Document of bibliographic reference 134327

BibliographicReference record

Type
Bibliographic resource
Type of document
Journal article
BibLvlCode
AS
Title
Predictability of marine nematode biodiversity
Abstract
In this paper, we investigated: (1) the predictability of different aspects of biodiversity, (2) the effect of spatial autocorrelation on the predictability and (3) the environmental variables affecting the biodiversity of free-living marine nematodes on the Belgian Continental Shelf. An extensive historical database of free-living marine nematodes was employed to model different aspects of biodiversity: species richness, evenness, and taxonomic diversity. Artificial neural networks (ANNs), often considered as “black boxes”, were applied as a modeling tool. Three methods were used to reveal these “black boxes” and to identify the contributions of each environmental variable to the diversity indices. Since spatial autocorrelation is known to introduce bias in spatial analyses, Moran's I was used to test the spatial dependency of the diversity indices and the residuals of the model. The best predictions were made for evenness. Although species richness was quite accurately predicted as well, the residuals indicated a lack of performance of the model. Pure taxonomic diversity shows high spatial variability and is difficult to model. The biodiversity indices show a strong spatial dependency, opposed to the residuals of the models, indicating that the environmental variables explain the spatial variability of the diversity indices adequately. The most important environmental variables structuring evenness are clay and sand fraction, and the minimum annual total suspended matter. Species richness is also affected by the intensity of sand extraction and the amount of gravel of the sea bed.
WebOfScience code
https://www.webofscience.com/wos/woscc/full-record/WOS:000266539700009
Bibliographic citation
Merckx, B.; Goethals, P.; Steyaert, M.; Vanreusel, A.; Vincx, M.; Vanaverbeke, J. (2009). Predictability of marine nematode biodiversity. Ecol. Model. 220(11): 1449-1458. dx.doi.org/10.1016/j.ecolmodel.2009.03.016
Topic
Marine
Is peer reviewed
true

Authors

author
Name
Bea Merckx
Affiliation
Universiteit Gent; Faculteit Wetenschappen; Vakgroep Biologie; Onderzoeksgroep Mariene Biologie
author
Name
Peter Goethals
Affiliation
Universiteit Gent; Faculteit Bio-ingenieurswetenschappen; Vakgroep Dierwetenschappen en Aquatische Ecologie; Onderzoeksgroep Aquatische ecologie
author
Name
Maaike Steyaert
Affiliation
Universiteit Gent; Faculteit Wetenschappen; Vakgroep Biologie; Onderzoeksgroep Mariene Biologie
author
Name
Ann Vanreusel
Identifier
https://orcid.org/0000-0003-2983-9523
Affiliation
Universiteit Gent; Faculteit Wetenschappen; Vakgroep Biologie; Onderzoeksgroep Mariene Biologie
author
Name
Magda Vincx
Affiliation
Universiteit Gent; Faculteit Wetenschappen; Vakgroep Biologie; Onderzoeksgroep Mariene Biologie
author
Name
Jan Vanaverbeke
Identifier
https://orcid.org/0000-0003-2488-8609
Affiliation
Universiteit Gent; Faculteit Wetenschappen; Vakgroep Biologie; Onderzoeksgroep Mariene Biologie

Links

referenced creativework
type
DOI
accessURL
https://dx.doi.org/10.1016/j.ecolmodel.2009.03.016

thesaurus terms

term
Artificial neural networks (term code: 103995 - defined in term set: Transportation Research Thesaurus)
Autocorrelation (term code: 677 - defined in term set: ASFA Thesaurus List)
Biodiversity (term code: 56584 - defined in term set: CSA Technology Research Database Master Thesaurus)
Marine (term code: 75944 - defined in term set: CSA Technology Research Database Master Thesaurus)

taxonomic terms

taxonomic terms associated with this publication
Nematoda [Nematodes]

Document metadata

date created
2009-04-27
date modified
2015-09-08