Variation in upper thermal tolerance among 19 species from temperate wetlands

1 This is the peer reviewed version of the article accepted for publication in Journal of Thermal 1 Biology, Volume 96, 2021, 102856, which has been published in final form at 2 https://doi.org/10.1016/j.jtherbio.2021.102856 It is deposited under the terms of the Creative 3 Commons Attribution-NonCommercial-NoDerivatives License 4 (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, 5 distribution, and reproduction in any medium, provided the original work is properly cited, 6 and is not altered, transformed, or built upon in any way.” 7 Running Title: CTmax variation in wetlands 8 9 Variation in upper thermal tolerance among 19 species from temperate wetlands 10 11 Marco Katzenberger 1, 2*, Helder Duarte 1, Rick Relyea 3, 4, Juan Francisco Beltrán 5, Miguel 12 Tejedo 1 13 14 1 Department of Evolutionary Ecology, Estación Biológica Doñana, CSIC, c/ Américo 15 Vespucio s/n, 41092 Sevilla, Spain 16 2 Laboratório de Bioinformática e Biologia Evolutiva, Department of Genetics, Universidade 17 Federal de Pernambuco, Av. Prof. Moraes Rego, 1235 - Cidade Universitária, CEP 18 50670-901 Recife, Pernambuco, Brazil 19 3 Darrin Fresh Water Institute, Department of Biological Sciences, Rensselaer Polytechnic 20 Institute, Troy, NY 12180 USA 21 4 Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA 15260, USA 22 5 Departament of Zoology, Universidad de Sevilla, Avda. Reina Mercedes s/n, 41012-Sevilla, 23 Spain 24 25 * corresponding author. E-mail: [email protected] 26 ORCID iD: 0000-0003-0023-9655 27 2 ABSTRACT 28 Communities usually possess a multitude of interconnected trophic interactions within 29 food webs. Their regulation generally depends on a balance between bottom-up and top- 30 down effects. However, if sensitivity to temperature varies among species, rising 31 temperatures may change trophic interactions via direct and indirect effects. We examined 32 the critical thermal maximum (CTmax) of 19 species from temperate wetlands (insect 33 predators, amphibian larvae, zooplankton and amphipods) and determined if they vary in 34 their sensitivity to warming temperatures. CTmax differed between the groups, with predatory 35 insects having higher CTmax than amphibians (both herbivorous larval anurans and predatory 36 larval salamanders), amphipods and zooplankton. In a scenario of global warming, these 37 differences in thermal tolerance may affect top-down and bottom-up processes, particularly 38 considering that insect predators are more likely to maintain or improve their performance at 39 higher temperatures, which could lead to increased predation rates on the herbivores in the 40 food web. Further studies are needed to understand how the energy flows through 41 communities, how species’ energy budgets may change and whether other physiological and 42 behavioral responses (such as phenotypic plasticity and thermoregulation) can buffer or 43 increase these changes in the top-down regulation of wetland food webs. 44 45 Keywords: critical thermal maximum; top-down regulation; amphibians; insects; 46 zooplankton; climate change 47 3 1. INTRODUCTION 48 Predicting the impacts of climate change and understanding species’ responses to 49 accelerating environmental changes has been a major challenge for the scientific community. 50 There is increasing evidence that species’ phenologies and distributions are changing in 51 response to current climate change (e.g., Parmesan and Yohe 2003, Parmesan 2006). 52 Renewed interest in thermal physiology has produced large databases that enable a global 53 perspective of species’ physiological limits and their relation to the environment (e.g., 54 Deutsch et al., 2008; Duarte et al., 2012; Katzenberger et al., 2014; Sunday et al., 2014;). 55 These data have given new insights into how species (and some communities) may respond 56 to current and future climate change and are providing a general assessment of which taxa 57 may be the most vulnerable. 58 In spite of increasing information on the responses of species and populations to 59 climate change, robust models of ecological systems are still badly needed to forecast the 60 future state of communities and ecosystems under long-term environmental changes (Jochum 61 et al., 2012; Shurin et al., 2012). However, the multitude of factors that affect ecosystems and 62 their complex interactions have hindered the development of these models. Predicted 63 environmental changes include an increase in the frequency of heat waves and other extreme 64 events (Diffenbaugh and Ashfaq, 2010; Schär et al., 2004). Shifts in UV radiation, 65 precipitation and temperature patterns are expected to vary geographically (IPCC, 2013). 66 Furthermore, several aspects of the environment are simultaneously affected by geochemical 67 cycles and changes in these cycles may influence local environmental conditions 68 (Christensen et al., 2006; Vinebrooke et al., 2004). Apart from the physical environment data, 69 models should also incorporate information about species’ physiological and life-history 70 traits. Differential evolutionary responses of species’ physiological traits to climate change 71 may also promote shifts in community interactions, food web dynamics and ecosystem 72 4 processes (Coulson et al., 2011; Gilman et al., 2010). However, current experimental 73 evidence is limited (Jochum et al., 2012). Moreover, the direct effects on species’ physiology 74 and demographics may be further altered by indirect effects via ecological interactions in 75 food webs (Bothwell et al., 1994; Ockendon et al., 2014; Suttle et al., 2007). 76 The critical thermal maximum (CTmax) is the temperature at which an organism loses 77 its ability to avoid the conditions that will lead to its death (Cowles and Bogert, 1944). 78 Thermal performance curves are usually asymmetrical, with the interval between the 79 optimum temperature and the critical thermal maximum commonly characterized by a steep 80 decline in performance (Huey and Kingsolver, 1989). However, determining optimum 81 temperature is usually methodologically more difficult than determining CTmax (e.g., 82 Katzenberger et al. 2014). Since optimum temperature and CTmax have been established as 83 co-adaptive traits (Angilletta, 2009; Huey et al., 2009), a species with high CTmax is expected 84 to also have a high optimum temperature. Hence, determining interspecific variation in CTmax 85 and warming tolerance (the difference between CTmax and current environmental 86 temperatures) is a simple way to assess species vulnerability to the direct effects of climate 87 change (Deutsch et al., 2008; Tewksbury et al., 2008). 88 Current global warming may promote changes in species interactions and community 89 structure (Dell et al. 2011), particularly when species have contrasting thermal niches. A 90 reduction in available niche space for species with low heat tolerance can potentially enhance 91 density-dependent interactions, whereas species with high heat tolerance could benefit from 92 the release of competitive pressures (Diamond et al., 2017). Warm-adapted consumers are 93 also expected to exert increased top-down pressure, leading to a reduction in the biomass of 94 species from the lower trophic levels if the latter are less heat tolerant (Urban et al., 2017). 95 Species asymmetries in thermal responses may also affect the dynamics of consumer– 96 producer interactions due to differences in activation energies (the life-dinner principle) 97 5 (Dawkins and Krebs, 1979; Dell et al., 2014, 2011). Top predators may be closer to their 98 tolerance limits (Pincebourde et al., 2008; Twomey et al., 2012), with carnivores having peak 99 performances at temperatures 10ºC lower than herbivores (Dell et al., 2014; Voigt et al., 100 2003). However, much more information is needed to establish a comprehensive 101 generalization of thermal tolerance across trophic levels. 102 Differences in thermal tolerance across trophic levels may also affect top-down and 103 bottom-up effects in food webs (Relyea and Ricklefs, 2018). Warming can influence trophic 104 interactions and alter the relative importance of these top-down and bottom-up effects by 105 increasing the metabolic requirements of species (Dillon et al., 2010). Several studies have 106 demonstrated that top-down effects increase with warming, strengthening the trophic cascade 107 from consumers to producers (Hoekman, 2010; Jochum et al., 2012; Kratina et al., 2012; 108 O’Connor et al., 2009; Shurin et al., 2012). This occurs when the metabolic requirements of 109 consumers increase faster with temperature than that of producers (Allen et al., 2005), 110 resulting in an increase in consumer activities (Dillon et al., 2010; Hoekman, 2010; O’Connor 111 et al., 2009; Shurin et al., 2012). However, metabolic demands can increase faster than 112 feeding rates (Rall et al., 2010) and increased feeding rates may also lead to resource 113 competition. Moreover, decreased food intake may also reduce growth rates, reduce optimal 114 temperatures, and reduce upper thermal limits for growth (Huey and Kingsolver, 2019). 115 Therefore, in the long-term, consumers may suffer from reduced fitness, lower abundance 116 and reduced biomass when compared to producers, thereby weakening the top-down effects 117 (O’Connor et al., 2011). In addition, warming tends to favor organisms that compete better 118 for nutrients (Falkowski and Oliver, 2007) and smaller organisms (Daufresne et al., 2009; 119 Yvon-Durocher et al., 2011; Yvon-Durocher and Allen, 2012). Both of these factors should 120 influence community size structure and alter species composition (Yvon-Durocher et al., 121 2011). 122 6 We aimed to understand how the current climate-change scenario may affect a 123 temporary freshwater wetland community by determining the critical thermal maxima of 124 species from different trophic levels. The species include primary consumers (tadpoles, 125 zooplankton and amphipods) and secondary and tertiary consumers (salamander larvae and 126 predatory insects, respectively; Fig. 1). These taxa have been used to study the dynamics of 127 food web structure and the mechanisms controlling the bottom-up and top-down processes in 128 temperate wetlands for several decades (Jones et al., 2016; Leibold and Wilbur, 1992; Stoler 129 and Relyea, 2016; Wilbur, 1997). CTmax values may be phylogenetically constrained (Huey, 130 1982; Huey et al., 2009; Kellermann et al., 2012), although they are adaptively associated 131 with environmental temperatures even when controlling for phylogeny (e.g., Duarte et al. 132 2012). Hence, we expected to find differences in thermal physiology among higher 133 taxonomic groups (e.g., Duarte et al. 2012; Sunday et al. 2014) and among trophic levels. 134 Based on previous studies, we expected predatory insect species to have higher CTmax values 135 than amphibians (e.g., Sunday et al. 2014). We also expected body mass to be a good 136 predictor of upper thermal resistance across species of ectotherms (Klockmann et al., 2017), 137 although this relationship may not be evident within species (Duarte et al., 2012). 138 139 2. METHODS 140 2.1. Field collection and animal husbandry 141 In spring 2010, we collected 11 species of amphibians (egg masses), four species of 142 aquatic insects, three species of amphipods and one species of zooplankton (Cladocera) from 143 natural ponds and wetlands. Each species was collected at a single location (Tables 1-2). All 144 animals were brought to the Pymatuning Laboratory of Ecology (University of Pittsburgh), in 145 northwest Pennsylvania, USA. Microenvironmental pond temperatures were measured in 146 seven locations by placing HOBO Pendant® temperature dataloggers in most collection sites 147 7 at the deepest part of the pond (Table 2). When thermal stratification occurs, usually during 148 sunny days with little to no wind (Boeckman and Bidwell, 2015), these measurements are 149 assumed to represent the minimum environmental temperatures to which the animals are 150 exposed during the time period considered; other locations within the pond (shallower 151 locations or higher in the water column) presumably had higher temperatures (Bancroft et al., 152 2008; Boeckman and Bidwell, 2015; Oberle et al., 2019; Song et al., 2013). Water 153 temperature was recorded every 5–15 min during the period in which most species in the 154 community were present. 155 The species we used belong to different trophic levels of a wetland food web, 156 including herbivores, detritivores, and predators (Figure 1). Most of these species overlap in 157 distribution so they can co-occur (at least partially) and interact. Since feeding preferences of 158 anuran larvae depend on species and may include multiple resources, such as periphyton, 159 zooplankton, phytoplankton and detritus (Altig et al., 2007; Arribas et al., 2015; Carreira et 160 al., 2016; Montaña et al., 2019), we considered several potential energy pathways for this 161 group. In the laboratory, the zooplankton and amphipod species were kept in plastic 162 containers (40 x 25 x 20 cm) with approximately 10 L, to which an aliquot of filtered (397- 163 mm net) local pond water was added as source of algae. Aquatic insects were kept 164 individually in 500-mL plastic cups (filled with 400 mL of water) and fed tadpoles every 2 d. 165 Outdoor pools were filled with aged well water to accommodate the amphibian eggs. All egg 166 masses from the same species were placed together in the same pool. Tadpoles were then fed 167 rabbit pellets ad libitum and allowed to grow until reaching the desired developmental stage. 168 Moreover, salamander larvae were fed zooplankton ad libitum. 169 170 2.2. Critical thermal maximum assessment 171 8 Sets of amphibian aquatic larvae (anuran tadpoles and larval salamanders) were 172 brought indoors to acclimate for the experiment. Amphibian larvae were tested at a 173 developmental stage where they were able to swim freely and begin feeding independently. 174 In most anuran species, this occurs after reaching Gosner stage 25 (Gosner, 1960). Other 175 organisms were tested at the same developmental stage as they were when collected (Table 176 3). Amphibian larvae, insects, amphipods and zooplankton were kept at an acclimation 177 temperature of 20°C (approximately the average temperature experienced in the outdoor 178 pools), with a 12L:12D photoperiod, for four days, as in previous studies (Duarte et al., 2012; 179 Gutiérrez-Pesquera et al., 2016; Simon et al., 2015). This allowed to the animals to acclimate 180 to the lab temperature and stabilize their CTmax (Allen et al., 2012; Brattstrom, 1968; 181 Buchanan et al., 1988; Hutchison, 1961). After the acclimation period, the species were tested 182 for their CTmax (Brattstrom, 1968; Hutchison, 1961) using Hutchison’s dynamic method 183 (Lutterschmidt and Hutchison, 1997a). 184 The CTmax trials used a water bath which consisted of a 250-mL container filled with 185 200 mL of dechlorinated water at 20 °C placed within a larger 2-L container, set upon a 186 magnetic stirrer hotplate. Water temperature was measured in the smaller container, whereas 187 the magnetic stirrer was placed in the larger container to avoid perturbing the organisms. We 188 exposed the organisms to a constant heating rate of 1.0 °C min-1, as in previous studies 189 (Duarte et al., 2012; Simon et al., 2015). This heating rate is fast enough to avoid acclimation 190 during the CTmax trials but also slow enough to avoid both heat shock and a significant lag 191 between water and body temperatures (Lutterschmidt and Hutchison, 1997a, 1997b). While 192 approaching their upper thermal limit, organism first lose their righting response, then go 193 through a stage of complete immobility before reaching the onset of spasms, which precedes 194 death (Lutterschmidt and Hutchison, 1997a, 1997b). For tadpoles, the onset of spasms was 195 considered the experimental endpoint. In the case of the insects, amphipods and zooplankton, 196 9 since spasms could not be observed during the experiment, we used complete immobility as 197 the endpoint of the critical thermal tolerance experiments. Once CTmax was reached, we 198 placed all organisms into cooler water (20°C) to allow for complete recovery. Those 199 individuals unable to recover were excluded for the analyses. All experiments were approved 200 by the Institutional Animal Care and Use Committee from the University of Pittsburgh 201 (Protocol #12050451). 202 203 2.3. Statistical analysis 204 To determine how the upper thermal limits varied across species, we conducted a 205 generalized linear model (log-linked gamma distribution) using CTmax as the dependent 206 variable, species as a categorical factor and mass as a covariate (including the interaction 207 between species and mass). Although it is recommended to incorporate phylogenetic 208 information (Felsenstein, 1985; Garland Jr. et al., 1992), we could not implement a PGLS 209 analysis since the number of species (n=19) is below the recommended threshold of >20 210 (Blomberg et al., 2003). Therefore, to account for the non-independence of species, we also 211 conducted a generalized linear mixed model (log-linked gamma distribution), that included 212 the taxonomic levels (from species to phylum) as nested, random effects (Seebacher et al., 213 2015), We then compared both models using the Akaike information criterion (AIC) (Akaike, 214 1974), to determine if the inclusion of higher taxonomic levels improved our model. Next, we 215 conducted Tukey HSD post-hoc tests to see which species differed from each other. To 216 examine the potential link between body size and CTmax, we also assessed the relationship 217 between CTmax and mass, within each species, using Pearson’s correlation coefficient. 218 Our second analysis examined the effects of trophic level on CTmax. For each species, 219 trophic level was determined as the longest chain length from a consumer to a basal species, 220 plus one (Pimm, 1980). The obtained trophic levels were then used as a grouping variable in 221 16 understand the temporal and spatial dynamics of these freshwater food webs under the 371 current and future global warming. 372 373 ACKNOWLEDGMENTS 374 We thank Aaron Stoler, Jessica Hua, Will Brogan, John Hammond and Rickey Cothran for 375 their assistance with field collection and in the laboratory. This work was funded by a 376 Fundação para a Ciência e Tecnologia (FCT) PhD fellowship (SFRH/BD/60271/2009) to 377 MK, a U.S. National Science Foundation grant (#0716149) to RR, and a Spanish MICINN 378 grant (CGL2009-12767-C02-02) and MINECO awards (CGL2012-40246-C02-01, 379 CGL2017-86924-P) to MT and JFB. 380 381 BIBLIOGRAPHY 382 Akaike, H., 1974. A new look at the statistical model identification. IEEE Trans. Automat. 383 Contr. 19, 716–723. 384 Allen, A.P., Gillooly, J.F., Brown, J.H., 2005. Linking the global carbon cycle to individual 385 metabolism. Funct. Ecol. 19, 202–213. 386 Allen, J.L., Clusella-Trullas, S., Chown, S.L., 2012. The effects of acclimation and rates of 387 temperature change on critical thermal limits in Tenebrio molitor (Tenebrionidae) and 388 Cyrtobagous salviniae (Curculionidae). J. Insect Physiol. 58, 669–678. 389 Altig, R., Whiles, M.R., Taylor, C.L., 2007. What do tadpoles really eat? Assessing the 390 trophic status of an understudied and imperiled group of consumers in freshwater 391 habitats. Freshw. Biol. 52, 386–395. 392 Anderson, P.J., Piatt, J.F., 1999. Community reorganization in the Gulf of Alaska following 393 ocean climate regime shift. Mar. Ecol. Prog. Ser. 189, 117–123. 394 Angilletta, M.J., 2009. Thermal Adaptation: A Theoretical and Empirical Synthesis. Oxford 395 17 University Press, USA, Oxford. 396 Araújo, M.B., Ferri-Yáñez, F., Bozinovic, F., Marquet, P.A., Valladares, F., Chown, S.L., 397 2013. Heat freezes niche evolution. Ecol. Lett. 16, 1206–1219. 398 Arim, M., Bozinovic, F., Marquet, P.A., 2007. On the relationship between trophic position, 399 body mass and temperature: reformulating the energy limitation hypothesis. Oikos 116, 400 1524–1530. 401 Arribas, R., Díaz-Paniagua, C., Caut, S., Gomez-Mestre, I., 2015. Stable isotopes reveal 402 trophic partitioning and trophic plasticity of a larval amphibian guild. PLoS One 10, 403 e0130897. 404 Bancroft, B.A., Baker, N.J., Searle, C.L., Garcia, T.S., Blaustein, A.R., 2008. Larval 405 amphibians seek warm temperatures and do not avoid harmful UVB radiation. Behav. 406 Ecol. 19, 879–886. 407 Blomberg, S.P., Garland Jr., T., Ives, A.R., 2003. Testing for phylogenetic signal in 408 comparative data: behavioral traits are more labile. Evolution (N. Y). 57, 717–745. 409 Boeckman, C.J., Bidwell, J.R., 2015. Spatial and seasonal variability in the water quality 410 characteristics of an ephemeral wetland. Proc. Oklahoma Acad. Sci. 87, 45–54. 411 Both, C., Van Asch, M., Bijlsma, R.G., Van Den Burg, A.B., Visser, M.E., 2009. Climate 412 change and unequal phenological changes across four trophic levels: Constraints or 413 adaptations? J. Anim. Ecol. 78, 73–83. 414 Bothwell, M.L., Sherbot, D.M.J., Pollock, C.M., 1994. Ecosystem response to solar 415 ultraviolet-B radiation: influence of trophic-level interactions. Science (80-. ). 265, 97– 416 100. 417 Brattstrom, B.H., 1968. Thermal acclimation in anuran amphibians as a function of latitude 418 and altitude. Comp. Biochem. Physiol. 24, 93–111. 419 Buchanan, J.A., Stewart, B.A., Davies, B.R., 1988. Thermal acclimation and tolerance to 420 18 lethal high temperature in the mountain stream amphipod Paramelita nigroculus 421 (Barnard). Comp. Biochem. Physiol. -- Part A Physiol. 89, 425–431. 422 Carreira, B.M., Segurado, P., Orizaola, G., Gonçalves, N., Pinto, V., Laurila, A., Rebelo, R., 423 2016. Warm vegetarians? Heat waves and diet shifts in tadpoles. Ecology 97, 2964– 424 2974. 425 Christensen, M.R., Graham, M.D., Vinebrooke, R.D., Findlay, D.L., Paterson, M.J., Turner, 426 M.A., 2006. Multiple anthropogenic stressors cause ecological surprises in boreal lakes. 427 Glob. Chang. Biol. 12, 2316–2322. 428 Coulson, T., MacNulty, D.R., Stahler, D.R., VonHoldt, B., Wayne, R.K., Smith, D.W., 2011. 429 Modeling effects of environmental change on wolf population dynamics, trait evolution, 430 and life history. Science (80-. ). 334, 1275–1278. 431 Cowles, R.B., Bogert, C.M., 1944. A preliminary study of the thermal requirements of desert 432 reptiles. Bull. Am. Museum Nat. Hist. 83, 261–296. 433 Dallas, H.F., Rivers-Moore, N.A., 2012. Critical Thermal Maxima of aquatic 434 macroinvertebrates: Towards identifying bioindicators of thermal alteration. 435 Hydrobiologia 679, 61–76. 436 Daufresne, M., Lengfellner, K., Sommer, U., 2009. Global warming benefits the small in 437 aquatic ecosystems. Proc. Natl. Acad. Sci. 106, 12788–12793. 438 Dawkins, R., Krebs, J.R., 1979. Arms races between and within species. Proc. R. Soc. 439 London B 205, 489–511. 440 Dell, A.I., Pawar, S., Savage, V.M., 2014. Temperature dependence of trophic interactions 441 are driven by asymmetry of species responses and foraging strategy. J. Anim. Ecol. 83, 442 70–84. 443 Dell, A.I., Pawar, S., Savage, V.M., 2011. Systematic variation in the temperature 444 dependence of physiological and ecological traits. Proc. Natl. Acad. Sci. 108, 10591– 445 19 10596. 446 Deutsch, C.A., Tewksbury, J.J., Huey, R.B., Sheldon, K.S., Ghalambor, C.K., Haak, D.C., 447 Martin, P.R., 2008. Impacts of climate warming on terrestrial ectotherms across latitude. 448 Proc. Natl. Acad. Sci. 105, 6668–6672. 449 Diamond, S.E., Chick, L., Penick, C.A., Nichols, L.M., Cahan, S.H., Dunn, R.R., Ellison, 450 A.M., Sanders, N.J., Gotelli, N.J., 2017. Heat tolerance predicts the importance of 451 species interaction effects as the climate changes. Integr. Comp. Biol. 57, 112–120. 452 Diffenbaugh, N.S., Ashfaq, M., 2010. Intensification of hot extremes in the United States. 453 Geophys. Res. Lett. 37, L15701. 454 Dillon, M.E., Wang, G., Huey, R.B., 2010. Global metabolic impacts of recent climate 455 warming. Nature 467, 704–706. 456 Dowd, W.W., King, F.A., Denny, M.W., 2015. Thermal variation, thermal extremes and the 457 physiological performance of individuals. J. Exp. Biol. 218, 1956–1967. 458 Duarte, H., Tejedo, M., Katzenberger, M., Marangoni, F., Baldo, D., Beltrán, J.F., Martí, 459 D.A., Richter-Boix, A., Gonzalez-Voyer, A., 2012. Can amphibians take the heat? 460 Vulnerability to climate warming in subtropical and temperate larval amphibian 461 communities. Glob. Chang. Biol. 18, 412–421. 462 Falkowski, P.G., Oliver, M.J., 2007. Mix and match: how climate selects phytoplankton. Nat. 463 Rev. 5, 813–819. 464 Felsenstein, J., 1985. Phylogenies and the comparative method. Am. Nat. 125, 1–15. 465 Franken, O., Huizinga, M., Ellers, J., Berg, M.P., 2018. Heated communities: large inter- and 466 intraspecific variation in heat tolerance across trophic levels of a soil arthropod 467 community. Oecologia 186, 311–322. 468 Garland Jr., T., Harvey, P.H., Ives, A.R., 1992. Procedures for the analysis of comparative 469 data using phylogenetically independent contrasts. Syst. Biol. 41, 18–32. 470 20 Gilbert, A.L., Miles, D.B., 2017. Natural selection on thermal preference, critical thermal 471 maxima and locomotor performance. Proc. R. Soc. B Biol. Sci. 284, 20170536. 472 Gilbert, A.L., Miles, D.B., 2016. Food, temperature and endurance: effects of food 473 deprivation on the thermal sensitivity of physiological performance. Funct. Ecol. 30, 474 1790–1799. 475 Gilman, S.E., Urban, M.C., Tewksbury, J., Gilchrist, G.W., Holt, R.D., 2010. A framework 476 for community interactions under climate change. Trends Ecol. Evol. 25, 325–331. 477 Gomez-Mestre, I., Kulkarni, S., Buchholz, D.R., 2013. Mechanisms and consequences of 478 developmental acceleration in tadpoles responding to pond drying. PLoS One 8, e84266. 479 Gosner, K.L., 1960. A simplified table for staging anuran embryos and larvae with notes on 480 identification. Herpetologica 16, 183–190. 481 Gutiérrez-Pesquera, L.M., Tejedo, M., Olalla-Tárraga, M.A., Duarte, H., Nicieza, A., Solé, 482 M., 2016. Testing the climate variability hypothesis in thermal tolerance limits of 483 tropical and temperate tadpoles. J. Biogeogr. 43, 1166–1178. 484 Herrando-Pérez, S., Ferri-Yáñez, F., Monasterio, C., Beukema, W., Gomes, V., Belliure, J., 485 Chown, S.L., Vieites, D.R., Araújo, M.B., 2019. Intraspecific variation in lizard heat 486 tolerance alters estimates of climate impact. J. Anim. Ecol. 88, 247–257. 487 Hoekman, D., 2010. Turning up the heat: temperature influences the relative importance of 488 top-down and bottom-up effects. Ecology 91, 2819–2825. 489 Huang, S.-P., Tu, M.-C., 2008. Heat tolerance and altitudinal distribution of a mountainous 490 lizard, Takydromus hsuehshanensis, in Taiwan. J. Therm. Biol. 33, 48–56. 491 Huey, R.B., 1982. Temperature, physiology, and the ecology of reptiles, in: Gans, C., Pough, 492 F.H. (Eds.), Perspectives of Biophysical Ecology. Academic Press, New York City, New 493 York, U.S.A., pp. 25–91. 494 Huey, R.B., Deutsch, C.A., Tewksbury, J.J., Vitt, L.J., Hertz, P.E., Alvarez Pérez, H.J., 495 21 Garland Jr., T., 2009. Why tropical forest lizards are vulnerable to climate warming. 496 Proc. R. Soc. London B 276, 1939–48. 497 Huey, R.B., Kearney, M.R., Krockenberger, A., Holtum, J.A.M., Jess, M., Williams, S.E., 498 2012. Predicting organismal vulnerability to climate warming: roles of behaviour, 499 physiology and adaptation. Phylosophical Trans. R. Soc. B Biol. Sci. 367, 1665–1679. 500 Huey, R.B., Kingsolver, J.G., 2019. Climate warming, resource availability, and the 501 metabolic meltdown of ectotherms. Am. Nat. 194, E140–E150. 502 Huey, R.B., Kingsolver, J.G., 1989. Evolution of thermal sensitivity of ectotherm 503 performance. Trends Ecol. Evol. 4, 131–135. 504 Hutchison, V.H., 1961. Critical thermal maxima in salamanders. Physiol. Zool. 34, 92–125. 505 IPCC, 2013. Climate Change 2013: The Physical Science Basis. Contribution of Working 506 Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate 507 Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY. 508 Jochum, M., Schneider, F.D., Crowe, T.P., Brose, U., O’Gorman, E.J., 2012. Climate- 509 induced changes in bottom-up and top-down processes independently alter a marine 510 ecosystem. Philos. Trans. R. Soc. B 367, 2962–2970. 511 Jones, D.K., Hua, J., Relyea, R.A., 2016. Effects of endosulfan in freshwater pond 512 communities. Freshw. Sci. 35, 152–163. 513 Katzenberger, M., 2014. Impact of Global Warming in Holarctic and Neotropical 514 communities of amphibians. Dissertation. University of Seville, Seville, Spain. 515 Katzenberger, M., Hammond, J., Duarte, H., Tejedo, M., Calabuig, C., Relyea, R.A., 2014. 516 Swimming with predators and pesticides: how environmental stressors affect the thermal 517 physiology of tadpoles. PLoS One 9, e98265. 518 Katzenberger, M., Hammond, J., Tejedo, M., Relyea, R.A., 2018. Source of environmental 519 data and warming tolerance estimation in six species of North American larval anurans. 520 22 J. Therm. Biol. 76, 171–178. 521 Kellermann, V., Overgaard, J., Hoffmann, A.A., Fløjgaard, C., Svenning, J.-C., Loeschcke, 522 V., 2012. Upper thermal limits of Drosophila are linked to species distributions and 523 strongly constrained phylogenetically. Proc. Natl. Acad. Sci. 109, 16228–16233. 524 Klockmann, M., Günter, F., Fischer, K., 2017. Heat resistance throughout ontogeny: body 525 size constrains thermal tolerance. Glob. Chang. Biol. 23, 686–696. 526 Kratina, P., Greig, H.S., Thompson, P.L., Carvalho-Pereira, T.S.A., Shurin, J.B., 2012. 527 Warming modifies trophic cascades and eutrophication in experimental freshwater 528 communities. Ecology 93, 1421–1430. 529 Leibold, M.A., Wilbur, H.M., 1992. Interactions between food-web structure and nutrients on 530 pond organisms. Nature 360, 341–343. 531 Litzow, M.A., Ciannelli, L., 2007. Oscillating trophic control induces community 532 reorganization in a marine ecosystem. Ecol. Lett. 10, 1124–1134. 533 Logan, M.L., Cox, R.M., Calsbeek, R., 2014. Natural selection on thermal performance in a 534 novel thermal environment. Proc. Natl. Acad. Sci. 111, 14165–14169. 535 Lutterschmidt, W.I., Hutchison, V.H., 1997a. The critical thermal maximum: history and 536 critique. Can. J. Zool. 75, 1561–1574. 537 Lutterschmidt, W.I., Hutchison, V.H., 1997b. The critical thermal maximum: data to support 538 the onset of spasms as the definitive end point. Can. J. Zool. 75, 1553–1560. 539 Martin, W.J., Garten, C.T., Gentry, J.B., 1976. Thermal Tolerances of Dragonfly Nymphs. I. 540 Sources of Variation in Estimating Critical Thermal Maximum. Physiol. Zool. 49, 200– 541 205. 542 May, M.L., 1978. Thermal adaptation of dragonflies. Odonatologica 7, 27–47. 543 Miller, K., Packard, G.C., 1977. An altitudinal cline in critical thermal maxima of chorus 544 frogs (Pseudacris triseriata). Am. Nat. 111, 267–277. 545 23 Montaña, C.G., Silva, S.D.G.T.M., Hagyari, D., Wager, J., Tiegs, L., Sadeghian, C., 546 Schriever, T.A., Schalk, C.M., 2019. Revisiting “what do tadpoles really eat?” A 10- 547 year perspective. Freshw. Biol. 64, 2269–2282. 548 Montoya, J.M., Raffaelli, D., 2010. Climate change, biotic interactions and ecosystem 549 services. Philos. Trans. R. Soc. B 365, 2013–2018. 550 Nowrouzi, S., Andersen, A.N., Bishop, T.R., Robson, S.K.A., 2018. Is thermal limitation the 551 primary driver of elevational distributions? Not for montane rainforest ants in the 552 Australian Wet Tropics. Oecologia 188, 333–342. 553 Noyola Regil, J., Mascaro, M., Díaz, F., Denisse Re, A., Sánchez-Zamora, A., Caamal- 554 Monsreal, C., Rosas, C., 2015. Thermal biology of prey (Melongena corona bispinosa, 555 Strombus pugilis, Callinectes similis, Libinia dubia) and predators (Ocyurus chrysurus, 556 Centropomus undecimalis) of Octopus maya from the Yucatan Peninsula. J. Therm. 557 Biol. 53, 151–161. 558 O’Connor, M.I., Gilbert, B., Brown, C.J., 2011. Theoretical predictions for how temperature 559 affects the dynamics of interacting herbivores and plants. Am. Nat. 178, 626–638. 560 O’Connor, M.I., Piehler, M.F., Leech, D.M., Anton, A., Bruno, J.F., 2009. Warming and 561 resource availability shift food web structure and metabolism. PLoS Biol. 7, e1000178. 562 O’Gorman, E.J., Petchey, O.L., Faulkner, K.J., Gallo, B., Gordon, T.A.C., Neto-Cerejeira, J., 563 Ólafsson, J.S., Pichler, D.E., Thompson, M.S.A., Woodward, G., 2019. A simple model 564 predicts how warming simplifies wild food webs. Nat. Clim. Chang. 9, 611–616. 565 Oberle, M., Salomon, S., Ehrmaier, B., Richter, P., Lebert, M., Strauch, S.M., 2019. Diurnal 566 stratification of oxygen in shallow aquaculture ponds in central Europe and 567 recommendations for optimal aeration. Aquaculture 501, 482–487. 568 Ockendon, N., Baker, D.J., Carr, J.A., White, E.C., Almond, R.E.A., Amano, T., Bertram, E., 569 Bradbury, R.B., Bradley, C., Butchart, S.H.M., Doswald, N., Foden, W., Gill, D.J.C., 570 24 Green, R.E., Sutherland, W.J., Tanner, E.V.J., Pearce-Higgins, J.W., 2014. Mechanisms 571 underpinning climatic impacts on natural populations: Altered species interactions are 572 more important than direct effects. Glob. Chang. Biol. 20, 2221–2229. 573 Ohlberger, J., 2013. Climate warming and ectotherm body size - from individual physiology 574 to community ecology. Funct. Ecol. 27, 991–1001. 575 Op de Beeck, L., Verheyen, J., Stoks, R., 2017. Integrating both interaction pathways 576 between warming and pesticide exposure on upper thermal tolerance in high- and low- 577 latitude populations of an aquatic insect. Environ. Pollut. 224, 714–721. 578 Parmesan, C., 2006. Ecological and evolutionary responses to recent climate change. Annu. 579 Rev. Ecol. Evol. Syst. 37, 637–669. 580 Parmesan, C., Yohe, G., 2003. A globally coherent fingerprint of climate change impacts 581 across natural systems. Nature 421, 37–42. 582 Peck, L.S., Clark, M.S., Morley, S.A., Massey, A., Rossetti, H., 2009. Animal temperature 583 limits and ecological relevance: effects of size, activity and rates of change. Funct. Ecol. 584 23, 248–256. 585 Petchey, O.L., McPhearson, P.T., Casey, T.M., Morin, P.J., 1999. Environmental warming 586 alters food-web structure and ecosystem function. Nature 402, 69–72. 587 Pimm, S.L., 1980. Properties of Food Webs. Ecology 61, 219–225. 588 Pincebourde, S., Sanford, E., Helmuth, B., 2008. Body temperature during low tide alters the 589 feeding performance of a top intertidal predator. Limnol. Oceanogr. 53, 1562–1573. 590 R Development core team, 2020. R. 591 Rall, B.C., Vucic-Pestic, O., Ehnes, R.B., EmmersoN, M., Brose, U., 2010. Temperature, 592 predator-prey interaction strength and population stability. Glob. Chang. Biol. 16, 2145– 593 2157. 594 Relyea, R.A., Ricklefs, R.E., 2018. Ecology: The Economy of Nature, 8th Editio. ed. W.H. 595 25 Freeman. 596 Richter-Boix, A., Katzenberger, M., Duarte, H., Tejedo, M., Laurila, A., 2015. Local 597 divergence of thermal reaction norms among amphibian populations is affected by pond 598 temperature variation. Evolution (N. Y). 69, 2210–2226. 599 Schär, C., Vidale, P.L., Lüthi, D., Frei, C., Häberli, C., Liniger, M.A., Appenzeller, C., 2004. 600 The role of increasing temperature variability in European summer heatwaves. Nature 601 427, 332–336. 602 Schwenk, K., Phillips, J.R., 2020. Circumventing surface tension: Tadpoles suck bubbles to 603 breathe air. Proc. R. Soc. B 287, 20192704. 604 Seebacher, F., White, C.R., Franklin, C.E., 2015. Physiological plasticity increases resilience 605 of ectothermic animals to climate change. Nat. Clim. Chang. 5, 61–66. 606 Shurin, J.B., Clasen, J.L., Greig, H.S., Kratina, P., Thompson, P.L., 2012. Warming shifts 607 top-down and bottom-up control of pond food web structure and function. Philos. Trans. 608 R. Soc. B 367, 3008–3017. 609 Simcic, T., Brancelj, A., 1997. Electron transport system (ETS) activity and respiration rate 610 in five Daphnia species at different temperatures. Hydrobiologia 360, 117–125. 611 Simon, M.N., Ribeiro, P.L., Navas, C.A., 2015. Upper thermal tolerance plasticity in tropical 612 amphibian species from contrasting habitats: Implications for warming impact 613 prediction. J. Therm. Biol. 48, 36–44. 614 Sinervo, B., Méndez-de-la-Cruz, F., Miles, D.B., Heulin, B., Bastiaans, E., Villagrán-Santa 615 Cruz, M., Lara-Resendiz, R., Martínez-Méndez, N., Calderón-Espinosa, M.L., Meza- 616 Lázaro, R.N., Gadsden, H., Avila, L.J., Morando, M., de La Riva, I.J., Victoriano 617 Sepulveda, P., Rocha, C.F.D., Ibargüengoytía, N., Aguilar Puntriano, C., Massot, M., 618 Lepetz, V., Oksanen, T.A., Chapple, D.G., Bauer, A.M., Branch, W.R., Clobert, J., 619 Sites, J.W., 2010. Erosion of lizard diversity by climate change and altered thermal 620 Table 5. Generalized linear mixed model (log-link gamma distribution) to determine the 701 effects of trophic level, body mass and their interaction on CTmax. Taxonomic levels from 702 species to phylum were included as nested, random effects to account for the non- 703 independence of related species. 704 705 Fixed effects df Sum sqt Mean Sq F p trophic 3 0.0820 0.0273 150.2 < 0.001 mass 1 0.0011 0.0011 5.8 0.017 trophic*mass 3 0.0003 0.0001 0.6 0.636 Random effects Variance ± SD phylum <0.00001 ± <0.00001 class <0.00001 ± 0.00004 order <0.00001 ± 0.00005 family <0.00001 ± 0.00011 genus 0.00002 ± 0.00426 species 0.00010 ± 0.00977 Residual 0.00018 ± 0.01349 706 Figure 1. Simplified wetland food web with trophic relations between the studied species 707 (modified from Wilbur 1997). Solid arrows indicate the primary direction of energy flow. 708 Doted arrows indicate potential energy flow pathways, depending on tadpole species (Altig et 709 al., 2007; Arribas et al., 2015; Montaña et al., 2019). Dashed arrow indicates a secondary 710 energy flow that occurs when salamander larvae grow bigger than some tadpole species and 711 are then able to consume them. A) predatory insects: Anax longipes, Erythemis simplicollis, 712 Lethocerus americanus and Noctonecta sp.. B) larval salamanders: Ambystoma laterale. C) 713 larval anurans: Anaxyrus americanus, Hyla versicolor, Pseudacris crucifer, P. feriarum, P. 714 triseriata, Rana catesbeiana, R. clamitans, R. palustris, R. pipiens and R. sylvatica. D) 715 zooplaknton: Daphnia magna. E) Amphipods: Hyalella sp., H. spinicauda and H. wellborni. 716 717 Figure 2. Boxplot (median and quartiles) of critical thermal maximum (CTmax) of the studied 718 species. Species were grouped according to their taxonomy. Amphipods and zooplankton 719 were grouped together (Zoo/Apod group) since they represent the main phytoplankton 720 consumers. Dashed lines indicate the average CTmax for each group and the respective 721 standard deviation. Species: ALO, Anax longipes; ESI, Erythemis simplicollis; LAM, 722 Lethocerus americanus; NOC, Noctonecta sp.; ALA, Ambystoma laterale; AAM, Anaxyrus 723 americanus; HVE, Hyla versicolor; PCR, Pseudacris crucifer; PFE, P. feriarum; PTR, P. 724 triseriata; LCA, Rana catesbeiana; RCL, R. clamitans; RPA, R. palustris; RPI, R. pipiens; 725 RSY, R. sylvatica; DMA, Daphnia magna; HYA, Hyalella sp.; HSP, H. spinicauda; HWE, 726 H. wellborni. 727 728 729 730 731