39 resultados para Spatially


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"The functional organization of auditory cortex (AC) is still poorly understood. Previous studies suggest segregation of auditory processing streams for spatial and nonspatial information located in the posterior and anterior AC, respectively (Rauschecker and Tian, 2000; Arnott et al., 2004; Lomber and Malhotra, 2008). Furthermore, previous studies have shown that active listening tasks strongly modulate AC activations (Petkov et al., 2004; Fritz et al., 2005; Polley et al., 2006). However, the task dependence of AC activations has not been systematically investigated. In the present study, we applied high-resolution functional magnetic resonance imaging of the AC and adjacent areas to compare activations during pitch discrimination and n-back pitch memory tasks that were varied parametrically in difficulty. We found that anterior AC activations were increased during discrimination but not during memory tasks, while activations in the inferior parietal lobule posterior to the AC were enhanced during memory tasks but not during discrimination. We also found that wide areas of the anterior AC and anterior insula were strongly deactivated during the pitch memory tasks. While these results are consistent with the proposition that the anterior and posterior AC belong to functionally separate auditory processing streams, our results show that this division is present also between tasks using spatially invariant sounds. Together, our results indicate that activations of human AC are strongly dependent on the characteristics of the behavioral task."

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Herbivorous insects, their host plants and natural enemies form the largest and most species-rich communities on earth. But what forces structure such communities? Do they represent random collections of species, or are they assembled by given rules? To address these questions, food webs offer excellent tools. As a result of their versatile information content, such webs have become the focus of intensive research over the last few decades. In this thesis, I study herbivore-parasitoid food webs from a new perspective: I construct multiple, quantitative food webs in a spatially explicit setting, at two different scales. Focusing on food webs consisting of specialist herbivores and their natural enemies on the pedunculate oak, Quercus robur, I examine consistency in food web structure across space and time, and how landscape context affects this structure. As an important methodological development, I use DNA barcoding to resolve potential cryptic species in the food webs, and to examine their effect on food web structure. I find that DNA barcoding changes our perception of species identity for as many as a third of the individuals, by reducing misidentifications and by resolving several cryptic species. In terms of the variation detected in food web structure, I find surprising consistency in both space and time. From a spatial perspective, landscape context leaves no detectable imprint on food web structure, while species richness declines significantly with decreasing connectivity. From a temporal perspective, food web structure remains predictable from year to year, despite considerable species turnover in local communities. The rate of such turnover varies between guilds and species within guilds. The factors best explaining these observations are abundant and common species, which have a quantitatively dominant imprint on overall structure, and suffer the lowest turnover. By contrast, rare species with little impact on food web structure exhibit the highest turnover rates. These patterns reveal important limitations of modern metrics of quantitative food web structure. While they accurately describe the overall topology of the web and its most significant interactions, they are disproportionately affected by species with given traits, and insensitive to the specific identity of species. As rare species have been shown to be important for food web stability, metrics depicting quantitative food web structure should then not be used as the sole descriptors of communities in a changing world. To detect and resolve the versatile imprint of global environmental change, one should rather use these metrics as one tool among several.

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Topics in Spatial Econometrics — With Applications to House Prices Spatial effects in data occur when geographical closeness of observations influences the relation between the observations. When two points on a map are close to each other, the observed values on a variable at those points tend to be similar. The further away the two points are from each other, the less similar the observed values tend to be. Recent technical developments, geographical information systems (GIS) and global positioning systems (GPS) have brought about a renewed interest in spatial matters. For instance, it is possible to observe the exact location of an observation and combine it with other characteristics. Spatial econometrics integrates spatial aspects into econometric models and analysis. The thesis concentrates mainly on methodological issues, but the findings are illustrated by empirical studies on house price data. The thesis consists of an introductory chapter and four essays. The introductory chapter presents an overview of topics and problems in spatial econometrics. It discusses spatial effects, spatial weights matrices, especially k-nearest neighbours weights matrices, and various spatial econometric models, as well as estimation methods and inference. Further, the problem of omitted variables, a few computational and empirical aspects, the bootstrap procedure and the spatial J-test are presented. In addition, a discussion on hedonic house price models is included. In the first essay a comparison is made between spatial econometrics and time series analysis. By restricting the attention to unilateral spatial autoregressive processes, it is shown that a unilateral spatial autoregression, which enjoys similar properties as an autoregression with time series, can be defined. By an empirical study on house price data the second essay shows that it is possible to form coordinate-based, spatially autoregressive variables, which are at least to some extent able to replace the spatial structure in a spatial econometric model. In the third essay a strategy for specifying a k-nearest neighbours weights matrix by applying the spatial J-test is suggested, studied and demonstrated. In the final fourth essay the properties of the asymptotic spatial J-test are further examined. A simulation study shows that the spatial J-test can be used for distinguishing between general spatial models with different k-nearest neighbours weights matrices. A bootstrap spatial J-test is suggested to correct the size of the asymptotic test in small samples.

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Sea level rise is among the most worrying consequences of climate change, and the biggest uncertainty of sea level predictions lies in the future behaviour of the ice sheets of Greenland and Antarctica. In this work, a literature review is made concerning the future of the Greenland ice sheet and the effect of its melting on Baltic Sea level. The relation between sea level and ice sheets is also considered more generally from a theoretical and historical point of view. Lately, surprisingly rapid changes in the amount of ice discharging into the sea have been observed along the coastal areas of the ice sheets, and the mass deficit of Greenland and West Antarctic ice sheets which are considered vulnerable to warming has been increasing from the 1990s. The changes are probably related to atmospheric or oceanic temperature variations which affect the flow speed of ice either via meltwater penetrating to the bottom of the ice sheet or via changes in the flow resistance generated by the floating parts of an ice stream. These phenomena are assumed to increase the mass deficit of the ice sheets in the warming climate; however, there is no comprehensive theory to explain and model them. Thus, it is not yet possible to make reliable predictions of the ice sheet contribution to sea level rise. On the grounds of the historical evidence it appears that sea level can rise rather rapidly, 1 2 metres per century, even during warm climate periods. Sea level rise projections of similar magnitude have been made with so-called semiempirical methods that are based on modelling the link between sea level and global mean temperature. Such a rapid rise would require considerable acceleration of the ice sheet flow. Stronger rise appears rather unlikely, among other things because the mountainous coastline restricts ice discharge from Greenland. The upper limit of sea level rise from Greenland alone has been estimated at half a metre by the end of this century. Due to changes in the Earth s gravity field, the sea level rise caused by melting ice is not spatially uniform. Near the melting ice sheet the sea level rise is considerably smaller than the global average, whereas farther away it is slightly greater than the average. Because of this phenomenon, the effect of the Greenland ice sheet on Baltic Sea level will probably be rather small during this century, 15 cm at most. Melting of the Antarctic ice sheet is clearly more dangerous for the Baltic Sea, but also very uncertain. It is likely that the sea level predictions will become more accurate in the near future as the ice sheet models develop.

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Habitat fragmentation produces patches of suitable habitat surrounded by unfavourable matrix habitat. A species may persist in such a fragmented landscape in an equilibrium between the extinctions and recolonizations of local populations, thus forming a metapopulation. Migration between local populations is necessary for the long-term persistence of a metapopulation. The Glanville fritillary butterfly (Melitaea cinxia) forms a metapopulation in the Åland islands in Finland. There is migration between the populations, the extent of which is affected by several environmental factors and variation in the phenotype of individual butterflies. Different allelic forms of the glycolytic enzyme phosphoglucose isomerase (Pgi) has been identified as a possible genetic factor influencing flight performance and migration rate in this species. The frequency of a certain Pgi allele, Pgi-f, follows the same pattern in relation to population age and connectivity as migration propensity. Furthermore, variation in flight metabolic performance, which is likely to affect migration propensity, has been linked to genetic variation in Pgi or a closely linked locus. The aim of this study was to investigate the association between Pgi genotype and the migration propensity in the Glanville fritillary both at the individual and population levels using a statistical modelling approach. A mark-release-recapture (MRR) study was conducted in a habitat patch network of M. cinxia in Åland to collect data on the movements of individual butterflies. Larval samples from the study area were also collected for population level examinations. Each butterfly and larva was genotyped at the Pgi locus. The MRR data was parameterised with two mathematical models of migration: the Virtual Migration Model (VM) and the spatially explicit diffusion model. VM model predicted and observed numbers of emigrants from populations with high and low frequencies of Pgi-f were compared. Posterior predictive data sets were simulated based on the parameters of the diffusion model. Lack-of-fit of observed values to the model predicted values of several descriptors of movements were detected, and the effect of Pgi genotype on the deviations was assessed by randomizations including the genotype information. This study revealed a possible difference in the effect of Pgi genotype on migration propensity between the two sexes in the Glanville fritillary. The females with and males without the Pgi-f allele moved more between habitat patches, which is probably related to differences in the function of flight in the two sexes. Females may use their high flight capacity to migrate between habitat patches to find suitable oviposition sites, whereas males may use it to acquire mates by keeping a territory and fighting off other intruding males, possibly causing them to emigrate. The results were consistent across different movement descriptors and at the individual and population levels. The effect of Pgi is likely to be dependent on the structure of the landscape and the prevailing environmental conditions.

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Landscape is shaped by natural environment and increasingly by human activity. In landscape ecology, the concept of landscape can be defined as a kilometre-scale mosaic formed by different land-use types. In Helsinki Metropolitan Region, the landscape change caused by urbanization has accelerated after the 1950s. Prior to that, the landscape of the region was mainly only shaped by agriculture. The goal of this study was in addition to describing the landscape change to discuss the factors impacting the landscape change and evaluate thelandscape ecological impacts of the change. Three study areas at different distances from Helsinki city centre were chosen in order to look at the landscape change. Study areas were Malmi, Espoo and Mäntsälä regions representing different parts of the urban-to-rural gradient in 1955, 1975, 1990 and 2009. Land-use of the maps was then digitized into five classes: agricultural lands, semi-natural grasslands, built areas, waters and others using GIS methods. First, landscape change was studied using landscape ecological indices. Indices used were PLAND i.e. the proportions of the different land-use types in the landscape; MPS, SHEI and SHDI which describe fragmentation and heterogeneity of the landscape; and MSI and ED which are measures of patch shape. Second, landscape change was studied statistically in relation to topography, soil and urban structure of the study areas. Indicators used concerning urban structure were number of residents, car ownership and travel-related zones of urban form which indicate the degree of urban sprawl within the study areas. For the statistical analyses, each of the 9.25 x 9.25 km sized study areas was further divided into grids with resolution of 0.25 x 0.25 kilometres. Third, the changes in the green structure of the study areas were evaluated. The landscape change reflected by the proportions of the land-use types was the most notable in Malmi area where a large amount of agricultural land was developed from 1955 to 2009. The proportion of semi-natural grasslands also showed an interesting pattern in relation to urbanization. When urbanization started, a great number of agricultural lands were abandoned and turned into semi-natural grasslands but as the urbanization accelerated, the number of semi-natural grasslands started to decline because of urban densification. Landscape fragmentation and heterogeneity were the most widespread in Espoo study area which is not only because of the great differences in relative heights within the region but also its location in the rural-urban fringe. According to the results, urbanization induced agricultural lands to be more regular in shape both spatially and temporally whereas for built areas and semi-natural grasslands the impact of urbanization was reverse. Changes in landscape were the most insignificant in the most rural study area Mäntsälä. In Mäntsälä, built area per resident showed the greatest values indicating a widespread urban sprawl. The values were the smallest in highly urbanized Malmi study area. Unlike other study areas, in Mäntsälä the proportion of developing land in the ecologically disadvantageous cardependent zone was on the increase. On the other hand, the green structure of the Mäntsälä study area was the most advantageous whereas Malmi study area showed the most ecologically disadvantageous structure. Considering all the landscape ecological criteria used, the landscape structure of Espoo study area proved to be the best not least because of the great heterogeneity of its landscape. Thus the study confirmed the previous results according to which landscape heterogeneity is the most significant in areas exposed to a moderate human impact.

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We present a laser-based system to measure the refractive index of air over a long path length. In optical distance measurements it is essential to know the refractive index of air with high accuracy. Commonly, the refractive index of air is calculated from the properties of the ambient air using either Ciddor or Edlén equations, where the dominant uncertainty component is in most cases the air temperature. The method developed in this work utilises direct absorption spectroscopy of oxygen to measure the average temperature of air and of water vapor to measure relative humidity. The method allows measurement of temperature and humidity over the same beam path as in optical distance measurement, providing spatially well matching data. Indoor and outdoor measurements demonstrate the effectiveness of the method. In particular, we demonstrate an effective compensation of the refractive index of air in an interferometric length measurement at a time-variant and spatially non-homogenous temperature over a long time period. Further, we were able to demonstrate 7 mK RMS noise over a 67 m path length using 120 s sample time. To our knowledge, this is the best temperature precision reported for a spectroscopic temperature measurement.

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In lake-rich regions, the gathering of information about water quality is challenging because only a small proportion of the lakes can be assessed each year by conventional methods. One of the techniques for improving the spatial and temporal representativeness of lake monitoring is remote sensing from satellites and aircrafts. The experimental material included detailed optical measurements in 11 lakes, air- and spaceborne remote sensing measurements with concurrent field sampling, automatic raft measurements and a national dataset of routine water quality measurements from over 1100 lakes. The analyses of the spatially high-resolution airborne remote sensing data from eutrophic and mesotrophic lakes showed that one or a few discrete water quality observations using conventional monitoring can yield a clear over- or underestimation of the overall water quality in a lake. The use of TM-type satellite instruments in addition to routine monitoring results substantially increases the number of lakes for which water quality information can be obtained. The preliminary results indicated that coloured dissolved organic matter (CDOM) can be estimated with TM-type satellite instruments, which could possibly be utilised as an aid in estimating the role of lakes in global carbon budgets. Based on the results of reflectance modelling and experimental data, MERIS satellite instrument has optimal or near-optimal channels for the estimation of turbidity, chlorophyll a and CDOM in Finnish lakes. MERIS images with a 300 m spatial resolution can provide water quality information in different parts of large and medium-sized lakes, and in filling in the gaps resulting from conventional monitoring. Algorithms that would not require simultaneous field data for algorithm training would increase the amount of remote sensing-based information available for lake monitoring. The MERIS Boreal Lakes processor, trained with the optical data and concentration ranges provided by this study, enabled turbidity estimations with good accuracy without the need for algorithm correction with field measurements, while chlorophyll a and CDOM estimations require further development of the processor. The accuracy of interpreting chlorophyll a via semi empirical algorithms can be improved by classifying lakes prior to interpretation according to their CDOM level and trophic status. Optical modelling indicated that the spectral diffuse attenuation coefficient can be estimated with reasonable accuracy from the measured water quality concentrations. This provides more detailed information on light attenuation from routine monitoring measurements than is available through the Secchi disk transparency. The results of this study improve the interpretation of lake water quality by remote sensing and encourage the use of remote sensing in lake monitoring.

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Periglacial processes act on cold, non-glacial regions where the landscape deveploment is mainly controlled by frost activity. Circa 25 percent of Earth's surface can be considered as periglacial. Geographical Information System combined with advanced statistical modeling methods, provides an efficient tool and new theoretical perspective for study of cold environments. The aim of this study was to: 1) model and predict the abundance of periglacial phenomena in subarctic environment with statistical modeling, 2) investigate the most import factors affecting the occurence of these phenomena with hierarchical partitioning, 3) compare two widely used statistical modeling methods: Generalized Linear Models and Generalized Additive Models, 4) study modeling resolution's effect on prediction and 5) study how spatially continous prediction can be obtained from point data. The observational data of this study consist of 369 points that were collected during the summers of 2009 and 2010 at the study area in Kilpisjärvi northern Lapland. The periglacial phenomena of interest were cryoturbations, slope processes, weathering, deflation, nivation and fluvial processes. The features were modeled using Generalized Linear Models (GLM) and Generalized Additive Models (GAM) based on Poisson-errors. The abundance of periglacial features were predicted based on these models to a spatial grid with a resolution of one hectare. The most important environmental factors were examined with hierarchical partitioning. The effect of modeling resolution was investigated with in a small independent study area with a spatial resolution of 0,01 hectare. The models explained 45-70 % of the occurence of periglacial phenomena. When spatial variables were added to the models the amount of explained deviance was considerably higher, which signalled a geographical trend structure. The ability of the models to predict periglacial phenomena were assessed with independent evaluation data. Spearman's correlation varied 0,258 - 0,754 between the observed and predicted values. Based on explained deviance, and the results of hierarchical partitioning, the most important environmental variables were mean altitude, vegetation and mean slope angle. The effect of modeling resolution was clear, too coarse resolution caused a loss of information, while finer resolution brought out more localized variation. The models ability to explain and predict periglacial phenomena in the study area were mostly good and moderate respectively. Differences between modeling methods were small, although the explained deviance was higher with GLM-models than GAMs. In turn, GAMs produced more realistic spatial predictions. The single most important environmental variable controlling the occurence of periglacial phenomena was mean altitude, which had strong correlations with many other explanatory variables. The ongoing global warming will have great impact especially in cold environments on high latitudes, and for this reason, an important research topic in the near future will be the response of periglacial environments to a warming climate.