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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Mar. Sci.</journal-id>
<journal-title>Frontiers in Marine Science</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Mar. Sci.</abbrev-journal-title>
<issn pub-type="epub">2296-7745</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fmars.2023.1136748</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Marine Science</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Performance of the long-snouted seahorse, <italic>Hippocampus guttulatus</italic>, under warming conditions</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Costa</surname>
<given-names>Ana Beatriz</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1913846"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Correia</surname>
<given-names>Miguel</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2190685"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Silva</surname>
<given-names>Gon&#xe7;alo</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/346614"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Lopes</surname>
<given-names>Ana Filipa</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2134256"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Faria</surname>
<given-names>Ana Margarida</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/556301"/>
</contrib>
</contrib-group>    <aff id="aff1">
<sup>1</sup>
<institution>MARE - Marine and Environmental Sciences Centre/ARNET - Aquatic Research Network, ISPA, Instituto Universit&#xe1;rio</institution>, <addr-line>Lisbon</addr-line>, <country>Portugal</country>
</aff>    <aff id="aff2">
<sup>2</sup>
<institution>IUCN Species Survival Commission - Seahorse, Pipefish and Seadragon Specialist Group, c/o Project Seahorse, Fisheries Centre, The University of British Columbia</institution>, <addr-line>Vancouver, BC</addr-line>, <country>Canada</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Miquel Planas, Institute of Marine Research (CSIC), Spain</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Carlos Rosas, National Autonomous University of Mexico, Mexico; Maite Mascaro, National Autonomous University of Mexico, Mexico</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Ana Margarida Faria, <email xlink:href="mailto:afaria@ispa.pt">afaria@ispa.pt</email>
</p>
</fn>
<fn fn-type="other" id="fn002">
<p>This article was submitted to Marine Biology, a section of the journal Frontiers in Marine Science</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>22</day>
<month>03</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="collection">
<year>2023</year>
</pub-date>
<volume>10</volume>
<elocation-id>1136748</elocation-id>
<history>
<date date-type="received">
<day>03</day>
<month>01</month>
<year>2023</year>
</date>
<date date-type="accepted">
<day>08</day>
<month>03</month>
<year>2023</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2023 Costa, Correia, Silva, Lopes and Faria</copyright-statement>
<copyright-year>2023</copyright-year>
<copyright-holder>Costa, Correia, Silva, Lopes and Faria</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>Temperature is a determinant cue for several behavioral, physiological, and metabolic processes in fish, which occur within a range set to optimize species fitness. Understanding how ocean warming will impact species, at individual and population levels, is, therefore, of utmost relevance for management and conservation purposes. This knowledge assumes particular relevance when it comes to species with unique life history traits that experience multiple threats, such as seahorses. This study aimed to assess the effects of warming on growth, feed intake, and behavioral patterns of the long-snouted seahorse, <italic>Hippocampus guttulatus</italic>. Fish were collected, before the breeding season, in the Sado estuary, Portugal, and subsequently exposed for an 8-week period to three different temperatures: 17&#xb0;C, 20&#xb0;C, and 24&#xb0;C. Three times a week, behavioral observations were performed. Feed intake was measured every day and individuals were weighed once a week. Results indicate differences in behavioral responses of seahorses exposed to increasingly warming conditions. Under extreme temperature conditions (24&#xb0;C), fish were more active, and fed more, but this increment of energy through feeding did not translate into increased growth in weight. Altogether, these results indicate that Sado&#x2019;s population of <italic>H. guttulatus</italic> may become under thermal stress when exposed, for a long term, to warming conditions that are expected to occur by the end of the century.</p>
</abstract>
<kwd-group>
<kwd>activity</kwd>
<kwd>feed intake</kwd>
<kwd>climate change</kwd>
<kwd>syngnathidae</kwd>
<kwd>body condition</kwd>
</kwd-group>    <contract-num rid="cn001">UIDB/MAR/ 04292/2020, UIDP/MAR/04292/2020, LA/P/0069/2020, PTDC/CTA-AMB/31532/2017, PTDC/BIA-BMA/32209/2017</contract-num>    <contract-sponsor id="cn001">Funda&#xe7;&#xe3;o para a Ci&#xea;ncia e a Tecnologia<named-content content-type="fundref-id">10.13039/501100001871</named-content>
</contract-sponsor>
<counts>
<fig-count count="6"/>
<table-count count="3"/>
<equation-count count="2"/>
<ref-count count="75"/>
<page-count count="11"/>
<word-count count="5566"/>
</counts>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>Anthropogenic influence on the production and release of greenhouse gases into the atmosphere has rapidly increased over the last century (<xref ref-type="bibr" rid="B56">Rahman, 2013</xref>; <xref ref-type="bibr" rid="B25">Fawzy et&#xa0;al., 2020</xref>). Since the mid of the 20<sup>th</sup> century, the ocean absorbed more than 90% of the excess heat in the atmosphere (<xref ref-type="bibr" rid="B35">Jewett and Romanou, 2017</xref>) and more than 25% of the atmospheric CO<sub>2</sub> (<xref ref-type="bibr" rid="B59">Sabine et&#xa0;al., 2004</xref>). According to the Intergovernmental Panel on Climate Change (IPCC) models, the temperature is projected to increase 1.4 to 4.4&#xb0;C (more conservative and more extreme scenarios, respectively) (<xref ref-type="bibr" rid="B32">IPCC, 2021</xref>), until the end of the century. Ocean warming is expected to affect all levels of the structure and function of marine ecosystems and organisms (<xref ref-type="bibr" rid="B49">Parmesan, 1996</xref>; <xref ref-type="bibr" rid="B43">McCarthy et&#xa0;al., 2001</xref>; <xref ref-type="bibr" rid="B71">Walther et&#xa0;al., 2002</xref>. For ectotherms, such as fish, the temperature is a determinant factor for several behavioral (<xref ref-type="bibr" rid="B72">Wong and Candolin, 2015</xref>), physiological (<xref ref-type="bibr" rid="B54">P&#xf6;rtner and Farrell, 2008</xref>), and metabolic processes (<xref ref-type="bibr" rid="B9">Clarke and Fraser, 2004</xref>). Warming has been shown to lead to increased metabolic rates (<xref ref-type="bibr" rid="B58">Roessig et&#xa0;al., 2004</xref>), interfere with growth (<xref ref-type="bibr" rid="B5">Bolta&#xf1;a et&#xa0;al., 2017</xref>), reproduction (<xref ref-type="bibr" rid="B37">Lopes et&#xa0;al., 2020</xref>; <xref ref-type="bibr" rid="B61">Servili et&#xa0;al., 2020</xref>), digestion processes and feeding rates (<xref ref-type="bibr" rid="B57">Rangel and Johnson, 2018</xref>; <xref ref-type="bibr" rid="B51">Pilakouta et&#xa0;al., 2020</xref>). It has also the potential to induce behavioral deviations, such as changes in swimming performance (<xref ref-type="bibr" rid="B63">Simon et&#xa0;al., 2017</xref>), predator-prey interactions (<xref ref-type="bibr" rid="B20">Domenici et&#xa0;al., 2019</xref>), and social interactions (<xref ref-type="bibr" rid="B10">Colchen et&#xa0;al., 2017</xref>).</p>
<p>In addition to ocean warming and other climate change-related stressors (e.g. acidification, hypoxia) (<xref ref-type="bibr" rid="B60">Sampaio et&#xa0;al., 2021</xref>), marine species are also being impacted by other human-related pressures, such as overexploitation of resources (<xref ref-type="bibr" rid="B34">Jackson et&#xa0;al., 2001</xref>), poaching (<xref ref-type="bibr" rid="B11">Correia, 2022</xref>), habitat degradation and fragmentation (<xref ref-type="bibr" rid="B1">Airoldi et&#xa0;al., 2008</xref>) and pollution (<xref ref-type="bibr" rid="B62">Shahidul Islam and Tanaka, 2004</xref>). When combined, these pressures are particularly severe for species with unique life history traits, such as seahorses. Seahorses (<italic>Hippocampus</italic> spp.) are benthic species, with low mobility, small home ranges, low fecundity, sparse distribution, mate fidelity, and lengthy parental care (<xref ref-type="bibr" rid="B26">Foster and Vincent, 2004</xref>). These traits, combined with illegal trade for Traditional Chinese Medicine and unsustainable aquarium display (<xref ref-type="bibr" rid="B26">Foster and Vincent, 2004</xref>), and habitat loss (<xref ref-type="bibr" rid="B30">Harasti, 2016</xref>; <xref ref-type="bibr" rid="B11">Correia, 2022</xref>), render them extremely vulnerable to population declines and local extinctions (<xref ref-type="bibr" rid="B26">Foster and Vincent, 2004</xref>; <xref ref-type="bibr" rid="B7">Chong et&#xa0;al., 2010</xref>; <xref ref-type="bibr" rid="B40">Macusi et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B69">Vincent et&#xa0;al., 2011</xref>). Hence, for better control over seahorse trade, all species in the genus have been included in Appendix II of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES Convention) (<xref ref-type="bibr" rid="B27">Foster and Vincent, 2005</xref>), and in the International Union for Conservation of Nature (IUCN) Red List of Threatened Species (<xref ref-type="bibr" rid="B33">IUCN, 2020</xref>). More recently, IUCN World Conservation Congress approved a resolution (WCC-2020-Res-095) that urges IUCN members to take action toward ensuring the status assessment of all syngnathids (seahorses, pipefish, and seadragons), and their inclusion in national/regional Red Lists, while promoting the protection and restoration of their habitats.</p>
<p>Experimental Studies on the effects of global warming on the behavior and physiology of seahorses are still scarce and limited to just a few species. The temperate long-snouted seahorse, <italic>Hippocampus guttulatus</italic>, distributes across most of Europe and North Africa, including the Atlantic Ocean, Mediterranean Sea, and Black Sea (<xref ref-type="bibr" rid="B74">Woodall et&#xa0;al., 2015</xref>; <xref ref-type="bibr" rid="B39">Lourie et&#xa0;al., 2016</xref>). Concurrent with this wide geographic range, the species can also experience a wide range of temperatures throughout the year (<xref ref-type="bibr" rid="B52">Planas et&#xa0;al., 2012</xref>), which will vary depending on the latitude. Temperatures in the South of the Iberian Peninsula can range from 10 to 28 &#xb0;C (Ria Formosa lagoon, <xref ref-type="bibr" rid="B18">Curtis and Vincent, 2006</xref>), which clearly differs from temperatures experienced in Northern France or the British Isles, where temperatures can range from 4 to 20&#xb0;C (<xref ref-type="bibr" rid="B28">Garrick-Maidment et&#xa0;al., 2014</xref>). To date, two studies looked into the effects of prolonged exposure (1 month) to increasingly warmer water conditions (18&#xb0;C &#x2013; 26&#xb0;C &#x2013; 30&#xb0;C) on <italic>H. guttulatus</italic> (<xref ref-type="bibr" rid="B2">Aur&#xe9;lio et&#xa0;al., 2013</xref>; <xref ref-type="bibr" rid="B23">Faleiro et&#xa0;al., 2015</xref>). Authors report an increase in ventilation and metabolic rates of adult seahorses with warming, but fail to detect any further physiological and behavioral impairments, which led the authors to conclude that adults of the species are thermally resilient to heat stress. A similar study on a congener sub-tropical species, <italic>H. erectus</italic>, which occurs from the Gulf of Mexico to Nova Scotia in water temperatures ranging from 5 to 28&#xb0;C (<xref ref-type="bibr" rid="B67">Teixeira and Musick, 2001</xref>; <xref ref-type="bibr" rid="B39">Lourie et&#xa0;al., 2016</xref>), exposed fish for 1 month to increasingly warmer water conditions (22&#xb0;C &#x2013; 26&#xb0;C &#x2013; 30&#xb0;C) (<xref ref-type="bibr" rid="B55">Qin et&#xa0;al., 2018</xref>). Authors found evidence of persistently higher basal metabolic rate at 30&#xb0;C, higher stress response on gene expression, and higher mortality rates. Further, a transcriptomic analysis suggests an arrest of muscle development processes, activation of heat shock proteins, and a switch to anaerobic metabolism from the first moments of exposure to high temperatures (30 or 33 &#xb0;C) (<xref ref-type="bibr" rid="B19">del Vecchio et&#xa0;al., 2022</xref>).</p>
<p>The extensive latitudinal range these species inhabit might contribute to differences in thermal tolerance across populations (<xref ref-type="bibr" rid="B31">Helmuth et&#xa0;al., 2002</xref>; <xref ref-type="bibr" rid="B50">Pereira et&#xa0;al., 2017</xref>), with population-specific thermal limits being set by physiological limitations in aerobic performance (<xref ref-type="bibr" rid="B22">Eliason et&#xa0;al., 2011</xref>). Therefore, when assessing the potential impact of climate change it is important to use scenarios that reflect temperatures within and outside a population&#x2019;s natural variability, and not only scenarios that reflect the variability across the species geographical distribution.</p>
<p>&#x2018;The present study aimed to assess the effects of chronic exposure to increasing temperature scenarios on growth, feed intake, and behavioral patterns of adults of <italic>H. guttulatus</italic>. Individuals were collected in the Sado estuary (Portugal), where temperature can annually range from average 15&#xb0;C to 19&#xb0;C, but minimum and maximum temperatures range from 13.8&#xb0;C (January) and 20.5&#xb0;C (September) (European Centre for Medium-Range Weather Forecasts, <xref ref-type="bibr" rid="B21">ECMWF, 2022</xref>) (<xref ref-type="supplementary-material" rid="SM1">
<bold>Table S1</bold>
</xref>). Fish were exposed for a 2-month period to three different temperature scenarios: ambient temperature (17&#xb0;C); high temperature (20&#xb0;C); and an extreme temperature scenario (24&#xb0;C), which is likely to occur by the end of the century (<xref ref-type="bibr" rid="B32">IPCC, 2021</xref>). Furthermore, as the study took place during the species&#x2019; breeding season, we provide a descriptive discussion of temperature effects on reproduction based on anecdotal observations.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<label>2</label>
<title>Materials and methods</title>
<sec id="s2_1">
<label>2.1</label>
<title>Study species</title>
<p>Two species of seahorses inhabit the Portuguese coastal areas, <italic>H. guttulatus</italic> (<xref ref-type="bibr" rid="B53">Pollom, 2017</xref>), and <italic>Hippocampus hippocampus</italic> (<xref ref-type="bibr" rid="B73">Pollom, 2016</xref>). Both species can be found in inshore waters from the coastal environment and are associated with habitats of different complexity (<xref ref-type="bibr" rid="B12">Correia et&#xa0;al., 2015</xref>; <xref ref-type="bibr" rid="B13">Correia et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B75">Woodall et&#xa0;al., 2018</xref>). National legislation has recently included syngnathids under Decree-Law n&#xb0;38/2021, which approves the legal regime applicable to the protection and conservation of wild flora and fauna and natural habitats of the species listed in the Berne and Bonn Conventions (<ext-link ext-link-type="uri" xlink:href="https://dre.pt/dre/detalhe/decreto-lei/38-2021-164258742">https://dre.pt/dre/detalhe/decreto-lei/38-2021-164258742</ext-link>). The most extensively studied population in Portugal is the Ria Formosa lagoon&#x2019;s population, where several studies have taken place to assess population status, identify major threats and apply mitigation measures to support its conservation (<xref ref-type="bibr" rid="B18">Curtis and Vincent, 2006</xref>; <xref ref-type="bibr" rid="B6">Caldwell and Vincent, 2012</xref>; <xref ref-type="bibr" rid="B14">Correia et&#xa0;al., 2013</xref>; <xref ref-type="bibr" rid="B12">Correia et&#xa0;al., 2015</xref>; <xref ref-type="bibr" rid="B13">Correia et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B11">Correia, 2022</xref>). However, there are newly recorded seahorse populations, such as in the Sado and Tagus estuaries which are understudied and in need of attention (unpublished data). The Sado Estuary is the second-largest estuary in Portugal and one of the most important wetlands in the national territory, integrating an important natural reserve. This region has the largest distribution of seagrass species in Portugal (<xref ref-type="bibr" rid="B16">Cunha and Serr&#xe3;o, 2011</xref>), only surpassed by the Ria Formosa lagoon, and supports species with both economic and conservation value, including seahorses.</p>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>Fish collection and experimental setup</title>
<p>Adult males and females (n=22 individuals; 11 males and 11 females) of the long-snouted seahorse were individually collected by scuba diving in the seagrass meadows of Tr&#xf3;ia, Portugal (38.462311, -8.856218), on April 8<sup>th</sup>, 2022 (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>). Permit to collect fish from the wild was granted by the National Institute of Nature Conservation and Forests (ICNF, permits 288 &#x2013; 290/2022/CAPT). Individuals were immediately placed in large containers filled with seawater from the collection site, with aeration, and controlled temperature, and transported to ISPA fish facilities.</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Field site location.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-10-1136748-g001.tif"/>
</fig>
<p>At arrival, seahorses were placed in six 80-L aquaria (40x40x60 cm), at a density of 2 males and 2 females per aquarium (except 1 tank, with only 1 male and 1 female). Soon after being in these conditions, males and females paired and formed couples based on body size. All aquaria were equipped with a protein skimmer (TMC Reef-Skim 200), biological and mechanical filtration (internal filter, Max 104&#xa0;F), and maintained under temperature and salinity conditions matching field site (average 15&#xb0;C and 35 PSU), and a photoperiod of 14L: 10D. To provide environmental enrichment and holdfast, plastic chains were added to each aquarium (<xref ref-type="bibr" rid="B14">Correia et&#xa0;al., 2013</xref>). Seahorses were left under these conditions for 15 days, to acclimate to laboratory conditions. Fish were fed once per day, <italic>ad libitum</italic>, with frozen wild-caught mysis (<italic>Mesopodopsis slabberi)</italic>. Temperature and salinity were daily measured, in the morning. Ammonia, nitrites and nitrates, were monitored frequently, and kept below critical levels (0.1, 0.3, and 10.0 mg L<sup>-1</sup>, respectively). Aquaria were cleaned daily, in the morning, before feeding. Subsequently, aquaria were randomly assigned to three temperature treatments: ambient temperature (17&#xb0;C), matching average temperature at the beginning of the species breeding season; high temperature (20&#xb0;C), matching temperatures within the species range of variability which they can experience in their natural habitat for a short period; and extreme temperature (24&#xb0;C), reflecting a scenario that falls outside the natural thermal variability of this population and are likely to occur by the end of the century. Sea surface temperatures, represented as monthly averages from daily means, were extracted from remotely sensed climate models (European Centre for Medium-Range Weather Forecasts, <xref ref-type="bibr" rid="B21">ECMWF, 2022</xref>) from spatial points (geo-referenced occurrence data) representing the habitat where the species was captured (<xref ref-type="supplementary-material" rid="SM1">
<bold>Table S1</bold>
</xref>). Temperatures in all treatments increased gradually, using heaters, by about 1&#xb0;C per day to avoid stress and heat shock associated with rapid temperature changes. Aquaria from the extreme treatment (24&#xb0;C) were the first to start increasing temperature, followed by aquaria from the high treatment (20&#xb0;C), 4 days later, and finally, aquaria from the ambient treatment (17&#xb0;C) had their temperature increased 7 days after the first aquaria. This ensured that all treatments reached the experimental treatment temperature (considered day 0 of exposure) at the same time. At this stage, each individual was measured for height (<xref ref-type="bibr" rid="B38">Lourie, 2003</xref>) and weight (wet weight) (<xref ref-type="supplementary-material" rid="SM1">
<bold>Table S2</bold>
</xref>). Within sex, initial weight (W) and height (H) did not differ across treatments (W<sub>males</sub>: F = 0.176, <italic>p</italic>&#xa0;= 0.277; H<sub>males</sub>: F = 0.933, <italic>p</italic> = 0.432; W<sub>females</sub>: F = 0.677, <italic>p</italic> = 0.535; H<sub>females</sub>: F = 0.402, <italic>p</italic> = 0.682), with males average weight and height of 11.99 &#xb1; 1.62&#xa0;g, and 13.79 &#xb1; 0.75&#xa0;cm, respectively, and females average weight and height of 10.70 &#xb1; 1.40&#xa0;g, and 13.71 &#xb1; 0.70&#xa0;cm, respectively. Each treatment had two replicate aquaria, each with 2 couples (i.e., 4 couples for treatment). Aquaria were placed side by side, divided by a white opaque plastic sheet to avoid intraspecific interactions between tanks (<xref ref-type="bibr" rid="B48">Papoutsoglou et&#xa0;al., 2000</xref>; <xref ref-type="bibr" rid="B66">Tamazouzt et&#xa0;al., 2000</xref>). Ambient temperature treatment had only 3 couples (one aquarium had only 1 couple), since it was only possible to collect 11 females and 11 males. As this is a species with national conservation status and protected by law, it was decided to keep only three couples under control conditions.</p>
<p>Exposure to temperature treatments lasted 2 months. At the end of the experimental period, temperatures from high and extreme treatments were gradually decreased till the matching temperature from ambient treatment, which matched the temperature at the collection site at that time of the year (<italic>i.e.</italic> July). Seahorses were then released back to the same area where were previously collected, as per requirement from the permit issuer.</p>
</sec>
<sec id="s2_3">
<label>2.3</label>
<title>Behavior</title>    <p>Behavioral observations were performed three times a week, based on an ethogram adapted from Faleiro et&#xa0;al. (<xref ref-type="bibr" rid="B24">Faleiro et&#xa0;al., 2008</xref>; <xref ref-type="bibr" rid="B23">Faleiro et&#xa0;al., 2015</xref>) (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>). Focal observations were made in the morning (between 07:00 and 10:00 hours), before feeding, to avoid post-prandial bias. Observations were made by a motionless observer standing in front of the aquarium. Each focal observation lasted 3 minutes, and sea horses were observed one at a time in each aquarium. In every observation day, the order of the seahorses observed changed, to add randomization to the process and avoid an effect of the order of observation. As individuals from each aquarium had a set of distinctive traits (body size and spot patterns), we were able to keep the ID of each individual throughout the exposure period (<xref ref-type="bibr" rid="B15">Correia et&#xa0;al., 2014</xref>) and thus avoiding invasive individual identification methods such as VIE tagging (<xref ref-type="bibr" rid="B17">Curtis, 2006</xref>).</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Ethogram of <italic>Hippocampus guttulatus</italic> describing activity patterns and holdfast attachment (adapted from <xref ref-type="bibr" rid="B24">Faleiro et&#xa0;al., 2008</xref>).</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Behaviour</th>
<th valign="top" align="center">Description</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">
<bold>Rest</bold>
</td>
<td valign="top" align="left">The seahorse stays immobile, without any movement</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Body movement</bold>
</td>
<td valign="top" align="left">The seahorse remains in the same place, but moving either the body or the fins</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Swimming</bold>
</td>
<td valign="top" align="left">The seahorse swims actively</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Attachment</bold>
</td>
<td valign="top" align="left">The seahorse is attached or to a holdfast or to another individual</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Unattachment</bold>
</td>
<td valign="top" align="left">The seahorse is not attached to anything</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s2_4">
<label>2.4</label>
<title>Feed intake</title>
<p>To allow <italic>ad libitum</italic> conditions for every fish, fish under treatments A and B were daily fed 5% of body weight (BW) and fish from treatment C were daily fed 7% of BW (<xref ref-type="bibr" rid="B46">Palma et&#xa0;al., 2011</xref>) . To maintain the proper feed rations, the daily wet weight of each ration was altered in accordance with the average wet weight growth for each treatment (<xref ref-type="bibr" rid="B47">Palma et&#xa0;al., 2008</xref>). The values were initially adjusted based on uneaten food to avoid degradation of water quality. Food was weighed and thawed before feeding seahorses, daily. After 24h, uneaten food items were siphoned out of the tank and collected in a hand-held net with fine mesh, over a paper to dry. Then, every piece of uneaten food was sorted using a tweezer and placed in a plastic petri dish for weighing. Indistinct matter was considered as debri and part of faeces and discarded from the weighing. Feed intake (FI) was calculated using the formula:</p>
<disp-formula>
<mml:math display="block" id="M1">
<mml:mrow>
<mml:mi>F</mml:mi>
<mml:mi>I</mml:mi>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:mi>F</mml:mi>
<mml:mi>S</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>F</mml:mi>
<mml:mi>U</mml:mi>
</mml:mrow>
<mml:mrow>
<mml:mi>F</mml:mi>
<mml:mi>S</mml:mi>
</mml:mrow>
</mml:mfrac>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where FS is the amount of food supplied (g) and FU is the amount of uneaten food (g). Feed intake was measured daily, except for weekends.</p>
</sec>
<sec id="s2_5">
<label>2.5</label>
<title>Weight</title>
<p>Individuals were weighed (g) on a weekly basis to determine the amount of food (5 and 7% of body weight) to provide throughout the exposure period. The procedure involved placing each individual in a shallow tray with seawater and placed on a scale, and was performed as quickly as possible. Manipulation of individuals might induce stress and alter behavioral responses. Although we did not measure stress responses to manipulation, we did not observe signs of disturbance attributable to handling stress. Fish resumed their normal rest state as soon as they were placed back in the aquaria, and were seen feeding when food was supplied. Therefore, we consider that fish recovered from handling stress in just a few hours, and this standardized procedure across treatments did not alter behavioral observations throughout the study period.</p>
<p>Data on the initial and final weight were used to calculate mean weight gain (<xref ref-type="bibr" rid="B46">Palma et&#xa0;al., 2011</xref>):</p>
<disp-formula>
<mml:math display="block" id="M2">
<mml:mrow>
<mml:mi>W</mml:mi>
<mml:mi>G</mml:mi>
<mml:mo stretchy="false">(</mml:mo>
<mml:mo>%</mml:mo>
<mml:mo stretchy="false">)</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:mi>W</mml:mi>
<mml:mi>f</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>W</mml:mi>
<mml:mi>i</mml:mi>
</mml:mrow>
<mml:mrow>
<mml:mi>W</mml:mi>
<mml:mi>i</mml:mi>
</mml:mrow>
</mml:mfrac>
<mml:mo>&#xd7;</mml:mo>
<mml:mn>100</mml:mn>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where Wf is the final seahorse wet weight and Wi is the initial wet weight.</p>
</sec>
<sec id="s2_6">
<label>2.6</label>
<title>Data analysis</title>
<p>Linear mixed-effects models (&#x201c;lmerTest&#x201d; package in R) were used to access the effect of temperature treatments throughout time in the different seahorse behaviours: rest, swimming, body movement, attach and unattached, and also feed intake. Treatment and Day of Observation (Dobs) were used as fixed effects and Animal ID (Individual) and Holding Aquarium as random effects, for all behaviours, except feed intake. For feed intake only Holding Aquarium was considered as random effect. Day of Observation (Dobs) considered the first day of observation as day 0.&#xa0;A generalized linear model was used to determine the effect of the treatments in the weight gain of the seahorses. Assumptions of homoscedasticity and normality of the residuals were examined by visual inspection of residual fitted plots.The statistical analysis was performed with R statistics, Rstudio (Version 4.2.1). Statistical significance was considered when p&lt;0.05.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<label>3</label>
<title>Results</title>
<sec id="s3_1">
<label>3.1</label>
<title>Temperature effects on behaviour</title>
<p>Long-snouted seahorses spent significantly less time resting when exposed to extreme (24&#xb0;C) temperature, and spent significantly more time swimming when compared with ambient temperature (17&#xb0;C), where individuals spent more time motionless (<xref ref-type="fig" rid="f2">
<bold>Figures&#xa0;2</bold>
</xref>, <xref ref-type="fig" rid="f3">
<bold>3</bold>
</xref>; <xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>, <xref ref-type="supplementary-material" rid="SM1">
<bold>Table S3</bold>
</xref>). Dobs had also a significant effect on rest and swimming behaviors, but no interation between Dobs and Temperature was detected (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>).</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Time spent in stationary behavior (s<sup>-1</sup>) by long-snouted seahorse exposed to different temperature treatments (17&#xb0;C, 20&#xb0;C and 24&#xb0;C). Bold * represent significant differences from control treatment.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-10-1136748-g002.tif"/>
</fig>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>    <p>Time spent swimming (s<sup>-1</sup>) by long-snouted seahorse exposed to different temperature treatments (17&#xb0;C, 20&#xb0;C and 24&#xb0;C). Bold * represent significant differences from control treatment.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-10-1136748-g003.tif"/>
</fig>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Statistical results of the Linear mixed effects models on time (s) seahorse spent in rest, body movement, swimming, attached and unattached, and feed intake of long-snouted seahorse exposed to three temperature treatments &#x2013; control (17&#xb0;C), high (20&#xb0;C), and extreme (24&#xb0;C).</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Variable</th>
<th valign="top" align="center"/>
<th valign="top" align="center">Estimate</th>
<th valign="top" align="center">S.E.</th>
<th valign="top" align="center">df</th>
<th valign="top" align="center">t-value</th>
<th valign="top" align="center">pr(&gt;|t|)</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" rowspan="5" align="left">
<bold>Rest</bold>
</td>
<td valign="top" align="left">Treatment High</td>
<td valign="top" align="center">-38.900</td>
<td valign="top" align="center">21.637</td>
<td valign="top" align="center">41.289</td>
<td valign="top" align="center">-1.798</td>
<td valign="top" align="center">0.080</td>
</tr>
<tr>
<td valign="top" align="left">Treatment Extreme</td>
<td valign="top" align="center">-68.143</td>
<td valign="top" align="center">21.637</td>
<td valign="top" align="center">41.289</td>
<td valign="top" align="center">-3.149</td>
<td valign="top" align="center">
<bold>0.003</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Day of Observation</td>
<td valign="top" align="center">0.811</td>
<td valign="top" align="center">0.371</td>
<td valign="top" align="center">440.000</td>
<td valign="top" align="center">2.183</td>
<td valign="top" align="center">
<bold>0.029</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Treatment High x Day of Observation</td>
<td valign="top" align="center">-0.404</td>
<td valign="top" align="center">0.491</td>
<td valign="top" align="center">440.000</td>
<td valign="top" align="center">-0.822</td>
<td valign="top" align="center">0.412</td>
</tr>
<tr>
<td valign="top" align="left">Treatment Extreme x Day of Observation</td>
<td valign="top" align="center">0.099</td>
<td valign="top" align="center">0.491</td>
<td valign="top" align="center">440.000</td>
<td valign="top" align="center">0.201</td>
<td valign="top" align="center">0.841</td>
</tr>
<tr>
<td valign="top" rowspan="5" align="left">
<bold>Body Movement</bold>
</td>
<td valign="top" align="left">Treatment High</td>
<td valign="top" align="center">29.919</td>
<td valign="top" align="center">18.189</td>
<td valign="top" align="center">63.830</td>
<td valign="top" align="center">1.645</td>
<td valign="top" align="center">0.105</td>
</tr>
<tr>
<td valign="top" align="left">Treatment Extreme</td>
<td valign="top" align="center">22.937</td>
<td valign="top" align="center">18.189</td>
<td valign="top" align="center">63.830</td>
<td valign="top" align="center">1.261</td>
<td valign="top" align="center">0.212</td>
</tr>
<tr>
<td valign="top" align="left">Day of Observation</td>
<td valign="top" align="center">-0.325</td>
<td valign="top" align="center">0.388</td>
<td valign="top" align="center">440.000</td>
<td valign="top" align="center">-0.837</td>
<td valign="top" align="center">0.403</td>
</tr>
<tr>
<td valign="top" align="left">Treatment High x Day of Observation</td>
<td valign="top" align="center">0.489</td>
<td valign="top" align="center">0.513</td>
<td valign="top" align="center">440.000</td>
<td valign="top" align="center">0.953</td>
<td valign="top" align="center">0.341</td>
</tr>
<tr>
<td valign="top" align="left">Treatment Extreme x Day of Observation</td>
<td valign="top" align="center">0.432</td>
<td valign="top" align="center">0.513</td>
<td valign="top" align="center">440.000</td>
<td valign="top" align="center">0.843</td>
<td valign="top" align="center">0.400</td>
</tr>
<tr>
<td valign="top" rowspan="5" align="left">
<bold>Swimming</bold>
</td>
<td valign="top" align="left">Treatment High</td>
<td valign="top" align="center">8.978</td>
<td valign="top" align="center">10.245</td>
<td valign="top" align="center">87.650</td>
<td valign="top" align="center">0.876</td>
<td valign="top" align="center">0.383</td>
</tr>
<tr>
<td valign="top" align="left">Treatment Extreme</td>
<td valign="top" align="center">45.206</td>
<td valign="top" align="center">10.245</td>
<td valign="top" align="center">87.650</td>
<td valign="top" align="center">4.412</td>
<td valign="top" align="center">
<bold>&lt;0.001</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Day of Observation</td>
<td valign="top" align="center">-0.486</td>
<td valign="top" align="center">0.241</td>
<td valign="top" align="center">440.000</td>
<td valign="top" align="center">-2.017</td>
<td valign="top" align="center">
<bold>0.044</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Treatment High x Day of Observation</td>
<td valign="top" align="center">-0.085</td>
<td valign="top" align="center">0.319</td>
<td valign="top" align="center">440.000</td>
<td valign="top" align="center">-0.268</td>
<td valign="top" align="center">0.789</td>
</tr>
<tr>
<td valign="top" align="left">Treatment Extreme x Day of Observation</td>
<td valign="top" align="center">-0.531</td>
<td valign="top" align="center">0.319</td>
<td valign="top" align="center">440.000</td>
<td valign="top" align="center">-1.666</td>
<td valign="top" align="center">0.096</td>
</tr>
<tr>
<td valign="top" rowspan="5" align="left">
<bold>Unattachment</bold>
</td>
<td valign="top" align="left">Treatment High</td>
<td valign="top" align="center">19.380</td>
<td valign="top" align="center">18.297</td>
<td valign="top" align="center">52.448</td>
<td valign="top" align="center">1.059</td>
<td valign="top" align="center">0.294</td>
</tr>
<tr>
<td valign="top" align="left">Treatment Extreme</td>
<td valign="top" align="center">44.756</td>
<td valign="top" align="center">18.297</td>
<td valign="top" align="center">52.448</td>
<td valign="top" align="center">2.446</td>
<td valign="top" align="center">
<bold>0.018</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Day of Observation</td>
<td valign="top" align="center">-0.720</td>
<td valign="top" align="center">0.359</td>
<td valign="top" align="center">440.000</td>
<td valign="top" align="center">-2.002</td>
<td valign="top" align="center">
<bold>0.046</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Treatment High x Day of Observation</td>
<td valign="top" align="center">-0.346</td>
<td valign="top" align="center">0.476</td>
<td valign="top" align="center">440.000</td>
<td valign="top" align="center">-0.729</td>
<td valign="top" align="center">0.467</td>
</tr>
<tr>
<td valign="top" align="left">Treatment Extreme x Day of Observation</td>
<td valign="top" align="center">-0.443</td>
<td valign="top" align="center">0.476</td>
<td valign="top" align="center">440.000</td>
<td valign="top" align="center">-0.932</td>
<td valign="top" align="center">0.353</td>
</tr>
<tr>
<td valign="top" rowspan="5" align="left">
<bold>Attachment</bold>
</td>
<td valign="top" align="left">Treatment High</td>
<td valign="top" align="center">-2.329</td>
<td valign="top" align="center">18.127</td>
<td valign="top" align="center">65.105</td>
<td valign="top" align="center">-0.128</td>
<td valign="top" align="center">0.898</td>
</tr>
<tr>
<td valign="top" align="left">Treatment Extreme</td>
<td valign="top" align="center">-36.434</td>
<td valign="top" align="center">18.127</td>
<td valign="top" align="center">65.105</td>
<td valign="top" align="center">-2.010</td>
<td valign="top" align="center">
<bold>0.049</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Day of Observation</td>
<td valign="top" align="center">1.086</td>
<td valign="top" align="center">0.389</td>
<td valign="top" align="center">440.000</td>
<td valign="top" align="center">2.791</td>
<td valign="top" align="center">
<bold>0.006</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Treatment High x Day of Observation</td>
<td valign="top" align="center">-0.350</td>
<td valign="top" align="center">0.515</td>
<td valign="top" align="center">440.000</td>
<td valign="top" align="center">-0.680</td>
<td valign="top" align="center">0.497</td>
</tr>
<tr>
<td valign="top" align="left">Treatment Extreme x Day of Observation</td>
<td valign="top" align="center">0.105</td>
<td valign="top" align="center">0.515</td>
<td valign="top" align="center">440.000</td>
<td valign="top" align="center">0.204</td>
<td valign="top" align="center">0.839</td>
</tr>
<tr>
<td valign="top" rowspan="5" align="left">
<bold>Feed Intake</bold>
</td>
<td valign="top" align="left">Treatment High</td>
<td valign="top" align="center">0.329</td>
<td valign="top" align="center">0.081</td>
<td valign="top" align="center">15.974</td>
<td valign="top" align="center">4.037</td>
<td valign="top" align="center">
<bold>&lt;0.001</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Treatment Extreme</td>
<td valign="top" align="center">0.417</td>
<td valign="top" align="center">0.081</td>
<td valign="top" align="center">15.974</td>
<td valign="top" align="center">5.130</td>
<td valign="top" align="center">
<bold>&lt;0.001</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Day of Observation</td>
<td valign="top" align="center">0.004</td>
<td valign="top" align="center">0.002</td>
<td valign="top" align="center">120.000</td>
<td valign="top" align="center">2.338</td>
<td valign="top" align="center">
<bold>0.021</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Treatment High x Day of Observation</td>
<td valign="top" align="center">-0.001</td>
<td valign="top" align="center">0.002</td>
<td valign="top" align="center">120.000</td>
<td valign="top" align="center">-0.368</td>
<td valign="top" align="center">0.714</td>
</tr>
<tr>
<td valign="top" align="left">Treatment Extreme x Day of Observation</td>
<td valign="top" align="center">-0.005</td>
<td valign="top" align="center">0.002</td>
<td valign="top" align="center">120.000</td>
<td valign="top" align="center">-1.803</td>
<td valign="top" align="center">0.074</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Shown are the parameter estimates, standard error (SE), degrees of freedom (df), t-statistic value, and P-value. Significant differences (p&lt;0.05) are indicated in bold.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>Under extreme temperature (24 &#xb0;C) fish were also seen spending less time attached compared to fish from ambient temperature, and Dobs had also a significant effect (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref>, <xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>, <xref ref-type="supplementary-material" rid="SM1">
<bold>Table S3</bold>
</xref>).</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Time spent attached (s<sup>-1</sup>) by long-snouted seahorse exposed to different temperature treatments (17&#xb0;C, 20&#xb0;C and 24&#xb0;C). Bold * represent significant differences from control treatment.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-10-1136748-g004.tif"/>
</fig>
<p>Time spent stationary but moving either the body or the fins (body movement) did not differ across treatments, or Dobs (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>, <xref ref-type="supplementary-material" rid="SM1">
<bold>Table S3</bold>
</xref>).</p>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>Temperature effects on feed intake</title>
<p>Fish under warming conditions (20 and 24&#xb0;C) showed significantly higher feed intake when compared to fish under ambient temperature (17&#xb0;C) (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5</bold>
</xref>, <xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>, <xref ref-type="supplementary-material" rid="SM1">
<bold>Table S3</bold>
</xref>). Dobs had also a significant effect on feed intake, but no interation between Dobs and Temperature was detected (<xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>).</p>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p>Impact of ocean warming on the feed intake of long-snouted seahorse exposed to different temperature treatments (17&#xb0;C, 20&#xb0;C and 24&#xb0;C). Bold * represent significant differences from control treatment.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-10-1136748-g005.tif"/>
</fig>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>Statistical results of the Generalized Linear on weight gain (%) of long-snouted seahorse exposed to three temperature treatments &#x2013; control (17&#xb0;C), high (20&#xb0;C), and extreme (24&#xb0;C).</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Variable</th>
<th valign="top" align="center"/>
<th valign="top" align="center">Estimate</th>
<th valign="top" align="center">Std.Error</th>
<th valign="top" align="center">t-value</th>
<th valign="top" align="center">Pr(&gt;|t|)</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>Weight gain</bold>
</td>
<td valign="top" align="left">Treatment High</td>
<td valign="top" align="center">7.289</td>
<td valign="top" align="center">12.935</td>
<td valign="top" align="center">0.564</td>
<td valign="top" align="center">0.580</td>
</tr>
<tr>
<td valign="top" align="left">Treatment Extreme</td>
<td valign="top" align="center">8.712</td>
<td valign="top" align="center">12.935</td>
<td valign="top" align="center">0.674</td>
<td valign="top" align="center">0.509</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Shown are the parameter estimates, standard error (SE), t-statistic value, and P-value. Significant differences (p&lt;0.05) are indicated in bold.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_3">
<label>3.3</label>
<title>Temperature effects on weight gain</title>
<p>Weight gain, at the end of the exposure period, did not differ across treatments (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6</bold>
</xref>, <xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>, <xref ref-type="supplementary-material" rid="SM1">
<bold>Table S2</bold>
</xref>).</p>
<fig id="f6" position="float">
<label>Figure&#xa0;6</label>
<caption>
<p>Impact of ocean warming on weight gain (%) of long-snouted seahorse exposed to different temperature treatments (17&#xb0;C, 20&#xb0;C and 24&#xb0;C).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-10-1136748-g006.tif"/>
</fig>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<label>4</label>
<title>Discussion</title>    <p>Results from the present study reflect differences in behavioral responses in seahorses exposed to different elevated temperatures for a long-term period (2 months). Fish were significantly more active under extreme temperature conditions (24&#xb0;C) (less time resting, more time swimming and unattached), and were also seen feeding more under both high and extreme temperatures (20&#xb0;C and 24&#xb0;C). Higher food ingestion did not translate into an increased body condition, though, as the weight gain of the fish did not differ across treatments. Temperature can impact differently fish locomotion and activity. While some studies suggest that individual activity increases with temperature (<xref ref-type="bibr" rid="B45">Ojanguren and Bra&#xf1;ta, 2000</xref>; <xref ref-type="bibr" rid="B3">Biro et&#xa0;al., 2010</xref>), others conclude that swimming ability decreases under warming conditions (<xref ref-type="bibr" rid="B36">Johansen and Jones, 2011</xref>). The elevated temperature was shown to increase swimming activity in Atlantic cod, <italic>Gadus morhua</italic> (<xref ref-type="bibr" rid="B8">Claireaux et&#xa0;al., 2000</xref>), but impact negatively swimming activity in juvenile brown trout, <italic>Salmo trutta</italic> (<xref ref-type="bibr" rid="B45">Ojanguren and Bra&#xf1;ta, 2000</xref>). In the current study, we found a significant temperature effect on swimming activity, with fish under extreme temperature treatment (24&#xb0;C) being more active (more time spent swimming) and spending less time resting. Similarly, a study on the activity of adult lined seahorses showed that when they were exposed to higher temperatures close to the species&#x2019; thermal limit (30&#xb0;C), they increased their swimming as opposed to seahorses maintained at lower temperatures (22 and 26&#xb0;C) (<xref ref-type="bibr" rid="B55">Qin et&#xa0;al., 2018</xref>). Interestingly, two other studies conducted on the long-snouted seahorse, from the same collection site, exposed to much more extreme temperature conditions (26&#xb0;C, 28&#xb0;C, 30&#xb0;C), did not find an effect of temperature on frequency of swimming or periods of inactivity when compared to fish from control temperatures (18&#xb0;C) (<xref ref-type="bibr" rid="B2">Aur&#xe9;lio et&#xa0;al., 2013</xref>; <xref ref-type="bibr" rid="B23">Faleiro et&#xa0;al., 2015</xref>). Some studies in other fish species have demonstrated that swimming activity decreases at low temperatures, increase to a peak and then decrease as the temperature approaches the upper thermal limit (<xref ref-type="bibr" rid="B44">Myrick and Cech, 2000</xref>; <xref ref-type="bibr" rid="B45">Ojanguren and Bra&#xf1;ta, 2000</xref>). This could explain the results from those authors&#x2019; studies &#x2013; the extreme temperatures the seahorses were exposed to might already be close to their thermal limit. Another possible explanation for the observed differences might relate to methodological aspects. In the current study, we run behavioral observations three times a week, for 2 months, and observations were performed early in the morning before feeding. <xref ref-type="bibr" rid="B2">Aur&#xe9;lio et&#xa0;al. (2013)</xref> and <xref ref-type="bibr" rid="B23">Faleiro et&#xa0;al. (2015)</xref> had shorter periods of behavioral observations and run observations 30&#xa0;min after feeding. This might have influenced the time spent swimming/inactive as fish might still be under post-prandial effects.</p>    <p>In response to a warmer environment, fish will increase their energetic demands and consequently will need to ingest more food (<xref ref-type="bibr" rid="B65">Sswat et&#xa0;al., 2018</xref>) , to maintain core activities. As expected, in our study, fish under the extreme temperature treatment (24&#xb0;C) significantly ingested more food than fish under ambient and high-temperature treatments (17&#xb0;C and 20&#xb0;C). Contrasting results were reported by <xref ref-type="bibr" rid="B2">Aur&#xe9;lio et&#xa0;al. (2013)</xref> and <xref ref-type="bibr" rid="B23">Faleiro et&#xa0;al. (2015)</xref>, with no changes in feed intake rates of <italic>H. guttulatus</italic> under extreme water temperatures (26&#xb0;C, 28&#xb0;C, 30&#xb0;C). Also, <xref ref-type="bibr" rid="B55">Qin et&#xa0;al. (2018)</xref> fail to detect an influence of temperature on the feeding frequency of the <italic>H. erectus</italic> after 1 week at 30&#xb0;C, which is close to the species&#x2019; thermal limit. However, in these 3 studies, authors observed an increase in metabolic rates and ventilation rates (which we did not measure in the current study), supporting an increased metabolic activity under higher temperatures. The increase in metabolic rates but the absence of a temperature effect on feeding rates might indicate that the species was already outside their optimum temperature limit, as feed intake might decrease if the temperature surpasses the species&#x2019; optimum limits (<xref ref-type="bibr" rid="B70">Volkoff and R&#xf8;nnestad, 2020</xref>). Therefore, individuals might have adopted a saving-energy strategy by not spending energy on feeding but making digestion more efficient.</p>    <p>Temperature increases within an appropriate range usually promote fish growth (<xref ref-type="bibr" rid="B29">Green and Fisher, 2004</xref>), and therefore we were expecting to have fish under the better condition at higher temperatures. In our study, fish did not show any significant change in their body weight among the different temperatures they were exposed to. Similarly, <xref ref-type="bibr" rid="B55">Qin et&#xa0;al. (2018)</xref> did not find differences in weight or body height of adult <italic>H. erectus</italic> exposed to different temperature scenarios (22, 26, and 30 &#xb0;C) for a 4-week period. However, the seahorse hepatosomatic index (HSI) was lower under 30 &#xb0;C, while metabolic rates were higher at this temperature. Authors argue that thermal stress inhibited hepatic energy reserves and leads to lower HSI by increasing energy consumption. In our study the lack of temperature-induces effects in fish growth was possible due to fish being more active under extreme temperatures (24&#xb0;C), thus spending more energy. Nonetheless, we can also not rule out the possibility that seahorses were already under thermal stress at these extreme temperatures. Mascar&#xf3; et&#xa0;al. (<xref ref-type="bibr" rid="B41">Mascar&#xf3; et&#xa0;al., 2016</xref>, <xref ref-type="bibr" rid="B42">Mascar&#xf3; et&#xa0;al., 2019</xref>), for example, report that chronic exposure (1 month) to the extreme temperature of 30&#xb0;C significantly reduced juvenile <italic>H. erectus</italic> growth. Using transcriptome data, <xref ref-type="bibr" rid="B19">del Vecchio et&#xa0;al. (2022)</xref> provide evidence of repression of the MEF2A gene within the first 0.5&#xa0;h of exposure of the <italic>H. erectus</italic> to target temperatures (30 and 33 &#xb0;C). This gene is implicated in the regulation of growth and differentiation of muscle fibers, and its repression might justify changes in growth under temperatures close to the s&#x2019;ecies&#x2019; thermal limits. Despite the relevance of this study, the rate of thermal increase untill reaching the target temperatures (abrupt: &lt; 5&#xa0;min; gradual, 1-1.5 &#xb0;C every 3&#xa0;h) and the fact that the authors only collected data after 0.5&#xa0;h of exposure prevents us from making further conclusions on the effects of prolonged warming on growth.</p>
<p>A word of caution is needed when interpreting results of the current study, as it took place during the breeding season of the species, and reproduction changes activity rate (which likely justifies the observed significant effect of Day of Observation) and physiological condition (weight gain) of individuals. Therefore, its influence on the response variables under measure is difficult to control. Nevertheless, courtship behaviors and daily greetings (<xref ref-type="bibr" rid="B68">Vincent, 1995</xref>) were regularly and evenly recorded across the three temperature treatments during the 8-week exposure period (19 courtship events under ambient temperature; 21 events under high temperature; 21 events under extreme temperatures). Moreover, all males across treatments were seen to become pregnant at a certain point of the experimental period, even though the number of successful pregnancies differed across treatments. Therefore, the observed changes at the behavioral level and feeding rate are likely to truly reflect a temperature effect, rather than just an influence of reproductive activity. A total of 7 successful breeding events were registered, being 4 events (in 3 out of the 4 males) in couples from the extreme temperature (24&#xb0;C), 2 events (in 2 out of the 4 males) in couples from the high temperature (20&#xb0;C), and 1 event (in 1 out of the 3 males) in ambient temperature (17&#xb0;C). As reproduction is considered to be sensitive to thermal stress (<xref ref-type="bibr" rid="B54">P&#xf6;rtner and Farrell, 2008</xref>) our results, then, might indicate that the range of tested temperatures was not enough to negatively impact reproduction, and it could even suggest that breeding is stimulated at higher temperatures. <xref ref-type="bibr" rid="B55">Qin et&#xa0;al. (2018)</xref> found no significant negative effects on gonad development or reproductive endocrine regulation genes in response to chronic thermal stress (1 month, at 30 &#xb0;C) in the <italic>H. erectus</italic>. The authors argue that the species&#x2019; reproductive behavior is adapted to higher-temperature conditions, as <italic>H. erectus</italic> seasonally migrate into warm waters for breeding and return to offshore areas when the water cools (<xref ref-type="bibr" rid="B4">Boehm et&#xa0;al., 2015</xref>). Nevertheless, in the present study, and despite the suggestion of increased reproductive activity under high and extreme temperature conditions (20 and 24&#xb0;C), episodes of unsuccessful egg transfer from the female to the male were recorded only under these temperature conditions and were frequently observed in couples where males were not responsive to females approach and courtship. Moreover, abortion was also registered at high temperatures (20&#xb0;C), with the male releasing embryos of several developmental stages. Altogether, these observations might suggest that there is a high but unsuccessful investment in reproduction under warming conditions. Consequences at the offspring level were not possible to infer, as we were unable to maintain the newborns. Future studies should take a closer look at the impacts of high temperatures on the reproductive success of these species.</p>
<p>Overall, and despite the limited number of individuals available to run this experimental study, our results points to a negative consequence of ocean warming on behavior and feeding rate of adult <italic>H. guttulatus</italic>. To truly understand if these individuals were already under thermal stress at the extreme temperature of 24&#xb0;C, additional physiological and biochemical endpoints would be needed. Determination of metabolic rates, such as minimum and maximum metabolic rate, is a highly useful physiological tool that allows a better understanding of fish metabolic performance under different environmental conditions, and, as it involves minimum manipulation of the individual, there is a low risk of death. The set of physiological responses to warming is the reflection of a prompt cellular stress reaction triggered to maintain the organism&#x2019;s homeostasis, and it involves biochemical adjustments of metabolic pathways and the regulatory activity of the antioxidant system (<xref ref-type="bibr" rid="B64">Sopinka et&#xa0;al., 2016</xref>). These indicators provide highly relevant information for evaluating stress response levels, but the downside is that they require the euthanasia of individuals, for tissue and blood sampling. To avoid invasive and lethal practices with a species that holds a special conservation status, we decided not to evaluate these physiological responses.</p>
<p>Seahorses are a great model to study the effects of climate change on the fitness and behavior of sedentary and low dispersal species, acting as an indicator of ecosystem health. These species can be used as flagship species for conservation issues and can be found worldwide in some of the most vulnerable marine ecosystems in shallow waters (<xref ref-type="bibr" rid="B69">Vincent et&#xa0;al., 2011</xref>). The population of the <italic>H. guttulatus</italic> from the Sado estuary is subject to intense pressure from other anthropogenic activities, such as overexploitation, pollution, and habitat destruction. All these pressures reduce the likelihood of these species to acclimatize and hinder the opportunity to persist in a changing environment. If protective measures are not taken, seahorse populations might suffer a sharp decline in numbers, and in long term affect this population&#x2019;s fitness and survival.</p>
</sec>
<sec id="s5" sec-type="data-availability">
<title>Data availability statement</title>
<p>The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.</p>
</sec>
<sec id="s6" sec-type="ethics-statement">
<title>Ethics statement</title>
<p>This study was carried out under the approval of Dire&#xe7;&#xe3;o-Geral de Alimenta&#xe7;&#xe3;o e Veterin&#xe1;ria (DGAV, Portuguese Authority for Animal Health, permit 0421/000/000/2020) and according to the ISPA University&#x2019;s animal ethics guidelines.</p>
</sec>
<sec id="s7" sec-type="author-contributions">
<title>Author contributions</title>
<p>AC: methodology, data collection, data analysis, writing- original draft preparation, writing - review and editing; MC: conceptualization, methodology, writing- original draft preparation, writing - review and editing; GS: methodology, writing - review and editing; AL: data analysis, writing - review and editing; AF: funding acquisition, project administration, conceptualization, methodology, writing- original draft preparation. All authors contributed to the article and approved the submitted version.</p>
</sec>
</body>
<back>
<sec id="s8" sec-type="funding-information">
<title>Funding</title>
<p>This study had the support of FCT through UIDB/MAR/04292/2020, UIDP/MAR/04292/2020 awarded to MARE, and through the project LA/P/0069/2020 granted to the Associate Laboratory ARNET. This work was further supported by the Projects NextGen (PTDC/CTA-AMB/31532/2017), and SARDITEMP (PTDC/BIA-BMA/32209/2017), co-financed by FCT and European Union through FEDER (European Regional Development Fund), and CavAlmar, funded by C&#xe2;mara Municipal Almada. The study also benefited from a PADI Foundation grant attributed to AF.</p>
</sec>
<ack>
<title>Acknowledgments</title>
<p>The authors would like to thank Ant&#xf3;nio Roleira for the valuable assistance throughout the experimental work; Friederike Peiffer, Mariana Coxey, M&#xe1;rio Rolim, Noelia Rios, and S&#xed;lvia Tavares for the support on the fieldwork; and Roland Pfeiffer for statistical advice.</p>
</ack>
<sec id="s9" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="s10" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec id="s11" sec-type="supplementary-material">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fmars.2023.1136748/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fmars.2023.1136748/full#supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="Table_1.docx" id="SM1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document"/>
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