Mar Biol DOI 10.1007/s00227-014-2478-7
Reliance of mobile species on sensitive habitats: a case study of manta rays (Manta alfredi) and lagoons Douglas J. McCauley · Paul A. DeSalles · Hillary S. Young · Yannis P. Papastamatiou · Jennifer E. Caselle · Mark H. Deakos · Jonathan P. A. Gardner · David W. Garton · John D. Collen · Fiorenza Micheli
Received: 10 December 2013 / Accepted: 14 June 2014 © Springer-Verlag Berlin Heidelberg 2014
Abstract Quantifying the ecological importance of individual habitats to highly mobile animals is challenging because patterns of habitat reliance for these taxa are complex and difficult to observe. We investigated the importance of lagoons to the manta ray, Manta alfredi, a wide-ranging and vulnerable species in a less-disturbed atoll ecosystem. Lagoons are highly sensitive to anthropogenic disturbance and are known to be ecologically important to a wide variety of mobile species. We used a novel combination of research tools to examine the reliance of M. alfredi on lagoon habitats. Stable isotope analysis was Communicated by C. Harrod. Douglas J. McCauley and Paul A. DeSalles have contributed equally to this work. Douglas J. McCauley was formerly in Hopkins Marine Station, Stanford University, Pacific Grove, CA 93950, USA. Electronic supplementary material The online version of this article (doi:10.1007/s00227-014-2478-7) contains supplementary material, which is available to authorized users. D. J. McCauley (*) · H. S. Young Department of Ecology, Evolution, and Marine Biology, University of California, Santa Barbara, CA 93106, USA e-mail: [email protected]
P. A. DeSalles · F. Micheli Hopkins Marine Station, Stanford University, Pacific Grove, CA 93950, USA Y. P. Papastamatiou School of Biology, University of St Andrews, St Andrews, Fife KY16 8LB, UK
used to assay the recent energetic importance of lagoons to M. alfredi; high-resolution tracking data provided information about how M. alfredi utilised lagoonal habitats over long and short time periods; acoustic cameras logged patterns of animal entrances and departures from lagoons; and photo identification/laser photogrammetry provided some insight into why they may be using this habitat. M. alfredi showed strong evidence of energetic dependence on lagoon resources during the course of the study and spent long periods of residence within lagoons or frequently transited into them from elsewhere. While within lagoons, they demonstrated affinities for particular structural features within this habitat and showed evidence of temporal patterning in habitat utilization. This work sheds light on how and why M. alfredi uses lagoons and raises questions about how this use may be altered in disturbed settings. More generally, these observations contribute to our knowledge of how to assess the ecological importance of particular habitats situated within the broader home range of mobile consumers.
M. H. Deakos Hawaii Association for Marine Education and Research, Inc., PMB#175 5095 Napilihau St. 109B, Lahaina, HI 96761, USA J. P. A. Gardner · J. D. Collen Centre for Marine Environmental and Economic Research, Victoria University of Wellington, Wellington 6012, New Zealand D. W. Garton School of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA
J. E. Caselle Marine Science Institute, University of California, Santa Barbara, CA 93106, USA
Introduction Mobile animals have been heavily impacted by anthropogenic activity in both terrestrial (e.g., wolves, mountain lion, African wild dog) and marine settings (e.g., whales, sharks, tuna) (Noss et al. 1996; Myers and Worm 2003; Terborgh and Estes 2010). Because they range across multiple habitats and even regularly traverse political jurisdictions, mobile animals are often at high risk of encountering and deleteriously interacting with humans (Woodroffe and Ginsberg 1998) and it is challenging to manage threats to such species in these spatially expansive regions using tools from conventional conservation policy (Techera and Klein 2011). It is sometimes assumed that anthropogenic effects that are confined to discrete habitats have little effect on mobile animals (as opposed to sessile or low-vagility taxa) because these taxa have the capacity to transit out of these affected habitats and concentrate activities in less perturbed habitats within their home range (Debinski and Holt 2000). Such assumptions would be erroneous, however, in instances where impacted habitats are disproportionately important to a mobile species. Thus, an important part of understanding how human pressure affects mobile species requires determining how mobile taxa use and rely upon the various habitats that they may traverse. This task is made difficult, however, because detailed descriptions of the habitat dependency patterns of mobile fauna are often lacking (Block et al. 2001, 2011; Ferraroli et al. 2004; James et al. 2005), particularly in marine settings where mobile study subjects are especially difficult to observe and enumerate (McCauley et al. 2012b). Here, we use a diverse set of tools to construct a comprehensive description of the ecological dependency of the large, mobile, and vulnerable manta ray (Manta alfredi) on a particularly sensitive habitat—atoll lagoon ecosystems (Amerson and Shelton 1976; Collen et al. 2009). Manta alfredi and other mobulids are capable of long-range movements (e.g., >100 km; Homma et al. 1997; Dewar et al. 2008; Luiz et al. 2009; Couturier et al. 2011; Graham et al. 2012; Braun et al. 2014) and have been observed in a variety of marine habitats, including lagoons. There is little available information, however, on the relative importance of specific habitats to manta rays and no information, to our knowledge, on their potential utilization of lagoons. Manta alfredi is classified by the IUCN as a Vulnerable species (Marshall et al. 2011a, b). There is uncertainty about how anthropogenic pressures (e.g., coastal development, harvesting) are affecting this species and where the majority of these negative interactions are occurring. The sheltered and readily accessible waters of lagoons are areas of concentrated and elevated human activity (e.g., fishing, boat traffic, pollution) (Blumenthal et al. 2010) and as such may be high-risk habitat for manta rays. Other highly mobile marine consumers are known to be
ecologically linked to lagoons in important ways; e.g., reef sharks (Economakis and Lobel 1998; Papastamatiou et al. 2009a); sea turtles (Mendonca and Ehrhart 1982); spinner dolphins (Karczmarski et al. 2005). The hypothesized uses of this vulnerable habitat by these particular species include suggestions that lagoons serve as thermal refuges, nursery or resting habitat, predator refuges, or that they provide valuable foraging opportunities. Determining how often and for what purposes Manta alfredi utilizes lagoons would help evaluate whether targeted management actions are necessary to protect them in these sensitive habitats. In this study, we used Palmyra Atoll—a remote coral reef ecosystem—to investigate how M. alfredi uses and relies upon lagoon habitats. While the lagoons of Palmyra were heavily altered between 1940 and 1945 during military occupation of the atoll (Collen et al. 2009), their relative insulation from disturbance in the last six decades, the steady breakdown of military-era anthropogenic modifications, and the atoll’s current status as a wildlife reserve have helped the lagoons become an important refuge for many large marine fish (McCauley et al. 2010; Papastamatiou et al. 2010). As such, they provide an excellent opportunity to study how M. alfredi uses lagoon habitats in the absence of human activity and to assess the importance of carefully managed lagoons to this species. At Palmyra, we endeavored to determine: (1) what proportion of its resources M. alfredi draws from lagoons during the time frame of our study; (2) how M. alfredi uses space (vertically and horizontally) in lagoons; (3) if these patterns vary between individuals and across temporal/physical boundaries; and (4) which sizes and sexes of M. alfredi are the most frequent users of this habitat. We used four main tools to answer these questions at Palmyra: stable isotopes, active and passive animal tracking, acoustic imaging, and photo identification/laser photogrammetry. To our knowledge, these diverse research methods have never been utilized together in a single study and they collectively contribute an integrative view of M. alfredi reliance on lagoons. The temporal scope of these data collection methods varied from 1 month to >1 year, necessitating that we focus on short-term facets of the relationship between M. alfredi and lagoon use. Our aim was not to provide a cross-seasonal portrait of habitat utilisation within lagoons, but rather to provide a snapshot assessment of the importance of these spatially discrete habitats for this wide-ranging species.
Materials and methods Study area Palmyra Atoll (5°53′N, 162°05′W) is located in the Northern Line Islands of the central Pacific Ocean. The atoll’s
lagoons and surrounding waters have been protected as a US National Wildlife Refuge since 2001, and the take of all marine organisms is prohibited within the refuge. Palmyra hosts only a low-impact research station. The atoll has three main lagoon basins: West, Center (3.37 km2, area of both basins combined), and East (1.12 km2) lagoon. West and Center lagoons are functionally similar with negligible physical separation between basins and so were grouped as West-Center lagoon hereafter. West-Center and East lagoon are largely separated from each other by a man-made causeway (constructed in 1943) with six narrow breaks (3–22 m wide, each of variable depth) (Collen et al. 2009). West-Center lagoon is directly connected to the open ocean by a channel that is a maximum of approximately 80 m wide and 8 m deep. Other much shallower and smaller reef passages provide additional, albeit less significant open ocean connections in both lagoon basins. Depths in West-Center and East lagoons do not exceed 60 m and 50 m, respectively (NOAA 2006). Energetic reliance of M. alfredi on lagoons We used stable isotopes to investigate the energetic dependency of M. alfredi on lagoon habitats. We assumed that manta rays feed on plankton in either of two source environments: lagoons or offshore waters. We collected zooplankton samples from surface waters in both of these source locations [lagoon n = 12; offshore (i.e., 1–5 km offshore of forereef) n = 21] using a 50-μm plankton net, with catch samples post-filtered through 250-μm sieves. Isotope ratios of nitrogen (n = 33), carbon (n = 33), and sulfur (n = 19) were measured in lagoon and offshore zooplankton samples. We then similarly analyzed muscle tissue collected from M. alfredi using biopsy poles in the lagoon (n = 5), the main channel connecting the lagoon to offshore waters (n = 15), and in offshore waters (2–5 km offshore of forereef, n = 6). Isotope samples were collected at multiple time points from September 2007 to August 2011 and multiple locations, but were pooled for analysis. We used twosource Bayesian isotope mixing models (mixSIR v.1.0.4) to estimate the probable contribution of lagoon and offshore zooplankton to the diet of (1) manta rays sampled inside the lagoons and in the lagoon channel and (2) manta rays sampled offshore (Moore and Semmens 2008; see Appendix S1 for details of mixing model). Relationships between manta rays’ isotope signatures (lagoon + channel manta rays only) and their size (disk width) and sex were examined for individuals for which these data were available. Spatial utilization of lagoon habitats by M. alfredi We used active acoustic tracking to determine how manta rays spatially utilize lagoon habitats. M. alfredi (n = 11)
were tagged and tracked with V16 acoustic transmitters (Vemco, Nova Scotia, Canada) in West-Center and East lagoon from June 6, 2009, to August 9, 2009. Tagged manta rays were detected using a directional hydrophone (Vemco VR110) connected to an acoustic receiver (Vemco VR100). Continuous tracking of manta rays was conducted by following tagged individuals in a small vessel and recording their positions with GPS every 5 min. During tracking, we maintained an estimated 5–25 m distance behind tagged subjects, but before recording their location, we would direct the boat into the last position occupied by the animal at the end of each sampling interval. Manta ray movement and behavior did not appear to be influenced by the presence of the vessel at these distances. Manta rays were tracked continuously during daytime and nighttime hours. If an animal was lost or departed the lagoon, tracking was resumed upon subsequent detection. Although manta rays did not display any observable differences in behavior directly after tagging, we omitted the first 30 min of tracking data to conservatively account for the possible influence of tagging stress on their movement. All track analysis was performed in ArcGIS version 10 and ArcView version 3.3 (Esri, CA, USA) using the Animal Movement Analyst Extension (Hooge and Eichenlaub 2000). Although some animals were tracked offshore, all tracking and associated analysis reported upon herein refer to properties of M. alfredi movement within Palmyra’s lagoon system where the majority of active tracking took place. As a complement to active acoustic tracking, we tagged 18 M. alfredi with V13 acoustic transmitters (Vemco, Nova Scotia, Canada) and monitored their locations using an array of 58 VR2W acoustic receivers positioned inside and outside the lagoon (i.e., on the forereef). For complete details of the array see Papastamatiou et al. (2010) and Pedersen and Weng (2013). Passive acoustic tags were deployed between September 2010 and August 2011 and were monitored continuously until the cessation of detections. Below, we describe five types of data gathered from active and passive tracking data used to characterize the spatial utilization of lagoons by manta rays. Activity space size To estimate the size of the activity space of manta rays actively tracked within the lagoons, we calculated kernel utilization distributions (KUDs) for all active-tracked individuals (Seaman and Powell 1996, Fig. S1). We report both 50 % KUD (i.e., core activity space) and 95 % KUD (i.e., total activity space) of these animals. Because only within-lagoon movement data were used to calculate these KUDs, these metrics exclusively describe the size of manta ray activity space inside lagoons. Habitat utilization We used selection indices to quantify the preference of active-tracked manta rays for different habitat types within the lagoons. We used bathymetric
maps (NOAA 2006) and satellite imagery to partition lagoon space that was physically accessible to manta rays into seven discrete types: deep water, ledges, subsurface mounts, subsurface mount borders, coastal subtidal flats, terrace coastline, and coral flats (see Appendix S2 and Fig. S2 for details). We tested the null hypothesis that individual manta rays used a habitat type within the lagoons in proportion to its availability using a chi-square goodness-of-fit test (Morrissey and Gruber 1993). Percent utilization of the different parts of lagoons was defined as: number of tracking points within a given lagoon habitat type/total number of points recorded. We restricted this analysis to the area within the confines of an individual’s 95 % KUD. Percent availability of the seven lagoon habitat types was thus calculated as: area that each habitat type occupied within the 95 % KUD/total 95 % KUD area. If the null hypothesis was rejected for an animal’s habitat utilization, we employed the modified Strauss linear index of food selection (L = ri − pi) to quantify lagoon habitat type selection; where L is the habitat type selection value, ri is the percent use of habitat type and pi is the percent availability of the habitat type (Morrissey and Gruber 1993). Positive selection values (L) for a particular habitat type indicate selection, negative values indicate avoidance, and zero values indicate random use of that habitat type. Depth To characterize vertical movement behavior, we fitted two of the eleven tagged animals with acoustic tags (Vemco V16P) that included a built-in pressure/depth sensor (max. depth rating 136 m). One individual was depthtagged in each of the West-Center and East lagoons. In situ testing of the tags prior to deployment indicated that instrument sensitivity limits required that all depth values 0–5 m be binned together. Depth data were recorded during active follows with position every 5 min. Diel changes in lagoon utilization To quantify diel changes in manta ray space use, we analyzed differences in activity space size and depth profiles across periods of daytime (0620–1930 h) and nighttime (1930–0620 h); boundaries were determined using defined cutoffs for dawn and dusk. Movement patterns between different marine habitats To examine rates and patterns of M. alfredi movement between the lagoon and offshore environment, we used a dual-frequency identification sonar (DIDSON 300; Sound Metrics Corp., WA, USA) to detect manta rays as they passed through the main channel that connects Palmyra’s West-Center lagoon to offshore habitats (Fig. S3). The device uses sonar to generate high-resolution digital images of animals traveling within the instrument’s sensor field (Belcher et al. 2002). The unit was installed in the midpoint of the channel at 3 m depth and set to visualize a 41.7-m3
section of water extending across the width of the channel. While range limitations prevented us from monitoring the entire channel width using the DIDSON, the area visualized was sufficiently large so as to provide an accurate depiction of animal movement through this key interhabitat transit zone. The DIDSON recorded footage for approximately 9.5 h per session and was operated nearly continuously from July 2, 2009, to July 29, 2009, and as such provides provisional insight into M. alfredi utilization of the lagoons during this 1-month period. We calculated the number of manta rays m−3 min−1 in the view area of the instrument as well as the directionality of animal movement (i.e., traveling into or out of the lagoons). We were unable to differentiate individuals among the animals that were detected. From these data, we compared the total number of sightings of manta rays entering and exiting the lagoons during four diel periods (dawn, day, dusk, night) and four tidal periods (ebb, flow, high slack, low slack); see Appendix S4 for period definitions. Characteristics of the M. alfredi population using lagoon habitats We used photo identification and laser photogrammetry to gather preliminary demographic information on the population of M. alfredi utilizing the lagoons at Palmyra, as well as to investigate longer term patterns of manta ray site fidelity to these lagoons. Images were taken using a camera coupled with paired, calibrated lasers during haphazardly conducted underwater surveys of lagoon, channel, and offshore habitats from June 7, 2010, to September 7, 2010. From each photographic record, we attempted to record the size (disk width), sex, and when possible, identity of each animal (from distinct dorsal and ventral patterning) (Deakos 2010; Fig. S4). The mean size of animals sighted in channel and offshore environments was compared against those observed within the lagoons. Statistical analysis Comparisons of focal properties of M. alfredi ecology were made using two-way parametric (Student’s t tests: East vs. West-Center lagoons 50 and 95 % KUD size, stable isotope comparisons) and nonparametric comparisons [Wilcoxon tests: diel 50 % and 95 % KUD size (paired), diel depths, and manta ray size]. Parametric statistics were applied only in instances where the assumptions of these parametric tests (e.g., normality) were met by the data. In instances where multiple points of comparison were required (DIDSON diel and tidal comparisons), data were analyzed using nonparametric Kruskal–Wallis tests with post hoc Holm’s sequential Bonferroni corrections. Linear regressions were used to examine the relationships between the isotopic
signatures of manta rays and their size. All tests were performed using the statistical software R (R Development Core Team 2013).
Results Energetic reliance of M. alfredi on lagoons Zooplankton collected in lagoon and offshore environments were isotopically distinct from one another both in terms of δ15N (t30.3 = 3.8, P