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Persistence of prey hot spots in southeast Alaska Scott M. Gende National Park Service, Glacier Bay Field Station, 3100 National Park, Juneau, Alaska,

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Presentation on theme: "Persistence of prey hot spots in southeast Alaska Scott M. Gende National Park Service, Glacier Bay Field Station, 3100 National Park, Juneau, Alaska,"— Presentation transcript:

1 Persistence of prey hot spots in southeast Alaska Scott M. Gende National Park Service, Glacier Bay Field Station, 3100 National Park, Juneau, Alaska, USA; Michael Sigler National Marine Fisheries Service, Alaska Fisheries Science Center, Auke Bay Laboratory, Juneau, Alaska, USA;

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3 1. 1. Are there high aggregations of pelagic fish prey in space and time? 2. 2.Do these hot spots persist through time? 3. 3.What is the response of predators to these aggregations? Questions:

4 ~40 km study area

5 Methods: 1. Hydroacoustic surveys for pelagic prey conducted June 2001-May 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 approximately 1.83 km)

6 Methods: 1. Hydroacoustic surveys for pelagic prey conducted June 2001-May 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 approximately 1.83 km)

7 Methods: 1. Hydroacoustic surveys for pelagic prey conducted June 2001-May 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 approximately 1.83 km)

8 Methods: 1. Hydroacoustic surveys for pelagic prey conducted June 2001-May 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 approximately 1.83 km) 5. Transformed data from estimates of biomass to energy densities integrated across the water column

9 Methods: 1. Hydroacoustic surveys for pelagic prey conducted June 2001-May Periodic midwater trawls to sample prey energy and confirm echo sound 3. Concurrent observations of top predators including Steller sea lions and humpback whales 5. Transformed data from estimates of biomass to energy densities integrated across the water column kJ x 10 6 /km 2 4. Blocked data into tenths of a latitudinal minute such that each block constituted approximately 1.83 km)

10 Results:

11 On average prey energy density is not equal across months Millions kJ/kg

12 Cold winter months (Nov-Feb) are hot Millions kJ/kg

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14 Seasonal haul-out > Distribution of pelagic prey energy November

15 Seasonal haul-out > Distribution of pelagic prey energy December

16 Seasonal haul-out > Distribution of pelagic prey energy January

17 Seasonal haul-out > Distribution of pelagic prey energy February

18 Seasonal haul-out > Distribution of pelagic prey energy March

19 Seasonal haul-out > Distribution of pelagic prey energy April

20 Seasonal haul-out > Distribution of pelagic prey energy May

21 Seasonal haul-out Distribution of pelagic prey energy November 2003

22 Seasonal haul-out % 60-80% 40-60% 20-40% Proportion of observed Steller sea lions November %

23 Seasonal haul-out % 60-80% 40-60% 20-40% 0-20% Proportion of observed Steller sea lions December 2003

24 Seasonal haul-out % 60-80% 40-60% 20-40% 0-20% Proportion of observed Steller sea lions January 2004

25 Seasonal haul-out % 60-80% 40-60% 20-40% 0-20% Proportion of observed Steller sea lions February 2004

26 R 2 = 0.38 Avg. energy density of each block % of months sea lions found foraging within that block Strong relationship between the average energy density of each block (winter) and the distribution of Steller sea lions

27 Seasonal haul-out >70% 60-70% Hot spot persistence: the probability of encountering a hot spot across all winter months 50-60%

28 Seasonal haul-out >70% 60-70% Hot spots do not persist during the non-winter months 50-60% 20-30%

29 Seasonal haul-out Proportion of winter surveys when sea lions seen foraging >40% 30-40% 20-30%

30 % of months when spot is hot R 2 = 0.02 No relationship between hot spot location and foraging sea lions during the non-winter months Non-winter % of months sea lions found foraging within that block

31 % of months when block is hot% of months sea lions found foraging at the spot R 2 = 0.02 R 2 = 0.41 Sea lions consistently utilized the prey hot spots during the winter (Nov-Feb) Non-winter Winter

32 1. Are prey aggregated in time and space? Overwintering herring schools result in high prey aggregations Nov-Feb and occur in consistent locations.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 exceeded 70% for some areasSome hot spot areas persisted through time; the probability of encountering a high concentration of prey exceeded 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 densityStrong 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

33 So what?

34 Abundance of prey j in the environment Encounter rate with prey j Attack rates on prey j Capture rates on prey j Consumption rates on prey j NjNj λjλj ajaj cjcj KjKj λ j /N j a j / λ j c j /a j K j /c j Relative Encounter rate Attack probability Capture success Consumption probability Foraging Efficiency (Intake/Effort)

35 T1T1T1T1 T2T2T2T2 T3T3T3T3 T4T4T4T4 High density, low persistence of prey patches x xxx

36 T1T1T1T1 T2T2T2T2 T3T3T3T3 T4T4T4T4 x xxx

37 T1T1T1T1 T2T2T2T2 T3T3T3T3 T4T4T4T4 x xxx = mid efficiency I E

38 T1T1T1T1 T2T2T2T2 T3T3T3T3 T4T4T4T4 High density, low persistence of prey patches x xxx = mid efficiency Low density, low persistence of prey patches x xxx I E

39 T1T1T1T1 T2T2T2T2 T3T3T3T3 T4T4T4T4 High density, low persistence of prey patches Low density, low persistence of prey patches x xxx x xxx = mid efficiency I E

40 T1T1T1T1 T2T2T2T2 T3T3T3T3 T4T4T4T4 High density, low persistence of prey patches Low density, low persistence of prey patches x xxx x xxx = mid efficiency = low efficiency I E I E

41 T1T1T1T1 T2T2T2T2 T3T3T3T3 T4T4T4T4 High density, low persistence of prey patches Low density, low persistence of prey patches x xxx x xxx = mid efficiency = low efficiency I E I E x xxx Low density, high persistence of prey patches

42 T1T1T1T1 T2T2T2T2 T3T3T3T3 T4T4T4T4 High density, low persistence of prey patches Low density, low persistence of prey patches x xxx x xxx = mid efficiency = low efficiency I E I E x xxx Low density, high persistence of prey patches

43 T1T1T1T1 T2T2T2T2 T3T3T3T3 T4T4T4T4 High density, low persistence of prey patches Low density, low persistence of prey patches x xxx x xxx = mid efficiency = low efficiency I E I E x xxx Low density, high persistence of prey patches = high efficiency I E

44 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.

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