Screening of antibacterial extracts from plants native to the Brazilian Amazon Rain Forest and Atlantic Forest

More than 20% of the world's biodiversity is located in Brazilian forests and only a few plant extracts have been evaluated for potential antibacterial activity. In the present study, 705 organic and aqueous extracts of plants obtained from different Amazon Rain Forest and Atlantic Forest plants were screened for antibacterial activity at 100 µg/ml, using a microdilution broth assay against Staphylococcus aureus, Enterococcus faecalis, Pseudomonas aeruginosa and Escherichia coli. One extract, VO581, was active against S. aureus (minimum inhibitory concentration (MIC) = 140 µg/ml and minimal bactericidal concentration (MBC) = 160 µg/ml, organic extract obtained from stems) and two extracts were active against E. faecalis, SM053 (MIC = 80 µg/ml and MBC = 90 µg/ml, organic extract obtained from aerial parts), and MY841 (MIC = 30 µg/ml and MBC = 50 µg/ml, organic extract obtained from stems). The most active fractions are being fractionated to identify their active substances. Higher concentrations of other extracts are currently being evaluated against the same microorganisms.

Forest inventory information needs in Northwest Russia

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.

Use of conventional PCR and smear microscopy to diagnose pulmonary tuberculosis in the Amazonian rainforest area

The diagnostic usefulness of Ziehl-Neelsen (ZN)-stained sputum smears combined with conventional polymerase chain reaction (ZN/PCR) to amplify IS6110 region DNA extracted from ZN slides was evaluated. The objective was to verify if this association could improve tuberculosis (TB) diagnosis in patients at remote sites. The study was carried out in 89 patients with culture-confirmed pulmonary TB as defined by the Brazilian Manual for TB Treatment. The participants were recruited in a reference unit for TB treatment in Rondônia, a state in the Amazonian area in northern Brazil. ZN, PCR, and culture performed in the sputum samples from these patients were analyzed in different combinations (i.e., ZN plus PCR and ZN plus culture). The prevalence rates of pulmonary TB in these patients were 32.6 and 28.1% considering culture and ZN/PCR, respectively. The sensitivity and specificity of ZN/PCR were 86 and 93%, respectively. ZN/PCR was able to detect more TB cases than ZN alone. This method could offer a new approach for accurate tuberculosis diagnosis, especially in remote regions of the world where culture is not available.

Nutritional characteristics of amazonian fish fat (Colossoma macropomum) and its effect on lipid metabolism of rats fed hypercholesterolemic diets

The effects of fat from tambaqui (Colossoma macropomum), an Amazonian fish, on some nutritional and lipid parameters in rats were evaluated. Weaned Wistar rats were fed for 6 weeks with hypercholesterolemic diets containing 7.5% of soybean oil (SO), cod liver oil (CO), lard (LA), or tambaqui fat (TF). Food consumption, weight gain, and food conversion were measured weekly. Plasma triglycerides was determined at the beginning and on the 6th week of experiment. Plasma cholesterol was determined at 0, 2, 4 and 6 weeks. After the sacrifice, hepatic lipids (triglycerides and cholesterol) and plasma triglycerides, total cholesterol and HDL fractions were determined. Food consumption and weight gain were the same for all groups. There were no differences in plasma triglycerides among the four groups in the 1st and 6th weeks. Regarding the cholesterolemia, TF animals were similar to those fed SO diet, significantly lower than in LA group but higher compared to the CO group. The levels of very low density lipoprotein + low density lipoprotein (VLDL+LDL) were higher in the TF and LA groups compared to the CO and SO groups. However, TA fed animals had high-density lipoprotein (HDL) cholesterol levels higher than the CO group. The ratio (VLDL+LDL)/HDL was higher in the LA group when compared with the remaining groups. In the TA group, the triglycerides and cholesterol concentrations in the liver were similar to the SO group. It may be concluded that tambaqui fat is a good dietary source of lipids as a substitute for lard and similar to soybean oil, as far as atherosclerosis risks is concerned.

Forest inventory information needs in Northwest Russia

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.

Suitability of LiDAR technology for forest inventory in Russia

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.

Study of the physical and physicochemical characteristics of fruits of the licuri palm (Syagrus coronata (Mart.) Becc.) found in the Atlantic Forest of Minas Gerais, Brazil

AbstractThe Atlantic Forest has species of native fruits, consumed fresh and processed, which have an important contribution to food sovereignty of families that consume it. This study examined the physical and physicochemical characteristics, proximate composition, concentration of carotenoids, vitamin C, vitamin E and minerals in the pulp and kernels of fruits of licuri (Syagrus coronata (Mart.) Becc.). Titratable acidity was analyzed by volumetric neutralization, soluble solids by refractometry, proteins by the micro-Kjeldahl method, lipids by gravimetry using soxhlet, dietary fiber by non-enzymatic gravimetry, carotenoids and vitamin C by HPLC-DAD, vitamin E by HPLC-fluorescence, and minerals by ICP-AES. Pulp were a source of Zn (0.95 mg 100–1), a good source of fiber (6.15 g 100–1), excellent source of provitamin A (758.75 RAE 100–1), Cu (0.69 mg 100–1), Fe (3.81 mg 100–1), Mn (3.40 mg 100–1) and Mo (0.06 mg 100–1). The kernel were a source of Fe (3.36 mg 100–1) and excellent source of Mn (6.14 mg 100–1), Cu (0.97 mg 100–1) and Mo (0.07 mg 100–1). The nutritional value and wide availability of licuri fruit make it an important resource for reducing food insecurity and improving nutrition of the rural population and other individuals who have access to it.

Use of airborne laser scanner data in demanding forest conditions

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.

Trophic cascades in boreal landscapes: top predator protection on tree seedlings and forest grouse

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.

Utilization of Statistical Methods for Management in the Forest Industry

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