949 resultados para Spatial points patterns analysis


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Mapping ecosystem services (ES) and their trade-offs is a key requirement for informed decision making for land use planning and management of natural resources that aim to move towards increasing the sustainability of landscapes. The negotiations of the purposes of landscapes and the services they should provide are difficult as there is an increasing number of stakeholders active at different levels with a variety of interests present on one particular landscape.Traditionally, land cover data is at the basis for mapping and spatial monitoring of ecosystem services. In light of complex landscapes it is however questionable whether land cover per se and as a spatial base unit is suitable for monitoring and management at the meso-scale. Often the characteristics of a landscape are defined by prevalence, composition and specific spatial and temporal patterns of different land cover types. The spatial delineation of shifting cultivation agriculture represents a prominent example of a land use system with its different land use intensities that requires alternative methodologies that go beyond the common remote sensing approaches of pixel-based land cover analysis due to the spatial and temporal dynamics of rotating cultivated and fallow fields.Against this background we advocate that adopting a landscape perspective to spatial planning and decision making offers new space for negotiation and collaboration, taking into account the needs of local resource users, and of the global community. For this purpose we introduce landscape mosaicsdefined as new spatial unit describing generalized land use types. Landscape mosaics have allowed us to chart different land use systems and land use intensities and permitted us to delineate changes in these land use systems based on changes of external claims on these landscapes. The underlying idea behindthe landscape mosaics is to use land cover data typically derived from remote sensing data and to analyse and classify spatial patterns of this land cover data using a moving window approach. We developed the landscape mosaics approach in tropical, forest dominated landscapesparticularly shifting cultivation areas and present examples ofour work from northern Laos, eastern Madagascarand Yunnan Province in China.

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The discovery of grid cells in the medial entorhinal cortex (MEC) permits the characterization of hippocampal computation in much greater detail than previously possible. The present study addresses how an integrate-and-fire unit driven by grid-cell spike trains may transform the multipeaked, spatial firing pattern of grid cells into the single-peaked activity that is typical of hippocampal place cells. Previous studies have shown that in the absence of network interactions, this transformation can succeed only if the place cell receives inputs from grids with overlapping vertices at the location of the place cell's firing field. In our simulations, the selection of these inputs was accomplished by fast Hebbian plasticity alone. The resulting nonlinear process was acutely sensitive to small input variations. Simulations differing only in the exact spike timing of grid cells produced different field locations for the same place cells. Place fields became concentrated in areas that correlated with the initial trajectory of the animal; the introduction of feedback inhibitory cells reduced this bias. These results suggest distinct roles for plasticity of the perforant path synapses and for competition via feedback inhibition in the formation of place fields in a novel environment. Furthermore, they imply that variability in MEC spiking patterns or in the rat's trajectory is sufficient for generating a distinct population code in a novel environment and suggest that recalling this code in a familiar environment involves additional inputs and/or a different mode of operation of the network.

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Calmodulin (CaM) is a ubiquitous Ca(2+) buffer and second messenger that affects cellular function as diverse as cardiac excitability, synaptic plasticity, and gene transcription. In CA1 pyramidal neurons, CaM regulates two opposing Ca(2+)-dependent processes that underlie memory formation: long-term potentiation (LTP) and long-term depression (LTD). Induction of LTP and LTD require activation of Ca(2+)-CaM-dependent enzymes: Ca(2+)/CaM-dependent kinase II (CaMKII) and calcineurin, respectively. Yet, it remains unclear as to how Ca(2+) and CaM produce these two opposing effects, LTP and LTD. CaM binds 4 Ca(2+) ions: two in its N-terminal lobe and two in its C-terminal lobe. Experimental studies have shown that the N- and C-terminal lobes of CaM have different binding kinetics toward Ca(2+) and its downstream targets. This may suggest that each lobe of CaM differentially responds to Ca(2+) signal patterns. Here, we use a novel event-driven particle-based Monte Carlo simulation and statistical point pattern analysis to explore the spatial and temporal dynamics of lobe-specific Ca(2+)-CaM interaction at the single molecule level. We show that the N-lobe of CaM, but not the C-lobe, exhibits a nano-scale domain of activation that is highly sensitive to the location of Ca(2+) channels, and to the microscopic injection rate of Ca(2+) ions. We also demonstrate that Ca(2+) saturation takes place via two different pathways depending on the Ca(2+) injection rate, one dominated by the N-terminal lobe, and the other one by the C-terminal lobe. Taken together, these results suggest that the two lobes of CaM function as distinct Ca(2+) sensors that can differentially transduce Ca(2+) influx to downstream targets. We discuss a possible role of the N-terminal lobe-specific Ca(2+)-CaM nano-domain in CaMKII activation required for the induction of synaptic plasticity.

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The combination of scaled analogue experiments, material mechanics, X-ray computed tomography (XRCT) and Digital Volume Correlation techniques (DVC) is a powerful new tool not only to examine the 3 dimensional structure and kinematic evolution of complex deformation structures in scaled analogue experiments, but also to fully quantify their spatial strain distribution and complete strain history. Digital image correlation (DIC) is an important advance in quantitative physical modelling and helps to understand non-linear deformation processes. Optical non-intrusive (DIC) techniques enable the quantification of localised and distributed deformation in analogue experiments based either on images taken through transparent sidewalls (2D DIC) or on surface views (3D DIC). X-ray computed tomography (XRCT) analysis permits the non-destructive visualisation of the internal structure and kinematic evolution of scaled analogue experiments simulating tectonic evolution of complex geological structures. The combination of XRCT sectional image data of analogue experiments with 2D DIC only allows quantification of 2D displacement and strain components in section direction. This completely omits the potential of CT experiments for full 3D strain analysis of complex, non-cylindrical deformation structures. In this study, we apply digital volume correlation (DVC) techniques on XRCT scan data of “solid” analogue experiments to fully quantify the internal displacement and strain in 3 dimensions over time. Our first results indicate that the application of DVC techniques on XRCT volume data can successfully be used to quantify the 3D spatial and temporal strain patterns inside analogue experiments. We demonstrate the potential of combining DVC techniques and XRCT volume imaging for 3D strain analysis of a contractional experiment simulating the development of a non-cylindrical pop-up structure. Furthermore, we discuss various options for optimisation of granular materials, pattern generation, and data acquisition for increased resolution and accuracy of the strain results. Three-dimensional strain analysis of analogue models is of particular interest for geological and seismic interpretations of complex, non-cylindrical geological structures. The volume strain data enable the analysis of the large-scale and small-scale strain history of geological structures.

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Background and Aims Ongoing global warming has been implicated in shifting phenological patterns such as the timing and duration of the growing season across a wide variety of ecosystems. Linear models are routinely used to extrapolate these observed shifts in phenology into the future and to estimate changes in associated ecosystem properties such as net primary productivity. Yet, in nature, linear relationships may be special cases. Biological processes frequently follow more complex, non-linear patterns according to limiting factors that generate shifts and discontinuities, or contain thresholds beyond which responses change abruptly. This study investigates to what extent cambium phenology is associated with xylem growth and differentiation across conifer species of the northern hemisphere. Methods Xylem cell production is compared with the periods of cambial activity and cell differentiation assessed on a weekly time scale on histological sections of cambium and wood tissue collected from the stems of nine species in Canada and Europe over 1–9 years per site from 1998 to 2011. Key Results The dynamics of xylogenesis were surprisingly homogeneous among conifer species, although dispersions from the average were obviously observed. Within the range analysed, the relationships between the phenological timings were linear, with several slopes showing values close to or not statistically different from 1. The relationships between the phenological timings and cell production were distinctly non-linear, and involved an exponential pattern. Conclusions The trees adjust their phenological timings according to linear patterns. Thus, shifts of one phenological phase are associated with synchronous and comparable shifts of the successive phases. However, small increases in the duration of xylogenesis could correspond to a substantial increase in cell production. The findings suggest that the length of the growing season and the resulting amount of growth could respond differently to changes in environmental conditions.

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This research examines prevalence of alcohol and illicit substance use in the United States and Mexico and associated socio-demographic characteristics. The sources of data for this study are public domain data from the U.S. National Household Survey of Drug Abuse, 1988 (n = 8814), and the Mexican National Survey of Addictions, 1988 (n = 12,579). In addition, this study discusses methodologic issues in cross-cultural and cross-national comparison of behavioral and epidemiologic data from population-based samples. The extent to which patterns of substance abuse vary among subgroups of the U.S. and Mexican populations is assessed, as well as the comparability and equivalence of measures of alcohol and drug use in these national samples.^ The prevalence of alcohol use was somewhat similar in the two countries for all three measures of use: lifetime, past year and past year heavy use, (85.0%, 68.1%, 39.6% and 72.6%, 47.7% and 45.8% for the U.S. and Mexico respectively). The use of illegal substances varied widely between countries, with U.S. respondents reporting significantly higher levels of use than their Mexican counterparts. For example, reported use of any illicit substance in lifetime and past year was 34.2%, 11.6 for the U.S., and 3.3% and 0.6% for Mexico. Despite these differences in prevalence, two demographic characteristics, gender and age, were important correlates of use in both countries. Men in both countries were more likely to report use of alcohol and illicit substances than women. Generally speaking, a greater proportion of respondents in both countries 18 years of age or older reported use of alcohol for all three measures than younger respondents; and a greater proportion of respondents between the ages of 18 and 34 years reported use of illicit substances during lifetime and past year than any other age group.^ Additional substantive research investigating population-based samples and at-risk subgroups is needed to understand the underlying mechanisms of these associations. Further development of cross-culturally meaningful survey methods is warranted to validate comparisons of substance use across countries and societies. ^

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Background: Motor symptoms are frequent phenomena across the entire course of schizophrenia1. Some have argued that disorganized behavior was associated with aberrant motor behavior. We have studied the association of motor disturbances and disorganization in two projects focusing on the timing of movements. Method: In two studies, we assessed motor behavior and psychopathology. The first study applied a validated test of upper limb apraxia in 30 schizophrenia patients2,3. We used standardized video assessments of hand gestures by a blinded rater. The second study tested the stability of movement patterns using time series analysis in actigraphy data of 100 schizophrenia patients4. Both stability of movement patterns and the overall amount of movement were calculated from data of two hours with high degrees of social interaction comparable across the 100 subjects. Results: In total, 67% of the patients had gesture performance deficits3. Most frequently, they made spatial, temporal and body-part-as-object errors. Gesture performance relied on frontal lobe function2. Poor gesture performance was associated with increased disorganization scores. In the second study, we found disorganization to be predicted only by more irregular movement patterns irrespective of the overall amount of movement4. Conclusion : Both studies provide evidence for a link between aberrant timing of motor behavior and disorganization. Disturbed movement control seems critical for disorganized behavior in schizophrenia.

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Local rates of change in ice-sheet thickness were calculated at IS sites in West Antarctica using the submergence velocity technique. This method entails a comparison of the vertical velocity of the ice sheet, measured using repeat global positioning system surveys of markers, and local long-term rates of snow accumulation obtained using firn-core stratigraphy. Any significant difference between these two quantities represents a thickness change with time. Measurements were conducted at sites located similar to 100-200 km apart along US ITASE traverse routes, and at several isolated locations. All but one of the sites are distributed in the Siple Coast and the Amundsen Sea basin along contours of constant elevation, along flowlines, across ice divides and close to regions of enhanced flow. Calculated rates of thickness change are different from site to site. Most of the large rates of change in ice thickness (similar to 10 cm a(-1) or larger) are observed in or close to regions of rapid flow, and are probably related to ice-dynamics effects. Near-steady-state conditions are calculated mostly at sites in the slow-moving ice-sheet interior and near the main West Antarctic ice divide. These results are consistent with regional estimates of ice-sheet change derived from remote-sensing measurements at similar locations in West Antarctica.

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Physical forcing and biological response within the California Current System (CCS) are highly variable over a wide range of scales. Satellite remote sensing offers the only feasible means of quantifying this variability over the full extent of the CCS. Using six years (1997-2003) of daily SST and chlorophyll imagery, we map the spatial dependence of dominant temporal variability at resolutions sufficient to identify recurrent mesoscale circulation and local pattern associated with coastal topography. Here we describe mean seasonal cycles and interannual variation; intraseasonal variability is left to a companion paper ( K. R. Legaard and A. C. Thomas, manuscript in preparation, 2006). Coastal upwelling dictates seasonality along north-central California, where weak cycles of SST fluctuate between spring minima and late summer maxima and chlorophyll peaks in early summer. Off northern California, chlorophyll maxima are bounded offshore by the seasonally recurrent upwelling jet. Seasonal cycles differ across higher latitudes and in the midlatitude Southern California Bight, where upwelling winds are less vigorous and/or persistent. Seasonality along south-central Baja is strongly affected by processes other than upwelling, despite year-round upwelling-favorable winds. Interannual variation is generally dominated by El Nino and La Nina conditions. Interannual SST variance is greatest along south-central Baja, although interannual variability constitutes a greater fraction of total variance inshore along southern Oregon and much of California. Patterns of interannual chlorophyll variance are consistent with dominant forcing through the widespread depression and elevation of the nutricline during El Nino and La Nina, respectively. Interannual variability constitutes a greater fraction of total chlorophyll variance offshore.

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Six years of daily satellite data are used to quantify and map intraseasonal variability of chlorophyll and sea surface temperature (SST) in the California Current. We define intraseasonal variability as temporal variation remaining after removal of interannual variability and stationary seasonal cycles. Semivariograms are used to quantify the temporal structure of residual time series. Empirical orthogonal function (EOF) analyses of semivariograms calculated across the region isolate dominant scales and corresponding spatial patterns of intraseasonal variability. The mode 1 EOFs for both chlorophyll and SST semivariograms indicate a dominant timescale of similar to 60 days. Spatial amplitudes and patterns of intraseasonal variance derived from mode 1 suggest dominant forcing of intraseasonal variability through distortion of large scale chlorophyll and SST gradients by mesoscale circulation. Intraseasonal SST variance is greatest off southern Baja and along southern Oregon and northern California. Chlorophyll variance is greatest over the shelf and slope, with elevated values closely confined to the Baja shelf and extending farthest from shore off California and the Pacific Northwest. Intraseasonal contributions to total SST variability are strongest near upwelling centers off southern Oregon and northern California, where seasonal contributions are weak. Intraseasonal variability accounts for the majority of total chlorophyll variance in most inshore areas save for southern Baja, where seasonal cycles dominate. Contributions of higher EOF modes to semivariogram structure indicate the degree to which intraseasonal variability is shifted to shorter timescales in certain areas. Comparisons of satellite-derived SST semivariograms to those calculated from co-located and concurrent buoy SST time series show similar features.

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Epileptic seizures are associated with high behavioral stereotypy of the patients. In the EEG of epilepsy patients characteristic signal patterns can be found during and between seizures. Here we use ordinal patterns to analyze EEGs of epilepsy patients and quantify the degree of signal determinism. Besides relative signal redundancy and the fraction of forbidden patterns we introduce the fraction of under-represented patterns as a new measure. Using the logistic map, parameter scans are performed to explore the sensitivity of the measures to signal determinism. Thereafter, application is made to two types of EEGs recorded in two epilepsy patients. Intracranial EEG shows pronounced determinism peaks during seizures. Finally, we demonstrate that ordinal patterns may be useful for improving analysis of non-invasive simultaneous EEG-fMRI.

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While several studies have investigated winter-time air pollution with a wide range of concentration levels, hardly any results are available for longer time periods covering several winter-smog episodes at various locations; e.g., often only a few weeks from a single winter are investigated. Here, we present source apportionment results of winter-smog episodes from 16 air pollution monitoring stations across Switzerland from five consecutive winters. Radiocarbon (14C) analyses of the elemental (EC) and organic (OC) carbon fractions, as well as levoglucosan, major water-soluble ionic species and gas-phase pollutant measurements were used to characterize the different sources of PM10. The most important contributions to PM10 during winter-smog episodes in Switzerland were on average the secondary inorganic constituents (sum of nitrate, sulfate and ammonium = 41 ± 15%) followed by organic matter (OM) (34 ± 13%) and EC (5 ± 2%). The non-fossil fractions of OC (fNF,OC) ranged on average from 69 to 85 and 80 to 95% for stations north and south of the Alps, respectively, showing that traffic contributes on average only up to ~ 30% to OC. The non-fossil fraction of EC (fNF,EC), entirely attributable to primary wood burning, was on average 42 ± 13 and 49 ± 15% for north and south of the Alps, respectively. While a high correlation was observed between fossil EC and nitrogen oxides, both primarily emitted by traffic, these species did not significantly correlate with fossil OC (OCF), which seems to suggest that a considerable amount of OCF is secondary, from fossil precursors. Elevated fNF,EC and fNF,OC values and the high correlation of the latter with other wood burning markers, including levoglucosan and water soluble potassium (K+) indicate that residential wood burning is the major source of carbonaceous aerosols during winter-smog episodes in Switzerland. The inspection of the non-fossil OC and EC levels and the relation with levoglucosan and water-soluble K+ shows different ratios for stations north and south of the Alps (most likely because of differences in burning technologies) for these two regions in Switzerland.

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Amongst the various hypotheses that challenged to explain the coexistence of species with similar life histories, theoretical, and empirical studies suggest that spatial processes may slow down competitive exclusion and hence promote coexistence even in the absence of evident trade-offs and frequent disturbances. We investigated the effects of spatial pattern and density on the relative importance of intra- and interspecific competition in a field experiment. We hypothesized that weak competitors increased biomass and seed production within neighborhoods of conspecifics, while stronger competitors would show increased biomass and seed production within neighborhoods of heterospecifics. Seeds of four annual plant species (Capsella bursa-pastoris, Stachys annua, Stellaria media, Poa annua) were sown in two spatial patterns (aggregated vs. random) and at two densities (low vs. high) in three different species combinations (monocultures, three and four species mixtures). There was a hierarchy in biomass production among the four species and C. bursa-pastoris and S. media were among the weak competitors. Capsella and Stellaria showed increased biomass production and had more individuals in the aggregated compared to the random pattern, especially when both superior competitors (S. annua, P. annua) were present. For P. annua we observed considerable differences among species combinations and unexpected pattern effects. Our findings support the hypothesis that weak competitors increase their fitness when grown in the neighborhood of conspecifics, and suggested that for the weakest competitors the species identity is not important and all other species are best avoided through intraspecific aggregation. In addition, our data suggest that the importance of spatial pattern for the other competitors might not only depend on the position within the hierarchy but also on the identity of neighbor species, species characteristics, below ground interactions, and other nonspatial factors.

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Vertebral compression fracture is a common medical problem in osteoporotic individuals. The quantitative computed tomography (QCT)-based finite element (FE) method may be used to predict vertebral strength in vivo, but needs to be validated with experimental tests. The aim of this study was to validate a nonlinear anatomy specific QCT-based FE model by using a novel testing setup. Thirty-seven human thoracolumbar vertebral bone slices were prepared by removing cortical endplates and posterior elements. The slices were scanned with QCT and the volumetric bone mineral density (vBMD) was computed with the standard clinical approach. A novel experimental setup was designed to induce a realistic failure in the vertebral slices in vitro. Rotation of the loading plate was allowed by means of a ball joint. To minimize device compliance, the specimen deformation was measured directly on the loading plate with three sensors. A nonlinear FE model was generated from the calibrated QCT images and computed vertebral stiffness and strength were compared to those measured during the experiments. In agreement with clinical observations, most of the vertebrae underwent an anterior wedge-shape fracture. As expected, the FE method predicted both stiffness and strength better than vBMD (R2 improved from 0.27 to 0.49 and from 0.34 to 0.79, respectively). Despite the lack of fitting parameters, the linear regression of the FE prediction for strength was close to the 1:1 relation (slope and intercept close to one (0.86 kN) and to zero (0.72 kN), respectively). In conclusion, a nonlinear FE model was successfully validated through a novel experimental technique for generating wedge-shape fractures in human thoracolumbar vertebrae.