Forest disturbance map for the Carpathian ecoregion, 1984-2012

Detailed knowledge of forest cover dynamics is crucial for many applications from resource management to ecosystem service assessments. Landsat data provides the necessary spatial, temporal and spectral detail to map and analyze forest cover and forest change processes. With the opening of the Landsat archive, new opportunities arise to monitor forest dynamics on regional to continental scales. In this study we analyzed changes in forest types, forest disturbances, and forest recovery for the Carpathian ecoregion in Eastern Europe. We generated a series of image composites at five year intervals between 1985 and 2010 and utilized a hybrid analysis strategy consisting of radiometric change classification, post-classification comparison and continuous index- and segment-based post-disturbance recovery assessment. For validation of the disturbance map we used a point-based accuracy assessment, and assessed the accuracy of our forest type maps using forest inventory data and statistically sampled ground truth data for 2010. Our Carpathian-wide disturbance map achieved an overall accuracy of 86% and the forest type maps up to 73% accuracy. While our results suggested a small net forest increase in the Carpathians, almost 20% of the forests experienced stand-replacing disturbances over the past 25 years. Forest recovery seemed to only partly counterbalance the widespread natural disturbances and clear-cutting activities. Disturbances were most widespread during the late 1980s and early 1990s, but some areas also exhibited extensive forest disturbances after 2000, especially in the Polish, Czech and Romanian Carpathians. Considerable shifts in forest composition occurred in the Carpathians, with disturbances increasingly affecting coniferous forests, and a relative decrease in coniferous and mixed forests. Both aspects are likely connected to an increased vulnerability of spruce plantations to pests and pathogens in the Carpathians. Overall, our results exemplify the highly dynamic nature of forest cover during times of socio-economic and institutional change, and highlight the value of the Landsat archive for monitoring these dynamics.

Permanent open water surfaces in central Siberia from ENVISAT ASAR wide swath data 2003/2004, link to shapefile

Permanent water bodies not only store dissolved CO2 but are essential for the maintenance of wetlands in their proximity. From the viewpoint of greenhouse gas (GHG) accounting wetland functions comprise sequestration of carbon under anaerobic conditions and methane release. The investigated area in central Siberia covers boreal and sub-arctic environments. Small inundated basins are abundant on the sub-arctic Taymir lowlands but also in parts of severe boreal climate where permafrost ice content is high and feature important freshwater ecosystems. Satellite radar imagery (ENVISAT ScanSAR), acquired in summer 2003 and 2004, has been used to derive open water surfaces with 150 m resolution, covering an area of approximately 3 Mkm**2. The open water surface maps were derived using a simple threshold-based classification method. The results were assessed with Russian forest inventory data, which includes detailed information about water bodies. The resulting classification has been further used to estimate the extent of tundra wetlands and to determine their importance for methane emissions. Tundra wetlands cover 7% (400,000 km**2) of the study region and methane emissions from hydromorphic soils are estimated to be 45,000 t/d for the Taymir peninsula.

Wetlands in central Siberia from ASAR WS 2003, link to shapefiles

An area in central Siberia (partial coverage of Turukhansky und Yeniseysky districts) was investigated using satellite data. It covers freshwater ecosystems of non-forested peatlands in boreal forests. The satellite data represent the growing seasons of 2003/2004. Microwave data were acquired by the Advanced Synthetic Aperture Radar (ASAR) instrument onboard ENVISAT. The multi-temporal capabilities and resolution (150mx150m in WS mode) of the ASAR wide swath mode enabled the detection of dynamic features >2ha over this vast area. Scatterometer (QuikScat) data could be employed to distinguish hydro-periods. Wetland types have been identified on the basis of seasonal changes in backscatter. Results for peatlands have been compared with Russian forest inventory data which contain information on wetland distribution.

Pollen from 50 lake surface samples in Brandenburg, Germany, in 2009

Past changes in plant and landscape diversity can be evaluated through pollen analysis, however, pollen based diversity indexes are potentially biased by differential pollen production and deposition. Studies examining the relationship between pollen and landscape diversity are therefore needed. The aim of this study is to evaluate how different pollen based indexes capture aspects of landscape diversity. Pollen counts were obtained from surface samples of 50 small to medium sized lakes in Brandenburg (Northeast Germany) and compiled into two sets, with one containing all pollen counts from terrestrial plants and the second restricted to wind-pollinated taxa. Both sets were adjusted for the pollen production/dispersal bias using the REVEALS model. A high resolution biotope map was used to extract the density of total biotopes and different biotopes per area as parameters describing landscape diversity. In addition tree species diversity was obtained from forest inventory data. The Shannon index and the number of taxa in a sample of 10 pollen grains are highly correlated and provide a useful measure of pollen type diversity which corresponds best to landscape diversity within one km of the lake and the proportion of non-forested area within seven km. Adjustments of the pollen production/dispersal bias only slightly improve the relationships between pollen diversity and landscape diversity for the restricted dataset as well as for the forest inventory data and corresponding pollen types. Using rarefaction analysis, we propose the following convention: pollen type diversity is represented by the number of types in a small sample (low count e.g. 10), pollen type richness is the number of types in a large sample (high count e.g. 500) and pollen sample evenness is characterized by the ratio of the two. Synthesis. Pollen type diversity is a robust index that captures vegetation structure and landscape diversity. It is ideally suited for between site comparisons as it does not require high pollen counts. In concert with pollen type richness and evenness, it helps evaluating the effect of climate change and human land use on vegetation structure on long timescales.

Spatially explicit methane inventory for Switzerland with 500 m x 500 m resolution for 2011 (NetCDF 25 MB)

We present the first high-resolution (500 m × 500 m) gridded methane (CH4) emission inventory for Switzerland, which integrates the national emission totals reported to the United Nations Framework Convention on Climate Change (UNFCCC) and recent CH4 flux studies conducted by research groups across Switzerland. In addition to anthropogenic emissions, we also include natural and semi-natural CH4 fluxes, i.e., emissions from lakes and reservoirs, wetlands, wild animals as well as uptake by forest soils. National CH4 emissions were disaggregated using detailed geostatistical information on source locations and their spatial extent and process- or area-specific emission factors. In Switzerland, the highest CH4 emissions in 2011 originated from the agricultural sector (150 Gg CH4/yr), mainly produced by ruminants and manure management, followed by emissions from waste management (15 Gg CH4/yr) mainly from landfills and the energy sector (12 Gg CH4/yr), which was dominated by emissions from natural gas distribution. Compared to the anthropogenic sources, emissions from natural and semi-natural sources were relatively small (6 Gg CH4/yr), making up only 3 % of the total emissions in Switzerland. CH4 fluxes from agricultural soils were estimated to be not significantly different from zero (between -1.5 and 0 Gg CH4/yr), while forest soils are a CH4 sink (approx. -2.8 Gg CH4/yr), partially offsetting other natural emissions. Estimates of uncertainties are provided for the different sources, including an estimate of spatial disaggregation errors deduced from a comparison with a global (EDGAR v4.2) and a European CH4 inventory (TNO/MACC). This new spatially-explicit emission inventory for Switzerland will provide valuable input for regional scale atmospheric modeling and inverse source estimation.