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Species-environment relationships and potential for distribution modelling in coastal waters
Stockholm University, Faculty of Science, Department of Ecology, Environment and Plant Sciences.
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2014 (English)In: Journal of Sea Research, ISSN 1385-1101, E-ISSN 1873-1414, Vol. 85, 116-125 p.Article in journal (Refereed) Published
Abstract [en]

Due to increasing pressure on the marine environment there is a growing need to understand species-environment relationships. To provide background for prioritising among variables (predictors) for use in distribution models, the relevance of predictors for benthic species was reviewed using the coastal Baltic Sea as a case-study area. Significant relationships for three response groups (fish, macroinvertebrates, macrovegetation) and six predictor categories (bottom topography, biotic features, hydrography, wave exposure, substrate and spatiotemporal variability) were extracted from 145 queried peer-reviewed field-studies covering three decades and six subregions. In addition, the occurrence of interaction among predictors was analysed. Hydrography was most often found in significant relationships, had low level of interaction with other predictors, but also had the most non-significant relationships. Depth and wave exposure were important in all subregions and are readily available, increasing their applicability for cross-regional modelling efforts. Otherwise, effort to model species distributions may prove challenging at larger scale as the relevance of predictors differed among both response groups and regions. Fish and hard bottom macrovegetation have the largest modelling potential, as they are structured by a set of predictors that at the same time are accurately mapped. A general importance of biotic features implies that these need to be accounted for in distribution modelling, but the mapping of most biotic features is challenging, which currently lowers the applicability. The presence of interactions suggests that predictive methods allowing for interactive effects are preferable. Detailing these complexities is important for future distribution modelling.

Place, publisher, year, edition, pages
Elsevier, 2014. Vol. 85, 116-125 p.
Keyword [en]
Baltic Sea, Environmental gradients, Predictions, Review, Benthos, Biophysical relationships
National Category
Oceanography, Hydrology, Water Resources
Identifiers
URN: urn:nbn:se:su:diva-101013DOI: 10.1016/j.seares.2013.04.008ISI: 000329884700011OAI: oai:DiVA.org:su-101013DiVA: diva2:699462
Note

AuthorCount:7;

Funding agencies:

European Community 217246 joint Baltic Sea research and development programme; BONUS;  Academy of Finland;  Swedish Research Council  

Available from: 2014-02-27 Created: 2014-02-21 Last updated: 2017-12-05Bibliographically approved

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