This data release contains numerous shapefiles that describe baseline characterization of the physical attributes of the riverine ecosystems in two national parks – Ozark National Scenic Riverways (ONSR), Missouri, and Buffalo National River (BNR), Arkansas. The individual metadata associated with each shapefile describe in detail the specific process steps, source inputs for the data, and the specific river the data characterizes.

This data release contains numerous shapefiles that describe baseline characterization of the physical attributes of the riverine ecosystems in two national parks – Ozark National Scenic Riverways (ONSR), Missouri, and Buffalo National River (BNR), Arkansas. The individual metadata associated with each shapefile describe in detail the specific process steps, source inputs for the data, and the specific river the data characterizes.

This data release contains numerous shapefiles that describe baseline characterization of the physical attributes of the riverine ecosystems in two national parks – Ozark National Scenic Riverways (ONSR), Missouri, and Buffalo National River (BNR), Arkansas. The individual metadata associated with each shapefile describe in detail the specific process steps, source inputs for the data, and the specific river the data characterizes.

This data release contains numerous shapefiles that describe baseline characterization of the physical attributes of the riverine ecosystems in two national parks – Ozark National Scenic Riverways (ONSR), Missouri, and Buffalo National River (BNR), Arkansas. The individual metadata associated with each shapefile describe in detail the specific process steps, source inputs for the data, and the specific river the data characterizes.

This data release contains numerous shapefiles that describe baseline characterization of the physical attributes of the riverine ecosystems in two national parks – Ozark National Scenic Riverways (ONSR), Missouri, and Buffalo National River (BNR), Arkansas. The individual metadata associated with each shapefile describe in detail the specific process steps, source inputs for the data, and the specific river the data characterizes.

The geology of the Ozark National Scenic Riverways (ONSR) in southern Missouri has been mapped at 1:24,000 scale. This was achieved through the combined efforts of U.S. Geological Survey and Missouri Geological Survey individual 7.5 minute quadrangle mapping and additional field work by the authors of this report. Geologic data covering the area of the ONSR, which also includes a 1 mile buffer zone surrounding the park, as well as a few key adjoining areas, have been compiled into a single, seamless GIS database.

The geology of the Ozark National Scenic Riverways (ONSR) in southern Missouri has been mapped at 1:24,000 scale. This was achieved through the combined efforts of U.S. Geological Survey and Missouri Geological Survey individual 7.5 minute quadrangle mapping and additional field work by the authors of this report. Geologic data covering the area of the ONSR, which also includes a 1 mile buffer zone surrounding the park, as well as a few key adjoining areas, have been compiled into a single, seamless GIS database.

These data consist of rectified aerial photographs, measurements of active channel width, measurements of river and floodplain bathymetry and topography, and ancillary data. These data are specific to the corridor of the Green River in Canyonlands National Park between Horseshoe Canyon and Deadhorse Canyon, Utah. The time period for these data are 1940 to 2018. The 'Channel Width' shapefile data are measurements of the active channel width of the Green River at 1-km intervals in and near Canyonlands National Park, Utah. The 'Mineral Bottom' csv data are river channel cross-sections for a 3-km study reach of the Green River upstream from Mineral Bottom, Utah. The study reach is near the mouth of Hell Roaring Canyon, 5 km upstream from the Mineral Bottom boat ramp, which is 85 km upstream from the confluence of the Green River with the Colorado River. Six cross-sections were originally established by the U.S. Fish and Wildlife Service in June 1995. Additional cross-sections were added by Utah State University in August 1995. A subset of the cross-sections (where original monuments were found) were re-surveyed by the U.S. Geological Survey Grand Canyon Monitoring and Research Center in cooperation with Utah State University in June 2015. The raster data are aerial images and digital elevation models (DEMs) for segments of the Green River in and near Canyonlands National Park, Utah. The aerial images depict the river channel and adjacent floodplains for most of the corridor of the Green River in Canyonlands National Park. The images were acquired from public sources and orthorectified and mosaiced for this study. The DEMs cover the river channel and adjacent floodplain for the Fort Bottom segment of the Green River within Canyonlands National Park and include both bathymetric and topographic data. The bathymetric data were collected by the U.S. Geological Survey Grand Canyon Monitoring and Research Center with funding provided by the National Park Service. The topographic data are airborne lidar data that were collected for the state of Utah by a contractor. The lidar data are available at https://doi.org/10.5069/G9RV0KSQ.

These data consist of rectified aerial photographs, measurements of active channel width, measurements of river and floodplain bathymetry and topography, and ancillary data. These data are specific to the corridor of the Green River in Canyonlands National Park between Horseshoe Canyon and Deadhorse Canyon, Utah. The time period for these data are 1940 to 2018. The 'Channel Width' shapefile data are measurements of the active channel width of the Green River at 1-km intervals in and near Canyonlands National Park, Utah. The 'Mineral Bottom' csv data are river channel cross-sections for a 3-km study reach of the Green River upstream from Mineral Bottom, Utah. The study reach is near the mouth of Hell Roaring Canyon, 5 km upstream from the Mineral Bottom boat ramp, which is 85 km upstream from the confluence of the Green River with the Colorado River. Six cross-sections were originally established by the U.S. Fish and Wildlife Service in June 1995. Additional cross-sections were added by Utah State University in August 1995. A subset of the cross-sections (where original monuments were found) were re-surveyed by the U.S. Geological Survey Grand Canyon Monitoring and Research Center in cooperation with Utah State University in June 2015. The raster data are aerial images and digital elevation models (DEMs) for segments of the Green River in and near Canyonlands National Park, Utah. The aerial images depict the river channel and adjacent floodplains for most of the corridor of the Green River in Canyonlands National Park. The images were acquired from public sources and orthorectified and mosaiced for this study. The DEMs cover the river channel and adjacent floodplain for the Fort Bottom segment of the Green River within Canyonlands National Park and include both bathymetric and topographic data. The bathymetric data were collected by the U.S. Geological Survey Grand Canyon Monitoring and Research Center with funding provided by the National Park Service. The topographic data are airborne lidar data that were collected for the state of Utah by a contractor. The lidar data are available at https://doi.org/10.5069/G9RV0KSQ.

To examine potential influence of tributaries on riparian habitat complexity along ~216 km of the Colorado River in Utah and ~300km of the Dolores River in Colorado and Utah, we first classified fluvial features and land cover of the bottomland on remotely sensed imagery. We then examined riparian and geomorphic patterns within the near channel zone with variably-sized spatial units. We used supervised image classification to create a 2-m resolution map of the primary land cover types within bottomlands of the Colorado and Dolores rivers, including two anthropogenic classes, four vegetation classes, bare ground, water and shadow. We selected these cover classes as major vegetation and land cover types that could be discerned from imagery. Our minimum mapping unit was 16m2. We were unable to map channel areas with flowing or standing water using supervised image classification, so we hand digitized channels based on a visual inspection of 2-m resolution imagery. We classified 6 channel classes based on their geomorphic characteristics and location within the river network (i.e., tributary vs. primary channel) or relation to the primary channel (e.g., split flow channels and secondary channels) and converted these to a 2-m resolution image (adapted from Moore et al 2012). We then combined land cover and channel classes to produce a single map representing both cover types along the Colorado and Dolores rivers. Our classification was based on 2-m resolution, multi-spectral (RGB NIR) aerial photographs for September 2013 and 2014 from the USDA National Agriculture Imagery Program (NAIP; http//www.fsa.usda.gov). We identified tributary junctions using the National Hydrography Dataset Plus Version 2 (NHDPlus V2) using the medium resolution (1:100,000 scale) National Hydrography Dataset (NHD) (http://nhd.usgs.gov/). To more accurately locate tributary junctions, we extracted flowlines corresponding to tributaries and converted each flowline to a point located at the terminus proximal to the channel centerline. We manually corrected tributary junction point locations with the NAIP images. We defined the near channel zone as within 20 meters of the edge of the Dolores low flow channel and within 100 meters of the edge of the Colorado low flow channel. These distances represented the average widths of the low flow channel for the two rivers. We assumed that habitat conditions closer to the channel would be more strongly influenced by fluvial processes and less strongly influenced by land management (e.g., farming, road development). We created spatial units for analysis within the near channel zone with Thiessen polygons - a polygon containing a point and defining an area closest to the point relative to all other systematically placed points (Fortin and Dale 2005). Beginning at the upstream study site boundary for each river, we placed regularly spaced points at three intervals: 10-, 25-, and 100-m to capture patterns for different sized spatial units around tributary junctions. For each point, we created a Thiessen polygon. Our use of Thiessen polygons as spatial units followed the example of other researchers (Alber and Piegay 2011). This data release includes shapefiles and associated metadata for: land and channel cover types along both rivers; tributary junction locations along both rivers; and the 10-, 25-, and 100-m Thiessen polygons along both rivers. Alber A., and Piégay H., 2011, Spatial disaggregation and aggregation procedures for characterizing fluvial features at the network-scale: application to the Rhône basin (France): Geomorphology, v. 125, p. 343-360. Fortin M.J., and Dale M.T., 2005, Spatial analysis: a guide for ecologists: Cambridge, Cambridge University Press, 365 p. Moore K., Jones K., Dambacher J., and Stein C., 2012, Aquatic inventories project methods for stream habitat surveys: Corvallis, OR, Conservation and recovery program, Oregon Department of Fish and Wildlife, 74 p.