The phenology of critical biological events in aquatic ecosystems is rapidly shifting due to climate change. Growing variability in phenological cues can increase the likelihood of trophic mismatches (i.e., mismatches in the timing of peak prey and predator abundances), causing recruitment failures in important fisheries. We assessed changes in the spawning phenology of walleye (Sander vitreus) in 194 Midwest US lakes 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. Ice-off phenology shifted earlier, about three times faster than walleye spawning phenology over time. Spawning phenology deviations from historic averages increased in magnitude over time, and large deviations were associated with poor offspring survival. Our results foreshadow the risks of increasingly frequent natural recruitment failures due to mismatches between historically tightly coupled spawning and ice-off phenology.

Recreational fisheries are valued at $190B globally and constitute the predominant way in which people use wild fish stocks in developed countries, with inland systems contributing the main fraction of recreational fisheries. Although inland recreational fisheries are thought to be highly resilient and self-regulating, the rapid pace of environmental change is increasing the vulnerability of these fisheries to overharvest and collapse. Here we directly evaluate angler harvest relative to the biomass production of individual stocks for a major inland recreational fishery. Using an extensive 28-y dataset of the walleye (Sander vitreus) fisheries in northern Wisconsin, United States, we compare empirical biomass harvest (Y) and calculated production (P) and biomass (B) for 390 lake year combinations. Production overharvest occurs when harvest exceeds production in that year. Biomass and biomass turnover (P/B) declined by ∼30 and ∼20%, respectively, over time, while biomass harvest did not change, causing overharvest to increase. Our analysis revealed that ∼40% of populations were production-overharvested, a rate >10× higher than estimates based on population thresholds often used by fisheries managers. Our study highlights the need to adapt harvest to changes in production due to environmental change.

Walleye (Sander vitreus) populations are declining in Wisconsin and neighboring regions, motivating broader interest in walleye biology amidst ecological change. In fishes, growth integrates variation in ecological drivers and provides a signal of changing ecological conditions. Weused a 23-year data set of length-at-age from 353 walleye populations across Wisconsin to test whether walleye growth rates changed over time and what ecological factors best predicted these changes. Using hierarchical models, we tested whether spatiotemporal variation in walleye growth was related to adult walleye density (density-dependent effects), water temperature, and largemouth bass (Micropterus salmoides) catch per unit effort (CPUE; predator or competitor effects). The average length of young walleye increased over time, and as a result, time to reach harvestable size declined significantly. In contrast, average lengths of older walleye have remained relatively constant over time. Juvenile walleye length-at-age was positively correlated with largemouth bass CPUE and surface water temperatures, but negatively correlated with adult walleye density. Our finding of widespread and long-term changes in walleye growth rates provides additional insights into how inland fisheries are responding to environmental change.

Assessment of the Walleye Sander vitreus angling and tribal spearing fisheries in the Ceded Territory of Wisconsin (CTWI) is critical for the sustainability of this resource. Key to these assessments is an understanding of harvest demographics, exploitation, catch and harvest efficiency, and relationships between catch or harvest and adult density. We characterized the size distribution and mean length of harvested Walleyes, harvest, exploitation rate, and catch (angling) or harvest (spearing) rate for both fisheries during 1990-2015. Then, we evaluated catch and harvest rates in relation to adult density and tested for self-regulation or hyperstability in each fishery. Size distribution and mean length of harvested Walleyes in both fisheries were statistically different but biologically similar. Anglers harvested significantly more Walleyes, and the mean exploitation rate was greater in the angling fishery. Spearfishers had significantly higher mean harvest rates compared with angler catch rates. Catch and harvest rates followed an asymptotic relationship with adult density, with the spear fishery showing more hyperstability than the angling fishery. In the CTWI, naturally reproducing Walleye populations are managed for densities 7.4adults/ha. Our results suggest that maintaining adult Walleye densities near the point of diminishing returns of the asymptotic relationship (10-15Walleyes/ha) will result in a sustainable fishery that also maximizes tribal harvest and angler catch. However, maintaining adult Walleye densities within this range in the unproductive lakes typical of the CTWI may be unrealistic. Due to the hyperstability observed in each fishery, active management of the spear fishery should continue and monitoring of the angling fishery should also continue given recent declines in natural recruitment and production observed in the CTWI in order to maintain Walleye populations in a safe operating space. An empirical understanding of CTWI Walleye angler and spearfisher effort dynamics is critically needed to mechanistically explain the observed hyperstability in each fishery.

Harvest of Muskellunge Esox masquinongy within the Ceded Territory of northern Wisconsin is managed using a quota system where safe harvest levels are established for individual populations based on estimates of adult abundance. When a reliable population estimate is not available for an individual lake, linear regression is used to predict adult abundance based on loge lake surface area (LRSA model). However, the amount of variation explained by the LRSA model is relatively low (r(2) < 0.49). Our objective was to determine if an alternative random forest (RF) analysis incorporating 24 predictor variables related to lake characteristics increased the accuracy of predicted estimates of adult abundance compared to the LRSA model. Random forest analysis increased predictive accuracy (measured as mean absolute error) by 45% and selected lake surface area, percent sand, muck, and gravel substrates, year of estimate, stocking intensity, shoreline length, and percent of shrub and grassland habitat in the watershed as important predictor variables. On average, use of RF analysis resulted in an 18% increase (range = -60% to 200% change) or an additional one fish per lake-year (range = -17-47 fish) in safe harvest compared to the LRSA model.

In Wisconsin, the management of Walleyes Sander vitreus relies on a set of log-linear regressions to predict Walleye abundance and to set safe harvest. The regression models predict mean Walleye abundance from lake area, but they ignore variability among years; they also predict equal Walleye populations in lakes with the same size and recruitment source. We evaluated three alternative models in terms of predictive accuracy and the risk of overharvest. We used 899 mark-recapture population estimates (collected between 1953 and 2013) from 219 lakes to develop and evaluate (1) a log-linear mixed-effects model that used all individual observations and estimated adult Walleye abundance from lake area and lake-specific deviations from the overall intercept; (2) a mixed-effects model that builds on model 1 by adding a linear fixed effect of sampling year; and (3) a mixed-effects model that builds on model 1 by adding a random year effect. Walleye abundance was positively correlated with lake area in all models and was negatively correlated with sampling year (when included). Alternative models improved predictive accuracy by 17-22% over the current regression model. Restricting data to those collected during the most recent 20 years improved model responsiveness to new data and reduced the value of including a linear time trend. When all data were used for model construction, the relative risk of overharvest was lowest under the mixed-effects model with a linear time trend; when the most recent 20 years of data were used, the risk was lowest under the mixed-effects model with a random year effect. Accounting for variability among years would allow harvest to track changing Walleye populations and would allow management to be more adaptive. We recommend using the mixed-effects model with a random year effect and restricting the data inputs to the most recent 20 years.