Nonylphenol induced changes in trophic web structure of plankton analysed by multivariate statistical approaches.
Microcosm studies unveil relevant information in ecotoxicology. However, statistical evaluation of data gained from the different parts of the ecosystem often remain on unsatisfying, discretely level, e.g. separately for different species communities. A combination of different multivariate statistical methods enables an ecological interpretation of the found changes in zoo- and phytoplankton abundances in connection with the physico-chemical variables. To investigate the effects of nonylphenol (NP) on plankton communities, NP was continuously applicated in microcosms by controlled release. Plankton taxa were identified and quantified, various physico-chemical variables were measured. Maximum NP concentration ranged between 29 and 129 microg/L. The most important abiotic variable explaining both zoo- and phytoplankton abundances was NP concentration. NP primarily inhibited Crustaceae, especially juveniles. Cladocera and Copepoda abundances decreased. Rotatoria tend to increase, probably due to a decline of competition and predator pressure. Shifts in phytoplankton structure occurred with a time lag. Aggregating phytoplankton on class level did not show NP effects, whereas aggregating them according to feeding protection strategies did. Thus NP influences phytoplankton at least prevailingly indirectly via zooplankton. Zooplankton shifts led to species composition with different feeding preferences and strategies. Thereby the feeding pressure on phytoplankton changed. NP reorganized the plankton interrelation. Whereas without NP phytoplankton composition was dominated by Rotatoria, in the NP treated microcosms the Crustaceae unveiled highest explanatory power. The found effects were reversible in all but the highest treated microcosm. There are indications that the found effects were caused by endocrine activity of the chemical. Iteratively combining multivariate statistical methods with ecological and toxicological knowledge proved to provide a deeper insight into the mode of ecosystem disturbance by toxic substances.
Hense
Burkhard A
BA
GSF-National Research Center for Environment and Health, Institute of Biomathematics and Biometry, Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany. hense@gsf.de
Welzl
Gerhard
G
Severin
Gabriele F
GF
Schramm
Karl-Werner
KW
D000818:Animals; D004305:Dose-Response Relationship, Drug; D017753:Ecosystem; D056890:Eukaryota / Q000187:drug effects* / Q000254:growth & development; D020387:Food Chain; D007448:Invertebrates / Q000187:drug effects* / Q000254:growth & development; D015233:Models, Statistical; D015999:Multivariate Analysis; D010636:Phenols / Q000633:toxicity*; D010933:Plankton / Q000187:drug effects*; D013045:Species Specificity
D010636:Phenols; C025256:nonylphenol