European aspen and hybrid aspen under changing environment : Leaf traits, growth and litter decomposition

Understanding the responses of species and ecosystems to human-induced global environmental change has become a high research priority. The main aim of this thesis was to investigate how certain environmental factors that relate to global change affect European aspen (Populus tremula), a keystone species in boreal forests, and hybrid aspen (P. tremula × P. tremuloides), cultivated in commercial plantations. The main points under consideration were the acclimatization potential of aspen through changes in leaf morphology, as well as effects on growth, leaf litter chemistry and decomposition. The thesis is based on two experiments, in which young aspen (< 1 year) were exposed either to an atmospheric pollutant [elevated ozone (O3)] or variable resource availability [water, nitrogen (N)]; and two field studies, in which mature trees (> 8 years) were growing in environments exposed to multiple environmental stress factors (roadside and urban environments). The field studies included litter decomposition experiments. The results show that young aspen, especially the native European aspen, was sensitive to O3 in terms of visible leaf injuries. Elevated O3 resulted in reduced biomass allocation to roots and accelerated leaf senescence, suggesting negative effects on growth in the long term. Water and N availability modified the frost hardening of young aspen: High N supply, especially when combined with drought, postponed the development of frost hardiness, which in turn may predispose trees to early autumn frosts. This effect was more pronounced in European aspen. The field studies showed that mature aspen acclimatized to roadside and urban environments by producing more xeromorphic leaves. Leaf morphology was also observed to vary in response to interannual climatic variation, which further indicates the ability of aspen for phenotypic plasticity. Intraspecific variation was found in several of the traits measured, although intraspecific differences in response to the abiotic factors examined were generally small throughout the studies. However, some differences between clones were found in sensitivity to O3 and the roadside environment. Aspen leaf litter decomposition was retarded in the roadside environment, but only initially. By contrast, decomposition was found to be faster in the urban than the rural environment throughout the study. The higher quality of urban litter (higher in N, lower in lignin and phenolics), as well as higher temperature, N deposition and humus pH at the urban site were factors likely to promote decay. The phenotypic plasticity combined with intraspecific variation found in the studies imply that aspen has potential for withstanding environmental changes, although some global change factors, such as rising O3 levels, may adversely affect its performance. The results also suggest that the multiple environmental changes taking place in urban areas which correspond closely with the main drivers of global change can modify ecosystem functioning by promoting litter decomposition, mediated partly by alterations in leaf litter quality.

Vision based indoor positioning in a retail environment

Modern smart phones often come with a significant amount of computational power and an integrated digital camera making them an ideal platform for intelligents assistants. This work is restricted to retail environments, where users could be provided with for example navigational in- structions to desired products or information about special offers within their close proximity. This kind of applications usually require information about the user's current location in the domain environment, which in our case corresponds to a retail store. We propose a vision based positioning approach that recognizes products the user's mobile phone's camera is currently pointing at. The products are related to locations within the store, which enables us to locate the user by pointing the mobile phone's camera to a group of products. The first step of our method is to extract meaningful features from digital images. We use the Scale- Invariant Feature Transform SIFT algorithm, which extracts features that are highly distinctive in the sense that they can be correctly matched against a large database of features from many images. We collect a comprehensive set of images from all meaningful locations within our domain and extract the SIFT features from each of these images. As the SIFT features are of high dimensionality and thus comparing individual features is infeasible, we apply the Bags of Keypoints method which creates a generic representation, visual category, from all features extracted from images taken from a specific location. A category for an unseen image can be deduced by extracting the corresponding SIFT features and by choosing the category that best fits the extracted features. We have applied the proposed method within a Finnish supermarket. We consider grocery shelves as categories which is a sufficient level of accuracy to help users navigate or to provide useful information about nearby products. We achieve a 40% accuracy which is quite low for commercial applications while significantly outperforming the random guess baseline. Our results suggest that the accuracy of the classification could be increased with a deeper analysis on the domain and by combining existing positioning methods with ours.

Effect of GPS on understanding relationship between mobile map and environment : A field experiment

Objectives: GPS technology enables the visualisation of a map reader s location on a mobile map. Earlier research on the cognitive aspects of map reading identified that searching for map-environment points is an essential element for the process of determining one s location on a mobile map. Map-environment points refer to objects that are visualized on the map and are recognizable in the environment. However, because the GPS usually adds only one point to the map that has a relation to the environment, it does not provide a sufficient amount of information for self-location. The aim of the present thesis was to assess the effect of GPS on the cognitive processes involved in determining one s location on a map. Methods: The effect of GPS on self-location was studied in a field experiment. The subjects were shown a target on a mobile map, and they were asked to point in the direction of the target. In order for the map reader to be able to deduce the direction of the target, he/she has to locate himself/herself on the map. During the pointing tasks, the subjects were asked to think aloud. The data from the experiment were used to analyze the effect of the GPS on the time needed to perform the task. The subjects verbal data was used to assess the effect of the GPS on the number of landmark concepts mentioned during a task (landmark concepts are words referring to objects that can be recognized both on the map and in the environment). Results and conclusions: The results from the experiment indicate that the GPS reduces the time needed to locate oneself on a map. The analysis of the verbal data revealed that the GPS reduces the number of landmark concepts in the protocols. The findings suggest that the GPS guides the subject s search for the map-environment points and narrows the area on the map that must be searched for self-location.