A random linear functional approach to efficiency bounds

This paper suggests a method for obtaining efficiency bounds in models containing either only infinite-dimensional parameters or both finite- and infinite-dimensional parameters (semiparametric models). The method is based on a theory of random linear functionals applied to the gradient of the log-likelihood functional and is illustrated by computing the lower bound for Cox's regression model

Improved predictive mapping of indoor radon concentrations using ensemble regression trees based on automatic clustering of geological units.

PURPOSE: According to estimations around 230 people die as a result of radon exposure in Switzerland. This public health concern makes reliable indoor radon prediction and mapping methods necessary in order to improve risk communication to the public. The aim of this study was to develop an automated method to classify lithological units according to their radon characteristics and to develop mapping and predictive tools in order to improve local radon prediction. METHOD: About 240 000 indoor radon concentration (IRC) measurements in about 150 000 buildings were available for our analysis. The automated classification of lithological units was based on k-medoids clustering via pair-wise Kolmogorov distances between IRC distributions of lithological units. For IRC mapping and prediction we used random forests and Bayesian additive regression trees (BART). RESULTS: The automated classification groups lithological units well in terms of their IRC characteristics. Especially the IRC differences in metamorphic rocks like gneiss are well revealed by this method. The maps produced by random forests soundly represent the regional difference of IRCs in Switzerland and improve the spatial detail compared to existing approaches. We could explain 33% of the variations in IRC data with random forests. Additionally, the influence of a variable evaluated by random forests shows that building characteristics are less important predictors for IRCs than spatial/geological influences. BART could explain 29% of IRC variability and produced maps that indicate the prediction uncertainty. CONCLUSION: Ensemble regression trees are a powerful tool to model and understand the multidimensional influences on IRCs. Automatic clustering of lithological units complements this method by facilitating the interpretation of radon properties of rock types. This study provides an important element for radon risk communication. Future approaches should consider taking into account further variables like soil gas radon measurements as well as more detailed geological information.

Testing the Random Walk Hypothesis on the Baltic Stock Markets

The purpose of the thesis is to analyze whether the returns of general stock market indices of Estonia, Latvia and Lithuania follow the random walk hypothesis (RWH), and in addition, whether they are consistent with the weak-form efficiency criterion. Also the existence of the day-of-the-week anomaly is examined in the same regional markets. The data consists of daily closing quotes of the OMX Tallinn, Riga and Vilnius total return indices for the sample period from January 3, 2000 to August 28, 2009. Moreover, the full sample period is also divided into two sub-periods. The RWH is tested by applying three quantitative methods (i.e. the Augmented Dickey-Fuller unit root test, serial correlation test and non-parametric runs test). Ordinary Least Squares (OLS) regression with dummy variables is employed to detect the day-of-the-week anomalies. The random walk hypothesis (RWH) is rejected in the Estonian and Lithuanian stock markets. The Latvian stock market exhibits more efficient behaviour, although some evidence of inefficiency is also found, mostly during the first sub-period from 2000 to 2004. Day-of-the-week anomalies are detected on every stock market examined, though no longer during the later sub-period.

Automated, adaptive methods for forest inventory

Forest inventories are used to estimate forest characteristics and the condition of forest for many different applications: operational tree logging for forest industry, forest health state estimation, carbon balance estimation, land-cover and land use analysis in order to avoid forest degradation etc. Recent inventory methods are strongly based on remote sensing data combined with field sample measurements, which are used to define estimates covering the whole area of interest. Remote sensing data from satellites, aerial photographs or aerial laser scannings are used, depending on the scale of inventory. To be applicable in operational use, forest inventory methods need to be easily adjusted to local conditions of the study area at hand. All the data handling and parameter tuning should be objective and automated as much as possible. The methods also need to be robust when applied to different forest types. Since there generally are no extensive direct physical models connecting the remote sensing data from different sources to the forest parameters that are estimated, mathematical estimation models are of "black-box" type, connecting the independent auxiliary data to dependent response data with linear or nonlinear arbitrary models. To avoid redundant complexity and over-fitting of the model, which is based on up to hundreds of possibly collinear variables extracted from the auxiliary data, variable selection is needed. To connect the auxiliary data to the inventory parameters that are estimated, field work must be performed. In larger study areas with dense forests, field work is expensive, and should therefore be minimized. To get cost-efficient inventories, field work could partly be replaced with information from formerly measured sites, databases. The work in this thesis is devoted to the development of automated, adaptive computation methods for aerial forest inventory. The mathematical model parameter definition steps are automated, and the cost-efficiency is improved by setting up a procedure that utilizes databases in the estimation of new area characteristics.

Litter fall production and decomposition in a fragment of secondary Atlantic Forest of São Paulo, sp, southeastern Brazil

Litter fall consists of all organic material deposited on the forest floor, being of extremely important for the structure and maintenance of the ecosystem through nutrient cycling. This study aimed to evaluate the production and decomposition of litter fall in a secondary Atlantic forest fragment of secondary Atlantic Forest, at the Guarapiranga Ecological Park, in São Paulo, SP. The litter samples were taken monthly from May 2012 to May 2013. To assess the contribution of litter fall forty collectors were installed randomly within an area of 0.5 ha. The collected material was sent to the laboratory to be dried at 65 °C for 72 hours, being subsequently separated into fractions of leaves, twigs, reproductive parts and miscellaneous, and weighed to obtain the dry biomass. Litterbags were placed and tied close to the collectors to estimate the decomposition rate in order to evaluate the loss of dry biomass at 30, 60, 90, 120 and 150 days. After collection, the material was sent to the laboratory to be dried and weighed again. Total litter fall throughout the year reached 5.7 Mg.ha-1.yr-1 and the major amount of the material was collected from September till March. Leaves had the major contribution for total litter fall (72%), followed by twigs (14%), reproductive parts (11%) and miscellaneous (3%). Reproductive parts had a peak during the wet season. Positive correlation was observed between total litter and precipitation, temperature and radiation (r = 0.66, p<0.05; r = 0.76, p<0.05; r = 0.58, p<0.05, respectively). The multiple regression showed that precipitation and radiation contributed significantly to litter fall production. Decomposition rate was in the interval expected for secondary tropical forest and was correlated to rainfall. It was concluded that this fragment of secondary forest showed a seasonality effect driven mainly by precipitation and radiation, both important components of foliage renewal for the plant community and that decomposition was in an intermediate rate.

NATURAL DURABILITY OF Eucalyptus dunnii Maiden, Eucalyptus robusta Sm., Eucalyptus tereticornis Sm. AND Hovenia dulcis Thunb. WOOD IN FIELD AND FOREST ENVIRONMENT

AB STRACT This study aimed at evaluating the natural durability of Eucalyptus dunnii, Eucalyptus robusta, Eucalyptus tereticornis and Hovenia dulcis woods submitted to a deterioration test in two environments, field and forest. The test samples were buried until half of their length (150 mm). Evaluations were carried out each 45 days, totalizing a 405-day period, with three-repetition withdrawal of each species for environment, totalizing nine samples from each environment, making up 24 test samples for evaluation. After percentage calculations of mass loss and resistance degree classification, the deterioration index was adopted for decomposition evaluation and fungal decay potential determination of test samples. The study has been carried out in completely randomized design (CRD), evaluated through analysis of variance (ANOVA) with subsequent comparison of means by Turkey' s test, in a 5%-level of probability of error, along with regression analysis. Eucalyptus tereticornis wood presented lesser mass loss in both environments. Hovenia dulcis presented lesser deterioration probability in both environments. Forest environment test samples presented greater mass loss percentages and lesser deterioration index.

Forest cover and its change in Unguja Island, Zanzibar

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.

The investigation of edge effects within ragmented forest islands in Short Hills Provincial Park

It has been well documented, within the field of landscape ecology, that terrestrial fragmentation contributes to increased heterogeneity at the landscape level. It has also been observed that elevated areas of edge habitat occur within fragmented landscapes. Spatial and temporal edge effects were investigated in four areas designated as Nature Reserve Zones within Short Hills Provincial Park, near St. Catharines, Ontario. Random sampling along exposed edges was performed on trees and saplings, at 5 and 25 ill edge depths, using the point-centred quarter method. Diameter at breast height (dbh) and distance from point measurements were used to establish relative density, dominance, frequency and importance value. One-way analyses of variance were used on dbh measurements of tree species and Chi-Square contingency tables were used on size class distributions of saplings species to determine significant differences between 5 and 25 metres. Qualitative comparisons of importance values were also used to determine differences between 5 and 25 metres as well as between trees and saplings. These statistical and qualitative comparisons suggest that a significant overall spatial edge effect is currently exhibited by fragmented wooded islands within the park. The major species of the park, Acersaccharuln, may be exhibiting a temporal edge effect. The heterogeneous nature of the park may be of importance in understanding this area as a complex, ecological system. It is possible that the remaining forest tracts of the park have been affected, and continue to be affected by previous disturbances. Based on these findings, recommendations are made to the Ontario Ministry of Natural Resources concerning the management of Short Hills Provincial Park in accordance with their 1990 proposed Management Plan.

Transaction costs of farmers’ participation in forest management: Policy implications of payments for environmental services schemes in Vietnam

Recent research on payments for environmental services (PES) has observed that high transaction costs (TCs) are incurred through the implementation of PES schemes and farmer participation. TCs incurred by households are considered to be an obstacle to the participation in and efficiency of PES policies. This study aims to understand transactions related to previous forest plantation programmes and to estimate the actual TCs incurred by farmers who participated in these programmes in a mountainous area of northwestern Vietnam. In addition, this study examines determinants of households’ TCs to test the hypothesis of whether the amount of TCs varies according to household characteristics. Results show that average TCs are not likely to be a constraint for participation since they are about 200,000 VND (USD 10) per household per contract, which is equivalent to one person’s average earnings for about two days of labour. However, TCs amount to more than one-third of the programmes’ benefits, which is relatively high compared to PES programmes in developed countries. This implies that rather than aiming to reduce TCs, an appropriate agenda for policy improvement is to balance the level of TCs with PES programme benefits to enhance the overall attractiveness of afforestation programmes for smallholder farmers. Regression analysis reveals that education, gender and perception towards PES programmes have significant effects on the magnitude of TCs. The analyses also points out the importance of local conditions on the level of TCs, with some unexpected results.

On the Noise Model of Support Vector Machine Regression

Support Vector Machines Regression (SVMR) is a regression technique which has been recently introduced by V. Vapnik and his collaborators (Vapnik, 1995; Vapnik, Golowich and Smola, 1996). In SVMR the goodness of fit is measured not by the usual quadratic loss function (the mean square error), but by a different loss function called Vapnik"s $epsilon$- insensitive loss function, which is similar to the "robust" loss functions introduced by Huber (Huber, 1981). The quadratic loss function is well justified under the assumption of Gaussian additive noise. However, the noise model underlying the choice of Vapnik's loss function is less clear. In this paper the use of Vapnik's loss function is shown to be equivalent to a model of additive and Gaussian noise, where the variance and mean of the Gaussian are random variables. The probability distributions for the variance and mean will be stated explicitly. While this work is presented in the framework of SVMR, it can be extended to justify non-quadratic loss functions in any Maximum Likelihood or Maximum A Posteriori approach. It applies not only to Vapnik's loss function, but to a much broader class of loss functions.

Short-term Response of Breeding Barred Owls to Forestry in a Boreal Mixedwood Forest Landscape

Forestry and other activities are increasing in the boreal mixedwood of Alberta, with a concomitant decrease in older forest. The Barred Owl (Strix varia) is an old-growth indicator species in some jurisdictions in North America. Hence, we radio-tagged Barred Owls in boreal mixedwood in Alberta to determine whether harvesting influenced habitat selection. We used three spatial scales: nest sites, i.e., nest tree and adjacent area of 11.7 m radius around nests, nesting territory of 1000 m radius around nests, and home range locations within 2000 m radius of the home range center. Barred Owls nested primarily in balsam poplar (Populus balsamifera) snags > 34 cm dbh and nest trees were surrounded by large, > 34 cm dbh, balsam poplar trees and snags. Nesting territories contained a variety of habitats including young < 80-yr-old, deciduous-dominated stands, old deciduous and coniferous-dominated stands, treed bogs, and recent clear-cuts. However, when compared to available habitat in the study area, they were more likely to contain old conifer-dominated stands and recent cutblocks. We assumed this is because all of the recent harvest occurred in old stands, habitat preferred by the owls. When compared with random sites, locations used for foraging and roosting at the home range scale were more likely to be in young deciduous-dominated stands, old conifer-dominated stands and cutblocks > 30 yr old, and less likely to occur in old deciduous-dominated stands and recent cutblocks. Hence, although recent clearcuts occurred in territories, birds avoided these microhabitats during foraging. To meet the breeding requirements of Barred Owls in managed forests, 10–20 ha patches of old deciduous and mixedwood forest containing large Populus snags or trees should be maintained. In our study area, nest trees had a minimum dbh of 34 cm. Although cut areas were incorporated into home ranges, the amount logged was low, i.e., 7%, in our area. Hence more research is required to determine harvest levels tolerated by owls over the long term.

Patch Scale Nest-Site Selection by Marbled Murrelets (Brachyramphus marmoratus)

The Marbled Murrelet (Brachyramphus marmoratus) is a threatened alcid that nests almost exclusively in old-growth forests along the Pacific coast of North America. Nesting habitat has significant economic importance. Murrelet nests are extremely difficult and costly to find, which adds uncertainty to management and conservation planning. Models based on air photo interpretation of forest cover maps or assessments by low-level helicopter flights are currently used to rank presumed Marbled Murrelet nesting habitat quality in British Columbia. These rankings are assumed to correlate with nest usage and murrelet breeding productivity. Our goal was to find the models that best predict Marbled Murrelet nesting habitat in the ground-accessible portion of the two regions studied. We generated Resource Selection Functions (RSF) using logistic regression models of ground-based forest stand variables gathered at plots around 64 nests, located using radio-telemetry, versus 82 random habitat plots. The RSF scores are proportional to the probability of nests occurring in a forest patch. The best models differed somewhat between the two regions, but include both ground variables at the patch scale (0.2-2.0 ha), such as platform tree density, height and trunk diameter of canopy trees and canopy complexity, and landscape scale variables such as elevation, aspect, and slope. Collecting ground-based habitat selection data would not be cost-effective for widespread use in forestry management; air photo interpretation and low-level aerial surveys are much more efficient methods for ranking habitat suitability on a landscape scale. This study provides one method for ground-truthing the remote methods, an essential step made possible using the numerical RSF scores generated herein.

Sampling the soil in long-term forest plots: The implications of spatial variation

Long-term monitoring of forest soils as part of a pan-European network to detect environmental change depends on an accurate determination of the mean of the soil properties at each monitoring event. Forest soil is known to be very variable spatially, however. A study was undertaken to explore and quantify this variability at three forest monitoring plots in Britain. Detailed soil sampling was carried out, and the data from the chemical analyses were analysed by classical statistics and geostatistics. An analysis of variance showed that there were no consistent effects from the sample sites in relation to the position of the trees. The variogram analysis showed that there was spatial dependence at each site for several variables and some varied in an apparently periodic way. An optimal sampling analysis based on the multivariate variogram for each site suggested that a bulked sample from 36 cores would reduce error to an acceptable level. Future sampling should be designed so that it neither targets nor avoids trees and disturbed ground. This can be achieved best by using a stratified random sampling design.

Genetic diversity and structure of natural and managed populations of Cedrus atlantica (Pinaceae) assessed using random amplified polymorphic DNA

Cedrus atlantica (Pinaceae) is a large and exceptionally long-lived conifer native to the Rif and Atlas Mountains of North Africa. To assess levels and patterns of genetic diversity of this species. samples were obtained throughout the natural range in Morocco and from a forest plantation in Arbucies, Girona (Spain) and analyzed using RAPD markers. Within-population genetic diversity was high and comparable to that revealed by isozymes. Managed populations harbored levels of genetic variation similar to those found in their natural counterparts. Genotypic analyses Of Molecular variance (AMOVA) found that most variation was within populations. but significant differentiation was also found between populations. particularly in Morocco. Bayesian estimates of F,, corroborated the AMOVA partitioning and provided evidence for Population differentiation in C. atlantica. Both distance- and Bayesian-based Clustering methods revealed that Moroccan populations comprise two genetically distinct groups. Within each group, estimates of population differentiation were close to those previously reported in other gymnosperms. These results are interpreted in the context of the postglacial history of the species and human impact. The high degree of among-group differentiation recorded here highlights the need for additional conservation measures for some Moroccan Populations of C. atlantica.