Stratospheric age of air variations between 1600 and 2100

The current understanding of preindustrial stratospheric age of air (AoA), its variability, and the potential natural forcing imprint on AoA is very limited. Here we assess the influence of natural and anthropogenic forcings on AoA using ensemble simulations for the period 1600 to 2100 and sensitivity simulations for different forcings. The results show that from 1900 to 2100, CO₂ and ozone-depleting substances are the dominant drivers of AoA variability. With respect to natural forcings, volcanic eruptions cause the largest AoA variations on time scales of several years, reducing the age in the middle and upper stratosphere and increasing the age below. The effect of the solar forcing on AoA is small and dominated by multidecadal total solar irradiance variations, which correlate negatively with AoA. Additionally, a very weak positive relationship driven by ultraviolett variations is found, which is dominant for the 11 year cycle of solar variability.

Lake-effect snow as the dominant control of mesic-forest distribution in Michigan, USA

1Recent studies demonstrated the sensitivity of northern forest ecosystems to changes in the amount and duration of snow cover at annual to decadal time scales. However, the consequences of snowfall variability remain uncertain for ecological variables operating at longer time scales, especially the distributions of forest communities. 2The Great Lakes region of North America offers a unique setting to examine the long-term effects of variable snowfall on forest communities. Lake-effect snow produces a three-fold gradient in annual snowfall over tens of kilometres, and dramatic edaphic variations occur among landform types resulting from Quaternary glaciations. We tested the hypothesis that these factors interact to control the distributions of mesic (dominated by Acer saccharum, Tsuga canadensis and Fagus grandifolia) and xeric forests (dominated by Pinus and Quercus spp.) in northern Lower Michigan. 3We compiled pre-European-settlement vegetation data and overlaid these data with records of climate, water balance and soil, onto Landtype Association polygons in a geographical information system. We then used multivariate adaptive regression splines to model the abundance of mesic vegetation in relation to environmental controls. 4Snowfall is the most predictive among five variables retained by our model, and it affects model performance 29% more than soil texture, the second most important variable. The abundance of mesic trees is high on fine-textured soils regardless of snowfall, but it increases with snowfall on coarse-textured substrates. Lake-effect snowfall also determines the species composition within mesic forests. The weighted importance of A. saccharum is significantly greater than of T. canadensis or F. grandifolia within the lake-effect snowbelt, whereas T. canadensis is more plentiful outside the snowbelt. These patterns are probably driven by the influence of snowfall on soil moisture, nutrient availability and fire return intervals. 5Our results imply that a key factor dictating the spatio-temporal patterns of forest communities in the vast region around the Great Lakes is how the lake-effect snowfall regime responds to global change. Snowfall reductions will probably cause a major decrease in the abundance of ecologically and economically important species, such as A. saccharum.

Ensemble prediction distribution maps of macroalgae for current conditions and four climate change scenarios and high resultion bathymetry for Potter Cove, WAP, Antarctica

Species distribution models (SDM) predict species occurrence based on statistical relationships with environmental conditions. The R-package biomod2 which includes 10 different SDM techniques and 10 different evaluation methods was used in this study. Macroalgae are the main biomass producers in Potter Cove, King George Island (Isla 25 de Mayo), Antarctica, and they are sensitive to climate change factors such as suspended particulate matter (SPM). Macroalgae presence and absence data were used to test SDMs suitability and, simultaneously, to assess the environmental response of macroalgae as well as to model four scenarios of distribution shifts by varying SPM conditions due to climate change. According to the averaged evaluation scores of Relative Operating Characteristics (ROC) and True scale statistics (TSS) by models, those methods based on a multitude of decision trees such as Random Forest and Classification Tree Analysis, reached the highest predictive power followed by generalized boosted models (GBM) and maximum-entropy approaches (Maxent). The final ensemble model used 135 of 200 calculated models (TSS > 0.7) and identified hard substrate and SPM as the most influencing parameters followed by distance to glacier, total organic carbon (TOC), bathymetry and slope. The climate change scenarios show an invasive reaction of the macroalgae in case of less SPM and a retreat of the macroalgae in case of higher assumed SPM values.

(Table 1) Dominant species and total biomass of macrozoobenthos communities in the southwestern Kara Sea

The structure and distribution of the macrobenthic communities were studied in the southwestern Kara Sea. The material was collected in Baidaratskaya Bay in July 2007 and in a section running westward of the Yamal Peninsula in September 2007. The depths of the sampling stations ranged from 5 to 25 m in the Baidaratskaya Bay area and between 16 and 46 m in the Yamal section. A total of 212 benthic invertebrate species were recorded. In both areas, Bivalvia was the group with the highest biomass (54.88 g/m**2 in the Yamal section and 59.71 g/m**2 in the Baidaratskaya Bay area), while polychaetes were the group with the highest number of species (45 in the Yamal section and 64 the Baidaratskaya Bay area). Three major macrozoobenthic communities were recognized: the Astarte borealis community (20-46 m, the deepest sampling stations in both areas); the 'medium-depth' community (10-20 m, extremely mosaic, usually dominated by Serripes groenlandicus); and the Nephtys longosetosa community (depth smaller than 10 m, characterized by low biomass and the absence of large bivalves and echinoderms). The western Yamal shallow-water communities were shown to be generally similar to those of Baidaratskaya Bay. The comparison of these results with those of the benthos censuses performed in 1927-1945, 1975, and 1993 showed that the benthic communities in the southwestern Kara Sea remained relatively stable during the second half of the 20th century and the early 21st century.