DECAF - Density Estimation for Cetaceans from passive Acoustic Fixed Sensors

2009 ◽  
Author(s):  
Len Thomas ◽  
Tiago Marques ◽  
David Borchers ◽  
Catriona Harris ◽  
David Moretti ◽  
...  
Keyword(s):  
Density Estimation ◽  
Passive Acoustic

Density estimation of leopard seals using a single stationary passive acoustic sensor.

2010 ◽  
Vol 127 (3) ◽  
pp. 1825-1825
Author(s):  
Holger Klinck ◽  
Nadine Constantinou ◽  
David K. Mellinger ◽  
Tracey Rogers
Keyword(s):  
Density Estimation ◽  
Acoustic Sensor ◽  
Passive Acoustic

Analysis of bearings of vocalizing marine mammals in relation to passive acoustic density estimation

2015 ◽  
Vol 138 (3) ◽  
pp. 1792-1792
Author(s):  
Julia A. Vernon ◽  
Jennifer L. Miksis-Olds ◽  
Danielle Harris
Keyword(s):  
Density Estimation ◽  
Marine Mammals ◽  
Passive Acoustic

scholarly journals Spatio-temporal variation in click production rates of beaked whales: Implications for passive acoustic density estimation

2017 ◽  
Vol 141 (3) ◽  
pp. 1962-1974 ◽  
Author(s):  
Victoria E. Warren ◽  
Tiago A. Marques ◽  
Danielle Harris ◽  
Len Thomas ◽  
Peter L. Tyack ◽  
...  
Keyword(s):  
Temporal Variation ◽  
Density Estimation ◽  
Production Rates ◽  
Beaked Whales ◽  
Spatio Temporal ◽  
Passive Acoustic

DECAF - Density Estimation for Cetaceans from Passive Acoustic Fixed Sensors

2007 ◽  
Author(s):  
Len Thomas ◽  
Tiago Marques ◽  
David Borchers ◽  
Catriona Stephenson ◽  
David Moretti ◽  
...  
Keyword(s):  
Density Estimation ◽  
Passive Acoustic

DECAF - Density Estimation for Cetaceans from Passive Acoustic Fixed Sensors

2010 ◽  
Author(s):  
Len Thomas ◽  
Tiago Marques ◽  
David Borchers ◽  
Catriona Harris ◽  
David Moretti ◽  
...  
Keyword(s):  
Density Estimation ◽  
Passive Acoustic

Passive acoustic density estimation of sperm whales in the Tongue of the Ocean, Bahamas

2012 ◽  
Vol 28 (4) ◽  
pp. E444-E455 ◽  
Author(s):  
Jessica A. W ard ◽  
Len Thomas ◽  
Susan Jarvis ◽  
Nancy DiMarzio ◽  
David Moretti ◽  
...  
Keyword(s):  
Density Estimation ◽  
Sperm Whales ◽  
Passive Acoustic

Density estimation of Yangtze finless porpoises using passive acoustic sensors and automated click train detection

2010 ◽  
Vol 128 (3) ◽  
pp. 1435 ◽  
Author(s):  
Satoko Kimura ◽  
Tomonari Akamatsu ◽  
Songhai Li ◽  
Shouyue Dong ◽  
Lijun Dong ◽  
...  
Keyword(s):  
Density Estimation ◽  
Acoustic Sensors ◽  
Click Train ◽  
Passive Acoustic

Spatiotemporal distribution of foraging in a marine predator: behavioural drivers of hotspot formation

2020 ◽  
Vol 635 ◽  
pp. 187-202
Author(s):  
T Brough ◽  
W Rayment ◽  
E Slooten ◽  
S Dawson
Keyword(s):  
Time Of Day ◽  
Spatiotemporal Distribution ◽  
Temporal Effects ◽  
Marine Predator ◽  
Marine Predators ◽  
Additive Mixed Models ◽  
Density Analysis ◽  
The Times ◽  
Passive Acoustic ◽  
Spatial Locations

Many species of marine predators display defined hotspots in their distribution, although the reasons why this happens are not well understood in some species. Understanding whether hotspots are used for certain behaviours provides insights into the importance of these areas for the predators’ ecology and population viability. In this study, we investigated the spatiotemporal distribution of foraging behaviour in Hector’s dolphin Cephalorhynchus hectori, a small, endangered species from New Zealand. Passive acoustic monitoring of foraging ‘buzzes’ was carried out at 4 hotspots and 6 lower-use, ‘reference areas’, chosen randomly based on a previous density analysis of visual sightings. The distribution of buzzes was modelled among spatial locations and on 3 temporal scales (season, time of day, tidal state) with generalised additive mixed models using 82000 h of monitoring data. Foraging rates were significantly influenced by all 3 temporal effects, with substantial variation in the importance and nature of each effect among locations. The complexity of the temporal effects on foraging is likely due to the patchy nature of prey distributions and shows how foraging is highly variable at fine scales. Foraging rates were highest at the hotspots, suggesting that feeding opportunities shape fine-scale distribution in Hector’s dolphin. Foraging can be disrupted by anthropogenic influences. Thus, information from this study can be used to manage threats to this vital behaviour in the locations and at the times where it is most prevalent.

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