Spatio-temporal variations of ozone and nitrogen dioxide concentrations under urban trees and in a nearby open area

The evergreen Quercus ilex L. is one of the most common trees in Italian urban environments and is considered effective in the uptake of particulate and gaseous atmospheric pollutants. However, the few available estimates on O3 and NO2 removal by urban Q. ilex originate from model-based studies (which indicate NO2/O3 removal capacity of Q. ilex) and not from direct measurements of air pollutant concentrations. Thus, in the urban area of Siena (central Italy) we began long-term monitoring of O3/NO2 concentrations using passive samplers at a distance of 1, 5, 10 m from a busy road, under the canopies of Q. ilex and in a nearby open-field. Measurements performed in the period June 2011-October 2013 showed always a greater decrease of NO2 concentrations under the Q. ilex canopy than in the open-field transect. Conversely, a decrease of average O3 concentrations under the tree canopy was found only in autumn after the typical Mediterranean post-summer rainfalls. Our results indicate that interactions between O3/NO2 concentrations and trees in Mediterranean urban ecosystems are affected by temporal variations in climatic conditions. We argue therefore that the direct measurement of atmospheric pollutant concentrations should be chosen to describe local changes of aerial pollution.

Spatio-temporal variations in the diet and stable isotope composition of the Argentine hake Merluccius hubbsi Marini, 1933 of the continental shelf of southeastern Brazil

The feeding ecology of Merluccius hubbsi was investigated in 2 regions of SE Brazil. The major food sources for the hakes were fish, crustaceans, and squid. In the upwelling system of Cabo Frio, the diet was very similar in the summers of 2001/2002 and spring 2002; fish were the most important prey followed by crustaceans. In Ubatuba, euphausiids were an important prey during the winter 2001 (100 m), while in the summer 2002, fish and amphipods predominated in the diet in the shallower site (40 m) and squid in the deeper site (100 m). The hakes showed temporal differences in stable isotope signatures in both regions, while C:N ratios varied only in Cabo Frio. delta(15)N and delta(13)C (bulk and corrected for lipid content) increased with fish length, which seems to be related to the increasing importance of fish and decreasing importance of euphausiids and amphipods in the diet of larger hakes. The mean trophic level of 3.7 for M. hubbsi was estimated using delta(15)N of bivalves as baseline and the fractionation of 3.4aEuro degrees between trophic levels.

Lateral sediment sources and knickzones as controls on spatio-temporal variations of sediment transport in an Alpine river

Modern mixed alluvial-bedrock channels in mountainous areas provide natural laboratories for understanding the time scales at which coarse-grained material has been entrained and transported from their sources to the adjacent sedimentary sink, where these deposits are preserved as conglomerates. This article assesses the shear stress conditions needed for the entrainment of the coarse-bed particles in the Glogn River that drains the 400 km2 Val Lumnezia basin, eastern Swiss Alps. In addition, quantitative data are presented on sediment transport patterns in this stream. The longitudinal stream profile of this river is characterized by three ca 500 m long knickzones where channel gradients range from 0·02 to 0·2 m m−1, and where the valley bottom confined into a <10 m wide gorge. Downstream of these knickzones, the stream is flat with gradients <0·01 m m−1 and widths ≥30 m. Measurements of the grain-size distribution along the trunk stream yield a mean D84 value of ca 270 mm, whereas the mean D50 is ca 100 mm. The consequences of the channel morphology and the grain-size distribution for the time scales of sediment transport were explored by using a one-dimensional step-backwater hydraulic model (Hydrologic Engineering Centre – River Analysis System). The results reveal that, along the entire trunk stream, a two to 10 year return period flood event is capable of mobilizing both the D50 and D84 fractions where the Shields stress exceeds the critical Shields stress for the initiation of particle motion. These return periods, however, varied substantially depending on the channel geometry and the pebble/boulder size distribution of the supplied material. Accordingly, the stream exhibits a highly dynamic boulder cover behaviour. It is likely that these time scales might also have been at work when coarse-grained conglomerates were constructed in the geological past.

Spatio-temporal variation of macrofaunal assemblages in the deep Blanes submarine canyon

The spatio-temporal variations in diversity and abundance of deep-sea macrofaunal assemblages (excluding meiofaunal taxa, as Nematoda, Copepoda and Ostracoda) from the Blanes Canyon (BC) and adjacent open slope are described. The Catalan Sea basin is characterized by the presence of numerous submarine canyons, which are globally acknowledged as biodiversity hot-spots, due to their disturbance regime and incremented conveying of organic matter. This area is subjected to local deep-sea fisheries activities, and to recurrent cold water cascading events from the shelf. The upper canyon (~900 m), middle slope (~1200 m) and lower slope (~1500 m) habitats were investigated during three different months (October 2008, May 2009 and September 2009). A total of 624 specimens belonging to 16 different taxa were found into 67 analyzed samples, which had been collected from the two study areas. Of these, Polychaeta, Mollusca and Crustacea were always the most abundant groups. As expected, the patterns of species diversity and evenness were different in time and space. Both in BC and open slope, taxa diversity and abundance are higher in the shallowest depth and lowest at -1500 m depth. This is probably due to different trophic regimes at these depths. The abundance of filter-feeders is higher inside BC than in the adjacent open slope, which is also related with an increment of predator polychaetes. Surface deposit-feeders are more abundant in the open slope than in BC, along with a decrement of filter-feeders and their predators. Probably these differences are due to higher quantities of suspended organic matter reaching the canyon. The multivariate analyses conducted on major taxa point out major differences effective taxa richness between depths and stations. In September 2009 the analyzed communities double their abundances, with a corresponding increase in richness of taxa. This could be related to a mobilizing event, like the release of accumulated food-supply in a nepheloid layer associated to the arrival of autumn. The highest abundance in BC is detected in the shallowest depth and in late summer (September), probably due to higher food availability caused by stronger flood events coming from Tordera River. The effects of such events seemed to involve adjacent open slope too. The nMDS conducted on major taxa abundance shows a slight temporal difference between the three campaigns samples, with a clear clustering between samples of Sept 09. All depth and all months were dominated by Polychaeta, which have been identified to family level and submitted to further analysis. Family richness have clearly minimum at the -1200 m depth of BC, highlighting the presence of a general impact affecting the populations in the middle slope. Three different matrices have been created, each with a different taxonomic level (All Taxa “AT”, Phylum Level “PL” and Polychaeta Families “PF”). Multivariate analysis (MDS, SIMPER) conducted on PL matrix showed a clear spatial differences between stations (BC and open slope) and depths. MDSs conducted on other two matrices (AT and PF) showed similar patterns, but different from PL analysis. A 2 nd stage analysis have been conducted to understand differences between different taxonomic levels, and PL level has been chosen as the most representative of variation. The faunal differences observed were explained by depth, station and season. All work has been accomplished in the Centre d’estudis avançats de Blanes (CEAB-CSIC), within the framework of Spanish PROMETEO project "Estudio Integrado de Cañones y Taludes PROfundos del MEdiTErráneo Occidental: un hábitat esencial", Ref. CTM2007-66316-C02- 01/MAR.

Addressing issues in sparseness, ecological bias and formulation of the adjacency matrix in Bayesian spatio-temporal analysis of disease counts

The main objective of this PhD was to further develop Bayesian spatio-temporal models (specifically the Conditional Autoregressive (CAR) class of models), for the analysis of sparse disease outcomes such as birth defects. The motivation for the thesis arose from problems encountered when analyzing a large birth defect registry in New South Wales. The specific components and related research objectives of the thesis were developed from gaps in the literature on current formulations of the CAR model, and health service planning requirements. Data from a large probabilistically-linked database from 1990 to 2004, consisting of fields from two separate registries: the Birth Defect Registry (BDR) and Midwives Data Collection (MDC) were used in the analyses in this thesis. The main objective was split into smaller goals. The first goal was to determine how the specification of the neighbourhood weight matrix will affect the smoothing properties of the CAR model, and this is the focus of chapter 6. Secondly, I hoped to evaluate the usefulness of incorporating a zero-inflated Poisson (ZIP) component as well as a shared-component model in terms of modeling a sparse outcome, and this is carried out in chapter 7. The third goal was to identify optimal sampling and sample size schemes designed to select individual level data for a hybrid ecological spatial model, and this is done in chapter 8. Finally, I wanted to put together the earlier improvements to the CAR model, and along with demographic projections, provide forecasts for birth defects at the SLA level. Chapter 9 describes how this is done. For the first objective, I examined a series of neighbourhood weight matrices, and showed how smoothing the relative risk estimates according to similarity by an important covariate (i.e. maternal age) helped improve the model’s ability to recover the underlying risk, as compared to the traditional adjacency (specifically the Queen) method of applying weights. Next, to address the sparseness and excess zeros commonly encountered in the analysis of rare outcomes such as birth defects, I compared a few models, including an extension of the usual Poisson model to encompass excess zeros in the data. This was achieved via a mixture model, which also encompassed the shared component model to improve on the estimation of sparse counts through borrowing strength across a shared component (e.g. latent risk factor/s) with the referent outcome (caesarean section was used in this example). Using the Deviance Information Criteria (DIC), I showed how the proposed model performed better than the usual models, but only when both outcomes shared a strong spatial correlation. The next objective involved identifying the optimal sampling and sample size strategy for incorporating individual-level data with areal covariates in a hybrid study design. I performed extensive simulation studies, evaluating thirteen different sampling schemes along with variations in sample size. This was done in the context of an ecological regression model that incorporated spatial correlation in the outcomes, as well as accommodating both individual and areal measures of covariates. Using the Average Mean Squared Error (AMSE), I showed how a simple random sample of 20% of the SLAs, followed by selecting all cases in the SLAs chosen, along with an equal number of controls, provided the lowest AMSE. The final objective involved combining the improved spatio-temporal CAR model with population (i.e. women) forecasts, to provide 30-year annual estimates of birth defects at the Statistical Local Area (SLA) level in New South Wales, Australia. The projections were illustrated using sixteen different SLAs, representing the various areal measures of socio-economic status and remoteness. A sensitivity analysis of the assumptions used in the projection was also undertaken. By the end of the thesis, I will show how challenges in the spatial analysis of rare diseases such as birth defects can be addressed, by specifically formulating the neighbourhood weight matrix to smooth according to a key covariate (i.e. maternal age), incorporating a ZIP component to model excess zeros in outcomes and borrowing strength from a referent outcome (i.e. caesarean counts). An efficient strategy to sample individual-level data and sample size considerations for rare disease will also be presented. Finally, projections in birth defect categories at the SLA level will be made.

Eigen-profiles of spatio-temporal fragments for adaptive region-based tracking

We propose a novel space-time descriptor for region-based tracking which is very concise and efficient. The regions represented by covariance matrices within a temporal fragment, are used to estimate this space-time descriptor which we call the Eigenprofiles(EP). EP so obtained is used in estimating the Covariance Matrix of features over spatio-temporal fragments. The Second Order Statistics of spatio-temporal fragments form our target model which can be adapted for variations across the video. The model being concise also allows the use of multiple spatially overlapping fragments to represent the target. We demonstrate good tracking results on very challenging datasets, shot under insufficient illumination conditions.

SPATIO-TEMPORAL DYNAMICS ALONG THE TERRAIN GRADIENT OF DIVERSE LANDSCAPE

Land use (LU) land cover (LC) information at a temporal scale illustrates the physical coverage of the Earth's terrestrial surface according to its use and provides the intricate information for effective planning and management activities. LULC changes are stated as local and location specific, collectively they act as drivers of global environmental changes. Understanding and predicting the impact of LULC change processes requires long term historical restorations and projecting into the future of land cover changes at regional to global scales. The present study aims at quantifying spatio temporal landscape dynamics along the gradient of varying terrains presented in the landscape by multi-data approach (MDA). MDA incorporates multi temporal satellite imagery with demographic data and other additional relevant data sets. The gradient covers three different types of topographic features, planes; hilly terrain and coastal region to account the significant role of elevation in land cover change. The seasonality is another aspect to be considered in the vegetation dominated landscapes; variations are accounted using multi seasonal data. Spatial patterns of the various patches are identified and analysed using landscape metrics to understand the forest fragmentation. The prediction of likely changes in 2020 through scenario analysis has been done to account for the changes, considering the present growth rates and due to the proposed developmental projects. This work summarizes recent estimates on changes in cropland, agricultural intensification, deforestation, pasture expansion, and urbanization as the causal factors for LULC change.

Spatio-temporal Variability of Atmospheric Ozone over Indian Subcontinent and its Relation to Meteorological Parameters

Ozone present in the atmosphere not only absorbs the biologically harmful ultraviolet radiation but also is an important ingredient of the climate system. The radiative absorption properties of ozone make it a determining factor in the structure of the atmosphere. Ozone in the troposphere has many negative impacts on humans and other living beings. Another significant aspect is the absorption of outgoing infrared radiation by ozone thus acting as a greenhouse gas. The variability of ozone in the atmosphere involves many interconnections with the incoming and outgoing radiation, temperature circulation etc. Hence ozone forms an important part of chemistry-climate as well as radiative transfer models. This aspect also makes the quantification of ozone more important. The discovery of Antarctic ozone hole and the role of anthropogenic activities in causing it made it possible to plan and implement necessary preventive measures. Continuous monitoring of ozone is also necessary to identify the effect of these preventive steps. The reactions involving the formation and destruction of ozone are influenced significantly by the temperature fluctuations of the atmosphere. On the other hand the variations in ozone can change the temperature structure of the atmosphere. Indian subcontinent is a region having large weather and climate variability which is evident from the large interannual variability of monsoon system over the region. Nearly half of Indian region comprises the tropical region. Most of ozone is formed in the tropical region and transported to higher latitudes. The formation and transport of ozone can be influenced by changes in solar radiation and various atmospheric circulation features. Besides industrial activities and vehicular traffic is more due to its large population. This may give rise to an increase in the production of tropospheric ozone which is greenhouse gas. Hence it becomes necessary to monitor the atmospheric ozone over this region. This study probes into the spatial distribution and temporal evolution of ozone over Indian subcontinent and discusses the contributing atmospheric parameters.

Detection of Flock Movement in Spatio-Temporal Database using Clustering Techniques - an Experience

In this paper, moving flock patterns are mined from spatio- temporal datasets by incorporating a clustering algorithm. A flock is defined as the set of data that move together for a certain continuous amount of time. Finding out moving flock patterns using clustering algorithms is a potential method to find out frequent patterns of movement in large trajectory datasets. In this approach, SPatial clusteRing algoRithm thrOugh sWarm intelligence (SPARROW) is the clustering algorithm used. The advantage of using SPARROW algorithm is that it can effectively discover clusters of widely varying sizes and shapes from large databases. Variations of the proposed method are addressed and also the experimental results show that the problem of scalability and duplicate pattern formation is addressed. This method also reduces the number of patterns produced

Spatio-temporal surface soil heat flux estimates from satellite data: results for the AMMA experiment at the Fakara (Niger) supersite

This paper describes a method that employs Earth Observation (EO) data to calculate spatiotemporal estimates of soil heat flux, G, using a physically-based method (the Analytical Method). The method involves a harmonic analysis of land surface temperature (LST) data. It also requires an estimate of near-surface soil thermal inertia; this property depends on soil textural composition and varies as a function of soil moisture content. The EO data needed to drive the model equations, and the ground-based data required to provide verification of the method, were obtained over the Fakara domain within the African Monsoon Multidisciplinary Analysis (AMMA) program. LST estimates (3 km × 3 km, one image 15 min−1) were derived from MSG-SEVIRI data. Soil moisture estimates were obtained from ENVISAT-ASAR data, while estimates of leaf area index, LAI, (to calculate the effect of the canopy on G, largely due to radiation extinction) were obtained from SPOT-HRV images. The variation of these variables over the Fakara domain, and implications for values of G derived from them, were discussed. Results showed that this method provides reliable large-scale spatiotemporal estimates of G. Variations in G could largely be explained by the variability in the model input variables. Furthermore, it was shown that this method is relatively insensitive to model parameters related to the vegetation or soil texture. However, the strong sensitivity of thermal inertia to soil moisture content at low values of relative saturation (<0.2) means that in arid or semi-arid climates accurate estimates of surface soil moisture content are of utmost importance, if reliable estimates of G are to be obtained. This method has the potential to improve large-scale evaporation estimates, to aid land surface model prediction and to advance research that aims to explain failure in energy balance closure of meteorological field studies.

Evaluation of the potential of InSAR time series to study the spatio-temporal evolution of piezometric levels in the Madrid aquifer

The Tertiary detritic aquifer of Madrid (TDAM), with an average thickness of 1500 m and a heterogeneous, anisotropic structure, supplies water to Madrid, the most populated city of Spain (3.2 million inhabitants in the metropolitan area). Besides its complex structure, a previous work focused in the north-northwest of Madrid city showed that the aquifer behaves quasi elastically trough extraction/recovery cycles and ground uplifting during recovery periods compensates most of the ground subsidence measured during previous extraction periods (Ezquerro et al., 2014). Therefore, the relationship between ground deformation and groundwater level through time can be simulated using simple elastic models. In this work, we model the temporal evolution of the piezometric level in 19 wells of the TDAM in the period 1997–2010. Using InSAR and piezometric time series spanning the studied period, we first estimate the elastic storage coefficient (Ske) for every well. Both, the Ske of each well and the average Ske of all wells, are used to predict hydraulic heads at the different well locations during the study period and compared against the measured hydraulic heads, leading to very similar errors when using the Ske of each well and the average Ske of all wells: 14 and 16 % on average respectively. This result suggests that an average Ske can be used to estimate piezometric level variations in all the points where ground deformation has been measured by InSAR, thus allowing production of piezometric level maps for the different extraction/recovery cycles in the TDAM.

Spatio-temporal Variability of Atmospheric Ozone over Indian Subcontinent and its Relation to Meteorological Parameters

Ozone present in the atmosphere not only absorbs the biologically harmful ultraviolet radiation but also is an important ingredient of the climate system. The radiative absorption properties of ozone make it a determining factor in the structure of the atmosphere. Ozone in the troposphere has many negative impacts on humans and other living beings. Another significant aspect is the absorption of outgoing infrared radiation by ozone thus acting as a greenhouse gas. The variability of ozone in the atmosphere involves many interconnections with the incoming and outgoing radiation, temperature circulation etc. Hence ozone forms an important part of chemistry-climate as well as radiative transfer models. This aspect also makes the quantification of ozone more important. The discovery of Antarctic ozone hole and the role of anthropogenic activities in causing it made it possible to plan and implement necessary preventive measures. Continuous monitoring of ozone is also necessary to identify the effect of these preventive steps. The reactions involving the formation and destruction of ozone are influenced significantly by the temperature fluctuations of the atmosphere. On the other hand the variations in ozone can change the temperature structure of the atmosphere. Indian subcontinent is a region having large weather and climate variability which is evident from the large interannual variability of monsoon system over the region. Nearly half of Indian region comprises the tropical region. Most of ozone is formed in the tropical region and transported to higher latitudes. The formation and transport of ozone can be influenced by changes in solar radiation and various atmospheric circulation features. Besides industrial activities and vehicular traffic is more due to its large population. This may give rise to an increase in the production of tropospheric ozone which is greenhouse gas. Hence it becomes necessary to monitor the atmospheric ozone over this region. This study probes into the spatial distribution and temporal evolution of ozone over Indian subcontinent and discusses the contributing atmospheric parameters.

Spatial and temporal variations of mechanical properties and mineral content of the external callus during bone healing

After bone fracture, various cellular activities lead to the formation of different tissue types, which form the basis for the process of secondary bone healing. Although these tissues have been quantified by histology, their material properties are not well understood. Thus, the aim of this study is to correlate the spatial and temporal variations in the mineral content and the nanoindentation modulus of the callus formed via intramembranous ossification over the course of bone healing. Midshaft tibial samples from a sheep osteotomy model at time points of 2, 3, 6 and 9 weeks were employed. PMMA embedded blocks were used for quantitative back scattered electron imaging and nanoindentation of the newly formed periosteal callus near the cortex. The resulting indentation modulus maps show the heterogeneity in the modulus in the selected regions of the callus. The indentation modulus of the embedded callus is about 6 GPa at the early stage. At later stages of mineralization, the average indentation modulus reaches 14 GPa. There is a slight decrease in average indentation modulus in regions distant to the cortex, probably due to remodelling of the peripheral callus. The spatial and temporal distribution of mineral content in the callus tissue also illustrates the ongoing remodelling process observed from histological analysis. Most interestingly the average indentation modulus, even at 9 weeks, remains as low as 13 GPa, which is roughly 60% of that for cortical sheep bone. The decreased indentation modulus in the callus compared to cortex is due to the lower average mineral content and may be perhaps also due to the properties of the organic matrix which might be different from normal bone.

Unusual Event Detection in Crowded Scenes Using Bag of LBPs in spatio-temporal patches

Modelling events in densely crowded environments remains challenging, due to the diversity of events and the noise in the scene. We propose a novel approach for anomalous event detection in crowded scenes using dynamic textures described by the Local Binary Patterns from Three Orthogonal Planes (LBP-TOP) descriptor. The scene is divided into spatio-temporal patches where LBP-TOP based dynamic textures are extracted. We apply hierarchical Bayesian models to detect the patches containing unusual events. Our method is an unsupervised approach, and it does not rely on object tracking or background subtraction. We show that our approach outperforms existing state of the art algorithms for anomalous event detection in UCSD dataset.