Jukuri, open repository of the Natural Resources Institute Finland (Luke) All material supplied via Jukuri is protected by copyright and other intellectual property rights. Duplication or sale, in electronic or print form, of any part of the repository collections is prohibited. Making electronic or print copies of the material is permitted only for your own personal use or for educational purposes. For other purposes, this article may be used in accordance with the publisher’s terms. There may be differences between this version and the publisher’s version. You are advised to cite the publisher’s version. This is an electronic reprint of the original article. This reprint may differ from the original in pagination and typographic detail. Author(s): Erkki Mäntymaa, Eija Pouta & Juha Hiedanpää Title: Forest owners' interest in participation and their compensation claims in voluntary landscape value trading: The case of wind power parks in Finland Year: 2021 Version: Published version Copyright: The Author(s) 2021 Rights: CC BY 4.0 Rights url: http://creativecommons.org/licenses/by/4.0/ Please cite the original version: Mäntymaa E., Pouta E., Hiedanpää J. (2021). Forest owners' interest in participation and their compensation claims in voluntary landscape value trading: The case of wind power parks in Finland. Forest Policy and Economics 124, 102382. https://doi.org/10.1016/j.forpol.2020.102382. Forest Policy and Economics 124 (2021) 102382 Available online 12 January 2021 1389-9341/© 2020 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Forest owners’ interest in participation and their compensation claims in voluntary landscape value trading: The case of wind power parks in Finland Erkki Mäntymaa a,*, Eija Pouta b, Juha Hiedanpää c a Natural Resources Institute Finland (Luke), Paavo Havaksen tie 3, FI-90014 Oulun, Finland b Natural Resources Institute Finland(Luke), Latokartanonkaari 9, FI-00790 Helsinki, Finland c Natural Resources Institute Finland (Luke), Itäinen Pitkäkatu 4a, FI-20520 Turku, Finland A R T I C L E I N F O JEL classification: Q23 Q42 Q51 Keywords: Payments for ecosystem services Harmful effects of wind turbines Forest landscapes Private forest owners Landscape value trade Willingness to accept compensation A B S T R A C T Although wind power is regarded as a sustainable way to produce electrical energy, wind turbines may cause harmful effects locally. A possible solution is to reduce the effects through forest management practices, for example leaving forest stands uncut as landscape shields to hide the turbines and stop them from spoiling the scenery. Using data from an online survey of landowners, we investigated whether voluntary mechanisms could encourage forest owners to change their forest management practices near wind farms to minimize the harmful effects. More precisely, we analyzed forest owners’ willingness to participate in an initiative involving payment for ecosystem services called Landscape Value Trade (LVT) and studied the related compensation claims in southwestern Finland. We explained willingness to participate and the claims made with the characteristics of the landowners or their holding and with attitudinal variables. According to our results, 73.6% of the re spondents would possibly or certainly participate in the mechanism. The average annual compensation requirement in this study was €298 per hectare. In addition, we found that low dependence on forestry and forest-related income tended to increase interest in participation in the LVT initiative and reduce the compen sation claims. An important result related to the cost-effective application of the mechanism, is that the more interested the respondents were in cooperation with the LVT initiative the less compensation they would claim. Thus, the voluntary nature of the LVT initiative simultaneously acted as a cost-reducing element. The results could help in detecting some of the key features of the supply side of LVT initiatives. 1. Introduction Compared to the use of fossil and biofuels, wind power is generally regarded as a sustainable way to produce electrical energy due to the possibility it provides to reduce carbon dioxide emissions into the at mosphere and help prevent climate change. Thus, investments in wind power are expected to increase in the future (Huttunen, 2017), which will lead to wind parks also being located closer to residential buildings and villages than currently, where they will be strongly present in the visual landscape of local people. Although wind power is globally seen as environmentally friendly, wind turbines may cause harmful effects on a local level (Groothuis et al., 2008). Tall wind turbines near homes, holiday homes, or outdoor recreation areas may visually disturb the scenery. The shadows from the towers or the shadow flicker of the turbine blades may disturb people. The low frequency noise of the rotors may cause stress. In addition, people may worry about the effects on their health or that of family members (Zerrahn, 2017). Thus, in the building of wind turbines global and national environmental benefits come into conflict with some of the local environmental drawbacks (Warren et al., 2005). Several studies have examined the externalities that wind turbines cause on the landscape and biodiversity. Using a data set from a choice experiment (CE) survey, Mariel et al. (2015), for example, analyzed the preferences of German citizens regarding wind farms and showed how preferences differed between inhabitants. Meyerhoff et al. (2010) investigated landscape externalities affected by onshore wind power with two CE surveys carried out in Westsachsen and Nordhessen, Ger many. Specifically, the study analyzed how the surface area of wind parks, the maximum height of turbines, the influence on biodiversity (i. e., the hawk population), the shortest distance to inhabited areas and the monthly addition to the electricity tariff affected the acceptability of wind power. Using a spatial CE survey, Meyerhoff (2013) examined how * Corresponding author at: Natural Resources Institute Finland (Luke), Paavo Havaksen tie 3, FI-90570 Oulu, Finland E-mail addresses: erkki.mantymaa@luke.fi (E. Mäntymaa), eija.pouta@luke.fi (E. Pouta), juha.hiedanpaa@luke.fi (J. Hiedanpää). Contents lists available at ScienceDirect Forest Policy and Economics journal homepage: www.elsevier.com/locate/forpol https://doi.org/10.1016/j.forpol.2020.102382 Received 27 February 2020; Received in revised form 9 December 2020; Accepted 12 December 2020 mailto:erkki.mantymaa@luke.fi mailto:eija.pouta@luke.fi mailto:juha.hiedanpaa@luke.fi www.sciencedirect.com/science/journal/13899341 https://www.elsevier.com/locate/forpol https://doi.org/10.1016/j.forpol.2020.102382 https://doi.org/10.1016/j.forpol.2020.102382 https://doi.org/10.1016/j.forpol.2020.102382 http://crossmark.crossref.org/dialog/?doi=10.1016/j.forpol.2020.102382&domain=pdf http://creativecommons.org/licenses/by/4.0/ Forest Policy and Economics 124 (2021) 102382 2 the respondents’ experience of turbines, e.g., the distance from a dwelling place to the nearest turbine, affected the propensity to support wind power generation. Furthermore, the welfare effects were also measured using a willingness to pay (WTP) measure. Bartczak et al. (2018) examined whether preferences for avoiding externalities from wind energy development near places of residence are influenced by personal beliefs about the negative effects of wind energy production in Poland. Using an approach based on the willingness to accept compen sation (WTA), Dimitropoulos and Kontoleon (2009) carried out a CE study to examine the factors affecting local acceptance of wind power in the Aegean Islands, Greece. Finally, Drechsler et al. (2011) constructed a model for optimizing the regional distribution of wind turbines, taking into account the social benefits and costs of wind energy production with the help of a CE survey of residents in West Saxony, Germany. If it were possible to reduce the negative local externalities, the acceptability of wind power might increase and the identification of locations for wind parks might become easier. A possible solution in the forested landscape, which is typical in Finland, may be to reduce the disturbing effects of wind turbines through forest management prac tices. This means that forest owners would avoid clear cuttings and use more cautious regeneration practices, i.e., continuous cover forestry or prolonged rotation, between residential areas and wind turbines. The aim would be that the standing trees would hide the turbines and stop them from spoiling the scenery. Here, we refer to these forest stands as landscape shields. If forest owners were willing to refrain from cutting mature forests between residences and the turbines, the harmful effects of the turbines could be alleviated or at best completely avoided. In recent years, the use of economic incentives for landowners, such as payments for ecosystem services (PES), has been presumed to help in environmental protection or the production of environmental benefits. Typically, in the implementation of these types of mechanisms, land owners make voluntary fixed-term contracts with a public authority or some other organization and receive monetary compensation for the protection or production of environmental benefits (Smith et al., 2013). In most cases, the funds for the compensation come from public sources (Mäntymaa et al., 2009; Gadaud and Rambonilaza, 2010). However, previous literature indicates that in some cases, private funding can additionally lead to landscape improvements (e.g., Tyrväinen et al., 2014). Some studies have also analyzed the acceptance of and condi tions for the participation of private forest owners in relation to the mechanism of providing landscape or recreational values for compen sation, i.e., Landscape Value Trade (LVT) (Gadaud and Rambonilaza, 2010; Mäntymaa et al., 2018b; Tyrväinen et al., 2020). The application of PES to counter the negative externalities of wind power using landscape shields in an LVT initiative is new but not straightforward. In the case of wind power, forest owners would be paid for the maintenance of landscape shields if they postponed cutting the forest at economically optimal points of time and suffered monetary losses as a consequence. From the social point of view, postponing forest cutting is rational, as mature forest provides the majority of landscape ecosystem services (ES) (e.g., Gundersen and Frivold, 2008; Ribe, 2009). With the payments, the landscape benefits of local residents and people who use the area for recreation and the economic losses of forest owners should be balanced. If the forest owners’ income losses are compensated for, then their attitude towards the provision of the landscape ES should be favorable. Of course, the case could also be that the compensation demanded by forest owners is higher than the benefits perceived by citizens. In this case, the program would not be feasible or worth implementing. Nevertheless, information is needed on the interest of landowners in taking part, as well as on their compensation requests. As far as we know, this theme has not been analyzed before. Thus, to ease the implementation of wind power plans, there is a clear need to investigate the determinants of participation in LVT, as well as the compensation requirements of forest owners. Using survey data, we investigate the interest of landowners in providing a landscape shield. We study the mechanisms that would encourage forest owners to manage their forests near wind farms so that their harmful or disturbing effects could be minimized. Specifically, we examine whether forest owners are willing to reduce the negative effects by using a new mechanism termed Landscape Value Trade (LVT). In addition, we identify the background variables that affect the re spondents’ interest in participating in LVT initiatives, in particular the role of socio-demographic and attitudinal variables. Finally, we analyze the amount of financial compensation that landowners are likely to claim for being ready to manage their forests to minimize the harmful effects of wind turbines. The focus of this study is on producing a general feasibility evaluation for the planning of the mechanism at the regional level. We do not aim to go to the forest stand level, where the detailed planning and negotiation regarding the practical application of LVT would take place if the mechanism is found generally feasible. 2. Previous literature: landowner participation in PES Scientific knowledge on the willingness of landowners to participate in ecosystem service provisioning is crucial when designing PES mech anisms. It helps to target those owner groups who are more willing to participate in such policies (e.g., Ross-Davis and Broussard, 2007). Un derstanding the factors underlying willingness is essential for the reasonable design and implementation of mechanisms and further tailoring of consulting and information services for landowners (Boon et al., 2004; Maybery et al., 2005; Kendra and Hull, 2005). We assume that the choice of landowners to participate in a program that provides non-market ES takes place in two phases. First, the land owners make a general decision as to whether they are interested in participating in the program. They will decide to participate if their expectations for the utility gained from the land are higher with participation than without participation. Second, the landowners consider a compensation request that guarantees the utility level to be higher after participation in the program. If the landowners also benefit from the non-market ES that they provide, the compensation request may be lower than the economic loss from the management practices they have given up (Mäntymaa et al., 2009). Previous landowner studies have indicated the empirical variables that associate with participation in providing ecosystem services and with the demand for compensation. Landowner characteristics, such as socio-demographics, values, attitudes and beliefs, the economic aspects of a holding as well as its other characteristics, have been shown to affect the willingness to offer environmental services (e.g., Knowler and Bradshaw, 2007; Grammatikopoulou et al., 2012). Socio-demographic characteristics, such as age (Wynn et al., 2001; Vanslembrouck et al., 2002; Langpap, 2004), educational background (Vanslembrouck et al., 2002), and on-farm as well as off-farm income (Wossink and van Wenum, 2003; Loftus and Kraft, 2003; Zbinden and Lee, 2005; Defran cesco et al., 2008), have predicted landowner behavior relatively well. Of the property characteristics, the size of the holding has proven to be an important determinant of participation (Vanslembrouck et al., 2002; Lynch and Lovell, 2003; Zbinden and Lee, 2005; Defrancesco et al., 2008). Geographical factors (Wossink and van Wenum, 2003; Lynch and Lovell, 2003; Jongeneel et al., 2008) have indicated that interest in participation may be spatially heterogeneous. Valuation studies have provided information on the compensation requests of landowners following ES provision. Such studies have indi cated that the compensation requests relate to the current management practices, the attributes of the new scheme, and landowner character istics, knowledge, and perceptions (e.g., Ruto and Garrod, 2009; Espi nosa-Goded et al., 2010; Christensen et al., 2011; Broch and Vedel, 2012; Vedel et al., 2015b; Villanueva et al., 2017). Broch and Vedel (2012) demonstrated that a compensation request is associated with the relevant ES, while the WTA of landowners is lower when the aim is to protect biodiversity or groundwater compared to opportunities for rec reation. Several studies have shown (Espinosa-Goded et al., 2010; Aslam et al., 2017) that regardless of the offer of compensation, a considerable E. Mäntymaa et al. Forest Policy and Economics 124 (2021) 102382 3 group of landowners prefer to remain in a status quo state, showing an aversion to changing their present management practices. One reason for this may originate from the attitudes of many forest owners towards all forms of protection that have been found to be negative (Bergseng and Vatn, 2009; Nordlund and Westin, 2011). In addition, the trans action costs may decrease the interest of forest owners in participating. Moreover, this may be an indication of status quo bias, i.e., the tendency to choose an alternative reflecting the current situation, which is well known in the stated preference literature (Bonnichsen and Ladenburg, 2015; Kahneman et al., 1991). Furthermore, previous studies have revealed the challenges in using a WTA measure in valuation, specif ically the disparity between WTP and WTA (Horowitz and McConnell, 2002; Tunçel and Hammitt, 2014), as well as low incentives to reveal true preferences, i.e., a low incentive compatibility. Beyond the landowner, holding, and environmental characteristics, which are easily observable, previous literature has highlighted the strong role of values, attitudes, beliefs, and perceptions in the back ground of conservation and management decisions (e.g., Vanslem brouck et al., 2002; van Putten et al., 2011; Grammatikopoulou et al., 2012; Defrancesco et al., 2008), the importance of production objec tives, or the intrinsic and social values of owning land (Emtage and Herbohn, 2012; de Young, 2000), in addition to bonds with the land (Ryan et al., 2003). The owners of small-scale forests are a heteroge neous group with a wide range of objectives and values that affect their decisions regarding conservation and land management (Karppinen, 1998; Kline et al., 2000; Bolkesjø et al., 2007; Butler et al., 2007; Finley et al., 2006; Ingemarson et al., 2006; Becker et al., 2013). Previous studies have revealed perceived trade-offs between producing timber and non-market services such as maintaining the landscape and recre ation opportunities (Gordon et al., 2010; MEA, 2003; Power, 2010; Rodríguez et al., 2006). Previous forest owner studies concerning the willingness to produce amenity values via PES schemes have especially focused on the con servation of biodiversity (e.g., Horne, 2006; Mäntymaa et al., 2009; Boon et al., 2010; Lindhjem and Mitani, 2012; Vedel et al., 2015a, 2015b). There has been much less research on the willingness of forest owners to provide scenic and leisure values in PES schemes (Ovaskainen et al., 2014; Gadaud and Rambonilaza, 2010; Mäntymaa et al., 2018a; Tyrväinen et al., 2020). Ovaskainen et al. (2014) observed heterogeneity in forest owners’ preferences towards ecosystem services. Many forest owners already provide some of these services spontaneously on their holdings, bearing the loss of income from timber sales themselves. They may benefit from the produced ES so much that the benefits compensate for the loss in timber sales. If, instead, they were to make a formal contract on the provision of these services for a fixed time period within a mechanism, LVT for example, they would lose not only income but also a part of their self-determination, which would imply a need for addi tional compensation. Depending on the magnitude of the perceived benefits and the self-determination cost, WTA may be under or over the loss in timber. Gadaud and Rambonilaza (2010) valued the compensa tion requests of forest owners for providing open access to nature-based recreational activities on private lands, and they introduced indicators of the fire risk as a factor affecting the financial compensation re quirements of forest owners. Mäntymaa et al. (2018a) found that more restrictive guidelines regarding forest management practices reduced the interest in participating and increased forest owners’ compensation requests in the proposed landscape value trading scheme. According to Tyrväinen et al. (2020), the largest marginal compensation requests were related to an extensive contract length and strict “no cutting” restrictions. Compared to holding characteristics or socio-demographic variables, previous studies have demonstrated the relative importance of attitu dinal factors in explaining the participation of land owners in PES schemes (Grammatikopoulou et al., 2012). Their interest in partici pating in a PES initiative can be interpreted as a behavioral intention following the attitude-behavior model presented by Ajzen and Fishbein (1980), in which actual behavior is preceded by behavioral intentions. In the causal sequence, a behavioral intention is a composite of attitudes towards a specific behavior. Attitudes towards an object are a composite of more detailed beliefs. The target of attitudes that significantly influ ence participation in a voluntary environmental scheme has been found to be quite broad (e.g., Grammatikopoulou et al., 2012). The probability of participation has been significantly and positively associated with attitudes towards the environment (Vanslembrouck et al., 2002; Lang pap, 2004), the perceived environmental benefits, and their state with and without a program (Söderqvist, 2003; Mäntymaa et al., 2009). Additionally, policies concerning current management practices and the perceived threat of regulation of landowner activities have been found to influence the decision to participate in PES schemes (Langpap, 2004). Attitudinal factors that concern environmental governance have also been considered as elements in the participation decision (Defrancesco et al., 2008; Wauters et al., 2010). In addition, participation may be driven by attitudes towards the voluntary scheme itself, beliefs con cerning its design and its implementation (Mäntymaa et al., 2009; Moon and Cocklin, 2011), as well as beliefs concerning the benefits to be ob tained with the scheme and the perceived difficulty of applying it (Defrancesco et al., 2008; Wauters et al., 2010; Moon and Cocklin, 2011; Reimer et al., 2012). This study contributes to the literature by applying the concept of PES to forest landscape services. Our application is novel, as it aims to reduce the harmful effects of other land uses, i.e. wind power. We show the strong role of attitudes in forest owners’ interest in participating in the suggested mechanism. We group the attitudinal factors into five categories while analyzing their effect on participation: 1) beliefs about the environmental good (landscape) and 2) about changes in the land scape due to wind power, 3) beliefs concerning the current governance of wind power externalities and 4) the governance of landscape issues in general, and 5) beliefs related to the introduced scheme, i.e., the LVT mechanism. We are interested in the relative importance of the two following types of variables: first, the characteristics of the landowner or their holdings, and second, attitudinal variables. This is because their roles in explaining participation have very different policy implications. If the landowner and holding characteristics are more important in explaining participation, the role of consultation and information services will be to find the right type of landowners. If attitudes based on information- driven factors are emphasized in participation decisions, the role of consultation and information services will be to target the beliefs behind the attitudes while providing information and designing counselling campaigns directed towards landowners. 3. Case study area, materials and methods 3.1. Case study area: two counties in southwestern Finland The case study area of this research comprises two counties, i.e., Varsinais-Suomi and Satakunta (Fig. 1), in southwestern Finland, where the wind power industry will be rapidly developed in the coming years (Huttunen, 2017). The regional land use plan presents an inventory of areas that are feasible for the development of wind power parks (Regional Council of Southwest Finland, 2011). The Regional Council of Southwest Finland chose to designate 20 larger areas for wind power parks allowing 10 or more turbines and 13 smaller parks with 6–9 tur bines, located either inland or on the coast of the Gulf of Bothnia. For wind power parks that are important on a county level, the Regional Council of Satakunta has designated 17 important areas comprising a target area of 128 km2. The designated areas, mostly located in sparsely populated, but not uninhabited, rural regions, will allow more than 300 wind turbines to be constructed with a total electric power output of 3.1 terawatt-hours (Regional Council of Satakunta, 2014). In the Finnish land use legislation, defining an area in a regional land use plan is a precondition for starting the detailed planning and building of a wind E. Mäntymaa et al. Forest Policy and Economics 124 (2021) 102382 4 power park (Land Use and Building Act 132/1999, 1999). Municipalities have the right to decide on detailed land use planning in their areas. After the master plans have been prepared, private energy companies are responsible for the permit processes and other practical aspects of building the wind turbines. 3.2. Questionnaire, data collection, and sample representativeness Data on interest among landowners in producing a landscape shield and participating in an LVT initiative to reduce the landscape distur bance caused by wind turbines were collected via an Internet survey. The questionnaire of the survey had four sections. The first section inquired about the respondents’ perceptions concerning the different types of changes in the landscape, their attitudes towards wind turbines and their impacts, as well as the respondents’ attitudes towards compensation for the externalities of wind turbines. In addition, the section included a map (Fig. 1) presenting the locations of current operating and planned future wind power parks. The zoomable map increased the spatial explicitness of the survey by allowing respondents to locate their homes, forest holdings, and summer cottages in relation to the wind power parks. The second section briefly described the idea of a landscape shield. Respondents were told that the harmful effects of wind turbines could be reduced with the certain types of forest management practices. This would mean that, between residential areas and wind turbines, forest owners would avoid clear-cutting or would use lighter management practices, e.g. continuous cover silviculture. In this way, narrow belts of forests would remain and hide the wind turbines. After this information, the section constructed a scenario for a claim for compensation. The respondents were asked to imagine a hypothetical situation in which a wind power park was planned to be built in the neighborhood of their forest parcel near other people’s homes or vacation homes. Then, the respondents were asked their opinions about the functionality of a landscape shield to reduce the harmful effects of wind turbines and to preserve the benefits of ES. Furthermore, the section asked the re spondents about their own interest in providing a shield and their perception of other forest owners’ interest in providing a shield. In these questions, respondents were asked to imagine that a possible landscape shield could prevent a wind turbine from being visible from local homes or vacation homes. The aim was that the scenario would be applicable to all the respondents, allowing them to imagine a hypothetical situation in which their own standing forest belt would hide a turbine. There was also a question about their interest in discussing forest management related to a landscape shield with neighboring residents. The section described a hypothetical possibility of making a contract to provide a landscape shield for a limited period of time and asked for the lowest possible amount of annual compensation per hectare re spondents would accept for this type of agreement. The question regarding compensation asked whether the respondent had indicated interest in providing a shield or not. Here, we reminded the respondents Fig. 1. Case study area: the counties of Satakunta and Varsinais-Suomi. Legend: red points = existing wind parks, green points = planned wind parks. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) E. Mäntymaa et al. Forest Policy and Economics 124 (2021) 102382 5 that overly large compensation claims may prevent a contract from being agreed. A payment card contingent valuation method was used to determine a value for the compensation. The respondents were pre sented a list of incremental monetary amounts and asked to indicate the lowest amount of their compensation requirement. The bid vector was €0, €5, €7, €10, €15, €20, €25, €35, €50, €75, €100, €140, €200, €300, €400, €550, €750, €1000, and more than €1000 per year per hectare; that is, the predicated WTA was revealed in 18 interval classes. Before the main survey, we conducted a pilot survey which demonstrated that the bid vector worked well. The section also included measures of atti tudes towards governance on landscape issues in general and towards the introduced LVT mechanism. The third section asked about details related to forest ownership including the total forest area owned, the amount of final felling over the previous few years, the amount of mature forest and the forest area a respondent would possibly be willing to provide as a landscape shield. Finally, the fourth section asked for some background features of the respondents. The survey was directed at private non-industrial forest owners in the counties of Varsinais-Suomi and Satakunta, in southwestern Finland. We received the names and e-mail addresses of possible survey re spondents from the Register of Forest Owners managed by Suomen Metsäkeskus (the Finnish Forest Centre). The number of private non- industrial forest owners owning forest in the case study area was 7200 persons. Most of the forest owners lived in the region. The sample of the study was a total sample, i.e., we sent the questionnaire to all forest owners in the area. After testing the questionnaire with a pilot survey of 100 respondents in January 2019, we conducted the main survey of 7100 respondents in February 2019. The practical data collection was organized by a commercial survey company, Taloustutkimus Oy, and the survey was conducted online by sending out a call and an internet link to the survey in e-mail messages. After two reminders, we received 1165 responses meaning a response rate of 16.4%. We evaluated the representativeness of our data in relation to the data from the same area in the national survey of forest owners con ducted by Hänninen et al. (2011) (Table 1). In our data, the respondents were slightly more often male, but concerning their age, we only found differences in the two oldest age groups. The lower level of participation in our study may reflect the fact that older generations less often respond to online surveys than younger ones. On the other hand, the distribu tions of the types of living environment, i.e. countryside or a city, were statistically equal in the two studies (chi-squared test of consistence, p = 0.996). The fact that the surface area of forest holdings was more extensive in our study than in that by Hänninen et al. (2011), specifically 48.4 ha vs. 30 ha, respectively, appears to show that in the present study the PES scheme was more often interesting for those who owned above- average acreages of forested land (compare this to Mäntymaa et al., 2018a). These differences indicate that those owners who were more concerned than average about the connection between forestry and wind turbines may be over-represented in our data. 3.3. Econometric models and variables The first task of the study was to explain the respondents’ interest in participating in LVT. As the interest was measured with a three-step scale, where 0 = no, 1 = maybe, and 2 = yes, we analyzed the depen dent variable (INTEREST) with an ordered probit model. The corre sponding distribution of the variable was 26.4%, 44.1%, and 29.5%, respectively. Analyzing more carefully those who were not interested in participation in LVT, we constructed a binary probit model in which those who responded “no” (26.4%) were compared to the rest of the respondents (73.6%) (NOINTEREST). The second task was to ask the respondents about possible compensation claims. As we used a payment card as an elicitation technique, the survey did not provide exact monetary amounts but ranges within which the WTAs are located. Table 2 presents the distri bution of WTAs across the bid vector. To explain WTA, i.e., the smallest annual monetary compensation per hectare for providing a landscape shield in the LVT scheme for 5 or 10 years, we constructed a grouped data model. In the analysis, the monetary amounts larger than €1000 were deleted from the data as outliers, because the amounts were probably unrealistically large for a practical implementation of the mechanism.1 Computed from the category centers of the bid vector of the payment card, the annual mean WTA was €297.6 per hectare (std dev. €248.8/ha/year, median class €200.01–300/ha/year) (Table 4). For those who responded “zero” or “don’t know” to the question related to compensation, we requested a rationale for the response with a follow-up question. Overall, the number of such responses was low, i.e. only 41 (Table 3). The actual number of respondents was even lower, as the answers were overlapping, with 17 respondents of 1381 giving these answers, meaning only 1.23% of all respondents. The rationale that “My forest is not suitable for a landscape shield”, for example, was only chosen by three respondents (0.22%). These results suggest that protest responses or outliers were not a serious problem in this survey. The potential socio-demographic and forest holding variables for the Table 1 Socio-demographic features of the respondents in the counties of Satakunta and Varsinais-Suomi in the wind turbine study and in the same area in a national study by Hänninen et al. (2011). Satakunta and Varsinais-Suomi in wind turbine study Satakunta and Varsinais-Suomi in national studya Sample sizeb 1381 Gender (%) Female 21.4 24 Male 78.6 76 Age (years, %) Below 45 16.0 15 45–54 22.3 18 55–64 29.8 31 65–74 26.2 21 75 or above 5.7 14 Mean 57.6 59 Type of living environment (%) Countryside 63.4 64 Town or city 36.6 37 Area of forest holding (%) Below 10 21.0 32 10–19.9 18.5 28 20–49.9 31.3 27 50–99.9 17.2 10 100 or above 11.9 4 Acreage of forest holding (ha) Mean 48.4 30 a Source: Hänninen et al. (2011). b The number of observations varies between questions. Table 2 Distribution of compensation claims across the bid vector (n = 1381). WTA, €/year/ha % WTA, €/year/ha % 0 1.2 75.01–100 13.6 0.01–5 0.2 100.01–140 3.6 5.01–7 0.1 140.01–200 13.1 7.01–10 0.7 200.01–300 13.6 10.01–15 0.1 300.01–400 10.2 15.01–20 0.4 400.01–550 9.0 20.01–25 1.2 550.01–750 3.9 25.01–35 0.4 750.01–1000 8.5 35.01–50 3.7 More than 1000 14.9 50.01–75 1.6 1 The number of deleted observations of WTA above €1000 was 205. We conducted a sensitivity analysis with and without the deleted observations and found that the models changed only marginally but they fitted the data much better without these observations. E. Mäntymaa et al. Forest Policy and Economics 124 (2021) 102382 6 models were selected based on a literature review. For the independent variables of the participation models and the compensation claim models, we selected 10 socio-economic variables, which are presented in Table 4. To analyze the role of the attitudinal variables and the landowner and holding characteristics in the participation decision, we modelled the decision on participation and the WTA in two types of models.2 As regressors in the first models, we used socio-economic and forest holding variables, and in the second type, socio-economic and holding variables together with attitudinal variables. While we received the socio- economic variables more or less straightforwardly from the original data set, the construction of the attitudinal variables was slightly more complex. In the questionnaire, we measured five attitudinal concepts with beliefs about the following: 1) landscape changes with a list of 10 items focused on the landscape effects of diverse economic activities, mostly in rural areas (Table A.1 in Appendix); 2) wind power with 17 statements related to local disadvantages and local, national, or global advantages of wind turbines and wind power (Table A.2); 3) the governance of wind power externalities with 9 statements (Table A.3); 4) governance concerning landscape issues with 11 different statements (Table A.4); and 5) the LVT mechanism with 7 statements (Table A.5). The respondents were requested to evaluate the statements on a five- step Likert scale from very negative to very positive in the first set of statements and from strongly disagree to strongly agree in the four latter sets. We used principal component analysis (PCA) to analyze whether the statements in these five sets measured unified concepts that could be combined in the same variable (e.g., Afifi and Clark, 1996). We based the explanation of the PCA results on the statements that had the highest loadings on each component (see Tables A.1–A.5). Based on the PCA, we selected statements that measured the same dimension. From the principal components of Tables A.1–A.5, we found 11 statistically significant variables concerning respondents’ attitudes and perceptions. From the first PCA, which included beliefs about landscape changes in general, we found three significant variables, i.e., “Economic development in rural areas” (ECONDEV), “Decline of rural areas” (DECLINE), and “Land or soil use in rural areas” (LANDUSE) (Table A.1). In the second PCA, including beliefs related to the advantages and disadvantages of wind power, two significant variables were detected, namely “Local disadvantages of wind turbines” (WPDISAD) and “Ad vantages of wind power” WPADVAN (Table A.2). Table A.3 presents the results of the PCA related to the governance of wind turbines’ exter nalities, where we found one significant variable, “Public compensation for the landscape externalities of wind power” (PUBCOMP). The fourth PCA condensed information on statements regarding the governance of landscape issues and produced three significant variables for the anal ysis (Table A.4). We named them “Mistrust in land use planning” (MISTRUST), “Freedom of entrepreneurship” (ENTREP), and “Recrea tional-ecological compensation” (RECOMP). The final analysis related to attitudes towards the LVT mechanism produced two variables: “In terest in cooperation and LRV” (COOPER) and “Takes landscape values into account in forest management” (MANAGE) (Table A.5). As a basis for the regressors, we did not directly use the loadings of PCA. Instead, we calculated the variables using the original Likert scale assessments of the attitudinal statements and computed an average value of the as sessments included in each principal component. Thus, the observations of attitudinal variables are average values combining the original as sessments of each respondent with several statements selected with the help of PCA. The statistically significant independent variables used in the second regression analyses explaining the respondents’ interest in participating in LVT schemes and explaining compensation claims for providing a landscape shield are summarized in Table 4. We also tested whether the total forest area owned by a respondent or several other socio-demographic characteristics, such as age, main living environment (town or city, or rural area), household structure, or the respondent’s personal income, could explain the interest in partici pation or the compensation claims. However, we did not find a signifi cant relationship, and neither did we find that attitudes related to private compensation for landscape externalities of wind turbines or attitudes towards and experiences of participation in local land use planning could significantly explain the dependent variables. Conse quently, we left these regressors out of the models. 4. Results 4.1. Interest in participation in LVT Table 5 shows how the socio-economic variables in the ordered probit model explained the forest owners’ interest in leaving a forest patch as a landscape shield, i.e., their interest in participating in an LVT scheme (INTEREST). Interest increased if other family members than the husband or wife or the responsible person in a co-ownership arrange ment made forest management decisions (OMEMBER), or if the re spondent’s level of education was higher (EDUC). On the other hand, interest decreased if the area of commercial cutting in the respondent’s forest during the previous five years increased (CUTTING) or if the re spondent’s occupation was in agriculture or forestry (AGRIFOR). A very significant and positive coefficient for a constant term indicates that the participation interest without regressors was positive. A very significant coefficient for a threshold parameter suggests that the categories of the dependent variable should not be combined into one, i.e., the use of the ordered probit model was justifiable instead of a binary model, for example. Table 6 presents an extended model in which in addition to socio- economic variables, attitudinal variables also explain forest owners’ interest in participating in LVT. Due to mutual correlations, bringing attitudinal variables into the model also changed the significance of some of the socio-economic variables. With respect to the socio- economic variables, if a respondent her/himself made forestry de cisions (MYSELF), if a family member other than the husband or wife or the responsible person in a co-ownership arrangement made forest management decisions (OMEMBER), if the respondent was male (GENDER), or if the respondent was working instead of being retired or unemployed (WORKING), the more often she or he was interested in Table 3 Rationale for “zero” or “don’t know” response for a compensation claim related to a possible landscape shield in the respondents’ forest (n = 1391). Rationale for a “zero” or “don’t know” response for a compensation claim Abs. % My forest is not suitable for a landscape shield. 3 0.22 I would probably not cut my forest anyway. 7 0.51 It is an obligation of wind power companies to minimize landscape effects. 1 0.07 In the landscape, wind turbines do not disturb me. 6 0.43 I would offer a landscape shield without compensation. 7 0.51 I do not believe that a landscape shield would work. 4 0.29 Despite compensation, I do not want any restrictions on the management of my forests. 3 0.22 I do not believe that landowners would gain any compensation for a landscape shield. 2 0.14 I have not received enough information. 1 0.07 Other problems are more important. 2 0.14 I do not believe that it would be possible to make an agreement for a landscape shield. 3 0.22 Do not know. 2 0.14 All rationales 41 2.97 2 We also considered using a sample selection model with a two-phase esti mation method suggested by Heckman (1979) (Mäntymaa et al., 2009; Mäntymaa et al., 2018a). However, the first step of the model uses a binary dependent variable. Thus, in this study with a three-step dependent variable, we would lose the information for respondents with “maybe” answers. E. Mäntymaa et al. Forest Policy and Economics 124 (2021) 102382 7 participation. Concerning attitudinal variables, the more positively the respondents perceived economic development in rural areas (ECON DEV), or possibilities to receive public compensation (PUBCOMP) or recreational-ecological compensation (RECOMP) for the landscape ex ternalities of wind power, or the more often they independently took landscape values into account in their forest management decisions (MANAGE), the more likely they were to be interested in participation. In contrast, the more positively they perceived the land or soil use in rural areas (LANDUSE) or the freedom of entrepreneurship (ENTREP), or the more often they identified local disadvantages of wind turbines (WPDISAD), the less likely they were to be interested in participation. The highly significant estimate of the threshold parameter justified the use of the ordered probit model. A comparison of the two models of participation interest shows that the value of the log-likelihood function and the McFadden Pseudo R2 both increased, from − 1329.228 to − 1161.266 and from 0.0168 to 0.1623, respectively, and the Akaike Information Criterion (AIC) decreased from 2670.5 (AIC/n = 2.114) to 2348.5 (AIC/n = 1.821) if we added the attitudinal variables into the analysis. Thus, the goodness of fit of the latter model with the attitudinal variables is considerably Table 4 Description and descriptive statistics of the variables used in the analysis. Variable Description Mean Std dev. Dependent variables INTEREST Forest owner’s interest in participating in LVT; ordinal variable: 0 = no (26.4%), 1 = maybe (44.1%), 2 = yes (29.5%). 1.03 0.747 NOINTEREST Forest owner’s interest in participating in LVT; binary variable: 0 = maybe or yes (73.6%). 1 = no (26.4%). 0.26 0.441 WTA Forest owners’ stated compensation request within an LVT for 5 (10) years; disclosure technique: payment card; bid vector: €0, €5, €7, €10, €15, €20, €25, €35, €50, €75, €100, €140, €200, €300, €400, €550, €750, €1000/year/ha. WTAs are coded into 1, 2, …, 18 categories; the first category (zero WTAs) equals the interval y* < 1; the second category (€5): 1 ≤ y* < 5; the third category (€7): 7 ≤ y* < 10 and so on; the 18th category: 750 ≤ y* < 1000. 297.6a 248.8a Socio-economic independent variables Characteristics of the forest holding MATURE Area of mature forest in the respondent’s holding (ha) 10.09 19.742 MYSELF Respondent him/herself makes forestry decisions; binary variable: 0 = no (40.3%), 1 = yes (59.7%) 0.60 0.491 OMEMBER A family member other than the husband or wife or the responsible person in co-ownership makes forest management decisions; binary variable: 0 = no (84.9%), 1 = yes (15.1%) 0.15 0.359 Financial characteristics of the respondents CUTTING Area of commercial cutting in one’s forest in the last 5 years; ordinal variable: 1 = 0 ha (36.8%), 2 = 0–1 ha (8.8%), 3 = 1–5 ha (36.0%), 4 = 5–10 ha (12.7%), 5 = 10–20 ha (3.4%), 6 = 20–30 ha (1.3%), 7 = more than 30 ha (0.8%) 2.72 1.779 METSO Respondent voluntarily restricted cutting in his/her forest within the METSO program; binary variable: 0 = no (93.3%), 1 = yes (6.7%) 0.07 0.251 Socio-demographic characteristics of the respondents GENDER Respondent’s gender; binary variable: 0 = female (21.4%), 1 = male (78.6%) 0.79 0.410 EDUC Level of education; ordinal variable: 1 = primary school (5.9%), 2 = vocational school (19.6%), 3 = high school (5.0%), 4 = polytechnic (41.2%), 5 = university (28.2%) 3.66 1.241 WORKING Respondent working; binary variable: 0 = no (34.0%), 1 = yes (66.0%) 0.66 0.474 AGRIFOR Occupation in agriculture or forestry; binary variable: 0 = no (78.4%), 1 = yes (21.6%) 0.22 0.412 ENVPRO Occupation in environmental protection or related areas; binary variable: 0 = no (97.0%), 1 = yes (3.0%) 0.03 0.170 Attitudinal independent variablesb Landscape changes ECONDEV Economic development in rural areasc (C1.1e) 3.43 0.622 DECLINE Decline of rural areas (C1.2e) 1.68 0.637 LANDUSE Land or soil use in rural areasc (C1.3e) 3.10 0.806 Wind power WPDISAD Local disadvantages of wind turbinesd (C2.1e) 3.00 1.051 WPADVAN Advantages of wind powerd (C2.2e) 3.50 0.966 Governance of wind turbines’ externalities PUBCOMP Public compensation for the landscape externalities of wind powerd (C3.2e) 2.83 1.078 Governance in landscape issues MISTRUST Mistrust in land use planningd (C4.1e) 3.62 0.815 ENTREP Freedom of entrepreneurshipd (C4.2e) 3.73 0.886 RECOMP Recreational-ecological compensationd (C4.3e) 2.38 0.991 LVT mechanism COOPER Interest in cooperation and LVTd (C5.1e) 3.07 1.110 MANAGE Takes landscape values into account in forest managementd (C5.2e) 3.32 0.815 a Computed from the category centers of the bid vector of the payment card. b Average value variables for the statements included in each principal component. c Originally calculated from observations of 5-step Likert scale, 1 = very negative … 5 = very positive. d Originally calculated from observations of 5-step Likert scale, 1 = strongly disagree … 5 = strongly agree. e Refers to the interpretation of principal components shown in Tables A.1–A.5 in the Appendix. Table 5 Ordered probit model of socio-economic variables explaining the interest of forest owners in leaving a forest patch as a landscape shield. Independent variable Coefficient Std Error z p Constant *****0.73918 0.11769 6.28 0.0000 OMEMBER ***0.23837 0.09079 2.63 0.087 CUTTING ***− 0.09087 0.02422 − 3.75 0.0002 EDUC *0.04825 0.02562 1.88 0.0596 AGRIFOR ***− 0.24537 0.07789 − 3.15 0.0016 Threshold parameter ***1.20727 0.04277 28.23 0.0000 Fit statistics Log likelihood function − 1329.228 McFadden Pseudo R2 0.0168 Inf. cr. AIC 2670.5 AIC/n 2.114 n 1263 *** Significant at the 0.01 level. ** Significant at the 0.05 level. * Significant at the 0.10 level. E. Mäntymaa et al. Forest Policy and Economics 124 (2021) 102382 8 better. Combining socio-economic and attitudinal variables in a probit model, Table 7 analyzes more carefully those who were not interested in participation in LVT, i.e. those who responded “no” to the interest question compared to the rest of the respondents (NOINTEREST). In the model, the plus sign of the coefficient means that the increase or the realization of the variable increased the probability of not being inter ested in participation, and vice versa. Thus, related to socio-economic variables, the positive and significant sign for CUTTING means that the larger the area where forest owners had conducted commercial final felling during the previous 5 years, the more likely they were to not be interested. On the other hand, the probability of not being interested in participation decreased if a family member other than the husband or wife or the responsible person in a co-ownership arrangement made forest management decisions (OMEMBER), and if a respondent was working instead of being retired or unemployed (WORKING). Related to attitudinal variables, the more positively they perceived the land or soil use in rural areas (LANDUSE) or the freedom of entrepreneurship (ENTREP), the more likely they were to not be interested in participa tion. In contrast, the more negatively the respondents perceived economic development in rural areas (ECONDEV) or the local, national, or global advantages of wind power (WPADVAN), or the more worried they were about the decline of rural areas (DECLINE), the less likely they were to answer “no” to the question concerning interest. 4.2. Compensation claims for participation in LVT Table 8 reports how forest owner’s interest in participating in LVT (“no”, “maybe”, or “yes”) affected the monetary compensation request for leaving a forest patch as a landscape shield. The results indicate that the greater was the interest in participating, the less forest owners claimed in compensation. The independent samples t-test (equal vari ances not assumed) for the pairwise comparison of the first two means (t = 5.181, p = 0.000) and the last two means (t = 3.619, p = 0.000), as well as the first and last means (t = 7.499, p = 0.000) showed that the mean WTAs significantly differed between the forest owners in different groups of interest. In Table 9, with a grouped data model, we present the socio- economic variables that explain forest owners’ possible WTA for participation in LVT, i.e., the smallest annual monetary compensation per hectare they would accept for providing a landscape shield. We found that an increase in the area of commercial cutting in the re spondent’s forest (CUTTING) or having an occupation in agriculture or forestry (AGRIFOR) increased the compensation claim. The WTA tended to decrease if the level of education of the respondent was higher (EDUC) or if the respondent’s occupation was in environmental pro tection or related areas (ENVPRO). Table 10 shows the combined model of socio-economic and attitu dinal variables that explain forest owners’ potential WTA. With respect to socio-economic variables, the larger the area of mature forest in the respondent’s holding (MATURE), or the more often a respondent had voluntarily restricted cutting in her/his forest within the METSO pro gram3 (METSO), or the more often a respondent worked (WORKING), the larger the WTA was. In contrast, having an occupation in Table 7 Ordered probit model of socio-economic and attitudinal variables explaining the lack of interest of forest owners in leaving a forest patch as a landscape shield. Independent variable Coefficient Std Error z p Constant *0.63851 0.37157 1.72 0.0857 CUTTING *0.06004 0.03329 1.80 0.0713 OMEMBER **− 0.32103 0.13263 − 2.42 0.0155 WORKING ***− 0.24624 0.09094 − 2.71 0.0068 ECONDEV ***− 0.25377 0.07280 − 3.49 0.0005 DECLINE *− 0.12643 0.07046 − 1.79 0.0728 LANDUSE ***0.25748 0.06741 3.82 0.0001 WPADVAN ***− 0.57657 0.04391 − 13.13 0.0000 ENTREP ***0.24513 0.05624 4.36 0.0000 Fit statistics Log likelihood function − 591.887 McFadden Pseudo R2 0.2029 Inf. cr. AIC 1201.8 AIC/n 0.920 n 1306 *** Significant at the 0.01 level. ** Significant at the 0.05 level. * Significant at the 0.10 level. Table 8 Interest of forest owners in participating in LVT and WTA compensation for leaving a forest patch as a landscape shield. Interest Mean WTA Std dev. n No 407.4 289.2 222 Maybe 294.2 238.7 563 Yes 240.4 216.3 392 Total 297.6 248.8 1177 Table 9 Grouped data regression model of socio-economic variables explaining forest owners’ WTA compensation for leaving a forest patch as a landscape shield. Independent variable Coefficient Std Error z p Constant ***225.377 18.97441 11.88 0.0000 CUTTING ***15.9082 3.99353 3.98 0.0001 EDUC **− 10.4422 4.21215 − 2.48 0.0132 AGRIFOR *20.7768 11.59918 1.79 0.0733 ENVPRO **− 60.8641 30.15006 − 2.02 0.0435 Disturbance standard deviation ***157.395 3.82922 41.10 0.0000 Fit statistics Log likelihood function − 2383.01852 Inf. cr. AIC 4778.0 AIC/N 4.8451 n 985 *** Significant at the 0.01 level. ** Significant at the 0.05 level. * Significant at the 0.10 level. Table 6 Ordered probit model of socio-economic and attitudinal variables explaining the interest of forest owners in leaving a forest patch as a landscape shield. Independent variable Coefficient Std. Error z p Constant ***0.24306 0.32788 3.79 0.0001 MYSELF *0.12239 0.07149 1.71 0.0869 OMEMBER *0.16652 0.09614 1.73 0.0833 GENDER **0.17221 0.08569 2.01 0.0445 WORKING ***0.24365 0.07071 3.45 0.0006 ECONDEV ***0.15199 0.05873 2.59 0.0097 LANDUSE ***− 0.29760 0.05351 − 5.56 0.0000 WPDISAD ***− 0.36357 0.03540 − 10.27 0.0000 PUBCOMP ***0.13488 0.03446 3.91 0.0010 MANAGE ***0.23614 0.04334 5.45 0.0000 ENTREP ***− 0.27993 0.04341 − 6.45 0.0000 RECOMP ***0.21359 0.03886 5.50 0.0000 Threshold parameter ***1.44783 0.05200 27.84 0.0000 Fit statistics Log likelihood function − 1161.266 McFadden Pseudo R2 0.1623 Inf. cr. AIC 2348.5 AIC/n 1.821 n 1290 *** Significant at the 0.01 level. ** Significant at the 0.05 level. * Significant at the 0.10 level. 3 METSO is a voluntary-based program for preserving biodiversity in pri vately owned forests in Finland (Gustafsson, 2008; Mäntymaa et al., 2009). E. Mäntymaa et al. Forest Policy and Economics 124 (2021) 102382 9 environmental protection or other related areas (ENVPRO) tended to reduce the respondent’s WTA. Regarding attitudinal variables, the lower the trust in the system of land use planning (MISTRUST), or the more positive the attitude to wards the freedom of entrepreneurship (ENTREP), the larger the claim was for possible compensation for participating in an LVT initiative. On the other hand, the more possible they perceived public compensation for the landscape externalities of wind power (PUBCOMP) to be, or the more interested they were in cooperation or LVT (COOPER), the smaller their WTA was. Additionally, adding the attitudinal variables into the analysis slightly reduced the goodness of fit of the WTA model, as the value of the log likelihood function decreased from − 2382.256 in the first model to − 2424.469 in the second model and the AIC increased from 4776.5 to 4868.9. However, with respect to the number of observations, i.e., the AIC/n, the goodness of fit increased slightly with the figure decreasing from 4.849 to 4.806. 5. Discussion We investigated the supply side of the LVT mechanism as an approach to preserve the provision of landscape values with forest management methods in areas around wind energy sites. Using a data set from an online survey and by means of models including either socio- economic regressors or socio-economic and attitudinal regressors, we analyzed both forest owners’ interest in participating in LVT schemes and their willingness to accept compensation for making a contract within an LVT. We found that only 29.5% of the respondents were expressly inter ested in participating in LVT initiatives, which is quite a small per centage. However, if we add the respondents who indicated that they would possibly participate, we end up with 73.6% of the forest owners who responded to the survey. When considering launching and imple menting a PES-type instrument, this is not a small share. In fact, given that LVT is a new mechanism and has not yet been implemented, the estimated rate of interest is surprisingly high. Additionally, this is true if compared to previous results regarding participation interest in forest- related PES (Mitani and Lindhjem, 2015; Markowski-Lindsay et al., 2011; Mäntymaa et al., 2018a). One reason for the high rate of interest might be that landowners in the area are accustomed to a similar policy mechanism for biodiversity preservation, i.e., the METSO program, which was first tested in the county of Satakunta from 2003 to 2007 (Juutinen et al., 2008; Mäntymaa et al., 2009). However, to turn the majority of the “maybe” responses into “yes” responses would require interaction, careful communication and deliberation on the features of the proposed instrument with the public (see e.g., Kurttila et al., 2019). The identification of willing candidates, drawing their attention and successful recruitment are the key features of effective implementation of a PES mechanism. The results indicate that the larger was the area that the forest owners had recently cut, the smaller was the probability that they would be interested in participation. It may be reasonable to assume that a large cut area increases the income earned from forestry and consequently the importance of forestry as a livelihood (Karppinen et al., 2020). Thus, the socio-economic variable reflecting the re spondents’ dependence on forest management and forest income in dicates a smaller tendency to become interested in participating in PES initiatives. Accordingly, the result indicates that owners earning a sub stantial share of their living from forestry and actively engaging in forest management are not the most likely segment to participate in LVT schemes. This may imply that LVT is perceived as a restriction on forest management rather than an alternative way to earn from the forest. This is in line with findings that the fear of tighter restrictions on forest management in the future tends to reduce the interest of forest owners in participating in voluntary protection measures (Karppinen et al., 2020; Lindhjem and Mitani, 2012; Mäntymaa et al., 2018a). Regarding the dependency, we found additional results: the more often the respondents’ occupation was in agriculture or forestry, the less likely they were to be interested in participation, and in contrast, the higher the educational level of owners was, the more likely they were to be interested. The latter makes sense if more highly educated people less often work in forest management or are less dependent on a forestry income. Previous studies (e.g., Meyer, 2015) have also shown that more educated forest owners tend to favor more nature conservation and may be more interested in landscape protection. An occupation in forestry also means that typical forest management practices are well known, but new types of forest management related to PES create uncertainty. Our results revealed that male respondents were more often ready to join the LVT initiative than the rest of the owners. This contradicts the findings from previous literature that females usually had stronger environmental concerns and more positive preferences towards envi ronmental protection than males (e.g., Xiao and McCright, 2015; Zelezny et al., 2000). Nevertheless, there are also research results indi cating that males are more willing than females to join and demand less compensation from PES programs seeking to enhance the preservation of forest biodiversity (Lindhjem and Mitani, 2012; Mitani and Lindhjem, 2015). We also found that working respondents were more interested in joining LVT initiatives than others. It might be reasonable to consider that people working in a profession have more economic flexibility to try out new ideas than retirees and unemployed people with lower incomes. The interpretation of an additional result that having a positive attitude towards rural economic development increases the probability of being interested in LVT participation appears logical if the construction of wind turbines is regarded as part of the development. In this study, the average annual compensation request was about €298 per hectare. This is a relatively large sum of money compared with the materialized mean compensation paid (€176/ha/year) in the Finnish program for forest biodiversity conservation (METSO), in which cutting is disallowed throughout the duration of an agreement, which is usually 10 years (Juutinen et al., 2008). The request is also higher than the annual operating profit of nonindustrial private forestry4 in Satakunta Table 10 Grouped data regression model of socio-economic and attitudinal variables explaining forest owners’ WTA compensation for leaving a forest patch as a landscape shield. Independent variable Coefficient Std Error z p Constant **101.212 42.98412 2.35 0.0185 MATURE **0.68576 0.34514 1.99 0.0469 METSO **43.1374 19.98748 2.16 0.0309 WORKING ***28.8005 10.48053 2.75 0.0060 ENVPRO **− 57.8251 29.21791 − 1.98 0.0478 PUBCOMP *− 9.32862 5.07027 − 1.84 0.0658 COOPER ***− 24.7315 5.51857 − 4.48 0.0000 MISTRUST ***23.0640 6.76923 3.41 0.0007 ENTREP ***36.5290 5.77096 6.33 0.0000 Disturbance standard deviation ***154.518 3.71737 41.57 0.0000 Fit statistics Log likelihood function − 2424.469 Inf. cr. AIC 4868.9 AIC/N 4.806 n 1013 *** Significant at the 0.01 level. ** Significant at the 0.05 level. * Significant at the 0.10 level. 4 The operating profit in non-industrial private forestry is the difference be tween the earnings from and costs of non-industrial private forestry. This comprises gross stumpage earnings (calculated on the basis of the volume of felled industrial wood and energy wood, as well as wood felled for own use and standing sales prices) and state subsidies for wood production. Expenditure includes investments in private silviculture and forest improvement, as well as administrative costs and other expenses. (Luke, 2020.) E. Mäntymaa et al. Forest Policy and Economics 124 (2021) 102382 10 and Varsinais-Suomi, which fluctuated between €133 and €201 per hectare in 2015–2018 (Official Statistics of Finland, 2019). However, as Nape et al. (2003) deduced, individuals in reality seem to accept less money in compensation than in a hypothetical situation. Hence, the paid sums in real LVT initiatives are expected to be slightly smaller than those elicited here. Furthermore, in the METSO program for biodiversity conservation, forest owners were paid to provide ES for society at large. In LVT, on the other hand, forest owners provide ES for particular, probably identified and known fellow citizens. In eliciting compensation claims, forest owners were asked to keep their own property in mind. It seems that they consider the community good more valuable than the public good. The public good and beneficiaries are dispersed in society, while the community good provided by the landscape shield is concrete, and it benefits real people and fellow citizens close to the forest property. A landscape shield has real value, as it undeniably improves the living conditions of the target people. For this reason, a higher value is indi cated, paradoxically perhaps from a fellow community member point of view, in higher compensation claims than is the case for biodiversity and more abstract ES. This calls for further investigation into the moral as pects of property regimes in the face of emerging PES schemes. Related to the cost-effective implementation of a PES mechanism, identifying and recruiting those forest owners who would claim low amounts of compensation for the production of environmental services is an essential issue. Just as it was found above that low dependence on forestry and forest-related income tended to increase interest in partic ipation in LVT schemes, it also seemed to reduce the compensation claims. This is suggested by the negative coefficients of variables describing higher levels of education or having an occupation in envi ronmental protection. On the other hand, while reducing interest, the variables suggesting a higher dependence, i.e., an increase in the area of commercial cutting or having an occupation in agriculture or forestry, were associated with higher compensation claims. In addition, as in previous studies by Lindhjem and Mitani (2012) and Mäntymaa et al. (2009), we found a positive dependence between the increase in the area of mature forests owned and WTA. This is a natural result, as the op portunity cost increases as trees in a protected stand grow. Moreover, the result is important for developing LVT, because forests in an ideal landscape shield should be high and dense and the principal in LVT should be ready to pay a reasonable price for an effective shield. The analysis revealed a positive association between previous agreements on voluntary biodiversity preservation in METSO and the monetary amount of claims. A plausible explanation for this might be that based on the forest owners’ experience of the previous program, PES is a trustworthy and profitable way to earn money from forests by postponing a decision to cut down a parcel of forest for a contract period. This result shows that the previous experience has not become an ethical motivation, because the payment claim would be lower if the internal motivation had increased. What may have happened here is that this kind of economic incentive structure reinforces a particular type of economic thinking and rationale and perhaps also external, compensation-driven motivation; this is a known general characteristic of any workable institutional arrangement (cf., Hiedanpää and Borgström, 2014; Hiedanpää and Bromley, 2012; Satz and Forejohn, 1994; North, 2005). Related to the cost-effective implementation of the mechanism, a noteworthy and important result is that the more interested the re spondents were in cooperation with an LVT initiative, the smaller the amount of compensation they would claim. Thus, the non-obligatory nature of LVT reduces the costs, as the more willing landowners engaged in the instrument will claim less compensation (Mäntymaa et al., 2018a). If the marketing of LVT schemes could find and recruit the most interested owners, it would also minimize the costs of landscape protection. Several attitudinal variables associated significantly with compen sation claims. An increasingly positive attitude towards the freedom of entrepreneurship, e.g., in forest management, tended to increase the compensation claims. This result is predictable, because the direct op portunity costs and financial losses increase with management re strictions. The result confirms previous findings that those owners who perceive preservation rules as too restrictive are less likely to participate (Mitani and Lindhjem, 2015; Mäntymaa et al., 2018a; Tyrväinen et al., 2020; Vedel et al., 2015b). Regarding the perceptions of governance in landscape issues, we found that lower trust in the system of land use planning tended to in crease the compensation claims. This is in line with the results of Broch and Vedel (2012) and Vedel et al. (2015a), who found that a control instrument developed to minimize the abuse of the system, i.e., the monitoring of landowners’ behavior related to compliance with the mechanism, increased compensation level required by farmers. Land owners may be annoyed by monitoring and see it as an incursion into their private holding, considering monitoring as a signal of mistrust, for example (Vedel et al., 2015a). Low confidence in the LVT initiative as such may be a matter of risk, as distrust increases risks and risks may become costly. Finally, we found that the more often the respondents felt that public compensation for the landscape externalities of wind power was possible, the smaller the WTA was. This indicates that respondents’ increasing support for the idea of public compensation, i.e. that mu nicipalities could compensate for the disadvantages of wind power by developing non-environmental local services or by otherwise enhancing the quality of landscape, would reduce the compensation claimed. This may suggest that forest owners would be ready to substitute private monetary gains with social benefits, i.e., municipal services or other types of landscape quality. This is an interesting result, suggesting that private income (WTA) can be compensated for by municipality-supplied public goods. 6. Conclusions The main findings of this study demonstrated that almost three- quarters of respondents were certainly or possibly interested in participating in LVT to minimize the harmful landscape effects of wind turbines. Related to the socio-economic characteristics of the land owners, a low dependence on forestry and forest-related income tended to increase interest in participation in LVT schemes, and vice versa. In addition, the compensation of the effects with municipal non- environmental services or other types of environmental benefits was inclined to increase the interest, whereas a positive attitude towards land or soil use or the freedom of entrepreneurship tended to decrease it. This study revealed that the annual mean compensation for preser ving one hectare as a landscape shield was about €300, tending to in crease if the probability of interest in participating decreased, and vice versa. The modeling of compensation claims demonstrated a compara ble message to participation interest: the socio-economic characteristics that indicate a high dependence on forestry and forest-related income tended to increase the compensation claim, and vice versa. With respect to attitudes, low trust in the land use planning system and a positive attitude towards entrepreneurial freedom inclined owners to increase their compensation claim, whereas the development of municipal non- environmental services and respondents’ increasing interest in cooper ation in landscape protection tended to decrease the claim. Knowledge of the interest of landowners in participating in LVT schemes and their willingness to accept compensation for making a contract within LVT is essential for policy makers to consider when planning and applying a new PES mechanism. To create a well- functioning policy instrument, it is necessary to evaluate the charac teristics of possible participants and the incentives that encourage forest owners to participate in LVT initiatives, or that discourage them. It is equally essential to evaluate the level of requests for monetary compensation and the factors influencing the claims. In particular, it is important to identify those landowners who are willing to accept a lower E. Mäntymaa et al. Forest Policy and Economics 124 (2021) 102382 11 level of compensation to effectively target and market LVT schemes. If the organizer of LVT knows the socio-economic characteristics and at titudes that increase or decrease the probability of participation with a reasonable level of compensation, this may enhance the process and improve the cost-effectiveness in the implementation of the mechanism. From a policy relevance point of view, our outcomes can assist in the recognition of some of the most significant features of the possible supply side of LVT. These features are crucial for the successful planning and application of an upcoming payment instrument to minimize the disturbing effects of wind turbines. However, attitudinal variables that did not help in identifying the possible providers of landscape shields had a considerable role in explaining the participation and compensa tion claims. The importance of attitudes in determining the landowners’ participation and compensation decisions highlights the significance of providing information to landowners. The attitudes and beliefs of those who are opposed to LVT need to be taken into account in planning counselling campaigns, as well as consulting and information services. These could provide evidence related to those beliefs that most strongly hinder participation. There are, however, some limitations in the interpretations and applicability of the present results. First of all, because the harmful ef fects of wind turbines and compensation claims are highly localized, the general results of this study only have limited direct use in planning local solutions. Local circumstances constrain the possibilities of forest management to minimize the effects. Thus, an important challenge for LVT initiatives is to negotiate and make contracts with those owners who possess forest stands in crucial sites. If deals are not reached and if the owners wish to cut the stands, landscape shields will be lost. Consequently, these owners have a kind of monopoly at that site and can claim relatively high compensation for agreements. Thus, the results of this study can serve as background information for organizing LVT locally. Second, the general regional scope of this study ignores the impor tance of the structure of a particular forest area and opportunity costs related to LVT. If a specific parcel that is crucial for a landscape shield is mature and ready for harvesting, the forest owner’s opportunity costs of joining the program would be relatively large. As we are not, however, dealing with the total protection of large areas but the delaying of cut ting of narrow belts of forests for a fixed period, the compensation need not be excessive. Alternatively, if forest owners have just clear-cut a parcel and planted new trees, they would probably agree to participa tion and not require much compensation, since the actual opportunity costs would be very low. In this case, however, the young stand would not act as an effective landscape shield for some time and would not be interesting for a manager of LVT. Shedding light on these aspects would require more detailed data than were generated in this study, and would be an interesting topic for further research. In the practical application of LVT in a local case, however, the structure of the forest and the op portunity cost of delaying a cut is essential information and should be taken into account when making a contract and defining the level of compensation. Third, related to the plausibility and trustworthiness of the results, we cannot rule out the possibility of hypothetical bias, as the survey was based on a hypothetical situation. In non-market valuation, the bias may, however, be a more serious problem in cases focusing on non-use or existence values. Here, we assessed quite concrete use values that relate to market-based goods, i.e., future timber revenues or recreational and landscape values, which may not be so sensitive to the hypothetical nature of the valued good (Foster and Burrows, 2017). Finally, in addition to the supply side, information related to the demand for the landscape shield is also essential. The public discussion and official complaints from residents indicate the landscape harm caused by wind turbines, which provides a reason to develop the idea of LVT schemes further. In addition to minimizing the costs of LVT, it is also necessary to maximize the net benefits of the mechanism. Knowl edge of the demand is needed to ensure this. The question is whether residents are interested in participating in the PES mechanism. If they are, we should know the terms and conditions of their participation and, furthermore, their willingness to pay for minimizing the landscape ef fects of wind turbines. These questions are among the topics that should be analyzed in the future. Author statement The manuscript “Forest owners’ interest in participation and their compensation claims in voluntary landscape value trading: The case of wind power parks in Finland” or a very similar manuscript has not been published, nor is under consideration by any other journal. Declaration of Competing Interest The authors of the manuscript “Forest owners’ interest in partici pation and their compensation claims in voluntary landscape value trading: The case of wind power parks in Finland” have no conflict of interest. Acknowledgements This paper is a result of work that was supported by the Strategic Research Council at the Academy of Finland [grant numbers 312671 and 312672]. Appendix A. Appendix Table A.1 Principal components based on perceptional statements on landscape changes (Oblimin rotation with Kaiser normalization. Loadings of 0.50 or above in boldface). Principal components C1.1 C1.2 C1.3 Expansion of built-up areas. 0.830 0.005 − 0.132 Construction of traffic routes. 0.697 − 0.003 0.095 Expansion of commercial centers. 0.679 0.203 0.051 Business activities using the landscape, e.g., construction of buildings for the tourism business or private holiday living. 0.594 − 0.169 0.131 Construction of new buildings in rural areas. 0.507 − 0.433 0.048 Abandonment of villages or buildings in a poor state of repair. − 0.019 0.845 0.126 Decline of farming or abandonment of fields. 0.064 0.790 − 0.164 Forest cuttings or intensive site preparations. 0.015 − 0.002 0.827 Intensive agriculture. − 0.081 − 0.132 0.816 Soil removal. 0.129 0.147 0.721 Eigenvalue (rotation sum) 30.235 10.493 10.274 Cumulative variance explained, % 32.350 47.275 60.015 E. Mäntymaa et al. Forest Policy and Economics 124 (2021) 102382 12 Note: Interpretation of principal components: C1.1 Economic development in rural areas. C1.2 Decline of rural areas. C1.3 Land or soil use in rural areas. Table A.2 Principal components based on attitudinal statements related to the advantages and disadvantages of wind turbines (Oblimin rotation with Kaiser normalization. Loadings of 0.50 or above in boldface). Principal components C2.1 C2.2 Wind turbines disturb birds and other animals. 0.921 0.106 Wind turbines cause disturbing noise. 0.877 0.034 Wind turbines may have harmful effects on people’s health. 0.871 0.092 Wind turbines may destroy the image of a region. 0.829 − 0.066 Wind turbines decrease the value of land. 0.816 − 0.032 Wind turbines destroy the scenery. 0.813 − 0.095 Wind turbines reduce possibilities to hunt. 0.791 − 0.028 Wind turbines make farming and forestry substantially more difficult. 0.755 − 0.076 Wind turbines reduce possibilities to take outdoor exercise. 0.745 − 0.122 Wind turbines restrain climate change. 0.072 0.911 Wind turbines are an example of the technology of the future. − 0.016 0.896 Wind turbines are a good source of domestic energy. − 0.059 0.869 Wind turbines are essential for future energy production. − 0.076 0.853 Future generations will benefit from the development of wind energy. − 0.034 0.849 Wind energy is clean. 0.008 0.824 Wind turbines help people to be orientated in wild areas. 0.020 0.547 Wind turbines strengthen the uniqueness of a region. − 0.356 0.403 Eigenvalue (rotation sum) 10.209 1.585 Cumulative variance explained, % 60.05 69.38 Note: Interpretation of principal components: C2.1 Local disadvantages of wind turbines. C2.2 Advantages of wind power. Table A.3 Principal components based on attitudinal statements related to compensation for the externalities of wind turbines (Oblimin rotation with Kaiser normalization. Loadings of 0.50 or above in boldface). Principal components C3.1 C3.2 Wind turbines cause so few disadvantages that they do not need compensation. 0.846 0.168 It is wrong to grant licenses for wind power parks, as those suffering from the disadvantages are not compensated. ¡0.821 − 0.170 It is a good practice not to provide compensation for the disadvantages of wind power. 0.818 0.031 All sufferers from the disadvantages of wind turbines should be compensated. ¡0.776 − 0.015 Wind turbines should be allowed to be built more freely. 0.757 0.243 Wind turbines should be designed to fit the local conditions. ¡0.558 0.267 Wind power should only be subsidized if the disadvantages are compensated for. ¡0.511 0.364 Municipalities could compensate for the disadvantages of wind power by developing other local services. 0.037 0.845 The disadvantages of wind power could be compensated for by otherwise increasing the quality of the landscape. 0.164 0.823 Eigenvalue (rotation sum) 3.928 1.642 Cumulative variance explained, % 43.642 61.884 Note: Interpretation of principal components: C3.1 Compensation for the landscape externalities of wind turbines. C3.2 Public compensation for the landscape externalities of wind power. Table A.4 Principal components based on attitudinal statements related to perceptions of the governance of landscape issues (Oblimin rotation with Kaiser normalization. Loadings of 0.50 or above in boldface). Principal components C4.1 C4.2 C4.3 C4.4 Companies causing changes in the landscape should always compensate those suffering from the disadvantages. 0.791 0.008 0.001 0.129 The sufferers of landscape-related disadvantages should always be heard. 0.768 − 0.161 0.031 0.133 Projects that change the landscape obtain permits for their realization too easily. 0.750 − 0.058 − 0.092 − 0.025 Changes in the landscape often come as a surprise. 0.685 0.134 0.032 − 0.231 At present, the rights of landowners are too restricted. 0.040 0.863 − 0.041 0.080 Statutes related to the environment have restricted the possibilities for entrepreneurship too much. − 0.086 0.806 0.153 − 0.024 Landowners should have the right to use their forests as they wish. − 0.001 0.779 − 0.105 0.019 A change in the landscape could be compensated for with a protected area somewhere else. 0.062 − 0.006 0.901 0.009 A change in the landscape could be compensated for with a new recreational service, e.g., an outdoor recreational route, somewhere else. − 0.052 − 0.003 0.880 0.006 (continued on next page) E. Mäntymaa et al. Forest Policy and Economics 124 (2021) 102382 13 Table A.4 (continued ) Principal components C4.1 C4.2 C4.3 C4.4 I am aware of different projects changing the landscape. − 0.143 − 0.013 0.044 0.805 If possible, I always participate in the preparation of regional plans in my neighborhood. 0.159 0.096 − 0.030 0.754 Eigenvalue (rotation sum) 2.632 2.007 1.436 1.273 Cumulative variance explained, % 23.930 42.178 55.233 66.806 Note: Interpretation of principal components: C4.1 Mistrust in land use planning. C4.2 Freedom of entrepreneurship. C4.3 Recreational-ecological compensation. C4.4 Participation in local land use planning. Table A.5 Principal components based on attitudinal statements related to interest in the LVT mechanism and forest management practices (Oblimin rotation with Kaiser normalization. Loadings of 0.50 or above in boldface). Principal components C5.1 C5.2 I would be interested in providing a landscape shield if I received monetary compensation. 0.902 0.029 I am interested in discussing the provision of a landscape shield. 0.894 0.118 I am interested in discussing my forest management practices to reduce the harmful landscape effects of wind power. 0.862 0.176 I am willing to lease a part of my land to wind power companies for building wind turbines. 0.786 − 0.225 I take into account the needs of my neighbors in my forest management. 0.084 0.857 I wish to hear the views of my neighbors when I plan my forest management. 0.177 0.750 I always take into account conditions related to the landscape in my forest management. − 0.149 0.664 Eigenvalue (rotation sum) 3.275 1.653 Cumulative variance explained, % 46.792 70.400 Note: Interpretation of principal components: C5.1 Interest in cooperation and LVT. C5.2 Takes landscape values into account in forest management. References Afifi, A.A., Clark, V., 1996. Computer-Aided Multivariate Analysis, 3rd ed. Chapman & Hall, London. Ajzen, I., Fishbein, M., 1980. Understanding Attitudes and Predicting Social Behavior. Prentice-Hall, Englewood Cliffs. Aslam, U., Termansen, M., Fleskens, L., 2017. Investigating farmers’ preferences for alternative PES schemes for carbon sequestration in UK agroecosystems. Ecosyst. Services 27, 103–112. https://doi.org/10.1016/j.ecoser.2017.08.004. Bartczak, A., Budziński, W., Gołębiowska, B., 2018. Impact of Beliefs About Negative Effects of Wind Turbines on Preference Heterogeneity Regarding Renewable Energy Development in Poland. University of Warsaw, Faculty of Economic Sciences. https://doi.org/10.26405/WP/WNE/2018/278/019. Working papers 19/2018 (278). Becker, D.R., Eryilmaz, D., Klapperich, J.J., Kilgore, M.A., 2013. Social availability of residual woody biomass from nonindustrial private woodland owners in Minnesota and Wisconsin. Biomass Bioenergy 56, 82–91. https://doi.org/10.1016/j. biombioe.2013.04.031. Bergseng, E., Vatn, A., 2009. Why protection of biodiversity creates conflict – some evidence from the Nordic countries. J. For. Econ. 15, 147–165. https://doi.org/ 10.1016/j.jfe.2008.04.002. Bolkesjø, T.F., Solberg, B., Wangen, K.R., 2007. Heterogeneity in nonindustrial private roundwood supply: lessons from a large panel of forest owners. J. Forest Econ. 13 (1), 7–28. https://doi.org/10.1016/j.jfe.2006.08.003. Bonnichsen, O., Ladenburg, J., 2015. Reducing status quo bias in choice experiments. Nordic J. Health Econ. 3, 47–67. https://doi.org/10.5617/njhe.645. Boon, T.E., Meilby, H., Thorsen, B.J., 2004. An empirically based typology of private forest owners in Denmark: improving communication between authorities and owners. Scand. J. For. Res. 19, 45–55. https://doi.org/10.1080/ 14004080410034056. Boon, T.E., Broch, S.W., Meilby, H., 2010. How financial compensation changes forest owners’ willingness to set aside productive forest areas for nature conservation in Denmark. Scand. J. For. Res. 25, 565–573. https://doi.org/10.1080/ 02827581.2010.512875. Broch, S.W., Vedel, S.E., 2012. Using choice experiments to investigate the policy relevance of heterogeneity in farmer Agri-environmental contract preferences. Environ. Resour. Econ. 51, 561–581. https://doi.org/10.1007/s10640-011-9512-8. Butler, B.J., Tyrrell, M., Feinberg, G., VanManen, S., Wiseman, L., Wallinger, S., 2007. Understanding and reaching family forest owners: lessons from social marketing research. J. For. 105, 348–357. https://doi.org/10.1093/jof/105.7.348. Christensen, T., Pedersen, A.B., Nielsen, H.O., Mørkbak, M.R., Hasler, B., Denver, S., 2011. Determinants of farmers’ willingness to participate in subsidy schemes for pesticide-free buffer zones—a choice experiment study. Ecol. Econ. 70, 1558–1564. https://doi.org/10.1016/j.ecolecon.2011.03.021. de Young, R., 2000. New ways to promote Proenvironmental behavior: expanding and evaluating motives for environmentally responsible behavior. J. Soc. Issues 56, 509–526. https://doi.org/10.1111/0022-4537.00181. Defrancesco, E., Gatto, P., Runge, F., Trestini, S., 2008. Factors affecting Farmers’ participation in Agri-environmental measures: a northern Italian perspective. J. Agric. Econ. 59, 114–131. https://doi.org/10.1111/j.1477-9552.2007.00134.x. Dimitropoulos, A., Kontoleon, A., 2009. Assessing the determinants of local acceptability of wind-farm investment: a choice experiment in the Greek Aegean Islands. Energy Policy 37, 1842–1854. https://doi.org/10.1016/j.enpol.2009.01.002. Drechsler, M., Ohl, C., Meyerhoff, J., Eichhorn, M., Monsees, J., 2011. Combining spatial modeling and choice experiments for the optimal spatial allocation of wind turbines. Energy Policy 39, 3845–3854. https://doi.org/10.1016/j.enpol.2011.04.015. Emtage, N., Herbohn, J., 2012. Implications of landowners’ management goals, use of information and thrust of others for the adoption of recommended practices in the wet tropics region of Australia. Landsc. Urban Plan. 107, 351–360. https://doi.org/ 10.1016/j.landurbplan.2012.07.003. Espinosa-Goded, M., Barreiro-Hurlé, J., Ruto, E., 2010. What do farmers want from Agri- environmental scheme design? A choice experiment approach. J. Agric. Econ. 61, 259–273. https://doi.org/10.1111/j.1477-9552.2010.00244.x. Finley, A.O., Kittredge, D.B., Muir, T., Doe, J., 2006. Different types of private forest owners need different kinds of forest management. North. J. Appl. For. 23, 27–34. https://doi.org/10.1093/njaf/23.1.27. Foster, H., Burrows, J., 2017. Hypothetical bias: A new meta-analysis. In: McFadden, D., Train, K. (Eds.), Contingent Valuation of Environmental Goods - a Comprehensive Critique. Edward Elgar Publishing Inc., Cheltenham & Northampton, pp. 270–291. https://doi.org/10.4337/9781786434692.00016. Gadaud, J., Rambonilaza, M., 2010. Amenity values and payment schemes for free recreation services from non-industrial private forest properties: a French case study. J. For. Econ. 16, 297–311. https://doi.org/10.1016/j.jfe.2010.05.001. Gordon, L.J., Finlayson, C.M., Falkenmark, M., 2010. Managing water in agriculture for food production and other ecosystem services. Agric. Water Manag. 97, 512–519. https://doi.org/10.1016/j.agwat.2009.03.017. Grammatikopoulou, I., Pouta, E., Iho, A., 2012. Willingness of farmers to participate in agri-environmental auctions in Finland. Food Econ. 9 (4), 215–230. https://doi.org/ 10.1080/2164828X.2013.845557. Groothuis, P.A., Groothuis, J.D., Whitehead, J.C., 2008. Green vs. green: measuring the compensation required to site electrical generation windmills in a viewshed. Energy Policy 36, 1545–1550. https://doi.org/10.1016/j.enpol.2008.01.018. Gundersen, V., Frivold, L., 2008. Public preferences for forest structures: a review of quantitative surveys from Finland, Norway and Sweden. Urban For. Urban Green. 7, 241–258. https://doi.org/10.1016/j.ufug.2008.05.001. E. Mäntymaa et al. http://refhub.elsevier.com/S1389-9341(20)30708-5/rf0005 http://refhub.elsevier.com/S1389-9341(20)30708-5/rf0005 http://refhub.elsevier.com/S1389-9341(20)30708-5/rf0010 http://refhub.elsevier.com/S1389-9341(20)30708-5/rf0010 https://doi.org/10.1016/j.ecoser.2017.08.004 https://doi.org/10.26405/WP/WNE/2018/278/019 https://doi.org/10.1016/j.biombioe.2013.04.031 https://doi.org/10.1016/j.biombioe.2013.04.031 https://doi.org/10.1016/j.jfe.2008.04.002 https://doi.org/10.1016/j.jfe.2008.04.002 https://doi.org/10.1016/j.jfe.2006.08.003 https://doi.org/10.5617/njhe.645 https://doi.org/10.1080/14004080410034056 https://doi.org/10.1080/14004080410034056 https://doi.org/10.1080/02827581.2010.512875 https://doi.org/10.1080/02827581.2010.512875 https://doi.org/10.1007/s10640-011-9512-8 https://doi.org/10.1093/jof/105.7.348 https://doi.org/10.1016/j.ecolecon.2011.03.021 https://doi.org/10.1111/0022-4537.00181 https://doi.org/10.1111/j.1477-9552.2007.00134.x https://doi.org/10.1016/j.enpol.2009.01.002 https://doi.org/10.1016/j.enpol.2011.04.015 https://doi.org/10.1016/j.landurbplan.2012.07.003 https://doi.org/10.1016/j.landurbplan.2012.07.003 https://doi.org/10.1111/j.1477-9552.2010.00244.x https://doi.org/10.1093/njaf/23.1.27 https://doi.org/10.4337/9781786434692.00016 https://doi.org/10.1016/j.jfe.2010.05.001 https://doi.org/10.1016/j.agwat.2009.03.017 https://doi.org/10.1080/2164828X.2013.845557 https://doi.org/10.1080/2164828X.2013.845557 https://doi.org/10.1016/j.enpol.2008.01.018 https://doi.org/10.1016/j.ufug.2008.05.001 Forest Policy and Economics 124 (2021) 102382 14 Gustafsson, L., 2008. Luonnonarvokaupan kokeiluhanke 2003–2007. Metsäkeskus Lounais-Suomi, Tuloksia ja ajatuksia jatkosta. Hänninen, H., Karppinen, H., Leppänen, J., 2011. Finnish forest owner 2010. (Suomalainen metsänomistaja 2010). In: Finnish Working Papers of the Finnish Forest Research Institute 208, p. 94. http://www.metla.fi/julkaisut/workingpapers/ 2011/mwp208.htm (Accessed 4 October 2019). Heckman, J.J., 1979. Sample selection bias as a specification error. Econometrica 47, 153–161. https://www.jstor.org/stable/1912352. Hiedanpää, J., Borgström, S., 2014. Why do some institutional arrangements succeed? Voluntary protection of forest biodiversity in southwestern Finland and of the Golden eagle in Finnish Lapland. Nat. Conserv. 7, 29–50. https://doi.org/10.3897/ natureconservation.7.6497. Hiedanpää, J., Bromley, D.W., 2012. Contestations over biodiversity protection: considering Peircean semiosis. Environ. Values 21, 357–378. https://doi.org/ 10.3197/096327112X13400390126091. Horne, P., 2006. Forest owners’ acceptance of incentive based policy instruments in forest biodiversity conservation – A choice experiment based approach. Silva Fennica 40, 169–178. https://doi.org/10.22004/ag.econ.59365. Horowitz, J.K., McConnell, K.E., 2002. A review of WTA/WTP studies. J. Environ. Econ. Manag. 44, 426–447. https://doi.org/10.1006/jeem.2001.1215. Huttunen, R., 2017. Valtioneuvoston selonteko kansallisesta energia- ja ilmastostrategiasta vuoteen 2030 (government report on the National Energy and climate strategy for 2030, in Finnish) publications of the Ministry of Economic Affairs and employment of Finland 4/2017, p. 119. ISBN (printed) 978-952-327- 189-0, ISBN (PDF) 978-952-327-190-6. http://urn.fi/URN:ISBN:978-952-327-190-6 (Accessed 17 December 2019). Ingemarson, F., Lindhagen, A., Eriksson, L., 2006. A typology of small-scale private forest owners in Sweden. Scandinavian J. Forest Resour. 21, 249–259. https://doi.org/ 10.1080/02827580600662256. Jongeneel, A.R., Polman, B.P.N., Slangen, H.G.L., 2008. Why are Dutch farmers going multifunctional? Land Use Policy 25, 81–94. https://doi.org/10.1016/j. landusepol.2007.03.001. Juutinen, A., Mäntymaa, E., Mönkkönen, M., Svento, R., 2008. Voluntary agreements in protecting privately owned forests in Finland – to buy or to lease? Forest Policy Econ. 10, 230–239. https://doi.org/10.1016/j.forpol.2007.10.005. Kahneman, D., Knetsch, J.L., Thaler, R.H., 1991. Anomalies: the endowment effect, loss aversion, and status quo bias. J. Econ. Perspect. 5, 193–206. https://doi.org/ 10.1257/jep.5.1