Grasslands as a sustainable tourism resource in

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Int. J. Services Technology and Management, Vol. 13, Nos. 3/4, 2010

Grasslands as a sustainable tourism resource in Germany: environmental knowledge effects on resource conservation preferences Jan Barkmann* Department of Agricultural Economics and Rural Development, Georg-August-Universität Göttingen, Platz der Göttinger Sieben 5, D-37073 Göttingen, Germany Fax: +49-(0)551-394813 E-mail: [email protected] *Corresponding author

Anne-Kathrin Zschiegner Institute of Geography, Georg-August-Universität Göttingen, Goldschmidtstr. 5, D-37077 Göttingen, Germany and University of Exeter, School of Business and Economics, Streatham Court, Rennes Drive, Exeter, Devon, EX4 4PU, UK Fax: +44-(0)1392-263242 E-mail: [email protected] Abstract: Resulting from centuries of traditional animal husbandry, extensive grasslands belong to the most important natural tourism resources in Central Europe adding to the amenity values of many landscapes. Facing agricultural market pressures, they are endangered by agricultural intensification as well as by abandonment. Both developments threaten grassland values for tourists and recreationists. However, many non-experts regard extensive grasslands as ‘natural’ and ignore the essential contribution of animal husbandry to their conservation. Against this background, we conducted choice experiments with respondents from two semi-rural suburbs of Göttingen City and from two Harz mountain villages (n = 336). Respondents either use the grassland landscape for recreation and/or operate tourism businesses. We document substantial preferences for vistas facilitated by local grasslands and for grassland species diversity. Residents with higher scores of an index of grassland knowledge prefer higher numbers of sheep and cattle for grassland conservation. Keywords: amenity value; environmental knowledge; pro-environmental action; open spaces; agriculture; willingness-to-pay; WTP; Lower Saxony; Saxony-Anhalt; Germany.

Copyright © 2010 Inderscience Enterprises Ltd.

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Reference to this paper should be made as follows: Barkmann, J. and Zschiegner, A-K. (2010) ‘Grasslands as a sustainable tourism resource in Germany: environmental knowledge effects on resource conservation preferences’, Int. J. Services Technology and Management, Vol. 13, Nos. 3/4, pp.174–191. Biographical notes: Barkmann is Deputy Head of the section of Environmental and Resource Economics at Georg-August-Universität Göttingen. He studied Biology, Psychology, Pedagogics and Philosophy at Christian-Albrechts-Universität zu Kiel (Germany), and graduated from University of Maine (USA) with a MS in Plant Biology. He obtained a PhD in Ecology from Kiel University in 2001. Since 2002, he is with Environmental and Resource Economics in Göttingen. His research interests focus on the economic valuation of ecosystem services and of biological diversity, and include topics such as sustainable tourism, smallholder agriculture around protected areas, and the treatment of environmental uncertainty in decisionmaking. Anne-Kathrin Zschiegner is currently a PhD student in Tourism Management at the Business and Economics School, University of Exeter, UK. She is interested in different aspects of sustainable tourism and has worked on cultural and attitudinal influences on the preferences of Chinese domestic tourists for nature- and landscape-based destinations. She received her Diplom (MS equivalent) in Geography for this study in 2006 from Georg-August-Universität Göttingen, Germany.

1

Introduction

The disappearance of extensive, species-rich grasslands in Europe since the 1950s has attracted much attention from the ecological sciences because important conservation values are lost (e.g., Dolek and Geyer, 2002; Isselstein et al., 2005; Hodgson et al., 2005). Increasingly, it is also recognised that grasslands add substantially to the amenity values of many landscapes, particularly when located close to densely inhabited or forested areas (Schüpbach et al., 2004, Evans et al., 2003; Schmitz et al., 2003). Facing increasing agricultural market pressures, extensive grasslands are endangered by agricultural intensification as well as by abandonment; the latter ultimately resulting in forest development (Green, 1990; MacDonald et al., 2000; Cousins et al., 2002; Maurer et al., 2006). The effects of intensification and abandonment threaten landscape values for tourists and recreationists: willingness-to-pay (WTP) of rural tourists, e.g., dropped for accommodations with more arable crop production or with increased forest cover nearby in Flanders (Belgium), but appreciated with an increased area of permanent grasslands (Vanslembrouck et al., 2005). Similarly, higher degrees of forest cover represent a disutility for local residents of Lahn-Dill highland in Central Germany (Schmitz et al., 2003). Although extensive grasslands usually result from centuries of traditional animal husbandry in Europe (Cousins et al., 2002; Isselstein et al., 2005; Maurer et al., 2006), non-experts often regard extensive grasslands as ‘natural’ and, in consequence, ignore the essential contribution of animal husbandry to their conservation. A pilot study conducted in the suburbia of Göttingen (Germany) had indicated that the environmental knowledge

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base of local citizens deviates from the academically accepted point of view: Few interviewees were aware that the local dry calcareous grasslands at Drakenberg are not ‘untouched nature’, but a landscape shaped by agricultural land use (Bargsten et al., 2004). In the light of prognoses that grassland cover will decrease across a suit of global change scenarios in Europe (Schröter et al., 2005), the apparent ecological knowledge deficit prompted us to study grasslands as tourism and recreation resources. First, do local residents – either as recreationists or as residents economically benefiting from tourism – prefer grassland management with cattle and sheep fostering amenity values? Second, are these preferences influenced by respondent knowledge on the most fundamental facts of grassland ecology? In this paper, we report on two choice experiments (CEs) that assess economic preferences in the form of WTP for grassland conservation with cattle and sheep. The research was conducted at two locations: 1

two suburbs of Göttingen City bordering Drakenberg grassland (Lower Saxony)

2

two resort municipalities in the Harz Mountains (Saxony-Anhalt).

At the Göttingen suburbs, recreational use dominates; the Harz resort municipalities rely economically on tourism. In the following literature review Section 2, we highlight prior knowledge effects on WTP for environmental goods. In the methodology section, the study sites are described in more detail (3.1), and the design and administration of the CE instrument is explained (3.2). Subsection 3.2 also contains details on the construction of a knowledge indicator assessing fundamentals of grassland knowledge. In Section 3.3, an outline on econometric model estimation and hypothesis testing is given. Results are presented in Section 4 and discussed in Section 5.

2

Knowledge effects on pro-environmental intentions

A stated WTP for the conservation of amenity values through traditional grassland management can be interpreted as an intention for pro-environmental action (cf. Ajzen and Driver, 1992). In this subsection, we focus on the effect of ‘knowledge’ on intentions at two levels. First, we address social science theory and evidence on the influence of prior knowledge on intentions. Next, the direct influence of providing information to survey respondents during a valuation interview is discussed. Numerous studies in environmental psychology and science education did not find any or only marginal influences of prior knowledge on self-reported intentions for environmental action (for a review, see e.g., Kaiser and Fuhrer, 2000). In a study on WTP for traditional landscape elements (hedges) conducted in Lower Saxony, self-reported prior knowledge and botanical prior knowledge were correlated significantly with log-transformed WTP values; they explained only less than 4% of log (WTP) variance, however [Fischer, (2004), p.196]. These findings are little surprising in light of current theories in social psychology. Protection motivation theory (Rogers and Prentice-Dunn, 1997), for example, only includes the response efficacy construct, i.e., a belief that an action has an adaptive or mitigating effect with respect to a certain issue. Ecological ‘textbook knowledge’ does rarely support response efficacy beliefs: knowing how the

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term ‘ecosystem’ is defined, for example, hardly influences the beliefs that intensive cattle grazing can be beneficial for the conservation of the amenity value of grasslands. But even knowledge that does support response efficacy beliefs is only a sufficient, not a necessary condition for pro-environmental action (Kaiser and Fuhrer, 2000). Because of its ‘distant’ relation to action, its potential influence is often masked by more proximate variables, such as self-efficacy beliefs (Badura, 1977) or the ascription of responsibility (Montada and Kals, 1995). Furthermore, intentions are often influenced by daily routines and habits which may need to be socially challenged at a ‘discoursive’ level of consciousness (Hobson, 2003). Remaining knowledge effects on intentions can be mediated by values. Individuals with a pro-environmental set of values may act accordingly and because of their values learn more about the environment (Eckensberger et al., 1992). For the conscious choice of cognitively non-trivial pro-environmental intentions, however, it has been hypothesised that a stronger influence of prior knowledge can be detected (Bögeholz and Barkmann, 1999). Information that is directly provided to respondents during a stated preference survey affects WTP estimates strongly because it can act as a form of persuasive communication (Ajzen et al., 1996). Information effects depend on the amount, strength and presentation of information (e.g., Ajzen et al., 1996; Hoehn and Randall, 2002; Spash, 2002). Any relevant additional information given to respondents during a valuation interview will either unduly influence the preference statement (information bias), or lead to a differing commodity definition (framing effect; Spash, 2002). The prior knowledge that respondents command before the interview acts as a moderating factor that affects information processing (Hoevenagel and van der Linden, 1993; Fischer, 2004). The less familiar respondents are with the valuation issue, the more pronounced are information effects (Spash, 2002; Tkac, 1998). In sum, it appears as an attractive questionnaire design strategy to include questions on prior knowledge in a valuation interview on grassland amenity values: 1

Because of the relative unfamiliarity of respondents with grassland ecology and evolution, strong information effects would be expected with extensive interview explanations of the issue.

2

The interview situation facilitates a consciously controlled choice on a (pro-) environmental intention regarding a cognitively non-trivial environmental topic.

Thus, prior knowledge effects should be statistically and materially significant.

3

Methodology

3.1 Study sites The research reported here was conducted at four communities in two federal states in Germany with important local grasslands. Traditionally, these grasslands were used for hay making and/or sheep and cattle grazing while serving recreational and/or tourism purposes today. The first site is the local recreational area Drakenberg hill between two suburban districts east of Göttingen City (Lower Saxony), Roringen and Herberhausen. For the second CE, citizens of Hasselfelde (~3,100 inhabitants) and Stiege (~1,100

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inhabitants) at the center of the Lower Harz region (Saxony-Anhalt) were interviewed. Tourism contributes substantially to the local economy with more than 70,000 person-nights in 2007 at Hasselfelde alone (Statistisches Landesamt, 2007). Geologically, Drakenberg is a lacustrine limestone bank that borders municipality owned Göttingen forest. It has steep slopes towards Roringen and Herberhausen, which are inhabited by a total of ~2,600 citizens. At its core, the Drakenberg area is about 141 ha in size. With the demise of sheep transhumance, the steeper slopes of the limestone bank were the first tracts of land where agricultural land use was abandoned (Koopmann, 1994). Today the slopes are mostly covered by impenetrable Prunus spinosa and Crataegus spp. thickets resulting in the loss of highly species-rich dry meadow habitat. Herberhausen citizens regularly clear smaller parts of the slope in order to conserve dry meadow plant communities featuring impressive orchid populations. There is considerable demand for agricultural grassland east of Göttingen; the extent of this demand depends strongly on agricultural policy (i.e., subsidy) decisions of the European Union, however. Neither in the Harz area nor around Göttingen, sufficient local public funds are available to maintain traditional agricultural grassland systems nor the associated, species-rich habitats to the extent favoured by conservation administration and conservation activists. The Harz mountain area is composed predominantly of sedimentary acidic rocks. The mountain meadows of the Harz region came into existence in the 16th century, largely as a result of attempts to attract personnel for a thriving mining industry (Vowinkel, 1996). The mountain meadows contain rare plant and animal species nowhere else found in the predominantly forested Harz landscape. Phyto-sociologically, Golden Oat grasslands (Trisetum flavescens; Trisetion) and False Oat Grass grasslands (Arrhenatherum elatius; Arrhenatherion) as well as Moor Matgrass lawns (Nardus stricta; Nardion) are the most important vegetation types (Bruelheide et al., 1997). The mountain meadow area around the investigated villages is about 2,100 ha in size. The reduction of traditional grassland agriculture let to the decline and near extinction of a regional sheep breed (Leine Sheep) formerly present at Drakenberg hill, and a regional cattle race formerly wide-spread in the Harz region (Rotes Höhenvieh/Harzer Rotvieh; Auferkamp et al., 2006). It is estimated that subsidies of about 400 to 600 €/ha/yr are necessary to sustain cattle farming with Harzer Rotvieh at stocking densities of 1 livestock unit/ha (Pfeiffer, 1998).

3.2 Design of the CE instruments CEs belong to a class of stated preference techniques that allow for the simultaneous elicitation of multi-attribute benefits of the non-use values of policy scenarios (Bateman et al., 2002; Adamowicz et al., 1994). Applications in environmental non-market valuation include, e.g., moose management in Finland (Horne and Petäjistö, 2003), sustainable development options for Navarino Island in Chile including tourism development (Cerda et al., 2007), visitor benefits for African rainforest reserves (Naidoo and Adamowicz, 2005), or WTP for sustainable tourism services in southwest China (Barkmann et al., 2008b). The development, pre-testing and piloting of the survey instrument is a crucial step in any stated preference study (Bateman et al., 2002). Recreationists intercepted at Drakenberg hill as well as various local stakeholders including home owners were

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interviewed in spring 2004 (Bargsten et al., 2004). The stated reasons for visiting and appreciating Drakenberg hill were identified, and developed into CE attributes. For the Harz CE, the instrument was adapted after literature search and expert interviews with officials from local conservation offices. Thus, two similar instruments were used in both CEs consisting of 1

a two-page policy and attribute introduction including handling and administration instructions

2

eight choice sets

3

three blocks of attitudinal and knowledge questions

4

one block of standard socio-economic questions.

An outline of instrument construction is provided in the following subsections.

3.2.1 Specification of attributes and attribute levels Vistas were identified in the pre-study as a highly important valuation aspect for recreationists at Drakenberg hill. Because the mix of forest and open landscape also contributes essentially to the attractiveness of Harz mountain landscapes, we included an attribute on the open character of the landscape in both CEs. While two attribute levels were used in the Drakenberg CE, four attribute levels focusing on shrub encroachment were used in the Harz CE. For a synopsis of attributes and attribute levels, see Table 1. In both CEs, the second attribute deals with the number of animals, either sheep and/or cattle. At Drakenberg hill, sheep and cattle are currently present. The conservation of endangered Harzer Rotvieh cattle is clearly the predominant issue in the Harz Mountains. The maximum level of animal numbers at Drakenberg hill is based on the number of sheep required to keep calcareous dry meadows permanently open (approx. 3–5 ewes/ha; Rahmann, 2000). For the Harz CE, the maximum level refers to the Harzer Rotvieh cattle population in the former province of Anhalt at the end of the 19th century (Auferkamp et al., 2006). Accounting for lower numbers of adult animals, a total of 4,000 cattle would amount to about 1 livestock unit/ha if all kept on the mountain meadows around the villages of Stiege and Hasselfelde. The inclusion of this attribute is essentially ‘policy driven’ as the further demise of agricultural animal husbandry must be expected for both study sites without additional financial support. Because of expected differences in the perception of agriculture between suburban and rural residents, the next two attributes are used only in one of the CEs each. In the Drakenberg CE, we focused on the question wether livestock farming was done explicitly for conservation purposes or not. For the rural Harz setting, it appeared more important to include the number of farms breeding Harzer Rotvieh cattle in the region. Pre-study interviews had indicated a certain awareness of the conservation value of Drakenberg hill, particularly as it harbours a substantial population of orchids. In the Drakenberg CE, we refer to the ‘occurrence of protected orchids and their habitat (dry meadows)’ in a semi-quantitative way (see coding). By using the loss of total plant species and loss of regionally endangered species, a quantitative measure of species conservation effects was employed in the Harz CE.

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Table 1

Attributes and attribute levels of the Drakenberg and the Harz CEs

Valuation aspect/attribute

Attributes levels [coding] § Drakenberg

Vistas

Harz

Good: 65% open land with flowers and hedges*

Very good: 0% shrub encroachment (SE) [0];

Bad: 15% open land with flowers and hedges

Good: 25% SE [–25] Bad: 50% SE [–50] Very bad: 90% SE* [–90]

Animal numbers (mainly sheep and cattle)

Purpose of livestock farming

No animals (0)

Very few animals (~400)*

A few animals (~50)*

Few animals (~800)

Many animals (~150)

Many animals (~2,000)

Very many animals (>500)

Very many animals (~4,000)

For not specifically identified purposes [0]* For conservation purposes [1]

Farms with Harzer Rotvieh

0*; 3; 6; 9 farms

Species conservation

Occurrence of orchids and their habitats: No [0]; A few [1]*; Many [2]

# of species lost: total [of those: red data book species]: 0 [0]; 100 [25]; 200 [50]; 400 [100]*

Permanent change in housing costs

–2; 0*; +1.5; +3 EUR per person/month

0*; 1.5; 2.5; 4; 7 EUR per person/month

Note: § Brackets indicate coding if not obvious from quantification given * Drakenberg: status quo level * Harz: worst case without remedial action in the year 2017 Table 2

Prior knowledge-related items

Item

Wording (‘truth value’ of item statement)

Past3-D

It would be best for the mountain meadows if all human management would cease. (false)

Cons3-H

For the red data book-species and their habitats, it would be best if grazing with sheep and cattle ceased. (false)

Cons4-H

Even many cattle and sheep at the Harz mountain meadows can be useful for nature conservation. (correct)

Cons5-D

The habitats of orchids at Drakenberg (‘dry meadows’) are a result for human influence. (correct)

Cons6-D

More than 500 sheep and cattle are probably a problem for the rare orchids and their habitats. (false)

Note: D: Drakenberg CE; H: Harz CE

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The cost attribute was operationalised via a change in permanent housing costs per person per month. For the Drakenberg CE, a mixed WTP and WTA format was used (one decreasing, two increasing levels of housing costs) because a further deterioration of the status quo may occur (Cerda et al., 2007)1. For the Harz CE, only the WTP format was used because the status quo option was defined in terms of a worst case scenario assumed to occur by the year 2017 if no additional actions for the conservation of the mountain meadows are taken.

3.2.2 Attitudinal and prior knowledge items The attitudinal and prior knowledge items are organised around the perception and appreciation of: 1

aesthetic site qualities

2

past landscape ideals

3

conservation issues focusing on livestock farming and species protection.

These themes reflect different visions of central management objectives regularly discussed in conservation and landscape planning. Direct references to the Drakenberg landscape and its biota in the different items were replaced with Harz mountain meadow equivalents in the Harz CE instrument. All items use a 5-point Likert scale answering format (++: I agree largely [+2]; +: I somewhat agree [+1]; O: I am undecided [0]; – : I rather disagree [–1]; – – : I largely disagree [2]; coding in brackets). Five of a total of 16 items assess prior knowledge on the relation of habitat and species conservation with traditional sheep and cattle farming in the project regions (translated items in Table 2). These five items were averaged to form a knowledge indicator ranging from –2 to +2 with +2 indicating a correct answer of ‘I largely agree/disagree’ for all five items.

3.2.3 Experimental design and CE administration From 42*22*31 (44*51) attribute level combinations in the Drakenberg (Harz) CE, profiles for two generic non-status quo choice cards were generated according to an orthogonal main effects design using SPSS 12.0 conjoint procedures. The resulting choice sets were assigned to blocks of eight choices each. A preliminary version of the Drakenberg CE instrument was piloted in Herberhausen and Roringen in 2004 (Bargsten et al., 2004). The results were discussed with local citizen representatives and NGO activists in February 2005. With an updated instrument, the Drakenberg CE was carried out in March and April 2005 in Roringen and Herberhausen. Survey activities were accompanied by press releases in several local media. A systematic sampling scheme was adopted, in which every third household was targeted. The study was introduced and questionnaires were handed out personally by a social science graduate supported by the second author. Questionnaires were picked up one or two days later; a few questionnaires were send back to Göttingen University by mail. Each target household was contacted at least three times before the adjacent household was contacted instead. Overall, 251 questionnaires from the Drakenberg investigation were obtained in time. Fifteen questionnaires were excluded because of

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missing attitudinal variables, or answering patterns that did obviously not refer to the content of the items posed. The Harz CE was administered in July 2005 to adult residents of Stiege and Hasselfelde by the second author, and conducted face-to-face. A systematic sampling procedure (see above) was applied to obtain 50 interviews from Stiege and Hasselfelde each. All 100 questionnaires from the Harz investigation are included in econometric analysis.

3.3 Model estimation and hypothesis testing Because the technical details of the application of the applied nested logit (NL) variant of the choice experiment are well documented in the literature, we refer to sources such as Hensher et al. (2005) here. For both CEs, linear functions are assumed for the relation between attributes and observable utility. As an inverted U-shape utility curve was expected according to the results of the pilot study for the animal numbers attribute, a quadratic utility term was added in model estimation. Because NL analysis relies on less restrictive statistical assumptions than multi-nomial logit models [independence from irrelevant alternatives/‘IIA’ condition; Bateman et al., (2002), p.280], we apply NL procedures. For the best eligible NL tree structure, the inclusive value was set to 1.0 for the degenerated branch, and all models initiated with starting values obtained from a non-nested NL model (Hensher et al., 2005). All scale parameters were normalised at the lowest level (‘RU1’). Estimation of NL models was carried with NLOGIT 3.0. For a comparison of model fit, we report adjusted Pseudo-R2 values: 1

improvements versus a no coefficients model

2

improvements versus a constants only model.

All models include a non-status quo alternative specific constant (ASC), and interactions of the ASC with age, sex and the income/wealth indicator. We hypothesised that higher prior knowledge results in higher economic preferences for sustainable tourism development. We test this hypothesis by examining the influence of the knowledge index on preferences for sheep and cattle husbandry that could ecologically stabilise local grasslands. Hypothesis testing utilises three models for each CE. First, a baseline model is generated with all attributes as well as with the ASC and ASC interactions (see Table 3: D1 base, H1 base). Next, we calculated interaction variables of the knowledge index with animal numbers and squared animal numbers (see 2.2). These interactions are included in the ‘extended’ models D2 and H2. Finally, D3 and H3 represent models in which only the interaction terms are included. We reject the null hypothesis of no (positive) influence if the interaction term with the linear animal numbers attribute is statistically significant at the 5% level. Additionally, any positive influence of prior knowledge on the linear term must persist after taking into account potentially adverse effects mediated via the squared term. To assess the potential impact of prior knowledge effects on preference estimates, a simple policy scenario is used. Resulting compensating variation values are added up and multiplied by the number of residents in the project regions. As we are mainly interested in prior knowledge effects on preference estimates, no attempt is made to correct preference estimates

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1

for the small number of potential protest responses

2

for the fact that a mixed WTP/WTA format of the monetary attribute is used in the Drakenberg CE.

Table 3

Socio-demographic sample characteristics Drakenberg

Sample size – total – included§ Mean age Female respondents Knowledge index mean (SD) 25-, 50-, 75-percentile

Harz

251

100

236

100

53.7

54.3

47.4 %

45 %

0.057 (0.62)

0.458 (0.567)

–0.333; 0.000; 0.414

0.167; 0.500; 0.833

Note: § For Drakenberg, all values below based on included 236 respondents.

4

Results

4.1 Sample characteristics The most important socio-demographic characteristics of the respondents are summarised in Table 2. Average age of respondents was between 51.5 and 54.3 years. Female respondents constitute between 45 and 47% of the sample. Mean price of the household car was around 13,200 € in the two Göttingen suburbs, mean income approximately 1,080 €/month for the interviewed Harz village respondents (data not shown). The mean knowledge indicator value for Drakenberg respondents is close to zero (0.057) implying that the same amount of correct and incorrect answers was given on average. In contrast, the mean value is clearly positive for the Harz village respondents (0.458) indicating a higher awareness of the relationship between agriculture and grassland conservation.

4.2 Nested logit models and hypothesis testing All six NL models predict choices highly significantly (Chi2-values indicate P < 0.001, see Table 3). In the Drakenberg base model D1, all attribute terms are most highly significant (P < 0.001), and display the expected signs: more sheep and cattle are viewed positively (positive sign of linear term) in combination with the hypothesised inverted U-shape overall relation (negative sign of squared term). Respondents appreciate animals particularly if kept for nature conservation purposes. Also, they favour better vistas, and more orchids and their habitats. The cost attribute displays a negative sign implying a disutility of higher housing costs. Of the interactions of the ASC with socio-demographic variables, only the interaction with age is significant. If the interactions of the knowledge indicator with the linear and the squared animal number terms are additionally introduced (model D2), model fit improves. The coefficient of the linear animal numbers term interacted with the knowledge index is significant (P = 0.021), and numerically similar to the linear coefficient itself (0.511 versus 0.532). An influence of prior knowledge on the squared term cannot be

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documented statistically. Focusing only on interaction terms (model D3); model fit neither improves over D1 nor over D2. Both interaction terms become significant in D3. In the Harz base model H1, the coefficient of the number of farms holding Harzer Rotvieh cattle is most highly significant, and positively valued. Also, animal numbers are positively appreciated (P = 0.025); the inverted U-shape relation can only be documented at the level of a statistical tendency (P = 0.086). The coefficient for improved vistas is also significant. Loss of endangered species is clearly valued as a disutility as are higher housing costs (P > 0.001). The higher the reported monthly income, the more the surveyed Harz respondents favour a status of the Harz mountain meadows different from the year 2017 worst case. This effect is smaller for older and female respondents. The no coefficients-adjusted Pseudo-R2 value of model H1 is 24.3%, the constants only value is 14.3%. If the interactions of the knowledge index with the linear and the squared animal number terms are additionally introduced (model H2), the LL function value improves only slightly (–2.1) as does the constants only-adjusted Pseudo-R2 (from 14.3% to 14.4%). The linear interaction of animal numbers and knowledge index displays a tendency towards significance at the α = 5% level (P = 0.065), while the linear term itself loses its influence on choices (P = 0.502). Neither the squared term (P = 0.745) nor the interaction of the squared term with the knowledge index display significance (P = 0.11). If only the interactions are included, we obtain model H3. H3 again displays only marginal improvements over the base model in terms of overall model fit, but the interaction term with the linear animal numbers attribute becomes highly significant (P = 0.008) while the interaction with the squared term becomes significant (P = 0.034). If we base hypothesis testing on the influence of the knowledge index on preferences for sheep and cattle herding on models D2 and H3, we obtain the following result: The null-hypothesis of no influence of the knowledge index on preferences has to be rejected at the α = 5% level (significance and positive sign of the coefficient of the linear term in both models). Instead, we accept the alternative hypothesis of a (positive) influence of knowledge on preferences. Taking into account that we employed a directed hypothesis of a positive influence of knowledge on preferences, reported significances would even improve because critical values for one-sided hypothesis testing could have been used.

4.3 WTP and exemplary scenario analysis As an exemplary policy scenario, we assume maximum or near maximum animal numbers that bring about optimal vistas and conditions for species and habitat conservation. For the Drakenberg case, we supply alternative results on 150 as well as on 500 sheep and cattle to show the effect of the inverted U-shape form of the utility function. For the Harz mountain meadow CE, only one scenario with 4,000 animals is presented. Because of a strongly negative valuation of high animal numbers by Drakenberg respondents (see Figure 1), the monthly compensating variation of an average respondent with median knowledge index value is only slightly positive (0.34 €/month/respondent) in the 500 animals scenario. For respondents of the 25-percentile with regard to the knowledge index, compensating variation is even negative (–1.20 €). In part, improvements brought about by the positive contribution of the linear term are off set by a more negative squared term. 150 animals are closer to optimal animal numbers than 500 animals. If multiplied by the 2,622 inhabitants of Herberhausen and Roringen, a total

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compensating variation between ~156,000 €/yr and 202,000 €/yr is obtained for the 150 animal scenario, and between roughly –38,000 and +71,000 in the 500 animal case. If this compensating variation could be turned into an actual financial contribution for conservation land use with animals for the 141 ha of potential grassland at Drakenberg hill, in excess of 500 €/ha/yr would be available. Table 4

Nested logit models for the Drakenberg and Harz choice experiments testing for prior knowledge effects

For Harz respondents, even animal numbers as high as 4,000 prompt positive preference statements (see Figure 1). The more positive contribution of better knowledge in the

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linear term is off set by a more negative squared term to a large extent. Thus, total compensating variation improves only from 4.84 € (25-percentile) to 5.28 € (75-percentile). For the Harz CE, we excluded the contribution of the ASC terms (sum: 1.32 €/month/respondent) because they represent preferences for the presented ‘non-worst case’ sustainable tourism development options that cannot be explained by the presented attributes. If we extrapolate these compensating variation results to all 4,464 inhabitants of Stiege and Hasselfelde, aggregated WTP is between about 259,000 €/yr for the 25-percentile of the knowledge index and 283,000 €/yr for the 75-percentile. With about 2,100 ha of available mountain meadows, this could result in an additional financial contribution of roughly 160 €/ha/yr. Figure 1

5

WTP for scenarios with full conservation benefits and 150/500 (Drakenberg) or 4,000 animals (Harz) differentiated for the 25-, 50-, and 75-percentile of the knowledge index

Discussion

The two case studies presented are not in all respects identical. In particular, the two grassland systems and their agricultural as well as their socio-geographic settings differ. This required adjustments of attribute contents and wording. For example, one attribute was exchanged (number of farms with Harzer Rotvieh cattle replaced purpose of sheep and cattle herding), and the quantification of the species and habitat conservation attribute was improved. Such adjustments preclude the econometric construction of one joint NL model for both CEs. The focus attribute of this paper, numbers of sheep and cattle, as well as the items from which the knowledge index was constructed are highly similar, however. The knowledge index can only be regarded as a rough approximation of prior knowledge by psychometric standards. Even in the version employed here, the knowledge index still exerts a statistically significant influence on preferences for sheep and cattle numbers. As in the study by Fischer (2004), the additional ‘variance’ – here in form of reductions in the value of the log likelihood function explained by prior

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knowledge – is rather low, however. Nevertheless, a comparison of mean compensating variations for three exemplary policy scenarios with high animal numbers suggests an appreciable real-world effect of prior knowledge for the Drakenberg study. Here, WTP improved from 4.94 €/month/respondent to 6.41 €/month/respondent for the 150 animal scenario. For the 500 animal scenario, compensating variation changes from a WTA of 1.20 €/month/respondent to a WTP of 2.26 €/month/respondent. Multiplied with roughly 2,600 citizens in the sampled Göttingen suburbs, even this low number results in an aggregate non-market value of the scenario change of about 71,000 €/yr. For the 141 ha of potential grassland at Drakenberg hill, this would result in approximately 500 €/ha/yr additional funds for species and habitat conservation by conservation farming with animals. This financial contribution is probably sufficient to keep a flock of about 500 sheep even without additional support from European Union agri-environmental programmes. For several years, Göttingen City has been facing severe budget problems. Recently, a public discussion process was started on the long-term objectives of spatial planning in and around Göttingen City. Thus, we expect results of the Drakenberg CE to spark a local discussion on how public environmental goods such as species-rich grasslands can be financed in the future. Based on the results presented here, this discussion is likely to raise the level of knowledge on the relation of animal husbandry and grassland conservation, and thus results in increasing WTP itself. In the more rural Harz mountain setting in Siege and Hasselfelde, high animal numbers were more appreciated than close to Göttingen. The Harz respondents had, on average, a clearly better understanding of the relation of traditional animal husbandry and the evolution and conservation of species-rich grasslands than their more urban Drakenberg counterparts (mean value of knowledge index Harz: 0.458 vs. 0.057 for Drakenberg respondents). Although present to a higher extent, prior knowledge had a relatively smaller influence on WTP for the high animal number scenario in the Harz CE than in the Drakenberg CE. Aggregated WTP for a 4,000 animal conservation scenario is calculated at between 330,000 and 350,000 €/yr. Divided by 2,100 ha, roughly 160 €/ha/yr would be available to support farms with holdings of Harzer Rotvieh cattle. This is unlikely to be enough to maintain a financially viable foundation for the conservation of species-rich Harz mountain grasslands with Harzer Rotvieh cattle breed under agricultural world market conditions as assumed for the year 2017 for all present mountain meadows. Even if local consumers are additionally willing to pay more for beef produced from Harzer Rotvieh cattle (Grotelüschen and Requardt, 2006) historical cattle numbers can probably not be supported. From a tourism perspective, the most recent surge in agricultural commodity prices may have positive effects by reducing the abandonment of grasslands. If higher world market beef prices translate into better conservation options for Harzer Rotvieh cattle, remains to be seen as it is not well suited for intensified production. In aggregating compensating variation values, we assumed that each single member of a household has the indicated WTP. Although technically justified, this procedure may overestimate actual WTP in multi-member households. Also, the Drakenberg CE used a mixed WTP/WTA format of the monetary attribute. Compared to a pure WTP format, this may facilitate higher value statements as choices are not restricted by available income. The insignificance of the interaction term ASC*wealth/income indicator in the Drakenberg CE (Table 3) can be interpreted to this effect. In a study using a similar

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mixed WTP/WTA format of the payment vehicle, a WTP/WTA disparity of 1:2.8 was found (Cerda et al., 2007). Accordingly, the absolute compensating variation values presented should be used with caution. The effect of prior knowledge on preferences is not affected by this issue, however. From a theoretical perspective, the appreciable influence of the knowledge index particularly on preferences of urban residents for the Drakenberg scenario with high-animal numbers underscore the idea that prior environmental knowledge exerts a more pronounced effect on behavioural intentions than generally acknowledged. This effect, however, appears restricted to situations in which 1

the relevant environmental knowledge is directly related to the investigated behavioural intention

2

the prior knowledge helps to connect the effects of a proposed action to relevant values.

The direct relation of the first point is clearly given in this study. Social psychology suggests a mechanism according to the second point. With the results of the presented study, we cannot judge, though, if the prior knowledge actually helped respondents to connect higher animal numbers with positive conservation and amenity value effects. This connection appears highly plausible, however. In applied terms, the absolute values of the knowledge index suggests that substantial deficits in prior knowledge exist regarding the relation of traditional extensive sheep and cattle farming, and the evolution and conservation of species-rich grasslands in the population at large. Because the ecological background is rather simple (sheep and cattle prevent shrub encroachment that endangers rare species and good vistas, i.e. main tourism resources), an educational intervention on the relation is likely to precipitate increased WTP for conservation scenarios employing high animal numbers. In turn, this will protect the amenity value of the investigated grassland landscape and their value for tourists and recreationalists.

Acknowledgements We acknowledge kind support by Stiege, Hasselfelde, Herberhausen and Roringen residents, namely I. Möring and U. Grothey, and by the conservation administration of Wernigerode County. Essential support for the Drakenberg study was provided by D. Barkmann; pre-testing and pilot study profited from support by A. Bargsten, M. Fader and D. Herrmann. Comments by two anonymous reviewers helped improving the manuscript.

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Notes 1

Using this format did not pose any particular econometric problems. By including zero € change in housing costs in choice cards A and B, for example, we precluded the problem of a perfect correlation of a zero € attribute level with the status quo.