Urbanisation of riverine landscapes is a major threat to river ecosystems because of the ecological consequences of the so called urban stream syndrome. Taxonomically, certain macroinvertebrate metrics such as the diversity of species of Ephemeroptera, Plecoptera and Trichoptera (EPT) are known to be sensitive to urban pollution, whereas chironomids and oligochaetes are relatively tolerant. Trait correlates of such taxonomic metrics are yet to be established even though traits are less constrained by geographical differences. Using the Swartkops as a case study of a river receiving urban pollution, the pattern of trait distribution in relation to a gradient of urban pollution was examined, and urban pollution signature and sensitive traits identified. Macroinvertebrates and physico-chemical analysis were undertaken over a period of three years between August 2009 and September 2012 at one control site and three impacted downstream sites. Seven traits resolved into 32 trait attributes including body size, respiration, body shape, mobility, biotope preference, preferred food, and feeding habits were fuzzy coded and analysed using RLQ and fourth-corner analyses. Of the 32 trait and ecological attributes, four, including large body size (>20 to 40 mm), animal materials as preferred food, predation and a preference for vegetation biotope, which were associated with the impacted sites, and were also significantly positively correlated with at least one physico-chemical indicator of increasing urban pollution were deemed signature traits. Three traits, swimming, fine particulate organic matter and grazing, associated with the control site, which showed significant negative correlations with at least one physico-chemical indicator of increasing urban pollution were identified as sensitive traits. The results indicate that urban pollution differentially influenced macroinvertebrate traits, with the identification of pollution signature and sensitive traits seen as an important step towards the development of trait-based i...