Phenotypic evolution in a venerid bivalve species lineage from the late Middle Miocene Central Paratethys Sea: a multi-approach morphometric analysis

A morphometric analysis was performed for the late Middle Miocene bivalve species lineage of Polititapes tricuspis (Eichwald, 1829) (Veneridae: Tapetini). Specimens from various localities grouped into two stratigraphically successive biozones, i.e. the upper Ervilia Zone and the Sarmatimactra Zone, were investigated using a multi-method approach. A Generalized Procrustes Analysis was computed for fifteen landmarks, covering characteristics of the hinge, muscle scars, and pallial line. The shell outline was separately quantified by applying the Fast Fourier Transform, which redraws the outline by fitting in a combination of trigonometric curves. Shell size was calculated as centroid size from the landmark configuration. Shell thickness, as not covered by either analysis, was additionally measured at the centroid. The analyses showed significant phenotypic differentiation between specimens from the two biozones. The bivalves become distinctly larger and thicker over geological time and develop circular shells with stronger cardinal teeth and a deeper pallial sinus. Data on the paleoenvironmental changes in the late Middle Miocene Central Paratethys Sea suggest the phenotypic shifts to be functional adaptations. The typical habitats for Polititapes changed to extensive, very shallow shores exposed to high wave action and tidal activity. Caused by the growing need for higher mechanical stability, the bivalves produced larger and thicker shells with stronger cardinal teeth. The latter are additionally shifted towards the hinge center to compensate for the lacking lateral teeth and improve stability. The deepening pallial sinus is related to a deeper burrowing habit, which is considered to impede being washed out in the new high-energy settings.

Deforesting Europe: pollen-inferred Holocene land cover change using the 'pseudobiomization' approach

Maps of continental-scale land cover are utilized by a range of diverse users but whilst a range of products exist that describe present and recent land cover in Europe, there are currently no datasets that describe past variations over long time-scales. User groups with an interest in past land cover include the climate modelling community, socio-ecological historians and earth system scientists. Europe is one of the continents with the longest histories of land conversion from forest to farmland, thus understanding land cover change in this area is globally significant. This study applies the pseudobiomization method (PBM) to 982 pollen records from across Europe, taken from the European Pollen Database (EPD) to produce a first synthesis of pan-European land cover change for the period 9000 BP to present, in contiguous 200 year time intervals. The PBM transforms pollen proportions from each site to one of eight land cover classes (LCCs) that are directly comparable to the CORINE land cover classification. The proportion of LCCs represented in each time window provides a spatially aggregated record of land cover change for temperate and northern Europe, and for a series of case study regions (western France, the western Alps, and the Czech Republic and Slovakia). At the European scale, the impact of Neolithic food producing economies appear to be detectable from 6000 BP through reduction in broad-leaf forests resulting from human land use activities such as forest clearance. Total forest cover at a pan-European scale moved outside the range of previous background variability from 4000 BP onwards. From 2200 BP land cover change intensified, and the broad pattern of land cover for preindustrial Europe was established by 1000 BP. Recognizing the timing of anthropogenic land cover change in Europe will further the understanding of land cover-climate interactions, and the origins of the modern cultural landscape.

Downscaled land surface temperatures obtained by a particle smoothing approach, with links to NetCDF files

This dataset contains continuous time series of land surface temperature (LST) at spatial resolution of 300m around the 12 experimental sites of the PAGE21 project (grant agreement number 282700, funded by the EC seventh Framework Program theme FP7-ENV-2011). This dataset was produced from hourly LST time series at 25km scale, retrieved from SSM/I data (André et al., 2015, doi:10.1016/j.rse.2015.01.028) and downscaled to 300m using a dynamic model and a particle smoothing approach. This methodology is based on two main assumptions. First, LST spatial variability is mostly explained by land cover and soil hydric state. Second, LST is unique for a land cover class within the low resolution pixel. Given these hypotheses, this variable can be estimated using a land cover map and a physically based land surface model constrained with observations using a data assimilation process. This methodology described in Mechri et al. (2014, doi:10.1002/2013JD020354) was applied to the ORCHIDEE land surface model (Krinner et al., 2005, doi:10.1029/2003GB002199) to estimate prior values of each land cover class provided by the ESA CCI-Land Cover product (Bontemps et al., 2013) at 300m resolution . The assimilation process (particle smoother) consists in simulating ensemble of LST time series for each land cover class and for a large number of parameter sets. For each parameter set, the resulting temperatures are aggregated considering the grid fraction of each land cover and compared to the coarse observations. Miniminizing the distance between the aggregated model solutions and the observations allow us to select the simulated LST and the corresponding parameter sets which fit the observations most closely. The retained parameter sets are then duplicated and randomly perturbed before simulating the next time window. At the end, the most likely LST of each land cover class are estimated and used to reconstruct LST maps at 300m resolution using ESA CCI-Land Cover. The resulting temperature maps on which ice pixels were masked, are provided at daily time step during the nine-year analysis period (2000-2009).