Food web perspectives and methods for riverine fish conservation

Abstract

Food web analyses offer useful insights into understanding how species interactions, trophic relationships, and energy flow underpin important demographic parameters of fish populations such as survival, growth, and reproduction. However, the vast amount of food web literature and the diversity of approaches can be a deterrent to fisheries practitioners engaged in on-the-ground research, monitoring, or restoration. Incorporation of food web perspectives into contemporary fisheries management and conservation is especially rare in riverine systems, where approaches often focus more on the influence of physical habitat and water temperature on fish populations. In this review, we first discuss the importance of food webs in the context of several common fisheries management issues, including assessing carrying capacity, evaluating the effects of habitat change, examining species introductions or extinctions, considering bioaccumulation of toxins, and predicting the effects of climate change and other anthropogenic stressors on riverine fishes. We then examine several relevant perspectives: basic food web description, metabolic models, trophic basis of production, mass-abundance network approaches, ecological stoichiometry, and mathematical modeling. Finally, we highlight several existing and emerging methodologies including diet and prey surveys, eDNA, stable isotopes, fatty acids, and community and network analysis. Although our emphasis and most examples are focused on salmonids in riverine environments, the concepts are easily generalizable to other freshwater fish taxa and ecosystems.

Influence of riparian thinning on trophic pathways supporting stream food webs in forested watersheds

“…While we could not run a mixing model to partition aquatic and terrestrial energy sources (Finlay, 2001; Middleburg, 2014), tracking shifts in δ 13 C signatures of stream periphyton paired with our BACI study design provided a useful approach for detecting changes in response to thinning. This approach was particularly effective when combined with predator diets for detecting shifts in trophic pathways supporting energy flow in these systems across short‐ and long‐term temporal scales (Naman et al, 2022).…”

“…Uncertainty in the outcomes of riparian forest management for aquatic systems can be partially attributed to the complexity of stream–riparian systems (Baxter et al, 2005; Gregory et al, 1991; Naiman et al, 2010; Nakano & Murakami, 2001): Responses depend on and can be mediated by the food web dynamics that link streams and riparian forests (Bascompte, 2010; Power & Dietrich, 2002; Whitney et al, 2020; Wootton, 2012). Management goals that focus on the productivity of target species such as salmonid fishes can be misleading (Bellmore et al, 2017; Whitney et al, 2020), as target species are part of complex ecological networks that require an understanding of species interactions and the trophic processes supporting them (Bascompte, 2010; Naman et al, 2022). Additionally, inherent spatial and temporal variation in environmental conditions and food web structure across stream networks can lead to context dependency in biological responses (Power & Dietrich, 2002; Whitney et al, 2020).…”

“…Additionally, inherent spatial and temporal variation in environmental conditions and food web structure across stream networks can lead to context dependency in biological responses (Power & Dietrich, 2002; Whitney et al, 2020). As a result, a food web perspective that explicitly considers the trophic dynamics and structure of ecological networks provides a more holistic understanding of stream ecosystems and can more effectively address the underlying mechanisms driving whether riparian thinning enhances aquatic productivity in forested streams (Bascompte, 2010; Bellmore et al, 2017; Benjamin et al, 2022; Naiman et al, 2012; Naman et al, 2022).…”

Graph embedding and transfer learning can help predict potential species interaction networks despite data limitations

“…As information on networks is increasingly leveraged for conservation actions (see e.g. Eero et al, 2021;Naman et al, 2022;Stier et al, 2017), the need to appraise and correct biases that are unwittingly propagated to algorithms when embedded from the original data is immense. These considerations are even more urgent in the specific context of biodiversity data.…”

Contrasting energy pathways suggest differing susceptibility of pelagic fishes to an invasive ecosystem engineer in a large lake system

“…Understanding food web structure and energy flow is critical for successful management and conservation of ecosystems threatened by anthropogenic change (Vander Zanden et al, 2006;Naman et al, 2022). For example, species invasions often lead to ecological regime shifts and have major impacts on ecosystem services (e.g., Charles and Dukes, 2007;Pejchar and Mooney, 2009); therefore, understanding the effects of invaders may be one of the most important ways managers can anticipate and effectively respond to ecosystem change.…”