Top predator hotspot persistence

Metadata also available as - [Questions & Answers] - [Parseable text] - [DIF]

Metadata:

Identification_Information
Data_Quality_Information
Spatial_Data_Organization_Information
Entity_and_Attribute_Information
Distribution_Information
Metadata_Reference_Information

Identification_Information:

Citation:

Citation_Information:

Originator: Mike Sigler (NOAA, Mike.Sigler@noaa.gov)
Originator: Kathy Kuletz (USFWS, Kathy.Kuletz@fws.gov)
Originator: Chris Wilson (NOAA, Chris.Wilson@noaa.gov)
Originator: Nancy Friday (NOAA, Nancy.Friday@noaa.gov)
Originator: Patrick Ressler (NOAA, Patrick.Ressler@noaa.gov)
Publication_Date: 20120615
Title: Top predator hotspot persistence
Geospatial_Data_Presentation_Form: spreadsheet

Description:

Abstract:: Predictable prey locations reduce search time and energetic costs of foraging; thus marine predators often exploit locations where prey concentrations persist. In our study, we examined whether this association is influenced by differences among predator species in foraging modes (travel cost, surface feeder or diver) or whether the predator species is a central place forager or not. We examined distributions of two seabird species during their nesting period, the surface-feeding black-legged kittiwake (Rissa tridactyla) and the pursuit-diving thick-billed murre (Uria lomvia), and two baleen whale species, the humpback whale (Megaptera novaeangliae) and the fin whale (Balaenoptera physalus), in relation to two key prey, age-1 walleye pollock (Theragra chalcogramma) and euphausiids (Euphausiidae). Prey surveys were conducted once each year during 2004 and 2006-2010. Concurrent predator surveys were conducted in 2006-2010 (seabirds) and 2008 and 2010 (whales). We compared the seabird and whale foraging locations to where age-1 pollock and euphausiids were concentrated and considered the persistence of these concentrations, where the time-scale of persistence is year (i.e., a comparison among surveys that are conducted once each year). Euphausiids were widespread and concentrations often were reliably found within specific 37 × 37 km blocks (‘persistent hot spots of prey’). In contrast, age-1 pollock were more concentrated and their hot spots were persistent only on coarser scales (> 37 km). Both seabird species, regardless of foraging mode, were associated with age-1 pollock but not with euphausiids, even though age-1 pollock were less persistent than euphausiids. The higher travel cost central place foragers, thick-billed murres, foraged at prey concentrations nearer their island colonies than black-legged kittiwakes, which were more widespread foragers. Humpback whales were not tied to a central place and mostly were located only where euphausiids were concentrated, and further, often in locations where these concentrations were persistent. Fin whales were associated with locations where age-1 pollock were more likely, similar to black-legged kittiwakes and thick-billed murres, but their association with euphausiids was unclear. Our results suggest that a predator’s foraging mode and their restrictions during breeding affect their response to prey persistence.
Purpose:: The ability to predict the location of prey is an important component of foraging behavior of predators. Predictable prey locations reduce search time and thus energetic costs of foraging. The top predator hotspot persistence study will quantify the distributions of pelagic forage fish and determine whether apex predators are associated with locations where prey concentrations persisted across years (hot spots). Seabird and cetacean foraging locations from at-sea visual surveys will be analyzed in relation to prey type and abundance data.
Supplemental_Information:: Acoustic surveys were conducted during daylight to measure age-1 pollock and euphausiid abundance in the eastern Bering Sea. Acoustic backscatter data (18, 38, 70, 120, and 200 kHz; ping interval of 1 s-1; survey speeds of 19–22 km h-1) were collected using a Simrad EK500 or a Simrad EK60 along north-south survey transects located 37 km apart on the middle and outer shelf of the eastern Bering Sea during June and July of 2004, 2006, 2007, 2008, 2009 and 2010 (Fig. 1). The 2004 and 2006 surveys were conducted from the NOAA ship Miller Freeman (66-m long) and the remaining surveys were conducted from the NOAA ship Oscar Dyson (64-m long). The Miller Freeman was not equipped with a 70 kHz transducer so 70 kHz data were not collected in 2004 and 2006. These acoustic surveys were designed to estimate pollock abundance and have been conducted using standard methods since 1979 (Traynor, 1996; Honkalehto et al., 2008). The transducers are mounted on the bottom of the vessels’ retractable centerboards to maximize acoustic data quality. As a result, the effective sampling depth began 9 m below the water surface, and the 20-30 cm near the surface where surface-feeding birds forage was not sampled; therefore we assume that the biomass of fish at depth is related to the biomass that is at the surface and vulnerable to surface-feeding birds. Acoustic backscatter at 38 kHz was attributed to walleye pollock based on a visual examination of echo sign and on the catch composition of midwater and bottom trawls that were targeted to identify the species composition of the echo sign (Traynor, 1996). Pollock backscatter densities were converted to biomass densities (kg km-2) using standard methods for analyzing acoustic backscatter (Traynor, 1996; Honkalehto et al., 2008). Age-1 pollock abundance was separated from the abundance of older age classes based on length-frequency and length-at-age data from survey trawl catches. For 2004, 2006, 2007 and 2009, age-1 pollock biomass was defined as biomass for all pollock of lengths < 19 cm; in 2008, for all lengths < 17 cm; in 2010, for all lengths < 20 cm. Few fish less than 9-10 cm are caught in survey trawls and so there are no age-0 biomass estimates from these acoustic surveys. Acoustic backscatter strength from zooplankton and fish is frequency-dependent, and this characteristic was used to infer euphausiid abundance (De Robertis et al., 2010; Ressler et al., This issue). Acoustic backscatter at 120 kHz was attributed to euphausiids using an objective analysis that compared the observed backscatter frequency response at 18, 38, 120, and 200 kHz to a known frequency response signature for euphausiids (De Robertis et al., 2010; Ressler et al., This issue). Euphausiid backscatter densities (m2 km-2) were converted to euphausiid biomass densities (kg km-2) using standard methods for analyzing acoustic backscatter in a new application to Bering Sea euphausiid species (Ressler et al., This issue).
Trained observers onboard the acoustic survey vessel during daylight conducted standard visual line-transect surveys for whales during 2008 and 2010 (Moore et al., 2002) and visual strip-transect surveys for seabirds during 2006, 2007, 2008, 2009 and 2010 (MBM, 2002) (Fig. 1). No predator data were collected in 2004. For seabird surveys, an observer on the bridge determined the species, abundance, and behavior of seabirds occurring within a 90○ arc from the bow out 300 m on the side of the ship where visibility was best. We kept all the sighting data collected under reasonable sighting conditions for seabirds (Beaufort ≤ 6) in the analysis, occasionally reducing the strip width to 100 or 200 m during reduced visibility. The threshold was chosen based on preliminary analysis of observations which showed that sightings decreased significantly at a Beaufort sea state of 7 and above. Beaufort sea state rarely prohibited acoustic data collection, so that some acoustic data did not have associated seabird or whale data. Behavior categories for seabirds were flying, sitting on the water, and feeding. For our analysis, we used data from birds feeding and sitting on the water because these birds most likely were feeding or had recently fed at the time of observation; exceptions were aerial foragers, specifically kittiwakes and storm-petrels, for which we also included flying birds (MBM, 2002). Visual survey effort for birds totaled 2,769 km in 2006, 6,438 km in 2007, 6,618 km in 2008, 7,203 km in 2009 and 10,406 km in 2010. Seabird density was computed as number per km2 surveyed. There are 10 major seabird colonies in this region (St. Paul, St. George, St. Matthew, St. Lawrence, Cape Navarin, Nunivak, Newenham, Amak, Tanginak, and Bogoslof colonies) (Fig. 1). A separate team conducted line-transect surveys for whales because individual groups can be tracked more easily than seabirds, species usually can be accurately determined at larger distances, and they are relatively rare; the larger survey area (to the horizon) increased the odds of sighting whales. Observers scanned for whales with 25× (Big Eye) binoculars from the flying bridge (platform height of 12 m from the Miller Freeman and 16 m from the Oscar Dyson). We kept all the sighting data with reasonable sighting conditions for whales (Beaufort ≤ 5 and a visible horizon) in the analysis. The maximum sighting distance for fin whales was 14 km and for humpback whales was 10 km; most (90%) of sightings occurred within 9 km for both species. The definition of reasonable sighting conditions was more restrictive for whale than seabird observations because the wider search area for whales was more easily affected by bad weather. The line transect data were not adjusted for detection probability or distance and all sighted animals were included in the analysis; ship location was used as a proxy for whale location even though the maximum sighting distance was 14 km; these simplifications seem reasonable given the large (37 × 37 km) blocks used to bin the data (see next section). Visual survey effort for whales totaled 4452 km in 2008 and 2039 km in 2010 (Fig. 1). Whale density was computed as number sighted by species per km surveyed.

Time_Period_of_Content:

Time_Period_Information:

Range_of_Dates/Times:

Beginning_Date: 20040101
Ending_Date: 20101231

Currentness_Reference: Dates refer to year

Status:

Progress: Complete
Maintenance_and_Update_Frequency: None planned

Spatial_Domain:

Description_of_Geographic_Extent: Bering Sea Shelf

Bounding_Coordinates:

West_Bounding_Coordinate: -179.53
East_Bounding_Coordinate: -158.20
North_Bounding_Coordinate: 63.69
South_Bounding_Coordinate: 54.01

Keywords:

Theme:

Theme_Keyword_Thesaurus: None
Theme_Keyword: project_number:B92
Theme_Keyword: data_url:<http://data.eol.ucar.edu/codiac/dss/id=245.B92-001>
Theme_Keyword: archive_url:<http://www.eol.ucar.edu/projects/bsierp>

Place:

Place_Keyword_Thesaurus: None
Place_Keyword: Bering Sea
Place_Keyword: Alaska
Place_Keyword: AK

Taxonomy:

Keywords/Taxon:

Taxonomic_Keyword_Thesaurus: None
Taxonomic_Keywords: black-legged kittiwake
Taxonomic_Keywords: thick-billed murre
Taxonomic_Keywords: fin whale
Taxonomic_Keywords: humpback whale
Taxonomic_Keywords: age-1 walleye pollock
Taxonomic_Keywords: euphausiids