Preferred temperature of intertidal ectotherms: Broad patterns and methodological approaches

Journal Pre-proof Preferred temperature of intertidal ectotherms: Broad patterns and methodological approaches S. Crickenberger, T.Y. Hui, F. Landry Yuan, T.C. Bonebrake, G.A. Williams PII:

S0306-4565(19)30325-0

DOI:

https://doi.org/10.1016/j.jtherbio.2019.102468

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TB 102468

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Journal of Thermal Biology

Received Date: 14 June 2019 Revised Date:

29 October 2019

Accepted Date: 23 November 2019

Please cite this article as: Crickenberger, S., Hui, T.Y., Landry Yuan, F., Bonebrake, T.C., Williams, G.A., Preferred temperature of intertidal ectotherms: Broad patterns and methodological approaches, Journal of Thermal Biology (2019), doi: https://doi.org/10.1016/j.jtherbio.2019.102468. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.

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Preferred temperature of intertidal ectotherms: broad patterns and methodological

3

approaches

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Crickenberger S1*, Hui TY1, Landry Yuan F2, Bonebrake TC2, Williams GA1

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1: The Swire Institute of Marine Science and School of Biological Sciences, The University of

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Hong Kong, Pokfulam Road, Hong Kong SAR, China

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2: School of Biological Sciences, The University of Hong Kong, Pokfulam Road, Hong Kong

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SAR, China

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*Corresponding author

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Abstract

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Preferred temperature (Tpref) has been measured in over 100 species of aquatic and 300 species

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of terrestrial ectotherms as a metric for assessing behavioural thermoregulation in variable

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environments and, as such, has been linked to ecological processes ranging from individual

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behaviour to population and community dynamics. Due to the asymmetric shape of performance

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curves, Tpref is typically lower than the optimal temperature (Topt, where physiological

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performance is at its peak), and the degree of this mismatch increases with variability in Tb.

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Intertidal ectotherms experience huge variability in Tb on a daily basis and therefore provide a

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good system to test whether the relationship between Tpref and variation in Tb holds in more

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extreme environments. A review of the literature, however, only revealed comparisons between

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Tpref and Topt for five intertidal species and measurements of Tpref for 23 species. An analysis

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of this limited literature for intertidal ectotherms showed a positive relationship between

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acclimation temperature and Tpref. There was, however, great variation in the methodologies

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employed to make these assessments. Factors contributing to behavioural thermoregulation in

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intertidal ectotherms including small body size; low mobility; interactions among individuals;

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endogenous clocks; metabolic effects; thermal sensitivity; sampling of the thermal environment

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and recent acclimation history were considered to varying degrees when measuring Tpref,

50

confounding comparisons between species. The methodologies used to measure Tpref in

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intertidal ectotherms were reviewed in light of each of these factors, and methodologies proposed

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to standardize approaches. Given the theoretical predictions about the relationships between

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Tpref and variability in Tb, the spatial and temporal thermal variability experienced by intertidal

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ectotherms provides numerous opportunities to test these expectations if assessed in a

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standardized manner, and can potentially provide insights into the value of behavioural

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thermoregulation in the more thermally variable environments predicted to occur in the near

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future.

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Keywords: thermoregulation; preferred temperature; acclimation; intertidal

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1.1 Preferred temperatures of ectotherms: a synthesis Body temperature (Tb) plays a key role in determining the performance of ectotherms

66

(Fry, 1947; Huey, 1982; Hochachka and Somero, 2002), a wide variety of which use behavioural

67

responses to modify their body temperatures to achieve certain temperature conditions (Johnson

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and Kelsch, 1998; Martin and Huey, 2008; Clusella-Trullas et al., 2011). These preferred

69

temperatures (Tpref, also referred to as “thermal preferenda” and “selected temperatures”, Pough

70

and Gans, 1982) have been defined as the temperature, or range of temperatures, selected

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through such behaviour, and are often measured over an artificial, laboratory-based, thermal

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gradient (Fry, 1947; Reynolds & Casterlin, 1979; Hertz et al., 1993; Angilleta et al., 2002).

73

These laboratory measurements of Tpref often match field measurements of preferred Tb

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(Angilleta et al., 2002; Allen and Levinton, 2014; Darnell et al., 2015). As such, Tpref has been

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measured in a wide variety of both terrestrial and aquatic ectotherms including at least 50 species

76

of terrestrial invertebrates (Almquist, 1970; Cokendolpher and Francke, 1985; Schmalhofer,

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1999; Buse et al., 2001; Rock et al., 2002; Guarneri et al., 2003; Castaneda, 2004; Kührt et al.,

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2006; Veloso et al., 2012; Alfaro et al., 2013; Sepúlveda et al., 2014; Webber and Bryson, 2015;

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Kuyucu and Caglar, 2016); 100 species of aquatic ectotherms (Johnson and Kelsch, 1998;

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Lagerspetz and Vainio, 2006; Reiser et al., 2013); and more than 300 species of lizards and frogs

81

(Tracy and Christian, 2005; Clusell-Trullas et al., 2011).

82

Tpref is an ecologically important metric for understanding the trade-offs involved in

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individual thermoregulation and, in some cases, has been linked to population and community

84

dynamics (Buckley, 2008; Buckley et al., 2010; Monaco et al., 2015). The Tpref of individuals

85

is generally considered to reflect selection of the most favourable thermal microhabitats

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available, and this selection is balanced against factors such as foraging opportunities and

87

predator avoidance (Huey and Slakin, 1976; Hughes and Grand, 2000; Lampert et al., 2003).

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Individual thermoregulation can, as a result, scale up to influence interspecific dynamics when

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selection of thermal microhabitats alters spatio-temporal distributions of resources and/or

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predators (Hugie and Dill, 1994; Alonzo et al., 2003; Monaco et al., 2015). Quantifying the

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Tpref of individuals is, therefore, important in understanding how thermal landscapes

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mechanistically contribute to shaping the distributions of species via behavioural

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thermoregulation. In a broader context, when predicting species performance and occurrence

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over a wide geographic range, Tpref also represents a critical parameter in enhancing predictive

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accuracy because behavioural thermoregulation can effectively buffer Tb against environmental

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temperature variation (Chapperon and Seuront, 2011). As a result of this difference between Tb

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and environmental temperatures, species distribution models informed by Tpref typically

98

produce more conservative and realistic estimates of species’ distributions (Kearney et al., 2009).

99

Implicit in the assumptions of many studies measuring Tpref is that it coevolved with

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species’ thermal performance to balance the benefits of maximizing overall performance (i.e.,

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Topt = Tb where performance is at its maximum) with reducing exposure to thermal extremes

102

(Jobling, 1981; Angilletta et al., 2002; Martin and Huey, 2008; Asbury and Angilletta, 2010).

103

The approaches adopted to link Tpref to Topt, however, have been applied differently to

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terrestrial and aquatic ectotherms. In aquatic ectotherms the thermal history prior to

105

measurement (i.e., acclimation) has been central to the assessment of Tpref. Fry (1947) in his

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seminal review of Tpref of fish, describes two different ways to measure preferred temperature

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(which he terms final preferendum). The first approach, the gravitational method, is the

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temperature where animals aggregate after a long-term exposure (24-96 hr) in a thermal gradient.

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In this case, the duration of exposure is assumed to remove any potential acclimation effects on

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the animals’ Tpref. The second approach measures Tpref of animals acclimated to a range of

111

temperatures and exposed to a thermal gradient for shorter time periods (< 2 hr). To more

112

clearly define the acclimation-based method of estimating final preferendum, Reynolds and

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Casterlin (1979) presented a graphical model of how to measure the final preferendum from a

114

range of Tpref acclimation experiments using bluegill sunfish (Lepomis macrochirus). Jobling

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(1981) built on the concept of final preferendum by comparing it to the temperature which

116

maximizes performance (i.e. growth in this case) in a number of different fish species and found

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that the final preferendum closely matches the optimum temperature for growth. Given this near

118

1:1 relationship, Jobling (1981) suggested measuring the final preferendum could provide a

119

faster and more economical way to estimate ideal temperatures for maximizing growth in

120

aquaculture species.

121

In terrestrial vertebrate and invertebrate ectotherms Tpref is commonly determined over

122

long-term time periods, equivalent to the gravitational method described by Fry (1947). Using

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this approach, Tpref has been linked to Topt for a wide variety of organismal performance

124

metrics and population growth rates of terrestrial ectotherms (reviewed by Martin and Huey,

125

2008). Daily variation in Tb experienced by terrestrial ectotherms is, however, much greater

126

than that experienced by fully aquatic ectotherms (Woods et al., 2015). This increased variation,

127

coupled with the fact that thermal performance curves have skewed distributions, has selected for

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Tpref to be less than Topt and, the greater the variation in Tb, the larger the difference between

129

Tpref and Topt (Angilletta, 2002; Martin and Huey, 2008). Individual-based models predict the

130

mismatch between Tpref and Topt is also dependent on other factors such as body size and the

131

spatial and temporal variation in habitat temperatures (Woods et al., 2015). In smaller

132

ectotherms, fitness may be maximized by reducing the probability of becoming trapped in

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thermally unfavourable environments rather than maximizing performance. Behavioural

134

thermoregulation to maintain preferred temperatures may, therefore, be less specific in small

135

ectotherms (Figure 1, dashed black line). In contrast, preferred temperatures of large ectotherms

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may be expected to exist within a more narrow range of temperatures (Figure 1, solid black line),

137

as they have greater abilities to sample their thermal environments.

138 139 140

1.2 Intertidal ectotherms: living on the fringes of aquatic and terrestrial environments Intertidal ectotherms live in the transition between aquatic and terrestrial environments

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where they experience large temperature variation both spatially and temporally with the rise and

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fall of the tides (Evans, 1948; Connell, 1961; Tomanek and Helmuth, 2002; Helmuth, 2006).

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Such periodic exposure to air and water also imposes drastically different media for a number of

144

physiological and behavioural functions, such as respiration and locomotion (McMahon &

145

Russell-Hunter, 1977; Hutchinson et al., 2007) which would, in turn, alter the ability for

146

ectotherms to locate thermally favourable microhabitats. Very few studies, however, have

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measured Tpref in intertidal ectotherms (to date 23 species) and direct comparisons between

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Tpref and Topt exist for only five intertidal species (Table 1). Studies on behavioural

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thermoregulation in intertidal animals have instead focused on individuals using a risk avoidance

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strategy to circumvent rare, but potentially lethal temperatures, by measuring microhabitat

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association rather than Tpref (Garrity, 1984; Williams and Morritt, 1995; Pincebourde et al.,

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2009; Miller and Denny, 2011; Monaco et al., 2015; Ng et al., 2017). If risk avoidance is the

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primary objective of behavioural thermoregulation in intertidal ectotherms, then it follows that

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their behavioural thermoregulation should be less specific than in terrestrial or aquatic

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ectotherms (Figure 1, black dashed line).

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157 158

1.3 Patterns and approaches to measure Tpref in intertidal ectotherms While general patterns and relationships for Tpref have been established for terrestrial

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and aquatic ectotherms (Jobling, 1981; Angilleta et al., 2002; Martin and Huey, 2008), it is

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unclear if similar patterns and relationships exist for their intertidal counterparts. Some studies,

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for example, have assumed the relationship between Tpref and Topt established for fully aquatic

162

species (Jobling, 1981) can be applied to intertidal ectotherms (Hecht, 1994; Diaz et al., 2000).

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It is, however, unknown if this relationship holds true, or if Tpref is primarily a mechanism of

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risk avoidance in intertidal species (Monaco et al., 2015). Such a generalization based on fully

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aquatic ectotherms and imposed upon intertidal ectotherms also overlooks the periodic exposure

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to air and water experienced by intertidal ectotherms, where Tpref could be weighed against

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other physiological functions depending on the surrounding medium. A limited number of

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studies have shown that Tpref of intertidal ectotherms can be altered by whether the substrate is

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wet or dry (Allen et al. 2012; Allen and Levinton, 2014), and shuttling behaviour between air

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and water can be an important means of thermoregulation for intertidal crabs (McGaw 2003),

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highlighting the important role of tidal state/duration of aerial exposure in shaping Tpref in

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intertidal ectotherms. As latitude increases, Tpref decreases in terrestrial ectotherms (Clusella-

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Trullas et al., 2011), whereas intertidal ectotherms are more dependent on local habitat than

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broad scale conditions (Helmuth et al., 2014; Marshall et al. 2015), which may result in different

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relationships between latitude and Tpref. Acclimation temperature can strongly influence Tpref

176

(Lagerspetz and Vainio, 2006), and has been considered in some studies on intertidal ectotherms

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(McGaw, 2003; Lewis and Ayers, 2014; Padilla-Ramirez et al., 2015), but it remains unknown if

178

the influence of acclimation temperature is as strong as has been demonstrated in aquatic

179

ectotherms (Jobling, 1981). Mobility is also rarely considered in the Tpref literature, but is an

180

important consideration as many intertidal ectotherms are unlikely to be able to sample all

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available thermal habitats, potentially leading to differences in Tpref between taxa (e.g.

182

gastropods vs. decapods) due to differences in mobility (Tepler et al., 2011; Woods et al., 2015).

183

In addition to the lack of clarity about the general patterns of Tpref, the approaches to measuring

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Tpref in intertidal ectotherms are highly variable between studies, making comparisons

185

challenging.

186 187

Based on these patterns and approaches to measuring Tpref we tested for similar patterns and highlight a number of specific issues to consider when measuring Tpref in intertidal

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ectotherms. Specifically, we tested 1) the effects of latitude, acclimation temperature, and

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mobility (i.e. gastropod vs decapod) on Tpref; 2) the differences between Tpref and Topt and

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Tpref and CTmax (the maximum temperature at which the selected performance metric in that

191

study was measured), to assess the role of Tpref in reducing exposure to thermal extremes versus

192

maximizing performance; 3) the effect of mobility on the difference between CTmax and Tpref,

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to determine if mobility (i.e. gastropods vs decapods) affected the relationship between CTmax

194

and Tpref; and finally the methodologies used to date were compiled and suggestions made to

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better standardize approaches for measuring Tpref in intertidal ectotherms.

196 197 198

2. Observed patterns in intertidal ectotherms To address these issues, published literature on Tpref for intertidal ectotherms was used to

199

test for the effect of acclimation and other factors on Tpref; examine the differences between

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Tpref and Topt and CTmax and compare methodologies used to measure Tpref. Published

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records for Tpref for intertidal ectotherms were compiled by searching for publications

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containing both ‘intertidal’ and ‘preferred temperature’, ‘thermal preferenda’, ‘setpoint

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temperature’, or ‘final preferendum’ in Google Scholar on 29 September 2019 (Table 1). The

204

reference sections of the compiled publications were also searched for additional relevant

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publications. For species where Tpref measurements were available we searched for

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measurements of Topt and CTmax (Table 1). When a range of values was reported we included

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the maximum value for Tpref and the maximum value for CTmax, and daytime Tpref was used

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when both daytime and night-time Tpref were measured.

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The effects of thermally-important variables on Tpref; including the key issue of

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acclimation (indicating recent thermal history); latitude of collection (indicating general thermal

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regime); taxa (indicating the ability to sample thermal environments due to different mobility,

212

i.e. gastropods vs decapod) and the interactions among the factors were tested with a general

213

linear model (GLM; ‘lm’ function, R 3.5.0, R Core Team, 2014) using studies where acclimation

214

temperature prior to Tpref trials was reported (15 species and 25 measurements of Tpref, Table

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1). Intertidal height was not included as a factor because reliable, comparative measurements of

216

intertidal height were unavailable for all species, and in some cases broad categories (i.e. low,

217

mid, high) reported in papers did not match field observations. Likelihood ratio tests (‘lmtest’

218

fuction, R 3.5.0) were used to select the best model using backward selection procedures. The

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best model included acclimation as the sole predictor of Tpref. Inclusion of absolute latitude,

220

taxonomy and their interactions did not improve the model further (Likelihood ratio tests, P >

221

0.05). Differences between Tpref and Topt and Tpref and CTmax were compared using paired t-

222

tests. The effect of taxonomy (i.e. gastropod vs decapod, as an indicator of mobility) on the

223

difference between CTmax and Tpref was tested using an ANCOVA with CTmax as a covariate.

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All statistical analyses were run in R (R 3.5.0, R Core Team, 2014).

225 226

227 228

Figure 1. Conceptual model illustrating two possible modes of behavioural thermoregulation in a

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hypothetical ectotherm and, as a reference, its thermal performance curve (grey solid line).

230

Preference scales from +1 to -1 which represents the change in probability an ectotherm would

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stop searching for new temperatures in its environment. A preference of +1 indicates an

232

ectotherm would stop immediately, while a preference of -1 indicates an ectotherm would always

233

move away from that temperature. A preference of 0 indicates an equal probability of stopping

234

or moving. If the ectotherm had a very specific range of Tpref (illustrated by dashed grey line) it

235

would continue to move until its body temperature reached a narrow temperature range, in this

236

case ~20 °C, where further movement stops. If the ectotherm had a wider range of Tpref (dashed

237

black line) preference would be unbiased at temperatures other than when experiencing those

238

causing physiological stress, when the animal would move to avoid this risk.

239 240

Table 1: Summary of published measurements of preferred temperature (Tpref); medium used

241

for measuring Tpref (Med.; i.e. air or water); time spent in the thermal gradient used for

242

measuring Tpref (Time); longitude (Long) and latitude (Lat) of collection; acclimation condition

243

or temperature (Acclim) prior to running Tpref experiments; duration of acclimation (Dur.) in

244

days; and other metrics of thermal tolerance including optimum temperature (Topt), performance

245

metric used to quantify Topt (Perform. Metric: turning: movement step initiation, speed: sprint

246

speed, respiration: oxygen consumption rate, shifts: number of shifts between zones of the

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thermal gradient), critical thermal maximum temperature (CTmax), and critical thermal

248

minimum temperature (CTmin) for intertidal ectotherms. Relevant publications are indicated by

249

superscripts.

250 251

252 Species and classification

Long

Lat

Haliotis fulgens

-116.38

31.26

Haliotis corrugate

-116.38

Haliotis rufescens

Acclim. Temp (°C)

Dur. (days)

Tpref (°C)

Med.

Time (hr)

Topt (°C)

Perform. Metric

CTmax (°C)

191

28

25.41

water

24

33.61

31.26

191

28

251

water

24

321

-116.78

31.78

172

>4

18.92

water

24

27.52

Haliotis midae

19.30

-34.63

15.53

14

24.53

water

72

27.93

Haliotis midae

19.30

-34.63

18.53

14

24.13

water

72

27.93

Californiconus californicus

-116

32.38

194

15

21.94

water

24

314

Conasprella perplexa

-114.68

30.7

254

21

22.74

water

24

39.84

Conasprella ximenes

-114.9

30.9

214

15

20.14

water

24

39.84

Bulla gouldiana

-116.63

31.73

195

27.45

water

34

6

CTmin (°C)

Gastropoda

6

Turbo militaris

153.45

-29.13

22

7

22

water

24

346

Lunella undulata

153.35

-29.35

236

7

246

water

24

306

Megathura crenulate

-116.75

31.7

167

30

18.97

water

24

28.27

Ilyanassa trivittata

-74.1

39.6

Unknown

358

water

24

9

Indothais rufotincta

120.93

24.78

Field

26.4

water

24

Indothais rufotincta

120.45

22.46

Field

24.19

water

24

Field

9

water

24

9

water

24

9

water

24

9

Indothais rufotincta Reishia keluo Reishia keluo

121.44 120.93 120.45

25.17 24.78 22.46

Field Field

23.5

25.7 25.3

Reishia clavigera

120.93

24.78

Field

27.5

water

24

43.510

Reishia clavigera

121.44

24.78

Field

26.79

water

24

43.510

Chlorostoma funebralis

-121.9

36.6

Field

311

air

>12

Nodilittorina peruviana

-71.63

-33.5

Unknown

1713

air

2

2011

turning

2911

312

Decapoda Cancer antennarius

116.38

31.27

1514

5

15.414

water

2

32.114

Cancer antennarius

116.38

31.27

1814

5

17.114

water

2

32.114

Cancer antennarius

116.38

31.27

2114

5

21.414

water

2

32.114

Cancer antennarius

116.38

31.27

2214

5

21.814

water

2

32.114

Cancer borealis

-71.04

42.36

1115

>14

16.315

water

1

>14

15

water

1

15

water

1

16

24.4

air

0.25

3516

speed

41.816

Cancer borealis Cancer borealis

-71.04 -71.04

15

42.36

14.5

42.36

15

20

>14

17.3 21.3

11.516

Uca panacea

-97.12

27.88

Unknown

Uca pugilator

-73.13

40.97

2017

0.5-10

27.617

air

0.25

3517

speed

43.117

Uca pugilator

-73.13

40.97

2017

0.5-10

26.717

air

0.25

3517

speed

43.117

Uca pugilator

-73.13

40.97

2017

0.5-10

17.517

air

0.25

3517

speed

43.117

Uca pugilator

-73.13

40.97

2017

0.5-10

19.617

air

0.25

3517

speed

43.117

Hemigrapsus nudus

-125.14

48.84

1618

>14

14.618

water

3

2419

respiration

35.318

3.918

Hemigrapsus nudus

-125.14

48.84

1018

>14

1718

water

3

2419

respiration

33.218

3.418

Clibanarius erythropus

32.82

34.95

Unknown

2620

air

0.5

2120

shifts

253 254

1.

255

Casterlin and Reynolds 1980; 9. Wu et al. 2006; 10. Stirling 1982; 11. Tepler et al. 2011; 12. Stenseng 2005; 13. Soto and Bozinovic 1998;

256

14.

257

Warbury and Shuchuman 1984

258

Diaz et al. 2006; 2. Diaz et al. 2010; 3. Hecht 1994; 4. Lugo et al. 2016; 5. Herrera et al. 1996; 6. Lah et al. 2017; 7. Diaz et al. 2015; 8. Padilla-Ramirez et al. 2015; 15. Lewis and Ayers 2014; 16. Darnell et al. 2015; 17. Allen et al. 2012; 18. McGaw; 19. Dehel 1960; 20.

259 260

3.1 The importance of acclimation There was a positive relationship between Tpref and acclimation temperature (Figure 2;

261

GLM, P < 0.01). Acclimation temperature, however, explained only ~ 28% of variation in

262

Tpref, possibly due to the highly variable methodologies employed when measuring Tpref (see

263

below). Variability in simulated tidal cycles and in the temperature conditions at which

264

ectotherms are held in the laboratory prior to measurements of Tpref are known to affect the

265

relationship between acclimation temperature and Tpref (Gunderson et al., 2017; Guzzo et al.,

266

2019). Exposure to tidal cycles rather than a constant aquatic acclimation regime, for example,

267

has been shown to elevate thermal tolerance of intertidal gastropods (Drake et al., 2017).

268

Acclimation of Tpref, nonetheless, is well documented in other subtidal ectotherms (fish:

269

Reynolds and Casterlin, 1979; crustaceans: Lagerspetz and Vainio, 2006) with some exceptions

270

(Buckle Ramirez et al., 1994). In intertidal ectotherms it remains unclear how rapidly these

271

acclimation responses may occur. Rapid acclimation of Tpref may, however, be favoured in the

272

highly heterogeneous and dynamic thermal landscape of the intertidal zone, similar to other

273

rapidly responding physiological responses (e.g. changes in cellular membranes, Williams and

274

Somero, 1996).

275 276

Figure 2. Linear regression to show the relationship between acclimation temperature and Tpref.

277

Circles = decapods and triangles = gastropods (data from Table 1, Tpref = 0.58 × Acclimation

278

temperature + 10.5, R2 = 0.28, P < 0.01).

279 280 281

3.2 Tpref is substantially lower than Topt and CTmax Behavioural thermoregulation can affect performance by both promoting avoidance of

282

stressful or lethal temperatures and by maximizing the amount of time spent near physiologically

283

optimal temperatures (Giattina and Garton, 1982; Jones and Boulding, 1999; Martin and Huey,

284

2008; Cartwright and Williams, 2012; Marshall et al., 2015; Ng et al., 2017). In all cases, Tpref

285

was much lower than CTmax (average difference of 14.0°C ± 6.3°C, mean ± SD, t24 = -11.1, P <

286

0.001, paired t-test, Fig. 3a) and Tpref did not vary with CTmax (P = 0.08). After accounting for

287

variation in CTmax, the degree of avoidance (measured as CTmax – Tpref) was not higher in

288

intertidal decapods than gastropods (difference in CTmax - Tpref ~ 3 °C, t22 = -1.5, P = 0.15,

289

ANCOVA, slopes did not differ between taxa, P = 0.86, Likelihood ratio test between models

290

with and without interaction, Fig. 4). On-shore observations also suggest behavioural

291

thermoregulation is primarily used as a risk-avoidance strategy in intertidal ectotherms. Seuront

292

and Ng (2016), for example, found Echinolittorina malaccana and E. radiata used shell standing

293

and towering behaviours to achieve shell temperatures 3-8°C less than rock temperatures, which

294

in some cases exceed their upper thermal limits, LT50 (Li, 2010). Monaco and colleagues (2015)

295

also found that the starfish, Pisaster ochraceus, rarely experienced lethal temperatures because

296

they occupied cooler habitats. While this habitat selection protected the starfish from potentially

297

lethal temperatures, it exposed them to temperatures below their optimum temperature range for

298

90 percent of the time. Such trade-offs between optimal foraging and risk-avoidance are

299

common in intertidal species, and avoidance of thermal extremes can play an important role in

300

determining subsequent foraging patterns (Burrow and Hughes, 1991; Burrows et al., 2000;

301

Santini et al., 2014).

302

One of the most well studied features of Tpref in aquatic and terrestrial species is its

303

relationship to Topt (Angilletta, 2002; Martin and Huey, 2008; Asbury and Angilletta, 2010;

304

Gvoždík, 2015), however there were only five studies where Topt was measured for comparison

305

to Tpref in intertidal ectotherms. In these studies, Tpref was as much as 17°C below the

306

measured Topt (average difference of 9.7°C ± 6.9°C, mean ± SD, t8 = -4.2, P < 0.01, paired t-

307

test, Fig. 3b) with the exception of one study on the hermit crab, Clibanarius erythropus, where

308

Tpref was higher than Topt which accounts for the large standard deviation recorded. At the

309

extreme end of this mismatch, Tepler and co-workers (2011) interpreted the Tpref of

310

Chlorostoma funebralis as a mechanism for these snails to find thermal refuges. Theoretical

311

predictions of Tpref assume there is no cost associated with selecting Tpref (Martin and Huey,

312

2008). This assumption is, however, unlikely to be met in intertidal systems where slow-moving

313

gastropods dominate. Locomotion of these species is relatively constrained compared to

314

terrestrial mobile ectotherms, as they are slow moving; movement using mucus trails is

315

energetically costly (Davies et al., 1990; Davies and Blackwell, 2007); and in some species

316

locomotion is only possible when submerged (e.g. Pisaster ochraceus, Monaco et al., 2015).

317

These species are, therefore, unable to sample a wide range of thermal environments, which

318

could result in important deviations in expected Tpref when compared to terrestrial ectotherms

319

(but see Denny et al., 2011; Miller and Dowd 2019). In the one case where Topt was similar to

320

Tpref, in the highly mobile fiddler crab Uca pugilator, its Tpref on wet sand closely matched

321

Topt for locomotor performance, however, Tpref was much lower when water resources were

322

limited (Allen et al., 2012; Allen and Levinton, 2014), similar to the pattern in two other crab

323

species (Hemigrapsus nudus, McGaw, 2003; Uca panacea, Darnell et al., 2015).

324

325 326

Figure 3. Box-plots of (a) Tpref and CTmax (n = 25) and (b) Tpref and Topt for studies in which

327

both measures were available (n = 9, see Table 1). The thick black line indicates the median, and

328

the box and whiskers indicate the 25th (and 75th) and 5th (and 95th) percentiles respectively.

329

CTmax and Topt were both significantly greater than Tpref (paired t-tests, P< 0.01 in both

330

cases).

331

332 333

Figure 4. Relationship between CTmax and the difference between CTmax and Tpref. Circles =

334

decapods and triangles = gastropods (data from Table 1; CTmax – Tpref = 0. 0.58 × CTmax –

335

4.48, R2 = 0.44, P < 0.01).

336 337 338

3.3 Methodological considerations for intertidal species Approaches to measuring Tpref in intertidal ectotherms have varied widely, confounding

339

interspecific comparisons. Standardization of methodologies is, therefore, required to help

340

understand general patterns of Tpref. The wide variation in techniques may be due to differing

341

definitions of ‘preference’. A biased distribution towards certain options (temperatures in the

342

case of a thermal gradient) does not necessarily represent preference, but could result from other

343

processes such as spatial proximity; incomplete sampling of the environment; ease to reach the

344

observed position; or some other unmeasured properties of the experimental setup (Liszka and

345

Underwood, 1990). ‘Preference’ among different possible options can, therefore, only be

346

assessed when compared to the distribution of animals when there is no choice between options

347

(see discussions in Underwood and Clarke, 2005). These types of issues are particularly salient

348

in small, low mobility, intertidal ectotherms which are likely to be strongly affected by numerous

349

factors such as interactions among individuals; endogenous clocks; metabolic state; thermal

350

sensitivity; ability to sample the thermal environments available and recent acclimation history.

351

Size and mobility of individuals relative to the grain of the thermal gradient is an important,

352

but often overlooked, consideration. In more mobile terrestrial, aquatic and intertidal animals it

353

is possible for organisms to quickly sample most possible thermal environments within their

354

habitat. This is not, however, necessarily the case in intertidal ectotherms with limited mobility

355

(i.e. gastropods) and consequently additional considerations need to be taken into account when

356

testing for thermal preferences in these species (e.g. Tepler et al., 2011). One consideration is

357

the appropriate spatial scale over which to measure thermal responses to avoid a mismatch

358

between the thermal sensitivity of intertidal ectotherms and the spatial scale of the provided

359

thermal gradient. Thermal gradients used in experiments for intertidal ectotherms range in

360

length from 0.9 to 7.14 m (3.7 ± 2.1 m, mean ± SD) with a 10 to 40 °C temperature range along

361

the thermal gradient (25.7 ± 9.4°C, mean ± SD, data from studies in Table 1). If we assume a

362

thermal gradient of 3.7 m (mean length used in intertidal studies), a temperature range of 25 °C

363

and a body length of 5 cm; an individual intertidal ectotherm may experience a 0.3 °C difference

364

in temperature along its body length. Such a small difference might be undetectable by intertidal

365

gastropods, especially at body temperatures below the Arrhenius break in metabolic rate (at

366

ranges where Q10 ≈ 1, McMahon and Russell-Hunter, 1977), and hinder their ability to select a

367

Tpref. Crustacean nervous systems also vary in sensitivity among species, being responsive to

368

0.2 to 2 °C differences in temperature (Lagerspetz and Vainio, 2006). Experimental procedures

369

such as bubbling air to aerate water along the gradient could further exacerbate such a small

370

difference in temperature (e.g. as in McGaw, 2003; Díaz et al., 2011; Paschke et al., 2013). In

371

such cases, intertidal ectotherms and particularly slow-moving gastropods may not be able to

372

differentiate such a small gradient and are, therefore, unable to demonstrate temperature

373

preference in terms of movement and directionality. Such fully submerged gradients may also

374

alter individual behaviour as compared to aerial exposure because intertidal ectotherms behave

375

very differently when immersed and emersed (Zann, 1973; Little, 1989; Davies et al., 2006).

376

In a number of thermal preference studies on intertidal ectotherms, more than one individual

377

(and up to 311 individuals, see Wu et al., 2006) was introduced into the same gradient runway at

378

the same time. This practice is problematic as individuals often interact with each other (Croll,

379

1983; Hutchinson et al., 2007; Ng et al., 2013). Many intertidal gastropods, for example, trail-

380

follow during locomotion to save energy; aggregate; seek mates; locate their homes and possibly

381

feed (Denny, 1980; Chelazzi 1990; Davies and Blackwell, 2007; Ng et al., 2013). Experiments

382

involving more than one individual in a runway, therefore, are testing a different hypothesis than

383

individual preferences, incorporating the effect of conspecifics. Such an experimental design is

384

appropriate when the interaction between thermal preference and conspecific density is of

385

interest which, in some cases, could indicate trade-offs between thermoregulation and perception

386

of predation risk (Gerald and Spezzano, 2005) or adjustments of group-wise temperature in

387

gregarious species (Simpson, 1961; Stafford et al. 2012).

388

The duration of thermal preference experiments for intertidal ectotherms varied greatly

389

from 15 min to 3 days (Casterlin and Reynolds, 1980; Allen and Levinton, 2014). In some cases

390

the experimental duration was based on the time needed for the animals to explore all surfaces of

391

the gradient (e.g. Pulgar et al. 2003; Allen et al. 2012), but in other cases it was determined as the

392

time after which the speed of the animals levels off at, or nears zero (e.g. McGaw, 2003; Lewis

393

and Ayers, 2014; Lugo et al., 2016). The differences in mobility and the presence of endogenous

394

circadial rhythms in intertidal invertebrates, in particular, render experimental time a critical

395

issue, as slow-moving invertebrates (e.g. gastropods) tend to stop completely and settle at certain

396

temperatures (Lugo et al., 2016; Lah et al., 2017), whereas fast-moving invertebrates such as

397

crabs can keep moving along the gradient with movement intensity varying endogenously with

398

tidal conditions, even in laboratory conditions (Palmer, 1990). Thigmotactic behaviours of

399

crustaceans also interfere with temperature selection, as many species often settle around shelters

400

or corners (McGaw, 2003; Lagerspetz and Vainio, 2006), and in some cases shelter seeking

401

behaviours can supersede Tpref (Neilsen and McGaw, 2016). Cessation of movement by fast-

402

moving invertebrates, therefore, can be confounded by tidal rhythms and topographic features of

403

the runways, and might not necessarily represent a temperature preference. If the experimental

404

duration is too short, however, the animals might still be exploring the environment and their

405

body temperatures measured at such a time will not represent their thermal preference.

406

Acclimation and the influences of recent thermal history, behaviour and organismal mobility

407

should, therefore, be carefully considered for measurements of Tpref to have ecological

408

relevance for intertidal ectotherms and allow interspecific comparisons.

409 410

In many studies, after the assigned experimental period body temperatures of animals are either directly measured (e.g. Darnell et al., 2015) or inferred from the temperature of the

411

surrounding seawater (e.g. Díaz et al., 2011) and then compiled to calculate preference via

412

descriptive statistics such as mean, median and mode. If behavioural thermoregulation of most

413

intertidal ectotherms has a wide range of Tpref (Figure 1, black dashed line), then measures of

414

variance such as standard deviation, standard error, interquartile ranges or complete distributions

415

of preferred temperatures are more informative as compared to measures of central tendency

416

(e.g. means, Casterlin and Reynolds, 1980; Darnell et al., 2015) as Tpref is likely to be

417

individual-specific, or consist of a range of temperatures instead of a definite value (Hertz et al.,

418

1993). In cases where multiple individuals are used in a single experimental run, however, the

419

meaning of these measures of variance is unclear because these data are pseudoreplicated (in that

420

the values obtained are not derived from independent replicates). To address these issues, the

421

complete distribution of Tpref should be reported whenever possible, as the variation in Tpref

422

across individuals conveys valuable information on the inherent variability in thermal physiology

423

and individual behaviour (Cerqueira et al., 2016) and/or the thermal heterogeneity of the

424

environment (Martin & Huey, 2008; Woods et al., 2015).

425

To allow more rigorous assessment and, as a result, unconfounded comparisons of

426

interspecies variation in Tpref in low mobility, intertidal ectotherms, we suggest two

427

methodological approaches; namely the Eulerian and Lagrangian approaches adopted by Turchin

428

(2015). The Eulerian approach measures the distribution of individual animals along a runway,

429

with the expected null distribution of individuals in the absence of a thermal gradient being

430

tested against their distribution in a thermal gradient. The treatment without the thermal gradient

431

represents a control for laboratory conditions that could affect individual movements and

432

provides expected positions of the animals inside the runway if the null hypothesis is true (i.e.

433

there is no thermal preference, see logical discussion in Liszka and Underwood, 1990). Such

434

controls, with no thermal gradient, were only adopted in five of the studies reviewed (Warbury

435

and Shuchman, 1984; McGaw, 2003; Lewis and Ayers, 2014; Padilla-Ramirez et al., 2015), and

436

differences between animal distributions along thermally uniform and thermal gradient runways

437

were only statistically compared in one study (Tepler et al., 2011). The Eulerian approach tends

438

to be a population-wise measure that summarizes distribution responses at the population level,

439

for instance the spatial variation in the number of individuals along the gradient (e.g. Soto and

440

Bozinovic 1998).

441

attributes such as speed and turning probability, and simulates animal trajectories using these

The Lagrangian approach, in contrast, measures individual movement

442

parameters in a given environment. Such an approach, therefore, provides individual-specific

443

measures which can be used to predict individual movements on a thermal landscape. Individual

444

movements are firstly parameterized in the absence of a thermal gradient to control for

445

movements due to unmeasured variables other than temperature. Expected trajectories of the

446

animals can then be simulated based on these parameters in the presence of a thermal gradient

447

via various random walk models (as in Tepler et al., 2011). Both Lagrangian and Eulerian

448

approaches predict behavioural responses to thermal landscapes (at the individual and population

449

level, respectively) and, therefore, can be used to assess how on-shore thermal heterogeneity may

450

drive spatial distribution and refuge-seeking behaviour of intertidal ectotherms.

451

Additionally, the percentage time spent by an individual in different temperature segments

452

can be measured and used as a multivariate response variable (such as kernel density, Worton,

453

1989) describing spatial use by an individual. Such a multivariate approach combines individual

454

attributes with spatial distribution, which could be tested via standard multivariate analyses (e.g.

455

principal component analysis) to investigate the effects of different experimental treatments on

456

the overall temperature preference of individuals. Specifically, the distribution of time spent in

457

different temperature segments by an individual could be ordinated in multidimensional space,

458

and principal components extracted to identify the key temperatures which drive the variation in

459

movement. Such an approach could be extended to compare groups of individuals from different

460

“treatments” (e.g. sites, acclimation condition, taxa, etc.) by assessing the spread and centroid of

461

the multivariate responses (e.g. via PERMANOVA), thereby incorporating the full range of

462

movement responses instead of only the final position in assessing individual’s Tpref.

463 464 465

3.4 Conclusions Given the extreme temperatures and variability in intertidal ecosystems, further work on

466

thermal preferences of intertidal ectotherms could provide insights into how both higher

467

temperatures and increased temperature variance may affect patterns of behavioural

468

thermoregulation. Whilst it is acknowledged that behavioural thermoregulation can dramatically

469

impact the realized body temperatures of intertidal ectotherms (Chapperon and Seuront, 2011;

470

Ng et al., 2017), as compared to terrestrial and fully aquatic species, measures of preferred

471

temperatures are rare and assessed using a variety of techniques and often in inappropriate

472

media. Better standardized experiments to measure preferred temperature are needed to improve

473

our understanding of the temperatures intertidal ectotherms actually experience, and the degree

474

to which behavioural thermoregulation can serve as an adaptive mechanism to their survival in

475

this dynamic and extreme thermal environment.

476 477

Acknowledgments

478

This work supported by the Research Grants Council of Hong Kong, HKU17138916.

479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503

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• • • •

Preferred temperature (Tp) is a fundamental and widely used metric in thermal ecology. Very few studies have measured Tp in intertidal ectotherms. In these studies, methodologies are variable, limiting interspecies comparisons. Methods are proposed to standardize measures of Tp in intertidal ectotherms.