On the Dynamic Nature of Omnivory in a Changing World

Gutgesell, Marie; McCann, Kevin S.; Gellner, Gabriel; Cazelles, Kévin; Greyson-Gaito, Christopher J.; Bieg, Carling; Guzzo, Matthew M.; Warne, Connor P; Ward, Charlotte; O'Connor, Reilly F; Scott, Alexa M; Graham, Brandon C; Champagne, Emily J; McMeans, Bailey

doi:10.1093/biosci/biab144

Cited by 9 publications

(20 citation statements)

References 72 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our understanding of animal diet and foraging ecology remains incomplete, due in part to biases within our theoretical and methodological frameworks (Mougi & Nishimura, 2008; Stearns, 2000). For instance, within community ecology, until recently models have neglected polyphagous species (Thompson et al, 2007), assuming they are rare, destabilizing members of food webs (Chubaty et al, 2014; Gutgesell et al, 2022). This assumption biased early research into categorizing species within a fixed dichotomy of carnivory versus herbivory separated by discrete trophic levels (Chubaty et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

Testing foraging optimization models in brown bears: Time for a paradigm shift in nutritional ecology?

Mikkelsen,

Hobson,

Sergiel

et al. 2023

Ecology

View full text Add to dashboard Cite

How organisms obtain energy to survive and reproduce is fundamental to ecology, yet researchers use theoretical concepts represented by simplified models to estimate diet and predict community interactions. Such simplistic models can sometimes limit our understanding of ecological principles. We used a polyphagous species with a wide distribution, the brown bear (Ursus arctos), to illustrate how disparate theoretical frameworks in ecology can affect conclusions regarding ecological communities. We used stable isotope measurements (δ13C, δ15N) from hairs of individually monitored bears in Sweden and Bayesian mixing models to estimate dietary proportions of ants, moose, and three berry species to compare with other brown bear populations. We also developed three hypotheses based on predominant foraging literature, and then compared predicted diets to field estimates. Our three models assumed (1) bears forage to optimize caloric efficiency (optimum foraging model), predicting bears predominately eat berries (~70% of diet) and opportunistically feed on moose (Alces alces) and ants (Formica spp. and Camponotus spp; ~15% each); (2) bears maximize meat intake (maximizing fitness model), predicting a diet of 35%–50% moose, followed by ants (~30%), and berries (~15%); (3) bears forage to optimize macronutrient balance (macronutrient model), predicting a diet of ~22% (dry weight) or 17% metabolizable energy from proteins, with the rest made up of carbohydrates and lipids (~49% and 29% dry matter or 53% and 30% metabolizable energy, respectively). Bears primarily consumed bilberries (Vaccinium myrtillus; 50%–55%), followed by lingonberries (V. vitis‐idaea; 22%–30%), crowberries (Empetrum nigrum; 8%–15%), ants (5%–8%), and moose (3%–4%). Dry matter dietary protein was lower than predicted by the maximizing fitness model and the macronutrient balancing model, but protein made up a larger proportion of the metabolizable energy than predicted. While diets most closely resembled predictions from optimal foraging theory, none of the foraging hypotheses fully described the relationship between foraging and ecological niches in brown bears. Acknowledging and broadening models based on foraging theories is more likely to foster novel discoveries and insights into the role of polyphagous species in ecosystems and we encourage this approach.

show abstract

Section: Discussionmentioning

confidence: 99%

Testing foraging optimization models in brown bears: Time for a paradigm shift in nutritional ecology?

Mikkelsen,

Hobson,

Sergiel

et al. 2023

Ecology

View full text Add to dashboard Cite

show abstract

“…The temporary nature of events such as these would lead to spatial asynchrony in resource availability (i.e., phytoplankton, zooplankton, cisco) or resource waves (e.g., pulses) that mobile consumers (i.e., lake trout) are able to capitalize on. Future research should investigate how asynchrony and variability in both theoretical and empirical multi‐trophic metacommunities contribute to an aggregate resource pool for consumers, creating what would be a consumptive PE in space and/or time (Firkowski et al, 2021; Gutgesell et al, 2022). However, more work still needs to be done to better understand how diversity, stability, and asynchrony interact across multiple trophic levels in food webs (Firkowski et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

Species portfolio effects dominate seasonal zooplankton stabilization within a large temperate lake

O'Connor

McMeans

Rooney

et al. 2022

Ecology

Self Cite

View full text Add to dashboard Cite

Portfolio effects (PEs) in ecology refer to the suite of phenomenon where the temporal variation of aggregate ecosystem properties (i.e., abundance) is lower than that of their ecosystem components. An example of this is where differential responses of species to environmental variation generate stability at higher levels of ecological organization (e.g., local community, metapopulation, metacommunity). Most of the research examining such PEs has focused on spatial or interannual variation of ecosystems; however, as global change continues to alter seasonality and ecosystem functioning, understanding the underlying food web structures that help maintain stability at multiple spatial and temporal scales is critical to managing ecological systems. Recent advances investigating diversity-stability relationships has led to the development of frameworks that incorporate a metacommunity perspective which allows for the partitioning of PEs across organizational scales (i.e., local community, metapopulation, cross-community, metacommunity) from local population dynamics (total). This partitioning yields insights into the mechanisms that generate observed PEs in nature. Here, we employed one of these recently developed frameworks on a temporally (1986)(1987)(1988)(1989)(1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018)(2019) and spatially (five sampling stations, local communities) extensive data set of zooplankton abundance (e.g., density) within a large temperate lake to investigate how temporal (seasonal) and spatial (among site) PEs influence stability within the zooplankton metacommunity. We found that seasonal asynchrony of different zooplankton species within local communities and across communities generated the vast majority of stabilization, while spatial (i.e., metapopulation) dynamics were more synchronous and contributed little to overall system stability. Furthermore, significantly positive diversity-asynchrony relationships at the total, local-and cross-community scales were found as asynchrony was positively correlated with local Shannon diversity. Last, a comparison of PEs over the time periods, during which significant local and global changes (i.e., climate warming, invasive species) have occurred suggests that PEs may be eroding, as increasingly synchronous dynamics and declining diversity in recent years have led to a rise in metacommunity variability. We end by arguing for the critical importance of understanding seasonally driven stabilizing

show abstract

“…Recent work has revealed that a diverse and complex food web can be represented by a simple repeating trophic pattern of relatively separate resource pathways coupled by higher order consumers, that is, a recursive optimal foraging problem (McCann & Rooney, 2009; Rooney et al, 2006). Effects of consumer choice at any trophic level can ripple throughout the entire ecosystem by means of functional and numerical responses, altering species composition, diversity, nutrient cycles, fecundity, and ecosystem stability, whether the consumer is a predator (Estes & Palmisano, 1974; Fortin et al, 2005; Power, 1990), an herbivore (Fox, 2011; Holomuzki et al, 2010), a parasite (Minchella & Scott, 1991), or an ominivore, feeding at different trophic levels (Gutgesell et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

“…Preference switching among alternative resources as their abundance fluctuates is expected of all generalist consumers (Abrams, 2006; Carnicer et al, 2008) and appears to be a pervasive and widespread phenomenon in ecological systems (Abrams, 2006; Carnicer et al, 2008; Kjellander & Nordström, 2003; Murdoch et al, 1975; Siddon & Witman, 2004). As well, the ability of a consumer to switch preference when resources vary asynchronously in space and time is thought to be a potent stabilizing mechanism (Gutgesell et al, 2022; Kalinkat et al, 2011; McCann & Rooney, 2009; Rooney et al, 2006; Ushio et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Addressing a potential weakness in indices of predation, herbivory, and parasitism

Adams

2023

Population Ecology

View full text Add to dashboard Cite

Quantification of predation, herbivory, and parasitism is critical to understanding the dynamics and trophic interactions of populations in an ecosystem. Such quantification can be challenging if the availability or consumption of the taxa are difficult to assess. Sometimes the consumption of a single prey, forage, or host is used as an overall index of the predation, herbivory, or parasitism for a population of interest. Occasionally, human‐manipulated baits are used to derive similar indices. However, all such indices are susceptible to influence by variation in the abundance of the preferred taxon relative to other taxa as the result of preference switching. In this article, I describe a test for preference switching (and an adjustment, if detected) that does not require availability and consumption of the prey (forage, or host) to be measured on the same scale. The ability to detect and adjust for preference switching in such situations may advance the understanding of biological preference in taxa not previously studied in this respect.

show abstract

On the Dynamic Nature of Omnivory in a Changing World

Cited by 9 publications

References 72 publications

Testing foraging optimization models in brown bears: Time for a paradigm shift in nutritional ecology?

Testing foraging optimization models in brown bears: Time for a paradigm shift in nutritional ecology?

Species portfolio effects dominate seasonal zooplankton stabilization within a large temperate lake

Addressing a potential weakness in indices of predation, herbivory, and parasitism

Contact Info

Product

Resources

About