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Accurate precipitation maps are essential for ecological, environmental, element cycle and hydrological models that have a spatial output component. It is well known that topography has a major influence on the spatial distribution of precipitation and that increasing topographical complexity is associated with increased spatial heterogeneity in precipitation. This means that when mapping precipitation using classical interpolation techniques (e.g. regression, kriging, spline, inverse distance weighting, etc.), a climate measuring network with higher spatial density is needed in mountainous areas in order to obtain the same level of accuracy as compared to flatter regions. In this study, we present a mean total annual precipitation mapping technique that combines topographical information (i.e. elevation and slope orientation)with average total annual rain gauge data in order to overcome this problem. A unique feature of this paper is the identification of the scale at which topography influences the precipitation pattern as well as the direction of the dominant weather circulation. This method was applied for Belgium and surroundings and shows that the identification of the appropriate scale at which topographical obstacles impact precipitation is crucial in order to obtain reliable mean total annual precipitation maps. The dominant weather circulation is determined at 260. Hence, this approach allows accurate mapping of mean annual precipitation patterns in regions characterized by rather high topographical complexity using a climate data network with a relatively low density and/or when more advanced precipitation measurement techniques, such as radar, aren’t available, for example in the case of historical data.

This research investigates the impact of human activities on carbon (C) dynamics in a mountainous and semi-arid environment. Despite the low C status of drylands, soil organic carbon (SOC) is the largest C pool in these systems and therefore may offer significant C sequestration potential in systems recovering from degradation. Nevertheless, quantification of this potential is limited by lack of knowledge concerning the magnitude of and controls on regional SOC stocks. Therefore, this study aimed to (i) investigate the variability of soil organic carbon in relation to recovery period and key soil and topographical variables, and (ii) quantify the effects of recovery period following abandonment on SOC stocks. Soil profiles were sampled in the Sierra de los Filabres (southeast Spain) in different land units along geomorphic and degradation gradients. SOC contents were modelled using recovery period and soil and topographical variables. Sample depth, topographic position, altitude, recovery period and stone content were identified as the main factors for predicting SOC concentrations. SOC stocks in 1 m depth of soil varied between 3.16 and 76.44 t/ha. Recovery period (years since abandonment), topographic position and altitude were used to predict and map SOC stocks in the top 0.2 m. The results show that C accumulates rapidly during the first 10-50 yr following abandonment; thereafter, the stocks evolve towards a steady-state level. The erosion zones in the study area demonstrate greater potential to increase their SOC stocks when abandoned. Deposition zones have greater SOC values, although their C accumulation rate is lower compared with erosional landscapes in the first 10-50 yr following abandonment. Therefore, full understanding of the C sequestration potential of land use change in areas of complex topography requires knowledge of spatial variability in soil properties and in particular SOC. © 2012 British Society of Soil Science.

Development of a quantitative understanding of soil organic carbon (SOC) dynamics is vital for management of soil to sequester carbon (C) and maintain fertility, thereby contributing to food security and climate change mitigation. There are well-established process-based models that can be used to simulate SOC stock evolution; however, there are few plant residue C input values and those that exist represent a limited range of environments. This limitation in a fundamental model component (i.e., C input) constrains the reliability of current SOC stock simulations. This study aimed to estimate crop-specific and environment-specific plant-derived soil C input values for agricultural sites in France based on data from 700 sites selected from a recently established French soil monitoring network (the RMQS database). Measured SOC stock values from this large scale soil database were used to constrain an inverse RothC modelling approach to derive estimated C input values consistent with the stocks. This approach allowed us to estimate significant crop-specific C input values (P < 0.05) for 14 out of 17 crop types in the range from 1.84 ± 0.69 t C ha-1 year-1 (silage corn) to 5.15 ± 0.12 t C ha-1 year-1 (grassland/pasture). Furthermore, the incorporation of climate variables improved the predictions. C input of 4 crop types could be predicted as a function of temperature and 8 as a function of precipitation. This study offered an approach to meet the urgent need for crop-specific and environment-specific C input values in order to improve the reliability of SOC stock prediction. © 2013 Soil Science Society of China.

This study addressed long-term land degradation and regeneration effects on soil organic carbon (SOC) composition. Thiswas done in a context of secondary succession following land abandonment in theMediterranean region of SE Spain. The effects of land use change and soil erosion on SOC composition were studied by using lignin as a biomarker. To get insight into the evolution of SOC composition along a land use and topographical gradient, differences in lignin contribution to SOC were determined at different soil depths (0–0.1m, 0.1–0.2 m, 0.2–0.3m). Three deposition locations, three positions on the hillslope and three zones on top of the hillslope (shoulder) were selected on croplands and fields that were abandoned since 10 and 50 years, respectively. Land use change was identified as a driver for the observed gradients in lignin, SOC and N in these semi-arid ecosystems. Abandoned sites were highest in soil lignin, which could be related to the higher lignin input. For deposition and shoulder positions lignin was less degraded at abandoned sites compared to cultivated sites. On croplands lignin was more degraded at hillslope locations compared to deposition zones. Observed differences in soil lignin quantity were highest for the topsoil (0–0.1 m). For deeper soil, differences are less pronounced. However, no differences were evident for lignin contribution to SOC (mg lignin phenols/g SOC). As modern soil erosion rates are very low in the study area, SOC composition on abandoned fields may be more influenced by present day vegetation and its degradation than by soil erosion. Surprisingly, lignin contribution to SOC was not favored by vegetation recovery either. The higher soil N contents for abandoned fields compared to croplands might explain why lignin is not preferentially preserved on recovered sites.

Given the importance of soil organic carbon (SOC) as a pool in the global carbon cycle and an indicator for soil quality, there exits an urgent need to monitor this dynamic soil property. Here, we present a modelling approach to analyze the spatial patterns and temporal evolution of organic carbon in mineral soils under agricultural land use in Belgium. An empirical model, predicting the SOC concentration in the top 0.3 m, as a function of precipitation, land use, soil type and management has been constructed and applied within a spatial context using data from different time slices. The results show that SOC content is strongly correlated with precipitation and temperature under cropland and with texture and drainage under grassland. Total SOC stock increased with 1.3% from 6.18 ± 0.03 kg C m−2 in 1960 to 6.26 ± 0.07 kg C m−2 in 2006. Although this increase was not significant (P>0.05), a significant discrepancy between cropland (−8%) and grassland (+10%) was observed. Foremost, the grasslands in the hilly southern part of the country, under relatively wet climate conditions, acted as important sinks of CO2. Under cropland, all soil types were characterized by a decrease in SOC, except for the clay soils in the north-west. Currently, croplands in the central loam region have SOC concentrations close to 10 g C kg−1 indicating that these soils are at risk of a decline in aggregate stability. An overall strong SOC decline in poorly drained soils is probably caused by artificial drainage. Further research is needed to gain more insight into the processes driving the observed SOC trends. Moreover, the use of updated drainage class information and land management history would improve the empirical models.