358 research outputs found

    Modelling of intensive and extensive farming in CLUE

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    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

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

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    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)

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    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

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

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    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

    Evaluation of agricultural ecosystem services in fallowing land based on farmers' participation and model simulation

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    Fallowing with green fertilizer can benefit agricultural ecosystem services (AES). Farmers in Taiwan do not implement fallow practices and plant green fertilizer because the current subsidy level (46,000 NTperha)istoolowtomanagefallowing.Thispaperdefinestheobjectiveofgovernmentagriculturepolicyorthefarmer’sobjectiveasmaximizationoffarmproductivity,approximatedtothevalueofsocialwelfareandAES.Farms,whichdonotfollowproperfallowingpractices,oftenhavepoorlymaintainedfallowlandorleftfarmlandabandoned.Thisresultsinnegativeenvironmentalconsequencessuchascutworminfestationsinabandonedland,whichinturncanaffectcropsinadjacentfarmlands.Theobjectivesofthisstudyaretwofold.First,itdeterminestheproperfallowingsubsidybasedontheconceptofpaymentforecosystemservicestoenticemorefarmerstoparticipateinfallowing.Second,itsimulatesthebenefitofplantinggreenmanureinfallowlandtothesupplyofAESbasedontherateoffarmerswhoarewillingtoparticipateinfallowlandpracticesandessentialparametersthatcanaffectsoilfertilitychange.Theapproachinvolvesaseriesofinterviewsandadevelopedempiricalmodel.ThevalueofAESwhentherateoffarmerparticipationis100 per ha) is too low to manage fallowing. This paper defines the objective of government agriculture policy or the farmer’s objective as maximization of farm productivity, approximated to the value of social welfare and AES. Farms, which do not follow proper fallowing practices, often have poorly maintained fallow land or left farmland abandoned. This results in negative environmental consequences such as cutworm infestations in abandoned land, which in turn can affect crops in adjacent farmlands. The objectives of this study are twofold. First, it determines the proper fallowing subsidy based on the concept of payment for ecosystem services to entice more farmers to participate in fallowing. Second, it simulates the benefit of planting green manure in fallow land to the supply of AES based on the rate of farmers who are willing to participate in fallow land practices and essential parameters that can affect soil fertility change. The approach involves a series of interviews and a developed empirical model. The value of AES when the rate of farmer participation is 100% represents a 1.5% increase in AES (448,317,000 NTperha)istoolowtomanagefallowingThispaperdefinestheobjectiveofgovernmentagriculturepolicyorthefarmer’sobjectiveasmaximizationoffarmproductivityapproximatedtothevalueofsocialwelfareandAESFarmswhichdonotfollowproperfallowingpracticesoftenhavepoorlymaintainedfallowlandorleftfarmlandabandonedThisresultsinnegativeenvironmentalconsequencessuchascutworminfestationsinabandonedlandwhichinturncanaffectcropsinadjacentfarmlandsTheobjectivesofthisstudyaretwofoldFirstitdeterminestheproperfallowingsubsidybasedontheconceptofpaymentforecosystemservicestoenticemorefarmerstoparticipateinfallowingSeconditsimulatesthebenefitofplantinggreenmanureinfallowlandtothesupplyofAESbasedontherateoffarmerswhoarewillingtoparticipateinfallowlandpracticesandessentialparametersthatcanaffectsoilfertilitychangeTheapproachinvolvesaseriesofinterviewsandadevelopedempiricalmodelThevalueofAESwhentherateoffarmerparticipationis100 ) over the value at the current participation rate of 14%. This study further concludes that the appropriate fallowing subsidy has a large positive impact on AES and social welfare (e.g., benefit from food and biofuel supplies) and is seen as a basis of ecological governance for sustainable agro-ecosystems

    An agent-based approach to model land-use change at a regional scale

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    Land-use/cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. A common approach to analyse and simulate LUCC as the result of individual decisions is agent-based modelling (ABM). However, ABM is often applied to simulate processes at local scales, while its application in regional studies is limited. This paper describes first a conceptual framework for ABM to analyse and explore regional LUCC processes. Second, the conceptual framework is represented by combining different concepts including agent typologies, farm trajectories and probabilistic decision-making processes. Finally, the framework is illustrated through a case study in the Netherlands, where processes of farm cessation, farm expansion and farm diversification are shaping the structure of the landscape. The framework is a generic, straightforward approach to analyse and explore regional LUCC with an explicit link to empirical approaches for parameterization of AB

    A high-resolution and harmonized model approach for reconstructing and analyzing historic land changes in Europe

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    Human-induced land use changes are nowadays the second largest contributor to atmospheric carbon dioxide after fossil fuel combustion. Existing historic land change reconstructions on the European scale do not sufficiently meet the requirements of greenhouse gas (GHG) and climate assessments, due to insufficient spatial and thematic detail and the consideration of various land change types. This paper investigates if the combination of different data sources, more detailed modelling techniques, and the integration of land conversion types allow us to create accurate, high-resolution historic land change data for Europe suited for the needs of GHG and climate assessments. We validated our reconstruction with historic aerial photographs from 1950 and 1990 for 73 sample sites across Europe and compared it with other land reconstructions like Klein Goldewijk et al. (2010, 2011), Ramankutty and Foley (1999), Pongratz et al. (2008) and Hurtt et al. (2006). The results indicate that almost 700 000 km<sup>2</sup> (15.5%) of land cover in Europe has changed over the period 1950–2010, an area similar to France. In Southern Europe the relative amount was almost 3.5% higher than average (19%). Based on the results the specific types of conversion, hot-spots of change and their relation to political decisions and socio-economic transitions were studied. The analysis indicates that the main drivers of land change over the studied period were urbanization, the reforestation program resulting from the timber shortage after the Second World War, the fall of the Iron Curtain, the Common Agricultural Policy and accompanying afforestation actions of the EU. Compared to existing land cover reconstructions, the new method considers the harmonization of different datasets by achieving a high spatial resolution and regional detail with a full coverage of different land categories. These characteristics allow the data to be used to support and improve ongoing GHG inventories and climate research

    Effecten van landgebruiksveranderingen op gemiddelde en extreme afvoer in het Rijnstroomgebied

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    Recentelijk heeft veel onderzoek plaatsgevonden om de invloed van klimaatverandering te kwantificeren. Dit kan op verschillende manieren gebeuren, bijvoorbeeld kan er op basis van gemeten data een extreme-waardenverdeling worden geëxtrapoleerd. Een dergelijke aanpak heeft als nadeel dat de aanpak gebaseerd is op statistische kenmerken van het huidige klimaat, terwijl die juist waarschijnlijk veranderen. Een andere mogelijkheid is daarom het doorberekenen van klimaatscenario's zoals die worden gegenereerd met klimaatmodellen. Het landoppervlaktemodel dat in deze studie is gebruikt, namelijk het Variable Infiltration Capacity (VIC) model maakt gebruik van statistische parameters voor de invloed van verzadigde bodems. Het gebied betreft de substroomgebieden van Ruhr, Lahn, Mosel, Main en Necka
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