The impact of spatial scales and spatial smoothing on the outcome of Bayesian spatial model

Discretization of a geographical region is quite common in spatial analysis. There have been few studies into the impact of different geographical scales on the outcome of spatial models for different spatial patterns. This study aims to investigate the impact of spatial scales and spatial smoothing on the outcomes of modelling spatial point-based data. Given a spatial point-based dataset (such as occurrence of a disease), we study the geographical variation of residual disease risk using regular grid cells. The individual disease risk is modelled using a logistic model with the inclusion of spatially unstructured and/or spatially structured random effects. Three spatial smoothness priors for the spatially structured component are employed in modelling, namely an intrinsic Gaussian Markov random field, a second-order random walk on a lattice, and a Gaussian field with Matern correlation function. We investigate how changes in grid cell size affect model outcomes under different spatial structures and different smoothness priors for the spatial component. A realistic example (the Humberside data) is analyzed and a simulation study is described. Bayesian computation is carried out using an integrated nested Laplace approximation. The results suggest that the performance and predictive capacity of the spatial models improve as the grid cell size decreases for certain spatial structures. It also appears that different spatial smoothness priors should be applied for different patterns of point data.

Spatial analysis of community-onset Staphylococcus aureus bacteremia in Queensland, Australia

OBJECTIVES To investigate and describe the relationship between indigenous Australian populations, residential aged care services, and community-onset Staphylococcus aureus bacteremia (SAB) among patients admitted to public hospitals in Queensland, Australia. DESIGN Ecological study. METHODS We used administrative healthcare data linked to microbiology results from patients with SAB admitted to Queensland public hospitals from 2005 through 2010 to identify community-onset infections. Data about indigenous Australian population and residential aged care services at the local government area level were obtained from the Queensland Office of Economic and Statistical Research. Associations between community-onset SAB and indigenous Australian population and residential aged care services were calculated using Poisson regression models in a Bayesian framework. Choropleth maps were used to describe the spatial patterns of SAB risk. RESULTS We observed a 21% increase in relative risk (RR) of bacteremia with methicillin-susceptible S. aureus (MSSA; RR, 1.21 [95% credible interval, 1.15-1.26]) and a 24% increase in RR with nonmultiresistant methicillin-resistant S. aureus (nmMRSA; RR, 1.24 [95% credible interval, 1.13-1.34]) with a 10% increase in the indigenous Australian population proportion. There was no significant association between RR of SAB and the number of residential aged care services. Areas with the highest RR for nmMRSA and MSSA bacteremia were identified in the northern and western regions of Queensland. CONCLUSIONS The RR of community-onset SAB varied spatially across Queensland. There was increased RR of community-onset SAB with nmMRSA and MSSA in areas of Queensland with increased indigenous population proportions. Additional research should be undertaken to understand other factors that increase the risk of infection due to this organism.

Characterising the spatial dynamics of sympatric Aedes aegypti and Aedes albopictus populations in the Philippines

Entomological surveillance and control are essential to the management of dengue fever (DF). Hence, understanding the spatial and temporal patterns of DF vectors, Aedes (Stegomyia) aegypti (L.) and Ae. (Stegomyia) albopictus (Skuse), is paramount. In the Philippines, resources are limited and entomological surveillance and control are generally commenced during epidemics, when transmission is difficult to control. Recent improvements in spatial epidemiological tools and methods offer opportunities to explore more efficient DF surveillance and control solutions: however, there are few examples in the literature from resource-poor settings. The objectives of this study were to: (i) explore spatial patterns of Aedes populations and (ii) predict areas of high and low vector density to inform DF control in San Jose village, Muntinlupa city, Philippines. Fortnightly, adult female Aedes mosquitoes were collected from 50 double-sticky ovitraps (SOs) located in San Jose village for the period June-November 2011. Spatial clustering analysis was performed to identify high and low density clusters of Ae. aegypti and Ae. albopictus mosquitoes. Spatial autocorrelation was assessed by examination of semivariograms, and ordinary kriging was undertaken to create a smoothed surface of predicted vector density in the study area. Our results show that both Ae. aegypti and Ae. albopictus were present in San Jose village during the study period. However, one Aedes species was dominant in a given geographic area at a time, suggesting differing habitat preferences and interspecies competition between vectors. Density maps provide information to direct entomological control activities and advocate the development of geographically enhanced surveillance and control systems to improve DF management in the Philippines.

Inferring lung cancer risk factor patterns through joint Bayesian spatio-temporal analysis

Background: Preventing risk factor exposure is vital to reduce the high burden from lung cancer. The leading risk factor for developing lung cancer is tobacco smoking. In Australia, despite apparent success in reducing smoking prevalence, there is limited information on small area patterns and small area temporal trends. We sought to estimate spatio-temporal patterns for lung cancer risk factors using routinely collected population-based cancer data. Methods: The analysis used a Bayesian shared component spatio-temporal model, with male and female lung cancer included separately. The shared component reflected exposure to lung cancer risk factors, and was modelled over 477 statistical local areas (SLAs) and 15 years in Queensland, Australia. Analyses were also run adjusting for area-level socioeconomic disadvantage, Indigenous population composition, or remoteness. Results: Strong spatial patterns were observed in the underlying risk factor exposure for both males (median Relative Risk (RR) across SLAs compared to the Queensland average ranged from 0.48-2.00) and females (median RR range across SLAs 0.53-1.80), with high exposure observed in many remote areas. Strong temporal trends were also observed. Males showed a decrease in the underlying risk across time, while females showed an increase followed by a decrease in the final two years. These patterns were largely consistent across each SLA. The high underlying risk estimates observed among disadvantaged, remote and indigenous areas decreased after adjustment, particularly among females. Conclusion: The modelled underlying exposure appeared to reflect previous smoking prevalence, with a lag period of around 30 years, consistent with the time taken to develop lung cancer. The consistent temporal trends in lung cancer risk factors across small areas support the hypothesis that past interventions have been equally effective across the state. However, this also means that spatial inequalities have remained unaddressed, highlighting the potential for future interventions, particularly among remote areas.

Identification of bacterial community composition in freshwater aquaculture system farming of Litopenaeus vannamei reveals distinct temperature-driven patterns

Change in temperature is often a major environmental factor in triggering waterborne disease outbreaks. Previous research has revealed temporal and spatial patterns of bacterial population in several aquatic ecosystems. To date, very little information is available on aquaculture environment. Here, we assessed environmental temperature effects on bacterial community composition in freshwater aquaculture system farming of Litopenaeus vannamei (FASFL). Water samples were collected over a one-year period, and aquatic bacteria were characterized by polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) and 16S rDNA pyrosequencing. Resulting DGGE fingerprints revealed a specific and dynamic bacterial population structure with considerable variation over the seasonal change, suggesting that environmental temperature was a key driver of bacterial population in the FASFL. Pyrosequencing data further demonstrated substantial difference in bacterial community composition between the water at higher (WHT) and at lower (WLT) temperatures in the FASFL. Actinobacteria, Proteobacteria and Bacteroidetes were the highest abundant phyla in the FASFL, however, a large number of unclassified bacteria contributed the most to the observed variation in phylogenetic diversity. The WHT harbored remarkably higher diversity and richness in bacterial composition at genus and species levels when compared to the WLT. Some potential pathogenenic species were identified in both WHT and WLT, providing data in support of aquatic animal health management in the aquaculture industry.

Comparing multilevel and Bayesian spatial random effects survival models to assess geographical inequalities in colorectal cancer survival: a case study

Background Multilevel and spatial models are being increasingly used to obtain substantive information on area-level inequalities in cancer survival. Multilevel models assume independent geographical areas, whereas spatial models explicitly incorporate geographical correlation, often via a conditional autoregressive prior. However the relative merits of these methods for large population-based studies have not been explored. Using a case-study approach, we report on the implications of using multilevel and spatial survival models to study geographical inequalities in all-cause survival. Methods Multilevel discrete-time and Bayesian spatial survival models were used to study geographical inequalities in all-cause survival for a population-based colorectal cancer cohort of 22,727 cases aged 20–84 years diagnosed during 1997–2007 from Queensland, Australia. Results Both approaches were viable on this large dataset, and produced similar estimates of the fixed effects. After adding area-level covariates, the between-area variability in survival using multilevel discrete-time models was no longer significant. Spatial inequalities in survival were also markedly reduced after adjusting for aggregated area-level covariates. Only the multilevel approach however, provided an estimation of the contribution of geographical variation to the total variation in survival between individual patients. Conclusions With little difference observed between the two approaches in the estimation of fixed effects, multilevel models should be favored if there is a clear hierarchical data structure and measuring the independent impact of individual- and area-level effects on survival differences is of primary interest. Bayesian spatial analyses may be preferred if spatial correlation between areas is important and if the priority is to assess small-area variations in survival and map spatial patterns. Both approaches can be readily fitted to geographically enabled survival data from international settings

Muscle activation patterns in the Nordic hamstring exercise: Impact of prior strain injury

This study aimed to determine: 1) the spatial patterns of hamstring activation during the Nordic hamstring exercise (NHE); 2) whether previously injured hamstrings display activation deficits during the NHE, and; 3) whether previously injured hamstrings exhibit altered cross-sectional area. Ten healthy, recreationally active males with a history of unilateral hamstring strain injury underwent functional magnetic resonance imaging (fMRI) of their thighs before and after 6 sets of 10 repetitions of the NHE. Transverse (T2) relaxation times of all hamstring muscles (biceps femoris long head, (BFlh); biceps femoris short head (BFsh); semitendinosus (ST); semimembranosus (SM)), were measured at rest and immediately after the NHE and cross-sectional area (CSA) was measured at rest. For the uninjured limb, the ST’s percentage increase in T2 with exercise was 16.8, 15.8 and 20.2% greater than the increases exhibited by the BFlh, BFsh and SM, respectively (p<0.002 for all). Previously injured hamstring muscles (n=10) displayed significantly smaller increases in T2 post-exercise than the homonymous muscles in the uninjured contralateral limb (mean difference -7.2%, p=0.001). No muscles displayed significant between limb differences in CSA. During the NHE, the ST is preferentially activated and previously injured hamstring muscles display chronic activation deficits compared to uninjured contralateral muscles.

Insights to urban dynamics through landscape spatial pattern analysis

Urbanisation is a dynamic complex phenomenon involving large scale changes in the land uses at local levels. Analyses of changes in land uses in urban environments provide a historical perspective of land use and give an opportunity to assess the spatial patterns, correlation, trends, rate and impacts of the change, which would help in better regional planning and good governance of the region. Main objective of this research is to quantify the urban dynamics using temporal remote sensing data with the help of well-established landscape metrics. Bangalore being one of the rapidly urbanising landscapes in India has been chosen for this investigation. Complex process of urban sprawl was modelled using spatio temporal analysis. Land use analyses show 584% growth in built-up area during the last four decades with the decline of vegetation by 66% and water bodies by 74%. Analyses of the temporal data reveals an increase in urban built up area of 342.83% (during 1973-1992), 129.56% (during 1992-1999), 106.7% (1999-2002), 114.51% (2002-2006) and 126.19% from 2006 to 2010. The Study area was divided into four zones and each zone is further divided into 17 concentric circles of 1 km incrementing radius to understand the patterns and extent of the urbanisation at local levels. The urban density gradient illustrates radial pattern of urbanisation for the period 1973-2010. Bangalore grew radially from 1973 to 2010 indicating that the urbanisation is intensifying from the central core and has reached the periphery of the Greater Bangalore. Shannon's entropy, alpha and beta population densities were computed to understand the level of urbanisation at local levels. Shannon's entropy values of recent time confirms dispersed haphazard urban growth in the city, particularly in the outskirts of the city. This also illustrates the extent of influence of drivers of urbanisation in various directions. Landscape metrics provided in depth knowledge about the sprawl. Principal component analysis helped in prioritizing the metrics for detailed analyses. The results clearly indicates that whole landscape is aggregating to a large patch in 2010 as compared to earlier years which was dominated by several small patches. The large scale conversion of small patches to large single patch can be seen from 2006 to 2010. In the year 2010 patches are maximally aggregated indicating that the city is becoming more compact and more urbanised in recent years. Bangalore was the most sought after destination for its climatic condition and the availability of various facilities (land availability, economy, political factors) compared to other cities. The growth into a single urban patch can be attributed to rapid urbanisation coupled with the industrialisation. Monitoring of growth through landscape metrics helps to maintain and manage the natural resources. (C) 2012 Elsevier B.V. All rights reserved.

Regional and seasonal patterns of epipelagic fish assemblages from the central California Current

The coastal Pacific Ocean off northern and central California encompasses the strongest seasonal upwelling zone in the California Current ecosystem. Headlands and bays here generate complex circulation features and confer unusual oceanographic complexity. We sampled the coastal epipelagic fish community of this region with a surface trawl in the summer and fall of 2000–05 to assess patterns of spatial and temporal community structure. Fifty-three species of fish were captured in 218 hauls at 34 fixed stations, with clupeiform species dominating. To examine spatial patterns, samples were grouped by location relative to a prominent headland at Point Reyes and the resulting two regions, north coast and Gulf of the Farallones, were plotted by using nonmetric multidimensional scaling. Seasonal and interannual patterns were also examined, and representative species were identified for each distinct community. Seven oceanographic variables measured concurrently with trawling were plotted by principal components analysis and tested for correlation with biotic patterns. We found significant differences in community structure by region, year, and season, but no interaction among main effects. Significant differences in oceanographic conditions mirrored the biotic patterns, and a match between biotic and hydrographic structure was detected. Dissimilarity between assemblages was mostly the result of differences in abundance and frequency of occurrence of about twelve common species. Community patterns were best described by a subset of hydrographic variables, including water depth, distance from shore, and any one of several correlated variables associated with upwelling intensity. Rather than discrete communities with clear borders and distinct member species, we found gradients in community structure and identified stations with similar fish communities by region and by proximity to features such as the San Francisco Bay.

Estimating exploitable stock biomass for the Maine green sea urchin (Strongylocentrotus droebachiensis) fishery using a spatial statistics approach

The objective of this study was to investigate the spatial patterns in green sea urchin (Strongylocentrotus droebachiensis) density off the coast of Maine, using data from a fishery-independent survey program, to estimate the exploitable biomass of this species. The dependence of sea urchin variables on the environment, the lack of stationarity, and the presence of discontinuities in the study area made intrinsic geostatistics inappropriate for the study; therefore, we used triangulated irregular networks (TINs) to characterize the large-scale patterns in sea urchin density. The resulting density surfaces were modified to include only areas of the appropriate substrate type and depth zone, and were used to calculate total biomass. Exploitable biomass was estimated by using two different sea urchin density threshold values, which made different assumptions about the fishing industry. We observed considerable spatial variability on both small and large scales, including large-scale patterns in sea urchin density related to depth and fishing pressure. We conclude that the TIN method provides a reasonable spatial approach for generating biomass estimates for a fishery unsuited to geostatistics, but we suggest further studies into uncertainty estimation and the selection of threshold density values.

Fish movement patterns in Virgin Islands National Park, Virgin Islands Coral Reef National Monument and adjacent waters

NOAA’s National Centers for Coastal Ocean Science (NCCOS)-Center for Coastal Monitoring and Assessment’s (CCMA) Biogeography Branch, National Park Service (NPS), US Geological Survey, and the University of Hawaii used acoustic telemetry to quantify spatial patterns and habitat affinities of reef fishes around the island of St. John, US Virgin Islands. The objective of the study was to define the movements of reef fishes among habitats within and between the Virgin Islands Coral Reef National Monument (VICRNM), the Virgin Islands National Park (VIIS), and Territorial waters surrounding St. John. In order to better understand species’ habitat utilization patterns among management regimes, we deployed an array of hydroacoustic receivers and acoustically tagged reef fishes. Thirty six receivers were deployed in shallow near-shore bays and across the shelf to depths of approximately 30 m. One hundred eighty four individual fishes were tagged representing 19 species from 10 different families with VEMCO V9-2L-R64K transmitters. The array provides fish movement information at fine (e.g., day-night and 100s meters within a bay) to broad spatial and temporal scales (multiple years and 1000s meters across the shelf). The long term multi-year tracking project provides direct evidence of connectivity across habitat types in the seascape and among management units. An important finding for management was that a number of individuals moved among management units (VICRNM, VINP, Territorial waters) and several snapper moved from near-shore protected areas to offshore shelf-edge spawning aggregations. However, most individuals spent the majority of their time with VIIS and VICRNM, with only a few wide-ranging species moving outside the management units. Five species of snappers (Lutjanidae) accounted for 31% of all individuals tagged, followed by three species of grunts (Haemulidae) accounting for an additional 23% of the total. No other family had more than a single species represented in the study. Bluestripe grunt (Haemulon sciurus) comprised 22% of all individuals tagged, followed by lane snappers (Lutjanus synagris) at 21%, bar jack (Carangoides ruber) at 11%, and saucereye porgy (Calamus calamus) at 10%. The largest individual tagged was a 70 cm TL nurse shark (Ginglymostoma cirratum), followed by a 65 cm mutton snapper (Lutjanus analis), a 47 cm bar jack, and a 41 cm dog snapper (Lutjanus jocu). The smallest individuals tagged were a 19 cm blue tang (Acanthurus coeruleus) and a 19.2 cm doctorfish (Acanthurus chirurgus). Of the 40 bluestriped grunt acoustically tagged, 73% were detected on the receiver array. The average days at large (DAL) was 249 (just over 8 months), with one individual detected for 930 days (over two and a half years). Lane snapper were the next most abundant species tagged (N = 38) with 89% detected on the array. The average days at large (DAL) was 221 with one individual detected for 351 days. Seventy-one percent of the bar jacks (N = 21) were detected on the array with the average DALs at 47 days. All of the mutton snapper (N = 12) were detected on the array with an average DAL of 273 and the longest at 784. The average maximum distance travelled (MDT) was ca. 2 km with large variations among species. Grunts, snappers, jacks, and porgies showed the greatest movements. Among all individuals across species, there was a positive and significant correlation between size of individuals and MDT and between DAL and MDT.

Quantifying seascape structure: extending terrestrial spatial pattern metrics to the marine realm

Spatial pattern metrics have routinely been applied to characterize and quantify structural features of terrestrial landscapes and have demonstrated great utility in landscape ecology and conservation planning. The important role of spatial structure in ecology and management is now commonly recognized, and recent advances in marine remote sensing technology have facilitated the application of spatial pattern metrics to the marine environment. However, it is not yet clear whether concepts, metrics, and statistical techniques developed for terrestrial ecosystems are relevant for marine species and seascapes. To address this gap in our knowledge, we reviewed, synthesized, and evaluated the utility and application of spatial pattern metrics in the marine science literature over the past 30 yr (1980 to 2010). In total, 23 studies characterized seascape structure, of which 17 quantified spatial patterns using a 2-dimensional patch-mosaic model and 5 used a continuously varying 3-dimensional surface model. Most seascape studies followed terrestrial-based studies in their search for ecological patterns and applied or modified existing metrics. Only 1 truly unique metric was found (hydrodynamic aperture applied to Pacific atolls). While there are still relatively few studies using spatial pattern metrics in the marine environment, they have suffered from similar misuse as reported for terrestrial studies, such as the lack of a priori considerations or the problem of collinearity between metrics. Spatial pattern metrics offer great potential for ecological research and environmental management in marine systems, and future studies should focus on (1) the dynamic boundary between the land and sea; (2) quantifying 3-dimensional spatial patterns; and (3) assessing and monitoring seascape change.

Acoustic tracking of reef fishes to elucidate habitat utilization patterns and residence times inside and outside marine protected areas around the island of St. John, USVI

This technical memorandum describes a developing project under the direction of NOAA’s Biogeography Branch in consultation with the National Park Service and US Geological Survey to understand and quantify spatial patterns and habitat affinities of reef fishes in the US Virgin Islands. The purpose of this report is to describe and disseminate the initial results from the project and to share information on the location of acoustic receivers and species electronic tag ID codes. The Virgin Islands Coral Reef National Monument (VICRNM), adjacent to Virgin Islands National Park (VIIS), was established by Executive Order in 2000, but resources within the monument are poorly documented and the degree of connectivity to VIIS is unknown. Whereas, VICRNM was established with full protection from resource exploitation, VIIS has incurred resource harvest by fishers since 1956 as allowed in its enabling legislation. Large changes in local reef communities have occurred over the past several decades, in part due to overexploitation. In order to better understand the habitat utilization patterns and movement of fishes among management regimes and areas open to fishing around St, John, an array of hydroacoustic receivers was deployed while a variety of reef fish species were acoustically tagged. In July 2006, nine receivers with a detection range of ca. 350 m were deployed in Lameshur Bay on the south shore of St. John, within VIIS. Receivers were located adjacent to reefs and in seagrass beds, inshore and offshore of these reefs. It was found that lane snappers and bluestriped grunts showed diel movement from reef habitats during daytime hours to offshore seagrass bed at night. Timing of migrations was highly predictable and coincided with changes in sunrise and sunset over the course of the year. Fish associated with reefs that did not have adjacent seagrass beds made more extensive movements than those fishes associated with reefs that had adjacent seagrass habitats. In April 2007, 21 additional receivers were deployed along much of the south shore of St. John (ca. 20 km of shoreline). This current array will address broader-scale movement among management units and examine the potential benefits of the VICRNM to provide adult “spillover” into VIIS and adjacent harvested areas. The results from this work will aid in defining fine to moderate spatial scales of reef fish habitat affinities and in designing and evaluating marine protected areas.

The spatial pattern of the small fish community in the Biandantang Lake - a small shallow lake along the middle reach of the Yangtze River, China

The spatial pattern of the small fish community was studied seasonally in 1996 in the Biandantang Lake. Based on plant cover, the lake was divided into five habitats, arranged in the order by plant structure complexity from complex to simple: Vallisneria spiralis habitat (V habitat), Vallisneria spiralis-Myriophyllum spicatum habitat (V-M habitat), Myriophyllum spicatum habitat (M habitat), Nelunbo nucefera habitat (N habitat), and no vegetation habitat (NV habitat). A modified popnet was used for quantitative sampling of small fishes. A total of 16 fish species were collected; Hypseleotris swinhonis, Ctenogobius giurinus, Pseudorasbora parva, Carassius auratus and Paracheilognathus imberis were the five numerically dominant species. In both summer and autumn, the total density of small fishes was about 10 ind m(-2). Generally, Ctenogobius giurinus, a sedatory, benthic fish, was distributed more or less evenly among the five habitats, while the other four species had lower densities in the N habitat and NV habitat, which had the simplest structures. The distribution of the small fish species showed seasonal variations. In winter, most species concentrated in the V habitat, which had the most complex structure. In spring, the fish had low densities in the N and NV habitat, and were more or less evenly distributed in the other habitats. In summer, the fish had a low density in the NV habitat, and were evenly distributed in the other habitats. In autumn, the fish had higher densities in the V-M and M habitats than in the others. Generally, spatial overlaps between the dominant species were higher in winter than in the other seasons. It was suggested that the variations in the importance of predation risk and resource competition in habitat choice determined the seasonal changes of spatial patterns in the small fishes in the Biandantang Lake.

Spatial variability in water quality and surface sediment diatom assemblages in a complex lake basin,lake of the woods,ontario,canada

Lake of the Woods (LOW) is an international waterbody spanning the Canadian provinces of Ontario and Manitoba, and the U.S. state of Minnesota. In recent years, there has been a perception that water quality has deteriorated in northern regions of the lake, with all increase in the frequency and intensity of toxin-producing cyanobacterial blooms. However, given the lack of long-term data these trends are difficult to verify. As a first step, we examine spatial and seasonal patterns in water quality in this highly complex lake on the Canadian Shield. Further, we examine surface sediment diatom assemblages across multiple sites to determine if they track within-take differences in environmental conditions. Our results show that there are significant spatial patterns in water quality in LOW. Principal Component Analysis divides the lake into three geographic zones based primarily on algal nutrients (i.e., total phosphorus, TP), with the highest concentrations at sites proximal to Rainy River. This variation is closely tracked by sedimentary diatom assemblages, with [TP] explaining 43% of the variation in diatom assemblages across sites. The close correlation between water quality and the surface sediment diatom record indicate that paleoecological models could be used to provide data on the relative importance of natural and anthropogenic sources of nutrients to the lake.