Every animal must acquire a proper balance of macronutrients to maximize their performance (Simpson and Raubenheimer, 2012). For all animals, protein is the main building block for growing tissues, and lipids and carbohydrates (non-protein) are the primary energy fuels. Comparative studies show that different animal species have a wide range of unique protein:carbohydrate (and/or lipid) targets that optimize growth, survival, and reproduction, and these are often thought of as species-specific (Behmer and Joern, 2008; Behmer, 2009; Hewson-Hughes et al., 2013). While a few studies indicate developmental effects on macronutrient intake, we lack a clear understanding about how and why ontogeny or body size affect macronutrient consumption and intake targets (Ojeda-Avila et al., 2003; Peters, 1983; Wang et al., 2019). To address this lack, we determined the effect body mass throughout ontogeny on macronutrient (protein and carbohydrate) intake and growth rate for the polyphagous and transboundary migratory pest, Schistocerca cancellata (Serville, 1838), the South American locust, and integrated our results with prior studies of this topic in animals.

Foraging decisions are often driven by the need to balance protein (p) with non-protein (np) energy because these macronutrients make up the vast majority of a consumer’s diet and food sources rarely match the balance needed. The relative macronutrient requirements of individuals across development and the factors that influence these intake targets have profound implications for population dynamics and ecosystems, particularly for herbivores. For example, in many cases, growth and population levels of freshwater invertebrate herbivores are limited by protein (or more specifically, essential amino acid) availability (Fink et al., 2011). In contrast, late instars of grasshoppers and some lepidopteran caterpillars have low protein to carbohydrate targets due to their high energy requirements for adult flight (Lee et al., 2004; Talal et al., 2020). In these cases, low nitrogen environments which harbor low-protein, high-carbohydrate plants promote outbreaks and devastating locust migratory swarms (Cease et al., 2012). Animals restricted to feeding on foods that diverge from their required p:np balance can experience pronounced performance deficits in development time, mass, reproduction, and survival (Behmer and Joern, 2008; Behmer, 2009; Raubenheimer et al., 2022; Simpson and Raubenheimer, 2012; Talal et al., 2020).

The Geometric Framework for Nutrition (Simpson and Raubenheimer, 2012) was developed to study how organisms balance multiple nutrients, and identifying intake targets is a key principle. Most organisms will self-select a balance of nutrients, and this can be tested by giving individuals a choice between two or more foods differing in the ratio of two or more nutrients. Individuals differentially eat the diets to achieve an intake target. Macronutrient targets can vary across species. For example, cats selectively consume and perform better on more protein-biased diets (52p:48np) than dogs, for which a 30p:70np diet is optimal (Hewson-Hughes et al., 2013; Hewson-Hughes et al., 2011). Such variation in nutritional targets can occur even among closely related species, and we are beginning to understand some of these patterns. For example, late-instar juveniles of seven species of congeneric grasshoppers that share the same habitat exhibit widely different species-specific p:np targets that maximize their growth performance (Behmer and Joern, 2008). Domestic dogs are omnivorous while wolves are carnivorous, likely due to the availability of diverse foods domesticated dogs can obtain from humans (Bosch et al., 2015). Within arthropods, predators prefer food with relatively more protein than their herbivorous prey, whose food is often lower in protein concentration (Wilder et al., 2013).

Some evidence suggests that intake of protein relative to carbohydrate (and or lipids) may generally decrease through ontogeny. Stable isotope analysis of tooth and skin suggested that mass-specific protein consumption declines during ontogeny in bottlenose dolphins (Tursiops truncates, Knoff et al., 2008). Similarly, in turtles (Trachemys scripta, Bouchard and Bjorndal, 2006), lizards (Stellagama stellio, Karameta et al., 2017), and sturgeons (Acipenser persicus, Babaei et al., 2011), food preference, digestive efficiency, and digestive enzymatic activities indicate decreasing mass-specific protein assimilation and need as ontogeny progresses. Decreases in the ratio of p:np in milk through ontogeny also suggest that offspring nutritional requirements shift with age. In northern elephant seals (Mirounga angustirostris), the lipid concentration of milk increases by approximately fivefold during 30 days of lactation (Riedman and Ortiz, 1979), while in humans, the protein concentration of milk decreases as lactation progresses (Ballard and Morrow, 2013; Bauer and Gerss, 2011). Tammar wallabies provide milk with a lower p:np ratio to older offspring, even when nursing two offspring simultaneously (Nicholas et al., 1997). A few studies have tested for an effect of ontogeny or body mass on preferred p:np consumption and utilization in invertebrates, but generally only over a short span of the life cycle. A study of brown-banded cockroaches showed that the self-selected ratio of casein:glucose decreased from third to final instar (Cohen et al., 1987). Lepidopteran caterpillars decrease p:np consumption over three instars (Stockhoff, 1993). We lack studies of how macronutrient targets are affected across whole-ontogeny or across broad body size ranges of species, and these are necessary to provide an understanding of whether a decline in mass-specific protein intake is a general pattern among animals.

Macronutrient consumption can also vary in response to environment and activity levels. For example, viral-infected caterpillars shifted toward a new self-selected macronutrient ratio that maximized survival (Cotter et al., 2011). During winter months (cold weather), golden snub-nosed monkeys increased their daily non-protein energy intake, probably due to the increased cost of thermoregulation (Guo et al., 2018). Many migratory birds adjust their nutrition to facilitate adequate fat accumulation (Bairlein, 2002). In early development, human energy requirements are highly correlated with basal metabolic rate and growth processes (0–6 months) (Butte et al., 2002). However, later when a child increases their physical activity, energy requirements correlate highly with activity level (reviewed in Savarino et al., 2021). For example, a single high-intensity exercise increases lipid consumption in humans (Klausen et al., 1999).

Based on this literature, we hypothesized that animals would steadily reduce protein consumption during ontogeny because mass-specific growth rate declines (Brown et al., 2004; West et al., 2001; White et al., 2022), causing a progressive decrease in the consumption of protein relative to carbohydrate. We tested this hypothesis using South American locusts, S. cancellata. We predicted that mass-specific protein consumption would decrease strongly during development, in tight correlation with a decrease in mass-specific growth rate and a decrease in the protein:carbohydrate intake ratio, and that these relationships would hold across all animals because growth rate scales hypometrically across animals of different body sizes as well as during ontogeny (Hatton et al., 2019; Peters, 1983; West et al., 2001). To partially test whether our lab results could predict the macronutrient requirements in more ecological-relevant conditions, we also compared intake targets between lab-reared animals with field-collected locusts at one developmental stage.

Overall, our results demonstrate that macronutrient targets change predictably from high protein:carbohydrate consumption in the young toward increasingly lower protein:carbohydrate intake targets during ontogeny in S. cancellata. From first instar to adult for S. cancellata, mass-specific protein consumption rate decreased fourfold with little change in mass-specific carbohydrate consumption (Figure 1). The decrease in mass-specific protein consumption rate was tightly correlated with a decline in specific growth rate, likely explaining the shift in protein requirements (Figure 2A). However, intake targets measured in the lab did not well-predict intake targets in the field, as protein demand did not differ between lab and field populations, but carbohydrate consumption rate was >50% higher in field populations (Figure 1).

It is important to note that we have not measured the fitness consequences of variation in diet composition across the various locust instars, so we cannot claim that the observed decline in protein:carbohydrate intake ratio is beneficial. This is a complex issue because the fitness consequences of larval diet can be measured in many ways, including growth and survival of the larvae, and adult reproduction and longevity; and these traits do not always correlate (Sentinella et al., 2013). However, the fact that many other studies have found that measured intake targets optimize fitness suggests that this pattern is a beneficial one (Raubenheimer and Simpson, 2018).

Here it is demonstrated for the first time that protein consumption rates decrease during ontogeny in a predictive way with animal mass. In our experiments with S. cancellata, we cannot determine the extent to which the observed pattern is due to developmental or body mass changes, though the observation that the pattern is similar to that seen across species differing in mass suggests that variation in body size is responsible. Thus, protein consumption can be added to the list of traits that scale predictably with body size (Schmidt-Nielsen, 1995; Sibly et al., 2012). The hypometric scaling of protein consumption across species is consistent with the general hypometric scaling of growth rates across animals (Hatton et al., 2019). Though ontogenetic slopes of protein consumption on mass were much lower than the cross-species pattern in a few groups, including cats and pigs, it will be interesting to determine whether such variation relates to interspecific variation in the scaling of ontogenetic growth and lifespan.

Assuming that energy needs and consumption are primarily set by metabolic rate, we would expect that mass-specific non-protein consumption to decrease with both animal mass and age due to the generally observed hypometric scaling of metabolic rates across animal taxa (Harrison et al., 2022; White et al., 2022). In locusts, we demonstrated that carbohydrate consumption scaled hypometrically, but with a slope very close to 1, a much higher mass-scaling exponent than observed for protein consumption (Figure 3A), but in the range of reported scaling for resting metabolic rate (0.77–1) for orthopterans (Fielding and DeFoliart, 2008; Greenlee and Harrison, 2004). Likely, in locusts, carbohydrate consumption of older individuals is increased due to the increase in mass-specific lipid stores that occurs in older juveniles and adults, as stored lipids are mainly synthesized from ingested carbohydrates (Talal et al., 2021). In addition, we demonstrated a positive correlation between mass-specific carbohydrate consumption rate and specific growth rate, with the highest of both parameters in early development (Figure 2B). This could be explained by the energy cost of new tissue growth and new protein synthesis, which are the highest in early development (Li et al., 2019; Pace and Manahan, 2007), and match the protein requirements during this period of time.

An important goal for the field of nutritional ecology is to predict nutritional needs, foraging behavior and strategies, and consequences of nutritional imbalance for animals in the field (Behmer and Joern, 2008). Relative to the lab population, we measured a 50–90% increase in carbohydrate consumption rates for field-collected fifth- and sixth-instar nymphs. In contrast, protein consumption rates did not vary between lab and field in our study. This may not be true under every ecological condition; for example, poor resource conditions that reduce growth will likely also reduce protein consumption. Nonetheless, these data support the hypothesis that protein consumption rates of animals in good field conditions may be predicted from results with lab-reared animals. There are multiple reasons why carbohydrate consumption in the field may be poorly predicted by laboratory consumption data. Consumption patterns can reflect their past feeding history (Marmonier et al., 2000; Wiggins et al., 2018), which was not known in the case of our field-captured animals. In the lab, consumption rates were measured from the first day of the instar, but likely over a later part of the instar in the field-collected animals, potentially affecting the results. Captive animals usually do not need to travel long distances to forage, which can be energetically expensive and cause long-term effects on resting metabolic rates (Bergman et al., 2001). Studies of monkeys and apes have demonstrated that decreases in foraging activity in captivity may promote metabolic suppression, diabetes, and obesity (reviewed in Bellisari, 2008). Increased energy demands and energy metabolism in field animals may also be due to a past history of consumption of tougher, better chemically defended plants (Clissold et al., 2009; Maskato et al., 2014). Field animals may be more likely to be coping with pathogens, and immune responses can elevate metabolic rates in insects (Catalán et al., 2012; Freitak et al., 2003). In addition, adaptation to lab conditions over multiple generations in captivity may reduce metabolic rates and carbohydrate consumption (Garland et al., 1987; Latorre et al., 2020). Also, it is important to note that because we only tested one instar in the field, we have not demonstrated that hypometric scaling of protein consumption occurs under field conditions, though this seems likely. Future studies will be necessary to confirm this, and to decipher the mechanisms that elevate metabolic rates and carbohydrate consumption for locusts and other animals in the field.

All data generated or analyzed during this study are included in the manuscript and supporting files; source data files have been provided for Figures 1—3.

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Author details

1. Stav Talal

   School of Life Sciences, Arizona State University, Tempe, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing

   For correspondence

   stalal@asu.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-1181-5291

2. Jon F Harrison

   School of Life Sciences, Arizona State University, Tempe, United States

   Contribution

   Conceptualization, Resources, Supervision, Funding acquisition, Investigation, Methodology, Project administration, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-5223-216X

3. Ruth Farington

   School of Life Sciences, Arizona State University, Tempe, United States

   Contribution

   Investigation, Methodology, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

4. Jacob P Youngblood

   1. School of Life Sciences, Arizona State University, Tempe, United States
   2. Department of Biology, Southern Oregon University, Ashland, United States

   Contribution

   Investigation, Methodology, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

5. Hector E Medina

   Dirección de Sanidad Vegetal, Buenos Aires, Argentina

   Contribution

   Investigation, Methodology, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

6. Rick Overson

   School of Life Sciences, Arizona State University, Tempe, United States

   Contribution

   Investigation, Methodology, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

7. Arianne J Cease

   1. School of Life Sciences, Arizona State University, Tempe, United States
   2. School of Sustainability, Arizona State University, Tempe, United States

   Contribution

   Conceptualization, Resources, Supervision, Funding acquisition, Investigation, Methodology, Project administration, Writing – review and editing

   Competing interests

   No competing interests declared

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