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Patrick Schwager [06-2017]:

„Utilization of two approaches of species distribution modelling (GLM, MaxEnt) to find new sites for seed collecting“ An application on six alpine vascular plant species in the eastern Alps (Styria)

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Since 2015, the Botanical Garden Graz has been part of the Alpine Seed Conservation and Research Network initialized by the Millennium Seedbank (Botanical Gardens, Kew). The overarching aim of the project is to use the European Alpine Seed Conservation Network to improve the conservation status of endangered plant species and communities in their habitats in the European Alps. Therefore, all project partners agreed to collect seeds from at least 100 vascular plant species from different regions of the Alps to reach the goal of 500 species for ex-situ conservation. Using the example of six species distribution models from alpine vascular plants, this thesis investigates whether models can be helpful in finding suitable collection areas. Two different and widely used approaches were compared; the proven generalized linear model (GLM) and the machine learning algorithm MaxEnt. Both modelling approaches were able to predict the distribution of the six vascular plant species across the Styrian Alps. The models were able to make plausible predictions and comply with known distributions provided by the Styrian distribution atlas. The prediction maps of both approaches show very similar results for one species, whereby GLM models tend to make less restrictive estimations. This means that the latter method deemed more regions as suitable for collection. With regard to the Alpine Seed Conservation and Research Network, species distribution models can assist in localizing special areas of interest. With the help of the prediction maps it is possible to restrict field surveys to particular areas that show higher probability values. And this could contribute significantly to the collection success.


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