Plant Functional Type (PFT) map over Siberia derived from GlobCover 2005 dataset, link to dataset in NetCDF format

High-latitude ecosystems play an important role in the global carbon cycle and in regulating the climate system and are presently undergoing rapid environmental change. Accurate land cover data sets are required to both document these changes as well as to provide land-surface information for benchmarking and initializing Earth system models. Earth system models also require specific land cover classification systems based on plant functional types (PFTs), rather than species or ecosystems, and so post-processing of existing land cover data is often required. This study compares over Siberia, multiple land cover data sets against one another and with auxiliary data to identify key uncertainties that contribute to variability in PFT classifications that would introduce errors in Earth system modeling. Land cover classification systems from GLC 2000, GlobCover 2005 and 2009, and MODIS collections 5 and 5.1 are first aggregated to a common legend, and then compared to high-resolution land cover classification systems, vegetation continuous fields (MODIS VCFs) and satellite-derived tree heights (to discriminate against sparse, shrub, and forest vegetation). The GlobCover data set, with a lower threshold for tree cover and taller tree heights and a better spatial resolution, tends to have better distributions of tree cover compared to high-resolution data. It has therefore been chosen to build new PFT maps for the ORCHIDEE land surface model at 1 km scale. Compared to the original PFT data set, the new PFT maps based on GlobCover 2005 and an updated cross-walking approach mainly differ in the characterization of forests and degree of tree cover. The partition of grasslands and bare soils now appears more realistic compared with ground truth data. This new vegetation map provides a framework for further development of new PFTs in the ORCHIDEE model like shrubs, lichens and mosses, to represent the water and carbon cycles in northern latitudes better. Updated land cover data sets are critical for improving and maintaining the relevance of Earth system models for assessing climate and human impacts on biogeochemistry and biophysics.

Crustaceans and fish abundances and species at and around artificially introduced tetrapod fields in the southern North Sea, 2009

The micro-scale spatial distribution patterns of a demersal fish and decapod crustacean assemblage were assessed in a hard-bottom kelp environment in the southern North Sea. Using quadrats along line transects, we assessed the in situ fish and crustacean abundance in relation to substratum types (rock, cobbles and large pebbles) and the density of algae. Six fish and four crustacean species were abundant, with Ctenolabrus rupestris clearly dominating the fish community and Galathea squamifera dominating the crustacean community. Differences in the substratum types had an even stronger effect on the micro-scale distribution than the density of the dominating algae species. Kelp had a negative effect on the fish abundances, with significantly lower average densities in kelp beds compared with adjacent open areas. Averaged over all of the substrata, the most attractive substratum for the fish was large pebbles. In contrast, crustaceans did not show a specific substratum affinity. The results clearly indicate that, similar to other complex systems, significant micro-scale species-habitat associations occur in northern hard-bottom environments. However, because of the frequently harsh environmental conditions, these habitats are mainly sampled from ships with sampling gear, and the resulting data cannot be used to resolve small-scale species-habitat associations. A detailed substratum classification and community assessment, often only possible using SCUBA diving, is therefore important to reach a better understanding of the functional relationships between species and their environment in northern temperate waters, knowledge that is very important with respect to the increasing environmental pressure caused by global climate change.