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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.2021.753484</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>Population Dynamics Reveal a Core Community of the Common Bottlenose Dolphin (<italic>Tursiops truncatus</italic>) in Open Waters of the South-Western Gulf of Mexico</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Bola&#x00F1;os-Jim&#x00E9;nez</surname> <given-names>Jaime</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/981389/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Morteo</surname> <given-names>Eduardo</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1391619/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Delf&#x00ED;n-Alfonso</surname> <given-names>Christian A.</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/986048/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Fruet</surname> <given-names>Pedro F.</given-names></name>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
<xref ref-type="aff" rid="aff5"><sup>5</sup></xref>
<xref ref-type="aff" rid="aff6"><sup>6</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/899160/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Secchi</surname> <given-names>Eduardo R.</given-names></name>
<xref ref-type="aff" rid="aff6"><sup>6</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/893452/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Bello-Pineda</surname> <given-names>Javier</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1164971/overview"/>
</contrib>
</contrib-group>
<aff id="aff1"><sup>1</sup><institution>Instituto de Ciencias Marinas y Pesquer&#x00ED;as (ICIMAP), Universidad Veracruzana</institution>, <addr-line>Veracruz</addr-line>, <country>Mexico</country></aff>
<aff id="aff2"><sup>2</sup><institution>Laboratorio de Mam&#x00ED;feros Marinos (LabMMar-IIB-ICIMAP), Universidad Veracruzana</institution>, <addr-line>Veracruz</addr-line>, <country>Mexico</country></aff>
<aff id="aff3"><sup>3</sup><institution>Instituto de Investigaciones Biol&#x00F3;gicas, Universidad Veracruzana</institution>, <addr-line>Xalapa</addr-line>, <country>Mexico</country></aff>
<aff id="aff4"><sup>4</sup><institution>Museu Oceanografico Prof. Eli&#x00E9;zer de C. Rios, Universidade Federal do Rio Grande/FURG</institution>, <addr-line>Rio Grande</addr-line>, <country>Brazil</country></aff>
<aff id="aff5"><sup>5</sup><institution>Kaosa</institution>, <addr-line>Rio Grande</addr-line>, <country>Brazil</country></aff>
<aff id="aff6"><sup>6</sup><institution>Laborat&#x00F3;rio de Ecologia e Conserva&#x00E7;&#x00E3;o da Megafauna Marinha (ECOMEGA), Instituto de Oceanografia, Universidade Federal do Rio Grande/FURG</institution>, <addr-line>Rio Grande</addr-line>, <country>Brazil</country></aff>
<author-notes>
<fn fn-type="edited-by"><p>Edited by: Rob Harcourt, Macquarie University, Australia</p></fn>
<fn fn-type="edited-by"><p>Reviewed by: Martina Duras, University of Zagreb, Croatia; Aimee R. Lang, Southwest Fisheries Science Center (NOAA), United States</p></fn>
<corresp id="c001">&#x002A;Correspondence: Eduardo Morteo, <email>eduardo.morteo@gmail.com</email></corresp>
<fn fn-type="other" id="fn004"><p>This article was submitted to Marine Megafauna, a section of the journal Frontiers in Marine Science</p></fn>
</author-notes>
<pub-date pub-type="epub">
<day>29</day>
<month>11</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="collection">
<year>2021</year>
</pub-date>
<volume>8</volume>
<elocation-id>753484</elocation-id>
<history>
<date date-type="received">
<day>04</day>
<month>08</month>
<year>2021</year>
</date>
<date date-type="accepted">
<day>11</day>
<month>10</month>
<year>2021</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2021 Bola&#x00F1;os-Jim&#x00E9;nez, Morteo, Delf&#x00ED;n-Alfonso, Fruet, Secchi and Bello-Pineda.</copyright-statement>
<copyright-year>2021</copyright-year>
<copyright-holder>Bola&#x00F1;os-Jim&#x00E9;nez, Morteo, Delf&#x00ED;n-Alfonso, Fruet, Secchi and Bello-Pineda</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>The presence of transient and temporary individuals in capture-mark-recapture studies may violate the assumption on equal catchability, and thus yield biased estimates. We investigated the effects of residency patterns on population parameters of bottlenose dolphins inhabiting the coastal waters off the Alvarado Lagoon System (ALS), Veracruz, Mexico. We hypothesized that this population is open but there exists a &#x201C;core community&#x201D; that behaves as a closed population. Between 2006 and 2010, we conducted 75 photo-identification surveys and recorded 263 dolphin group encounters, in which 231 dolphins were identified. Individuals present during only one season, classified as transients (<italic>n</italic> = 85), were excluded from the study, and a standardized residency index (IH<sub>4</sub>) was computed for each dolphin that remained in the sample (<italic>n</italic> = 146). We used the K-means clustering method to split the sample into groups based on individual (seasonal, annual) IH<sub>4</sub> values. These clusters were named as regular residents (RR, <italic>n</italic> = 55), occasional residents (OR, <italic>n</italic> = 45), and occasional visitors (OV, <italic>n</italic> = 46). The cumulative frequency of newly identified individuals displayed an asymptotic trend for the whole sample and all clusters, indicating that most of the individuals present in the study area during the study period were identified. The assumption of demographic closure was tested to define the core community, and was rejected for the whole sample and the OV cluster (<italic>p</italic> &#x003C; 0.001 in both cases), indicating that the population is open. The closure assumption was not rejected for RR and OR clusters (&#x03C7;<sup>2</sup> = 6.88, DF = 13, <italic>p</italic> = 0.91, and &#x03C7;<sup>2</sup> = 17.8, DF = 16, <italic>p</italic> = 0.33, respectively), indicating that these clusters were demographically closed over the 5-year period. Thus, we defined this aggregation of individuals as the &#x201C;core community&#x201D;. The closed population model M<sub><italic>th</italic></sub> indicated that the total abundance of this core community was 123 individuals (95% CI: 114&#x2013;133). Our results provide quantitative evidence of the existence of a core community in open waters of the Gulf of Mexico, and points toward residency pattern as a main driver of population dynamics. These results highlight the importance of considering residency patterns when dealing with heterogeneity in the sample of a highly mobile species.</p>
</abstract>
<kwd-group>
<kwd>core community</kwd>
<kwd>residency pattern</kwd>
<kwd>transients</kwd>
<kwd>Alvarado Lagoon System</kwd>
<kwd>closed population</kwd>
<kwd>open population</kwd>
<kwd>population structure</kwd>
</kwd-group>
<counts>
<fig-count count="5"/>
<table-count count="3"/>
<equation-count count="6"/>
<ref-count count="92"/>
<page-count count="14"/>
<word-count count="12349"/>
</counts>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="S1">
<title>Introduction</title>
<p>In most wildlife populations, sex and age have profound effects on the chances of an individual dying, or producing offspring (<xref ref-type="bibr" rid="B45">Neal, 2004</xref>), thus these factors are routinely considered when studying population structure and dynamics (<xref ref-type="bibr" rid="B46">Ojasti and Dallmeier, 2000</xref>). Other factors with the potential to influence population structure are site fidelity (SF) and philopatry (<xref ref-type="bibr" rid="B6">Bose et al., 2017</xref>). SF has been defined as the &#x201C;tendency to return to a previously occupied location&#x201D; (<xref ref-type="bibr" rid="B30">Greenwood, 1980</xref>; <xref ref-type="bibr" rid="B66">Switzer, 1993</xref>), whereas philopatry is the tendency to stay in a familiar environment, mainly related to the natal habitat (<xref ref-type="bibr" rid="B4">Begon et al., 1995</xref>). Several environmental factors have been suggested to influence species&#x2019; site fidelity and/or philopatry, such as habitat stability, predictability of reproductive failure, variability in territory quality within a habitat, and population pressure; individual characteristics may also include an individual&#x2019;s previous reproductive success, age, and knowledge of other sites (<xref ref-type="bibr" rid="B66">Switzer, 1993</xref>).</p>
<p>In cetacean studies, SF and residency patterns are evaluated using information on the number of recaptures, the duration of stay, and/or the average recurrence of individuals (see <xref ref-type="bibr" rid="B2">Ballance, 1990</xref> and <xref ref-type="bibr" rid="B43">Morteo et al., 2012b</xref>). In this regard, <xref ref-type="bibr" rid="B2">Ballance (1990)</xref>, stated that &#x201C;a high number of resightings, a long period time between the first sighting and the last resighting, and a short time interval between adjacent sightings describes an animal with a high degree of residence.&#x201D; Thus, individual residency patterns can be considered as a manifestation of SF and philopatry.</p>
<p>For cetacean social species such as delphinids, other factors that are thought to shape population and social structure are kinship and reproductive condition (<xref ref-type="bibr" rid="B5">Bigg, 1982</xref>; <xref ref-type="bibr" rid="B84">Wells et al., 1987</xref>). Sex and age also influence the way that delphinids use their habitats. In general, females try to ensure the survival of their offspring, thus their distribution is often closely related to the quality and/or accessibility of food resources and habitats that have a lower risk of predation; conversely, the distribution of males is often related more to female distribution than to the availability of food (<xref ref-type="bibr" rid="B29">Gowans et al., 2007</xref>). Delphinids routinely travel throughout the day and can be exposed to large areas, their entire home range, or even multiple habitats on a daily basis (<xref ref-type="bibr" rid="B29">Gowans et al., 2007</xref>). Consequently, individual home ranges -that may depend on the age and sex of the individual- result in structured societies that are usually stable over time (<xref ref-type="bibr" rid="B83">Wells et al., 1980</xref>, <xref ref-type="bibr" rid="B84">1987</xref>), in which females tend to be more resident to specific areas than males (<xref ref-type="bibr" rid="B29">Gowans et al., 2007</xref>).</p>
<p>Since <xref ref-type="bibr" rid="B2">Ballance&#x2019;s (1990)</xref> work, several methods have been used to evaluate cetacean residence and this lack of standardization hinders proper comparison among SF studies (<xref ref-type="bibr" rid="B68">Tschopp et al., 2018</xref>, see below). <xref ref-type="bibr" rid="B68">Tschopp et al. (2018)</xref> found that, in general, the methods to quantify site fidelity include three approaches: (1) proportions (a ratio between the number of sightings or resightings, and a measure of effort), (2) categories (e.g., high, moderate, low), and (3) models (maximum likelihood methods). Recently, <xref ref-type="bibr" rid="B68">Tschopp et al. (2018)</xref> developed and compared the performance of a series of standardized indexes -based on Ballance&#x2019;s parameters- to be able to quantify the site fidelity degree and ensure accurate comparability across related investigations. Regarding delphinids, several authors (e.g., <xref ref-type="bibr" rid="B29">Gowans et al., 2007</xref>; <xref ref-type="bibr" rid="B82">Wells and Scott, 2018</xref>) have predicted that in offshore environments, where food availability is patchy and unpredictable and predation risk might be high, dolphins range more widely and form larger groups to forage on sparsely distributed prey schools and to reduce predation. In contrast, in complex inshore environments with predictable resource availability and potentially lower predation, dolphins are predicted to remain resident in relatively small areas and to form smaller groups to avoid feeding competition. This seems to be the case for the bottlenose dolphin (<italic>Tursiops truncatus</italic>) populations inhabiting semi-enclosed bays or sounds, or inshore habitats in the Gulf of Mexico (GoM). This species has been widely studied in the northern GoM on the basis of photo-ID methods and capture-mark-recapture (CMR) models (see review in <xref ref-type="bibr" rid="B77">Vollmer and Rosel, 2013</xref>). In the northern GoM, where long-term, year-round residents are best documented, there is also evidence for seasonal changes in abundance; most often these are thought to result from movements of seasonal, short-term residents and/or transients (very short-term visitors) to the area. It is generally thought that these shorter-term residents and visitors come from the adjacent coastal population, although comprehensive and directed studies to address this question have yet to be performed (<xref ref-type="bibr" rid="B77">Vollmer and Rosel, 2013</xref>).</p>
<p>The bottlenose dolphin has been widely documented in some localities in the southern GoM (<xref ref-type="bibr" rid="B48">Ortega Ortiz, 2002</xref>; <xref ref-type="bibr" rid="B49">Ortega Ortiz et al., 2004</xref>; <xref ref-type="bibr" rid="B55">Ram&#x00ED;rez-Le&#x00F3;n et al., 2020</xref>), including waters off the Tamiahua Lagoon System (<xref ref-type="bibr" rid="B27">Galindo et al., 2009</xref>; <xref ref-type="bibr" rid="B36">Mart&#x00ED;nez-Serrano et al., 2011</xref>; <xref ref-type="bibr" rid="B73">Vald&#x00E9;s-Arellanes et al., 2011</xref>); Nautla (<xref ref-type="bibr" rid="B40">Morteo et al., 2019</xref>); and the Alvarado Lagoon System (ALS) in Veracruz state (<xref ref-type="bibr" rid="B39">Morteo, 2011</xref>; <xref ref-type="bibr" rid="B43">Morteo et al., 2012b</xref>, <xref ref-type="bibr" rid="B41">2014</xref>, <xref ref-type="bibr" rid="B42">2017</xref>, <xref ref-type="bibr" rid="B40">2019</xref>; <xref ref-type="bibr" rid="B38">Morales-Rinc&#x00F3;n et al., 2019</xref>), and some coastal areas in the states of Tabasco, Campeche and Yucat&#x00E1;n (<xref ref-type="bibr" rid="B20">Delgado-Estrella, 2015</xref>).</p>
<p>Off the ALS, <xref ref-type="bibr" rid="B41">Morteo et al. (2014)</xref> found that this population is sexually segregated, where females were more resident, had higher site fidelity, and had weaker associations with a higher number of partners than males. On the other side, males were assumed to be primarily responsible for gene flow among adjacent locations (<xref ref-type="bibr" rid="B41">Morteo et al., 2014</xref>).</p>
<p>Capture-mark-recapture (CMR) studies have been used as a general sampling and analysis method to assess population status and trends in many biological populations (<xref ref-type="bibr" rid="B85">White and Burnham, 1999</xref>). The photographic documentation of long-lasting natural marks on the dorsal fin or flukes (i.e., photo-identification, photo-ID) has been used since the early 1970&#x2019;s to study aspects such as group structure, site fidelity, movement patterns, and abundance using CMR models in cetaceans (<xref ref-type="bibr" rid="B91">W&#x00FC;rsig and Jefferson, 1990</xref>). Models usually require a set of restrictive assumptions about the properties of the population under study, such as individual homogeneity in capture and survival probabilities, among others (<xref ref-type="bibr" rid="B34">Krebs, 1972</xref>). Failure to comply with these assumptions implies that the model does not adequately fit the data, and thus may introduce severe bias in parameter estimates (<xref ref-type="bibr" rid="B34">Krebs, 1972</xref>). In structured delphinid populations, heterogeneity in capture or survival probabilities is often produced by age, sex, or size of the individuals (<xref ref-type="bibr" rid="B88">Williams et al., 1993</xref>), as well as inconspicuous marks, low photographic quality, and social bonds (<xref ref-type="bibr" rid="B44">Morteo et al., 2012a</xref>).</p>
<p>In recent studies, researchers started to include site fidelity and residency pattern as factors to account for heterogeneity in the data when studying demographics or population ecology of several cetacean species, including the southern Australian bottlenose dolphin (<italic>Tursiops</italic> cf <italic>australis</italic>, <xref ref-type="bibr" rid="B92">Zanardo et al., 2016</xref>; <xref ref-type="bibr" rid="B51">Passadore et al., 2017</xref>), the Australian humpback dolphin (<italic>Sousa sahulensis</italic>, <xref ref-type="bibr" rid="B32">Hunt et al., 2017</xref>), the Risso&#x2019;s dolphin (<italic>Grampus griseus</italic>, <xref ref-type="bibr" rid="B10">Carlucci et al., 2020</xref>) and the fin whale (<italic>Balaenoptera physalus</italic>, <xref ref-type="bibr" rid="B58">Schleimer et al., 2019</xref>). These researchers calculated sighting rates and site fidelity indexes for each individual and then used agglomerative clustering methods (<xref ref-type="bibr" rid="B35">Legendre and Legendre, 1998</xref>) to identify clusters of individuals with similar degrees of site fidelity, before running CMR analysis. In particular, <xref ref-type="bibr" rid="B31">Haughey et al. (2020)</xref> used for the first time <xref ref-type="bibr" rid="B68">Tschopp et al. (2018)</xref> standardized indexes to stratify the sample and estimate population parameters of Indo-Pacific bottlenose dolphin (<italic>T. aduncus</italic>) off western Australia by residency pattern.</p>
<p>In this paper, we used the recently developed standardized site fidelity index (SSFI) IH<sub>4</sub> (<xref ref-type="bibr" rid="B68">Tschopp et al., 2018</xref>) to study potential differences in population parameters between resident and non-resident common bottlenose dolphins (<italic>Tursiops truncatus</italic>) that use the open, coastal waters off Alvarado Lagoon System, south-western Gulf of Mexico. On the basis of our knowledge of the study area, we hypothesized that bottlenose dolphins using the marine coastal waters adjacent to the ALS are part of an open population within which exists a core community (<italic>sensu</italic> <xref ref-type="bibr" rid="B84">Wells et al., 1987</xref>), that behaves as a closed population, in the sense that it is composed of all the groups and individuals &#x201C;<italic>&#x2026; that share large portions of their ranges and interact with each other to a much greater extent than with members of similar units in adjacent waters, but genetics exchange occurrs between communities</italic>.&#x201D;</p>
</sec>
<sec id="S2" sec-type="materials|methods">
<title>Materials and Methods</title>
<p>For this study, we used the photo-ID catalog and database from the Marine Mammal Lab at Universidad Veracruzana (LabMMar-IIB-ICIMAP). This database includes the sighting histories of 231 bottlenose dolphins from 75 survey trips conducted between May 2006 and August 2010 (<xref ref-type="bibr" rid="B39">Morteo, 2011</xref>; <xref ref-type="bibr" rid="B43">Morteo et al., 2012b</xref>, <xref ref-type="bibr" rid="B41">2014</xref>, <xref ref-type="bibr" rid="B42">2017</xref>). Previously, <xref ref-type="bibr" rid="B41">Morteo et al. (2014</xref>, <xref ref-type="bibr" rid="B42">2017)</xref> used a partial subset of these databases, covering the period May 2006&#x2013;April 2008, to explore the abundance and social ecology of this dolphin population under open population modeling by considering the population as a homogeneous unit, and without considering temporal variations or population structure in the parameters. Detailed definitions of methodological terms are presented in <xref ref-type="supplementary-material" rid="FS1">Supplementary Material 1</xref>.</p>
<sec id="S2.SS1">
<title>Study Area</title>
<p>The coastal waters of Alvarado, Veracruz, are shallow (less than 20 m), with an average temperature of 27&#x00B0;C (<xref ref-type="bibr" rid="B39">Morteo, 2011</xref>), and are strongly influenced by the discharge of the Alvarado Lagoon System (ALS, <xref ref-type="bibr" rid="B19">de la Lanza Espino and Lozano Montes, 1999</xref>; <xref ref-type="bibr" rid="B17">Cruz-Escalona et al., 2007</xref>). The ALS is a coastal wetland located in the center-south of the State of Veracruz, southwestern Gulf of Mexico, formed by the confluence of the Acula, Blanco, Lim&#x00F3;n, and -mainly- the Papaloapan rivers (<xref ref-type="fig" rid="F1">Figure 1</xref>). The ALS has an elongated shape, parallel to the coastline, with an approximate length of 26 km, with a maximum width of 5 km and an average depth of 2.5 m, for a total area of about 80 km<sup>2</sup> (<xref ref-type="bibr" rid="B19">de la Lanza Espino and Lozano Montes, 1999</xref>). The weather is tropical, with three marked climatic seasons; following <xref ref-type="bibr" rid="B39">Morteo (2011)</xref> and <xref ref-type="bibr" rid="B41">Morteo et al. (2014)</xref>, we defined these seasons as: Dry, with a significant reduction in average precipitation, from March to June; Rainy, in which runoff causes high organic matter and nutrient input into coastal waters, from July to October, and, finally, the &#x201C;Nortes&#x201D; or &#x201C;Northern Winds,&#x201D; with strong winds associated to cold fronts which may last several days (<xref ref-type="bibr" rid="B19">de la Lanza Espino and Lozano Montes, 1999</xref>; <xref ref-type="bibr" rid="B17">Cruz-Escalona et al., 2007</xref>).</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption><p>Location of the study area. ALS = Alvarado Lagoon System, Tam = Tamaulipas, Ver = Veracruz, Tab = Tabasco, Cam = Campeche, Yuc = Yucat n, QRoo = Quintana Roo. Nearby locations with studies on bottlenose dolphins are also shown (e.g., Tamiahua Lagoon, Nautla, VRS = Veracrus Reef System National Park). Zigzag lines indicate line transect surveys.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-08-753484-g001.tif"/>
</fig>
</sec>
<sec id="S2.SS2">
<title>Survey Protocol</title>
<p>The survey protocol represents an extension of the procedures described in <xref ref-type="bibr" rid="B39">Morteo (2011)</xref>, and <xref ref-type="bibr" rid="B41">Morteo et al. (2014</xref>, <xref ref-type="bibr" rid="B42">2017)</xref>. All sampling surveys were conducted following a zigzag pattern that started at the mouth of the ALS and extended 4 km offshore, and 9 km on each side of the estuary mouth (<xref ref-type="bibr" rid="B39">Morteo, 2011</xref>; <xref ref-type="bibr" rid="B41">Morteo et al., 2014</xref>, <xref ref-type="bibr" rid="B42">2017</xref>, see <xref ref-type="fig" rid="F1">Figure 1</xref>). Typically, all surveys covered the whole study area, and no surveys were conducted inside the lagoon system, based on previous data showing virtually no presence of dolphins (Morteo, pers. obs.).</p>
</sec>
<sec id="S2.SS3">
<title>Dolphin Photo-ID</title>
<p>Standard photo-ID techniques were used to individually identify and catalog adult dolphins based on long-lasting marks in their dorsal fins (<xref ref-type="bibr" rid="B91">W&#x00FC;rsig and Jefferson, 1990</xref>; <xref ref-type="bibr" rid="B41">Morteo et al., 2014</xref>, <xref ref-type="bibr" rid="B42">2017</xref>; <xref ref-type="bibr" rid="B72">Urian et al., 2015</xref>). All photographs were graded for quality (PQ) and dolphin distinctiveness (D). Following <xref ref-type="bibr" rid="B71">Urian et al. (2013</xref>, <xref ref-type="bibr" rid="B72">2015)</xref>, only excellent (PQ1) and good quality (PQ2) pictures of very (D1) and average (D2) distinctive dolphins were used for analysis, to minimize misidentification. We then plotted discovery curves for new identified individuals across time (<xref ref-type="bibr" rid="B24">Fisher et al., 1943</xref>; <xref ref-type="bibr" rid="B14">Colwell et al., 2004</xref>).</p>
</sec>
<sec id="S2.SS4">
<title>Mark Rate</title>
<p>A mark rate (&#x03B8;), representing the proportion of marked animals in the groups, was calculated for each sighting to adjust abundance estimates by accounting for the unmarked fraction of the population, and thus produce estimates of seasonal abundances for the full population (<xref ref-type="bibr" rid="B89">Wilson et al., 1999</xref>; <xref ref-type="bibr" rid="B86">Wickman et al., 2020</xref>). Following <xref ref-type="bibr" rid="B41">Morteo et al. (2014</xref>, <xref ref-type="bibr" rid="B42">2017)</xref>, we used a combination of field and analytical approaches to accurately estimate group size and &#x03B8; for each encounter. In the field, minimum, maximum, and best group size estimates were recorded, and the best estimate was used to calculate a mark rate for each sighting. By using the full dataset [<italic>N</italic> = 263 groups], we found that the average difference between the minimum and maximum group size estimates was 0.92 dolphins (&#x00B1; 3.70 SD) and this difference increased with larger groups. As the average group size for the full study period was fairly small (9.0 &#x00B1; 11.2 SD) and the standard deviation of the difference between extreme field estimates was less than one individual, we considered that our group size estimates are highly accurate, and thus representative of the total number of animals in the group. Additionally, we used the empirical criteria developed independently by <xref ref-type="bibr" rid="B90">W&#x00FC;rsig (1978)</xref> and <xref ref-type="bibr" rid="B2">Ballance (1990)</xref> to double-check dolphin counts on the field; this approach states that the probability of having photographed all the dolphins in a group is higher than 95% if all marked individuals in the sighting were correctly photographed at least four times (<xref ref-type="bibr" rid="B2">Ballance, 1990</xref>; <xref ref-type="bibr" rid="B91">W&#x00FC;rsig and Jefferson, 1990</xref>).</p>
</sec>
<sec id="S2.SS5">
<title>Residency Pattern Assessment</title>
<p><xref ref-type="bibr" rid="B43">Morteo et al. (2012b)</xref> reviewed the parameters proposed by <xref ref-type="bibr" rid="B2">Ballance (1990)</xref>, suggested modifications, and established &#x201C;Occurrence,&#x201D; &#x201C;Permanence&#x201D; and &#x201C;Periodicity,&#x201D; as their names. The occurrence was redefined as the number of times the animal was recaptured (that is, eliminating the first sighting from the calculation); the permanence was defined as &#x201C;the time over which an individual was recorded, determined by the difference between its first and last sighting,&#x201D; whereas the periodicity was redefined as &#x201C;the recurrence of the individual, determined by the inverse of the average time (in days) between consecutive recaptures.&#x201D; <xref ref-type="bibr" rid="B68">Tschopp et al. (2018)</xref> used these definitions to evaluate the performance of their standardized indexes. For the purpose of this study, the periodicity was calculated by season and year.</p>
<p>We used the IH<sub>4</sub> index of <xref ref-type="bibr" rid="B68">Tschopp et al. (2018)</xref> to split the sample into clusters according to individual&#x2019;s site fidelity. We chose this index because it consistently had the best performance in all of the scenarios, and the authors proposed it as a standardized measure of site fidelity (SSFI). The IH<sub>4</sub> is based on the harmonic mean of parameters permanence (IT) and periodicity (It), as expressed in equation 1:</p>
<disp-formula id="S2.E1"><label>(1)</label><mml:math id="M1" display="block"><mml:mrow><mml:mrow><mml:mi>I</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mpadded width="+3.3pt"><mml:msub><mml:mi>H</mml:mi><mml:mn>4</mml:mn></mml:msub></mml:mpadded></mml:mrow><mml:mo rspace="5.8pt">=</mml:mo><mml:mfrac><mml:mn>2</mml:mn><mml:mrow><mml:mfrac><mml:mn>1</mml:mn><mml:mrow><mml:mi>I</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mi>T</mml:mi></mml:mrow></mml:mfrac><mml:mo rspace="5.8pt">+</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mrow><mml:mi>I</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mi>t</mml:mi></mml:mrow></mml:mfrac></mml:mrow></mml:mfrac></mml:mrow></mml:math></disp-formula>
<p>Where: IT = Permanence</p>
<p>It = Periodicity</p>
<p>For each dolphin, we calculated the IH<sub>4</sub> per season and year, to account for their presence in the study area across the studied period under different temporal stratifications. We then constructed a matrix (IH<sub>4</sub>-matrix) in which each line corresponded to an individual dolphin and columns included the two IH<sub>4</sub> measures. We used the IH<sub>4&#x2013;</sub>matrix to split the sample into groups by using the K-means clustering method (<xref ref-type="bibr" rid="B35">Legendre and Legendre, 1998</xref>). With the K-means method, a set of n objects (= dolphins) in a p-dimensional space (= IH<sub>4</sub>-matrix) can be partitioned into K groups -or clusters- such that the objects within each cluster are more similar to one another than to objects in other clusters; the number of groups (K) is often determined by the user based on expert knowledge (<xref ref-type="bibr" rid="B35">Legendre and Legendre, 1998</xref>), but there exist some numeric criteria to select the best grouping strategy (see below). The function cascade KM of the &#x201C;vegan&#x201D; package (<xref ref-type="bibr" rid="B47">Oksanen et al., 2019</xref>) of the R environment (<xref ref-type="bibr" rid="B53">R Core Team, 2020</xref>) was used to determine the groupings with the K-means method. The best-fitting K was selected by means of the Calinski-Harabasz index (ICH, <xref ref-type="bibr" rid="B9">Calinski and Harabasz, 1974</xref>; <xref ref-type="bibr" rid="B35">Legendre and Legendre, 1998</xref>) available in the <italic>vegan</italic> package. According to the ICH, the grouping with the highest index value corresponds to the best grouping given the data (<xref ref-type="bibr" rid="B9">Calinski and Harabasz, 1974</xref>; <xref ref-type="bibr" rid="B47">Oksanen et al., 2019</xref>). As we were interested in population analysis by the residency pattern, we excluded the transient individuals from the sample. We defined as transients those individuals that were present in the study area only during one season, independently of the number of recaptures during that season. Through the cluster analysis, we then compared the performance of 2 and 3 clusters (K), respectively.</p>
</sec>
<sec id="S2.SS6">
<title>Population Parameters</title>
<p>Estimates were made under standard CMR models in the program MARK (<xref ref-type="bibr" rid="B85">White and Burnham, 1999</xref>). Parameters can be established as time-variant or time-invariant, as well as variant or invariant among groups. Following <xref ref-type="bibr" rid="B85">White and Burnham (1999)</xref>, the notation (.) was used to indicate time-invariant parameters and (t) to indicate those time-variant parameters. The notation (g) was used to indicate time-invariant parameters, different for each residency group, and (g&#x002A;t) to indicate parameters different for each group and time-variant. The model(s) that best fitted the data were selected by using the lowest value of the Akaike Information Criterion, corrected for small samples (AICc, <xref ref-type="bibr" rid="B1">Akaike, 1973</xref>; <xref ref-type="bibr" rid="B85">White and Burnham, 1999</xref>). Before analyses, sighting histories were collapsed by season and stratified by residency pattern. We used two steps to estimate population parameters. In the first step, we used the POPAN superpopulation approach of the Jolly-Seber model (<xref ref-type="bibr" rid="B59">Schwarz and Arnason, 1996</xref>; <xref ref-type="bibr" rid="B85">White and Burnham, 1999</xref>) to determine survival, recruitment, and seasonal abundance of the dolphins according to their residency pattern under the assumption of open population. In the second step, we used closed capture-recapture methods available in the CAPTURE routine of the MARK program to determine the seasonal abundances of the core community only. Finally, total abundances were estimated as:</p>
<disp-formula id="S2.E2"><label>(2)</label><mml:math id="M2" display="block"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi>T</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mfrac><mml:msub><mml:mi>N</mml:mi><mml:mi>m</mml:mi></mml:msub><mml:mi>&#x03B8;</mml:mi></mml:mfrac></mml:mrow></mml:math></disp-formula>
<p>where N<sub><italic>total</italic></sub> = total abundance, N<sub><italic>m</italic></sub> = abundance of marked individuals, and &#x03B8; = mark rate. The variance was calculated by using the Delta method (<xref ref-type="bibr" rid="B89">Wilson et al., 1999</xref>) as:</p>
<disp-formula id="S2.E3"><label>(3)</label><mml:math id="M3" display="block"><mml:mrow><mml:mrow><mml:mi>V</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mi>a</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mi>r</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:msub><mml:mi>N</mml:mi><mml:mi>T</mml:mi></mml:msub><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>=</mml:mo><mml:mrow><mml:msubsup><mml:mi>N</mml:mi><mml:mi>T</mml:mi><mml:mn>2</mml:mn></mml:msubsup><mml:mo>&#x2062;</mml:mo><mml:mrow><mml:mo>[</mml:mo><mml:mrow><mml:mfrac><mml:mrow><mml:mi>v</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mi>a</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mi>r</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:msub><mml:mi>N</mml:mi><mml:mi>m</mml:mi></mml:msub><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:msubsup><mml:mi>N</mml:mi><mml:mi>m</mml:mi><mml:mn>2</mml:mn></mml:msubsup></mml:mfrac><mml:mo>+</mml:mo><mml:mfrac><mml:mrow><mml:mn>1</mml:mn><mml:mo>-</mml:mo><mml:mi mathvariant="normal">&#x03B8;</mml:mi></mml:mrow><mml:mrow><mml:mi>n</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mi mathvariant="normal">&#x03B8;</mml:mi></mml:mrow></mml:mfrac></mml:mrow><mml:mo>]</mml:mo></mml:mrow></mml:mrow></mml:mrow></mml:math></disp-formula>
<p>where n is the total number of individuals on which &#x03B8; was estimated. The standard error was calculated as:</p>
<disp-formula id="S2.E4"><label>(4)</label><mml:math id="M4" display="block"><mml:mrow><mml:mrow><mml:mi>S</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mi>E</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:msub><mml:mi>N</mml:mi><mml:mi>T</mml:mi></mml:msub><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>=</mml:mo><mml:msqrt><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>V</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mi>a</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mi>r</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:msub><mml:mi>N</mml:mi><mml:mi>T</mml:mi></mml:msub><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:msqrt></mml:mrow></mml:math></disp-formula>
<p>and then, log-normal 95 % confidence intervals (<xref ref-type="bibr" rid="B7">Burnham et al., 1987</xref>; <xref ref-type="bibr" rid="B67">Tezanos-Pinto et al., 2013</xref>) were calculated as:</p>
<disp-formula id="S2.Ex1"><mml:math id="M5" display="block"><mml:mrow><mml:mpadded width="+3.3pt"><mml:msub><mml:mi>N</mml:mi><mml:mrow><mml:mi>l</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mi>o</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mi>w</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mi>e</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mi>r</mml:mi></mml:mrow></mml:msub></mml:mpadded><mml:mo rspace="5.8pt">=</mml:mo><mml:mrow><mml:mpadded width="+3.3pt"><mml:mfrac><mml:msub><mml:mi>N</mml:mi><mml:mi>T</mml:mi></mml:msub><mml:mi>C</mml:mi></mml:mfrac></mml:mpadded><mml:mo>&#x2062;</mml:mo><mml:mi>a</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mi>n</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mpadded width="+3.3pt"><mml:mi>d</mml:mi></mml:mpadded><mml:mo>&#x2062;</mml:mo><mml:mpadded width="+3.3pt"><mml:msub><mml:mi>N</mml:mi><mml:mrow><mml:mi>u</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mi>p</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mi>p</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mi>e</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mi>r</mml:mi></mml:mrow></mml:msub></mml:mpadded></mml:mrow><mml:mo rspace="5.8pt">=</mml:mo><mml:mrow><mml:mpadded width="+3.3pt"><mml:msub><mml:mi>N</mml:mi><mml:mi>T</mml:mi></mml:msub></mml:mpadded><mml:mo rspace="5.8pt">&#x00D7;</mml:mo><mml:mi>C</mml:mi></mml:mrow></mml:mrow></mml:math></disp-formula>
<p>where N<sub><italic>lower</italic></sub> and N<sub><italic>upper</italic></sub> are the lower and upper bound, respectively, of the confidence interval, and</p>
<disp-formula id="S2.E5"><label>(5)</label><mml:math id="M6" display="block"><mml:mrow><mml:mpadded width="+3.3pt"><mml:mi>C</mml:mi></mml:mpadded><mml:mo rspace="5.8pt">=</mml:mo><mml:mrow><mml:msub><mml:mi>z</mml:mi><mml:mn>0.025</mml:mn></mml:msub><mml:mo>&#x00D7;</mml:mo><mml:msqrt><mml:mrow><mml:mi>l</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mi>o</mml:mi><mml:mo>&#x2062;</mml:mo><mml:msub><mml:mi>g</mml:mi><mml:mi>e</mml:mi></mml:msub><mml:mo>&#x2062;</mml:mo><mml:mrow><mml:mo>[</mml:mo><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:msup><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>C</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mi>V</mml:mi><mml:mo>&#x2062;</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:msub><mml:mi>N</mml:mi><mml:mi>T</mml:mi></mml:msub><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mn>2</mml:mn></mml:msup></mml:mrow><mml:mo>]</mml:mo></mml:mrow></mml:mrow></mml:msqrt></mml:mrow></mml:mrow></mml:math></disp-formula>
<p>where z<sub>0.025</sub> is the normal deviate (1.96), and CV is the coefficient of variation.</p>
</sec>
<sec id="S2.SS7">
<title>Assumption Compliance and Parameter Estimations</title>
<p>Valid inference in CMR studies requires compliance with several assumptions (<xref ref-type="bibr" rid="B52">Pollock et al., 1990</xref>; <xref ref-type="bibr" rid="B85">White and Burnham, 1999</xref>). The U-CARE software (version 2.3.2, <xref ref-type="bibr" rid="B12">Choquet et al., 2009</xref>, <xref ref-type="bibr" rid="B13">2005</xref>) was used to assess the goodness of fit of the model(s) to the data.</p>
<p>We used the POPAN parameterization of the Jolly-Seber model (<xref ref-type="bibr" rid="B59">Schwarz and Arnason, 1996</xref>) to get estimates for each group of apparent survival (Phi, hereafter survival), catchability (p), and probability of entrance of individuals from the superpopulation (hereafter recruitment) to the study area. Survival is termed &#x201C;apparent&#x201D; as the algorithm cannot discriminate between mortality and permanent emigration (<xref ref-type="bibr" rid="B85">White and Burnham, 1999</xref>). We used the Closed Population approach (<xref ref-type="bibr" rid="B50">Otis et al., 1978</xref>; <xref ref-type="bibr" rid="B11">Chao et al., 1992</xref>; <xref ref-type="bibr" rid="B64">Stanley and Burnham, 1999</xref>) to get estimates of the population size for the more resident fraction of the population. The closure assumption was confirmed with the closure test by <xref ref-type="bibr" rid="B64">Stanley and Burnham (1999)</xref>, as provided by the Close Test software (<xref ref-type="bibr" rid="B64">Stanley and Burnham, 1999</xref>: <xref ref-type="bibr" rid="B65">Stanley and Richards, 2005</xref>). We applied these tests to the whole sample (<italic>n</italic> = 231 individuals), as well as to the clusters obtained through the k-means method. In all cases, the probability of first capture was set equal to the probability of recapture (p = c), as the process of taking photographs does not involve the physical capture of individuals so no behavioral effect is expected (<xref ref-type="bibr" rid="B67">Tezanos-Pinto et al., 2013</xref>).</p>
</sec>
</sec>
<sec sec-type="results" id="S3">
<title>Results</title>
<p>Between May 2006 and August 2010, we conducted 75 surveys, totaling 6,328.8 km surveyed, 288.1 h of search effort, and 110.4 h photographing dolphin groups (<xref ref-type="table" rid="T1">Table 1</xref>). Search effort ranged from 3.8 to 8.15 h day<sup>&#x2212;1</sup> (x&#x0304; = 3.6 &#x00B1; 1.1 SD) and the full study area was covered in each and all survey trips. In general, the effort was greater during the first two seasons, but we found no evidence of a difference in search effort among seasons (Kruskal-Wallis, <italic>H</italic> = 0.91, <italic>p</italic> = 0.63). Photo-ID effort (h day<sup>&#x2013;1</sup>) ranged from 0.0 to 3.6 (mean 1.4 &#x00B1; 0.8 SD), and no seasonal differences were found (Kruskal-Wallis, <italic>H</italic> = 10.55, p = 0.10).</p>
<table-wrap position="float" id="T1">
<label>TABLE 1</label>
<caption><p>Summary of survey and photo-identification effort of bottlenose dolphins off Alvarado Veracruz System, south-western Gulf of Mexico.</p></caption>
<table cellspacing="5" cellpadding="5" frame="hsides" rules="groups">
<thead>
<tr>
<td valign="top" align="left">Season</td>
<td valign="top" align="center">n</td>
<td valign="top" align="center">sT (hs)</td>
<td valign="top" align="center">pT (hs)</td>
<td valign="top" align="center">nE</td>
<td valign="top" align="center">km</td>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Dry-2006</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">22.9</td>
<td valign="top" align="center">5.5</td>
<td valign="top" align="center">19</td>
<td valign="top" align="center">368.6</td>
</tr>
<tr>
<td valign="top" align="left">Rainy-2006</td>
<td valign="top" align="center">13</td>
<td valign="top" align="center">56.3</td>
<td valign="top" align="center">25.1</td>
<td valign="top" align="center">48</td>
<td valign="top" align="center">1031.6</td>
</tr>
<tr>
<td valign="top" align="left">NW-2007</td>
<td valign="top" align="center">5</td>
<td valign="top" align="center">20.4</td>
<td valign="top" align="center">7.4</td>
<td valign="top" align="center">25</td>
<td valign="top" align="center">357.3</td>
</tr>
<tr>
<td valign="top" align="left">Dry-2007</td>
<td valign="top" align="center">7</td>
<td valign="top" align="center">27.3</td>
<td valign="top" align="center">10.0</td>
<td valign="top" align="center">25</td>
<td valign="top" align="center">519.9</td>
</tr>
<tr>
<td valign="top" align="left">Rainy-2007</td>
<td valign="top" align="center">6</td>
<td valign="top" align="center">23.5</td>
<td valign="top" align="center">9.4</td>
<td valign="top" align="center">18</td>
<td valign="top" align="center">512.1</td>
</tr>
<tr>
<td valign="top" align="left">NW-2008</td>
<td valign="top" align="center">2</td>
<td valign="top" align="center">7.1</td>
<td valign="top" align="center">1.3</td>
<td valign="top" align="center">7</td>
<td valign="top" align="center">131.6</td>
</tr>
<tr>
<td valign="top" align="left">Dry-2008</td>
<td valign="top" align="center">2</td>
<td valign="top" align="center">10.9</td>
<td valign="top" align="center">2.1</td>
<td valign="top" align="center">6</td>
<td valign="top" align="center">214.9</td>
</tr>
<tr>
<td valign="top" align="left">Rainy-2008</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">11.9</td>
<td valign="top" align="center">8.6</td>
<td valign="top" align="center">17</td>
<td valign="top" align="center">308.3</td>
</tr>
<tr>
<td valign="top" align="left">NW-2009</td>
<td valign="top" align="center">5</td>
<td valign="top" align="center">20.6</td>
<td valign="top" align="center">9.6</td>
<td valign="top" align="center">21</td>
<td valign="top" align="center">658.4</td>
</tr>
<tr>
<td valign="top" align="left">Dry-2009</td>
<td valign="top" align="center">8</td>
<td valign="top" align="center">27.4</td>
<td valign="top" align="center">9.5</td>
<td valign="top" align="center">30</td>
<td valign="top" align="center">797.7</td>
</tr>
<tr>
<td valign="top" align="left">Rainy-2009</td>
<td valign="top" align="center">7</td>
<td valign="top" align="center">20.2</td>
<td valign="top" align="center">6.6</td>
<td valign="top" align="center">15</td>
<td valign="top" align="center">463.3</td>
</tr>
<tr>
<td valign="top" align="left">NW-2010</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">12.3</td>
<td valign="top" align="center">2.7</td>
<td valign="top" align="center">6</td>
<td valign="top" align="center">308.4</td>
</tr>
<tr>
<td valign="top" align="left">Dry-2010</td>
<td valign="top" align="center">6</td>
<td valign="top" align="center">20.9</td>
<td valign="top" align="center">9.9</td>
<td valign="top" align="center">20</td>
<td valign="top" align="center">515.0</td>
</tr>
<tr>
<td valign="top" align="left">Rainy-2010</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">6.6</td>
<td valign="top" align="center">2.8</td>
<td valign="top" align="center">6</td>
<td valign="top" align="center">141.6</td>
</tr>
<tr>
<td valign="top" align="left">Totals</td>
<td valign="top" align="center">75</td>
<td valign="top" align="center">288.1</td>
<td valign="top" align="center">110.4</td>
<td valign="top" align="center">263</td>
<td valign="top" align="center">6328.8</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p><italic>n = No. of surveys, sT = Search effort, pT = Photo-ID effort, nE = No. of dolphin group encounters, km = km surveyed.</italic></p></fn>
</table-wrap-foot>
</table-wrap>
<p>Two hundred and sixty-three groups were encountered totaling 2,320 dolphins sampled, of which 231 distinct individuals were identified. We processed 30,402 pictures of which 10,958 (36%) were useful for photo-ID. Group size averaged 9.0 individuals (&#x00B1; 11.2 SD, range: 1&#x2013;100), and remained similar among seasons (Kruskal-Wallis, <italic>H</italic> = 2.62, <italic>p</italic> = 0.27). The number of recaptures for marked dolphins ranged from 0 to 12 occasions, where 36.8 % (<italic>n</italic> = 85) were transients (<xref ref-type="fig" rid="F2">Figure 2</xref>).</p>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption><p>Frequency of individual resightings of bottlenose dolphins off the Alvarado Lagoon between May 2006 through August 2010 (<italic>n</italic> = 146 distinct adult dolphins). RR = regular residents, OR = occasional residents, OV = occasional visitors.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-08-753484-g002.tif"/>
</fig>
<sec id="S3.SS1">
<title>Clustering of Individuals</title>
<p>The ICH (<xref ref-type="bibr" rid="B9">Calinski and Harabasz, 1974</xref>) indicated that <italic>K</italic> = 3 (ICH = 389.4) was the best grouping strategy according to the data. Cluster 1 consisted of 46 individuals with low seasonal (mean = 0.27 &#x00B1; 0.08 SD) and annual (mean = 0.31 &#x00B1; 0.18 SD) site fidelity indexes. These individuals were resighted between 1 and 4 seasons. Cluster 2 comprised 45 individuals with medium seasonal (mean = 0.49 &#x00B1; 0.10 SD) and annual (mean = 0.76 &#x00B1; 0.10 SD) site fidelity indexes; these individuals were resighted between 2 and 8 seasons. Cluster 3 consisted of 55 individuals with high seasonal (mean = 0.79 &#x00B1; 0.09 SD) and annual (mean = 0.96 &#x00B1; 0.06 SD) site fidelity indexes; these individuals were recaptured between 5 and 12 seasons. Following <xref ref-type="bibr" rid="B92">Zanardo et al. (2016)</xref> and <xref ref-type="bibr" rid="B51">Passadore et al. (2017)</xref> these clusters were defined as &#x201C;occasional visitors&#x201D; (OV), &#x201C;occasional residents&#x201D; (OR), and &#x201C;regular residents&#x201D; (RR), respectively (<xref ref-type="fig" rid="F3">Figures 3</xref>, see definitions in <xref ref-type="supplementary-material" rid="FS1">Supplementary Material 1</xref>).</p>
<fig id="F3" position="float">
<label>FIGURE 3</label>
<caption><p>Boxplot of IH<sub>4</sub> values, by season and year, according to the residency pattern. OV = occasional visitors (<italic>n</italic> = 46), OR = occasional residents (<italic>n</italic> = 45), RR = regular residents (<italic>n</italic> = 55).</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-08-753484-g003.tif"/>
</fig>
<p>The Kruskal-Wallist test showed that there were differences in the medians of the IH<sub>4</sub> values among groups (IH<sub>4</sub>-season: <italic>p</italic> &#x003C; 0.001, IH<sub>4</sub>-year: <italic>p</italic> &#x003C; 0.001). The Mann-Whitney pairwise <italic>post-hoc</italic> test showed that the medians of the groups were different (IH<sub>4</sub>-season: <italic>p</italic> &#x003C; &#x003C; 0.001; IH<sub>4</sub>-year: <italic>p</italic> &#x003C; &#x003C; 0.001, in all cases), indicating differences in the time spent in the study area for individuals classified in different clusters.</p>
</sec>
<sec id="S3.SS2">
<title>Discovery Curves</title>
<p>The cumulative frequency of newly identified individuals by residency pattern displayed an asymptotic trend in all cases (<xref ref-type="fig" rid="F4">Figure 4</xref>), indicating that most of the individuals present in the study area for the duration of the study were identified. For RR and OR individuals, the curve reached a plateau within the first seasons of our study. Additionally, for OV, transients (TR), and the whole sample, the curves presented two plateaus, indicating at least one occasional pulse of incorporation of individuals to the study area (<xref ref-type="fig" rid="F4">Figure 4</xref>).</p>
<fig id="F4" position="float">
<label>FIGURE 4</label>
<caption><p>Discovery curve of the cumulative frequency of newly identified bottlenose dolphins off the Alvarado Lagoon System, between 2006 and 2010, by residency pattern. FS = full sample, TR = transients, RR = regular residents, OV = occasional visitors, OR = occasional residents, NW = Northern Winds. Number of individuals belonging to each cluster are indicated.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-08-753484-g004.tif"/>
</fig>
</sec>
<sec id="S3.SS3">
<title>Goodness of Fit Tests and Model Selection</title>
<p>The global test for the sample stratified by residency pattern (excluding transients) was non-significant (&#x03C7;2 = 70.1, D.F. = 78, P-value = 0.73), indicating compliance with the model assumptions.</p>
<p>The most parsimonious model (AICc = 1810.9; AICc weight = 0.83) indicated that survival was time-invariant, different among groups, and that both catchability and recruitment were time-variant and group-variant [Phi(g), p(g&#x002A;t) pent(g&#x002A;t), model 1 in <xref ref-type="table" rid="T2">Table 2</xref>]. Formulations with invariant recruitment [pent(g), pent(.) or equal for all groups pent(t)] failed to converge or presented unrealistic values or null standard error, thus they were not included in the analyses.</p>
<table-wrap position="float" id="T2">
<label>TABLE 2</label>
<caption><p>Set of candidate models arranged in ascending order by AICc for population analysis of the bottlenose dolphin off Alvarado Veracruz System, southwestern Gulf of Mexico, between 2006 and 2010.</p></caption>
<table cellspacing="5" cellpadding="5" frame="hsides" rules="groups">
<thead>
<tr>
<td valign="top" align="left">Model</td>
<td valign="top" align="center">AICc</td>
<td valign="top" align="center">Delta AICc</td>
<td valign="top" align="center">AICc weights</td>
<td valign="top" align="center">Model likelihood</td>
<td valign="top" align="center">Number of parameters</td>
<td valign="top" align="center">Deviance</td>
<td valign="top" align="center">&#x2212;2log(L)</td>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">1 {Phi(g) p(g&#x002A;t) pent(g&#x002A;t)}</td>
<td valign="top" align="right">1810.9</td>
<td valign="top" align="right">0.0</td>
<td valign="top" align="center">0.83</td>
<td valign="top" align="center">1.00</td>
<td valign="top" align="center">87</td>
<td valign="top" align="right">544.3</td>
<td valign="top" align="right">1616.5</td>
</tr>
<tr>
<td valign="top" align="left">2 {Phi(.) p(g&#x002A;t) pent(g&#x002A;t)}</td>
<td valign="top" align="right">1814.7</td>
<td valign="top" align="right">3.8</td>
<td valign="top" align="center">0.13</td>
<td valign="top" align="center">0.15</td>
<td valign="top" align="center">85</td>
<td valign="top" align="right">553.1</td>
<td valign="top" align="right">1625.2</td>
</tr>
<tr>
<td valign="top" align="left">3 {Phi(t) p(g&#x002A;t) pent(g&#x002A;t)}</td>
<td valign="top" align="right">1816.9</td>
<td valign="top" align="right">6.0</td>
<td valign="top" align="center">0.04</td>
<td valign="top" align="center">0.05</td>
<td valign="top" align="center">84</td>
<td valign="top" align="right">557.8</td>
<td valign="top" align="right">1629.9</td>
</tr>
<tr>
<td valign="top" align="left">4 {Phi(g) p(t) pent(g&#x002A;t)}</td>
<td valign="top" align="right">1977.7</td>
<td valign="top" align="right">166.8</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">59</td>
<td valign="top" align="right">778.4</td>
<td valign="top" align="right">1850.6</td>
</tr>
<tr>
<td valign="top" align="left">5 {Phi(g&#x002A;t) p(t) pent(g&#x002A;t)}</td>
<td valign="top" align="right">1986.2</td>
<td valign="top" align="right">175.2</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">81</td>
<td valign="top" align="right">734.4</td>
<td valign="top" align="right">1806.6</td>
</tr>
<tr>
<td valign="top" align="left">6 {Phi(t) p(t) pent(g&#x002A;t)}</td>
<td valign="top" align="right">2035.1</td>
<td valign="top" align="right">224.2</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">60</td>
<td valign="top" align="right">833.5</td>
<td valign="top" align="right">1905.7</td>
</tr>
<tr>
<td valign="top" align="left">7 {Phi(.) p(t) pent(g&#x002A;t)}</td>
<td valign="top" align="right">2049.5</td>
<td valign="top" align="right">238.6</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">57</td>
<td valign="top" align="right">854.8</td>
<td valign="top" align="right">1927.0</td>
</tr>
<tr>
<td valign="top" align="left">8 {Phi(g&#x002A;t) p(g) pent(g&#x002A;t)}</td>
<td valign="top" align="right">2055.6</td>
<td valign="top" align="right">244.7</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">83</td>
<td valign="top" align="right">798.9</td>
<td valign="top" align="right">1871.1</td>
</tr>
<tr>
<td valign="top" align="left">9 {Phi(t) p(g) pent(g&#x002A;t)}</td>
<td valign="top" align="right">2057.4</td>
<td valign="top" align="right">246.5</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">58</td>
<td valign="top" align="right">860.4</td>
<td valign="top" align="right">1932.6</td>
</tr>
<tr>
<td valign="top" align="left">10 {Phi(g) p(g) pent(g&#x002A;t)}</td>
<td valign="top" align="right">2088.3</td>
<td valign="top" align="right">277.4</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">48</td>
<td valign="top" align="right">914.2</td>
<td valign="top" align="right">1986.4</td>
</tr>
<tr>
<td valign="top" align="left">11 {Phi(.) p(g) pent(g&#x002A;t)}</td>
<td valign="top" align="right">2126.0</td>
<td valign="top" align="right">315.1</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">46</td>
<td valign="top" align="right">956.4</td>
<td valign="top" align="right">2028.6</td>
</tr>
<tr>
<td valign="top" align="left">12 {Phi(g) p(.) pent(g&#x002A;t)}</td>
<td valign="top" align="right">2174.2</td>
<td valign="top" align="right">363.2</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">13</td>
<td valign="top" align="right">1075.6</td>
<td valign="top" align="right">2147.7</td>
</tr>
<tr>
<td valign="top" align="left">13 {Phi(g&#x002A;t) p(.) pent(g&#x002A;t)}</td>
<td valign="top" align="right">2208.8</td>
<td valign="top" align="right">397.9</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">82</td>
<td valign="top" align="right">954.6</td>
<td valign="top" align="right">2026.8</td>
</tr>
<tr>
<td valign="top" align="left">14 {Phi(t) p(.) pent(g&#x002A;t)}</td>
<td valign="top" align="right">2240.9</td>
<td valign="top" align="right">429.9</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">56</td>
<td valign="top" align="right">1048.5</td>
<td valign="top" align="right">2120.7</td>
</tr>
<tr>
<td valign="top" align="left">15 {Phi(.) p(.) pent(g&#x002A;t)}</td>
<td valign="top" align="right">2251.2</td>
<td valign="top" align="right">440.3</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">13</td>
<td valign="top" align="right">1152.6</td>
<td valign="top" align="right">2224.8</td>
</tr>
<tr>
<td valign="top" align="left">16 {Phi(g&#x002A;t) p(g&#x002A;t) pent(g&#x002A;t)}</td>
<td valign="top" align="right">57050.9</td>
<td valign="top" align="right">55239.9</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">0.00</td>
<td valign="top" align="center">116</td>
<td valign="top" align="right">55709.0</td>
<td valign="top" align="right">56781.2</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p><italic>Sample stratified by residency pattern.</italic></p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="S3.SS4">
<title>Population Parameters</title>
<p>Catchability (<xref ref-type="fig" rid="F5">Figure 5</xref>) for RR (mean 0.67 &#x00B1; 0.25 SD) was higher than for OR (0.35 &#x00B1; 0.20 SD) and OV (mean 0.33 &#x00B1; 0.27 SD) (Anova, <italic>F</italic> = 8.64, <italic>p</italic> = 0.0008).</p>
<fig id="F5" position="float">
<label>FIGURE 5</label>
<caption><p>Catchability of the bottlenose dolphin (<italic>T. truncatus</italic>) in the coastal waters off Alvarado Lagoon System according to their residency pattern. OV = occasional visitors (<italic>n</italic> = 46), OR = occasional residents (<italic>n</italic> = 45), RR = regular residents (<italic>n</italic> = 55).</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-08-753484-g005.tif"/>
</fig>
</sec>
<sec id="S3.SS5">
<title>Apparent Survival and Recruitment</title>
<p>According to the most parsimonious model, seasonal survival was time-invariant and resulted in 1.00 (95% CI: 1.00&#x2013;1.00) for RR and OR, and 0.91 (95% CI: 0.85&#x2013;0.95) for OV individuals. When scaled to represent annual rates (see <xref ref-type="bibr" rid="B16">Cooch and White, 2019</xref>, p. 4.27), survival was 1.00 (95% CI: 1.00&#x2013;1.00) for RR and OR, and 0.75 (95% CI: 0.61&#x2013;0.86) for OV. Recruitment for the duration of the study was 0.72, 0.20, and 0.02 for OV, OR, and RR clusters, respectively, such that 28%, 80%, and 98% of OV, OR, and RR individuals, respectively, were already present in the population just before the beginning of the study (<xref ref-type="table" rid="T3">Table 3</xref>).</p>
<table-wrap position="float" id="T3">
<label>TABLE 3</label>
<caption><p>Recruitment from the superpopulation of the bottlenose dolphin off the Alvarado Lagoon System, southwestern Gulf of Mexico, 2006&#x2013;2010.</p></caption>
<table cellspacing="5" cellpadding="5" frame="hsides" rules="groups">
<thead>
<tr>
<td valign="top" align="left">Season</td>
<td valign="top" align="center">Occasional visitors</td>
<td valign="top" align="center">Occasional residents</td>
<td valign="top" align="center">Regular residents</td>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Rainy 2006</td>
<td valign="top" align="center">0.23 (0.12&#x2013;0.41)</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">NW 2007</td>
<td valign="top" align="center"/>
<td valign="top" align="center">0.16 (0.02&#x2013;0.57)</td>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Dry 2007</td>
<td valign="top" align="center">0.14 (0.03&#x2013;0.44)</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Rainy 2007</td>
<td valign="top" align="center">0.03 (0.00&#x2013;0.98)</td>
<td valign="top" align="center"/>
<td valign="top" align="center">0.02 (0.00&#x2013;0.12)</td>
</tr>
<tr>
<td valign="top" align="left">NW 2008</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Dry 2008</td>
<td valign="top" align="center">0.02 (0.00&#x2013;1.00)</td>
<td valign="top" align="center">0.03 (0.00&#x2013;0.62)</td>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Rainy 2008</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">NW 2009</td>
<td valign="top" align="center">0.30 (0.14&#x2013;0.52)</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Dry 2009</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Rainy 2009</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">NW 2010</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Dry 2010</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Rainy 2010</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Total for the study period</td>
<td valign="top" align="center">0.72</td>
<td valign="top" align="center">0.20</td>
<td valign="top" align="center">0.02</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p><italic>95% CI&#x2019;s are indicated between parentheses. Occasions with null recruitment are not indicated. NW = northern winds.</italic></p></fn>
</table-wrap-foot>
</table-wrap>
<p>Occasional visitors were recruited in up to five out of 14 sampling occasions, with peaks in the rainy season of 2006 (23%), and the northern winds season of 2009 (30%). Occasional residents were recruited only during the NW 2007 and Dry 2008 seasons, with the highest percentage in the dry season of 2007 (16 %). Regular residents were recruited only in the Rainy season of 2007, but in a low proportion (2%).</p>
<p>The high survival values of the RR and OR clusters, as well as the null and low recruitment rates of RR and OR individuals, respectively, were consistent with the assumption of demographic or geographical closure for these clusters. As stated earlier, additional analyses were conducted to determine abundance for the core community, under the assumption of closed populations (see below).</p>
</sec>
<sec id="S3.SS6">
<title>Abundance</title>
<p>All abundances were adjusted by &#x03B8; to include the unmarked fraction of the population. The total abundance of occasional visitors averaged 34 individuals (&#x00B1; 6.0 D.E., range: 18&#x2013;42). The abundance of occasional residents averaged 57 (&#x00B1; 7.3 D.E., range: 44&#x2013;76), and regular residents averaged 72 (&#x00B1; 7.2 D.E., range: 65&#x2013;93) dolphins. A regression analysis indicated a low, positive, non-significant trend in the seasonal abundance of OV individuals (<italic>p</italic> = 0.09, <italic>R</italic><sup>2</sup> = 0.21). The residual plot of abundances for all clusters showed a non-random pattern (see <xref ref-type="supplementary-material" rid="FS1">Supplementary Material 2</xref>).</p>
</sec>
<sec id="S3.SS7">
<title>Closed Population Approach</title>
<p>The closure assumption was rejected for the whole sample and the OV cluster (<italic>p</italic> &#x003C; 0.001 in both cases), however, this was not the case for the RR and OR clusters (&#x03C7;<sup>2</sup> = 6.88, DF = 13, <italic>p</italic> = 0.91, and &#x03C7;<sup>2</sup> = 17.8, DF = 16, <italic>p</italic> = 0.33, respectively). Thus, we defined the aggregation of these clusters as the &#x201C;core community&#x201D; (<xref ref-type="bibr" rid="B84">Wells et al., 1987</xref>), and then used closed models in MARK to determine its abundance by means of the M<sub><italic>th</italic></sub> formulation (<xref ref-type="bibr" rid="B11">Chao et al., 1992</xref>), which includes heterogeneity (<xref ref-type="bibr" rid="B11">Chao et al., 1992</xref>; <xref ref-type="bibr" rid="B85">White and Burnham, 1999</xref>; <xref ref-type="bibr" rid="B16">Cooch and White, 2019</xref>). We chose the M<sub><italic>th</italic></sub> estimator (<xref ref-type="bibr" rid="B11">Chao et al., 1992</xref>) because the sampling protocol does not require the animals to be physically captured, and because of the heterogeneity in the capture probabilities of the OR an RR clusters (see section &#x201C;Population parameters&#x201D;). According to the M<sub><italic>th</italic></sub> formulation, the abundance of marked adult individuals (RR+OR) was 100 individuals (SE = 0.21). When corrected for the average mark rate (0.81 &#x00B1; 0.17 SD), total abundance of the core community was 123 individuals (95% CI: 114&#x2013;133). Interestingly, the closure test for the &#x201C;core community&#x201D; (OR+RR) was rejected (&#x03C7;<sup>2</sup> = 49.5, DF = 16, <italic>p</italic> = 0.00003), indicating a potential violation of this assumption; nevertheless, as both OR and RR clusters separately complied with the closure assumption, we believe that the significant result is an artifact of the different capture probabilities of each cluster (0.35 and 0.67, respectively). In this regard, it is well-known that heterogeneity in capture probabilities can cause both the tests of immigration and emigration to reject the null hypothesis of closure (<xref ref-type="bibr" rid="B16">Cooch and White, 2019</xref>, p. 14.6).</p>
</sec>
</sec>
<sec sec-type="discussion" id="S4">
<title>Discussion</title>
<p>Population structure of highly mobile marine organisms can be complex and difficult to study, but it is important to understand how individuals within a population partition their environment, in order to better address conservation challenges (<xref ref-type="bibr" rid="B78">Vollmer et al., 2021</xref>). In this regard, recent advancements in the implementation of standardized site fidelity indexes (<xref ref-type="bibr" rid="B68">Tschopp et al., 2018</xref>) and considerations on residency patterns when studying cetacean population dynamics (e.g., <xref ref-type="bibr" rid="B92">Zanardo et al., 2016</xref>; <xref ref-type="bibr" rid="B32">Hunt et al., 2017</xref>; <xref ref-type="bibr" rid="B51">Passadore et al., 2017</xref>; <xref ref-type="bibr" rid="B58">Schleimer et al., 2019</xref>; <xref ref-type="bibr" rid="B10">Carlucci et al., 2020</xref>; <xref ref-type="bibr" rid="B31">Haughey et al., 2020</xref>) provide improved methodological tools for dealing with heterogeneity in capture or survival probabilities inherent to the dynamics of social species with fission-fusion societies such as bottlenose dolphins (<xref ref-type="bibr" rid="B15">Connor et al., 2000</xref>). This is the first study to explore the population dynamics of the common bottlenose dolphin (<italic>T. truncatus</italic>) in the Gulf of Mexico based on its residency patterns, and to provide quantitative evidence of the existence of a &#x201C;core community&#x201D; (<italic>sensu</italic> <xref ref-type="bibr" rid="B84">Wells et al., 1987</xref>) in an open, coastal habitat. As this study is an extension of previous work by <xref ref-type="bibr" rid="B39">Morteo (2011)</xref> and <xref ref-type="bibr" rid="B41">Morteo et al. (2014</xref>, <xref ref-type="bibr" rid="B42">2017)</xref>, we included new data on previously unknown parameters, improving the temporal coverage as well as a more comprehensive analytical approach that yielded more refined estimates, and a more robust assessment of the population structure.</p>
<p>Due to the longevity of bottlenose dolphins, we acknowledge that short-term studies such as this one may not encapsulate the population processes related to factors such as mortality or emigration (<xref ref-type="bibr" rid="B31">Haughey et al., 2020</xref>). Despite the high number of transient individuals in the sample (<xref ref-type="fig" rid="F2">Figure 2</xref>), the asymptotic trend in the discovery curves (<xref ref-type="fig" rid="F4">Figure 4</xref>) indicated that most of the marked individuals in the population had been photographed by the end of the study period. For the full sample, the existence of two plateaus and decrease in the discovery rate of new individuals after the rainy season of 2009 suggest that the addition of new members is low, with sporadic immigration pulses as occurs in this, and other areas within the southern Gulf of Mexico (e.g., <xref ref-type="bibr" rid="B36">Mart&#x00ED;nez-Serrano et al., 2011</xref>; <xref ref-type="bibr" rid="B73">Vald&#x00E9;s-Arellanes et al., 2011</xref>; <xref ref-type="bibr" rid="B41">Morteo et al., 2014</xref>, <xref ref-type="bibr" rid="B42">2017</xref>, <xref ref-type="bibr" rid="B40">2019</xref>; <xref ref-type="bibr" rid="B20">Delgado-Estrella, 2015</xref>). On the other side, the similarity between the discovery curves of the whole sample, occasional visitors, and transients showed that the dynamics of this population is mainly regulated by the influx of non-resident individuals.</p>
<p>Catchability of RR (mean 0.67 &#x00B1; 0.27 SD) individuals was greater than for OR (0.35 &#x00B1; 0.20) and OV (0.32 &#x00B1; 0.27 SD) individuals, and thus abundance estimates for this cluster will be more precise (<xref ref-type="bibr" rid="B87">Williams et al., 2002</xref>). In general, catchability should be directly related to research effort alone but, in this case, it probably reflects that regular residents are more catchable by unit of effort than individuals in any other clusters (<xref ref-type="bibr" rid="B87">Williams et al., 2002</xref>).</p>
<p>High values of annual survival for the core community (cluster RR + OR) (1.00, 95% CI: 1.00&#x2013;1.00) contrast sharply to those of occasional visitors: (0.75, 95% CI: 0.59&#x2013;0.87). As transients were not included in the analysis, and RR and OR clusters behave as a closed population, these highest values for the core community are most probably the result of both a high survival rate and a very low emigration rate.</p>
<p>For long-lived species with complex life history processes, such as cetaceans, adult survival is expected to be high and variable with age, sex, and individual fitness (<xref ref-type="bibr" rid="B54">Ralls et al., 1980</xref>). Higher survival rates for resident individuals were indirectly assumed by <xref ref-type="bibr" rid="B43">Morteo et al. (2012b)</xref>, who showed that these animals interact less frequently with fisheries, when compared to non-residents, thus facing lower exposure to entanglements in fishing gear and retaliation measures by fishers. Therefore, although much lower survival estimates for the visitor fraction is largely based on a high proportion of dolphins permanently leaving the study area shortly after the sampling, it is likely that higher mortality for non-residents is also due to a greater risk of predation by sharks and higher risk of entanglement in fishing gear (<xref ref-type="bibr" rid="B43">Morteo et al., 2012b</xref>, <xref ref-type="bibr" rid="B41">2014</xref>, <xref ref-type="bibr" rid="B42">2017</xref>; <xref ref-type="bibr" rid="B56">Rechimont et al., 2018</xref>; <xref ref-type="bibr" rid="B38">Morales-Rinc&#x00F3;n et al., 2019</xref>). The latter is supported by reports from recently stranded animals &#x2013; recorded between 2002 and 2019 (decomposition code 1&#x2013;3, according to <xref ref-type="bibr" rid="B28">Geraci and Lounsbury, 1993</xref>) &#x2013; showing that fisheries-related injuries only occurred in individuals that had not been previously photographed in the study area (Fuentes Del Muro and Morteo, unpublished data, LabMMar-UV).</p>
<p>Survival values recorded for regular and occasional residents in this study are higher than those reported elsewhere (e.g., <xref ref-type="bibr" rid="B81">Wells and Scott, 1990</xref>; <xref ref-type="bibr" rid="B63">Speakman et al., 2010</xref>; <xref ref-type="bibr" rid="B18">Daura-Jorge et al., 2013</xref>; <xref ref-type="bibr" rid="B67">Tezanos-Pinto et al., 2013</xref>; <xref ref-type="bibr" rid="B25">Fruet et al., 2015</xref>; <xref ref-type="bibr" rid="B74">Vermeulen and Br&#x00E4;ger, 2015</xref>; <xref ref-type="bibr" rid="B76">Vermeulen et al., 2017</xref>; <xref ref-type="bibr" rid="B37">Methion and D&#x00ED;az L&#x00F3;pez, 2018</xref>), probably because of differences in the way we stratified the sample by residency pattern. It is important to notice that the null standard error in the point estimate of survival for both RR and OR is commonly attributed to problems with the data (<xref ref-type="bibr" rid="B16">Cooch and White, 2019</xref>, p. 6&#x2013;24); nevertheless, because of the stratification by residency type, it probably reflects true high values and precision of the estimates due to effective population closure within the study timeframe (i.e., 5-y).</p>
<p>In general, coastal bottlenose dolphins are known to exhibit a wide spectrum of residency patterns, which include transients, seasonal migrants, year-round residents, and a combination of occasional long-range movements, and repeated local residency (<xref ref-type="bibr" rid="B41">Morteo et al., 2014</xref>; <xref ref-type="bibr" rid="B82">Wells and Scott, 2018</xref>). This seems to be the case for the population in our study area, where <xref ref-type="bibr" rid="B57">Ru&#x00ED;z-Hern&#x00E1;ndez (2014)</xref> and <xref ref-type="bibr" rid="B40">Morteo et al. (2019)</xref> recorded a limited exchange of individuals between coastal waters off ALS and two northern locations (the Veracruz Reef System and Nautla, see <xref ref-type="fig" rid="F1">Figure 1</xref>), for which dolphins need to travel at least 100 and 230 km, respectively. Our results are similar to other contributions made to the south of our study area, where it was documented that some individuals traveled 270 km on average in a few months, including a dolphin that traveled more than 800 km between the states of Quintana Roo and Tabasco (<xref ref-type="bibr" rid="B20">Delgado-Estrella, 2015</xref>, see <xref ref-type="fig" rid="F1">Figure 1</xref>).</p>
<p>Differences in recruitment rate and timing between the core community (RR + OR) and visitors, as found in this study, could correspond to sex-related movement patterns, as reported previously in the Gulf of Mexico, the Caribbean (e.g., <xref ref-type="bibr" rid="B70">Urian et al., 2009</xref>; <xref ref-type="bibr" rid="B8">Caballero et al., 2012</xref>; <xref ref-type="bibr" rid="B80">Wells, 2014</xref>) and also in the study area, through greater residency in females and larger dispersion by males (<xref ref-type="bibr" rid="B42">Morteo et al., 2017</xref>, <xref ref-type="bibr" rid="B40">2019</xref>). In this sense, natal site philopatry of both sexes is common and associated to age, as it occurs in the Sarasota population (<xref ref-type="bibr" rid="B79">Wells, 2003</xref>, <xref ref-type="bibr" rid="B80">2014</xref>; <xref ref-type="bibr" rid="B60">Sellas et al., 2005</xref>). In the northern Gulf of Mexico, molecular data also suggest that some females may move and breed among different communities (<xref ref-type="bibr" rid="B21">Duffield and Wells, 2002</xref>), but implications at a local level remain to be investigated.</p>
<p>The existence of two plateaus in the discovery curves of the full sample, OV and OR individuals, indicates at least one occasional pulse of individuals entering from the superpopulation to the study area. These results are consistent with previous findings (<xref ref-type="bibr" rid="B39">Morteo, 2011</xref>; <xref ref-type="bibr" rid="B41">Morteo et al., 2014</xref>, <xref ref-type="bibr" rid="B42">2017</xref>), suggesting that it is an open population, but the rate of incorporation of new individuals is low in the medium-long term.</p>
<p>Comparable absolute abundances of several estuarine bottlenose dolphin communities around the world are often estimated between 60 and 150 individuals (e.g., <xref ref-type="bibr" rid="B88">Williams et al., 1993</xref>; <xref ref-type="bibr" rid="B89">Wilson et al., 1999</xref>; <xref ref-type="bibr" rid="B79">Wells, 2003</xref>; <xref ref-type="bibr" rid="B3">Balmer et al., 2008</xref>; <xref ref-type="bibr" rid="B75">Vermeulen and Cammareri, 2009</xref>; <xref ref-type="bibr" rid="B26">Fruet et al., 2011</xref>, <xref ref-type="bibr" rid="B25">2015</xref>; <xref ref-type="bibr" rid="B23">F&#x00E9;lix et al., 2017</xref>). Monthly averages of daily abundances by <xref ref-type="bibr" rid="B42">Morteo et al. (2017)</xref> in the study area were about 125 dolphins under the Jolly-Seber model. This number looks consistent with our estimates both within and between years, but results are not directly comparable because of differences in the treatment of the samples.</p>
<p>Our results support the assumption that the dolphin population that uses the coastal waters off ALS is open (<xref ref-type="bibr" rid="B42">Morteo et al., 2017</xref>), but emphasizes the existence of a core community of resident individuals that, occasionally, receives an influx of individuals from neighboring waters, with no apparent seasonal trend. It is noteworthy that, unlike other study areas, this core community -living in an open habitat- largely behaves as a closed population. This situation may be more common than previously thought for the species across the Gulf of Mexico, where many individuals remain in relatively small but well provisioned areas, whereas short-term residents and visitors come from the adjacent coastal populations, or have nomadic habits in their constant pursuit of food and mates (<xref ref-type="bibr" rid="B61">Shane, 1980</xref>; <xref ref-type="bibr" rid="B33">Irvine et al., 1981</xref>; <xref ref-type="bibr" rid="B84">Wells et al., 1987</xref>; <xref ref-type="bibr" rid="B57">Ru&#x00ED;z-Hern&#x00E1;ndez, 2014</xref>; <xref ref-type="bibr" rid="B20">Delgado-Estrella, 2015</xref>; <xref ref-type="bibr" rid="B40">Morteo et al., 2019</xref>, among others). The existence of such core communities in the northern Gulf of Mexico has been generally established based on qualitative criteria, mainly the overlap in the presence of transients with year-round and seasonal residents (i.e., <xref ref-type="bibr" rid="B61">Shane, 1980</xref>, <xref ref-type="bibr" rid="B62">1990</xref>; <xref ref-type="bibr" rid="B84">Wells et al., 1987</xref>; <xref ref-type="bibr" rid="B3">Balmer et al., 2008</xref>; <xref ref-type="bibr" rid="B69">Tyson et al., 2011</xref>, among others) and, in most cases, refer to dolphin populations living in inshore, estuarine habitats. However, in a coastal habitat adjacent to the Sarasota Bay, <xref ref-type="bibr" rid="B22">Fazioli et al. (2006)</xref> found that the dolphin community that prefer the Gulf of Mexico is primarily composed of transients, seasonal residents an individuals with a home range greater than the study area, with fewer year-round residents; nevertheless, details on the process to compute individual residency, and quantitative approaches on the classification of such individuals based on the dynamics of the population is generally lacking.</p>
<p>The permanent presence of dolphin groups and the existence of a core community in the coastal waters off ALS are probably related to a predictable supply of prey and a sheltered environment. Interestingly the dynamic flux of individuals, abundance at a local level (i.e., the core community) seems stable over time, which suggests that a sort of carrying capacity effect is in place. High site fidelity and/or restricted ranging patterns are likely driving population parameters for the core community of bottlenose dolphins in the coastal waters of Alvarado; as this could increase their chances of living in a provisioned habitat, it could also make them more prone to detrimental effects by both documented and currently unknown local threats. Future work should focus on exploring at a finer scale the relationship between these population parameters, the structure of the population (sex/age), and relevant environmental variables for the species.</p>
<p>Differences in residency patterns for the dolphins in our study area could be explained by the socioecological model of <xref ref-type="bibr" rid="B29">Gowans et al. (2007)</xref> such that, as resources are spatially and temporally predictable, dolphins remain resident in relatively small areas (<xref ref-type="bibr" rid="B41">Morteo et al., 2014</xref>, <xref ref-type="bibr" rid="B42">2017</xref>). Conversely, competition with local dolphins may lead non-resident individuals (mostly males) to range widely to find sufficient resources and mating opportunities (<xref ref-type="bibr" rid="B29">Gowans et al., 2007</xref>). This strategy helps to prevent inbreeding (<xref ref-type="bibr" rid="B8">Caballero et al., 2012</xref>), and would cause male dolphins of this population to prey on other species that may be available off river mouths and estuaries along coastal waters off the southwestern Gulf of Mexico (<xref ref-type="bibr" rid="B36">Mart&#x00ED;nez-Serrano et al., 2011</xref>; <xref ref-type="bibr" rid="B41">Morteo et al., 2014</xref>, <xref ref-type="bibr" rid="B42">2017</xref>, <xref ref-type="bibr" rid="B40">2019</xref>). As the existence of many resident communities has evidenced limited genetic exchange among adjacent sites all along the Gulf of Mexico (<xref ref-type="bibr" rid="B60">Sellas et al., 2005</xref>; <xref ref-type="bibr" rid="B8">Caballero et al., 2012</xref>; <xref ref-type="bibr" rid="B77">Vollmer and Rosel, 2013</xref>), this raises the question of a probable structure at metapopulation level, which should also be investigated.</p>
</sec>
<sec sec-type="data-availability" id="S5">
<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. The reduced m-array produced by the MARK output, that contains summary information on the numbers of individuals released at each occasion, and is the basis for the estimation of parameters, is presented in <xref ref-type="supplementary-material" rid="FS1">Supplementary Material 3</xref> for reproducibility and replicability.</p>
</sec>
<sec id="S6">
<title>Ethics Statement</title>
<p>This animal study was accomplished through federal permits SGPA/DGVS/00351/06, 01407/08 (EM) and SGPA/DGVS/00870/07, 02788/07, 01344/08, and 01649/08 (M. C. Baz&#x00FA;a) issued by the Subsecretaria de Gestion para la Proteccion Ambiental.</p>
</sec>
<sec id="S7">
<title>Author Contributions</title>
<p>JB-J: conceptualization, formal analysis, investigation, methodology, validation, visualization, and writing &#x2013; original draft. EM: conceptualization, data curation, funding acquiring, methodology, project administration, resources, supervision, validation, and writing &#x2013; review and editing. CD-A and JB-P: methodology, supervision, validation, and writing &#x2013; review and editing. PF and ES: conceptualization, methodology, supervision, validation, and writing &#x2013; review and editing. All authors contributed to the article 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="pudiscl1">
<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>
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<back>
<ack>
<p>This research was part of the first author&#x2019;s doctoral thesis at Universidad Veracruzana, supported through doctoral fellowship Number 291197/CVU636908 by the Mexican National Council for Science and Technology (CONACyT). This work was also part of the CONACyT project 221750 on the&#x201D; Trophic ecology of bottlenose dolphins (<italic>Tursiops truncatus</italic>) and artisanal fisheries interactions in coastal waters off Veracruz State&#x201D;. Fieldwork was accomplished through federal permits SGPA/DGVS/00351/06, 01407/08 (EM) and SGPA/DGVS/00870/07, 02788/07, 01344/08, and 01649/08 (M. C. Baz&#x00FA;a). Surveys were always conducted by at least one of the authors and many undergraduate students at LabMMar, which were also involved in data collection, photographic analyses and data processing. Israel Huesca helped produce the figures. Local fishers R. Tiburcio, J. Tiburcio and E. Tiburcio always returned the crew safely back to shore. Dagmar Fertl and Nathalie Ward reviewed earlier versions of this manuscript. Paul Conn, Manuel Cach, Alberto Delgado Estrella, Tim Gerrodette, Carlos Lira, Manuel Mendoza Carranza, Cecilia Passadore, Grgur Plesli&#x0107;, Pedro S&#x00E1;nchez Palomino, Kate Sprogis, Gabriela Tezanos Pinto, Fernando Trujillo, and Randy Wells provided valuable information and/or references. This manuscript was greatly improved by comments from MD and AL. This study was part of a collaboration between LabMMar-ICIMAP-IIB, Universidad Veracruzana, and ECOMEGA, Universidade Federal do Rio Grande-FURG. All the fieldwork was conducted in compliance with the &#x201C;Guidelines for the Treatment of Marine Mammals in Field Research&#x201D; of the Society for Marine Mammalogy (available at <ext-link ext-link-type="uri" xlink:href="https://marinemammalscience.org/about-us/ethics/marine-mammal-treatment-guidelines">https://marinemammalscience.org/about-us/ethics/marine-mammal-treatment-guidelines</ext-link>).</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.2021.753484/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fmars.2021.753484/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="Presentation_1.pdf" id="FS1" mimetype="application/pdf" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
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