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Pyrogenic carbon (PyC) is considered one of the most stable components in soil and can represent more than 30% of total soil organic carbon (SOC). However, few estimates of global PyC stock or distribution exist and thus PyC is not included in any global carbon cycle models, despite its potential major relevance for the soil pool. To obtain a global picture, we reviewed the literature for published PyC content in SOC data. We generated the first PyC database including more than 560 measurements from 55 studies. Despite limitations due to heterogeneous distribution of the studied locations and gaps in the database, we were able to produce a worldwide PyC inventory. We found that global PyC represent on average 13.7% of the SOC and can be even up to 60%, making it one of the largest groups of identifiable compounds in soil, together with polysaccharides. We observed a consistent range of PyC content in SOC, despite the diverse methods of quantification. We tested the PyC content against different environmental explanatory variables: fire and land use (fire characteristics, land use, net primary productivity), climate (temperature, precipitation, climatic zones, altitude), and pedogenic properties (clay content, pH, SOC content). Surprisingly, soil properties explain PyC content the most. Soils with clay content higher than 50% contain significantly more PyC (>30% of the SOC) than with clay content lower than 5% (<6% of the SOC). Alkaline soils contain at least 50% more PyC than acidic soils. Furthermore, climatic conditions, represented by climatic zone or mean temperature or precipitation, correlate significantly with the PyC content. By contrast, fire characteristics could only explain PyC content, if site-specific information was available. Datasets derived from remote sensing did not explain the PyC content. To show the potential of this database, we used it in combination with other global datasets to create a global worldwide PyC content and a stock estimation, which resulted in around 200 Pg PyC for the uppermost 2 m. These modeled estimates indicated a clear mismatch between the location of the current PyC studies and the geographical zones where we expect high PyC stocks.

<p><strong>Abstract.</strong> The ongoing debate about the effects of changes in the high-mountain cryosphere on rockfalls and rock avalanches suggests a need for more knowledge about characteristics and distribution of recent rock-slope instabilities. This paper investigates 56 sites with slope failures between 1900 and 2007 in the central European Alps with respect to their geological and topographical settings and zones of possible permafrost degradation and glacial recession. Analyses of the temporal distribution show an increase in frequency within the last decades. A large proportion of the slope failures (60%) originated from a relatively small area above 3000 m a.s.l. (i.e. 10% of the entire investigation area). This increased proportion of detachment zones above 3000 m a.s.l. is postulated to be a result of a combination of factors, namely a larger proportion of high slope angles, high periglacial weathering due to recent glacier retreat (almost half of the slope failures having occurred in areas with recent deglaciation), and widespread permafrost occurrence. The lithological setting appears to influence volume rather than frequency of a slope failure. However, our analyses show that not only the changes in cryosphere, but also other factors which remain constant over long periods play an important role in slope failures.</p>

Place names are often used to describe and to enquire about geographical information. It is common for users to employ vernacular names that have vague spatial extent and which do not correspond to the official and administrative place name terminology recorded within typical gazetteers. There is a need therefore to enrich gazetteers with knowledge of such vague places and hence improve the quality of place name-based information retrieval. Here we describe a method for modelling vague places using knowledge harvested from Web pages. It is found that vague place names are frequently accompanied in text by the names of more precise co-located places that lie within the extent of the target vague place. Density surface modelling of the frequency of co-occurrence of such names provides an effective method of representing the inherent uncertainty of the extent of the vague place while also enabling approximate crisp boundaries to be derived from contours if required. The method is evaluated using both precise and vague places. The use of the resulting approximate boundaries is demonstrated using an experimental geographical search engine.