Functional classification of phytoplankton could be a valuable tool in water quality monitoring in the eutrophic riverine ecosystems. This study is novel from the Bangladeshi perspective. In this study, phytoplankton cell density and diversity were studied with particular reference to the functional groups (FGs) approach during pre-monsoon, monsoon, and post-monsoon at four sampling stations in Karatoya River, Bangladesh. A total of 54 phytoplankton species were recorded under four classes, viz. Chlorophyceae (21 species) Cyanophyceae (16 species), Bacillariophyceae (15 species), and Euglenophyceae (2 species). A significantly higher total cell density of phytoplankton was detected during the pre-monsoon season (24.20 × 103 cells/l), while the lowest in monsoon (9.43 × 103 cells/l). The Shannon-Wiener diversity index varied significantly (F = 16.109, P = 000), with the highest value recorded during the post-monsoon season. Analysis of similarity (ANOSIM) identified significant variations among the three seasons (P
The investigation of sediment transport in tropical rivers is essential for planning effective integrated river basin management to predict the changes in rivers. The characteristics of rivers and sediment in the tropical region are different compared to those of the rivers in Europe and the USA, where the median sediment size tends to be much more refined. The origins of the rivers are mainly tropical forests. Due to the complexity of determining sediment transport, many sediment transport equations were recommended in the literature. However, the accuracy of the prediction results remains low, particularly for the tropical rivers. The majority of the existing equations were developed using multiple non-linear regression (MNLR). Machine learning has recently been the method of choice to increase model prediction accuracy in complex hydrological problems. Compared to the conventional MNLR method, machine learning algorithms have advanced and can produce a useful prediction model. In this research, three machine learning models, namely evolutionary polynomial regression (EPR), multi-gene genetic programming (MGGP) and M5 tree model (M5P), were implemented to model sediment transport for rivers in Malaysia. The formulated variables for the prediction model were originated from the revised equations reported in the relevant literature for Malaysian rivers. Among the three machine learning models, in terms of different statistical measurement criteria, EPR gives the best prediction model, followed by MGGP and M5P. Machine learning is excellent at improving the prediction distribution of high data values but lacks accuracy compared to observations of lower data values. These results indicate that further study needs to be done to improve the machine learning model's accuracy to predict sediment transport.
We studied the water quality of the riparian firefly sanctuary of Sungai Rembau, or Rembau River, in Negeri Sembilan, Malaysia, from January 2018 to November 2018 to determine the possible influence of the physico-chemical characteristics of the water on the firefly populations living within the sanctuary. We set up a total of five water quality sampling stations and 10 firefly sampling stations along the river. Dissolved oxygen (DO), temperature, pH and electrical conductivity (EC) were measured in situ, while chemical oxygen demand (COD), total suspended solids (TSS), biochemical oxygen demand (BOD) and ammonia-nitrogen (NH3-N) were analysed in the laboratory. Firefly samples were collected using a sweep net at both day and night for 1 min. Sungai Rembau was categorized as Class II on the Malaysian water quality index (WQI), which indicates slight pollution. Except for EC and DO, the water quality parameter values were not significantly different (p > 0.05) between the sampling stations. A total of 529 firefly individuals consisting of Pteroptyx tener (n = 525, 99.24%), P. malaccae (n = 3, 0.57%) and P. asymmetria (n = 1, 0.19%) were collected. There was significant correlation between firefly abundance and BOD (r = - 0.198, p
Microplastics have been considered as contaminants of emerging concern due to ubiquity in the environment; however, the occurrence of microplastics in river estuaries is scarcely investigated. The Klang River estuary is an important ecosystem that receives various contaminants from urbanised, highly populated areas and the busiest maritime centre in Selangor, Malaysia. This study investigates the abundance and characteristics of microplastics in surface water of the Klang River estuary. The abundance of microplastics ranged from 0.5 to 4.5 particles L-1 with a mean abundance of 2.47 particles L-1. There is no correlation between the abundance of microplastics and physicochemical properties, while there is a strong correlation between salinity and conductivity. The microplastics were characterised with a stereomicroscope and attenuated total reflection-Fourier transform infrared spectroscopy to analyse size, shape, colour, and polymer composition. The microplastics in the surface water were predominantly in the 300-1000 μm size class, followed by > 1000 μm and
Knowledge of the fundamental aspects of ecology such as the patterns of fish species distribution and biodiversity in the forest streams is the first and basic step to develop effective conservation strategies. Yet, studies on altitudinal changes of fish composition and assemblages in Bornean forest streams are scarce despite being one of the hotspots of biodiversity conservation. Hence, surveys on freshwater fish composition along the altitudinal gradients of the Baleh River Basin in Sarawak, Borneo were conducted from April 2014 to August 2015. The Baleh River Basin was divided into seven altitudinal groups with a total of 72 stations. Group elevation ranged from 53 to 269 m above sea level. The fish samples and environmental parameters were taken concurrently during samplings. A total of 3565 specimens belonging to six orders, 14 families, and 76 species were found in the present study. The most dominant family in the Baleh River Basin was Cyprinidae (74.4%), followed by Gastromyzontidae (16.2%) while the most dominant species was Tor tambra (12.9%), followed by Lobocheilos ovalis (12.3%). Fish abundance significantly higher at high altitude sites than those at low altitude sites except for Mengiong River which has the lowest fish abundance despite with high elevation. Species richness was found significantly lower in midstream segment. Noticeable altitudinal gradient of fish assemblages was observed along the Baleh River except a discontinuity at the midstream segment which is attributable to the poorer quality inflow from the Mengiong River coupled with the meandering feature of the segment. Fish abundance was significantly and positively correlated with elevation, water pH and conductivity while negatively correlated with turbidity. Anthropogenic activities in the Baleh River Basin had altered the environmental variables thus disrupted the altitudinal gradient of fish assemblages. This phenomenon is apparent when the Canonical Correspondence Analysis (CCA) revealed that the first axis (CCA1) explained 42.5% of the variation and has positive loading on dissolved oxygen (DO) and negative loading on water conductivity; whereas CCA2 explained 37.5% of the variation and positively loaded on elevation, water pH, and DO. The results demonstrated that Gastromyzon fasciatus preferred more oxygenated water than Protomyzon sp., G. sp 1, and G. punctulatus although they are all from Gastromyzontidae family that inhabiting high altitude sites. Barbonymus schwanenfeldii was also found most abundant with elevated dissolved oxygen value. On the other hand, Rasbora volzii and R. hosii inhabiting lower altitude sites with less oxygenated and more acidic water.
Land use plays a significant role in determining the spatial patterns of water quality in the Johor River Basin (JRB), Malaysia. In the recent years, there have been several occurrences of pollution in these rivers, which has generated concerns over the long-term sustainability of the water resources in the JRB. Specifically, this water resource is a shared commodity between two states, namely, Johor state of Malaysia and Singapore, a neighbouring country adjacent to Malaysia. Prior to this study, few research on the influence of land use configuration on water quality have been conducted in Johor. In addition, it is also unclear how water quality varies under different seasonality in the presence of point sources. In this study, we investigated the influence of land use and point sources from wastewater treatment plants (WWTPs) on the water quality in the JRB. Two statistical techniques - Multivariate Linear Regression (MLR) and Redundancy Analysis (RA) were undertaken to analyse the relationships between river water quality and land use configuration, as well as point sources from WWTPs under different seasonality. Water samples were collected from 49 sites within the JRB from March to December in 2019. Results showed that influence from WWTPs on water quality was greater during the dry season and less significant during the wet season. In particular, point source was highly positively correlated with ammoniacal‑nitrogen (NH3-N). On the other hand, land use influence was greater than point source influence during the wet season. Residential and urban land use were important predictors for nutrients and organic matter (chemical oxygen demand); and forest land use were important sinks for heavy metals but a significant source of manganese.
Metal contaminations in commercial fish have become a great public health concern worldwide including Bangladesh. The current study was conducted to provide preliminary evidence of nine metals in three commercially significant fish namely Pampus argenteus, Sardinella longiceps and Tenualosa ilisha collected from four coastal stations- Kuakata, Pathorghata, Cox's Bazar, and Pirojpur, and eight stations of five rivers- Padma, Meghna, Jamuna, Katcha, and Nobogonga in Bangladesh. High magnitudes of Pb (0.74-4.59 mg/kg ww), Cd (0.07-0.24 mg/kg ww), and Mn (0.45-2.03 mg/kg ww) were recorded in the sampling stations that exceeded the maximum permissible limits (MPL) proposed by different recognized organizations. Significant mean differences of metal concentrations were observed (p
Deforestation and forest degradation are among the leading global concerns, as they could reduce the carbon sink and sequestration potential of the forest. The impoundment of Kenyir River, Hulu Terengganu, Malaysia, in 1985 due to the development of hydropower station has created a large area of water bodies following clearance of forested land. This study assessed the loss of forest carbon due to these activities within the period of 37 years, between 1972 and 2019. The study area consisted of Kenyir Lake catchment area, which consisted mainly of forests and the great Kenyir Lake. Remote sensing datasets have been used in this analysis. Satellite images from Landsat 1-5 MSS and Landsat 8 OLI/TRIS that were acquired between the years 1972 and 2019 were used to classify land uses in the entire landscape of Kenyir Lake catchment. Support vector machine (SVM) was adapted to generate the land-use classification map in the study area. The results show that the total study area includes 278,179 ha and forest covers dominated the area for before and after the impoundment of Kenyir Lake. The assessed loss of carbon between the years 1972 and 2019 was around 8.6 million Mg C with an annual rate of 0.36%. The main single cause attributing to the forest loss was due to clearing of forest for hydro-electric dam construction. However, the remaining forests surrounding the study area are still able to sequester carbon at a considerable rate and thus balance the carbon dynamics within the landscapes. The results highlight that carbon sequestration scenario in Kenyir Lake catchment area shows the potential of the carbon sink in the study area are acceptable with only 17% reduction of sequestration ability. The landscape of the study area is considered as highly vegetated area despite changes due to dam construction.
Chemical pollution in the transboundary Langat River in Malaysia is common both from point and non-point sources. Therefore, the water treatment plants (WTPS) at the Langat River Basin have experienced frequent shutdown incidents. However, the Langat River is one of the main sources of drinking water to almost one-third of the population in Selangor state. Meanwhile, several studies have reported a high concentration of Arsenic (As) in the Langat River that is toxic if ingested via drinking water. However, this is a pioneer study that predicts the As concentration in the Langat River based on time-series data from 2005-2014 to estimate the health risk associated with As ingestion via drinking water at the Langat River Basin. Several time-series prediction models were tested and Gradient Boosted Tree (GBT) gained the best result. This GBT model also fits better to predict the As concentration until December 2024. The mean concentration of As in the Langat River for both 2014 and 2024, as well as the carcinogenic and non-carcinogenic health risks of As ingestion via drinking water, were within the drinking water quality standards proposed by the World Health Organization and Ministry of Health Malaysia. However, the ingestion of trace amounts of As over a long period might be detrimental to human health because of its non-biodegradable characteristics. Therefore, it is important to manage the drinking water sources to minimise As exposure risks to human health.
Foodborne outbreaks of hepatitis A virus (HAV) are most commonly associated with fresh and frozen produce and with various types of shellfish. Alcoholic beverage-borne outbreaks of hepatitis A are extremely rare. Here, we report an outbreak of hepatitis A associated with the consumption of a traditional wine at a funeral ceremony in the Sabah state of Malaysian Borneo. Confirmed cases were determined by serum anti-HAV immunoglobulin M and/or for fecal HAV by reverse transcription polymerase chain reaction (RT-PCR). The amplicons of RT-PCR were subjected to nucleotide sequencing followed by phylogenetic analysis. We conducted a 1:2 case-control study to identify the possible exposure that led to the outbreak. Sixteen patients met the case definition, they were 18 to 58 years old and 90% of them were males. The case-control study showed that the consumption of nipa palm wine during the ceremony was significantly associated (P = 0.0017) with hepatitis A infection (odds ratio, 5.44; 95% CI, 1.80-16.43). Untreated river water was used to dilute the traditional wine, which was assumed to be the source of the infection. Phylogenetically, these viruses belonged to genotype IA and formed an independent cluster with strains from Taiwan, Japan, and the Philippines. This strain might be an emerging HAV in Asian countries. Environmental assessments were performed and environmental samples were negative for HAV. The incidence of hepatitis A in Sabah was also determined and it was 0.795/100,000 population. Strict monitoring of traditional wine production should be implemented by the local authority to prevent future outbreaks.
The heavy metal contents (Cr, Cu, Zn, Cd, Pb, Hg, and As) of 88 surface sediment samples from the western Sunda Shelf were analyzed to determine their spatial distribution patterns and contamination status. The results demonstrated that high enrichment regions of heavy metals were focused in the Kelantan, Pahang, and Ambat river estuaries, and deep water regions of the study area. These high enrichment regions were mainly controlled by riverine inputs and their hydrodynamic conditions. The enrichment factor (EF), geoaccumulation index (Igeo), and potential ecological risk index (PERI) were used to assess heavy metal accumulation. The results indicated that the study area was not significantly contaminated overall at the time of the study; however, Cd, As, and Hg were at levels corresponding to moderate contamination at many stations located in the Pahang River estuary, Kelantan River estuary, and north-eastern region of the study area, primarily because of anthropogenic activities.
The current world economy needs to undergo a green transformation. Green total factor productivity provides the basis for judging whether a country or region can attain long-term sustainable development. However, there is little research into the factors that influence green total factor productivity and this has become an obstacle in the transition to a greener economy. On filtering relevant articles and interviews data collected from 2009 to 2019, open decoding, spindle decoding, and selective decoding are carried out to classify research conducted into green total factor productivity. From this analysis, cutting-edge research and knowledge gaps in green total factor productivity are identified. Also, an influencing factor model of green total factor productivity is built. Findings suggest that technical, economic, and government are the three main research streams involved in this transformation process. In particular, technology plays a decisive role, economy plays a guaranteeing role, and government plays a regulatory role. Moreover, the impact of these factors cannot be isolated, as each influence and mediate the other two. Results from this study will help further popularize green total factor productivity and provide a new starting point for reducing energy consumption and environmental pollution.
Rivers in Malaysia are classified based on water quality index (WQI) that comprises of six parameters, namely, ammoniacal nitrogen (AN), biochemical oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO), pH, and suspended solids (SS). Due to its tropical climate, the impact of seasonal monsoons on river quality is significant, with the increased occurrence of extreme precipitation events; however, there has been little discussion on the application of artificial intelligence models for monsoonal river classification. In light of these, this study had applied artificial neural network (ANN) and support vector machine (SVM) models for monsoonal (dry and wet seasons) river classification using three of the water quality parameters to minimise the cost of river monitoring and associated errors in WQI computation. A structured trial-and-error approach was applied on input parameter selection and hyperparameter optimisation for both models. Accuracy, sensitivity, and precision were selected as the performance criteria. For dry season, BOD-DO-pH was selected as the optimum input combination by both ANN and SVM models, with testing accuracy of 88.7% and 82.1%, respectively. As for wet season, the optimum input combinations of ANN and SVM models were BOD-pH-SS and BOD-DO-pH with testing accuracy of 89.5% and 88.0%, respectively. As a result, both optimised ANN and SVM models have proven their prediction capacities for river classification, which may be deployed as effective and reliable tools in tropical regions. Notably, better learning and higher capacity of the ANN model for dataset characteristics extraction generated better predictability and generalisability than SVM model under imbalanced dataset.
The Soil and Water Assessment Tool (SWAT) ecohydrological model was utilized to simulate fecal contamination in the 1937 km2 Selangor River Watershed in Malaysia. The watershed conditions posed considerable challenges owing to data scarcity and tropical climate conditions, which are very different from the original conditions that SWAT was developed and tested for. Insufficient data were compensated by publicly available data (e.g., land cover, soil, and weather) to run SWAT. In addition, field monitoring and interviews clarified representative situations of pollution sources and loads, which were used as input for the model. Model parameters determined by empirical analyses in the USA (e.g., surface runoff, evapotranspiration, and temperature adjustment for bacteria die-off) are thoroughly discussed. In particular, due consideration was given to tropical climate characteristics such as intense rainfall, high potential evapotranspiration, and high temperatures throughout the year. As a result, the developed SWAT successfully simulated fecal contamination ranging several orders of magnitude along with its spatial distribution (i.e., Nash-Sutcliffe Efficiency (NSE) = 0.64, Root Mean Square Error-Observations Standard Deviation Ratio (RSR) = 0.64 at six mainstem sites, and NSE = 0.67 and RSR = 0.57 at 12 major tributaries). Moreover, mitigation countermeasures for future worsening of fecal contamination (i.e., E.coli concentration > 20,000 CFU/100 mL for 690 days during nine years at a raw water intake point for Kuala Lumpur [KL] residents) were analyzed through scenario simulations, thereby contributing to discussing effective watershed management. The results propose improving decentralized sewage treatment systems and treating chicken manure with effective microorganisms in order to guarantee water safety for KL residents (i.e., E.coli concentrations <20,000 CFU/100 mL throughout the period, considering Malaysian standards). Accordingly, this study verified the applicability of SWAT to simulate fecal contamination in areas that are difficult to model and suggests solutions for watershed management based on quantitative evidence.
The determinant factors for macroinvertebrate assemblages in river ecosystems are varied and are unique and specific to the type of macroinvertebrate family. This study aims to assess the determinant factors for macroinvertebrate assemblages in a recreational river. The study was conducted on the Ulu Bendul River, Negeri Sembilan, Malaysia. A total of ten sampling stations were selected. The research methodology included (1) water quality measurement, (2) habitat characterization, and (3) macroinvertebrate identification and distribution analysis. The statistical analysis used in this study was canonical correspondence analysis (CCA) to represent the relationship between the environmental factors and macroinvertebrate assemblages in the recreational river. This study found that most of the families of macroinvertebrates were very dependent on the temperature, DO, NH3-N, type of riverbed, etc. All of these factors are important for the survival of the particular type of macroinvertebrate, plus they are also important for selecting egg-laying areas and providing suitable conditions for the larvae to grow. This study advises that improved landscape design for watershed management be implemented in order to enhance water quality and physical habitats, and hence the protection and recovery of the macroinvertebrate biodiversity.
Chlorine radical plays an important role in the formation of ozone and secondary aerosols in the troposphere. It is hence important to develop comprehensive emissions inventory of chlorine precursors in order to enhance our understanding of the role of chlorine chemistry in ozone and secondary pollution issues. Based on a bottom-up methodology, this study presents a comprehensive emission inventory for major atomic chlorine precursors in the Yangtze River Delta (YRD) region of China for the year 2017. Four primary chlorine precursors are considered in this study: hydrogen chloride (HCl), fine particulate chloride (Cl-) (Cl- in PM2.5), chlorine gas (Cl2), and hypochlorous acid (HClO) with emissions estimated for twelve source categories. The total emissions of these four species in the YRD region are estimated to be 20,424 t, 15,719 t, 1556 and 9331 t, respectively. The emissions of HCl are substantial, with major emissions from biomass burning and coal combustion, together accounting for 68% of the total HCl emissions. Fine particulate Cl- is mainly emitted from industrial processing, biomass burning and waste incineration. The emissions of Cl2 and HClO are mainly associated with usage of chlorine-containing disinfectants, for example, water treatment, wastewater treatment, and swimming pools. Emissions of each chlorine precursor are spatially allocated based on the characteristics of individual source category. This study provides important basic dataset for further studies with respect to the effects of chlorine chemistry on the formation of air pollution complex in the YRD region.
Pinpointing environmental antibiotic resistance (AR) hot spots in low-and middle-income countries (LMICs) is hindered by a lack of available and comparable AR monitoring data relevant to such settings. Addressing this problem, we performed a comprehensive spatial and seasonal assessment of water quality and AR conditions in a Malaysian river catchment to identify potential "simple" surrogates that mirror elevated AR. We screened for resistant coliforms, 22 antibiotics, 287 AR genes and integrons, and routine water quality parameters, covering absolute concentrations and mass loadings. To understand relationships, we introduced standardized "effect sizes" (Cohen's D) for AR monitoring to improve comparability of field studies. Overall, water quality generally declined and environmental AR levels increased as one moved down the catchment without major seasonal variations, except total antibiotic concentrations that were higher in the dry season (Cohen's D > 0.8, P < 0.05). Among simple surrogates, dissolved oxygen (DO) most strongly correlated (inversely) with total AR gene concentrations (Spearman's ρ 0.81, P < 0.05). We suspect this results from minimally treated sewage inputs, which also contain AR bacteria and genes, depleting DO in the most impacted reaches. Thus, although DO is not a measure of AR, lower DO levels reflect wastewater inputs, flagging possible AR hot spots. DO measurement is inexpensive, already monitored in many catchments, and exists in many numerical water quality models (e.g., oxygen sag curves). Therefore, we propose combining DO data and prospective modeling to guide local interventions, especially in LMIC rivers with limited data.
Rivers, the main source of the domestic water supply in Malaysia, have been threatened by frequent flooding in recent years. This study aims to assess human health risks associated with exposure to concentrated heavy metals in a flood-prone region of Malaysia and investigate the affected individuals' willingness to participate in managing water resources. Hazard indices and cancer risks associated with water contamination by heavy metals have been assessed following the method prescribed by the US Environmental Protection Agency. Yearly data of heavy metal contamination (Cd, Cr, Pb, Zn, Fe), water quality parameters (DO, BOD, COD, pH), and climatic information (annual rainfall, annual temperature) have been collected from the Department of Environment and Meteorological Department of Malaysia, respectively. The inductively coupled plasma mass spectrometry technique has been used by the department of environment for analyzing heavy metal concentration in river water samples. In this study, data from a stratified random sample of households in the affected region were analyzed, using partial least squares structural equation modeling, to predict the link between individuals' perceptions and attitudes about water resources and their willingness to engage in water management program. The health risk estimation indicated that the hazard index values were below the acceptable limit, representing no non-carcinogenic risk to adults and children residing in the study area via oral intake and dermal adsorption of water. However, the calculated value for cancer risk signified possible carcinogenic risks associated with Pb and Cd. In general, contamination due to pollution and flooding tends to increase in the basin region, and appropriate management is needed. The results identified perceived water quality as a significant factor influencing people's attitudes toward involvement in water management programs. As in many developing countries, there is no legal provision guaranteeing public representation in water management in Malaysia. The conclusion discusses the importance of these for the literature and for informing future policy actions.
Over the years, pipelines have been the most economic medium for transporting crude oil to production and distribution facilities in the Niger Delta area of Nigeria. However, damages to the pipelines in this area by interdiction have hampered the continuous flow of crude oil to the facilities. Consequently, the revenue of the government dwindles, and the environment is severely degraded. This study assesses the economic and environmental impacts of pipeline interdiction in the Niger Delta region. Data from National oil spills detection and response agency, Nigeria is used to map spatial distribution of oil spills using Kernel Density Estimation with Geographic Information System. Literature was assessed to synthesize the historical, socioeconomic, and environmental impacts of oil spills and pipeline interdiction. Soil samples were collected from study area to determine the types of hydrocarbon pollutants and their concentrations in comparison with uncontaminated sites in the area. Results show that the range of concentrations of total petroleum hydrocarbon (TPH) for the impacted soil (IMP) was 17.27-58.36 mg/kg; remediated soil (RS) was 11.73-50.78 mg/kg which were higher than the concentrations of 0.68 mg/kg in the control samples (CS). Polycyclic aromatic hydrocarbons (PAH) concentrations were in the range of 0.43-77.54 mg/kg for IMP, 0.42-10.65 mg/kg for RS, against CS value of 0.49 mg/kg while BTEX ranged between 0.02 - 0.38 mg/kg for IMP, 0.01-2.7 for RS against CS value of 0.01. The values of the PAH were higher than the limits of the Department of Petroleum Resources, Nigeria. This study also revealed that pipeline interdiction has affected the livelihood of the inhabitants of the study area and the revenue of the Nigerian government. The major hotspots for oil spills in the Niger Delta region are Bayelsa, Rivers and Delta states.
The king of rivers or mahseer comprises three genera: Tor, Neolissochilus, and Naziritor, under the Cyprinidae family. The Tor genus has been classified as the true mahseer due to the presence of a median lobe among the three genera. The Tor species are widely distributed across Southeast (SE) Asia, and 13 Tor species have been reported previously: Tor ater, Tor dongnaiensis, Tor douronensis, Tor laterivittatus, Tor mosal, Tor mekongensis, Tor putitora, Tor sinensis, Tor soro, Tor tambra, Tor tambroides, Tor tor and Tor yingjiangensis. However, the exact number of valid Tor species remains debatable. Different and unstandardized approaches of applying genetic markers in taxonomic identification and morphology variation within the same species have further widened the gap and ameliorated the instability of Tor species taxonomy. Therefore, synchronized and strategized research among Tor species researchers is urgently required to improve and fill the knowledge gap. This review is a current update of SE Asia's Tor species, outlining their distribution, morphology, and genetic identification. In addition, the present review proposes that there are ten valid Tor species in the SE Asian region. This list will serve as a template and standard to improve the taxonomy of the SE Asian Tor species, which could serve as a basis to open new directions in Tor research.