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All gillnet data represented here expand upon vessel operations (OP table) data, all of which are collected by the United States Geological Survey, Great Lakes Science Center and its partners. The Gillnet Tables contain data collected from the research vessel deploying various gear used for gillnet data collection. The database uses sample_type to indicate the gear deployed. The tables relating to Gillnet are: GN_Annulus.csv, GN_Catch.csv, GN_Effort.csv, GN_Fish.csv, GN_L, GN_LF.csv, GN_OP.csv, GN_Prey.csv, GN_Stomach.csv, LMMB_Fish_Prey.csv, and LMMB_Invert_Prey.csv Data Quality: Note that the following data release is a snapshot of the database at the time of release. Some data quality checks are still being...
Efforts to conserve stream and river biota could benefit from tools that allow managers to evaluate landscape-scale changes in species distributions in response to water management decisions. We present a framework and methods for integrating hydrology, geographic context and metapopulation processes to simulate effects of changes in streamflow on fish occupancy dynamics across a landscape of interconnected stream segments. We illustrate this approach using a 482 km2 catchment in the southeastern US supporting 50 or more stream fish species. A spatially distributed, deterministic and physically based hydrologic model is used to simulate daily streamflow for sub-basins composing the catchment. We use geographic data...
Categories: Publication;
Types: Citation;
Tags: Rivers, Streams and Lakes,
Southeast CASC,
Water, Coasts and Ice,
aquatic biodiversity,
fluvial geomorphology,
This USGS data release documents species distribution models for 271 fluvial fish species in their native ranges of the conterminous United States. Source data, supporting code and model results are documented in this data package. Boosted Regression Tree (BRT) models were used to develop presence/absence predictions for each of the National Hydrography Dataset Plus Version 2.1 stream segments within a species' native range. The predictions provided can be linked to the NHDPlusV2.1 geospatial dataset through the COMID to create a spatial depiction of the models. The primary results are stored in the file "BRT Predictions" and are provided in comma separated value (CSV) and Parquet file formats. Parquet file format...
Categories: Data;
Tags: USGS Science Data Catalog (SDC),
United States of America,
aquatic biology,
biogeography,
biota,
This USGS data release is intended to provide a baselayer of information on likely stream crossings throughout the United States. The geopackage provides likely crossings of infrastructure and streams and provides observed information that helps validate modeled crossings and build knowledge about associated conditions through time (e.g. crossing type, crossing condition). Stream crossings were developed by intersecting the 2020 United States Census Bureau Topologically Integrated Geographic Encoding and Referencing (TIGER) U.S. road lines with the National Hydrography Dataset High Resolution flowlines. The current version of this data release specifically focuses on road stream crossings (i.e. TIGER2020 Roads)...
All mensuration data represented here expand upon vessel operations (OP table) data, all of which are collected by the United States Geological Survey, Great Lakes Science Center and its partners. The Mensuration Tables contain data collected from the research vessel deploying various gear used for mensuration data collection. The database uses sample_type to indicate the gear deployed. The tables relating to Mensuration are: Mensuration.csv, MS_head_rope_depth.csv, MS_FOOT_ROPE_DEPTH, MS_Primary.csv, MS_Temperature.csv, and MS_Wingspread.csv Data Quality: Note that the following data release is a snapshot of the database at the time of release. Some data quality checks are still being undertaken after the time...
The dataset includes ecoregion specific species distribution models for 149 common fluvial fishes of the Conterminous U.S. Species models were developed for fluvial fishes considered common and native in each of the nine EPA Wadeable Streams Assessment program aquatic ecoregions (Herlihy et al. 2008) in which the species occurred. Common native species were identified as being geographically widespread and relatively abundant within ecoregions and utilize a wide variety of habitat types. Boosted regression tree models were used to develop presence/absence predictions for each of the National Hydrography Plus Dataset Version 1.0 (NHDPlusV1) stream reaches. The text files provided can be linked to the NHDPlusV1 data...
This USGS data release documents coarse ranges for 123 fish species in the conterminous United States for level 8 hydrologic units from the Watershed Boundary Dataset (WBD). These range maps were derived by combining known fish occurrence information from four data sources: point occurrences from the Aquatic Gap Analysis Project (AGAP) fish database, point occurrences from the IchthyMaps dataset, point occurrences from the Global Biodiversity Information Facility (GBIF), and HUC-8 level range maps developed by NatureServe. Data can be linked to geospatial units of the WBD using the HUC8 field. Data are provided in comma separated value (CSV) and zipped Parquet file formats. Parquet file format is provided to help...
Categories: Data;
Tags: USGS Science Data Catalog (SDC),
United States of America,
aquatic biology,
biogeography,
biota,
Data were collected by the River Studies Program, Texas Parks and Wildlife Department. River Studies is an interdisciplinary river and stream assessment program. Its primary goal is to assure sufficient quantity and quality of water to maintain the natural biodiversity of aquatic ecosystems and their associated wetlands and riparian lands. The program staff works to characterize aquatic ecosystems, evaluate impacts to those systems, and determine water quantity and quality needs to address policy and regulatory issues. Results from long-term projects provide data from large geographic areas to address broad-scale policy and regulatory issues. Aquatic biological samples (fish, mussels, and benthic macroinvertebrates)...
Metadata specific to this state's data is not available. The MARIS Master metadata record can be accessed to help provide general data descriptions and guidance to users. MARIS is an internet-based information sharing network that allows multiple states to provide a common set of variables via a single web interface. MARIS is not a “dataset” but rather links specific content of multiple states’ datasets. MARIS does not capture all of the information from a state’s aquatic dataset – only a subset of data collected as part of aquatic species sampling surveys. The MARIS structure was developed by a consortium of state fish and wildlife agencies and implemented through contracts with various universities. In the past,...
Metadata specific to this state's data is not available. The MARIS Master metadata record can be accessed to help provide general data descriptions and guidance to users. MARIS is an internet-based information sharing network that allows multiple states to provide a common set of variables via a single web interface. MARIS is not a “dataset” but rather links specific content of multiple states’ datasets. MARIS does not capture all of the information from a state’s aquatic dataset – only a subset of data collected as part of aquatic species sampling surveys. The MARIS structure was developed by a consortium of state fish and wildlife agencies and implemented through contracts with various universities. In the past,...
Fish occurrence data to support high-resolution distribution models and test various community and macroecological hypotheses have not been available at the national scale. We present IchthyMaps, a database of high-quality historical fish occurrences covering fishes of the conterminous United States. Designed on the principles of metacommunity ecology, IchthyMaps is a compilation of presence records from atlases up to 1990, at the resolution of the 1:100,000 National Hydrography Database Plus (NHDPlus) inter-confluence stream segment, readily aggregated into hierarchically coarser units (e.g. hydrologic unit code 8-digit and 12-digit watersheds). IchthyMaps contains about 606,550 presence records for 1,038 species...
Categories: Data,
Publication;
Types: Citation;
Tags: Alabama,
Arizona,
Arkansas,
Biological Data,
Biological sampling,
Metadata specific to this state's data is not available. The MARIS Master metadata record can be accessed to help provide general data descriptions and guidance to users. MARIS is an internet-based information sharing network that allows multiple states to provide a common set of variables via a single web interface. MARIS is not a “dataset” but rather links specific content of multiple states’ datasets. MARIS does not capture all of the information from a state’s aquatic dataset – only a subset of data collected as part of aquatic species sampling surveys. The MARIS structure was developed by a consortium of state fish and wildlife agencies and implemented through contracts with various universities. In the past,...
Metadata specific to this state's data is not available. The MARIS Master metadata record can be accessed to help provide general data descriptions and guidance to users. MARIS is an internet-based information sharing network that allows multiple states to provide a common set of variables via a single web interface. MARIS is not a “dataset” but rather links specific content of multiple states’ datasets. MARIS does not capture all of the information from a state’s aquatic dataset – only a subset of data collected as part of aquatic species sampling surveys. The MARIS structure was developed by a consortium of state fish and wildlife agencies and implemented through contracts with various universities. In the past,...
Metadata specific to this state's data is not available. The MARIS Master metadata record can be accessed to help provide general data descriptions and guidance to users. MARIS is an internet-based information sharing network that allows multiple states to provide a common set of variables via a single web interface. MARIS is not a “dataset” but rather links specific content of multiple states’ datasets. MARIS does not capture all of the information from a state’s aquatic dataset – only a subset of data collected as part of aquatic species sampling surveys. The MARIS structure was developed by a consortium of state fish and wildlife agencies and implemented through contracts with various universities. In the past,...
Metadata specific to this state's data is not available. The MARIS Master metadata record can be accessed to help provide general data descriptions and guidance to users. MARIS is an internet-based information sharing network that allows multiple states to provide a common set of variables via a single web interface. MARIS is not a “dataset” but rather links specific content of multiple states’ datasets. MARIS does not capture all of the information from a state’s aquatic dataset – only a subset of data collected as part of aquatic species sampling surveys. The MARIS structure was developed by a consortium of state fish and wildlife agencies and implemented through contracts with various universities. In the past,...
Metadata specific to this state's data is not available. The MARIS Master metadata record can be accessed to help provide general data descriptions and guidance to users. MARIS is an internet-based information sharing network that allows multiple states to provide a common set of variables via a single web interface. MARIS is not a “dataset” but rather links specific content of multiple states’ datasets. MARIS does not capture all of the information from a state’s aquatic dataset – only a subset of data collected as part of aquatic species sampling surveys. The MARIS structure was developed by a consortium of state fish and wildlife agencies and implemented through contracts with various universities. In the past,...
Service definition used to drive the MARIS application at marisdata.org. MARIS is an internet-based information sharing network that allows multiple states to provide a common set of variables via a single web interface. MARIS is not a "dataset" but rather links specific content of multiple states' datasets. MARIS does not capture all of the information from each state's aquatic dataset only a subset of data collected as part of aquatic species sampling surveys. The MARIS structure was developed by a consortium of state fish and wildlife agencies and implemented through contracts with various universities. In the past, federal agency partners have provided the core funding for developing and implementing MARIS as...
This script applies topic modeling to analyze literature trends of climate impacts to inland fish based on the papers within the Fish and Climate Change Database (FiCli, DOI: 10.5066/P9973SMC). Sections 1-8 loaded the .bib file with all of the papers in the database and cleaned the text. This included combining the title/abstract/keywords, removing non-informative words, stemming words, removing punctuation, and forming phrases (ie. climate change to climate_change). Sections 9-10 divided the papers into discrete topics by identifying the ideal number of topics and then using Latent Dirichlet Allocation (LDA) modeling and Gibbs sampling to assign topics to each paper. Sections 11-17 analyzed the topic modeling results...
Categories: Data,
Publication;
Types: Citation;
Tags: FiCli,
Fish and Climate Change Database,
Latent Dirichlet Allocation,
biota,
freshwater fishes,
Maryland Department of Natural Resources, Information Technology Service and Inland Fisheries Service developed a data management system referred to as the Geographic Inland Fisheries Survey system (GIFS). The GIFS database contains all parameters typical of fisheries information including date, location, fish species, invertebrate species, habitat, water quality, and tournament details. The information is often oriented to sport fish surveys though not exclusively. MARIS is an internet-based information sharing network that allows multiple states to provide a common set of variables via a single web interface. MARIS is not a “dataset” but rather links specific content of multiple states’ datasets. MARIS does not...
This data represents fish samples collected by Fisheries and Water Resource staff of the Wisconsin Department of Natural Resources between 1945 to 2014. Only electrofishing data were included in this dataset. Data include both community index sampling and targeted gamefish data from lakes, large rivers and wadeable streams. Data were restructured to meet MARIS standards. MARIS is an internet-based information sharing network that allows multiple states to provide a common set of variables via a single web interface. MARIS is not a “dataset” but rather links specific content of multiple states’ datasets. MARIS does not capture all of the information from a state’s aquatic dataset – only a subset of data collected...
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