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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.2021.742907</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>Patterns of Consumption Across a Caribbean Seascape: Roles of Habitat and Consumer Species Composition Through Time</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name><surname>Ritter</surname> <given-names>Carmen J.</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1401312/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Harper</surname> <given-names>Leah M.</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="http://loop.frontiersin.org/people/1476985/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Lefcheck</surname> <given-names>Jonathan S.</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="http://loop.frontiersin.org/people/671887/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Paul</surname> <given-names>Valerie J.</given-names></name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/342734/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Whippo</surname> <given-names>Ross</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1515123/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Jones</surname> <given-names>Scott</given-names></name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/755227/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Ogburn</surname> <given-names>Matthew B.</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/387836/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Duffy</surname> <given-names>J. Emmett</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="http://loop.frontiersin.org/people/510541/overview"/>
</contrib>
</contrib-group>
<aff id="aff1"><sup>1</sup><institution>Tennenbaum Marine Observatories Network and MarineGEO Program, Smithsonian Institution</institution>, <addr-line>Edgewater, MD</addr-line>, <country>United States</country></aff>
<aff id="aff2"><sup>2</sup><institution>Smithsonian Environmental Research Center</institution>, <addr-line>Edgewater, MD</addr-line>, <country>United States</country></aff>
<aff id="aff3"><sup>3</sup><institution>Smithsonian Marine Station</institution>, <addr-line>Fort Pierce, FL</addr-line>, <country>United States</country></aff>
<aff id="aff4"><sup>4</sup><institution>Oregon Institute of Marine Biology</institution>, <addr-line>Charleston, OR</addr-line>, <country>United States</country></aff>
<author-notes>
<fn fn-type="edited-by"><p>Edited by: Cataldo Pierri, University of Bari Aldo Moro, Italy</p></fn>
<fn fn-type="edited-by"><p>Reviewed by: Aldo S. Pacheco, National University of San Marcos, Peru; Alice Rogers, Victoria University of Wellington, New Zealand</p></fn>
<corresp id="c001">&#x002A;Correspondence: Carmen J. Ritter, <email>carmenjeanritter@gmail.com</email></corresp>
<fn fn-type="other" id="fn004"><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>27</day>
<month>10</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="collection">
<year>2021</year>
</pub-date>
<volume>8</volume>
<elocation-id>742907</elocation-id>
<history>
<date date-type="received">
<day>16</day>
<month>07</month>
<year>2021</year>
</date>
<date date-type="accepted">
<day>06</day>
<month>10</month>
<year>2021</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2021 Ritter, Harper, Lefcheck, Paul, Whippo, Jones, Ogburn and Duffy.</copyright-statement>
<copyright-year>2021</copyright-year>
<copyright-holder>Ritter, Harper, Lefcheck, Paul, Whippo, Jones, Ogburn and Duffy</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>Herbivores, omnivores, and predators transfer energy and structure the communities of many coastal marine ecosystems, and the intensity with which they consume prey and contribute to ecosystem functioning varies substantially among habitats over short time periods. Whether generalities across habitats might emerge for longer time series and using standard methods remains largely untested. Here, we deployed standardized assays of consumption using dried squid (&#x201C;squidpops&#x201D;) and five common macrophytes (&#x201C;weedpops&#x201D;) to quantify consumption across coral fore reef and patch reefs, mangroves, seagrass meadows, and bare sand from 2015 to 2019 around Carrie Bow Cay, Belize. We also used video in 2017 to identify the species responsible for consumption. We found that both squid- and weedpop consumption were consistently highest on patch and fore reef habitats, moderate in mangroves, and lowest in seagrass and sand across all years of the survey. Videos showed that the majority of consumption on the reefs in 2017 could be attributed to &#x003C; 5 fish species, and the identity of the dominant consumers differed among habitats. This study validates a key but implicit assumption in marine ecology that relative patterns in consumption across habitats are consistent through space and time in tropical nearshore environments, and reveals that high consumption rates may be the consequence of one or few species in each location.</p>
</abstract>
<kwd-group>
<kwd>herbivory</kwd>
<kwd>predation</kwd>
<kwd>coral reef</kwd>
<kwd>seagrass</kwd>
<kwd>mangrove</kwd>
<kwd>Belize</kwd>
<kwd>squidpop</kwd>
</kwd-group>
<counts>
<fig-count count="8"/>
<table-count count="3"/>
<equation-count count="0"/>
<ref-count count="61"/>
<page-count count="12"/>
<word-count count="8351"/>
</counts>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="S1">
<title>Introduction</title>
<p>Both herbivory and predation are key processes within food webs that control biomass distribution and species composition within and across communities (<xref ref-type="bibr" rid="B3">Borer et al., 2006</xref>; <xref ref-type="bibr" rid="B23">Halpern et al., 2006</xref>). Understanding spatial and temporal variation in consumption is crucial for predicting how ecosystems will respond to global and local change, including warming climate and fishing impacts (<xref ref-type="bibr" rid="B38">Ling et al., 2009</xref>; <xref ref-type="bibr" rid="B59">Verg&#x00E9;s et al., 2011</xref>). Although relative variation in primary production and producer biomass can be compared efficiently in both terrestrial and marine environments, the mobility, diet, and behavior of consumers (e.g., fishes) make their distribution and top-down impacts challenging to quantify, especially in marine habitats (<xref ref-type="bibr" rid="B11">Duffy et al., 2015</xref>; <xref ref-type="bibr" rid="B17">Fraser et al., 2020</xref>; <xref ref-type="bibr" rid="B60">Whalen et al., 2020</xref>). However, an increasing number of studies have demonstrated that top-down processes vary predictably across latitude within a handful of marine habitats (<xref ref-type="bibr" rid="B18">Freestone et al., 2011</xref>; <xref ref-type="bibr" rid="B54">Rodemann and Brandl, 2017</xref>; <xref ref-type="bibr" rid="B44">Musrri et al., 2019</xref>; <xref ref-type="bibr" rid="B60">Whalen et al., 2020</xref>; <xref ref-type="bibr" rid="B33">Lefcheck et al., 2021</xref>), which may give insight into fish presence and behaviors, and help with the interpretation of consumption processes (<xref ref-type="bibr" rid="B15">Ferreira et al., 2004</xref>; <xref ref-type="bibr" rid="B47">Navarrete et al., 2005</xref>).</p>
<p>Tropical marine seascapes contain a patchwork of nearshore habitats and therefore are an ideal test bed for understanding variation in consumption among habitat types and trophic guilds, including various types of consumers. In the past decade, a landscape-level perspective has informed the value of coastal habitats as nurseries (<xref ref-type="bibr" rid="B46">Nagelkerken et al., 2015</xref>), and this perspective could also help to unite the large body of literature examining within-habitat variation in consumption rates. Coral reefs, for example, are among the best-studied marine ecosystems with respect to trophic processes, and there is a long history exploring how grazing by herbivorous fishes is critical in maintaining a coral-dominated state (<xref ref-type="bibr" rid="B36">Lewis, 1986</xref>; <xref ref-type="bibr" rid="B5">Burkepile and Hay, 2010</xref>; <xref ref-type="bibr" rid="B57">Tootell and Steele, 2016</xref>). Seagrasses have also long been the focus of comparative experiments to understand how predation&#x2014;generally in the form of tethered prey&#x2014;varies across space and through time (<xref ref-type="bibr" rid="B27">Heck and Wilson, 1987</xref>). Nevertheless, fewer studies explore how consumption changes across multiple habitats within the same coastal seascape, and those that do have revealed inconsistent patterns in terms of the degree of consumption observed in different habitats (<xref ref-type="bibr" rid="B6">Chittaro et al., 2005</xref>; <xref ref-type="bibr" rid="B24">Hammerschlag et al., 2010</xref>). Indeed, a recent meta-analysis on nursery function uncovered only a dozen or so studies comparing among multiple habitats (coral reefs, mangroves, and/or seagrasses), and these failed to reveal any general patterns in terms of juvenile survival/predation risk associated with each (<xref ref-type="bibr" rid="B31">Lefcheck et al., 2019a</xref>). One potential explanation is that studies to date have rarely had temporal breadth to uncover such generalities, as longer time series may reduce natural variability enough to resolve differences among habitats in trophic processes.</p>
<p>The question of how consumption varies across tropical seascapes is timely, as both the habitats and the species they support are changing rapidly and might lead to substantial changes in ecosystem functioning. Caribbean marine ecosystems in particular have suffered declines in coral cover and structural complexity (<xref ref-type="bibr" rid="B20">Gardner et al., 2003</xref>; <xref ref-type="bibr" rid="B2">Alvarez-Filip et al., 2009</xref>), seagrass cover and density (<xref ref-type="bibr" rid="B56">Stallings, 2009</xref>), and mangrove forest extent (<xref ref-type="bibr" rid="B61">Wilson, 2017</xref>). Concurrently, herbivorous, omnivorous, and predatory fishes have all declined in abundance, biomass, and diversity in the Caribbean (<xref ref-type="bibr" rid="B50">Paddack et al., 2009</xref>; <xref ref-type="bibr" rid="B56">Stallings, 2009</xref>), leaving them less able to control macroalgal accumulation on coral reefs (<xref ref-type="bibr" rid="B53">Rasher et al., 2013</xref>; <xref ref-type="bibr" rid="B1">Adam et al., 2015</xref>; <xref ref-type="bibr" rid="B32">Lefcheck et al., 2019b</xref>). Establishing a strong baseline for consumption throughout the region is a critical step in evaluating change, including recovery. Belize, for example, has recently banned the harvest of parrotfishes and surgeonfishes, leading to a recovery in parrotfish abundance and consequent reductions in macroalgae and increases in coral cover (<xref ref-type="bibr" rid="B43">Mumby et al., 2021</xref>).</p>
<p>To better understand how the intensity of consumption by herbivores and predators varies with habitat, over time, and with fish assemblage across a Caribbean seascape, we deployed standard assays of macrophyte and dried squid consumption annually over five consecutive years (2015&#x2013;2019) across seventeen sites and five habitats around Carrie Bow Cay, Belize, including fore reef, patch reef, mangrove, seagrass, and sand. Additionally, we conducted visual surveys of fish communities annually in habitats to quantify fish biomass and diversity and, in 2017, used video analysis at a subset of habitats to directly identify the fish species responsible for consumption. Our primary goal was to establish a baseline of relative consumption, and further we expected that&#x2014;as in previous studies (e.g., <xref ref-type="bibr" rid="B26">Hay, 1984</xref>; <xref ref-type="bibr" rid="B11">Duffy et al., 2015</xref>)&#x2014;consumption would be highest on highly structured reefs and lowest on unstructured sand flats, and that most consumption would be attributable to a small number of consumer species (<xref ref-type="bibr" rid="B1">Adam et al., 2015</xref>).</p>
</sec>
<sec id="S2" sec-type="materials|methods">
<title>Materials and Methods</title>
<sec id="S2.SS1">
<title>Study Sites</title>
<p>We conducted consumption assays at sites off the coast of Belize surrounding the Smithsonian Institution&#x2019;s field station at Carrie Bow Cay (<xref ref-type="fig" rid="F1">Figure 1</xref> and <xref ref-type="supplementary-material" rid="DS1">Supplementary Table 1</xref>). We chose 3&#x2013;4 representative sites in each of: fore reef, patch reef, mangrove, sand, and seagrass habitats. Sites within each habitat were selected to be as similar to one another as possible, taking into account areal extent, sessile species cover, and depth. Lagoonal patch reef sites are distinguished from fore reef sites by having generally lower wave energy, higher turbidity (<xref ref-type="bibr" rid="B29">Koltes and Opishinski, 2009</xref>), and smaller areal extent. Patch reefs were leeward of the fore reef sites and approximately 3 m shallower in depth.</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption><p>Map of all Carrie Bow Cay sites off the coast of Belize.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-08-742907-g001.tif"/>
</fig>
</sec>
<sec id="S2.SS2">
<title>Predation Assays (Squidpops)</title>
<p>We quantified relative prey consumption by mid-level generalist carnivores using the &#x201C;squidpop&#x201D; method, offering dried squid as a standard prey item (<xref ref-type="bibr" rid="B11">Duffy et al., 2015</xref>). This method has been used successfully in the past to examine spatial and temporal variation in consumer pressure (<xref ref-type="bibr" rid="B54">Rodemann and Brandl, 2017</xref>; <xref ref-type="bibr" rid="B21">Gauff et al., 2018</xref>), and has the advantage of using a single standard bait type consistently across all habitats and years. To craft a squidpop, whole dried squid mantle was cut into 1.3 cm diameter discs of 1&#x2013;2 mm width, and each disc was attached to a 60 cm garden stake using a 1 cm length of monofilament, which was fixed to the stake with electrical tape. Twenty to twenty-five squidpops were deployed at each location, near the weedpops (see next section). Squidpop stakes were planted vertically into soft substrate 2 m apart along a single 50 m transect and scored for presence or absence of squid at 1 and 24 h.</p>
</sec>
<sec id="S2.SS3">
<title>Herbivory Assays (Weedpops)</title>
<p>To quantify relative herbivory rates, we constructed &#x201C;weedpops&#x201D; by selecting a set of local macrophytes and weaving a 4&#x2013;5 cm portion of each into a braided nylon rope, which was then deployed on the reef following established protocol (<xref ref-type="bibr" rid="B25">Hay, 1981</xref>). We used five common macrophytes known to vary in palatability and defenses against grazers (<xref ref-type="bibr" rid="B51">Paul and Hay, 1986</xref>) representing different functional groups of macrophytes that are widely distributed across the world&#x2019;s tropical reefs (<xref ref-type="bibr" rid="B39">Littler et al., 1983</xref>): a palatable red alga (<italic>Acanthophora spicifera</italic>), a common brown macroalga (<italic>Dictyota</italic> sp.), a calcareous green alga (<italic>Halimeda opuntia</italic> or <italic>Halimeda tuna</italic>), a tough brown alga (<italic>Sargassum histrix</italic>), and the most locally common seagrass (<italic>Thalassia testudinum</italic>). This selection offers a range in toughness, appearance, palatability, growth form, chemical and structural defenses, and nutrient content, and includes algal species previously used in similar choice assays (<xref ref-type="bibr" rid="B25">Hay, 1981</xref>; <xref ref-type="bibr" rid="B35">Lewis, 1985</xref>; <xref ref-type="bibr" rid="B51">Paul and Hay, 1986</xref>). The natural form of these five distinct macrophytes was preserved when cutting them to similarly sized pieces, which were then inserted in random positions along a single braided nylon rope and gently looped into the braid to secure them in place.</p>
<p>Weedpops were deployed vertically with a weight attached to the bottom of the rope and a small float attached to the top, and were spaced approximately 2 m apart along a single 50 m transect at each location in the fall (mid-September through early November) within a 2 week period of each year from 2015 to 2019 (<xref ref-type="supplementary-material" rid="DS1">Supplementary Table 1</xref>). Twenty-five weedpops were deployed in 2015, and twenty were deployed each year from 2016 to 2019. After 1 and 24 h, each weedpop was scored for the presence or absence of each macrophyte species to obtain the overall proportion of each macrophyte lost in each habitat.</p>
</sec>
<sec id="S2.SS4">
<title>Video Capture of Consumption Assays</title>
<p>In 2017, we deployed video cameras to record the identity and numbers of consumers visiting the baits. At each site, we positioned a GoPro (Hero 3 +, San Mateo, CA, United States) such that two squidpops or weedpops were visible in the frame (<italic>n</italic> = 10 videos in total) and recorded 1 h of video footage. Weedpops were filmed at three sites each in fore reef and patch reef habitats. Squidpops were filmed at three sites each in fore reef, patch reef, mangrove, and seagrass habitats (<xref ref-type="supplementary-material" rid="DS1">Supplementary Table 1</xref>). Filming habitats were chosen based upon higher levels of consumption activity observed in previous years of the survey.</p>
<p>Each video period began after divers placed the squidpops or weedpops in view of the camera and left the scene, minimizing human interference. A single observer scored all videos by watching the footage and recording each &#x201C;bite event.&#x201D; Because fish occasionally mouthed the bait without consuming it, or immediately rejected it, we defined a bite event as the visually apparent removal and ingestion of some portion of the bait. For squidpops, a bite event was defined as the total removal of the bait from the stake, as all observed consumption events removed the bait in one piece. For each observed bite, we recorded the species of fish, the species of macrophyte (for weedpops), and the time elapsed after the start of the video.</p>
</sec>
<sec id="S2.SS5">
<title>Fish Assemblage Surveys</title>
<p>At each site from 2015 to 2019, during the same 2-week period that assays were deployed, fish community composition and size structure were assessed using a visual census following the Reef Life Survey method (<xref ref-type="bibr" rid="B14">Edgar and Stuart-Smith, 2014</xref>). SCUBA divers surveyed one 50 m x 10 m transect at each site, identifying, counting, and visually estimating the total length (categorized into size classes) of each fish observed within the transect. Visual reach of surveyors varied by habitat but was consistently greater than 5 m (range 5&#x2013;35 m) for all habitats except for the mangrove fringe. Because of limited visibility (6 m on average) in the mangroves and because divers were unable to swim through the center of a mangrove forest, the mangrove sites were divided into two 50 m &#x00D7; 5 m transects along the prop root boundary, and fish were surveyed within the root-containing side of each transect. Fish lengths were converted to biomass using length-weight regression equations with coefficients sourced from Fishbase (<xref ref-type="bibr" rid="B19">Froese and Pauly, 2021</xref>), following methods described by <xref ref-type="bibr" rid="B13">Edgar et al. (2020)</xref>, with length corrected for diver bias (<xref ref-type="bibr" rid="B12">Edgar et al., 2004</xref>).</p>
</sec>
<sec id="S2.SS6">
<title>Statistical Analysis</title>
<p>To test for differences in macrophyte consumption among habitats, we fit a generalized linear model (GLM) regressing the proportion of each macrophyte type lost (number lost out of total number of ropes) in a deployed set of weedpops at 1 and 24 h against year, habitat, macrophyte type, and the interactions between habitat and macrophyte type, and habitat and year, to test whether certain items were more heavily preferred in certain habitats, and if consumption pressure changed significantly between years (<xref ref-type="table" rid="T1">Table 1</xref>). We additionally modeled location as a fixed effect to account for any spatial autocorrelation. The GLM was fit to a quasibinomial distribution using a logit-link, and model assumptions were assessed visually. To determine the significance of our effects (with an experiment-wide &#x03B1; = 0.05), we applied Analysis of Deviance to the GLM using Type II Sums-of-Squares as implemented in the <italic>car</italic> package (<xref ref-type="bibr" rid="B16">Fox and Weisberg, 2019</xref>) in R version 4.0.3 (<xref ref-type="bibr" rid="B52">R Core Team., 2020</xref>). To test for differences in squidpop bait loss among habitats, we fit separate GLMs regressing the proportion bait lost at the 1 and 24 h time points against the interaction between habitat and year, with location as a fixed effect using a quasibinomial distribution due to observed variance substantially greater than the mean (<xref ref-type="supplementary-material" rid="DS2">Supplementary Table 2</xref>).</p>
<table-wrap position="float" id="T1">
<label>TABLE 1</label>
<caption><p>Type II Analysis of Deviance predicting the proportion of macrophyte types lost after 1 h <bold>(A)</bold> and 24 h <bold>(B)</bold>.</p></caption>
<table cellspacing="5" cellpadding="5" frame="hsides" rules="groups">
<thead>
<tr>
<td valign="top" align="left"><bold>(A)</bold></td>
<td/>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="center" colspan="4"><hr/></td>
</tr>
<tr>
<td valign="top" align="left"></td>
<td valign="top" align="center"><bold>LR &#x03C7;<sup>2</sup></bold></td>
<td valign="top" align="center"><bold>Df</bold></td>
<td valign="top" align="center"><bold>Pr (&#x003E; &#x03C7;<sup>2</sup>)</bold></td>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Habitat</td>
<td valign="top" align="center">260.414</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">&#x003C;2.2e-16</td>
</tr>
<tr>
<td valign="top" align="left"><italic>Macrophyte</italic> sp.</td>
<td valign="top" align="center">138.004</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">&#x003C;2.2e-16</td>
</tr>
<tr>
<td valign="top" align="left">Year</td>
<td valign="top" align="center">0.024</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">0.8774</td>
</tr>
<tr>
<td valign="top" align="left">Location</td>
<td valign="top" align="center">45.103</td>
<td valign="top" align="center">5</td>
<td valign="top" align="center">1.383e-08</td>
</tr>
<tr>
<td valign="top" align="left">Habitat: Macrophyte type</td>
<td valign="top" align="center">32.265</td>
<td valign="top" align="center">16</td>
<td valign="top" align="center">0.009234</td>
</tr>
<tr>
<td valign="top" align="left">Habitat: Year</td>
<td valign="top" align="center">2.710</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">0.6076</td>
</tr>
<tr>
<td valign="top" align="center" colspan="4"><hr/></td>
</tr>
<tr>
<td valign="top" align="left"><bold>(B)</bold></td>
<td/>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="center" colspan="4"><hr/></td>
</tr>
<tr>
<td valign="top" align="left"></td>
<td valign="top" align="center"><bold>LR &#x03C7;<sup>2</sup></bold></td>
<td valign="top" align="center"><bold>Df</bold></td>
<td valign="top" align="center"><bold>Pr (&#x003E; &#x03C7;<sup>2</sup>)</bold></td>
</tr>
<tr>
<td valign="top" align="center" colspan="4"><hr/></td>
</tr>
<tr>
<td valign="top" align="left">Habitat</td>
<td valign="top" align="center">264.996</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">&#x003C;2.2e-16</td>
</tr>
<tr>
<td valign="top" align="left"><italic>Macrophyte</italic> sp.</td>
<td valign="top" align="center">209.230</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">&#x003C;2.2e-16</td>
</tr>
<tr>
<td valign="top" align="left">Year</td>
<td valign="top" align="center">0.603</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">0.4374</td>
</tr>
<tr>
<td valign="top" align="left">Location</td>
<td valign="top" align="center">61.347</td>
<td valign="top" align="center">5</td>
<td valign="top" align="center">6.400e-12</td>
</tr>
<tr>
<td valign="top" align="left">Habitat: Macrophyte Type</td>
<td valign="top" align="center">64.420</td>
<td valign="top" align="center">16</td>
<td valign="top" align="center">9.268e-08</td>
</tr>
<tr>
<td valign="top" align="left">Habitat: Year</td>
<td valign="top" align="center">2.554</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">0.6350</td>
</tr>
</tbody>
</table></table-wrap>
<p>To analyze the weedpops video data, we fit a generalized linear mixed effects model (GLMM) of the log<sub>10</sub>-transformed number of bites per hour (bite rate) against the habitat type (fore vs. patch reef), macrophyte species, and their interaction, plus location as a fixed covariate, and camera as a varying-intercept random effect (<xref ref-type="table" rid="T2">Table 2</xref>). Fish species with fewer than five documented bites on any macrophyte across all videos were removed from the data set. As with the GLM, the model assumptions were assessed visually, and the significance of fixed effects was determined using Type II Analysis of Variance. We further calculated the marginal (fixed effects only) <italic>R</italic><sup>2</sup> using the <italic>piecewiseSEM</italic> package (<xref ref-type="bibr" rid="B30">Lefcheck, 2016</xref>).</p>
<table-wrap position="float" id="T2">
<label>TABLE 2</label>
<caption><p>Type II Analysis of Variance predicting the number of bites on the macrophyte types observed over a 1 h period using video assays.</p></caption>
<table cellspacing="5" cellpadding="5" frame="hsides" rules="groups">
<thead>
<tr>
<td valign="top" align="left"></td>
<td valign="top" align="center"><bold>&#x03C7;<sup>2</sup></bold></td>
<td valign="top" align="center"><bold>Df</bold></td>
<td valign="top" align="center"><bold>Pr (&#x003E; &#x03C7;<sup>2</sup>)</bold></td>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left"><italic>Macrophyte</italic> sp.</td>
<td valign="top" align="center">48.400</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">7.788e-10</td>
</tr>
<tr>
<td valign="top" align="left">Habitat</td>
<td valign="top" align="center">28.268</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">1.056e-07</td>
</tr>
<tr>
<td valign="top" align="left">Location</td>
<td valign="top" align="center">31.729</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">2.173e-06</td>
</tr>
<tr>
<td valign="top" align="left"><italic>Macrophyte</italic> sp.: Habitat</td>
<td valign="top" align="center">18.556</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">9.604e-04</td>
</tr>
<tr>
<td valign="top" align="left" colspan="4">Marginal R-squared = 0.38</td>
</tr>
</tbody>
</table></table-wrap>
<p>To identify the key herbivore species responsible for the bites in the video assays, we conducted a redundancy analysis (RDA) using the <italic>vegan</italic> package (<xref ref-type="bibr" rid="B49">Oksanen et al., 2020</xref>), predicting the species-by-site matrix of total bites per hour from a presence-absence matrix of fish species.</p>
<p>To quantify temporal stability in proportion of bait lost across the habitat types, we calculated a coefficient of variation for each site by dividing the variance across all 5 years by the mean across all 5 years (<italic>n</italic> = 3 sites per habitat) (<xref ref-type="supplementary-material" rid="DS3">Supplementary Table 3</xref> and <xref ref-type="fig" rid="F2">Figure 2</xref>). For weedpops assays, we first calculated the mean loss of all algal types to arrive at a single mean macrophyte bait loss value for each site. Finally, we calculated a mean and standard error of the coefficient of variation for squid and macrophyte bait loss in each habitat. For both squidpops and weedpops, we conducted pairwise tests to determine significance of difference between habitats using the emmeans package (<xref ref-type="bibr" rid="B34">Lenth, 2020</xref>).</p>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption><p>Mean coefficients of variation for sites (<italic>n</italic> = 3) within each habitat over 5 years (&#x00B1; 1 S.E.). Differing letters denote significant differences between values.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-08-742907-g002.tif"/>
</fig>
<p>We tested for relationships between consumer biomass and bait loss after 24 h for both squid and macrophyte baits using a series of GLMs fit with quasibinomial distributions (<xref ref-type="supplementary-material" rid="DS4">Supplementary Tables 4</xref>, <xref ref-type="supplementary-material" rid="DS5">5</xref>). Each GLM included year, habitat, location, and fish biomass as fixed covariates, allowing for an interaction between habitat and fish biomass. For squidpops, the biomass terms included all fish in the first model, only carnivores, invertivores, and omnivores in the second model, and only key families identified as key consumers in video assays (Lutjanidae, Haemulidae, and Labridae) in the third model. For weedpops, the biomass terms included all fish in the first model, only herbivorous and omnivorous taxa in the second model, and only key families identified as key consumers in video assays (Acanthuridae and Scaridae) in the third model. The same was done to test for a relationship between log<sub>10</sub>-transformed biomass of dominant herbivore families (Acanthuridae and Scaridae) from the surveys and macrophyte loss across weedpop deployments in fore reef and patch reef habitats, without the location fixed covariate, and with an added interaction between habitat and macrophyte species (<xref ref-type="table" rid="T3">Table 3</xref>). We calculated significance of effects within each of these models using a Type II ANOVA.</p>
<table-wrap position="float" id="T3">
<label>TABLE 3</label>
<caption><p>Type II Analysis of Deviance comparing the effects of habitat type (patch reef vs. fore reef), macrophyte type, key macrophyte consumer (Acanthuridae and Scaridae) biomass (log<sub>10</sub>-transformed), and year on the proportion of macrophyte types lost after 24 h.</p></caption>
<table cellspacing="5" cellpadding="5" frame="hsides" rules="groups">
<thead>
<tr>
<td valign="top" align="left"></td>
<td valign="top" align="center"><bold>LR &#x03C7;<sup>2</sup></bold></td>
<td valign="top" align="center"><bold>Df</bold></td>
<td valign="top" align="center"><bold>Pr (&#x003E;&#x03C7;<sup>2</sup>)</bold></td>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Biomass</td>
<td valign="top" align="center">11.843</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">0.0006</td>
</tr>
<tr>
<td valign="top" align="left">Habitat</td>
<td valign="top" align="center">12.095</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">0.0005</td>
</tr>
<tr>
<td valign="top" align="left">Macrophyte type</td>
<td valign="top" align="center">177.911</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">&#x003C;2.2e-16</td>
</tr>
<tr>
<td valign="top" align="left">Year</td>
<td valign="top" align="center">0.212</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">0.6455</td>
</tr>
<tr>
<td valign="top" align="left">log<sub>1</sub><sub>0</sub>(Biomass): Habitat</td>
<td valign="top" align="center">25.368</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">4.738e-07</td>
</tr>
<tr>
<td valign="top" align="left">Habitat: Macrophyte type</td>
<td valign="top" align="center">27.072</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">1.923e-05</td>
</tr>
</tbody>
</table></table-wrap>
<p>All data and R code necessary to reproduce the analyses are included in <xref ref-type="supplementary-material" rid="DS1">Supplementary Material</xref> and at <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.25573/serc.16744585">10.25573/serc.16744585</ext-link>.</p>
</sec>
</sec>
<sec sec-type="results" id="S3">
<title>Results</title>
<sec id="S3.SS1">
<title>Consumption Across Time and Space</title>
<p>Loss of both squid bait and macrophytes varied among habitats with consistent trends through time, being generally highest in structured reef habitats and lowest in unstructured sand (<xref ref-type="fig" rid="F2">Figures 2</xref>&#x2013;<xref ref-type="fig" rid="F4">4</xref> and <xref ref-type="supplementary-material" rid="DS8">Supplementary Figure 2</xref>). The consistency through time was corroborated by a non-significant effect of year in our GLM analysis of macrophytes (<italic>P</italic> = 0.88 and <italic>P</italic> = 0.44 for 1 and 24 h; <xref ref-type="table" rid="T1">Table 1</xref>). An exception was the near total loss of squid in sand habitats in 2017 after 24 h, leading to a significant effect of year in our GLM (<italic>P</italic> &#x003C; 0.01, <xref ref-type="supplementary-material" rid="DS2">Supplementary Table 2</xref>). However, squid consumption returned to pre-2017 levels in the following 2 years and consumption in other habitats remained consistent through time (<xref ref-type="fig" rid="F4">Figure 4</xref>). Macrophyte consumption varied significantly among habitats after 24 h (<italic>P</italic> &#x003C; 0.001) and was consistently highest in the structured habitats of fore and patch reefs (mean% lost &#x00B1; 1 SD = 45 &#x00B1; 5% and 56 &#x00B1; 6%), lower in seagrasses (8 &#x00B1; 5%) and mangroves (5 &#x00B1; 4%), and minimal (&#x003C; 2%) in bare sand. There was also a clear preference for certain macrophytes after 24 h, with <italic>Acanthophora</italic> being the most preferred (46 &#x00B1; 5% consumed, on average), followed by the seagrass <italic>Thalassia</italic> (35 &#x00B1; 5%), <italic>Dictyota</italic> (19 &#x00B1; 5%), and <italic>Sargassum</italic> (17 &#x00B1; 5%), and <italic>Halimeda</italic> was rarely consumed (4 &#x00B1; 3%) (<xref ref-type="fig" rid="F3">Figure 3</xref>). Similarly, squid baits were consumed the most in more structured habitats, with 94% or greater average loss of squid after 24 h on reefs and in mangroves in all years (<xref ref-type="fig" rid="F4">Figure 4</xref>).</p>
<fig id="F3" position="float">
<label>FIGURE 3</label>
<caption><p>Mean proportion of each macrophyte type consumed after 1 and 24 h (&#x00B1; 1 S.E.) across each year of the study, parsed by macrophyte type and habitat.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-08-742907-g003.tif"/>
</fig>
<fig id="F4" position="float">
<label>FIGURE 4</label>
<caption><p>Mean proportion of squid baits consumed after 1 and 24 h (&#x00B1; 1 S.E.) across each year of the study, parsed by habitat.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-08-742907-g004.tif"/>
</fig>
</sec>
<sec id="S3.SS2">
<title>Video Assays of Herbivory</title>
<p>One-hour video observations of the macrophyte assays in 2017 generally corroborated the patterns of macrophyte loss in the 1 and 24 h macrophyte assays, showing that grazing differed among fore reef and patch reef habitats and with a preference for <italic>Acanthophora</italic>, <italic>Dictyota</italic>, and <italic>Sargassum</italic>. <italic>Thalassia</italic> was grazed at a similar but slow rate in patch and fore reef habitats, and consumption rates of all macrophytes varied by both habitat and macrophyte type (interactive <italic>P</italic> &#x003C; 0.001, <xref ref-type="table" rid="T2">Table 2</xref>): <italic>Dictyota, Halimeda</italic>, and particularly <italic>Sargassum</italic> were all grazed at significantly higher rates on the patch reef than on the fore reef (<xref ref-type="fig" rid="F5">Figure 5</xref>).</p>
<fig id="F5" position="float">
<label>FIGURE 5</label>
<caption><p>Differences in bites per hour by location during a 1-h video survey in 2017 on patch and fore reef sites. Asterisks denote significance in pairwise contrasts conducted <italic>post hoc</italic> (&#x002A; = &#x003C; 0.05, &#x002A;&#x002A;&#x002A; = &#x003C; 0.001).</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-08-742907-g005.tif"/>
</fig>
<p>In the weedpop video assays, eight fish species were observed consuming macrophytes in fore reef habitats, while 14 species were observed feeding on them in patch reefs, and the dominant herbivores varied by both macrophyte type and habitat. These species were previously identified in diver visual surveys over all 5 years of the study period (<xref ref-type="supplementary-material" rid="DS8">Supplementary Figure 3B</xref>). Because the videos had a limited viewing window and fish would often pass in and out of frame while interacting with the assays, we could not differentiate between individual fish and potentially new consumers of the same species. Surgeonfishes (<italic>Acanthurus</italic> spp.) were the dominant grazers of <italic>Acanthophora</italic> in fore reef habitats. <italic>Sparisoma aurofrenatum</italic> was the dominant herbivore on patch reefs, consuming <italic>Sargassum</italic> and to a lesser extent <italic>Dictyota</italic> (<xref ref-type="fig" rid="F6">Figure 6</xref>). Supporting <xref ref-type="fig" rid="F6">Figure 6</xref>, our redundancy analysis (<xref ref-type="supplementary-material" rid="DS8">Supplementary Figure 4</xref>) also shows strong resource partitioning of the macrophytes among both habitats and herbivore species (<italic>F</italic><sub>14</sub> = 2.913, <italic>P</italic> = 0.003).</p>
<fig id="F6" position="float">
<label>FIGURE 6</label>
<caption><p>Mean bite rate for each fish herbivore per 1 h on each macrophyte observed in 2017 patch and fore reef. The size of the point is scaled by the total number of bites across all species and colored by habitat.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-08-742907-g006.tif"/>
</fig>
<p>In squidpop video assays, consumption on fore reefs was dominated by the wrasses <italic>Halichoeres garnoti</italic> and <italic>Halichoeres bivittatus</italic>, whereas consumption on patch reef habitats was attributable to a more diverse assemblage including species of wrasse (<italic>H. garnoti</italic>), grunt (<italic>Haemulon plumierii</italic>), and snapper (<italic>Lutjanus apodus</italic>) (<xref ref-type="fig" rid="F7">Figure 7</xref>). In mangrove habitats, three species of snappers (<italic>Lutjanus</italic> spp.) were responsible for nearly all bait consumption caught on video. Few squid baits were consumed in seagrass habitats, all by <italic>H. bivittatus</italic>.</p>
<fig id="F7" position="float">
<label>FIGURE 7</label>
<caption><p>Total number of squid baits consumed by each fish species observed on video in 2017. The size of the point is scaled by the total number of bites across all species and colored by habitat.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-08-742907-g007.tif"/>
</fig>
</sec>
<sec id="S3.SS3">
<title>Fish Assemblage Characteristics</title>
<p>Within habitats, consumption of squid baits was not significantly related to either the biomass of all fishes observed in visual surveys (<italic>P</italic> = 0.7575), nor to biomass of squid consumers (<italic>P</italic> = 0.8697), nor biomass of wrasses, snappers, and grunts specifically (<italic>P</italic> = 0.5886) (<xref ref-type="supplementary-material" rid="DS4">Supplementary Table 4</xref>). Rather, habitat and year were the only consistently significant predictors of squid bait loss in the model (<xref ref-type="supplementary-material" rid="DS4">Supplementary Table 4</xref>). For weedpop assays, total consumption of macrophytes differed among habitats but was unrelated to total fish biomass (<italic>P</italic> = 0.1660, <xref ref-type="supplementary-material" rid="DS5">Supplementary Table 5</xref>). However, when the fish assemblage was reduced to the subset of herbivores in the families Acanthuridae and Scaridae, there was a significant interaction between herbivorous fish log<sub>10</sub>-transformed biomass and habitat type (<italic>P</italic> &#x003C; 0.001, <xref ref-type="fig" rid="F8">Figure 8</xref> and <xref ref-type="supplementary-material" rid="DS5">Supplementary Table 5</xref>). Specifically, on patch reefs, consumption of all macrophyte types (except for <italic>Acanthophora</italic>) was greater where the herbivorous fish community biomass was highest, whereas in fore reefs, herbivorous fish biomass had no correlation with consumption (<xref ref-type="fig" rid="F8">Figure 8</xref>).</p>
<fig id="F8" position="float">
<label>FIGURE 8</label>
<caption><p>Relationships between acanthurid and scarid fish biomass (log10 g) and macrophyte loss after 24 h in <bold>(A)</bold> fore reef and <bold>(B)</bold> patch reef habitats. Macrophyte types are color coded and confidence intervals were applied using a linear model smoother.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-08-742907-g008.tif"/>
</fig>
</sec>
</sec>
<sec sec-type="discussion" id="S4">
<title>Discussion</title>
<p>Standardized assays of macrophyte and dried squid consumption over a 5-year period across a Belizean tropical seascape revealed that consumption rates differed among habitats and these differences were consistent through time (<xref ref-type="fig" rid="F2">Figures 2</xref>&#x2013;<xref ref-type="fig" rid="F4">4</xref>). Specifically, consumption was generally higher in structured coral reef and mangrove habitats, and lower in less structured seagrasses and sand flats. Video footage from 2017 indicated that a limited set of species was responsible for the observed consumption rates, and that the identities of the dominant consumers varied among habitats. Thus, it appears that a suite of common consumers may be responsible for maintaining a hierarchy of trophic processes across the coastal habitat mosaic in Belize, and that consumption across the seascape relies on this biodiversity (<xref ref-type="supplementary-material" rid="DS8">Supplementary Figure 3</xref>).</p>
<p>One explanation for the observed variation in consumption rates across habitats is structural complexity: three-dimensionally complex habitats like coral reefs and mangrove prop roots can provide refuge for numerous fishes and invertebrates that are responsible for consuming the types of bait we use here, while less complex structures like shorter seagrass canopies and sand flats do not provide such a variety of microhabitats for small fish to occupy (<xref ref-type="bibr" rid="B8">Dean and Connell, 1987</xref>; <xref ref-type="bibr" rid="B22">Hackradt et al., 2011</xref>). Although we did not directly measure habitat complexity in our study due to challenges in comparably measuring this quantity across the range of habitats sampled, we did observe the highest biomasses of most key consumer families&#x2014;those which previously have been linked with habitat heterogeneity (<xref ref-type="bibr" rid="B41">Mumby et al., 2004</xref>; <xref ref-type="bibr" rid="B45">Nagelkerken, 2007</xref>)&#x2014;on the fore reefs, patch reefs, and in mangroves (<xref ref-type="supplementary-material" rid="DS8">Supplementary Figure 5</xref>). The increased consumption of both macrophytes and squid we saw in these more complex habitats is consistent with previous studies (<xref ref-type="bibr" rid="B58">Valentine et al., 2007</xref>) and highlights the fact that the squid bait captures a complementary trophic group to herbivores&#x2014;likely benthic invertivores and mid-sized predators&#x2014;rather larger predators on them. Indeed, large predators are now scarce throughout the Caribbean (<xref ref-type="bibr" rid="B50">Paddack et al., 2009</xref>; <xref ref-type="bibr" rid="B42">Mumby et al., 2012</xref>), limiting the potential for interactions among consumers of both types of assays deployed in tandem, and some predators may only have interest in live prey.</p>
<p>The higher interannual variability in consumption in less structured sand and seagrass habitats (evidenced by their relatively high coefficients of variation) (<xref ref-type="fig" rid="F2">Figure 2</xref>) likely reflects the transient use of these habitats by fish, creating a &#x201C;hit-or-miss&#x201D; assessment of consumption, where foraging grounds are spatially vast but consumers spend little time in them, such that consumers may fail to encounter baits during their foray. Another possible explanation is that the fishes that consumed our baits are more visible to their own predators in these open areas, limiting their foraging and leading to lower consumption, which is more consistent with the overall lower rates of consumption observed in seagrasses and especially sand flats. The interannual variation in consumption in unstructured habitats was unexpected and suggests the importance of including unstructured habitats in cross-habitat comparisons of ecological processes.</p>
<p>The generally lower rates of consumption we found in less structured habitats were accompanied by different species consuming the baits in different habitats. Previous work suggested that a diverse fish assemblage becomes more important in controlling turf algae when moving from the local to regional scale, incorporating more heterogeneity in both the foundational species and also the fish community itself (<xref ref-type="bibr" rid="B32">Lefcheck et al., 2019b</xref>). Our work similarly highlights that macrophyte browsing and squid consumption are attributable to largely different species, illustrating that a diverse consumer assemblage more effectively drives multiple trophic processes across the larger coastal seascape (<xref ref-type="bibr" rid="B4">Brandl et al., 2019</xref>).</p>
<p>Variation in the dominant consumers across habitats could stem from a reduced exchange of adult fishes among nearby habitats, but not from an exchange of juveniles, which are well known to mature in seagrasses and mangroves before moving to coral reefs. This would explain why squid consumption was lowest in the sand flats that act as conduits, shuttling fishes between multiple habitats. It could also be a consequence of the habitat-specific foraging adaptations of the various fish species and their familiarity with the baits. For example, acanthurid and scarid fishes were the dominant herbivores we observed on both patch reefs and fore reefs (<xref ref-type="supplementary-material" rid="DS8">Supplementary Figure 3B</xref>), as is typical of Caribbean reefs (<xref ref-type="bibr" rid="B37">Lewis and Wainwright, 1985</xref>; <xref ref-type="bibr" rid="B5">Burkepile and Hay, 2010</xref>; <xref ref-type="bibr" rid="B32">Lefcheck et al., 2019b</xref>; <xref ref-type="bibr" rid="B9">Dell et al., 2020</xref>). However, weedpops deployed to patch reefs were also targeted by omnivorous angelfish (pomacanthids), and the benthic invertivore <italic>Halichoeres garnoti</italic>, which frequently bites at benthic algae to access its target arthropod and echinoderm prey (<xref ref-type="bibr" rid="B7">Clifton and Motta, 1998</xref>).</p>
<p>In contrast, squid baits presented a novel resource, isolating the effect of species identity irrespective of either prey or predator behavior. In this case, squid bait was consumed primarily by wrasses on fore reefs, by snappers in mangrove habitats, and by the widest variety of fish species on patch reefs, including two species of snapper (<xref ref-type="fig" rid="F7">Figure 7</xref>). The placement of patch reefs within the coastal seascape may be an explanation for this finding, as they are generally isolated from the continuous reefs and more proximate to other habitats like seagrasses and mangroves, which could lead to greater spillover of species from these other habitats (<xref ref-type="fig" rid="F1">Figure 1</xref> and <xref ref-type="supplementary-material" rid="DS8">Supplementary Figure 2</xref>). Seascape configuration, or the spatial orientation of habitats in relation to one another, is likely to play a large role in the exchange of species, the connectivity of ecosystems, and ultimately the functioning of coastal habitats and is worthy of further exploration with respect to trophic processes (<xref ref-type="bibr" rid="B41">Mumby et al., 2004</xref>; <xref ref-type="bibr" rid="B28">Jones et al., 2020</xref>).</p>
<p>Of particular note is our finding that fish biomass (from transect surveys) was generally uncorrelated with loss of either squid baits or macrophytes except in the case of the biomass of the subset of browsing herbivores on patch reefs. It is well known that fish biomass is a strong determinant of ecosystem processes in tropical marine ecosystems, including herbivory (e.g., <xref ref-type="bibr" rid="B32">Lefcheck et al., 2019b</xref>). That total fish biomass did not explain consumption in the current study could stem from a few causes. First, the biomass threshold of key consumers necessary to consume all assays within 24 h is easily met in the deployment area, leading to overall high rates of consumption, which is certainly true for squid and likely also the highly palatable <italic>Acanthophora</italic>. The resulting lack of variation when consumption is uniformly high or low prevents further evaluation of potential patterns. Second, patch reefs are smaller and more isolated than fore reefs. Consequently, they may attract more and varied browsers that are concentrated in a smaller area, one which is also less likely to offer alternative resources. Hence, small patch reefs are generally associated with seagrass-depleted sand halos generated by foragers temporarily leaving the reef (<xref ref-type="bibr" rid="B48">Ogden et al., 1973</xref>; <xref ref-type="bibr" rid="B40">Madin et al., 2011</xref>; <xref ref-type="bibr" rid="B10">DiFiore et al., 2019</xref>). Whether reef &#x201C;patchiness&#x201D; (size and proximity to other habitats) plays a role in herbivores&#x2019; abilities to control algal proliferation through consumption remains a question for future research. Finally, the surveys were not conducted exactly when the assays were deployed (to avoid diver artifacts), and the fish community observed on the transects may differ somewhat from those interacting with the experimental assays (<xref ref-type="fig" rid="F6">Figures 6</xref>, <xref ref-type="fig" rid="F7">7</xref> and <xref ref-type="supplementary-material" rid="DS8">Supplementary Figure 3</xref>).</p>
<p>We raise several final caveats with our study. Since videos were only filmed in 2017 and not over the entire range of habitats for both squidpops and weedpops, we can only draw firm conclusions about the identity of consumers at the times and places filmed. Additionally, much of the consumption observed in the videos may have been the result of patchy and opportunistic feeding, possibly creating the illusion of consistency in consumer identity. These questions could be answered by capturing video footage over multiple years and habitats to improve our understanding of the role of individual species in sustaining trophic processes across the coastal mosaic.</p>
<p>Overall, our 5-year study of macrophyte and squid bait consumption across a nearshore tropical seascape suggests that spatio-temporal patterns in consumption are primarily explained by habitat type, with the majority of herbivory occurring in structured reef habitats and carnivorous consumption occurring in reefs and mangroves. Notably, these relative differences persisted throughout the duration of the study, establishing a baseline to evaluate future change. Moreover, differences in consumer diversity and consumption patterns emerged between patch reefs and fore reefs, likely due to seascape characteristics including patchiness, proximity, and connectivity to other habitat types. Because a large proportion of the trophic interactions we measured occurred in structurally complex habitats, continued reef flattening and mangrove and seagrass loss and fragmentation may create cascading effects in Caribbean food webs, potentially shifting this baseline. Continued management of fish communities in Belize, particularly of the species known to be strong interactors with benthic macroalgae, is therefore key in maintaining trophic processes and mitigating the consequences of habitat change.</p>
</sec>
<sec sec-type="data-availability" id="S5">
<title>Data Availability Statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="supplementary-material" rid="DS1">Supplementary Material</xref>, further inquiries can be directed to the corresponding author/s.</p>
</sec>
<sec id="S6">
<title>Author Contributions</title>
<p>JED, VP, JL, and LH contributed to conception and design of the study. VP, JED, LH, RW, and SJ performed field research. CR analyzed video footage with guidance from JED and MO. JL, CR, and LH performed analysis and wrote the first draft of the manuscript. All authors contributed to manuscript revision, and read and approved the submitted version.</p>
</sec>
<sec sec-type="COI-statement" id="conf1">
<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 sec-type="disclaimer" id="S7">
<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>
</body>
<back>
<sec sec-type="funding-information" id="S8">
<title>Funding</title>
<p>This work was supported by the Caribbean Coral Reef Ecosystems program, the Smithsonian&#x2019;s Tennenbaum Marine Observatories Network, and the Smithsonian Environmental Research Center&#x2019;s internship program. JL was supported by the Michael E. Tennenbaum Secretarial Scholar gift to the Smithsonian Institution.</p>
</sec>
<ack>
<p>We thank the Carrie Bow Cay Field Station team for their assistance in the field: Andrew Altieri, Maggie Benson, David Branson, Justin Campbell, Kieran Cox, Zach Foltz, Michael Goodison, Maggie Johnson, Scott Ling, Alex Lowe, Emily Nixon, Laurie Penland, Janina Seemann, and Doug Schleiger. We also thank Claire Murphy for her assistance in initial video scoring. We thank the Belize Fisheries Department for their cooperation and issuing annual research permits for this work. This is contribution 89 from the Smithsonian&#x2019;s MarineGEO and Tennenbaum Marine Observatories Network and CCRE Program contribution 1055.</p>
</ack>
<sec id="S9" 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.2021.742907/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fmars.2021.742907/full#supplementary-material</ext-link></p>
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<supplementary-material xlink:href="Data_Sheet_2.csv" id="DS2" mimetype="text/csv" xmlns:xlink="http://www.w3.org/1999/xlink"/>
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