Persistence of prey hot spots in southeast Alaska Scott M. Gende National Park Service, Glacier Bay Field Station, 3100 National Park, Juneau, Alaska, USA; Scott_Gende Gende@nps.gov Michael Sigler National Marine Fisheries Service, Alaska Fisheries Science Center, Auke Bay Laboratory, Juneau, Alaska, USA; Mike.Sigler@noaa noaa.gov
Questions: 1. Are there high aggregations of pelagic fish prey in space and time? 2.Do these hot spots persist through time? 3.What is the response of predators to these aggregations?
~40 km study area
Methods: 1. Hydroacoustic surveys for pelagic prey conducted June 2001-May 2004 2. Periodic midwater trawls to sample prey energy and confirm echo sound 3. Concurrent observations of top predators including Steller sea lions and humpback whales 4. Transformed data from estimates of biomass to energy densities integrated across the water column 5. Blocked data into tenths of a latitudinal minute such that each block constituted approimately 1.83 km)
Methods: 1. Hydroacoustic surveys for pelagic prey conducted June 2001-May 2004 2. Periodic midwater trawls to sample prey energy and confirm echo sound 3. Concurrent observations of top predators including Steller sea lions and humpback whales 4. Transformed data from estimates of biomass to energy densities integrated across the water column 5. Blocked data into tenths of a latitudinal minute such that each block constituted approimately 1.83 km)
Methods: 1. Hydroacoustic surveys for pelagic prey conducted June 2001-May 2004 2. Periodic midwater trawls to sample prey energy and confirm echo sound 3. Concurrent observations of top predators including Steller sea lions and humpback whales 4. Transformed data from estimates of biomass to energy densities integrated across the water column 5. Blocked data into tenths of a latitudinal minute such that each block constituted approimately 1.83 km)
Methods: 1. Hydroacoustic surveys for pelagic prey conducted June 2001-May 2004 2. Periodic midwater trawls to sample prey energy and confirm echo sound 3. Concurrent observations of top predators including Steller sea lions and humpback whales 4. Blocked data into tenths of a latitudinal minute such that each block constituted approimately 1.83 km) 5. Transformed data from estimates of biomass to energy densities integrated across the water column
Methods: 1. Hydroacoustic surveys for pelagic prey conducted June 2001-May 2004 2. Periodic midwater trawls to sample prey energy and confirm echo sound 3. Concurrent observations of top predators including Steller sea lions and humpback whales 4. Blocked data into tenths of a latitudinal minute such that each block constituted approimately 1.83 km) 5. Transformed data from estimates of biomass to energy densities integrated across the water column kj 10 6 /km 2
Results:
On average prey energy density is not equal across months 30,000 25,000 Millions kj/kg 2 20,000 15,000 10,000 5,000 0 JUN AUG OCT DEC FEB APR JUN AUG OCT DEC FEB APR JUN AUG OCT DEC FEB APR 2001 2004
Cold winter months (Nov-Feb) are hot 30,000 25,000 20,000 15,000 10,000 5,000 0 JUN AUG OCT DEC FEB APR JUN AUG OCT DEC FEB APR JUN AUG OCT DEC FEB APR 2001 2004 Millions kj/kg 2
Distribution of pelagic prey energy November 2003 Seasonal haul-out > 20000 10000-20000 5000-10000 1000-5000 1-1000
Distribution of pelagic prey energy December 2003 Seasonal haul-out > 20000 10000-20000 5000-10000 1000-5000 1-1000
Distribution of pelagic prey energy January 2004 Seasonal haul-out > 20000 10000-20000 5000-10000 1000-5000 1-1000
Distribution of pelagic prey energy February 2004 Seasonal haul-out > 20000 10000-20000 5000-10000 1000-5000 1-1000
Distribution of pelagic prey energy March 2004 Seasonal haul-out > 20000 10000-20000 5000-10000 1000-5000 1-1000
Distribution of pelagic prey energy April 2004 Seasonal haul-out > 20000 10000-20000 5000-10000 1000-5000 1-1000
Distribution of pelagic prey energy May 2004 Seasonal haul-out > 20000 10000-20000 5000-10000 1000-5000 1-1000
Distribution of pelagic prey energy November 2003 Seasonal haul-out
Proportion of observed Steller sea lions November 2003 Seasonal haul-out 80-100% 60-80% 40-60% 20-40% 0-20%
Proportion of observed Steller sea lions December 2003 Seasonal haul-out 80-100% 60-80% 40-60% 20-40% 0-20%
Proportion of observed Steller sea lions January 2004 Seasonal haul-out 80-100% 60-80% 40-60% 20-40% 0-20%
Proportion of observed Steller sea lions February 2004 Seasonal haul-out 80-100% 60-80% 40-60% 20-40% 0-20%
Strong relationship between the average energy density of each block (winter) and the distribution of Steller sea lions % of months sea lions found foraging within that block 50% 40% 30% R 2 = 0.4084 20% 10% 0% R 2 = 0.38-5,000 10,000 15,000 20,000 25,000 Avg. energy density of each block
Hot spot persistence: the probability of encountering a hot spot across all winter months Seasonal haul-out >70% 60-70% 50-60%
Hot spots do not persist during the non-winter months Seasonal haul-out >70% 60-70% 50-60% 20-30%
Proportion of winter surveys when sea lions seen foraging Seasonal haul-out >40% 30-40% 20-30%
No relationship between hot spot location and foraging sea lions during the non-winter months % of months sea lions found foraging within that block 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% R 2 = 0.02 0% 10% 20% 30% 40% 50% 60% 70% % of months when spot is hot Non-winter
Sea lions consistently utilized the prey hot spots during the winter (Nov-Feb) % of months sea lions found foraging at the spot 45% 45% 40% 40% 35% 35% 30% 30% 25% 25% 20% 20% 15% 15% 10% 10% 5% 5% R 2 = 0.02 R 2 = 0.41 0% 0% 0% 0% 10% 10% 20% 20% 30% 30% 40% 50% 60% 70% Winter Non-winter % of months when block is hot
1. Are prey aggregated in time and space? Overwintering herring schools result in high prey aggregations Nov-Feb and occur in consistent locations. 2. Do these prey hot spots persist? Some hot spot areas persisted through time; the probability of encountering a high concentration of prey eceeded 70% for some areas 3.Do predators respond to this persistence? Strong relationship (during the winter) between sea lion distribution and distribution of prey. However, it appears that sea lions response is greatest in areas with highest prey persistence rather than highest prey density
So what?
Abundance of prey j in the environment Encounter rate with prey j N j λ j Relative Encounter rate Attack λ j /N j Attack rates on prey j Capture rates on prey j Consumption rates on prey j a j c j K j probability Capture success Consumption probability a j / λ j c j /a j K j /c j Foraging Efficiency (Intake/Effort)
High density, low persistence of prey patches T1 T 2 T 3 T 4
High density, low persistence of prey patches T1 T 2 T 3 T 4
High density, low persistence of prey patches T1 T 2 T 3 T 4 I E = mid efficiency
High density, low persistence of prey patches T1 T 2 T 3 T 4 I E = mid efficiency Low density, low persistence of prey patches
High density, low persistence of prey patches T 1 T 2 T 3 T 4 I E = mid efficiency Low density, low persistence of prey patches
High density, low persistence of prey patches T 1 T 2 T 3 T 4 I E = mid efficiency Low density, low persistence of prey patches I E = low efficiency
High density, low persistence of prey patches T 1 T 2 T 3 T 4 I E = mid efficiency Low density, low persistence of prey patches I E = low efficiency Low density, high persistence of prey patches
High density, low persistence of prey patches T 1 T 2 T 3 T 4 I E = mid efficiency Low density, low persistence of prey patches I E = low efficiency Low density, high persistence of prey patches
High density, low persistence of prey patches T 1 T 2 T 3 T 4 I E = mid efficiency Low density, low persistence of prey patches I E = low efficiency Low density, high persistence of prey patches I E = high efficiency
Density may not be the only characteristic of prey aggregations that are important to predators; persistence may be just as important, particularly for those that do not have the ability to search large areas efficiently.