Of 18 Value Is Anticipated

Home , Choptank River, Marshyhope Creek

Easygrants ID: 34809 National Fish and Wildlife Foundation NFWF/Legacy Grant Project ID: 0104.12.034809 Marine Keystone - River Herring Conservation - Fall 2012 - Submit Final Programmatic Report (Activities and Outcomes) Grantee Organization: Smithsonian Institution, Environmental Research Center Project Title: Imaging Sonar Run Counts of River Herring in Chesapeake Bay

Project Period 12/15/2012 - 01/31/2014 Award Amount $202,533.00 Matching Contributions $202,533.00 Project Location Description (from Proposal) We propose to work in two NFWF priority streams including Patuxent River (Middle Bay), Mattawoman Creek (Lower Potomac), Nanticoke River (Lower Eastern Shore), Choptank River (Upper Eastern Shore).

Project Summary (from Proposal) Develop imaging sonar tool for counting river herring in Chesapeake Bay. Project will establish scientifically rigorous run counts for alewife and blueback herring in spawning streams.

Summary of Accomplishments This report describes the accomplishments of Year 1 of a two-year evaluation of methods for conducting scientifically-rigorous run counts for river herring in Chesapeake Bay. From March to May 2013, we conducted Dual-frequency Imaging Sonar (DIDSON) run counts for alewife and blueback herring in the Choptank River (Upper Eastern Shore) and Marshyhope Creek (Lower Eastern Shore), two important spawning streams for river herring in Chesapeake Bay. We evaluated ichthyoplankton sampling (in cooperation with citizen scientists) and boat electrofishing as low-cost methods providing proxy indices of spawning run size. Of the methods tested, hourly DIDSON fish counts provided high quality data for assessing year-to-year variation in numbers of spawning fish, whereas proxy indices conducted at weekly intervals (ichthyoplankton sampling and electrofishing) had high variability that called into question their value for annual run size assessments. However, the results of genetic barcoding analyses indicated that citizen science ichthyoplankton sampling is an effective, relatively inexpensive method for determining the presence and timing of spawning runs.

Lessons Learned The major lessons learned during this project are: 1) DIDSON imaging sonar can be used to provide scientifically-rigorous run counts for river herring in Chesapeake Bay spawning streams. 2) Hourly sampling is likely needed for generating rigorous run counts. 3) Moving a single DIDSON unit back and forth between two streams once or twice each week is not feasible for producing high quality run counts. 4) Indices of run size generated from weekly sampling are useful for assessing the presence and timing of runs, but are not likely to provide rigorous data for evaluating year-to-year variability in run size. 5) Citizen science ichthyoplankton sampling combined with genetic barcoding was an effective way to document the presence of river herring in spawning streams.

Conservation Activities Volunteer participation Progress Measures Other (# volunteers participating in projects) Value at Grant Completion 20

Conservation Outcome(s) Monitoring Conservation Indicator Metric(s) Other (# monitoring programs established or underway) Baseline Metric Value 0 Metric Value at Grant Completion 2 Long-term Goal Metric Value 8 Year in which Long Term Metric 2016

Instructions: Save this document on your computer and complete the narrative in the format provided. The final narrative should not exceed ten (10) pages; do not delete the text provided below. Once complete, upload this document into the on-line final programmatic report task as instructed.

1. Summary of Accomplishments In four to five sentences, provide a brief summary of the project’s key accomplishments and outcomes that were observed or measured.

This report describes the accomplishments of Year 1 of a two-year evaluation of methods for conducting scientifically- rigorous run counts for river herring in Chesapeake Bay. From March to May 2013, we conducted Dual-frequency Imaging Sonar (DIDSON) run counts for alewife and blueback herring in the Choptank River (Upper Eastern Shore) and Marshyhope Creek (Lower Eastern Shore), two important spawning streams for river herring in Chesapeake Bay. We evaluated ichthyoplankton sampling (in cooperation with citizen scientists) and boat electrofishing as low-cost methods providing proxy indices of spawning run size. Of the methods tested, hourly DIDSON fish counts provided high quality data for assessing year-to-year variation in numbers of spawning fish, whereas proxy indices conducted at weekly intervals (ichthyoplankton sampling and electrofishing) had high variability that called into question their value for annual run size assessments. However, the results of genetic barcoding analyses indicated that citizen science ichthyoplankton sampling is an effective, relatively inexpensive method for determining the presence and timing of spawning runs.

2. Project Activities & Outcomes

Activities  Describe and quantify (using the approved metrics referenced in your grant agreement) the primary activities conducted during this grant.  Briefly explain discrepancies between the activities conducted during the grant and the activities agreed upon in your grant agreement.

Citizen science A total of 20 citizen scientists participated in our study during 2013, exceeding our proposed target of 14 citizen scientist participants. The majority of citizen scientists participated in collections of ichthyoplankton samples from Mattawoman Creek (7 citizen scientists from Mattawoman Watershed Society), Patuxent River (5 citizen scientists from Patuxent Research Refuge) , and Marshyhope Creek (3 citizen scientists from Nanticoke Watershed Alliance). Mattawoman Watershed Society has conducted a long-term citizen science study of ichthyoplankton abundance in cooperation with Maryland Department of Natural Resources and collected duplicate samples for our study. Other citizen scientist participation included two individuals who participated in backpack electrofishing in the Choptank River, one who conducted preliminary aging estimates using herring scales, and one who participated in the analysis of DIDSON video files and fish dissections.

Chesapeake Bay River Herring Workshop The first Chesapeake Bay river herring workshop was held at SERC on 11 January 2013 with 25 participants representing NFWF, SERC, Maryland Department of Natural Resources, District of Columbia Department of the Environment, Potomac River Fisheries Commission, George Mason University, and Mattawoman Watershed Society (Fig. 1). Participants discussed the status of river herring populations in the Chesapeake and current/planned research and monitoring efforts. A portion of the workshop was devoted to choosing sampling locations for our DIDSON, electrofishing, and ichthyoplankton sampling efforts. Mattawoman Creek Fig. 1. 2013 workshop (Lower Potomac River) and Marshyhope Creek (Lower Eastern Shore) were participants at SERC. initially chosen as the monitoring sites. These sites were selected because: 1) they The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the opinions or policies of the National Fish and Wildlife Foundation. Mention of trade names or commercial products does not constitute their endorsement by the National Fish and Wildlife Foundation. Page 3 of 18 were thought to have relatively strong herring runs necessary for testing DIDSON technology, 2) they had existing surveys that provided indices of run strength, 3) they were accessible from SERC (within 90 minutes driving time), and 4) they were the appropriate width (<15 m) for DIDSON sampling across the entire width of the stream.

Outcomes  Describe and quantify progress towards achieving the project outcomes described in your grant agreement. (Quantify using the approved metrics referenced in your grant agreement or by using more relevant metrics not included in the application.)  Briefly explain discrepancies between what actually happened compared to what was anticipated to happen.  Provide any further information (such as unexpected outcomes) important for understanding project activities and outcome results.

DIDSON sampling We successfully established two monitoring programs for river herring in Chesapeake Bay as described in our grant agreement. The work described below is for Year 1 of our two-year study evaluating the use of DIDSON imaging sonar for river herring run counts in Chesapeake Bay. These included the Choptank River (Upper Eastern Shore) and Marshyhope Creek, a tributary of the Nanticoke River (Lower Eastern Shore). These two streams were chosen because they 1) were thought by Maryland DNR to contain relatively healthy runs of river herring, 2) had substantial amounts of healthy riparian habitat upstream, 3) were an appropriate Fig. 2. Deploying the DIDSON unit width for conducting whole-stream DIDSON monitoring (see below for at Marshyhope Creek (attached to details), 4) were within 90 minutes driving time from SERC, and 5) had aluminum frame at left). The private landowners who were willing to provide both access to the stream construction fence was used to and electricity to power the DIDSON units. Although we initially prevent fish from swimming out of attempted to conduct monitoring at Mattawoman Creek, we moved to the the field of view behind it. Choptank River after vandals stole a generator used to power the Mattawoman Creek DIDSON unit.

At each site, the DIDSON unit was set up near the bank on one side of the stream with the field of view extending across the stream to the far bank (Fig. 2). Orange construction fencing was used to prevent river herring from swimming behind the DIDSON unit so that all fish had to pass within the field of view. DIDSON units were connected to a Panasonic Toughbook laptop computer on shore which recorded data. Power was provided by owners of the private properties where sampling was conducted. A 12 V battery backup system was used to maintain power to the DIDSON units and laptops in case of brief power outages (>48 hrs). This system was successful in providing uninterrupted power throughout the spawning season. DIDSON units were set to record 10 minutes of data each hour at a frame rate of 7 fs-1, with a random start time within Fig. 3. River herring (bright areas) each hour. recorded using DIDSON imaging sonar at Marshyhope Creek. DIDSON data were analyzed manually to determine the number of fish that passed the sampling location during each 10-min sampling interval (Fig. 3). Manual data processing was conducted within the software program Didson V5.25.52, which allows for measurement of fish detected in sonar image files. Fish were counted if they were within the size range of 200-350 mm. For each file, separate counts were made for fish swimming upstream and those swimming downstream. This made it possible to calculate net upstream movement, which was especially important for the Marshyhope Creek site where substantial milling of fish back and forth was observed. Manual processing of DIDSON images is time-consuming, but provides the highest possible data quality. Subsampling was employed to generate a preliminary estimate of run counts in time for this report. Hourly data for 10 days at the Marshyhope site and 5 days at the Choptank site were investigated to develop a subsampling strategy. The majority of fish (5/6 at Marshyhope and 2/3 at Choptank) moved upstream during the day. To reduce the number of files analyzed per day, we sampled every other hour from 7 am to 7 pm (seven 10-min files per day instead of 24). We then converted fish

Biological sampling To generate species specific run counts, we modified the DIDSON run counts described above using species composition data obtained from weekly electrofishing samples. At the Choptank site, we conducted backpack electrofishing a short distance upstream of the DIDSON unit during the alewife run, then switched to boat electrofishing later in the season when it became apparent that blueback herring were passing the DIDSON unit but not showing up at the backpack electrofishing site. At Fig. 4. Biological samples were the Marshyhope site, boat electrofishing was used throughout the study collected by boat electrofishing to (Fig. 4). For the backpack electrofishing, we conducted two passes determine the species composition (separated by one hour) of a 75 m stream following the Maryland of herring-sized fish each week. Biological Stream Survey protocol SERC Biologist Rob Aguilar is (http://www.dnr.state.md.us/streams/MBSS.asp). The stream segment holding the first alewife collected was enclosed prior to sampling using block nets at the upstream and as part of this project. downstream ends. Boat electrofishing was conducted by sampling for a standard 600 s time period at sites within 100 m (Marshyhope) or 500 m (Choptank River) of the DIDSON unit. The size distribution of fish collected by electrofishing was similar to the size distribution observed in DIDSON videos in the hour prior to electrofishing, indicating that there was little bias in the size of fish sampled with each method. C The percent composition of species was determined for all individuals within the size range 190-360 mm. A slightly larger size range was used N than for DIDSON run counts to account for variance in DIDSON length P measurements within this size range (Hightower et al. 2013). Linear interpolation was used between sample dates to generate a dataset of M daily species composition. This data set was used to convert daily DIDSON run counts to daily species-specific run counts.

Preliminary species-specific run counts Species-specific daily run counts for net upstream fish migration were summed to generate preliminary estimates of run size for 2013 (Fig. 5). Gaps in the daily datasets (8 days at the Marshyhope site and 15 days at the Choptank site) were filled using linear interpolation. Our preliminary run size estimate at the Marshyhope site was 151,973 alewife and 203,336 blueback herring. For the Choptank site, we estimated 268,441 alewife and 355,089 blueback herring. It should be noted that the first 2- 3 weeks of the alewife run were not sampled in 2013, making it likely that the alewife runs could have been substantially larger than these preliminary estimates. These run counts are estimates of the fish entering Map of Chesapeake Bay showing sub-watersheds representing about 14% of the area of both the Choptank 2 2 locations of study streams River (372 of 2,600 km ) and Nanticoke River (411 of 2,934 km ) including Patuxent River (P), watersheds. As stated previously, the run count locations were chosen to Mattawoman Creek (M), provide the highest possible quality run count data using DIDSON technology. If annual monitoring of these sites is continued in the long Marshyhope Creek on the term, these counts should provide high quality data that are Nanticoke River (N), and the representative of the runs in these river systems. This assumption is Choptank River (C). supported by the best available data on river herring population genetics, which suggest that there is little genetic differentiation among individuals within a river system (Palkovacs et al. 2013). Together, these two sub-watersheds represent <0.5% of the total Chesapeake Bay watershed. It is unknown what proportion of the total Chesapeake herring population they represent.

The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the opinions or policies of the National Fish and Wildlife Foundation. Mention of trade names or commercial products does not constitute their endorsement by the National Fish and Wildlife Foundation. Page 5 of 18 Fig. 5. Preliminary daily species-specific DIDSON run counts for net upstream fish passage at the Marshyhope Creek (top) and Choptank River (bottom) sites. Black bars at the top of each panel indicate dates when either no data were collected or dates when too much sediment from runoff impeded data analysis. These data gaps were filled using linear interpolation prior to calculating annual run totals. These preliminary estimates are conservative for several reasons: 1) The use of net upstream movement assumes that downstream swimming fish are milling and will eventually move upstream, whereas some of the fish moving downstream had likely spawned and were migrating back out to the ocean. If we assumed instead that there was no milling back and forth and used total upstream movement for run counts, the run size estimates would be 296,903 alewife and 806,648 blueback herring at the Marshyhope site and 367,524 alewife and 422,841 blueback herring at the Choptank site. We decided to use the more conservative net upstream movement for our preliminary run counts because the ratio of milling to out-migrating fish was not known. 2) Fish cast shadows in the DIDSON images. When large schools of fish enter the DIDSON field of view, some fish get lost in the shadows and are not counted. This results in an undercount of fish during times when fish passage rates are high. 3) River herring can be harder to capture during boat electrofishing surveys than some other species such as striped bass and white perch and their percent composition in biological samples may be underestimated. This occurs because river herring are schooling fish and it is more difficult to capture all individuals of a school than it is to capture all individuals of non-schooling fish. River herring also seem to have a weaker response to the electric current and may not rise to the surface or stay stunned as long as other species, making them harder to capture in dip nets.

Evaluation of minimum sampling interval needed for scientifically-rigorous run counts DIDSON imaging sonar units are expensive and data analysis requires a substantial amount of staff time. To explore the possibility of monitoring two streams with a single DIDSON unit, we subsampled the daily alewife and blueback herring run count data described above to quantify variability in run size estimates among different possible sampling strategies. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the opinions or policies of the National Fish and Wildlife Foundation. Mention of trade names or commercial products does not constitute their endorsement by the National Fish and Wildlife Foundation. Page 6 of 18

Table 1. Effect of sampling strategy on estimates of run count by species. Percent (%) difference is the difference in minimum and maximum counts simulated under each strategy. Site Species Strategy Actual count Minimum count Maximum count % diff Choptank Alewife 4-day 268,441 189,305 319,977 169% Choptank Alewife 7-day 268,441 169,673 416,367 245% Choptank Blueback 4-day 355,089 173,448 576,123 332% Choptank Blueback 7-day 355,089 231,780 504,049 217% Marshyhope Alewife 4-day 151,973 101,186 191,502 189% Marshyhope Alewife 7-day 151,973 99,515 244,566 246% Marshyhope Blueback 4-day 203,336 23,944 381,651 1,594% Marshyhope Blueback 7-day 203,336 49,527 508,173 1,026%

The two sampling strategies we tested were moving a single DIDSON unit back and forth between two streams sampling each stream either four or seven days at a time (Table 1). These strategies were simulated using our preliminary daily run count data and altering the start date of sampling. Because there are multiple possible start dates of both sampling and moving the unit to and from a stream, there are 16 and 49 possible counts for the 4-day and 7-day strategies, respectively. The percent difference of maximum and minimum possible counts varied from 169% to 1,594%. In the most extreme case, estimates of blueback herring in Marshyhope creek varied from 23,944 to 381,651 fish, a 1,594% difference, when our preliminary estimate from daily data was 203,336 fish. The potential for order of magnitude differences indicates that moving a single DIDSON unit back and forth between two streams is not a viable strategy for increasing the number of streams at which DIDSON run counts are conducted.

Unexpected challenges of DIDSON run counts Several challenges associated with initiating a new sampling program inhibited our ability to collect run count data during part of the spawning run at each site, but these problems were easily resolved prior to 2014 sampling. In 2013, we originally selected Mattawoman Creek as one of our two sampling sites. Although secured with heavy metal locks, vandals cut the locks and stole the generator we were using to power our equipment. The decision was made to find a new, more secure location with existing electric power. The first several weeks of the alewife run passed while we identified and made arrangements to access a new site on the Choptank River and amended our sampling permits. We also became aware of a malfunction in the DIDSON unit deployed at the Choptank site which caused it to stop recording data after time intervals of one to several days. After the sampling season ended, we sent the unit back to the manufacturer and it was repaired successfully. No further problems have been experienced. Finally, a flaw in the connector for an external hard drive caused the loss of two weeks of data during the alewife run at the Marshyhope site. Despite these unanticipated challenges, we were able to collect high quality run count data for 53% of the spawning run at the Choptank site and 70% at the Marshyhope site. It should be noted that we have not had any similar issues to date in our 2014 sampling.

Unexpected benefit of monitoring the Choptank River – Comparison with 1970’s run counts The move to the Choptank River provided an unexpected benefit, as we became aware of a fish weir survey of anadromous spawning runs conducted near our DIDSON site in the 1970’s by Maryland Department of Natural Resources. In the prior study, Speir et al. (2008) used electronic fish counters and trap samples to estimate run sizes in 1972 (39,397 alewife and 531,146 blueback herring) and 1973 (271,497 alewife and 34,297 blueback herring). Because the prior study was conducted approximately 100 m downstream of our Choptank River location, it is possible to make comparisons between our run count data and spawning run counts conducted 40 years earlier. Our preliminary estimates for 2013 of 268,000 alewife (which does not include the first 2-3 weeks of the spawning run) and 355,000 blueback herring compare favorably with the earlier study, indicating that spawning runs in this stream may have changed little during the last 40 years. In 2014, our graduate intern will make a rigorous comparison of our run counts and the counts in Speir et al. (2008) as his independent research project.

Proxies for run size – Ichthyoplankton sampling We evaluated the effectiveness of ichthyoplankton sampling as a method for monitoring river herring spawning. Ichthyoplankton samples were collected following standard methods used by Maryland DNR. Plankton nets (360x400 mm rectangular opening, 360 µm mesh size) were mounted on a long vertical pole and held at the stream bottom for 5 min. Temperature, salinity, dissolved oxygen, and current speed were measured. Samples were rinsed into the cod end and transferred to jars containing 70% denatured ethanol for sample preservation. Ethanol was used for sample preservation

An important component of our evaluation of ichthyoplankton as a proxy for herring spawning was determining whether the duplicate samples collected for us by Mattawoman Watershed Society, as well as the samples we collected, were in fact river herring. Previous ichthyoplankton studies conducted by Maryland DNR and Mattawoman Watershed Society have relied upon morphological identification of eggs and larvae to determine presence of river herring. While this method is effective at separating out most non-target species, it is difficult to identify larvae to species and impossible to identify eggs beyond a species group including alewife, blueback herring, hickory shad, and possibly other species. Subsamples of eggs collected in Mattawoman Creek, Patuxent River, Choptank River, and Marshyhope Creek were analyzed individually using genetic barcoding techniques (www.barcodeoflife.org). Seventy-six percent of the 376 individual eggs analyzed to date were sequenced successfully. Samples that did not sequence likely suffered from poor preservation due to the use of 70% ethanol. Preservation of DNA would have been improved in 95% non-denatured ethanol. However, 95% non-denatured ethanol is not safe for unsupervised use by citizen scientists. The genetic sequences obtained (n = 284) were compared against a database we are Fig. 6. Comparison of the proxy run size developing of all fish species in Chesapeake Bay. Using this variables egg density from ichthyoplankton technique, we were able to determine that 56% of the eggs sampling (top panel) and electrofishing collected were alewife, 27% were blueback herring, 8% were catch per unit effort (CPUE) (bottom panel) hickory shad, and 9% were from other species (mostly gizzard shad). These results give us confidence that citizen scientist with the count of fish passing the DIDSON site the day or hour before proxy sampling ichthyoplankton surveys in freshwater streams are effective for 2 obtaining river herring eggs and larvae. However, a substantial was conducted. The r value for the time investment is required by individuals trained in regression line indicates the proportion of morphological identification to separate herring variability in each proxy variable that could ichthyoplankton from other material in samples (leaves, algae, be explained by DIDSON run counts. Note etc.) and especially from non-target species. Maryland DNR that although both relationships were currently provides this expertise to Mattawoman Watershed statistically significant, they were strongly Society, but stated at our workshop that they would not be able dependent on the single high values of each to process additional samples at current funding levels. variable collected the week of April 8-12.

To determine the utility of ichthyoplankton sampling for estimating spawner abundance, we compared egg density to the count of fish passing DIDSON unit on the day sampling was conducted (Fig. 6). Data were analyzed for the Marshyhope site, where both standardized species-specific run count data and ichthyoplankton data were available for the entire spawning season. There was a significant relationship between DIDSON fish counts and egg density, however the relationship was due to a single week with the highest value of each data set. These results are not surprising, as egg density likely reflects actual spawning activity upstream of the sampling location, which may or may not be related to the number of adult fish present on a given day.

Proxies for run size – electrofishing catch per unit effort (CPUE) The second weekly proxy for run size that we evaluated was electrofishing catch per unit effort (CPUE) (Fig. 6). Electrofishing is a relatively low-cost method for estimating fish abundance, as most management jurisdictions and some academic institutions in the Chesapeake Bay region currently have equipment and trained staff for electrofishing. Electrofishing CPUE was calculated as the number of fish of 190-360 mm TL collected per hour of sampling, which was The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the opinions or policies of the National Fish and Wildlife Foundation. Mention of trade names or commercial products does not constitute their endorsement by the National Fish and Wildlife Foundation. Page 8 of 18 Table 2. Effect of weekly sampling on estimates of run count by species. Percent (%) difference is the difference in minimum and maximum counts simulated under each strategy. N/A indicates a non-applicable value due to a negative minimum run count. Site Species Actual count Minimum count Maximum count % diff Choptank Alewife 268,441 155,631 476,688 306% Choptank Blueback 355,089 85,209 846,007 993% Marshyhope Alewife 151,973 61,476 215,356 350% Marshyhope Blueback 203,336 -64,486 414,339 N/A

Fig. 7. Age distribution of river herring spawning runs based on otolith aging. The proportion of males or females in each age class is presented for (A) Marshyhope Creek alewife, (B) Marshyhope Creek blueback herring, (C) Choptank River alewife, (D) Choptank River blueback herring.

calculated using the data from our standardized weekly sampling of species composition. These data were compared to the number of fish with estimated TL of 200-350 mm passing the DIDSON unit during the hour just prior to electrofishing. Data analyzed were for the Marshyhope Creek site only. There was a significant relationship between weekly electrofishing CPUE and DIDSON run counts. However, this relationship was clearly driven by a single week when both datasets had their highest value. Removing this single data point causes the relationship to disappear completely, suggesting that electrofishing CPUE may be a relatively poor indicator of river herring abundance. This result was expected, as electrofishing is a poor method for estimating the abundance of schooling fish because it is difficult to capture an entire school at once with a hand-held dip net. At the Choptank River site, too few data were available for this analysis due to the mid-season shift from backpack electrofishing to boat electrofishing, which do not provide equivalent data.

The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the opinions or policies of the National Fish and Wildlife Foundation. Mention of trade names or commercial products does not constitute their endorsement by the National Fish and Wildlife Foundation. Page 9 of 18 Challenges with using weekly proxy variables Proxy variables for run size conducted at weekly intervals (ichthyoplankton, electrofishing, gillnets, fyke nets, etc.) are unlikely to provide reliable estimates of annual run size. Our 2013 run count data indicated that river herring spawning runs are highly episodic, with substantial differences in numbers of fish passing the DIDSON units at time scales from hours to a few days. When sampling only occurs once each week, an interval much longer than these important time scales, most of the variability is missed leading to poor estimates of run size. The effect of a weekly sampling interval was evaluated by simulating weekly sampling using our daily net upstream run count data for each species and sampling stream. The resulting estimates of annual run counts varied widely depending on the start date of simulated sampling (Table 2). As was the case for our simulations of sampling strategy described above, blueback herring at the Marshyhope site were most variable, with a minimum count that was negative because there was net downstream movement on several of the sampling days when one of the seven possible start dates was used. A study of similar episodic processes in the migration of blue crab postlarvae from the ocean to estuarine nursery habitats indicated that weekly sampling provided a very poor estimate of total annual recruitment in most years (Ogburn et al. 2012). The Ogburn et al. (2012) study indicated that weekly sampling intervals were only effective for assessing the seasonal timing of recruitment, whereas daily sampling was likely necessary to generate annual estimates. In fact, our data from this study indicate that hourly run count monitoring is likely required for estimating annual river herring run counts, as much of each run occurred within a relatively few hours each day that might be missed if sampling was conducted only once per day.

Sex and age composition of spawning runs Fish collected during electrofishing surveys in Marshyhope Creek and Choptank River were dissected to determine the age composition by sex. Ages were estimated using standard otolith aging techniques and a subset of otolith ages was checked by an independent reader (Catherine Schlick at George Mason University). These ages should be considered preliminary until the otoliths are analyzed by a second reader, which will be completed in 2014. There were substantial differences in the sex ratio by site, with nearly equal sex ratios in Marshyhope Creek (56% of 124 alewife and 50% of 54 blueback herring were male) and male-dominated sex ratios in Choptank River (71% of 84 alewife and 67% of 87 blueback herring were male). The cause of this difference in sex ratio is unknown and will be investigated further in 2014. The majority of fish in all river herring runs were four years old, and females tended to be older than males (Fig. 7). These results indicate that each run has a substantial proportion of repeat spawners. In 2014, we anticipate confirming this hypothesis by analyzing spawning marks on scales.

Population genetics A second unexpected outcome of this project is that we were able to add to the population genetic database for river herring that was developed by Eric Palkovacs and Tom Schultz in a prior project funded by NFWF. We were able to conduct microsatellite analysis of alewife and blueback herring genetic material collected from the Choptank River, Marshyhope Creek, and Patuxent River (blueback herring only). The samples add new spawning streams to the coast- wide population genetic database. The microsatellite analyses were carried out by Dr. Tom Schultz at the Duke University Marine Laboratory. Understanding the genetic structure of river herring stocks in Chesapeake Bay will be an important factor in understanding population dynamics and will inform decisions about how many and which spawning streams should be monitored. It will also ensure that Chesapeake river herring stock are adequately accounted for in genetic analyses of river herring collected as bycatch in offshore fisheries.

References Hightower, J.E., Magowan, K.J., Brown, L.M., Fox, D.A. 2013. Reliability of fish size estimates obtained from multibeam imaging sonar. Journal of Fish and Wildlife Management 4:86-96.

Ogburn, M.B. and Forward, R.B., Jr. 2012. Effect of sampling interval on estimates of larval supply. Fishery Bulletin 110:451-457.

Palkovacs, E.P., Hasselman, D.J., Argo, E.E., Gephardt, S.R., Limburg, K.E., Post, D.M., Schultz, T.F., Willis, T.V. 2013. Combining genetic and demographic information to prioritize conservation efforts for anadromous alewife and blueback herring. Evolutionary Applications 7:212-226.

Speir, H., Carter, W.R., Foster, J.W. 2008. Aspects and characteristics of spawning populations of anadromous fish in the upper Choptank River, Maryland 1972-1973. Maryland Department of Natural Resources Fisheries Service Technical Report No. 54. 26 pp.

Lessons learned from Year 1 of this two-year study: A. DIDSON imaging sonar can be used to provide scientifically-rigorous run counts of river herring in spawning streams. DIDSON imaging sonar provided recordings of fish in spawning runs of sufficient quality to run counts in turbid coastal plain streams of Chesapeake Bay. Monitoring sites are preferably no wider than 12 m, have access to power, have a high enough bluff near shore to keep equipment above flood level, be accessible for biological sampling to determine species composition, are non-tidal with laminar flow, and secure enough to prevent vandalism. Primary challenges to DIDSON run counts are: 1) equipment costs (approximately $80,000 in equipment per site), 2) identification of appropriate long-term sampling locations, and 3) technician support for setup, maintenance, frequent biological sampling (at least weekly), and data processing. B. Hourly sampling is likely needed for generating rigorous run counts. Substantial portions of spawning runs were observed to occur within a few hours. For example, fish migrated past our Choptank site at a rate of about 25,000 fish/h for 3-4 h in the evening on two days, making up 34% of all fish passing the site in 2013. In order to provide accurate run counts, sampling strategies must be able to capture these episodic events. For this reason, sampling 10 minutes each hour as in our study is standard for monitoring of spawning runs and is recommended for river herring monitoring in Chesapeake Bay. DIDSON imaging sonar is likely the best option for run counts in relatively small, turbid streams. Video monitoring and electronic fish counters provide lower-cost options at fish ladders or where fish weirs could be constructed to funnel fish through a narrow opening. C. Moving a single DIDSON unit back and forth between two streams once or twice a week is not feasible for producing high quality data. When this sampling strategy was simulated using our 2013 dataset, estimates of run size were as much as an order of magnitude different depending on the start date of simulated sampling. Such high variability due to sampling strategy alone would make it impossible to detect actual year-to-year differences in run size. D. Indices of run size generated from weekly sampling are likely useful for assessing the presence and timing of runs, but are not likely to provide rigorous data for evaluating year-to-year variability in run size. As in Lesson C above, we simulated weekly sampling of our 2013 daily run count data and estimated that run counts from weekly sampling could vary by an order of magnitude or more depending on the start date of simulated sampling. This suggests that ichthyoplankton density, electrofishing catch per unit effort, gillnet catch per unit effort, and other weekly sampling strategies are unlikely to produce abundance indices for which year-to-year variability reflects actual changes in run size. E. Citizen science ichthyoplankton sampling was an effective way to document the presence of river herring in spawning streams. Genetic barcoding techniques indicated that 83% of the herring-like eggs collected by citizen scientists were in fact river herring eggs. With relatively little training and at a cost of approximately $500 per site, citizen scientists could conduct ichthyoplankton sampling and remove fish eggs and larvae from samples for genetic barcoding. Pooled genetic samples would be inexpensive to analyze (roughly $10 per sample) to determine herring presence or absence.

In 2014, we are conducting a second year of monitoring at the Choptank River and Marshyhope Creek sites. We are also drafting a strategy for conducting long term monitoring of river herring runs throughout Chesapeake Bay. The plan will incorporate these lessons learned and the best available science in order to provide a rigorous scientific assessment of river herring runs throughout Chesapeake Bay

4. Dissemination Briefly identify any dissemination of lessons learned or other project results to external audiences, such as the public or other conservation organizations.

Preliminary results from our project have been presented at: 1) the American Fisheries Society national meeting in Little Rock, Arkansas and Mid-Atlantic Chapter meeting in Norfolk, Virginia, 2) the Nanticoke Watershed Alliance’s Lower Shore Stewardship Institute, Salisbury, Maryland, 3) the Northeast Interagency River Herring Meeting, Hadley, Massachusetts, 4) the Chesapeake Bay Program Fish Passage Work Group, Annapolis, Maryland, 5) the East Coast Commercial Fishermen’s Aquaculture and Trade Exposition, Ocean City, Maryland, and 6) our 2014 Chesapeake Bay River Herring Workshop in Edgewater, Maryland. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the opinions or policies of the National Fish and Wildlife Foundation. Mention of trade names or commercial products does not constitute their endorsement by the National Fish and Wildlife Foundation. Page 11 of 18 5. Project Documents Include in your final programmatic report, via the Uploads section of this task, the following:

 2-10 representative photos from the project. Photos need to have a minimum resolution of 300 dpi and must be accompanied with a legend or caption describing the file name and content of the photos;  report publications, GIS data, brochures, videos, outreach tools, press releases, media coverage;  any project deliverables per the terms of your grant agreement.

Six photos were uploaded with this document. The photos are property of and should be credited to the Smithsonian Environmental Research Center (SERC). Photo captions are as follows: 1) Hines_2013_workshop.jpg – Participants in the 2013 Chesapeake Bay River Herring Workshop hosted by the Smithsonian Environmental Research Center. 2) Hines_citizen_science1.jpg – Members of the Nanticoke Watershed Alliance participate in river herring ichthyoplankton sampling in Marshyhope Creek. 3) Hines_citizen_science2.jpg – Washing down an ichthyoplankton net with help of a citizen scientist Lauren Mott. 4) Hines_DIDSON.jpg – Dr. Matt Ogburn, Research Associate at the Smithsonian Environmental Research Center, installs the DIDSON imaging sonar unit in Marshyhope Creek. The orange construction fencing in the photo was used to prevent river herring from swimming behind the sonar unit and out of the field of view. 5) Hines_electrofishing.jpg – Smithsonian Environmental Research Center biologists Rob Aguilar and Kim Richie showing off the first alewife collected in 2013 in Marshyhope Creek during an electrofishing survey. 6) Hines_ichthyoplankton.jpg – Smithsonian Environmental Research Center biologist Kim Richie conducting ichthyoplankton sampling in Marshyhope Creek.

POSTING OF FINAL REPORT: This report and attached project documents may be shared by the Foundation and any Funding Source for the Project via their respective websites. In the event that the Recipient intends to claim that its final report or project documents contains material that does not have to be posted on such websites because it is protected from disclosure by statutory or regulatory provisions, the Recipient shall clearly mark all such potentially protected materials as “PROTECTED” and provide an explanation and complete citation to the statutory or regulatory source for such protection.