Summary of shipboard physical properties of mudstones, carbonates, and clastic at DSDP Holes 72-515B and 72-516F

Compressional-wave velocity, wet-bulk density, and porosity were measured on sediments and rocks recovered from Deep Sea Drilling Project Holes 515B and 516F. Wet-bulk densities were measured by both gravimetric and GRAPE methods. Velocities were measured on trimmed samples with the Hamilton frame velocimeter. The shipboard measurement techniques are discussed in the explanatory notes chapter (Coulbourn, this volume) and are described in detail by Boyce (1976a). Only the shipboard measurements are reported here.

Whale sightings, group sizes and krill biomass in West Greenland in 2005

This study combined data on fin whale Balaenoptera physalus, humpback whale Megaptera novaeangliae, minke whale B. acutorostrata, and sei whale B. borealis sightings from large-scale visual aerial and ship-based surveys (248 and 157 sightings, respectively) with synoptic acoustic sampling of krill Meganyctiphanes norvegica and Thysanoessa sp. abundance in September 2005 in West Greenland to examine the relationships between whales and their prey. Krill densities were obtained by converting relationships of volume backscattering strengths at multiple frequencies to a numerical density using an estimate of krill target strength. Krill data were vertically integrated in 25 m depth bins between 0 and 300 m to obtain water column biomass (g/m**2) and translated to density surfaces using ordinary kriging. Standard regression models (Generalized Additive Modeling, GAM, and Generalized Linear Modeling, GLM) were developed to identify important explanatory variables relating the presence, absence, and density of large whales to the physical and biological environment and different survey platforms. Large baleen whales were concentrated in 3 focal areas: (1) the northern edge of Lille Hellefiske bank between 65 and 67°N, (2) north of Paamiut at 63°N, and (3) in South Greenland between 60 and 61° N. There was a bimodal pattern of mean krill density between depths, with one peak between 50 and 75 m (mean 0.75 g/m**2, SD 2.74) and another between 225 and 275 m (mean 1.2 to 1.3 g/m**2, SD 23 to 19). Water column krill biomass was 3 times higher in South Greenland than at any other site along the coast. Total depth-integrated krill biomass was 1.3 x 10**9 (CV 0.11). Models indicated the most important parameter in predicting large baleen whale presence was integrated krill abundance, although this relationship was only significant for sightings obtained on the ship survey. This suggests that a high degree of spatio-temporal synchrony in observations is necessary for quantifying predator-prey relationships. Krill biomass was most predictive of whale presence at depths >150 m, suggesting a threshold depth below which it is energetically optimal for baleen whales to forage on krill in West Greenland.

Species occurrence and richness of lichen, bryophytes and vascular plants near Abisko, Sweden and Toolik lake, Alaska

Little is known about the impact of changing temperature regimes on composition and diversity of cryptogam communities in the Arctic and Subarctic, despite the well-known importance of lichens and bryophytes to the functioning and climate feedbacks of northern ecosystems. We investigated changes in diversity and abundance of lichens and bryophytes within long-term (9-16 years) warming experiments and along natural climatic gradients, ranging from Swedish subarctic birch forest and subarctic/subalpine tundra to Alaskan arctic tussock tundra. In both Sweden and Alaska, lichen diversity responded negatively to experimental warming (with the exception of a birch forest) and to higher temperatures along climatic gradients. Bryophytes were less sensitive to experimental warming than lichens, but depending on the length of the gradient, bryophyte diversity decreased both with increasing temperatures and at extremely low temperatures. Among bryophytes, Sphagnum mosses were particularly resistant to experimental warming in terms of both abundance and diversity. Temperature, on both continents, was the main driver of species composition within experiments and along gradients, with the exception of the Swedish subarctic birch forest where amount of litter constituted the best explanatory variable. In a warming experiment in moist acidic tussock tundra in Alaska, temperature together with soil ammonium availability were the most important factors influencing species composition. Overall, dwarf shrub abundance (deciduous and evergreen) was positively related to warming but so were the bryophytes Sphagnum girgensohnii, Hylocomium splendens and Pleurozium schreberi; the majority of other cryptogams showed a negative relationship to warming. This unique combination of intercontinental comparison, natural gradient studies and experimental studies shows that cryptogam diversity and abundance, especially within lichens, is likely to decrease under arctic climate warming. Given the many ecosystem processes affected by cryptogams in high latitudes (e.g. carbon sequestration, N2-fixation, trophic interactions), these changes will have important feedback consequences for ecosystem functions and climate.

Global macrozoobenthos production and energy budget data base V150731, with link to database

I developed a new model for estimating annual production-to-biomass ratio P/B and production P of macrobenthic populations in marine and freshwater habitats. Self-learning artificial neural networks (ANN) were used to model the relationships between P/B and twenty easy-to-measure abiotic and biotic parameters in 1252 data sets of population production. Based on log-transformed data, the final predictive model estimates log(P/B) with reasonable accuracy and precision (r2 = 0.801; residual mean square RMS = 0.083). Body mass and water temperature contributed most to the explanatory power of the model. However, as with all least squares models using nonlinearly transformed data, back-transformation to natural scale introduces a bias in the model predictions, i.e., an underestimation of P/B (and P). When estimating production of assemblages of populations by adding up population estimates, accuracy decreases but precision increases with the number of populations in the assemblage.

Concentrations of brominated and chlorinated contaminants in adipose tissue of polar bears (Ursus maritimus) between 1991-2007

Adipose tissue was sampled from the western Hudson Bay (WHB) subpopulation of polar bears at intervals from 1991 to 2007 to examine temporal trends of PCB and OCP levels both on an individual and sum-contaminant basis. We also determined levels and temporal trends of emerging polybrominated diphenyl ethers (PBDEs), hexabromocyclododecane (HBCD), polybrominated biphenyls (PBBs) and other current-use brominated flame retardants. Over the 17-year period, sum DDT (and p,p'-DDE, p,p'-DDD, p,p'-DDT) decreased (-8.4%/year); alpha-hexachlorocyclohexane (alpha-HCH) decreased (-11%/year); beta-HCH increased ( + 8.3%/year); and sum PCB and sum chlordane (CHL), both contaminants at highest concentrations in all years (>1 ppm), showed no distinct trends even when compared to previous data for this subpopulation dating back to 1968. Some of the less persistent PCB congeners decreased significantly (-1.6%/year to -6.3%/year), whereas CB153 levels tended to increase (+ 3.3%/year). Parent CHLs (c-nonachlor, t-nonachlor) declined, whereas non-monotonic trends were detected for metabolites (heptachlor epoxide, oxychlordane). sum chlorobenzene, octachlorostyrene, sum mirex, sum MeSO2-PCB and dieldrin did not significantly change. Increasing sum PBDE levels (+13%/year) matched increases in the four consistently detected congeners, BDE47, BDE99, BDE100 and BDE153. Although no trend was observed, total-(alpha)-HBCD was only detected post-2000. Levels of the highest concentration brominated contaminant, BB153, showed no temporal change. As long-term ecosystem changes affecting contaminant levels may also affect contaminant patterns, we examined the influence of year (i.e., aging or "weathering" of the contaminant pattern), dietary tracers (carbon stable isotope ratios, fatty acid patterns) and biological (age/sex) group on congener/metabolite profiles. Patterns of PCBs, CHLs and PBDEs were correlated with dietary tracers and biological group, but only PCB and CHL patterns were correlated with year. DDT patterns were not associated with any explanatory variables, possibly related to local DDT sources. Contaminant pattern trends may be useful in distinguishing the possible role of ecological/diet changes on contaminant burdens from expected dynamics due to atmospheric sources and weathering.