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Construction of data-driven models to predict the occurrence of planktonic species in the North-Sea

Gert Everaert, Frederik De Laender UGent, Klaas Deneudt, Peter Goethals UGent and Colin Janssen UGent (2011) COMMUNICATIONS IN AGRICULTURAL AND APPLIED BIOLOGICAL SCIENCES. 76(1). p.15-19
abstract
Marine habitat suitability models typically predict the potential distribution of organisms based on basic abiotic variables such as salinity, oxygen concentrations, temperature fluctuations (Gogina & Zettler, 2010) or sediment class information (Degraer et al., 2008; Willems et al., 2008). Recently, Dachs & Méjanelle (2010) claimed that the modification of biota composition due to marine pollution is a factor to be taken into account in marine habitat suitability models. Although the anthropogenic pressure on the environment has been exponentially increasing during the last six decades (Dachs & Méjanelle, 2010), the global effect of human inputs on oceanic phytoplankton remains unknown (Echeveste et al., 2010). A limited number of studies have assessed the impact of anthropogenic stressors on phytoplankton in marine environments at a global level (Faust et al., 2003; Magnusson et al.,2008). In order to fill this knowledge gap, this research tries to determine to what extent pollution data can be used to predict the occurrence of the phytoplanktonic organisms compared to basic abiotic variables. Here we explored this issue by developing classification trees relating physical-chemical variables with the occurrence of the potential harmful toxic algae Odontella sinensis.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
journal title
COMMUNICATIONS IN AGRICULTURAL AND APPLIED BIOLOGICAL SCIENCES
Comm. Agric. Appl. Biol. Sci.
volume
76
issue
1
pages
15 - 19
ISSN
1379-1176
language
English
UGent publication?
yes
classification
A4
copyright statement
I have transferred the copyright for this publication to the publisher
id
2052726
handle
http://hdl.handle.net/1854/LU-2052726
date created
2012-02-29 16:31:44
date last changed
2016-12-19 15:42:24
@article{2052726,
  abstract     = {Marine habitat suitability models typically predict the potential distribution of organisms based on basic abiotic variables such as salinity, oxygen concentrations, temperature fluctuations (Gogina \& Zettler, 2010) or sediment class information (Degraer et al., 2008; Willems et al., 2008). Recently, Dachs \& M{\'e}janelle (2010) claimed that the modification of biota composition due to marine pollution is a factor to be taken into account in marine habitat suitability models.
Although the anthropogenic pressure on the environment has been exponentially increasing during the last six decades (Dachs \& M{\'e}janelle, 2010), the global effect of human inputs on oceanic phytoplankton remains unknown (Echeveste et al., 2010). A limited number of studies have assessed the impact of anthropogenic stressors on phytoplankton in marine environments at a global level (Faust et al., 2003; Magnusson et al.,2008).
In order to fill this knowledge gap, this research tries to determine to what extent pollution data can be used to predict the occurrence of the phytoplanktonic organisms compared to basic abiotic variables. Here we explored this issue by developing classification trees relating physical-chemical variables with the occurrence of the potential harmful toxic algae Odontella sinensis.},
  author       = {Everaert, Gert and De Laender, Frederik and Deneudt, Klaas and Goethals, Peter and Janssen, Colin},
  issn         = {1379-1176},
  journal      = {COMMUNICATIONS IN AGRICULTURAL AND APPLIED BIOLOGICAL SCIENCES},
  language     = {eng},
  number       = {1},
  pages        = {15--19},
  title        = {Construction of data-driven models to predict the occurrence of planktonic species in the North-Sea},
  volume       = {76},
  year         = {2011},
}

Chicago
Everaert, Gert, Frederik De Laender, Klaas Deneudt, Peter Goethals, and Colin Janssen. 2011. “Construction of Data-driven Models to Predict the Occurrence of Planktonic Species in the North-Sea.” Communications in Agricultural and Applied Biological Sciences 76 (1): 15–19.
APA
Everaert, Gert, De Laender, F., Deneudt, K., Goethals, P., & Janssen, C. (2011). Construction of data-driven models to predict the occurrence of planktonic species in the North-Sea. COMMUNICATIONS IN AGRICULTURAL AND APPLIED BIOLOGICAL SCIENCES, 76(1), 15–19.
Vancouver
1.
Everaert G, De Laender F, Deneudt K, Goethals P, Janssen C. Construction of data-driven models to predict the occurrence of planktonic species in the North-Sea. COMMUNICATIONS IN AGRICULTURAL AND APPLIED BIOLOGICAL SCIENCES. 2011;76(1):15–9.
MLA
Everaert, Gert, Frederik De Laender, Klaas Deneudt, et al. “Construction of Data-driven Models to Predict the Occurrence of Planktonic Species in the North-Sea.” COMMUNICATIONS IN AGRICULTURAL AND APPLIED BIOLOGICAL SCIENCES 76.1 (2011): 15–19. Print.