TY  - JOUR
A1  - Rusak, James A.
A1  - Tanentzap, Andrew J.
A1  - Klug, Jennifer L.
A1  - Rose, Kevin C.
A1  - Hendricks, Susan P.
A1  - Jennings, Eleanor
A1  - Laas, Alo
A1  - Pierson, Donald C.
A1  - Ryder, Elizabeth
A1  - Smyth, Robyn L.
A1  - White, D. S.
A1  - Winslow, Luke A.
A1  - Adrian, Rita
A1  - Arvola, Lauri
A1  - de Eyto, Elvira
A1  - Feuchtmayr, Heidrun
A1  - Honti, Mark
A1  - Istvanovics, Vera
A1  - Jones, Ian D.
A1  - McBride, Chris G.
A1  - Schmidt, Silke Regina
A1  - Seekell, David
A1  - Staehr, Peter A.
A1  - Guangwei, Zhu
T1  - Wind and trophic status explain within and among-lake variability of algal biomass
JF  - Limnology and oceanography letters / ASLO, Association for the Sciences of Limnology and Oceanography
N2  - 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.
Y1  - 2018
U6  - https://doi.org/10.1002/lol2.10093
SN  - 2378-2242
VL  - 3
IS  - 6
SP  - 409
EP  - 418
PB  - Wiley
CY  - Hoboken
ER  - 
TY  - JOUR
A1  - Brentrup, Jennifer A.
A1  - Williamson, Craig E.
A1  - Colom-Montero, William
A1  - Eckert, Werner
A1  - de Eyto, Elvira
A1  - Grossart, Hans-Peter
A1  - Huot, Yannick
A1  - Isles, Peter D. F.
A1  - Knoll, Lesley B.
A1  - Leach, Taylor H.
A1  - McBride, Chris G.
A1  - Pierson, Don
A1  - Pomati, Francesco
A1  - Read, Jordan S.
A1  - Rose, Kevin C.
A1  - Samal, Nihar R.
A1  - Staehr, Peter A.
A1  - Winslow, Luke A.
T1  - The potential of high-frequency profiling to assess vertical and seasonal patterns of phytoplankton dynamics in lakes: an extension of the Plankton Ecology Group (PEG) model
JF  - Inland waters : journal of the International Society of Limnology
N2  - The use of high-frequency sensors on profiling buoys to investigate physical, chemical, and biological processes in lakes is 
increasing rapidly. Profiling buoys with automated winches and sensors that collect high-frequency chlorophyll fluorescence 
(ChlF) profiles in 11 lakes in the Global Lake Ecological Observatory Network (GLEON) allowed the study of the vertical 
and temporal distribution of ChlF, including the formation of subsurface chlorophyll maxima (SSCM). The effectiveness of 3 
methods for sampling phytoplankton distributions in lakes, including (1) manual profiles, (2) single-depth buoys, and (3) 
profiling buoys were assessed. High-frequency ChlF surface data and profiles were compared to predictions from the 
Plankton Ecology Group (PEG) model. The depth-integrated ChlF dynamics measured by the profiling buoy data revealed a 
greater complexity that neither conventional sampling nor the generalized PEG model captured. Conventional sampling 
techniques would have missed SSCM in 7 of 11 study lakes. Although surface-only ChlF data underestimated average water 
column ChlF, at times by nearly 2-fold in 4 of the lakes, overall there was a remarkable similarity between surface and mean 
water column data. Contrary to the PEG model’s proposed negligible role for physical control of phytoplankton during the 
growing season, thermal structure and light availability were closely associated with ChlF seasonal depth distribution. Thus, 
an extension of the PEG model is proposed, with a new conceptual framework that explicitly includes physical metrics to 
better predict SSCM formation in lakes and highlight when profiling buoys are especially informative.
KW  - chlorophyll fluorescence
KW  - Global Lake Ecological Observatory Network (GLEON)
KW  - high-frequency sensors
KW  - PEG model
KW  - phytoplankton
KW  - profiling buoys
KW  - subsurface chlorophyll maximum
Y1  - 2016
U6  - https://doi.org/10.5268/IW-6.4.890
SN  - 2044-2041
SN  - 2044-205X
VL  - 6
SP  - 565
EP  - 580
PB  - Freshwater Biological Association
CY  - Ambleside
ER  -