. 2015. Portfolio theory as a management tool to guide conservation and restoration of multi-stock fish populations. Ecosphere 6(12):296. http://dx.doi.org/10.1890/ES15-00237.1Abstract. Habitat degradation and harvest have upset the natural buffering mechanism (i.e., portfolio effects) of many large-scale multi-stock fisheries by reducing spawning stock diversity that is vital for generating population stability and resilience. The application of portfolio theory offers a means to guide management activities by quantifying the importance of multi-stock dynamics and suggesting conservation and restoration strategies to improve naturally occurring portfolio effects. Our application of portfolio theory to Lake Erie Sander vitreus (walleye), a large population that is supported by riverine and open-lake reef spawning stocks, has shown that portfolio effects generated by annual inter-stock larval fish production are currently suboptimal when compared to potential buffering capacity. Reduced production from riverine stocks has resulted in a single open-lake reef stock dominating larval production, and in turn, high inter-annual recruitment variability during recent years. Our analyses have shown (1) a weak average correlation between annual river and reef larval production (q ¼ 0.24), suggesting that a natural buffering capacity exists in the population, and (2) expanded annual production of larvae (potential recruits) from riverine stocks could stabilize the fishery by dampening inter-annual recruitment variation. Ultimately, our results demonstrate how portfolio theory can be used to quantify the importance of spawning stock diversity and guide management on ecologically relevant scales (i.e., spawning stocks) leading to greater stability and resilience of multi-stock populations and fisheries.

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Management agencies often estimate the ages of Largemouth Bass Micropterus salmoides based on the examination of scales—a structure that is known to produce biased estimates—without knowing how the associated bias affects management decisions. We sought to understand the effects of this bias by comparing population metrics that were predicted using scale‐derived and otolith‐derived age data. We collected scales and otoliths from Largemouth Bass that were sampled during standard electrofishing surveys. The age of each fish was estimated independently by three separate readers using both scales and otoliths. We assessed the average coefficient of variation for scale‐derived and otolith‐derived age estimates, examined the bias of scale‐derived age estimates, and estimated von Bertalanffy growth model parameters by using ages estimated from scales and otoliths. These parameter estimates were used in yield‐per‐recruit simulations that predicted yield and the percentage of individuals in the cohort surviving to 380 mm (proportional size distribution [PSD] 380) or to 470 mm (PSD 470) at several levels of natural mortality and fishing mortality. Otolith‐derived age estimates were more precise; scale‐derived age estimates showed significant positive bias for fish younger than age 6 and significant negative bias for fish older than age 6. Von Bertalanffy parameter estimates were significantly different when using ages estimated from scales and those estimated from otoliths. Modeling indicated that estimates of yield and PSD 380 resulting from the two structures were similar. However, the use of scale‐derived ages resulted in underestimating the impact of fishing mortality on PSD 470 by as much as five times at low levels of natural mortality and fishing mortality. Our estimates of precision and bias were similar to other comparisons of scales and otoliths, and the results of our yield‐per‐recruit simulations are likely generally applicable for Largemouth Bass management. Trophy fishing is a common management objective, and managers relying on scale‐based age data could be less likely to adopt the restrictive harvest regulations that are critical for producing trophy Largemouth Bass. Received November 17, 2016; accepted June 22, 2017 Published online August 22, 2017

In his seminal work, Hjort (in Fluctuations in the great fisheries of Northern Europe. Conseil Parmanent International Pour L'Exploration De La Mar. Rapports et Proces-Verbaux, 20: 1–228, 1914) observed that fish population levels fluctuated widely, year-class strength was set early in life, and egg production by adults could not alone explain variability in year-class strength. These observations laid the foundation for hypotheses on mechanisms driving recruitment variability in marine systems. More recently, researchers have sought to explain year-class strength of important fish in the Laurentian Great Lakes and some of the hypotheses developed for marine fisheries have been transferred to Great Lakes fish. We conducted a literature review to determine the applicability of marine recruitment hypotheses to Great Lakes fish. We found that temperature, interspecific interactions, and spawner effects (abundance, age, and condition of adults) were the most important factors in explaining recruitment variability in Great Lakes fish, whereas relatively fewer studies identified bottom-up trophodynamic factors or hydrodynamic factors as important. Next, we compared recruitment between Great Lakes and Baltic Sea fish populations and found no statistical difference in factors driving recruitment between the two systems, indicating that recruitment hypotheses may often be transferable between Great Lakes and marine systems. Many recruitment hypotheses developed for marine fish have yet to be applied to Great Lakes fish. We suggest that future research on recruitment in the Great Lakes should focus on forecasting the effects of climate change and invasive species. Further, because the Great Lakes are smaller and more enclosed than marine systems, and have abundant fishery-independent data, they are excellent candidates for future hypothesis testing on recruitment in fish.

Conserving rare species and protecting biodiversity and ecosystem functioning depends on sound information on the nature of rarity. Rarity is multidimensional and has a variety of definitions, which presents the need for a quantitative classification scheme with which to categorize species as rare or common. We constructed such a classification for North American freshwater fishes to better describe rarity in fishes and provide researchers and managers with a tool to streamline conservation efforts. We used data on range extents, habitat specificities, and local population sizes of North American freshwater fishes and a variety of quantitative methods and statistical decision criteria, including quantile regression and a cost-function algorithm to determine thresholds for categorizing a species as rare or common. Species fell into eight groups that conform to an established framework for rarity. Fishes listed by the American Fisheries Society (AFS) as endangered, threatened, or vulnerable were most often rare because their local population sizes were low, ranges were small, and they had specific habitat needs, in that order, whereas unlisted species were most often considered common on the basis of these three factors. Species with large ranges generally had few specific habitat needs, whereas those with small ranges tended to have narrow habitat specificities. We identified 30 species not designated as imperiled by AFS that were rare along all dimensions of rarity and may warrant further study or protection, and we found three designated species that were common along all dimensions and may require a review of their imperilment status. Our approach could be applied to other taxa to aid conservation decisions and serve as a useful tool for future revisions of listings of fish species.

Egg deposition and use of restored spawning substrates by lithophilic fishes (e.g., Lake Sturgeon Acipenser fulvescens, Lake Whitefish Coregonus clupeaformis, and Walleye Sander vitreus) were assessed throughout the St. Clair–Detroit River system from 2005 to 2016. Bayesian models were used to quantify egg abundance and presence/absence relative to site‐specific variables (e.g., depth, velocity, and artificial spawning reef presence) and temperature to evaluate fish use of restored artificial spawning reefs and assess patterns in egg deposition. Lake Whitefish and Walleye egg abundance, probability of detection, and probability of occupancy were assessed with detection‐adjusted methods; Lake Sturgeon egg abundance and probability of occurrence were assessed using delta‐lognormal methods. The models indicated that the probability of Walleye eggs occupying a site increased with water velocity and that the rate of increase decreased with depth, whereas Lake Whitefish egg occupancy was not correlated with any of the attributes considered. Egg deposition by Lake Whitefish and Walleyes was greater at sites with high water velocities and was lower over artificial spawning reefs. Lake Sturgeon eggs were collected least frequently but were more likely to be collected over artificial spawning reefs and in greater abundances than elsewhere. Detection‐adjusted egg abundances were not greater over artificial spawning reefs, indicating that these projects may not directly benefit spawning Walleyes and Lake Whitefish. However, 98% of the Lake Sturgeon eggs observed were collected over artificial spawning reefs, supporting the hypothesis that the reefs provided spawning sites for Lake Sturgeon and could mitigate historic losses of Lake Sturgeon spawning habitat.