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.

Late Miocene palaeoflora and palaeoclimate of Lincang (China)

The Miocene Lincang leaf assemblage is used in this paper as proxy data to reconstruct the palaeoclimate of southwestern Yunnan (SW China) and the evolution of monsoon intensity. Three quantitative methods were chosen for this reconstruction, i.e. Leaf Margin Analysis (LMA), Climate Leaf Analysis Multivariate Program (CLAMP), and the Coexistence Approach (CA). These methods, however, yield inconsistent results, particularly for the precipitation, as also shown in European and other East Asian Cenozoic floras. The wide range of the reconstructed climatic parameters includes the Mean Annual Temperature (MAT) of 18.5-24.7 °C and the Mean Annual Precipitation (MAP) of 1213-3711 mm. Compared with the modern Lincang climate (MAT, 17.3 °C; MAP, 1178.7 mm), the Miocene climate is slightly warmer, wetter and has a higher temperature seasonality. A detailed comparison on the palaeoclimatic variables with the coeval Late Miocene Xiaolongtan flora from the eastern part of Yunnan allows us to investigate the development and interactions of both South Asian and East Asian monsoons during the Late Miocene in southwest China, now under strong influence of these monsoon systems. Our results suggest that the monsoon climate has already been established in southwest Yunnan during the Late Miocene. Furthermore, our results support that both Southeast Asian and East Asian monsoons co-occurred in Yunnan during the Late Miocene.

Neogene floras and palaeoclimatic estimates from various sites of South-West China

Neogene climates and vegetation history of western Yunnan are reconstructed on the basis of known fossil plants using the Coexistence Approach (CA) and Leaf Margin Analysis (LMA). Four Neogene leaf floras from Tengchong, Jianchuan and Eryuan in southwestern China are analyzed by the CA, and the paleoclimatic data of one Miocene carpoflora from Longling and three Pliocene palynofloras from Longling, Yangyi and Eryuan are used for comparison. The Miocene vegetation of the whole of West Yunnan is subtropical evergreen broad-leaved forest, and a similar mean annual precipitation is inferred for Tengchong, Longling and Jianchuan. However, by the Late Pliocene a large difference in vegetation occurred between the two slopes of Gaoligong Mountain, western Yunnan. The region of Tengchong retained a subtropical evergreen broad-leaved forest vegetation, whereas in Yangyi and Eryuan a vertical vegetation zonation had developed, which consists, in ascending order, of humid evergreen broad-leaved, needle and broad-leaved mixed evergreen, and coniferous forests. Distinctively, the Late Pliocene vegetational patterns of West Yunnan were already very similar to those of the present, and the Pliocene mean annual precipitation in Tengchong was markedly higher than that of Yangyi and Eryuan. Considering that the overall vegetation of West Yunnan and the precipitation at Yangyi and Eryuan have undergone no distinct change since the Late Pliocene, we conclude that the Hengduan Mountains on the northern boundary of West Yunnan must have arisen after the Miocene and approached their highest elevation before the Late Pliocene. Furthermore, the fact of the eastern portion of the Tibetan Plateau underwent a slight uplift after the Late Pliocene is also supported.

Seagrass time-series analysis products, in Moreton Bay, Australia, with links to GeoTIFFs

The spatial and temporal dynamics of seagrasses have been well studied at the leaf to patch scales, however, the link to large spatial extent landscape and population dynamics is still unresolved in seagrass ecology. Traditional remote sensing approaches have lacked the temporal resolution and consistency to appropriately address this issue. This study uses two high temporal resolution time-series of thematic seagrass cover maps to examine the spatial and temporal dynamics of seagrass at both an inter- and intra-annual time scales, one of the first globally to do so at this scale. Previous work by the authors developed an object-based approach to map seagrass cover level distribution from a long term archive of Landsat TM and ETM+ images on the Eastern Banks (~200 km**2), Moreton Bay, Australia. In this work a range of trend and time-series analysis methods are demonstrated for a time-series of 23 annual maps from 1988 to 2010 and a time-series of 16 monthly maps during 2008-2010. Significant new insight was presented regarding the inter- and intra-annual dynamics of seagrass persistence over time, seagrass cover level variability, seagrass cover level trajectory, and change in area of seagrass and cover levels over time. Overall we found that there was no significant decline in total seagrass area on the Eastern Banks, but there was a significant decline in seagrass cover level condition. A case study of two smaller communities within the Eastern Banks that experienced a decline in both overall seagrass area and condition are examined in detail, highlighting possible differences in environmental and process drivers. We demonstrate how trend and time-series analysis enabled seagrass distribution to be appropriately assessed in context of its spatial and temporal history and provides the ability to not only quantify change, but also describe the type of change. We also demonstrate the potential use of time-series analysis products to investigate seagrass growth and decline as well as the processes that drive it. This study demonstrates clear benefits over traditional seagrass mapping and monitoring approaches, and provides a proof of concept for the use of trend and time-series analysis of remotely sensed seagrass products to benefit current endeavours in seagrass ecology.

Geospatial analysis of groundwater depth for manual well drilling suitability in the Zinder Region, Niger

Manual and low-tech well drilling techniques have potential to assist in reaching the United Nations' millennium development goal for water in sub-Saharan Africa. This study used publicly available geospatial data in a regression tree analysis to predict groundwater depth in the Zinder region of Niger to identify suitable areas for manual well drilling. Regression trees were developed and tested on a database for 3681 wells in the Zinder region. A tree with 17 terminal leaves provided a range of ground water depth estimates that were appropriate for manual drilling, though much of the tree's complexity was associated with depths that were beyond manual methods. A natural log transformation of groundwater depth was tested to see if rescaling dataset variance would result in finer distinctions for regions of shallow groundwater. The RMSE for a log-transformed tree with only 10 terminal leaves was almost half that of the untransformed 17 leaf tree for groundwater depths less than 10 m. This analysis indicated important groundwater relationships for commonly available maps of geology, soils, elevation, and enhanced vegetation index from the MODIS satellite imaging system.

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.