210 resultados para TABULEIRO FOREST
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Forest biomass represents a geographically distributed feedstock, and geographical location affects the greenhouse gas (GHG) performance of a given forest-bioenergy system in several ways. For example, biomass availability, forest operations, transportation possibilities and the distances involved, biomass end-use possibilities, fossil reference systems, and forest carbon balances all depend to some extent on location. The overall objective of this thesis was to assess the GHG emissions derived from supply and energy-utilization chains of forest biomass in Finland, with a specific focus on the effect of location in relation to forest biomass’s availability and the transportation possibilities. Biomass availability and transportation-network assessments were conducted through utilization of geographical information system methods, and the GHG emissions were assessed by means of lifecycle assessment. The thesis is based on four papers in which forest biomass supply on industrial scale was assessed. The feedstocks assessed in this thesis include harvesting residues, smalldiameter energy wood and stumps. The principal implication of the findings in this thesis is that in Finland, the location and availability of biomass in the proximity of a given energyutilization or energy-conversion plant is not a decisive factor in supply-chain GHG emissions or the possible GHG savings to be achieved with forest-biomass energy use. Therefore, for the greatest GHG reductions with limited forest-biomass resources, energy utilization of forest biomass in Finland should be directed to the locations where most GHG savings are achieved through replacement of fossil fuels. Furthermore, one should prioritize the types of forest biomass with the lowest direct supply-chain GHG emissions (e.g., from transport and comminution) and the lowest indirect ones (in particular, soil carbon-stock losses), regardless of location. In this respect, the best combination is to use harvesting residues in combined heat and power production, replacing peat or coal.
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Julkaisumaa: 578 NO NOR Norja
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Tropical forests are sources of many ecosystem services, but these forests are vanishing rapidly. The situation is severe in Sub-Saharan Africa and especially in Tanzania. The causes of change are multidimensional and strongly interdependent, and only understanding them comprehensively helps to change the ongoing unsustainable trends of forest decline. Ongoing forest changes, their spatiality and connection to humans and environment can be studied with the methods of Land Change Science. The knowledge produced with these methods helps to make arguments about the actors, actions and causes that are behind the forest decline. In this study of Unguja Island in Zanzibar the focus is in the current forest cover and its changes between 1996 and 2009. The cover and changes are measured with often used remote sensing methods of automated land cover classification and post-classification comparison from medium resolution satellite images. Kernel Density Estimation is used to determine the clusters of change, sub-area –analysis provides information about the differences between regions, while distance and regression analyses connect changes to environmental factors. These analyses do not only explain the happened changes, but also allow building quantitative and spatial future scenarios. Similar study has not been made for Unguja and therefore it provides new information, which is beneficial for the whole society. The results show that 572 km2 of Unguja is still forested, but 0,82–1,19% of these forests are disappearing annually. Besides deforestation also vertical degradation and spatial changes are significant problems. Deforestation is most severe in the communal indigenous forests, but also agroforests are decreasing. Spatially deforestation concentrates to the areas close to the coastline, population and Zanzibar Town. Biophysical factors on the other hand do not seem to influence the ongoing deforestation process. If the current trend continues there should be approximately 485 km2 of forests remaining in 2025. Solutions to these deforestation problems should be looked from sustainable land use management, surveying and protection of the forests in risk areas and spatially targeted self-sustainable tree planting schemes.
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High elevation treelines are formed under common temperature conditions worldwide, but the functional mechanisms that ultimately constrain tree growth are poorly known. In addition to environmental constraints, the distribution of high elevation forests is largely affected by human influence. Andean Polylepis (Rosaceae) forests are an example of such a case, forests commonly growing in isolated stands disconnected from the lower elevation montane forests. There has been ample discussion as to the role of environmental versus anthropogenic causes of this fragmented distribution of Polylepis forests, but the importance of different factors is still unclear. In this thesis, I studied functional, environmental and anthropogenic aspects determining Polylepis forest distribution. Specifically, I assessed the degree of genetic determinism in the functional traits that enable Polylepis species to grow in cold and dry conditions. I also studied the role of environment and human influence constraining Polylepis forest distribution. I found evidence of genetically determined climatic adaptations in the functional traits of Polylepis. High elevation species had reduced leaf size and increased root tip abundance compared to low elevation species. Thus these traits have potentially played an important role in species evolution and adaptation to high elevation habitats, especially to low temperatures. I also found reduced photosynthesis rate among high elevation tree species compared to low elevation species, supporting carbon source limitation at treelines. At low elevations, Polylepis forest distribution appeared to be largely defined by human influence. This suggests that the absence of Polylepis forests in large areas in the Andes is the result of several environmental and anthropogenic constraints, the role of environment becoming stronger towards high elevations. I also show that Polylepis trees grow at remarkably low air and soil temperatures near treelines, and present new evidence of the role of air temperatures in constraining tree growth at high elevations. I further show that easily measurable indices of accessibility are related to the degree of degradation of Polylepis forest, and can therefore be used in the rapid identification of potentially degraded Polylepis forests. This is of great importance for the conservation and restoration planning of Polylepis forests in the Andes. In a global context, the results of this thesis add to our scientific knowledge concerning high elevation adaptations in trees, and increase our understanding of the factors constraining tree growth and forest distribution at high-elevation treelines worldwide.
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The report presents the results of the commercialization project called the Container logistic services for forest bioenergy. The project promotes new business that is emerging around overall container logistic services in the bioenergy sector. The results assess the European markets of the container logistics for biomass, enablers for new business creation and required service bundles for the concept. We also demonstrate the customer value of the container logistic services for different market segments. The concept analysis is based on concept mapping, quality function deployment process (QFD) and business network analysis. The business network analysis assesses key shareholders and their mutual connections. The performance of the roadside chipping chain is analysed by the logistic cost simulation, RFID system demonstration and freezing tests. The EU has set the renewable energy target to 20 % in 2020 of which Biomass could account for two-thirds. In the Europe, the production of wood fuels was 132.9 million solid-m3 in 2012 and production of wood chips and particles was 69.0 million solidm3. The wood-based chips and particle flows are suitable for container transportation providing market of 180.6 million loose- m3 which mean 4.5 million container loads per year. The intermodal logistics of trucks and trains are promising for the composite containers because the biomass does not freeze onto the inner surfaces in the unloading situations. The overall service concept includes several packages: container rental, container maintenance, terminal services, RFID-tracking service, and simulation and ERP-integration service. The container rental and maintenance would provide transportation entrepreneurs a way to increase the capacity without high investment costs. The RFID-concept would lead to better work planning improving profitability throughout the logistic chain and simulation supports fuel supply optimization.
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This thesis applies the customer value hierarchy model to forestry in order to determine strategic options to enhance the value of LiDAR technology in Russian forestry. The study is conducted as a qualitative case study with semi-structured interviews as a main source of the primary data. The customer value hierarchy model constitutes a theoretical base for the research. Secondary data incorporates information on forest resource management, LiDAR technology and Russian forestry. The model is operationalised using forestry literature and forms a basis for analyses of primary data. Analyses of primary data coupled with comprehension of Russian forest inventory system and knowledge on global forest inventory have led to conclusions on the forest inventory methods selection criteria and the organizations that would benefit the most from LiDAR technology use. The thesis recommends strategic options for LiDAR technology’s value enhancement in Russian forestry.
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This research report applies the customer value hierarchy model to forestry in order to determine strategic options to enhance the value of LiDAR technology in Russian forestry. The study is conducted as a qualitative case study with semi-structured interviews as a main source of the primary data. The customer value hierarchy model constitutes a theoretical base for the research. Secondary data incorporates information on forest resource management, LiDAR technology and Russian forestry. The model is operationalised using forestry literature and forms a basis for analyses of primary data. Analyses of primary data coupled with comprehension of Russian forest inventory system and knowledge on global forest inventory have led to conclusions on the forest inventory methods selection criteria and the organizations that would benefit the most from LiDAR technology use. The report recommends strategic options for LiDAR technology’s value enhancement in Russian forestry. This work has been conducted as a part of the project ‘Finnish-Russian Forest Academy 2 - Exploiting and Piloting’, which has been supported financially by the South-East Finland- Russia ENPI CBC 2007-2014 Programme.
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LiDAR is an advanced remote sensing technology with many applications, including forest inventory. The most common type is ALS (airborne laser scanning). The method is successfully utilized in many developed markets, where it is replacing traditional forest inventory methods. However, it is innovative for Russian market, where traditional field inventory dominates. ArboLiDAR is a forest inventory solution that engages LiDAR, color infrared imagery, GPS ground control plots and field sample plots, developed by Arbonaut Ltd. This study is an industrial market research for LiDAR technology in Russia focused on customer needs. Russian forestry market is very attractive, because of large growing stock volumes. It underwent drastic changes in 2006, but it is still in transitional stage. There are several types of forest inventory, both with public and private funding. Private forestry enterprises basically need forest inventory in two cases – while making coupe demarcation before timber harvesting and as a part of forest management planning, that is supposed to be done every ten years on the whole leased territory. The study covered 14 companies in total that include private forestry companies with timber harvesting activities, private forest inventory providers, state subordinate companies and forestry software developer. The research strategy is multiple case studies with semi-structured interviews as the main data collection technique. The study focuses on North-West Russia, as it is the most developed Russian region in forestry. The research applies the Voice of the Customer (VOC) concept to elicit customer needs of Russian forestry actors and discovers how these needs are met. It studies forest inventory methods currently applied in Russia and proposes the model of method comparison, based on Multi-criteria decision making (MCDM) approach, mainly on Analytical Hierarchy Process (AHP). Required product attributes are classified in accordance with Kano model. The answer about suitability of LiDAR technology is ambiguous, since many details should be taken into account.
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Most of the applications of airborne laser scanner data to forestry require that the point cloud be normalized, i.e., each point represents height from the ground instead of elevation. To normalize the point cloud, a digital terrain model (DTM), which is derived from the ground returns in the point cloud, is employed. Unfortunately, extracting accurate DTMs from airborne laser scanner data is a challenging task, especially in tropical forests where the canopy is normally very thick (partially closed), leading to a situation in which only a limited number of laser pulses reach the ground. Therefore, robust algorithms for extracting accurate DTMs in low-ground-point-densitysituations are needed in order to realize the full potential of airborne laser scanner data to forestry. The objective of this thesis is to develop algorithms for processing airborne laser scanner data in order to: (1) extract DTMs in demanding forest conditions (complex terrain and low number of ground points) for applications in forestry; (2) estimate canopy base height (CBH) for forest fire behavior modeling; and (3) assess the robustness of LiDAR-based high-resolution biomass estimation models against different field plot designs. Here, the aim is to find out if field plot data gathered by professional foresters can be combined with field plot data gathered by professionally trained community foresters and used in LiDAR-based high-resolution biomass estimation modeling without affecting prediction performance. The question of interest in this case is whether or not the local forest communities can achieve the level technical proficiency required for accurate forest monitoring. The algorithms for extracting DTMs from LiDAR point clouds presented in this thesis address the challenges of extracting DTMs in low-ground-point situations and in complex terrain while the algorithm for CBH estimation addresses the challenge of variations in the distribution of points in the LiDAR point cloud caused by things like variations in tree species and season of data acquisition. These algorithms are adaptive (with respect to point cloud characteristics) and exhibit a high degree of tolerance to variations in the density and distribution of points in the LiDAR point cloud. Results of comparison with existing DTM extraction algorithms showed that DTM extraction algorithms proposed in this thesis performed better with respect to accuracy of estimating tree heights from airborne laser scanner data. On the other hand, the proposed DTM extraction algorithms, being mostly based on trend surface interpolation, can not retain small artifacts in the terrain (e.g., bumps, small hills and depressions). Therefore, the DTMs generated by these algorithms are only suitable for forestry applications where the primary objective is to estimate tree heights from normalized airborne laser scanner data. On the other hand, the algorithm for estimating CBH proposed in this thesis is based on the idea of moving voxel in which gaps (openings in the canopy) which act as fuel breaks are located and their height is estimated. Test results showed a slight improvement in CBH estimation accuracy over existing CBH estimation methods which are based on height percentiles in the airborne laser scanner data. However, being based on the idea of moving voxel, this algorithm has one main advantage over existing CBH estimation methods in the context of forest fire modeling: it has great potential in providing information about vertical fuel continuity. This information can be used to create vertical fuel continuity maps which can provide more realistic information on the risk of crown fires compared to CBH.
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Changes in the abundance of top predators have brought about notable, cascading effects in ecosystems around the world. In this thesis, I examined several potential trophic cascades in boreal ecosystems, and their separate interspecific interactions. The main aim of the thesis was to investigate whether predators in the boreal forests have direct or indirect cascading effects on the lower trophic levels. First, I compared the browsing effects of different mammalian herbivores by excluding varying combinations of voles, hares and cervids from accessing the seedlings of silver birch (Betula pendula), Scots pine (Pinus sylvestris) and Norway spruce (Picea abies). Additionally, I studied the effect of simulated predation risk on vole browsing by using auditory cues of owls. Moving upwards on the trophic levels, I examined the intraguild interactions between the golden eagle (Aquila chrysaetos), and its mesopredator prey, the red fox (Vulpes vulpes) and the pine marten (Martes martes). To look at an entire potential trophic cascade, I further studied the combined impacts of eagles and mesopredators on the black grouse (Tetrao tetrix) and the hazel grouse (Tetrastes bonasia), predicting that the shared forest grouse prey would benefit from eagle presence. From the tree species studied, birch appears to be the most palatable one for the mammalian herbivores. I observed growth reductions in the presences of cervids and low survival associated with hares and voles, which suggests that they all weaken regeneration in birch stands. Furthermore, the simulated owl predation risk appeared to reduce vole browsing on birches in late summer, although the preferred grass forage is then old and less palatable. Browsing by voles and hares had a negative effect on the condition and survival of Scots pine, but in contrast, the impact of mammalian herbivores on spruce was found to be small, at least when more preferred food is available. I observed that the presence of golden eagles had a negative effect on the abundance of adult black grouse but a positive, protective effect on the proportion of juveniles in both black grouse and hazel grouse. Yet, this positive effect was not dependent on the abundance foxes or martens, nor did eagles seem to effectively decrease the abundance of these mesopredators. Conversely, the protection effect on grouse could arise from fear effects and also be mediated by other mesopredators. The results of this thesis provide important new information about trophic interactions in the boreal food webs. They highlight how different groups of mammalian herbivores vary in their effects on the growth and condition of different tree seedlings. Lowered cervid abundances could improve birch regeneration, which indirectly supports the idea that the key predators of cervids could cause cascading effects also in Fennoscandian forests. Owls seem to reduce vole browsing through an intimidation effect, which is a novel result of the cascading effects of owl vocalisation and could even have applications for protecting birch seedlings. In the third cascade examined in this thesis, I found the golden eagle to have a protective effect on the reproducing forest grouse, but it remains unclear through which smaller predators this effect is mediated. Overall, the results of this thesis further support the idea that there are cascading effects in the forests of Northern Europe, and that they are triggered by both direct and non‐lethal effects of predation.
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The strongest wish of the customer concerning chemical pulp features is consistent, uniform quality. Variation may be controlled and reduced by using statistical methods. However, studies addressing the application and benefits of statistical methods in forest product sector are scarce. Thus, the customer wish is the root cause of the motivation behind this dissertation. The research problem addressed by this dissertation is that companies in the chemical forest product sector require new knowledge for improving their utilization of statistical methods. To gain this new knowledge, the research problem is studied from five complementary viewpoints – challenges and success factors, organizational learning, problem solving, economic benefit, and statistical methods as management tools. The five research questions generated on the basis of these viewpoints are answered in four research papers, which are case studies based on empirical data collection. This research as a whole complements the literature dealing with the use of statistical methods in the forest products industry. Practical examples of the application of statistical process control, case-based reasoning, the cross-industry standard process for data mining, and performance measurement methods in the context of chemical forest products manufacturing are brought to the public knowledge of the scientific community. The benefit of the application of these methods is estimated or demonstrated. The purpose of this dissertation is to find pragmatic ideas for companies in the chemical forest product sector in order for them to improve their utilization of statistical methods. The main practical implications of this doctoral dissertation can be summarized in four points: 1. It is beneficial to reduce variation in chemical forest product manufacturing processes 2. Statistical tools can be used to reduce this variation 3. Problem-solving in chemical forest product manufacturing processes can be intensified through the use of statistical methods 4. There are certain success factors and challenges that need to be addressed when implementing statistical methods