Sediment and soil organic matter source assessment as revealed by the molecular distribution and carbon isotopic composition of n-alkanes

The assessment of organic matter (OM) sources in sediments and soils is a key to better understand the biogeochemical cycling of carbon in aquatic environments. While traditional molecular marker-based methods have provided such information for typical two end member (allochthonous/terrestrial vs. autochthonous/microbial)-dominated systems, more detailed, biomass-specific assessments are needed for ecosystems with complex OM inputs such as tropical and sub-tropical wetlands and estuaries where aquatic macrophytes and macroalgae may play an important role as OM sources. The aim of this study was to assess the utility of a combined approach using compound specific stable carbon isotope analysis and an n-alkane based proxy (Paq) to differentiate submerged and emergent/terrestrial vegetation OM inputs to soils/sediments from a sub-tropical wetland and estuarine system, the Florida Coastal Everglades. Results show that Paq values (0.13–0.51) for the emergent/terrestrial plants were generally lower than those for freshwater/marine submerged vegetation (0.45–1.00) and that compound specific δ13C values for the n-alkanes (C23 to C31) were distinctively different for terrestrial/emergent and freshwater/marine submerged plants. While crossplots of the Paq and n-alkane stable isotope values for the C23n-alkane suggest that OM inputs are controlled by vegetation changes along the freshwater to marine transect, further resolution regarding OM input changes along this landscape was obtained through principal component analysis (PCA), successfully grouping the study sites according to the OM source strengths. The data show the potential for this n-alkane based multi-proxy approach as a means of assessing OM inputs to complex ecosystems.

Solar radiation–enhanced dissolution of particulate organic matter from coastal marine sediments

We investigated the influence of solar radiation on the transfer of organic matter from the particulate to dissolved phase during resuspension of coastal sediments collected from seven sites across Florida Bay (organic carbon values ranged from 2% to 9% by weight). Sediments were resuspended in oligotrophic seawater for 48 h in 1-liter quartz flasks in the dark and under simulated solar radiation (SunTest XLS+) at wet weight concentrations of 100 mg L21 and 1 g L21 (dry weights ranged from 27 to 630 mg L21). There were little to no dissolved organic carbon (DOC) increases in dark resuspensions, but substantial DOC increases occurred in irradiated resuspensions. DOC levels increased 4 mg C L21 in an irradiated 1 g L21 suspension (dry weight 400 mg L21) of an organic-rich (7% organic carbon) sediment. At a particle load commonly found in coastal waters (dry weight 40 mg L21), an irradiated suspension of the same organic-rich sediment produced 1 mg C L21. DOC increases in irradiated resuspensions were well-correlated with particulate organic carbon (POC) added. Photodissolution of POC ranged from 6% to 15% at high sediment levels and 10% to 33% at low sediment levels. Parallel factor analysis modeling of excitation-emission matrix fluorescence data (EEM PARAFAC) suggested the dissolved organic matter (DOM) produced during photodissolution included primarily humic-like components and a less important input of protein-like components. Principal component analysis (PCA) of EEM data revealed a marked similarity in the humic character of photodissolved DOM from organic-rich sediments and the humic character of Florida Bay waters.

A novel signal processing method for intraoperative neurophysiological monitoring in spinal surgeries

Intraoperative neurophysiologic monitoring is an integral part of spinal surgeries and involves the recording of somatosensory evoked potentials (SSEP). However, clinical application of IONM still requires anywhere between 200 to 2000 trials to obtain an SSEP signal, which is excessive and introduces a significant delay during surgery to detect a possible neurological damage. The aim of this study is to develop a means to obtain the SSEP using a much less, twelve number of recordings. The preliminary step involved was to distinguish the SSEP with the ongoing brain activity. We first establish that the brain activity is indeed quasi-stationary whereas an SSEP is expected to be identical every time a trial is recorded. An algorithm was developed using Chebychev time windowing for preconditioning of SSEP trials to retain the morphological characteristics of somatosensory evoked potentials (SSEP). This preconditioning was followed by the application of a principal component analysis (PCA)-based algorithm utilizing quasi-stationarity of EEG on 12 preconditioned trials. A unique Walsh transform operation was then used to identify the position of the SSEP event. An alarm is raised when there is a 10% time in latency deviation and/or 50% peak-to-peak amplitude deviation, as per the clinical requirements. The algorithm shows consistency in the results in monitoring SSEP in up to 6-hour surgical procedures even under this significantly reduced number of trials. In this study, the analysis was performed on the data recorded in 29 patients undergoing surgery during which the posterior tibial nerve was stimulated and SSEP response was recorded from scalp. This method is shown empirically to be more clinically viable than present day approaches. In all 29 cases, the algorithm takes 4sec to extract an SSEP signal, as compared to conventional methods, which take several minutes. The monitoring process using the algorithm was successful and proved conclusive under the clinical constraints throughout the different surgical procedures with an accuracy of 91.5%. Higher accuracy and faster execution time, observed in the present study, in determining the SSEP signals provide a much improved and effective neurophysiological monitoring process.

Evaluating the Distribution of Terrestrial Dissolved Organic Matter in a Complex Coastal Ecosystem Using Fluorescence Spectroscopy

The coastal zone of the Florida Keys features the only living coral reef in the continental United States and as such represents a unique regional environmental resource. Anthropogenic pressures combined with climate disturbances such as hurricanes can affect the biogeochemistry of the region and threaten the health of this unique ecosystem. As such, water quality monitoring has historically been implemented in the Florida Keys, and six spatially distinct zones have been identified. In these studies however, dissolved organic matter (DOM) has only been studied as a quantitative parameter, and DOM composition can be a valuable biogeochemical parameter in assessing environmental change in coastal regions. Here we report the first data of its kind on the application of optical properties of DOM, in particular excitation emission matrix fluorescence with parallel factor analysis (EEM-PARAFAC), throughout these six Florida Keys regions in an attempt to assess spatial differences in DOM sources. Our data suggests that while DOM in the Florida Keys can be influenced by distant terrestrial environments such as the Everglades, spatial differences in DOM distribution were also controlled in part by local surface runoff/fringe mangroves, contributions from seasgrass communities, as well as the reefs and waters from the Florida Current. Application of principal component analysis (PCA) of the relative abundance of EEM-PARAFAC components allowed for a clear distinction between the sources of DOM (allochthonous vs. autochthonous), between different autochthonous sources and/or the diagenetic status of DOM, and further clarified contribution of terrestrial DOM in zones where levels of DOM were low in abundance. The combination between EEM-PARAFAC and PCA proved to be ideally suited to discern DOM composition and source differences in coastal zones with complex hydrology and multiple DOM sources.

Combined effects of short-term exposure to elevated CO2 and decreased O2 on the physiology and energy budget of the thick shell mussel Mytilus coruscus

Hypoxia and ocean acidification are two consequences of anthropogenic activities. These global trends occur on top of natural variability. In environments such as estuarine areas, short-term acute pH and O2 fluctuations are occurring simultaneously. The present study tested the combined effects of short-term seawater acidification and hypoxia on the physiology and energy budget of the thick shell mussel Mytilus coruscus. Mussels were exposed for 72 h to six combined treatments with three pH levels (8.1, 7.7 and 7.3) and two dissolved oxygen (DO) levels (2 mg/L, 6 mg/L). Clearance rate (CR), food absorption efficiency (AE), respiration rate (RR), ammonium excretion rate (ER), O:N ratio and scope for growth (SFG) were significantly reduced, and faecal organic dry weight ratio (E) was significantly increased at low DO. Low pH did not lead to a reduced SFG. Interactive effects of pH and DO were observed for CR, E and RR. Principal component analysis (PCA) revealed positive relationships among most physiological indicators, especially between SFG and CR under normal DO conditions. These results demonstrate that Mytilus coruscus was sensitive to short-term (72 h) exposure to decreased O2 especially if combined with decreased pH levels. In conclusion, the short-term oxygen and pH variation significantly induced physiological changes of mussels with some interactive effects.

Conservação genética da orquídea Cattleya granulosa Lindley

Cattleya granulosa Lind is a large and endemic orchid in Atlantic Forest fragments in Northeast Brazil. The facility of collecting, uniqueness of their flowers, which have varying colors between green and reddish brown, and distribution in coastal areas of economic interest make their populations a constant target of predation, which also suffer from environmental degradation. Due to the impact on their populations, the species is threatened. In this study, we evaluate the levels of spatial aggregation in a preserved population, analyze the phylogenetic relationships of C. granulosa Lindl. with four other Laeliinae species (Brassavola tuberculata, C. bicolor, C. labiata and C. schofieldiana) and also to evaluate the genetic diversity of 12 remaining populations of C. granulosa Lindl. through ISSR. There was specificity of epiphytic C. granula Lindl. with a single host tree, species of Eugenia sp. C. granulosa Lindl. own spatial pattern, with the highest density of neighbors within up to 5 m. Regarding the phylogenetic relationships and genetic patterns with other species of the genus, C. bicolor exhibited the greatest genetic diversity (HE = 0.219), while C. labiata exhibited the lowest level (HE = 0.132). The percentage of genetic variation among species (AMOVA) was 23.26%. The principal component analysis (PCA) of ISSR data showed that unifoliate and bifoliolate species are genetically divergent. PCA indicated a close relationship between C. granulosa Lindl. and C. schofieldiana, a species considered to be a variety of C. granulosa Lindl. by many researchers. Population genetic analysis using ISSR showed all polymorphic loci. The high genetic differentiation between populations (ФST = 0.391, P < 0.0001) determined the structure into nine groups according to log-likelihood of Bayesian analysis, with a similar pattern in the dendrogram (UPGMA) and PCA. A positive and significant correlation between geographic and genetic distances between populations was identified (r = 0.794, P = 0.017), indicating isolation by distance. Patterns of allelic diversity suggest the occurrence of population bottlenecks in most populations of C. granulosa Lindl. (n = 8). Genetic data indicate that enable the maintenance of genetic diversity of the species is complex and is directly related to the conservation of different units or groups that are spatially distant.

Determinação da concentração de metais no material particulado (PM10 e PM2,5) do ar atmosférico em uma área urbana da cidade do Natal – RN

This study aimed to assess ambient air quality in a urban area of Natal, capital of Rio Grande do Norte (latitude 5º49'29 '' S and longitude 35º13'34'' W), aiming to determine the metals concentration in particulate matter (PM10 and PM2,5) of atmospheric air in the urban area o the Natal city. The sampling period for the study consisted of data acquisition from January to December 2012. Samples were collected on glass fiber filters by means of two large volumes samplers, one for PM2,5 (AGV PM 2,5) and another for PM10 (PM10 AGV). Monthly averages ranged from 8.92 to 19.80 g.m-3 , where the annual average was 16,21 g.m-3 for PM10 and PM2,5 monthly averages ranged from 2,84 to 7,89 g.m -3 , with an annual average of 5,61 g.m-3 . The results of PM2,5 and PM10 concentrations were related meteorological variables and for information on the effects of these variables on the concentration of PM, an exploratory analysis of the data using Principal Component Analysis (PCA) was performed. The results of the PCA showed that with increasing barometric pressure, the direction of the winds, the rainfall and relative humidity decreases the concentration of PM and the variable weekday little influence compared the meteorological variables. Filters containing particulate matter were selected in six days and subjected to microwave digestion. After digestion samples were analyzed by with Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The concentrations for heavy metals Vanadium, Chromium, Manganese, Nickel, Copper, Arsenic and lead were determined. The highest concentrations of metals were for Pb and Cu, whose average PM10 values were, respectively, 5,34 and 2,34 ng.m-3 and PM2,5 4,68 and 2,95 ng.m-3 . Concentrations for metals V, Cr, Mn, Ni, and Cd were respectively 0,13, 0,39, 0,48, 0,45 and 0,03 ng.m-3 for PM10 fraction and PM2,5 fraction, 0,05, 0,10, 0,10, 0,34 and 0,01 ng.m-3. The concentration for As was null for the two fractions

Uso do índice de pobreza hídrica (WPI) através da análise de componentes principais

To contribute in the performance of policies and strategies formulated by development agencies, indexes have been created in anticipation of expressing the multiple dimensions of water resources in an easily interpretable form. Use of Hydro Poverty Index ( WPI) is spreading worldwide , with the same formed by the combination of sub - indices Resource, access, capacity , use and environment. S ome critics a s to its formation have emerged, a mong them stands out the allo cation of weights of sub - indexes , made by an arbitrary process attributing subjectivity to the selection criteria. By involving statistical analysis, when considering the characteristics of the variables generated by the Principal Component Analysis (PCA), it turns out that it is able to solve this problem. The objective of this study is to compare the results of the original WPI with content generated by Principal Com ponent Analysis (PCA) for the indicati on of the weights of sub - indec es applicable in the Seridó River hydrographic Basin . We conclude that the use of Principal Component Analysis in the allocation of weights of Water Poverty Index has identified the sub - indices Resources, Access and Environment are the most representative for the river basin Seridó , and that this new index, WPI' , presented the most comprehensive ranges of values , allowing more easily identify disparities among municipalities. In addition, t he evaluation of the sub - indec es in the study area has great potential to inform the decision - maker in the management of water resources, the most critical locations and deserve greater investments in the aspects analyzed, as the index itself can not cap ture this information.

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.

Exploring the joint compositional variability of major components and trace elements in the Tellus soil geochemistry survey (Northern Ireland)

The complexity of modern geochemical data sets is increasing in several aspects (number of available samples, number of elements measured, number of matrices analysed, geological-environmental variability covered, etc), hence it is becoming increasingly necessary to apply statistical methods to elucidate their structure. This paper presents an exploratory analysis of one such complex data set, the Tellus geochemical soil survey of Northern Ireland (NI). This exploratory analysis is based on one of the most fundamental exploratory tools, principal component analysis (PCA) and its graphical representation as a biplot, albeit in several variations: the set of elements included (only major oxides vs. all observed elements), the prior transformation applied to the data (none, a standardization or a logratio transformation) and the way the covariance matrix between components is estimated (classical estimation vs. robust estimation). Results show that a log-ratio PCA (robust or classical) of all available elements is the most powerful exploratory setting, providing the following insights: the first two processes controlling the whole geochemical variation in NI soils are peat coverage and a contrast between “mafic” and “felsic” background lithologies; peat covered areas are detected as outliers by a robust analysis, and can be then filtered out if required for further modelling; and peat coverage intensity can be quantified with the %Br in the subcomposition (Br, Rb, Ni).

Effect of Wealth on Health Care Seeking Behavior And Out of Pocket Health Expenditure in Malawi

Thesis (Master's)--University of Washington, 2016-06

Macroinvertebrate communities and habitat structure in least-impacted hill streams of central Portugal

We surveyed macroinvertebrate communities in 31 hill streams in the Vouga River and Mondego River catchments in central Portugal. Despite applying a "least-impacted" criterion, channel and bank management was common, with 38% of streams demonstrating channel modification (damming) and 80% with evidence of bank modification. Principal component analysis (PCA) at the family and species level related the macroinvertebrates to habitat variables derived at three spatial scales -- site (20 m), reach (200 m), and catchment. Variation in community structure between sites was similar at the species and family level and was statistically related to pH, conductivity, temperature, flow, shade, and substrate size at the site scale; channel and bank habitat and riparian vegetation and land-use at the reach scale; and altitude and slope at the catchment scale. While the effects of river management were apparent in various ecologically important habitat features at the site and reach scale, a direct relationship with macroinvertebrate assemblages was only apparent between the extent of walled banks and the secondary PCA axis described by species data. The strong relationship between catchment scale variables and descriptors of physical structure at the reach and site scale suggests that catchment-scale parameters are valuable predicators of macroinvertebrate community structure in these streams despite the anthropogenic modifications of the natural habitat.

Estrutura da comunidade arbórea e suas relações com fatores edáficos na floresta de restinga paludosa da Estrada Velha, Rio Grande, Rio Grande do Sul

(Estrutura da comunidade arbórea e suas relações com fatores edáficos na floresta de restinga paludosa da estrada Velha, Rio Grande, Rio Grande do Sul). O presente estudo tem como objetivo estudar a estrutura da comunidade arbórea da floresta de restinga paludosa da Estrada Velha (32º07’S; 52º09’W) localizada no município do Rio Grande, na Planície Costeira do Rio Grande do Sul e suas correlações com fatores edáficos. Para a amostragem do componente arbóreo foram demarcadas três transecções paralelas, ao longo das quais foram alocadas 30 unidades amostrais de 10m X 10m, de forma não contígua e amostrados todos os indivíduos com perímetro a altura do peito maior ou igual a 15 cm. Foram coletadas amostras de solo para análises químicas e granulométricas e realizadas medidas da coluna d’água nas unidades amostrais. Os principais parâmetros fitossociológicos foram estimados para descrever a estrutura da floresta, bem como os índices de Diversidade de Shannon (H’) e de Equabilidade de Pielou (J’). A similaridade com outras florestas no Rio Grande do Sul foi estimada pelo índice de Jaccard (ISj). As relações entre a abundância das espécies nas unidades amostrais e fatores edáficos foram avaliadas por meio de análise de componentes principais (PCA) e análise de correspondência canônica (CCA). Foram registrados 585 indivíduos distribuídos em 19 espécies, 17 gêneros e 16 famílias. A família com maior riqueza específica foi Moraceae e as espécies com maiores valores de importância foram Citronela gongonha (Mart.) R.A. Howard, Erythrina crista-galli L., Sebastiania brasiliensis Spreng., Ficus cestrifolia Schott. e Syagrus romanzoffiana (Cham.) Glassman. O Índice de diversidade foi 1,99 nat.ind-1 e o de Equabilidade foi 0,68. As análises multivariadas de ordenação evidenciaram um gradiente de distribuição das espécies correlacionado principalmente com a densidade de C. gongonha e fatores edáficos como pH, Ca, CTC(t), MO, K e nível de alagamento. O componente arbóreo mostrou similaridade florística (ISj) com outras florestas paludosas localizadas em maiores latitudes no Estado.

Padrões de organização das assembleias de aves florestais em uma paisagem fragmentada de Floresta Atlântica

Brazil is home to one of the richest avifaunas the world, which is subject to high levels of environmental degradation, in particular forest fragmentation. The Atlantic Forest biome depicts this history of devastation and today remains as small isolated fragments on highly degraded landscapes. This project aimed to evaluate the effects of forest fragmentation in an area with Atlantic Forest remnants in northern Paraná (Brazil) on the distribution and the organization of assemblage of forest birds and tested the hypothesis that the structure of the assembly in the fragments is different than expected by chance. We did four qualitative samplings of birds in three sets of forest fragments in the landscape, each with three fragments: large, medium and small. The method applied in the sampling was point counts along transects, traveled randomly for four hours in each fragment. Samples were taken in two periods: from September to November / 2013, and between March and May / 2014. The structure of the meeting was assessed by rates of co-occurring species (Checkerboard and CScore) and α diversity patterns (wealth) and β (turnover of species), while the landscape structure was analyzed from the parameters: area, distance between fragments, fractal dimension, edge density, fragment shape index and nuclear area index. The null hypothesis of no structure in the assembly of birds in the landscape was tested with null models from the co-occurrence indexes. The effects of landscape structure on the assembly of the structure were analyzed by the Mantel test and principal component analysis (PCA). The assembly of the structure in the landscape showed a pattern of spatiotemporal organization significantly different from that expected by chance, revealing a structure most influenced by segregation of the species. The fragments showed significant differences in richness, unlike sets of fragments, indicating relative homogeneity in the landscape structure. The differences between the size and the distance between the fragments significantly influenced the patterns of organization of the meeting of forest birds in the landscape and patterns of α and β diversity, indicating that the higher the fragment and smaller distances between them, more the standard of species cooccurrence is different than expected by chance. Thus, the fragmented landscape of remnants of the northern Paraná Atlantic Forest still has availability of environmental resources and physical characteristics that allow a persistent organizational structure of the assembly of forest birds in space over time.

Estrutura e dinâmica de populações de Hydrochoerus hydrochaeris (Linnaeus, 1766) (Rodentia) em duas áreas urbanas no norte do Paraná, Brasil

This study aimed to evaluate the population ecology of Hydrochoerus hydrochaeris (Linnaeus, 1766) in two urban areas in the north of Paraná, an open and other protected by assessing the effects of these two different types of environments on the structure and dynamics of the population and its implications for conservation of the species. The monitoring of the populations were performed monthly between June 2014 and March 2015 in Jaboti Lake Park (Apucarana / PR) and Conservation Unit Parque Arthur Thomas (Londrina / PR). To conduct the survey population data was used the methodology of total census (direct counting of individuals).They were evaluated ecological parameters of the populations of capybaras, such as ecological density, abundance, age distribution and birth rate, as well as performed the analysis of the landscape. It was applied to analysis of variance (ANOVA) to test the differences between the averages of the abundance of each age group per year of observation, as well as the differences between the average ecological density over the years of observation. The standard relationship between the use of classes and land use in the landscape and the ecological parameters of the capybara populations was evaluated by Principal Component Analysis (PCA). The trend of variation of average abundance over time to Thomas Arthur Park revealed abrupt decrease of the population in a short period of time (2014 16 ± 9, 14 ± 1 and 2015 7±1) as well as ecological density in 2015 (0.05 ind./ha). On the other hand, the Jaboti Lake Park, showed an increase in absolute abundance, with marked recovery of the population in the same period (2014 38±8,30 and 2015 45±1,73) and coming up with an ecological density in 2015 (2 ind ./ha). The birth rate found Lake Park Jaboti was superior to Arthur Thomas Park, which had a negative rate between 2012 and 2015. The use and land cover analysis showed significant differences from the point of view of the relative contribution of landscape elements in the spatial heterogeneity. Arthur Thomas Park shows areas of dense vegetation and urban areas relatively higher than those observed in Jaboti Lake Park that revealed relatively higher proportions of the areas of agriculture / field and exposed soil. Thus, the present study revealed that the local population structure is directly related to the spatial characteristics of both studied landscapes, as can be seen by the greater abundance and density seen in Jaboti Lake Park compared to Arthur Thomas Park in recent years of study.