Fisheries Biologist
Great Lakes Science Center
Email:
dmwarner@usgs.gov
Office Phone:
734-214-9392
Fax:
734-944-8780
ORCID:
0000-0003-4939-5368
Location
GLSC - AA - R and D Bldg
1451 Green Road
Ann Arbor
, MI
48105
US
Supervisor:
Kurt R Newman
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Description of Work USGS will conduct seasonal sampling of benthic invertebrates, zooplankton, prey fish, and their diets to complement the seasonal lower trophic level sampling by EPA. A point of emphasis is describing the vertical distribution of planktivores and their zooplankton prey, to fill a knowledge gap on these predator/prey interactions. These data will provide a more holistic understanding of how invasive-driven, food-web changes could be altering energy available to sport fishes in the Great Lakes and used to build bioenergetics models that can evaluate whether zooplankton dynamics are being driven by limited resources or excessive predation. Understanding the key drivers of zooplankton will provide...
Categories: Project;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Accountability,
CSMI,
Ecosystem health,
Energy transfer,
Fish production, All tags...
GLRI,
Great Lakes Restoration Initiative,
Great Lakes Restoration Initiative,
Invasive Species,
Invasive species,
Lake,
Lake:Lake Huron,
Predator/prey balance,
Template 183,
Trend analysis,
Uploaded in Batch,
Watershed,
Watershed:Lake Huron Basin, Fewer tags
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Abstract (from http://www.sciencedirect.com/science/article/pii/S0380133014002597): Fish stock-recruitment dynamics may be difficult to elucidate because of nonstationary relationships resulting from shifting environmental conditions and fluctuations in important vital rates such as individual growth or maturation. The Great Lakes have experienced environmental stressors that may have changed population demographics and stock-recruitment relationships while causing the declines of several prey fish species, including rainbow smelt (Osmerus mordax). We investigated changes in the size and maturation of rainbow smelt in Lake Michigan and Lake Huron and recruitment dynamics of the Lake Michigan stock over the past...
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Acoustic seabed classification (ASC) is an important method for understanding landscape-level physical and biological patterns in the aquatic environment. Bottom habitats in the Laurentian Great Lakes are poorly mapped to date, and will require a variety of contributors and data sources to complete. We repurposed a long-term split-beam echosounder dataset gathered for purposes of fisheries assessment to estimate lakebed properties utilizing unsupervised classification of echo return data. We extracted first echo properties and analyzed lakebed hardness and roughness to define and map three statistically supported lakebed classes revealed through cluster analysis. Our results indicate coherent and logical class boundaries,...
Categories: Data;
Tags: Geomorphology,
Lake Huron,
Lake Michigan,
Remote Sensing,
Sedimentology, All tags...
USGS Science Data Catalog (SDC),
bathymetry,
biota,
cartography,
elevation,
environment,
geoscientificInformation,
inlandWaters,
lakebed acoustic reflectivity,
lakebed characteristics,
single-beam echo sounder, Fewer tags
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Each line in the file “Lake Michigan fish acoustic data from 2011 to 2016.csv” represents the acoustic data and estimated fish density for a single depth layer of water. Surveys are conducted along transects, transects are divided horizontally into successive intervals, and then within an interval there are multiple successive depth layers. Area backscattering (ABC), mean acoustic size (sigma), and fish density are reported for each unique transect-interval – layer from Lake Michigan in the years 2011-2016. Area backscattering (PRC_ABC), mean acoustic size (sigma), and fish density in the intervals and layers of acoustic survey transects of Lake Michigan in the years 2011-2016. The survey is carried out using a...
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These data were derived from hydroacoustic data collected by uncrewed surface vehicles (USVs) and powered research vessels. The powered vessels overtook the USVs in Lakes Huron and Michigan to study fish avoidance of survey vessels during traditional acoustic surveys. The water column was divided into three depth groups (epilimnion, metalimnion, hypolimnion) for analysis. Each drone transect was binned into 30-sec intervals and measured hydroacoustic values were averaged in this region. To compare vessels and drones, parallel overtakes (overtakes where vessel and drone followed the same path) which were ~2 km long, were measured by both platforms and the differences between acoustic measures compared.
Categories: Data;
Tags: Aquatic Biology,
Great Lakes,
Lake Huron,
Lake Michigan,
USGS Science Data Catalog (SDC), All tags...
acoustics,
biota,
fishery management,
multibeam sonar,
transect sampling, Fewer tags
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