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A probabilistic eco-hydrological model to predict the effects of climate change on natural vegetation at a regional scale

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Abstract

Climate change may hamper the preservation of nature targets, but may create new potential hotspots of biodiversity as well. To timely design adequate measures, information is needed about the feasibility of nature targets under a future climate. Habitat distribution models may provide this, but current models have certain drawbacks: they apply indirect empirical relationships between habitat and vegetation, they often disregard spatially explicit information about groundwater, and they are designed for too coarse spatial scales. We introduce a model that explicitly takes into account spatial effects through groundwater and that can easily be adapted to new scientific approaches and the needs of end-users. It combines (spatially explicit) data sources, transfer functions derived from mechanistic models, and robust relationships between habitat factors and plant characteristics. Outputs are maps showing the occurrence probabilities of vegetation types and their associated conservation values, both on a spatial scale that fits the needs of nature managers and spatial planners. The model was applied to a catchment of 270 km2 to forecast, on a 25 m resolution, the effects of a national climate scenario (related to IPCC A2 and A1B). Computation time was a couple of minutes on a standard PC. Severe loss was predicted for wet and mesotrophic species-rich grasslands, while vegetation of dry and acidic soils appeared to profit. The results were not univocal though, and could probably not have been foreseen on the basis of expert judgement and logic alone, especially because of edaphic factors and spatial hydrological relationships.

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Acknowledgments

This work was carried out within the joint research programme of the Dutch Water Utility sector (http://www.kwrwater.nl/BTO), and the project Climate Adaptation for Rural Areas (CARE), which was funded by the Knowledge for Climate Programme (http://knowledgeforclimate.climateresearchnetherlands.nl/climateadaptationforruralareas) as well as by the province of Gelderland and the water board Rijn en IJssel.

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Authors and Affiliations

  1. KWR Watercycle Research Institute, P.O. Box 1072, 3430 BB, Nieuwegein, The Netherlands

    Jan-Philip M. Witte, Ruud P. Bartholomeus, D. Gijsbert Cirkel, Yuki Fujita & Han Runhaar

  2. Systems Ecology, Department of Ecological Science, VU University Amsterdam, De Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands

    Jan-Philip M. Witte & Peter M. van Bodegom

  3. Deltares, P.O. Box 85467, 3508 AL, Utrecht, The Netherlands

    Remco van Ek & Gijs M. C. M. Janssen

  4. Provincie Gelderland, P.O. Box 9090, 6800 GX, Arnhem, The Netherlands

    Teun J. Spek

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  1. Jan-Philip M. Witte
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  2. Ruud P. Bartholomeus
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Correspondence to Jan-Philip M. Witte.

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Witte, JP.M., Bartholomeus, R.P., van Bodegom, P.M. et al. A probabilistic eco-hydrological model to predict the effects of climate change on natural vegetation at a regional scale. Landscape Ecol 30, 835–854 (2015). https://doi.org/10.1007/s10980-014-0086-z

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