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      Home sweet home: spatiotemporal distribution and site fidelity of the reef manta ray ( Mobula alfredi) in Dungonab Bay, Sudan

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          Abstract

          Background

          Reef manta ray ( Mobula alfredi) populations along the Northeastern African coastline are poorly studied. Identifying critical habitats for this species is essential for future research and conservation efforts. Dungonab Bay and Mukkawar Island National Park (DMNP), a component of a UNESCO World Heritage Site in Sudan, hosts the largest known M. alfredi aggregation in the Red Sea.

          Methods

          A total of 19 individuals were tagged using surgically implanted acoustic tags and tracked within DMNP on an array of 15 strategically placed acoustic receivers in addition to two offshore receivers. Two of these acoustically monitored M. alfredi were also equipped with satellite linked archival tags and one individual was fitted with a satellite transmitting tag. Together, these data are used to describe approximately two years of residency and seasonal shifts in habitat use.

          Results

          Tagged individuals were detected within the array on 96% of monitored days and recorded an average residence index of 0.39 across all receivers. Detections were recorded throughout the year, though some individuals were absent from the receiver array for weeks or months at a time, and generalized additive mixed models showed a clear seasonal pattern in presence with the highest probabilities of detection occurring in boreal fall. The models indicated that M. alfredi presence was highly correlated with increasing chlorophyll-a levels and weakly correlated with the full moon. Modeled biological factors, including sex and wingspan, had no influence on animal presence. Despite the high residency suggested by acoustic telemetry, satellite tag data and offshore acoustic detections in Sanganeb Atoll and Suedi Pass recorded individuals moving up to 125 km from the Bay. However, all these individuals were subsequently detected in the Bay, suggesting a strong degree of site fidelity at this location.

          Conclusions

          The current study adds to growing evidence that M. alfredi are highly resident and site-attached to coastal bays and lagoons but display seasonal shifts in habitat use that are likely driven by resource availability. This information can be used to assist in managing and supporting sustainable ecotourism within the DMNP, part of a recently designated UNESCO World Heritage Site.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s40462-022-00314-9.

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          Most cited references76

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          The package “adehabitat” for the R software: A tool for the analysis of space and habitat use by animals

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            Prey Uncertainty and the Balancing of Antipredator and Feeding Needs

            Andrew Sih (1992)
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              Persistent Leatherback Turtle Migrations Present Opportunities for Conservation

              Introduction Leatherback turtles (Dermochelys coriacea) in the eastern Pacific (EP) have exhibited population declines of up to 90% during the past two decades [1,2]. These declines have been driven by a number of factors, including incidental mortality in fisheries, loss of nesting habitats, and unsustainable egg harvest [1,3]. Of the extant leatherback nesting beaches in the EP, Playa Grande in Parque Nacional Marino Las Baulas (PNMB), Costa Rica, supports the largest nesting colony [1]. After the nesting period (approximately 60 d), EP leatherbacks perform long-distance migrations from breeding areas to feeding areas, where they remain for 2 to 7 y [4]. Therefore, while protection of nesting habitat is important to enhance recruitment into the population, an improved understanding of the at-sea distribution and movements of EP leatherbacks is vital to ensuring their long-term survival. In particular, long-range tracking studies using electronic tags can inform conservation efforts by identifying high-use areas for leatherbacks in time and space, as well as environmental influences on leatherback behavior [5]. Leatherback turtles globally undertake long-distance migrations over thousands of kilometers [6–14]. Morreale et al. [6] first described the movements of EP leatherbacks from the tracks of eight turtles (durations 3–87 d) and identified a persistent southbound migration corridor from PNMB toward the Galápagos Islands. Additional tagging efforts at a nesting beach in Mexiquillo, México, about 965 km north of Costa Rica, revealed that leatherbacks traveled routes that shared the same directional heading and general high seas habitats in the eastern South Pacific as those traveled by Costa Rican turtles [7]. In contrast, leatherbacks from other populations demonstrate inter-individual behavioral variation with respect to post-nesting migration routes [8–10,13,14]. The apparent persistence of the EP leatherback migration pattern provides a unique opportunity to generate a cohesive conservation management approach for this endangered population. Conservation of highly migratory marine species requires international cooperation for implementation of transboundary management strategies. Specifically, information on movements and distributions of large marine predators collected by electronic tracking devices can provide guidance to the development of national and multinational fisheries management strategies and bycatch mitigation efforts, as well as support related policy efforts [15]. One such framework is the Eastern Tropical Pacific Seascape (ETPS) initiative [16], which is a multinational coordination of marine resource management within the combined exclusive economic zones of Costa Rica, Panama, Colombia, and Ecuador. The ETPS is an area that is home to several marine protected areas (MPAs) (e.g., PNMB) and World Heritage sites (e.g., Cocos Island, Coiba Island National Park, Malpelo Island, Galápagos Islands and Marine Reserve). Thus, the ETPS represents a framework through which habitat use and movement data for migratory animals, such as leatherbacks, can be translated into tangible management actions. Here we present the largest multi-year tracking data set collected for this species, based on 46 individuals satellite-tagged during 2004–2007 at PNMB. Our approach is consistent with a recent review [17], which emphasized the importance of tracking large sample sizes and an interdisciplinary approach integrating oceanographic cues with behavior. These data enabled us to (1) describe the distribution and horizontal movements of leatherbacks in the EP, (2) examine the influence of oceanic currents on leatherback migrations, (3) assess leatherback high-use habitats, (4) confirm and elucidate a leatherback migration corridor from the nesting beach to 5 °S, and (5) describe leatherback movements beyond 10 °S into the South Pacific. In addition, these data identify critical areas for directed conservation efforts to ensure the survival of this species in the EP. Results We tagged 46 female leatherback turtles during oviposition, resulting in 12,095 tracking days spanning 21 January 2004–5 July 2007, with a mean track duration of 263 d, a distance of 8,070 km, and a travel speed of 37.7 km d−1 (Table 1). Movements by cohorts from a given year displayed cohesion, even though initiation of the post-nesting migration among individuals differed by up to several weeks (Figure 1). Only one individual tagged in 2005 (tag ID 56280) remained in coastal waters off Costa Rica and Panama for the entire tag duration (Figure 1A). Table 1 Tracking Data from 46 Satellite-Linked Tags Deployed on Leatherback Turtles on Playa Grande, Costa Rica, 2004–-2007 Figure 1 Map and Timeline of Leatherback Sea Turtle Tracking Data (A) Satellite transmission positions for 46 leatherback turtles from 2004 (n = 27, orange), 2005 (n = 8, purple), and 2007 (n = 11, green), tagged at Playa Grande, Costa Rica, overlaid on bathymetry (in m). Prominent bathymetric features and island groups are labeled (EPR = East Pacific Rise). (B) Timeline of satellite transmissions for each tag (tag ID is the ARGOS-assigned transmitter number). Upon completion of nesting activity, leatherbacks embarked on rapid (42.9 km d−1, standard deviation (sd) = 27.7 km d−1) directed southward migrations through the equatorial region. Once south of 5 °S, the turtles dispersed throughout the South Pacific Gyre following slower (23.8 km d−1, sd = 16 km d−1), meandering paths, and remained there through the duration of the tracking period (Figure 2A–2C). Across their migrations, turtles experienced a wide range of surface temperatures (11.2–32.7 °C, mean = 25.2 °C, sd = 3.2 °C; Table 1). They encountered areas of high–eddy kinetic energy (EKE) in the equatorial region (>100 cm2s−2), and areas of very low EKE ( 0.3 mg m−3), and lowest in the South Pacific Gyre ( + ). These calculations were performed separately for the February–April period of each tracking year, since the emphasis was on assessing the impact of inter-annual variability in geostrophic current strength on turtle migration while crossing the equatorial region. On the other hand, we computed EKE as a long-term mean for the period 14 October 1992–18 April 2007 from the mean geostrophic velocity anomalies (u′ and v′), as EKE = 0.5*( + ). In this case, the emphasis was on examining turtle distribution in relation to a region of low mesoscale variability in the South Pacific Gyre. Phytoplankton CHL concentration. The distribution of phytoplankton standing stock is a useful indicator of biogeography and ecosystem structure [24]. Near-surface CHL concentration, a proxy for phytoplankton standing stock, was obtained from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) satellite ocean-color observations at 9-km resolution. We computed a long-term mean for the period September 1997–March 2007 for comparison of turtle movements in relation to phytoplanktonic biomass distribution throughout their range. Individual 8-d averages were also obtained for each turtle median daily position. The relationship between CHL and the turtles' median daily speed was investigated using linear regression, after log- and square-root-transformation, respectively, to meet normality assumptions. Digital bathymetry. We extracted bathymetry from the global sea-floor topography of Smith and Sandwell [52], version 8.2 (November 2000) (http://topex.ucsd.edu/WWW_html/mar_topo.html). This dataset combines all available depth soundings with high-resolution marine gravity information provided by the Geosat, ERS-1/2, and TOPEX/Poseidon satellite altimeters, and has a nominal resolution of 2 arc min (∼4 km). The 2000-m isobath was extracted from this dataset to obtain the outline of the Cocos Ridge, the most prominent bathymetric feature in the migration corridor region (12 °N–5 °S) running northeast (∼43° azimuth) for ∼1,200 km between Galápagos and Central America. Geomagnetism. Data on Earth's magnetic field (force and inclination) in the study area were calculated using the software GeoMag 6.0, available from the NOAA National Geophysical Data Center (http://www.ngdc.noaa.gov/seg/geom_util/geomutil.shtml), and the most recent (2005) International Geomagnetic Reference Field 10th generation (IGRF-10) coefficients. Supporting Information Figure S1 Surface Currents and Vertical Thermal Structure in the Eastern Tropical and South Pacific Schematic representation of near-surface currents and vertical thermal structure in the eastern tropical and South Pacific, based on climatological annual data. (A) Current vectors (black) overlaid on current magnitude (colors; in cm s−1). Dashed black line denotes subsurface flow; dashed white line indicates a section along 95 °W. (B) Surface zonal (black arrows) and meridional (orange arrows) velocities (in cm s−1) along 95 °W. (C) Water-column temperature (colors; in °C) and the 15, 20, and 25 °C isotherms (black contours) along 95 °W. Zonal currents are represented as encircled x's for westward flows and encircled dots for eastward flows. Abbreviations are defined in the text. (2.57 MB TIF) Click here for additional data file. Text S1 Currents and Thermal Structure of the Eastern Tropical and South Pacific (29 KB DOC) Click here for additional data file.
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                Author and article information

                Contributors
                anna.knochel@kaust.edu.sa
                Journal
                Mov Ecol
                Mov Ecol
                Movement Ecology
                BioMed Central (London )
                2051-3933
                28 April 2022
                28 April 2022
                2022
                : 10
                : 22
                Affiliations
                [1 ]GRID grid.45672.32, ISNI 0000 0001 1926 5090, Red Sea Research Center, Division of Biological and Environmental Science and Engineering, , King Abdullah University of Science and Technology, ; Thuwal, 23955 Kingdom of Saudi Arabia
                [2 ]GRID grid.267455.7, ISNI 0000 0004 1936 9596, Department of Integrative Biology, , University of Windsor, ; 401 Sunset Avenue, Windsor, ON Canada
                [3 ]Equipe Cousteau, Paris, France
                [4 ]GRID grid.448406.a, ISNI 0000 0000 9957 9219, Daniel P. Haerther Center for Conservation and Research, , John G. Shedd Aquarium, ; Chicago, IL 60605 USA
                [5 ]GRID grid.56466.37, ISNI 0000 0004 0504 7510, Biology Department, , Woods Hole Oceanographic Institution, ; Woods Hole, MA 02543 USA
                [6 ]The Deep Aquarium, Hull, UK
                [7 ]Wildlife Conservation General Administration, Port Sudan, Sudan
                Author information
                http://orcid.org/0000-0002-7396-4586
                Article
                314
                10.1186/s40462-022-00314-9
                9052681
                35484613
                8cb3fc4f-e4da-43fb-9f92-aae672d4a0f8
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 16 January 2022
                : 16 March 2022
                Funding
                Funded by: The Deep Aquarium
                Award ID: 00176
                Award Recipient :
                Funded by: The Darwin Initiative
                Award ID: 21-019
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100004052, King Abdullah University of Science and Technology;
                Award ID: Baseline Funding
                Award Recipient :
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                © The Author(s) 2022

                mobula alfredi,movement ecology,sudan,acoustic telemetry,conservation,red sea

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