This case study uses several univariate and multivariate statistical techniques to evaluate and interpret a water quality data set obtained from the Klang River basin located within the state of Selangor and the Federal Territory of Kuala Lumpur, Malaysia. The river drains an area of 1,288 km(2), from the steep mountain rainforests of the main Central Range along Peninsular Malaysia to the river mouth in Port Klang, into the Straits of Malacca. Water quality was monitored at 20 stations, nine of which are situated along the main river and 11 along six tributaries. Data was collected from 1997 to 2007 for seven parameters used to evaluate the status of the water quality, namely dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, suspended solids, ammoniacal nitrogen, pH, and temperature. The data were first investigated using descriptive statistical tools, followed by two practical multivariate analyses that reduced the data dimensions for better interpretation. The analyses employed were factor analysis and principal component analysis, which explain 60 and 81.6% of the total variation in the data, respectively. We found that the resulting latent variables from the factor analysis are interpretable and beneficial for describing the water quality in the Klang River. This study presents the usefulness of several statistical methods in evaluating and interpreting water quality data for the purpose of monitoring the effectiveness of water resource management. The results should provide more straightforward data interpretation as well as valuable insight for managers to conceive optimum action plans for controlling pollution in river water.

Water Quality Index (WQI) is the most common determinant of the quality of the stream-flow. According to the Department of Environment (DOE, Malaysia), WQI is chiefly affected by six factors, which are, chemical oxygen demand (COD), biochemical oxygen demand (BOD), dissolved oxygen (DO), suspended solids (SS),-potential for hydrogen (pH), and ammoniacal nitrogen (AN). In fact, understanding the interrelationships between these variables and WQI can improve predicting the WQI for better water resources management. The aim of this study is to create an input approach using ANNs (Artificial Neural Networks) to compute the WQI from input parameters instead of using the indices of the parameters when one of the parameters is absent. The data are collected from the nine water quality monitoring stations at the Klang River basin, Malaysia. In addition, comprehensive sensitivity analysis has been carried out to identify the most influential input parameters. The model is based on the frequency distribution of the significant factors showed exceptional ability to replicate the WQI and attained very high correlation (98.78%). Furthermore, the sensitivity analysis showed that the most influential parameter that affects WQI is DO, while pH is the least one. Additionally, the performance of models shows that the missing DO values caused deterioration in the accuracy.

BackgroundThe brown widow spider (Latrodectus geometricus Koch, 1841) has colonised many parts of the world from its continent of origin, Africa. By at least 1841, the species had successfully established populations in South America and has more recently expanded its range to the southern states of North America. This highly adaptable spider has been far more successful in finding its niche around the world than its famous cousins, the black widow, Latrodectus mactans, found in the south-eastern states of North America, and the red-back, Latrodectus hasselti, found mostly in Australia, New Zealand and Japan.MethodsWe performed an extensive web search of brown widow sightings and mapped the location of each sighting using ArcGIS. Specimens reputedly of the species L. geometricus were collected at three localities in Peninsular Malaysia. The spiders were identified and documented based on an examination of morphological characteristics and DNA barcoding.ResultsThe spiders found in Peninsular Malaysia were confirmed to be Latrodectus geometricus based on their morphological characteristics and DNA barcodes. We recorded 354 sightings of the brown widow in 58 countries, including Peninsular Malaysia.ConclusionReports from the Americas and the Far East suggest a global-wide invasion of the brown widow spider. Herein we report the arrival of the brown widow spider in Peninsular Malaysia and provide notes on the identification of the species and its recently expanded range.