WestBanks
understanding benthic, pelagic and air-borne ecosystem interactions in shallow coastal seas

WestBanks Metadata Database
List all

By choosing an item from the pick list, you can list all the projects, persons, institutes, literature and datasets in the database.

[ meld een fout in dit record ]mandje (0): toevoegen | toon Print deze pagina

Where is the worm? Predictive modelling of the habitat preferences of the tube-building polychaete Lanice conchilega
Willems, W.; Goethals, P.; Van den Eynde, D.; Van Hoey, G.; Van Lancker, V.; Verfaillie, E.; Vincx, M.; Degraer, S. (2008). Where is the worm? Predictive modelling of the habitat preferences of the tube-building polychaete Lanice conchilega. Ecol. Model. 212(1-2): 74-79. dx.doi.org/10.1016/j.ecolmodel.2007.10.017
In: Ecological Modelling. Elsevier: Amsterdam; Lausanne; New York; Oxford; Shannon; Tokyo. ISSN 0304-3800; e-ISSN 1872-7026
Peer reviewed article  

Beschikbaar in  Auteurs 

Trefwoorden
    Habitat selection
    Lanice conchilega (Pallas, 1766) [WoRMS]; Lanice conchilega (Pallas, 1766) [WoRMS]; Polychaeta [WoRMS]
    Marien/Kust
Author keywords
    Lanice conchilega; Polychaeta; Habitat preference; Generalized linear models (GLM); Artificial neural networks (ANN)

Auteurs  Top 
  • Willems, W.
  • Goethals, P.
  • Van den Eynde, D., meer
  • Van Hoey, G.
  • Van Lancker, V.
  • Verfaillie, E.
  • Vincx, M., meer
  • Degraer, S., meer

Abstract
    Grab samples to monitor the distribution of marine macrobenthic species (animals >1 mm, living in the sand) are time consuming and give only point based information. If the habitat preference of a species can be modelled, the spatial distribution can be predicted on a full coverage scale from the environmental variables. The modelling techniques Generalized Linear Models (GLM) and Artificial Neural Networks (ANN) were compared in their ability to predict the occurrence of Lanice conchilega, a common tube-building polychaete along the North-western European coastline. Although several types of environmental variables were in the data set (granulometric, currents, nutrients) only three granulometric variables were used in the final models (median grain-size, % mud and % coarse fraction). ANN slightly outperformed GLM for a number of performance indicators (% correct predictions, specificity and sensitivity), but the GLM were more robust in the crossvalidation procedure.

Alle informatie in het Integrated Marine Information System (IMIS) valt onder het VLIZ Privacy beleid Top | Auteurs 
Westbanks is a project Supported by the Belgian Science Policy (BELSPO): SSD Science for sustainable Development
General coordination: Magda Vincx & Jan Vanaverbeke
Hosted by the Flanders Marine Institute VLIZ