TY - GEN
T1 - Linking weather patterns, water quality and invasive mussel distributions in the development and application of a water clarity index for the Great Lakes
AU - Ransibrahmanakul, Varis
AU - Pittman, Simon J.
AU - Pirhalla, Douglas E.
AU - Sheridan, Scott C.
AU - Lee, Cameron C.
AU - Barnes, Brian B.
AU - Hu, Chuanmin
AU - Shein, Karsten
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/10/31
Y1 - 2018/10/31
N2 - The Great Lakes contain 84% of the fresh water in North America and provide many critical and valuable ecosystem services to lakeside communities. In the past decade, a rapid ecosystem regime shift has occurred where changing precipitation and runoff patterns, along with invasive zebra and quagga mussels, have contributed to dramatic lake-specific responses in water clarity, reductions in phytoplankton, increases in toxic algal blooms, and disruptions in the food chain. Focusing on Lake Michigan, this study applies a newly improved remote sensing algorithm for water clarity and integrates meteorological data and in-situ sampling of mussels to understand the spatial and temporal linkages between historical weather patterns, water clarity and mussel abundance. Results from a decade of satellite-derived ocean color images reveal the complex spatio-temporal patterns of ‘bio-clarification’ occurring in Lake Michigan. Mussel biomass was negatively correlated with phytoplankton concentrations and turbidity, but association was likely weakened by unmeasured variables such as nearshore runoff, patterns of plankton and nutrient dynamics, thermal structure and mixing.
AB - The Great Lakes contain 84% of the fresh water in North America and provide many critical and valuable ecosystem services to lakeside communities. In the past decade, a rapid ecosystem regime shift has occurred where changing precipitation and runoff patterns, along with invasive zebra and quagga mussels, have contributed to dramatic lake-specific responses in water clarity, reductions in phytoplankton, increases in toxic algal blooms, and disruptions in the food chain. Focusing on Lake Michigan, this study applies a newly improved remote sensing algorithm for water clarity and integrates meteorological data and in-situ sampling of mussels to understand the spatial and temporal linkages between historical weather patterns, water clarity and mussel abundance. Results from a decade of satellite-derived ocean color images reveal the complex spatio-temporal patterns of ‘bio-clarification’ occurring in Lake Michigan. Mussel biomass was negatively correlated with phytoplankton concentrations and turbidity, but association was likely weakened by unmeasured variables such as nearshore runoff, patterns of plankton and nutrient dynamics, thermal structure and mixing.
KW - Dreissenid mussels
KW - Lake Michigan
KW - Phytoplankton bloom
KW - Regime shift
KW - Turbidity
UR - http://www.scopus.com/inward/record.url?scp=85064150721&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85064150721&partnerID=8YFLogxK
U2 - 10.1109/IGARSS.2018.8518935
DO - 10.1109/IGARSS.2018.8518935
M3 - Conference contribution
AN - SCOPUS:85064150721
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 120
EP - 123
BT - 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018
Y2 - 22 July 2018 through 27 July 2018
ER -