@article{RusakTanentzapKlugetal.2018,
  author    = {Rusak, James A. and Tanentzap, Andrew J. and Klug, Jennifer L. and Rose, Kevin C. and Hendricks, Susan P. and Jennings, Eleanor and Laas, Alo and Pierson, Donald C. and Ryder, Elizabeth and Smyth, Robyn L. and White, D. S. and Winslow, Luke A. and Adrian, Rita and Arvola, Lauri and de Eyto, Elvira and Feuchtmayr, Heidrun and Honti, Mark and Istvanovics, Vera and Jones, Ian D. and McBride, Chris G. and Schmidt, Silke Regina and Seekell, David and Staehr, Peter A. and Guangwei, Zhu},
  title     = {Wind and trophic status explain within and among-lake variability of algal biomass},
  series = {Limnology and oceanography letters / ASLO, Association for the Sciences of Limnology and Oceanography},
  volume    = {3},
  journal   = {Limnology and oceanography letters / ASLO, Association for the Sciences of Limnology and Oceanography},
  number    = {6},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {2378-2242},
  doi       = {10.1002/lol2.10093},
  pages     = {409 -- 418},
  year      = {2018},
  abstract  = {Phytoplankton biomass and production regulates key aspects of freshwater ecosystems yet its variability and subsequent predictability is poorly understood. We estimated within-lake variation in biomass using high-frequency chlorophyll fluorescence data from 18 globally distributed lakes. We tested how variation in fluorescence at monthly, daily, and hourly scales was related to high-frequency variability of wind, water temperature, and radiation within lakes as well as productivity and physical attributes among lakes. Within lakes, monthly variation dominated, but combined daily and hourly variation were equivalent to that expressed monthly. Among lakes, biomass variability increased with trophic status while, within-lake biomass variation increased with increasing variability in wind speed. Our results highlight the benefits of high-frequency chlorophyll monitoring and suggest that predicted changes associated with climate, as well as ongoing cultural eutrophication, are likely to substantially increase the temporal variability of algal biomass and thus the predictability of the services it provides.},
  language  = {en}
}
@misc{MarceGeorgeBuscarinuetal.2016,
  author    = {Marce, Rafael and George, Glen and Buscarinu, Paola and Deidda, Melania and Dunalska, Julita and de Eyto, Elvira and Flaim, Giovanna and Grossart, Hans-Peter and Istvanovics, Vera and Lenhardt, Mirjana and Moreno-Ostos, Enrique and Obrador, Biel and Ostrovsky, Ilia and Pierson, Donald C. and Potuzak, Jan and Poikane, Sandra and Rinke, Karsten and Rodriguez-Mozaz, Sara and Staehr, Peter A. and Sumberova, Katerina and Waajen, Guido and Weyhenmeyer, Gesa A. and Weathers, Kathleen C. and Zion, Mark and Ibelings, Bas W. and Jennings, Eleanor},
  title     = {Automatic High Frequency Monitoring for Improved Lake and Reservoir Management},
  series = {Frontiers in plant science},
  volume    = {50},
  journal   = {Frontiers in plant science},
  publisher = {American Chemical Society},
  address   = {Washington},
  issn      = {0013-936X},
  doi       = {10.1021/acs.est.6b01604},
  pages     = {10780 -- 10794},
  year      = {2016},
  abstract  = {Recent technological developments have increased the number of variables being monitored in lakes and reservoirs using automatic high frequency monitoring (AHFM). However, design of AHFM systems and posterior data handling and interpretation are currently being developed on a site-by-site and issue-by-issue basis with minimal standardization of protocols or knowledge sharing. As a result, many deployments become short-lived or underutilized, and many new scientific developments that are potentially useful for water management and environmental legislation remain underexplored. This Critical Review bridges scientific uses of AHFM with their applications by providing an overview of the current AHFM capabilities, together with examples of successful applications. We review the use of AHFM for maximizing the provision of ecosystem services supplied, by lakes and reservoirs (consumptive and non consumptive uses, food production, and recreation), and for reporting lake status in the EU Water Framework Directive. We also highlight critical issues to enhance the application of AHFM, and suggest the establishment of appropriate networks to facilitate knowledge sharing and technological transfer between potential users. Finally, we give advice on how modern sensor technology can successfully be applied on a larger scale to the management of lakes and reservoirs and maximize the ecosystem services they provide.},
  language  = {en}
}