These data describe estimates of large-bodied fish activity and their direction of movement with respect to a restored wetland located in Ottawa National Wildlife Refuge, Oak Harbor, Ohio, USA. Acoustic sonar technology was used to monitor fish activity following restoration and reconnection of a hydrologically isolated wetland pool to the wider Lake Erie system. Fish activity was measured during 56 multi-day observational events spanning four years following reconnection (2011-2014). Each hour of acoustic data was processed as an observational unit using a combination of commercial and purpose-built software. The resulting dataset quantifies fish activity and characterizes this movement as immigration into or emigration out of the restored area for 2,022 hours of observation.

Acoustic Telemetry is gaining popularity for use in fisheries research as a method to estimate survival and observe behaviors of native fish species. Methodology for capture and tagging of fish is typically context and species-specific, requiring a case by case basis for best practices to maximize survival of tagged individuals. This dataset includes acoustic detection data from 320 adult Lake Trout, Salvelinus namaycush, captured and acoustic-tagged in Lake Ontario during April-June of 2023. Biological data (total length), capture data (surface water temperature, capture depth), capture location, and capture gear (angling, bottom trawls, gillnets) are also included in the dataset as covariates that can be analyzed to determine if any of these factors affect post-release survival of tagged Lake Trout. Acoustic detection data is available from April 2023 to November 2024. Survival of acoustic-tagged Lake Trout was estimated through acoustic telemetry detections indicating the status of the Lake Trout (alive vs. dead).

Overview The Central Valley Project Improvement Act (CVPIA) funds habitat improvement work and associated monitoring in the Central Valley of California to increase salmonid populations in furtherance of meeting CVPIA fish doubling goals. This data package contains three datasets for larval White Sturgeon (Acipenser transmontanus) monitoring in the San Joaquin River (SJR) conducted by the US Fish and Wildlife Service, Lodi Fish and Wildlife Office. SJR_Larval_WST_Set Data: This dataset contains data on an experimental sampling program using boat-mounted drift nets (D-frame nets), a large drift net attached to a stationary pontoon (pontoon net), and otter trawls to catch larval White Sturgeon in the San Joaquin River. Sets were made at targeted locations from March-July in 2013, 2015, 2016, and 2017. A total of ten White Sturgeon were captured in 2016 and 11 in 2017, all with D-frame driftnets. SJR_Larval_WST_Catch Data: This dataset contains data for individual fish caught in the San Joaquin River. Species and fork length were recorded for most individuals. SJR_Fish_Taxonomy Data: This dataset contains data for fish codes used in the Catch datafile. For each species that was captured, the Species codes are listed with the corresponding Interagency Ecological Program code, common name, taxonomy (Phylum, Class, Order, Family, Genus, and Species), and whether or not the species is native to the region.

Overview The Central Valley Project Improvement Act (CVPIA) funds habitat improvement work and associated monitoring in the Central Valley of California to increase salmonid populations in furtherance of meeting CVPIA fish doubling goals. This data package contains three datasets for larval White Sturgeon (Acipenser transmontanus) monitoring in the San Joaquin River (SJR) conducted by the US Fish and Wildlife Service, Lodi Fish and Wildlife Office. SJR_Larval_WST_Set Data: This dataset contains data on an experimental sampling program using boat-mounted drift nets (D-frame nets), a large drift net attached to a stationary pontoon (pontoon net), and otter trawls to catch larval White Sturgeon in the San Joaquin River. Sets were made at targeted locations from March-July in 2013, 2015, 2016, and 2017. A total of ten White Sturgeon were captured in 2016 and 11 in 2017, all with D-frame driftnets. SJR_Larval_WST_Catch Data: This dataset contains data for individual fish caught in the San Joaquin River. Species and fork length were recorded for most individuals. SJR_Fish_Taxonomy Data: This dataset contains data for fish codes used in the Catch datafile. For each species that was captured, the Species codes are listed with the corresponding Interagency Ecological Program code, common name, taxonomy (Phylum, Class, Order, Family, Genus, and Species), and whether or not the species is native to the region.

Hydroacoustic estimates of fish density are used for fisheries management in central Lake Erie. Hydroacoustic data were collected along up to four cross-lake transects in central Lake Erie July 2010 through July 2019. Software-generated raw variables used for calculating estimates of hydroacoustic fish densities are presented here.

Kootenai river hydraulic conditions were simulated using the iRIC FaSTMECH two-dimensional hydraulic flow model (Nelson, 2003). In addition to this study, FaSTMECH 2D flow models have been developed for numerous Kootenai River studies dating back to 2005. The methods used to develop, calibrate, and simulate FaSTMECH 2D flow models are described at length in multiple previous studies (Fosness and Dudunake, in press; Barton and others, 2005; Barton and others, 2007; Logan and others, 2011; McDonald and others, 2016; McDonald and Nelson, 2018; McDonald and Nelson, 2020). Model simulations were combined with white sturgeon telemetry data to explain fish positions with respect to selected depths and depth-averaged velocity.

Kootenai river hydraulic conditions were simulated using the iRIC FaSTMECH two-dimensional hydraulic flow model (Nelson, 2003). In addition to this study, FaSTMECH 2D flow models have been developed for numerous Kootenai River studies dating back to 2005. The methods used to develop, calibrate, and simulate FaSTMECH 2D flow models are described at length in multiple previous studies (Fosness and Dudunake, in press; Barton and others, 2005; Barton and others, 2007; Logan and others, 2011; McDonald and others, 2016; McDonald and Nelson, 2018; McDonald and Nelson, 2020). Model simulations were combined with white sturgeon telemetry data to explain fish positions with respect to selected depths and depth-averaged velocity.

Data includes grass carp position and sampling data from 2020 to 2022. We used grass carp that were implanted with acoustic transmitters. The position data was generated in Fathom Position from receivers that composed several VEMCO Positioning Systems (VPS). We also queried the Great Lakes Acoustic Telemetry Observation Network (GLATOS) to obtain non-VPS position detections from receivers made from multiple projects across Lake Erie and associated tributaries. Sampling data was downloaded from the grass carp capture database hosted on ArcGIS Online These data contain information such as location of event, time gears were deployed and retrieved, and number of grass carp caught.

We initiated a project in 2011 to identify lake-wide movement patterns and spawning areas of invasive lake trout in Yellowstone Lake, WY. We implanted acoustic transmitters in lake trout and established a network of stationary telemetry receivers in Yellowstone Lake. Lake Trout tagged with acoustic transmitters (Vemco V - series) were tracked with stationary acoustic receivers (Vemco VR2W - 69 kHz) from 2011 to 2015. The number of active receivers ranged from 17 - 65 as short term goals of the project changed. Coordinates for each detection represent the location of the receiver reading the transmitter. Additionally, detection ranges can vary from apporximately 500 - 1200 meters (but see Vemco.com for more details). In total, the dataset consists of more than 24 million detections from 470 Lake Trout and 21 Yellowstone Cutthroat Trout that were tagged over the course of the study. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Detection data for Gulf sturgeon in the Suwannee River using a series of passive acoustic receivers. Data set includes receiver locations (river kilometer), detections, time periods, and individual transmitter ID.