5. A 4500-Year Time-Series of Otariid Abundance on Sanak Island, Western Gulf of Alaska

2019 ◽  
pp. 93-110
Keyword(s):  
Time Series ◽  
Gulf Of Alaska

Loss of spawning habitat and prerecruits of Pacific cod during a Gulf of Alaska heatwave

2020 ◽  
Vol 77 (4) ◽  
pp. 644-650 ◽  
Author(s):  
Benjamin J. Laurel ◽  
Lauren A. Rogers
Keyword(s):  
Time Series ◽  
Laboratory Data ◽  
Reproductive Potential ◽  
Gulf Of Alaska ◽  
Spawning Habitat ◽  
Pacific Cod ◽  
Pacific Cod Gadus Macrocephalus ◽  
Gadus Macrocephalus ◽  
Hatch Success ◽  
Negative Impacts

Pacific cod (Gadus macrocephalus) stocks in the Gulf of Alaska experienced steep, unexpected declines following an unprecedented 3-year marine heatwave (i.e., “warm blob”) from 2014 to 2016. We contend that stock reproductive potential was reduced during this period, evidenced by a combination of new laboratory data demonstrating narrow thermal hatch success (3–6 °C), mechanistic-based models of spawning habitat, and correlations with prerecruit time series. With the exception of single-year El Niño events (1998, 2003), the recent 3-year heatwave (2014–2016) and return to similar conditions in 2019 were potentially the most negative impacts on spawning habitat for Pacific cod in the available time series (1994–2019). Continued warming will likely reduce the duration and spatial extent of Pacific cod spawning in the Gulf of Alaska.

Phenological and geographical patterns of walleye pollock (Theragra chalcogramma) spawning in the western Gulf of Alaska

2007 ◽  
Vol 64 (4) ◽  
pp. 713-722 ◽  
Author(s):  
Lorenzo Ciannelli ◽  
Kevin M Bailey ◽  
Kung-Sik Chan ◽  
Nils Chr. Stenseth
Keyword(s):  
Time Series ◽  
Additive Model ◽  
Gulf Of Alaska ◽  
Walleye Pollock ◽  
Theragra Chalcogramma ◽  
Geographical Patterns ◽  
Spawning Aggregations ◽  
Egg Distribution ◽  
Walleye Pollock Theragra Chalcogramma ◽  
Egg Density

Over 20 years of egg sampling data were used to reconstruct the geographical and phenological patterns of walleye pollock (Theragra chalcogramma) spawning aggregations in the Gulf of Alaska (GOA). The analyzed time series (1972, 1978–1979, 1981–2000) included a documented event of climate change (i.e., 1988–1989) and the rise and fall of the GOA pollock population abundance and harvests. We compared results from two generalized additive model (GAM) formulations: one assuming no change of egg distribution and phenology over the examined time series (stationary) and the other admitting such changes (nonstationary) across an epoch determined from the data. Results from both model formulations corroborate the existence of a high egg concentration in Shelikof Strait, historically the primary spawning area of pollock in the GOA. However, model results also highlight the presence of other secondary, and possibly transitory, centers of egg distribution at various locations along the shelf and slope regions of the GOA. In addition, results from the nonstationary (and statistically superior) formulation indicate that the abundance of the non-Shelikof aggregations has increased over time, along with a tendency for earlier occurrence and displacement toward shallower areas of the high egg density regions.

Evaluating the performance of Gulf of Alaska walleye pollock (Theragra chalcogramma) recruitment forecasting models using a Monte Carlo resampling strategy

2009 ◽  
Vol 66 (3) ◽  
pp. 367-381 ◽  
Author(s):  
Yong-Woo Lee ◽  
Bernard A. Megrey ◽  
S. Allen Macklin
Keyword(s):  
Time Series ◽  
Monte Carlo ◽  
Gulf Of Alaska ◽  
Data Set ◽  
Forecasting Models ◽  
Walleye Pollock Theragra Chalcogramma ◽  
Sample Data ◽  
Out Of Sample ◽  
Data Points ◽  
Recruitment Model

Multiple linear regressions (MLRs), generalized additive models (GAMs), and artificial neural networks (ANNs) were compared as methods to forecast recruitment of Gulf of Alaska walleye pollock ( Theragra chalcogramma ). Each model, based on a conceptual model, was applied to a 41-year time series of recruitment, spawner biomass, and environmental covariates. A subset of the available time series, an in-sample data set consisting of 35 of the 41 data points, was used to fit an environment-dependent recruitment model. Influential covariates were identified through statistical variable selection methods to build the best explanatory recruitment model. An out-of-sample set of six data points was retained for model validation. We tested each model’s ability to forecast recruitment by applying them to an out-of-sample data set. For a more robust evaluation of forecast accuracy, models were tested with Monte Carlo resampling trials. The ANNs outperformed the other techniques during the model fitting process. For forecasting, the ANNs were not statistically different from MLRs or GAMs. The results indicated that more complex models tend to be more susceptible to an overparameterization problem. The procedures described in this study show promise for building and testing recruitment forecasting models for other fish species.

scholarly journals Zooplankton abundance trends and patterns in Shelikof Strait, western Gulf of Alaska, USA, 1990–2017

2020 ◽  
Vol 42 (3) ◽  
pp. 334-354 ◽  
Author(s):  
David G Kimmel ◽  
Janet T Duffy-Anderson
Keyword(s):  
Time Series ◽  
Generalized Additive Models ◽  
Zooplankton Community ◽  
Strong Relationship ◽  
Gulf Of Alaska ◽  
Additive Models ◽  
Environmental Data ◽  
Dynamic Factor ◽  
Zooplankton Abundance ◽  
Underlying Trend

Abstract A multivariate approach was used to analyze spring zooplankton abundance in Shelikof Strait, western Gulf of Alaska. abundance of individual zooplankton taxa was related to environmental variables using generalized additive models. The most important variables that correlated with zooplankton abundance were water temperature, salinity and ordinal day (day of year when sample was collected). A long-term increase in abundance was found for the calanoid copepod Calanus pacificus, copepodite stage 5 (C5). A dynamic factor analysis (DFA) indicated one underlying trend in the multivariate environmental data that related to phases of the Pacific Decadal Oscillation. DFA of zooplankton time series also indicated one underlying trend where the positive phase was characterized by increases in the abundance of C. marshallae C5, C. pacificus C5, Eucalanus bungii C4, Pseudocalanus spp. C5 and Limacina helicina and declines in the abundance of Neocalanus cristatus C4 and Neocalanus spp. C4. The environmental and zooplankton DFA trends were not correlated over the length of the entire time period; however, the two time series were correlated post-2004. The strong relationship between environmental conditions, zooplankton abundance and time of sampling suggests that continued warming in the region may lead to changes in zooplankton community composition and timing of life history events during spring.

Relationship among adult body length, abundance, and ocean temperature for British Columbia and Alaska sockeye salmon (Oncorhynchus nerka), 1967–1997

1999 ◽  
Vol 56 (10) ◽  
pp. 1716-1720 ◽  
Author(s):  
Brian J Pyper ◽  
Randall M Peterman
Keyword(s):  
British Columbia ◽  
Time Series ◽  
Body Length ◽  
Sockeye Salmon ◽  
Oncorhynchus Nerka ◽  
Gulf Of Alaska ◽  
Reduced Body ◽  
Adult Body ◽  
Northeastern Pacific ◽  
Length Data

Body length of adult Pacific sockeye salmon (Oncorhynchus nerka) has decreased significantly in recent years. We used 69 time series of age-specific body-length data (1967-1997) for 30 sockeye salmon stocks from southern British Columbia to western Alaska to test hypotheses about the effects of oceanographic conditions and competition on growth rate of sockeye salmon. Using principal components analysis (PCA), we constructed a single time series (PC1) that represented the dominant pattern of variability in length-at-age shared among these stocks. Taking into account time trends and autocorrelation in residuals, we found that increases in total Gulf of Alaska sockeye abundance and increases in sea-surface temperature (SST) across the Gulf of Alaska were significantly associated with reduced adult body length. Abundance and SST together accounted for 71% of the variability in PC1. Although researchers have documented increases in both abundance of sockeye salmon and their food in the northeastern Pacific Ocean over the last few decades, it is possible that increased food was more than offset by increased sockeye abundance, leading to greater competition and reduced body size.

The LDE-Type Flare Occurrence (1969-1993)

1994 ◽  
Vol 144 ◽  
pp. 279-282
Author(s):  
A. Antalová
Keyword(s):  
Time Series ◽  
Fourier Analysis ◽  
Sunspot Cycle ◽  
List Type ◽  
Type Number ◽  
Solar Cycles ◽  
Type Iv ◽  
Long Duration ◽  
Cycle Maximum ◽  
Flare Index

AbstractThe occurrence of LDE-type flares in the last three cycles has been investigated. The Fourier analysis spectrum was calculated for the time series of the LDE-type flare occurrence during the 20-th, the 21-st and the rising part of the 22-nd cycle. LDE-type flares (Long Duration Events in SXR) are associated with the interplanetary protons (SEP and STIP as well), energized coronal archs and radio type IV emission. Generally, in all the cycles considered, LDE-type flares mainly originated during a 6-year interval of the respective cycle (2 years before and 4 years after the sunspot cycle maximum). The following significant periodicities were found:• in the 20-th cycle: 1.4, 2.1, 2.9, 4.0, 10.7 and 54.2 of month,• in the 21-st cycle: 1.2, 1.6, 2.8, 4.9, 7.8 and 44.5 of month,• in the 22-nd cycle, till March 1992: 1.4, 1.8, 2.4, 7.2, 8.7, 11.8 and 29.1 of month,• in all interval (1969-1992):a)the longer periodicities: 232.1, 121.1 (the dominant at 10.1 of year), 80.7, 61.9 and 25.6 of month,b)the shorter periodicities: 4.7, 5.0, 6.8, 7.9, 9.1, 15.8 and 20.4 of month.Fourier analysis of the LDE-type flare index (FI) yields significant peaks at 2.3 - 2.9 months and 4.2 - 4.9 months. These short periodicities correspond remarkably in the all three last solar cycles. The larger periodicities are different in respective cycles.

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