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Spatial patterns of arctic sponge ground fauna and demersal fish are detectable in autonomous underwater vehicle (AUV) imagery. / Meyer, Heidi Kristina; Roberts, Emyr Martyn; Rapp, Hans Tore et al.
Yn: Deep Sea Research Part I: Oceanographic Research Papers, Cyfrol 153, Rhif 103137, 103137, 01.11.2019.

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HarvardHarvard

Meyer, HK, Roberts, EM, Rapp, HT & Davies, A 2019, 'Spatial patterns of arctic sponge ground fauna and demersal fish are detectable in autonomous underwater vehicle (AUV) imagery', Deep Sea Research Part I: Oceanographic Research Papers, cyfrol. 153, rhif 103137, 103137. https://doi.org/10.1016/j.dsr.2019.103137

APA

Meyer, H. K., Roberts, E. M., Rapp, H. T., & Davies, A. (2019). Spatial patterns of arctic sponge ground fauna and demersal fish are detectable in autonomous underwater vehicle (AUV) imagery. Deep Sea Research Part I: Oceanographic Research Papers, 153(103137), Erthygl 103137. https://doi.org/10.1016/j.dsr.2019.103137

CBE

Meyer HK, Roberts EM, Rapp HT, Davies A. 2019. Spatial patterns of arctic sponge ground fauna and demersal fish are detectable in autonomous underwater vehicle (AUV) imagery. Deep Sea Research Part I: Oceanographic Research Papers. 153(103137):Article 103137. https://doi.org/10.1016/j.dsr.2019.103137

MLA

VancouverVancouver

Meyer HK, Roberts EM, Rapp HT, Davies A. Spatial patterns of arctic sponge ground fauna and demersal fish are detectable in autonomous underwater vehicle (AUV) imagery. Deep Sea Research Part I: Oceanographic Research Papers. 2019 Tach 1;153(103137): 103137. Epub 2019 Hyd 10. doi: 10.1016/j.dsr.2019.103137

Author

Meyer, Heidi Kristina ; Roberts, Emyr Martyn ; Rapp, Hans Tore et al. / Spatial patterns of arctic sponge ground fauna and demersal fish are detectable in autonomous underwater vehicle (AUV) imagery. Yn: Deep Sea Research Part I: Oceanographic Research Papers. 2019 ; Cyfrol 153, Rhif 103137.

RIS

TY - JOUR

T1 - Spatial patterns of arctic sponge ground fauna and demersal fish are detectable in autonomous underwater vehicle (AUV) imagery

AU - Meyer, Heidi Kristina

AU - Roberts, Emyr Martyn

AU - Rapp, Hans Tore

AU - Davies, Andrew

PY - 2019/11/1

Y1 - 2019/11/1

N2 - Deep-sea sponge grounds are important habitats that provide several ecosystem services, yet relatively little is known about their distribution and ecology. While most surveys have focused on the broad-scale distribution patterns of sponge grounds (100s–1000s m), only rarely have the finer-scale (<10 m) spatial distribution patterns of the primary organisms been studied. In this study, the autonomous underwater vehicle (AUV) Hugin 1000 was used to map an area of an arctic sponge ground located on the summit of the Schulz Bank (Arctic Mid-Ocean Ridge), with the aim of detecting small-scale spatial patterns produced by the dominant megafauna. Using low-light cameras to construct a photomosaic comprising of 9,953 images and a virtual quadrat spatial sampling approach, density hotspots of the most prominent megafauna were visualized. The primary megafauna detected were demosponges, hexactinellids, ascidians, cnidarians, echinoderms, and demersal fish species. Most megafauna, like the primary structure-forming sponge species Geodia parva and Stelletta rhaphidiophora, were distributed evenly throughout the sample area, though species like Lissodendoryx (Lissodendoryx) complicata and Gersemia rubiformis displayed clear fine-scale spatial preferences. The three demersal fish species, Macrourus berglax, Reinhardtius hippoglossoides, and Amblyraja hyperborea, were uniformly distributed throughout the sample area. Based on the presence of skate egg cases and juveniles within many images, it is likely that the site is being used as a nursery ground for A. hyperborea. This study demonstrates the potential of using AUVs to detect fine-scale spatial patterns of the structure-forming sponges and demersal fish species. The use of AUVs for deep-water benthic surveys can help visualize how fauna (e.g. fish) utilise deep-sea habitats, and act as a tool for quantifying individuals through relatively unbiased means (e.g. pre-programmed track, no sampling). Such information is crucial for future conservation and management efforts.

AB - Deep-sea sponge grounds are important habitats that provide several ecosystem services, yet relatively little is known about their distribution and ecology. While most surveys have focused on the broad-scale distribution patterns of sponge grounds (100s–1000s m), only rarely have the finer-scale (<10 m) spatial distribution patterns of the primary organisms been studied. In this study, the autonomous underwater vehicle (AUV) Hugin 1000 was used to map an area of an arctic sponge ground located on the summit of the Schulz Bank (Arctic Mid-Ocean Ridge), with the aim of detecting small-scale spatial patterns produced by the dominant megafauna. Using low-light cameras to construct a photomosaic comprising of 9,953 images and a virtual quadrat spatial sampling approach, density hotspots of the most prominent megafauna were visualized. The primary megafauna detected were demosponges, hexactinellids, ascidians, cnidarians, echinoderms, and demersal fish species. Most megafauna, like the primary structure-forming sponge species Geodia parva and Stelletta rhaphidiophora, were distributed evenly throughout the sample area, though species like Lissodendoryx (Lissodendoryx) complicata and Gersemia rubiformis displayed clear fine-scale spatial preferences. The three demersal fish species, Macrourus berglax, Reinhardtius hippoglossoides, and Amblyraja hyperborea, were uniformly distributed throughout the sample area. Based on the presence of skate egg cases and juveniles within many images, it is likely that the site is being used as a nursery ground for A. hyperborea. This study demonstrates the potential of using AUVs to detect fine-scale spatial patterns of the structure-forming sponges and demersal fish species. The use of AUVs for deep-water benthic surveys can help visualize how fauna (e.g. fish) utilise deep-sea habitats, and act as a tool for quantifying individuals through relatively unbiased means (e.g. pre-programmed track, no sampling). Such information is crucial for future conservation and management efforts.

U2 - 10.1016/j.dsr.2019.103137

DO - 10.1016/j.dsr.2019.103137

M3 - Article

VL - 153

JO - Deep Sea Research Part I: Oceanographic Research Papers

JF - Deep Sea Research Part I: Oceanographic Research Papers

SN - 0967-0637

IS - 103137

M1 - 103137

ER -