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Transferability of predictive fish distribution models in two coastal systems
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Evolution, Limnology.
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2009 (English)In: Estuarine, Coastal and Shelf Science, ISSN 0272-7714, E-ISSN 1096-0015, Vol. 83, no 1, 90-96 p.Article in journal (Refereed) Published
Abstract [en]

Species distribution modelling has emerged as a tool both for exploring niche theory and for producing distribution maps for management. To understand and predict potential effects of large scale habitat change there is a need for proper model validation and applicability also in unstudied areas. However, knowledge about factors influencing the transferability of distribution models, i.e. the accuracy of the models when applying them in a new geographical area, is limited. We have successfully modelled the larval distribution of two fish species, northern pike (Esox lucius L.) and roach (Rutilus rutilus L.), on a regional scale in the Baltic Sea using a few and easily measured environmental variables. When models were transferred from the training area to the testing area the models showed reasonable to very good discrimination (ROC 0.75 and 0.93) based on external validation using independent data separated also in time (1–2 years). The predicted larval distribution also overlapped with the distribution of young-of-the-year fish later in the season. Performance when reversing the transfer, by constructing the models in the testing area and predicting back to the original training area, was less successful. This discrepancy was species-specific and could be explained by differences in the species presence ranges along the predictor variables in the testing area compared to the training area. Our results illustrate how transferability success can be influenced by area-specific differences in the range of the predictor variables and show the necessity of validating model predictions properly.


Place, publisher, year, edition, pages
2009. Vol. 83, no 1, 90-96 p.
Keyword [en]
prediction, modelling, fish larvae, habitat selection, GAM, Baltic Sea
National Category
Biological Sciences
URN: urn:nbn:se:uu:diva-111709DOI: 10.1016/j.ecss.2009.03.025ISI: 000266540000010OAI: oai:DiVA.org:uu-111709DiVA: diva2:282544
Available from: 2009-12-21 Created: 2009-12-21 Last updated: 2011-01-13Bibliographically approved
In thesis
1. Spatial Modelling of Coastal Fish – Methods and Applications
Open this publication in new window or tab >>Spatial Modelling of Coastal Fish – Methods and Applications
2010 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Environmental factors influence species and habitats on multiple scales creating a mosaic of distribution patterns. Studying factors shaping these patterns are central to our understanding of population dynamics and ultimately ecosystem functioning. Information on the distribution of resources and conservation values are also highly needed in marine management as coastal areas are increasingly influenced by human activities.

In this thesis, large-scale field data is used to explore how strong environmental gradients found on multiple scales in the coastal areas of the Baltic Sea influence fish habitats. The underlying concepts are based in the field of species distribution modelling, whereby habitat maps can be produced using environmental layers in a geographic information system. Distribution modelling is further used to address both ecological and applied questions by examining effects of habitat limitation on fish population sizes and to evaluate management actions aimed at habitat conservation.

I show that specific habitat requirements for fish species of both freshwater and marine origin can be described using environmental variables and that species-environment relationships can be used to predict the distribution of early life-stages of fish in the Baltic Sea archipelagos. Further, predicted habitat availability of a specific life-stage was directly related to adult population size of Eurasian perch Perca fluviatilis, signifying that the abundance of large predatory fish can be limited by specific recruitment habitats. Lastly, by predicting the distribution of an assemblage of coastal fish species and their associated habitats, an assessment of a network of marine protected areas was performed. Results revealed large gaps in the current network and identified areas suitable for future protection. By demonstrating how current habitat protection can be improved by including critical habitats for coastal fish population sizes this thesis points to the benefits of integrating nature conservation and fisheries management.

Based on these findings I conclude that species distribution modelling provides a suitable analytical framework for assessing the habitat requirements of organisms. An increased understanding of habitat-population relationships and an ability to accurately map ecologically important features will be of great value for an ecosystem-based marine management. ­



Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2010. 43 p.
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 779
habitat, niche, species distribution modelling, juvenile, fish, larvae, spawning
National Category
Ecology Natural Sciences Ecology Biological Sciences
Research subject
Biology with specialization in Limnology; Biology with specialization in Animal Ecology; Limnology
urn:nbn:se:uu:diva-132620 (URN)978-91-554-7928-2 (ISBN)
Public defence
2010-12-10, Friessalen, Evolutionary Biology Centre (EBC), Uppsala University, Norbyvägen 18, 752 36 Uppsala, Uppsala, 10:00 (English)
Felaktigt tryckt som Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology 709Available from: 2010-11-19 Created: 2010-10-22 Last updated: 2011-03-21Bibliographically approved

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