The role of mechanistic physiology in investigating impacts of global 1
warming on fishes 2
3
Sjannie Lefevre1*, Tobias Wang2 and David J. McKenzie3 4
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1Section for Physiology and Cell Biology, Department of Biosciences, University of Oslo, 6
0316 Oslo, Norway 7
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2Department of Biology – Zoophysiology, Aarhus University, 8000 Aarhus C, Denmark 9
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3MARBEC, Université de Montpellier, CNRS, Ifremer, IRD, Palavas-les-Flots, France 11
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*Corresponding author:
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Sjannie Lefevre 15
Department of Biosciences, University of Oslo 16
Postbox 1066 Blindern 17
0316 Oslo, Norway 18
Email: sjannie.lefevre@imbv.uio.no 19
Telephone: +47-48364745 20
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Running title (max 40 characters): Mechanisms of thermal tolerance in fishes 22
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Keywords (3-6): metabolism; scope for activity; critical thermal maximum; CTmax; 24
temperature tolerance 25
Abstract 26
Warming of aquatic environments as a result of climate change is already having 27
measurable impacts on fishes, manifested as changes in phenology, range shifts and 28
reductions in body size. Understanding the physiological mechanisms underlying these 29
seemingly universal patterns is crucial if we are to reliably predict the fate of fish 30
populations with future warming. This includes an understanding of mechanisms for acute 31
thermal tolerance, as extreme heatwaves may be a major driver of observed effects. The 32
hypothesis of gill oxygen limitation (GOL) is claimed to explain asymptotic fish growth, and 33
why some fish species are decreasing in size with warming, but its underlying assumptions 34
conflict with established knowledge and direct mechanistic evidence is lacking. The 35
hypothesis of oxygen- and capacity-limited thermal tolerance (OCLTT) has stimulated a 36
wave of research into the role for oxygen supply capacity and thermal performance curves 37
for aerobic scope, but results vary greatly between species, indicating that it is unlikely to 38
be a universal mechanism. Since thermal performance curves remain important for 39
incorporating physiological tolerance into models, we discuss potentially fruitful 40
alternatives to aerobic scope, notably specific dynamic action and growth rate. We 41
consider the limitations of estimating acute thermal tolerance by a single rapid measure 42
whose mechanism of action is not known. We emphasise the continued importance of 43
experimental physiology, particularly in advancing our understanding of underlying 44
mechanisms, but also the challenge of making this knowledge relevant to the more 45
complex reality.
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Summary statement (15-30 words): Performance curves are important for predicting 48
warming effects on fish. A review of current data indicate that aerobic scope is not 49
universally limited by warming, and alternative measures are suggested.
50 51
Introduction 52
Global warming is accelerating at an alarming rate, causing progressive elevations of 53
seasonal temperatures but also wider thermal variation, with increased frequency of 54
extreme heatwaves (Frölicher et al., 2018; Collins and Sutherland, 2019). The responses 55
to climate warming by animal populations are commonly divided into three “universal”
56
phenomena. Firstly, a seasonal change in timing of life-cycle events, for example earlier 57
spawning or longer reproductive seasons (Poloczanska et al., 2013; Crozier and 58
Hutchings, 2014; Myers et al., 2017; Rogers and Dougherty, 2019). Secondly, latitudinal 59
shifts in species distributions, notably a poleward invasion by temperate and sub-tropical 60
species (Parmesan and Yohe, 2003; Perry et al., 2005; Hickling et al., 2006; Poloczanska 61
et al., 2013). The third phenomenon is a reduction in average body size, due to a decline 62
in final adult size and increases in the proportion of younger and smaller individuals 63
(Daufresne et al., 2009; Gardner et al., 2011; Audzijonyte et al., 2020). The increased 64
frequency, intensity and duration of heatwaves is, however, considered to be the major 65
challenge for the survival and fitness of aquatic ectotherm fauna (Vasseur et al., 2014;
66
Buckley and Huey, 2016; Williams et al., 2016; Stillman, 2019). Indeed, mortality events of 67
fishes after unusually high summer temperatures and heatwaves are increasingly 68
documented in freshwater and marine habitats (Gunn and Snucins, 2010; Hinch et al., 69
2012; Pearce and Feng, 2013; Till et al., 2019). The mechanisms underlying all of these 70
phenomena are not understood, but will be based on physiological functions and 71
responses by individual animals, so experimental biology holds much promise in 72
advancing the understanding of global warming impacts on fishes (Wang and Overgaard, 73
2007; Pörtner and Farrell, 2008; Pörtner and Peck, 2010; Huey et al., 2012; Seebacher 74
and Franklin, 2012; Seebacher et al., 2015; Stillman, 2019).
75
The study of fish thermal physiology has a long history and much is now understood 76
about fundamental mechanisms underlying biochemical and physiological responses to 77
temperature changes (Fry,1958; Cossins and Bowler, 1987; Prosser and Heath, 1991;
78
Schulte, 2011; Currie and Schulte, 2014; Little et al., 2020). There are relatively long- 79
standing theories about the universal principles that would define how water temperature 80
influences the physiology of fishes and, consequently, determines their performance in 81
their environment. Two theories in particular have been actively promulgated to the 82
scientific community, decision makers and media. These are the ‘gill oxygen limitation’
83
(GOL; Pauly, 1981) and ‘oxygen and capacity-limited thermal tolerance’ (OCLTT; Pörtner, 84
2001; 2010) hypotheses. Fishes are valuable resources, from food to tourism, and 85
negative effects of global warming on their populations threaten many ecosystem services 86
globally. Research into the thermal physiology of fishes has therefore intensified, with 87
particular focus on evaluating how temperature affects physiological performance and on 88
defining thermal tolerance. This research has contributed greatly to our knowledge and 89
understanding, but also provoked vivid controversy about the validity and universality of 90
the GOL and the OCLTT paradigms, and animated discussions on proper experimental 91
methods and strategies, particularly regarding the design of protocols to evaluate thermal 92
tolerance in fishes. Here, the evidence is reviewed for and against the GOL and OCLTT 93
models, with emphasis on the latter. Experimental physiologists have focussed heavily on 94
the use of aerobic scope (AS) to develop thermal performance curves (TPCs), in the 95
specific context of the OCLTT. We consider the value of TPCs that use traits of 96
physiological energetics, to broaden future experimental research. The limitations of the 97
critical thermal protocol are reviewed, considering the various mechanisms that can be 98
involved in morbidity and mortality from thermal stress at different timescales. The review 99
concludes by considering the value of laboratory and field studies, in understanding 100
mechanisms of thermal tolerance in fishes and the physiological impacts of global warming 101
on natural populations.
102 103
Universal patterns - universal explanations?
104
The GOL paradigm has been proposed as a universal physiological mechanism to explain 105
the global decline in adult size of many fish species (Pauly, 1981; Cheung et al., 2012).
106
The OCLTT hypothesis has a much broader scope, it seeks to explain all elements of 107
thermal tolerance in fishes, by defining their ability to perform over their natural thermal 108
range (or when exposed to future warming scenarios) as well as their absolute upper and 109
lower tolerance boundaries (Pörtner, 2010). Both paradigms focus on cardiorespiratory 110
physiology and the capacity to supply oxygen for aerobic metabolism when fishes are 111
warmed. The basic premise is that, because water is relatively poor in oxygen, meeting 112
requirements for aerobic metabolism may become challenging when metabolic rate is 113
raised by warming. There are, however, distinct mechanistic physiological details to each 114
model, and distinct reasons why they are the focus of controversy.
115
The Gill Oxygen Limitation paradigm 116
That adult body size decreases in fish grown at warm temperatures is fairly well 117
established based on laboratory and field measurements (Audzijonyte et al., 2019; Hume, 118
2019; Loisel et al., 2019), and referred to as the temperature-size rule (TSR; Atkinson, 119
1994). The mechanisms underlying the TSR remain to be understood and have been 120
carefully reviewed (Verberk et al., 2020). Although initial theories focussed on life-history 121
traits (Angilletta and Dunham, 2003; Angilletta et al., 2004; Arendt, 2011) there has been 122
growing interest in a potential role for oxygen supply in fishes, stimulated to some extent 123
by the GOL paradigm (Hoefnagel and Verberk, 2015; Leiva et al., 2019; Verberk et al., 124
2020; Rubalcaba et al., 2020). The GOL model proposes that, as fishes grow, body 125
volume increases proportionally more than gill respiratory surface area, due to geometric 126
volume-to-surface scaling of spherical bodies. Fishes would therefore become increasingly 127
less able to meet their oxygen requirements as they grow and are proposed to reach 128
maximum size when their gills can only meet oxygen demands of basal metabolism. That 129
is, larger fish would eventually have no aerobic scope (AS), which is defined as the 130
capacity to provide oxygen for all aerobic activities beyond basal maintenance (Fry, 1971).
131
Such activities include tissue anabolism and growth (Pauly, 1981; Cheung et al., 2011). As 132
warming raises basal oxygen demands, the GOL model predicts that the limited branchial 133
capacity for oxygen uptake would occur at smaller maximum sizes, and has therefore 134
been used to project global declines in fish size in a warmer future (Cheung et al., 2011;
135
2012; Pauly and Cheung, 2017).
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The GOL model is not, however, supported by physiological knowledge or data.
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Fish gills are folded surfaces, there is no theoretical support for the notion that they suffer 138
from surface-to-volume constraints of spherical bodies (Lefevre et al., 2017; 2018). Data 139
on multiple fish species shows that AS does not decline with mass (Killen et al., 2016;
140
Lefevre et al., 2017; Audzijonyte et al., 2019; Blasco et al., 2020a). The model also 141
disregards universal allometric scaling of basal metabolic rate with mass in animals 142
(Schmidt-Nielsen, 1982; Killen et al., 2010). Many studies focus on food limitation as the 143
causative factor for declining fish sizes in the field (Morita et al., 2015; Myrvold and 144
Kennedy, 2015; Dantas et al., 2019; Huret et al., 2019; Queiros et al., 2019). Reduced size 145
with warming may also reflect changes to life-history traits that cause an earlier shift from 146
investment in somatic growth to investment in reproduction, resulting in smaller asymptotic 147
size (Audzijonyte et al., 2016; Audzijonyte and Richards, 2018).
148
Although the GOL model is fundamentally flawed, this does not mean that oxygen 149
supply as such might not be one factor underlying the TSR in water-breathing ectotherms 150
(Atkinson et al., 2006; Hoefnagel and Verberk, 2015; Leiva et al., 2019; Verberk et al., 151
2020; Rubalcaba et al., 2020). The theory of ‘maintain aerobic scope and regulate oxygen 152
supply’ (MASROS) proposes that evolution has modified growth trajectories to avoid 153
oxygen limitation at warm temperatures. If warming causes standard metabolic rate (SMR;
154
basal metabolic rate at the temperature) to rise more steeply with mass than does 155
maximum metabolic rate (MMR; maximum rate of oxygen consumption at the 156
temperature), this will reduce AS (calculated as MMR-SMR) with increasing mass. If AS is 157
lower at high temperatures, fishes may limit some oxygen demanding activities, like 158
foraging and growth, if these would constrain their ability to face transient demanding 159
conditions such as disease, episodes of hypoxia or predator attack (Atkinson et al., 2006;
160
Verberk et al., 2020). Modelling provides some support for this, indicating that oxygen 161
supply capacity might decline with body mass in aquatic ectotherms at warm temperatures 162
(Rubalcaba et al., 2020). Such modelling is, however, largely based upon metabolic data 163
that were collated from separate studies. Datasets that include several temperatures and a 164
sufficiently large range of body masses for a single species, to determine the scaling 165
exponents for metabolic traits accurately, are very rare. In Atlantic cod Gadus morhua, 166
Tirsgaard et al. (2015) found SMR did rise more steeply than MMR with mass at warm 167
temperatures (15°C and 20°) but not at cooler ones (2°C, 5°C and 10°C), but the slope for 168
MMR did not decline at higher temperature. In European perch Perca fluviatilis, the slopes 169
for MMR and AS did appear to be lower at 28°C compared to 20°C and Christensen et al.
170
(2020) concluded that a reduction in AS at the optimal temperature (ASTopt) with body size 171
was due to limitations of gas transfer. Messmer et al. (2017) found that the slope for MMR 172
was significantly higher at 33°C than at 28.5°C, while the slope for AS did not differ. While 173
more studies of this nature are clearly needed, the examples illustrate that caution is 174
warranted when using cross-species data to model the response of individual species.
175
Overall, the MASROS theory still awaits concrete evidence.
176
If constraints on oxygen supply do occur with increasing size in aquatic ectotherms, 177
this might render larger animals less able to perform aerobic activities at warm 178
temperatures (Rubalcaba et al., 2020). It is interesting, therefore, that acute thermal 179
tolerance declines with body size in many fish species (reviewed by McKenzie et al., 180
2020). Blasco et al. (2020a) evaluated the capacity of Nile tilapia Oreochromis niloticus to 181
perform intense aerobic exercise when acutely warmed and found a negative relationship 182
between body mass and the temperature at which animals fatigued. This was linked to a 183
very significant mass-related decline in MMR achieved at fatigue, which may indicate that 184
the warming challenge revealed constraints on capacity for oxygen supply in larger 185
animals (Blasco et al., 2020a). Effects of mass on oxygen supply capacity, and potential 186
links to tolerance of warming, are therefore topics for further research.
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The Oxygen and Capacity Limited Thermal Tolerance paradigm 188
Although the OCLTT has been proposed as a universal explanation for the influence of 189
temperature on performance in fishes (Pörtner, 2010), the hypothesis is intensely debated 190
with various reviews and experimental studies voicing major criticisms (Clark et al., 2013;
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Pörtner, 2014; Farrell, 2016; Jutfelt et al., 2018). The OCLTT is directly based on the Fry 192
paradigm that describes a thermal performance curve (TPC) for AS in fishes (Fry, 1947;
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1971). Briefly, fishes are exposed (either acutely, acclimated or acclimatised) to a range 194
of temperatures, then SMR and MMR are measured by respirometry, to calculate AS (Fry, 195
1971). In the Fry and OCLTT paradigms, a unimodal curve for AS is expected due to the 196
assumed differential thermal responses of SMR and MMR: SMR would increase 197
exponentially due to direct kinetic effects, while the increase in MMR is assumed to 198
increase up until a maximum extent defined by cardiorespiratory capacity, beyond which it 199
increases no further [Fry, 1971; see explanatory figures in McKenzie et al. (2016) and 200
Pörtner (2010)]. This would then reveal the temperature where AS is maximal, which 201
would presumably be the optimal temperature (ToptAS) for physiological performance. The 202
TPCs for AS have been reported in many species, with MMR measured either in a 203
swimming respirometer or by chasing to exhaustion. Indeed, swimming or chasing fish to 204
exhaustion has become the norm to describe AS for most fish physiologists.
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It seems intuitive that aerobic capacity is linked to Darwinian fitness, as fish will die 206
if unable to escape from predators or unable to forage and feed. Moreover, while fish can 207
survive for some time without allocating energy to growth and reproduction, both are 208
essential for fitness. Fitness is, however, the outcome of a complex interplay among 209
physiology, behaviour and ecology. Thus, while it may seem straightforward to assume 210
that any reduction in AS will reduce fitness (Fry, 1971; Pörtner and Farrell, 2008) direct 211
evidence is lacking. Furthermore, different species have different life histories and many 212
may rarely utilize their full AS, making it a complex task to predict how short- or long-term 213
reductions in AS affect fitness in the wild. In addition to the problems of linking AS to 214
fitness, the universality of the OCLTT hypothesis is questioned by empirical data. Many 215
species do not show a unimodal TPC for AS and maintain high AS until very close to 216
critical temperatures (Lefevre, 2016; see Table S1). Within a large diversity of species 217
(Fig. 1) it is clear that, in some, AS does decrease at high temperatures, but in others, AS 218
increases across the entire thermal tolerance range, while numerous species maintain AS 219
over a broad range of biologically relevant temperatures. The shape of the TPC for AS 220
could depend on many factors, such as life stage, climatic region and abiotic habitat 221
characteristics. Methodological issues may also be significant. We explored these possible 222
variables using a multiple correspondence analysis (MCA; Fig. 2) and, while there are 223
major disparities among studies (Fig. 2A), there are some interesting tendencies.
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Adults tend to reduce AS, while juveniles tend to maintain or increase AS (Fig. 2B).
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A greater resilience of juveniles in terms of sustaining AS under exposure to environmental 226
stressors, has also been observed for the effect of elevated CO2 (Lefevre, 2019), though 227
interpretation is complicated by the limited number of studies on different life stages of the 228
same species. In sockeye salmon Oncorhynchus nerka, reduced AS with warming has 229
been reported regardless of life stage (Brett, 1964; Lee et al., 2003; Eliason et al., 2011);
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in common triplefin Forsterygion lapillum, AS is reduced in juveniles (McArley et al., 2018), 231
but effects were mixed in adults (Khan and Herbert, 2012; Khan et al., 2014).
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Regarding region and temperature range, some polar species tend to reduce AS 233
(Lowe and Davison, 2006; Seth et al., 2013) while others maintain it (Seth et al., 2013;
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Drost et al., 2016; Kunz et al., 2018). Sub-tropical species more often maintain (Marras et 235
al., 2015; Fu et al., 2018; Laubenstein et al., 2018; Frenette et al., 2019; Mohammadi et 236
al., 2019) or increase AS (Fry, 1947; Claireaux et al., 2006; Tu et al., 2012; Pang et al., 237
2016; Zhou et al., 2019; Crear et al., 2019; 2020) (Fig. 2C). This pattern may reflect that 238
sub-tropical species are more likely to occur over a broad temperature range with larger 239
variations and thus be eurythermal, while polar and tropical species are adapted to a more 240
narrow temperature range and are typically considered stenothermal. A cross-species 241
analysis found that species with higher ToptAS also tended to have a relatively higher 242
ASTopt, but there was no correlation, and hence no trade-off, between this ASTopt and 243
breadth of the thermal range (Nati et al., 2016).
244
While one might not expect salinity itself to play a major role in how temperature 245
affects AS, the majority of freshwater fishes studied maintain or increase AS, while AS is 246
reduced in half the marine species studied (Fig. 2D; Table S1). This may be a result of 247
many freshwater species living in more variable thermal environments (i.e. lakes or rivers) 248
than most marine species. Some of the most heat-tolerant freshwater species, in terms of 249
AS, are the barramundi Lates calcarifer that maintain AS from 23 to 38°C (Norin et al., 250
2014; 2016; Gomez Isaza et al., 2019), the hot-springs population of lake Magadi tilapia 251
Alcolapia grahami with highest AS at 39°C (Wood et al., 2016), and central stoneroller 252
Campostoma anomalum and Southern redbelly dace Chrosomus erythrogaster that 253
maintain AS from 10 to 30°C (Frenette et al., 2019). Most of the marine species that 254
decrease AS are tropical coral reef cardinalfishes (Apogonidae) and damselfishes 255
(Pomacentridae) (Nilsson et al., 2009; Gardiner et al., 2010; Rummer et al., 2014; Motson 256
and Donelson, 2017; Laubenstein et al., 2019). Other marine species seem more resilient 257
(Duthie, 1982; Mallekh and Lagardere, 2002; Marras et al., 2015; Mazloumi et al., 2017;
258
Laubenstein et al., 2018; Crear et al., 2019; 2020; Bouyoucos et al., 2020; Table S1).
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In addition to biological factors inherent to each species, there are methodological 260
factors that may influence study outcomes. There is a problem of researchers using poor 261
experimental methods, despite numerous papers describing best-practices (Clark et al., 262
2013; Norin and Clark, 2016; Rummer et al., 2016; Svendsen et al., 2016). Studies with 263
flawed respirometry are obviously unsound and pollute the literature with invalid data, 264
irrespective of how highbrow the hypothesis and impactful the journal. Common flaws 265
include very short recovery times after handling, no mixing devices in respirometers, and 266
very short measurement periods to estimate metabolic traits. Ideally, fish should not be air- 267
exposed when transferred, given at least 4h recovery (overnight is best), then measured at 268
least 24h.
269
Beyond these methodological faux-pas, the form of an AS curve may be affected by 270
the choice of exposure temperatures, especially how these relate to the acclimation (or 271
acclimatisation) temperature and the natural thermal range of the species. The number of 272
test temperatures is often limited, due to the labour-intensive and lengthy nature of 273
respirometry, and criteria for selecting the highest temperature vary among studies. In 274
roughly a third of studies, upper temperature was based on climate-change projections 275
while, in another large group, upper temperature was based on current average maxima. A 276
limited number of studies used temperatures that are either lower or higher than the 277
ecologically relevant range (Table S1). Not surprisingly, in studies where the highest 278
chosen temperature is lower than the maximum of the natural thermal range, AS increases 279
with temperature, although this pattern can also be observed for some species exposed to 280
temperatures that exceed their ecologically relevant maximum (Fig. 2E).
281
A key methodological constraint for laboratory experiments is the difficulty of 282
replicating the timescale at which climate change is occurring, which questions their 283
ecological validity. The general expectation is that longer acclimation should be beneficial, 284
giving the fish time to make compensatory physiological modifications that enable AS to be 285
maintained over a broad range of temperatures, i.e. reduced SMR and/or increased MMR 286
in acclimated vs. non-acclimated individuals. In other words, longer acclimation periods 287
make it less likely to find a decline in AS at upper temperatures (Lefevre, 2016). The 288
number of studies using an acclimation period of several weeks and even months has now 289
increased (Habary et al., 2017; Motson and Donelson, 2017; Slesinger et al., 2019;
290
Vagner et al., 2019; Zhou et al., 2019), although studies using transgenerational and 291
developmental acclimation remain quite rare. In three coral-reef wrasses (Labridae), AS at 292
elevated temperature did not improve with developmental exposure, and the same was the 293
case for spiny chromis damselfish Acanthochromis polyacanthus (Laubenstein et al., 294
2019), though in this case AS at elevated temperature was restored with transgenerational 295
acclimation (Munday et al., 2017). Transgenerational studies on reproduction, growth and 296
size (Salinas and Munch, 2012; Shama et al., 2014; Donelson and Munday, 2015;
297
Donelson et al., 2016; Loisel et al., 2019) indicate that there is potential for adaptation of 298
these traits, even in the most sensitive species. In addition to exploring the role of 299
transgenerational acclimation on whole-animal performance, epigenetics and gene 300
expression analyses are increasingly being probed to get insights into underlying 301
mechanisms (Veilleux et al., 2015; Bernal et al., 2018; Chen et al., 2018; Metzger and 302
Schulte, 2018; Ryu et al., 2018; 2020). Another means of making temperature treatments 303
more realistic is to use a fluctuating regime; in lake trout Salvelinus namaycush the AS of 304
fish held and measured at 10°C was significantly improved by daily short exposures to 305
17°C (Guzzo et al., 2019). When considering the data collectively, the inclusion of more 306
long-term studies does not, however, reveal a clear effect of timescale of acclimation (Fig.
307
2F). That is, among studies that compared acute and longer acclimation periods, there are 308
several cases where AS at high temperatures is lower after longer acclimation. For 309
example, barramundi increased MMR and AS with an acute temperature increase from 310
23°C and were highest at the highest temperature of 38°C, largely due to a faster increase 311
in MMR then SMR. However, after 5 weeks acclimation, AS at 29°C and 38°C was similar, 312
mainly due to a reduction in MMR (Norin et al., 2014). A very similar pattern was observed 313
in black sea-bass Centropristis striata (Slesinger et al., 2019). In common triplefin, there 314
was a reduction in AS after 12 weeks at 24°C, but AS was higher after 4 weeks 315
acclimation (Khan et al., 2014; McArley et al., 2017). Looking at an even longer 316
perspective, in three-spined stickleback Gasterosteus aculeatus populations with different 317
evolutionary thermal histories, fish from warmer lakes often had lower AS than fish from 318
colder lakes, and there was more variation in the response to warming in the former 319
(Pilakouta et al., 2020). More studies are necessary to confirm this pattern, but it opens a 320
question regarding AS and MMR as measures that are assumed to be set by limitation. If it 321
is beneficial to have higher AS at higher temperature, and it is evidently physiologically 322
possible for fishes to achieve a higher AS (i.e. the cardiorespiratory system is capable of 323
delivering the oxygen needed), then why, in some cases, does MMR decline with time?
324
Perhaps there are costs of having a high MMR (e.g. a large respiratory surface area 325
increases infection risk and need for ion regulation), which may be higher at high 326
temperature, such that if the achievable maximum is not actually needed to achieve 327
sufficient oxygen supply, it is more beneficial to reduce MMR slightly.
328
Recently it has been argued that AS, as measured in most of the studies discussed 329
above, is not an appropriate measure of aerobic capacity and that “Analyses of the OCLTT 330
should mimic natural conditions and consider routine activities displayed by the animal in 331
the field, as well as minimising stress phenomena that would transiently mobilise functional 332
reserves” (Pörtner et al. 2017). In other words, the MMR and AS measured during 333
exercise in the laboratory overestimates the aerobic capacity a fish would have under 334
‘routine’ conditions, for their activities in the wild. Pörtner et al. (2017) suggest “functional 335
capacity” and “functional scope” as more relevant terms, though it is unclear how this 336
performance should be measured in the lab to allow for experimentation and hypothesis 337
testing. The boundaries for AS, as it is most commonly measured, are easy to interpret.
338
The maximum (MMR) is the maximum oxygen supply rate, whether this reflects limitation 339
or optimization of cardiorespiratory systems. The minimum (SMR) is set by the minimum 340
oxygen uptake needed to sustain basal life functions. That routine oxygen demand or 341
“functional scope” would be supply limited is not intuitive, given the knowledge we have of 342
both the long-term plasticity (acclimation) and ability to increase e.g. respiratory surface 343
area. It should also be noted that in the above analyses (Fig. 1, 2), for simplicity, the 344
degree of reduction in AS has not been taken into account, but obviously varies (Lefevre, 345
2016). According to the OCLTT hypothesis, any reduction would represent a reduction in 346
fitness, but this mechanistic link remains hypothetical.
347
Overall, it is clear from the growing number of papers that AS, measured by 348
traditional means using enforced exercise, is not universally limited at warm temperatures, 349
even if the OCLTT paradigm holds true for some salmonids and coral reef species (Table 350
S1). There has been further debate around the hypothesis and its underlying principles 351
(Pörtner et al., 2017; Jutfelt et al., 2018), but the current empirical data represent 352
incontrovertible evidence that the OCLTT is not a universal principle underlying heat 353
tolerance in fishes.
354
Using the OCLTT paradigm in modelling 355
If, however, the OCLTT paradigm holds for a species, and there is a clear ToptAS
356
within the ecologically relevant temperature range, then it can be a very useful tool for 357
predicting impacts of global warming (Eliason et al., 2011), although an explicit link 358
between AS and fitness remains to be demonstrated for any fish species. The form of AS 359
curves has been used to explain ongoing effects of warming such as changes in fish 360
population abundance (Pörtner and Knust, 2007), failure of reproductive migrations 361
(Eliason et al., 2011) and the spread of invasive species (Marras et al., 2015). The OCLTT 362
has also been used as a basis for modelling, for example of growth in the field. Moyano et 363
al. (2020) measured the Arrhenius breakpoint temperature and critical temperature for 364
heart rate of Atlantic herring Clupea harengus in the lab, and showed that the number of 365
days that temperature had been above this temperature over the past 20 years correlated 366
with growth in the field over that period. The authors argue that these traits can therefore 367
project further changes expected from ocean warming.
368
That aerobic capacity can be limiting is theoretically conceivable, given that ATP 369
production must be aerobic to be sustainable. Whether this is limiting in practice for fish in 370
the wild is another question, considering all the other factors that affect energy budgets 371
and survival. Modelling distribution based on a TPC and projected temperature, regardless 372
of which performance measure is used, may indicate the absolute theoretical physiological 373
limit for the distribution of a species, which can then reveal that certain areas may become 374
uninhabitable. Dahlke et al. (2017) measured egg survival for polar cod Boreogadus saida 375
and Atlantic cod at various temperatures in the lab, and then mapped potential egg 376
survival (PES) across the seas in the North, using information about known spawning sites 377
from 1985 to 2004 as a baseline. They then projected changes in the PES across the 378
region, concluding that suitable spawning habitat would shrink. The authors also measured 379
oxygen uptake of the eggs over the same temperature range as egg survival was 380
measured, but while egg survival dropped from 80% at 6°C to 40% at 9°C, oxygen uptake 381
was highest at 9°C, and maintained at 12°C, where egg survival was almost zero. In this 382
case, a limitation in oxygen supply would not seem to explain the reduced survival at 9°C.
383
It could be contributing at 12°C, but without other measurements (e.g. anaerobic end- 384
products, oxygen) it is difficult to separate cause and effect. Since spawning is a crucial 385
event in the life-history of fishes, constraints on this stage are obviously important. The 386
problem of spawning habitat contraction expected from ocean warming was recently 387
emphasised using a multispecies analysis (Dahlke et al., 2020), where the patterns were 388
attributed directly to OCLTT although it is not clear why, based on the information 389
provided.
390
Rather than temperature effects on capacity for oxygen supply itself, Deutsch et al.
391
(2020) argue that a metabolic index, which includes hypoxia tolerance, may explain 392
boundaries of the geographical ranges of species, somewhat similar to the ‘oxygen- and 393
temperature limited metabolic niche’ framework proposed by Ern (2019). While these 394
examples illustrate that it is certainly possible to model and project changes in distribution 395
ranges using physiological traits, wider applicability is less certain. For many species, a 1- 396
2°C increase in temperature would probably not restrict the theoretical physiological 397
maximum for the distribution but, rather, expand it. Whether a species will actually be able 398
to take advantage and expand its range depends on many other factors in addition to 399
physiological performance, such as habitat and food requirements (e.g. Feary et al., 2014).
400
For many species, the adaptation capacity is unknown, as is the relative importance of 401
different selection pressures (Crozier and Hutchings, 2014).
402
Thermal performance curves based on physiological energetics 403
Despite the controversy surrounding OCLTT, the TPC is a valuable concept in 404
understanding thermal tolerance in fishes, towards predicting future effects of global 405
warming. They do require significant man-power, infrastructure and time, but it seems 406
clear that long-term studies are essential for climate-change research. For ectothermic 407
fishes, all TPCs may share some common features, notably that performance and scope 408
for activity are low at the cold end of the thermal range, but they then increase with 409
warming due to thermodynamic effects of water on biochemical and physiological 410
reactions (Schulte et al., 2011; Currie and Schulte, 2014). Why (and if) different 411
performance measures decline beyond an optimum is a more complex question, and 412
mechanisms may differ depending upon the trait in question (Clark et al., 2013).
413
Furthermore, life-history, morphological, and physiological differences among species are 414
likely to determine the ecological relevance of a given trait and therefore the usefulness of 415
its TPC in investigating responses to climate warming at the population level (Clark et al., 416
2013). There are TPCs based upon traits of cardiorespiratory physiology other than AS.
417
Aerobic locomotor performance curves may be interesting for active species (Bennett, 418
1990; Claireaux et al., 2006; Pang and Cao, 2013; Pang et al., 2016). Cardiac 419
performance curves (Casselman et al., 2012; Anttila et al., 2014; Ferreira et al., 2014) are 420
quick to perform but focus on a single organ and results are always interpreted in relation 421
to the OCLTT. Here we consider TPCs for traits of physiological energetics, which rely on 422
the integrated function of multiple organ systems, have an outcome that is readily related 423
to fitness, and may apply to fishes of all lifestyles.
424
Specific Dynamic Action 425
The specific dynamic action of food (SDA) response is the ubiquitous and transient rise in 426
metabolism during digestion, and likely has both ecological and evolutionary relevance 427
because it reflects processes and costs of nutrient handling, tissue turnover and 428
deposition, hence growth (Jobling, 1994; McCue, 2006; Wang et al., 2006). The response 429
requires the integrated performance of multiple organs, including digestion and absorption 430
by the gut, nutrient and oxygen transport by the cardiovascular system, nutrient handling 431
by the liver, nutrient turnover and deposition in all body tissues, plus gas exchange at the 432
gills to support the rise in aerobic metabolism as well as nitrogen excretion (McCue, 2006;
433
Wang et al., 2006). The SDA can occupy a sizable proportion of AS in fishes (Sandblom et 434
al., 2014; Steell et al., 2019) and is considered, along with locomotor activity, to represent 435
a major component of the overall cost of living (Jobling, 1994). In some species, AS 436
measured in digestion may exceed that measured in activity (Steell et al., 2019). The SDA 437
response is measured by respirometry on animals that either feed spontaneously or are 438
force-fed (Chabot et al., 2016). Measures of performance include the peak rate of oxygen 439
uptake, duration of the response, and the SDA coefficient, which is proportion of the SDA 440
response to the amount of energy in the meal: how much of the meal’s energy is used to 441
digest it (McCue, 2006; Chabot et al., 2016). There are theoretical reasons to assume that 442
warming should increase the peak, reduce the duration but not affect the coefficient, and 443
this has some empirical support (Jobling and Davies, 1980; Jobling, 1994; McCue, 2006;
444
Wang et al., 2006; Luo and Xie, 2008; Steell et al., 2019). The SDA performance can also, 445
however, have a Topt in some species such that warming can cause declines in 446
performance, which can reflect local adaptation to thermal regimes (McKenzie et al., 2013;
447
Tirsgaard et al., 2014). The response has been used to investigate the functional 448
consequences of exposure to future warming scenarios (Sandblom et al., 2014) and the 449
invasion potential of species and how this will be affected by warming (Steell et al., 2019).
450
As such, the SDA response seems to hold promise as a means of investigating thermal 451
tolerance in fishes and predicting responses to future warming, and is not that much more 452
challenging to perform than a TPC for AS.
453
Growth 454
Like the SDA, growth depends on multiple physiological systems and behaviours including 455
appetite, but with a temporal dimension that can provide much greater insight into how 456
fishes are affected by temperature. Growth rate is a major component of life history 457
strategies in fishes and global warming has been shown to affect growth (Metcalfe et al., 458
1995; Réale et al., 2010; Morrongiello et al., 2012; Audzijonyte et al., 2020). Growth TPCs 459
have been developed extensively in aquaculture, where the objective is to maximise 460
growth potential under farming conditions, so feed is provided ad-libitum (Jobling, 1994;
461
Imsland and Jonassen, 2001; Volkoff and Rønnestad, 2020). The overall pattern of a 462
growth TPC in farmed fishes is a progressive increase in rate with temperature up to a 463
maximum that is the optimum temperature for growth (ToptG); this is followed by a decline 464
beyond ToptG that can be very steep (Brett, 1979; Imsland and Jonassen, 2001; Volkoff and 465
Rønnestad, 2020). Scope for growth is determined by the balance of energy supply and 466
demand, namely the difference between energy consumed in feed and energy dissipated 467
to sustain metabolism (Brett, 1979). As temperatures rise to ToptG, thermal acceleration of 468
metabolism provides for increased rates of feed intake, capacity for processing food, and 469
the efficiency with which it is assimilated and deposited as tissue (Brett, 1979; Brett and 470
Groves, 1979; Imsland and Jonassen, 2001; Volkoff and Rønnestad, 2020). This provides 471
for increased scope for growth, up to a maximum at ToptG. Beyond this, growth rates and 472
scope for growth decrease because, while metabolic costs continue to increase with 473
temperature, there is a progressive decline in feed conversion efficiency and appetite 474
(Imsland and Jonassen, 2001; Volkoff, 2020; Volkoff and Rønnestad, 2020). The reduced 475
conversion efficiency may just reflect a changing balance of energy supply and demand, 476
while the mechanisms that cause the decline in appetite are not yet understood (Volkoff 477
and Rønnestad, 2020). One proximate cause of the decline in appetite may be impaired 478
mitochondrial function as temperatures rise beyond the optimum (Salin et al., 2016) 479
although the neural or endocrine pathways by which such sub-cellular effects are 480
transduced into the observed feeding response remain to be explored (Volkoff and 481
Rønnestad, 2020).
482
Thus, fish physiologists would benefit from collaborating with aquaculture 483
researchers. It is commonplace to couple growth studies with measures of feed intake in 484
aquaculture, this reveals how temperature affects appetite and feed efficiency (Imsland 485
and Jonassen, 2001). Tank respirometry can then provide simple energy budgets on 486
feeding, growing animals (McKenzie et al., 2007; 2012). Variable thermal regimes can be 487
incorporated, to improve ecological realism (Morash et al., 2018; Guzzo et al., 2019).
488
Results can be interpreted further by sampling fish to measure thermal impacts at a 489
cellular level, like oxidative damage, mitochondrial function, and expression of heat shock 490
proteins (Khan et al., 2014; Salin et al., 2016; Stillman, 2019). Furthermore, extreme 491
events can be integrated into tank energetics studies, with downstream tissue sampling, 492
for example to investigate whether there is evidence of cellular stress responses, from 493
oxidative damage to expression of heat shock proteins (Stillman, 2019; Williams et al., 494
2016) in different target organs and tissues (see below).
495
The advantage of growth rate as a TPC is that the response seems to be universal 496
across fish species, with a definable ToptG followed by a decline linked to reduced appetite 497
(Volkoff and Rønnestad, 2020). Interestingly, in the Atlantic halibut Hippoglossus 498
hippoglossus, the effects of temperature acclimation on growth and AS are not linked, 499
growth declines at high temperatures while AS does not (Gräns et al., 2014). The major 500
drawbacks are the technical challenges of long-term growth studies and their lack of 501
ecological realism. Growth rates of fishes in the wild are not solely driven by effects of 502
temperature on energy demand, feed intake and scope for growth. Factors such as food 503
availability, time and energy spent foraging, and how foraging rates are affected by 504
perceived risks, will all contribute to the capacity of a fish to allocate energy to growth in 505
the wild (Holt and Jørgensen, 2015; Guzzo et al., 2017; Neubauer and Andersen, 2019;
506
van Denderen et al., 2020).
507
Growth rate seems, nonetheless, to be the most promising alternative TPC to those 508
that focus on the OCLTT. In terms of experimental biology in climate change research, 509
growth rate has been used to investigate mechanisms that define tolerance of warming in 510
fishes (Gräns et al., 2014; Salin et al., 2016) and to develop dynamic energy budget 511
models and to map habitat suitability (Teal et al., 2012; 2015). Childress and Letcher 512
(2017) modelled a TPC for growth on wild salmonids based on repeated field observations 513
and found that it returned a significantly lower ToptG than when modelled on data for growth 514
of captive conspecifics, such that TPCs developed in the laboratory may overestimate 515
ToptG for wild fishes. Wild fishes also show weaker effects of temperature on growth rates 516
than do fish in aquaculture (van Denderen et al., 2020).
517
Tolerance of extreme events 518
Not only the slow and long-term change in temperature with global warming impacts 519
fishes. Extreme heatwave events, or thermal pulses, may cause increased morbidity and 520
even direct mortality in fishes, either due to direct effects of temperature or to associated 521
biotic interactions, such as increased susceptibility to parasites, disease and predation 522
(Hinch et al., 2012; Miller et al., 2014; Roberts et al., 2019; Till et al., 2019). Magel et al.
523
(2020) found that heatwaves caused a 50% reduction in abundance and diversity in a 524
coral reef fish community, notably due to emigration of several species, among which 525
coral-dependent species never returned. This example highlights the complexity and 526
severe consequences extreme temperature events can have, and why measures of acute 527
and upper thermal tolerance limits remain ecologically relevant.
528
The upper limit of thermal tolerance that might be tested by heatwaves is typically 529
estimated in the laboratory using the critical thermal maximum (CTmax) protocol.
530
Temperature is increased in increments until the fish loses equilibrium (LOE), an incipient 531
lethal threshold because the moribund animal would be unable to escape the conditions 532
(Lutterschmidt and Hutchison, 1997; Beitinger and Lutterschmidt, 2011). There are quite 533
major limitations to the critical thermal protocol as an experimental tool (Rezende et al., 534
2014; Blasco et al., 2020b). Notably, the idea that the complexity of thermal tolerance 535
limits can be captured by a single measure is a major oversimplification (Rezende et al., 536
2014; Rezende and Bozinovic, 2019). There are also methodological issues; particularly 537
that the measured CTmax depends upon heating rate (Becker and Genoway, 1979;
538
Lutterschmidt and Hutchison, 1997; Rezende et al., 2014; Vinagre et al., 2015).
539
Furthermore, the mechanism(s) that causes LOE are not known (Currie and Schulte, 540
2014; Healy et al., 2018; Blasco et al., 2020b) and may differ among species and with 541
warming rate (e.g. Wang et al., 2014; Brijs et al., 2015; Ekström et al., 2016; Ern et al., 542
2016; Vinagre et al., 2016; Jutfelt et al., 2019). This lack of mechanistic understanding 543
hinders comprehension of essential questions such as why fish species differ in their 544
CTmax, or why it is modified by thermal acclimation (Currie and Schulte, 2014; Comte and 545
Olden, 2017b; McKenzie et al., 2020). Also, much of the search for physiological 546
mechanisms underlying acute tolerance has focused on the function of organs that are 547
critical for immediate survival, the heart and brain (e.g. Ekström et al., 2014; 2017;
548
Friedlander et al., 1976; Gilbert et al., 2019; Jutfelt et al., 2019) (Fig. 3) and mechanisms 549
related to oxygen supply, such as mitochondrial function (Chung and Schulte, 2020). This 550
is a problem because dire effects on other organs may limit thermal tolerance during 551
longer exposures to more benign temperature, but will not be identified with the same ease 552
in current protocols. Thus, there is the danger that fast rates of temperature increments to 553
determine CTmax will pinpoint the organs with the most immediate effects, namely the brain 554
or the heart, but these organs are merely identified because destruction of their functions 555
leads to immediate death. An equally destructive effect by heat on the intestines or the 556
liver would kill the fish in days, and with the same effect on fitness (i.e. no reproduction, no 557
fitness). In other words, we tend to make the mistake that the organs with fastest effects 558
are identified as the culprits for thermal tolerance, while the more correct picture is likely to 559
be that most organs fail at similar temperatures, but the time course of the effects vary.
560
Seeking a single ubiquitous mechanism that explains CTmax in all fish species therefore 561
seems an illusion.
562
Nevertheless, the CTmax protocol has provided important knowledge about potential 563
impacts of global warming on fishes. For example, to demonstrate that tropical fish species 564
live closer to their upper thermal limits and are, consequently, more vulnerable to future 565
warming than temperate species (Comte and Olden, 2017a; Pinsky et al., 2019). Also, the 566
latitudinal range boundaries of fishes and how these are being modified by global warming 567
are related to their limits of thermal tolerance as measured by CTmax and the equivalent for 568
cold tolerance (CTmin) (Sunday et al., 2011; 2012; 2019). Tolerance thresholds based upon 569
fatigue from exercise performance are, potentially, preferable to LOE at CTmax, because 570
fatigue may have a common physiological mechanism across all species (Steinhausen et 571
al., 2008; Blasco et al., 2020a, b). This does not move away from the limitations of having 572
a single value that is expected to define ‘tolerance’ (Rezende et al., 2014). As argued 573
above, we need to move beyond the heart and brain and must consider other organ 574
systems (osmoregulation, digestion, immune system) that may cause mortality and 575
declines in fitness as a result of extreme events, and thresholds for such effects (Fig. 3).
576
Mortality, or reduced fitness due to carry-over effects (Stillman, 2019), could 577
depend upon impacts on multiple organ systems that become significant over timescales 578
of days to weeks, rather than hours in the laboratory (Fig. 3). Coping with thermal stress 579
may have physiological costs and consequences, for example in the increased production 580
of heat-shock proteins (Kingsolver and Woods, 2016; Williams et al., 2016) that, coupled 581
with a loss of appetite, would challenge energy balance at warm temperatures. This may 582
weaken fishes and render them more at risk from predation and disease. Warm 583
temperatures, especially pulse heat stress, can increase susceptibility to both parasites 584
and bacterial infections over a timescale of days and weeks (Miller et al., 2014; Bruneaux 585
et al., 2017; Teffer et al., 2019; Claar and Wood, 2020), which can then cause further 586
declines in physiological performance (Bruneaux et al., 2017). Examination of mortalities 587
after heatwaves consistently find evidence of high tissue bacterial and/or parasite loads, 588
and disease is considered a major factor in die-offs (Miller et al., 2014; Strepparava et al., 589
2018; Roberts et al., 2019).
590 591
Conclusions and perspectives 592
Our analysis aims to highlight the challenges experimental fish physiologists face when 593
seeking to provide a mechanistic foundation to predict the effects of global warming. While 594
the importance of physiology seems beyond intuitive dispute, we need evidence-based 595
approaches in moving forward. The GOL hypothesis is not based on current knowledge 596
and data. It has been valuable in focussing attention on a possible role for respiratory 597
physiology in size-related differences in thermal tolerance, but should be disregarded as 598
an explanation for why fishes might be shrinking. The evidence collected to date clearly 599
indicates that the OCLTT is not a universal paradigm, so the time seems ripe to move on 600
to different paradigms for TPCs. Traits of physiological energetics, particularly SDA and 601
growth, seem promising candidates. Growth studies have the advantage of a temporal 602
dimension that can incorporate thermal variation and extreme events.
603
Laboratory studies can never capture the complexity of real life and the multiple 604
interacting stressors that a fish may face (Currie and Schulte, 2014; Williams et al., 2016;
605
Morash et al., 2018; Stillman, 2019). Technologies for biologging and biotelemetry hold 606
much promise and are advancing (Treberg et al., 2016) but field physiology on fish lags far 607
behind research on mammals and birds, due to the problems with transmitting data 608
through water or recapturing animals to retrieve data from biologgers. Some species, such 609
as smallmouth bass Micropterus salmoides that guard nests in lakes (Prystay et al., 2019) 610
or sockeye salmon from populations that spawn and die in a particular mountain stream 611
(Prystay et al., 2017), provide increased likelihood of recovering loggers, which is 612
promising for future studies. Marine species present major technical challenges, but the 613
economic value of species like bluefin tuna may drive advances in the field.
614
Laboratory studies can continue to be used to investigate mechanisms, especially 615
of thermal tolerance, acclimation and plasticity, but also, conceivably, of evolutionary 616
adaptation to temperature, especially when including genomics. Field studies can reveal 617
mechanisms but also the impacts of thermal stress on fishes, and the consequences for 618
their fitness. We clearly need more knowledge on more species to improve our ability to 619
predict effects of global change, including warming. We hope that advances in techniques 620
for biotelemetry and biologging will provide information about what is going under natural 621
conditions. If we can understand what has and is happening with populations, this can only 622
improve our ability to predict what may happen in the future.
623 624
Figure legends 625
626
Fig. 1. Taxonomic orders to which species in different studies belong. For each study 627
it was determined whether the aerobic scope at the highest temperature used was 628
decreased, increased or maintained compared to the temperature at which it was 629
maximised. Compared to the number of species in the order, salmonids stand out as 630
having been studied particularly often. The large number of studies on Perciformes is not 631
surprising given that the order comprises almost a third of all fish species. The plot was 632
generated using circlize (0.4.10) in R (4.0.2). All collected details and references are 633
available in Table S1 and S2.
634
Fig. 2. Multiple correspondence analysis bi-plot. Plots showing the aerobic scope 635
response as a supplementary variable (triangles) and individual study/species data points 636
coloured by A) whether AS was decreased, maintained or increased in response to 637
elevated temperature, B) life stage, C) region, D) salinity, E) temperature treatment 638
regime, and F) treatment time-frame. Data was analysed and plotted using factoextra 639
(1.0.7), FactoMineR (2.3) and ggplot2 (3.3.2) in R (4.0.2). All collected details are available 640
in Table S1 and S2.
641
Fig. 3. Upper thermal temperature as a function of time. The upper temperature that 642
causes mortality and morbidity shows an exponential decline with exposure duration in 643
ectotherms (Rezende et al., 2014). Physiologists have focussed on acute tolerance over 644
timescales of hours (or less) using the critical thermal maximum protocol, where fish are 645
warmed incrementally until loss of equilibrium due, presumably, to dysfunction of critical 646
organs such as nervous system and heart. Over longer durations, morbidity and mortality 647
from chronic thermal stress may reflect impaired energy balance due to increased 648
metabolic costs coupled with loss of appetite. The energy imbalance would reduce health, 649
visible as increased parasite and bacterial loads, and reduce performance, in particular 650
swimming ability. Thus, over longer durations at less extreme warm temperatures, major 651
die-offs may occur due to disease and predation.
652 653
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