Modelling of intensive and extensive farming in CLUE

land use modelling framework EURURALIS, and will allow EURURALIS to predict the effect on land use intensity of future policy under different scenarios. In turn, this makes it possible to predict policy effects on intensity-related biodiversity issues on the EU-level. Our method defines agricultural land use intensity in terms of nitrogen input. For arable land, it first combines the Land Use / Cover Area frame statistical Survey (LUCAS) dataset with Common Agricultural Policy Regionalised Impact modelling system (CAPRI) results to assess probability of occurrence for three classes of intensity. For grassland, it uses available spatially explicit predictions of livestock intensity to assess probability of occurrence for two classes of intensity. Then, agricultural land in different intensity classes is spatially allocated using a simple allocation algorithm. We illustrate and evaluate this method for five countries: the Netherlands, Portugal, Spain, Greece and Poland. Intensity predictions are made for two years: 2000 (ex-post) and 2025 (using the Financial Policy Reform Scenario from the FP6 EU SENSOR project). This report contains building bocks for a possible future quality status of the method

Adaptation to climate change on arable farms in the Dutch province of Flevoland. An inventory for the AgriAdapt project

In Flevoland, arable farming is the most dominant land use. Adaptation options related to water, pests and diseases have been studied using a literature review. The green-blue zone Oostvaarderswold in Flevoland contributes to water storage, to nature conservation and to recreation. Compensation costs for structural wetting that are associated with various frequencies of flooding have been calculated. At inundation frequencies greater than once in 5 years, buying the agricultural land might be a better option than compensating for inundation damage or income loss. Various policies will have an effect on future agriculture in the province. A literature survey of spatial policy plans shows that urbanisation will increase and that some cities, like Almere, Lelystad, Dronten and Emmeloord, will continue to grow and expand. As a consequence, more inhabitants will require more space for nature and recreational activities, which in turn will lead to agricultural land being required

Global change of land use systems : IMAGE: a new land allocation module

The Integrated Model to Assess the Global Environment (IMAGE) aims at assessing the state of the environment taking into account the effects of human activities. Although human population often makes use of a land area to satisfy various needs, most of the current global land use datasets and models use a classification based on dominant land use/cover types disregarding the diversity and intensity of human activities. In this working document we investigate if the simulation of land use change and the IMAGE outcomes can be improved by using a classification based on land use systems. An expert based cluster analysis was used to identify and map land use systems. The analysis accounted for population density, accessibility, land use / cover types and livestock and provided a new insight on human interactions with the environment. Then, a conceptual framework was developed and implemented to simulate land use systems changes based on local conditions and demand for agricultural products and accounting for land management changes

Sensitivity of discharge and flood frequency to twenty-first century and late Holocene changes in climate and land use (River Meuse, northwest Europe)

We used a calibrated coupled climate–hydrological model to simulate Meuse discharge over the late Holocene (4000–3000 BP and 1000–2000 AD). We then used this model to simulate discharge in the twenty-first century under SRES emission scenarios A2 and B1, with and without future land use change. Mean discharge and medium-sized high-flow (e.g. Q99) frequency are higher in 1000–2000 AD than in 4000–3000 BP; almost all of this increase can be attributed to the conversion of forest to agriculture. In the twentieth century, mean discharge and the frequency of medium-sized high-flow events are higher than in the nineteenth century; this increase can be attributed to increased (winter half-year) precipitation. Between the twentieth and twenty-first centuries, anthropogenic climate change causes a further increase in discharge and medium-sized high-flow frequency; this increase is of a similar order of magnitude to the changes over the last 4,000 years. The magnitude of extreme flood events (return period 1,250-years) is higher in the twenty-first century than in any preceding period of the time-slices studied. In contrast to the long-term influence of deforestation on mean discharge, changes in forest cover have had little effect on these extreme floods, even on the millennial timescale

Towards a low carbon economy in the Amazon: the role of land-use policies

Climate change, rising oil prices and the global financial crisis has put sustainability and ‘green growth’ of the economy on the political agenda. While the transition towards a “low carbon” economy in developed countries like in the European Union should mainly be found in renewable energy production, developing countries like Brazil face with high land use emissions which will further rise in the coming decades without proper policy instruments. Deforestation and cattle production are the main sources of land use emissions in Brazil and we expect that these emissions will further rise with liberalisation of agricultural trade. A transition towards a “low carbon” economy in Brazil thus calls for appropriate, and effective land-use policies. Agricultural intensification on one hand can meet the world demand for soy and beef. For example we calculate that increasing the meat content of cattle can reduce emissions from deforestation up to 30%, but intensification may also accelerate further deforestation of Cerrado and Amazon forests. In order to avoid such additional deforestation, large areas of degraded lands have to be taken back into production, which requires large agricultural investments. In addition, (new) economic instruments, monitoring, law enforcement and appropriate conservation policies are also needed to halt further deforestation and biodiversity loss. The recently amended change of the Forest Code policy, for example, is expected to accelerate deforestation further, thus making more difficult to reach mitigation targets for the Brazilian State

Land-use change simulation and assessment of driving factors in the loess hilly region - a case study as Pengyang County

The main objective of this study is to evaluate the land-use change and its relationship with its driving factors in the loess hilly region. In this study, a case study was carried out in Pengyang County. We set two land-use demand scenarios (a baseline scenario (scenario 1) and a real land-use requirement scenario (scenario 2)) during year 2001-2005 via assuming the effect of driving factors on land-use change keeps stable from 1993 to 2005. Two simulated land-use patterns of 2005 are therefore achieved accordingly by use of the conversion of land use and its effects model at small regional extent. Kappa analyses are conducted to compare each simulated land-use pattern with the reality. Results show that (1) the associated kappa values were decreased from 0.83 in 1993-2000 to 0.27 (in scenario 1) and 0.23 (in scenario 2) in 2001-2005 and (2) forest and grassland were the land-use types with highest commission errors, which implies that conversion of both the land-use types mentioned above is the main determinant of change of kappa values. Our study indicates the land-use change was driven by the synthetic multiply factors including natural and social-economic factors (e.g., slope, aspect, elevation, distance to road, soil types, and population dense) in 1993-2000 until "Grain for Green Project" was implemented and has become the dominant factor in 2001-2005

Assessing spatial uncertainties of land allocation using the scenario approach and sensitivity analysis

The paper assess uncertainty of future spatial allocation of agricultural land in Europe. To assess the possible future development of agricultural production and land for the period 2000 – 2030, two contrasting scenarios are constructed. The scenarios storylines lead to different measurable assumptions concerning scenario specific drivers (variables) and parameters. Many of them are estimations and thus include a certain level of uncertainty regarding their true values. This leads to uncertainty of the scenario outcomes. In this study we use sensitivity analysis to estimate the uncertainty of agricultural land use.spatial uncertainty, scenario approach, sensitivity analysis., Agribusiness, Agricultural and Food Policy, Community/Rural/Urban Development, Food Consumption/Nutrition/Food Safety, Labor and Human Capital,

An Altered Derivatives Marketplace: Clearing Swaps Under Dodd-Frank

Though over a year has passed, the impact of the Dodd Frank Act remains unclear. This Note examines the provisions of the Act that relate to swap transactions within the context of pre-reform and postreform markets. In order to reduce the uncertainties inherent in unregulated swap transactions, the Act employs a comprehensive framework, which includes mandatory clearing through derivative clearing organizations, extensive reporting requirements, margin requirements, and position limits. This Note argues that, in doing so, the Dodd Frank Act addresses the fundamental failures of pre-reform derivative markets. However, the importance of the role for derivative clearing organizations under this framework creates a risk that these organizations will become systemically significant, mirroring problems with under-capitalized and over-exposed financial institutions in the downturn