Geology topics

Milo D. Adkison

Publications and source records attributed to Milo D. Adkison.

5 recordsLinked to original sources

USGS2019

Influences of spawning timing, water temperature, and climatic warming on early life history phenology in western Alaska sockeye salmon

We applied an empirical model to predict hatching and emergence timing for 25 western Alaska sockeye salmon (Oncorhynchus nerka) populations in four lake-nursery systems to explore current patterns and potential responses of early life history phenology to warming water temperatures. Given experienced temperature regimes during development, we predicted hatching to occur in as few as 58 d to as many as 260 d depending on spawning timing and temperature. For a focal lake spawning population, our climate-lake temperature model predicted a water temperature increase of 0.7 to 1.4 °C from 2015 to 2099 during the incubation period, which translated to a 16 d to 30 d earlier hatching timing. The most extreme scenarios of warming advanced development by approximately a week earlier than historical minima and thus climatic warming may lead to only modest shifts in phenology during the early life history stage of this population. The marked variation in the predicted timing of hatching and emergence among populations in close proximity on the landscape may serve to buffer this metapopulation from climate change.

Canadian Journal of Fisheries and Aquatic Sciences↗

USGS2007

Early marine growth in relation to marine-stage survival rates for Alaska sockeye salmon ( Oncorhynchus nerka )

We tested the hypothesis that larger juvenile sockeye salmon ( Oncorhynchus nerka ) in Bristol Bay, Alaska, have higher marine-stage survival rates than smaller juvenile salmon. We used scales from returning adults (33 years of data) and trawl samples of juveniles (n= 3572) collected along the eastern Bering Sea shelf during August through September 2000−02. The size of juvenile sockeye salmon mirrored indices of their marine-stage survival rate (e.g., smaller fish had lower indices of marine-stage survival rate). However, there was no relationship between the size of sockeye salmon after their first year at sea, as estimated from archived scales, and brood-year survival size was relatively uniform over the time series, possibly indicating size-selective mortality on smaller individuals during their marine residence. Variation in size, relative abundance, and marine-stage survival rate of juvenile sockeye salmon is likely related to ocean conditions affecting their early marine migratory pathways along the eastern Bering Sea shelf.

Fishery Bulletin↗

USGS2000

Predictability of Bristol Bay, Alaska, sockeye salmon returns one to four years in the future

Historically, forecast error for returns of sockeye salmon Oncorhynchus nerka to Bristol Bay, Alaska, has been large. Using cross-validation forecast error as our criterion, we selected forecast models for each of the nine principal Bristol Bay drainages. Competing forecast models included stock-recruitment relationships, environmental variables, prior returns of siblings, or combinations of these predictors. For most stocks, we found prior returns of siblings to be the best single predictor of returns; however, forecast accuracy was low even when multiple predictors were considered. For a typical drainage, an 80% confidence interval ranged from one half to double the point forecast. These confidence intervals appeared to be appropriately wide.

Alaska↗

USGS1996

Results of Bayesian methods depend on details of implementation: An example of estimating salmon escapement goals

Bayesian methods have been proposed to estimate optimal escapement goals, using both knowledge about physical determinants of salmon productivity and stock-recruitment data. The Bayesian approach has several advantages over many traditional methods for estimating stock productivity: it allows integration of information from diverse sources and provides a framework for decision-making that takes into account uncertainty reflected in the data. However, results can be critically dependent on details of implementation of this approach. For instance, unintended and unwarranted confidence about stock-recruitment relationships can arise if the range of relationships examined is too narrow, if too few discrete alternatives are considered, or if data are contradictory. This unfounded confidence can result in a suboptimal choice of a spawning escapement goal.

Fisheries Research↗

USGS1995

Population differentiation in Pacific salmon: local adaptation, genetic drift, or the environment?

Morphological, behavioral, and life-history differences between Pacific salmon (Oncorhynchus spp.) populations are commonly thought to reflect local adaptation, and it is likewise common to assume that salmon populations separated by small distances are locally adapted. Two alternatives to local adaptation exist: random genetic differentiation owing to genetic drift and founder events, and genetic homogeneity among populations, in which differences reflect differential trait expression in differing environments. Population genetics theory and simulations suggest that both alternatives are possible. With selectively neutral alleles, genetic drift can result in random differentiation despite many strays per generation. Even weak selection can prevent genetic drift in stable populations; however, founder effects can result in random differentiation despite selective pressures. Overlapping generations reduce the potential for random differentiation. Genetic homogeneity can occur despite differences in selective regimes when straying rates are high. In sum, localized differences in selection should not always result in local adaptation. Local adaptation is favored when population sizes are large and stable, selection is consistent over large areas, selective diffeentials are large, and straying rates are neither too high nor too low. Consideration of alternatives to local adaptation would improve both biological research and salmon conservation efforts.

Canadian Journal of Fisheries and Aquatic Sciences↗