14 research outputs found
Applicability of low-cost cameras for monitoring suspended sediment in rivers through close-range remote sensing
No full textSuspended sediment in rivers is a major problem globally. Monitoring of water turbidity and suspended sediment concentration (SSC) using satellites and in-situ sampling has been used widely to assess fine sediment pollution. However, due to low image resolution, application of satellite remote sensing is limited to only large water bodies, while in-situ sampling does not provide the continuous spatial data that are needed to address certain scientific questions or management problems. This research aimed to understand the potential of using low-cost cameras to estimate SSC in smaller rivers and streams and produce reach scale ‘maps’ of SSC. The study consists of development and testing of statistical models to predict SSC from pixel information contained in digital images, and validation of these models through field tests. An overarching goal was to assess the transferability of models between rivers and the effects of different camera sensors on SSC predictions. Laboratory experiments developed predictive models for two cameras (Vivo V9 smartphone and DJI Mavic Pro drone). Experiments involved manipulation of SSC in a water filled tank, with images taken with each camera and over a different coloured bed at each controlled sediment concentration. Digital Number (DN) values for each bed colour, camera and colour channel combination was extracted, with Generalised Additive Models fitted to Red, Blue and Green (R, G, B) colour bands.
In general, there were significant relations between SSC and the mean DN values, with G and B most frequently providing the best fits. Relations differed appreciably depending on bed characteristics, as a function of the relative colour of the bed and the material in suspension; some relations were direct (positive) and some indirect (negative). Thus, laboratory tests indicated that predictive relations need to be developed on a river-by-river basis due to differences in bed characteristics. There were some subtle differences between the two cameras, but in general both yielded images from which SSC could be predicted reliably in laboratory conditions. However, almost all relations broke down at very high SSCs depending on the bed colour, camera and colour channel combination; once the amount of fine material in suspension exceeded a certain threshold, SSC could not be predicted reliably from DN values. The field tests demonstrated that it is possible to produce accurate maps of SSC using an orthomosaic developed directly using DN values. These involved developing a calibration relationship for SSC v DN from images collected from drone flights at 30 m height above a reach of the Semenyih River, Malaysia. This relationship successfully predicted SSC, with the B colour band providing the best fit (R2 >0.86 for the observed v predicted). The SSC map was able to shed light on the influence of a tributary on main stem SSCs and patterns of mixing of the fine sediment delivered by the tributary. Such fine scale spatial patterns (1cm2/pixel) are evident neither from satellite data nor in-situ monitoring. The methods presented here are applicable to a variety of questions and contexts, from understanding downstream changes in SSC in glacial rivers to assessing effects of forest loss on SSC in tropical systems
Applicability of low-cost cameras for monitoring suspended sediment in rivers through close-range remote sensing
No full textSuspended sediment in rivers is a major problem globally. Monitoring of water turbidity and suspended sediment concentration (SSC) using satellites and in-situ sampling has been used widely to assess fine sediment pollution. However, due to low image resolution, application of satellite remote sensing is limited to only large water bodies, while in-situ sampling does not provide the continuous spatial data that are needed to address certain scientific questions or management problems. This research aimed to understand the potential of using low-cost cameras to estimate SSC in smaller rivers and streams and produce reach scale ‘maps’ of SSC. The study consists of development and testing of statistical models to predict SSC from pixel information contained in digital images, and validation of these models through field tests. An overarching goal was to assess the transferability of models between rivers and the effects of different camera sensors on SSC predictions. Laboratory experiments developed predictive models for two cameras (Vivo V9 smartphone and DJI Mavic Pro drone). Experiments involved manipulation of SSC in a water filled tank, with images taken with each camera and over a different coloured bed at each controlled sediment concentration. Digital Number (DN) values for each bed colour, camera and colour channel combination was extracted, with Generalised Additive Models fitted to Red, Blue and Green (R, G, B) colour bands.
In general, there were significant relations between SSC and the mean DN values, with G and B most frequently providing the best fits. Relations differed appreciably depending on bed characteristics, as a function of the relative colour of the bed and the material in suspension; some relations were direct (positive) and some indirect (negative). Thus, laboratory tests indicated that predictive relations need to be developed on a river-by-river basis due to differences in bed characteristics. There were some subtle differences between the two cameras, but in general both yielded images from which SSC could be predicted reliably in laboratory conditions. However, almost all relations broke down at very high SSCs depending on the bed colour, camera and colour channel combination; once the amount of fine material in suspension exceeded a certain threshold, SSC could not be predicted reliably from DN values. The field tests demonstrated that it is possible to produce accurate maps of SSC using an orthomosaic developed directly using DN values. These involved developing a calibration relationship for SSC v DN from images collected from drone flights at 30 m height above a reach of the Semenyih River, Malaysia. This relationship successfully predicted SSC, with the B colour band providing the best fit (R2 >0.86 for the observed v predicted). The SSC map was able to shed light on the influence of a tributary on main stem SSCs and patterns of mixing of the fine sediment delivered by the tributary. Such fine scale spatial patterns (1cm2/pixel) are evident neither from satellite data nor in-situ monitoring. The methods presented here are applicable to a variety of questions and contexts, from understanding downstream changes in SSC in glacial rivers to assessing effects of forest loss on SSC in tropical systems
The freshwater mussels (Bivalvia: Unionida) of Java: first island-wide assessment reveals new species, endemism, and urgent conservation needs
No full textThe freshwater mussel (Bivalvia: Unionida) fauna of Java has never been examined comprehensively in a modern context, leading to a lack of a species inventory and knowledge on current species distributions and how these have been impacted by human activities over the past 70 years. In 2022/23, we surveyed 66 sites across 18 river basins of Java, and one site near the Rectidens sumatrensis type locality in Sumatra. Species were delineated and identified through an integrated morphological–molecular approach using COI-based phylogenetic and haplotype analyses. We found and sequenced 76 populations (= species-site occurrences) across 42 sites and 16 river basins, comprising eight native and one non-native species. Whilst confirming the presence of Lens contradens, Physunio superbus, Pilsbryoconcha exilis, Pseudodon vondembuschianus stat. rev., Rectidens orientalis comb. rev., and Sinanodonta pacifica (non-native), we provide the first records of Lens lugens, Pilsbryoconcha linguaeformis, and Pseudodon cokelatus sp. nov. Rectidens sumatrensis is absent from Java. Comparing our data to historical records indicates considerable population losses of most native species driven by the steep increase in urbanization, industrialization, mining, and other human activities. Conservation actions are urgently needed, particularly in the species-rich Bengawan Solo and Brantas River basins
Promoting conservation of fireflies in Kuala Lumpur’s urban park through experiential learning
No full textKuala Lumpur is a megacity beaming in streetlights, but few are aware of nature's light show—the fireflies. Bukit Kiara, an urban park in the heart of Kuala Lumpur, is home to eight species of fireflies. Among them is an unidentified species of the enigmatic genus Lamprigera, of which the females are large and wingless but the winged males have a crepuscular courtship period. The larvae are noteworthy for their green glow. However, with highway and housing developments bordering Bukit Kiara, fireflies in the area are potentially at risk from the increasing impact of human activities.During March–May 2023, six students of Monash University Malaysia's School of Science, in collaboration with Friends of Bukit Kiara—a non-profit organization working on long-term conservation of the park—conducted undergraduate research projects on the fireflies of Bukit Kiara. The projects received support from the Department of National Landscape, the park administrator of the area. The goal of the projects was to understand how firefly distribution and abundance can change in response to biotic and abiotic factors, such as the effects of artificial light at night, microhabitat types and plant species composition. We also designed a study to verify the accuracy of the firefly larval measurement data that volunteers have collected through the Friends of Bukit Kiara's citizen science flagship programme, Magical Mysteries at Bukit Kiara.After the 3 months of experiential learning, students who had never worked in limited light conditions or handled nocturnal insects could identify firefly species from their flashing patterns. After all projects concluded in late May, we co-organized a guided firefly walk for the public to celebrate World Firefly Day on 1 July 2023. About 60 participants aged 5 years and above took part, guided by 20 Citizen Science Ambassadors, which included Monash University Malaysia students who received training to conduct the firefly survey. Following the walk, we hosted a public webinar on 5 July featuring three talks, including one student project on the impact of light pollution on fireflies. We plan to continue this experiential learning with future students and volunteers and to collaborate with other organizations to improve firefly conservation in Malaysia
Molecular dynamic simulations of WT and P822L.
No full textThe stability of the WT apo form of Bat SARS-CoV PLpro homodimer (green) and P822L (orange) were evaluated using (A) RMSD, (B) SASA, (C) Rg and (D) RMSF simulations, which was plotted for both chain A (left) and chain B (right). In Chain B, a zoomed view of residues 3–150 was provided to highlight the fluctuations of the P822L mutant. Our simulations demonstrate that P822L is stabler than the WT.</p
Patient comorbidities including number of comorbidities, stage of COVID-19 infection and sequenced lineage of SARS-CoV-2 for each corresponding patient.
No full textPatient comorbidities including number of comorbidities, stage of COVID-19 infection and sequenced lineage of SARS-CoV-2 for each corresponding patient.</p
Lollipop plot summarising the frequencies of SARS-CoV-2 amino acid substitutions in our study cohort (n = 99) in Table 2.
No full textRed boxes represent genes and blue boxes represent coding sequences. A SARS-CoV-2 genome map with base-pair positions is displayed at the bottom. The bubbles in the Y-coordinates indicate mutation frequencies.</p
Genomic distribution of the identified SARS-CoV-2 mutations.
No full textGenomic distribution of the identified SARS-CoV-2 mutations.</p
The top five occurring mutations within ORF1a.
No full textGenomic surveillance is crucial for tracking emergence and spread of novel variants of pathogens, such as SARS-CoV-2, to inform public health interventions and to enforce control measures. However, in some settings especially in low- and middle- income counties, where sequencing platforms are limited, only certain patients get to be selected for sequencing surveillance. Here, we show that patients with multiple comorbidities potentially harbour SARS-CoV-2 with higher mutation rates and thus deserve more attention for genomic surveillance. The relationship between the patient comorbidities, and type of amino acid mutations was assessed. Correlation analysis showed that there was a significant tendency for mutations to occur within the ORF1a region for patients with higher number of comorbidities. Frequency analysis of the amino acid substitution within ORF1a showed that nsp3 P822L of the PLpro protease was one of the highest occurring mutations. Using molecular dynamics, we simulated that the P822L mutation in PLpro represents a system with lower Root Mean Square Deviation (RMSD) fluctuations, and consistent Radius of gyration (Rg), Solvent Accessible Surface Area (SASA) values—indicate a much stabler protein than the wildtype. The outcome of this study will help determine the relationship between the clinical status of a patient and the mutations of the infecting SARS-CoV-2 virus.</div
