Improving the performance of the EPT Index to ...

African Journal of Aquatic Science

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Improving the performance of the EPT Index to accommodate multiple stressors in Afrotropical streams FO Masese & PO Raburu To cite this article: FO Masese & PO Raburu (2017) Improving the performance of the EPT Index to accommodate multiple stressors in Afrotropical streams, African Journal of Aquatic Science, 42:3, 219-233, DOI: 10.2989/16085914.2017.1392282 To link to this article: http://dx.doi.org/10.2989/16085914.2017.1392282

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African Journal of Aquatic Science 2017, 42(3): 219–233 Printed in South Africa — All rights reserved

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AFRICAN JOURNAL OF AQUATIC SCIENCE

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ISSN 1608-5914 EISSN 1727-9364 http://dx.doi.org/10.2989/16085914.2017.1392282

Improving the performance of the EPT Index to accommodate multiple stressors in Afrotropical streams FO Masese1,2,* and PO Raburu1 Department of Fisheries and Aquatic Sciences, University of Eldoret, Eldoret, Kenya. College of Agriculture, Engineering and Science, University of KwaZulu-Natal, Pietermaritzburg, South Africa. * Corresponding author, e-mail: [email protected]; [email protected] 1

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The EPT index (Ephemeroptera, Plecoptera and Trichoptera) may be skewed by the wide tolerance to multiple stressors of the Baetid, Caenid and Hydropsychid families, which affects the performance of the EPT index as an indicator of multiple stressors in aquatic ecosystems. The effect of the BCH families on the EPT index was evaluated and alternatives were considered to improve its performance. The hypothesis that the removal of the BCH families improves sensitivity of the EPT index to human-induced stressors in streams and rivers was tested. Macroinvertebrates were collected in January–March 2009 at 22 sites in the Nyando and Nzoia Rivers, Lake Victoria basin, Kenya. Nine derivatives and modifications of the EPT index were tested for responses to a disturbance gradient, ranked into three condition categories (reference, intermediate and impaired). The sensitivity of the proportionate abundance derivative of the EPT index improved when the BCH families were removed, whereas that of the richness derivative improved marginally. Other modifications considered performed poorly when compared with the EPT-BCH metrics. Wide distribution of the BCH across all sites, irrespective of the level of disturbance, reduced the sensitivity of the EPT index in the studied streams. The removal of the BCH families enhanced the sensitivity of the index to multiple stressors in Afrotropical streams and rivers. Keywords: biomonitoring, EPT index, macroinvertebrates, urban streams, water pollution, water quality Online Supplementary Material: Table S1: Distribution and relative abundances of macroinvertebrate taxa at sampling sites and site condition categories in streams and rivers in the Lake Victoria basin, Kenya in January–March 2009, is available online at http://dx.doi.org. 10.2989/16085914.2017.1392282

Introduction Macroinvertebrates are important indicators for various stressors in streams and rivers (Resh and Jackson 1993; Barbour et al. 1999; Ollis et al. 2006; Masese et al. 2013), because they play an important role in the food webs of streams and rivers (Vannote et al. 1980; Merritt and Cummins 1996). They are also relatively immobile, widely distributed, and easy to sample and identify to family level (Merritt and Cummins 1996). The orders Ephemeroptera, Plecoptera and Trichoptera, often abbreviated as EPT, are sensitive to many stressors and hence are commonly used in bioassessment programs (Barbour et al. 1996; Barbour et al. 1999). Thus, although sensitive to pollution in temperate streams and rivers, they have been widely used in biomonitoring programs in many regions around the world without evaluating their sensitivity (Ollis et al. 2006; Herman and Nejadhashemi 2015). Due to regional differences in assemblage characteristics, it is not possible simply to adopt these temperate indices and programmes for use in Afrotropical streams and rivers. It is therefore necessary to evaluate the performance of such indices and to modify them to suit local conditions, if necessary. The EPT index, calculated as the number of different taxa (species, genera or families) that belong to the orders Ephemeroptera, Plecoptera and Trichoptera (Lenat 1988)

is one of the most sensitive and prominent indicators of environmental quality in riverine ecosystems (Kerans and Karr 1994; Barbour et al. 1999). In addition, two other derivatives, percent of total EPT taxa and percent of total EPT individuals in a composite sample (e.g. Weigel et al. 2002; Klemm et al. 2003), have commonly been used . Most of the EPT taxa are intolerant to water pollution and will be among the first macroinvertebrate taxa to react to changes in their environment (Lenat 1988; Resh and Jackson 1993; Harding et al. 1998). However, in tropical Africa, the EPT taxa have been shown to provide mixed results, with taxa, such as Baetis spp. (Baetidae), and Cheumatopsyche spp. (Hydropsychidae) displaying tolerance to stressors in streams and rivers (Thorne and Williams 1997; Kasangaki et al. 2008; Masese et al. 2009a, 2009b; Minaya et al. 2013; Kilonzo et al. 2014; Masese et al. 2014a; Mbaka et al. 2014; Lakew and Moog 2015; Kaboré et al. 2016). In developing macroinvertebrate-based multimetric indices for monitoring riverine ecosystems in the Lake Victoria basin, three versions of the EPT index have been considered as metrics, albeit with mixed results (Kobingi et al. 2009; Masese et al. 2009a, 2009b; Raburu et al. 2009a). This is partly because of the tolerance exhibited by the

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Baetidae, Caenidae (Ephemeroptera) and Hydropsychidae (Trichoptera) {BCH} families to organic pollution and habitat disturbance (Thorne and Williams 1997; Minaya et al. 2013). This tolerance enables them to be widely distributed, with higher abundance in areas receiving point sources of organic, agro-industrial and animal waste (Thorne and Williams 1997; Raburu et al. 2009a, 2009b; Masese et al. 2014a). In addition, the Plecoptera has low taxon richness with only one family (Perlidae) recorded from Kenyan streams (Minaya et al. 2013; Masese et al. 2014a, 2014b), as opposed to its ubiquity in temperate streams and rivers. This situation further dampens the variability of EPT metrics across sites experiencing different levels of impairment. Therefore, the effect of the omission of BCH families from the EPT index was tested and the performance of the index across a gradient of human disturbance in Afrotropical streams was evaluated. Metrics in which the three tolerant families are included have been found to offer poor discrimination among sites suffering from different levels of impairment. Where this has been observed elsewhere for the Hydropsychidae (Quinn et al. 1997; Buss et al. 2002) the common practice has been its elimination during EPT index calculations. However, this practice has not been widely applied for the Baetidae and Caenidae, which, together with Hydropsychidae, are considered to be the families most tolerant to pollution among the EPT orders (Dudgeon 1990; Thorne and Williams 1997). These families also display wide distribution among sites affected by different levels and types of pollutants (e.g. Benstead et al. 2003; Beyene et al. 2009; Kaboré et al. 2016). In an attempt to eliminate the problem, Klemm et al. (2003) excluded the Hydropsychidae and tolerant Ephemeroptera taxa from metrics used to develop a macroinvertebrate index of biotic integrity for mid-Atlantic highland streams in the US. The metrics performed well, but they were disqualified, because they displayed the same information with Ephemeroptera and Plecoptera richness metrics that were included in the final index. In order to improve the performance and discriminatory power of metrics and indices used in monitoring the effects of human disturbance in riverine ecosystems, studies have considered combining the EPT with other insect orders, such as the Coleoptera (e.g. Céréghino et al. 2003; Compin and Céréghino 2003, Minaya et al. 2013). Coleoptera are major components of stream invertebrate assemblages and contain sensitive taxa, particularly in the family Elmidae (Buss et al. 2002). In addition, Barbour et al. (1996) found that both the number of Coleoptera and EPT taxa decreased with increasing disturbance. Odonata are another group that are considered as important indicators of environmental conditions in aquatic habitats (Watson et al. 1982; Clark and Samways 1996; Stewart and Samways 1998). Odonates inhabit both aquatic and terrestrial habitats during their life cycle and therefore may better reflect disturbance to the transitional riparian buffer than do other strict aquatic obligates. As a result, they have been used to monitor the effects of grazing on wetland condition (Foote and Hornung 2005) and in evaluating water conditions along a gradient of temporary to permanent water presence (Johansson and Suhling 2004). Because odonates are apex aquatic predators (Merritt and Cummins 1996), their

presence is a good indicator of the presence of other invertebrate prey. Thus, because of the diverse nature of human impacts on streams and rivers in the Lake Victoria Basin (Kairu 2001; Mati et al. 2008), and in eastern Africa generally (Mathooko 2001; Ndaruga et al. 2004; Kasangaki et al. 2008; Mathooko et al. 2009; Kaaya et al. 2015), considering these five insect orders (EPT plus Coleoptera and Odonata) might enhance the accuracy of biological assessments of water quality. The use of macroinvertebrate assemblages as indicators of environmental quality in streams and rivers is becoming popular in eastern Africa (Kibichii et al. 2007; Kasangaki et al. 2008; Kobingi et al. 2009; Masese et al. 2009a, 2009b; Raburu et al. 2009a, 2009b; Minaya et al. 2013; Masese et al. 2013; Elias et al. 2014; Mbaka et al. 2014; Abong’o et al. 2015; Aschalew and Moog 2015; Kaaya et al. 2015; Shimba and Jonah 2016). In these studies, the focus was to identify potential macroinvertebrate metrics that can respond to organic pollution from towns and villages, land-use change, flow variation, urbanisation, discharge of agro-industrial wastes and habitat disturbance by human and livestock activities in streams and rivers. In some of these studies, use of the combined EPT index to monitor changes in water quality has not been satisfactory, because it displays low separation powers among sites suffering from different levels of impairment. This has often been attributed to the wide distribution and sometimes the increased relative abundance, of the BCH families at degraded sites (Masese et al. 2009a, 2009b; Raburu 2009a, 2009b). In tropical Africa, where streams and rivers contain low EPT richness, because of biogeographic reasons, it is sometimes necessary to combine the three orders into a single group, in order to increase the number of taxa, and hence the variability of derived metrics across a gradient of human influence (e.g. Kobingi et al. 2009). By combining the three orders, the proportionate abundance of the three tolerant families is significantly increased, especially in organically polluted sites. The current study investigated possible ways of eliminating this problem, in order to increase the sensitivity of the EPT index. The hypothesis tested is that the removal of the BCH families from among the EPT orders improves the sensitivity of the EPT index to human-induced stress in streams and rivers. Alternatives among other taxonomic groups were also investigated to determine their performance as discriminators of pollution gradients in riverine ecosystems in the Lake Victoria Basin, Kenya. Materials and methods Study area This study was conducted in January–March 2009 in the Nyando River and in two tributaries of the Nzoia River, the Moiben and Kipkarren rivers. The Nyando and Nzoia rivers drain the Kenyan side of the Lake Victoria Basin (Figure 1). The two rivers originate from the western escarpment of the Eastern Rift Valley at altitudes ranging between 1 500 m and 3 000 m above sea level (asl). The two river basins have a hilly topography in the northern and eastern upper reaches, with their elevation decreasing to about

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KENYA Lake Victoria

KENYA

Somalia

AFRICA

Uganda

Ethiopia

M8 M7

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Tanzania

Stations River Catchment Lake Victoria National boundary Town/village

M6 M1

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S5 S3 S2

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oia

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1° N

M2 M3

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Kisumu

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N4 N5

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45

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Figure 1: Map showing positions of sites (stations) in the Nyando and Nzoia Rivers

1 100 m asl in the lowlands at the lakeshore. The lowland climate is sub-humid tropical with bi-modal rainfall, which is characteristic of equatorial latitudes. The highland climate is humid tropical, exhibiting moderated bi-modal rainfall, due to convectional currents from Lake Victoria. Both air temperature and rainfall vary with altitude. The average mean temperature on the upper highlands is about 18 °C, whereas on the lowlands the average mean temperature is 25 °C, although normally it ranges between 20 °C and 28 °C depending on the month of the year (Jaetzold and Schmidt 1983). Rainfall varies from a high of around 1 600 mm per annum in the forested uplands to around 850 mm per annum in the lowlands. Geology, climate and human activities also influence the limnological characteristics of streams and rivers in western Kenya (Davies 1996). The lowlands consist primarily of Pleistocene lake plain deposits (planisols and vertisols) with deep profiles and moderate to low fertility. Highland soils are deeply weathered (nitisols, cambisols) and structurally stable. Native ecological communities include perennial grasslands in the lowlands and evergreen broadleaf forest in the highlands. Most small (below third order) streams in the upper reaches of the catchment are rocky, with coarse substrate often covered by decomposing detritus. Steep hydrological gradients occur in these areas, with long

slopes in excess of 40° inclination, with cascading instream gradients in some areas. In the floodplains of the rivers the gradient reduces considerably (gradient 0.5–0.8) with incidences of flooding being reported during the heavy rains (LBDA 1987; Kadomura 2005). Rivers draining the Kenyan side of the Lake Victoria drainage basin experience multiple threats arising from rapid human population growth and unsustainable land-use practices (Okungu and Opango 2005; Mati et al 2008; Swallow et al 2009; Masese and McClain 2012). For the Nzoia and Nyando river basins, some streams in the upper catchments have minimally disturbed natural habitats and good water quality, while others have suffered from a combination of excessive livestock grazing, human settlement and poor agriculture practices (Masese et al 2009a; Swallow et al. 2009; Abong’o et al. 2015). The human population growth rate is about 3% per annum and the density in some areas, such as western Kenya (parts of the Nzoia River basin), is more than 1 000 persons per km2. The population depends mainly on extensive rain-fed agriculture for domestic and commercial purposes. Dominant lowland agricultural land uses are maize, sugarcane and communal rangeland. In the highlands maize, commercial woodlots and paddock grazing dominate, in addition to large-scale wheat farming in the

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Nzoia River basin and tea plantations in the Nyando River basin. These activities have led to the creation of erosion hot spots in the two river basins (Walsh et al. 2004). The arable and fertile uplands have high agricultural potential, and as a result, they have suffered widespread deforestation in the past. This has been a major cause of concern, because the forests are the main sources of water for the the rivers during base flow conditions. Human settlement and wastewater discharge from agro-industrial activities within the basins are threats to water quality (Osano et al. 2003; Okungu and Opango 2005) and to ecological processes in the rivers, including energy resources and fish production (Ojwang et al. 2007). Selection of sampling sites Site selection was done by identifying all forms of degradation in the two catchments and then selecting a stratified random sampling design. To capture the effects of point sources of pollution from municipal and industrial wastewater discharges, sites were located both upstream and downstream of the discharge point for comparison of their macroinvertebrate assemblage characteristics. Additional reference sites were selected in forest streams. To minimise the effects of stream size on assemblage characteristics, and on metric values and performance, sampling sites were selected in streams and rivers ranging from 3rd order to 7th order (Strahler 1957). In the Nyando River Basin, Raburu et al. (2009b) showed that the number of taxa does not change with river size from stream order 3 to order 7. This also allowed for the use of upstream sites as reference for downstream sites without the effect of changes in stream order on metric values, since available data show that taxon composition does not change along the river (Raburu et al. 2009b). A total of 22 sites in 10 streams were chosen to represent natural environmental conditions and human-influence types and intensities in the area (Figure 1). Habitat and water quality assessment Habitat quality characteristics and selected water quality parameters were determined at each sampling site. The assessed habitat characteristics included channel morphology, modifications, riparian quality, bank stability and erosion, point and non-point sources of pollution all according to Rankin (1995) and with slight modifications for the Lake Victoria Basin (Masese et al. 2009a; Raburu and Masese 2012). Triplicate water physico-chemical parameters were measured at each station before macroinvertebrates were sampled. Conductivity was measured in situ using a conductivity meter (OAKTON®, Model WD-3560710, Singapore), while water temperature and pH were also measured in situ by a combined pH-and-temperature-meter, (OAKTON®, Model pH/Mv/°C METER, Singapore). Water samples for determination of alkalinity, biological oxygen demand (BOD), hardness, nutrients [phosphate phosphorus (PO4−P) and nitrate nitrogen (NO3−N)], total dissolved solids (TDS) and turbidity were collected and analysed according to standard methods (American Public Health Association [APHA] 1998). Total suspended solids (TSS) were determined from GF/F filters gravimetrically after drying (60 °C) to constant weight (APHA 1998).

Masese and Raburu

Macroinvertebrate sampling and sorting At each sampling site, three replicate macroinvertebrate samples were collected from different biotopes using a Surber sampler (0.09 m 2, 300 µm mesh size). Prior to sampling, each site was assessed to identify various available biotopes, from which three random samples were collected. Sampled biotopes included pools (mainly gravel, sand and mud), riffles (mainly stony substrate) and marginal submerged vegetation, encompassing different flow velocities, depths and substrate types. The macroinvertebrates were washed through a 300 µm mesh sieve, hand sorted in the field and preserved in 70% alcohol and delivered to the laboratory. Macroinvertebrates were identified to the lowest taxonomic level possible, mainly family, according to a number of keys (Quigley 1977; Merritt and Cummins 1996; Day et al. 2002; de Moor et al. 2003a, 2003b; Stals and de Moor 2007) and then counted. Characterisation of sites The sampling sites were classified into three condition categories; reference (6 sites), intermediate (10 sites) and impaired (6 sites), based on their habitat and water quality characteristics. Sites were considered as reference if they were located in streams and rivers whose catchments were forested or in mixed land use catchments with no towns or communities living within 500 m of the riparian zone, intact riparian vegetation, no detectable effects of grazing or human activity within 1 km upstream of the sampling site and no hydrologic modification in the watershed (no dams or reservoirs and major water withdrawals upstream of the study site), and no wastewater discharges within 1 km of the sampling site. Impaired sites were identified as those in agricultural or urbanised riparian or catchment land use areas with damaged and eroded riverbanks associated with livestock grazing, row crop agriculture, and obvious point and non-point sources of pollution, such as industrial and municipal wastewater discharges within 10 kilometres upstream. Impaired sites also had a 2 species of Baetidae and/or Hydropsychidae available they have a score of 12, but if 2 or 1 species are encountered they receive scores of 6 and 4, respectively. The findings of this study simplify the scoring by eliminating the necessity to use different scores depending on the richness of Baetidae and Hydropsychidae taxa. The richness derivative of the EPT index slightly improved upon removal of the BCH families. This improvement saw the number of EPT-BCH taxa metric distinguish reference from impaired condition categories, but neither of the two from the intermediate category. This could be attributed to the low number of taxa in the order Plecoptera in the study area, with only one genus occurring in the

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Lake Victoria basin. A study on the global diversity of Plecoptera (Vinson and Hawkins 2003) indicated a peak at 40° N and 40° S. Because of this, metrics developed for temperate streams that separate the EPT into their individual orders do not seem to be applicable to tropical streams. The low number of Plecoptera taxa in Africa (for instance, only one genus has been reported so far in West Africa (Durand and Leveque 1981), limits the use of the Plecoptera as an indicator group for various stressors. Nevertheless, the EPT-BCH taxa metric can be used in the Afrotropics to differentiate between reference and impaired conditions. The performances of other derivatives and modifications of the EPT index were not satisfactory, because they showed similar responses to degradation. While the EPT, EPTC and EPTO displayed similar responses to degradation, the level of redundancy displayed with EPT-BCH metrics was low. Hence, the addition of Coleoptera and Odonata did not improve the EPT index when BCH were still part of the EPT. Moreover, the wide distribution of some Coleopteran genera (e.g. Elmis, Gyrinus and Dineutus) and Odonatan genera (e.g. Gomphus and Aeshna) across the three condition categories in the study area might have resulted in the low performance of the EPTC and EPTO metrics. Similar poor performance has also been reported for the combined COPTE richness index, when it failed to discriminate catchment-scale and reach-scale human influences on stream condition (Minaya et al. 2013). Factors that might have influenced the performance of the EPT index include a lack of significant differences in some water quality parameters among the condition categories, notably water temperature, DO and pH, and the coarse taxonomic identification of macroinvertebrate taxa to the family level. However, available evidence indicates that the BCH families are not as sensitive to changes in water quality as the rest of the EPT families and therefore should be removed from the EPT index. In a study where water quality significantly changed as a result of increased pollution and reach disturbance by humans and animals, the BCH families either increased or maintained their abundance at disturbed sites (especially those receiving organic inputs from livestock and hippopotamus defecation) compared with least disturbed sites (Masese 2016). In another study, the BCH families were among taxa occurring downstream of wastewater discharge points and in stabilisation ponds treating wastewater from sugar cane and molasses industries (Raburu et al. 2017). The same trend has been observed in similar studies in Africa (Thorne and Williams 1997; Lakew and Moog 2015; Shimba and Jonah 2016). It is thus plausible that the three families should not be included in the EPT index when assessing human influences in streams. The EPT-BCH and other indices were further evaluated by using an independent dataset collected from another river basin. The performances of the richness and proportionate versions of the EPT-BCH index were consistent during both the dry and wet seasons (Figures 6 and 7). However, the proportionate version of the metric performed better by discriminating the three condition categories during the dry season, suggesting that the index is more stable during the dry season. It has been noted that human activities are patchy along streams draining agricultural

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catchment, resulting in greater inter-site differences in physico-chemical conditions during the dry season, in turn resulting in greater differentiation in macroinvertebrate assemblage characteristics across sites (Masese et al. 2014a). Conversely, during the wet season, high flows increase longitudinal connectivity and reset systems by flushing fines and increasing dissolved oxygen levels, enabling taxa to colonise new areas. At the same time, spates and scouring make stream substrata more uniform, and this reduces inter-site differences in community structure (Leung et al. 2012). These factors may explain the poor performance of both the richness and proportionate EPT-BCH indices in the Mara River basin, because taxa were probably more uniform and widespread across all sites during the wet season and more patchy during the dry season (Masese et al. 2014a). Thus, the reduced performance of the EPT-BCH index during the wet season was most likely due to the reduced instream disturbance and the improvement in water quality during the wet season (Shivoga 2001; Masese et al. 2009; Masese et al. 2014a). Wider considerations Many of the studies that have used the EPT index to assess water quality in Africa have used family level identifications. This raises the question whether family level identifications are appropriate to discriminate different sources of impairment in streams and rivers. Consequently, it is likely that the family level identifications used in this study lowered the discriminatory ability of the richness derivative of the EPT index. While this cannot be ruled out, lack of taxonomic knowledge of most EPT taxa and a lack of identification keys for many macroinvertebrates in African streams and rivers makes identification beyond the family level difficult and uncertain. Moreover, considering that there might be limited distributions of genera and/or species within a widespread family across the Afrotropics, it is suitable to use family level identifications. As demonstrated in this study, the performance of the EPT-BCH index is satisfactory and it can be used to discriminate between reference and impaired conditions in streams. The EPT-BCH index performed better, compared with other commonly used indices, such as the sensitivity values of SASS5, SASS-ASPT, BMWP and BMWP-ASPT. However, the sampling method used in this study is not according to the requirements of both SASS5 and BMWP, and only the SASS5 and BMWP sensitivity ratings have been used. Thus, the findings should be interpreted with caution. The index can further be improved as we improve our taxonomic knowledge of macroinvertebrates and their tolerance to various pollutants in African streams. In the current study, the EPT-BCH index was derived from samples collected in streams greater than 2nd order. In the Lake Victoria basin, 1st and 2nd order streams recorded low macroinvertebrate taxon richness (Raburu et al. 2009; Minaya et al. 2013). Because of this low diversity, the EPT richness index failed to discriminate between the three levels of human disturbances (high, intermediate and low) at both the catchment- and reach-scale (Minaya et al. 2013). It is thus unclear whether the same effect will dampen the discriminatory ability of the index when lower order streams are evaluated.

Conclusions Although the EPT orders are recognised as the most sensitive taxa to degradation in riverine ecosystems, the inclusion of BCH families in any of the derivatives of the EPT index compromises their ability as discriminators of pollution gradients. In this study, the removal of BCH families from the EPT orders improved the sensitivity of the EPT index to human-induced stress. The BCH families should therefore be removed from any of the derivatives of the EPT index used as a metric in biomonitoring programs for Afrotropical riverine ecosystems. The performance of the richness derivatives of the EPT index is not guaranteed and the inclusion of Coleoptera or Odonata does not noticeably improve its performance Acknowledgements—Financial support for this study came from the Kenya National Council for Science and Technology. We thank Mrs William Kinyua and Lubango Lunaligo, Department of Fisheries and Aquatic Sciences, University of Eldoret, for assistance during fieldwork and sample processing. We are grateful to Alfred Achieng (University of Eldoret) for help with a map of the study area. Comments by two reviewers improved earlier drafts of this manuscript.

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Manuscript received 15 January 2017, revised 28 September 2017, accepted 9 October 2017 Associate Editor: C Thirion