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Uncertainty in predicting range dynamics of endemic alpine plants under climate warming
Authors:Dietmar Moser  Michael Kuttner  Franz Essl  Michael Leitner  Manuela Winkler  Siegrun Ertl  Wolfgang Willner  Ingrid Kleinbauer  Norbert Sauberer  Thomas Mang  Niklaus E Zimmermann  Stefan Dullinger
Institution:1. Division of Conservation Biology, Vegetation Ecology and Landscape Ecology, Department of Botany and Biodiversity Research, University of Vienna, Vienna, Austria;2. Vienna Institute for Nature Conservation & Analyses, Vienna, Austria;3. Faculty of Physics, University of Vienna, Vienna, Austria;4. GLORIA Co‐ordination, Center for Global Change and Sustainability & Austrian Academy of Sciences, Institute for Interdisciplinary Mountain Research, University of Natural Resources and Life Sciences Vienna, Vienna, Austria;5. Landscape Dynamics Unit, Swiss Federal Research Institute WSL, Birmensdorf, Switzerland
Abstract:Correlative species distribution models have long been the predominant approach to predict species’ range responses to climate change. Recently, the use of dynamic models is increasingly advocated for because these models better represent the main processes involved in range shifts and also simulate transient dynamics. A well‐known problem with the application of these models is the lack of data for estimating necessary parameters of demographic and dispersal processes. However, what has been hardly considered so far is the fact that simulating transient dynamics potentially implies additional uncertainty arising from our ignorance of short‐term climate variability in future climatic trends. Here, we use endemic mountain plants of Austria as a case study to assess how the integration of decadal variability in future climate affects outcomes of dynamic range models as compared to projected long‐term trends and uncertainty in demographic and dispersal parameters. We do so by contrasting simulations of a so‐called hybrid model run under fluctuating climatic conditions with those based on a linear interpolation of climatic conditions between current values and those predicted for the end of the 21st century. We find that accounting for short‐term climate variability modifies model results nearly as differences in projected long‐term trends and much more than uncertainty in demographic/dispersal parameters. In particular, range loss and extinction rates are much higher when simulations are run under fluctuating conditions. These results highlight the importance of considering the appropriate temporal resolution when parameterizing and applying range‐dynamic models, and hybrid models in particular. In case of our endemic mountain plants, we hypothesize that smoothed linear time series deliver more reliable results because these long‐lived species are primarily responsive to long‐term climate averages.
Keywords:climate change  dispersal/demographic rates  dynamic model  endemic plant species  European Alps  extinction risk  range shift  species distribution model
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