Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry Characterization of Primary Amine End-Functionalized Polystyrene and Poly(methyl methacrylate) Synthesized by Living Anionic Polymerization Techniques

The reaction of living anionic polymers with 2,2,5,5-tetramethyl-1-(3-bromopropyl)-1-aza-2,5- disilacyclopentane (1) was investigated using coupled thin layer chromatography and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Structures of byproducts as well as the major product were determined. The anionic initiator having a protected primary amine functional group, 2,2,5,5-tetramethyl- 1-(3-lithiopropyl)-1-aza-2,5-disilacyclopentane (2), was synthesized using all-glass high-vacuum techniques, which allows the long-term stability of this initiator to be maintained. The use of 2 in the preparation of well-defined aliphatic primary amine R-end-functionalized polystyrene and poly(methyl methacrylate) was investigated. Primary amino R-end-functionalized poly(methyl methacrylate) can be obtained near-quantitatively by reacting 2 with 1,1-diphenylethylene in tetrahydrofuran at room temperature prior to polymerizing methyl methacrylate at -78 °C. When 2 is used to initiate styrene at room temperature in benzene, an additive such as N,N,N',N'- tetramethylethylenediamine is necessary to activate the polymerization. However, although the resulting polymers have narrow molecular weight distributions and well-controlled molecular weights, our mass spectra data suggest that the yield of primary amine α-end-functionalized polystyrene from these syntheses is very low. The majority of the products are methyl α-end-functionalized polystyrene.

Stability in The Proportion of Harbor Seals Hauled Out Under Locally Ideal Conditions

We monitored the haul-out behavior of 68 radio-tagged harbor seals (Phoca vitulina) during the molt season at two Alaskan haul-out sites (Grand Island, August-September 1994; Nanvak Bay, August-September 2000). For each site, we created a statistical model of the proportion of seals hauled out as a function of date, time of day, tide, and weather covariates. Using these models, we identified the conditions that would result in the greatest proportion of seals hauled out. Although those “ideal conditions” differed between sites, the proportion of seals predicted to be hauled out under those conditions was very similar (81.3% for Grand Island and 85.7% for Nanvak Bay). The similar estimates for both sites suggest that haul-out proportions under locally ideal conditions may be constant between years and geographic regions, at least during the molt season.

The Abundance of Harbor Seals in the Gulf of Alaska

The abundance of harbor seals (Phoca vitulina richardii) has declined in recent decades at several Alaska locations. The causes of these declines are unknown, but there is concern about the status of the populations, especially in the Gulf of Alaska. To assess the status of harbor seals in the Gulf of Alaska, we conducted aerial surveys of seals on their haul-out sites in August-September 1996. Many factors influence the propensity of seals to haul out, including tides, weather, time of day, and time of year. Because these “covariates” cannot simultaneously be controlled through survey design, we used a regression model to adjust the counts to an estimate of the number of seals that would have been ashore during a hypothetical survey conducted under ideal conditions for hauling out. The regression, a generalized additive model, not only provided an adjustment for the covariates, but also confirmed the nature and shape of the covariate effects on haul-out behavior. The number of seals hauled out was greatest at the beginning of the surveys (mid-August). There was a broad daily peak from about 1100-1400 local solar time. The greatest numbers were hauled out at low tide on terrestrial sites. Tidal state made little difference in the numbers hauled out on glacial ice, where the area available to seals did not fluctuate with the tide. Adjusting the survey counts to the ideal state for each covariate produced an estimate of 30,035 seals, about 1.8 times the total of the unadjusted counts (16,355 seals). To the adjusted count, we applied a correction factor of 1.198 from a separate study of two haul-out sites elsewhere in Alaska, to produce a total abundance estimate of 35,981 (SE 1,833). This estimate accounts both for the effect of covariates on survey counts and for the proportion of seals that remained in the water even under ideal conditions for hauling out.