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Environmental modelling combined with scenarios provides insights into drivers of change, potential implications of different trajectories, and options for action. So far, there has been no endeavor to assess the breadth of assumptions concerning drivers of ecosystem change on a global and European level as used in various scenario approaches. Our paper fills this gap by reviewing drivers of 27 global and European scenarios to provide an overview of extreme assumptions. Additionally, results can support quantification efforts of storylines to test environmental and ES models and to facilitate participatory scenario development to improve the usefulness of modelling approaches for stakeholders.

Land-use and land-cover changes are driving unprecedented changes in ecosystems and environmental processes at different scales. This study was aimed at identifying the potential land-use drivers in the Jedeb catchment of the Abbay basin by combining statistical analysis, field investigation and remote sensing. To do so, a land-use change model was calibrated and evaluated using the SITE (SImulation of Terrestrial Environment) modelling framework. SITE is cellular automata based multi-criteria decision analysis framework for simulating land-use conversion based on socio-economic and environmental factors. Past land-use trajectories (1986–2009) were evaluated using a reference Landsat-derived map (agreement of 84%). Results show that major land-use change drivers in the study area were population, slope, livestock and distances from various infrastructures (roads, markets and water). It was also found that farmers seem to increasingly prefer plantations of trees such as Eucalyptus by replacing croplands perhaps mainly due to declining crop yield, soil fertility and climate variability. Potential future trajectory of land-use change was also predicted under a business-as-usual scenario (2009–2025). Results show that agricultural land will continue to expand from 69.5% in 2009 to 77.5% in 2025 in the catchment albeit at a declining rate when compared with the period from 1986 to 2009. Plantation forest will also increase at a much higher rate, mainly at the expense of natural vegetation, agricultural land and grasslands. This study provides critical information to land-use planners and policy makers for a more effective and proactive management in this highland catchment.

Biofuel initiatives in India have gained momentum with the national biofuel policy targeting 20% blending of both petrol and diesel by 2017. Most of India's biofuel plans revolve around using sugarcane for bioethanol and jatropha for biodiesel production. This study, taking the southern Indian state of Karnataka as an example, aims at estimating the potential to achieve policy targets. The study spatially analyses land-use change owing to biofuel expansion and its effects on food production. We used an integrated modelling framework to simulate land-use change and bioenergy production under two scenarios Industrial Economy (IE) and Agricultural Economy (AE). Results indicate that meeting the 20% blending target is a challenging goal to achieve under both scenarios. Bioethanol requirements can be nearly fulfilled (88% under IE and 93% under AE) because of sugarcane expansion. However, biodiesel demands cannot be fulfilled using only degraded lands as currently planned in India, but additional agricultural land (34% of the total cropland) will be required for jatropha-based biodiesel production. Food production will not be directly impacted until 2025, because the largest source of additional land could be short- and long-term fallows. We conclude that conservation oriented initiatives, such as water harvesting and energy conservation measures can increase productivities of biofuel crops and reduce fuel demands, respectively. State support and Clean Development Mechanism opportunities can enhance economic incentives for energy cropping. Therefore, a simultaneous and multipronged approach is needed to accommodate food and fuel demands in India.

Agriculture has become a key element within the earth system as it changes global biogeochemical and water cycles, while global environmental change affects land productivity and thus future land-use decisions. To address these issues and their complex interdependency in a consistent modelling approach we adapted the agro-ecosystem model DayCent for the simulation of major crops at the global scale. Based on a global compilation of environmental and management data and an algorithm to calculate global planting dates, DayCent was parameterised and calibrated to simulate global yield levels for wheat, maize, rice and soybeans. Simulation results show that the DayCent model is able to reproduce the major effects of climate, soil and management on crop production. Average simulated crop yield per country agree well with agricultural statistics (Modelling efficiency is about 0.66 for wheat, rice and maize, and 0.32 for soybean) and spatial patterns of yields generally correspond to observed crop distributions and sub-national census data.

Nutrient flux and balance studies are valuable tools to assess the sustainability of agro-ecosystems and potential consequences for agricultural productivity. This paper presents results from a study at the field/farm scale representing mixed farming systems typical for the East African Highlands. We selected catchments in the Dega (cool highlands and Woina Dega (warm-to-cool mid-highlands) of the Central Highlands of Ethiopia, to get more insight on how individual land use strategies and access to resources affect the magnitude of nutrient flows and resulting balances and to explore some of reasons of the variability within and between farming systems at different altitudes. Our results show that environmental condition, farming system (e.g. choice of crop), access to resources (e.g. land, livestock and fertilizer) and smallholders’ source of off farm income influence the magnitude of nutrient fluxes and the degree to which nutrient fluxes may be imbalanced. In some respects our results differ from studies carried out at larger (i.e. more aggregated) spatial scales, which consistently show that homestead fields are zones of accumulation and distant fields as zone of depletion. Our results indicate that this is not always the case, and highlight the need for studies at the field and farm scales to include detailed biophysical and socioeconomic information to help explain major nutrient fluxes and to evaluate the system with respect to sustainable production.

Natural vegetation mosaics of heterogeneous forests, shrubs and savanna are characteristic for the thinly populated Venezuelan Guayana. Vegetation studies and 14C data suggested that the mosaic represents a stage in a long-term process of savannisation, which is originally triggered by forest fires. In the paper, we are looking for the possible role the soil plays in this process. Vegetation structure and soil chemical conditions were analyzed in 74 plots. We further studied the composition of soil solution or water extract, fine root distribution, aboveground biomass and total nutrient stores in selected sites. The soils are humic ferralsols and under woody vegetation, always covered by an organic layer (8–114 t ha−1). The mineral soil is characterized by high organic matter content (0–50 cm: 113–165 t C ha−1), a low cation exchange capacity of the mineral soil (0.94 cmolc kg−1 of clay), and a dominant Al saturation of the exchange complex. Under forest, Ca concentrations on the exchange complex, and in the soil solution/water extract, rank below that of NH4, K, Mg and Fe. Ca-deficiency is considered the main element of the chemical stress responsible for the extremely shallow rooting (

The distribution of vegetation types in Venezuelan Guyana (in the ‘Canaima’ National Park) represents a transitional stage in a long term process of savannization, a process considered to be conditioned by a combined chemical and intermittent drought stress. All types of woody vegetation in this environment accumulate large amounts of litter and soil organic carbon (SOC). We hypothesized that this accumulation is caused by low microbial activity. During 1 year we measured microbial biomass carbon (Cmic), microbial respiration and soil respiration of stony Oxisols (Acrohumox) at a tall, a medium and a low forest and with three chemical modifications of site conditions by the addition of NO 3 − , Ca 2+ and PO 4 3− as possible limiting elements. Due to high SOC contents, mean Cmic was 1 mg g soil −1 in the mineral topsoil and 3 mg g soil −1 in the forest floor. Mean microbial respiration in the mineral topsoil and the forest floor were 165 and 192 μg CO 2 -C g soil −1 d −1 , respectively. We calculated high mean metabolic quotients ( q CO 2 ) of 200 mg CO 2 -C g Cmic −1 d −1 in the litter layer and 166 mg CO 2 -C g Cmic −1 d −1 in the mineral topsoil, while the Cmic-to-SOC ratios were as low as 1.0% in the litter layer and 0.8% in the mineral topsoil. Annual soil respiration was 9, 12 and 10 Mg CO 2 -C ha −1 yr −1 in the tall, medium and low forest, respectively. CO 2 production was significantly increased by CaHPO 4 fertilization, but no consistent effects were caused by Ca 2+ and NO 3 − , fertilization. Our findings indicate that Cmic and microbial respiration are reduced by low nutrient concentrations and low litter and SOC quality. Reduced microbial decomposition may have contributed to SOC accumulation in these forests.

Climate change scenarios vary considerably over the Amazon region, with an extreme scenario projecting a dangerous (from the human perspective) increase of 3.8°C in temperature and 30% reduction in precipitation by 2050. The impacts of such climate change on Amazonian land-use dynamics, agricultural production, and deforestation rates are still to be determined. In this study, the authors make a first attempt to assess these impacts through a systemic approach, using a spatially explicit modeling framework to project crop yield and land-use/land-cover changes in the Brazilian Amazon by 2050. The results show that, without any adaptation, climate change may exert a critical impact on the yields of crops commonly cultivated in the Amazon (e.g., soybean yields are reduced by 44% in the worst-case scenario). Therefore, following baseline projections on crop and livestock production, a scenario of severe regional climate change would cause additional deforestation of 181 000 km2 (+20%) in the Amazon and 240 000 km2 (+273%) in the Cerrado compared to a scenario of moderate climate change. Putting an end to deforestation in the Brazilian Amazon forest by 2020 (and of the Cerrado by 2025) would require either a reduction of 26%–40% in livestock production until 2050 or a doubling of average livestock density from 0.74 to 1.46 head per hectare. These results suggest that (i) climate change can affect land use in ways not previously explored, such as the reduction of yields entailing further deforestation, and (ii) there is a need for an integrated/multidisciplinary plan for adaptation to climate change in the Amazon.

The planned expansion of biofuel plantations in Brazil could potentially cause both direct and indirect land-use changes (e.g., biofuel plantations replace rangelands, which replace forests). In this study, we use a spatially explicit model to project land-use changes caused by that expansion in 2020, assuming that ethanol (biodiesel) production increases by 35 (4) x 10 9 liter in the 2003-2020 period. Our simulations show that direct land-use changes will have a small impact on carbon emissions because most biofuel plantations would replace rangeland areas. However, indirect land-use changes, especially those pushing the rangeland frontier into the Amazonian forests, could offset the carbon savings from biofuels. Sugarcane ethanol and soybean biodiesel each contribute to nearly half of the projected indirect deforestation of 121,970 km 2 by 2020, creating a carbon debt that would take about 250 years to be repaid using these biofuels instead of fossil fuels. We also tested different crops that could serve as feedstock to fulfill Brazil’s biodiesel demand and found that oil palm would cause the least land-use changes and associated carbon debt. The modeled livestock density increases by 0.09 head per hectare. But a higher increase of 0.13 head per hectare in the average livestock density throughout the country could avoid the indirect land-use changes caused by biofuels (even with soybean as the biodiesel feedstock), while still fulfilling all food and bioenergy demands. We suggest that a closer collaboration or strengthened institutional link between the biofuel and cattle-ranching sectors in the coming years is crucial for effective carbon savings from biofuels in Brazil.

The governments of Brazil and India are planning a large expansion of bioethanol and biodiesel production in the next decade. Considering that limitation of suitable land and/or competition with other land uses might occur in both countries, assessments of potential crop productivity can contribute to an improved planning of land requirements for biofuels under high productivity or marginal conditions. In this paper we model the potential productivity of sugarcane and jatropha in both countries. Land requirements for such expansions are calculated according to policy scenarios based on government targets for biofuel production in 2015. Spatial variations in the potential productivity lead to rather different land requirements, depending on where plantations are located. If jatropha is not irrigated, land requirements to fulfill the Indian government plans in 2015 would be of 410000 to 95000 km(2) if grown in low or high productivity areas respectively (mean of 212000 km(2)). In Brazil land requirements, are of 18000-89000 km(2) (mean of 29 000 km(2)), suggesting a promising substitute to soybean biodiesel. Although future demand for sugarcane ethanol in Brazil is approximately ten times larger than in India, land requirements are comparable in both countries due to large differences in ethanol production systems. in Brazil this requirement ranges from 25 000 to 211000 km(2) (mean of 33000 km(2)) and in India from 7000 to 161000 km(2) (mean 17000 km. Irrigation could reduce the land requirements by 63% and 41% (24% and 15%) in India (Brazil) for jatropha and sugarcane respectively. (C) 2009 Elsevier Ltd. All rights reserved.

Forest soils in central Europe have received high atmospheric inputs of protons, sulphate and nitrogen (Chap. 15) since the beginning of industrialisation. As a result, chemical and biological processes in many German forest soils have changed (Godbold and Huttermann 1994) and soil characteristics like pH, base saturation and C/N ratios have altered (Chap. 21). The mechanisms of the fate and the retention of this high atmospheric input of nitrogen still remain unclear. There are reports indicating that, despite high N-deposition since the beginning of the nineteenth century, most forests continue to retain nitrogen (Ulrich 1994; Johnson et al. 1997; Dise et al. 1998; Borken and Matzner 2004) even when the low C/N ratios in the surface organic layer have become low (Brumme and Khanna 2008). This raises the question of the retention mechanisms of nitrogen in forest soils. The use of labelled nitrogen makes it easy to follow internal nitrogen cycle of N-inputs in forest ecosystems (Nadelhoffer et al. 2004; Tietema et al. 1998; Feng et al. 2008) and soils (Mochoge and Beese 1983a, b). Often, labelled nitrogen is applied in a single dose which provides information on the nitrogen transformation rates under the current environmental conditions of addition. We applied constant rates of 15N labelled ammonium and nitrate as an artificial crown drip for long periods on undisturbed soil columns (Brumme and Aden 1995) under field and laboratory conditions in order to simulate continuous N-depositions so as to follow N-transformations under close to field conditions.

Carbon and nitrogen are squantitatively important elements in forest ecosystems. Most of the carbon and nitrogen are stored in the soil and have a long turnover time. Only a small fraction of the N-pool is cycled every year through growth and litter fall and mineralisation of litter. Industrialisation has caused high acid and nitrogen inputs to ecosystems which have affected carbon and nitrogen stocks and mineralisation processes in forest ecosystems. In addition, global change of temperature and precipitation will also have a direct influence on carbon and nitrogen cycles in the short-term and on their stocks in the long-term. In order to detect measurable changes in the carbon and nitrogen stocks of forest soils, several decades and sometimes centuries may be needed because they have by nature high spatial variability and occur in large stocks. Therefore, it is very difficult to obtain information on fluxes of these elements by measuring changes in the bulk stocks. Direct measurements of input and output fluxes may provide useful information to assess any changes of the bulk stocks, and on understanding of human-induced changes in the mineralisation processes, as long as the values of input and output fluxes can be accurately measured.

Biomass for bioenergy is debated for its potential synergies or tradeoffs with other provisioning and regulating ecosystem services (ESS). This biomass may originate from different production systems and may be purposefully grown or obtained from residues. Increased concerns globally about the sustainable production of biomass for bioenergy has resulted in numerous certification schemes focusing on best management practices, mostly operating at the plot/field scale. In this study, we compare the ESS of two watersheds in the southeastern US. We show the ESS tradeoffs and synergies of plantation forestry, i.e., pine poles, and agricultural production, i.e., wheat straw and corn stover, with the counterfactual natural or semi-natural forest in both watersheds. The plantation forestry showed less distinct tradeoffs than did corn and wheat production, i.e., for carbon storage, P and sediment retention, groundwater recharge, and biodiversity. Using indicators of landscape composition and configuration, we showed that landscape planning can affect the overall ESS supply and can partly determine if locally set environmental thresholds are being met. Indicators on landscape composition, configuration and naturalness explained more than 30% of the variation in ESS supply. Landscape elements such as largely connected forest patches or more complex agricultural patches, e.g., mosaics with shrub and grassland patches, may enhance ESS supply in both of the bioenergy production systems. If tradeoffs between biomass production and other ESS are not addressed by landscape planning, it may be reasonable to include rules in certification schemes that require, e.g., the connectivity of natural or semi-natural forest patches in plantation forestry or semi-natural landscape elements in agricultural production systems. Integrating indicators on landscape configuration and composition into certification schemes is particularly relevant considering that certification schemes are governance tools used to ensure comparable sustainability standards for biomass produced in countries with variable or absent legal frameworks for landscape planning.

Soil fertility depletion in smallholder farms is one of the fundamental biophysical causes for declining per capita food production in Ethiopia. In the present study, we assess soil nutrient depletion and its spatial variability for Ethiopia and its regional states, using nutrient balances as a tool. Data on crop production, fertilizer use and land management practices were collected from the Agricultural sample survey, which was carried out by the Central Statistics Authority (CSA) for the production year 1999/2000. We used a Geographic Information System (GIS) to process, and analyze spatially referenced information like soil properties, precipitation and land use types. We calculated nutrient balances for N, P and K from five nutrient fluxes entering and five nutrient fluxes leaving cultivated lands of smallholders. Some of the fluxes (e.g. leaching, denitrification and wet deposition) were estimated using transfer functions. Erosion was estimated by universal soil loss equation (USLE) and landscape process modelling at multi-dimensions and scales (LAPSUS). At the national level, full nutrient balance results indicate a depletion rate of 122 kg N ha −1 yr −1 , 13 kg P ha −1 yr −1 and 82 kg K ha −1 yr −1 . Soil nutrient stocks in all regional states were decreasing with the exception of areas under permanent and vegetable crops. In the analysis, soil erosion was the major cause for nutrients depletion, but this flux shows significant variability between different estimates and was highly uncertain. We calculated that the contribution of erosion to N losses was 70%, while its contribution to P and K losses were 80% and 63%, respectively. Nutrient losses under permanent and vegetable cropping were caused mainly by residues removal, harvested products and leaching, while losses under cereals and other annuals were dominated by erosion.

Changes in land use affect input and output fluxes of nutrients and carbon in soils and vegetation. This can lead to changing soil fertility, which in turn will affect biomass production and human decisions in land management. Next to a local impact on land quality, changing biogeochemical cycles can also have a global impact through the emission of greenhouse gasses. The drivers and processes of land use change related nutrient and carbon fluxes are scale-dependent. In this paper, we propose a conceptual dynamic approach (CLUE–Nuts) for the modelling of the interaction between land use change and nutrient and carbon fluxes. It is based on the integration of a spatially explicit multi-scale land use change model (CLUE) with a nutrient monitoring approach (NUTMON). Near future changes in the areas of agricultural crops and natural vegetation can be modelled in scenarios and their effects on soil nutrient and carbon status estimated. Feedback mechanisms for major crops can be included, taking into account that matter fluxes can alter carbon and nutrient stocks considerably. The feasibility of the new approach is illustrated with data from a case study for Ecuador. From these preliminary results it is concluded that CLUE–Nuts is a powerful tool to predict crop specific near future land use and related nutrient fluxes. The suggested feedback mechanisms are suitable for major crops with excellent data representation, and are subject of further refinement and research.