Remote sensing of coccolithophore blooms in selected oceanic regions using the PhytoDOAS method applied to hyper-spectral satellite data

In this study temporal variations of coccolithophore blooms are investigated using satellite data. Eight years (from 2003 to 2010) of data of SCIAMACHY, a hyper-spectral satellite sensor on-board ENVISAT, were processed by the PhytoDOAS method to monitor the biomass of coccolithophores in three selected regions. These regions are characterized by frequent occurrence of large coccolithophore blooms. The retrieval results, shown as monthly mean time series, were compared to related satellite products, including the total surface phytoplankton, i.e. total chlorophyll a (from GlobColour merged data) and the particulate inorganic carbon (from MODIS-Aqua). The inter-annual variations of the phytoplankton bloom cycles and their maximum monthly mean values have been compared in the three selected regions to the variations of the geophysical parameters: sea-surface temperature (SST), mixed-layer depth (MLD) and surface wind-speed, which are known to affect phytoplankton dynamics. For each region, the anomalies and linear trends of the monitored parameters over the period of this study have been computed. The patterns of total phytoplankton biomass and specific dynamics of coccolithophore chlorophyll a in the selected regions are discussed in relation to other studies. The PhytoDOAS results are consistent with the two other ocean color products and support the reported dependencies of coccolithophore biomass dynamics on the compared geophysical variables. This suggests that PhytoDOAS is a valid method for retrieving coccolithophore biomass and for monitoring its bloom developments in the global oceans. Future applications of time series studies using the PhytoDOAS data set are proposed, also using the new upcoming generations of hyper-spectral satellite sensors with improved spatial resolution

Properties of hierarchically forming star clusters

We undertake a systematic analysis of the early (< 0.5 Myr) evolution of clustering and the stellar initial mass function in turbulent fragmentation simulations. These large scale simulations for the first time offer the opportunity for a statistical analysis of IMF variations and correlations between stellar properties and cluster richness. The typical evolutionary scenario involves star formation in small-n clusters which then progressively merge; the first stars to form are seeds of massive stars and achieve a headstart in mass acquisition. These massive seeds end up in the cores of clusters and a large fraction of new stars of lower mass is formed in the outer parts of the clusters. The resulting clusters are therefore mass segregated at an age of 0.5 Myr, although the signature of mass segregation is weakened during mergers. We find that the resulting IMF has a smaller exponent (alpha=1.8-2.2) than the Salpeter value (alpha=2.35). The IMFs in subclusters are truncated at masses only somewhat larger than the most massive stars (which depends on the richness of the cluster) and an universal upper mass limit of 150 Msun is ruled out. We also find that the simulations show signs of the IGIMF effect proposed by Weidner & Kroupa, where the frequency of massive stars is suppressed in the integrated IMF compared to the IMF in individual clusters. We identify clusters through the use of a minimum spanning tree algorithm which allows easy comparison between observational survey data and the predictions of turbulent fragmentation models. In particular we present quantitative predictions regarding properties such as cluster morphology, degree of mass segregation, upper slope of the IMF and the relation between cluster richness and maximum stellar mass. [abridged]Comment: 21 Pages, 25 Figure

Direction of the association between body fatness and self-reported screen time in Dutch adolescents

<p>Abstract</p> <p>Background</p> <p>Screen time has been associated with pediatric overweight. However, it is unclear whether overweight predicts or is predicted by excessive amounts of screen time. The aim of this study was to examine the direction of the association between screen time and body fatness in Dutch adolescents.</p> <p>Methods</p> <p>Longitudinal data of 465 Dutch adolescents (mean age at baseline 13 years, 53% boys) was used. Body fatness (objectively measured BMI, four skin folds and waist- and hip circumference), self-reported time spent watching TV and computer use, and aerobic fitness (shuttle run test) were assessed in all participants at three time points during 12 months. Multi-level linear autoregressive analyses was used to examine whether screen time predicted body fatness in the following time period and whether body fatness predicted screen time. Analyses were performed for boys and girls separately and adjusted for ethnicity and aerobic fitness.</p> <p>Results</p> <p>Time spent TV viewing did predict changes in BMI and hip circumference in boys, but not in girls, in the subsequent period. Computer time significantly predicted increases in skinfolds in boys and girls and increases in BMI in girls. Body fatness did not predict any changes in screen time.</p> <p>Conclusion</p> <p>The present study only partly supports the widely posited hypothesis that higher levels of screen time cause increases in body fatness. In addition, this study demonstrates that high levels of body fatness do not predict increases in screen time.</p

Improvement to the PhytoDOAS method for identification of coccolithophores using hyper-spectral satellite data

The goal of this study was to improve PhytoDOAS, which is a new retrieval method for quantitative identification of major phytoplankton functional types (PFTs) using hyper-spectral satellite data. PhytoDOAS is an extension of the Differential Optical Absorption Spectroscopy (DOAS, a method for detection of atmospheric trace gases), developed for remote identification of oceanic phytoplankton groups. Thus far, PhytoDOAS has been successfully exploited to identify cyanobacteria and diatoms over the global ocean from SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) hyper-spectral data. This study aimed to improve PhytoDOAS for remote identification of coccolithophores, another functional group of phytoplankton. The main challenge for retrieving more PFTs by PhytoDOAS is to overcome the correlation effects between different PFT absorption spectra. Different PFTs are composed of different types and amounts of pigments, but also have pigments in common, e.g. chl &lt;i&gt;a&lt;/i&gt;, causing correlation effects in the usual performance of the PhytoDOAS retrieval. Two ideas have been implemented to improve PhytoDOAS for the PFT retrieval of more phytoplankton groups. Firstly, using the fourth-derivative spectroscopy, the peak positions of the main pigment components in each absorption spectrum have been derived. After comparing the corresponding results of major PFTs, the optimized fit-window for the PhytoDOAS retrieval of each PFT was determined. Secondly, based on the results from derivative spectroscopy, a simultaneous fit of PhytoDOAS has been proposed and tested for a selected set of PFTs (coccolithophores, diatoms and dinoflagellates) within an optimized fit-window, proven by spectral orthogonality tests. The method was then applied to the processing of SCIAMACHY data over the year 2005. Comparisons of the PhytoDOAS coccolithophore retrievals in 2005 with other coccolithophore-related data showed similar patterns in their seasonal distributions, especially in the North Atlantic and the Arctic Sea. The seasonal patterns of the PhytoDOAS coccolithophores indicated very good agreement with the coccolithophore modeled data from the NASA Ocean Biochemical Model (NOBM), as well as with the global distributions of particulate inorganic carbon (PIC), provided by MODIS (MODerate resolution Imaging Spectroradiometer)-Aqua level-3 products. Moreover, regarding the fact that coccolithophores belong to the group of haptophytes, the PhytoDOAS seasonal coccolithophores showed good agreement with the global distribution of haptophytes, derived from synoptic pigment relationships applied to SeaWiFS chl &lt;i&gt;a&lt;/i&gt;. As a case study, the simultaneous mode of PhytoDOAS has been applied to SCIAMACHY data for detecting a coccolithophore bloom which was consistent with the MODIS RGB image and the MODIS PIC map of the bloom, indicating the functionality of the method also in short-term retrievals

Integration of genetic and physical maps of the Primula vulgaris S locus and localization by chromosome in situ hybridization

•Heteromorphic flower development in Primula is controlled by the S locus. The S locus genes, which control anther position, pistil length and pollen size in pin and thrum flowers, have not yet been characterized. We have integrated S-linked genes, marker sequences and mutant phenotypes to create a map of the P. vulgaris S locus region that will facilitate the identification of key S locus genes. We have generated, sequenced and annotated BAC sequences spanning the S locus, and identified its chromosomal location. •We have employed a combination of classical genetics and three-point crosses with molecular genetic analysis of recombinants to generate the map. We have characterized this region by Illumina sequencing and bioinformatic analysis, together with chromosome in situ hybridization. •We present an integrated genetic and physical map across the P. vulgaris S locus flanked by phenotypic and DNA sequence markers. BAC contigs encompass a 1.5-Mb genomic region with 1 Mb of sequence containing 82 S-linked genes anchored to overlapping BACs. The S locus is located close to the centromere of the largest metacentric chromosome pair. •These data will facilitate the identification of the genes that orchestrate heterostyly in Primula and enable evolutionary analyses of the S locus

Stellar tracers of the Cygnus Arm. II: A young open cluster in Cam OB3

Cam OB3 is the only defined OB association believed to belong to the Outer Galactic Arm or Cygnus Arm. Very few members have been observed and the distance modulus to the association is not well known. We attempt a more complete description of the population of Cam OB3 and a better determination of its distance modulus. We present uvby photometry of the area surrounding the O-type stars BD +56 864 and LS I +57 138, finding a clear sequence of early-type stars that define an uncatalogued open cluster, which we call Alicante 1. We also present spectroscopy of stars in this cluster and the surrounding association. From the spectral types for 18 very likely members of the association and UBV photometry found in the literature, we derive individual reddenings, finding a extinction law close to standard and an average distance modulus DM=13.0+-0.4. This value is in excellent agreement with the distance modulus to the new cluster Alicante 1 found by fitting the photometric sequence to the ZAMS. In spite of the presence of several O-type stars, Alicante 1 is a very sparsely populated open cluster, with an almost total absence of early B-type stars. Our results definitely confirm Cam OB3 to be located on the Cygnus Arm and identify the first open cluster known to belong to the association.Comment: Accepted for publication in Astronomy & Astrophysics. Tables 7 & 8 to appear only in electronic forma