Benthic macroinvertebrates collected at seven different streams displaying different pollution levels were used to investigate species abundance patterns in polluted streams. Community response to disturbances in streams was analysed using species abundance distribution (SAD) for benthic macroinvertebrates across different levels of pollution. The slopes of rank abundance were characteristically steeper with decreasing species richness at the polluted sample sites, while the slopes were less steep with higher species richness at the clean or slightly disturbed sample sites. The SADs were broadly fitted to the log normal distribution in benthic macroinvertebrate communities across different levels of pollution. A geometric series was partly accepted for the communities at the severely polluted sites where new species could not be readily introduced. A power law was applied to the SADs, and the parameters reflected the states pertaining to the sample sites. The SADs were also efficient in revealing ecological state of communities where physico-chemical indicators could not be easily differentiated for stressful conditions in streams.

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The estimation of self-mixing interferometry (SMI) parameters such as optical feedback factor C and linewidth enhancement factor α is essential to self-mixing (SM) displacement sensors with sub-wavelength resolution. We propose a new method, which is a very simple and fast method to estimate C and α when C > 1 based on an analysis of self-mixing signals (SMSs) in a laser diode. The proposed method is extremely simple, because it takes advantage of analytic relations which enable one to obtain C and α from the simple algebraic operations of the data from SMSs. The simplicity of the method is a great help to developing a compact and low-cost self-mixing (SM) displacement sensor with sub-wavelength resolution which cannot ensure complex operation such as optimization. And the proposed method is highly effective in developing real-time and fast algorithm for the C estimation. This method is applicable when the sensor operates under a moderate or strong feedback regime. The estimation accuracy of C and α are comparable to the results of Yu et al 2004 IEEE Photon. Technol. Lett. 16 990-2; Zabit 2010 PhD Thesis Toulouse; and Fan 2011 MS Thesis University of Wollongong, respectively, and the estimation time of the C parameter is over 30 times faster than Zabit and Fan.