Climate and total tree cover reconstructions based on the 43.7-kyr fossil pollen record from Khoe (NW Sakhalin Island) and modern climate variables of 236 modern surface pollen sampling sites

A late Quaternary pollen record from northern Sakhalin Island (51.34°N, 142.14°E, 15 m a.s.l.) spanning the last 43.7 ka was used to reconstruct regional climate dynamics and vegetation distribution by using the modern analogue technique (MAT). The long-term trends of the reconstructed mean annual temperature (TANN) and precipitation (PANN), and total tree cover are generally in line with key palaeoclimate records from the North Atlantic region and the Asian monsoon domain. TANN largely follows the fluctuations in solar summer insolation at 55°N. During Marine Isotope Stage (MIS) 3, TANN and PANN were on average 0.2 °C and 700 mm, respectively, thus very similar to late Holocene/modern conditions. Full glacial climate deterioration (TANN = -3.3 °C, PANN = 550 mm) was relatively weak as suggested by the MAT-inferred average climate parameters and tree cover densities. However, error ranges of the climate reconstructions during this interval are relatively large and the last glacial environments in northern Sakhalin could be much colder and drier than suggested by the weighted average values. An anti-phase relationship between mean temperature of the coldest (MTCO) and warmest (MTWA) month is documented during the last glacial period, i.e. MIS 2 and 3, suggesting more continental climate due to sea levels that were lower than present. Warmest and wettest climate conditions have prevailed since the end of the last glaciation with an optimum (TANN = 1.5 °C, PANN = 800 mm) in the middle Holocene interval (ca 8.7-5.2 cal. ka BP). This lags behind the solar insolation peak during the early Holocene. We propose that this is due to continuous Holocene sea level transgression and regional influence of the Tsushima Warm Current, which reached maximum intensity during the middle Holocene. Several short-term climate oscillations are suggested by our reconstruction results and correspond to Northern Hemisphere Heinrich and Dansgaard-Oeschger events, the Bølling-Allerød and the Younger Dryas. The most prominent fluctuation is registered during Heinrich 4 event, which is marked by noticeably colder and drier conditions and the spread of herbaceous taxa.

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.