Nature-based entrepreneurship in private forests – The preconditions for the sustainable co-operation between private forest owners and entrepreneurs

Nature-based tourism is one of the fastest growing tourism sectors at the moment. It is also the form of tourism that often benefits the economy of rural areas. In addition to state owned forests, nature-based tourism is in many countries situated in private forests, which are not owned by entrepreneurs themselves. Therefore, the ownership issues and property rights form central challenges for the business activities. The maintenance of good relationships between private forest owners and entrepreneurs, as well as combining their interests, becomes vital. These relationships are typically exceptionally asymmetrical, granting the forest owner unilateral rights regulating the business activities in their forests. Despite this, the co-operation is typically very informal and the existing economic compensation models do not necessarily cover all the forest owners’ costs. The ownership issues bring their own characteristics to the relationship. Therefore, we argue that different aspects of ownership, especially psychological ones, have to be more critically examined and taken into consideration in order to build truly successful relations between these parties. This is crucial for sustaining the business activities. The core of psychological ownership is the sense of possession. Psychological ownership can be defined as a state, in which individuals perceive the target of ownership, the object or idea, as “theirs”. The concept of psychological ownership has so far been mainly used in the context of professional organizations. In this research, it has been used to explain the relationships between private forest owners and nature-based entrepreneurs. The aim of this study is to provide new information concerning the effect of psychological ownership on the collaboration and to highlight the good practices. To address the complexity of the phenomenon, qualitative case study methods were adopted to understand the role of ownership at the level of subjective experience. The empirical data was based on 27 in-depth interviews with private forest owners and nature-based tourism entrepreneurs. The data was analysed by using the methods of qualitative analysis to construct different typologies to describe the essence of successful collaboration. As a result of the study, the special characteristics and the practical level expressions of the psychological ownership in the privately owned forest context were analysed. Four different strategies to perceive these ownership characteristics in co-operation relationships were found. By taking the psychological ownership into consideration via these strategies, the nature-based entrepreneurs aim to balance the co-operation relationship and minimise the risks in long term activities based on privately owned forests.

Phytoplankton succession from 1968 to 1990 in the subarctic Lokka reservoir

Tiivistelmä: Kasviplanktonin kehitys vuosina 1968-1990 subarktisessa Lokan tekoaltaassa

Juvenile diversity of tree species in Theobroma cacao L. agroforestry and primary forest – Central Sulawesi, Indonesia

This thesis studies the tree species’ juvenile diversity in cacao (Theobroma cacao L.) based agroforestry and in primary forest in a natural conservation forest environment of Lore Lindu National Park, Sulawesi, Indonesia. Species’ adult composition in Lore Lindu National Park is relatively well studied, less is known about tree species’ diversity in seedling communities particularly in frequently disturbed cacao agroforestry field environment. Cacao production forms a potentially serious thread for maintaining the conservation areas pristine and forested in Sulawesi. The impacts of cacao production on natural environment are directly linked to the diversity and abundance of shade tree usage. The study aims at comparing differences between cacao agroforestry and natural forest in the surrounding area in their species composition in seedling and sapling size categories. The study was carried out in two parts. Biodiversity inventory of seedlings and saplings was combined with social survey with farmer interviews. Aim of the survey was to gain knowledge of the cacao fields, and farmers’ observations and choices regarding tree species associated with cacao. Data was collected in summer 2008. The assessment of the impact of environmental factors of solar radiation, weeding frequency, cacao tree planting density, distance to forest and distance to main park road, and type of habitat on seedling and sapling compositions was done with Non-metric Multidimensional Scaling (NMS). Outlier analysis was used to assess distorting variables for NMS, and Multi-Response Permutation Procedures (MRPP) analysis to differentiate the impact of categorical variables. Sampling success was estimated with rarefaction curves and jackknife estimate of species richness. In the inventory 135 species of trees and shrubs were found. Only some agroforestry related species were dominating. The most species rich were sapling communities in forest habitat. NMS was showing generally low linear correlation between variation of species composition and environmental variables. Solar radiation was having most significance as explaining variable. The most clearly separated in ordination were cacao and forest habitats. The results of seedling and sapling inventory were only partly coinciding with farmers’ knowledge of the tree species occurring on their fields. More research with frequent assessment of seedling cohorts is needed due to natural variability of cohorts and high mortality rate of seedlings.

Mercury in Finnish forest lakes and reservoirs : anthropogenic contribution to the load and accumulation in fish

Yhteenveto: Elohopea Suomen metsäjärvissä ja tekoaltaissa: ihmisen vaikutus kuormitukseen ja pitoisuuksiin kaloissa.

Reducing the babel in plant volatile communication: using the forest to see the trees

While plants of a single species emit a diversity of volatile organic compounds (VOCs) to attract or repel interacting organisms, these specific messages may be lost in the midst of the hundreds of VOCs produced by sympatric plants of different species, many of which may have no signal content. Receivers must be able to reduce the babel or noise in these VOCs in order to correctly identify the message. For chemical ecologists faced with vast amounts of data on volatile signatures of plants in different ecological contexts, it is imperative to employ accurate methods of classifying messages, so that suitable bioassays may then be designed to understand message content. We demonstrate the utility of `Random Forests' (RF), a machine-learning algorithm, for the task of classifying volatile signatures and choosing the minimum set of volatiles for accurate discrimination, using datam from sympatric Ficus species as a case study. We demonstrate the advantages of RF over conventional classification methods such as principal component analysis (PCA), as well as data-mining algorithms such as support vector machines (SVM), diagonal linear discriminant analysis (DLDA) and k-nearest neighbour (KNN) analysis. We show why a tree-building method such as RF, which is increasingly being used by the bioinformatics, food technology and medical community, is particularly advantageous for the study of plant communication using volatiles, dealing, as it must, with abundant noise.

Forest governance and climate change adaptation : Case studies of four African countries

Africa is threatened by climate change. The adaptive capacity of local communities continues to be weakened by ineffective and inefficient livelihood strategies and inappropriate development interventions. One of the greatest challenges for climate change adaptation in Africa is related to the governance of natural resources used by vulnerable poor groups as assets for adaptation. Practical and good governance activities for adaptation in Africa is urgently and much needed to support adaptation actions, interventions and planning. The adaptation role of forests has not been as prominent in the international discourse and actions as their mitigation role. This study therefore focused on the forest as one of the natural resources used for adaptation. The general objective of this research was to assess the extent to which cases of current forest governance practices in four African countries Burkina Faso, The Democratic Republic of Congo (DRC), Ghana and Sudan are supportive to the adaptation of vulnerable societies and ecosystems to impacts of climate change. Qualitative and quantitative analyses from surveys, expert consultations and group discussions were used in analysing the case studies. The entire research was guided by three conceptual sets of thinking forest governance, climate change vulnerability and ecosystem services. Data for the research were collected from selected ongoing forestry activities and programmes. The study mainly dealt with forest management policies and practices that can improve the adaptation of forest ecosystems (Study I) and the adaptive capacity through the management of forest resources by vulnerable farmers (Studies II, III, IV and V). It was found that adaptation is not part of current forest policies, but, instead, policies contain elements of risk management practices, which are also relevant to the adaptation of forest ecosystems. These practices include, among others, the management of forest fires, forest genetic resources, non-timber resources and silvicultural practices. Better livelihood opportunities emerged as the priority for the farmers. These vulnerable farmers had different forms of forest management. They have a wide range of experience and practical knowledge relevant to ensure and achieve livelihood improvement alongside sustainable management and good governance of natural resources. The contributions of traded non-timber forest products to climate change adaptation appear limited for local communities, based on their distribution among the stakeholders in the market chain. Plantation (agro)forestry, if well implemented and managed by communities, has a high potential in reducing socio-ecological vulnerability by increasing the food production and restocking degraded forest lands. Integration of legal arrangements with continuous monitoring, evaluation and improvement may drive this activity to support short, medium and long term expectations related to adaptation processes. The study concludes that effective forest governance initiatives led by vulnerable poor groups represent one practical way to improve the adaptive capacities of socio-ecological systems against the impacts of climate change in Africa.

Markov random fields and spatial smoothing in improving of forest inventory estimates

Markov random fields (MRF) are popular in image processing applications to describe spatial dependencies between image units. Here, we take a look at the theory and the models of MRFs with an application to improve forest inventory estimates. Typically, autocorrelation between study units is a nuisance in statistical inference, but we take an advantage of the dependencies to smooth noisy measurements by borrowing information from the neighbouring units. We build a stochastic spatial model, which we estimate with a Markov chain Monte Carlo simulation method. The smooth values are validated against another data set increasing our confidence that the estimates are more accurate than the originals.

CSR in forest industry – Case study of reporting and implementation of social responsibility in three international companies

Corporate Social Responsibility (CSR) has become increasingly important topic in forest industries, and other global companies, in recent years. Globalisation, faster information delivery and demand for sustainable development have set new challenges for global companies in their business operations. Also the importance of stakeholder relations, and pressure to become more transparent has increased in the forest industries. Three dimensions of corporate responsibility economic, environmental and social, are often included in the concept of CSR. Global companies mostly claim that these dimensions are equally important. This study analyses CSR in forest industry and has focus on reporting and implementation of social responsibility in three international companies. These case-companies are Stora Enso, SCA and Sappi, and they have different geographical base, product portfolios and therefore present interesting differences about forest industry strategy and CSR. Global Reporting Initiative (GRI) has created the most known and used reporting framework in CSR reporting. GRI Guidelines have made CSR reporting a uniform function, which can also be measured between companies and different sectors. GRI Guidelines have also made it possible to record and control CSR data in the companies. In recent years the use of GRI Guidelines has increased substantially. Typically CSR reporting on economic and environmental responsibility have been systematic in the global companies and often driven by legistlation and other regulations. However the social responsibility has been less regulated and more difficult to compare. Therefore it has previously been often less focused in the CSR reporting of the global companies. The implementation and use of GRI Guidelines have also increased dialogue on social responsibility issues and stakeholder management in global companies. This study analyses the use of GRI´s framework in the forest industry companies´ CSR reporting. This is a qualitative study and the disclosure of data is empricially analysed using content analysis. Content analysis has been selected as a method for this study because it makes it possible to use different sources of information. The data of this study consists of existing academic literature of CSR, sustainability reports of thecase-companies during 2005-2009, and the semi-structured interviews with company representatives. Different sources provide the possibility to look at specific subject from more than one viewpoint. The results of the study show that all case-companies have relatively common themes in their CSR disclosure, and the differences rise mainly from their product-portfolios, and geographic base. Social impacts to local communities, in the CSR of the companies, were mainly dominated by issues concerning creating wealth to the society and impacting communities through creation of work. The comparability of the CSR reporting, and especially social indicators increased significally from 2007 onwards in all case-companies. Even though the companies claim that three dimensions of CSR economic, environmental and social are equally important economic issues and profit improvement still seem to drive most of the operations in the global companies. Many issues that are covered by laws and regulations are still essentially presented as social responsibility in CSR. However often the unwelcome issues in companies like closing operations are covered just briefly, and without adequate explanation. To make social responsibility equally important in the CSR it would demand more emphasis from all the case-companies. A lot of emphasis should be put especially on the detail and extensiveness of the social reponsibility content in the CSR.

Understorey vegetation as an indicator of forest site potential in Southern Finland.

The relationship between site characteristics and understorey vegetation composition was analysed with quantitative methods, especially from the viewpoint of site quality estimation. Theoretical models were applied to an empirical data set collected from the upland forests of southern Finland comprising 104 sites dominated by Scots pine (Pinus sylvestris L.), and 165 sites dominated by Norway spruce (Picea abies (L.) Karsten). Site index H100 was used as an independent measure of site quality. A new model for the estimation of site quality at sites with a known understorey vegetation composition was introduced. It is based on the application of Bayes' theorem to the density function of site quality within the study area combined with the species-specific presence-absence response curves. The resulting posterior probability density function may be used for calculating an estimate for the site variable. Using this method, a jackknife estimate of site index H100 was calculated separately for pine- and spruce-dominated sites. The results indicated that the cross-validation root mean squared error (RMSEcv) of the estimates improved from 2.98 m down to 2.34 m relative to the "null" model (standard deviation of the sample distribution) in pine-dominated forests. In spruce-dominated forests RMSEcv decreased from 3.94 m down to 3.16 m. In order to assess these results, four other estimation methods based on understorey vegetation composition were applied to the same data set. The results showed that none of the methods was clearly superior to the others. In pine-dominated forests, RMSEcv varied between 2.34 and 2.47 m, and the corresponding range for spruce-dominated forests was from 3.13 to 3.57 m.

Non-industrial private forest landowners’ choices of timber management strategies and potential allowable cut.

In the study, the potential allowable cut in the district of Pohjois-Savo - based on the non-industrial private forest landowners' (NIPF) choices of timber management strategies - was clarified. Alternative timber management strategies were generated, and the choices and factors affecting the choices of timber management strategies by NIPF landowners were studied. The choices of timber management strategies were solved by maximizing the utility functions of the NIPF landowners. The parameters of the utility functions were estimated using the Analytic Hierarchy Process (AHP). The level of the potential allowable cut was compared to the cutting budgets based on the 7th and 8th National Forest Inventories (NFI7 and NFI8), to the combining of private forestry plans, and to the realized drain from non-industrial private forests. The potential allowable cut was calculated using the same MELA system as has been used in the calculation of the national cutting budget. The data consisted of the NIPF holdings (from the TASO planning system) that had been inventoried compartmentwise and had forestry plans made during the years 1984-1992. The NIPF landowners' choices of timber management strategies were clarified by a two-phase mail inquiry. The most preferred strategy obtained was "sustainability" (chosen by 62 % of landowners). The second in order of preference was "finance" (17 %) and the third was "saving" (11 %). "No cuttings", and "maximum cuttings" were the least preferred (9 % and 1 %, resp.). The factors promoting the choices of strategies with intensive cuttings were a) "farmer as forest owner" and "owning fields", b) "increase in the size of the forest holding", c) agriculture and forestry orientation in production, d) "decreasing short term stumpage earning expectations", e) "increasing intensity of future cuttings", and f) "choice of forest taxation system based on site productivity". The potential allowable cut defined in the study was 20 % higher than the average of the realized drain during the years 1988-1993, which in turn, was at the same level as the cutting budget based on the combining of forestry plans in eastern Finland. Respectively, the potential allowable cut defined in the study was 12 % lower than the NFI8-based greatest sustained allowable cut for the 1990s. Using the method presented in this study, timber management strategies can be clarified for non-industrial private forest landowners in different parts of Finland. Based on the choices of timber managemet strategies, regular cutting budgets can be calculated more realistically than before.

Non-industrial private forest landowners’ choices of timber management strategies.

The factors affecting the non-industrial, private forest landowners' (hereafter referred to using the acronym NIPF) strategic decisions in management planning are studied. A genetic algorithm is used to induce a set of rules predicting potential cut of the landowners' choices of preferred timber management strategies. The rules are based on variables describing the characteristics of the landowners and their forest holdings. The predictive ability of a genetic algorithm is compared to linear regression analysis using identical data sets. The data are cross-validated seven times applying both genetic algorithm and regression analyses in order to examine the data-sensitivity and robustness of the generated models. The optimal rule set derived from genetic algorithm analyses included the following variables: mean initial volume, landowner's positive price expectations for the next eight years, landowner being classified as farmer, and preference for the recreational use of forest property. When tested with previously unseen test data, the optimal rule set resulted in a relative root mean square error of 0.40. In the regression analyses, the optimal regression equation consisted of the following variables: mean initial volume, proportion of forestry income, intention to cut extensively in future, and positive price expectations for the next two years. The R2 of the optimal regression equation was 0.34 and the relative root mean square error obtained from the test data was 0.38. In both models, mean initial volume and positive stumpage price expectations were entered as significant predictors of potential cut of preferred timber management strategy. When tested with the complete data set of 201 observations, both the optimal rule set and the optimal regression model achieved the same level of accuracy.

A participatory approach to tactical forest planning.

The paper examines the needs, premises and criteria for effective public participation in tactical forest planning. A method for participatory forest planning utilizing the techniques of preference analysis, professional expertise and heuristic optimization is introduced. The techniques do not cover the whole process of participatory planning, but are applied as a tool constituting the numerical core for decision support. The complexity of multi-resource management is addressed by hierarchical decision analysis which assesses the public values, preferences and decision criteria toward the planning situation. An optimal management plan is sought using heuristic optimization. The plan can further be improved through mutual negotiations, if necessary. The use of the approach is demonstrated with an illustrative example, it's merits and challenges for participatory forest planning and decision making are discussed and a model for applying it in general forest planning context is depicted. By using the approach, valuable information can be obtained about public preferences and the effects of taking them into consideration on the choice of the combination of standwise treatment proposals for a forest area. Participatory forest planning calculations, carried out by the approach presented in the paper, can be utilized in conflict management and in developing compromises between competing interests.

Factors affecting partitioning of private forest holdings in Finland.

Questions of the small size of non-industrial private forest (NIPF) holdings in Finland are considered and factors affecting their partitioning are analyzed. This work arises out of Finnish forest policy statements in which the small average size of holdings has been seen to have a negative influence on the economics of forestry. A survey of the literature indicates that the size of holdings is an important factor determining the costs of logging and silvicultural operations, while its influence on the timber supply is slight. The empirical data are based on a sample of 314 holdings collected by interviewing forest owners in the years 1980-86. In 1990-91 the same holdings were resurveyed by means of a postal inquiry and partly by interviewing forest owners. The principal objective in compiling the data is to assist in quantifying ownership factors that influence partitioning among different kinds of NIPF holdings. Thus the mechanism of partitioning were described and a maximum likelihood logistic regression model was constructed using seven independent holding and ownership variables. One out of four holdings had undergone partitioning in conjunction with a change in ownership, one fifth among family owned holdings and nearly a half among jointly owned holdings. The results of the logistic regression model indicate, for instance, that the odds on partitioning is about three times greater for jointly owned holdings than for family owned ones. Also, the probabilities of partitioning were estimated and the impact of independent dichotomous variables on the probability of partitioning ranged between 0.02 and 0.10. The low value of the Hosmer-Lemeshow test statistic indicates a good fit of the model and the rate of correct classification was estimated to be 88 per cent with a cutoff point of 0.5. The average size of holdings undergoing ownership changes decreased from 29.9 ha to 28.7 ha over the approximate interval 1983-90. In addition, the transition probability matrix showed that the trends towards smaller size categories mostly involved in the small size categories, less than 20 ha. The results of the study can be used in considering the effects of the small size of holdings for forestry and if the purpose is to influence partitioning through forest or rural policy.