Assessment of the Spatial and Temporal Distribution of Functional Connectivity in Resting-State BOLD fMRI

Recent research into resting-state functional magnetic resonance imaging (fMRI) has shown that the brain is very active during rest. This thesis work utilizes blood oxygenation level dependent (BOLD) signals to investigate the spatial and temporal functional network information found within resting-state data, and aims to investigate the feasibility of extracting functional connectivity networks using different methods as well as the dynamic variability within some of the methods. Furthermore, this work looks into producing valid networks using a sparsely-sampled sub-set of the original data.

In this work we utilize four main methods: independent component analysis (ICA), principal component analysis (PCA), correlation, and a point-processing technique. Each method comes with unique assumptions, as well as strengths and limitations into exploring how the resting state components interact in space and time.

Correlation is perhaps the simplest technique. Using this technique, resting-state patterns can be identified based on how similar the time profile is to a seed region’s time profile. However, this method requires a seed region and can only identify one resting state network at a time. This simple correlation technique is able to reproduce the resting state network using subject data from one subject’s scan session as well as with 16 subjects.

Independent component analysis, the second technique, has established software programs that can be used to implement this technique. ICA can extract multiple components from a data set in a single analysis. The disadvantage is that the resting state networks it produces are all independent of each other, making the assumption that the spatial pattern of functional connectivity is the same across all the time points. ICA is successfully able to reproduce resting state connectivity patterns for both one subject and a 16 subject concatenated data set.

Using principal component analysis, the dimensionality of the data is compressed to find the directions in which the variance of the data is most significant. This method utilizes the same basic matrix math as ICA with a few important differences that will be outlined later in this text. Using this method, sometimes different functional connectivity patterns are identifiable but with a large amount of noise and variability.

To begin to investigate the dynamics of the functional connectivity, the correlation technique is used to compare the first and second halves of a scan session. Minor differences are discernable between the correlation results of the scan session halves. Further, a sliding window technique is implemented to study the correlation coefficients through different sizes of correlation windows throughout time. From this technique it is apparent that the correlation level with the seed region is not static throughout the scan length.

The last method introduced, a point processing method, is one of the more novel techniques because it does not require analysis of the continuous time points. Here, network information is extracted based on brief occurrences of high or low amplitude signals within a seed region. Because point processing utilizes less time points from the data, the statistical power of the results is lower. There are also larger variations in DMN patterns between subjects. In addition to boosted computational efficiency, the benefit of using a point-process method is that the patterns produced for different seed regions do not have to be independent of one another.

This work compares four unique methods of identifying functional connectivity patterns. ICA is a technique that is currently used by many scientists studying functional connectivity patterns. The PCA technique is not optimal for the level of noise and the distribution of the data sets. The correlation technique is simple and obtains good results, however a seed region is needed and the method assumes that the DMN regions is correlated throughout the entire scan. Looking at the more dynamic aspects of correlation changing patterns of correlation were evident. The last point-processing method produces a promising results of identifying functional connectivity networks using only low and high amplitude BOLD signals.

Grain size distribution and sea level changes in Gåsfjärden fjord

We analysed long-term variations in grain-size distribution in sediments from Gåsfjärden, a fjord-like inlet on the south-west Baltic Sea, and explored potential drivers of the recorded changes in sediment grain-size data. Over the last 5.4 thousand years (ka), the relative sea level decreased 17 m in the study region, caused by isostatic land uplift. As a consequence, Gåsfjärden has been transformed from an open coastal setting into a semi-closed inlet surrounded on the east by numerous small islands. To quantitatively estimate the morphological changes in Gåsfjärden over the last 5.4 ka and to further link the changes to our grain-size data, a digital elevation model (DEM)-based openness index was calculated. In the period between 5.4 and 4.4 ka BP, the inlet was characterised by the largest openness index. During this interval, the highest sand contents (~0.4 %) and silt/clay ratios (~0. 3) in the sediment sequence were recorded, indicating relatively high bottom water energy. After 4.4 ka BP, the average sand content was halved to ~0.2 % and the silt/clay ratios showed a significant decreasing trend over the last 4 ka. These changes are found to be associated with the gradual embayment of Gåsfjärden as represented in the openness index. The silt/clay ratios exhibited a delayed and slower change compared with the sand contents, which further suggest that finer particles are less sensitive to changes in hydrodynamic energy. Our DEM-based coastal openness index has proved to be a useful tool for interpreting the sedimentary grain-size record.

Tourism in Albarracín and Region. Local Public Action and dynamics in recent key sustainable tourism development

Spanish tourist destinations in rural areas have been established over more than two decades of implementation of various public policy instruments (mainly tourism and rural development policies). These convey complementary objectives in theory but provoke distant results in practice. The intervention of these instruments produces in the region of Sierra de Albarracín (Teruel) two types of destination whose sustainability is committed: the historical urban site of Albarracín as a consolidated cultural tourism destination based on heritage and the Sierra as a generic and incipient destination of rural tourism. It is discussed how the deployment of the local public action causes a fragmented territory in two models of management and tourism development. Cooperation is presented as a key element for the necessary rethinking of tourism development in the region.

Nonlinear Dynamics Near the Cell Membrane of Chara Corallina

The phenomenon of patterned distribution of pH near the cell membrane of the algae Chara corallina upon illumination is well-known. In this paper, we develop a mathematical model, based on the detailed kinetic analysis of proton fluxes across the cell membrane, to explain this phenomenon. The model yields two coupled nonlinear partial differential equations which describe the spatial dynamics of proton concentration changes and transmembrane potential generation. The experimental observation of pH pattern formation, its period and amplitude of oscillation, and also its hysteresis in response to changing illumination, are all reproduced by our model. A comparison of experimental results and predictions of our theory is made. Finally, a mechanism for pattern formation in Chara corallina is proposed.

DYNAMICS OF THE SHORT TERM AND LONG TERM AVIAN DISTRIBUTIONS IN NORTH AMERICA - THE ROLES OF VEGETATION HEIGHT HETEROGENEITY AND CLIMATIC FACTORS

Understanding how biodiversity spatially distribute over both the short term and long term, and what factors are affecting the distribution, are critical for modeling the spatial pattern of biodiversity as well as for promoting effective conservation planning and practices. This dissertation aims to examine factors that influence short-term and long-term avian distribution from the geographical sciences perspective. The research develops landscape level habitat metrics to characterize forest height heterogeneity and examines their efficacies in modelling avian richness at the continental scale. Two types of novel vegetation-height-structured habitat metrics are created based on second order texture algorithms and the concepts of patch-based habitat metrics. I correlate the height-structured metrics with the richness of different forest guilds, and also examine their efficacies in multivariate richness models. The results suggest that height heterogeneity, beyond canopy height alone, supplements habitat characterization and richness models of two forest bird guilds. The metrics and models derived in this study demonstrate practical examples of utilizing three-dimensional vegetation data for improved characterization of spatial patterns in species richness. The second and the third projects focus on analyzing centroids of avian distributions, and testing hypotheses regarding the direction and speed of these shifts. I first showcase the usefulness of centroids analysis for characterizing the distribution changes of a few case study species. Applying the centroid method on 57 permanent resident bird species, I show that multi-directional distribution shifts occurred in large number of studied species. I also demonstrate, plain birds are not shifting their distribution faster than mountain birds, contrary to the prediction based on climate change velocity hypothesis. By modelling the abundance change rate at regional level, I show that extreme climate events and precipitation measures associate closely with some of the long-term distribution shifts. This dissertation improves our understanding on bird habitat characterization for species richness modelling, and expands our knowledge on how avian populations shifted their ranges in North America responding to changing environments in the past four decades. The results provide an important scientific foundation for more accurate predictive species distribution modeling in future.

Effect of soil structure on temporal and spatial dynamics of bacteria

Soil is a complex heterogeneous system comprising of highly variable and dynamic micro-habitats that have significant impacts on the growth and activity of resident microbiota. A question addressed in this research is how soil structure affects the temporal dynamics and spatial distribution of bacteria. Using repacked microcosms, the effect of bulk-density, aggregate sizes and water content on growth and distribution of introduced Pseudomonas fluorescens and Bacillus subtilis bacteria was determined. Soil bulk-density and aggregate sizes were altered to manipulate the characteristics of the pore volume where bacteria reside and through which distribution of solutes and nutrients is controlled. X-ray CT was used to characterise the pore geometry of repacked soil microcosms. Soil porosity, connectivity and soil-pore interface area declined with increasing bulk-density. In samples that differ in pore geometry, its effect on growth and extent of spread of introduced bacteria was investigated. The growth rate of bacteria reduced with increasing bulk-density, consistent with a significant difference in pore geometry. To measure the ability of bacteria to spread thorough soil, placement experiments were developed. Bacteria were capable of spreading several cm’s through soil. The extent of spread of bacteria was faster and further in soil with larger and better connected pore volumes. To study the spatial distribution in detail, a methodology was developed where a combination of X-ray microtopography, to characterize the soil structure, and fluorescence microscopy, to visualize and quantify bacteria in soil sections was used. The influence of pore characteristics on distribution of bacteria was analysed at macro- and microscales. Soil porosity, connectivity and soil-pore interface influenced bacterial distribution only at the macroscale. The method developed was applied to investigate the effect of soil pore characteristics on the extent of spread of bacteria introduced locally towards a C source in soil. Soil-pore interface influenced spread of bacteria and colonization, therefore higher bacterial densities were found in soil with higher pore volumes. Therefore the results in this showed that pore geometry affects the growth and spread of bacteria in soil. The method developed showed showed how thin sectioning technique can be combined with 3D X-ray CT to visualize bacterial colonization of a 3D pore volume. This novel combination of methods is a significant step towards a full mechanistic understanding of microbial dynamics in structured soils.

Lifetime and distribution of ozone and related pollutants in the eastern United States

Most major cities in the eastern United States have air quality deemed unhealthy by the EPA under a set of regulations known as the National Ambient Air Quality Standards (NAAQS). The worst air quality in Maryland is measured in Edgewood, MD, a small community located along the Chesapeake Bay and generally downwind of Baltimore during hot, summertime days. Direct measurements and numerical simulations were used to investigate how meteorology and chemistry conspire to create adverse levels of photochemical smog especially at this coastal location. Ozone (O3) and oxidized reactive nitrogen (NOy), a family of ozone precursors, were measured over the Chesapeake Bay during a ten day experiment in July 2011 to better understand the formation of ozone over the Bay and its impact on coastal communities such as Edgewood. Ozone over the Bay during the afternoon was 10% to 20% higher than the closest upwind ground sites. A combination of complex boundary layer dynamics, deposition rates, and unaccounted marine emissions play an integral role in the regional maximum of ozone over the Bay. The CAMx regional air quality model was assessed and enhanced through comparison with data from NASA’s 2011 DISCOVER-AQ field campaign. Comparisons show a model overestimate of NOy by +86.2% and a model underestimate of formaldehyde (HCHO) by –28.3%. I present a revised model framework that better captures these observations and the response of ozone to reductions of precursor emissions. Incremental controls on electricity generating stations will produce greater benefits for surface ozone while additional controls on mobile sources may yield less benefit because cars emit less pollution than expected. Model results also indicate that as ozone concentrations improve with decreasing anthropogenic emissions, the photochemical lifetime of tropospheric ozone increases. The lifetime of ozone lengthens because the two primary gas-phase sinks for odd oxygen (Ox ≈ NO2 + O3) – attack by hydroperoxyl radicals (HO2) on ozone and formation of nitrate – weaken with decreasing pollutant emissions. This unintended consequence of air quality regulation causes pollutants to persist longer in the atmosphere, and indicates that pollutant transport between states and countries will likely play a greater role in the future.

Ecological drivers of a vector borne pathogen: distribution and abundance of Borrelia burgdorferi sensu lato and its vector Ixodes ricinus in Scotland

Vector-borne disease emergence in recent decades has been associated with different environmental drivers including changes in habitat, hosts and climate. Lyme borreliosis is among the most important vector-borne diseases in the Northern hemisphere and is an emerging disease in Scotland. Transmitted by Ixodid tick vectors between large numbers of wild vertebrate host species, Lyme borreliosis is caused by bacteria from the Borrelia burgdorferi sensu lato species group. Ecological studies can inform how environmental factors such as host abundance and community composition, habitat and landscape heterogeneity contribute to spatial and temporal variation in risk from B. burgdorferi s.l. In this thesis a range of approaches were used to investigate the effects of vertebrate host communities and individual host species as drivers of B. burgdorferi s.l. dynamics and its tick vector Ixodes ricinus. Host species differ in reservoir competence for B. burgdorferi s.l. and as hosts for ticks. Deer are incompetent transmission hosts for B. burgdorferi s.l. but are significant hosts of all life-stages of I. ricinus. Rodents and birds are important transmission hosts of B. burgdorferi s.l. and common hosts of immature life-stages of I. ricinus. In this thesis, surveys of woodland sites revealed variable effects of deer density on B. burgdorferi prevalence, from no effect (Chapter 2) to a possible ‘dilution’ effect resulting in lower prevalence at higher deer densities (Chapter 3). An invasive species in Scotland, the grey squirrel (Sciurus carolinensis), was found to host diverse genotypes of B. burgdorferi s.l. and may act as a spill-over host for strains maintained by native host species (Chapter 4). Habitat fragmentation may alter the dynamics of B. burgdorferi s.l. via effects on the host community and host movements. In this thesis, there was lack of persistence of the rodent associated genospecies of B. burgdorferi s.l. within a naturally fragmented landscape (Chapter 3). Rodent host biology, particularly population cycles and dispersal ability are likely to affect pathogen persistence and recolonization in fragmented habitats. Heterogeneity in disease dynamics can occur spatially and temporally due to differences in the host community, habitat and climatic factors. Higher numbers of I. ricinus nymphs, and a higher probability of detecting a nymph infected with B. burgdorferi s.l., were found in areas with warmer climates estimated by growing degree days (Chapter 2). The ground vegetation type associated with the highest number of I. ricinus nymphs varied between studies in this thesis (Chapter 2 & 3) and does not appear to be a reliable predictor across large areas. B. burgdorferi s.l. prevalence and genospecies composition was highly variable for the same sites sampled in subsequent years (Chapter 2). This suggests that dynamic variables such as reservoir host densities and deer should be measured as well as more static habitat and climatic factors to understand the drivers of B. burgdorferi s.l. infection in ticks. Heterogeneity in parasite loads amongst hosts is a common finding which has implications for disease ecology and management. Using a 17-year data set for tick infestations in a wild bird community in Scotland, different effects of age and sex on tick burdens were found among four species of passerine bird (Chapter 5). There were also different rates of decline in tick burdens among bird species in response to a long term decrease in questing tick pressure over the study. Species specific patterns may be driven by differences in behaviour and immunity and highlight the importance of comparative approaches. Combining whole genome sequencing (WGS) and population genetics approaches offers a novel approach to identify ecological drivers of pathogen populations. An initial analysis of WGS from B. burgdorferi s.s. isolates sampled 16 years apart suggests that there is a signal of measurable evolution (Chapter 6). This suggests demographic analyses may be applied to understand ecological and evolutionary processes of these bacteria. This work shows how host communities, habitat and climatic factors can affect the local transmission dynamics of B. burgdorferi s.l. and the potential risk of infection to humans. Spatial and temporal heterogeneity in pathogen dynamics poses challenges for the prediction of risk. New tools such as WGS of the pathogen (Chapter 6) and blood meal analysis techniques will add power to future studies on the ecology and evolution of B. burgdorferi s.l.

The interplay between tectonics, sediment dynamics and gateways evolution in the Danube system from the Pannonian Basin to the western Black Sea

Understanding the natural evolution of a river–delta–sea system is important to develop a strong scientific basis for efficient integrated management plans. The distribution of sediment fluxes is linked with the natural connection between sediment source areas situated in uplifting mountain chains and deposition in plains, deltas and, ultimately, in the capturing oceans and seas. The Danube River–western Black Sea is one of the most active European systems in terms of sediment re-distribution that poses significant societal challenges. We aim to derive the tectonic and sedimentological background of human-induced changes in this system and discuss their interplay. This is obtained by analysing the tectonic and associated vertical movements, the evolution of relevant basins and the key events affecting sediment routing and deposition. The analysis of the main source and sink areas is focused in particular on the Miocene evolution of the Carpatho-Balkanides, Dinarides and their sedimentary basins including the western Black Sea. The vertical movements of mountains chains created the main moments of basin connectivity observed in the Danube system. Their timing and effects are observed in sediments deposited in the vicinity of gateways, such as the transition between the Pannonian/Transylvanian and Dacian basins and between the Dacian Basin and western Black Sea. The results demonstrate the importance of understanding threshold conditions driving rapid basins connectivity changes superposed over the longer time scale of tectonic-induced vertical movements associated with background erosion and sedimentation. The spatial and temporal scale of such processes is contrastingly different and challenging. The long-term patterns interact with recent or anthropogenic induced modifications in the natural system and may result in rapid changes at threshold conditions that can be quantified and predicted. Their understanding is critical because of frequent occurrence during orogenic evolution, as commonly observed in the Mediterranean area and discussed elsewhere.

Hydrothermal-vent alvinellid polychaete dispersal in the eastern Pacific .1. Influence of vent site distribution, bottom currents, and biological patterns

Deep-sea hydrothermal-vent habitats are typically linear, discontinuous, and short-lived. Some of the vent fauna such as the endemic polychaete family Alvinellidae are thought to lack a planktotrophic larval stage and therefore not to broadcast-release their offspring. The genetic evidence points to exchanges on a scale that seems to contradict this type of reproductive pattern. However, the rift valley may topographically rectify the bottom currents, thereby facilitating the dispersal of propagules between active vent sites separated in some cases by 10s of kilometers or more along the ridge axis. A propagule flux model based on a matrix of intersite distances, long-term current-meter data, and information on the biology and ecology of Alvinellidae was developed to test this hypothesis. Calculations of the number of migrants exchanged between two populations per generation (N-m) allowed comparisons with estimates obtained from genetic studies. N, displays a logarithmic decrease with increasing dispersal duration and reaches the critical value of 1 after 8 d when the propagule Aux model was run in standard conditions. At most, propagule traveling time cannot reasonably exceed 15-30 d, according to the model, whereas reported distances between sites would require longer lasting dispersal abilities. Two nonexclusive explanations are proposed. First, some aspects of the biology of Alvinellidae have been overlooked and long-distance dispersal does occur. Second, such dispersal never occurs in Alvinellidae, but the spatial-temporal dynamics of vent sites over geological timescales allows short-range dispersal processes to maintain gene flow.

Essays on Uncertainty, Imperfect Information, and Investment Dynamics

Understanding how imperfect information affects firms' investment decision helps answer important questions in economics, such as how we may better measure economic uncertainty; how firms' forecasts would affect their decision-making when their beliefs are not backed by economic fundamentals; and how important are the business cycle impacts of changes in firms' productivity uncertainty in an environment of incomplete information. This dissertation provides a synthetic answer to all these questions, both empirically and theoretically. The first chapter, provides empirical evidence to demonstrate that survey-based forecast dispersion identifies a distinctive type of second moment shocks different from the canonical volatility shocks to productivity, i.e. uncertainty shocks. Such forecast disagreement disturbances can affect the distribution of firm-level beliefs regardless of whether or not belief changes are backed by changes in economic fundamentals. At the aggregate level, innovations that increase the dispersion of firms' forecasts lead to persistent declines in aggregate investment and output, which are followed by a slow recovery. On the contrary, the larger dispersion of future firm-specific productivity innovations, the standard way to measure economic uncertainty, delivers the ``wait and see" effect, such that aggregate investment experiences a sharp decline, followed by a quick rebound, and then overshoots. At the firm level, data uncovers that more productive firms increase investments given rises in productivity dispersion for the future, whereas investments drop when firms disagree more about the well-being of their future business conditions. These findings challenge the view that the dispersion of the firms' heterogeneous beliefs captures the concept of economic uncertainty, defined by a model of uncertainty shocks. The second chapter presents a general equilibrium model of heterogeneous firms subject to the real productivity uncertainty shocks and informational disagreement shocks. As firms cannot perfectly disentangle aggregate from idiosyncratic productivity because of imperfect information, information quality thus drives the wedge of difference between the unobserved productivity fundamentals, and the firms' beliefs about how productive they are. Distribution of the firms' beliefs is no longer perfectly aligned with the distribution of firm-level productivity across firms. This model not only explains why, at the macro and micro level, disagreement shocks are different from uncertainty shocks, as documented in Chapter 1, but helps reconcile a key challenge faced by the standard framework to study economic uncertainty: a trade-off between sizable business cycle effects due to changes in uncertainty, and the right amount of pro-cyclicality of firm-level investment rate dispersion, as measured by its correlation with the output cycles.

Rare sex or out of reach equilibrium? The dynamics of F-IS in partially clonal organisms

Background: Partially clonal organisms are very common in nature, yet the influence of partial asexuality on the temporal dynamics of genetic diversity remains poorly understood. Mathematical models accounting for clonality predict deviations only for extremely rare sex and only towards mean inbreeding coefficient (F-IS) over bar < 0. Yet in partially clonal species, both F-IS < 0 and F-IS > 0 are frequently observed also in populations where there is evidence for a significant amount of sexual reproduction. Here, we studied the joint effects of partial clonality, mutation and genetic drift with a state-and-time discrete Markov chain model to describe the dynamics of F-IS over time under increasing rates of clonality. Results: Results of the mathematical model and simulations show that partial clonality slows down the asymptotic convergence to F-IS = 0. Thus, although clonality alone does not lead to departures from Hardy-Weinberg expectations once reached the final equilibrium state, both negative and positive F-IS values can arise transiently even at intermediate rates of clonality. More importantly, such "transient" departures from Hardy Weinberg proportions may last long as clonality tunes up the temporal variation of F-IS and reduces its rate of change over time, leading to a hyperbolic increase of the maximal time needed to reach the final mean (F-IS,F-infinity) over bar value expected at equilibrium. Conclusion: Our results argue for a dynamical interpretation of F-IS in clonal populations. Negative values cannot be interpreted as unequivocal evidence for extremely scarce sex but also as intermediate rates of clonality in finite populations. Complementary observations (e.g. frequency distribution of multiloci genotypes, population history) or time series data may help to discriminate between different possible conclusions on the extent of clonality when mean (F-IS) over bar values deviating from zero and/or a large variation of F-IS over loci are observed.

PHYSICAL FACTORS IN B CELL ACTIN DYNAMICS AND ACTIVATION

Cells adapt to their changing world by sensing environmental cues and responding appropriately. This is made possible by complex cascades of biochemical signals that originate at the cell membrane. In the last decade it has become apparent that the origin of these signals can also arise from physical cues in the environment. Our motivation is to investigate the role of physical factors in the cellular response of the B lymphocyte. B cells patrol the body for signs of invading pathogens in the form of antigen on the surface of antigen presenting cells. Binding of antigen with surface proteins initiates biochemical signaling essential to the immune response. Once contact is made, the B cell spreads on the surface of the antigen presenting cell in order to gather as much antigen as possible. The physical mechanisms that govern this process are unexplored. In this research, we examine the role of the physical parameters of antigen mobility and cell surface topography on B cell spreading and activation. Both physical parameters are biologically relevant as immunogens for vaccine design, which can provide laterally mobile and immobile antigens and topographical surfaces. Another physical parameter that influences B cell response and the formation of the cell-cell junction is surface topography. This is biologically relevant as antigen presenting cells have highly convoluted membranes, resulting in variable topography. We found that B cell activation required the formation of antigen-receptor clusters and their translocation within the attachment plane. We showed that cells which failed to achieve these mobile clusters due to prohibited ligand mobility were much less activation competent. To investigate the effect of topography, we use nano- and micro-patterned substrates, on which B cells were allowed to spread and become activated. We found that B cell spreading, actin dynamics, B cell receptor distribution and calcium signaling are dependent on the topographical patterning of the substrate. A quantitative understanding of cellular response to physical parameters is essential to uncover the fundamental mechanisms that drive B cell activation. The results of this research are highly applicable to the field of vaccine development and therapies for autoimmune diseases. Our studies of the physical aspects of lymphocyte activation will reveal the role these factors play in immunity, thus enabling their optimization for biological function and potentially enabling the production of more effective vaccines.

Estimating abundance and spatial distribution patterns of the bubble crab Dotilla fenestrata (Crustacea : Brachyura)

The bubble crab Dotilla fenestrata forms very dense populations on the sand flats of the eastern coast of Inhaca Island, Mozambique, making it an interesting biological model to examine spatial distribution patterns and test the relative efficiency of common sampling methods. Due to its apparent ecological importance within the sandy intertidal community, understanding the factors ruling the dynamics of Dotilla populations is also a key issue. In this study, different techniques of estimating crab density are described, and the trends of spatial distribution of the different population categories are shown. The studied populations are arranged in discrete patches located at the well-drained crests of nearly parallel mega sand ripples. For a given sample size, there was an obvious gain in precision by using a stratified random sampling technique, considering discrete patches as strata, compared to the simple random design. Density average and variance differed considerably among patches since juveniles and ovigerous females were found clumped, with higher densities at the lower and upper shore levels, respectively. Burrow counting was found to be an adequate method for large-scale sampling, although consistently underestimating actual crab density by nearly half. Regression analyses suggested that crabs smaller than 2.9 mm carapace width tend to be undetected in visual burrow counts. A visual survey of sampling plots over several patches of a large Dotilla population showed that crab density varied in an interesting oscillating pattern, apparently following the topography of the sand flat. Patches extending to the lower shore contained higher densities than those mostly covering the higher shore. Within-patch density variability also pointed to the same trend, but the density increment towards the lowest shore level varied greatly among the patches compared.