Changes over time in the spatial distribution of walleye pollock (Theragra chalcogramma) in the Gulf of Alaska, 1984-1996

Triennial bottom trawl survey data from 1984 to 1996 were used to evaluate changes in the summer distribution of walleye pollock in the western and central Gulf of Alaska. Differences between several age groups of pollock were evaluated. Distribution was examined in relation to several physical characteristics, including bottom depth and distance from land. Interspecies associations were also analyzed with the Bray-Curtis clustering technique to better understand community structure. Our results indicated that although the population numbers decreased, high concentrations of pollock remained in the same areas during 1984–96. However, there was an increase in the number of stations where low-density pollock concentrations of all ages were observed, which resulted in a decrease in mean population density of pollock within the GOA region. Patterns emerging from our data suggested an alternative to Mac-Call’s “basin hypothesis” which states that as population numbers decrease, there should be a contraction of the population range to optimal habitats. During 1984–96 there was a concurrent precipitous decline in Steller sea lions in the Gulf of Alaska. The results of our study suggest that decreases in the mean density of adult pollock, the main food in the Steller sea lion diet, combined with slight changes in the distribution of pollock (age-1 pollock in particular) in the mid-1980s, may have contributed to decreased foraging efficiency in Steller sea lions. Our results support the prevailing conceptual model for pollock ontogeny, although there is evidence that substantial spawning may also occur outside of Shelikof Strait.

Design of a Recreational Fishing Survey and Mark-Recapture Study for the Blue Crab, Callinectes sapidus, in Chesapeake Bay

The development of bay wide estimates of recreational harvest has been identified as a high priority by the Chesapeake Bay Scientific Advisory Committee (CBSAC) and by the Chesapeake Bay Program as reflected in the Chesapeake Bay Blue Crab Fishery Management Plan (Chesapeake Bay Program 1996). In addition, the BiState Blue Crab Commission (BBCAC), formed in 1996 by mandate from the legislatures of Maryland and Virginia to advise on crab management, has also recognized the importance of estimating the levels and trends in catches in the recreational fishery. Recently, the BBCAC has adopted limit and target biological reference points. These analyses have been predicated on assumptions regarding the relative magnitude of the recreational and commercial catch. The reference points depend on determination of the total number of crabs removed from the population. In essence, the number removed by the various fishery sectors, represents a minimum estimate of the population size. If a major fishery sector is not represented, the total population will be accordingly underestimated. If the relative contribution of the unrepresented sector is constant over time and harvests the same components of the population as the other sectors, it may be argued that the population estimate derived from the other sectors is biased but still adequately represents trends in population size over time. If either of the two constraints mentioned above is not met, the validity of relative trends over time is suspect. With the recent increases in the human population in the Chesapeake Bay watershed, there is reason to be concerned that the recreational catch may not have been a constant proportion of the total harvest over time. It is important to assess the catch characteristics and the magnitude of the recreational fishery to evaluate this potential bias. (PDF contains 70 pages)

Removing observational noise from fisheries-independent time series data using ARIMA models

Abundance indices derived from fishery-independent surveys typically exhibit much higher interannual variability than is consistent with the within-survey variance or the life history of a species. This extra variability is essentially observation noise (i.e. measurement error); it probably reflects environmentally driven factors that affect catchability over time. Unfortunately, high observation noise reduces the ability to detect important changes in the underlying population abundance. In our study, a noise-reduction technique for uncorrelated observation noise that is based on autoregressive integrated moving average (ARIMA) time series modeling is investigated. The approach is applied to 18 time series of finfish abundance, which were derived from trawl survey data from the U.S. northeast continental shelf. Although the a priori assumption of a random-walk-plus-uncorrelated-noise model generally yielded a smoothed result that is pleasing to the eye, we recommend that the most appropriate ARIMA model be identified for the observed time series if the smoothed time series will be used for further analysis of the population dynamics of a species.