Miocene flora and paleoclimate estimations of Schrotzburg, South Germany

We present a detailed palaeoclimate analysis of the Middle Miocene (uppermost Badenian-lowermost Sarmatian) Schrotzburg locality in S Germany, based on the fossil macro- and micro-flora, using four different methods for the estimation of palaeoclimate parameters: the coexistence approach (CA), leaf margin analysis (LMA), the Climate-Leaf Analysis Multivariate Program (CLAMP), as well as a recently developed multivariate leaf physiognomic approach based on an European calibration dataset (ELPA). Considering results of all methods used, the following palaeoclimate estimates seem to be most likely: mean annual temperature ~15-16°C (MAT), coldest month mean temperature ~7°C (CMMT), warmest month mean temperature between 25 and 26°C, and mean annual precipiation ~1,300 mm, although CMMT values may have been colder as indicated by the disappearance of the crocodile Diplocynodon and the temperature thresholds derived from modern alligators. For most palaeoclimatic parameters, estimates derived by CLAMP significantly differ from those derived by most other methods. With respect to the consistency of the results obtained by CA, LMA and ELPA, it is suggested that for the Schrotzburg locality CLAMP is probably less reliable than most other methods. A possible explanation may be attributed to the correlation between leaf physiognomy and climate as represented by the CLAMP calibration data set which is largely based on extant floras from N America and E Asia and which may be not suitable for application to the European Neogene. All physiognomic methods used here were affected by taphonomic biasses. Especially the number of taxa had a great influence on the reliability of the palaeoclimate estimates. Both multivariate leaf physiognomic approaches are less influenced by such biasses than the univariate LMA. In combination with previously published results from the European and Asian Neogene, our data suggest that during the Neogene in Eurasia CLAMP may produce temperature estimates, which are systematically too cold as compared to other evidence. This pattern, however, has to be further investigated using additional palaeofloras.

A fractional vegetation cover remote sensing product on pan-arctic scale with link to geotiff image

The paper presents first results of a pan-boreal scale land cover harmonization and classification. A methodology is presented that combines global and regional vegetation datasets to extract percentage cover information for different vegetation physiognomy and barren for the pan-arctic region within the ESA Data User Element Permafrost. Based on the legend description of each land cover product the datasets are harmonized into four LCCS (Land Cover Classification System) classifiers which are linked to the MODIS Vegetation Continuous Field (VCF) product. Harmonized land cover and Vegetation Continuous Fields products are combined to derive a best estimate of percentage cover information for trees, shrubs, herbaceous and barren areas for Russia. Future work will concentrate on the expansion of the developed methodology to the pan-arctic scale. Since the vegetation builds an isolation layer, which protects the permafrost from heat and cold temperatures, a degradation of this layer due to fire strongly influences the frozen conditions in the soil. Fire is an important disturbance factor which affects vast processes and dynamics in ecosystems (e.g. biomass, biodiversity, hydrology, etc.). Especially in North Eurasia the fire occupancy has dramatically increased in the last 50 years and has doubled in the 1990s with respect to the last five decades. A comparison of global and regional fire products has shown discrepancies between the amounts of burn scars detected by different algorithms and satellite data.

European Leaf Physiognomic Approach ELPA

Physiognomic traits of plant leaves such as size, shape or margin are decisively affected by the prevailing environmental conditions of the plant habitat. On the other hand, if a relationship between environment and leaf physiognomy can be shown to exist, vegetation represents a proxy for environmental conditions. This study investigates the relationship between physiognomic traits of leaves from European hardwood vegetation and environmental parameters in order to create a calibration dataset based on high resolution grid cell data. The leaf data are obtained from synthetic chorologic floras, the environmental data comprise climatic and ecologic data. The high resolution of the data allows for a detailed analysis of the spatial dependencies between the investigated parameters. The comparison of environmental parameters and leaf physiognomic characters reveals a clear correlation between temperature related parameters (e.g. mean annual temperature or ground frost frequency) and the expression of leaf characters (e.g. the type of leaf margin or the base of the lamina). Precipitation related parameters (e.g. mean annual precipitation), however, show no correlation with the leaf physiognomic composition of the vegetation. On the basis of these results, transfer functions for several environmental parameters are calculated from the leaf physiognomic composition of the extant vegetation. In a next step, a cluster analysis is applied to the dataset in order to identify "leaf physiognomic communities". Several of these are distinguished, characterised and subsequently used for vegetation classification. Concerning the leaf physiognomic diversity there are precise differences between each of these "leaf physiognomic classes". There is a clear increase of leaf physiognomic diversity with increasing variability of the environmental parameters: Northern vegetation types are characterised by a more or less homogeneous leaf physiognomic composition whereas southern vegetation types like the Mediterranean vegetation show a considerable higher leaf physiognomic diversity. Finally, the transfer functions are used to estimate palaeo-environmental parameters of three fossil European leaf assemblages from Late Oligocene and Middle Miocene. The results are compared with results obtained from other palaeo-environmental reconstructing methods. The estimates based on a direct linear ordination seem to be the most realistic ones, as they are highly consistent with the Coexistence Approach.

ELPA (European Leaf Physiognomic Approach): Grid data set of the leaf physiognomic composition of the extant European hardwood vegetation

Physiognomic traits of plant leaves such as size, shape or margin are decisively affected by the prevailing environmental conditions of the plant habitat. On the other hand, if a relationship between environment and leaf physiognomy can be shown to exist, vegetation represents a proxy for environmental conditions. This study investigates the relationship between physiognomic traits of leaves from European hardwood vegetation and environmental parameters in order to create a calibration dataset based on high resolution grid cell data. The leaf data are obtained from synthetic chorologic floras, the environmental data comprise climatic and ecologic data. The high resolution of the data allows for a detailed analysis of the spatial dependencies between the investigated parameters. The comparison of environmental parameters and leaf physiognomic characters reveals a clear correlation between temperature related parameters (e.g. mean annual temperature or ground frost frequency) and the expression of leaf characters (e.g. the type of leaf margin or the base of the lamina). Precipitation related parameters (e.g. mean annual precipitation), however, show no correlation with the leaf physiognomic composition of the vegetation. On the basis of these results, transfer functions for several environmental parameters are calculated from the leaf physiognomic composition of the extant vegetation. In a next step, a cluster analysis is applied to the dataset in order to identify "leaf physiognomic communities". Several of these are distinguished, characterised and subsequently used for vegetation classification. Concerning the leaf physiognomic diversity there are precise differences between each of these "leaf physiognomic classes". There is a clear increase of leaf physiognomic diversity with increasing variability of the environmental parameters: Northern vegetation types are characterised by a more or less homogeneous leaf physiognomic composition whereas southern vegetation types like the Mediterranean vegetation show a considerable higher leaf physiognomic diversity. Finally, the transfer functions are used to estimate palaeo-environmental parameters of three fossil European leaf assemblages from Late Oligocene and Middle Miocene. The results are compared with results obtained from other palaeo-environmental reconstructing methods. The estimates based on a direct linear ordination seem to be the most realistic ones, as they are highly consistent with the Coexistence Approach.

Circumarctic wetland dataset based on ENVISAT ASAR Global Monitoring Mode with links to geotiff image and NetCDF files (2005-01 to 2011-12)

A circumpolar representative and consistent wetland map is required for a range of applications ranging from upscaling of carbon fluxes and pools to climate modelling and wildlife habitat assessment. Currently available data sets lack sufficient accuracy and/or thematic detail in many regions of the Arctic. Synthetic aperture radar (SAR) data from satellites have already been shown to be suitable for wetland mapping. Envisat Advanced SAR (ASAR) provides global medium-resolution data which are examined with particular focus on spatial wetness patterns in this study. It was found that winter minimum backscatter values as well as their differences to summer minimum values reflect vegetation physiognomy units of certain wetness regimes. Low winter backscatter values are mostly found in areas vegetated by plant communities typically for wet regions in the tundra biome, due to low roughness and low volume scattering caused by the predominant vegetation. Summer to winter difference backscatter values, which in contrast to the winter values depend almost solely on soil moisture content, show expected higher values for wet regions. While the approach using difference values would seem more reasonable in order to delineate wetness patterns considering its direct link to soil moisture, it was found that a classification of winter minimum backscatter values is more applicable in tundra regions due to its better separability into wetness classes. Previous approaches for wetland detection have investigated the impact of liquid water in the soil on backscatter conditions. In this study the absence of liquid water is utilized. Owing to a lack of comparable regional to circumpolar data with respect to thematic detail, a potential wetland map cannot directly be validated; however, one might claim the validity of such a product by comparison with vegetation maps, which hold some information on the wetness status of certain classes. It was shown that the Envisat ASAR-derived classes are related to wetland classes of conventional vegetation maps, indicating its applicability; 30% of the land area north of the treeline was identified as wetland while conventional maps recorded 1-7%.