Parallel structure among environmental gradients and three trophic levels in a subarctic estuary

The fishery for Alaska pollock Theragra chalcogramma in the western Gulf of Alaska is dependent on the strength of incoming year classes. Methods were developed to measure latelarval stage abundance and sizes at-sea and to use such data in a near real-time model to forecast recruitment about 4 yr in advance. Larval abundances were weighted for size-and temperaturedependent mortality to project the number attaining a critical size of 15 mm; this weighting reflects the greater survival value of larger larvae to the population. The method was applied to catches in the 2007 and 2008 larval surveys to show the feasibility of attaining near real-time estimates. The accuracy of the method to forecast recruitment was evaluated from historical data. Adjusting larval abundance for size-and temperature-dependent mortality improved the trend with recruitment, but the relationship was not significant over the entire time series (1979 to 2007) because of an increasing trend in predators of juvenile stages, decoupling the parameters. A threshold-based generalized additive recruitment forecast model was developed to account for autocorrelative structure caused by inter-cohort interactions and mortality-related factors occurring after the larval period. The model closely tracks past recruitment trends. Based on low larval abundances and high numbers of predators, low to moderate abundances of age-4 recruits were predicted for 2007 to 2011, which matched observed levels reasonably well.

Section: Discussionsupporting

confidence: 69%

Near real-time forecasting of recruitment from larval surveys: application to Alaska pollock

Bailey¹,

Zhang²,

Chan³

et al. 2012

“…Temperature gradients can affect the distribution of fish and zooplankton (e.g. Coyle & Pinchuk 2005, Speckman et al 2005, and create concentrations of prey within and slightly above or below water masses of different tempera- ΔDepth ( -1000 0 -1500 -500 1000 500 Fig. 6.…”

Section: Discussionmentioning

confidence: 99%

“…There are a number of ways to summarize these data into a single value, including averaging over selected depth bins, or calculating the depth of the maximum temperature change (e.g. Speckman et al 2005). However, as we were interested in capturing the overall structure of the temperature-depth profile, we chose to develop our own summary method by calculating individual deviance values from the observed temperaturedepth data and a number of proposed temperaturedepth profile shapes (TDPS).…”

Section: Temperature-depth Profilesmentioning

confidence: 99%

Relationships among Kittlitz’s murrelet habitat use, temperature-depth profiles, and landscape features in Prince William Sound, Alaska, USA

Allyn¹,

McKnight²,

McGarigal³

et al. 2012

Although seabirds search large areas for food, their distributions often correlate with physical characteristics of the marine environment that can serve to aggregate prey. Kittlitz's murrelets Brachyramphus brevirostris are found almost exclusively in Alaskan waters, where they are closely associated with glacial fjords, suggesting that the distribution of this bird might be tightly linked to specific physical habitat characteristics of the fjords. We investigated relationships among locations used by Kittlitz's murrelets, water column characteristics, and landscape features in Harriman Fjord and Heather Bay, Prince William Sound, Alaska, USA. In Harriman Fjord, Kittlitz's murrelets were observed in shallow water near upwelling areas, indicated by a cold-water wedge near the surface (~10 m depth) in temperature-depth profiles. In Heather Bay, Kittlitz's murrelets used locations closer to the glacial moraine than the average available habitat. The temperature-depth profiles at these locations showed a cold, fresh surface layer (near surface to 5 m depth); however, the temperature-depth profile variable was statistically insignificant, likely because of small sample size. Although the best temperature-depth profile variables were dramatically different between the 2 fjords, both of these glacially influenced water column characteristics may serve to concentrate prey at an optimal depth, allowing Kittlitz's murrelets to focus their effort at predictable foraging locations. Given the widespread wasting of glaciers throughout their range, Kittlitz's murrelets may face increased pressure as changes in water column dynamics within glacial fjords affect the distribution and concentration of preferred prey.

“…This study was conducted during 5 consecutive seasons (1995 to 1999) at 3 common murre Uria aalge colonies in lower Cook Inlet, Alaska (Speckman et al 2005, providing us with 15 colony-years of data. The colonies are separated from each other by about 100 km, and are in oceanographically distinct habitats (Speckman 2004).…”

Section: Methodsmentioning

confidence: 99%

“…We defined this behavioral threshold as the level of food density below which there is a positive correlation between attendance and food density, and above which there is no such relationship. In order to ensure a broad range of food densities required to assess functional relationships, we designed a 5 yr study around 3 colonies with contrasting oceanographic conditions and an order of magnitude range in local food density (Abookire & Piatt 2005, Speckman et al 2005. We used 15 colony-years of data gathered in this study to characterize the functional relationship between time spent at the colony and food density and contrast the relationship between incubation and chick-rearing periods.…”

Section: Introductionmentioning

confidence: 99%

Seabird behavior as an indicator of food supplies: sensitivity across the breeding season

Harding¹,

Piatt

Schmutz³

2007

We used empirical data on the time allocation of common murres Uria aalge in relation to measures of local prey density to examine whether adults provisioning chicks are more sensitive to changes in prey density than birds that are incubating eggs. We hypothesized that seasonal differences in food requirements of incubating and chick-rearing parents would affect the form of the relationship between time spent at the colony and local food density. We found that the relationship did differ between the incubation and chick-rearing period in 3 important ways: (1) there was a strong non-linear relationship between food density and colony attendance during chick-rearing and a weaker relationship during incubation; (2) incubating birds were able to maintain relatively constant rates of attendance over a wider range of food densities than chick-rearing birds and only reduced colony attendance under extremely poor feeding conditions, if at all; and (3) incubating birds spent more time attending nest sites at the colony than provisioning birds. These differences confirmed that chick-rearing parents are more sensitive to changes in food density than incubating parents, and that measurements of time allocation during the incubation period would have limited value as an indicator of ecosystem change.