Environmental Factors and Spatial Heterogeneity Affect Occupancy Estimates of Waterbirds in Peninsular Malaysia

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Chukwuemeka Onwuka Martins ◽  
Oluwatobi Emmanuel Olaniyi ◽  
Mohamed Zakaria
Keyword(s):  
Environmental Factors ◽  
Spatial Heterogeneity ◽  
Peninsular Malaysia

scholarly journals Occurrence of virulent multidrug-resistantEnterococcus faecalisandEnterococcus faeciumin the pigs, farmers and farm environments in Malaysia

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5353 ◽  
Author(s):  
Shiang Chiet Tan ◽  
Chun Wie Chong ◽  
Cindy Shuan Ju Teh ◽  
Peck Toung Ooi ◽  
Kwai Lin Thong
Keyword(s):  
Polymerase Chain Reaction ◽  
Antibiotic Resistance ◽  
Environmental Factors ◽  
Environmental Samples ◽  
Virulence Genes ◽  
Multidrug Resistant ◽  
Peninsular Malaysia ◽  
Chain Reaction ◽  
Swine Farms ◽  
Polymerase Chain

BackgroundEnterococcus faecalisandEnterococcus faeciumare ubiquitous opportunistic pathogens found in the guts of humans and farmed animals. This study aimed to determine the occurrence, antimicrobial resistance, virulence, biofilm-forming ability and genotypes ofE. faecalisandE. faeciumfrom swine farms. Correlations between the genotypes, virulotypes, antibiotic resistance, and the environmental factors such as locality of farms and farm hygiene practice were explored.MethodsE. faecalisandE. faeciumstrains were isolated from the oral, rectal and fecal samples of 140 pigs; nasal, urine and fecal samples of 34 farmers working in the farms and 42 environmental samples collected from seven swine farms located in Peninsular Malaysia. Antibiotic susceptibility test was performed using the disk diffusion method, and the antibiotic resistance and virulence genes were detected by Polymerase Chain Reaction. Repetitive Extragenic Palindromic-Polymerase Chain Reaction and Pulsed-Field Gel Electrophoresis were performed to determine the clonality of the strains. Crosstab/Chi-square test and DistLM statistical analyses methods were used to determine the correlations between the genotypes, virulence factors, antibiotic resistance, and the environmental factors.ResultsA total of 211E. faecalisand 42E. faeciumwere recovered from 140 pigs, 34 farmers and 42 environmental samples collected from seven swine farms in Peninsular Malaysia. Ninety-eight percent of the strains were multidrug-resistant (resistant to chloramphenicol, tetracycline, ciprofloxacin and erythromycin). Fifty-two percent of the strains formed biofilms. Virulence genesefa, asaI, gelE,esp,cylandacegenes were detected. Virulence genesefaandasaI were most prevalent inE. faecalis(90%) andE. faecium(43%), respectively. Cluster analyses based on REP-PCR and PFGE showed the strains were genetically diverse. Overall, the strains isolated from pigs and farmers were distinct, except for three highly similar strains found in pigs and farmers. The strains were regional- and host-specific.DiscussionThis study revealed alarming high frequencies of multidrug-resistant enterococci in pigs and swine farmers. The presence of resistance and virulence genes and the ability to form biofilm further enhance the persistence and pathogenicity of the strains. Although the overall clonality of the strains were regionals and host-specific, strains with high similarity were found in different hosts. This study reiterates a need of a more stringent regulation to ensure the proper use of antibiotics in swine husbandry to reduce the wide spread of multidrug-resistant strains.

Spatial heterogeneity of vegetation and environmental factors on talus slopes of the Niagara Escarpment

1993 ◽  
Vol 71 (2) ◽  
pp. 323-332 ◽  
Author(s):  
Janet E. Cox ◽  
Douglas W. Larson
Keyword(s):  
Multivariate Analysis ◽  
Environmental Factors ◽  
Spatial Heterogeneity ◽  
Positive Feedback ◽  
Local Scale ◽  
Vegetation Development ◽  
Niagara Escarpment ◽  
Scale Heterogeneity ◽  
Vegetation Heterogeneity ◽  
Talus Slopes

Spatial heterogeneity of vegetation and environmental factors were studied on talus slopes of the Niagara Escarpment, southern Ontario, Canada. Random sampling of 197 taxa and 19 environmental variables along the length of the Escarpment permitted multivariate analysis of heterogeneity that occurred at both geographical and local scales. While previous work on these slopes had indicated that rockfall disturbance was the main organizing factor of vegetation, this variable was shown to be unimportant. Instead, we found geographical-scale control of vegetation heterogeneity related to one component of macroclimate and local-scale heterogeneity controlled by a complex of soil factors. The local-scale heterogeneity appeared to be too patchy, however, to be explained by normal soil development processes. We suggest that the talus vegetation develops in response to a positive feedback mechanism involving inputs of slowly decomposing wood from the neighbouring cliffs, followed by accelerated vegetation development on patches of fertile organic matter. Key words: talus vegetation, cliff, multivariate analysis, Niagara Escarpment, plant community, positive feedback, spatial heterogeneity.

scholarly journals Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

2015 ◽  
Vol 12 (13) ◽  
pp. 3993-4004 ◽  
Author(s):  
U. Mishra ◽  
W. J. Riley
Keyword(s):  
Environmental Factors ◽  
Organic Carbon ◽  
Spatial Structure ◽  
Spatial Heterogeneity ◽  
Spatial Scale ◽  
Environmental Variables ◽  
Spatial Scales ◽  
Statistical Properties ◽  
Environmental Controls ◽  
Soc Stocks

Abstract. The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data set with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales (s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions (R2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks (R2 ∼ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.

scholarly journals Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

2015 ◽  
Vol 12 (2) ◽  
pp. 1721-1751 ◽  
Author(s):  
U. Mishra ◽  
W. J. Riley
Keyword(s):  
Environmental Factors ◽  
Organic Carbon ◽  
Spatial Structure ◽  
Spatial Heterogeneity ◽  
Spatial Scale ◽  
Environmental Variables ◽  
Spatial Scales ◽  
Statistical Properties ◽  
Environmental Controls ◽  
Soc Stocks

Abstract. The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing heterogeneity of terrestrial hydrological and biogeochemical processes in earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a dataset with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales (s = 100, 200, 500 m, 1, 2, 5, 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions (R2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98% of variability in the variance of SOC stocks. We found moderately-accurate linear relationships between mean and higher-order moments of predicted SOC stocks (R2 ~ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks can improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.

scholarly journals Effects of socio-economic and environmental factors on the spatial heterogeneity of dengue fever investigated at a fine scale

2018 ◽  
Vol 13 (2) ◽  
Author(s):  
Yubing Qu ◽  
Xun Shi ◽  
Yong Wang ◽  
Rendong Li ◽  
Liang Lu ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Environmental Factors ◽  
Spatial Heterogeneity ◽  
Dengue Fever ◽  
Scan Statistics ◽  
Fine Scale ◽  
Road Density ◽  
Risk Area ◽  
High Risk Area ◽  
Guangzhou City

The spatial pattern of dengue fever cases is the result of complex interactions between the virus, the host and the vector, which may be affected by environmental conditions. The largest outbreak of dengue fever in Guangzhou city, China occurred in 2014 with case numbers 2.7 times the number of cumulative cases since 1978 and a significantly non-random spatial distribution. Selecting Guangzhou City as the study area, we used scan statistics to analyze the spatial heterogeneity of dengue fever and a generalized additive model to evaluate and examine the effects of socio-economic and environmental factors on spatial heterogeneity at a fine scale. The study found that the spatial distribution of dengue fever is highly heterogeneous and various factors differ in relative importance. The junction of the central districts of Guangzhou is a high-risk area with the urban village and urban-rural fringe zone formed by urbanization as important regional factors. The low gross domestic product per capita, the high population density, the high road density were perceived as risk factors. The Asian subtropical coastal area together with the socioeconomic and environmental factors were found to be the key drivers at the fine scale explaining the high spatial heterogeneity of dengue fever in Guangzhou City.

scholarly journals Environmental Factors Driving Spatial Heterogeneity in Desert Halophile Microbial Communities

2020 ◽  
Vol 11 ◽  
Author(s):  
Gherman Uritskiy ◽  
Adam Munn ◽  
Micah Dailey ◽  
Diego R. Gelsinger ◽  
Samantha Getsin ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Spatial Heterogeneity ◽  
Microbial Communities

scholarly journals Ecological determinants of effect of a free pit and fissure sealant program in Shanxi, China, 2017–2018

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiangyu Wang ◽  
Wenjuan Ren ◽  
Yufang Li ◽  
Bin Zhao ◽  
Tingting Yang ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Spatial Heterogeneity ◽  
North China ◽  
Retention Rate ◽  
Explanatory Power ◽  
Ecological Factors ◽  
Retention Rates ◽  
Shanxi Province ◽  
Medical Resources ◽  
The Government

Abstract Background The aim of this study is to explore the spatial heterogeneity of the retention of PFS in children aged 7–9 years in Shanxi Province, North China and investigate the risk factors associated with PFS retention. Methods In this study, 937 children aged 7–9 years from Shanxi Province, China were randomly selected, all of whom had at least one first permanent tooth sealed with PFS in 2016. The children were surveyed after 12 months (in 2017) and 24 months (in 2018). The Geo-detector model was used to explore the spatial heterogeneity of the retention rate of PFS and analyze the influence and interactions of the ecological factors on PFS. Results 3299 teeth from 937 children were analyzed. The PFS full retention rates after 12 months (in 2017) and 24 months (in 2018) were 81.6% and 75.1%, respectively. The incidence of caries of the first molar was 2.1% after 12 months and 5.4% after 24 months. The spatial heterogeneity of the PFS retention rate after 24 months was significant, which was shown as the retention rate of PFS increased from north to south after 24 months. Remarkably, the natural environmental factors exerted greater influence than the socioeconomic and medical resources factors after 12 months, where the interaction of fluorine in water (FW) had the strongest explanatory power of 52% (P < 0.05). The medical resources were important ecological factors after 24 months, and the percentage of medical technicians (PMT) had the strongest explanatory power of 70% (P < 0.05). Conclusion The natural environmental factors and medical resources factors are important ecological factors determining the spatial pattern. The government should strengthen medical and technician construction in North China, comprehensively control fluoride in water, optimize the allocation of medical resources, and promote the balanced development of regional medicine.

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