Tamara Münkemüller1, Laure Gallien1, Sébastien Lavergne1, Julien Renaud1, Cristina Roquet1, Sylvain Abdulhak2, Stefan Dullinger3, Luc Garraud2, Antoine Guisan4, Jonathan Lenoir5, Jens-Christian Svenning6, Jérémie Van Es2, Pascal Vittoz4, Wolfgang Willner7, Thomas Wohlgemuth8, Niklaus E Zimmermann8, Wilfried Thuiller1. 1. Laboratoire d'Ecologie Alpine, UMR CNRS 5553, University Joseph Fourier, Grenoble 1, BP 53, 38041 Grenoble Cedex 9, France. 2. Domaine de Charance, Conservatoire Botanique National Alpin, Gap, 05000, France. 3. Department of Conservation Biology, Vegetation- and Landscape Ecology, Faculty Centre of Biodiversity, Rennweg 14, 1030 Vienna. 4. Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland ; Institute of Earth Sciences, University of Lausanne, 1015 Lausanne, Switzerland. 5. Ecologie et Dynamique des Systèmes Anthropisés (EDYSAN, FRE 3498 CNRS), Plant Biodiversity Lab, Jules Verne University of Picardie, 1 Rue des Louvels, FR-80037 Amiens Cedex 1, France. 6. Ecoinformatics and Biodiversity Group, Department of Bioscience, Aarhus University, Ny Munkegade 114, DK-8000 Aarhus C, Denmark. 7. Vienna Institute for Nature Conservation and Analyses, Giessergasse 6/7, 1090 Vienna, Austria. 8. Landscape Dynamics, Swiss Federal Research Institute WSL, CH-8903 Birmensdorf, Switzerland.
Abstract
AIM: Phylogenetic diversity patterns are increasingly being used to better understand the role of ecological and evolutionary processes in community assembly. Here, we quantify how these patterns are influenced by scale choices in terms of spatial and environmental extent and organismic scales. LOCATION: European Alps. METHODS: We applied 42 sampling strategies differing in their combination of focal scales. For each resulting sub-dataset, we estimated the phylogenetic diversity of the species pools, phylogenetic α-diversities of local communities, and statistics commonly used together with null models in order to infer non-random diversity patterns (i.e. phylogenetic clustering versus over-dispersion). Finally, we studied the effects of scale choices on these measures using regression analyses. RESULTS: Scale choices were decisive for revealing signals in diversity patterns. Notably, changes in focal scales sometimes reversed a pattern of over-dispersion into clustering. Organismic scale had a stronger effect than spatial and environmental extent. However, we did not find general rules for the direction of change from over-dispersion to clustering with changing scales. Importantly, these scale issues had only a weak influence when focusing on regional diversity patterns that change along abiotic gradients. MAIN CONCLUSIONS: Our results call for caution when combining phylogenetic data with distributional data to study how and why communities differ from random expectations of phylogenetic relatedness. These analyses seem to be robust when the focus is on relating community diversity patterns to variation in habitat conditions, such as abiotic gradients. However, if the focus is on identifying relevant assembly rules for local communities, the uncertainty arising from a certain scale choice can be immense. In the latter case, it becomes necessary to test whether emerging patterns are robust to alternative scale choices.
AIM: Phylogenetic diversity patterns are increasingly being used to better understand the role of ecological and evolutionary processes in community assembly. Here, we quantify how these patterns are influenced by scale choices in terms of spatial and environmental extent and organismic scales. LOCATION: European Alps. METHODS: We applied 42 sampling strategies differing in their combination of focal scales. For each resulting sub-dataset, we estimated the phylogenetic diversity of the species pools, phylogenetic α-diversities of local communities, and statistics commonly used together with null models in order to infer non-random diversity patterns (i.e. phylogenetic clustering versus over-dispersion). Finally, we studied the effects of scale choices on these measures using regression analyses. RESULTS: Scale choices were decisive for revealing signals in diversity patterns. Notably, changes in focal scales sometimes reversed a pattern of over-dispersion into clustering. Organismic scale had a stronger effect than spatial and environmental extent. However, we did not find general rules for the direction of change from over-dispersion to clustering with changing scales. Importantly, these scale issues had only a weak influence when focusing on regional diversity patterns that change along abiotic gradients. MAIN CONCLUSIONS: Our results call for caution when combining phylogenetic data with distributional data to study how and why communities differ from random expectations of phylogenetic relatedness. These analyses seem to be robust when the focus is on relating community diversity patterns to variation in habitat conditions, such as abiotic gradients. However, if the focus is on identifying relevant assembly rules for local communities, the uncertainty arising from a certain scale choice can be immense. In the latter case, it becomes necessary to test whether emerging patterns are robust to alternative scale choices.
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