Climate warming may alter predator–prey interactions and predator feeding behaviour due to increased metabolic demands. How predators meet these increased demands may depend on trade-offs in prey energy content and body size, handling time and other functional constraints.
We tested hypotheses associated with these trade-offs with the predatory mite Stratiolaelaps scimitus, and three prey that differed in body size, energy content, and defenses (Folsomia candida, Oppia nitens, and Carpoglyphus lactis). We estimated metabolic rate, predation in choice and no choice feeding trials, movement rate, and lipid and protein content for all four species at 16°C and 24°C. We used these data to estimate the predator's energy demands and compared these to estimated energy intake in the choice feeding trials.
Predators had greater metabolic demands at 24°C than at 16°C, but temperature did not affect predator or prey movement rates. Warming decreased lipid content, but not protein content, of all three prey species, leading to lower energy content for C. lactis and O. nitens, but not F. candida. In both feeding trials at 24°C, predators increased their feeding on the smaller, energy-poor C. lactis, but not the larger, energy-rich F. candida, resulting in lower estimated energy intake. S. scimitus did not feed on O. nitens at either temperature.
Predators increasingly fed on small-bodied prey under warming and not the large-bodied prey despite the potential for greater energetic gains from larger prey. We posit that predators minimized energy lost during feeding through lower handling costs associated with C. lactis, rather than maximize energy gain. We conclude that selection of prey based on body size changes with temperature as a trade-off for predators to balance increased metabolic demands. As predators provide top-down control and regulate energy flow through the consumption of their prey, changes to predator feeding behaviour with climate warming may affect food web dynamics and ecosystem-level processes.

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1 INTRODUCTION

Predators expend energy searching for, capturing and handling their prey. Optimal foraging theory predicts that predators should select and prefer prey that maximizes energy intake while balancing the energetic costs associated with prey capture and handling, alongside digestion and metabolism (Stephens et al., 2007; Stephens & Krebs, 1986). Specifically, predators may select prey according to their nitrogen: carbon ratio (Jensen et al., 2012), energy density (Kiyota et al., 2013), body size (Johnson et al., 2012) or defences (Llewelyn et al., 2012). However, these prey characteristics are not necessarily independent of one another. For instance, body size influences prey movement rate, which in turn affects capturability and handling time (Brose et al., 2008; Hirt et al., 2017), suggesting that prey body size strongly factors into predator foraging decisions.

Increased temperatures associated with climate warming affect predator–prey dynamics. Because warming increases ectotherm metabolic rates, the balance between energetic costs and energetic gains shifts (Rall et al., 2010; Vucic-Pestic et al., 2011) and can increase both predator and prey movement rates (Kruse et al., 2008) and change nutrient demands (Bestion et al., 2019). Acclimation to warming may buffer against rising metabolic demands (Sentis et al., 2015; Sohlström et al., 2021), or predators can simply eat more (Ramachandran et al., 2021; Walker et al., 2020), and/or prioritize the prey that are easiest to subdue and capture. For example, Frances and McCauley (2018) found that intraguild predation of dragonfly larvae under warming shifted the body size distribution towards larger-bodied individuals of three species, as individuals increasingly fed on smaller-bodied conspecifics. The increased feeding on small-bodied prey is possibly because smaller prey typically have slower movement rates than their larger predators (Alexander, 1982; Peters, 1983) making those prey easier to catch. Consuming small-bodied prey also lowers handling times for predators (Brose et al., 2008; Rall et al., 2012), making them less energetically costly to capture and feed on. However, because smaller prey are less energy-rich than larger prey (Portalier et al., 2019), predators need to consume more small-bodied prey to satisfy their energetic demands. In addition to increasing metabolic demands, predators' need to balance changing demands for carbon (to fuel metabolism) and nitrogen (for growth and maintenance) (Bestion et al., 2019; Lee et al., 2015; Lemoine et al., 2013). Thus, climate warming produces trade-offs for ectothermic predators, which must choose between consuming easy-to-capture, small-bodied prey or difficult-to-capture, large-bodied prey of higher nutritional value.

Warming-induced shifts in predator feeding behaviour and prey preference may affect multiple trophic levels. For instance, if ectothermic predators increase their feeding rates under warming then top-down control might increase, shifting control of primary production to predators (Kratina et al., 2012; Shurin et al., 2012) and producing trophic cascades towards basal resources (Lang et al., 2014). However, changing predator feeding behaviour may also have unexpected predator–prey outcomes that affect other ecosystem-level processes. For example, collembolan abundance in the Arctic tundra increased with wolf spider density under warming, possibly due to changes in predator feeding behaviour (Koltz et al., 2018). These changes corresponded with slower decomposition rates as greater abundances of collembolans likely surpressed fungal biomass, one of the main decomposers in below-ground systems. Thus, developing a better understanding of how predators alter their feeding behaviour under warming is key to predicting changes to overall food web structure and interactions.

In this study we examined how an ectothermic predator alters its feeding rate and behaviour to compensate for increased metabolic demands under warming by conducting choice and no choice feeding trials and offering predators three prey species that differed in capturability, energy content and defences. Optimal foraging theory suggests predators should select for prey based on trade-offs related to the energetic gains versus losses related to handling and consumption. We tested three possible outcomes in our feeding trials. First, if predators increase their overall feeding rate to compensate for the increased metabolic demands, then the survival rate of all three prey species will decrease with increasing temperature. Second, if predators alter their feeding behaviour under warming to minimize the cost of feeding, then predators will feed more on small-bodied prey under warming because they are easier to capture and consume. Third, if predators alter their feeding behaviour under warming to maximize energy intake, then predators will feed more on large-bodied prey under warming.

2 MATERIALS AND METHODS

2.1 Predator and prey species

We used the predatory mite Stratiolaelaps scimitus and three prey species in our experiment: one collembolan, Folsomia candida, and two mites: Oppia nitens and Carpoglyphus lactis. S. scimitus is a medium-sized (600–700 μm in length) generalist soil predator that actively feeds on a wide variety of soil invertebrates (Cabrera et al., 2005; Xie et al., 2018) using piercing-sucking extra-oral digestion. The prey we used differ in body size, shape, as well as defensive traits. F. candida is large (adult body length can reach 2,000 μm; Fountain & Hopkin, 2005) and is readily consumed by mesostigmatid predators (Jensen et al., 2019; Thakur et al., 2017). Like many Collembola, F. candida can escape predators by jumping using its furcula (Fountain & Hopkin, 2005). O. nitens is a well-sclerotized, medium-sized oribatid mite (~510 μm; Fajana et al., 2019), while the astigmatid C. lactis is small (body length ~ 300 μm) and has no known defences (Zhan et al., 2017).

We maintained cultures of F. candida and O. nitens from Environment and Climate Change Canada on a dry yeast (Active Dry Yeast, Fleischmann's Instant Yeast) diet in sterilized soil. We purchased and maintained cultures of C. lactis from Koppert Canada Limited on dry wheat bran spiked with small pieces of dried apricot. We also purchased S. scimitus from Koppert Canada Limited; cultures were shipped with Tyrophagus putrescentiae as prey, the supply of which was exhausted 7 days after arrival. Thereafter, we maintained S. scimitus cultures on C. lactis for the duration of the experiment. Because >95% of individuals in our S. scimitus cultures were female, we only used adult females in our feeding trials. We maintained cultures of our animals in plastic containers of various sizes. We added food and moistened culture media once per week for F. candida and O. nitens cultures, and twice per week for S. scimitus. We moistened C. lactis cultures at the start but did not water cultures again to limit potential mould growth on bran. The dried apricot offered at the beginning of culturing supplemented their diet for the entire experiment.

We kept predator and prey cultures in B.O.D. Low-temperature incubators (VWR Model 2005) at 16°C or 24°C (±0.5°C) with 60%–90% relative humidity in constant darkness for at least one full generation (5 weeks for F. candida, O. nitens and S. scimitus and 3 weeks for C. lactis), before moving them to a GCHA-10 Environmental Growth Chamber at 16°C or 24°C (±0.5°C) with 40%–70% relative humidity in constant darkness 1 week prior to our experiments. Switching from incubators to the growth chamber allowed us to measure movement rate and conduct the feeding experiments within the same apparatus.

2.2 Stop-flow respirometry

We used stop-flow respirometry to measure CO₂ production at 12°C, 16°C, 20°C, 24°C and 28°C of S. scimitus individuals that we had maintained at 16°C or 24°C (Smith et al., 2021). We only included data for 16°C-maintained S. scimitus measured at 16°C, and 24°C-maintained S. scimitus measured at 24°C; but we present the entire temperature–CO₂ relationship in Supplementary Information Figure S1. We measured the CO₂ production of groups of 25 adult female S. scimitus, with four replicates at each temperature. S. scimitus were in chambers consisted of c. 3 cm lengths of Bev-A-Line V tubing (Cole-Parmer) in a temperature-controlled Peltier cabinet (PELT-4; Sable Systems International; SSI). We equilibrated each group of animals for 30 min at each test temperature and flushed each chamber with dry, CO₂-free air for 10 min prior to recording. We included a blank chamber when measuring CO₂ production to act as a control for our four experimental chambers and used an RM8 multiplexor (SSI) to manage air flow. We allowed S. scimitus to respire in the chambers for 230 min before sequentially flushing air through a LiCor Li7000 infrared gas analyser (Lincoln, NE, USA) at 200 ml/min against a baseline stream of dry, CO₂-free air to measure the volume of accumulated CO₂. We collected data in Expedata software (ver. 1.8.5.; SSI) via a UI2 interface (SSI) and estimated rate of CO₂ production (V̇CO₂) by dividing the volume of CO₂ produced by the duration we sealed each chamber.

We converted V̇CO₂ to estimated energy demands during the feeding trials for S. scimitus individuals (mJ 8 hr⁻¹ individual⁻¹) to gauge energy lost through respiration versus the energy intake by predators when feeding. Briefly, we converted V̇CO₂ into V̇O₂ by dividing V̇CO₂ by an assumed respiratory quotient of 0.8 (Lighton, 2008). We then multiplied V̇O₂ by the oxyjoule equivalent (20.13 J/ml) to calculate metabolic rate (J/s), which we then converted to estimate energy demands during the feeding trials (mJ 8 hr⁻¹ individual⁻¹; see Supplementary Methods for more details).

2.3 Lipid and protein content

We measured the total neutral lipids and soluble protein of all taxa (C. lactis, F. candida, O. nitens and S. scimitus) after acclimation to 16°C or 24°C using methods adapted from Williams et al. (2012). For each species, we pooled individuals into samples of 0.3–2.5 mg wet mass, which included both adult and juveniles of C. lactis and F. candida, but only adults for O. nitens and S. scimitus. For total neutral lipids, we homogenized tissue and extracted lipids in 2.5 ml of Folch reagent [2:1 chloroform: methanol (v:v) mixture containing 0.1% butylated hydroxytoluene (w/v, BHT)]. We did not detect cholesterol during preliminary analyses, so we added 100 μl of 1 mg/ml cholesterol in chloroform (Sigma-Aldrich) to every sample as an internal standard to correct for lipid lost during extraction. We vortexed and centrifuged samples (2,000 g for 15 min), then added 1 ml of 0.25% KCl to each sample before incubating at 70°C for 10 min. After incubation, we collected the organic phase, containing the neutral lipids, and dried it under a stream of nitrogen gas. Samples were then reconstituted in 100 μl of Folch reagent and stored at −20°C until analysis.

We dried samples again before reconstituting lipid samples in 50 μl chloroform. We separated neutral lipid classes in triplicate on chromarods (Shell-USA) in a development tank of 49:21:0.35 benzene: chloroform: formic acid for 45 min. We used a known standard mixture to identify classes of neutral lipids in our samples by comparing the retention time of individual peaks (Williams et al., 2011). We measured the cholesterol esters (CEs), triacylglycerols (TAGs) and non-esterified ‘free’ fatty acids (FFAs), as we detected them in our samples, using three standard curves [Triarchin (TCI), triplamitin (Sigma-Aldrich) and triolein (Sigma-Aldrich) mixed equally into a TAG standard; cholesterol palmitate (Sigma-Aldrich) as a CE standard; and stearic and palmitic acid (Sigma-Aldrich) mixed equally into a FFA standard]. We quantified these lipids using an Iatroscan MK-6 TLC-FID (thin-layer chromatography–flame ionization detection) at a scanning speed of 3 cm/s and flow rates of 2 L/min air and 160 ml/min hydrogen and normalized each value to our cholesterol internal standard (Supplementary Information Figure 2). We had three biological replicates for each taxon at each temperature but discarded one replicate of O. nitens at 24°C because we did not detect FFAs in the sample.

We used a bicinchoninic acid (BCA) assay (Thermo Fisher Scientific; Williams et al., 2012) to quantify total soluble protein content of each taxon. We homogenized groups of animals in 40 μl 0.05% Tween-20 before centrifuging (600 g, 5 min), and diluting 5 μl of supernatant in 40 μl 0.05% Tween-20. We added 200 μl of BCA reagent [50:1 bicinchoninic acid: 4% copper(II) sulphate w/w in water] and incubated overnight at room temperature (c. 21°C). We read absorbance at 562 nm and compared our values to a bovine serum albumin standard (Sigma-Aldrich; 0.025 to 2 mg/ml in 0.05% Tween-20). For total soluble protein content, we had three technical replicates for each of three biological replicates for each taxon at each temperature.

Finally, we used average soluble protein and lipid concentration (total mg / mg of sample) values at each temperature (16°C and 24°C) to estimate the total energy content of an average-sized individual (in mJ/individual) for each species. We used length-mass conversion formulae to estimate the body mass of our four species based on species description and available literature (see Supplemental Methods). We calculated energy content by assuming an energy density of 17.8 J/mg for soluble protein and 39.3 J/mg for lipids (Schmidt-Nielsen, 1990). For each species, we multiplied their estimated body mass by the concentration of lipids and protein with their respective energy densities to calculate their energy content at 16°C and 24°C. For more details on how we calculated energy content of each taxon, see the Supplemental Methods.

2.4 Movement rate

We measured the movement rate of all four species within a given time at each acclimation temperature using protocols adapted from Drosophila studies (Chang et al., 2006; Simon et al., 2009) to determine the speed of predators, relative to their prey. We placed an individual animal on a printed grid (2 × 2 mm cells) covered by a 3D-printed ring (height: 5 mm) with a 2 mm thick glass covering. We varied the diameter of the ring between predator (6 cm) and prey (4 cm) to accommodate the faster movement rates of the predators and give individuals more interior space to move in. We recorded total movement of individuals inside the GCHA-10 Environmental Growth Chamber using a Nikon D610 digital SLR camera paired with the AF-S Micro NIKKOR 105 mm1:2.8G ED lens with a red LED light illuminating the grid. We recorded 60 s videos to ensure at least one continuous period of 15 to 30 s of constant movement (see Supplementary Information; SI Image 1A and B) with a clear view of both the individual and the grid lines. We scored the total movement of predators and prey by counting the number of cell lines each individual crossed. We scored the same 15–30 s video clip three times and recorded the mean number of lines crossed and measured 11–12 replicates of total movement for each taxon at 16°C and 24°C.

2.5 Feeding assays

We conducted choice (three prey) or no choice (single prey) feeding trials for adult female S. scimitus in constant darkness at 16°C or 24°C in the GCHA-10 Environmental Growth Chamber. To ensure predators would feed during the trials, we deprived individual predators of food for 3 days prior to feeding trials in constant darkness in 1.5 ml microcentrifuge tubes with a moist piece of filter paper to prevent desiccation of predator mites. We used predator and prey individuals of roughly similar size for the feeding trials at both temperatures. This consisted of adult O. nitens and a mixture of adult and juveniles for C. lactis and F. candida in feeding trials. We selected F. candida individuals that were the same size or larger than S. scimitus (>700 μm body length), with individuals between 700 μm and 2,000 μm long.

The feeding arena consisted of a 40 mm diameter petri dish containing a solid substrate of 9:1 plaster of Paris to activated charcoal, where we added four drops of distilled water to maintain humidity in the arena. We observed feeding through a 5 × 5 cm glass covering secured to the top of the petri dish to stop animals from escaping (Supplementary Information, SI Image 2). In the choice feeding experiment, we placed five individuals of each prey species (C. lactis, F. candida and O. nitens) and one S. scimitus (15 prey: 1 predator) into the feeding arena for 8 hr. In the no choice feeding experiment, we placed five individuals of a single prey species into an arena with a single S. scimitus (5 prey: 1 predator) for 8 hr. We recorded the number of live prey remaining every 30 min to determine the survival rate of each prey species. We completed 9–10 choice trials and 8–12 no-choice trials for each prey species at each temperature.

2.6 Estimated energy intake

We estimated the energy intake (in mJ 8 hr⁻¹ individual⁻¹) for each S. scimitus individual in the choice feeding trials at 16°C and 24°C by multiplying the feeding rate of the individual predator by the change in mass of a predator (post feeding; see Supplementary Methods and Table S1 for details), along with the energy density of their prey and the assimilation efficiency of predators (Equation 1):

I_{T} = \sum_{j}^{T} (F_{j, T} \times C_{j, T} \times E_{j, T}) \times Ae

(1)

where I = the energy intake in 8 hr by a single S. scimitus (mJ 8 hr⁻¹ individual⁻¹) at temperature T (16°C or 24°C) feeding on all prey, F = feeding rate (number of prey individuals∙8 hr⁻¹) of S. scimitus at temperature T (16°C or 24°C) for a given prey j (C. lactis or F. candida), C = the change in body mass (μg prey eaten⁻¹) for S. scimitus at temperature T (16°C or 24°C) when feeding on prey j (C. lactis or F. candida; Supplementary Methods and Table S1), E = the energy density (mJ/μg) at temperature T (16°C or 24°C) for prey j (C. lactis or F. candida; Table 1). We assumed the assimilation efficiency (Ae) for S. scimitus to be 0.85 (Jochum et al., 2017).

TABLE 1. Estimated body mass and lipid and protein concentration of taxa (Stratiolaelaps scimitus, Folsomia candida, Carpoglyphus lactis, Oppia nitens) used to calculate energy content and energy density after chronic exposure to 16°C and 24°C. We calculated energy content by assuming an energy density of 17.8 J/mg for protein and 39.3 J/mg for lipid (Schmidt-Nielsen, 1990)

Taxa	Estimated body mass (μg)	Temperature (°C)	% lipid	% protein	Energy content (mJ/individual)	Energy density (mJ/μg)
S. scimitus	38.3	16	9.6	9.2	207.2	5.4
S. scimitus	38.3	24	2.4	10.9	110.4	2.9
F. candida	28.7	16	13.8	13.6	225.1	7.8
F. candida	28.7	24	11.0	24.5	249.2	8.7
C. lactis	3.76	16	10.5	5.4	19.1	5.1
C. lactis	3.76	24	1.6	7.1	7.1	1.9
O. nitens	17.4	16	18.2	3.5	135.3	7.8
O. nitens	17.4	24	4.9	4.5	47.4	2.7

2.7 Statistical analysis

We used a one-way analysis of variance (ANOVA) to determine the effect of temperature (16°C or 24°C) on the CO₂ production of S. scimitus. In addition, we tested for differences between species in their total soluble protein (in mg) and neutral lipid content (in mg) at 16°C and 24°C using analysis of covariance (ANCOVA). For total lipid and protein content, the fixed factors were taxon, temperature and their interaction, with the sample mass (pooled wet mass, in mg) as the covariate. In conjunction, we analysed how movement rate between our four species was affected by temperature using a two-way ANOVA, with taxon, temperature and their interaction as the fixed factors.

We used mixed effected Cox proportional hazard regressions to determine how prey survival (C. lactis and F. candida) differed under 16°C and 24°C while under risk of predation by S. scimitus. Here, temperature, prey and their interaction as the fixed effects using C. lactis at 16°C as the baseline measurement. We did not include O. nitens in the choice or no choice Cox regressions as predator mites did not consume a single individual of O. nitens in either feeding trial at both temperatures. We ran separate Cox regressions for our choice and no choice feeding trials and used arena number as the random effect due to lack of independence between samples (i.e. prey survival may differ between individual arenas). For these Cox regressions, we reported the hazard ratio (and 95% confidence intervals), and corresponding p-values for each factor. Hazard ratios above 1 equate to prey survival probability being lower, relative to the baseline. Conversely, hazard ratios below 1 are equal to prey survival probability being higher, relative to the baseline. In addition, we compared survival curves by partitioning the data and running individual mixed effect Cox regressions for each pairing of treatments and corrected the p-values for each test using a Bonferroni correction. We plotted prey survival probability using Kaplan–Meier survival curves. Finally, we used Kruskal-Wallis Rank Sum test to determine if temperature significantly affected the estimated energy intake of predators during the choice feeding trials. We performed all analyses using R version 3.5.1 (R Core Team, 2018).

3 RESULTS

We found that S. scimitus produced more CO₂ at 24°C (1.52 ± 0.07 μl/hr; mean ± SEM) than at 16°C (1.19 ± 0.07 μl/hr; F_1,6 = 11.69, p = 0.014; SI Figure 1), meaning that predators had higher metabolic demands under warming. We estimated the energy requirements for S. scimitus individuals during the feeding trials maintained at 16°C were 9.6 mJ 8 hr⁻¹ individual⁻¹, which was ~1.3× lower than that of their counterparts maintained at 24°C (12.2 mJ 8 hr⁻¹ individual⁻¹).

Details are in the caption following the image — **FIGURE 1**
Open in figure viewer PowerPoint

(a) Soluble protein, (b) neutral lipid and (c) movement of taxa (*Stratiolaelaps scimitus*, *Folsomia candida*, *Carpoglyphus lactis*, *Oppia nitens*) after chronic exposure to 16°C and 24°C. *Indicates p < 0.05, and *** indicates p < 0.001. Bars represent mean ± SEM, whereas points are individual data values. We present mass-specific soluble protein and neutral lipid for ease of interpretation, but statistical analyses were performed as an ANCOVA with sample mass as covariates.

We found that total protein content did not differ between 24°C and 16°C (F_1,15 = 1.28, p = 0.276), but that F. candida had the highest protein content at both 16°C and 24°C (F_3,15 = 12.63, p < 0.001). However, the interaction between taxon and temperature was also not significant (F_3,15 = 0.389, p = 0.763; Figure 1a). Conversely, we found that total lipid content was lower at 24°C, compared with 16°C (F_1,14 = 24.14, p < 0.001). But we did not find significant differences among taxa (F_3,14 = 2.44, p = 0.107) nor did we find a significant taxon × temperature interaction (F_3,14 = 0.80, p = 0.512; Figure 1b).

Using mean soluble protein and neutral lipid concentrations at each temperature, we estimated that F. candida had the highest energy content at both 16°C and 24°C and that energy content (and thus energy density) decreased for all species, except F. candida, at 24°C (Table 1). The average body mass of F. candida (28.7 μg) was considerably greater than the those of C. lactis (3.76 μg) and O. nitens (17.4 μg), and a single F. candida consequently contained more energy than the other species (Table 1). However, energy content was also temperature-dependent. The total energy content of F. candida at 16°C was 11.8 times greater than C. lactis and 1.6 times greater than O. nitens. At 24°C, energy content of F. candida was 35.1 times greater than C. lactis and 5.3 times greater than O. nitens at 24°C.

Movement rate differed significantly among taxa (F_3,86 = 82.33, p < 0.001) with the predator S. scimitus fastest at both 16°C and 24°C, followed by F. candida (Figure 1c). We found that the average movement rate of S. scimitus was approximately nine times faster than that of the other mites at both temperatures. Movement rate did not change significantly with temperature, with all taxa exhibiting similar movement between 16°C and 24°C (F_1,86 = 0.078, p = 0.78), while the interaction between temperature and taxon was also not significant (F_3,86 = 1.24, p = 0.299).

S. scimitus did not consume any O. nitens in either the choice or no choice feeding trials. Although we observed S. scimitus attacking O. nitens at both temperatures, it failed to successfully feed. The collembolan F. candida had a higher survival probability than C. lactis in both the choice (Prey, HR = 0.23, 95% CI = 0.11 to 0.47, p < 0.001) and no choice (Prey, HR = 0.13, 95% CI = 0.07 to 0.25, p < 0.001) trials (Figure 2). Moreover, in both choice (Temperature, HR = 2.89, 95% CI = 1.59 to 5.27, p < 0.001) and no choice (Temperature, HR = 3.34, 95% CI = 2.12 to 5.27, p < 0.001) trials, a higher temperature decreased the survival of C. lactis prey species, with no effect on the survival of F. candida leading to a significant interaction between prey and temperature (choice: Prey × Temperature, HR = 0.14, 95% CI = 0.042 to 0.435, p < 0.001; no choice: Prey × Temperature, HR = 0.26, 95% CI = 0.10 to 0.66, p = 0.005; Figure 2). We observed that predators frequently abandoned captured large-bodied prey, F. candida, at 24°C, but this was not observed with the small-bodied prey, C. lactis. This change in feeding rate and behaviour resulted in the energy intake for S. scimitus individuals at 16°C being significantly higher (H₁ = 6.91, p = 0.009; 80.89 ± 8.10 mJ 8 hr⁻¹ individual⁻¹) than individuals at 24°C (30.63 ± 9.62 mJ 8 hr⁻¹ individual⁻¹).

4 DISCUSSION

Climate warming could affect predator–prey dynamics by increasing the metabolic demands of predators, which we speculate would drive novel feeding behaviours as predators navigate trade-offs in prey selection, including changes in energy content, handling time and body size (among other functional constraints). We found that increasing the temperature from 16°C to 24°C increased the metabolic demands of our predator, S. scimitus, by ~30%, and observed that S. scimitus altered its feeding behaviour at 24°C. Predators increasingly fed on small-bodied prey, C. lactis, at 24°C in both the choice and no choice trials, leading to a lower survival rate. This was not observed with the large-bodied prey, F. candida, as survival rate did not significantly change with temperature. Together, these results strongly support our second hypothesis, that predators will alter their feeding behaviour under warming to minimize energy lost when feeding (in this case, favouring the small, easy to capture C. lactis). Optimal foraging theory suggests that predators should select prey based on cost–benefit trade-offs of energetic gains and losses. Thus, we interpret our results as indicating a trade-off in prey selection that is driven by the differences in energy content and ‘capturability’ (i.e. body size, movement rates) of C. lactis and F. candida. C. lactis is energy-poor compared to F. candida, but is smaller, slower and has no defences, which should make C. lactis easier to capture and consume under increased metabolic demands. Conversely, because of their larger size, faster movement and defences (i.e. an appendage used for jumping) F. candida could repel against attacks from S. scimitus, which should make F. candida harder to capture.

Past studies have also found that some ectothermic predators, like dragonfly larvae and fish, increase their feeding on small-bodied prey under warming (Dobashi et al., 2018; Frances & McCauley, 2018). Smaller prey are typically slower than larger prey (making them easier to catch; Hirt et al., 2017) and require less time to capture and handle (Brose et al., 2008; Rall et al., 2012). Jensen et al. (2019) also found that the feeding rate of predator mites increased more under warming on ‘easy’ prey (i.e. the slower moving collembolan) than on faster collembolan prey, which were likely harder to catch. We observed that predators could capture and handle the larger prey at the higher temperatures, but predators were more likely to release the individual before feeding despite the abandoned F. candida appearing injured and undefended (Meehan, 2022). Thus, based on both qualitative and quantitative data from the feeding trials, we conclude that predators fed more on small-bodied prey under warming due to lower capture and handling costs and not due to higher escape efficiency of the larger prey. Ectothermic predators may increase their feeding rates under warming to compensate for higher metabolic demands. However, because metabolic rate can increase faster with temperature than feeding rates (Rall et al., 2010; Vucic-Pestic et al., 2011), even modest increases in metabolic demands may shift predator feeding behaviour to limit energetic losses. Similar to these past studies, we found that the ratio of energy intake versus demands for predators decreased under warming (8.4× at 16°C vs. 2.5× at 24°C). We posit that the increased feeding by predators on the small-bodied, easy-to-capture prey was because predators prioritized lower handling costs to combat higher metabolic demands instead of maximizing energetic gains associated with larger prey. As a result, energy intake decreased as predators traded off higher energy gains for lower energy losses.

We calculated a lower energy intake for S. scimitus at 24°C, compared to 16°C during the choice feeding trials, but this estimate still exceeded our calculated energy requirements. Nevertheless, there may be long-term consequences for predators under climate warming when energy intake decreases while still exceeding overall energy requirements. Predators have lower starvation tolerance at higher temperatures and lay fewer eggs when food-deprived under warming (Jensen et al., 2017, 2018). Predators could compensate for this by accumulating energy stores (Jensen et al., 2010). However, in our study, S. scimitus maintained at 24°C had less body lipid content than at 16°C and did not increase consumption on the more energy-rich prey, F. candida. This suggests that S. scimitus are not accumulating energy stores and may, therefore, have a lower safety margin for missed feeding opportunities at higher temperatures.

Climate warming strengthens top-down control by predators through increased feeding rates (Barton et al., 2009; Ramachandran et al., 2021; Tanentzap et al., 2020; Walker et al., 2020), and an increased consumption of small-bodied prey (as we show here) can further alter food web dynamics as a predator–prey mass ratio can be positively correlated with interaction strength but negatively correlated with trophic transfer efficiency (Barnes et al., 2010; Emmerson & Raffaelli, 2004). Increased consumption of smaller, energy-poor prey may also alter prey community composition, increasing the prevalence of large-bodied prey (Yvon-Durocher et al., 2015). However, we found that the medium-sized prey in our study, O. nitens, was not consumed at either test temperature. We speculate that this was because of O. nitens heavy sclerotization. This suggests that increased energy demands for S. scimitus do not change the prey species available to the predator – and thus the structure of the food web remains unchanged – at least in our system.

4.1 Caveats

We had three main limitations in our study. First, because of the parabolic relationship between predator–prey mass ratio and feeding rate (Brose et al., 2008), changes to prey body size preferences for predators is possibly context-dependent, based on the available prey and predator body size. If offered other species, S. scimitus may have abandoned both small- and large-bodied prey in favour of a intermediate-sized prey (i.e. an undefended prey similar in size to O. nitens) to maximize their feeding rates, changing our underlying conclusions and interpretations. Potentially, using different-sized individuals of the same prey species (e.g. F. candida) may better detect the effect of prey body size on predator feeding behaviour. Second, we used highly variable protein and lipid data from C. lactis and F. candida to estimate energy intake that could over (or under) estimated predators' caloric intake during the feeding trials. However, our overall conclusion that predator mites had lower energy intake at 24°C versus 16°C holds because of the increased feeding on the smaller prey C. lactis under warming. Our conclusions are also supported by the observation that the change in predator body mass after feeding on C. lactis was much lower than when feeding on the larger F. candida. Third, we used a simplified invertebrate predator–prey system to test for predator feeding behaviour. Although this system allowed us to test hypotheses and explore how ectothermic predator feeding behaviour changes at higher temperatures, direct measurements of energy intake and expenditure were often not possible. Similar studies have used the average weight and/or energy density of their prey to calculate energy gains for predators (Rall et al., 2010; Sentis et al., 2012; Sohlström et al., 2021; Vucic-Pestic et al., 2011), but we expanded on this work by including an empirical measurement of change in predator body mass in our energy intake formula. This is still an indirect measurement of energy intake but it provides additional evidence that feeding behaviour for ectothermic predators changes under warming.

5 CONCLUSIONS

Climate warming will have both direct and indirect effects on species at physiological, behavioural and population levels with cascading effects on community composition, diversity and ecosystem processes. We showed that warmer temperatures may increase top-down control on some ectothermic predator–prey interactions, but weaken others, and that prey body size, defence tactics and handling time are important factors in predator–prey dynamics under climate warming. We found that predators increased feeding on small-bodied, energy-poor prey in favour of large-bodied, energy-rich prey under warming but that energy intake was lower at the higher temperature. Thus, some predators may prioritize minimizing handling costs over maximizing energy gains when feeding under greater metabolic demands with climate warming.

AUTHORS' CONTRIBUTIONS

The project was conceived by M.L.M., B.J.S. and Z.L.; data were collected by M.L.M. and K.F.T.; M.L.M. analysed the data; M.L.M. and Z.L. wrote the manuscript with editorial inputs from K.F.T. and B.J.S.

ACKNOWLEDGEMENTS

From Western University, thanks to Yolanda Morbey, Anne Simon and Jeff Martin for feedback on experimental design and earlier drafts of the manuscript. In addition, thanks to Mitch Zimmer for assistance with videography, Adam Tepperman for assistance making movement rate apparatus and Eileen Reinke for collecting some additional data on predator feeding behaviour. Thank you to Andrew Cook (University of Alberta) for the stimulating and thought-provoking conversations about predator energy intake estimates. Finally, thanks to Juliska Princz, Heather Lemieux and Patrick Boyd (Environment and Climate Change Canada) for providing animal cultures. This work was supported by Natural Sciences and Engineering Council of Canada (NSERC) Discovery Grants to Z.L. and B.J.S. and NSERC postgraduate scholarships to M.L.M. and K.F.T.

CONFLICT OF INTEREST

The authors have no conflict of interests to report.

Open Research

DATA AVAILABILITY STATEMENT

Data and R code are deposited on M.L.M. figshare account https://doi.org/10.6084/m9.figshare.13360073.v1 (Meehan et al., 2022).

Supporting Information

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Citing Literature

Volume36, Issue9

September 2022

Pages 2279-2288

Predators minimize energy costs, rather than maximize energy gains under warming: Evidence from a microcosm feeding experiment

Abstract

1 INTRODUCTION