Predicting mobulid ray distribution in coastal areas of Lesser Sunda Seascape: Implication for spatial and fisheries management

作者: I. Putra , M.I.H. , Setyawan , E. , Laglbauer

DOI: 10.1016/J.OCECOAMAN.2020.105328

关键词: GeographyInternational watersFisherySeascapeFisheries managementHabitatSubmarine pipelinePredationMultiple dataSpatial distribution

摘要: Abstract The Lesser Sunda Seascape (LSS) is considered one of the regions with largest mobulid fisheries in Indonesia, although their spatial distribution and habitat preference LSS still largely unknown. goal present study was to describe oceanic manta rays, spinetail devil Chilean rays coastal area LSS. We used multiple data sources ray sightings selected significant environmental predictors execute maximum entropy model. model performed well predicting indicated that sea-surface chlorophyll-a (SSC-a), temperature (SST), salinity (SSS), distance 200-m isobath, 3000-m slope were all distribution. This confirms areas close isobath higher concentration as proxy for prey density. Combining models activity records where these overlaps may represent key habitats. highlights a critical need species-specific populations-level management measures Indonesian whereas current MPA design has focused on broad-scale ecosystem approach, which have limited effectiveness practice. provides valuable information improvement tools, through modeling powerful means species’ distributions preference. recommend future efforts focus documenting incorporating from large-scale commercial improve our knowledge offshore high seas, assess versus

参考文章(91)
Ana Hacohen-Domené, Raúl O. Martínez-Rincón, Felipe Galván-Magaña, Natalí Cárdenas-Palomo, Rafael de la Parra-Venegas, Beatriz Galván-Pastoriza, Alistair D. M. Dove, Habitat suitability and environmental factors affecting whale shark (Rhincodon typus) aggregations in the Mexican Caribbean Environmental Biology of Fishes. ,vol. 98, pp. 1953- 1964 ,(2015) , 10.1007/S10641-015-0413-5
Janet Franklin, Jennifer A. Miller, Mapping Species Distributions: Spatial Inference and Prediction ,(2010)
T.R Jarnevich, C.S., Stohlgren, T.J., Kumar, S., Morisette, J.T., and Holcombe, Caveats for correlative species distribution modeling Ecological Informatics. ,vol. 29, pp. 6- 15 ,(2015) , 10.1016/J.ECOINF.2015.06.007
Karina Bohrer do Amaral, Diego J Alvares, Larissa Heinzelmann, Márcio Borges-Martins, Salvatore Siciliano, Ignacio B Moreno, None, Ecological niche modeling of Stenella dolphins (Cetartiodactyla: Delphinidae) in the southwestern Atlantic Ocean Journal of Experimental Marine Biology and Ecology. ,vol. 472, pp. 166- 179 ,(2015) , 10.1016/J.JEMBE.2015.07.013
Dharmadi, Fahmi, F Satria, Fisheries management and conservation of sharks in Indonesia African Journal of Marine Science. ,vol. 37, pp. 249- 258 ,(2015) , 10.2989/1814232X.2015.1045431
Richard G. Pearson, Christopher J. Raxworthy, Miguel Nakamura, A. Townsend Peterson, Predicting species distributions from small numbers of occurrence records: A test case using cryptic geckos in Madagascar Journal of Biogeography. ,vol. 34, pp. 102- 117 ,(2006) , 10.1111/J.1365-2699.2006.01594.X
Ana Sequeira, Camille Mellin, David Rowat, Mark G. Meekan, Corey J. A. Bradshaw, Ocean-scale prediction of whale shark distribution Diversity and Distributions. ,vol. 18, pp. 504- 518 ,(2012) , 10.1111/J.1472-4642.2011.00853.X
ALISTAIR J. HOBDAY, JASON R. HARTOG, TRENT TIMMISS, JOSH FIELDING, Dynamic spatial zoning to manage southern bluefin tuna (Thunnus maccoyii) capture in a multi‐species longline fishery Fisheries Oceanography. ,vol. 19, pp. 243- 253 ,(2010) , 10.1111/J.1365-2419.2010.00540.X
Sarah A Lewis, Naneng Setiasih, Fahmi, Dharmadi Dharmadi, Mary P O'Malley, Stuart J Campbell, Muhammad Yusuf, Abraham B Sianipar, Assessing Indonesian manta and devil ray populations through historical landings and fishing community interviews PeerJ Inc.. ,(2015) , 10.7287/PEERJ.PREPRINTS.1334V1