Variation in the biomass density and demography of Antarctic krill in the vicinity of the South Shetland Islands during the 1999/2000 austral summer

2004 ◽  
Vol 51 (12-13) ◽  
pp. 1411-1419 ◽  
Author(s):  
R HEWITT ◽  
S KIM ◽  
M NAGANOBU ◽  
M GUTIERREZ ◽  
D KANG ◽  
...  
2013 ◽  
Vol 160 (6) ◽  
pp. 1311-1323 ◽  
Author(s):  
Michael J. Polito ◽  
Christian S. Reiss ◽  
Wayne Z. Trivelpiece ◽  
William P. Patterson ◽  
Steven D. Emslie

Polar Biology ◽  
1995 ◽  
Vol 15 (1) ◽  
Author(s):  
Jun Nishikawa ◽  
Mikio Naganobu ◽  
Taro Ichii ◽  
Haruto Ishii ◽  
Makoto Terazaki ◽  
...  

2013 ◽  
Vol 70 (2) ◽  
pp. 131-140 ◽  
Author(s):  
LM Olsen ◽  
MV Ardelan ◽  
CD Hewes ◽  
O Holm-Hansen ◽  
C Reiss ◽  
...  

Drones ◽  
2019 ◽  
Vol 3 (2) ◽  
pp. 39 ◽  
Author(s):  
Pfeifer ◽  
Barbosa ◽  
Mustafa ◽  
Peter ◽  
Brenning ◽  
...  

Antarctic marine ecosystems undergo enormous changes, presumably due to climate change and fishery. Unmanned aerial vehicles (UAVs) have an unprecedented potential for measuring these changes by mapping indicator species such as penguins even in remote areas. We used a battery-powered fixed-wing UAV to survey colonies along a 30-km stretch of the remote coast of southwest King George Island and northwest Nelson Island (South Shetland Islands, Antarctica) during the austral summer 2016/17. With multiple flights, we covered a total distance of 317 km. We determined the exact position of 14 chinstrap penguin colonies, including two small unknown colonies, with a total abundance of 35,604 adults. To model the number of occupied nests based on the number of adults counted in the UAV imagery we used data derived from terrestrial time-lapse imagery. The comparison with previous studies revealed a decline in the total abundance of occupied nests. However, we also found four chinstrap penguin colonies that have grown since the 1980s against the general trend on the South Shetland Islands. The results proved the suitability of the use of small and lightweight fixed-wing UAVs with electric engines for mapping penguin colonies in remote areas in the Antarctic.


2008 ◽  
Vol 65 (4) ◽  
pp. 497-508 ◽  
Author(s):  
Christian S. Reiss ◽  
Anthony M. Cossio ◽  
Valerie Loeb ◽  
David A. Demer

Abstract Reiss, C. S., Cossio, A. M., Loeb, V., and Demer, D. A. 2008. Variations in the biomass of Antarctic krill (Euphausia superba) around the South Shetland Islands, 1996–2006. – ICES Journal of Marine Science, 65: 497–508. The time-series of acoustically surveyed Antarctic krill (Euphausia superba) biomass near the South Shetland Islands (SSI) between 1996 and 2006 is re-estimated using a validated physics-based model of target strength (TS), and a species-discrimination algorithm based on the length-range of krill in plankton samples to identify krill acoustically, derived from TS-model predictions. The SSI area is surveyed each austral summer by the US Antarctic Marine Living Resources Program, and the acoustic data are used to examine trends in krill biomass and to assess the potential impact of fishing to the reproductive success of land-based predators (seals and penguins). The time-series of recomputed biomass densities varies greatly from that computed using an empirical log-linear TS-model and fixed-ranges of differences in volume–backscattering strengths (ΔSv), conventionally used to identify krill acoustically. The new acoustic estimates of biomass are significantly correlated with both proportional recruitment and krill abundance estimated from zooplankton samples. Two distinct peaks in biomass (1996 and 2003) are in accord with recruitment events shown by net-based krill time-series. The foundation for the new TS-model and the associated krill-discrimination algorithm, coupled with the agreement between acoustic- and net-survey results, provides strong support for the use of the new analytical technique. Variable biases in the re-estimated krill biomass have been greatly reduced. However, survey variability increased as a result of the increased rejection of acoustic backscatter previously attributed to krill. Management of Southern Ocean krill stocks based on a precautionary approach may therefore result in decreased allocations of krill, given its dependence on the variability of survey estimates.


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