Data Descriptor: A European Multi Lake Survey dataset of environmental variables, phytoplankton pigments and cyanotoxins
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Show full item recordEditorial
Springer Nature
Date
2018-10-23Referencia bibliográfica
Mantzouki, E. et al. A European Multi Lake Survey dataset of environmental variables, phytoplankton pigments and cyanotoxins. Sci. Data. 5:180226
Sponsorship
Evanthia Mantzouki was supported by a grant from the Swiss State Secretariat for Education, Research and Innovation (SERI) to Bas Ibelings and by supplementary funding from University of Geneva. We thank Wendy Beekman for the nutrient analysis and the University of Wageningen for covering the costs of this analysis from the personal funding of dr. Miquel Lürling. We thank Pieter Slot for assisting with the pigment analysis and the University of Amsterdam for covering the costs of the analysis through funding from the group of Prof. Jef Huisman and dr. Petra Visser (IBED)Abstract
Under ongoing climate change and increasing anthropogenic activity, which continuously challenge ecosystem
resilience, an in-depth understanding of ecological processes is urgently needed. Lakes, as providers of
numerous ecosystem services, face multiple stressors that threaten their functioning. Harmful cyanobacterial
blooms are a persistent problem resulting from nutrient pollution and climate-change induced stressors, like
poor transparency, increased water temperature and enhanced stratification. Consistency in data collection
and analysis methods is necessary to achieve fully comparable datasets and for statistical validity, avoiding
issues linked to disparate data sources. The European Multi Lake Survey (EMLS) in summer 2015 was an
initiative among scientists from 27 countries to collect and analyse lake physical, chemical and biological
variables in a fully standardized manner. This database includes in-situ lake variables along with nutrient,
pigment and cyanotoxin data of 369 lakes in Europe, which were centrally analysed in dedicated laboratories.
Publishing the EMLS methods and dataset might inspire similar initiatives to study across large geographic
areas that will contribute to better understanding lake responses in a changing environment.