Hydroacoustic estimation of zooplankton biomass at two shoal complexes in the Apostle Islands Region of Lake Superior

Beth V. Holbrook; Thomas R Hrabik; Donn K Branstrator; Dan L. Yule; Jason D. Stockwell

doi:10.3394/0380-1330(2006)32[680:HEOZBA]2.0.CO;2

Hydroacoustic estimation of zooplankton biomass at two shoal complexes in the Apostle Islands Region of Lake Superior

Beth V. Holbrook, Thomas R Hrabik, Donn K Branstrator, Dan L. Yule, Jason D. Stockwell

Biology (Duluth)

Research output: Contribution to journal › Article › peer-review

14 Scopus citations

Abstract

Hydroacoustics can be used to assess zooplankton populations, however, backscatter must be scaled to be biologically meaningful. In this study, we used a general model to correlate site-specific hydroacoustic backscatter with zooplankton dry weight biomass estimated from net tows. The relationship between zooplankton dry weight and backscatter was significant (p < 0.001 ) and explained 76% of the variability in the dry weight data. We applied this regression to hydroacoustic data collected monthly in 2003 and 2004 at two shoals in the Apostle Island Region of Lake Superior. After applying the regression model to convert hydroacoustic backscatter to zooplankton dry weight biomass, we used geostatistics to analyze the mean and variance, and ordinary kriging to create spatial zooplankton distribution maps. The mean zooplankton dry weight biomass estimates from plankton net tows and hydroacoustics were not significantly different (p = 0.19) but the hydroacoustic data had a significantly lower coefficient of variation (p < 0.001). The maps of zooplankton distribution illustrated spatial trends in zooplankton dry weight biomass that were not discernable from the overall means.

Original language	English (US)
Pages (from-to)	680-696
Number of pages	17
Journal	Journal of Great Lakes Research
Volume	32
Issue number	4
DOIs	https://doi.org/10.3394/0380-1330(2006)32[680:HEOZBA]2.0.CO;2
State	Published - 2006

Bibliographical note

Funding Information:
We thank Michigan Technological University (MTU) and the captains of the R/V Aggasiz for collaborating on this project. Steve Schram and the fisheries technicians at the Wisconsin Department of Natural Resources-Bayfield Station provided a great deal of equipment and field advice. Stacey Stark provided guidance with the GIS analysis and Olaf Jen-son provided invaluable geostastical knowledge. We are also particularly grateful to Ed Verhamme who helped collect the zooplankton and hydroacoustic data. This work is the result of research sponsored by the Minnesota Sea Grant College Program supported by the NOAA Office of Sea Grant, United States Department of Commerce, under grant No. NA03OAR4170048. The U.S. Government is authorized to reproduce and distribute reprints for government purposes, not withstanding any copyright notation that may appear hereon. This paper is journal reprint No. JR527 of the Minnesota Sea Grant College Program.

Keywords

Backscatter
Hydroacoustic
Lake Superior
Spatial analysis
Zooplankton

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title = "Hydroacoustic estimation of zooplankton biomass at two shoal complexes in the Apostle Islands Region of Lake Superior",

abstract = "Hydroacoustics can be used to assess zooplankton populations, however, backscatter must be scaled to be biologically meaningful. In this study, we used a general model to correlate site-specific hydroacoustic backscatter with zooplankton dry weight biomass estimated from net tows. The relationship between zooplankton dry weight and backscatter was significant (p < 0.001 ) and explained 76% of the variability in the dry weight data. We applied this regression to hydroacoustic data collected monthly in 2003 and 2004 at two shoals in the Apostle Island Region of Lake Superior. After applying the regression model to convert hydroacoustic backscatter to zooplankton dry weight biomass, we used geostatistics to analyze the mean and variance, and ordinary kriging to create spatial zooplankton distribution maps. The mean zooplankton dry weight biomass estimates from plankton net tows and hydroacoustics were not significantly different (p = 0.19) but the hydroacoustic data had a significantly lower coefficient of variation (p < 0.001). The maps of zooplankton distribution illustrated spatial trends in zooplankton dry weight biomass that were not discernable from the overall means.",

keywords = "Backscatter, Hydroacoustic, Lake Superior, Spatial analysis, Zooplankton",

author = "Holbrook, {Beth V.} and Hrabik, {Thomas R} and Branstrator, {Donn K} and Yule, {Dan L.} and Stockwell, {Jason D.}",

note = "Funding Information: We thank Michigan Technological University (MTU) and the captains of the R/V Aggasiz for collaborating on this project. Steve Schram and the fisheries technicians at the Wisconsin Department of Natural Resources-Bayfield Station provided a great deal of equipment and field advice. Stacey Stark provided guidance with the GIS analysis and Olaf Jen-son provided invaluable geostastical knowledge. We are also particularly grateful to Ed Verhamme who helped collect the zooplankton and hydroacoustic data. This work is the result of research sponsored by the Minnesota Sea Grant College Program supported by the NOAA Office of Sea Grant, United States Department of Commerce, under grant No. NA03OAR4170048. The U.S. Government is authorized to reproduce and distribute reprints for government purposes, not withstanding any copyright notation that may appear hereon. This paper is journal reprint No. JR527 of the Minnesota Sea Grant College Program.",

year = "2006",

doi = "10.3394/0380-1330(2006)32[680:HEOZBA]2.0.CO;2",

language = "English (US)",

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AU - Yule, Dan L.

AU - Stockwell, Jason D.

N1 - Funding Information: We thank Michigan Technological University (MTU) and the captains of the R/V Aggasiz for collaborating on this project. Steve Schram and the fisheries technicians at the Wisconsin Department of Natural Resources-Bayfield Station provided a great deal of equipment and field advice. Stacey Stark provided guidance with the GIS analysis and Olaf Jen-son provided invaluable geostastical knowledge. We are also particularly grateful to Ed Verhamme who helped collect the zooplankton and hydroacoustic data. This work is the result of research sponsored by the Minnesota Sea Grant College Program supported by the NOAA Office of Sea Grant, United States Department of Commerce, under grant No. NA03OAR4170048. The U.S. Government is authorized to reproduce and distribute reprints for government purposes, not withstanding any copyright notation that may appear hereon. This paper is journal reprint No. JR527 of the Minnesota Sea Grant College Program.

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N2 - Hydroacoustics can be used to assess zooplankton populations, however, backscatter must be scaled to be biologically meaningful. In this study, we used a general model to correlate site-specific hydroacoustic backscatter with zooplankton dry weight biomass estimated from net tows. The relationship between zooplankton dry weight and backscatter was significant (p < 0.001 ) and explained 76% of the variability in the dry weight data. We applied this regression to hydroacoustic data collected monthly in 2003 and 2004 at two shoals in the Apostle Island Region of Lake Superior. After applying the regression model to convert hydroacoustic backscatter to zooplankton dry weight biomass, we used geostatistics to analyze the mean and variance, and ordinary kriging to create spatial zooplankton distribution maps. The mean zooplankton dry weight biomass estimates from plankton net tows and hydroacoustics were not significantly different (p = 0.19) but the hydroacoustic data had a significantly lower coefficient of variation (p < 0.001). The maps of zooplankton distribution illustrated spatial trends in zooplankton dry weight biomass that were not discernable from the overall means.

AB - Hydroacoustics can be used to assess zooplankton populations, however, backscatter must be scaled to be biologically meaningful. In this study, we used a general model to correlate site-specific hydroacoustic backscatter with zooplankton dry weight biomass estimated from net tows. The relationship between zooplankton dry weight and backscatter was significant (p < 0.001 ) and explained 76% of the variability in the dry weight data. We applied this regression to hydroacoustic data collected monthly in 2003 and 2004 at two shoals in the Apostle Island Region of Lake Superior. After applying the regression model to convert hydroacoustic backscatter to zooplankton dry weight biomass, we used geostatistics to analyze the mean and variance, and ordinary kriging to create spatial zooplankton distribution maps. The mean zooplankton dry weight biomass estimates from plankton net tows and hydroacoustics were not significantly different (p = 0.19) but the hydroacoustic data had a significantly lower coefficient of variation (p < 0.001). The maps of zooplankton distribution illustrated spatial trends in zooplankton dry weight biomass that were not discernable from the overall means.

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KW - Zooplankton

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ER -

Hydroacoustic estimation of zooplankton biomass at two shoal complexes in the Apostle Islands Region of Lake Superior

Abstract

Bibliographical note

Keywords

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