Displaying publications 1 - 20 of 36 in total

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  1. Sanchez-Bezanilla S, Hood RJ, Collins-Praino LE, Turner RJ, Walker FR, Nilsson M, et al.
    J Cereb Blood Flow Metab, 2021 09;41(9):2439-2455.
    PMID: 33779358 DOI: 10.1177/0271678X211005877
    There is emerging evidence suggesting that a cortical stroke can cause delayed and remote hippocampal dysregulation, leading to cognitive impairment. In this study, we aimed to investigate motor and cognitive outcomes after experimental stroke, and their association with secondary neurodegenerative processes. Specifically, we used a photothrombotic stroke model targeting the motor and somatosensory cortices of mice. Motor function was assessed using the cylinder and grid walk tasks. Changes in cognition were assessed using a mouse touchscreen platform. Neuronal loss, gliosis and amyloid-β accumulation were investigated in the peri-infarct and ipsilateral hippocampal regions at 7, 28 and 84 days post-stroke. Our findings showed persistent impairment in cognitive function post-stroke, whilst there was a modest spontaneous motor recovery over the investigated period of 84 days. In the peri-infarct region, we detected a reduction in neuronal loss and decreased neuroinflammation over time post-stroke, which potentially explains the spontaneous motor recovery. Conversely, we observed persistent neuronal loss together with concomitant increased neuroinflammation and amyloid-β accumulation in the hippocampus, which likely accounts for the persistent cognitive dysfunction. Our findings indicate that cortical stroke induces secondary neurodegenerative processes in the hippocampus, a region remote from the primary infarct, potentially contributing to the progression of post-stroke cognitive impairment.
    Matched MeSH terms: Spatio-Temporal Analysis*
  2. Asghar MA, Khan MJ, Rizwan M, Shorfuzzaman M, Mehmood RM
    Multimed Syst, 2021 Apr 21.
    PMID: 33897112 DOI: 10.1007/s00530-021-00782-w
    Classification of human emotions based on electroencephalography (EEG) is a very popular topic nowadays in the provision of human health care and well-being. Fast and effective emotion recognition can play an important role in understanding a patient's emotions and in monitoring stress levels in real-time. Due to the noisy and non-linear nature of the EEG signal, it is still difficult to understand emotions and can generate large feature vectors. In this article, we have proposed an efficient spatial feature extraction and feature selection method with a short processing time. The raw EEG signal is first divided into a smaller set of eigenmode functions called (IMF) using the empirical model-based decomposition proposed in our work, known as intensive multivariate empirical mode decomposition (iMEMD). The Spatio-temporal analysis is performed with Complex Continuous Wavelet Transform (CCWT) to collect all the information in the time and frequency domains. The multiple model extraction method uses three deep neural networks (DNNs) to extract features and dissect them together to have a combined feature vector. To overcome the computational curse, we propose a method of differential entropy and mutual information, which further reduces feature size by selecting high-quality features and pooling the k-means results to produce less dimensional qualitative feature vectors. The system seems complex, but once the network is trained with this model, real-time application testing and validation with good classification performance is fast. The proposed method for selecting attributes for benchmarking is validated with two publicly available data sets, SEED, and DEAP. This method is less expensive to calculate than more modern sentiment recognition methods, provides real-time sentiment analysis, and offers good classification accuracy.
    Matched MeSH terms: Spatio-Temporal Analysis
  3. Ooi CH, Phang WK, Kent Liew JW, Lau YL
    Am J Trop Med Hyg, 2021 Mar 22;104(5):1814-1819.
    PMID: 33755585 DOI: 10.4269/ajtmh.20-1304
    Zoonotic knowlesi malaria has replaced human malaria as the most prevalent malaria disease in Malaysia. The persistence of knowlesi malaria in high-risk transmission areas or hotspots can be discouraging to existing malaria elimination efforts. In this study, retrospective data of laboratory-confirmed knowlesi malaria cases were obtained from the Sarawak Health Department to investigate the spatiotemporal patterns and clustering of knowlesi malaria in the state of Sarawak from 2008 to 2017. Purely spatial, purely temporal, and spatiotemporal analyses were performed using SaTScan software to define clustering of knowlesi malaria incidence. Purely spatial and spatiotemporal analyses indicated most likely clusters of knowlesi malaria in the northern region of Sarawak, along the Sarawak-Kalimantan border, and the inner central region of Sarawak between 2008 and 2017. Temporal cluster was detected between September 2016 and December 2017. This study provides evidence of the existence of statistically significant Plasmodium knowlesi malaria clusters in Sarawak, Malaysia. The analysis approach applied in this study showed potential in establishing surveillance and risk management system for knowlesi malaria control as Malaysia approaches human malaria elimination.
    Matched MeSH terms: Spatio-Temporal Analysis*
  4. Phang WK, Hamid MHA, Jelip J, Mudin RN, Chuang TW, Lau YL, et al.
    PMID: 33322414 DOI: 10.3390/ijerph17249271
    The life-threatening zoonotic malaria cases caused by Plasmodium knowlesi in Malaysia has recently been reported to be the highest among all malaria cases; however, previous studies have mainly focused on the transmission of P. knowlesi in Malaysian Borneo (East Malaysia). This study aimed to describe the transmission patterns of P. knowlesi infection in Peninsular Malaysia (West Malaysia). The spatial distribution of P. knowlesi was mapped across Peninsular Malaysia using Geographic Information System techniques. Local indicators of spatial associations were used to evaluate spatial patterns of P. knowlesi incidence. Seasonal autoregressive integrated moving average models were utilized to analyze the monthly incidence of knowlesi malaria in the hotspot region from 2012 to 2017 and to forecast subsequent incidence in 2018. Spatial analysis revealed that hotspots were clustered in the central-northern region of Peninsular Malaysia. Time series analysis revealed the strong seasonality of transmission from January to March. This study provides fundamental information on the spatial distribution and temporal dynamic of P. knowlesi in Peninsular Malaysia from 2011 to 2018. Current control policy should consider different strategies to prevent the transmission of both human and zoonotic malaria, particularly in the hotspot region, to ensure a successful elimination of malaria in the future.
    Matched MeSH terms: Spatio-Temporal Analysis
  5. Tabasi M, Alesheikh AA, Sofizadeh A, Saeidian B, Pradhan B, AlAmri A
    Parasit Vectors, 2020 Nov 11;13(1):572.
    PMID: 33176858 DOI: 10.1186/s13071-020-04447-x
    BACKGROUND: Zoonotic cutaneous leishmaniasis (ZCL) is a neglected tropical disease worldwide, especially the Middle East. Although previous works attempt to model the ZCL spread using various environmental factors, the interactions between vectors (Phlebotomus papatasi), reservoir hosts, humans, and the environment can affect its spread. Considering all of these aspects is not a trivial task.

    METHODS: An agent-based model (ABM) is a relatively new approach that provides a framework for analyzing the heterogeneity of the interactions, along with biological and environmental factors in such complex systems. The objective of this research is to design and develop an ABM that uses Geospatial Information System (GIS) capabilities, biological behaviors of vectors and reservoir hosts, and an improved Susceptible-Exposed-Infected-Recovered (SEIR) epidemic model to explore the spread of ZCL. Various scenarios were implemented to analyze the future ZCL spreads in different parts of Maraveh Tappeh County, in the northeast region of Golestan Province in northeastern Iran, with alternative socio-ecological conditions.

    RESULTS: The results confirmed that the spread of the disease arises principally in the desert, low altitude areas, and riverside population centers. The outcomes also showed that the restricting movement of humans reduces the severity of the transmission. Moreover, the spread of ZCL has a particular temporal pattern, since the most prevalent cases occurred in the fall. The evaluation test also showed the similarity between the results and the reported spatiotemporal trends.

    CONCLUSIONS: This study demonstrates the capability and efficiency of ABM to model and predict the spread of ZCL. The results of the presented approach can be considered as a guide for public health management and controlling the vector population .

    Matched MeSH terms: Spatio-Temporal Analysis*
  6. Ganasegeran K, Ch'ng ASH, Aziz ZA, Looi I
    Sci Rep, 2020 Jul 09;10(1):11353.
    PMID: 32647336 DOI: 10.1038/s41598-020-68335-1
    Stroke has emerged as a major public health concern in Malaysia. We aimed to determine the trends and temporal associations of real-time health information-seeking behaviors (HISB) and stroke incidences in Malaysia. We conducted a countrywide ecological correlation and time series study using novel internet multi-timeline data stream of 6,282 hit searches and conventional surveillance data of 14,396 stroke cases. We searched popular search terms related to stroke in Google Trends between January 2004 and March 2019. We explored trends by comparing average relative search volumes (RSVs) by month and weather through linear regression bootstrapping methods. Geographical variations between regions and states were determined through spatial analytics. Ecological correlation analysis between RSVs and stroke incidences was determined via Pearson's correlations. Forecasted model was yielded through exponential smoothing. HISB showed both cyclical and seasonal patterns. Average RSV was significantly higher during Northeast Monsoon when compared to Southwest Monsoon (P 
    Matched MeSH terms: Spatio-Temporal Analysis
  7. Zohner CM, Mo L, Renner SS, Svenning JC, Vitasse Y, Benito BM, et al.
    Proc Natl Acad Sci U S A, 2020 06 02;117(22):12192-12200.
    PMID: 32393624 DOI: 10.1073/pnas.1920816117
    Late-spring frosts (LSFs) affect the performance of plants and animals across the world's temperate and boreal zones, but despite their ecological and economic impact on agriculture and forestry, the geographic distribution and evolutionary impact of these frost events are poorly understood. Here, we analyze LSFs between 1959 and 2017 and the resistance strategies of Northern Hemisphere woody species to infer trees' adaptations for minimizing frost damage to their leaves and to forecast forest vulnerability under the ongoing changes in frost frequencies. Trait values on leaf-out and leaf-freezing resistance come from up to 1,500 temperate and boreal woody species cultivated in common gardens. We find that areas in which LSFs are common, such as eastern North America, harbor tree species with cautious (late-leafing) leaf-out strategies. Areas in which LSFs used to be unlikely, such as broad-leaved forests and shrublands in Europe and Asia, instead harbor opportunistic tree species (quickly reacting to warming air temperatures). LSFs in the latter regions are currently increasing, and given species' innate resistance strategies, we estimate that ∼35% of the European and ∼26% of the Asian temperate forest area, but only ∼10% of the North American, will experience increasing late-frost damage in the future. Our findings reveal region-specific changes in the spring-frost risk that can inform decision-making in land management, forestry, agriculture, and insurance policy.
    Matched MeSH terms: Spatio-Temporal Analysis
  8. Sriwahyuni E, Sriwahyuni E, Fuad A, Ahmad RA, Ahmad RA, Rustamaji R, et al.
    Med J Malaysia, 2020 05;75(Suppl 1):41-47.
    PMID: 32483106
    INTRODUCTION: Rubella infection during early pregnancy may cause fatal consequences such as congenital rubella syndrome (CRS). The incidence rate (IR) of CRS confirmed cases in Yogyakarta, Indonesia between July 2008 and June 2013 was high at 0.05 per 1,000 live births. This study aimed to discover the spatiotemporal pattern of rubella and CRS and also identify whether the proximity of rubella cases was associated with the occurrence of CRS cases.

    METHODS: This observational research used a spatiotemporal approach. We obtained CRS and rubella surveillance data from Dr. Sardjito Hospital, Provincial, and District Health Offices in Yogyakarta, Indonesia during January-April 2019. The home addresses of rubella and CRS cases were geocoded using the Global Positioning System. Average of the nearest neighbour and space-time permutation analyses were conducted to discover the spatiotemporal patterns and clusters of rubella and CRS cases.

    RESULTS: The peak of rubella cases occurred in 2017 (IR: 22.3 per 100,000 population). Twelve confirmed cases of CRS were found in the 2016-2018 period (IR: 0.05 per 1,000 live births). The occurrence of CRS in Yogyakarta was detected 6-8 months after the increase and peak of rubella cases. The spatiotemporal analysis showed that rubella cases were mostly clustered, while CRS cases were distributed in a dispersed pattern. Rubella cases were found within a buffer zone of 2.5 km from any CRS case.

    CONCLUSIONS: Rubella cases were spatiotemporally associated with the occurrence of CRS in Yogyakarta. We recommend strengthening the surveillance system of CRS and rubella cases in order to contain any further spreading of the disease.

    Matched MeSH terms: Spatio-Temporal Analysis
  9. Abdul Shakor AS, Pahrol MA, Mazeli MI
    J Environ Public Health, 2020;2020:1561823.
    PMID: 32351580 DOI: 10.1155/2020/1561823
    Particulate matter with an aerodynamic diameter of 10 μm or less (PM10) pollution poses a considerable threat to human health, and the first step in quantifying health impacts of human exposure to PM10 pollution is exposure assessment. Population-weighted exposure level (PWEL) estimation is one of the methods that provide a more refined exposure assessment as it includes the spatiotemporal distribution of the population into the pollution concentration estimation. This study assessed the population weighting effects on the estimated PM10 concentrations in Malaysia for years 2000, 2008, and 2013. Estimated PM10 annual mean concentrations with a spatial resolution of 5 kilometres retrieved from satellite data and population count obtained from the Gridded Population of the World version 4 (GPWv4) from the Centre for International Earth Science Information Network (CIESIN) were overlaid to generate the PWEL of PM10 for each state. The calculated PWEL of PM10 concentrations were then classified based on the World Health Organization (WHO) and the national Air Quality Guidelines (AQG) and interim targets (IT) for comparison. Results revealed that the annual mean PM10 concentrations in Malaysia ranged from 31 to 73 µg/m3 but became generally lower, ranging from 20 to 72 µg/m3 after population weighting, suggesting that the PM10 population exposure in Malaysia might have been overestimated. PWEL of PM10 distribution showed that the majority of the population lived in areas that complied with the national AQG, but were vulnerable to exposure level 3 according to the WHO AQG and IT, indicating that the population was nevertheless potentially exposed to significant health effects from long-term exposure to PM10 pollution.
    Matched MeSH terms: Spatio-Temporal Analysis
  10. Nguyen TTN, Pham HV, Lasko K, Bui MT, Laffly D, Jourdan A, et al.
    Environ Pollut, 2019 Dec;255(Pt 1):113106.
    PMID: 31541826 DOI: 10.1016/j.envpol.2019.113106
    Satellite observations for regional air quality assessment rely on comprehensive spatial coverage, and daily monitoring with reliable, cloud-free data quality. We investigated spatiotemporal variation and data quality of two global satellite Aerosol Optical Depth (AOD) products derived from MODIS and VIIRS imagery. AOD is considered an essential atmospheric parameter strongly related to ground Particulate Matter (PM) in Southeast Asia (SEA). We analyze seasonal variation, urban/rural area influence, and biomass burning effects on atmospheric pollution. Validation indicated a strong relationship between AERONET ground AOD and both MODIS AOD (R2 = 0.81) and VIIRS AOD (R2 = 0.68). The monthly variation of satellite AOD and AERONET AOD reflects two seasonal trends of air quality separately for mainland countries including Myanmar, Laos, Cambodia, Thailand, Vietnam, and Taiwan, Hong Kong, and for maritime countries consisting of Indonesia, Philippines, Malaysia, Brunei, Singapore, and Timor Leste. The mainland SEA has a pattern of monthly AOD variation in which AODs peak in March/April, decreasing during wet season from May-September, and increasing to the second peak in October. However, in maritime SEA, AOD concentration peaks in October. The three countries with the highest annual satellite AODs are Singapore, Hong Kong, and Vietnam. High urban population proportions in Singapore (40.7%) and Hong Kong (21.6%) were associated with high AOD concentrations as expected. AOD values in SEA urban areas were a factor of 1.4 higher than in rural areas, with respective averages of 0.477 and 0.336. The AOD values varied proportionately to the frequency of biomass burning in which both active fires and AOD peak in March/April and September/October. Peak AOD in September/October in some countries could be related to pollutant transport of Indonesia forest fires. This study analyzed satellite aerosol product quality in relation to AERONET in SEA countries and highlighted framework of air quality assessment over a large, complicated region.
    Matched MeSH terms: Spatio-Temporal Analysis*
  11. Chénard C, Wijaya W, Vaulot D, Lopes Dos Santos A, Martin P, Kaur A, et al.
    Sci Rep, 2019 Nov 08;9(1):16390.
    PMID: 31704973 DOI: 10.1038/s41598-019-52648-x
    Singapore, an equatorial island in South East Asia, is influenced by a bi-annual reversal of wind directions which defines two monsoon seasons. We characterized the dynamics of the microbial communities of Singapore coastal waters by collecting monthly samples between February 2017 and July 2018 at four sites located across two straits with different trophic status, and sequencing the V6-V8 region of the small sub-unit ribosomal RNA gene (rRNA gene) of Bacteria, Archaea, and Eukaryota. Johor Strait, which is subjected to wider environmental fluctuations from anthropogenic activities, presented a higher abundance of copiotrophic microbes, including Cellvibrionales and Rhodobacterales. The mesotrophic Singapore Strait, where the seasonal variability is caused by changes in the oceanographic conditions, harboured a higher proportion of typically marine microbe groups such as Synechococcales, Nitrosupumilales, SAR11, SAR86, Marine Group II Archaea and Radiolaria. In addition, we observed seasonal variability of the microbial communities in the Singapore Strait, which was possibly influenced by the alternating monsoon regime, while no seasonal pattern was detected in the Johor Strait.
    Matched MeSH terms: Spatio-Temporal Analysis
  12. GBD 2017 Child and Adolescent Health Collaborators, Reiner RC, Olsen HE, Ikeda CT, Echko MM, Ballestreros KE, et al.
    JAMA Pediatr, 2019 06 01;173(6):e190337.
    PMID: 31034019 DOI: 10.1001/jamapediatrics.2019.0337
    Importance: Understanding causes and correlates of health loss among children and adolescents can identify areas of success, stagnation, and emerging threats and thereby facilitate effective improvement strategies.

    Objective: To estimate mortality and morbidity in children and adolescents from 1990 to 2017 by age and sex in 195 countries and territories.

    Design, Setting, and Participants: This study examined levels, trends, and spatiotemporal patterns of cause-specific mortality and nonfatal health outcomes using standardized approaches to data processing and statistical analysis. It also describes epidemiologic transitions by evaluating historical associations between disease indicators and the Socio-Demographic Index (SDI), a composite indicator of income, educational attainment, and fertility. Data collected from 1990 to 2017 on children and adolescents from birth through 19 years of age in 195 countries and territories were assessed. Data analysis occurred from January 2018 to August 2018.

    Exposures: Being under the age of 20 years between 1990 and 2017.

    Main Outcomes and Measures: Death and disability. All-cause and cause-specific deaths, disability-adjusted life years, years of life lost, and years of life lived with disability.

    Results: Child and adolescent deaths decreased 51.7% from 13.77 million (95% uncertainty interval [UI], 13.60-13.93 million) in 1990 to 6.64 million (95% UI, 6.44-6.87 million) in 2017, but in 2017, aggregate disability increased 4.7% to a total of 145 million (95% UI, 107-190 million) years lived with disability globally. Progress was uneven, and inequity increased, with low-SDI and low-middle-SDI locations experiencing 82.2% (95% UI, 81.6%-82.9%) of deaths, up from 70.9% (95% UI, 70.4%-71.4%) in 1990. The leading disaggregated causes of disability-adjusted life years in 2017 in the low-SDI quintile were neonatal disorders, lower respiratory infections, diarrhea, malaria, and congenital birth defects, whereas neonatal disorders, congenital birth defects, headache, dermatitis, and anxiety were highest-ranked in the high-SDI quintile.

    Conclusions and Relevance: Mortality reductions over this 27-year period mean that children are more likely than ever to reach their 20th birthdays. The concomitant expansion of nonfatal health loss and epidemiological transition in children and adolescents, especially in low-SDI and middle-SDI countries, has the potential to increase already overburdened health systems, will affect the human capital potential of societies, and may influence the trajectory of socioeconomic development. Continued monitoring of child and adolescent health loss is crucial to sustain the progress of the past 27 years.

    Matched MeSH terms: Spatio-Temporal Analysis
  13. Andrew NL, Bright P, de la Rua L, Teoh SJ, Vickers M
    PLoS One, 2019;14(9):e0223249.
    PMID: 31568527 DOI: 10.1371/journal.pone.0223249
    The coastal zones of Small Island States are hotspots of human habitation and economic endeavour. In the Pacific region, as elsewhere, there are large gaps in understandings of the exposure and vulnerability of people in coastal zones. The 22 Pacific Countries and Territories (PICTs) are poorly represented in global analyses of vulnerability to seaward risks. We combine several data sources to estimate populations to zones 1, 5 and 10 km from the coastline in each of the PICTs. Regional patterns in the proximity of Pacific people to the coast are dominated by Papua New Guinea. Overall, ca. half the population of the Pacific resides within 10 km of the coast but this jumps to 97% when Papua New Guinea is excluded. A quarter of Pacific people live within 1 km of the coast, but without PNG this increases to slightly more than half. Excluding PNG, 90% of Pacific Islanders live within 5 km of the coast. All of the population in the coral atoll nations of Tokelau and Tuvalu live within a km of the ocean. Results using two global datasets, the SEDAC-CIESIN Gridded Population of the World v4 (GPWv4) and the Oak Ridge National Laboratory Landscan differed: Landscan under-dispersed population, overestimating numbers in urban centres and underestimating population in rural areas and GPWv4 over-dispersed the population. In addition to errors introduced by the allocation models of the two methods, errors were introduced as artefacts of allocating households to 1 km x 1 km grid cell data (30 arc-seconds) to polygons. The limited utility of LandScan and GPWv4 in advancing this analysis may be overcome with more spatially resolved census data and the inclusion of elevation above sea level as an important dimension of vulnerability.
    Matched MeSH terms: Spatio-Temporal Analysis*
  14. Tan KK, Nellis S, Zulkifle NI, Sulaiman S, AbuBakar S
    Epidemiol Infect, 2018 10;146(13):1635-1641.
    PMID: 29860959 DOI: 10.1017/S0950268818001425
    Dengue virus type 3 genotype III (DENV-3/III) is widely distributed in most dengue-endemic regions. It emerged in Malaysia in 2008 and autochthonously spread in the midst of endemic DENV-3/I circulation. The spread, however, was limited and the virus did not cause any major outbreak. Spatiotemporal distribution study of DENV-3 over the period between 2005 and 2011 revealed that dengue cases involving DENV-3/III occurred mostly in areas without pre-existing circulating DENV-3. Neutralisation assays performed using sera of patients with the respective infection showed that the DENV-3/III viruses can be effectively neutralised by sera of patients with DENV-3 infection (50% foci reduction neutralisation titres (FRNT50) > 1300). Sera of patients with DENV-1 infection (FRNT50 ⩾ 190), but not sera of patients with DENV-2 infection (FRNT50 ⩽ 50), were also able to neutralise the virus. These findings highlight the possibility that the pre-existing homotypic DENV-3 and the cross-reacting heterotypic DENV-1 antibody responses could play a role in mitigating a major outbreak involving DENV-3/III in the Klang Valley, Malaysia.
    Matched MeSH terms: Spatio-Temporal Analysis
  15. Aburas MM, Ho YM, Ramli MF, Ash'aari ZH
    Environ Monit Assess, 2018 Feb 20;190(3):156.
    PMID: 29464400 DOI: 10.1007/s10661-018-6522-9
    The identification of spatio-temporal patterns of the urban growth phenomenon has become one of the most significant challenges in monitoring and assessing current and future trends of the urban growth issue. Therefore, spatio-temporal and quantitative techniques should be used hand in hand for a deeper understanding of various aspects of urban growth. The main purpose of this study is to monitor and assess the significant patterns of urban growth in Seremban using a spatio-temporal built-up area analysis. The concentric circles approach was used to measure the compactness and dispersion of built-up area by employing Shannon's Entropy method. The spatial directions approach was also utilised to measure the sustainability and speed of development, while the gradient approach was used to measure urban dynamics by employing landscape matrices. The overall results confirm that urban growth in Seremban is dispersed, unbalanced and unsustainable with a rapid speed of regional development. The main contribution of using existing methods with other methods is to provide several spatial and statistical dimensions that can help researchers, decision makers and local authorities understand the trend of growth and its patterns in order to take the appropriate decisions for future urban planning. For example, Shannon's Entropy findings indicate a high value of dispersion between the years 1990 and 2000 and from 2010 to 2016 with a growth rate of approximately 94 and 14%, respectively. Therefore, these results can help and support decision makers to implement alternative urban forms such as the compactness form to achieve an urban form that is more suitable and sustainable. The results of this study confirm the importance of using spatio-temporal built-up area and quantitative analysis to protect the sustainability of land use, as well as to improve the urban planning system via the effective monitoring and assessment of urban growth trends and patterns.
    Matched MeSH terms: Spatio-Temporal Analysis
  16. Gardner PC, Goossens B, Goon Ee Wern J, Kretzschmar P, Bohm T, Vaughan IP
    PLoS One, 2018;13(4):e0195444.
    PMID: 29649279 DOI: 10.1371/journal.pone.0195444
    Identifying the consequences of tropical forest degradation is essential to mitigate its effects upon forest fauna. Large forest-dwelling mammals are often highly sensitive to environmental perturbation through processes such as fragmentation, simplification of habitat structure, and abiotic changes including increased temperatures where the canopy is cleared. Whilst previous work has focused upon species richness and rarity in logged forest, few look at spatial and temporal behavioural responses to forest degradation. Using camera traps, we explored the relationships between diel activity, behavioural expression, habitat use and ambient temperature to understand how the wild free-ranging Bornean banteng (Bos javanicus lowi) respond to logging and regeneration. Three secondary forests in Sabah, Malaysian Borneo were studied, varying in the time since last logging (6-23 years). A combination of generalised linear mixed models and generalised linear models were constructed using >36,000 trap-nights. Temperature had no significant effect on activity, however it varied markedly between forests, with the period of intense heat shortening as forest regeneration increased over the years. Bantengs regulated activity, with a reduction during the wet season in the most degraded forest (z = -2.6, Std. Error = 0.13, p = 0.01), and reductions during midday hours in forest with limited regeneration, however after >20 years of regrowth, activity was more consistent throughout the day. Foraging and use of open canopy areas dominated the activity budget when regeneration was limited. As regeneration advanced, this was replaced by greater investment in travelling and using a closed canopy. Forest degradation modifies the ambient temperature, and positively influences flooding and habitat availability during the wet season. Retention of a mosaic of mature forest patches within commercial forests could minimise these effects and also provide refuge, which is key to heat dissipation and the prevention of thermal stress, whilst retention of degraded forest could provide forage.
    Matched MeSH terms: Spatio-Temporal Analysis*
  17. Dalu T, Wasserman RJ, Magoro ML, Mwedzi T, Froneman PW, Weyl OLF
    Sci Total Environ, 2017 Dec 01;601-602:73-82.
    PMID: 28551541 DOI: 10.1016/j.scitotenv.2017.05.162
    This study explores diatom community dynamics in a highly modified semi-arid temperate region river system characterised by inconsistent river flow. Various water and sediment environmental variables were assessed using a multi-faceted analysis approach to determine the spatio-temporal drivers of benthic diatom communities in the river system. Overall, the diatom community was generally dominated by pollution tolerant species, reflecting the anthropogenic intensity and activities on the river system. Diatom community composition was found to be largely determined by water column chemistry variables particularly nutrient concentrations in comparison to sediment chemistry and physical variables. Strong seasonal diatom species composition was also observed and this was driven by strong seasonal variations in nutrient loads and metal concentrations, a result of the variable water flow across the two seasons. However, the greater temporal variation in communities was observed in the smaller systems with the mainstream river system being more homogenous over time. In addition, diatom community composition and environmental variables were found to be different and more pronounced between streams and mainstream sites, than between canals and streams. The study highlights the complex interaction between water column, sediment and physical variables in determining the diatom species composition in small river systems. It also highlights the importance of river flow inconsistency as an indirect variable that alters primary drivers such as nutrient concentrations in the water column and heavy metal levels in the sediment.
    Matched MeSH terms: Spatio-Temporal Analysis
  18. Usinowicz J, Chang-Yang CH, Chen YY, Clark JS, Fletcher C, Garwood NC, et al.
    Nature, 2017 10 05;550(7674):105-108.
    PMID: 28953870 DOI: 10.1038/nature24038
    The tropical forests of Borneo and Amazonia may each contain more tree species diversity in half a square kilometre than do all the temperate forests of Europe, North America, and Asia combined. Biologists have long been fascinated by this disparity, using it to investigate potential drivers of biodiversity. Latitudinal variation in many of these drivers is expected to create geographic differences in ecological and evolutionary processes, and evidence increasingly shows that tropical ecosystems have higher rates of diversification, clade origination, and clade dispersal. However, there is currently no evidence to link gradients in ecological processes within communities at a local scale directly to the geographic gradient in biodiversity. Here, we show geographic variation in the storage effect, an ecological mechanism that reduces the potential for competitive exclusion more strongly in the tropics than it does in temperate and boreal zones, decreasing the ratio of interspecific-to-intraspecific competition by 0.25% for each degree of latitude that an ecosystem is located closer to the Equator. Additionally, we find evidence that latitudinal variation in climate underpins these differences; longer growing seasons in the tropics reduce constraints on the seasonal timing of reproduction, permitting lower recruitment synchrony between species and thereby enhancing niche partitioning through the storage effect. Our results demonstrate that the strength of the storage effect, and therefore its impact on diversity within communities, varies latitudinally in association with climate. This finding highlights the importance of biotic interactions in shaping geographic diversity patterns, and emphasizes the need to understand the mechanisms underpinning ecological processes in greater detail than has previously been appreciated.
    Matched MeSH terms: Spatio-Temporal Analysis*
  19. Ibrahim RW, Nashine HK, Kamaruddin N
    Math Biosci, 2017 10;292:10-17.
    PMID: 28728968 DOI: 10.1016/j.mbs.2017.07.007
    A biological dynamic system carries engineering properties such as control systems and signal processing (or image processing) addicted to molecular biology at the level of bio-molecular communication networks. Dynamical system features and signal reply functions of cellular signaling pathways are some of the main topics in biological dynamic systems (for example the biological segmentation). In the present paper, we introduce new generalized hybrid time-space dynamical systems of growing bacteria. We impose the approximate analytic solution for the system. The generalization adapted the concepts of the Riemann-Liouville fractional operators for time and the Srivastava-Owa fractional operators for space. Moreover, we introduce a numerical perturbation method of two operators to obtain the approximate solutions. We establish the existence and uniqueness results and impose some applications in the sequel. Moreover, we study the Ulam stability and apply these stable solutions to improve the segmentation of a class of growing bacteria.
    Matched MeSH terms: Spatio-Temporal Analysis
  20. Maynard AJ, Ambrose L, Cooper RD, Chow WK, Davis JB, Muzari MO, et al.
    PLoS Negl Trop Dis, 2017 04;11(4):e0005546.
    PMID: 28410388 DOI: 10.1371/journal.pntd.0005546
    BACKGROUND: Within the last century, increases in human movement and globalization of trade have facilitated the establishment of several highly invasive mosquito species in new geographic locations with concurrent major environmental, economic and health consequences. The Asian tiger mosquito, Aedes albopictus, is an extremely invasive and aggressive daytime-biting mosquito that is a major public health threat throughout its expanding range.

    METHODOLOGY/PRINCIPAL FINDINGS: We used 13 nuclear microsatellite loci (on 911 individuals) and mitochondrial COI sequences to gain a better understanding of the historical and contemporary movements of Ae. albopictus in the Indo-Pacific region and to characterize its population structure. Approximate Bayesian computation (ABC) was employed to test competing historical routes of invasion of Ae. albopictus within the Southeast (SE) Asian/Australasian region. Our ABC results show that Ae. albopictus was most likely introduced to New Guinea via mainland Southeast Asia, before colonizing the Solomon Islands via either Papua New Guinea or SE Asia. The analysis also supported that the recent incursion into northern Australia's Torres Strait Islands was seeded chiefly from Indonesia. For the first time documented in this invasive species, we provide evidence of a recently colonized population (the Torres Strait Islands) that has undergone rapid temporal changes in its genetic makeup, which could be the result of genetic drift or represent a secondary invasion from an unknown source.

    CONCLUSIONS/SIGNIFICANCE: There appears to be high spatial genetic structure and high gene flow between some geographically distant populations. The species' genetic structure in the region tends to favour a dispersal pattern driven mostly by human movements. Importantly, this study provides a more widespread sampling distribution of the species' native range, revealing more spatial population structure than previously shown. Additionally, we present the most probable invasion history of this species in the Australasian region using ABC analysis.

    Matched MeSH terms: Spatio-Temporal Analysis
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