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

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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.

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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.
@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},
}