Habitat Improvement Projects for Stream and Oxbow

Fish of Greatest Conservation Need

2017 Annual Progress Report to:

U.S. Fish and Wildlife Service

Iowa Department of Natural Resources Minnesota Department of Natural Resources

Submitted by:

Courtney L. Zambory1, Alexander P. Bybel1, Clay L. Pierce2, Kevin J. Roe1, and Michael J. Weber1

1Department of Natural Resource Ecology and Management, Iowa State University

2Iowa Cooperative Fish and Wildlife Research Unit, U.S. Geological Survey

December 31, 2017

Introduction As one of the most physically modified states in the country, Iowa’s landscape has been dramatically altered from its original condition by intensive agricultural practices (Bogue 1994). Once an expansive wetland and prairie ecosystem with meandering streams and countless off-channel habitats, Iowa is now dominated by row crop agriculture and channelized waterways (Bishop 1981; Smith 1981). Southwest Minnesota has experienced similar land use changes (Waters 1977; Minnesota Department of Natural Resources 2016). These drastic alterations of the landscape and hydrology are thought to be primary reasons for decline of Topeka Shiner (Notropis topeka) and Plains Topminnow (Fundulus sciadicus) populations (Russell et al. 1997; Tabor 1998; Bakevich et al. 2015). Both species are listed as species of greatest conservation need in Iowa (Iowa Department of Natural Resources 2015) and Minnesota (Minnesota Department of Natural Resources 2006). Topeka Shiners were once common throughout prairie regions of Iowa, Minnesota, Kansas, Missouri, Nebraska, and South Dakota; however, declines have led to the federal listing of this species as endangered (Tabor 1998). Traditionally, Topeka Shiners were thought only to be common in relatively clear, low-order prairie streams with permanent flow and gravel, cobble, or sand substrates (Minckley and Cross 1959, Tabor 1998, Blausey 2001). Research from the early 2000s, however, has found that this species occurs commonly in off-channel habitats (OCH) such as oxbow lakes or side channels and in streams with silt or detritus substrates in Iowa and Minnesota (Clark 2000, Dahle 2001, Hatch 2001, Bakevich et al. 2013), even within livestock watering ponds near streams (Thomson and Berry 2009; Ceas and Larson 2010; Bakevich 2012). Despite the propensity of these OCH for shrinking or drying completely during droughts, a recent Iowa study found Topeka Shiners in 52% of OCH sampled compared with only 9% of in-stream habitats (Bakevich 2012, Bakevich et al. 2015). Thus, OCH may serve as vital source habitats for Topeka Shiners. Plains Topminnows once occurred in parts of Iowa, Minnesota, South Dakota, Nebraska, Colorado, Wyoming, Missouri, Kansas, and Oklahoma (Pasbrig et al. 2012), but have declined dramatically within their historic range (Lee et al. 1980). Although no single factor seems to explain the decline, habitat degradation resulting from land use changes and introduction of non-native species have been identified as likely causes (Fischer and Paukert 2008; Pasbrig et al. 2012). A portion of the remaining range of Plains Topminnows in southwest Minnesota (Minnesota Department of Natural Resources 2013) overlaps the present Topeka Shiner range, and like Topeka Shiners, Plains Topminnows are also associated with OHC in these areas. Plains Topminnows are generally associated with vegetated sloughs and backwater habitats that have shallow, clear water. They are tolerant of hypoxic conditions (Rahel and Thel 2004). The Plains Topminnow is threatened by any activity causing alteration of its habitat, particularly groundwater withdrawal and drainage of wetlands. Plains Topminnows were believed to be extirpated from Iowa (IAGFA 2005) until 2011 when they were found in four northwest Iowa locations (J. Olson, Iowa DNR, personal communication) adjacent to their known distribution in Minnesota. OCH may serve as vital source habitats for Plains Topminnows as well as federally endangered Topeka Shiners. Threats that are suspected to have contributed to the declines of Topeka Shiners and Plains Topminnow include channelization, levee and impoundment creation, tile construction, and upland native prairie removal. These land use changes alter the hydrology, temperature, and water quality of streams, result in the degradation of the substrate as well as in-stream and riparian vegetative cover. These threats are ranked in the Iowa Wildlife Action Plan (IWAP) (Iowa Department of Natural Resources 2015). Loss of habitat and hydrologic connections are identified as threats in the Minnesota Wildlife Action Plan (MWAP) (Minnesota Department of Natural Resources 2006). Being Midwestern/Great Plains species, both Topeka Shiners and Plains Topminnows are resilient to changes in water temperature and quality. However, without appropriate spawning and nursery areas or predation refuge, these species will most likely continue to decline. Effective habitat restoration strategies are now emerging that show promise in reversing the declines of these species and hopefully will promote their continued existence. In Iowa, less than 2% of the landscape is permanently protected public habitat and managed under conservation practices (Iowa Department of Natural Resources 2015). The majority of known locations for these two Species of Greatest Conservation Need (SGCN) are on private land (Aleshia Kenney, US Fish and Wildlife Service, personal communication). In Minnesota, less than 0.1% of prairie habitat remains in the Inner Coteau ecological subsection (Minnesota Department of Natural Resources 2016) within which this project occurs. Restoration of native prairie

habitats surrounding naturally meandering streams and associated oxbows are critical to the restoration success of these fishes. Project Objectives This report addresses SWG-C Objectives 1 and 3 only. Objectives 2 and 4 pertain to responsibilities of the Iowa and Minnesota DNR, and Iowa State University’s responsibility for Objective 5 is fulfilled by submission of this report.

SWG-C Objective 1: GIS Analyses of Potential Restoration Locations

a. Species occurrence databases from both states will be compiled and combined to reveal locations where the two species have been documented as occurring.

Accomplished to date: Database Creation Methodology: Data were obtained for Topeka Shiner presence and absence (when available) locations within the North Raccoon River watershed, Boone River watershed, and Rock River watershed and compiled into a master database by source to be shared amongst stakeholders (Table 1). Per the licensing agreement with the Minnesota Department of Natural Resources (MnDNR), exact locations of records derived from the MnDNR Natural Heritage Information System were not included in the database, but they were used to create new species distribution models for the Topeka Shiner. Results: Topeka Shiner record sources range from 1890 to 2017. Topeka Shiner presence and absence within HUC 10 watersheds were compared through time to understand how Topeka Shiner ranges have expanded, contracted, or remained stable (Figure 1; Figure 2). We are working to update a Topeka Shiner status map for the North Raccoon and Boone River watersheds in Iowa using this data (Table 2; Figure 3). Additionally, this database was used to create an updated species distribution model of Topeka Shiners in all watersheds (see below). Species Distribution Modeling: Methodology: Data from 2010 to present for all watersheds of study were selected to model Topeka Shiner distribution. Presence and absence data were plotted on a 30m x 30m resolution grid in the Universal Transverse Mercator (UTM) 15N spatial projection. Environmental data were collected at three different spatial scales: local, HUC 12, and HUC 10. Local data included land use within a 30m buffer of each stream segment and physical characteristics of the stream network. Several 2m horizontal resolution Light Detection and Ranging (LiDAR) bare-earth digital elevation models (DEM)s provided by Iowa State University’s GIS Facility (ISGISF; http://www.gis.iastate.edu/gisf/projects/acpf) were used to create flow paths using a 40.5ha drainage threshold. Flow paths were manually coded as either being true stream flow paths or non-stream flow paths using 2015 aerial imagery. Once flow paths were coded for the entire watersheds, a final stream network was created using the agricultural conservation planning framework (ACPF) tool within ESRI’s ArcGIS 10.4 (Redlands, CA, USA). The resulting final stream network was populated with Strahler stream order, slope, length, Shreve magnitude, upstream confluence drainage area, and downstream confluence drainage area based on the DEM. Sinuosity for each segment was calculated by dividing the total length of the stream segment by the straight line distance between the stream segment’s upstream and downstream confluence. Variables will be used to model species distribution with multiple single model approaches including a Generalized Linear Model (GLM), a Generalized Additive Model (GAM), an Artificial Neural Network model (ANN), a Random Forest (RF) model, and a Maximum Entropy (MAXENT) model. Additionally an ensemble model that combines these five approaches to reduce individual model error and bias and generate a more accurate species distribution model will be created for Topeka Shiners in all watersheds. Modeling will be performed using R software and the biomod2 R package

(https://cran.r-project.org/web/packages/biomod2/index.html). The accuracy of these different approaches will be evaluated, and we hope to develop a future model of range shifts as a result of simulated future restoration sites. Potential Restoration Location Identification Methodology: A GIS tool has been created to identify off-channel habitats, relic stream channels, and off-channel habitat scars. Several 2m horizontal resolution Light Detection and Ranging (LiDAR) bare-earth digital elevation models (DEM)s were provided by Iowa State University’s GIS Facility (ISGISF; http://www.gis.iastate.edu/gisf/projects/acpf). These high resolution DEMs were used to create flow paths that drained at least 40.5ha. Flow paths were visually examined using 2015 aerial imagery to determine if the flow paths were non-stream flow paths, perennial stream paths, or drainage ditches. Stream segments coded as perennial stream paths and drainage ditches were used to create a final stream network. A relative height above channel dataset for each watershed was created using the Height Above Channel tool from the ACPF ArcGIS toolbox to describe each cell’s vertical position in relation to the nearest stream cell to which it would flow. After speaking with USFWS personnel it was determined that off-channel restorations for Topeka Shiner conservation were only conducted adjacent to perennial streams (Aleshia Kenny, US Fish and Wildlife Service, personal communication). To comply with this stipulation, a 500m buffer around only stream segments determined to be perennial streams was used as a search radius for potential restoration locations. The original DEM (oDEM) within the 500m perennial stream buffer was filled using the ArcGIS Fill tool to create a filled DEM (fDEM). The oDEM was subtracted from the fDEM to identify depressions within the landscape (Figure 4). Depressions less than 100m2 were eliminated from consideration as potential restoration sites as they were determined to be too small. Depressions that intersected the stream network were also eliminated from consideration as, by definition, an off-channel habitat is disconnected from the stream channel. Field boundary shapefiles that described the general use of each field as agricultural, non-agricultural, and pasture for all watersheds were obtained from the ACPF Watershed Database Land Use Viewing and Data Downloading website. Depressions that had less than 100m2 outside an agricultural field were also eliminated from consideration as potential restoration sites because off-channel restorations are not conducted within agricultural fields. Topographic characteristics were calculated for each depression including mean depth, maximum depth, mean slope, and mean height above channel. Morphometric characteristics such as circularity, solidity, convexity, concavity, rectangularity, and perimeter were calculated for each depression to describe its shape. All depressions were visually binary coded as either a target feature (an oxbow, an oxbow scar, or a relic stream channel) or a non-target feature by two readers using historical and present-day aerial imagery (Figure 5). Once all features were coded, a classification and regression tree (CART) model was created in R statistical software to create models to distinguish target features (potential restoration sites) from non-target features. Watersheds were analyzed separately, all together, and by ecoregion. Potential restoration sites were then ranked by their model’s conditional probability (Figure 6).

Results: We evaluated all models for specificity (true negative rate), sensitivity (true positive rate), precision (how often a modeled target feature was actually a target feature), overall correct classification, and the area under the receiver operator curve (AUC/ROC) (Table 3). Specificity and sensitivity were high in all models ranging from 0.89 to 0.94 for the former and 0.75 to 0.89 for the latter. Correct classification rates ranged from 0.88 to 0.94 with the Rock River watershed having the highest correct classification and the Boone River Watershed having the lowest correct classification rate. AUC/ROC scores ranged from 0.82 to 0.91 for all model combinations. The AUC/ROC score performance follows the academic grading scale with a score of 0.7-0.8 representing a good model and 0.9-1.0 representing an excellent predictive model. The weakest performance metric was precision which ranged from 0.16 to 0.24 indicating that all models had substantial noise. We addressed this noise issue by ranking modeled targets from 0-6 based on their normalized conditional probabilities. Higher ranked features were more likely to be true target features and better candidate restoration sites while lower ranked features were more likely to be noise. This process was designed to visually direct managers to the sites most likely to be quality candidate restoration sites. Because the model that was

calibrated to include all watersheds performed well in all metrics, it was chosen to be included in development of a tool that will be able to be used for future restoration selections in other geographic ranges. The final model included both morphometric and topographic characteristics in determining whether a depression was a potential restoration site. Solidity, or a proxy for a shape’s curvature, was the first and most important split within all models. Mean height above channel, mean slope, area, mean depth, circularity, rectangularity, and concavity were also included in the final combined model.

To be completed:

- Complete final species distribution modeling Deviations:

- None

b. Minnesota’s Watershed Health Assessment Framework (WHAF) will be used in MN portions of

the project area, and WHAF will be implemented in Iowa portions utilizing existing geospatial resources.

Accomplished to date:

Calculation of watershed health indices has continued for Iowa using the Minnesota WHAF

methodology (Minnesota Department of Natural Resources 2015; see Table 1). Data have been obtained for all but two of the targeted watershed health indices. The two data sources that are still to be obtained have been located, and we are just awaiting delivery. In total, 12 indices have been completed and calculated out of 21 total indices planned. Health scores have been calculated at the HUC 12, HUC 10, and HUC 8 spatial scales and will be compared with the presence of fish species of greatest conservation need.

To be completed: Nine health indices have yet to be calculated at each watershed scale, and watershed health has yet to be compared with the distribution of species of greatest conservation need as well as the results of the Topeka Shiner resiliency model developed by the USFWS.

Deviations:

- None

SWG-C Objective 3: Assess the effectiveness of conservation actions (habitat restoration) by monitoring Topeka Shiner and Plains Topminnow presence, abundance, and genetic diversity of populations compared to connectivity and habitat response.

a. Survey at least 20 sites in Iowa and Minnesota for Topeka Shiners and Plains Topminnows.

Data will be collected on all fish species encountered.

Methodology: Sampling for Topeka Shiners was conducted during the summers of 2016 and 2017 (Figure 7). Each oxbow was considered one site. Oxbows were sampled for fish using a bag seine (10.7m X 1.8m, 6.35mm mesh or 16.8 X 1.8m, 6.35mm mesh) following methods from previous studies (Thompson and Berry 2009; Bakevich et al. 2013). All fish were collected using a 3-pass depletion. Fish were

identified to species, counted, placed in live baskets, and released after all passes are complete. If Topeka Shiners were collected at any site they were considered present at that site, but if no Topeka Shiners were collected they were considered completely absent (Figure 8). Stream site length was 20 times the average wetted stream width with a minimum of 150m and a maximum of 400m. Stream sites were sampled for fish using methods modified from Bakevich et al. (2013). Fish sampling was conducted with a single upstream electrofishing pass using a barge electrofishing unit. If the stream was too shallow to be sampled with a barge shocker, sampling was carried out with a Smith-Root LR-20 backpack electrofishing unit. Electrofishing was followed by a variable number of seine pulls with either a seine (4.6m X 1.8m, 6.35mm mesh) or a bag seine (10.7m X 1.8m, 6.35mm mesh or 16.8m X 1.8m, 6.35mm mesh) as conditions permitted. Each electrofishing pass began at the bottom of the reach and proceeded upstream. For both oxbows and streams, lengths of all piscivores (Black Crappie Pomoxis nigromaculatus, White Crappie Pomoxis annularis, Bluegill Lepomis macrochirus, Pumpkinseed Lepomis gibbosus, Largemouth Bass Micropterus salmoides, Smallmouth Bass Micropterus dolomieu, Channel Catfish Ictalurus punctatus, Flathead Catfish Pylodictis olivaris, Walleye Sander vitreus, Yellow Perch Perca flavescens, Northern Pike Esox lucius, and Yellow Bullhead Ameiurus natalis, and Black Bullhead Ameiurus melas), Topeka Shiners, and Plains Topminnows were measured to nearest millimeter. Up to 20 Topeka Shiners and 20 Plains Topminnows were randomly selected, and a portion of the anal fin that was clipped and preserved in 95% ethanol for genetic analysis.

Accomplished to date: Summary 2016

North Raccoon River Watershed - 14 in-stream segments, 35 restored oxbows, and 2 unrestored oxbows were sampled - 44 fish species collected (4 are SGCNs; Table 5) - Topeka Shiners present in 7 stream segments and 11 restored oxbows - 5 pre-restoration sites were sampled

Rock River Watershed - 11 stream segments and 1 restored oxbow sampled in Minnesota - 4 unrestored oxbow channels and 2 stream sites sampled pre-restoration in Iowa - 37 fish species collected (4 are SGCNs; Table 6) - Topeka Shiners present in 7 stream segments and 3 oxbows - Plains Topminnow found in 4 stream sites and 1 unrestored oxbow channel

2017

North Raccoon River Watershed - 10 stream segments and 19 oxbows sampled - 38 fish species (3 are SGCNs; Table 5) - Topeka Shiners present in 9 oxbows and 1 stream segment Rock River Watershed - 3 stream segments and 9 oxbows sampled - 30 fish species (2 are SGCNs; Table 6) - Topeka Shiners present in 7 oxbows

Details

2016 North Raccoon River Watershed During the 2016 season the field crew sampled in 6 different streams in the North Raccoon River watershed. Two Cedar Creeks are present in the North Raccoon River watershed the upper Cedar Creek is located in HUC 0710000602 while the lower Cedar Creek is located in HUC 0710000609. The lower Cedar Creek was the most thoroughly sampled of these streams as it contained the most restored oxbows with 21 completed by 2015. The field crew sampled 16 of these oxbows and found Topeka Shiners in 6 of them. Topeka Shiners were found in high number in two of the smaller and shallower oxbows that had been typically dry in previous years. We also sampled 6 stream sites on Cedar Creek and found Topeka Shiners in 5 of them. All but one Topeka Shiner found in this stream came sites near a large cluster of restored oxbows. West Buttrick Creek has 12 restored oxbows, and 9 of these restored sites were sampled with 7 containing Topeka Shiners. Despite Topeka Shiners presence observed in the majority of oxbows, they were found in low abundance. Sampling occurred in two oxbow clusters a couple of miles apart. The upstream cluster contained 3 oxbows where Topeka Shiners were present in the past. However, only one Topeka Shiner was found among the three oxbows in 2016. The oxbows had been connected to the stream in the spring and other fishes were present in the oxbows. The downstream cluster consisted of 6 oxbows. Topeka Shiners were observed in low abundance here as well with 3 oxbows with 2 or less Topeka Shiners and 3 oxbows with less than 20 individuals. Two stream sites, one on the upstream end and one on the downstream end of the oxbow cluster were sampled, but no Topeka Shiners were found in either. The only other stream in the North Raccoon River watershed that had Topeka Shiners was Lake Creek which has 6 restorations. The 2 restored oxbows that were sampled contained Topeka Shiners initially after restoration, but Topeka Shiners had not been observed in the past 4 years and neither contained Topeka Shiners when sampled in 2016. One stream site was sampled on Lake Creek where a single Topeka Shiner was found in a stagnant side channel. Camp Creek and Prairie Creek were sampled but contained no Topeka Shiners. Two restorations and one adjacent stream site were sampled on Camp Creek and 5 recently restored oxbows were sampled Prairie Creek. Low numbers of fish were collected, but species that were collected included Largemouth Bass, Green Sunfish, and Black Bullhead in these oxbows despite connection to the stream weeks before sampling. Two stream sites were also sampled as well as 3 unrestored oxbows that had high diversity of fishes, but no Topeka Shiners. Pre-restoration sampling There were 4 restoration sites sampled in the North Raccoon Watershed, but none contained Topeka Shiners. The restoration site on Lake Creek was almost completely dry and contained no fishes. There were two restoration sites on the upper Cedar Creek located in HUC 0710000602.. One site contained only Green Sunfish and was holding 0.5 m of water when sampled August 2016. The other restoration site appeared to be an oxbow scar that does not seem to have held water recently. Stream sampling occurred in a small tributary stream to Cedar Creek that was close to the site. There was also one site off of the North Raccoon River. This was the largest site sampled over the summer as the oxbow was several hundred meters long. Sampling was difficult as a result of high siltation and duckweed. Fish were present in low numbers consisting of Green Sunfish and Black Bullhead, which could be partially attributed to the difficulty of sampling. Rock River Watershed There were a total of 18 sites sampled in the Rock River watershed with 12 sites in Minnesota and 6 in Iowa.

Minnesota pre- and post-restoration sites There were 4 stream sites that were sampled in small tributaries to Rock River, and 2 tributaries were sampled on the same property near Edgerton. Both contained high numbers of Topeka Shiners. Therefore, it was unnecessary to seine the entire reach. One tributary near Hardwick contained no Topeka Shiners, but had Plains Topminnows in high abundance. Seven Plains Topminnows were captured using backpack electrofishing and 63 were captured with seines. The seine hauls with the most success were along heavily vegetated stream edges. There was one tributary that was sampled in the town of Luverne, MN where 27 Topeka Shiners were captured despite being less than 1m wide in a majority of the sample reach. There were 2 sites on Elk Creek, both contained Topeka Shiners and Plains Topminnows. One site contained high numbers of Plains Topminnows and also 3 Topeka Shiners although Topeka Shiners were not collected when sampled earlier in the year. The other sites contained low numbers of both Topeka Shiners and Plains Topminnows. Mound Creek within Blue Mounds State Park, MN was also sampled. An oxbow that was restored in 2015 was sampled and found to have over 100 Topeka Shiners following one seine pass, including young-of–year. Additional seining was not conducted to prevent fatalities of fishes. The oxbows had been connected to the stream multiple times in 2016 and was flooded a week before sampling. A stream site was sampled adjacent to this oxbow and Topeka Shiners were present in good numbers. Two Plains Topminnows were found, one during backpack electrofishing and one was spotted near instream vegetation and caught with a seine. Sampling also occurred between the two dams in the parks and 3 Topeka Shiners were caught. No Topeka Shiners were captured above either dam, but these sites did contain abundant of Fathead Minnows, Creek Chubs and Common Shiners. Iowa pre-restoration sites: There were 5 potential restoration sites in the Iowa portion of the Rock River Watershed. Two restoration sites were sampled near the Minnesota border in a disconnected side channel of the Rock River. These were close to sites that contained Plains Topminnows when sampled by John Olsen (Iowa DNR) in 2011. The site closer to the stream was covered in duckweed and shallow but had both Plains Topminnows and Topeka Shiners. The second site was father up the channel much deeper and wide with lots of woody debris. Over 20 Topeka Shiners were found at that that site. There was a restoration site off of Little Rock Creek, while there was some water in this oxbow, it was overgrown with vegetation and could not be sampled, but the field crew was able to sample in the stream next to it and found no Topeka Shiners or Plains Topminnows. There were more pre-restoration sites in a disconnected side-channel of Otter Creek. Two sites were sampled in the channel and one adjacent site was sampled in the stream and no Topeka Shiners or Plains Topminnows were found. 2017 North Raccoon River Watershed

Topeka Shiners were historically found in East Buttrick Creek, but were not detected in 2016. No restorations have yet occurred on East Buttrick, so 2 unrestored oxbows and a stream site were sampled in 2017. Topeka Shiners were found in both sampled oxbows, but not in the stream. The farthest upstream oxbow is adjacent to a section of the stream which strongly resembles a drainage ditch. This upstream oxbow was sampled in May when flow in the area appeared slightly higher than average, but the oxbow itself was very shallow (water depth < 15.2cm) and was found to contain only and 1 Topeka Shiner along with a few Fathead and Brassy Minnows. Later in the summer (from June to August) the oxbow dried up. The other oxbow, located further downstream, was also shallow (<60cm) and was also found to have 12 Topeka Shiners. Like the upstream oxbow, this site was also observed to be completely dry in August.

There was a mix of new sites and repeated sites on West Buttrick Creek in 2017. Although Topeka Shiners were found in this stream in 2016, none were found in 2017. Topeka Shiners were found

in the sampled oxbows in previous studies as well as in 2016, but not in 2017. The fish community in these oxbows was dominated by Black Bullhead and Green Sunfish. There were also few smaller cyprinids with larger Common Shiners being the most abundant. It is worth noting that multiple landowners reported that the oxbows had gone dry and then had been reconnected to the stream between the 2016 and 2017 samplings. These oxbows became either dry or extremely shallow during the summer of 2017.

The majority of sites on the lower Cedar Creek were repeated from 2016. No sites that did not have Topeka Shiners in 2016 were observed to have held Topeka Shiners in 2017. Only 2 oxbows contained Topeka Shiners both years. Both of those oxbows became dry during the 2017 field season. Only one new site for this study was added in this stream as all other potential sites had become dry before they were able to be sampled. The new site in 2017 was a gravel pit located on private land north of the University 40 property. This site was unable to be sampled in 2016 due to deep water, but due to the dry conditions into August 2017, this oxbow was able to be sampled thoroughly. Topeka Shiners had been observed in very high numbers at this site in 2015, but sampling in 2017 only produced 14 individuals.

Purgatory Creek was another new drainage added to this study in 2017. There are no oxbow restorations on Purgatory Creek, so 2 unrestored oxbows and 1 stream segment were sampled. One oxbow was very nearly dry and contained no fish. The other site was deeper and contained larger fish such as Largemouth Bass, Crappie, and Black Bullhead, but no Topeka Shiners. The stream segment between theses oxbows did produce 2 Topeka Shiners, an adult male and adult female. There were other HUC 10 watersheds that were sampled with no Topeka Shiners being found. Lake Creek was the most sampled of these with 4 restored oxbows and a stream site. The connection between the stream and the oxbows seemed very high. The only fish species found were Fathead Minnows and species of sunfish. An oxbow and 2 stream segments were sampled in the headwaters of the north Raccoon River. Other HUC 10s sampled were Buck Run and Dickson Branch. Iowa Pre Restoration sites. There were 4 potential restoration sites visited in 2017, all of which were located in the Whitehorse Complex on the North Raccoon River in Sac County. These sites were visited in August and like most other oxbows in the drainage, both restored and unrestored, were dry at the time. Rock River Watershed There were 3 unrestored oxbows and one stream segment sampled in the Iowa portion of the Little Rock River. Only 2 of the oxbows contained Topeka Shiners, but in low numbers (1 and 4). Both were large oxbows that were partially wooded and had a lot of macrophyte cover. No Topeka Shiners were found in the adjacent stream section. Two other Iowa sites were sampled in the Rock River Watershed. One, a stream site on Otter Creek, contained no Topeka Shiners. The other site was an old stream channel that was disconnected from the Rock River near Rock Valley making this the most downstream site sampled in the Rock River drainage. This site was too large and filled with debris to use the standard oxbow protocol, but it was seined where accessible. Observed fish species included Common Carp, Largemouth Bass and Green Sunfish. Additionally, this site contained the highest abundance of Iowa Darters of any site sampled. Topeka Shiner fin clips were obtained from 6 oxbows during sampling of restored oxbows with USFWS in May. Two additional sites were sampled. Both were restored oxbows. The oxbow on Elk Creek was on a property containing 3 other oxbows. Topeka Shiners and Plains Topminnows

were found here during sampling of the stream in 2016 and when USFWS sampled it after being restored in 2017, as well as during sampling for this study. The other site was a restored oxbow on Mound Creek within Blue Mounds state park that was sampled in 2016. Topeka Shiners were present both years. An additional site was sampled in the Beaver Creek HUC 10 which is part of the Big Sioux drainage. Because Topeka Shiners were so abundant in this stream genetic samples were taken to compare to other drainages. Topeka Shiners were very abundant with 732 being captured with one seine pass.

To be accomplished:

This sub-objective has been fully accomplished.

b. Genetic analysis of Topeka Shiners and Plains Topminnows through the use of microsatellite markers. Additional samples will be collected by partners on this application and analyzed under this application. Methodology: This study will use a total of 13 polymorphic loci for Topeka Shiners. Eight polymorphic microsatellite loci were developed for the Topeka Shiner (Anderson and Sarver 2008) and five other loci were developed for other cyprinids and were shown to be polymorphic for and amplify Topeka Shiners (Bessert and Orti 2003; Burridge and Gold 2003; Turner et al. 2004; Blank et al. 2011). Genomic DNA will be extracted from Topeka Shiner fin samples using the Qiagen DNeasy Blood and Tissue Kit. Polymerase chain reaction (PCR) amplification of the microsatellite loci will be performed using 10ul reactions. Approximately 2 ng of genomic DNA will be used as the template for the reaction. Microsatellite forward primers will be modified with fluorescently labeled M13 (-21) attached to their 5’ ends (Schuelke 2000). The PCR reactions will then be carried out in an Eppendorf Master Cycler thermal cycler. PCR products will be visualized on 1% agarose gels. The genotyping and allele size will be determined using capillary electrophoresis at the Iowa State DNA Facility. The raw data will be evaluated and edited using the software GeneMarker version 1.95 (SoftGenetics).

The microsatellite genotypes will be checked for null alleles using the software MICROCHECKER (van Oosterhout et al. 2004). Allelic richness, which is the mean number of alleles per locus, corrected for sample size and expected heterozygosity calculated by HP-RARE will be used to summarize genetic diversity of the population sample (Kalinowski 2005). The allele frequencies at each locus for every population will be tested for conformity to Hardy Weinberg equilibrium and also linkage disequilibrium among all combinations of loci using GENEPOP version 3.4 (Raymond and Rousset 1995). Rarefaction will be used in the case of unequal samples sizes across populations. Allelic richness and expected heterozygosity will be calculated and compared for each basin.

Population structure across the range of the study sites will be assessed using Bayesian genotype assignment analyses. There will be a combination of non-spatial (STRUCTURE software: Pritchard et al. 2000; Falush et al. 2003) and also spatial (TESS software: Chen et al. 2007; Durand et al. 2009) models. Bayesian clustering techniques will assign q individuals to k populations. I will use the program BIMR 1.0 (Faubert and Gaggioti 2008) to estimate recent rates of movement and allow for asymmetrical rates between the groups identified in the assignment analyses, which will determine how far Topeka Shiners are migrating. The Bayesian assignment procedure of Rannala and Mountain (1997), as implemented in GENCLASS 2 (Piry et al. 2004) will be used to determine if populations sampled for this study contain individuals that represent first generation migrants from un-sampled populations.

Estimation of effective population size (Ne) for each population will be calculated based on a method using a single temporal population sample based on gametic disequilibrium and assumption of selective neutrality of unlinked markers using the program LDNE (Waples and Do 2008). We will use the program BIMR 1.0 (Faubert and Gaggioti 2008) to estimate recent rates of movement and allow for asymmetrical rates between oxbow and stream sites. The estimation of both methods will be

compared to determine which sites are contributing to the stream populations (sources) and ones that are not (sinks).

Accomplished to date:

• DNA of 837 Topeka Shiners has been extracted and quantified • Started PCR of microsatellite loci of Topeka Shiner DNA samples • DNA of 87 Plains Topminnows are being extracted and quantified

To be accomplished:

• PCR of microsatellite loci of Topeka Shiner DNA samples will continue into spring • PCR of Plains Topminnow microsatellites will be conducted • Allelic richness will be used to summarize genetic diversity of populations and will be calculated

and compared for each basin • The number of genetic populations of Topeka Shiners in each basin will be determined using

Bayesian genotype assignment analyses • Recent rates of movement will be estimated between the groups identified in the assignment

analyses • Effective population size and migration of oxbows will be to determine which oxbows are acting

as sources or sinks c. Collect habitat variables at each sampling location.

Methodology: Habitat and water chemistry was assessed at each site. Water chemistry measurements were taken before any other sampling to prevent changes to stream conditions. Measurements of temperature, dissolved oxygen, conductivity, and pH were taken using a model 556 MPS YSI meter and turbidity will be measured using a Hach 2100Q Portable Turbidometer. Habitat sampling occurred after both water chemistry and fish sampling to prevent disturbances. Habitat was measured in stream sites using the Iowa Department of Natural Resources’ Biological Sampling and Physical Habitat Assessment Standard Operating Procedure (IDNR 2015). Stream sites consist of ten evenly spaced transects and eighteen mini transects (33% and 67% of the distance between each transect; Figure 9). Since oxbows are generally homogeneous in habitat, they were broken up into three transects at 25%, 50%, and 75% of the site. Wetted width was recorded at each transect. Substrate and water velocity (in streams) was characterized at 10%, 30%, 50%, 70% and 90% of the wetted width (Figure 10). Canopy cover was estimated at left bank, right bank, and in the center of each transect using a spherical densitometer. Right and left bank angles was also recorded at each transect. Instream cover metrics (filamentous algae, macrophytes, woody debris >0.3m diam., small brush <0.3m diam., trees/roots, over-hanging banks, under-cut banks, boulders, artificial structure, depth/pool) will be estimated by a five level categorical classification (0=absent; 1=sparse (<10%); 2=moderate (10-40%); 3=heavy (40-75%); 4=very heavy (>75%)). Riparian estimates including canopy, understory, groundcover, and human influence was recorded at transect 1, 5, and 10 in streams and transect 2 in oxbows. Macrohabitat type (riffle, run, pool) and thalweg depth was recorded at each of the mini transects as well as each transect. Accomplished to date:

• Habitat metrics including: wetted width, substrate, bank angle, canopy cover, riparian

characteristics, and human impact, temperature, dissolved oxygen, conductivity, pH and turbidity were measured at every site during the 2016- 2017 field seasons

To be accomplished:

• Topeka Shiner presence, abundance and genetic data will be correlated to habitat metrics

Products Three short popular-type articles were published in 2017: Zambory, C., A. Bybel, and N. Simpson. 2017. A multifaceted approach to Topeka Shiner research in Iowa. Getting

Into Soil And Water 2017, Iowa Water Center and Soil & Water Conservation Club, Iowa State University. Simpson, N. 2017. Working with an endangered Iowa fish. Boone River Watershed Newsletter. Simpson, N., Zambory, C., and A. Bybel. 2017. A team effort in Topeka Shiner research. Fishers & Farmers

Partnership Newsletter.

References Anderson, C. M. and Sarver, S. K. 2008. Development of polymorphic microsatellite loci for the endangered Topeka Shiner, Notropis topeka. Molecular Ecology. 8, 311–313 Bakevich, B. D. 2012. Status, distribution, and habitat associations of Topeka Shiners in West-Central Iowa. M.S. Thesis, Iowa State University, Ames. Bakevich, B.D., Pierce, C.L., Quist, M.C. 2013 Habitat, Fish Species, and Fish Assemblage Associations of the Topeka Shiner in West-Central Iowa. North American Journal of Fisheries Management, 33:6, 1258-1268. Bakevich, B. D., Pierce, C.L, Quist, M.C. 2015. Status of the Topeka Shiner in West-Central Iowa. The American Midland Naturalist. 174(2): 350-358. Bessert, M. L. and Orti G. 2003. Microsatellite loci for paternity analysis in the Fathead Minnow, Pimephales promelas (Teleostei : Cyprinidae) Microsatellite loci for paternity analysis in the Fathead Minnow , Pimephales promelas ( Teleostei : Cyprinidae ). Blank, M, B. Bramblett, S. Kalinowski, J. Cahoon, K. Nixon. 2011. Impacts of Barriers on Topeka Shiner Populations. Report SD2006-07-F to South Dakota Department of Transportation, Office of Research. Blausey, CM. 2001. The status and distribution of the Topeka Shiner Notropis Topeka in eastern South Dakota. Ph.D. Dissertation. South Dakota State University, Brookings, SD. Bogue, A. G. 1994. From prairie to cornbelt: farming on the Illinois and Iowa prairies in the nineteenth century. Iowa State University Press, Ames. 309 p. Burridge C.P. and J.R. Gold. 2003. Conservation genetic studies of the endangered Cape Fear Shiner Notropis mekistocholas (Teleostei: Cyprinidae). Conservation Genetics 4:219−225. Durand E., F. Jay, O.E. Gaggiotti, and O. Francois. 2009. Spatial inference of admixture proportions and secondary contact zones. Molecular Biology and Evolution, 26: 1963–1973. Ceas, P. A. and K. A. Larson. 2010. Topeka Shiner monitoring in Minnesota: year seven. Final report submitted to the Division of Ecological Resources, Minnesota Department of Natural Resources, St. Paul, Minnesota. Chen, C, E Durand, F Forbes, and O Francois. 2007. Bayesian clustering algorithms ascertaining spatial population structure: a new computer program and a comparison study. Molecular Ecology Notes. 7: 747-756. Clark, S. J. 2000. Relationship of Topeka Shiner distribution to geographic features of the Des Moines Lobe in Iowa. Master’s Thesis, Iowa State University, Ames, Iowa. Dahl, SP. 2001. Studies of Topeka Shiner life history and distribution in Minnesota. M.S. Thesis, University of Minnesota. Minneapolis, MN. Hatch, J.T. 2001. What we Known about Minnesota’s First Endangered Fish Species: the Topeka Shiner. Journal of Minnesota Academy of Science 65: 31-38. Iowa Department of Natural Resources. 2015. Securing a future for fish and wildlife: a conservation legacy for Iowans. The Iowa Wildlife Action Plan. Third Edition. Faubet, P. and Gaggiotti, O. E. 2008. A new Bayesian method to identify the environmental factors that influence recent migration. Genetics 178, 1491–1504. Fischer, J. R., and C. P. Paukert. 2008. Historical and current environmental influences on an endemic Great Plains fish. The American Midland Naturalist. 159:364-377.

IAGFA (Iowa Aquatic Gap Fish Atlas). 2005. Iowa Aquatic Gap Fish Atlas, Iowa Rivers Information System. (http://maps.gis.iastate.edu/iris/fishatlas/), accessed February 2013.

Kalinowski, S.T. 2005. HP-RARE 1.0: a computer program for performing rarefaction on measures of allelic richness. Molecular Ecology Notes 5:187-189. Kenny, A. 2013. The Topeka Shiner: Shining a Spotlight on an Iowa Success Story. Endangered Species Program News Bulletin. Lee, D. S., C. R. Gilbert, C. H. Hocutt, R. E. Jenkins, D. E. McAllister, and J. R. Stauffer. 1980. Atlas of North American freshwater fishes. North Carolina Museum of Natural History, Raleigh. Loan-Wilsey, A. K., Pierce, C. L., Kane, K. L., Brown, P. D., & McNeely, R. L. (2005). The Iowa aquatic gap analysis project: Final report. Iowa Cooperative Fish and Wildlife Research Unit, Iowa State University, Ames, IA. http://lib.dr.iastate.edu/cfwru_reports/6/ (10-2016). Minckley, WL, and FB Cross. 1959. Distribution, habitat, and abundance of the Topeka shiner (Notropis topeka) in Kansas. American Midland Naturalist. 61: 210-217. Minnesota Department of Natural Resources. 2006. Tomorrow’s habitat for the wild and rare: an action plan for Minnesota Wildlife. Comprehensive Wildlife Conservation Strategy. Division of Ecological Services, Minnesota Department of Natural Resources, St. Paul. (http://files.dnr.state.mn.us/assistance/nrplanning/bigpicture/cwcs/tomorrows_habitat.pdf) Accessed February 2013. Minnesota Department of Natural Resources. 2013. Species profile: plains topminnow Fundulus sciadicus Cope, 1865. (http://www.dnr.state.mn.us/rsg/plains_topminnow/index.html) Accessed February 2013. Minnesota Department of Natural Resources. 2015. Watershed health assessment framework. (http://www.dnr.state.mn.us/whaf/index.html) Last accessed December 2017. Minnesota Department of Natural Resources. 2016. Ecological Classification System. Available: http://www.dnr.state.mn.us/ecs/index.html (accessed 12-206). Pasbrig, C. A., K. D. Koupal, S. Schainost, and W. W. Hoback. 2012. Changes in range-wide distribution of Plains Topminnow Fundulus sciadicus. Endangered Species Research 16:235-247. Piry, S., A. Alapetite, J.-M. Cornuet, D. Paetkau, L. Baudouin, and A. Estroup. 2004. GENECLASS2: software for genetic assignment and first-generation migrant detection. Journal of Heredity 95(6):536-539. Pritchard J.K., Stephens M., Donnelly P. 2000. Inference of population structure using multilocus genotype data. Genetics, 155, 945–959. Rahel, FJ and LA Thel. 2004. Plains Topminnow (Fundulus sciadicus): A technical conservation assessment. USDA Forest Service, Rocky Mountain Region. http://www.fs.fed.us/r2/projects/scp/assessments/plainstopminnow.pdf Rannala, B., and J. L. Mountain. 1997. Detecting immigration by using multilocus genotypes. Proceedings of the National Academy of Science 94(17):9197-9201 Raymond, M., and F. Rousset, 1995 GENEPOP (version 1.2): a population genetic software for exact tests and ecumenicism. Journal of Heredity 86: 248–249. Russell, G.D., Hawkins, C.P., O’Neill, M.P. 1997. The Role of GIS in Selecting Sites for Riparian Restoration Based on Hydrology and Land Use. Restoration Ecology. Vol. 5 No. 4S, pp. 56-68.

Schuelke M 2000. An economic method for the fluorescent labeling of PCR fragments: a poor man’s approach to genotyping for research and high-throughput diagnostics. Nature Biotechnology, 18, 233–234. Smith, D. D. 1981. Iowa prairie – an endangered ecosystem. Proc. Iowa Acad. Sci. 88:7-10. Turner, T. F., Dowling, T. E., Broughton, R. E. Gold, J. R. 2004. Variable microsatellite markers amplify across divergent lineages of cyprinid fishes (subfamily Leuciscinae). Conserv Genet 5 : 279-281. 279–281 Tabor, V.M. 1997. Endangered and threatened wildlife and plants: final rule to list the Topeka Shiner as endangered. Ibid. 63(240):69008-69021. Thomson, S. K., and C. R. Berry. 2009. Stream fishes inhabit livestock watering ponds (dugouts) near Six Mile Creek, Brookings County, South Dakota. Proceedings of the South Dakota Academy of Science. 88:127-138. Thomson, S. 2010. Dugouts and Stream Fishes, Especially the Endangered Topeka Shiner. Fish Insight 91. USFWS (U.S. Fish and Wildlife Service). 2009. Topeka Shiner 5-Year Review: Summary and Evaluation. Kansas Ecological Services Field Office, Manhattan, Kansas. Waples, R. S. and C. Do. 2008. LDNE: a program for estimating effective population size from data on linkage disequilibrium. Molecular Ecology Resources, 8: 753-756. Waters, TF. 1977. The streams and rivers of Minnesota. University of Minnesota Press. Minneapolis, MN.

Table 1. Topeka Shiner presence/absence source data Source Presence Absence

Loan-Wilsey et al. 2005

Cleary, R.E. 1953. An annotated check-list of fishes of the Cedar-Iowa River drainage basin in Iowa. Proceedings of the Iowa Academy of Sciences 60: 626-635.

X

Harrison, H. 1952. Fish populations of Boone County for 1946 through 1951. Iowa Conservation Commission Quarterly Biology Reports 4(1): 41-49.

X

Howell, D. 2003. NAI database. Iowa Department of Natural Resources, Des Moines, Iowa.

X

Iowa State University Museum. 1985. Collection of fishes catalog, 1878-1985. Iowa State University, Ames, Iowa.

X

Kaminski, M.T. 1996. Smallmouth bass habitat and fish community relationships in central Iowa streams. Master’s thesis. Iowa State University, Ames, Iowa.

X

Meek, S.E. 1892. Report upon the fishes of Iowa, based upon observations and collections made during 1889, 1890, 1891. Bulletin of the United States Fish Commission 10(1890):217-248.

X

Meek, S.E. 1894. Notes on the fishes of Western Iowa and Eastern Nebraska. Bulletin of the United States Fish Commission 14(1894):133-138.

X

Menzel, B.W. 1984. Field notes: Des Moines-Skunk. Iowa State University, Ames, Iowa

X X

Menzel, B.W. 1997. Field notes: Topeka shiner survey. Iowa State University, Ames, Iowa.

X X

Menzel, B.W. 1998. Field notes: Topeka shiner survey. Iowa State University, Ames, Iowa.

X X

Menzel, B.W. 1999. Field notes: Topeka shiner survey, 1999 in-channel collections. Iowa State University, Ames, Iowa.

X X

Menzel, B.W. 2000. Field notes: Topeka shiner survey, 2000 in-channel collections. Iowa State University, Ames, Iowa.

X X

Museum of Zoology. 2002. Division of Fishes collection database. University of Michigan, Ann Arbor, Michigan. http://www.ummz.lsa.umich.edu/. (May, 2002)

X

Nickum, J.G. and J.A. Sinning. 1971. Fishes of the Big Sioux River. Proceedings of the South Dakota Academy of Science, 50: 143-154.

X

Olson, C.L.. 1975. Effects of chlorinated sewage effluent on fish in the Iowa River, Marshalltown, Iowa. Master’s thesis. Iowa State University, Ames, Iowa.

X

Olson, J.R. 1998. Historic fish survey database. Water Quality Bureau, Iowa Department of Natural Resources, Des Moines, Iowa.

X

Paragamian, V.L. 1990. Fish populations of Iowa rivers and streams. Technical Bulletin No. 3, Iowa Department of Natural Resources, Des Moines, Iowa.

X

Minnesota Department of Natural Resources Natural Heritage Information System

Cunningham, George R. (2015) X X

Dodd, Hope R. (2011) X

Nagle, Brett (2013-2014) X X

Schmidt, Konrad P. (2013-2014) X

Iowa State 2016-2017

Simpson, N. (2016) X X

Simpson, N. (2017) X X

Bybel, A. (2016) X X

Bybel, A. (2017) X X

USFWS Uttrup, N. and Emerson, K. (2015-2017) X X

Table 2. Topeka Shiner status designation for HUC10s sampled in the Boone and North Raccoon Watersheds in 2016-2017 based on previous collections.

Topeka Shiners Collected

HUC10 HUC8 Historic 1997-2000 2010-2011 2016-2017 Status

Eagle Creek Boone Yes Yes Yes Yes Stable

Headwaters Boone River Boone Yes No No Yes Possibly Recovering

Lower Boone River Boone Yes Yes No No At Risk

Middle Boone River Boone Yes Yes No Yes Possibly Stable

Otter Creek Boone Yes No No Yes Possibly Recovering

Prairie Creek Boone Yes Yes No Yes Possibly Stable

White Fox Creek Boone Yes No No No Possibly Extirpated

Prairie Creek-Cedar Creek North Raccoon Yes No No No Possibly Extirpated

Headwaters North Raccoon North Raccoon Yes No No No Possibly Extirpated

Camp Creek North Raccoon Yes Yes No No At Risk

Lake Creek North Raccoon Yes Yes No Yes Possibly Stable

Purgatory Creek North Raccoon Yes Yes Yes Yes Stable Elk Run-North Raccoon River North Raccoon Yes Yes No No At Risk Welshs Slough-Cedar Creek North Raccoon Yes Yes Yes Yes Stable East Buttrick Creek North Raccoon Yes Yes Yes Yes Stable Buttrick Creek North Raccoon Yes Yes Yes Yes Stable

Table 3. Summary statistics for watershed classification and regression trees.

Table 4: A summary table of data used, processing methodology, and deviations of Iowa calculations from Minnesota WHAF methodology.

Index Metric Scale Data Used Process Deviations from MN Hydrology

HUC 8 HUC 12

Perennial Cover X X

▪ 2011 National Land Cover Dataset

▪ Waterbody Shapefile (NRGIS 2007)

The dataset was reclassified so forest, shrub, grassland, pasture, and woody wetlands were considered “perennial” vegetation. The of land area within HUC8 and HUC12 watershed boundaries that was classified as perennial was divided by the total watershed area excluding areas of open water, which were defined by the nrgis waterbodies shapefile. Perennial cover percentages were used in the index, but linear scoring was applied for visual comparison of watershed health

Only the 2015 National Land Cover Dataset was used. Previous years were not included

Impervious Cover X X

▪ 2011 National Land Cover Dataset Impervious Surface Raster

▪ Waterbody Shapefile (NRGIS 2007)

The Multi Resolution Land Characteristics Consortium data that represents imperviousness as a percentage was obtained and masked with the NRGIS Iowa waterbodies dataset to exclude large areas of water that may skew scoring. Average percentages of imperviousness were calculated according to HUC8 and HUC12 boundaries. A threshold value of 4% or more impervious surfaces was applied to represent a score of zero. The remaining scores were linearly scaled from 0 to 100 with a score of 100 representing areas of least impervious surface percentage.

None.

Water Withdrawal X X

▪ Water use surface intakes dataset (GIS shapefile)

▪ Ground water wells use (GIS shapefile)

▪ Groundwater and surface water uptake permits (IDNR Water Supply Engineering Section)

Permitted water withdrawal from both surface and groundwater sources were summed in the HUC8 and HUC12 watershed boundaries. Total permitted water consumption was then linearly scaled for watersheds to provide relative potential water withdrawal threat.

The Minnesota WHAF takes into account the use of water in a catchment and its upstream catchments as a perfect of the surface water runoff, and then values are adjusted for consumptive use. Because these calculations involve a detailed understanding of predicting annual runoff coefficients, watersheds were scored according to permitted water withdrawal. Because sites will use much less water than they are permitted to withdraw, this score will predict relative potential risk for Iowa.

Loss of Hydrologic Storage

Altered Watercourses X X ▪ Stream Centerline ▪ Channelized Streams 2011

(NRGIS)

Length of channelized streams and stream centerlines were calculated for the HUC12 and HUC12 levels. The ratio of channelized streams to total stream length were calculated, and the ratios were rescaled to range from 0 to 100 and then applied at the watershed level for scores.

Minnesota WHAF used a statewide assessment of its watercourses to determine whether they were national, impounded, or non-definable. Methodology included using GIS software including LiDAR and aerial imagery to visually assess each channel. This process was determined to be

too labor intensive, and so the altered stream channel/total stream channel length was determined to be a proxy. Another methodology considered was utilizing a LiDAR derived stream centerline shapefile with calculated stream sinuosity and then reclassifying any stream with a sinuosity below 1.23 as channelized or altered (Rosgen 1994).

Wetland Loss X ▪ SURRGO Soils Database ▪ National Wetland Inventory

of Iowa (2002)

To determine the extent of wetland storage loss, the current area of wetlands as defined by the national wetland inventory of Iowa was compared with a proxy for historical wetland storage (SURRGO “hydric” soil class). Current wetland extent is subtracted by historical area within the HUC8 and HUC12 watershed boundaries, and then divided by total watershed area. Ratios of wetland loss are then linearly scored with a score of 100 being zero loss of wetland storage, and a score of 0 being total storage loss.

None.

Flow Variability

Using USGS mean daily discharge values for the past 30 year record, stream level of alteration will be examined in Iowa using the Indicators of Hydrologic Alteration software. Scoring methodology has yet to be decided.

The Minnesota WHAF estimated 33 variables with the IHA using mean daily discharge for a 30-year record between 1986 and 2007. Area of drainage was calculated for the areas above year gage, and precipitation time series were obtained from the National Oceanic and Atmospheric Administration (NOAA). A fixed-effects model and scoring was used to account for differing drainage area and precipitation between years and gages. Variables were scored with a coefficient derived from accounting for varying area and precipitation, and then variables were summed, divided by the maximum score, and then averaged to yield the final score.

Index Metric Scale Data Used Process Deviations from MN Biology

Terrestrial Habitat Quality

Stream Species Quality

Fish IBI X X ▪ BioNet Access Database (IDNR)

Fish quality scores were calculated for both HUC 12 and HUC 8 watersheds. FIBI and

MBIBI scores were obtained from Jamie Mootz, a water data analyst of the IDNR. Data was

delivered in the form of an Access Database. FIBI scores were queried for the Site_ID, the HUC12, the Latitude and Longitude, the FIBI

score, the FIBI class, the FIBI type, and the last date of sample. Only scores that were taken in

warm water streams were used, and if a site was sampled multiple times, the most current

sampling date was used. Dates of scores ranged from August 10, 1994 to June, 20 2016. Points were transformed to UTM projection, and then

spatially joined with HUC_8 watershed boundaries. FIBI scores were averaged and

summarized by HUC_8 and HUC_12 watersheds and applied to the projections.

FIBI scores for warm water streams were used as reported for Iowa as scores were already standardized across the state. No

rescaling of scores were deemed necessary.

Invertebrate IBI X X ▪ BioNet Access Database (IDNR)

Invertebrate quality scores were calculated for both HUC12 and HUC 8 watersheds. FIBI and

MBIBI scores were obtained from Jamie Mootz, a water data analyst of the IDNR. Data was

delivered in the form of an Access Database. BMIBI scores were queried for SiteID, last date of sample, BMIBI type, if it was a valid sample,

BMIBI score, BMIBI class, HUC12, Latitude and Longitude. Only scores that were taken in

warm water streams were used, and if a site was sampled multiple times, the most current

sampling date was used. Dates of scores ranged from August 10, 1994 to June 20, 2016. Points were transformed to UTM projection, and then

spatially joined with HUC_8 watershed boundaries. BMIBI scores were averaged and

summarized by HUC_8 and HUC_12 watersheds and applied to the projections.

BMIBI scores for warm water streams were used as reported for Iowa as scores

were already standardized across the state. No rescaling of scores were deemed

necessary.

Mussel Quality ▪ Mussel IBI from Jennifer Kurth Yet to be determined once data is obtained

Animal Species Richness X X

▪ BioNet Access Database (IDNR)

▪ Iowa Breeding Bird Atlas I (1985 to 1990) (NRGIS)

Species richness for fish and invertebrates were calculated from the BioNet access database

shared with me by Jamie Mootz from the Iowa DNR. Breeding bird richness for fish were

calculated from the Breeding Bird Atlas I (1985 to 1990). Two datasets were used for fish and

invertebrates: one from data collected as part of

Minnesota used the North American Breeding Bird Survey for species counts

from 1995 to 2008, but Iowa-specific breeding bird atlas was thought to provide

more intensive coverage of watersheds.

the ambient biological stream monitoring program, and one from DNR Fisheries

collections that used the ambient biological stream monitoring program. Data queried were

the site ID, the HUC12, the Latitude and Longitude, sample date, and the count of fish

species. Sample collections ranged from August 10, 1994 to June 20, 2016. If sites were

collected multiple times, only the most recent collections were used. Counts were averaged in HUC12 and HUC8 and the average number of

species per HUC8 were used in the species richness index. Number of species were

rescaled to have 0 be the fewest number of species and 100 as the greatest number of

species. Rescaled values were then applied to HUC8 and HUC12 watersheds and averaged according to their boundaries. The resulting scores were then used as the watershed final

score

At-Risk Animal Richness X X

▪ BioNet Access Database (IDNR)

▪ Iowa Breeding Bird Atlas I (1985 to 1990) (NRGIS)

Fish species of greatest conservation counts were tallied for each HUC 8 and HUC 12

watershed from collection events from 2005-2015 for fish and between 1985 to 1990 for

birds. Lists of species of special conservation need were obtained from IDNR Iowa Wildlife

Action Plan. Number of observed species richness were linearly scored and applied as

species richness final scores.

None.

Index Metric Scale Data Used Process Deviations from MN Connectivity

Terrestrial Habitat

Connectivity

Aquatic Connectivity X X

▪ Inventory of Dams in the State of Iowa (NRGIS, 2013)

▪ Stream_Centerlines (2016) ▪ Road Centerlines of Iowa,

2006, from DOT County-wide GIMS files (NRGIS)

Stream and Road Crossing intersections were created and used as a proxy for bridge and culvert locations using the centerline and Iowa Road data. Stream/Road Intersections and the Iowa Dam Inventory were merged together. The number of dams, culvert, and bridge points were dissolved into a single attribute point dataset, and then points were tallied for each HUC_8 and HUC_12 watershed within Iowa. Centerline data was dissolved by HUC_8 and HUC_12 watershed boundaries, and then length in kilometers was calculated for each watershed. The density of points (representing bridge, culvert, and dams) per length of stream within the watershed was calculated. Per Minnesota’s methodology, a threshold of the 95% percentile was assigned a score of 0, and then remaining scores were scored from 0 to 100.

Minnesota data input was a dams and culverts dataset, while Iowa data inputs were Iowa Dams dataset obtained from the DNR as well as stream and road intersections that were used as a proxy for culverts or bridges.

Riparian Connectivity X X

▪ 200m buffer of Stream_Centerlines (2016)

▪ National Land Cover dataset 2011

A 200m buffer was generated around the Iowa Centerline data to represent the riparian zone. The National Land Cover Dataset for 2015 was masked by the riparian zone buffer and zonal statistics were calculated for HUC8 and HUC12 levels to determine the percentage of agricultural and developed land area that was present within the riparian zone. Land classes that were reclassified as “agricultural and developed land” were: developed open space, developed low intensity, developed medium intensity, developed high intensity, hay/pasture, and cultivated crops. Percentage of land covered by agricultural or developed land were calculated and linearly scored. Zones with the lowest percentages of developed or agricultural land were scored as 100 and zones with the highest percentages were scored with a 0

Minnesota used floodplain coverage in its calculations. Because Iowa’s Floodplain mapping project is not yet completed, it was excluded from this first analysis, but will be implemented when it is completed statewide.

Index Metric Scale Data Used Process Deviations from MN Geomorphology

Soil Erosion Potential X X

• SURRGO Soils Database • 3M Digital Elevation Model • Waterbody Shapefile

(NRGIS 2007)

Extract by mask the 3M DEM with the Iowa Border and calculated the slope for the DEM by percent rise. Values were reclassified so that slopes from 0-1 were classified as a 1, slopes 1-2 were classified as 2, slopes 3-4 were classified as 3, and any percent slope value above 4 were classified as 4. SURRGO data was obtained and converted into a raster dataset with the same cell size as the newly reclassified slope percent layer. Lakes and major impoundments were erased from the layer to remove biased weighting from water values. Kf values for the SURRGO were used and multiplied by the reclassified slope percent layer to yield the erodibility index. Erodibility indices were then averaged by HUC8 and HUC12 and then those average erodibility scores were rescaled from 0 to 100 and applied to the HUC8 and HUC12 watersheds.

A 3M DEM rather than a 10M DEM for the state of Iowa was used to represent a fine-scale DEM while also accommodating a reasonable processing time for a large dataset. SURRGO was used for the entire state of Iowa.

Groundwater Contamination Susceptibility

X X • Ground water vulnerability regions (NRGIS)

A model depicting the level of threat of groundwater contamination will be modified from the ground water vulnerability region shapefile and level of contamination threat will be scored at the HUC8 and HUC12 levels.

The Minnesota WHAF used a Groundwater Contamination Susceptibility model developed by the Minnesota pollution control agency. No such model was available for Iowa, and so a model will be developed based on available data.

Climate Vulnerability X • High Plains Regional

Climate Center

Annual precipitation and evapotranspiration values will be obtained from monitoring stations in Iowa for at least 20 years of collection. Precipitation minus evapotranspiration will be used to score the stability of an area. Deviations from a steady state of precipitation in areas will result in lower scoring than balanced areas.

Precipitation and evapotranspiration values were used from 1961-1990 collections. Deviations from a steady state were scored by magnitude of deviation.

Index Metric Scale Data Used Process Deviations from MN Water Quality

Localized Pollution Sources

Animal Units X X ▪ Animal Feeding Operations (NRGIS)

Spatially join Animal Feeding Operations dataset with the HUC8 and HUC12 watershed shapefiles. Create a summary table of the HUC8 and HUC12 of the sum of animal units. Animal unit density per acres of watershed was calculated. A threshold of 95% was found and assigned a score of 0 (worst) and the remaining values were linearly scored with the greatest densities having a value of 0 and watersheds with the lowest density would have a score of 100 (best).

None

Potential Contaminants

▪ Air emission points title V ▪ LUST sites (NRGIS) ▪ Solid_waste_permit_facilities

(NRGIS) ▪ UST_sites (NRGIS) ▪ Contaminated sites facilities

(NRGIS) ▪ Chemical storage facility tier

2 (NRGIS)

Total number of cumulated sites were calculated for each HUC8 and HUC12 watershed boundary and divided by watershed area. Densities were linearly scored with scores of 100 being watersheds with the lowest densities, and scores of 0 being watersheds with the highest densities.

Industrial and construction storm water permit sites were not included in this analysis.

Superfund Sites

• National Priority List (NRGIS)

• Non-National Priority List (NRGIS)

Density of listed superfund sites will be calculated at the HUC12 and HUC8 levels and linearly scored. Scores of 100 represent zero designated superfund sites while scores of 0 represent maximum density.

None

Wastewater Treatment Plants • Wastewater Treatment Plants

(NRGIS) 2016

Sums of wastewater treatment plant permitted outflows of nitrogen and carbonaceous biochemical oxygen demand (CBOD) were attributed to wastewater treatment plants. The total quantity of these two metrics were calculated per HUC8 and HUC12 level and then linearly scored. Scores of 100 were given to sites with the lowest amount of discharge while scores of 0 were given to the highest amount of discharge.

Due to lack of historical regulation of phosphorous discharge from wastewater treatment plants in Iowa, this metric was not included.

Open Pit Mines

Septic Systems ▪ all_wells (NRGIS)

The density of all wells within the watershed boundaries of HUC8 and HUC12 watersheds were calculated and linearly scored. Scores of 100 were attributed to the least dense watersheds and a score of zero was given to the densest watershed.

This dataset used all registered wells while the Minnesota WHAF used only domestic wells.

Non-Point Source Pollution

Non-Point Source Pollution

Phosphorous Risk from Uplands ▪ SURRGO Soils Database

(NRGIS) The NASS Crop Data Layer will be used as a base. Nutrient deliverance based on land use

None

▪ 3M Digital Elevation Model (NRGIS)

▪ NASS Crop Data Layer

type have been calculated and the NASS Crop Data layer will be used as a base for this data. Nutrient coefficients will be multiplied by the soil erodibility factor plus the slope rescaled from 0 to 15%. The average of the grid values was scored for each watershed at the HUC8 and HUC12 level. Scores of 100 represented the lowest average cell value while scores of 0 represent the highest.

Assessments

• 2012 Impaired Lakes (NRGIS)

• 2012 Impaired Streams (NRGIS)

A combined shapefile of 2012 Impaired Lakes and Streams were used to discover the percentage of assessed sites that were considered impaired. Inconclusive sites were not considered. Percentages were linearly scored from 0 to 100. A score of 100 was all sites assessed met water quality standards, and a score of 0 meant that all sites assessed were considered impaired.

The Minnesota WHAF used the percentage of assessments from unpublished 2014 Impaired List to score watersheds.

Table 5. Total number of fish by species sampled in oxbows and streams of the North Raccoon River drainage in 2016-2017. Species in bold are SGCNs.

2016 2017 Species Stream Oxbow Stream Oxbow Bigmouth Shiner (Ictiobus cyprinellus) 585 7 44 1 Black Bullhead (Ameiurus melas) 1 13085 6 1386 Black Crappie (Pomoxis nigromaculatus)

2

1

Blacknose Dace (Rhinichthys atratulus) 76

136 Blackside Darter (Percina maculata) 45 2 16 Bluegill (Lepomis macrochirus) 4 770 5 340

Bluntnose Minnow (Pimephales notatus) 1861 159 594 19 Brassy Minnow (Hybognathus hakinsoni) 64 496 3 128 Brook Stickleback (Culaea inconstans) 5 433 5 14 Central Stoneroller (Campostoma anomalum) 196

548 1

Channel Catfish (Ictalurus punctatus) 29

8 Common Carp (Cyprinus carpio) 18 402 2 1602

Common Shiner (Luxilus cornutus) 572 961 372 227 Creek Chub (Semotilus atromaculatus) 624 89 608 51 Fantail Darter (Etheostoma flabellare)

20

Fathead Minnow (Pimephales promelas) 31 4592 29 889 Flathead Catfish (Pylodictis olivaris) 247

Gizzard Shad (Dorosoma cepedianum) 1 3728 3 83 Golden Redhorse (Moxostoma erythrurum) 15 3 26

Green Sunfish (Lepomis cyanellus) 193 6794 81 2006 Highfin Carpsucker (Carpiodes velifer) 380

5

Iowa Darter (Etheostoma exile) 17 Johnny Darter (Etheostoma nigrum)

40 184 3

Largemouth Bass (Micropterus salmoides)

1661 3 66 Bigmouth Buffalo (Ictiobus cyprinellus) 418 3

Northern Hogsucker (Hypentelium nigricans) 16

63 Northern Pike (Esox lucius) 3

Orangespotted Sunfish (Lepomis humilis) 34 5997 8 505 Plains Topminnow (Fundulus sciadicus)

Quillback Carpsucker (Carpiodes cyprinus)

7 44 1 Red Shiner (Cyprinella lutrensis) 180

River Carpsucker (Carpiodes carpio)

1 Sand Shiner (Notropis stramineus) 20 224 1714 6

Shorthead Redhorse (Moxostoma macrolepidotum)

81 Shortnose Gar (Lepisosteus platostomus) 4

Slender Madtom (Noturus exilis)

1 4 Slenderhead Darter (Percina phoxocephala) 3465

Smallmouth Bass (Micropterus dolomieu) 102 2 55 Smallmouth Buffalo (Ictiobus bubalus)

9

1

Southern Redbelly Dace (Chrosomus erythrogaster) Spotfin Shiner (Cyprinella spiloptera) 14 234 624 115

Stonecat (Noturus flavus) 21

7 Suckermouth Minnow (Phenacobius mirabilis)

25

Tadpole Madtom (Noturus gyrinus)

Topeka Shiner (Notropis topeka) 1088 142 2 63 Walleye (Sander vitreus) 23 7

White Crappie (Pomoxis annularis) 73 1097

76 White Sucker (Catostomus commersonii)

85 63 12

Yellow Bullhead (Ameiurus natalis) 39 67 11 8 Yellow Perch (Perca flavescens)

Golden Shiner (Notemigonus crysoleucas) Pumpkinseed (lepomis gibbosus) 27

3

Table 6. Total number of fish by species sampled in oxbows and streams of the Rock River drainage in 2016-2017. Species in bold are SGCNs.

2016 2017 Species Stream Oxbow Stream Oxbow Bigmouth Shiner (Ictiobus cyprinellus) 31

Black Bullhead (Ameiurus melas) 76 536 27 301 Black Crappie (Pomoxis nigromaculatus)

1

Blacknose Dace (Rhinichthys atratulus) 63

24 Blackside Darter (Percina maculata) 4

4

Bluegill (Lepomis macrochirus) 8 18 63 12 Bluntnose Minnow (Pimephales notatus) 701 4 8 22 Brassy Minnow (Hybognathus hakinsoni) 4 18

115

Brook Stickleback (Culaea inconstans) 109 209

36 Central Stoneroller (Campostoma anomalum) 232 27 55 189 Channel Catfish (Ictalurus punctatus)

Common Carp (Cyprinus carpio) 16 173

10 Common Shiner (Luxilus cornutus) 1581 36 21 24 Creek Chub (Semotilus atromaculatus) 829 69 163 135 Fantail Darter (Etheostoma flabellare)

Fathead Minnow (Pimephales promelas) 4139 1227 2 393 Flathead Catfish (Pylodictis olivaris)

Gizzard Shad (Dorosoma cepedianum) 20

6 Golden Redhorse (Moxostoma erythrurum)

Green Sunfish (Lepomis cyanellus) 202 193 26 69 Highfin Carpsucker (Carpiodes velifer)

Iowa Darter (Etheostoma exile) 8 2

21 Johnny Darter (Etheostoma nigrum) 88

64 2

Largemouth Bass (Micropterus salmoides) 4 80 1 4 Bigmouth Buffalo (Ictiobus cyprinellus)

3

1

Northern Hogsucker (Hypentelium nigricans) 9 Northern Pike (Esox lucius) 5 Orangespotted Sunfish (Lepomis humilis) 102 839 5 59

Plains Topminnow (Fundulus sciadicus) 128 8 27 Quillback Carpsucker (Carpiodes cyprinus) 1

11

Red Shiner (Cyprinella lutrensis) 175 251 32 37 River Carpsucker (Carpiodes carpio)

1

Sand Shiner (Notropis stramineus) 607 2 620 Shorthead Redhorse (Moxostoma macrolepidotum)

7

Shortnose Gar (Lepisosteus platostomus)

6 Slender Madtom (Noturus exilis)

Slenderhead Darter (Percina phoxocephala) Smallmouth Bass (Micropterus dolomieu) 1

7

Smallmouth Buffalo (Ictiobus bubalus) Southern Redbelly Dace (Chrosomus erythrogaster) 2

Spotfin Shiner (Cyprinella spiloptera) Stonecat (Noturus flavus) 10

Suckermouth Minnow (Phenacobius mirabilis)

Tadpole Madtom (Noturus gyrinus) 9 Topeka Shiner (Notropis topeka) 163 183

1241

Walleye (Sander vitreus) White Crappie (Pomoxis annularis)

125

2 White Sucker (Catostomus commersonii) 869 57 187 168 Yellow Bullhead (Ameiurus natalis)

Yellow Perch (Perca flavescens)

2 Golden Shiner (Notemigonus crysoleucas)

83

58

Pumpkinseed (lepomis gibbosus)

Figure 1. Topeka Shiner HUC 10 Watershed Detection throughout time in the North Raccoon (bottom left in each panel) and Boone Watersheds (top right in each panel) a) historical distribution (1890-1996) b) data obtained 1997 to 2000 c) data obtained 2010-2011, and d) data obtained 2016-2017

Figure 2. Topeka Shiner HUC 10 watershed detection through time in the Rock River Watershed a) data from 1971-2002 b) data from 2011-2014 c) data obtained from 2015 to 2017.

Figure 3. Topeka Shiner HUC 10 Watershed Status in the North Raccoon and Boone Watersheds determined from historical distribution (1890-1996) distribution, and sampling from 1997 to 2000, 2010-2011, and 2016-2017.

Figure 4. Top Left: Filled DEM; Bottom Left: hydro-conditioned original DEM; Right: identified depressions outlined in white

Figure 5. Left; Target and Non-Target features identified using historical 1930 aerial imagery; Right; recent 2015 aerial imagery

Figure 6. Left: 1930s aerial imagery; middle: present day aerial imagery; right: candidate restoration sites that were identified and ranked using this methodology

Figure 7. Topeka Shiner sampling locations of this project between years 2016 and 2017 in the Boone River, North Raccoon River, Rock River, and Bear Creek watersheds.

Figure 8. Topeka Shiner presence and absence detections found during 2016 and 2017 in the Boone River, North Raccoon River, Rock River, and Bear Creek watersheds.

Figure 9. Habitat transects layout for oxbow (eft) and stream (right). Two mini transects are between each Transect on streams.

Figure 10. Measurement points for an individual transect.