Palaeoenvironment of Eocene prodelta in Spitsbergen recorded by the trace fossil Phycosiphon incertum

Ichnological, sedimentological and geochemical analyses were conducted on the Eocene Frysjaodden Formation in order to interpret palaeoenvironment prodelta sediments in the Central Basin of Spitsbergen. Phycosiphon incertum is the exclusive ichnotaxon showing differences in size, distribution, abundance and density, and relation to laminated/bioturbated intervals. Large P. incertum mainly occur dispersed, isolated and randomly distributed throughout the weakly laminated/non-laminated intervals. Small P. incertum occur occasionally in patches of several burrows within laminated intervals or as densely packed burrows in thin horizons in laminated intervals or constituting fully bioturbated intervals that are several centimetres thick. Ichnological changes are mainly controlled by oxygenation, although the availability of benthic food cannot be discarded. Changes in oxygenation and rate of sedimentation can be correlated with the registered variations in the Bouma sequence of the distal turbiditic beds within prodeltal shelf sediments.Funding for this research was provided by Project CGL2012-33281 (Secretaría de Estado de Investigación, Desarrollo e Innovación, Spain), Project RYC-2009-04316 (Ramón y Cajal Programme) and Projects RNM-3715 and RNM-7408 and Research Group RNM-178 (Junta de Andalucía). The authors benefited from a bilateral agreement between the universities of Granada and Oslo, supported by the University of Granada

Implications of within-farm transmission for network dynamics:Consequences for the spread of avian influenza

AbstractThe importance of considering coupled interactions across multiple population scales has not previously been studied for highly pathogenic avian influenza (HPAI) in the British commercial poultry industry. By simulating the within-flock transmission of HPAI using a deterministic S-E-I-R model, and by incorporating an additional environmental class representing infectious faeces, we tracked the build-up of infectious faeces within a poultry house over time. A measure of the transmission risk (TR) was computed for each farm by linking the amount of infectious faeces present each day of an outbreak with data describing the daily on-farm visit schedules for a major British catching company. Larger flocks tended to have greater levels of these catching-team visits. However, where density-dependent contact was assumed, faster outbreak detection (according to an assumed mortality threshold) led to a decreased opportunity for catching-team visits to coincide with an outbreak. For this reason, maximum TR-levels were found for mid-range flock sizes (~25,000–35,000 birds). When assessing all factors simultaneously using multivariable linear regression on the simulated outputs, those related to the pattern of catching-team visits had the largest effect on TR, with the most important movement-related factor depending on the mode of transmission. Using social network analysis on a further database to inform a measure of between-farm connectivity, we identified a large fraction of farms (28%) that had both a high TR and a high potential impact at the between farm level. Our results have counter-intuitive implications for between-farm spread that could not be predicted based on flock size alone, and together with further knowledge of the relative importance of transmission risk and impact, could have implications for improved targeting of control measures