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Using predicted lake temperatures from uncalibrated, process-based models (PB0) and process-guided deep learning models (PGDL), this dataset summarized a collection of thermal metrics to characterize lake temperature impacts on fish habitat for 881 lakes. Included in the metrics are daily thermal optical habitat areas and a set of over 172 annual thermal metrics.
Categories: Data;
Tags: MN,
Minnesota,
SD,
South Dakota,
US, All tags...
United States,
climate change,
deep learning,
environment,
hybrid modeling,
inlandWaters,
machine learning,
modeling,
reservoirs,
temperate lakes,
temperature,
thermal habitat,
thermal profiles,
water,
water resources, Fewer tags
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Understanding age and growth are important for fisheries science and management; however, age data are not routinely collected for many populations. We propose and test a method of borrowing age–length data across increasingly broader spatiotemporal levels to create a hierarchical age–length key (HALK). We assessed this method by comparing growth and mortality metrics to those estimated from lake–year age–length keys ages using seven common freshwater fish species across the upper Midwestern United States. Levels used for data borrowing began most specifically by borrowing within lake across time and increased in breadth to include data within the Hydrologic Unit Code (HUC) 10 watershed, HUC8 watershed, Level III...
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Daily lake surface temperatures estimates for 185,549 lakes across the contiguous United States from 1980 to 2020 generated using an entity-aware long short-term memory deep learning model. In-situ measurements used for model training and evaluation are from 12,227 lakes and are included as well as daily meteorological conditions and lake properties. Median per-lake estimated error found through cross validation on lakes with in-situ surface temperature observations was 1.24 °C. The generated dataset will be beneficial for a wide range of applications including estimations of thermal habitats and the impacts of climate change on inland lakes.
Categories: Data;
Tags: AL,
AR,
AZ,
Alabama,
Aquatic Biology, All tags...
Arizona,
Arkansas,
CA,
CO,
CT,
California,
Colorado,
Connecticut,
DC,
DE,
Delaware,
District of Columbia,
Ecology,
FL,
Florida,
GA,
Georgia,
Hydrology,
IA,
ID,
IL,
IN,
Idaho,
Illinois,
Indiana,
Iowa,
KS,
KY,
Kansas,
Kentucky,
LA,
Limnology,
Louisiana,
MA,
MD,
ME,
MI,
MN,
MO,
MS,
MT,
Maine,
Maryland,
Massachusetts,
Michigan,
Minnesota,
Mississippi,
Missouri,
Montana,
NC,
ND,
NE,
NH,
NJ,
NM,
NV,
NY,
Nebraska,
Nevada,
New Hampshire,
New Jersey,
New Mexico,
New York,
North Carolina,
North Dakota,
OH,
OK,
OR,
Ohio,
Oklahoma,
Oregon,
PA,
Pennsylvania,
RI,
Rhode Island,
SC,
SD,
South Carolina,
South Dakota,
TN,
TX,
Tennessee,
Texas,
US,
USGS Science Data Catalog (SDC),
UT,
United States,
Utah,
VA,
VT,
Vermont,
Virginia,
WA,
WI,
WV,
WY,
Washington,
Water Quality,
Water Resources,
West Virginia,
Wisconsin,
Wyoming,
climate change,
deep learning,
environment,
inlandWaters,
machine learning,
modeling,
reservoirs,
surface temperature,
temperate lakes,
temperature,
water,
water resources, Fewer tags
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Sport fisheries of lakes are embedded in complex system of ecological and social interactions. The multiple drivers that affect lake sport fisheries, along with the complex interactions within lakes, make it difficult to forecast changes in sport fisheries and plan adaptive responses to build resilience of these important resources. Resilience involves managing with an eye toward critical thresholds for behavior of ecosystems. Project researchers are working to develop quantitative tools for assessment of thresholds in sport fisheries that can be used by management agencies to evaluate potential impacts of climate change mediated through species and habitat interactions. Several outputs of the project will be adaptable...
Categories: Project;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: 2011,
2011,
CASC,
CASC,
Data Visualization & Tools, All tags...
Data Visualization & Tools,
Fish,
Fish,
Fish,
Fish,
National CASC,
National CASC,
National CASC,
National CASC,
Projects by Region,
Projects by Region,
Rivers, Streams and Lakes,
Rivers, Streams and Lakes,
Rivers, Streams and Lakes,
Rivers, Streams and Lakes,
Science Tools for Managers,
Science Tools for Managers,
Water, Coasts and Ice,
Water, Coasts and Ice,
Water, Coasts and Ice,
Water, Coasts and Ice,
Wildlife and Plants,
Wildlife and Plants,
Wildlife and Plants,
Wildlife and Plants, Fewer tags
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Observed water temperatures from 1980-2018 were compiled for 877 lakes in Minnesota (USA). There were four lakes included in this data release that did not have temperature observations available at the time of compilation or these data existed elsewhere and were unknown to the compilation team. These data were used as training, test, and error-estimation data for process-guided deep learning models and the evaluation of process-based models. The data are formatted as a single csv (comma separated values) file with attributes corresponding to the unique combination of lake identifier, time, and depth. Data came from a variety of sources, including the Water Quality Portal, the North Temperate Lakes Long-Term Ecological...
Tags: MN,
Minnesota,
SD,
South Dakota,
US, All tags...
United States,
climate change,
deep learning,
environment,
hybrid modeling,
inlandWaters,
machine learning,
modeling,
reservoirs,
temperate lakes,
temperature,
thermal profiles,
water,
water resources, Fewer tags
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