(Table 1) Number of alleles per locus and heterozygosity of Arctic charr (Salvelinus alpinus) populations in Iceland

The ecological theory of adaptive radiation predicts that the evolution of phenotypic diversity within species is generated by divergent natural selection arising from different environments and competition between species. Genetic connectivity among populations is likely also to have an important role in both the origin and maintenance of adaptive genetic diversity. Our goal was to evaluate the potential roles of genetic connectivity and natural selection in the maintenance of adaptive phenotypic differences among morphs of Arctic charr, Salvelinus alpinus, in Iceland. At a large spatial scale, we tested the predictive power of geographic structure and phenotypic variation for patterns of neutral genetic variation among populations throughout Iceland. At a smaller scale, we evaluated the genetic differentiation between two morphs in Lake Thingvallavatn relative to historically explicit, coalescent-based null models of the evolutionary history of these lineages. At the large spatial scale, populations are highly differentiated, but weakly structured, both geographically and with respect to patterns of phenotypic variation. At the intralacustrine scale, we observe modest genetic differentiation between two morphs, but this level of differentiation is nonetheless consistent with strong reproductive isolation throughout the Holocene. Rather than a result of the homogenizing effect of gene flow in a system at migration-drift equilibrium, the modest level of genetic differentiation could equally be a result of slow neutral divergence by drift in large populations. We conclude that contemporary and recent patterns of restricted gene flow have been highly conducive to the evolution and maintenance of adaptive genetic variation in Icelandic Arctic charr.

Planktonic foraminifera in the Arabian Sea

Variations in primary productivity (PP) have been reconstructed in eutrophic, mesotrophic and oligotrophic parts of the Arabian Sea over the past 135 000 years applying principal component analysis and transfer function to planktic foraminiferal assemblages. Temporal variation in paleoproductivity is most pronounced in the mesotrophic northern (NAST site) and oligotrophic eastern (EAST site) Arabian Sea, and comparatively weak in the western eutrophic GeoB 3011-1 site in the upwelling area off Oman. Higher PP during interglacials (250-320 g C/m**2 year) than during cold stages (210-270 g C/m**2 year) at GeoB 3011-1 could have been caused by a strengthened upwelling during intensified summer monsoons and increased wind velocities. At NAST, during interglacials, PP is estimated to exceed g C/m**2 year 1, and during glacials to be as low as 140-180 g C/m**2 year. These fluctuations may result from a (1) varying impact of filaments that are associated to the Oman coastal upwelling, and (2) from open-ocean upwelling associated to the Findlater Jet. At EAST, highest productivity of about 380 g C/m**2 year is documented for the transition from isotope stage 5 to 4. We suggest that during isotope stages 2, 4, 5.2, the transition 5/4, and the end of stage 6, deep mixing of surface waters was caused by moderate to strong winter monsoons, and induced an injection of nutrients into the euphotic layer leading to enhanced primary production. The deepening of the mixed layer during these intervals is confirmed by an increased concentration of deep-dwelling planktic foraminiferal species. A high-productivity event in stage 3, displayed by estimated PP values, and by planktic foraminifera and radiolaria flux and accumulation rate, likely resulted from a combination of intensified SW monsoons with moderate to strong NE monsoons. Differential response of Globigerina bulloides, Globigerinita glutinata and mixed layer species to the availability of food is suited to subdivide productivity regimes on a temporal and spatial scale.

Profile of sediment echo sounding with links to ParaSound data files and swath sonar multibeam bathymetry during METEOR cruise M70/2b

Two highly active mud volcanoes located in 990-1,265 m water depths were mapped on the northern Egyptian continental slope during the BIONIL expedition of R/V Meteor in October 2006. High-resolution swath bathymetry and backscatter imagery were acquired with an autonomous underwater vehicle (AUV)-mounted multibeam echosounder, operating at a frequency of 200 kHz. Data allowed for the construction of ~1 m pixel bathymetry and backscatter maps. The newly produced maps provide details of the seabed morphology and texture, and insights into the formation of the two mud volcanoes. They also contain key indicators on the distribution of seepage and its tectonic control. The acquisition of high-resolution seafloor bathymetry and acoustic imagery maps with an AUV-mounted multibeam echosounder fills the gap in spatial scale between conventional multibeam data collected from a surface vessel and in situ video observations made from a manned submersible or a remotely operating vehicle.

Aboveground community and species-specific plant biomass from the Jena Experiment (Main Experiment, year 2008)

This data set contains aboveground community biomass (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Aboveground community biomass was harvested twice in 2008 just prior to mowing (during peak standing biomass in early June and in late August) on all experimental plots of the main experiment. This was done by clipping the vegetation at 3 cm above ground in three rectangles of 0.2 x 0.5 m per large plot. The location of these rectangles was assigned prior to each harvest by random selection of coordinates within the core area of the plots (i.e. the central 10 x 15 m). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material (i.e., dead plant material in the data file), and remaining plant material that could not be assigned to any category (i.e., unidentified plant material in the data file). All biomass was dried to constant weight (70°C, >= 48 h) and weighed. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The data for individual samples and the mean over samples for the biomass measures on the community level are given. Overall, analyses of the community biomass data have identified species richness as well as functional group composition as important drivers of a positive biodiversity-productivity relationship.

Aboveground community and species-specific plant biomass from the Jena Experiment (Dominance Experiment, year 2002)

This data set contains aboveground community biomass (Sown plant community, Weed plant community, and Unidentified plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of the dominance experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the dominance experiment, 206 grassland plots of 3.5 x 3.5 m were established from a pool of 9 plant species that can be dominant in semi-natural grassland communities of the study region. In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 3, 4, 6, and 9 species). Plots were maintained by bi-annual weeding and mowing. Aboveground community biomass was harvested in September 2002 on all experimental plots of the dominance experiment. This was done by clipping the vegetation at 3 cm above ground in two rectangles of 0.2 x 0.5 m per experimental plot. The location of these rectangles was assigned by random selection of coordinates within the central area of the plots (excluding an outer edge of 50cm). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material, and remaining plant material that could not be assigned to any category. The fresh mass of all biomass was determined and only biomass of one sample per plot could be dried to constant weight (70°C, >= 48 h). Dry mass of the other sample was calculated from the ratio of fresh to dry mass. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The mean of both samples per plot and the individual measurements are provided in the data file. Overall, analyses of the community biomass data have identified species richness and the presence of particular species as an important driver of a positive biodiversity-productivity relationship.

Aboveground community and species-specific plant biomass from the Jena Experiment (Dominance Experiment, year 2004)

This data set contains aboveground community plant biomass (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of the dominance experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the dominance experiment, 206 grassland plots of 3.5 x 3.5 m were established from a pool of 9 plant species that can be dominant in semi-natural grassland communities of the study region. In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 3, 4, 6, and 9 species). Plots were maintained by bi-annual weeding and mowing. Aboveground community biomass was harvested twice in May and August 2004 on all experimental plots of the dominance experiment. This was done by clipping the vegetation at 3 cm above ground in two rectangles of 0.2 x 0.5 m per experimental plot. The location of these rectangles was assigned by random selection of coordinates within the central area of the plots (excluding an outer edge of 50cm). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material, and remaining plant material that could not be assigned to any category. All biomass was dried to constant weight (70°C, >= 48 h) and weighed. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The mean of both samples per plot and the individual measurements are provided in the data file. Overall, analyses of the community biomass data have identified species richness and the presence of particular species as an important driver of a positive biodiversity-productivity relationship.

Nematode abundance in cold seep sediments of the Nordic Margins (Nyregga, Styregga, Haakon Mosby Mud Volcano)

Cold-seep environments and their associated symbiont-bearing mega faunal communities create islands of primary production for macro-and meiofauna in the otherwise monotonous and nutrient-poor deep-sea environment. To examine the spatial variation and distribution patterns of metazoan meiobenthos in different seepage-related habitats, samples were collected in two regions off Norway: several pockmarks associated with the Storegga Slide including the Nyegga pockmark area, and the active, methane-venting Haakon Mosby Mud Volcano west of the Barents Sea during the Vicking cruise aboard the RV ''PourquoiPas?'' in May-June 2006. Meiofaunal samples at control sites were sampled with a multiple corer, while the other sites were sampled with push cores operated by the ROV Victor6000.The meiofaunal samples were fixed in 4% buffered formaldehyde and washed over a 32 mm-mesh sieve. Metazoan meiofauna were extracted by density gradient centrifugation. All material was fixed with 4% buffered formalin and stained with Rose Bengal. The metazoan meiofauna was sorted out, enumerated and identified down to major taxa under the stereomicroscope. Afterwards, abundances of Nematodes were depth integrated over the top 5 cm to gain individual abundances per 10 cm**2.

Aboveground community and species-specific plant biomass from the Jena Experiment (Dominance Experiment, year 2005)

This data set contains aboveground community plant biomass (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of the dominance experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the dominance experiment, 206 grassland plots of 3.5 x 3.5 m were established from a pool of 9 plant species that can be dominant in semi-natural grassland communities of the study region. In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 3, 4, 6, and 9 species). Plots were maintained by bi-annual weeding and mowing. Aboveground community biomass was harvested twice in May and August 2005 on all experimental plots of the dominance experiment. This was done by clipping the vegetation at 3 cm above ground in two rectangles of 0.2 x 0.5 m per experimental plot. The location of these rectangles was assigned by random selection of coordinates within the central area of the plots (excluding an outer edge of 50cm). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material, and remaining plant material that could not be assigned to any category. All biomass was dried to constant weight (70°C, >= 48 h) and weighed. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The mean of both samples per plot and the individual measurements are provided in the data file. Overall, analyses of the community biomass data have identified species richness and the presence of particular species as an important driver of a positive biodiversity-productivity relationship.

Comparison and Assessment of Two Emission inventories for the Madrid Region

Emission inventories are databases that aim to describe the polluting activities that occur across a certain geographic domain. According to the spatial scale, the availability of information will vary as well as the applied assumptions, which will strongly influence its quality, accuracy and representativeness. This study compared and contrasted two emission inventories describing the Greater Madrid Region (GMR) under an air quality simulation approach. The chosen inventories were the National Emissions Inventory (NEI) and the Regional Emissions Inventory of the Greater Madrid Region (REI). Both of them were used to feed air quality simulations with the CMAQ modelling system, and the results were compared with observations from the air quality monitoring network in the modelled domain. Through the application of statistical tools, the analysis of emissions at cell level and cell – expansion procedures, it was observed that the National Inventory showed better results for describing on – road traffic activities and agriculture, SNAP07 and SNAP10. The accurate description of activities, the good characterization of the vehicle fleet and the correct use of traffic emission factors were the main causes of such a good correlation. On the other hand, the Regional Inventory showed better descriptions for non – industrial combustion (SNAP02) and industrial activities (SNAP03). It incorporated realistic emission factors, a reasonable fuel mix and it drew upon local information sources to describe these activities, while NEI relied on surrogation and national datasets which leaded to a poorer representation. Off – road transportation (SNAP08) was similarly described by both inventories, while the rest of the SNAP activities showed a marginal contribution to the overall emissions.

Plasma kinetics issues in an ESA study for a plasma laboratory in space

A study supported by the European Space Agency (ESA), in the context of its General Studies Programme, performed an investigation of the possible use of space for studies in pure and applied plasma physics, in areas not traditionally covered by ‘space plasma physics’. A set of experiments have been identified that can potentially provide access to new phenomena and to allow advances in several fields of plasma science. These experiments concern phenomena on a spatial scale (101–104 m) intermediate between what is achievable on the ground and the usual solar system plasma observations. Detailed feasibility studies have been performed for three experiments: active magnetic experiments, largescale discharges and long tether–plasma interactions. The perspectives opened by these experiments are discussed for magnetic reconnection, instabilities, MHD turbulence, atomic excited states kinetics, weakly ionized plasmas,plasma diagnostics, artificial auroras and atmospheric studies. The discussion is also supported by results of numerical simulations and estimates.

The ESA "Plasma Laboratory in Space" study

The European Space Agency has initiated, in the context of its General Studies Programme, a study of the possible use of space for studies in pure and applied plasma physics, in areas not traditionally covered by “space plasma physics”. A team of experts has been set-up to review a broad range of area including industrial plasma physics and pure plasma physics, astrophysical and solar-terrestrial areas. A set of experiments have been identified that can potentially provide access to new phenomena and to allow advances in several fields of plasma science. These experiments concern phenomena on spatial scale (102 to104 m) intermediate between what is achievable on ground experiment and usual solar system plasma observations.

Higher temporal variability of forest breeding bird communities in fragmented landscapes

Understanding the relationship between animal community dynamics and landscape structure has become a priority for biodiversity conservation. In particular, predicting the effects of habitat destruction that confine species to networks of small patches is an important prerequisite to conservation plan development. Theoretical models that predict the occurrence of species in fragmented landscapes, and relationships between stability and diversity do exist. However, reliable empirical investigations of the dynamics of biodiversity have been prevented by differences in species detection probabilities among landscapes. Using long-term data sampled at a large spatial scale in conjunction with a capture-recapture approach, we developed estimates of parameters of community changes over a 22-year period for forest breeding birds in selected areas of the eastern United States. We show that forest fragmentation was associated not only with a reduced number of forest bird species, but also with increased temporal variability in the number of species. This higher temporal variability was associated with higher local extinction and turnover rates. These results have major conservation implications. Moreover, the approach used provides a practical tool for the study of the dynamics of biodiversity.

Multiscale assessment of patterns of avian species richness

The search for a common cause of species richness gradients has spawned more than 100 explanatory hypotheses in just the past two decades. Despite recent conceptual advances, further refinement of the most plausible models has been stifled by the difficulty of compiling high-resolution databases at continental scales. We used a database of the geographic ranges of 2,869 species of birds breeding in South America (nearly a third of the world's living avian species) to explore the influence of climate, quadrat area, ecosystem diversity, and topography on species richness gradients at 10 spatial scales (quadrat area, ≈12,300 to ≈1,225,000 km2). Topography, precipitation, topography × latitude, ecosystem diversity, and cloud cover emerged as the most important predictors of regional variability of species richness in regression models incorporating 16 independent variables, although ranking of variables depended on spatial scale. Direct measures of ambient energy such as mean and maximum temperature were of ancillary importance. Species richness values for 1° × 1° latitude-longitude quadrats in the Andes (peaking at 845 species) were ≈30–250% greater than those recorded at equivalent latitudes in the central Amazon basin. These findings reflect the extraordinary abundance of species associated with humid montane regions at equatorial latitudes and the importance of orography in avian speciation. In a broader context, our data reinforce the hypothesis that terrestrial species richness from the equator to the poles is ultimately governed by a synergism between climate and coarse-scale topographic heterogeneity.

Psychophysical evidence for fast region-based segmentation processes in motion and color.

Theories of image segmentation suggest that the human visual system may use two distinct processes to segregate figure from background: a local process that uses local feature contrasts to mark borders of coherent regions and a global process that groups similar features over a larger spatial scale. We performed psychophysical experiments to determine whether and to what extent the global similarity process contributes to image segmentation by motion and color. Our results show that for color, as well as for motion, segmentation occurs first by an integrative process on a coarse spatial scale, demonstrating that for both modalities the global process is faster than one based on local feature contrasts. Segmentation by motion builds up over time, whereas segmentation by color does not, indicating a fundamental difference between the modalities. Our data suggest that segmentation by motion proceeds first via a cooperative linking over space of local motion signals, generating almost immediate perceptual coherence even of physically incoherent signals. This global segmentation process occurs faster than the detection of absolute motion, providing further evidence for the existence of two motion processes with distinct dynamic properties.

Nesting In The Clouds: Evaluating And Predicting Sea Turtle Nesting Beach Parameters From Lidar Data

Humans' desire for knowledge regarding animal species and their interactions with the natural world have spurred centuries of studies. The relatively new development of remote sensing systems using satellite or aircraft-borne sensors has opened up a wide field of research, which unfortunately largely remains dependent on coarse-scale image spatial resolution, particularly for habitat modeling. For habitat-specialized species, such data may not be sufficient to successfully capture the nuances of their preferred areas. Of particular concern are those species for which topographic feature attributes are a main limiting factor for habitat use. Coarse spatial resolution data can smooth over details that may be essential for habitat characterization. Three studies focusing on sea turtle nesting beaches were completed to serve as an example of how topography can be a main deciding factor for certain species. Light Detection and Ranging (LiDAR) data were used to illustrate that fine spatial scale data can provide information not readily captured by either field work or coarser spatial scale sources. The variables extracted from the LiDAR data could successfully model nesting density for loggerhead (Caretta caretta), green (Chelonia mydas), and leatherback (Dermochelys coriacea) sea turtle species using morphological beach characteristics, highlight beach changes over time and their correlations with nesting success, and provide comparisons for nesting density models across large geographic areas. Comparisons between the LiDAR dataset and other digital elevation models (DEMs) confirmed that fine spatial scale data sources provide more similar habitat information than those with coarser spatial scales. Although these studies focused solely on sea turtles, the underlying principles are applicable for many other wildlife species whose range and behavior may be influenced by topographic features.