Mapping landscape services: a case study in a multifunctional rural landscape in The Netherlands
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Ecological Indicators 24 (2013) 273283
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Mappin muThe Ne
M.M.C. G . Va Soil Geograph Netheb Institute for E msterdc Faculty of Geo 0 AA E
a r t i c l
Article history:Received 28 DReceived in reAccepted 2 Jul
Keywords:Ecosystem servicesSpatial characteristicsIndicatorsLandscape functionsMultifunctionalityGIS
s, e.ges foriffereandsc
Asten in provinceNoord-Brabant, TheNetherlands:wetland habitat, forest recreation, land-based animalhusbandry, and recreation for hikers. The landscape services were identied through ground observa-tions at 389 locations. Spatial indicators were used to identify and map the landscape services. Basedon the ground observations, correlations between the landscape services and spatial characteristics (e.g.elevation, soil, road-type) were calculated within a neighbourhood with a radius of 0m, 50m, and 100m.These correlations identied several site-specic indicators to map the landscape services. The accuracy
The impand culturaet al., 1997;2009; Verbusystems thahumans inets (DeFrilandscape svided by a l(Termorshuservices ovetionships, ulocal practiof landscapregulation,
1470-160X/$ http://dx.doi.oof the landscape service maps created was assessed. The indicators proved to be adequately reliable forforest recreation and reasonably reliable for land-based animal husbandry and recreation for hikers. Onlylandscape service map forest recreation was shown to be highly accurate. The four landscape servicesrarely coincide, but within a 1km radius it is apparent that some occur closer together. The approachthat we have used is applicable for a wide range of different services and establishes a fundamental basisfor determining their spatial variation. As such, it should provide vital information for policy makers andspatial planners.
2012 Elsevier Ltd. All rights reserved.
ortance of landscape services, provided by both naturall landscapes, is increasingly recognised (e.g. CostanzaMA, 2005; de Groot, 2006; Termorshuizen and Opdam,rg et al., 2009). Landscapes are spatial social-ecologicalt deliver a wide range of functions, which are valued byterms of economic, sociocultural, and ecological ben-es et al., 2004; Termorshuizen and Opdam, 2009). Aervice is dened here as the goods and services pro-andscape to satisfy human needs, directly or indirectlyizen and Opdam, 2009). We prefer the term landscaper ecosystem services, as it infers pattern-process rela-nites scientic disciplines, and is better understood bytioners (Termorshuizen and Opdam, 2009). Examplese services include food production, pollination, waterand provision of recreation.
ding author. Tel.: +31 317 482947; fax: +31 317 419000.ress: email@example.com (M.M.C. Gulickx).
Increasing attention is paid, both by policy makers and scien-tists, to the multifunctionality (Fry, 2001; Holmes, 2006; Wilson,2008) and the potential synergies and conicts that may arise.Policy makers and spatial planners are gradually directing theirpolicies and plans to provide and strengthen desired landscapeservices. To support the establishment of these policies and plans,geographical maps of existing and desired services are requiredto identify where services border each other or coincide and, thus,lead to possible synergies or conicts. In thisway, theymay be usedto determine optimal solutions. Hence, it is necessary to developmethods and tools to quantify andmap the different services acrossthe landscape.
The spatial distribution of intended landscape services that arerelated to the intended land use (e.g. food and bre production)are often documented. However, the spatial distribution of land-scape services that are often an unintended consequence of landmanagement (e.g. provision of aesthetic beauty), are commonlyunknown. Additionally, they may be unrelated to a single land-coveror land-use type,whichmakes themmoredifcult toquantifyand map. It is postulated that landscape analyses based on land-cover and land-use are inadequate for landscape characterisation
see front matter 2012 Elsevier Ltd. All rights reserved.rg/10.1016/j.ecolind.2012.07.005g landscape services: A case study in atherlands
ulickxa,, P.H. Verburgb, J.J. Stoorvogela, K. Koka, Ay and Landscape Group, Wageningen University, PO Box 47, 6700 AA Wageningen, Thenvironmental Studies (IVM), VU University Amsterdam, De Boelelaan 1087, 1081 HV A-Information Science and Earth Observation (ITC), University of Twente, PO Box 6, 750
e i n f o
ecember 2011vised form 29 June 2012y 2012
a b s t r a c t
The wide variety of landscape servicethe use of a wide range of data sourcrequired to analyse and map differ dApproaches to identify and map four l/ locate /eco l ind
ltifunctional rural landscape in
rlandsam, The Netherlandsnschede, The Netherlands
. food production, water quality, and recreation, necessitatestheir identication. Subsequently, an array of approaches is
nt landscape services, which we have explored in this study.ape services are illustrated for the municipalities Deurne and
274 M.M.C. Gulickx et al. / Ecological Indicators 24 (2013) 273283
of such unintended services, since these approaches are speci-cally related to the intended use of the land (Verburg et al., 2009).Hence, common observation techniques, available land covermapsand spatial datasets, are insufcient for quantifying and mappingthese landsious spatialsocial, are uof landscapet al., 2008cators relaton generaltial for thethe quantilandscape stors. Yet, siinvestigated
The vastrange of teapply to difterm carboExamples osupply (up tof architectstandard prpered by thamongst lanet al., 2008)
The objeand map vasidering spservices anwere analyservices. Thmaps. Thescape servianimal husof Deurne aThis case stlandscape sderived arelandscape s
2. Data an
2.1. Study a
The stu(120km2; 5(72km2; 3 vof Noord-Brpart ofDe Pits intensivPeel (peat-ting). This alandscape. Fon the enviimpact on rand regionation areawquality of th
At rst,Based on re
e spthesdoloape srelatof imponents are described in the paragraphs below. First, weed the sampling method that was used to obtain point dataobservation of landscape services and the spatial character-The study area was divided into grid cells of 1 km2. Withinid cell, twopointswere selected approximately 500mapart.ructured sample design provided an equal distribution ofoints, resulting in a total of 389 points. Per data point, exist-dscape services were identied using ground observations,mes complemented with information from governmentalses or management strategies (Table 1). In addition, the spa-racteristics (Table 2)were assembled at a radius of 0, 50, and
Fig. 2. Overview of the overall methodology.cape services (Verburg et al., 2009). Consequently, var-attributes, mainly biophysical, but also economic andsed as indicators to quantify and map the spatial extente services (e.g. Gimona and van der Horst, 2007; Egoh; Willemen et al., 2008; Kienast et al., 2009). Yet, indi-ed to landscape services are often unknown or basedassumptions. Identifying suitable indicators is essen-improvement of landscape service maps. Therefore,cation of relations between site-specic attributes andervices are required in order to develop reliable indica-te-specic indicators for landscape services are hardly.array of landscape services is delivered across a greatmporal and spatial scales. Examples of services thatferent temporal scales are carbon sequestration (long-n storage) and seasonal recreation (short-term visits).f services that apply to different spatial scales are wateromany km2) and cultural heritage, such asmonumentsure (as small as m2). Therefore, the development of aocedure to quantify andmap landscape services is ham-e fact that the appropriate spatial scales differs greatlydscape services (de Groot and Hein, 2007; Prez-Soba.ctive of this study is to develop an approach to identifyrious landscape services, by using indicators and con-atial scales. Correlations between observed landscaped spatial characteristics of the surrounding landscapesed to ascertain site-specic indicators for landscapeese indicatorswere extrapolated into landscape servicemethodology and results are illustrated for four land-ces (i.e. wetland habitat, forest recreation, land-basedbandry, and recreation for hikers) in the municipalitiesnd Asten, province of Noord-Brabant, The Netherlands.udy aimed to obtain insights into the relations betweenervices and the surrounding landscape. The indicatorsspecic to this area, but highlight linkages between
ervices and their surroundings.
dy area comprised the municipalities of Deurnevillages; 31.496 inhabitants; May 2009) and Asten
illages; 16.398 inhabitants; May 2009) in the provinceabant, The Netherlands (Fig. 1). Both municipalities areeel region (approximately 600km2), which is known fore livestock production and nature reserve De Grootebog that has remained partly untouched by peat cut-rea has to deal with various conicting services in theor example, intensive animal husbandry has an impact
ronment, such as odour emission, which has a negativeecreation, suchas farmcamping. As a result, thenationall authority has assigned this region as a reconstruc-ith high priority, in order to improve the environmentale rural area (Provincie Noord-Brabant, 2005).
l design of methodology
point observations of landscape services were made.lations between the occurrence of landscape services
Fig. 1. Sright, th
and thtion ofmetholandsc(3) corolationfour codescribfor theistics.each grThis stdata ping lansometidatabatial chaarea comprising municipalities Asten and Deurne. At the top on thetion of the study area (black mark) in The Netherlands is shown.
atial characteristics of these locations, an extrapola-e services to the whole study area was conducted. Thegyconsistsof four components: (1)pointobservationsofervices; (2) point observations of spatial characteristics;ion analysis and selection of indicators; and (4) extrap-ndicators for mapping landscape services (Fig. 2). The
M.M.C. Gulickx et al. / Ecological Indicators 24 (2013) 273283 275
Table 1Landscape services and the expected data sources that are required to identify the landscape service. Services in bold are further described in this paper.
Landscape service Service category Map Governmental Database Management strategy Fieldwork
Land cover Routes ERDa GIABb Observe Counts
Residential Carrier XIndustrial production Provision XOutdoor sport Information XFruit and nut production Provision XGreenhouse food production Provision XForest habitat Habitat XWetland habitat Habitat XWater storage Regulatory XWater supply Regulatory X XEnergy conversion Carrier X XHobby gardening Information X X XCrop production Provision X X X XOvernight tourism Information X X XForest recreation Information X X X X XWetland recreation Information X X X X XRecreation for hikers Information X X XRecreation for cyclists Information X X XRecreation for horse riders Information X X XNon-land-based animal husbandry Provision X XLand-based animal husbandry Provision X XHorse boarding Provision X X XHobby farming Information X X XDitch bank protection Habitat X X X XWading bird protection in agricultural land Habitat X X XWading bird habitat in agricultural land Habitat X X
aERD: environmental registration database (StraMis, 2009).bGIAB: agricultural assessment database.
100m to ascertain the neighbourhoods of the landscape service.Field observations were carried out from June to August 2009.
2.3. Point o
Landscatheir propeent methodservices (W
between landscape services with a one-to-one relation toland-cover; those, which require one data source and are there-
sy tole dast oftenti1). Ts (deontr
Table 2List of include
At data poin
a Soil map:b TOP10-SE:c CHW Brabd AHN: Dutcbservations of landscape services
pe services vary greatly as they, for instance, differ inrties (de Groot and Hein, 2007). Consequently, differ-s and data sources are required to identify landscapeillemen et al., 2008). In general, we can differentiate
A lithe po(Tableegorieood cd spatial characteristics and used data sources, divided into point observations, distance
Spatial characteristics Field
t Soil typeGround water table
Unpaved road XRural road XProvincial road XHighway XNatural area XCity/village XCultural heritage (monuments) XIndustrial area XGreenhouse XRecreational area/element X
ood Relief XDitch XPond XSolitaire tree XTree line XHedgerow XBush XCultural heritage XOpennessHilliness X
Digitised soil map of The Netherlands at scale 1:50,000 with PAWN-units (de Vries, 2008topographical map spatial edition (vector), including land use classication of TDN (Topant: cultural historical valuable (monumental buildings), Atlas Province Noord-Brabant.h digital elevation map, spatial resolution 5m5m.identify, and other landscape services which requireta sources and are more laborious to identify.25 landscape services present in the study area andal data sources to identify the service was composedo account for diversity of landscape services, ve cat-Groot, 2006) are included: regulatory services (e.g.
ol), habitat services (e.g. provision of natural habitat),to, and neighbourhood (occurrence within a radius of 50 and 100m).
Soil mapa (2006)Soil map (2006)
TOP10-SEb (2006)TOP10-SE (2006)TOP10-SE (2006)TOP10-SE (2006)TOP10-SE (2006)TOP10-SE (2006)CHW Brabantc (2006)TOP10-SE (2006)TOP10-SE (2006)TOP10-SE (2006)
TOP10-SE (2006)Google Earth (2009)TOP10-SE (2006)
CHW Brabant (2006)Calculated (Weitkamp et al., 2011)AHN (2002)
).ographical Service Netherlands), scale 1:10,000.
276 M.M.C. Gulickx et al. / Ecological Indicators 24 (2013) 273283
provision services (e.g. food production), information services (e.g.recreation), and carrier services (e.g. habitation).
Broad categories of landscape services bring about a wider setof required data sources to identify the service. For example, foodproductionof landscapConversely,taining maiincludes leslandscape s
We opteferent landsources): wand land-ba
region for bharbour a glanicum, Bointermedia)Grebe Podicrare buttereropterus maddition, hismall peatpa land-cove
2.3.2. ForesThe area
were predosand driftinforests starof the wetlOver the lahas increasein a forest lEdition, 200areas. Withtained usintrails, cyclinThese indiccycling andorder to ideamount of vtime consumforested arefor recreati
scapes suitamap (knootify recreatpoints of inon good quof hiking rois expected
correspondin outbreaktriggering ation of livethe produc
that depend on the land quality (i.e. they use their own landfor fodder production). Land-based husbandry is an importantsource of income in the region. The environmental RegistrationDatabase (StraMis), which details farm types (e.g. land-based, non-
eralindiof spses wnd dmapure p
otal,e thetabaspe ofof 38es weerale, he
nt =1nd tetretedwit
ve toape sal syaractPearsoverdete
pliedng widens intionusin
sionwtic (Rwhice pro. A Rrandisticore,ollinnd spevaltionmanof otnt sete dierviis a very broad category that contains different typese services, and as such, a diverse set of data sources.the subcategory land-based animal husbandry (con-
nly milk production) is more specied, and as a result,s diversity in the required data sources. The 25 selectedervices are therefore specied explicitly.d to present the methodology by describing four dif-scape services with different requirements (i.e. dataetland habitat, forest recreation, recreation for hikers,sed animal husbandry.
nd habitathabitat in the study area is of great importance to theoth nature conservation and historical value. Wetlandsreat variety of ora (e.g. peat moss Sphagnum magel-g Rosemary Andromeda polifolia, and Sundews Drosera, and fauna, including rare birds (e.g. Black-neckedeps nigricollis and Nightjar Caprimulgus europaeus), andies and dragon ies (e.g. Large Chequered Skipper Het-orpheus and White-faced Darter Leucorrhinia dubia). Instorical traces of peat extraction, such as big lakes andits, are still visible.Wetlandhabitatwas identiedusingr map (TOP10-SE, 2006).
t recreationcontains several fragments of forested areas. Forests
minantly planted between 1840 and 1900 to preventg and to provide wood (Bont de, 1993). Some naturalted to grow on the drier and more nutrient-rich soilsand areas. These are dominated by birch Betula trees.st few decades, recreational use of the forested areasd. Forest recreation is dened as recreational activities
arger than 2 hectares. A land-cover map (TOP10 Spatial6) was used to determine the location of the forestedin these forested areas, recreational activity was ascer-g simple indicators, namely, the presence of walkingg paths, horse riding trails, picnic tables, and car parks.ators were derived from management plans, walking,horse riding routes, and from eld observations. Inntify the actual service, it is preferred to quantify theisitors to the forested areas,which is unfortunately verying. Instead, we enquired with the land owners of the
as to deduce whether these areas are used by peopleonal purposes.
ation for hikerson for hikers is dened as (perceived) attractive land-ble for leisure walking activity. We used a hiking routeppuntenroute network of hiking routes, 2008) to iden-ion for hikers. The route is designed to pass importantterest, along attractive landscapes, and where possibleality roads. This hiking route map is the most sold typeutes by the tourist information centre, and therefore, itthat they are actually used by recreational hikers.
-based animal husbandryk production has intensied rapidly in the study area,ingly to other parts of theNetherlands. This has resulteds of various infectious diseases amongst livestock, andrenovation plan to improve the environmental situa-
stock production. Land-based husbandry is dened astion of food and goods (e.g. milk and wool) by farms
In tbecaustial da(the tya totalanalys
Sevtree lin(presevices a100-mcalculaculatednot halandscnumertial chusingland-cspatialrelatiolationsnot apmappi
Theused acorrelaculatedregresacteris2004),positiv0 and 1pletely
Tocorrela(Spearrencedifferecalculascape s, horticulture) and their location, was used to identifyanimal husbandry.
bservations of spatial characteristics
spatial characteristics were identied to analyse thecators of each landscape service (Table 2). For the col-atial characteristics, both eld observations and spatialere used (Table 2). This predominantly comprises ofata sources from 2006, with the exception of the ele-(AHN, 2002). The openness was calculated using theroposed by Weitkamp et al. (2011).
tion analysis and indicator selection
ve data points were excluded from data analyses,groundobservationwasnot in agreementwith the spa-es. For instance, the land was leased out and the userfarm) of an arable eld was not retraceable. Therefore,4 data points were included in the analyses. Statisticalre calculated in SPSS Statistics 17.spatial characteristics (i.e. ditch, pond, solitaire tree,dgerow, bush, cultural heritage) have binary variables; absent =0). The relation between the landscape ser-he binomial spatial characteristics within a 0, 50, andradius, andcorrelationsbetween landscape serviceswasusing Spearmans Rho. Cultural heritage was also cal-hin a 500m radius, considering cultural heritage doesbe visible to have an inuence. Correlations betweenervices and spatial characteristics with a continuous
stem(i.e. openness, elevation, relief, anddistance to spa-eristics) were calculated for a 0, 50, and 100-m radiusons r. In The Netherlands, wetland is a well-mappedtype, and therefore, land-cover is considered as therminant for wetland habitat. Due to this one-to-one
th land-cover, further calculations for assessing corre-een wetland habitat and spatial characteristics were
, considering these correlations are not necessary foretland habitat.tied correlations between landscape services weredicators to map the service. For each service, thebetween the set of indicators and the services was cal-g logistic regression. The goodness of t of the logisticasmeasured bymeans of the ReceiverOperating Char-
OC) curve (Pontius and Schneider, 2001; Verburg et al.,h involves plotting each pair of true positive and falseportions for every possible decision threshold betweenOC curve value of 0.5 indicates that the model is com-om and a value of 1 indicates perfect discrimination.regression assumes that the variables are independent.we tested the variables for their independency, i.e. forearity (Variance Ination Factors (VIF) and toleranceatial autocorrelation (Morans I).uate spatial synergies between landscape services,s between the location of services were calculateds Rho). In addition, within a radius of 1 km, the occur-her landscape services, and the distance between thervices were assessed. A KruskalWallis test was used tofferences between the distances to the different land-ces.
M.M.C. Gulickx et al. / Ecological Indicators 24 (2013) 273283 277
2.6. Mapping landscape services
Wetland habitat was mapped by extracting land-cover wetlandfrom the land-cover map (TOP10 Spatial Edition) using ArcGIS 9.3.Land-basedfor hikers w(ArcGIS9.3)two contingthe landscaa users acc
The landof the analythe data po41% (N=15At 7% of thewas provide
3.1. Correlaservices map
(Fig. 3). Valaccuracy ofa users accdemonstrat
3.1.2. ForesThe occu
of the landational acti(i.e. landscateristics expnegative cosoil type, grparing foreand withouwas observcover on pepeat, r=0.2r=0.15, P