Hunting spectro-temporal information in unevenly spaced paleoclimate time series

18 p.

Contributions to time series data mining departing from the problem of road travel time modeling

194 p.

A 4500-year time series of Pacific cod (Gadus macrocephalus) size and abundance: archaeology, oceanic regime shifts, and sustainable fisheries

A 4500-year archaeological record of Pacific cod (Gadus macrocephalus) bones from Sanak Island, Alaska, was used to assess the sustainability of the modern fishery and the effects of this fishery on the size of fish caught. Allometric reconstructions of Pacific cod length for eight prehistoric time periods indicated that the current size of the nearshore, commercially fished Pacific cod stocks is statistically unchanged from that of fish caught during 4500 years of subsistence harvesting. This finding indicates that the current Pacific cod fishery that uses selective harvesting technolog ies is a sustainable commercial fishery. Variation in relative Pacific cod abundances provides further insights into the response of this species to punctuated changes in ocean climate (regime shifts) and indicates that Pacific cod stocks can recover from major environmental perturbations. Such palaeofisheries data can extend the short time-series of fisheries data (<50 yr) that form the basis for fisheries management in the Gulf of Alaska and place current trends within the context of centennial- or millennial-scale patterns.

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.