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Rinnakkaistallenteet Luonnontieteiden ja metsätieteiden tiedekunta
2019
Application of multi criteria analysis methods for a participatory
assessment of non-wood forest
products in two European case studies
Huber, P
Elsevier BV
Tieteelliset aikakauslehtiartikkelit
© Elsevier B.V.
CC BY-NC-ND https://creativecommons.org/licenses/by-nc-nd/4.0/
http://dx.doi.org/10.1016/j.forpol.2017.07.003
https://erepo.uef.fi/handle/123456789/7592
Downloaded from University of Eastern Finland's eRepository
of non-wood forest products in two European case studies
*Huber P.a,b, Hujala T.c, Kurttila M.c, Wolfslehner B.a,b, Vacik H.a
a University of Natural Resources and Life Sciences Vienna (BOKU), Peter Jordanstr. 82, A-1190 Vienna, Austria. bernhard.wolfslehner@efi.int, harald.vacik@boku.ac.at
b European Forest Institute Central-East and South-East European Regional Office (EFICEEC EFISEE), Feistmantelstr. 4, A-1180 Vienna, Austria.
c Natural Resources Institute Finland (Luke), Bio-based Business and Industry, Viikinkaari 4, FI 00790 Helsinki. teppo.hujala@luke.fi, mikko.kurttila@luke.fi
* Corresponding author: patrick.huber@boku.ac.at
Abstract
With the advent of the European bioeconomy and a shift in in lifestyle among European citizens, non-wood forest products (NWFPs) are given more attention in the public debate. Their potential to strengthen the economic viability of rural economies appears to be high, particularly in regions where wood is not the most profitable forest product. However, information on NWFP production potentials are scarce and tools to support forest owners in decision making about NWFP management are rarely available. Considering the complex relationships between a sustained production of NWFPs, the use of the available ecological
resources, as well as the organizational and the market potential of forest management regimes, we introduce a knowledge-based expert model for supporting NWFP management. In a mixed-method approach
qualitative and quantitative techniques are combined to depict regional production and business potentials of NWFPs, explicitly addressing different environmental and socio-economic contexts. For the model building multi-criteria analysis methods were used for preference elicitations in an iterative form, including
stakeholders and experts. Within two distinct case study settings (i.e. Austria and Finland) the expert model is tested for applicability and to depict the most suitable option from a suite of selected NWFPs. Results for both case studies well reflect current NWFP business potentials and provide insights to the opportunities of mixing more resilient and more risky NWFPs to a solid regional business portfolio, fostering the co-
production of wood and non-wood resources. The approach presented has a potential to steer the mindset of different forest owner types to critically revise their interests in forest management. It could act as an eye- opener for forestry-oriented stakeholders who have not yet considered NWFPs as potential assets in forest management systems. With its ability to include various NWFPs and to consider different forest owner preferences, future applications can be tailored towards the needs of both smallscale (non-industrial) forest owners and bigger forest holdings.
Keywords: non-timber forest products; decision support; expert model; small scale forestry
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Application of Multi Criteria Analysis Methods for a participatory
2
assessment of non-wood forest products in two European case studies
3 1. Introduction
4 While Non-Wood Forest Products (NWFPs) constitute a fundamental resource for sustaining livelihoods 5 in several parts of the world, e.g. as a source of food for personal consumption, for medicinal purposes 6 or as goods to be marketed for economic benefits (Stanley et al. 2012; Chukwuone and Okeke, 2012;
7 Huber et al. 2010), they are still seen of minor relevance in European forestry (Wolfslehner et al. 2014).
8 NWFPs are defined in this context as products of biological origin other than wood derived from forests, 9 other wooded land and trees outside forests (FAO, 1999). According to recent international policy 10 developments in the light of circular and bio-economies as well as changes in people´s life styles, public 11 awareness towards non-wood goods and related services is being reinvigorated due to an array of 12 opportunities around the multiplicity of resources available and a huge portfolio of potential end- 13 products that can be derived from them (Wolfslehner et al. 2014). Thus, the interest in NWFPs is 14 growing throughout Europe (Ludvig et al. 2016a; Schulp et al. 2014; Keca et al. 2013; Voces et al.
15 2012) and forest owners’ motivation to engage in related businesses is gaining momentum (Weiss et al.
16 2011; Rametsteiner et al. 2005).
17 NWFPs are therefore assumed to have the potential to play a more important role in rural development, 18 generating socio-economic benefits to a range of actors along the entire value-chain spanning from the 19 forest owner to the retailer who sells a product as a service to the final customer (Bonet et al. 2014;
20 Stryamets et al. 2012). Although the institutional framework regarding the production, harvesting and 21 marketing of NWFPs is heterogeneous among European countries (Wolfslehner et al. 2014; Prokofieva 22 and Gorriz, 2013) and despite the fact that available data are still scarce (Baycheva-Merger and 23 Wolfslehner, 2016; European Forest Institute, 2013), the market value of NWFPs was reported to reach 24 almost 2.28 billion € in the latest State of Europe´s Forests report (Forest Europe, 2015). Hence there 25 seems to be high latent potential to strengthen the economic viability of actors across the NWFP supply 2
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26 chain (Cai et al. 2011), providing additional income also to forest owners who are willing to invest in the 27 joint management of wood and non-wood forest resources (de Miguel et al. 2014).
28 Given the socio-economic relevance, particularly in regions where more is demanded from forests and 29 particularly where wood is not dominantly the most profitable forest product, the need for information 30 and tools to support forest owners in sound decision making targeting at the co-production of wood and 31 non-wood forest resources is increasing (Turtiainen et al. 2013; Martínez-Peña et al. 2012; Calama et al.
32 2011; Bonet et al. 2008; Sanchéz-González et al. 2007). Since forest management planning methods 33 have been traditionally tailored towards wood and wood products, and most forest management models 34 as well as silvicultural techniques were designed to ensure a sustained production of timber, there is thus 35 far only a limited number of NWFPs covered e.g. by the existing models (Calama et al. 2010).
36 Furthermore, empirical data providing a comprehensive coverage of NWFPs yield phenomena are 37 scarce and thus particularly problematic for the development of statistical models. Partly this explains 38 the current situation in which silvicultural guidelines on how to manage forests for different NWFPs are 39 largely missing (Sheppard et al. 2016). However, the complex causal relationships between the 40 sustained production of NWFPs, the available ecological resources, as well as the organizational and the 41 market potential of forest management regimes are well suited for quantification with knowledge-based 42 expert models (Turtiainen et al. 2009).
43 In order to identify the regional production and business potentials of NWFPs, explicitly addressing 44 different environmental and socio-economic contexts, this study aims to develop a model that is 45 applicable under different regions and conditions (e.g. socio-economic, ecological) across Europe. The 46 application aims to support forest owners in the sustainable management of their natural resources, 47 fostering co-production of wood and NWFP. It is tailored towards the use for extension service 48 providers who give advice to forest and landowners as well as for regional to national policy makers 49 who might transfer findings to new governance mechanisms targeting at business development and 50 innovation support for regional development. It was developed in a series of iterative steps including 51 expert consultation and stakeholder involvement. As a result, an indicator framework was defined to 52 depict the most promising NWFPs from a larger suite of selected products. In this article, the activities 61
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53 and processes of the core development of the model as well as the interaction with the regional 54 stakeholders and involved experts are described. We will also discuss the applicability of the generated 55 decision support model with regard to regional case studies in Austria and Finland. Conclusions on the 56 findings are drawn towards forestry extension service providers with the aim to support forest owners in 57 the sustainable management of their entire portfolio of forest resources.
58 2. Methods
59 2.1 Modelling framework
60 To generate a regionally explicit ranking of a set of selected NWFPs, several multi criteria analysis 61 (MCA) methods were applied. Before application of the methods, a modelling structure that allows 62 for expert-based assessments of NWFPs was created. The model is able to take into account the 63 specific environmental and socio-economic conditions in different regions in Europe and the varying 64 forest owner preferences (Huber et al. 2015).
65 The model was compiled iteratively including a) an initial two-day workshop of a core development 66 group of researchers (authors), b) subsequent expert and stakeholder consultation, and c) repeated 67 review and adaptation processes dedicated to the final definition of underlying rationales for the 68 model’s criteria and sub-criteria. For the decomposition of the decision problem (Figure 1) a cognitive 69 mapping approach was applied to list relevant criteria and their relationships and to design a basic 70 decision hierarchy structure to which the MCA methods can be applied. MCA methods have been 71 widely used in decision making, planning and resource allocation as well as in conflict resolution 72 (Kajanus et al. 2012; Mendoza and Martins, 2006) and they typically allow for systematic evaluation 73 of both qualitative and quantitative criteria or alternatives by means of method-specific comparison 74 techniques which are modified to be suitable for addressing different kinds of complex decision 75 situations (e.g. Kangas et al. 2015; Wolfslehner et al. 2005).
76 In the proposed model, the upper level of the hierarchy is decomposed into four main criteria a) 77 Market potential, b) Institutional potential, c) Requirements, and d) Resource potential. “Market 78 potential” synthesizes the current existing opportunities of a distinct NWFP to bring it to local, 120
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79 regional, national, or international markets. “Institutional potential” depicts the chances with regard to 80 a single NWFP in utilising supportive structures and organisations. While “Requirements” highlight 81 necessities for NWFP production and harvesting, “Resource potential” gives an estimate of the 82 potential to successfully produce and/or harvest a single NWFP. The lower level of the hierarchy (i.e.
83 Sub-Criteria) is used to further decompose the higher-level criteria and aims to specifically address 84 the perceptions and interests of a single forest owner/manager in producing, harvesting and selling 85 NWFPs (see Table 1).
179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236
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87 Figure 1: Hierarchy of the decision problem structured info goal (white box), criteria (light-grey boxes) and sub-criteria (dark-grey boxes)
88 Table 1: Description of the criteria and sub-criteria (italics) applied for the MCA evaluation of NWFP alternatives
(Sub-)Criterion Rationale Preference1
Market potential indicates the current market potential of a distinct NWFP and synthesizes the current existing opportunities to bring it to local, regional, national, or international [European] markets.
+
Competitiveness* expresses how competitive a single NWFP (i.e. the raw material, not the potential end products) is compared to other products, i.e. substitutes (e.g. organic tannins vs. fossil fuel based ones), derivates (e.g. wild berries vs. cultivated berries) , other products in the same category (e.g. wild fruits vs. fruits in general)
+ 238
239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276
6 Current end
product diversity
reflects the portfolio of final products that can be derived from a single NWFP (e.g. berries can be marketed raw or processed [e.g. dried, powder, jam, mash, liquor,…])
+
Current end product value*
assesses the range of value added for a single NWFP (e.g. berries sold raw on local markets á € 10/kg and berries sold as distilled liquid for € 70/litre ), i.e. the highest price that can be achieved for a distinct end product derived out of a NWFP taking into account its market share on national markets (e.g. high price but low market share would be less preferable than lower price but high market share)
+
Low resource input for end product value
considers the raw material input required to generate the respective end product value and mirrors raw material efficiency (i.e. how much of the resource is needed in order to produce a certain output) - it thus relates to the end product assessed under criterion “Current end product value” (e.g. berries sold as distilled liquid = around 40 %, berries sold as powder = 100 %)
-
Institutional potential
depicts the chances with regard to a single NWFP in utilising supportive structures and organisations +
Future innovation potential
focuses on the future innovation potential (i.e. within the next 10 years) for production and/or harvesting processes taking into account the current state of knowledge (e.g. new machinery to harvest mushrooms – is it realistic to be implemented within the next 10 years?; cultivation of wild mushrooms – is it realistic to produce Chanterelles on straw within the next 10 years?)
+ 279
280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317
7 Supporting
policy instruments*
pinpoints existing economic policy instruments that support the production/harvesting of NWFP, like subsidies, taxes, incentives,.. (e.g. LEADER supports projects that foster regional development and was used to create NWFP businesses;
tax exemption for NWFP pickers)
+
Potential for cooperation
estimates the current potential to cooperate with other actors in the same field (e.g. association of Christmas tree producers provides support for its members)
+
Requirements highlights necessities for NWFP production and harvesting -
Time needed for production
indicates how time consuming the production of a single NWFP may be (e.g. artificial introduction and thus planting, tending,…) – also taking into account the rotation period (i.e. how long it takes to harvest the NWFP for the first time) initiating the production from bare land (but: assuming it was forest land before)
-
Time needed for harvesting
mirrors the time needed to harvest a single NWFP in relation to the yield/working hrs and only considers the harvesting process (e.g. manually harvest mushrooms/berries, harvest machinery for wild fruits, shoot game)
-
Resources (needed investments)
depicts how much resources would be needed for the management (i.e. production and harvesting as outlined above) of a single NWFP (e.g. mushrooms = knife, basket; game = hunting license, weapon, munitions, night vision device/binocular, car,…;honey= beehive, beekeeper´s equipment, honey separator), assuming to start from scratch (everything has to be purchased)
- 320
321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358
8 Required skills /
know-how
estimates the level of knowledge necessary to successfully produce/harvest a single NWFP (e.g. mushrooms = how to sustainably harvest them; game = legal framework, hunting exam, species dependent know-how,…)
-
Resource potential
gives an estimate on the potential to successfully produce and/or harvest a single NWFP +
Low level of threats
relates to biotic and/or abiotic risks with regard to a single NWFP (e.g. chestnut = chestnut blight, gall wasp,..; honey = varroa mite, pesticides/insecticides,...)
-
Exclusion potential
indicates the potential to exclude others (i.e. the general public) from production/harvesting of a single NWFP and thus relates to access , harvest and property rights (e.g. berries are a common good in FI and can be harvested by everybody;
berries in AT may be picked for personal use but the owner has the right to exclude the general public from picking
+
Uniqueness refers to the uniqueness of a single NWFP and mirrors ecological aspects (e.g. endemic species -> how unique is the regional availability/existence of the resource compared to the national availability/existence)
+
Quantity reflects how much of a single NWFP can be produced within one production cycle on a defined spatial scale (i.e. within the region under consideration) and relates to the regional potential of a single NWFP (e.g. the potential to produce bilberry in N-Karelia is quite high – the potential for birch sap even higher); assessing the (practical) realisable potential
+
89 *...assessment on European level
90 1...”+” indicates “the higher the better”; “-“ indicates “the lower the better”
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91 To identify the relative priorities for both the criteria and sub-criteria, two options for comparative 92 judgments were defined. The preferences of the main criteria are specific to the region, i.e. the weight 93 for each criterion was derived in strong collaboration with experts who are actively engaged in NWFP 94 management in their area. The preferences of the sub-criteria were defined by a set of individual 95 forest owner profiles to mirror diverging interests of various forest owner types. The model 96 development process and needs for model implementation in diverse environmental and socio- 97 economic settings are highlighted in Figure 2.
98
99 Figure 2: Overview of the model development process highlighting activities (in diamonds) and results (in squares), indicating the
100 modelling structure (A) and tasks for case study validation (B)
101 2.2 Case study validation
102 With the objective to derive at a consensual agreement on the relative importance of the criteria (i.e.
103 Market potential, Institutional potential, Requirements, Resource potential) for the case study regions, 104 and to mirror potential regional divergence of NWFPs´ markets, stakeholder interaction was a 402
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105 prerequisite. In order to elicit preference ratings for the criteria, selected regional stakeholders (Table 106 3) who are actively involved in NWFP management (both business and governance) were invited to 107 contribute to the development of a regionally explicit weighting scenario. Two different methods were 108 defined and, each of them applied within one of the case studies to verify the feasibility and reliability 109 as substitutable approaches, tested as a basis for replication in similar case study settings: i) 110 stakeholder workshop, ii) Delphi approach (Linstone and Turoff, 1975; Brooks, 1979). While the 111 former built on a Simple Multi-Attribute Rating Technique (SMART) exercise (Edwards and Barron, 112 1994; Pezdevsek Malovrh et al. 2016) to elicit preference ratings within one stakeholder meeting, the 113 latter was prepared as two-stage electronic survey among stakeholders involved and allowed for 114 adaptation after the first round of judgements, following the Delphi method routine. Also in the latter 115 approach SMART was applied to elicit the preferences of the stakeholders.
116 To represent the interests of different forest owners, four generic forest owner types were developed.
117 On a rural-urban-continuum of lifestyles (Hujala et al. 2009; Hogl et al. 2005), four relevant profiles 118 could be identified and used to define the individual priorities for the sub-criteria. The profiles take 119 primarily into account the owner’s potential interest, know-how, financial assets and time available to 120 the required NWFP-related business activities on their holding. The owner types and underlying 121 rationales are listed in Table 2 in more detail.
122 Table 2: Description of forest owner types used in the lower level of the hierarchy
Forest owner type ID Description
Hands-on nurturer FO 1 Full-time (more) agricultural type of active NWFP producer who is capable and willing for self-active work, living close to the
farm/forest
Part-time outsourcer FO 2 Part-time (less) agricultural type of active NWFP producer, who is capable and willing for self-active work but has to outsource various tasks due to a lack of time, living close to the farm/forest
461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518
11 Urban value
extractor with rural background
FO 3 NWFP harvester who is motivated to make active use of opportunities and has some connection to the forest (e.g. agricultural/forestry education, aims to increase the benefits of the family forest holding although living in a city), living in quite some distance to the
farm/forest hence rarely able to actively work in/manage the forest but willing to do so, less capital available
Urban value extractor without connection to agriculture/forestry
FO 4 NWFP harvester who is motivated to make active use of opportunities, without practical knowledge but high interest in economic benefits, outsourcing all tasks/ not willing to actively work in the forest, more financial power
123 For these owner types, different weightings (FO 1 – 4) as regards the lower level of the hierarchy 124 were defined in a Delphi-like approach within the core development team (i.e. an iterative, multistep 125 group communication process was used to find consensus on the individual preferences) so that they 126 form a set of forest owner profiles (Figure 3). According to the region´s forest ownership structure, 127 each of those profiles can be applied individually. However, the weightings for the sub-criteria remain 128 unchanged for a single profile.
129 To identify the most promising NWFPs for a given region we defined a framework including the 130 spatial dimension (i.e. case study region and boundaries) and the selection of relevant species (i.e.
131 NWFPs to be assessed), in close collaboration with regional domain experts (i.e. expert 132 consultation). Four relevant NWFP categories, i.e. i) mushrooms and truffles, ii) understory plants, 133 iii) tree products, and iv), animal origin were considered, each were to be represented by at least one 134 single evaluated species. This allowed a wide representation of different NWFPs within a region and 135 supported an in-depth analysis of the performance of the four NWFP categories.
136 In the final step, nominated experts (i.e. a single individual or a group of experts; Table 3) evaluated 137 the set of NWFPs under each sub-criterion on a 9-point rating scale by means of pairwise 138 comparisons applied in the Analytic Hierarchy Process (AHP) method, an indicator-based MCA 520
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139 method that supports collaborative decision making based on the values and judgements of 140 individuals (Saaty, 1990). The method generates local priorities that are then synthesized and result in 141 a global priority vector (i.e. performances). Final results provide a cardinal ranking of alternatives 142 including their relative priorities. In case that quantitative information from existing literature was 143 available, the data were used as input for the pairwise comparisons. We used Expert Choice Desktop 144 (v. 11.5.1683) to conduct the comparative judgments and calculate the final results.
145 Table 3: Quantity and quality of stakeholders and experts involved including the method applied per case study
Stakeholder interaction Case study
Method Stakeholders involved
Expert consultation
Austria Workshop 1 Forest owner
1 Forest owner interest group representative 1 Provincial forest authority representative 1 NWFP association representative 1 NWFP entrepreneur
2 Senior researchers 1 Junior researcher
Finland Delphi 1 Forest owner 1 NWFP entrepreneur 1 NWFP yield expert
1 Provincial land-use authority representative 1 Provincial forest policy group representative
2 Senior researchers 2 Junior researchers
146
147 2.3 Case studies
148 The two case studies in Austria and Finland were used to test the applicability of the generated model 149 with regard to the specific regional contexts.
150 For Austria the second largest province out of nine federal states was chosen (i.e. Styria). Austria is a 151 predominantly alpine Central European country with an area size of 83 871 km² situated in the Central 152 European climatic zone (moderate, humid). The case study region Styria has an area size of 16 401 579
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153 km², is situated in the south-eastern region of the country and influenced by illyric, pannonian and 154 sub-alpine climate. Around 61% of the territory is forested, totalling some 1 million ha of forest land 155 (i.e. ~ ¼ of the total forest area in Austria). The share of conifers is around 70 %, with Norway spruce 156 (Picea Abies L.) as the dominant tree species. In 2010 the number of forest holdings in Styria, which 157 is continuously decreasing since the end of the 1990s, was around 39 000 providing employment for 158 nearly 96 000 people (Statistics Styria, 2013). More than half of the forests in Styria are properties of 159 small-scale forest owners (< 200 ha), mostly comprising a low degree of mechanisation and 160 silvicultural know-how. As Styria is mainly dominated by mountain forests, various ecosystem 161 services have to be balanced simultaneously (e.g. producing timber, protecting infrastructure and 162 settlements from gravitational hazards such as avalanches, mud flow and water torrents, preventing 163 fragile mountain sites from soil erosion, providing sustained yield of high quality water resources).
164 NWFPs are usually perceived as by-products of forestry production systems. Timber production is the 165 main production goal of forest enterprises and has helped to develop a strong timber industry.
166 However, there are management approaches known that address a range of products (Vacik et al.
167 2008): i) fodder trees to improve habitat for deer, ii) silvo-pastoral practices (e.g. larch meadows), iii) 168 pruning and tending of highly valuable multi-purpose trees (e.g. cherry, walnut, chestnut), iv) 169 protection forests for gene conservation (e.g. yew) and v) plantations for Christmas tree and for 170 chestnut production.
171 From Finland, which mainly represents the boreal ecological zone in northern Europe, North Karelia 172 from eastern Finland was chosen as the case study region. North Karelia has a total area of 21 584 173 km2, including 3 821 km2 inland water areas. Most of the land area is forestry land (e.g. forest land, 174 poorly productive forest land, unproductive land, forest roads, depots, etc.) accounting for 15 890 175 km2. Private non-industrial forest ownership (i.e. family forests) dominates the landscape, which is 176 moderately hilly with altitudinal range of some 75 to 345 metres above the sea level. In addition to 177 families, companies (mainly forest industry related) and the state own good shares of the region’s 178 forests. The typical tree species are the same as in the whole of Finland, namely Scots pine (Pinus 179 sylvestris L.), Norway spruce (Picea abies L.) and birches (Betula pendula and Betula pubescens).
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180 Most forests are actively managed, with the main aim being timber production. Forest management 181 follows the principles of even-aged management, although also uneven-aged forest management is 182 possible if owners aim for such approaches. Despite the strong position of timber production, the use 183 of forests in North Karelia is diverse. In addition to roundwood cuttings which e.g. in 2013 summed 184 up to 5.5 million m3, the region’s forests are actively used for berry and mushroom picking, hunting 185 as well as various other recreational activities, including hiking, cross-country skiing, trail cycling and 186 running.
187 The following NWFPs were selected for the examination in the two case study regions by involved 188 experts based on the current state of research on the relevance of NWFPs and regional to international 189 market activities for related products (Table 4).
190 Table 4: NWFPs investigated in the case studies according to the four categories defined (incl. scientific name of the
191 resource)
Category N-Karelia Styria
Mushrooms & truffles Cep (Boletus edulis) Chanterelles (Cantharellus cibarius) Cep (Boletus edulis)
Understorey plants Bilberry (Vaccinium myrtillus) Bilberry (Vaccinium myrtillus) Wild garlic (Allium ursinum) Tree products Birch sap (Betula pendula)
Pakuri mushroom (Inonotus obliquus)
Christmas tree (Abies nordmanniana) Larch resin (Larix decidua)
Animal origin Honey (Apis mellifera) Game meat (Cervus elaphus) Honey (Apis mellifera) 192
193 3. Results 697
698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754
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194 Building on the stakeholder interaction processes, the weights for the criteria (i.e. upper level 195 hierarchy of the model) could be defined in a participatory manner (Table 5). They give indication on 196 the relative importance of a single criterion within a distinct case study and allow for comparison with 197 other case studies. “Resource potential” is perceived as highly relevant in both regions (0.30; 0.33).
198 While Styrian stakeholders valued “Market potential” as utterly important (0.35), assigning lower 199 weights to “Requirements” (0.275) and “Institutional potential” (0.075), in N-Karelia the preferences 200 for individual criteria are rather uniformly distributed (0.23; 0.21; 0.23).
201 Table 5: Weights for upper-level criteria for the two case study regions
Criteria Styria N-Karelia
Market potential 0.35 0.23
Institutional potential 0.075 0.21
Requirements 0.275 0.23
Resource potential 0.30 0.33
202
203 Originating from the Delphi exercise on the forest owner profiles regarding individual preferences 204 towards the importance of the sub-criteria, Figure 3 highlights the four different weighting scenarios 205 for the four forest owner types (FO 1 – 4).
206 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813
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207 Figure 3: Spider diagram for forest owner profiles and related preferences towards sub-criteria (5=very high, 4=high, 3=medium,
208 2=low, 1=very low).
209 The most diverging interests can be recognized for “Time needed for production” (i.e. range of 1-5, 210 divergence = 4) and “Required know-how/skills” (i.e. range of 1-5, divergence = 4). Whereas 211 “Exclusion potential” is assumed to be equally relevant to all owner types (i.e. value = 5, divergence = 212 0), the relative importance of all other sub-criteria differs to a certain extent (i.e. in the range of 2-5, 213 divergence ranges between 1 and 3).
214 According to the different weightings applied for the four owner profiles, a regional and an equal 215 scenario, Table 6 indicates the final results for NWFP alternatives that synthesize both, the AHP 216 routine including pairwise comparisons and the regional weightings originating from the Delphi or the 217 workshop respectively (i.e. global priorities and ranks). While “equal” assumes that all criteria and 218 sub-criteria are similarly relevant and depicts the baseline scenario of the model, “regional” integrates
219 the relative priorities for criteria.
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17 220
221 Table 6: Global priorities and rankings for NWFP alternatives regarding different weighting scenarios per region
Priorities Ranks
Case study
Alternative
FO 1 FO 2 FO 3 FO4 regional equal FO 1 FO 2 FO 3 FO4 regional equal
Birch sap 0.163 0.168 0.171 0.169 0.166 0.153 4 4 4 4 4 4
Cep 0.137 0.124 0.121 0.110 0.125 0.131 5 5 5 5 5 5
Honey 0.187 0.211 0.220 0.232 0.210 0.219 3 3 3 3 3 2
Bilberry 0.281 0.263 0.261 0.255 0.270 0.277 1 1 1 1 1 1
N-Karelia
Pakuri 0.232 0.234 0.227 0.234 0.230 0.219 2 2 2 2 2 3
Larch resin 0.165 0.149 0.149 0.156 0.151 0.142 1 2 2 2 2 3
Chanterelles 0.121 0.113 0.108 0.107 0.114 0.108 4 6 7 6 6 7
Game meat 0.110 0.122 0.125 0.129 0.119 0.120 8 4 4 4 4 4
Bilberry 0.110 0.101 0.099 0.086 0.100 0.102 7 8 8 8 8 8
Christmas tree 0.138 0.157 0.161 0.168 0.153 0.162 2 1 1 1 1 1
Cep 0.129 0.116 0.111 0.112 0.118 0.110 3 5 6 5 5 6
Wild garlic 0.117 0.112 0.112 0.106 0.114 0.113 5 7 5 7 7 5
Styria
Honey 0.111 0.129 0.135 0.136 0.131 0.143 6 3 3 3 3 2
874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912
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223 At least partly due to small differences in highest level rankings of four main criteria, there is no 224 variation between weighting scenarios in N-Karelia. Therefore, in N-Karelia bilberries (Vaccinium 225 myrtillus) appear to be the most promising NWFP (0.277) in all scenarios, followed by honey (Apis 226 mellifera; 0.219) and Pakuri mushroom (Inonotus obliquus; 0.219). Less relevant are birch sap 227 (Betula pendula; 0.153) and Cep (Boletus edulis; 0,131).
228 In Styria the most promising NWFPs are Christmas trees (Abies nordmanniana; 0.162), honey (Apis 229 mellifera; 0.143), Larch resin (Larix decidua; 0.142) and game meat from red deer (Cervus elaphus;
230 0.120). Other NWFPs tend to be less relevant given the underlying scenario (i.e. equal), resulting in 231 the following global priorities: i) 0.113 wild garlic (Allium ursinum), ii) 0.110 Cep (Boletus edulis), 232 iii) 0.108 Chantarelles (Cantharellus cibarius), and iv) 0.102 bilberry (Vaccinium myrtillus).
233 The integration of different weighting scenarios results in diverging performances (i.e. global 234 priorities) of NWFP alternatives. Both the regional and the four owner type dependent scenarios (FO1 235 - FO 4) affect the performance results of the investigated NWFP options. While for N-Karelia the 236 results are quite robust, effects of the different scenarios are noteworthy in Styria as they lead to rank 237 reversals in several cases. Due to different weights for (sub-)criteria the performance of NWFP 238 alternatives differs and results in changing rankings.
239 4. Discussion 240 4.1 Regional results
241 When looking at the overall results of NWFP priorities, it is no surprise that bilberry appears as the 242 most relevant production option in N-Karelia. But it was not expected that honey would be placed 243 second, because in the public discussion Pakuri (chaga mushroom) and birch sap were gaining 244 momentum recently, perhaps due to their innovation activities and market potential as well as health 245 effects, which however are obvious also for bilberry. The fact that bilberry was evaluated as the 246 NWFP with the highest potential and there was no variation between forest owner profiles may also 247 relate to the existence of Finnish everyman’s rights which are valid for cep and bilberry only, 248 indicating that regional conditions favour them despite forest owners’ and the resources they govern.
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249 On the other hand, regarding the resources forest owners can control, the position of Pakuri is not a 250 surprise due to recent discussions around it. Thus, the results for N-Karelia appear as valid and 251 meaningful estimates while offering insights to the opportunities of mixing more resilient and more 252 risky NWFPs to a solid regional business portfolio.
253 Likewise for Styria the rankings of the most relevant NWFPs reflect current business opportunities.
254 However, it has to be taken into consideration that Christmas trees are usually grown on former 255 agricultural land and managed as short-rotation plantations, sometimes in combination with 256 compatible silvo-pastoral practices (e.g. livestock grazing of Shropshire sheep). The high performance 257 of Larch resin comes as a surprise but depicts latent potentials of innovation (both product and 258 process) and fits well with ongoing bio-economy developments (e.g. substitution of fossil-based raw 259 materials, by- or end-products). Honey and game meat are gaining momentum recently in the public 260 debate, inter alia due to upcoming trends in nutrition and gastronomy, whereas remaining NWFPs are 261 controversially discussed but play a minor role for income generation due to their public goods 262 characteristics (e.g. mushroom picking is regulated by law, allowing everyman to pick quantities up to 263 2 kg/person/day as long as the forest owner does not restrict it). Overall, the results for Styria appear 264 to be appropriate estimates and depict suitable future options for NWFP developments in the region.
974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031
20 266 4.2 Evaluation of the Model
267 The application developed in this study adopted a mixed method-approach (Myllyviita et al. 2014).
268 First, it combined qualitative (cognitive mapping) and quantitative (MCA methods) techniques, as 269 demonstrated by Wolfslehner and Vacik (2011). Secondly, it applied two different MCA methods 270 (SMART, AHP). The use and application of different methods in decision making is becoming an 271 important element for natural resource management to harvest synergies of their strengths (Vacik et 272 al. 2014). The MCA methods in this study were selected so that the preference input demanded from 273 stakeholders was reasonable and the characteristics of outputs from methods were balanced to meet 274 the requirements of the model use. It was possible to utilize informal expert knowledge for the 275 evaluation of the criteria, where hard facts and figures are missing (e.g. competitiveness, future 276 innovation potential). On the other hand, existing data could be used by the experts in the evaluation 277 regarding other criteria (e.g. current end product value and end product diversity). However, the 278 methods also set some limits to the practical application of the developed model. For example, when 279 AHP and its pairwise comparison technique is used, the number of examined NWFPs is limited due to 280 the increasing number of pairwise comparisons. As a solution, it is possible to use a more advanced 281 version of AHP (e.g. Leskinen and Kangas, 2005, Leskinen et al. 2003) or add new levels to the 282 hierarchy. For example, it could be possible to examine a larger number of NWFPs by adding the new 283 hierarchy level “NWFP category” to the model and then examine larger amount of NWFPs. A new 284 hierarchy level however, would have made the evaluation more complex to understand.
285 The model building and preference elicitations took place in an iterative form. It started with a two- 286 day workshop to enable wide incorporation of viewpoints, and gaining a solid model structure. In 287 particular, the cognitive mapping approach facilitated the combination of individual expertise and 288 different disciplines. It provided enough flexibility to incorporate the different viewpoints and 289 mindsets of the involved experts, and provided a conceptual structure for the evaluation hierarchy 290 (Wolfslehner and Vacik, 2011). On the other hand, structuring a model that would immediately fit 291 different local contexts appeared challenging as it had to contain rather general concepts that had to be 292 defined and localized when considering the model and its potential use with stakeholders. In 1033
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293 hindsight, a consistent terminology, clear explanations of the meanings of (sub-)criteria and 294 transparent visions of the benefits of the whole process in advance to the consultations could have 295 benefitted the model structuring process. It is important to make such a process comprehensible and 296 create links between the conceptual model and the real world that are easier to understand for experts 297 and stakeholders. The indicators designed for the evaluation of the NWFP potential can serve as a 298 valuable standard in other contexts as well.
299 Through the intensive discussions and verifications by experts and stakeholders, it can be assumed, 300 that the framework allows for a very holistic assessment of NWFP contexts. Operability was verified 301 with stakeholder consultations, which can be seen as a necessary step in this type of expert model 302 construction processes. Also, the use of two concrete case studies to test the rationality and 303 functionality of the model was obviously an asset. Additionally, in the light of contemporary 304 European policy developments fostering a more bio-based, integrated economy this approach could 305 also provide a solid base to inform forest-policy decision making when e.g. regional forest programs 306 are created that exceed the traditional views of biomass supply. It has to be acknowledged that a 307 forest-based bio-economy has to go beyond the sheer supply of biomass to respond to rural 308 development and the nexus of food, energy, and ecosystem services (Wolfslehner et al. 2016a).
309 Considering a stronger implementation of sustainable forest management towards more ecosystem- 310 based approaches that account for a broad set of management objectives and recognize the importance 311 of biodiversity, the multi-functional role of forests and the related stand neighbourhoods and 312 landscape-level processes (e.g. Maes et al. 2015; Messier et al. 2015), new decisions support 313 approaches are needed (Vacik and Lexer, 2014). The presented model could act as an eye-opener for 314 forestry-oriented stakeholders who have not yet counted on NWFPs as potential assets for their forest 315 management systems as it pinpoints latent potentials of co-production. With its ability to include 316 various NWFPs and consider different forest owner preferences, future applications can be tailored 317 towards the needs of both small-scale (non-industrial) forest owners and bigger forest holdings. Given 318 the multiplicity of resources available and Europe´s rich forest owner landscape that builds upon the 319 interests of around 16 million private forest owners who manage approximately 60 % of forests in 1092
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320 Europe (CEPF, s.a.), the opportunities to strengthen the economic viability of rural economies appear 321 to be imposing at first sight (Rodriguez-Vicente and Maray-Pérez, 2010). It has been demonstrated 322 that a diversification of forest products and services can be a particularly viable income source for 323 small-scale and non-industrial private forest owners (Wolfslehner et al. 2016b). When aiming to move 324 further towards more practical solutions with the constructed expert model, regional policymakers and 325 extension service providers appear as relevant change agents, the former in the role of using the model 326 in preparing policy actions regarding NWFPs and the latter in the role of disseminating information to 327 land owners who might then initiate new NWFP related businesses. It is the diversification of 328 business opportunities that finally bridges the span from traditional to new, innovative uses of NWFP, 329 both of them equally important in a rural bio-economy. To make that happen, public discussion of the 330 approach and of the various potentials and their determinants are needed. Moreover, extension 331 services might benefit from specific training for these topics, and an open source tool for free access 332 and application would support the uptake in practice. The approach could in this way also contribute 333 to foster the knowledge transfer at the science-policy and science-practice interface that helps to 334 balance a currently biomass-centered discourse in the forest-based sector.
335 However, the expert model is still in an early development stage and one asset of this article is 336 promoting this methodological approach. In the future, it has to be tested in different socio-economic 337 and environmental contexts by means of additional case studies to allow for a more comprehensive 338 applicability improving the potential for up scaling to the findings on the European level. Diverging 339 conditions such as legal frameworks, ownership structures, resources management, tenure as well as 340 property rights in the EU member states are important denominators for a broad applicability and 341 robustness of the expert model.
342 5. Conclusions
343 Although the presented approach represents an expert model that strongly builds on individual expert 344 skills disposing extensive knowledge of the NWFP sector, it integrates the experiences and 345 perceptions of various stakeholders across the NWFP value chain. This interplay between expert and 346 lay knowledge as well as science-driven and experience-driven knowledge has been implemented 1151
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347 from an early development towards a sequence of distinct stakeholder interaction processes.
348 Combining diverse knowledge and experience was beneficial for several reasons: i) to gain insights 349 on different notions of NWFP potentials, ii) to investigate and understand stakeholder perceptions of 350 regional NWFP markets, iii) to revise potential knowledge gaps or errors in interpretation of NWFP 351 potentials and limitations, iv) to align the preference model to fit into regional contexts, and thus, v) to 352 justify its credibility and operability in the selected case study settings. At hindsight, it has to be 353 acknowledged that the selection of NWFP options was also driven by expert knowledge and might not 354 fully reflect the potentials or limitations of the entire NWFP portfolio that is available and used in the 355 region as it is based on the subjective viewpoints of individuals. However, the experts were selected 356 based on their experience in the field and consulted to objectively suggest NWFP alternatives that 357 could play a significant role for individual forest owners interested in the management thereof.
358 Furthermore, the set of NWFPs used can be adopted to individual future applications in other case 359 study settings, integrating additional alternatives to the demand of the user.
360 Given this flexibility of the tool, it has a potential to convey new concepts to the mindset of individual 361 forest owners who might not yet know where to focus concerning their forest assets. More 362 importantly, the tool may help those forest owners who are already interested in multi-functional 363 forestry or NWFP production and in particular to adapt their management approaches. These forest 364 owners can assess their own capabilities as forest owners and business managers can learn about the 365 requirements and potentials of producing alternative NWFPs in their region. This may result in the 366 formation of value networks with benefit sharing across resource managers and entrepreneurs what 367 may be particularly relevant in a modern bioeconomy. For many small companies value creation by 368 more dynamic, networked and innovative business models and products gives better possibilities to 369 avoid hard competition. That could lead to the development of more comprehensive business plans 370 where traditional, wood-production oriented forest management planning can be complemented with 371 NWFP management planning, resulting in co-production of forest products. This may be important 372 for small-scale forest owners and family businesses in particular. For this broadening of management 373 objectives further information and consultations are provided by forest extension services to create an 1210
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374 operational support for the grown interest among forest and landowners. Therefore, clear guidelines 375 and recommendations for management of different NWFPs, educational trails, demonstration field 376 trips, NWFP seminars, individual consultation service packages, and a NWFP peer community need 377 to be available. At best, the regional forest policy and innovation system can take the responsibility to 378 nurture and safeguard the availability of these options (Ludvig et al. 2016b) in order to support both 379 innovations and entrepreneurship, some of the key drivers to fuel and sustain regional development.
380
381 Acknowledgements
382 This study has been financially supported by FP7 Project no. 311919 KBBE.2012.1.2-06 StarTree – 383 Multipurpose trees and non-wood forest products a challenge and opportunity, and COST-Action 384 FP1203: European non-wood forest products (NWFPs) network. The authors want to express their 385 sincere gratitude to all supporters of the study (i.e. case study responsible persons, experts and 386 stakeholders involved).
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