Scientific Article
previous document  unige:27395  next document
add to browser collection
Title

An Automated Platform for Phytoplankton Ecology and Aquatic Ecosystem Monitoring

Authors
Pomati, Francesco
Jokela, Jukka
Simona, Marco
Veronesi, Mauro
Published in Environmental Science & Technology. 2011, vol. 45, no. 22, p. 9658-9665
Abstract High quality monitoring data are vital for tracking and understanding the causes of ecosystem change. We present a potentially powerful approach for phytoplankton and aquatic ecosystem monitoring, based on integration of scanning flow-cytometry for the characterization and counting of algal cells with multiparametric vertical water profiling. This approach affords high-frequency data on phytoplankton abundance, functional traits and diversity, coupled with the characterization of environmental conditions for growth over the vertical structure of a deep water body. Data from a pilot study revealed effects of an environmental disturbance event on the phytoplankton community in Lake Lugano (Switzerland), characterized by a reduction in cytometry-based functional diversity and by a period of cyanobacterial dominance. These changes were missed by traditional limnological methods, employed in parallel to high-frequency monitoring. Modeling of phytoplankton functional diversity revealed the importance of integrated spatiotemporal data, including circadian time-lags and variability over the water column, to understand the drivers of diversity and dynamic processes. The approach described represents progress toward an automated and trait-based analysis of phytoplankton natural communities. Streamlining of high-frequency measurements may represent a resource for understanding, modeling and managing aquatic ecosystems under impact of environmental change, yielding insight into processes governing phytoplankton community resistance and resilience.
Identifiers
Full text
Article - document accessible for UNIGE members only Limited access to UNIGE
Citation
(ISO format)
POMATI, Francesco et al. An Automated Platform for Phytoplankton Ecology and Aquatic Ecosystem Monitoring. In: Environmental Science & Technology, 2011, vol. 45, n° 22, p. 9658-9665. https://archive-ouverte.unige.ch/unige:27395

188 hits

1 download

Update

Deposited on : 2013-04-09

Export document
Format :
Citation style :