Ecological Modelling 174(2004)
5–18
Combined ecological and economic modelling
in agricultural land u scenarios
B.Münier ∗,K.Birr-Pedern,J.S.Schou
Department of Policy Analysis,National Environmental Rearch Institute,Frederiksborgvej 399,DK 4000Roskilde,Denmark
Abstract
Agricultural production and its associated land u compri the most important key factor regarding biodiversity and en-vironmental impact within the wider countryside in Denmark.Recently,a number of options for land u changes have been implemented in environmental action plans,such as afforestation,restoring wetlands and protection of drinking water catchments.At the same time,growing attention is put on the potential of Geographic Information System (GIS)as spatial decision support tools in local and regional environmental impact asssment,planning and implementation of governmental policies at local level.The work prented is part of a multidisciplinary rearch project,addressing the conquences of changes in agricultural production
with respect to ecology,environment and economy.In this paper,focus is put upon linking vegetation ecology and farm economy.Ecological effects are assd in terms of type,area and fragmentation of biotopes at landscape level.Asssment is bad upon the output of a spatial detailed Biotope Landscape Model,describing the distribution of plant communities and nature types in Danish (mi-)natural terrestrial biotopes.In addition an agro-economic model,asssing the costs of agricultural land u changes at the farm level,has been implemented.Input and output of the economic model has been linked to the GIS-bad Biotope Landscape Model,allowing scenario definition and integrated evaluation of results,including their spatial reprentation.The prent situation has been modelled as a ba line scenario.Afterwards,three scenarios aiming at more extensive agricultural production have been lected so they reflect different ecological or economic priorities.Results show economic as well as ecological conquences,compared to the prent situation.©2004Elvier B.V .All rights rerved.
Keywords:GIS;Land u;Agriculture;Scenario studies;Ecological modelling;Economic modelling;Environmental impact asssment
1.Introduction
Over the last century or more,(mi-)natural biotopes in Denmark have suffered from a quantita-tive as well as a qualitative decline.Increasing de-mands for environmental biodiversity,recreational areas and non-contaminated groundwater imply a need for regulations of agricultural land u.Restoring wetlands,afforestation and conversion of
∗Corresponding author.Tel.:+45-46-30-12-22;fax:+45-46-30-12-12.
E-mail address:bem@dmu.dk (B.Münier).
arable land to extensively grazed pasture reprent examples of land u changes,which are supported by public policies.Accordingly,there is a need for predicting the ecological and economic conquences of changes in land u,such as tho arising from shifting Danish or EU agricultural policies.
During the past 5years,the multidisciplinary re-arch project ‘ARLAS ’(ARealanvendel og Landsk-absudvikling ,belyst ved Scenariestudier =Land u and landscape development,illustrated with scenarios)has been carried out.The project is a co-operation be-tween Danish environmental and agricultural rearch institutes and the Danish county of Viborg.Rearch
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0304-3800/$–e front matter ©2004Elvier B.V .All rights rerved.doi:10.lmodel.2003.12.040
6 B.Münier et al./Ecological Modelling174(2004)5–18
英国的历史
within ARLAS focus on interaction of land u, agriculture,nature conrvation and the environment. The ARLAS project aims at tting up decision sup-port systems for sustainable management of the Dan-ish agricultural landscapes(ARLAS,2002;Dalgaard et al.,2003).
Few papers published deal with integration of economic and ecological information to improve gov-ernment policy.From a German ca,Herrmann and Osinski(1999)found that planning sustainable land u in rural areas requires a holistic approach,combin-ing different spatial federal state,regional and local administrations)to ensure coherence be-tween governmental policy and local implementation. Planning is not only a top-down but also a bottom-up approach.In the UK rearch project NELUP, ecological models have been t up in a Geographic Information System(GIS)environment as part of a computerid Decision Support System(DSS)for rural policy formulation,working at a1-km2grid (O’Callaghan,1996;Rushton et al.,1995;Watson and Wadsworth,1996).NELUP integrates models bad on economics,ecology and hydrology in one modelling framework with a common databa and ur interface.zinc
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Walker and Young(1997)provide a number of ex-amples demonstrating the potential of GIS for strate-gic policy analysis,giving politicians the opportunity of thinking locally while acting nationally.They ac-centuate the necessity of integrated data ts at a sim-ilar scale.In a recent paper,Weber et al.(2001)exam-ined economic forces leading to land u changes in a peripheral German region and their effect on ecology and hydrology.Three simulation models from agricul-tural economic,ecological and hydrological sciences have been linked via GIS.The workflow of this in-tegrated modelling framework has been tested using the implementation of a grassland bonus system in a watershed located in central Germany.
The purpo of this paper is to prent a subt of ARLAS’s modelling framework,targeted at as-ssing the costs of agricultural land u changes and to compare tho with ecological benefits from expected vegetation changes and reduced fragmenta-tion of(mi-)natural terrestrial biotopes.The phra ‘(mi-)natural’is ud as a common term for all terrestrial nature types except forests,from almost untouched areas such as raid bogs over extensively utilid fens,meadows,dry grasslands and heathlands to intensively managed dry and moist grasslands(pas-tures).The paper starts with a detailed description of the general methodological approach,including the economic and ecological modelling and t up of three different scenario examples in Section2.S
复旦附中国际部ection3fo-cus on the economic and ecological results.Section 4provides a discussion of results and conclusions. 2.Method
2.1.Model structure
The modelling approach described in this paper integrates spatial and non-spatial information from agricultural databas,land u and ownership and physical ttings within a common framework.Fig.1 provides an overview of the modelling framework, its software components and the data ts involved. Geo-referenced nation-wide agricultural databas provide data on land u and livestock husbandry for each farm in the study area,which are ud to derive economic output in terms of gross output and the eco-nomic rent.This allows mapping of the spatial varia-tion of the economic output on farm level,by which opportunity costs can be estimated in terms of re-duced agricultural production caud by area-specific changes in land u.Knowing the ecological require-ments of terrestrial plant communities,the expected distribution of(mi-)natural vegetation can be de-rived from maps on land u and abiotic grazing,hay cutting,soil types,soil moisture and ge-omorphology.Resulting maps of vegetation types are analyd to reveal changes in fragmentation of the entire landscape as well as key types of vegetation. Scenarios highlighting economic as well as ecological outcomes impod by agri-environmental policies and different policy
objectives and instruments may be appraid and compared against each other using the combined ecological and economic model.Scenario definition may u spatial and non-spatial regulations,
2.2.Software applied
All integrated modelling was built up around ESRI’s desktop GIS ArcView3.2.The GIS facilitated
B.Münier et al./Ecological Modelling 174(2004)5–187
Input Model
国际英文Output
Excel spreadsheet |
ArcView GIS
Fig.1.Framework for integrated spatial economic and ecological modelling.
the collection of ba maps,linkage with databa files,definition of scenarios and prentation of re-sulting maps.The Biotope Landscape Model has been built as an ArcView extension,requiring the ArcView Spatial Analyst extension (ESRI,1999).As most ex-perts are expected to have a little familia
rity with GIS,the extension facilitates scenario t up and modelling including linkage to the vegetation databa stored in Microsoft ®Access.Furthermore,the FRAGSTATS software (version 3.1build 3)(McGarigal et al.,2003)has been applied for landscape fragmentation anal-ysis.FRAGSTATS works directly on the vegetation maps generated by the Biotope Landscape Model.Microsoft ®Excel has been ud for economic mod-elling and for prentation of output from all models as tables and charts.2.3.Study area
英国驻华使馆Applications of the modelling frameworks are demonstrated in a study area located within the two municipalities Bjerringbro and Hvorslev in the cen-tre of the peninsula of Jutland (Denmark).The two municipalities cover 425km 2of which almost 3/4is agricultural land.A 10km ×10km area has been
chon for in depth modelling of the ecological part of the analysis in the ARLAS project (Fig.2),while some farms have field located outside this area but in-side the two municipalities (Fig.3).Land u within this 100km 2is divided into 53%cultivated arable land,9%extensively utilid (mi-)natural areas and 2%lakes and streams.Forests occupy another 25%,while urban areas,roads and other land u take the remaining 11%.All types of agricultural production are found in the area ranging from intensive pig and cash crop production,organic dairy farming to part time agriculture.The total number of farms in 1997was 878with an average farm size of 36.3ha,which is 15%smaller than the a
verage farm size in the whole of Denmark.Agricultural land u area sums at 13.911ha,shared between cash crops (59%of the area)and roughage (41%of the area).Livestock hold consists of ruminants (mainly cows),pigs and poultry.2.4.Economic modelling
When analysing land u related policy measures,the spatial dimension becomes a key factor with re-spect to appointing relevant areas.The costs and ben-efits of land u changes may vary considerably even
8 B.Münier et al./Ecological Modelling174(2004)5–18
Fig.2.Prent land u in the study area.
电影英语within small regions.Environmental conditions,in-frastructure and location of different types of farming differ at regional and local level.The spatial dimension of agri-environmental analysis has been recognid in a large number of economic studies.Non-point pol-lution has been analyd theoretically by Segerson (1988)and empirically in a number of studies applied to agricultural non-point pollution(Braden et al.,1989; Moxey and White,1994;Pan and Hodge,1994;Vatn et al.,1997).In the study by Opaluch and Segerson (1991)the application of a Geographic Information System is recognid as a uful tool in the environ-mental and economic analysis of groundwater con-tamination from agriculture(Schou et al.,2000).A GIS enables the quantification of economic and envi-ronmental effects on a site-specific as well as on an aggregate level.Bateman et al.(1999)utili a GIS to analy individual farm costs and revenues and extrap-olate predictions from the resulting models to yield agricultural value maps.The maps are suitable for policy identify the economically op-timal areas for conversion of farmland to woodlands. The possibilities for including spatial aspects in agri-environmental analysis have been improved sig-nificantly,as the Danish national authorities admin-istrating the European Union’s subsidy scheme need information about land u and livestock husbandry on each single farm.The data are stored in a general registe
r(GAR/CHR,General Agricultural Register/ General Husbandry Register)and each farm can be geo-referenced with the location of stalls and agricul-turalfield.
An economic model is ud for estimating the eco-nomic output from each farm bad on information on land u(crop types),livestock husbandry and the main soil type of the farm.The information of land u and livestock husbandry on each farm is com-bined with a Farm Account Databa holding data on average economic output from each production ac-tivity(Danish Institute of Agricultural and Fisheries Economics,2000).From this,coefficients for eco-nomic rent per hectare and per animal have been calculated.In this way the information on production structure on each farm is utilid in order to reflect as much as possible of the spatial variations.For more details of model construction refer to Schou and Birr-Pedern(2001).
The economic rent(πi)of farm i,is modelled as:πi=
j=1
a ijπC j+
h=1
余切h ihπH h(1)白朗听力
B.Münier et al./Ecological Modelling174(2004)5–189
Fig.3.Costs in DKK of changing cultivated arable land to pasture,modelled at farm level.
where a ij is the number of hectares on farm i with crop j;πC j the average profit(or economic rent)per hectare from crop j;h ih the number of livestock type h on farm i andπH h the average profit(or economic rent)per animal from livestock type h.
The calculation only includes lines of production, which are sold off the farm.Excess roughage is ex-pected to be sold off farm at cost prices when the production of roughage exceeds the expected need for feeding the livestock husbandry by more than10%. In the prent study,the economic output is ex-presd using the profit,which is identical to the eco-nomic rent of crop production and of husbandry.The economic rent is what remains when all costs,includ-ing labour and capital costs except the capital costs of owning soil,are subtracted.Alternative indicators of economic ss margins,can also be calculated using the model.
A t of decision rules was introduced for all farms to reprent the farm adjustments implied by the land u changes from cultivated arable land to pasture.Ad-justments were determined bad upon the percentage of total farmland converted to pasture and the number of livestock units per hectare at the farm.If less than 25%of the farmland is converted to pasture there are no radical changes on t
he farm,while a change be-tween25and75%of the farmland results in veral adaptations.If more than75%of the farmland is con-verted to pasture the whole farm will be converted to suckler cow production(for detail,refer to Abildtrup et al.(2001)).
2.5.Ecological modelling
Evaluation of land u scenarios has been bad upon further maturation of the Biotope Landscape Model previously developed and implemented for a broader study area in Denmark(Münier et al., 2001).The model asss ecological conquences for(mi-)natural terrestrial vegetation on landscape
