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Mammalian Biology xxx (2014) xxx–xxx

Contents lists available at ScienceDirect

Mammalian Biology

jou rn al hom epage: www.elsev ier .com/ locate /mambio

riginal Investigation

nferring spatial and temporal behavioral patterns of free-ranginganatees using saltwater sensors of telemetry tags

elma Nataly Castelblanco-Martíneza,b,∗, Benjamin Morales-Velab, Daniel H. Slonec,anneth Adriana Padilla-Saldívarb, James P. Reidc, Héctor Abuid Hernández-Aranab

Oceanic Society, 30 Sir Francis Drake Boulevard, P.O. Box 437, Ross, CA 94957, USAEl Colegio de la Frontera Sur, Av. Centenario Km. 5.5, CP 77900 Chetumal, Quintana Roo, MexicoSoutheast Ecological Science Center, U.S. Geological Survey, 2201 NW 40th Terrace, Gainesville, FL 32605, USA

r t i c l e i n f o

rticle history:eceived 30 April 2014ccepted 9 July 2014andled by Frank E. Zachosvailable online xxx

eywords:richechus manatusthology

a b s t r a c t

Diving or respiratory behavior in aquatic mammals can be used as indicator of physiological activityand consequently, to infer behavioral patterns. Five Antillean manatees, Trichechus manatus manatus,were captured in Chetumal Bay and tagged with GPS tracking devices. The radios were equipped witha micropower saltwater sensor (SWS), which records the times when the tag assembly was submerged.The information was analyzed to establish individual fine-scale behaviors. For each fix, we establishedthe following variables: distance (D), sampling interval (T), movement rate (D/T), number of dives (N),and total diving duration (TDD). We used logic criteria and simple scatterplots to distinguish betweenbehavioral categories: ‘Travelling’ (D/T ≥ 3 km/h), ‘Surface’ (↓TDD, ↓N), ‘Bottom feeding’ (↑TDD, ↑N) and

elemetryireniansutoecology

‘Bottom resting’ (↑TDD, ↓N). Habitat categories were qualitatively assigned: Lagoon, Channels, Caye shore,City shore, Chanel edge, and Open areas. The instrumented individuals showed a daily rhythm of bot-tom activities, with surfacing activities more frequent during the night and early in the morning. Moreinvestigation into those cycles and other individual fine-scale behaviors related to their proximity toconcentrations of human activity would be informative.

© 2014 Deutsche Gesellschaft für Säugetierkunde. Published by Elsevier GmbH. All rights reserved.

ntroduction

For the last few decades, biotelemetry has proven to be aery useful tool for marine species tracking (Aarts et al., 2008).hese tools offer increasingly sophisticated means – e.g. large-scaleelemetry arrays, fine-scale positioning, and use of physiologicalnd environmental sensors – of evaluating the behavior, spatialcology, energetics, and physiology of free-living animals in theiratural environment (Cooke, 2008). Telemetry has been widelysed to investigate the behavior of seabirds (Adams and Flora, 2010;ilson et al., 2009; Wood et al., 2000), marine mammals (Bailleul

t al., 2007; Baumgartner and Mate, 2005; Mate et al., 1998), rep-iles (Jonsen et al., 2007; McMahon et al., 2007; Read et al., 2007)nd fishes (Mate et al., 1998; Sims et al., 2009).

Please cite this article in press as: Castelblanco-Martínez, D.N., et al., Imanatees using saltwater sensors of telemetry tags. Mammal. Biol. (2

Most of the broad scale studies of manatee radio tracking havemployed VHF radio-transmitters and/or Platform Terminal Trans-itters (PTTs) with the Argos data service (www.argos-system.org)

∗ Corresponding author at: Oceanic Society, 30 Sir Francis Drake Boulevard, P.O.ox 437, Ross, CA 94957, USA. Tel.: +55 9832850209.

E-mail address: castelblanco.nataly@gmail.com (D.N. Castelblanco-Martínez).

ttp://dx.doi.org/10.1016/j.mambio.2014.07.003616-5047/© 2014 Deutsche Gesellschaft für Säugetierkunde. Published by Elsevier Gmb

(Deutsch et al., 2003). A major limitation of VHF and PTT is theinfrequent intervals between fixes limiting their application at finerspatial resolutions (Schofield et al., 2007). Another issue is the spa-tial precision of locations, which lack the high resolution accuracyneeded for fine-scale tracking (Hazel, 2009). However, recent radiotracking studies of manatees in Florida and the Caribbean haveutilized Argos-linked Global Positioning System (GPS) tags, whichprovide much more accurate spatial precision.

A large number of studies have addressed the fine-scale habitatselection by marine megafauna species as turtles (Fossette et al.,2010; Schofield et al., 2007; Senko et al., 2010; Yasuda and Arai,2009), cetaceans (Allen et al., 2001; Hastie et al., 2003; Johnstonet al., 2005; MacLeod and Zuur, 2005; Skov and Thomsen, 2008),seals (Burns et al., 2008; Hindell et al., 2002; Lea and Dubroca,2003), sea lions (Wolf and Trillmich, 2007) and dugongs (Sheppardet al., 2006). However, studies of fine-scale behavior of endangeredmanatees (Order Sirenia: Trichechus spp.) are underrepresented inthe literature. Our understanding of fine-scale behavior may be

nferring spatial and temporal behavioral patterns of free-ranging014), http://dx.doi.org/10.1016/j.mambio.2014.07.003

improved by examining the diving behavior and correlating it withphysical features (Burns et al., 2008).

Data loggers recording depth at specific time interval(Time–Depth recorders, TDRs) have been widely used to describe

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ARTICLEAMBIO-40685; No. of Pages 10

D.N. Castelblanco-Martínez et al. /

ne-scale behavior of depth-diving mammals as cetaceans (Aokit al., 2007; Baird et al., 2002, 2005; Davis et al., 2007), sea ottersBodkin et al., 2007), elephant seals (Campagna et al., 1999; Costat al., 2003; Le Boeuf et al., 1993; Muelbert et al., 2004), sealsBekkby and Bjorge, 2000; Blix and Nordoy, 2007; Frost et al., 2001),s well as in shallow-depth animals as dugongs (Chilvers et al.,004; Churchward, 2001) and turtles (Fossette et al., 2010; Hayst al., 2001a; Hochscheid et al., 2005; Reina et al., 2004). However,or shallow marine mammals as manatees, the use of TDRs to studyiving patterns has been limited due to issues in the interpretationf data (Hagihara et al., 2009), and alternative technical tools shoulde explored.

We aimed to investigate the fine-scale behavior of satellite-agged Antillean manatees in Chetumal Bay. This technology notnly enables animals to be located but can also provide informationn their diving activities (Bailleul et al., 2007). The GPS radios werequipped with a saltwater sensor (SWS), which records the timeshen the tag assembly is submerged. Diving or respiratory behav-

or can be used as an indicator of physiological activity (Read andaskin, 1985), and consequently, to infer behavioral patterns (Boyd,997). Therefore, we used the information obtained from SWS toescribe the diving behavior, and to infer behavioral patterns ofanatees captured in Chetumal Bay.

ethods

tudy area

Chetumal Bay is a large estuary located between Belize andhe southern section of the state of Quintana Roo, Mexico17◦52′–18◦50′ N, 87◦50′–88◦25′ W) (Fig. 1). It covers an area ofbout 2450 km2. The connection with the sea is located in theoutheast section of the bay, and it receives fresh water from theondo River and many smaller creeks. Its depth ranges from 1 to

m, with several nearly circular depressions known as “pozas” thatan attain up to 40 m depth (Carrillo et al., 2009b). With an aver-ge salinity of 13 psu it is considered hyposaline (Gasca et al., 1994)nd has low productivity (Gasca and Castellanos, 1993). The climates tropical with seasonal rains between June and September andn annual precipitation of 1245 mm on average; the mean annualemperature is 27 ◦C with a maximum of 31 ◦C and a minimumf 20 ◦C (Carrillo et al., 2009a). The region has three climatic sea-ons typified by drought (February to May), rains (June to October),nd north winds (November to January) (Carrillo et al., 2009b). Theay is characterized by a low abundance and variety of sub-aquaticegetation (Espinoza-Ávalos et al., 2009), although manatees canlso forage for mangroves and other riparian plants (Castelblanco-artínez et al., 2009b).

apture, tagging and radio-tracking

From March 2006 to May 2007, five Antillean manatees (threeemales and two males) were captured in northwestern Chetu-

al Bay and fitted with radio tags (Table 1). Capture proceduresre explained in Morales-Vela and Padilla-Saldívar (2009). The tagssembly consisted of a buoyant, cylindrical housing containing anrgos-linked GPS tag (TMT-460, Telonics, Inc.) that was attachedy a flexible nylon tether to a belt that fit snugly around the cau-al peduncle (Reid et al., 1995). The tags collected GPS position datavery 20 or 30 min with a measured accuracy of <5 m for >95% of theocations. In this research, the tag also incorporated micro-power

Please cite this article in press as: Castelblanco-Martínez, D.N., et al., Imanatees using saltwater sensors of telemetry tags. Mammal. Biol. (2

altwater sensor (SWS) that functions to suppress transmissionshile the unit is submerged thereby saving power (Telonics, Inc.).

he SWS synchronize uplink transmissions to resume at the pre-ise time when the animal actually breaks the sea surface following

PRESSalian Biology xxx (2014) xxx–xxx

a dive. By transmitting immediately upon resurfacing, the unithas the best chance of successfully getting uplink transmissions toavailable orbiting satellites. The units were recovered at the com-pletion of the study, the GPS locations and sensor data (number andduration of individual tag submergences/dives) were downloadedfrom memory for analysis.

Data analysis

Each manatee was treated as a sampling unit to avoid pseudoreplication (Hurlbert, 1984). The telemetry data were edited toeliminate telemetry fixes before and after tracking time andon land. Points were also eliminated based on excessive speedbetween consecutive fixes. Each fix was associated to a depth valueusing the nearest-neighbor interpolation of ArcMap. Bathymetricinformation was obtained by Laboratory of Physic Oceanographyof ECOSUR (Chetumal), and complementary depth values for fresh-water system of Guerrero Lagoon were collected by the authors.To reduce the effect of shallow depths on data interpretation, fixesobtained at depth values lesser than 2 m were discarded from theanalysis.

The information obtained by the SWS was used to record sub-mergence frequency and duration. The start of the dive was definedby the time that the SWS perceived that the transmitter wassubmerged, and the end of the dive was defined when the SWSrecorded the transmitter breaking the surface (Hays et al., 2004).For each 20 or 30 min interval between the remaining consecu-tive fixes, distance (D) between coordinates, number of dives (N),and total diving duration in seconds (TDD) were used to infer thebehavioral category performed by the individual during the inter-val. Four behavioral categories were broadly defined based on priorknowledge of the species behavior. Long distances between twoconsecutive fixes – i.e. >1000 m (for 20 min interval) or >1500 m(for 30 min interval) – suggested that the manatee was traveling>3 km/h, so the second fix was classified as ‘traveling fast’. For allintervals that were shorter than this distance criterion, the inter-val end point was labeled as idling activities, which were furthersubdivided among behavioral categories using simple logic crite-ria, as shown in Table 2, Fig. 1. Bottom behaviors can be interpretedas resting or feeding. When a manatee is resting on the bottom, itcomes up only a few times to breathe (↓N◦ dives), and the under-water time is high (↑dive duration). When a manatee is feeding onthe bottom, the total dive duration is also high, but since the indi-vidual is more active, it comes to the surface to breathe more often(↑N◦ dives). When a manatee is resting at the surface, the numberof dives is low, and the duration of those dives is shorter (often 0).This pattern could also correspond to feeding or other behaviorsin shallow water. All behaviors calculated from analysis of thesetime intervals were assigned to the second, or ending point of theinterval (Table 2, Fig. 2).

Scatter plots of the data were created first to allow visual assess-ment of the data and to establish cut points for behavioral typesbased on the appearance of the data. The occurrence of behav-ioral categories was expressed as the proportion of fixes whereeach behavior pattern occurred (Martin and Bateson, 1993). Totest if there is a correlation between behavior and ecological vari-ables, habitat categories were qualitatively assigned according tothe locality and general geomorphologic characteristics, and weremutually exclusive, as follow: Lagoon, Channels, Caye shore, Cityshore, Chanel edge, and Open areas. Behavioral frequency wasrepresented in terms of percentages [Fb1 = (nb1/N1) × 100; whereFb1 = frequency of the behavior b in the habitat 1, nb1 = number

nferring spatial and temporal behavioral patterns of free-ranging014), http://dx.doi.org/10.1016/j.mambio.2014.07.003

of fixes assigned to the behavior b in the habitat 1, andN1 = total of fixes in the habitat 1]. The Pearson rank correlation(R2 statistic) method was used to determine a level of corre-lation between the rough behavior category (bottom, surface

Please cite this article in press as: Castelblanco-Martínez, D.N., et al., Inferring spatial and temporal behavioral patterns of free-rangingmanatees using saltwater sensors of telemetry tags. Mammal. Biol. (2014), http://dx.doi.org/10.1016/j.mambio.2014.07.003

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Fig. 1. Area of study.

Table 1Manatees Trichechus manatus manatus tagged with Argos-linked GPS tags in Chetumal Bay.

ID Length (cm) Beginning Ending Tracking time (days) Fixes/day

ID35-M 267 26/03/2006 21/04/2006 26 54.5ID36-M 292 27/03/2006 22/01/2007 301 46.4ID51-F 293 26/04/2007 05/05/2007 9 52.4ID52-F 312 18/05/2007 04/10/2007 139 27.4ID53-F 285 24/05/2007 20/06/2007 27 4.1

Table 2Logical interpretation of the variables (average duration and distance) based on prior knowledge of the species behavior.

Variable Traveling Idling

Bottom resting Surface resting/surface feeding Bottom feeding

Distance (D) ↑ ↓ ↓ ↓Number of dives (ND) – ↓ ↓ ↑Total diving duration (TDD) – ↑ ↓ ↑

Symbols are interpreted as: ↑ = above average duration or distance, ↓ = below average duration, and — = not applicable.

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Fig. 2. Examples of diving patterns corresponding to idling behaviors, obtained from the SWS for a 20-min period. Diving time (s) is showing in black and surface time inwhite. (a) Bottom resting, (b) bottom feeding and (c) surface resting.

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r traveling) and the habitat categories. We used the individ-al behavioral pattern as a proxy for the proportion of timeerforming a behavior over the 24-h cycle. Data were stored

n 6 h periods (A = 06:00–12:00; B = 12:00–18:00; C = 18:00–00nd D = 00:00–06:00) roughly corresponding to light/dark dailyycles. Differences between daily segments were compared using

Kruskal–Wallis one-way non-parametric analysis of variance,ollowing by pairwise Mann–Whitney U-testing for multiple com-arisons (Bonferroni-corrected). The analyses were performedsing the software PAST 2.17 (Harper and Ryan, 2001)

Please cite this article in press as: Castelblanco-Martínez, D.N., et al., Imanatees using saltwater sensors of telemetry tags. Mammal. Biol. (2

esults

Manatees were tracked in depths <6 m, often in very shal-ow waters (1–2 m). Depth ranges and manatee’s fixes percentage

for each range were: <2 m, 51.6%; 2–4 m, 34%, and 4–6 m, 14.4%.There were a total of 14,334 fix attempts in Chetumal Bay, withan average failure rate of 44.29 ± 29.05% (x ± SD). In 19.04% ofthe fixes we could not assess the behavior. It was due to the factthat in those cases, the second fix of the segment failed; there-fore the distance between the points was unknown. For the restof the points, manatees performed Surface behaviors 42.9% of thetime, Bottom Resting 32.2%, Traveling 3.94% and Bottom Feed-ing 1.88% of the time. The categories of behavior were variablebetween individuals and were not influenced by the sex (Fig. 3,Table 3).

nferring spatial and temporal behavioral patterns of free-ranging014), http://dx.doi.org/10.1016/j.mambio.2014.07.003

The studied animals performed all four behavioral pat-terns across their home ranges, but some areas showed ahigher frequency of bottom behaviors, specifically in Guer-rero Lagoon (‘Lagoon’), La Barra (‘Chanel edge’) and Chetumal

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Fig. 3. Assignment of behavioral categories for five satellite-tagged manatees, using diving variables and distance between consecutive points. Each point represents ac

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oordinate that was assigned a behavioral category.

ity (‘City shore’). Surface behaviors were concentrated in theuerrero Lagoon system (Fig. 4). Nevertheless, interestinglyottom behaviors were relatively more frequent in habi-ats known for highest subaquatic vegetation abundance suchs Caye shores and Channels. In the other hand, in openreas traveling behaviors were relatively more abundant (81%)Table 4).

Manatees showed an apparent daily rhythm of activities in

Please cite this article in press as: Castelblanco-Martínez, D.N., et al., Imanatees using saltwater sensors of telemetry tags. Mammal. Biol. (2

hich bottom behaviors were more frequent between 12:00 and8:00 pm, and surfacing activities occurred more often during theight and early in the morning (Fig. 5).

Discussion

The knowledge of fine-scale behavior is fundamental to under-standing many key aspects of a mammal’s ecology. Even animalswith large home ranges often concentrate their activities on smallpatches where they locate food, mates and shelter (Burt, 1943).When large numbers of animals overlap in range, foraging patchesare likely to be subject to high levels of use, and may be sites

nferring spatial and temporal behavioral patterns of free-ranging014), http://dx.doi.org/10.1016/j.mambio.2014.07.003

of potential competition. Obtaining quantitative measures of fine-scale behavior is therefore the first step to evaluate the extent ofintra-specific resource competition (Hindell et al., 2002). Sirenians

Please cite this article in press as: Castelblanco-Martínez, D.N., et al., Inferring spatial and temporal behavioral patterns of free-rangingmanatees using saltwater sensors of telemetry tags. Mammal. Biol. (2014), http://dx.doi.org/10.1016/j.mambio.2014.07.003

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Table 3Numerical values assigned to discriminate behavior categories in tagged manatees. The values were obtained by creating scatter plots of each manatee data, in order toestablish behavioral types on individual-basis.

Manatee T Variable Behavior

Traveling Idling activities

Bottom resting Surface resting or feeding Bottom feeding

ID35-M 20D ≥1000 <1000 <1000 <1000N – <20 <20 ≥20TDD – ≥370 <370 ≥370

ID36-M 20D ≥1000 <1000 <1000 <1000N – <20 <20 ≥20TDD – ≥200 <200 ≥200

ID51-F 20D ≥1000 <1000 <1000 <1000N – <15 <15 ≥15TDD – ≥200 <200 ≥200

ID52-F 20D ≥1000 <1000 <1000 <1000N – <20 <20 ≥20TDD – ≥200 <200 ≥200

ID53-F 30D ≥1500 <1500 <1500 <1500N – <15 <15 ≥15TDD – ≥400 <400 ≥400

T = sampling interval in minutes, D = distance in meters, N = number of dives, TDD = total diving duration in seconds.

Fig. 4. Low, medium and high frequency of Bottom and Surface behaviors performed by tagged Antillean manatees in Chetumal Bay. Bottom activities were performedmainly in ‘City shore’ and ‘Lagoon’ habitats.

Table 4Geomorphologic and ecological characteristics of habitat types.

Habitat type Characteristics N (%) Depth (m)

Channel Relatively narrow body of water that cuts between mangrove islands, generally, there ismangrove shoreline on two sides*

1307 (18.6%) 0.76 ± 0.327

City shore Area in front of Chetumal City 1807 (25.8%) 0.823 ± 1.052Caye shore Areas surrounding emergent land features (islands or cayes) 307 (4.4%) 1.208 ± 0.771Chanel edge An area of deeper water that cuts through areas of shallower water* 1015 (14.5%) 1.058 ± 0.513Lagoon A large open water area separated from a larger body of water by channels 2548 (36.4%) 2.182 ± 1.641Open Encompasses the central area of Chetumal Bay, with a distance >2 km from any shore 19 (0.3%) 1.787 ± 1.277

N = number of fixes. The values of depth are given in mean ± standard deviation. Some fixes were excluded from the analysis, because the behavior was unknown. Descriptionswith an asterisk were adapted from LaCommare et al. (2008).

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ig. 5. Daily rhythm of bottom activities of five manatees in Chetumal Bay. D = 00:00–06:00) with periods C and D (in gray) roughly corresponding to dark dail

ften clearly make use of multiple, distinct, core habitats sepa-ated by areas apparently only used for traveling between themSheppard et al., 2006).

patial pattern of activities

Bottom behaviors can be interpreted as resting or feeding activ-ties. Manatees in Chetumal Bay are mainly seagrasses eatersCastelblanco-Martínez et al., 2009b), and it is plausible to assumehat bottom feeding could be driven by the presence and abun-ance of benthic plants. In the near area of Drowned Cayes (Belize),eagrass abundance was an important variable explaining the prob-bility of sighting a manatee (LaCommare et al., 2008). It is knownhat seagrasses, the main component of manatee diet, are foundn small, isolated patches along Chetumal Bay, representing only.07% of the total biomass of the ecosystem (Castelblanco-Martínezt al., 2012). When forage is only available in small, low densityatches, herbivores dedicate more time traveling among feedingites, which results in a low probability of encounter within theatches of vegetation and a dilution of the observed correlationBailey et al., 1996). Heithaus et al. (2006) stated that expected habi-at use under random movement is difficult to assess if resourcesre irregularly distributed and patchy, animals are tracked overelatively short periods, have ill-defined home ranges, or showirectional biases to their movements that are related to habi-at preference. Manatees in estuarine areas are supposed to beottom feeders, but, due to the low abundance of seagrasses inhetumal Bay, they might also forage on riparian vegetation, likeangrove (Castelblanco-Martínez et al., 2009b); and in this case

ottom behaviors not necessarily will be related to feeding activi-ies.

All manatees showed a “bottom” activity peak during, near and

Please cite this article in press as: Castelblanco-Martínez, D.N., et al., Imanatees using saltwater sensors of telemetry tags. Mammal. Biol. (2

fter noon, while surface activities were more frequent during theight and early morning. (Table 5). Our data indicate that the mana-ees showed more surface activities during the night, but we cannotetermine from our data whether the manatees were feeding,

ere stored in 6 h periods (A = 06:00–12:00; B = 12:00–18:00; C = 18:00–00 andes.

resting or socializing during those times. Though we did not rigor-ously test it because of the few animals in our data set, this diurnalpattern is evidence that manatee behavior is not random in time ashas been suggested in earlier publications (Bernier, 1985; Hartman,1979; Parker, 1922). Reynolds (1979) suggested that as manateeslack natural predators and have abundant food, they may spendtheir time feeding, resting and socializing in a random fashion. Inthe other hand, it has been found that dugongs (Dugon dugong)learn diurnal behavioral patterns in response to hunting or harass-ment (Anderson, 1981). Manatees in the Drowned Cayes (Belize)use resting holes more frequently during the day than at night(Bacchus et al., 2009), suggesting that manatees are more activeduring the night; so the authors hypothesized that manatees mightchange their behavioral state in response to approaching vessels.Therefore, the need of energy conservation in response to seasonalchanges in temperature, food availability or even hunting pressureor boating activity, can alter the lack of pattern (Miksis-Olds et al.,2007a,b). In Chetumal Bay, human pressures on manatees are rel-atively scarce, and more research is needed to clarify the origin ofthe suggested daily pattern of activities.

Depth selection

In general, Caribbean and Florida manatees have been reportedin waters shallower than 8 m (Áxis-Arroyo et al., 1998; de Thoisyet al., 2003; Hartman, 1979; Kochman et al., 1985; Morales-Velaet al., 2000; Olivera-Gómez and Mellink, 2005; Paludo, 1997),though this may be reflective of the available depth range wherethey are found rather than a preference. For instance, mana-tees have been spotted in Orinoco Basin in water depths of21.2 m, but probably only during movements between core areas(Castelblanco-Martínez et al., 2009a). Previous research in Chetu-

nferring spatial and temporal behavioral patterns of free-ranging014), http://dx.doi.org/10.1016/j.mambio.2014.07.003

mal Bay showed that habitat use is spatially and temporallyheterogeneous, with a preference for shallow water. However,those studies employed aerial (Morales-Vela et al., 1996; Morales-Vela and Olivera-Gómez, 1994; Olivera-Gómez and Mellink, 2002,

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Table 5Differences in bottom behavior frequency between daily segments (A = 06:00–12:00; B = 12:00–18:00; C = 18:00–00 and D = 00:00–06:00), when compared using aKruskal–Wallis one-way non-parametric analysis of variance (H), following by pairwise Mann–Whitney U-testing for multiple comparisons. Values with asterisk showed tobe significantly different (Bonferroni-corrected *p < 0.017, **p < 0.0033, ***p < 0.00033).

ID35-M ID36-M ID51-F ID52-F ID53-F

H = 30.97; p = 8.47E−07 H = 40.43; p = 6.059E−12 H = 41.78, p = 3.307E−09 H = 40.43, p = 8.604E−09 H = 17.34, p = 0.0002821A–B 0.3258 1.37E−06*** 0.8192 0.3671 0.04417A–C 7.04E−06*** 3.21E−07*** 4.68E−07*** 5.28E−07*** 0.001227*A–D 0.02629 1.39E−06*** 2.765E−04*** 4.82E−06*** 0.0001152***

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B–C 1.33E−05*** 7.85E−07*** 4.2B–D 0.03953 0.006172* 1.6C–D 0.02759 1.133E−04*** 0.0

005) and boat surveys (Áxis-Arroyo et al., 1998). In thoseases, statistical tests were performed only for the shallow zones<4.5 m), because manatees in deeper waters had lower detectabil-ty (Olivera-Gómez and Mellink 2002, 2005), suggesting that thereference for shallow water may have been confounded with aampling bias. In the present study, the same bias may be presents most of the GPS fix failures occurred when the manatees weren deeper water, most probably because the tags would be pullednderwater more often there. The addition of time–depth recordersn future tracked animals would address this potential bias thatccurs with current sampling methodologies.

ethodological constraints

Satellite tracking has proved successfully to document long-istance animal movements. However, once more detailed aspectsf animal behavior are considered, the location accuracy is likely toecome a much more important issue (Hays et al., 2001b). WhilePS loggers are routinely used for terrestrial and aerial animals

Steiner et al., 2000), tracking marine vertebrates with GPS log-ers can be more problematic. This is because infrequent surfacingehaviors limits the time when loggers are available for acquiringatellite signals (Schofield et al., 2007), therefore increasing the fixailure (Vincent et al., 2002). The limited available bandwidth ofhe Argos system severely constrains the amount of data that cane transmitted so that, for example, complete dive profiles cannotenerally be obtained for marine animals (Hays et al., 2001a). Ournalysis is limited to the coordinates’ acquisition, since positionsre needed to estimate distances between points, and conversely,o discriminate between traveling and idling behaviors. Fine-scalenalyses of manatee habitat use and movements may requireestricting the data set to the highest location quality or devel-ping new analytical techniques to incorporate locational error.dditionally, when a tagged manatee occupies shallow areas, satel-

ites are more likely to acquire coordinates because the housings frequently floating. An empirical approach is needed to deter-

ine if fine-scale behaviors in very shallow waters can reliably bedentified. By the other hand, when a manatee is undertaking aast traveling movement, the satellite housing is pulled horizon-ally through the water, and the underwater antenna is unable toommunicate with the satellites (Sheppard et al., 2006). Here, salt-ater switch data is used to infer diving behavior. An additionalroblem is the switch triggering without an actual dive (e.g. a waveashed over the tag). Evaluating and correcting biases affectingata collection is needed.

Argos system’s constraints have led to the use of artificialisplacements of animals carrying data loggers, rather than trans-itters, so that their behavior can be recorded in even more

etail as they travel (Webb et al., 1998). Archival time–depth

Please cite this article in press as: Castelblanco-Martínez, D.N., et al., Imanatees using saltwater sensors of telemetry tags. Mammal. Biol. (2

ecorders (Time–Depth Recorders, TDRs) are suitable for gather-ng large quantities of continuous dive-related behavioral datan air-breathing diving vertebrates. Interpreting dive data in aehavioral context requires identifying specific dive types (feeding,

*** 2.40E−05*** 0.04594*** 0.001248** 0.01723

0.01998 0.7738

traveling, interacting, etc.) based on dive profiles (Bodkin et al.,2007). For shallow marine mammals as sirenians, the use ofTDRs has been limited due to issues in the interpretation of data(Hagihara et al., 2009). However, improving TDR technologies anddata analysis could help in answering unresolved questions aboutmanatee behavior at very fine spatial level.

Acknowledgements

This research was funded by SEMARNAT-CONACyT (Project2002-C01-1128). CONACyT also provided Ph.D. funding for DNC-M.We thank Hilda Chavez for her valuable help in data processing, andto Holger Weissenberger and Laura Carrillo for helping in variousdatabase analyses.

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