Spatial variation in the structure and floristic composition of "restinga" vegetation in southeastern Brazil

We examined large-scale spatial variation of structural parameters and floristic composition in open Clusia scrub, a vegetation type of the Brazilian "restingas" (sandy coastal plain vegetation). This vegetation is organized in islands separated by sandy stretches with sparse herbaceous vegetation. We located 12 sample areas on three consecutive beach ridges, lying parallel to the coastline and at different distances from the ocean, in close proximity to two lagoons (Cabiúnas and Comprida). Each sample area was divided into three strips. We used the line intercept method to sample all woody plants ³ 50 cm tall. We used nested ANOVA to verify structural variation between different sampling scales. TWINSPAN analysis was performed to examine the variation in floristic composition between areas. The overall diversity index was 3.07. Six species are repeatedly dominant throughout the entire sampling area. There was homogeneity in relation to diversity and species richness between beach ridges but not within beach ridges. Floristic composition and structural parameters did not vary in relation to distance from the sea but floristic composition did vary as a function of proximity to Cabiúnas or Comprida lagoon. Differences in plant cover between sample areas may be related to the paleoformation of this sandy coastal plain.

Spatial variations at different observational scales and the seasonal distributions of stream macroalgae in a Brazilian subtropical region

We examined the relationships between environmental variations in lotic ecosystems with the seasonal dynamics of macroalgae communities at different spatial scales: drainage basin of two rivers (Rio das Pedras and Rio Marrecas), shading (open and shaded stream segments), mesohabitat (riffles and pools), and microhabitats. Data collections were made on a monthly basis between January and December/2007. A total of 16 taxa were encountered (13 species and 3 vegetative groups). All of the biotic parameters (richness, abundance, diversity, equitability, and dominance) were found to be highly variable at all of the spatial scales evaluated. On the other hand, abiotic variables demonstrated differences only at mesohabitat (in terms of current velocity) and shaded habitat (in terms of irradiance) scales. The seasonality of the macroalgae community structure was strongly influenced by microhabitat variables (current velocity, substrate H', and irradiance), demonstrating their importance over time and at different scales. Regional variables (temperature, oxygen saturation, specific conductance, pH, and turbidity) were found to have little influence on the temporal dynamics of the macroalgae communities evaluated.

Ecological distribution of stream macroalgae in different spatial scales using taxonomic and morphological groups

We examined the ecological distribution of macroalgal communities in streams using species groups (taxonomic units = algal phyla, and morphological = morphological types) with similar structures and functions instead of the species themselves. The study was conducted from June to July/2007 in two drainage basins located in mid-southern region of Paraná State , Brazil. Evaluations of macroalgal communities took into consideration the following spatial scales: the drainage basin (the Pedras river and Marrecas river basins), shading regime (open and shaded stream segments), mesohabitats (riffles and pools), and microhabitats (sampling units of 0.05m2). A total of 29 taxa (23 subgeneric, one generic, and five vegetative groups) were identified. On these, 12 taxa belong to Chlorophyta, 11 to Cyanobacteria, four to Heterokontophyta, and two to Rhodophyta. The proportions of morphological types were: 24% free filaments, 17.25% mats, tufts, gelatinous colonies, and gelatinous filaments, 7% crusts. In terms of spatial scales, we observed a predominance of Chlorophyta in open stream segments and Cyanobacteria in shaded stream segments, reflecting the loss of competitive advantage of green algae in sites with low energy availability. In the mesohabitats, the morphological types recorded in pools were predominantly poorly adapted to fast currents (free filaments), while those found in riffles (mats, tufts and gelatinous filaments) were highly resistant to fast water flows. As such, the use of species groupings based on algal taxonomy associated with morphological characteristics proved to be useful to understanding the distributions of these organisms in lotic environments.

Adaptive Markov chain Monte Carlo and Bayesian filtering for state space models

This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.

The 9-O-acetyl GD3 gangliosides are expressed by migrating chains of subventricular zone neurons in vitro

Neurons from the anterior subventricular zone (SVZ) of the cerebral cortex migrate tangentially to become interneurons in the olfactory bulb during development and in adult rodents. This migration was defined as neuronophilic, independent of a radial glial substrate. The cortical SVZ and the rostral migratory stream to the olfactory bulb were shown to be rich in 9-O-acetyl GD3 gangliosides (9-O-acGD3), which have been previously shown to be implicated in gliophilic migration in the rodent cerebral cortex and cerebellum. In the present study, we performed SVZ explant cultures using rats during their first postnatal week to analyze the expression of these gangliosides in chain migration of neuronal precursors. We characterized migrating chains of these neuroblasts through morphological analysis and immunocytochemistry for the neural cell adhesion molecule. By using the Jones monoclonal antibody which binds specifically to 9-O-acGD3 we showed that migrating chains from the SVZ explants express 9-O-acGD3 which is distributed in a punctate manner in individual cells. 9-O-acGD3 is also present in migrating chains that form in the absence of radial glia, typical of the neuronophilic chain migration of the SVZ. Our data indicate that 9-O-acetylated gangliosides may participate in neuronophilic as well as gliophilic migration.

JNK regulates dendrite and spine architecture in the central nervous system influencing spatial learning and motor tasks

JNK1 is a MAP-kinase that has proven a significant player in the central nervous system. It regulates brain development and the maintenance of dendrites and axons. Several novel phosphorylation targets of JNK1 were identified in a screen performed in the Coffey lab. These proteins were mainly involved in the regulation of neuronal cytoskeleton, influencing the dynamics and stability of microtubules and actin. These structural proteins form the dynamic backbone for the elaborate architecture of the dendritic tree of a neuron. The initiation and branching of the dendrites requires a dynamic interplay between the cytoskeletal building blocks. Both microtubules and actin are decorated by associated proteins which regulate their dynamics. The dendrite-specific, high molecular weight microtubule associated protein 2 (MAP2) is an abundant protein in the brain, the binding of which stabilizes microtubules and influences their bundling. Its expression in non-neuronal cells induces the formation of neurite-like processes from the cell body, and its function is highly regulated by phosphorylation. JNK1 was shown to phosphorylate the proline-rich domain of MAP2 in vivo in a previous study performed in the group. Here we verify three threonine residues (T1619, T1622 and T1625) as JNK1 targets, the phosphorylation of which increases the binding of MAP2 to microtubules. This binding stabilizes the microtubules and increases process formation in non-neuronal cells. Phosphorylation-site mutants were engineered in the lab. The non-phosphorylatable mutant of MAP2 (MAP2- T1619A, T1622A, T1625A) in these residues fails to bind microtubules, while the pseudo-phosphorylated form, MAP2- T1619D, T1622D, Thr1625D, efficiently binds and induces process formation even without the presence of active JNK1. Ectopic expression of the MAP2- T1619D, T1622D, Thr1625D in vivo in mouse brain led to a striking increase in the branching of cortical layer 2/3 (L2/3) pyramidal neurons, compared to MAP2-WT. The dendritic complexity defines the receptive field of a neuron and dictates the output to the postsynaptic cells. Previous studies in the group indicated altered dendrite architecture of the pyramidal neurons in the Jnk1-/- mouse motor cortex. Here, we used Lucifer Yellow loading and Sholl analysis of neurons in order to study the dendritic branching in more detail. We report a striking, opposing effect in the absence of Jnk1 in the cortical layers 2/3 and 5 of the primary motor cortex. The basal dendrites of pyramidal neurons close to the pial surface at L2/3 show a reduced complexity. In contrast, the L5 neurons, which receive massive input from the L2/3 neurons, show greatly increased branching. Another novel substrate identified for JNK1 was MARCKSL1, a protein that regulates actin dynamics. It is highly expressed in neurons, but also in various cancer tissues. Three phosphorylation target residues for JNK1 were identified, and it was demonstrated that their phosphorylation reduces actin turnover and retards migration of these cells. Actin is the main cytoskeletal component in dendritic spines, the site of most excitatory synapses in pyramidal neurons. The density and gross morphology of the Lucifer Yellow filled dendrites were characterized and we show reduced density and altered morphology of spines in the motor cortex and in the hippocampal area CA3. The dynamic dendritic spines are widely considered to function as the cellular correlate during learning. We used a Morris water maze to test spatial memory. Here, the wild-type mice outperformed the knock-out mice during the acquisition phase of the experiment indicating impaired special memory. The L5 pyramidal neurons of the motor cortex project to the spinal cord and regulate the movement of distinct muscle groups. Thus the altered dendrite morphology in the motor cortex was expected to have an effect on the input-output balance in the signaling from the cortex to the lower motor circuits. A battery of behavioral tests were conducted for the wild-type and Jnk1-/- mice, and the knock-outs performed poorly compared to wild-type mice in tests assessing balance and fine motor movements. This study expands our knowledge of JNK1 as an important regulator of the dendritic fields of neurons and their manifestations in behavior.

Sec61alpha synthesis is enhanced during translocation of nascent chains of collagen type IV in F9 teratocarcinoma cells after retinoic acid treatment

Nascent procollagen peptides and other secretory proteins are transported across the endoplasmic reticulum (ER) membrane through a protein-conducting channel called translocon. Sec61alpha, a multispanning membrane translocon protein, has been implicated as being essential for translocation of polypeptide chains into the cisterns of the ER. Sec61alpha forms a protein complex with collagen and Hsp47, an ER-resident heat shock protein that binds specifically to collagen. However, it is not known whether Sec61alpha is ubiquitously produced in collagen-producing F9 teratocarcinoma cells or under heat shock treatment. Furthermore, the production and utilization of Sec61alpha may depend on the stage of cell differentiation. Cultured F9 teratocarcinoma cells are capable of differentiation in response to low concentrations of retinoic acid. This differentiation results in loss of tumorigenicity. Mouse F9 cells were grown in culture medium at 37ºC and 43ºC (heat shock treatment) treated or not with retinoic acid, and labeled in certain instances with 35S-methionine. Membrane-bound polysomes of procollagen IV were then isolated. Immunoprecipitation and Western blot analysis were performed using polyclonal antibodies against collagen IV, Hsp47 and Sec61alpha. Under retinoic acid-untreated conditions, F9 cells produced undetectable amounts of Sec61alpha. Sec61alpha, Hsp47 and type IV collagen levels were increased after retinoic acid treatment. Heat shock treatment did not alter Sec61alpha levels, suggesting that Sec61alpha production is probably not affected by heat shock. These data indicate that the enhanced production of Sec61alpha in retinoic acid-induced F9 teratocarcinoma cells parallels the increased synthesis of Hsp47 and collagen type IV.

The modulation of simple reaction time by the spatial probability of a visual stimulus

Simple reaction time (SRT) in response to visual stimuli can be influenced by many stimulus features. The speed and accuracy with which observers respond to a visual stimulus may be improved by prior knowledge about the stimulus location, which can be obtained by manipulating the spatial probability of the stimulus. However, when higher spatial probability is achieved by holding constant the stimulus location throughout successive trials, the resulting improvement in performance can also be due to local sensory facilitation caused by the recurrent spatial location of a visual target (position priming). The main objective of the present investigation was to quantitatively evaluate the modulation of SRT by the spatial probability structure of a visual stimulus. In two experiments the volunteers had to respond as quickly as possible to the visual target presented on a computer screen by pressing an optic key with the index finger of the dominant hand. Experiment 1 (N = 14) investigated how SRT changed as a function of both the different levels of spatial probability and the subject's explicit knowledge about the precise probability structure of visual stimulation. We found a gradual decrease in SRT with increasing spatial probability of a visual target regardless of the observer's previous knowledge concerning the spatial probability of the stimulus. Error rates, below 2%, were independent of the spatial probability structure of the visual stimulus, suggesting the absence of a speed-accuracy trade-off. Experiment 2 (N = 12) examined whether changes in SRT in response to a spatially recurrent visual target might be accounted for simply by sensory and temporally local facilitation. The findings indicated that the decrease in SRT brought about by a spatially recurrent target was associated with its spatial predictability, and could not be accounted for solely in terms of sensory priming.

Evaluating land-use related environmental impacts of biomass value chains for decision-support : Comparison and testing of methodologies proposed for environmental life cycle assessment

Life cycle assessment (LCA) is one of the most established quantitative tools for environmental impact assessment of products. To be able to provide support to environmentally-aware decision makers on environmental impacts of biomass value-chains, the scope of LCA methodology needs to be augmented to cover landuse related environmental impacts. This dissertation focuses on analysing and discussing potential impact assessment methods, conceptual models and environmental indicators that have been proposed to be implemented into the LCA framework for impacts of land use. The applicability of proposed indicators and impact assessment frameworks is tested from practitioners' perspective, especially focusing on forest biomass value chains. The impacts of land use on biodiversity, resource depletion, climate change and other ecosystem services is analysed and discussed and the interplay in between value choices in LCA modelling and the decision-making situations to be supported is critically discussed. It was found out that land use impact indicators are necessary in LCA in highlighting differences in impacts from distinct land use classes. However, many open questions remain on certainty of highlighting actual impacts of land use, especially regarding impacts of managed forest land use on biodiversity and ecosystem services such as water regulation and purification. The climate impact of energy use of boreal stemwood was found to be higher in the short term and lower in the long-term in comparison with fossil fuels that emit identical amount of CO2 in combustion, due to changes implied to forest C stocks. The climate impacts of energy use of boreal stemwood were found to be higher than the previous estimates suggest on forest residues and stumps. The product lifetime was found to have much higher influence on the climate impacts of woodbased value chains than the origin of stemwood either from thinnings or final fellings. Climate neutrality seems to be likely only in the case when almost all the carbon of harvested wood is stored in long-lived wooden products. In the current form, the land use impacts cannot be modelled with a high degree of certainty nor communicated with adequate level of clarity to decision makers. The academia needs to keep on improving the modelling framework, and more importantly, clearly communicate to decision-makers the limited certainty on whether land-use intensive activities can help in meeting the strict mitigation targets we are globally facing.

Developing short sea shipping transportation chains at Helsinki-Tallinn route

Short sea shipping is an important part of the European economy and an alternative to road transport of goods in Europe. It represents an intermodal transport combination of sea and land on a Door-to-Door basis, and it aims to develop more sustainable transport network with the least negative impacts by the transport modes. This Master’s thesis addresses the development of short sea shipping transportation chains at Helsinki-Tallinn route. The Master´s thesis explores the development of short sea shipping at Helsinki-Tallinn route by analyzing the shipping costs per unit transported by different ship types and sizes between port of Helsinki-Vuosaari harbour and port of Tallinn-Muuga harbour, and examining the possibility of Ro-Ro traffic as well. The study is qualitative-quantitative method and it is based on a case study, data is collected from secondary and primary sources, and mixed methods analysis is used to implement the interviews and observations results with the databases analysis. In the thesis factors affecting on short sea shipping are explored and analyzed, also the possibility of Ro-Ro shipping is examined, by comparing the shipping cost and the environmental impact of different ships like container ships, Ropax, and CONRO ships. The finding of this research shows the importance of time at port and utilization as a shipping cost determinants, the relationship between ship type and costing, and the possibility of Ro-Ro shipping.

Spatial modeling techniques for mapping and characterization of acid sulfate soils

Acid sulfate (a.s.) soils constitute a major environmental issue. Severe ecological damage results from the considerable amounts of acidity and metals leached by these soils in the recipient watercourses. As even small hot spots may affect large areas of coastal waters, mapping represents a fundamental step in the management and mitigation of a.s. soil environmental risks (i.e. to target strategic areas). Traditional mapping in the field is time-consuming and therefore expensive. Additional more cost-effective techniques have, thus, to be developed in order to narrow down and define in detail the areas of interest. The primary aim of this thesis was to assess different spatial modeling techniques for a.s. soil mapping, and the characterization of soil properties relevant for a.s. soil environmental risk management, using all available data: soil and water samples, as well as datalayers (e.g. geological and geophysical). Different spatial modeling techniques were applied at catchment or regional scale. Two artificial neural networks were assessed on the Sirppujoki River catchment (c. 440 km2) located in southwestern Finland, while fuzzy logic was assessed on several areas along the Finnish coast. Quaternary geology, aerogeophysics and slope data (derived from a digital elevation model) were utilized as evidential datalayers. The methods also required the use of point datasets (i.e. soil profiles corresponding to known a.s. or non-a.s. soil occurrences) for training and/or validation within the modeling processes. Applying these methods, various maps were generated: probability maps for a.s. soil occurrence, as well as predictive maps for different soil properties (sulfur content, organic matter content and critical sulfide depth). The two assessed artificial neural networks (ANNs) demonstrated good classification abilities for a.s. soil probability mapping at catchment scale. Slightly better results were achieved using a Radial Basis Function (RBF) -based ANN than a Radial Basis Functional Link Net (RBFLN) method, narrowing down more accurately the most probable areas for a.s. soil occurrence and defining more properly the least probable areas. The RBF-based ANN also demonstrated promising results for the characterization of different soil properties in the most probable a.s. soil areas at catchment scale. Since a.s. soil areas constitute highly productive lands for agricultural purpose, the combination of a probability map with more specific soil property predictive maps offers a valuable toolset to more precisely target strategic areas for subsequent environmental risk management. Notably, the use of laser scanning (i.e. Light Detection And Ranging, LiDAR) data enabled a more precise definition of a.s. soil probability areas, as well as the soil property modeling classes for sulfur content and the critical sulfide depth. Given suitable training/validation points, ANNs can be trained to yield a more precise modeling of the occurrence of a.s. soils and their properties. By contrast, fuzzy logic represents a simple, fast and objective alternative to carry out preliminary surveys, at catchment or regional scale, in areas offering a limited amount of data. This method enables delimiting and prioritizing the most probable areas for a.s soil occurrence, which can be particularly useful in the field. Being easily transferable from area to area, fuzzy logic modeling can be carried out at regional scale. Mapping at this scale would be extremely time-consuming through manual assessment. The use of spatial modeling techniques enables the creation of valid and comparable maps, which represents an important development within the a.s. soil mapping process. The a.s. soil mapping was also assessed using water chemistry data for 24 different catchments along the Finnish coast (in all, covering c. 21,300 km2) which were mapped with different methods (i.e. conventional mapping, fuzzy logic and an artificial neural network). Two a.s. soil related indicators measured in the river water (sulfate content and sulfate/chloride ratio) were compared to the extent of the most probable areas for a.s. soils in the surveyed catchments. High sulfate contents and sulfate/chloride ratios measured in most of the rivers demonstrated the presence of a.s. soils in the corresponding catchments. The calculated extent of the most probable a.s. soil areas is supported by independent data on water chemistry, suggesting that the a.s. soil probability maps created with different methods are reliable and comparable.

Specific structural features of syndecans and heparan sulfate chains are needed for cell signaling

The syndecans, heparan sulfate proteoglycans, are abundant molecules associated with the cell surface and extracellular matrix and consist of a protein core to which heparan sulfate chains are covalently attached. Each of the syndecan core proteins has a short cytoplasmic domain that binds cytosolic regulatory factors. The syndecans also contain highly conserved transmembrane domains and extracellular domains for which important activities are becoming known. These protein domains locate the syndecan on cell surface sites during development and tumor formation where they interact with other receptors to regulate signaling and cytoskeletal organization. The functions of cell surface heparan sulfate proteoglycan have been centered on the role of heparan sulfate chains, located on the outer side of the cell surface, in the binding of a wide array of ligands, including extracellular matrix proteins and soluble growth factors. More recently, the core proteins of the syndecan family transmembrane proteoglycans have also been shown to be involved in cell signaling through interaction with integrins and tyrosine kinase receptors.

Spatial and temporal variation in fish populations and assemblages in coastal waters of the northern Baltic Proper

The distribution and traits of fish are of interest both ecologically and socio-economically. In this thesis, phenotypic and structural variation in fish populations and assemblages was studied on multiple spatial and temporal scales in shallow coastal areas in the archipelago of the northern Baltic Proper. In Lumparn basin in Åland Islands, the fish assemblage displayed significant seasonal variation in depth zone distribution. The results indicate that investigating both spatial and temporal variation in small scale is crucial for understanding patterns in fish distribution and community structure in large scale. The local population of Eurasian perch Perca fluviatilis L displayed habitat-specific morphological and dietary variation. Perch in the pelagic zone were on average deeper in their body shape than the littoral ones and fed on fish and benthic invertebrates. The results differ from previous studies conducted in freshwater habitats, where the pelagic perch typically are streamlined in body shape and zooplanktivorous. Stable isotopes of carbon and nitrogen differed between perch with different stomach contents, suggesting differentiation of individual diet preferences. In the study areas Lumparn and Ivarskärsfjärden in Åland Islands and Galtfjärden in Swedish east coast, the development in fish assemblages during the 2000’s indicated a general shift towards higher abundances of small-bodied lower-order consumers, especially cyprinids. For European pikeperch Sander lucioperca L., recent declines in adult fish abundances and high mortalities (Z = 1.06–1.16) were observed, which suggests unsustainably high fishing pressure on pikeperch. Based on the results it can be hypothesized that fishing has reduced the abundances of large predatory fish, which together with bottom-up forcing by eutrophication has allowed the lower-order consumer species to increase in abundances. This thesis contributes to the scientific understanding of aquatic ecosystems with new descriptions on morphological and dietary adaptations in perch in brackish water, and on the seasonal variation in small-scale spatial fish distribution. The results also demonstrate anthropogenic effects on coastal fish communities and underline the urgency of further reducing nutrient inputs and regulating fisheries in the Baltic Sea region.

Fish hemoglobins

Vertebrate hemoglobin, contained in erythrocytes, is a globular protein with a quaternary structure composed of 4 globin chains (2 alpha and 2 beta) and a prosthetic group named heme bound to each one. Having myoglobin as an ancestor, hemoglobin acquired the capacity to respond to chemical stimuli that modulate its function according to tissue requirements for oxygen. Fish are generally submitted to spatial and temporal O2 variations and have developed anatomical, physiological and biochemical strategies to adapt to the changing environmental gas availability. Structurally, most fish hemoglobins are tetrameric; however, those from some species such as lamprey and hagfish dissociate, being monomeric when oxygenated and oligomeric when deoxygenated. Fish blood frequently possesses several hemoglobins; the primary origin of this finding lies in the polymorphism that occurs in the globin loci, an aspect that may occasionally confer advantages to its carriers or even be a harmless evolutionary remnant. On the other hand, the functional properties exhibit different behaviors, ranging from a total absence of responses to allosteric regulation to drastic ones, such as the Root effect.

Methodological approaches to planar and volumetric scintigraphic imaging of small volume targets with high spatial resolution and sensitivity

Single-photon emission computed tomography (SPECT) is a non-invasive imaging technique, which provides information reporting the functional states of tissues. SPECT imaging has been used as a diagnostic tool in several human disorders and can be used in animal models of diseases for physiopathological, genomic and drug discovery studies. However, most of the experimental models used in research involve rodents, which are at least one order of magnitude smaller in linear dimensions than man. Consequently, images of targets obtained with conventional gamma-cameras and collimators have poor spatial resolution and statistical quality. We review the methodological approaches developed in recent years in order to obtain images of small targets with good spatial resolution and sensitivity. Multipinhole, coded mask- and slit-based collimators are presented as alternative approaches to improve image quality. In combination with appropriate decoding algorithms, these collimators permit a significant reduction of the time needed to register the projections used to make 3-D representations of the volumetric distribution of target’s radiotracers. Simultaneously, they can be used to minimize artifacts and blurring arising when single pinhole collimators are used. Representation images are presented, which illustrate the use of these collimators. We also comment on the use of coded masks to attain tomographic resolution with a single projection, as discussed by some investigators since their introduction to obtain near-field images. We conclude this review by showing that the use of appropriate hardware and software tools adapted to conventional gamma-cameras can be of great help in obtaining relevant functional information in experiments using small animals.