Paul-Valéry Montpellier - EPHE, 1919, route de Mende, 34293 Montpellier Cedex 5, France;4. Department of Biology, University of Vermont, Burlington, USA;5. Computational Ecology and Environmental Science Group, Microsoft Research Cambridge, 7 J J Thomson Ave, Cambridge CB3 0FB, UK;6. CIBIO-InBIO, Universidade de Évora, CIBIO, Largo dos Colegiais, 7000 Évora, Portugal;7. Centre for Macroecology, Evolution and Climate, Department of Biology, University of Copenhagen, Copenhagen DK-2100, Denmark |
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| Abstract: | Methods to design a sampling strategy should depend on the research question involved when conducting the experiment. The objective of this study is to design a seed trap configuration surrounding a parent plant when the long distance component of the seed dispersal kernel is of interest. In particular, as a population’s invasion speed depends mainly on the tail of the dispersal kernel, the sampling design in this study is based on calculating this quantity. The optimality criterion is to minimize the mean squared error (MSE) of the estimated invasion speed (using a limited number of traps) with respect to the “true” calculated invasion speed. Detailed procedures are given on how to calculate an invasion speed, both in a 1D and a 2D setting, with examples on how to implement the method to get a local optimal sampling strategy using Calluna vulgaris as a test system. Results show a trade-off between nearby sampling (many seeds, no long-distance dispersal measured) and distant sampling (few seeds, but long-distance dispersal measured). |
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