The development and application of fish bioenergetics models have flourished in recent years, due in part to the complexity of the issues being faced by fisheries biologists. As with any model, the accuracy of bioenergetics models can be hampered by uncertainty in model parameters. A review of the literature showed that field and laboratory tests of bioenergetics models often result in poor agreement between model predictions and independent data. Nonetheless, bioenergetics modeling continues to be used to make important management decisions. Recent tests of model predictions have shown that parameter uncertainty is influenced by factors such as feeding rate, physiological adaptations, and prey composition and abundance. In an attempt to reduce the uncertainty in modeling applications, we propose a framework that highlights the importance of (1) model evaluation, (2) hypothesis-based parameter testing, and (3) improved communication between model developers and model users. Adherence to this framework will help reduce uncertainty in modeling applications and simultaneously contribute to a broader knowledge of fish physiology and feeding ecology.

Bioenergetics modeling is a widely used tool in fisheries management and research. Although popular, currently available software (i.e., Fish Bioenergetics 3.0) has not been updated in over 20 years and is incompatible with newer operating systems (i.e., 64‐bit). Moreover, since the release of Fish Bioenergetics 3.0 in 1997, the number of published bioenergetics models has increased appreciably from 56 to 105 models representing 73 species. In this article, we provide an overview of Fish Bioenergetics 4.0 (FB4), a newly developed modeling application that consists of a graphical user interface (Shiny by RStudio) combined with a modeling package used in the R computing environment. While including the same capabilities as previous versions, Fish Bioenergetics 4.0 allows for timely updates and bug fixes and can be continuously improved based on feedback from users. In addition, users can add new or modified parameter sets for additional species and formulate and incorporate modifications such as habitat‐dependent functions (e.g., dissolved oxygen, salinity) that are not part of the default package. We hope that advances in the new modeling platform will attract a broad range of users while facilitating continued application of bioenergetics modeling to a wide spectrum of questions in fish biology, ecology, and management.

We investigated zooplanktivory and nutrient regeneration by the opossum shrimp Mysis relicta and kokanee Oncorhynchus nerka to assess the relative roles of these planktivores in oligotrophic food webs. Using bioenergetic models and clearance rate estimates, we quantified phosphorus (P) excretion rates and consumption of cladoceran prey by Mysis and kokanees in Lake Pend Oreille, Idaho, from 1995 to 1996. Consumption of cladoceran prey by Mysis was 186 kg·ha Ϫ1 ·year Ϫ1 , whereas consumption by kokanees was less than one quarter as much, at 45 kg·ha Ϫ1 ·year Ϫ1 . Similarly, Mysis excreted approximately 0.250 kg P·ha Ϫ1 ·year Ϫ1 during nighttime migrations into the upper water column, whereas P excretion by kokanees was less than one third as much, at approximately 0.070 kg P·ha Ϫ1 ·year Ϫ1 . On a volumetric basis, nocturnal excretion by Mysis ranged from 0.002 to 0.007 g P·L Ϫ1 ·d Ϫ1 and accounted for less than 1% of the soluble reactive P typically measured in the upper water column of the lake. Hence, nutrient recycling by Mysis may be limited in the upper water column because of the nocturnal feeding habitats that constrain Mysis to deeper strata for much of the day. In spring and autumn months, low abundance of cladoceran prey coincided with high seasonal energy requirements of the Mysis population that were linked to timing of annual Mysis brood release and abundance of age-0 Mysis. Predation by Mysis accounted for 5-70% of daily cladoceran standing stock, supporting the notion that seasonal availability of cladocerans may be regulated by Mysis predation. In lakes where Mysis experience little predation mortality, they likely play a dominant role in food web interactions (e.g., trophic cascades) relative to planktivorous fishes. Biotic mechanisms, such as successful predator-avoidance behavior, omnivorous feeding habits, and seasonal variation in Mysis biomass, enhance the ability of Mysis to influence food web interactions from an intermediate trophic level.