CalCOFI Marine Mammal Monitoring
Greg Campbell1, Lisa Munger1, Karlina Merkens1, DominqueCamacho2, Andrea Havron2 and John Hildebrand1
Sara Kerosky
1Scripps Institution of Oceanography, La Jolla
2Spatial Ecosystems, Olympia, WA
• Detailed knowledge of cetacean distribution, habitat use, density and abundance critical
for impact assessment/management.Importance
•Cetacean habitat use and abundance in SOCAL are not clearly defined.
• Characterize cetacean distribution and habitat, estimate population size/density,
detect and compare vocalizations.
Status
Goals
Background
• Examine cetacean distribution relativeto environmental variables to elucidate habitat use patterns.
Habitat Modeling
• Develop cetacean density and abundance estimates across seasons and years.
• Examine acoustical data for species and/or population specific calls.
• Assess acoustic line-transect methods.
DistanceSampling
AcousticMonitoring
Approach
MethodsMethods –– Visual Monitoring Visual Monitoring •• Visual monitoring conducted during daylight transits between Visual monitoring conducted during daylight transits between CalCOFICalCOFI stations.stations.•• Two trained marine mammal observers on port and starboard, Two trained marine mammal observers on port and starboard, scanning 90scanning 90°°with 7with 7--power and 25power and 25--power binoculars.power binoculars.•• Species, group size, distance, angle and environmental data.Species, group size, distance, angle and environmental data.
Towed Array Schematic
6-elements with 2-200 kHz bandwidth
300 m
6 sensors
9 kt15 m
Methods Methods –– Acoustic Monitoring Acoustic Monitoring •• Towed acoustic array deployed on transits between stations.Towed acoustic array deployed on transits between stations.
•• Navy Navy sonobuoyssonobuoys deployed during ondeployed during on--station sampling.station sampling.
Hydrophone
Navy Sonobuoy
1-element: 0-26 kHz
Acoustic Monitoring
Distance Sampling
Habitat Modeling
Stock Structure
AbundanceThermal Fronts
Distance Sampling?
DensitySST and Zooplankton
Acoustic Detections
Visual Sightings
Visual Sightings
Habitat Modeling: Baleen WhalesHabitat Modeling: Baleen Whales
r
x
d
Sum
mer
200
5S
prin
g 20
05
Sea Surface Temp. Total Zooplankton Biomass
Habitat Modeling Habitat Modeling –– Baleen WhalesBaleen Whales
Fal
l 200
5W
inte
r 20
06
Sea Surface Temp. Total Zooplankton Biomass
Habitat Modeling Habitat Modeling –– Baleen WhalesBaleen Whales
Thermal Front Activity DetectionThermal Front Activity Detection
AVHRR AVHRR (Advanced Very High Resolution Radiometer) (Advanced Very High Resolution Radiometer) Pathfinder 5.0Pathfinder 5.0
•• 4km resolution satellite images from 4km resolution satellite images from NOAAsNOAAs NESDISNESDIS
WIM WIM (Windows Image Manager) (Windows Image Manager) –– SIED SIED (Single Image Edge Detection)(Single Image Edge Detection)
Dominique Camacho
Acoustic Monitoring
Distance Sampling
Habitat Modeling
Stock Structure
AbundanceThermal Fronts
Distance Sampling?
DensitySST and Zooplankton
Acoustic Detections
Visual Sightings
Visual Sightings
Distance Sampling: CetaceansDistance Sampling: Cetaceans
r
x
d
Strip Transects
L
w
Density = (# animals seen) / (area searched)
D = n · S2 · w · L
n = # sightingsS = mean group size
Abundance
N = A · DA = study area
Line Transects
Density
D = n · S
2 · ESW · L
ESW = effective strip width
Distance Sampling Distance Sampling –– Density & AbundanceDensity & Abundance
0
0.2
0.4
0.6
0.8
1
200 400 600 800 1000 1200 1400 1600
Distance from Trackline (m)
Det
ectio
n P
roba
bilit
y
r d
d = r · sin xx trackline
Blue Whales
Humpback Whales
Fin Whales
Abundance Estimation Abundance Estimation –– Baleen WhalesBaleen Whales
2.35179-79242668Humpback
1.87190-52833867Fin
1.06104-32519137Blue
Density1000 km295% CINnSpecies
15
23
n
690
491
N
35
30
n
338
171
N
387131585Fin
49181516Blue
NnNnSpecies
Probability of detection with distance from track-line.
Truncation Distance: 2 km
Abundance/Density Estimate: Pooled 2004-2009
Abundance Estimates: Stratified by Season 2004-2009
n=number of observations; N=abundance estimate
n=number of observations; N=abundance estimate
winter spring summer fall
Acoustic Monitoring
Distance Sampling
Habitat Modeling
Stock Structure
AbundanceThermal Fronts
Distance Sampling?
DensitySST and Zooplankton
Acoustic Detections
Visual Sightings
Visual Sightings
Acoustic Monitoring: CetaceansAcoustic Monitoring: Cetaceans
r
x
d
Requirements for Passive Acoustics Requirements for Passive Acoustics Density Estimation Density Estimation
�Detection
�Localization
�Species Recognition
�Group Size Estimation
Pacific White-Sided DolphinsRisso’s Dolphin
0 0.5 1.00 0.5 1.0Time (hours)
22253139
Fre
quen
cy(k
Hz)
96
50
0
Time (hours)
Click Type B
222637
2227.540
Click Type A
Click Type B
Time (sec)
Fre
q (k
Hz)
Time (sec)
25
00 1.5
Bottlenose Dolphin Common Dolphin
0 1.5
chanceCDBND
50%
50%
70%30%CD
10%90%BND
DFA Classification Accuracy
Acoustic Monitoring Acoustic Monitoring –– Species Call RecognitionSpecies Call Recognition
Los Angeles
Acoustic
Los Angeles
Visual
Acoustic vs. Visual Detections: HumpbacksAcoustic vs. Visual Detections: Humpbacks
Visual Detections – Inshore: Spring-Fall Sonobuoy Detections – Offshore: Winter
• Expand habitat modeling analysis through integration of larger and more diverse sample of visual/environmental data.
Habitat Modeling
• Produce new density and abundance estimates for nine cetacean species.
• Improve acoustical census methods with advancements in localization software,species-ID and group size estimation.
DistanceSampling
AcousticMonitoring
Next Steps
AcknowledgementsAcknowledgements
� Observers and Acousticians:Robin Baird, Jessica Burtenshaw, Annie Douglas, E. Elizabeth Henderson, Veronica Iriarte, Autumn Miller, Laura Morse, Erin Oleson Nadia Rubio Michael Smith, Melissa Soldevilla, Ernesto Vasquez, Katherine Whitaker, Suzanne Yin and Stephen Claussen.
� SIO & SWFSC CalCOFI Scientists:Dave Wolgast, Jim Wilkinson, Amy Hays, Dave Griffith, Grant Susner, and Robert Tombley
� CNO N45 and NPSFrank Stone and Curt Collins