Improved cerebellar tissue classification on magnetic resonance images of brain.

PURPOSE: To develop and implement a method for improved cerebellar tissue classification on the MRI of brain by automatically isolating the cerebellum prior to segmentation. MATERIALS AND METHODS: Dual fast spin echo (FSE) and fluid attenuation inversion recovery (FLAIR) images were acquired on 18 normal volunteers on a 3 T Philips scanner. The cerebellum was isolated from the rest of the brain using a symmetric inverse consistent nonlinear registration of individual brain with the parcellated template. The cerebellum was then separated by masking the anatomical image with individual FLAIR images. Tissues in both the cerebellum and rest of the brain were separately classified using hidden Markov random field (HMRF), a parametric method, and then combined to obtain tissue classification of the whole brain. The proposed method for tissue classification on real MR brain images was evaluated subjectively by two experts. The segmentation results on Brainweb images with varying noise and intensity nonuniformity levels were quantitatively compared with the ground truth by computing the Dice similarity indices. RESULTS: The proposed method significantly improved the cerebellar tissue classification on all normal volunteers included in this study without compromising the classification in remaining part of the brain. The average similarity indices for gray matter (GM) and white matter (WM) in the cerebellum are 89.81 (+/-2.34) and 93.04 (+/-2.41), demonstrating excellent performance of the proposed methodology. CONCLUSION: The proposed method significantly improved tissue classification in the cerebellum. The GM was overestimated when segmentation was performed on the whole brain as a single object.

Induction of root-resistance by leaf-herbivory follows a vertical gradient

Leaf-herbivory can lead to systemic changes in root metabolism and resistance. As yet, it is unknown if these changes affect the whole root system, or if they are more pronounced in the upper root parts, which are closer to the actual site of attack. As this spatial aspect may be an important determinant of the interactions that can be expected to occur within the rhizosphere, we investigated if leaf-herbivore induced root resistance differs between upper and lower roots of maize. We also tested if the density of leaf-herbivores correlates with intensity of the root response. The systemic increase in resistance was found to be more pronounced in the upper than the lower roots and was independent of leaf herbivore density. The results suggest that there is a vertical gradient in the strength of the root response following leaf-herbivory, and that soil organisms living closer to the surface may be more affected by leaf-attack than the ones living in deeper soil layers.

Verification of intensity modulated stereotactic radiotherapy using Monte Carlo calculations and EPID dosimetry

The purpose of this work was to develop a comprehensive IMSRT QA procedure that examined, using EPID dosimetry and Monte Carlo (MC) calculations, each step in the treatment planning and delivery process. These steps included verification of the field shaping, treatment planning system (RTPS) dose calculations, and patient dose delivery. Verification of each step in the treatment process is assumed to result in correct dose delivery to the patient. ^ The accelerator MC model was verified against commissioning data for field sizes from 0.8 × 0.8 cm 2 to 10 × 10 cm 2. Depth doses were within 2% local percent difference (LPD) in low gradient regions and 1 mm distance to agreement (DTA) in high gradient regions. Lateral profiles were within 2% LPD in low gradient regions and 1 mm DTA in high gradient regions. Calculated output factors were within 1% of measurement for field sizes ≥1 × 1 cm2. ^ The measured and calculated pretreatment EPID dose patterns were compared using criteria of 5% LPD, 1 mm DTA, or 2% of central axis pixel value with ≥95% of compared points required to pass for successful verification. Pretreatment field verification resulted in 97% percent of the points passing. ^ The RTPS and Monte Carlo phantom dose calculations were compared using 5% LPD, 2 mm DTA, or 2% of the maximum dose with ≥95% of compared points required passing for successful verification. RTPS calculation verification resulted in 97% percent of the points passing. ^ The measured and calculated EPID exit dose patterns were compared using criteria of 5% LPD, 1 mm DTA, or 2% of central axis pixel value with ≥95% of compared points required to pass for successful verification. Exit dose verification resulted in 97% percent of the points passing. ^ Each of the processes above verified an individual step in the treatment planning and delivery process. The combination of these verification steps ensures accurate treatment delivery to the patient. This work shows that Monte Carlo calculations and EPID dosimetry can be used to quantitatively verify IMSRT treatments resulting in improved patient care and, potentially, improved clinical outcome. ^

Statistical Machine Learning for Automatic Assessment of Physical Activity Intensity Using Multi-axial Accelerometry and Heart Rate

This work explores the automatic recognition of physical activity intensity patterns from multi-axial accelerometry and heart rate signals. Data collection was carried out in free-living conditions and in three controlled gymnasium circuits, for a total amount of 179.80 h of data divided into: sedentary situations (65.5%), light-to-moderate activity (17.6%) and vigorous exercise (16.9%). The proposed machine learning algorithms comprise the following steps: time-domain feature definition, standardization and PCA projection, unsupervised clustering (by k-means and GMM) and a HMM to account for long-term temporal trends. Performance was evaluated by 30 runs of a 10-fold cross-validation. Both k-means and GMM-based approaches yielded high overall accuracy (86.97% and 85.03%, respectively) and, given the imbalance of the dataset, meritorious F-measures (up to 77.88%) for non-sedentary cases. Classification errors tended to be concentrated around transients, what constrains their practical impact. Hence, we consider our proposal to be suitable for 24 h-based monitoring of physical activity in ambulatory scenarios and a first step towards intensity-specific energy expenditure estimators

Frequency and Intensity of drought events over Ebro River basin.

Lately, several researchers have pointed out that climate change is expected to increase temperatures and lower rainfall in Mediterranean regions, simultaneously increasing the intensity of extreme rainfall events. These changes could have consequences regarding rainfall regime, erosion, sediment transport and water quality, soil management, and new designs in diversion ditches. Climate change is expected to result in increasingly unpredictable and variable rainfall, in amount and timing, changing seasonal patterns and increasing the frequency of extreme weather events. Consequently, the evolution of frequency and intensity of drought periods is of most important as in agro-ecosystems many processes will be affected by them. Realising the complex and important consequences of an increasing frequency of extreme droughts at the Ebro River basin, our aim is to study the evolution of drought events at this site statistically, with emphasis on the occurrence and intensity of them. For this purpose, fourteen meteorological stations were selected based on the length of the rainfall series and the climatic classification to obtain a representative untreated dataset from the river basin. Daily rainfall series from 1957 to 2002 were obtained from each meteorological station and no-rain period frequency as the consecutive numbers of days were extracted. Based on this data, we study changes in the probability distribution in several sub-periods. Moreover we used the Standardized Precipitation Index (SPI) for identification of drought events in a year scale and then we use this index to fit log-linear models to the contingency tables between the SPI index and the sub-periods, this adjusted is carried out with the help of ANOVA inference.

HOG-Like gradient-based descriptor for visual vehicle detection

One of the main challenges for intelligent vehicles is the capability of detecting other vehicles in their environment, which constitute the main source of accidents. Specifically, many methods have been proposed in the literature for video-based vehicle detection. Most of them perform supervised classification using some appearance-related feature, in particular, symmetry has been extensively utilized. However, an in-depth analysis of the classification power of this feature is missing. As a first contribution of this paper, a thorough study of the classification performance of symmetry is presented within a Bayesian decision framework. This study reveals that the performance of symmetry-based classification is very limited. Therefore, as a second contribution, a new gradient-based descriptor is proposed for vehicle detection. This descriptor exploits the known rectangular structure of vehicle rears within a Histogram of Gradients (HOG)-based framework. Experiments show that the proposed descriptor outperforms largely symmetry as a feature for vehicle verification, achieving classification rates over 90%.

Sea Bottom Classification by Means of Bathymetric LIDAR Data

Light Detection and Ranging (LIDAR) provides high horizontal and vertical resolution of spatial data located in point cloud images, and is increasingly being used in a number of applications and disciplines, which have concentrated on the exploit and manipulation of the data using mainly its three dimensional nature. Bathymetric LIDAR systems and data are mainly focused to map depths in shallow and clear waters with a high degree of accuracy. Additionally, the backscattering produced by the different materials distributed over the bottom surface causes that the returned intensity signal contains important information about the reflection properties of these materials. Processing conveniently these values using a Simplified Radiative Transfer Model, allows the identification of different sea bottom types. This paper presents an original method for the classification of sea bottom by means of information processing extracted from the images generated through LIDAR data. The results are validated using a vector database containing benthic information derived by marine surveys.

Automated detection and classification of brain injury lesions on structural magnetic resonance imaging

El daño cerebral adquirido (DCA) es un problema social y sanitario grave, de magnitud creciente y de una gran complejidad diagnóstica y terapéutica. Su elevada incidencia, junto con el aumento de la supervivencia de los pacientes, una vez superada la fase aguda, lo convierten también en un problema de alta prevalencia. En concreto, según la Organización Mundial de la Salud (OMS) el DCA estará entre las 10 causas más comunes de discapacidad en el año 2020. La neurorrehabilitación permite mejorar el déficit tanto cognitivo como funcional y aumentar la autonomía de las personas con DCA. Con la incorporación de nuevas soluciones tecnológicas al proceso de neurorrehabilitación se pretende alcanzar un nuevo paradigma donde se puedan diseñar tratamientos que sean intensivos, personalizados, monitorizados y basados en la evidencia. Ya que son estas cuatro características las que aseguran que los tratamientos son eficaces. A diferencia de la mayor parte de las disciplinas médicas, no existen asociaciones de síntomas y signos de la alteración cognitiva que faciliten la orientación terapéutica. Actualmente, los tratamientos de neurorrehabilitación se diseñan en base a los resultados obtenidos en una batería de evaluación neuropsicológica que evalúa el nivel de afectación de cada una de las funciones cognitivas (memoria, atención, funciones ejecutivas, etc.). La línea de investigación en la que se enmarca este trabajo de investigación pretende diseñar y desarrollar un perfil cognitivo basado no sólo en el resultado obtenido en esa batería de test, sino también en información teórica que engloba tanto estructuras anatómicas como relaciones funcionales e información anatómica obtenida de los estudios de imagen. De esta forma, el perfil cognitivo utilizado para diseñar los tratamientos integra información personalizada y basada en la evidencia. Las técnicas de neuroimagen representan una herramienta fundamental en la identificación de lesiones para la generación de estos perfiles cognitivos. La aproximación clásica utilizada en la identificación de lesiones consiste en delinear manualmente regiones anatómicas cerebrales. Esta aproximación presenta diversos problemas relacionados con inconsistencias de criterio entre distintos clínicos, reproducibilidad y tiempo. Por tanto, la automatización de este procedimiento es fundamental para asegurar una extracción objetiva de información. La delineación automática de regiones anatómicas se realiza mediante el registro tanto contra atlas como contra otros estudios de imagen de distintos sujetos. Sin embargo, los cambios patológicos asociados al DCA están siempre asociados a anormalidades de intensidad y/o cambios en la localización de las estructuras. Este hecho provoca que los algoritmos de registro tradicionales basados en intensidad no funcionen correctamente y requieran la intervención del clínico para seleccionar ciertos puntos (que en esta tesis hemos denominado puntos singulares). Además estos algoritmos tampoco permiten que se produzcan deformaciones grandes deslocalizadas. Hecho que también puede ocurrir ante la presencia de lesiones provocadas por un accidente cerebrovascular (ACV) o un traumatismo craneoencefálico (TCE). Esta tesis se centra en el diseño, desarrollo e implementación de una metodología para la detección automática de estructuras lesionadas que integra algoritmos cuyo objetivo principal es generar resultados que puedan ser reproducibles y objetivos. Esta metodología se divide en cuatro etapas: pre-procesado, identificación de puntos singulares, registro y detección de lesiones. Los trabajos y resultados alcanzados en esta tesis son los siguientes: Pre-procesado. En esta primera etapa el objetivo es homogeneizar todos los datos de entrada con el objetivo de poder extraer conclusiones válidas de los resultados obtenidos. Esta etapa, por tanto, tiene un gran impacto en los resultados finales. Se compone de tres operaciones: eliminación del cráneo, normalización en intensidad y normalización espacial. Identificación de puntos singulares. El objetivo de esta etapa es automatizar la identificación de puntos anatómicos (puntos singulares). Esta etapa equivale a la identificación manual de puntos anatómicos por parte del clínico, permitiendo: identificar un mayor número de puntos lo que se traduce en mayor información; eliminar el factor asociado a la variabilidad inter-sujeto, por tanto, los resultados son reproducibles y objetivos; y elimina el tiempo invertido en el marcado manual de puntos. Este trabajo de investigación propone un algoritmo de identificación de puntos singulares (descriptor) basado en una solución multi-detector y que contiene información multi-paramétrica: espacial y asociada a la intensidad. Este algoritmo ha sido contrastado con otros algoritmos similares encontrados en el estado del arte. Registro. En esta etapa se pretenden poner en concordancia espacial dos estudios de imagen de sujetos/pacientes distintos. El algoritmo propuesto en este trabajo de investigación está basado en descriptores y su principal objetivo es el cálculo de un campo vectorial que permita introducir deformaciones deslocalizadas en la imagen (en distintas regiones de la imagen) y tan grandes como indique el vector de deformación asociado. El algoritmo propuesto ha sido comparado con otros algoritmos de registro utilizados en aplicaciones de neuroimagen que se utilizan con estudios de sujetos control. Los resultados obtenidos son prometedores y representan un nuevo contexto para la identificación automática de estructuras. Identificación de lesiones. En esta última etapa se identifican aquellas estructuras cuyas características asociadas a la localización espacial y al área o volumen han sido modificadas con respecto a una situación de normalidad. Para ello se realiza un estudio estadístico del atlas que se vaya a utilizar y se establecen los parámetros estadísticos de normalidad asociados a la localización y al área. En función de las estructuras delineadas en el atlas, se podrán identificar más o menos estructuras anatómicas, siendo nuestra metodología independiente del atlas seleccionado. En general, esta tesis doctoral corrobora las hipótesis de investigación postuladas relativas a la identificación automática de lesiones utilizando estudios de imagen médica estructural, concretamente estudios de resonancia magnética. Basándose en estos cimientos, se han abrir nuevos campos de investigación que contribuyan a la mejora en la detección de lesiones. ABSTRACT Brain injury constitutes a serious social and health problem of increasing magnitude and of great diagnostic and therapeutic complexity. Its high incidence and survival rate, after the initial critical phases, makes it a prevalent problem that needs to be addressed. In particular, according to the World Health Organization (WHO), brain injury will be among the 10 most common causes of disability by 2020. Neurorehabilitation improves both cognitive and functional deficits and increases the autonomy of brain injury patients. The incorporation of new technologies to the neurorehabilitation tries to reach a new paradigm focused on designing intensive, personalized, monitored and evidence-based treatments. Since these four characteristics ensure the effectivity of treatments. Contrary to most medical disciplines, it is not possible to link symptoms and cognitive disorder syndromes, to assist the therapist. Currently, neurorehabilitation treatments are planned considering the results obtained from a neuropsychological assessment battery, which evaluates the functional impairment of each cognitive function (memory, attention, executive functions, etc.). The research line, on which this PhD falls under, aims to design and develop a cognitive profile based not only on the results obtained in the assessment battery, but also on theoretical information that includes both anatomical structures and functional relationships and anatomical information obtained from medical imaging studies, such as magnetic resonance. Therefore, the cognitive profile used to design these treatments integrates information personalized and evidence-based. Neuroimaging techniques represent an essential tool to identify lesions and generate this type of cognitive dysfunctional profiles. Manual delineation of brain anatomical regions is the classical approach to identify brain anatomical regions. Manual approaches present several problems related to inconsistencies across different clinicians, time and repeatability. Automated delineation is done by registering brains to one another or to a template. However, when imaging studies contain lesions, there are several intensity abnormalities and location alterations that reduce the performance of most of the registration algorithms based on intensity parameters. Thus, specialists may have to manually interact with imaging studies to select landmarks (called singular points in this PhD) or identify regions of interest. These two solutions have the same inconvenient than manual approaches, mentioned before. Moreover, these registration algorithms do not allow large and distributed deformations. This type of deformations may also appear when a stroke or a traumatic brain injury (TBI) occur. This PhD is focused on the design, development and implementation of a new methodology to automatically identify lesions in anatomical structures. This methodology integrates algorithms whose main objective is to generate objective and reproducible results. It is divided into four stages: pre-processing, singular points identification, registration and lesion detection. Pre-processing stage. In this first stage, the aim is to standardize all input data in order to be able to draw valid conclusions from the results. Therefore, this stage has a direct impact on the final results. It consists of three steps: skull-stripping, spatial and intensity normalization. Singular points identification. This stage aims to automatize the identification of anatomical points (singular points). It involves the manual identification of anatomical points by the clinician. This automatic identification allows to identify a greater number of points which results in more information; to remove the factor associated to inter-subject variability and thus, the results are reproducible and objective; and to eliminate the time spent on manual marking. This PhD proposed an algorithm to automatically identify singular points (descriptor) based on a multi-detector approach. This algorithm contains multi-parametric (spatial and intensity) information. This algorithm has been compared with other similar algorithms found on the state of the art. Registration. The goal of this stage is to put in spatial correspondence two imaging studies of different subjects/patients. The algorithm proposed in this PhD is based on descriptors. Its main objective is to compute a vector field to introduce distributed deformations (changes in different imaging regions), as large as the deformation vector indicates. The proposed algorithm has been compared with other registration algorithms used on different neuroimaging applications which are used with control subjects. The obtained results are promising and they represent a new context for the automatic identification of anatomical structures. Lesion identification. This final stage aims to identify those anatomical structures whose characteristics associated to spatial location and area or volume has been modified with respect to a normal state. A statistical study of the atlas to be used is performed to establish which are the statistical parameters associated to the normal state. The anatomical structures that may be identified depend on the selected anatomical structures identified on the atlas. The proposed methodology is independent from the selected atlas. Overall, this PhD corroborates the investigated research hypotheses regarding the automatic identification of lesions based on structural medical imaging studies (resonance magnetic studies). Based on these foundations, new research fields to improve the automatic identification of lesions in brain injury can be proposed.

Remote Sensing of Vegetation Change Across a Latitudinal Gradient in the Canadian Arctic

Global air surface temperatures and precipitation have increased over the last several decades resulting in a trend of greening across the Circumpolar Arctic. The spatial variability of warming and the inherent effects on plant communities has not proven to be uniform or homogeneous on global or local scales. We can apply remote sensing vegetation indices such as the Normalized Difference Vegetation Index (NDVI) to map and monitor vegetation change (e.g., phenology, greening, percent cover, and biomass) over time. It is important to document how Arctic vegetation is changing, as it will have large implications related to global carbon and surface energy budgets. The research reported here examined vegetation greening across different spatial and temporal scales at two disparate Arctic sites: Apex River Watershed (ARW), Baffin Island, and Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, NU. To characterize the vegetation in the ARW, high spatial resolution WorldView-2 data were processed to create a supervised land-cover classification and model percent vegetation cover (PVC) (a similar process had been completed in a previous study for the CBAWO). Meanwhile, NDVI data spanning the past 30 years were derived from intermediate resolution Landsat data at the two Arctic sites. The land-cover classifications at both sites were used to examine the Landsat NDVI time series by vegetation class. Climate variables (i.e., temperature, precipitation and growing season length (GSL) were examined to explore the potential relationships of NDVI to climate warming. PVC was successfully modeled using high resolution data in the ARW. PVC and plant communities appear to reside along a moisture and altitudinal gradient. The NDVI time series demonstrated an overall significant increase in greening at the CBAWO (High Arctic site), specifically in the dry and mesic vegetation type. However, similar overall greening was not observed for the ARW (Low Arctic site). The overall increase in NDVI at the CBAWO was attributed to a significant increase in July temperatures, precipitation and GSL.

Assessment of P availability in heavily fertilized soils using the diffusive gradient in thin films (DGT) technique

Phosphorus-availability tests typically provide an indication of quantity of P available (Colwell bicarbonate-extractable P), or of the intensity of supply (0.01 M CaCl2-extractable P). The soil's capacity to buffer P is more difficult to assess, and is generally estimated using a P-adsorption curve. The diffusive gradient in thin films (DGT) approach may provide a simpler means of assessing a soil's ability to maintain soil solution P. Optimal extraction conditions were found to be 24 h exposure of DGT samplers to saturated soil. The DGT approach was evaluated on a range of 24 soils, some of which had high Colwell- (>100 mu g g(-1)) and Bray 1- (>30 mu g g(-1)) extractable P content, but showed a tomato (Lycopersicon esculentum Mill.) yield response to the addition of P fertilizer. The DGT approach provided an excellent separation of soils on which tomato showed a yield response, from those where fertilizer P did not increase dry-matter yield. Phosphorus accumulation was strongly correlated with soil solution P concentration and anion exchange resin-extractable P, but showed poor correlation with Colwell- or Bray 1-extractable P. The DGT P accumulation rate of 3.62 x 10(-7) to 4.79 x 10(-5) mol s(-1) m(-3) for the soils tested was comparable to the uptake rate of roots of tomato plants that were adequately supplied with P (2.25 x 10(-5) mol s(-1) m(-3)).

Plasma cytokine changes in relation to exercise intensity and muscle damage

The purpose of this study was to compare the effects of exercise intensity and exercise-induced muscle damage on changes in anti-inflammatory cytokines and other inflammatory mediators. Nine well-trained male runners completed three different exercise trials on separate occasions: ( 1) level treadmill running at 60% VO2max (moderate-intensity trial) for 60 min; (2) level treadmill running at 85% VO2max (high-intensity trial) for 60 min; (3) downhill treadmill running ( - 10% gradient) at 60% VO2 max (downhill running trial) for 45 min. Blood was sampled before, immediately after and 1 h after exercise. Plasma was analyzed for interleukin-1 receptor antagonist (IL-1ra), IL-4, IL-5, IL-10, IL-12p40, IL-13, monocyte chemotactic protein-1 (MCP-1), prostaglandin E-2, leukotriene B-4 and heat shock protein 70 (HSP70). The plasma concentrations of IL-1ra, IL-12p40, MCP-1 and HSP70 increased significantly (P< 0.05) after all three trials. Plasma prostaglandin E-2 concentration increased significantly after the downhill running and high-intensity trials, while plasma IL-10 concentration increased significantly only after the high-intensity trial. IL-4 and leukotriene B4 did not increase significantly after exercise. Plasma IL-1ra and IL-10 concentrations were significantly higher ( P< 0.05) after the high-intensity trial than after both the moderate-intensity and downhill running trials. Therefore, following exercise up to 1 h duration, exercise intensity appears to have a greater effect on anti-inflammatory cytokine production than exercise-induced muscle damage.

Resonant gradient force on atom interacting with laser field

The gradient force, as a function of position and velocity, is derived for a two-level atom interacting with a standing-wave laser field. Basing on optical Bloch equations, the numerical solutions for the gradient force f_(|_;n) (n = 0, 1, 2, 3, 4, ...) pointing in the direction of the transverse of the laser beam are given. It is shown the higher order gradient force plays important role at strong intensity (G = 64), the contribution of them can not be neglected.

The structure and dynamics of saxicolous lichen communities

The saxicolous lichen vegetation on Ordovician slate rock at the mouth of the River Dovey, South Merionethshire, Wales was described in relation to several environmental variables which include aspect, slope angle, light intensity, rock porosity, rock microtopography and rock stability. Each of the measured environmental variables was shown to influence the lichen vegetation. A number of groups of species which were characteristic of certain environments were described. The data from the saxicolous lichen communities were analysed using multivariate analysis. Qualitative and quantitative data were ordinated, the qualitative data being easier to interpret ecologically, and site number (which reflects distance from the sea and altitude), rock porosity and light intensity were shown to be important environmental variables. A classification of the data was also carried out. The results of the ordination and classification were combined together and a model constructed which describes saxicolous lichen vegetation. A method which uses the model as an aid to the design and interpretation of field experiments is described. The model is applied to an experiment which investigates the effect on growth of transplanting four saxicolous lichens to different aspects. Growth was inhibited in Physcia orbicularis and Parmelia conspersa on rock surfaces of northwest aspect compared with growth on rock surfaces of southeast aspect. Growth was inhibited in Parmelia glabratula ssp. fuliginosa on rock surfaces of southeast aspect compared with rock surfaces of northwesr aspect. The growth of Parmelia saxatilis was similar at both southeast and northwesr aspects. Growth inhibition or stimulation in thalli of Physcia orbicularis, Parmelia conspersa and Parmelia glabratula ssp. fuliginosa after transplantation was consistent with the predictions of the model while the results for Parmelia saxatilis were not as expected. There was evidence that the frequency of Parmelia conspersa and Parmelia glabratula at a site is related to an effect of the environment on the growth of the thalli. There was also evidence that the frequency of Physcia orbicularis at a site is related to an effect of the environment on the establishment phase of the thalli and for the competitive exclusion of Parmelia saxatilis thalli from southeast facing rock surfaces. The distribution of lichens in relation to height on nine rock surfaces was investigated. It was suggested that the distribution of the lichens was influenced by microclimatic factors which are related to height on the rock, environmental variables which are associated with the rock substratum (e.g. rock porosity and rock microtopography) and by historical factors. The pattern of one crustose and one foliose lichen on four rock surfaces of different aspect and slope was investigated. On the vertically inclined surface the density of small thalli of Buellia aethalea and Parmelia glabratula ssp fuliginosa was correlated with the microtopography of the surface in transects horizontally across the rock surface but not in transects vertically down the rock surface. there were consitent differences in the scale and intensity of pattern horizontally and vertically and also a decrease in the intensity of pattern vertically as the slope of the rock surface decreased. These results were consistent with the suggestion of a gradient of microclimatic factors up the rock. The differences in the scale and intensity of pattern in different size classes in the population were consistent with the changes in pattern with time which have been shown to occur during succession in sand dune and salt marsh vegetation. The relationship between thallus size and height on a rock surface and between the radial growth rate and location of a thallus on a rock surface were investigated. Thalli of Parmelia glabratula ssp. fuliginosa were larger at the top of the rock surface than at the bottom and the data were consistent with the suggestion that the colonisation of the rock surface began at the top and, in time, spread downwards. The radial growth rate of the thalli could not be related to variation in slope, porosity, microtopography or directly to height on the rock but could be related to the horizontal location of the thalli on the rock. These results were consistent with the suggestion that here is a gradient of microclimatic factors across the rock surface which is also modified by height on the rock surface. The succession of lichen communities was described by relating the vegetation to rock porosity, rock microtopography, species diversity and rock stability. An initial stage dominated by crustose lichens leads to communities dominated by crustose, foliose and fruticose species. In the late stages of the succession on some rock surfaces crustose species again become dominant. The occurrence of the climax state and cyclic vegetation change in lichen communities are discussed. A mthod of estimating the age structure of a lichen population by relating thallus size to growth rate is described. The sources of error in the method are discussed in some detail and several refinements suggested to increase the accuracy of the method. The population dynamics of Parmelia glabratula ssp. fuliginosa was investigated by applying life tables to the age structures of eight different populations. The data were consistent with a period of relatively constant recruitment of thalli into the populations. Mortality in lichen populations was divided into deaths which occur after fragmentation of the thallus and deaths which occur after catastrophic environmental events. THe data suggest that the rate of fragmenting death is dependent on the age of the thallus while the rate of catastrophic death is dependent on the number of thalli established in an age class. A comparison of the numbers of thalli in each age class in the eight populations suggested that population density is controlled firstly, by climate and secondly, by variables related to the local rock surface environment. The rate of fragmenting death is related to the diversity of the community and the influence of diversity together with environmental variables in fluctuating or cyclic changes in population number.

Remote Sensing of Vegetation Change Across a Latitudinal Gradient in the Canadian Arctic

Global air surface temperatures and precipitation have increased over the last several decades resulting in a trend of greening across the Circumpolar Arctic. The spatial variability of warming and the inherent effects on plant communities has not proven to be uniform or homogeneous on global or local scales. We can apply remote sensing vegetation indices such as the Normalized Difference Vegetation Index (NDVI) to map and monitor vegetation change (e.g., phenology, greening, percent cover, and biomass) over time. It is important to document how Arctic vegetation is changing, as it will have large implications related to global carbon and surface energy budgets. The research reported here examined vegetation greening across different spatial and temporal scales at two disparate Arctic sites: Apex River Watershed (ARW), Baffin Island, and Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, NU. To characterize the vegetation in the ARW, high spatial resolution WorldView-2 data were processed to create a supervised land-cover classification and model percent vegetation cover (PVC) (a similar process had been completed in a previous study for the CBAWO). Meanwhile, NDVI data spanning the past 30 years were derived from intermediate resolution Landsat data at the two Arctic sites. The land-cover classifications at both sites were used to examine the Landsat NDVI time series by vegetation class. Climate variables (i.e., temperature, precipitation and growing season length (GSL) were examined to explore the potential relationships of NDVI to climate warming. PVC was successfully modeled using high resolution data in the ARW. PVC and plant communities appear to reside along a moisture and altitudinal gradient. The NDVI time series demonstrated an overall significant increase in greening at the CBAWO (High Arctic site), specifically in the dry and mesic vegetation type. However, similar overall greening was not observed for the ARW (Low Arctic site). The overall increase in NDVI at the CBAWO was attributed to a significant increase in July temperatures, precipitation and GSL.