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1. Creel Surveys for Social-Ecological-Systems Focused Fisheries Management

   https://doi.org/10.1080/23308249.2020.1869696  

   Nieman, Chelsey L. ; Iwicki, Carolyn ; Lynch, Abigail J. ; Sass, Greg G. ; Solomon, Christopher T. ; Trudeau, Ashley ; van Poorten, Brett ( January 2021 , Reviews in Fisheries Science & Aquaculture)

   null (Ed.)

   Recreational fisheries are social-ecological systems (SES), and knowledge of human dimensions coupled with ecology are critically needed to understand their system dynamics. Creel surveys, which typically occur in-person and on-site, serve as an important tool for informing fisheries management. Recreational fisheries creel data have the potential to inform large-scale understanding of social and ecological dynamics, but applications are currently limited by a disconnect between the questions posed by social-ecological researchers and the methods in which surveys are conducted. Although innovative use of existing data can increase understanding of recreational fisheries as SES, creel surveys should also adapt to changing information needs. These opportunities include using the specific temporal and spatial scope of creel survey data, integrating these data with alternative data sources, and increasing human dimensions understanding. This review provides recommendations for adapting survey design, implementation, and analysis for SES-focused fisheries management. These recommendations are: (1) increasing human dimensions knowledge; (2) standardization of surveys and data; (3) increasing tools and training available to fisheries scientists; and (4) increasing accessibility and availability of data. Incorporation of human dimensions information into creel surveys will increase the ability of fisheries management to regulate these important systems from an integrated SES standpoint. 

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2. Walleye spawning, ice phenology, and covariate data for Upper Midwestern Lakes: 1939-2019

   https://doi.org/10.6073/pasta/f7a55f08dfe2a9514067e5c633313ef4  

   Feiner, Zachary S ; Barta, Martha ; Sass, Greg ; Reed, Jeffrey ; Cichosz, Thomas ; Shultz, Aaron ; Luehring, Mark ( January 2023 , Environmental Data Initiative)

   The phenology of critical biological events in aquatic ecosystems are rapidly shifting due to climate change. Growing variability in phenological cues can increase the likelihood of trophic mismatches, causing recruitment failures in commercially, culturally, and recreationally important fisheries. We tested for changes in spawning phenology of regionally important walleye (Sander vitreus) populations in 194 Midwest US lakes in Minnesota, Michigan, and Wisconsin spanning 1939-2019 to investigate factors influencing walleye phenological responses to climate change and associated climate variability, including ice-off timing, lake physical characteristics, and population stocking history. Data from Wisconsin and Michigan lakes (185 and 5 out of 194 total lakes, respectively) were collected by the Wisconsin Department of Natural Resources (WDNR) and the Great Lakes Indian Fish and Wildlife Commission (GLIFWC) through standardized spring walleye mark-recapture surveys and spring tribal harvest season records. Standardized spring mark-recapture population estimates are performed shortly after ice-off, where following a marking event, a subsequent recapture sampling event is conducted using nighttime electrofishing (typically AC – WDNR, pulsed-DC – GLIFWC) of the entire shoreline including islands for small lakes and index stations for large lakes (Hansen et al. 2015) that is timed to coincide with peak walleye spawning activity (G. Hatzenbeler, WDNR, personal communication; M. Luehring, GLIFWC, personal communication; Beard et al. 1997). Data for four additional Minnesota lakes were collected by the Minnesota Department of Natural Resources (MNDNR) beginning in 1939 during annual collections of walleye eggs and broodstock (Schneider et al. 2010), where date of peak egg take was used to index peak spawning activity. For lakes where spawning location did not match the lake for which the ice-off data was collected, the spawning location either flowed into (Pike River) or was within 50 km of a lake where ice-off data were available (Pine River) and these ice-off data were used. Following the affirmation of off-reservation Ojibwe tribal fishing rights in the Ceded Territories of Wisconsin and the Upper Peninsula of Michigan in 1987, tribal spearfishers have targeted walleye during spring spawning (Mrnak et al. 2018). Nightly harvests are recorded as part of a compulsory creel survey (US Department of the Interior 1991). Using these records, we calculated the date of peak spawning activity in a given lake-year as the day of maximum tribal harvest. Although we were unable to account for varying effort in these data, a preliminary analysis comparing spawning dates estimated using tribal harvest to those determined from standardized agency surveys in the same lake and year showed that they were highly correlated (Pearson’s correlation: r = 0.91, P < 0.001). For lakes that had walleye spawning data from both agency surveys and tribal harvest, we used the data source with the greatest number of observation years. Ice-off phenology data was collected from two sources – either observed from the Global Lake and River Ice Phenology database (Benson et al. 2000)t, or modeled from a USGS region-wide machine-learning model which used North American Land Data Assimilation System (NLDAS) meteorological inputs combined with lake characteristics (lake position, clarity, size, depth, hypsography, etc.) to predict daily water column temperatures from 1979 - 2022, from which ice-off dates could be derived (https://www.sciencebase.gov/catalog/item/6206d3c2d34ec05caca53071; see Corson-Dosch et al. 2023 for details). Modeled data for our study lakes (see (Read et al. 2021) for modeling details), which performed well in reflecting ice phenology when compared to observed data (i.e., highly significant correlation between observed and modeled ice-off dates when both were available; r = 0.71, p < 0.001). Lake surface area (ha), latitude, and maximum depth (m) were acquired from agency databases and lake reports. Lake class was based on a WDNR lakes classification system (Rypel et al. 2019) that categorized lakes based on temperature, water clarity, depth, and fish community. Walleye stocking history was defined using the walleye stocking classification system developed by the Wisconsin Technical Working Group (see also Sass et al. 2021), which categorized lakes based on relative contributions of naturally-produced and stocked fish to adult recruitment by relying heavily on historic records of age-0 and age-1 catch rates and stocking histories. Wisconsin lakes were divided into three groups: natural recruitment (NR), a combination of stocking and natural recruitment (C-ST), and stocked only (ST). Walleye natural recruitment was indexed as age-0 walleye CPE (number of age-0 walleye captured per km of shoreline electrofished) from WDNR and GLIFWC fall electrofishing surveys (see Hansen et al. 2015 for details). We excluded lake-years where stocking of age-0 fish occurred before age-0 surveys to only include measurements of naturally-reproduced fish. 

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3. Celebrating 75 Years of Wisconsin’s Northern Highland Fishery Research Area: The Past, Present, and Future

   https://doi.org/10.1002/fsh.10687  

   Sass, Greg_G ; Shaw, Stephanie_L ; Renik, Kathryn_M ( December 2021 , Fisheries)

   On June 20, 2021, the Northern Highland Fishery Research Area (NHFRA) celebrated its 75th anniversary of continuous fisheries population monitoring and compulsory angler creel census on five lakes in northern Wisconsin. In 1946, five lakes were designated as experimental fisheries research lakes and all anglers have been required to adhere to the compulsory creel census to record catch information. We review the history of the NHFRA, its role in evaluating experimental regulations, how data derived from the NHFRA were paramount in developing a critical Walleye Sander vitreus management plan for a joint tribal subsistence and recreational angling fishery, discuss the NHFRA as a training ground for early career fisheries professionals, and speculate on its future. By learning from the past and adapting to new challenges and emerging fisheries research needs, the NHFRA is poised to add to its 75-year legacy of research and training to inform science-based decision making and to prepare generations of new fisheries professionals. The 75-year history of the NHFRA exemplifies the importance of adaptation, long-term data, establishing sentinel lakes for observations of environmental change, field stations, and partnerships for successful fisheries management.

    

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4. Data‐driven predictions of summertime visits to lakes across 17 US states

   https://doi.org/10.1002/ecs2.4457  

   Nelson, Erik ; Rogers, Maggie ; Wood, Spencer A. ; Chung, Jesse ; Keeler, Bonnie ( April 2023 , Ecosphere)

   Using a dataset of more than 51,000 US lakes, we estimated the relationship between summertime lake visits, lake water clarity, landscape features, and other amenities, where visits were estimated with counts of geo‐located photographs. Given the size and complexity of our dataset, we used a combination of machine learning techniques, imputation techniques, and a Poisson count model to estimate these relationships. We found that every additional meter of average summertime Secchi depth was associated with at least 7% more summertime lake visits, all else equal. Second, we found that lake amenities, such as beaches, boat launches, and public toilets, were more powerful predictors of visits than water clarity. Third, we found that visits to a lake were strongly influenced by the lake's accessibility and its distance to nearby lakes and the amenities the nearby lakes offered. Our research highlights the need for (1) a better understanding of how representative social media data are of actual recreational behavior, (2) the development of best practices to account for nonrandom patterns in missing natural feature data, and (3) a better understanding of the potential endogeneity in the lake visit–water quality relationships.

    

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5. Trophic coupling of the microbial and the classical food web in Lake Baikal, Siberia

   https://doi.org/10.1111/fwb.13201  

   Moore, Marianne V. ; De Stasio, Jr., Bart T. ; Huizenga, Kristin N. ; Silow, Eugene A. ( November 2018 , Freshwater Biology)

   Pelagic copepods often couple the classical and microbial food webs by feeding on microzooplankton (e.g. ciliates) in oligotrophic aquatic systems, and this consumption can trigger trophic cascades within the microbial food web. Consumption of mixotrophic microzooplankton, which are both autotrophic and heterotrophic within the same individual, is of particular interest because of its influence on carbon transfer efficiency within aquatic food webs.

   In Lake Baikal, Siberia, it is unknown how carbon from a well‐developed microbial food web present during summer stratification moves into higher trophic levels within the classical food web.

   We conducted in situ experiments in August 2015 to test the hypotheses that: (a)  the lake's dominant endemic copepod (Epischura baikalensis), previously assumed to be an herbivore feeding on diatoms, connects the microbial and classical food webs by ingesting ciliates; and (b) this feeding initiates top‐down effects within the microbial food web.

   Our results supported these hypotheses.E. baikalensisindividuals consumed on average 101–161 ciliates per day, obtaining 96%–98% of their ingested carbon from ciliates and the remainder from small diatoms. Clearly,E. baikalensisis omnivorous, and it is probably channelling more primary production from both the microbial food web and the classical food web of Lake Baikal to higher trophic levels than any other pelagic consumer.

   Most ciliates consumed were a mixotrophic oligotrich and such taxa are often abundant in summer in other oligotrophic lakes. Consumption of these mixotrophs is likely to boost substantially the transfer efficiency of biomass to higher trophic levels with potential implications for fish production, but this has seldom been investigated in oligotrophic lakes.

   Feeding ofE. baikalensisinitiated a three‐link predatory cascade which reduced the abundance of ciliates and elevated growth rates of heterotrophic nanoflagellates but did not affect abundance or growth rates of autotrophic picoplankton. This demonstration of a potential trophic cascade in Lake Baikal indicates that investigations at larger spatial–temporal scales are needed to identify the conditions promoting or precluding trophic cascades in this lake.

    

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