A generalist strategy, as an adaptation to environmental heterogeneity, is common in Arctic freshwater systems, often accompanied, however, by intraspecific divergence that promotes specialization in niche use. To better understand how resources may be partitioned in a northern system that supports intraspecific diversity of Lake Trout, trophic niches were compared among four shallow‐water morphotypes in Great Bear Lake (N65° 56′ 39″, W120° 50′ 59″). Bayesian mixing model analyses of stable isotopes of carbon and nitrogen were conducted on adult Lake Trout. Major niche overlap in resource use among four Lake Trout morphotypes was found within littoral and pelagic zones, which raises the question of how such polymorphism can be sustained among opportunistic generalist morphotypes. Covariances of our morphological datasets were tested against δ13C and δ15N values. Patterns among morphotypes were mainly observed for δ15N. This link between ecological and morphological differentiation suggested that selection pressure(s) operate at the trophic level (δ15N), independent of habitat, rather than along the habitat‐foraging opportunity axis (δ13C). The spatial and temporal variability of resources in Arctic lakes, such as Great Bear Lake, may have favored the presence of multiple generalists showing different degrees of omnivory along a weak benthic–pelagic gradient. Morphs 1–3 had more generalist feeding habits using both benthic and pelagic habitats than Morph 4, which was a top‐predator specialist in the pelagic habitat. Evidence for frequent cannibalism in Great Bear Lake was found across all four morphotypes and may also contribute to polymorphism. We suggest that the multiple generalist morphs described here from Great Bear Lake are a unique expression of diversity due to the presumed constraints on the evolution of generalists and contrast with the development of multiple specialists, the standard response to intraspecific divergence.

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While juvenile Atlantic goliath grouper, Epinephelus itajara (Lichtenstein, 1822), are known to depend on mangrove root structure, relationships with water properties (e.g., salinity) and depth remain unclear or understudied. Because availability of suitable mangrove habitat has been suggested as the primary bottleneck to the recovery of this threatened species in the US, we investigated habitat associations of juvenile Atlantic goliath grouper with respect to physical water properties within mangrove habitats. Our study was conducted in six coastal rivers and three canals within the Ten Thousand Islands region of southwest Florida. Results suggested that juvenile Atlantic goliath grouper differed in how they associated with specific mangrove habitats based on season and size. We found that smaller juveniles (<340 mm TL) appeared to have stronger associations to physical water characteristics than larger (≥340 mm TL) juveniles. Both large and small juveniles showed the strongest associations with DO (i.e., >3 mg L −1 ) within mangrove habitat. For small juveniles, extreme temperatures influenced habitat association; for large juveniles, extreme salinity influenced distribution. We also found evidence that juvenile Atlantic goliath grouper associated more with natural rivers over man-made canals. The present study has utility for delineating suitable mangrove habitats for protection and potentially in the design of sampling surveys that aim to estimate population abundance.

Depth is usually considered the main driver of Lake Trout intraspecific diversity across lakes in North America. Given that Great Bear Lake is one of the largest and deepest freshwater systems in North America, we predicted that Lake Trout intraspecific diversity to be organized along a depth axis within this system. Thus, we investigated whether a deep-water morph of Lake Trout co-existed with four shallow-water morphs previously described in Great Bear Lake. Morphology, neutral genetic variation, isotopic niches, and life-history traits of Lake Trout across depths (0–150 m) were compared among morphs. Due to the propensity of Lake Trout with high levels of morphological diversity to occupy multiple habitat niches, a novel multivariate grouping method using a suite of composite variables was applied in addition to two other commonly used grouping methods to classify individuals. Depth alone did not explain Lake Trout diversity in Great Bear Lake; a distinct fifth deep-water morph was not found. Rather, Lake Trout diversity followed an ecological continuum, with some evidence for adaptation to local conditions in deep-water habitat. Overall, trout caught from deep-water showed low levels of genetic and phenotypic differentiation from shallow-water trout, and displayed higher lipid content (C:N ratio) and occupied a higher trophic level that suggested an potential increase of piscivory (including cannibalism) than the previously described four morphs. Why phenotypic divergence between shallow- and deep-water Lake Trout was low is unknown, especially when the potential for phenotypic variation should be high in deep and large Great Bear Lake. Given that variation in complexity of freshwater environments has dramatic consequences for divergence, variation in the complexity in Great Bear Lake (i.e., shallow being more complex than deep), may explain the observed dichotomy in the expression of intraspecific phenotypic diversity between shallow- vs. deep-water habitats. The ambiguity surrounding mechanisms driving divergence of Lake Trout in Great Bear Lake should be seen as reflective of the highly variable nature of ecological opportunity and divergent natural selection itself.

Data‐limited approaches to managing fisheries are widespread in regions where insufficient data prevent traditional stock assessments from determining stock status with sufficient certainty to be useful for management. Where severe data limitations persist, a catch‐only approach is commonly employed, such as in the U.S. Caribbean region. This approach, however, has not received the level of scrutiny required to determine the potential long‐term risks (e.g., probability of overfishing) to fish stocks. In this study, we present a framework for comparison and implementation of data‐limited methods, including the static Status Quo approach, which uses average catch landings. Candidate species for stock evaluation were identified through a data triage and included Yellowtail Snapper Ocyurus chrysurus (Puerto Rico), Queen Triggerfish Balistes vetula (St. Thomas and St. John), and Stoplight Parrotfish Sparisoma viride (St. Croix). Feasible data‐limited methods, based on data availability and quality, included empirical indicator approaches using relative abundance (i.e., catch per unit effort) or mean length. Results from the management strategy evaluation support the use of adaptive data‐limited methods, which incorporate feedback in contrast to the static Status Quo approach. The proposed framework can help guide the development of catch advice for dynamic fisheries management in data‐limited regions.

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Specifying annual catch limits for artisanal fisheries, low economic value stocks, or bycatch species is problematic due to data limitations. Many empirical management procedures (MPs) have been developed that provide catch advice based on achieving a stable catch or a historical target (i.e., instead of maximum sustainable yield). However, a thorough comparison of derived yield streams between empirical MPs and stock assessment models has not been explored. We first evaluate trade-offs in conservation and yield metrics for data-limited approaches through management strategy evaluation (MSE) of seven data-rich reef fish species in the Gulf of Mexico. We then apply data-limited approaches for each species and compare how catch advice differs from current age-based assessment models. MSEs identified empirical MPs (e.g., using relative abundance) as a compromise between data requirements and the ability to consistently achieve management objectives (e.g., prevent overfishing). Catch advice differed greatly among data-limited approaches and current assessments, likely due to data inputs and assumptions. Adaptive MPs become clearly viable options that can achieve management objectives while incorporating auxiliary data beyond catch-only approaches.

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