Energy intake, body mass, and ambient temperature jointly regulate torpid metabolic rate in the big brown bat (Eptesicus fuscus)

Energy intake, body mass, and ambient temperature jointly regulate torpid metabolic rate in the big brown bat (Eptesicus fuscus) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Energy intake, body mass, and ambient temperature jointly regulate torpid metabolic rate in the big brown bat (Eptesicus fuscus) Jorge Ayala-Berdon, Kevin I. Medina-Bello, Jorge E. Schondube, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9500426/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Small endotherms frequently experience fluctuations in ambient temperature ( T a ) and food availability that challenge the maintenance of energy balance. Many species cope with these conditions by entering torpor, a reversible physiological state characterized by reductions in metabolic rate and body temperature ( T b ). Although T a , body mass ( M b ), and food availability are known to influence torpor expression, how environmental conditions interact with the energetic state of individuals to regulate torpid metabolism remains poorly understood. We experimentally manipulated energy intake and measured metabolic responses across a range of T a to evaluate how M b , energy intake, and T a influence torpid metabolic rate in the big brown bat ( Eptesicus fuscus ). Torpid metabolic rate during cooling increased with M b and T a but decreased with increasing energy intake. In addition, the influence of energy intake on torpid metabolic rate depended on T a , with the strongest reductions occurring at lower T a s. Minimum torpid metabolic rate also differed between energetic treatments and was influenced by an interaction between M b and energetic state. Energy-supplied individuals reached lower minimum torpid metabolic rates than energy-restricted bats, suggesting that energetic condition modulates the physiological limits of metabolic suppression. Together, these results reveal two complementary levels of torpor regulation in E. fuscus : dynamic metabolic responses during cooling shaped by M b , T a , and energy intake, and intrinsic limits to metabolic suppression determined by body size and energetic state. Our findings highlight the joint roles of environmental and physiological factors in shaping torpor expression in heterothermic mammals. ambient temperature energetic state metabolic suppression heterothermy torpor Figures Figure 1 Figure 2 Figure 3 Introduction Small endotherms are exposed to pronounced daily and seasonal fluctuations in ambient temperature ( Tₐ ) and resource availability, conditions that can generate recurrent imbalances in their energy budgets (Körtner and Geiser 2000 ; Vuarin et al. 2015 ). Because of their high surface-to-volume ratio, these organisms experience elevated heat loss and consequently incur high metabolic costs to maintain homeothermy (McNab 1969 ). To cope with these energetic challenges, many species employ torpor, a reversible physiological state characterized by controlled reductions in metabolic rate, body temperature ( T b ), heart rate, and other physiological processes (Geiser 1988 ; Wang and Wolowyk 1988 ; Geiser 2021 ). By reducing metabolic expenditure, torpor allows animals to conserve energy during periods when environmental conditions or food availability limit energy acquisition. The depth and duration of torpor are influenced by multiple factors, including ambient temperature ( T a ), body mass ( M b ), and food availability (Geiser 2021 ). Ambient temperature strongly affects torpor expression because metabolic heat production is largely determined by the thermal gradient between T b and the surrounding environment (Geiser 2004 ; Ruf and Geiser 2015 ). Lower T a s generally facilitate deeper reductions in metabolic rate by promoting passive heat loss, whereas higher T a s limit the extent of metabolic suppression. Body mass can also influence torpor physiology through its effects on metabolic scaling and thermal conductance. Smaller mammals typically have higher mass-specific metabolic rates and greater heat loss due to their larger surface-to-volume ratios, which may allow them to reach lower metabolic rates during torpor compared with larger individuals (Speakman and Thomas 2003 ; Riek and Geiser 2013 ). Food availability is another major driver of torpor use. In many species, torpor is primarily interpreted as a strategy to cope with energetic constraints, such that individuals experiencing food limitation or low energy reserves exhibit deeper or more frequent torpor bouts (Körtner and Geiser 2000 ; Boyles et al. 2007 ; Landry-Cuerrier et al. 2008 ; Doucette et al. 2012 ). However, growing evidence suggests that torpor expression may also depend on the energetic state of individuals in more complex ways. For example, some heterothermic mammals exhibit deeper or longer torpor bouts when food availability is high, potentially allowing individuals to conserve energy in anticipation of future resource scarcity or to optimize energy budgets under variable environmental conditions (Stawski and Geiser 2010 ; Humphries et al. 2003 ; Vuarin and Henry 2014 ). Despite these advances, the combined effects of energetic state and environmental conditions on the regulation of torpor metabolic rate remain poorly understood. Bats are particularly suitable models for studying the drivers of torpor expression because many species regularly employ daily torpor or seasonal hibernation to cope with fluctuating environmental conditions (Geiser and Brigham 2012 ). The big brown bat ( Eptesicus fuscus ) is a widely distributed insectivorous bat species that uses torpor extensively during cold periods and food shortages. However, the combined effects of M b energy intake, and T a on torpid metabolic regulation remain poorly understood. In particular, it remains unclear whether torpor expression is primarily driven by environmental conditions or whether the energetic state of individuals modulates the depth of metabolic suppression. In this study, we experimentally manipulated energy intake and measured metabolic responses across a range of T a to evaluate how M b , energy intake, and T a influence torpid metabolic rate in E. fuscus . We hypothesized that torpor expression is jointly determined by environmental conditions and the energetic state of individuals. Under this framework, torpid metabolic rate during cooling should reflect dynamic metabolic regulation across the thermal gradient, while the minimum torpid metabolic rate achieved by individuals may represent a physiological limit to metabolic suppression that depends on the energetic state of bats. By disentangling these mechanisms, our study provides new insights into how environmental conditions and energetic state jointly regulate torpor expression, revealing how dynamic metabolic responses during cooling interact with physiological limits to metabolic suppression in heterothermic bats. Materials and methods Study site Bats were captured during the dry-cold season (early October 2021 to late February 2022) in Santa Cruz Moxolahuac, a montane ecosystem located in Puebla, central Mexico (3,121 m a.s.l.; 19º 27' 2.188'' N, 98º 34' 10.131'' W) (Fig. 1 ). The site has a temperate subhumid cold climate and is dominated by coniferous forests, including oyamel ( Abies religiosa ), Hartweg’s pine ( Pinus hartwegii ), and Moctezuma’s pine ( P. montezumae ). Mean T a during the study period was 9.3 ± 0.07 (mean ± SE). Bat capture and housing Bats were captured using mist nets (2 x 6 and 2 x 12 m) placed near water bodies used for foraging and drinking. Nets were opened at dusk and closed at ∼ 24:00 hours. Only adult, non-reproductive males (n = 8) were selected to avoid potential confounding effects of sex and reproductive condition. Body mass was measured using a digital balance (Ohaus, Newark, New Jersey, USA; ± 0.2 g), and forearm length was measured to the nearest 0.1 mm using calipers. Age class was determined by examining the epiphyseal gap in the fourth metacarpal of the third and fifth fingers, following Wilkinson and Brunet-Rossinni ( 2009 ). After capture, bats were transported in cloth bags to the experimental facility and housed in flight cages (75 × 75 × 75 cm) under controlled conditions (12 h:12 h light-dark cycle, Ta ~ 28°C, a relative humidity above 50%). Water was provided ad libitum . The experimental protocol followed a standardized sequence. After capture, bats were fasted for 6–8 h to ensure post-absorptive state. Basal metabolic rate and thermal critical temperatures (lower critical temperature — T LC — and upper critical temperature — T UC —) were measured the following day under standardized conditions (see below). Subsequently, bats were subjected to two energy availability treatments in a repeated-measures design: Energy-supplied condition. Individuals were fed mealworms ad libitum at 20:00 h, coinciding with the onset of natural foraging activity (Rydell et al. 1996 ; Grindal and Brigham 1999). Torpor measurements were conducted during the subsequent light phase (inactive period), approximately 12–13 hours after feeding. Energy-restricted condition. Following completion of the energy-supplied trial, bats were deprived of food for 36 h, a duration that may reflect short-term energy limitations under natural conditions (Grindal and Brigham 1998 ). This deprivation period included the intervening light phase, to ensure torpor assessment at the same circadian stage in both treatments. In this design, each individual served as its own control across treatments. The energy-supplied treatment was conducted first for all individuals to avoid prolonged fasting immediately after capture and to standardize the duration of food restriction of 36 h. Respirometry Metabolic measurements were obtained using open-flow indirect calorimetry (FoxBox®, Sable Systems International, Las Vegas, NV, USA) recording O 2 consumption and CO 2 production simultaneously, which provides accurate metabolic rate estimates in terrestrial endotherms (Lighton 2018 ). Each bat was placed in a 410 mL metabolic chamber located within a temperature-controlled cabinet (Pelt-drop-in®, Sable Systems International). Plastic mesh allowed individuals to hang in a natural posture while preventing flight activity. Ambient temperature inside the cabinet was controlled to ± 0.5°C using a precision controller (Pelt5®, Sable Systems International). Dry CO 2 -free air, scrubbed upstream using drierite (calcium sulfate) and ascarite (sodium hydroxide) was pushed through the chamber at 150 mL min − 1 , adjusted according to the expected metabolic rates following Lighton and Halsey ( 2011 ). Flow rates were verified using a calibrated flowmeter. Excurrent air was dried before analysis, and fractional concentrations (%/100) of both O 2 (FeO 2 ) and CO 2 (FeCO 2 ) were recorded every second. To correct for instrumental drift, an empty chamber (410 mL) of identical volume was maintained under identical conditions and monitored in a second calibrated FoxBox® system. Data from the empty chamber were used to correct baseline drift. Basal metabolic rate, and thermal critical temperatures Torpor is a controlled hypometabolic state characterized by a substantial reduction in metabolic rate below BMR . Basal metabolic rate represents the minimal metabolic rate within the thermoneutral zone ( TNZ ), bounded by T LC and T UC (Speakman and Thomas 2003 ; Geiser 2021 ; Genoud et al. 2018 ). Each bat was first maintained at 28°C (within the TNZ ; Ayala-Berdon and Medina-Bello 2025) for 60 min to allow acclimation, followed by a 30 min recording period. Ambient temperature was then gradually reduced to 8°C. During cooling, metabolic rate was recorded at 1°C intervals (5 min per ºC) and at 5 ºC intervals (30 min per step) to determine T LC . After returning to 28 ºC for 30 min, temperature was increased to 43 ºC following the same protocol to determine T UC . If torpor was initiated during this procedure, T a was returned to the TNZ and the protocol restarted to ensure measurements reflected euthermic responses. All individuals remained normothermic during these trials, as indicated by the expected increase in metabolic rate below T LC and above T UC . Torpor trials under contrasting energy availability Following BMR and thermal limit determination, torpor trials were conducted under both energy treatments. Bats were placed in the chamber at 28 ºC for 60 min and metabolic rate was recorded for 75 minutes before cooling. Ambient temperature was then gradually reduced to 8°C. During cooling, metabolic rate was recorded at 1°C intervals (5 minutes per ºC) with extended recordings at 23, 18, 13, and 8°C (75 min per step) to improve detection of torpid metabolic rate. Minimum torpid metabolic rate was defined as the lowest stable metabolic rate maintained approximately two hours below the threshold T a at which metabolic rate stabilized (Ayala-Berdon and Medina-Bello 2024 ). Metabolic rate values obtained at each 1 ºC step during cooling were used to analyze the temperature-dependent trajectory of torpid metabolic rate, whereas minimum torpid metabolic rate was estimated from the stable asymptote once metabolic rate had plateaued. After reaching 8 ºC, T a was returned to 28°C for 30 min to minimize rewarming costs. Upon completion of all experimental trials, bats were released at their capture site. Metabolic rate calculations We calculated O 2 consumption (V̇O₂) (in mL O 2 h −1 ) following Lighton ( 2018 ): V̇O₂ = FR [(FiO 2 -FeO 2 )-FeO 2 (FeCO 2 -FiCO 2 )]/(1-FeO 2 ) Where FR is the flow rate (mL min − ¹), FiO₂ and FeO₂ represent the fractional concentration of O₂ in the incurrent and excurrent air, respectively, while FiCO₂ and FeCO₂ correspond to the fractional concentration of CO₂ in the incurrent and excurrent air. Mean metabolic rates were calculated from continuous recordings (1s resolution) at each temperature step. Statistical analyses All analyses were conducted in R (version 4.4.0). Critical temperatures and minimum torpid metabolic rate were determined using broken-stick models (Ayala-Berdon and Medina-Bello 2024 ). We fitted linear regressions with the “lm” function from the “stats” package. In these models, experimental temperatures were the independent variables, and the mean values of the metabolic rate, the dependent variable. We estimated the inflection points of the regression models by using the “davies.test” function of the “segmented” package (Muggeo 2008 ). When individuals were in a euthermic state, the two inflection points represented T LC and T UC . During torpid state, the points indicated the T a at which animals entered torpor (first inflection point) and the T a at which torpid metabolic rate approached its minimum values (second inflection point). We first evaluated determinants of temperature-dependent trajectory of torpid metabolic rate during cooling under the energy-supplied condition. Torpid metabolic rate measured at each 1 ºC step was modeled as a function of centered M b , standardized energy intake, standardize T a and the intake * T a interaction. Because measurements were repeated within individuals, we initially fitted mixed-effect models including individual identity as a random intercept. However, the random-intercept variance was estimated as ~ 0 (singular fit), indicating negligible residual clustering after accounting for fixed effects. Consequently, the mixed model reduced to the corresponding fixed-effects model. To evaluate whether the effect was strongest under cold conditions, we tested the intake * T a interaction and quantified simple slopes of intake at low (-1 SD), mean (0), and high (+ 1 SD) T a . Additionally, we applied the Johnson-Neyman procedure to identify the range of T a values over which the intake effect was statistically significant. To examine whether minimum torpid metabolic rate differed between energy treatments, we fitted a mixed-effects models with treatment as fixed effect and individual identity as a random intercept ("lmer" function from the "lme4" package). Because treatment groups could differ in M b , we first compared M b between treatments (Wilcoxon rank-sum test). Because M b differed between treatments, we further evaluated a model including centered M b and the treatment * M b interaction to assess whether energetic state modified the scaling relationship between M b and minimum torpid metabolic rate. Given the small number of individuals (G = 8), we conducted sensitivity analyses for both models using small-sample cluster-robust standard errors (CR2 estimator with Satterthwaite degrees of freedom) clustered by individual identity. Significance was assessed using likelihood ratio test comparing full and reduced models for the mixed-effect models and confirmed with small-sample cluster-robust inference for both models. In both sets of analyses, torpid metabolic rate was log-transformed to meet assumptions of normality and homoscedasticity. Slopes (β) were extracted from the model summaries. Statistical significance was assessed at ⍺ < 0.05. Data are presented as mean ± standard error unless otherwise indicated. Results During cooling under the energy-supplied condition, small-sample cluster-robust inference (CR2) showed that torpid metabolic rate was significantly associated with centered M b (β = 5.91 ± 1.06, p = 0.007), standardized energy intake (β = -0.34 ± 0.06, p = 0.008), standardized T a (β = 0.27 ± 0.03, p = 0.001), and the intake * T a interaction (β = 0.15 ± 0.02, p = 0.003). The overall model explained 57% of the variance in log-transformed torpid metabolic rate (R 2 = 0.57). Simple slope analyses indicated that the negative association between intake and torpid metabolic rate was strongest at low T a (-1 SD; β = -0.49 ± 0.06 SE), intermediate at mean T a (β = -0.34 ± 0.06 SE), and weakest at high T a (+ 1 SD; β = -0.19 ± 0.07 SE) (Fig. 2 A). Thus, the suppressive effect of intake progressively diminished as T a increased. The Johnson-Neyman procedure indicated that the effect of intake on torpid metabolic rate was statistically significant at T a s below 22.32 ºC (corresponding to 1.36 SD above the mean T a ). Because the observed temperature range spanned 13–24 ºC, the intake effect was significant across nearly the entire thermal gradient and weakened only at the highest temperatures (Fig. 2 B). Body mass differed between treatments (Wilcoxon rank-sum test: W = 64, p < 0.001), with energy-supplied bats being heavier (16.12 ± 0.29 g) than energy-restricted individuals (13.93 ± 0.25 g) (W = 64, p < 0.001). Small-sample cluster-robust inference (CR2) indicated that treatment significantly affected minimum torpid metabolic rate (β = 0.54 ± 0.11, p = 0.003). In addition, the interaction between treatment and centered M b was significant (β = 4.58 ± 1.48, p = 0.03), indicating that the relationship between M b and minimum torpid metabolic rate differed between energetic states. In energy-supplied individuals, minimum torpid metabolic rate tended to decline with increasing M b (β = -2.63 ± 1.05, t = -2.50, p = 0.08). In contrast, in energy-restricted individuals the relationship was reversed, with larger individuals exhibiting higher minimum torpid metabolic rates (β = 1.96 [derived from the treatment * M b interaction]; Fig. 3 ). Discussion In this study, we found that torpor expression in E. fuscus is jointly shaped by body mass ( M b ), energy intake, ambient temperature ( T a ), and the energetic state of individuals. Our results revealed two levels of torpor regulation. Torpid metabolic rate during cooling was influenced by M b , energy intake, and T a , indicating dynamic metabolic regulation across the thermal gradient. In contrast, minimum torpid metabolic rate —representing the physiological limit of metabolic suppression within the range of T a tested— depended on the interaction between M b and the energetic state of individuals. Torpid metabolic rate during cooling increased with M b . Body mass is a key morphological trait influencing thermal physiology across mammals, affecting variables such as BMR and critical temperatures (e.g., Savage et al. 2004 ; Kozłowski et al. 2020 ; Speakman and Thomas 2003 ; Farrell-Gray and Gotelli 2005 ; McNab 2008 ; Riek and Geiser 2013 , Ayala-Berdon et al. 2025 , among others). Because metabolically active tissue generally scales with body size, larger individuals are expected to exhibit higher absolute metabolic rates, even during torpor. In addition, smaller bats tend to have higher mass-specific thermal conductance, which promotes faster passive cooling and may allow them to reach lower metabolic rates during torpor (Geiser 2021 ). This pattern is consistent with the greater heat loss experienced by smaller endotherms due to their higher surface-to-volume ratio. Ambient temperature also played an important role in shaping torpid metabolic rate during cooling. As expected, torpid metabolic rate increased with T a , reflecting the strong influence of the thermal gradient between T b and the surrounding environment on metabolic heat production. In heterothermic mammals, reductions in metabolic rate during torpor are closely linked to passive heat exchange with the environment, such that lower T a´ s facilitate deeper metabolic depression by promoting greater heat loss (Geiser 2004 ; Ruf and Geiser 2015 ; Geiser 2021 ). Consequently, individuals exposed to colder conditions can achieve lower metabolic rates during torpor, whereas higher T a s limit the extent of metabolic suppression. This temperature dependence highlights the importance of the thermal environment in determining the energetic benefits of torpor in bats across different energetic conditions and provides a physiological context for the interaction between T a and energy intake observed in our models. Torpid metabolic rate during cooling decreased with increasing energy intake. At first glance, this pattern appears to contrast with the traditional view that torpor is primarily used by animals experiencing energy constraints (Körtner and Geiser 2000 ; Boyles et al. 2007 ; Landry-Cuerrier et al. 2008 ; Doucette et al. 2012 ). However, for small torpor-users or hibernators facing low prey availability and low T a , deeper reductions in metabolic rate when individuals possess greater energetic reserves may increase survival during prolonged periods of harsh environmental conditions (Geiser 2004 ; Ruf and Geiser 2015 ). Deep torpor may also facilitate temporal resource partitioning and reduce intraspecific competition. Asynchrony in periods of activity, such as the timing of emergence, may allow differentiated use of the environment, preventing all individuals from accessing the same resources simultaneously (Kronfeld-Schor and Dayan 2003 ). Interestingly, we also detected an interaction between energy intake and T a . Simple slope analyses indicated that the negative effect of energy intake on torpid metabolic rate was strongest at low T a , intermediate at moderate T a , and weakest at high T a . Moreover, the effect of intake remained statistically significant across nearly the entire range of T a tested. This pattern suggests that individuals with higher energy intake may be able to actively suppress metabolism more deeply, particularly at low T a where energetic demands are greatest. Together, these results indicate that the thermal environment modulates the influence of energy intake on torpid metabolic rate during cooling in E. fuscus , which may help explain why bats often select cold hibernation roosts, particularly when individuals possess sufficient energetic reserves to sustain deep metabolic suppression (Boyles et al. 2007 ; Willis and Brigham 2007 ). Conversely, individuals in poorer energetic condition may benefit from occupying slightly warmer roosts, where metabolic regulation may be less energetically demanding. Beyond the dynamic regulation of torpid metabolic rate observed during cooling, our results also revealed variation in the minimum torpid metabolic rate achieved by individuals, representing the physiological limit of metabolic suppression under the experimental conditions. Metabolic inhibition during cooling is expected to influence the minimum torpid metabolic rate achieved under different energetic conditions. Because the strongest reduction in torpid metabolic rate occurred in bats with higher energy intake at the lowest T a , energy-supplied individuals were expected to reach lower minimum torpid metabolic rates, which are typically achieved at colder T a s. Consistent with this expectation, energy-supplied bats exhibited lower minimum torpid metabolic rates. A similar pattern has been reported for the greater long-eared bat ( Nyctophilus bifax ) and fat-tailed dwarf lemurs ( Microcebus griseorufus ), where individuals expressed deeper and longer torpor bouts during periods of increased food availability (Stawski and Geiser 2010 ; Kobbe et al. 2014 ; Vuarin et al. 2013). According to these authors, deeper and prolonged torpor bouts may reduce predation risk by shortening periods of activity or conserve energy in anticipation of future resource scarcity. Importantly, our models also revealed an interaction between M b and energetic treatment: minimum torpid metabolic rate declined with increasing M b in energy-supplied individuals, whereas the relationship was reversed in energy-restricted bats. This pattern suggests that larger individuals with sufficient energy reserves may achieve deeper metabolic suppression, possibly due to their lower surface-to-volume ratios and greater fuel availability. In contrast, when energy is limited, larger bats may be unable to suppress metabolism to the same extent because maintenance costs remain higher. Nevertheless, the physiological mechanisms underlying this interaction require further investigation to better understand how energetic state and M b jointly determine the limits of metabolic suppression. Together, our results demonstrate that torpor regulation in E. fuscus operates at two complementary physiological levels: dynamic modulation of metabolic rate during cooling and intrinsic limits to metabolic suppression determined by M b and energetic state. By integrating these mechanisms, individuals can flexibly adjust energy expenditure under varying thermal and energetic conditions. Such flexibility may play an important role in determining overwinter survival and roost selection strategies in heterothermic bats. Declarations Acknowledgements We thank O. Juárez, and the staff of the "El Rey" site for their logistical support. Funding This work was funded by the CONACYT program (Consejo Nacional de Humanidades, Ciencias y Tecnologías), currently the Secretaría de Ciencia, Humanidades, Tecnología e Innovación (SECIHTI) in Mexico, through the FOSEC CB2017–2018 project (A1-S-39572). Author information Authors and Affiliations SECIHTI, Centro Tlaxcala de Biología de la Conducta, Universidad Autónoma de Tlaxcala, Carretera Tlaxcala-Puebla Km. 1.5, C.P. 90062, Tlaxcala de Xicohténcatl, Tlaxcala, Mexico Jorge Ayala-Berdon Doctorado en Ciencias Biológicas, Centro Tlaxcala de Biología de la Conducta, Universidad Autónoma de Tlaxcala. Carretera Tlaxcala-Puebla Km. 1.5, C.P. 90062, Tlaxcala de Xicohténcatl, Tlaxcala, Mexico Kevin I. Medina-Bello Instituto de Investigaciones en Ecosistemas y Sustentabilidad, Universidad Nacional Autónoma de México, Antigua Carretera a Pátzcuaro No. 8701, Col. Ex-Hacienda de San José de La Huerta, C.P. 58190, Morelia Michoacán, México Jorge E. Schondube Universidad Autónoma de Tlaxcala, Tlaxcala de Xicohténcatl, Tlaxcala, Mexico Departamento de Biología Celular y Fisiología, Universidad Nacional Autónoma de México, Tlaxcala de Xicohténcatl, Mexico. Carretera Tlaxcala-Puebla Km. 1.5, C.P. 90062, Tlaxcala de Xicohténcatl, Tlaxcala, Mexico Margarita Martínez-Gómez Corresponding author Correspondence to Jorge Ayala-Berdon Ethics declarations Conflict of Interest The authors declare no conflict of interest. Ethical approval All procedures were conducted under permit of the Mexican Wildlife Department (Secretaría de Medio Ambiente y Recursos Naturales, SEMARNAT: SGPA/DGVS/06795/21) and approved by the ethics committee of the Universidad Autónoma de Tlaxcala and conducted in accordance with national guidelines for animal care. Supplementary Information Supplementary material is presented along with submission. Author contributions J.A.B. and K.I.M. conceived and designed the study. J.A.B. analyzed the data. 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Oikos 76:243–252. https://doi.org/10.2307/3546193 Savage VM, Gillooly JF, Woodruff WH, West GB, Allen AP, Enquist BJ, Brown JH (2004) The predominance of quarter-power scaling in biology. Funct Ecol 18:257–282. https://doi.org/10.1111/j.0269-8463.2004.00856.x Speakman JR, Thomas DW (2003) Physiological ecology and energetics of bats. In: Kunz TH, Fenton MB (eds) Bat Ecology. University of Chicago Press, Chicago, pp 430–490. Stawski C, Geiser F (2010) Fat and fed: frequent use of summer torpor in a subtropical bat. Naturwissenschaften 97:29–35. https://doi.org/10.1007/s00114-009-0612-x Vuarin P, Dammhahn M, Kappeler PM, Henry PY (2015) When to initiate torpor use? Food availability times the transition to winter phenotype in a tropical heterotherm. Oecologia 179:43–53. https://doi.org/10.1007/s00442-015-3328-0 Vuarin P, Henry PY (2014) Field evidence for a proximate role of food shortage in the regulation of hibernation and daily torpor: a review. J Comp Physiol B 184:683–697. https://doi.org/10.1007/s00360-014-0820-0 Wang LC, Wolowyk MW (1988) Torpor in mammals and birds. Can J Zool 66:133–137. https://doi.org/10.1139/z88-019 Wilkinson GS, Brunet-Rossinni AK (2009) Methods for age estimation and the study of senescence in bats. In: Kunz TH, Parsons S (eds) Ecological and Behavioral Methods for the Study of Bats. Johns Hopkins University Press, Baltimore, pp 315–325 Willis CK, Brigham RM (2007) Social thermoregulation exerts more influence than microclimate on forest roost preferences by a cavity-dwelling bat. Behav Ecol Sociobiol 62:97–108. https://doi.org/10.1007/s00265-007-0442-y Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9500426","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":631931433,"identity":"cdf5f20c-e80d-4906-9cc2-6d32901c41e4","order_by":0,"name":"Jorge Ayala-Berdon","email":"data:image/png;base64,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","orcid":"","institution":"SECIHTI, Universidad Autónoma de Tlaxcala, Tlaxcala de Xicohténcatl","correspondingAuthor":true,"prefix":"","firstName":"Jorge","middleName":"","lastName":"Ayala-Berdon","suffix":""},{"id":631931444,"identity":"03042e40-9ff1-481d-a3e6-433ad271ef68","order_by":1,"name":"Kevin I. Medina-Bello","email":"","orcid":"","institution":"Universidad Autónoma de Tlaxcala, Tlaxcala de Xicohténcatl","correspondingAuthor":false,"prefix":"","firstName":"Kevin","middleName":"I.","lastName":"Medina-Bello","suffix":""},{"id":631931446,"identity":"b02bb06d-7e8d-4f46-9946-ee9e90ce948e","order_by":2,"name":"Jorge E. Schondube","email":"","orcid":"","institution":"Universidad Nacional Autónoma de México","correspondingAuthor":false,"prefix":"","firstName":"Jorge","middleName":"E.","lastName":"Schondube","suffix":""},{"id":631931448,"identity":"8b4c45e0-795d-428a-84b3-21d5a1ad4f9f","order_by":3,"name":"Margarita Martínez-Gómez","email":"","orcid":"","institution":"Universidad Autónoma de Tlaxcala, Tlaxcala de Xicohténcatl","correspondingAuthor":false,"prefix":"","firstName":"Margarita","middleName":"","lastName":"Martínez-Gómez","suffix":""}],"badges":[],"createdAt":"2026-04-22 21:53:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9500426/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9500426/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108499917,"identity":"9be94542-f5ee-47d7-8b39-64fc86fe2aed","added_by":"auto","created_at":"2026-05-05 10:31:43","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":504711,"visible":true,"origin":"","legend":"\u003cp\u003eLocation of the study area in Santa Cruz Moxolahuac, Puebla, within the montane coniferous forest of central Mexico. \u0026nbsp;The inset map shows the position of the study site within Mexico, while the enlarged panel indicates the sampling locality (black polygon). \u0026nbsp;Bats were captured during the dry-cold season from early October 2021 to late February 2022. \u0026nbsp;Base map created with MapChart (https://www.mapchart.net) and edited in GIMP-3.0.8 (https://www.gimp.org).\u003c/p\u003e","description":"","filename":"Fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9500426/v1/b7a984a4701c2600d9d6222f.jpg"},{"id":108804726,"identity":"6292b83f-2f25-42c4-8a0e-f1b84270d3f5","added_by":"auto","created_at":"2026-05-08 15:23:00","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":481984,"visible":true,"origin":"","legend":"\u003cp\u003eA) Simple slopes of the interaction between standardized energy intake and ambient temperature (Ta) on torpid metabolic rate during the cooling phase in energy-supplied bats. \u0026nbsp;The negative relationship between energy intake and torpid metabolic rate became progressively weaker as Ta increased, being strongest at low Ta (β = -0.49), intermediate at mean Ta (β = -0.34), and weakest at high Ta (β = -0.19). B) Johnson-Neyman plot showing the conditional effect of energy intake on torpid metabolic rate across the range of ambient temperatures. \u0026nbsp;The effect of intake was statistically significant at Ta values below 22.32 ºC (vertical dashed line), encompassing nearly the entire temperature range (13-24 ºC; tick horizontal line). \u0026nbsp;Shaded areas represent 95 % confidence intervals around the conditional effect (simple slope) of energy intake on torpid metabolic rate.\u003c/p\u003e","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9500426/v1/2becccad050d6c1d76a913f3.jpg"},{"id":108499919,"identity":"93545620-5e0f-4d7f-a472-9caa6dc88b1c","added_by":"auto","created_at":"2026-05-05 10:31:43","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":306585,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between centered body mass (\u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e) and minimum torpid metabolic rate under different energetic states.\u0026nbsp; In energy-supplied individuals, minimum torpid metabolic rate tended to decline with increasing \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb \u003c/em\u003e\u003c/sub\u003e(β = -2.63), whereas in energy-restricted individuals the relationship was reversed, with larger individuals exhibiting higher minimum torpid metabolic rates (β = 1.96).\u0026nbsp; Points represent individual observations, lines show model predictions, and shaded areas indicate 95 % confidence intervals\u003c/p\u003e","description":"","filename":"Fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9500426/v1/801cc73e374aa468491b4d5e.jpg"},{"id":108976529,"identity":"8c29adf7-1359-4041-91a1-6f0dbbfaa696","added_by":"auto","created_at":"2026-05-11 11:24:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1459829,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9500426/v1/7ce42972-5b89-4c95-bd17-7f9784b1766c.pdf"},{"id":108499916,"identity":"5fb65c00-6f9f-47e3-8795-d88c453fdb08","added_by":"auto","created_at":"2026-05-05 10:31:43","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":13193,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9500426/v1/be73289f5402094ec16ca061.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Energy intake, body mass, and ambient temperature jointly regulate torpid metabolic rate in the big brown bat (Eptesicus fuscus)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSmall endotherms are exposed to pronounced daily and seasonal fluctuations in ambient temperature (\u003cem\u003eTₐ\u003c/em\u003e) and resource availability, conditions that can generate recurrent imbalances in their energy budgets (K\u0026ouml;rtner and Geiser \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Vuarin et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Because of their high surface-to-volume ratio, these organisms experience elevated heat loss and consequently incur high metabolic costs to maintain homeothermy (McNab \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1969\u003c/span\u003e). To cope with these energetic challenges, many species employ torpor, a reversible physiological state characterized by controlled reductions in metabolic rate, body temperature (\u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e), heart rate, and other physiological processes (Geiser \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Wang and Wolowyk \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Geiser \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). By reducing metabolic expenditure, torpor allows animals to conserve energy during periods when environmental conditions or food availability limit energy acquisition.\u003c/p\u003e \u003cp\u003eThe depth and duration of torpor are influenced by multiple factors, including ambient temperature (\u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e), body mass (\u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e), and food availability (Geiser \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Ambient temperature strongly affects torpor expression because metabolic heat production is largely determined by the thermal gradient between \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e and the surrounding environment (Geiser \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Ruf and Geiser \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Lower \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003es generally facilitate deeper reductions in metabolic rate by promoting passive heat loss, whereas higher \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003es limit the extent of metabolic suppression. Body mass can also influence torpor physiology through its effects on metabolic scaling and thermal conductance. Smaller mammals typically have higher mass-specific metabolic rates and greater heat loss due to their larger surface-to-volume ratios, which may allow them to reach lower metabolic rates during torpor compared with larger individuals (Speakman and Thomas \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Riek and Geiser \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFood availability is another major driver of torpor use. In many species, torpor is primarily interpreted as a strategy to cope with energetic constraints, such that individuals experiencing food limitation or low energy reserves exhibit deeper or more frequent torpor bouts (K\u0026ouml;rtner and Geiser \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Boyles et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Landry-Cuerrier et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Doucette et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). However, growing evidence suggests that torpor expression may also depend on the energetic state of individuals in more complex ways. For example, some heterothermic mammals exhibit deeper or longer torpor bouts when food availability is high, potentially allowing individuals to conserve energy in anticipation of future resource scarcity or to optimize energy budgets under variable environmental conditions (Stawski and Geiser \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Humphries et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Vuarin and Henry \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Despite these advances, the combined effects of energetic state and environmental conditions on the regulation of torpor metabolic rate remain poorly understood.\u003c/p\u003e \u003cp\u003eBats are particularly suitable models for studying the drivers of torpor expression because many species regularly employ daily torpor or seasonal hibernation to cope with fluctuating environmental conditions (Geiser and Brigham \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The big brown bat (\u003cem\u003eEptesicus fuscus\u003c/em\u003e) is a widely distributed insectivorous bat species that uses torpor extensively during cold periods and food shortages. However, the combined effects of \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e energy intake, and \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e on torpid metabolic regulation remain poorly understood. In particular, it remains unclear whether torpor expression is primarily driven by environmental conditions or whether the energetic state of individuals modulates the depth of metabolic suppression.\u003c/p\u003e \u003cp\u003eIn this study, we experimentally manipulated energy intake and measured metabolic responses across a range of \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e to evaluate how \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e, energy intake, and \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e influence torpid metabolic rate in \u003cem\u003eE. fuscus\u003c/em\u003e. We hypothesized that torpor expression is jointly determined by environmental conditions and the energetic state of individuals. Under this framework, torpid metabolic rate during cooling should reflect dynamic metabolic regulation across the thermal gradient, while the minimum torpid metabolic rate achieved by individuals may represent a physiological limit to metabolic suppression that depends on the energetic state of bats. By disentangling these mechanisms, our study provides new insights into how environmental conditions and energetic state jointly regulate torpor expression, revealing how dynamic metabolic responses during cooling interact with physiological limits to metabolic suppression in heterothermic bats.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy site\u003c/h2\u003e \u003cp\u003eBats were captured during the dry-cold season (early October 2021 to late February 2022) in Santa Cruz Moxolahuac, a montane ecosystem located in Puebla, central Mexico (3,121 m a.s.l.; 19\u0026ordm; 27' 2.188'' N, 98\u0026ordm; 34' 10.131'' W) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The site has a temperate subhumid cold climate and is dominated by coniferous forests, including oyamel (\u003cem\u003eAbies religiosa\u003c/em\u003e), Hartweg\u0026rsquo;s pine (\u003cem\u003ePinus hartwegii\u003c/em\u003e), and Moctezuma\u0026rsquo;s pine (\u003cem\u003eP. montezumae\u003c/em\u003e). Mean \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e during the study period was 9.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07 (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SE).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eBat capture and housing\u003c/h3\u003e\n\u003cp\u003eBats were captured using mist nets (2 x 6 and 2 x 12 m) placed near water bodies used for foraging and drinking. Nets were opened at dusk and closed at \u0026sim; 24:00 hours. Only adult, non-reproductive males (n\u0026thinsp;=\u0026thinsp;8) were selected to avoid potential confounding effects of sex and reproductive condition. Body mass was measured using a digital balance (Ohaus, Newark, New Jersey, USA; \u0026plusmn; 0.2 g), and forearm length was measured to the nearest 0.1 mm using calipers. Age class was determined by examining the epiphyseal gap in the fourth metacarpal of the third and fifth fingers, following Wilkinson and Brunet-Rossinni (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). After capture, bats were transported in cloth bags to the experimental facility and housed in flight cages (75 \u0026times; 75 \u0026times; 75 cm) under controlled conditions (12 h:12 h light-dark cycle, Ta\u0026thinsp;~\u0026thinsp;28\u0026deg;C, a relative humidity above 50%). Water was provided \u003cem\u003ead libitum\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eThe experimental protocol followed a standardized sequence. After capture, bats were fasted for 6\u0026ndash;8 h to ensure post-absorptive state. Basal metabolic rate and thermal critical temperatures (lower critical temperature \u0026mdash;\u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003eLC\u003c/em\u003e\u003c/sub\u003e\u0026mdash; and upper critical temperature \u0026mdash;\u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003eUC\u003c/em\u003e\u003c/sub\u003e\u0026mdash;) were measured the following day under standardized conditions (see below). Subsequently, bats were subjected to two energy availability treatments in a repeated-measures design:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eEnergy-supplied condition. Individuals were fed mealworms \u003cem\u003ead libitum\u003c/em\u003e at 20:00 h, coinciding with the onset of natural foraging activity (Rydell et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Grindal and Brigham 1999). Torpor measurements were conducted during the subsequent light phase (inactive period), approximately 12\u0026ndash;13 hours after feeding.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eEnergy-restricted condition. Following completion of the energy-supplied trial, bats were deprived of food for 36 h, a duration that may reflect short-term energy limitations under natural conditions (Grindal and Brigham \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). This deprivation period included the intervening light phase, to ensure torpor assessment at the same circadian stage in both treatments. In this design, each individual served as its own control across treatments.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThe energy-supplied treatment was conducted first for all individuals to avoid prolonged fasting immediately after capture and to standardize the duration of food restriction of 36 h.\u003c/p\u003e\n\u003ch3\u003eRespirometry\u003c/h3\u003e\n\u003cp\u003eMetabolic measurements were obtained using open-flow indirect calorimetry (FoxBox\u0026reg;, Sable Systems International, Las Vegas, NV, USA) recording O\u003csub\u003e2\u003c/sub\u003e consumption and CO\u003csub\u003e2\u003c/sub\u003e production simultaneously, which provides accurate metabolic rate estimates in terrestrial endotherms (Lighton \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Each bat was placed in a 410 mL metabolic chamber located within a temperature-controlled cabinet (Pelt-drop-in\u0026reg;, Sable Systems International). Plastic mesh allowed individuals to hang in a natural posture while preventing flight activity. Ambient temperature inside the cabinet was controlled to \u0026plusmn;\u0026thinsp;0.5\u0026deg;C using a precision controller (Pelt5\u0026reg;, Sable Systems International). Dry CO\u003csub\u003e2\u003c/sub\u003e-free air, scrubbed upstream using drierite (calcium sulfate) and ascarite (sodium hydroxide) was pushed through the chamber at 150 mL min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, adjusted according to the expected metabolic rates following Lighton and Halsey (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Flow rates were verified using a calibrated flowmeter. Excurrent air was dried before analysis, and fractional concentrations (%/100) of both O\u003csub\u003e2\u003c/sub\u003e (FeO\u003csub\u003e2\u003c/sub\u003e) and CO\u003csub\u003e2\u003c/sub\u003e (FeCO\u003csub\u003e2\u003c/sub\u003e) were recorded every second. To correct for instrumental drift, an empty chamber (410 mL) of identical volume was maintained under identical conditions and monitored in a second calibrated FoxBox\u0026reg; system. Data from the empty chamber were used to correct baseline drift.\u003c/p\u003e\n\u003ch3\u003eBasal metabolic rate, and thermal critical temperatures\u003c/h3\u003e\n\u003cp\u003eTorpor is a controlled hypometabolic state characterized by a substantial reduction in metabolic rate below \u003cem\u003eBMR\u003c/em\u003e. Basal metabolic rate represents the minimal metabolic rate within the thermoneutral zone (\u003cem\u003eTNZ\u003c/em\u003e), bounded by \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003eLC\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003eUC\u003c/em\u003e\u003c/sub\u003e (Speakman and Thomas \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Geiser \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Genoud et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Each bat was first maintained at 28\u0026deg;C (within the \u003cem\u003eTNZ\u003c/em\u003e; Ayala-Berdon and Medina-Bello 2025) for 60 min to allow acclimation, followed by a 30 min recording period. Ambient temperature was then gradually reduced to 8\u0026deg;C. During cooling, metabolic rate was recorded at 1\u0026deg;C intervals (5 min per \u0026ordm;C) and at 5 \u0026ordm;C intervals (30 min per step) to determine \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003eLC\u003c/em\u003e\u003c/sub\u003e. After returning to 28 \u0026ordm;C for 30 min, temperature was increased to 43 \u0026ordm;C following the same protocol to determine \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003eUC\u003c/em\u003e\u003c/sub\u003e. If torpor was initiated during this procedure, \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e was returned to the \u003cem\u003eTNZ\u003c/em\u003e and the protocol restarted to ensure measurements reflected euthermic responses. All individuals remained normothermic during these trials, as indicated by the expected increase in metabolic rate below \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003eLC\u003c/em\u003e\u003c/sub\u003e and above \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003eUC\u003c/em\u003e\u003c/sub\u003e.\u003c/p\u003e\n\u003ch3\u003eTorpor trials under contrasting energy availability\u003c/h3\u003e\n\u003cp\u003eFollowing \u003cem\u003eBMR\u003c/em\u003e and thermal limit determination, torpor trials were conducted under both energy treatments. Bats were placed in the chamber at 28 \u0026ordm;C for 60 min and metabolic rate was recorded for 75 minutes before cooling. Ambient temperature was then gradually reduced to 8\u0026deg;C. During cooling, metabolic rate was recorded at 1\u0026deg;C intervals (5 minutes per \u0026ordm;C) with extended recordings at 23, 18, 13, and 8\u0026deg;C (75 min per step) to improve detection of torpid metabolic rate. Minimum torpid metabolic rate was defined as the lowest stable metabolic rate maintained approximately two hours below the threshold \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e at which metabolic rate stabilized (Ayala-Berdon and Medina-Bello \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Metabolic rate values obtained at each 1 \u0026ordm;C step during cooling were used to analyze the temperature-dependent trajectory of torpid metabolic rate, whereas minimum torpid metabolic rate was estimated from the stable asymptote once metabolic rate had plateaued. After reaching 8 \u0026ordm;C, \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e was returned to 28\u0026deg;C for 30 min to minimize rewarming costs. Upon completion of all experimental trials, bats were released at their capture site.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMetabolic rate calculations\u003c/h2\u003e \u003cp\u003eWe calculated O\u003csub\u003e2\u003c/sub\u003e consumption (V̇O₂) (in mL O\u003csub\u003e2\u003c/sub\u003e h\u003csup\u003e\u0026minus;1\u003c/sup\u003e) following Lighton (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e):\u003c/p\u003e \u003cp\u003eV̇O₂ = FR [(FiO\u003csub\u003e2\u003c/sub\u003e-FeO\u003csub\u003e2\u003c/sub\u003e)-FeO\u003csub\u003e2\u003c/sub\u003e(FeCO\u003csub\u003e2\u003c/sub\u003e-FiCO\u003csub\u003e2\u003c/sub\u003e)]/(1-FeO\u003csub\u003e2\u003c/sub\u003e)\u003c/p\u003e \u003cp\u003eWhere FR is the flow rate (mL min\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup1;), FiO₂ and FeO₂ represent the fractional concentration of O₂ in the incurrent and excurrent air, respectively, while FiCO₂ and FeCO₂ correspond to the fractional concentration of CO₂ in the incurrent and excurrent air. Mean metabolic rates were calculated from continuous recordings (1s resolution) at each temperature step.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStatistical analyses\u003c/h3\u003e\n\u003cp\u003eAll analyses were conducted in R (version 4.4.0). Critical temperatures and minimum torpid metabolic rate were determined using broken-stick models (Ayala-Berdon and Medina-Bello \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). We fitted linear regressions with the \u0026ldquo;lm\u0026rdquo; function from the \u0026ldquo;stats\u0026rdquo; package. In these models, experimental temperatures were the independent variables, and the mean values of the metabolic rate, the dependent variable. We estimated the inflection points of the regression models by using the \u0026ldquo;davies.test\u0026rdquo; function of the \u0026ldquo;segmented\u0026rdquo; package (Muggeo \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). When individuals were in a euthermic state, the two inflection points represented \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003eLC\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003eUC\u003c/em\u003e\u003c/sub\u003e. During torpid state, the points indicated the \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e at which animals entered torpor (first inflection point) and the \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e at which torpid metabolic rate approached its minimum values (second inflection point).\u003c/p\u003e \u003cp\u003eWe first evaluated determinants of temperature-dependent trajectory of torpid metabolic rate during cooling under the energy-supplied condition. Torpid metabolic rate measured at each 1 \u0026ordm;C step was modeled as a function of centered \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e, standardized energy intake, standardize \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e and the intake * \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e interaction. Because measurements were repeated within individuals, we initially fitted mixed-effect models including individual identity as a random intercept. However, the random-intercept variance was estimated as ~\u0026thinsp;0 (singular fit), indicating negligible residual clustering after accounting for fixed effects. Consequently, the mixed model reduced to the corresponding fixed-effects model. To evaluate whether the effect was strongest under cold conditions, we tested the intake * \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e interaction and quantified simple slopes of intake at low (-1 SD), mean (0), and high (+\u0026thinsp;1 SD) \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e. Additionally, we applied the Johnson-Neyman procedure to identify the range of \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e values over which the intake effect was statistically significant.\u003c/p\u003e \u003cp\u003eTo examine whether minimum torpid metabolic rate differed between energy treatments, we fitted a mixed-effects models with treatment as fixed effect and individual identity as a random intercept (\"lmer\" function from the \"lme4\" package). Because treatment groups could differ in \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e, we first compared \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e between treatments (Wilcoxon rank-sum test). Because \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e differed between treatments, we further evaluated a model including centered \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e and the treatment * \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e interaction to assess whether energetic state modified the scaling relationship between \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e and minimum torpid metabolic rate. Given the small number of individuals (G\u0026thinsp;=\u0026thinsp;8), we conducted sensitivity analyses for both models using small-sample cluster-robust standard errors (CR2 estimator with Satterthwaite degrees of freedom) clustered by individual identity. Significance was assessed using likelihood ratio test comparing full and reduced models for the mixed-effect models and confirmed with small-sample cluster-robust inference for both models.\u003c/p\u003e \u003cp\u003eIn both sets of analyses, torpid metabolic rate was log-transformed to meet assumptions of normality and homoscedasticity. Slopes (β) were extracted from the model summaries. Statistical significance was assessed at ⍺ \u0026lt; 0.05. Data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error unless otherwise indicated.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eDuring cooling under the energy-supplied condition, small-sample cluster-robust inference (CR2) showed that torpid metabolic rate was significantly associated with centered \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e (β\u0026thinsp;=\u0026thinsp;5.91\u0026thinsp;\u0026plusmn;\u0026thinsp;1.06, p\u0026thinsp;=\u0026thinsp;0.007), standardized energy intake (β = -0.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06, p\u0026thinsp;=\u0026thinsp;0.008), standardized \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e (β\u0026thinsp;=\u0026thinsp;0.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03, p\u0026thinsp;=\u0026thinsp;0.001), and the intake * \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e interaction (β\u0026thinsp;=\u0026thinsp;0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02, p\u0026thinsp;=\u0026thinsp;0.003). The overall model explained 57% of the variance in log-transformed torpid metabolic rate (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.57). Simple slope analyses indicated that the negative association between intake and torpid metabolic rate was strongest at low \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e (-1 SD; β = -0.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 SE), intermediate at mean \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e (β = -0.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 SE), and weakest at high \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e (+\u0026thinsp;1 SD; β = -0.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07 SE) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Thus, the suppressive effect of intake progressively diminished as \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e increased. The Johnson-Neyman procedure indicated that the effect of intake on torpid metabolic rate was statistically significant at \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003es below 22.32 \u0026ordm;C (corresponding to 1.36 SD above the mean \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e). Because the observed temperature range spanned 13\u0026ndash;24 \u0026ordm;C, the intake effect was significant across nearly the entire thermal gradient and weakened only at the highest temperatures (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBody mass differed between treatments (Wilcoxon rank-sum test: W\u0026thinsp;=\u0026thinsp;64, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with energy-supplied bats being heavier (16.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29 g) than energy-restricted individuals (13.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25 g) (W\u0026thinsp;=\u0026thinsp;64, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Small-sample cluster-robust inference (CR2) indicated that treatment significantly affected minimum torpid metabolic rate (β\u0026thinsp;=\u0026thinsp;0.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11, p\u0026thinsp;=\u0026thinsp;0.003). In addition, the interaction between treatment and centered \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e was significant (β\u0026thinsp;=\u0026thinsp;4.58\u0026thinsp;\u0026plusmn;\u0026thinsp;1.48, p\u0026thinsp;=\u0026thinsp;0.03), indicating that the relationship between \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e and minimum torpid metabolic rate differed between energetic states. In energy-supplied individuals, minimum torpid metabolic rate tended to decline with increasing \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e (β = -2.63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05, t = -2.50, p\u0026thinsp;=\u0026thinsp;0.08). In contrast, in energy-restricted individuals the relationship was reversed, with larger individuals exhibiting higher minimum torpid metabolic rates (β\u0026thinsp;=\u0026thinsp;1.96 [derived from the treatment * \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e interaction]; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we found that torpor expression in \u003cem\u003eE. fuscus\u003c/em\u003e is jointly shaped by body mass (\u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e), energy intake, ambient temperature (\u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e), and the energetic state of individuals. Our results revealed two levels of torpor regulation. Torpid metabolic rate during cooling was influenced by \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e, energy intake, and \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e, indicating dynamic metabolic regulation across the thermal gradient. In contrast, minimum torpid metabolic rate \u0026mdash;representing the physiological limit of metabolic suppression within the range of \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e tested\u0026mdash; depended on the interaction between \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e and the energetic state of individuals.\u003c/p\u003e \u003cp\u003eTorpid metabolic rate during cooling increased with \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e. Body mass is a key morphological trait influencing thermal physiology across mammals, affecting variables such as \u003cem\u003eBMR\u003c/em\u003e and critical temperatures (e.g., Savage et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Kozłowski et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Speakman and Thomas \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Farrell-Gray and Gotelli \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; McNab \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Riek and Geiser \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2013\u003c/span\u003e, Ayala-Berdon et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2025\u003c/span\u003e, among others). Because metabolically active tissue generally scales with body size, larger individuals are expected to exhibit higher absolute metabolic rates, even during torpor. In addition, smaller bats tend to have higher mass-specific thermal conductance, which promotes faster passive cooling and may allow them to reach lower metabolic rates during torpor (Geiser \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This pattern is consistent with the greater heat loss experienced by smaller endotherms due to their higher surface-to-volume ratio.\u003c/p\u003e \u003cp\u003eAmbient temperature also played an important role in shaping torpid metabolic rate during cooling. As expected, torpid metabolic rate increased with \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e, reflecting the strong influence of the thermal gradient between \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e and the surrounding environment on metabolic heat production. In heterothermic mammals, reductions in metabolic rate during torpor are closely linked to passive heat exchange with the environment, such that lower \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u0026acute;\u003c/em\u003e\u003c/sub\u003es facilitate deeper metabolic depression by promoting greater heat loss (Geiser \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Ruf and Geiser \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Geiser \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Consequently, individuals exposed to colder conditions can achieve lower metabolic rates during torpor, whereas higher \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003es limit the extent of metabolic suppression. This temperature dependence highlights the importance of the thermal environment in determining the energetic benefits of torpor in bats across different energetic conditions and provides a physiological context for the interaction between \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e and energy intake observed in our models.\u003c/p\u003e \u003cp\u003eTorpid metabolic rate during cooling decreased with increasing energy intake. At first glance, this pattern appears to contrast with the traditional view that torpor is primarily used by animals experiencing energy constraints (K\u0026ouml;rtner and Geiser \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Boyles et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Landry-Cuerrier et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Doucette et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). However, for small torpor-users or hibernators facing low prey availability and low \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e, deeper reductions in metabolic rate when individuals possess greater energetic reserves may increase survival during prolonged periods of harsh environmental conditions (Geiser \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Ruf and Geiser \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Deep torpor may also facilitate temporal resource partitioning and reduce intraspecific competition. Asynchrony in periods of activity, such as the timing of emergence, may allow differentiated use of the environment, preventing all individuals from accessing the same resources simultaneously (Kronfeld-Schor and Dayan \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Interestingly, we also detected an interaction between energy intake and \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e. Simple slope analyses indicated that the negative effect of energy intake on torpid metabolic rate was strongest at low \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e, intermediate at moderate \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e, and weakest at high \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e. Moreover, the effect of intake remained statistically significant across nearly the entire range of \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e tested. This pattern suggests that individuals with higher energy intake may be able to actively suppress metabolism more deeply, particularly at low \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e where energetic demands are greatest. Together, these results indicate that the thermal environment modulates the influence of energy intake on torpid metabolic rate during cooling in \u003cem\u003eE. fuscus\u003c/em\u003e, which may help explain why bats often select cold hibernation roosts, particularly when individuals possess sufficient energetic reserves to sustain deep metabolic suppression (Boyles et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Willis and Brigham \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Conversely, individuals in poorer energetic condition may benefit from occupying slightly warmer roosts, where metabolic regulation may be less energetically demanding.\u003c/p\u003e \u003cp\u003eBeyond the dynamic regulation of torpid metabolic rate observed during cooling, our results also revealed variation in the minimum torpid metabolic rate achieved by individuals, representing the physiological limit of metabolic suppression under the experimental conditions. Metabolic inhibition during cooling is expected to influence the minimum torpid metabolic rate achieved under different energetic conditions. Because the strongest reduction in torpid metabolic rate occurred in bats with higher energy intake at the lowest \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e, energy-supplied individuals were expected to reach lower minimum torpid metabolic rates, which are typically achieved at colder \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003es. Consistent with this expectation, energy-supplied bats exhibited lower minimum torpid metabolic rates. A similar pattern has been reported for the greater long-eared bat (\u003cem\u003eNyctophilus bifax\u003c/em\u003e) and fat-tailed dwarf lemurs (\u003cem\u003eMicrocebus griseorufus\u003c/em\u003e), where individuals expressed deeper and longer torpor bouts during periods of increased food availability (Stawski and Geiser \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Kobbe et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Vuarin et al. 2013). According to these authors, deeper and prolonged torpor bouts may reduce predation risk by shortening periods of activity or conserve energy in anticipation of future resource scarcity. Importantly, our models also revealed an interaction between \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e and energetic treatment: minimum torpid metabolic rate declined with increasing \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e in energy-supplied individuals, whereas the relationship was reversed in energy-restricted bats. This pattern suggests that larger individuals with sufficient energy reserves may achieve deeper metabolic suppression, possibly due to their lower surface-to-volume ratios and greater fuel availability. In contrast, when energy is limited, larger bats may be unable to suppress metabolism to the same extent because maintenance costs remain higher. Nevertheless, the physiological mechanisms underlying this interaction require further investigation to better understand how energetic state and \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e jointly determine the limits of metabolic suppression.\u003c/p\u003e \u003cp\u003eTogether, our results demonstrate that torpor regulation in \u003cem\u003eE. fuscus\u003c/em\u003e operates at two complementary physiological levels: dynamic modulation of metabolic rate during cooling and intrinsic limits to metabolic suppression determined by \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e and energetic state. By integrating these mechanisms, individuals can flexibly adjust energy expenditure under varying thermal and energetic conditions. Such flexibility may play an important role in determining overwinter survival and roost selection strategies in heterothermic bats.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank O. Ju\u0026aacute;rez, and the staff of the \u0026quot;El Rey\u0026quot; site for their logistical support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was funded by the CONACYT program (Consejo Nacional de Humanidades, Ciencias y Tecnolog\u0026iacute;as), currently the Secretar\u0026iacute;a de Ciencia, Humanidades, Tecnolog\u0026iacute;a e Innovaci\u0026oacute;n (SECIHTI) in Mexico, through the FOSEC CB2017\u0026ndash;2018 project (A1-S-39572).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors and Affiliations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSECIHTI, Centro Tlaxcala de Biolog\u0026iacute;a de la Conducta, Universidad Aut\u0026oacute;noma de Tlaxcala, Carretera Tlaxcala-Puebla Km. 1.5, C.P. 90062, Tlaxcala de Xicoht\u0026eacute;ncatl, Tlaxcala, Mexico\u003c/p\u003e\n\u003cp\u003eJorge Ayala-Berdon\u003c/p\u003e\n\u003cp\u003eDoctorado en Ciencias Biol\u0026oacute;gicas, Centro Tlaxcala de Biolog\u0026iacute;a de la Conducta, Universidad Aut\u0026oacute;noma de Tlaxcala. Carretera Tlaxcala-Puebla Km. 1.5, C.P. 90062, Tlaxcala de Xicoht\u0026eacute;ncatl, Tlaxcala, Mexico\u003c/p\u003e\n\u003cp\u003eKevin I. Medina-Bello\u003c/p\u003e\n\u003cp\u003eInstituto de Investigaciones en Ecosistemas y Sustentabilidad, Universidad Nacional Aut\u0026oacute;noma de M\u0026eacute;xico, Antigua Carretera a P\u0026aacute;tzcuaro No. 8701, Col. Ex-Hacienda de San Jos\u0026eacute; de La Huerta, C.P. 58190, Morelia Michoac\u0026aacute;n, M\u0026eacute;xico\u003c/p\u003e\n\u003cp\u003eJorge E. Schondube\u003c/p\u003e\n\u003cp\u003eUniversidad Autónoma de Tlaxcala, Tlaxcala de Xicohténcatl, Tlaxcala, Mexico\u003cbr\u003e\u0026nbsp;Departamento de Biología Celular y Fisiología, Universidad Nacional Autónoma de México, Tlaxcala de Xicohténcatl, Mexico. Carretera Tlaxcala-Puebla Km. 1.5, C.P. 90062, Tlaxcala de Xicoht\u0026eacute;ncatl, Tlaxcala, Mexico\u003c/p\u003e\n\u003cp\u003eMargarita Mart\u0026iacute;nez-G\u0026oacute;mez\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to Jorge Ayala-Berdon\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures\u0026nbsp;were conducted under permit of the Mexican Wildlife Department (Secretar\u0026iacute;a de Medio Ambiente y Recursos Naturales, SEMARNAT: SGPA/DGVS/06795/21) and approved by the ethics committee of the Universidad Aut\u0026oacute;noma de Tlaxcala and conducted in accordance with national guidelines for animal care.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSupplementary material is presented along with submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJ.A.B. and K.I.M. conceived and designed the study. J.A.B. analyzed the data. K.I.M.B. performed the experiments. All authors reviewed and wrote the final version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAyala-Berdon J, Medina-Bello KI (2024) Torpor energetics are related to the interaction between body mass and climate in bats of the family Vespertilionidae. J Exp Biol 227:jeb246824. https://doi.org/10.1242/jeb.246824\u003c/li\u003e\n\u003cli\u003eAyala-Berdon J, Medina-Bello KI, Carballo-Morales JD, Salda\u0026ntilde;a-V\u0026aacute;zquez RA, Villalobos F (2025) Thermal energetics of bats of the family Vespertilionidae: an evolutionary approach. Zoology 170:126271. https://doi.org/10.1016/j.zool.2025.126271\u003c/li\u003e\n\u003cli\u003eBoyles JG, Dunbar MB, Storm JJ, Brack V Jr (2007) Energy availability influences microclimate selection of hibernating bats. 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University of Chicago Press, Chicago, pp 430\u0026ndash;490.\u003c/li\u003e\n\u003cli\u003eStawski C, Geiser F (2010) Fat and fed: frequent use of summer torpor in a subtropical bat. Naturwissenschaften 97:29\u0026ndash;35. https://doi.org/10.1007/s00114-009-0612-x\u003c/li\u003e\n\u003cli\u003eVuarin P, Dammhahn M, Kappeler PM, Henry PY (2015) When to initiate torpor use? Food availability times the transition to winter phenotype in a tropical heterotherm. Oecologia 179:43\u0026ndash;53. https://doi.org/10.1007/s00442-015-3328-0\u003c/li\u003e\n\u003cli\u003eVuarin P, Henry PY (2014) Field evidence for a proximate role of food shortage in the regulation of hibernation and daily torpor: a review. J Comp Physiol B 184:683\u0026ndash;697. https://doi.org/10.1007/s00360-014-0820-0\u003c/li\u003e\n\u003cli\u003eWang LC, Wolowyk MW (1988) Torpor in mammals and birds. Can J Zool 66:133\u0026ndash;137. https://doi.org/10.1139/z88-019\u003c/li\u003e\n\u003cli\u003eWilkinson GS, Brunet-Rossinni AK (2009) Methods for age estimation and the study of senescence in bats. In: Kunz TH, Parsons S (eds) Ecological and Behavioral Methods for the Study of Bats. Johns Hopkins University Press, Baltimore, pp 315\u0026ndash;325\u003c/li\u003e\n\u003cli\u003eWillis CK, Brigham RM (2007) Social thermoregulation exerts more influence than microclimate on forest roost preferences by a cavity-dwelling bat. Behav Ecol Sociobiol 62:97\u0026ndash;108. https://doi.org/10.1007/s00265-007-0442-y\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"ambient temperature, energetic state, metabolic suppression, heterothermy, torpor","lastPublishedDoi":"10.21203/rs.3.rs-9500426/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9500426/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSmall endotherms frequently experience fluctuations in ambient temperature (\u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e) and food availability that challenge the maintenance of energy balance. Many species cope with these conditions by entering torpor, a reversible physiological state characterized by reductions in metabolic rate and body temperature (\u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e). Although \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e, body mass (\u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e), and food availability are known to influence torpor expression, how environmental conditions interact with the energetic state of individuals to regulate torpid metabolism remains poorly understood. We experimentally manipulated energy intake and measured metabolic responses across a range of \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e to evaluate how \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e, energy intake, and \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e influence torpid metabolic rate in the big brown bat (\u003cem\u003eEptesicus fuscus\u003c/em\u003e). Torpid metabolic rate during cooling increased with \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e but decreased with increasing energy intake. In addition, the influence of energy intake on torpid metabolic rate depended on \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e, with the strongest reductions occurring at lower \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003es. Minimum torpid metabolic rate also differed between energetic treatments and was influenced by an interaction between \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e and energetic state. Energy-supplied individuals reached lower minimum torpid metabolic rates than energy-restricted bats, suggesting that energetic condition modulates the physiological limits of metabolic suppression. Together, these results reveal two complementary levels of torpor regulation in \u003cem\u003eE. fuscus\u003c/em\u003e: dynamic metabolic responses during cooling shaped by \u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e, and energy intake, and intrinsic limits to metabolic suppression determined by body size and energetic state. Our findings highlight the joint roles of environmental and physiological factors in shaping torpor expression in heterothermic mammals.\u003c/p\u003e","manuscriptTitle":"Energy intake, body mass, and ambient temperature jointly regulate torpid metabolic rate in the big brown bat (Eptesicus fuscus)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-05 10:31:33","doi":"10.21203/rs.3.rs-9500426/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"45ee5b3b-26b0-4564-b3f0-177fe912dbd8","owner":[],"postedDate":"May 5th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"321479185076885221217393017297478556908","date":"2026-04-29T16:42:24+00:00","index":21,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-05T10:31:33+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-05 10:31:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9500426","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9500426","identity":"rs-9500426","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}