| one publication added to basket [286353] | Marine species distributions: from data to predictive models
Bosch, S. (2017). Marine species distributions: from data to predictive models. PhD Thesis. Phycology Research Group, Ghent University: Gent. 231 pp. |  |
| Available in | Author | | Document type: Dissertation
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| Content | - Vandepitte, L.; Bosch, S.; Tyberghein, L.; Waumans, F.; Vanhoorne, B.; Hernandez, F.; De Clerck, O.; Mees, J. (2017). Fishing for data and sorting the catch: assessing the data quality, completeness and fitness for use of data in marine biogeographic databases, in: Bosch, S. Marine species distributions: from data to predictive models. pp. 25-48, more
- Bosch, S.; Tyberghein, L.; De Clerck, O. (2017). sdmpredictors: an R package for species distribution modelling predictor datasets, in: Bosch, S. Marine species distributions: from data to predictive models. pp. 49-60, more
- Bosch, S.; Tyberghein, L.; Deneudt, K.; Hernandez, F.; De Clerck, O. (2017). Chapter 4. In search of relevant predictors for marine species distribution modelling using the MarineSPEED benchmark dataset, in: Bosch, S. Marine species distributions: from data to predictive models. pp. 61-96, more
- Bosch, S.; De Clerck, O.; Mineur, F. (2017). Spatio-temporal patterns of introduced seaweeds in European waters, a critical review, in: Bosch, S. Marine species distributions: from data to predictive models. pp. 97-118, more
- Vranken, S.; Bosch, S.; Peña, V.; Leliaert, F.; Mineur, F.; De Clerck, O. (2017). A risk assessment of aquarium trade introductions of seaweed in European waters, in: Bosch, S. Marine species distributions: from data to predictive models. pp. 119-146, more
- Bosch, S.; Giron, E.G.; Martínez, B.; De Clerck, O. (2017). Modelling the past, present and future distributions of invasive seaweeds in Europe, in: Bosch, S. Marine species distributions: from data to predictive models. pp. 147-178, more
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| Abstract | The increased anthropogenic pressure on the marine environment through over-use and overfishing, invasion of species and global climate change has led to an urgent need for more knowledge on the marine ecosystem. Marine species distribution modelling is an important element of marine ecosystem management. It is relied upon by marine spatial planning for i.e. predicting biological resources, the design of marine protected areas, the designation of essential fish habitats, the assessment of species invasion risk, pest control, human-animal conflict prevention, ….This study aims to improve and contribute to the process and understanding of marine species distribution modelling in order to facilitate an in depth study of the trends, vectors and distribution of introduced seaweeds in Europe. More specifically we wanted to 1) provide quality indicators for the marine species distribution data available in the Ocean Biogeographic Information System (OBIS), 2) make global datasets for species distribution modelling in the past, current and future climate more accessible in R, 3) explore the relevance of different predictors of marine species distributions with MarineSPEED, a marine benchmark dataset of more than 500 species, 4) investigate the introduction history and trends in introduced seaweeds in Europe, 5) evaluate the risk of aquarium trade as a vector for future introductions of seaweeds and 6) study the ability of species distribution modelling to predict the introduction and spread of introduced seaweeds and propose a method for identifying candidate areas for further spreading under climate change. The first part of this thesis concerns general aspects of marine species distributions, the environmental data used for modelling and the relevance of marine predictors of species distributions. |
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