Item talk:Q227366

{

 "@context": "http://schema.org/",
 "@type": "WebPage",
 "additionalType": "Project",
 "url": "https://www.usgs.gov/centers/chesapeake-bay-activities/science/assessing-habitat-conditions-support-freshwater-fisheries",
 "headline": "Assessing the habitat conditions to support freshwater fisheries in the Chesapeake Watershed",
 "datePublished": "March 22, 2022",
 "author": [
   {
     "@type": "Person",
     "name": "Kelly O Maloney, Ph.D.",
     "url": "https://www.usgs.gov/staff-profiles/kelly-o-maloney",
     "identifier": {
       "@type": "PropertyValue",
       "propertyID": "orcid",
       "value": "0000-0003-2304-0745"
     }
   }
 ],
 "description": [
   {
     "@type": "TextObject",
     "text": "Community measures \u2013Models were built to relate community measures with landscape predictors within each region."
   },
   {
     "@type": "TextObject",
     "text": "The results of the study have been published in Ecological Indicators (with open access), titled: \u201cUsing fish community and population indicators to assess the biological condition of streams and rivers of the Chesapeake Bay watershed, USA.\u201d (https://doi.org/10.1016/j.ecolind.2021.108488)"
   },
   {
     "@type": "TextObject",
     "text": "Conducting the fish-habitat assessments are challenging due to the size of the Bay and its watershed, which precludes direct surveys of all waters in an efficient and cost-effective manner. Predictive models can fill this gap by providing estimates of condition for these unsurveyed locations. Therefore, the USGS and NOAA are collaborating to improve fish-habitat assessments for inland waters and the estuary, using available data and innovative analytical methods with plans for a joint assessment in a pilot area."
   },
   {
     "@type": "TextObject",
     "text": "The species analyses focused on those native to the watershed and considered sensitive (e.g., Brook Trout and northern hog sucker)."
   },
   {
     "@type": "TextObject",
     "text": "Predictions were made for the years 2001, 2006, 2011, and 2016 based on changes in landcover."
   },
   {
     "@type": "TextObject",
     "text": "Fish community and species distribution predictions for streams and rivers of the Chesapeake Bay Watershed. https://doi.org/10.5066/P9B4BMAG"
   },
   {
     "@type": "TextObject",
     "text": "Successful management of freshwater systems hinges on the ability to effectively identify where to best invest resources toward conservation and restoration. Here the authors developed a flexible approach for non-tidal streams and rivers that considers both a novel composite measure of community biological condition and a species level occurrence analysis with similar data. This approach provides results that can give multiple views of condition and address multiple management needs. When examined at a finer scale (e.g., Fig. 5) results can be used to identify potential problem areas that require attention or areas that are experiencing biological improvement (i.e., lift) possibly via management actions."
   },
   {
     "@type": "TextObject",
     "text": "2.    Region-specific fish community measure identification:"
   },
   {
     "@type": "TextObject",
     "text": "5.    Model prediction:"
   },
   {
     "@type": "TextObject",
     "text": "Managers also wanted assessment for important game species, so species like Smallmouth Bass were included."
   },
   {
     "@type": "TextObject",
     "text": "The steps taken to achieve this assessment (Figure 1) included:"
   },
   {
     "@type": "TextObject",
     "text": "1.    Watershed-wide fish and landscape predictor data set generation:"
   },
   {
     "@type": "TextObject",
     "text": "The project team included Kelly Maloney, Kevin Krause, Matthew Cashman, Wesley Daniel, Benjamin Gressler, Daniel Wieferich, and John Young of the USGS. Kelly Maloney (kmaloney@usgs.gov) and Kevin Krause (kkrause@usgs.gov) are the primary contacts for this project."
   },
   {
     "@type": "TextObject",
     "text": "Results are presented in figure 4 for brook trout (BRT), Northern hog sucker (NHS), Smallmouth bass (SMB), and Torrent Sucker (TRS). The areas where species are predicted to be present (light blue shades) represent places with landscape conditions that could support the species, while areas predicted to be absent (dark blue shades) represent places that may not support the populations of the species."
   },
   {
     "@type": "TextObject",
     "text": "Investigators compiled 56 landscape predictors from the USEPA StreamCat dataset and USGS National Water Quality Assessment program that have been previously summarized to the NHDPlusV2.1 and that have been found to strongly affect or potentially affect stream health and fish habitat."
   },
   {
     "@type": "TextObject",
     "text": "The watershed was divided into ecoregions to better reflect gradient of ecological conditions across the watershed (Figure 2). Fish community metrics were selected based on their utility to indicate overall condition within each region. The regions for the Chesapeake watershed included the Coastal Plains (CPL), Northern Appalachians (NAP), Southern Appalachians Northwest (SAPNW), and Southern Appalachians Piedmont (SAPPIED)."
   },
   {
     "@type": "TextObject",
     "text": "4.    Model development:"
   },
   {
     "@type": "TextObject",
     "text": "The investigators used the optimized region-specific models to predict fish community measures in 66,867 stream and river reaches across the watershed. Community measures were combined into a single index that reflected the degree of community alteration calculated by taking an average of the decile scores from each community measure, with higher deciles indicating less altered habitat conditions."
   },
   {
     "@type": "TextObject",
     "text": "Comparisons were made between the community and selected species assessments of condition."
   },
   {
     "@type": "TextObject",
     "text": "Investigators worked with 20 programs and data providers to gather fish community and species-specific sampling data. A total of 31,660 fish sampling events from 01 January 1969 through 13 December 2019 were collated."
   },
   {
     "@type": "TextObject",
     "text": "Species measures \u2013 Separate models were built for each species to relate landscape variables to species occurrence."
   },
   {
     "@type": "TextObject",
     "text": "The USGS examined and tested methods needed for a fish-habitat assessment in the nontidal portion of the Chesapeake Bay watershed. The investigators evaluated a large amount of data as part of the study including (1) fish community and species data, and (2) landscape variables that affect fish habitat conditions in nontidal streams and rivers. The investigators determined there was an insufficient number of comparable reference sites to develop a traditional measure of biological conditions, so they developed a novel method that combined community and species-level indicators."
   },
   {
     "@type": "TextObject",
     "text": "Results also allow managers to compare and identify areas where both community and population level measures align (or differ) in predicting reach condition, which could aid in management efforts. For example, a site with a predicted Brook Trout presence but predicted marginal community index habitat score may indicate an area to target restoration to protect this key species, as the community assessment suggests potential habitat degradation which was missed by the species level assessment."
   },
   {
     "@type": "TextObject",
     "text": "3.    Key species of interest identification:"
   },
   {
     "@type": "TextObject",
     "text": "Findings are provided for both fish community and species-specific results."
   },
   {
     "@type": "TextObject",
     "text": "Issue: The Chesapeake Bay Program partners are striving to improve habitat conditions for recreational fisheries and other native fishes in the Bay and its watershed. While national fish habitat assessments have been conducted, resource managers need more local information to focus restoration and protection efforts in Chesapeake Bay watershed."
   },
   {
     "@type": "TextObject",
     "text": "Species-specific models were used to predict species occurrence within the native range of each key species identified."
   },
   {
     "@type": "TextObject",
     "text": "Community metrics from inter-agency compilation of inland fish sampling data within the Chesapeake Bay Watershed. https://doi.org/10.5066/P9D6JU4X"
   },
   {
     "@type": "TextObject",
     "text": "The predicted community conditions are shown in figure 3. Higher decile values (green shades) represent places with less altered habitat conditions, while lower deciles (brown shades) are areas with more altered habitat conditions. Decile scores have been averaged by ecoregion so direct comparisons across regions are not possible. Based on figure 3, the summary of the spatial conditions for each ecoregion were:"
   },
   {
     "@type": "TextObject",
     "text": "Measures of the fish community were calculated including metrics describing composition, tolerances, habitat preferences, and functional traits."
   }
 ],
 "funder": {
   "@type": "Organization",
   "name": "Chesapeake Bay Activities",
   "url": "https://www.usgs.gov/centers/chesapeake-bay-activities"
 },
 "about": [
   {
     "@type": "Thing",
     "name": "Fish and Aquatic Species"
   },
   {
     "@type": "Thing",
     "name": "Krause"
   },
   {
     "@type": "Thing",
     "name": "Science Technology"
   },
   {
     "@type": "Thing",
     "name": "Freshwater and Coastal Ecology"
   },
   {
     "@type": "Thing",
     "name": "Biology"
   },
   {
     "@type": "Thing",
     "name": "Information Systems"
   },
   {
     "@type": "Thing",
     "name": "Geology"
   },
   {
     "@type": "Thing",
     "name": "Chesapeake Bay"
   },
   {
     "@type": "Thing",
     "name": "Habitat\u00a0and Species\u00a0Modeling"
   },
   {
     "@type": "Thing",
     "name": "Fish and Aquatic Species Conservation"
   },
   {
     "@type": "Thing",
     "name": "Ecosystems"
   },
   {
     "@type": "Thing",
     "name": "Environmental Health"
   },
   {
     "@type": "Thing",
     "name": "Fish, Streams, and Water Quality"
   },
   {
     "@type": "Thing",
     "name": "Maloney"
   },
   {
     "@type": "Thing",
     "name": "Water"
   },
   {
     "@type": "Thing",
     "name": "Methods and Analysis"
   },
   {
     "@type": "Thing",
     "name": "Energy"
   },
   {
     "@type": "Thing",
     "name": "Freshwater Fish and Habitats"
   }
 ]

}