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Setyawan, Edy

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Setyawan
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Edy
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    Data from: Residency and use of an important nursery habitat, Raja Ampat’s Wayag lagoon, by juvenile reef manta rays (Mobula alfredi)
    (2022-05-27) Setyawan, Edy; Mambrasar, Ronald; Sianipar, Abraham; Lewis, Sarah; Mofu, Imanuel; Ambafen, Orgenes; Izuan, Muhamad; Hasan, Abdi; Erdmann, Mark
    The behaviour and spatial use patterns of juvenile manta rays within their critical nursery habitats remain largely undocumented. Here, we report on the horizontal movements and residency of juvenile reef manta rays (Mobula alfredi) at a recently discovered nursery site in the Wayag lagoon, Raja Ampat, Indonesia. Using a multi-disciplinary approach, we provide further corroborative evidence that the lagoon serves as an important M. alfredi nursery. A total of 34 juvenile rays were photo-identified from 47 sightings in the sheltered nursery between 2013–2021. Five (14.7%) of these individuals were resighted for at least 486 days (~1.3 years), including two juveniles resighted after 641 and 649 days (~1.7 years), still using the nursery. Visually estimated (n=34) disc widths (DW) of juveniles using the nursery site ranged from 150–240 cm (mean ± SD: 199 ± 19), and the DW of two juveniles measured using drones were 218 and 219 cm. Five juveniles were tracked using GPS-enabled satellite transmitters for 12–69 days (mean ± SD: 37 ± 22) in 2015 and 2017, and nine juveniles were tracked using passive acoustic transmitters for 69–439 days (mean ± SD: 182 ± 109) from May 2019–September 2021. Satellite-tracked individuals exhibited restricted movements within Wayag lagoon. The minimum core activity space (50% Utilisation Distribution-UD) estimated for these five individuals ranged from 1.1–181.8 km2 and the extent of activity space (95% UD) between 5.3–1,195.4 km2 in area. All acoustically tagged individuals displayed high residency within the nursery area, with no acoustic detections recorded outside the lagoon in the broader Raja Ampat region. These juveniles were detected by receivers in the lagoon throughout the 24 h diel cycle, with more detections recorded at night and different patterns of spatial use of the lagoon between day and night. The observed long-term residency of juvenile M. alfredi provides further compelling evidence that the Wayag lagoon is an important nursery area for this globally vulnerable species. These important findings have been used to underpin the formulation of management strategies to specifically protect the Wayag lagoon, which will be instrumental for the survival and recovery of M. alfredi populations in Raja Ampat region.
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    Data from: Correcting for missing and irregular data in home-range estimation
    (2018-03-02) Setyawan, Edy; Sianipar, Abraham
    Home-range estimation is an important application of animal tracking data that is frequently complicated by autocorrelation, sampling irregularity, and small effective sample sizes. We introduce a novel, optimal weighting method that accounts for temporal sampling bias in autocorrelated tracking data. This method corrects for irregular and missing data, such that oversampled times are downweighted and undersampled times are upweighted to minimize error in the home-range estimate. We also introduce computationally efficient algorithms that make this method feasible with large datasets. Generally speaking, there are three situations where weight optimization improves the accuracy of home-range estimates: with marine data, where the sampling schedule is highly irregular, with duty cycled data, where the sampling schedule changes during the observation period, and when a small number of homerange crossings are observed, making the beginning and end times more independent and informative than the intermediate times. Using both simulated data and empirical examples including reef manta ray, Mongolian gazelle, and African buffalo, optimal weighting is shown to reduce the error and increase the spatial resolution of home-range estimates. With a conveniently packaged and computationally efficient software implementation, this method broadens the array of datasets with which accurate space-use assessments can be made.