Extant population monitoring and habitat assessment data sets of benthic species were used as inputs for occupancy models focused on Sicklefin and Sturgeon chub with the goals of describing temporal, spatial, and environmental factors associated with occupancy patterns of each chub species, assessing co-occurrence of the two species, and determining relationships between co-occurrence and environmental factors. We also used three-species occupancy models to assess co-occurrence of these chubs with other primarily benthic species. This data set is comprised of the outputs of these models.

We simulate over 28,000 datasets and saved their model outputs to answer the following three questions: (1) what is an adequate sampling design for the multi-scale occupancy model when there are a priori expectations of parameter estimates?, (2) what is an adequate sampling design when we have no expectations of parameter estimates?, and (3) what is the cost (in terms of bias, accuracy, precision and coverage) in occupancy estimates) if availability is not accounted for? Specifically, we simulated data under four scenarios: Scenario 1 (n = 10,000): Species availability is constant across sites (but less than one), Scenario 2 (n = 9,358): Species availability is heterogenous across sites, Scenario 3 (n = 2,815): Species availability is heterogenous across years, and Scenario 4 (n = 5,942): Species availability is correlated to their detection probability. Then, for each scenario except the first, we analyzed the data using four different estimators: (i) constant multi-scale occupancy model, (ii) multi-scale occupancy model with a random-effects term in the availability part of the model, (iii) constant single-scale occupancy model, and (iv) single-scale occupancy model with a random-effects term in the detection part of the model. Note the formulation of the random-effects terms included in the models mimicked the way that data were simulated (e.g., if species availability was heterogenous across sites, then a site random-effects term was included in the models). The first scenario was analyzed using models (i) and (iii) only. For simplicity, we refer to models (i) and (iii) as ‘constant’ models or 'fixed-effects' models. We refer to models (ii) and (iv) as ‘random-effects’ models. The summary of simulated data and model estimates are located in four folders, each corresponding to a different simulated scenario: Scenario 1 (n = 10,000): Folder ModelOutput_Scen1_TwolevelSim = csv files holding data are named Results_TwoLevelAvail_2lev_x.csv Scenario 2 (n = 9,358): Folder ModelOutput_Scen2_HeteroSite = csv files holding data are named Results_TwoLevelAvail_Hetero_x.csv Scenario 3 (n = 2,815): Folder ModelOutput_Scen3_HeteroYear = csv files holding data are named Results_TwoLevelAvail_HeteroSeason_x.csv Scenario 4 (n = 5,942): Folder ModelOutput_Scen4_Cor = csv files holding data are named Results_TwoLevelAvail_Cor_x.csv Each row in each of the csv files contains information related to a different simulated dataset and includes information related to: sampling design, true parameter values, and model estimates. Other files in the folder correspond to the entire model output (.rda files), time for model run to complete (time_..csv), and a file indicating whether or not the model run finished (nsim...csv). For more information related to those files, we point the user to the code that generated them: Scenario 1 (n = 10,000): Scen1_Constant.R Scenario 2 (n = 9,358): Scen2_HeteroSite.R Scenario 3 (n = 2,815): Scen3_HeteroYear.R Scenario 4 (n = 5,942): Scen4_Corr.R

These data represent the results of trapping efforts for native northwestern pond turtles (Actinemys marmorata) and non-native red-eared sliders (Trachemys scripta elegans) in wetlands and irrigation canals in agricultural regions of the Sacramento Valley in 2018 and the Sacramento-San Joaquin River Delta in 2019. In addition to detection data for these two turtle species, the dataset includes habitat data from each trapped site and data on the capture rate of fish, frogs, and tadpoles at each site.

Data includes fish abundance and habitat data collected at ten sites in the Sandusky River, OH. Fish were collected using two 3.67 m long hoop nets with an initial hoop diameter of 0.91 m. Nets were set perpendicular to the current, opening toward the shoreline. Nets were set for approximately 24 hours and catch rates for each set were defined as the number of fish caught in the two hoop nets per 24-hour sampling period. Fish were identified to species, measured for total length (mm), and released. Water quality was taken daily at each site at approximately the same time of day with a YSI Exo2 multiparameter sonde. Physical habitat data was recorded at the start of each trial. Vegetation coverage was characterized by type of vegetation and genus (submerged, emerged, or floating) and substrate was also categorized (silt, sand, clay, rock). Physical habitat was recorded as percent and defined as the percentage of the sampling area (e.g. within 50-m of each platform) covered by a feature at the time of data collection. Daily minimum and maximum depths (m) were calculated from data recorded Onset HOBO water level data loggers, which were attached to two of the floating platforms approximately 0.5-m above the substrate. The distance of each site from the confluence of Muddy Creek Bay (m) was estimated from the mid-point of a site using ArcGIS Pro v. 2.7.1. This data was used to assess the fish assemblage in the Sandusky River, focusing on changes in assemblage following the removal of the Ballville Dam in 2018.

These data were used to describe temporal trends in fish and invertebrate communities in the Scientific Investigators Report: Evaluation and Review of Ecology-Focused Stream Studies to Support Cooperative Monitoring, Fountain Creek Basin, Colorado. This data release consists of invertebrate data collected between 1985 and 2022, fish data collected between 2003 and 2022, and the input and output files from the trend analyses.

These data were used to describe temporal trends in fish and invertebrate communities in the Scientific Investigators Report: Evaluation and Review of Ecology-Focused Stream Studies to Support Cooperative Monitoring, Fountain Creek Basin, Colorado. This data release consists of invertebrate data collected between 1985 and 2022, fish data collected between 2003 and 2022, and the input and output files from the trend analyses.

Largely supported by the Interagency Ecological Program (IEP), the California Department of Water Resources (DWR) has operated a fisheries and invertebrate monitoring program in the Yolo Bypass since 1998. The main objectives of the Yolo Bypass Fish Monitoring Program (YBFMP) are to collect baseline data on lower trophic levels (phytoplankton, zooplankton and insect drift), juvenile and adult fish, hydrology, and water quality parameters. As the Yolo Bypass has been identified as a high restoration priority by numerous regulatory agencies, these baseline data are critical for evaluating success of future restoration projects. In addition, the data have already served to increase our understanding of the role of the Yolo Bypass in the life history of native fishes, and its ecological function in the San Francisco Estuary. Zooplankton are an important component in the diet of larval, juvenile, and small adult fishes within the San Francisco Estuary, including Delta Smelt, juvenile Chinook Salmon, Striped Bass, and Sacramento Splittail. The YBFMP collects zooplankton year-round from two sites. Since 2011, samples have been collected biweekly (every other week) to weekly (during floodplain inundation) using 150- and 50- micrometer mesh plankton nets. Zooplankton are identified and enumerated by contractors (currently BSA Environmental Services). The goals of the zooplankton monitoring program are to compare the seasonal variation in species densities and trends between (1) the Sacramento River channel, and (2) the Yolo Bypass, the river’s seasonal floodplain. Data on zooplankton catch and associated water quality parameters are presented in this dataset.

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 adult White Sturgeon (Acipenser transmontanus) monitoring in the San Joaquin River (SJR) conducted by the US Fish and Wildlife Service, Lodi Fish and Wildlife Office. The primary purpose for this sampling was to capture White Sturgeon and implant acoustic telemetry tags for a tracking project. Therefore, the data are useful for determining when and where White Sturgeon were captured, but they should not be used to determine actual distribution or abundance. SJR_Adult_WST_Set contains data from a sampling program using various methods to catch adult White Sturgeon in the San Joaquin River. Sets were made at targeted locations primarily from March-May in 2012-2018 (other dates were occasionally sampled). SJR_Adult_WST_Catch contains data for individual fish caught via gillnets, trammel nets, setlines, or angling in the San Joaquin River. Species and fork length were recorded for all fish. For White Sturgeon, girth, maturation, tag, and surgery information are provided. SJR_Fish_Taxonomy 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.

The study was designed to assess the strength of the innate linkage of substrate and food in foraging by early juvenile Pallid and Shovelnose Sturgeon and their hybrids and adult Sicklefin and Shoal Chub. The data include information on the fish weights throughout the duration of the experiment as well as observed fish behavior data. Wet weights from fish were recorded to monitor feeding consumption and the behavior data was generated in response to watching the fish during feeding. Information found in the fish weights data table includes the fish name, the tank number, the food treatment given, the light treatment given, the week of the trial, the date when the weight was taken, the substrate material, where food was delivered, and lastly the fish weight in grams. Information found in the fish behavior data table includes the observed behavior of the fish, a numerical identifier given to the observation, the fish name, the week of the experiment, the food treatment given, the light treatment given, the substrate material, where food was delivered, the time in seconds an observed behavior started, the date of the observed behavior, the time the observation period started, and lastly the tank number.