delta Deuterium of alkenone and BIT index of sediment core 64PE304-80 samples

Reconstructing past ocean salinity is important for assessing paleoceanographic change and therefore past climatic dynamics. Commonly, sea water salinity reconstruction is based on foraminifera oxygen isotope ratio values combined with sea surface temperature reconstruction. However, the approach relies on multiple proxies, resulting in relatively large uncertainty and, consequently, relatively low accuracy of salinity estimates. An alternative tool for past ocean salinity reconstruction is the hydrogen isotope composition of long chain (C37) alkenones (dDalkenone). Here, we applied dDalkenone to a 39 ka long coastal sediment record from the Eastern South African continental shelf in the Mozambique Channel, close to the Zambezi River mouth. Despite changes in global sea water dD related to glacial - interglacial ice volume effects, no clear changes were observed in the dDalkenone record throughout the entire 39 ka. The BIT index record from the same core showed high BIT values during the glacial and low values during the Holocene. This indicates a more pronounced freshwater influence at the core location during the glacial, resulting in alkenones depleted in deuterium during that time and, thereby, explains the lack of a clear glacial-interglacial alkenone dD shift. Correlation between the BIT index and dDalkenone during the glacial period suggests that increased continental runoff potentially changed the growth conditions of the alkenone producing haptophytes, promoting coastal haptophyte species with generally more enriched dDalkenone values. We therefore suggest that the application of dDalkenone for reconstructing past salinity in coastal settings may be complicated by changes in the alkenone producing haptophyte community.

Drought index from tree-rings in Kongton Mountains, China

The Kongtong Mountain area is a marginal area of the Asian summer monsoon and is sensitive to monsoon dynamics. The sensitivity highlights the need to establishing long-term climate records there and evaluating links with the Asian monsoon. Using "signal-free" methods, we developed a tree-ring chronology based 52 ring-width series from 23 Pinus tabulaeformis and Pinus armandidi trees in the Kongtong Mountain, northern China. Tree growth is highly correlated (0.844) with the Palmer Drought Severity Index (PDSI) from May to July, demonstrating the strength of PDSI in modeling drought conditions in this region. We therefore developed a robust May-July PDSI reconstruction spanning 1615-2009, which explained 71.2% of the instrumental variance for the period 1951-2005. Extremely dry epochs are found in periods of 1723-1727 and 1928-1932, and significant wet conditions are seen from 1696-1700, 1753-1757 and 1963-1969. These persistent dry and wet epochs were also found in northeastern Mongolia, suggesting similar drought regimes between these two regions. The dryness that occurred in the 1920s-1930s was the most severe and was concurrent with a warming period. This warming/drying relationship of the 1920s-1930s may be an analog to the current drying trend in northern China.

Sea surface temperature (TEX86), marine GDGTs and BIT index from ODP Hole 161-977A

The TEX86H temperature proxy is a relatively new proxy based on crenarchaeotal lipids and has rarely been applied together with other temperature proxies. In this study, we applied the TEX86H on a sediment core from the Alboran Sea (western Mediterranean, core ODP-977A) covering the penultimate climate cycle, that is, from 244 to 130 ka, and compared this with previously published sea surface temperatures derived from the Uk'37 of alkenones of haptophyta and Mg/Ca records of planktonic foraminifera. The TEX86H temperature record shows remarkably similar stadial-interstadial patterns and abrupt temperature changes to those observed with the Uk'37 palaeothermometer. Absolute TEX86H temperature estimates are generally higher than those of Uk'37, though this difference (<3°C in 81% of the data points) is mainly within the temperature calibration error for both proxies, suggesting that crenarchaeota and haptophyta experienced similar temperature variations. During occasional events (<5% of the analyzed time span), however, the TEX86H exhibits considerably higher absolute temperature estimates than the Uk'37. Comparison with Mg/Ca records of planktonic foraminifera as well as other Mediterranean TEX86 and Uk'37 records suggests that part of this divergence may be attributed to seasonal differences, that is, with TEX86H reflecting mainly the warm summer season while Uk'37 would show annual mean. Biases in the global calibration of both proxies or specific biases in the Mediterranean are an alternative, though less likely, explanation. Despite differences between absolute TEX86H and Uk'37 temperatures, the correlation between the two proxies (r**2 = 0.59, 95% significance) provides support for the occurrence of abrupt temperature variations in the western Mediterranean during the penultimate interglacial-to-glacial cycle.

A suite of global, cross-scale topographic variables for environmental and biodiversity modeling, links to files in GeoTIFF format

Topographic variation, the spatial variation in elevation and terrain features, underpins a myriad of patterns and processes in geography and ecology and is key to understanding the variation of life on the planet. The characterization of this variation is scale-dependent, i.e. it varies with the distance over which features are assessed and with the spatial grain (grid cell resolution) of analysis. A fully standardized and global multivariate product of different terrain features has the potential to support many large-scale basic research and analytical applications, however to date, such technique is unavailable. Here we used the digital elevation model products of global 250 m GMTED and near-global 90 m SRTM to derive a suite of topographic variables: elevation, slope, aspect, eastness, northness, roughness, terrain roughness index, topographic position index, vector ruggedness measure, profile and tangential curvature, and 10 geomorphological landform classes. We aggregated each variable to 1, 5, 10, 50 and 100 km spatial grains using several aggregation approaches (median, average, minimum, maximum, standard deviation, percent cover, count, majority, Shannon Index, entropy, uniformity). While a global cross-correlation underlines the high similarity of many variables, a more detailed view in four mountain regions reveals local differences, as well as scale variations in the aggregated variables at different spatial grains. All newly-developed variables are available for download at http://www.earthenv.org and can serve as a basis for standardized hydrological, environmental and biodiversity modeling at a global extent.