Spatial and seasonal variation in the macro-invertebrates and physico-chemical parameters of the Enfranz River, Lake Tana sub-basin (Ethiopia)

MS-Abrehet43/11/012

Spatial and seasonal variation in the Macro-invertebrate Community Structure and physico-chemical parameters of Enfranz River, Lake TanaSub-Basin (Ethiopia)

Abrehet Kahsay Mehari1, Ayalew Wondie2, Minwyelet Mingist1 and

Jacobus Vijverberg3*

1Fisheries, Wetlands and Wildlife Management Program, Bahir Dar

University, PO Box 79, Bahir Dar, Ethiopia2Biology Program, Bahir Dar University, PO Box 79, Bahir Dar,

Ethiopia3Department of Aquatic Ecology, Netherlands Institute of

Ecology (NIOO-KNAW), Droevendaalsesteeg 10, 6708 PB Wageningen,

The Netherlands*) Corresponding author: e-mail: [email protected]

AbstractThe macro-invertebrate community of the Enfranz River,

located northwest of Bahir Dar city in the southern part of

Lake Tana Watershed, was studied in wet and dry seasons from

August 2010 to May 2011. This river feeds Lake Tana and has a

catchment area of 198 km2. The river was sampled along its

whole length at four sites from headwaters until its outflow

in Lake Tana. The following physico-chemical parameters were

measured: temperature, dissolved oxygen, total dissolved

solids, conductivity and pH. Most physico-chemical parameters

varied significantly (P < 0.05) among sampling sites. Mean

values of dissolved oxygen concentrations at the head of the

river (6.08 mg l-1) were significantly higher (P < 0.05) than

the concentrations at the more downstream sites (3.3-5.2 mg

l-1). Macro-invertebrates were identified to the family

level; a total of 15286 individuals belonging to 30 families

were collected. The Shannon-Wiener Diversity Index and the

Hilsenhoff Family-level Biotic Index and several macro-

invertebrate community metrics for water quality assessment

were calculated. Macro-invertebrate diversity indices and

community metrics differed significantly among sampling sites

(ANOVA, P < 0.05), diversity being higher at the headwaters.

Diversity differed significantly among sampling seasons (P <

0.05); the highest values were observed in the wet season.

Pearson’s correlation coefficients showed that, dissolved

oxygen, total dissolved solids and conductivity were

II

significantly correlated with macro-invertebrate diversity

and community metrics, but pH and temperature did not show

any relationship. We conclude that the River downstream is

severely affected by land use of the local people. Mitigating

management measures are urgently needed to restore the

quality of this river.

Key words: Water quality, Water quality management, Effects

of land use, Biodiversity.

III

1. Introduction

Freshwater ecosystems have been altered by human disturbances

such as agriculture, urban development, impoundment,

channelization, mining, forest fire suppression, road

construction and species introductions (LaBonte et al., 2001). All

of which have lead to severe degradation and loss of biodiversity

(Vinson and Hawking, 1998) and as a result these ecosystems have

become the most endangered ecosystems on the planet (Dudgeon et

al., 2006). While many taxa contribute to biodiversity in

freshwater ecosystems, aquatic macro-invertebrates play a central

ecological role in many running water ecosystems (Boulton, 2003)

and are among the most ubiquitous (Voelz and McArthur, 2000) and

diverse organisms in fresh waters (Strayer, 2006). Aquatic macro-

invertebrates form an important component of the trophic

structure of freshwater ecosystems since they play an important

role in the food webs (Grubh and Mitsch, 2004; Xie et al., 2006)

and stimulate nutrient cycling by reducing the size of organic

particles (Callisto et al., 2001). They are important food items

for fish (Findlay et al., 1989) and aquatic birds (Kostecke et al.,

2005).

Macro-invertebrates are often used as biomonitoring tools

(Dallas and Mosepele, 2007). Biomonitoring is based on the

principle that organisms are the ultimate indicators of the

environment they are within (Mandaville, 2002 and U.S. EPA,

2002). Biomonitoring has the advantage above monitoring physico-

4

chemical parameters that it can detect cumulative physical,

chemical and biological impacts of adverse activities to an

aquatic system (Davis et al., 2003).

Aquatic macro-invertebrates are often preferred for

biomonitoring because of the following three reasons: Firstly,

they are not very mobile and therefore they are representative of

the area from which they are collected, secondly they have

relatively short life cycles and therefore can reflect

environmental changes quickly through changes in their community

composition and finally they respond to pollutants in both water

column and sediments (Reece and Richardson, 2000).

Despite the important roles of macro-invertebrates in

aquatic ecosystems, published information about macro-

invertebrates in Ethiopia is scarce and this is the first study

on macro-invertebrates in one of the ca. 47 rivers flowing into

Lake Tana, Ethiopia’s largest lake.

The purpose of this study on Enfranz River was three fold:

(1) To assess the spatial and seasonal variation of physico-

chemical parameters and macro-invertebrate diversity and other

community metrics over a river continuum from headwaters until

its outflow into Lake Tana, (2) to assess the spatial and

seasonal variation in water quality over this river continuum,

and (3) to conclude if water management measures are necessary to

mitigate the observed water quality.

5

2. Materials and methods

2.1. Description of study area

Enfranz River is situated northwest of Bahir Dar city and is a

source of drinking water for its people. The upper stream of the

river is rich with a number of springs. It drains to southwest of

Lake Tana and its catchment area is ca. 198 km2 (Woldegeriel G.

Kidan, 2010). The climate of the Enfranz river area is

characterized by a main-rainy season with heavy rains during

July–September, dry season during December–April, pre-rainy

season during May–June and post-rainy season during October–

November.

The riparian vegetation of the river area was studied by

Kidan (2010). He reported about 27 species of riparian vegetation

of which three species were endemic to Ethiopia (Erythrina brucei,

Mellitia ferruguina and Acanthus senni). The main water source of the

Enfranz River, besides surface water, is groundwater. From wells

drilled near the river, this water is directly, without storage,

pumped to the people in the city (Kassahun, 2008). The total

population of Bahir Dar was in 2007 ca. 220000 inhabitants and

has a population growth rate of 6.6 % per year (CSA, 2007), which

is more than twice as high as the average population growth rate

in Ethiopia.

6

2.2. Sampling

This study was conducted in wet and dry seasons of 2010-2011.

Samples for both physico-chemical and macro-invertebrates were

collected in August and October 2010 and January and May 2011

covering both the wet and the dry seasons. Four sampling sites

along the river gradient of the Enfranz River were selected and

the sites were designated as E1 to E4. Sampling sites ranged from

head waters (E1) to the mouth of the river (E4), where the water

flows into Lake Tana. The detailed description of the sampling

site is presented in (Fig. 1, Table 1).

Physico-chemical parameters

Samples for physico-chemical parameters were taken at the same

location and almost simultaneously with the samples for macro-

invertebrates. Water temperature, dissolved oxygen (DO), pH,

total dissolved solids (TDS) and conductivity were measured in situ

using electronic measure equipment.

Macro-invertebrates

Quantitative sampling was carried out based on the rapid bio-

assessment protocols that are used for rivers and wadable streams

(Barbour et al., 1999). Samples were taken using dip net with mesh

size of 500 µm. In the field, the collected material was sieved

through 500 µm and 250 µm mesh sieves and put into collection

bottles. The sampling effort at each site was 30 minutes. Then

macro-invertebrates collected from riffles and pools of each site

7

were pooled so as to obtain a single sample from each site. All

samples were preserved with 70% ethanol until laboratory analyses

and counting. All the organisms in the sample were enumerated and

identified to the lowest possible taxonomic level (family level)

using a dissecting microscope and standard keys (Edmondson,

1959; Jessup et al., 1999; Gooderham and Tysrlin, 2002 and

Bouchard, 2004).

2.4. Data Analysis

Descriptive statistics were used to analyze physico-chemical

data. For the macro-invertebrate communities two biotic indices

were calculated for each site and each sampling date. The

Shannon-Wiener Diversity Index (H′) is a diversity index that

incorporates richness and evenness. A high H′ indicates a good

water quality. H′ was calculated as follows:

:

H′ = - (P∑ i ln [Pi])

Eqn 1

Where: Pi is the relative abundance (ni/N) of species i, ni =

number of individuals in species i and N = total number of

individuals in all species. H′ is ranging from 0 for a community

with a single species, to over 7 for a very diverse community.

The Hilsenhoff Family-level Biotic Index (HFBI) is a biotic index

that is calculated by multiplying the number of individuals of

each family by an assigned tolerance value for that family.

8

Assigned tolerance values range from 0 to 10 for families and

increase as water quality decreases (Hilsenhoff, 1988; Bode et

al., 1996). This Index was calculated as follows:

HFBI = Σ [(TVi) (ni)] ⁄ N …………………………………..Eqn 2

Where: TVi is tolerance value for species i, ni is the number of

individuals in species i and N is the total number of individual

in the sample collection. High HFBI community values are an

indication of organic pollution, while low values indicate good

water quality.

Excel spreadsheets and statistical software (SPSS version 16)

were used for the statistical analysis. Two ways ANOVA was used

to evaluate differences in physico-chemical data and macro-

invertebrate metrics among the sampling sites and seasons. Macro-

invertebrate metrics were Arcsine transformed before analysis.

Data used in ANOVA analyses were first tested on homogeneity of variances. Differences among means were tested using Tukey HSD.

Pearson’s correlation coefficients were used to determine the

relationships between physico-chemical parameters and macro-

invertebrate metrics.

3. Results

3.1. Physico-chemical Parameters

9

Dissolved oxygen

The mean values of dissolved oxygen (DO) range from 3.27 mg/l at

the mouth of the river (E4) to 6.08mg/l in the head waters (E1)

(Table 2). The mean value of dissolved oxygen showed significantvariation among sampling sites (F=61.25, P=0.000), the value at

E1 being significantly higher than at the other sites. The mean

values of dissolved oxygen in wet and dry season were similar and

not significant different (F=0.044, P=0.84).

Temperature

Temperature did not differ significantly among sampling sites

(F=0.59, P= 0.62) and seasons (F=0.72, P=0.42).

Total dissolved solids

The mean value of total dissolved solids along the study sites

ranged from 82.78 ppm at E2 to 146.5 ppm at E4, while its value

in wet and dry season was 92.45 ppm and 117.9, respectively

(Table 2). The value of total dissolved solids along sampling

sites showed significant variation (F=4.55, P=0.04), the value at

E4 being significantly higher than at E1, E2 and E3. Contrary to

our expectations, differences among seasons were not significant

(F=3.70, P=0.09).

Conductivity

Mean values for conductivity ranged from 165.50 μS/cm at E2 to

246.75 μS/cm at E4 (Table 2). There was significant variation

10

among sampling sites (F=4.55, P=0.04); the value at E4 being

significantly higher than at E1, E2 and E3. Differences among

seasons were not significant (F=3.702, P=0.091).

pH

The mean value of pH was 7.1 (Table 2). Values did not differ

significantly among sampling sites (F=0.522, P=0.679) and seasons

(F=0.44, P=0.83).

3.2. Macro-invertebrates

A total of 15286 macro-invertebrate individuals belonging to 30

families were collected from 4 sites during the survey work

(Table 3). The total number of individuals present at each site

ranged from 2690 at E1 to 6473 at E4 and 6512 and 8774 during wet

and dry seasons, respectively. Libellulidae were the most

abundant family (2540 individuals), followed by Chironomidae

(1747 individuals), Belostomatidae (1135 individuals),

Coenagrionidae (1106 individuals), Culicidae (678 individuals),

then Corixidae (675 individuals).

Composition of taxa The mean proportions of ephemeropterans varied between 0.12 % and

23.59 %. The lowest value was observed at E4 and the highest

value at E1 (Table 4), differences among sampling sites were

11

significant (F = 433.09, P = 0.000). In contrast, the difference

between seasons was not significant (F = 0.72, P = 0.42).The mean poportions of trichopterans ranged from 0.00 % at

E4 and E3 to 12.59 % at E1 (Table 4), differences were

significant (F = 241.58, P = 0.000). The differences between

seasons was relatively large (Table 4) and significant (F =

17.79, P = 0.03).

The mean proportions of dipterans varied from 4.29 % at E1

to 29.77 % at E3 (Table 4), differences were significant (F =

71.44, P = 0.000). Value at E4 was significantly higher than at

E1, E2 and E3. The differences among seasons were not significant

(F = 3.22, P = 0.11).

Biotic indices

The mean values of H’ at sampling sites ranged from 2.39 at E4 to

3.02 at E2 (Table 4). The H′ value showed significant variation

among sampling sites (F = 143.08, P = 0.000); the value being

significantly higher in E2 than E1, E3 and E4. Differences amongseasons were not significant (F= 4.78, P = 0.60).,,,,

The mean values of HFBI ranged from 5.38 to 8.19.The lowest

value was at E1 and the highest value was at E4 (Table 4).

Differences among sampling sites were significant (F = 938.64, P

= 0.00). Mean values for wet and dry season were 6.86 and 7.17,

respectively (Table 4); differences were significant (F = 44.86,

P = 0.000).

12

3.3. Correlations between physico-chemical parameters and macro-

invertebrate metrics

Pearson correlation coefficients between physico-chemical

parameters and macro-invertebrate metrics are presented in Table

5. Macro-invertebrate metrics were significantly correlated to

some of the physico-chemical parameters.

Of all parameters, dissolved oxygen was the only one which

was significantly correlated with all macro-invertebrate metrics

(P < 0.05). In contrast, temperature and pH did not show any

significant correlations. Shannon-Wiener Diversity Index, percent

Ephemeroptera and percent Trichoptera were positively correlated

to dissolved oxygen, whereas HFBI and percent dipterans showed

negative correlations.

TDS (total dissolved solids) and conductivity were

negatively related to the Shannon-Wiener Diversity Index.

4. Discussion

4.1. Physico-chemical parameters

In this study, all measured physico-chemical parameters were not

significantly different between seasons. This may have been

partially caused by the sampling dates during the wet season.

August was in the main rainy season, but October was in the post-13

rainy season. During this season it was still rainy, but rain

fall and runoff with sediments was less and therefore water

quality parameters were less affected. In contrast with the non-

significant differences among seasons, differences among sampling

sites were often significant, but only for dissolved oxygen

content (DO) we observed a clear trend along the river from

headwaters until the outflow in Lake Tana. Only E1 (headwaters)

had DO levels between 6 and 9 mg l-1, which is typical for

unspoiled small tropical forest rivers (Neill et al., 2006). The

others sites showed significant reductions in DO, particularly

sites E3 and E4 had low DO values. The decline in the DO at these

sites is most probably caused by the increased organic matter

content from cattle grazing, agricultural activities and

fisheries. The pH showed very little variation among sites and

values were within the permissible range for natural waters

(USEPA, 2002).

4.2 Macro-invertebrates

The total number of taxa (30) we found in the Enfranz River was

similar to the number of taxa observed by Sitotaw (2006) for the

Ethiopian Baro River (29), but lower than the number of taxa (42-

49) in three other large Ethiopian Rivers (Blue Nile, Omo River,

Awash River). The total number of taxa observed in our study is

also low when compared with the over 50 total taxa reported for

most tropical African rivers (Victor and Ogbeiu,1985; Endokpayi14

et al., 2000; Ogbeibu, 2001; Adakole and Annue, 2003). The

relatively low number of taxa recorded in the present study could

be due to physico-chemical condition like low DO (Uwadiae, 2009)

and the relative small catchment size of the Enfranz River.

Libellulidae were the most dominant taxon. The high

densities of Libellulidae in the outflow of the river was

probably caused by the high deposition rate of fine sediment and

detritus in this area (Merrit and Cummins, 1988). Dipterans were

dominant too, most individuals belonged to the family

Chironomidae. This is a common phenomenon in both temperate and

tropical waters (Victor and Onomivbori, 1996; Ogbeibu, 2001).

Composition of macro-invertebrate taxa We observed that Ephemeroptera and Trichoptera were more abundant

in the headwater sites E1 and E2 than downstream, especially the

proportion of Baetidae (Ephemeroptera) was very high. One reason

may be that the downstream sites were dominated by agriculture

and grazing activities. It is well known that distribution of

macro-invertebrates in rivers is strongly influenced by

anthropogenic impacts (e.g., Matthaei et al., 2000). Another reason

for the reduced abundance of Ephemeroptera and Trichoptera

downstream may be the decreasing size of the particulate organic

matter (Vannote et al., 1980; Bradt et al., 1999). The relative high

abundance of Trichoptera during the wet season can probably be

explained by the increased particulate organic matter

concentrations from leaf litter inputs (Afonso et al., 2000).

15

Dipterans showed relatively high abundances in downstream

stations. Since most dipteran larvae contain hemoglobin they are

able to survive low oxygen conditions (Lake, 2003). High

abundance of dipterans indicate poor water quality (Hooper et al.,

2003). An increase in its densities in response to organic

enrichment by anthropogenic activities frequently eliminates all

other macro-invertebrates (Marques and Barbosa, 2001).

Biotic indices

Downstream stations had lower Shannon-Wiener diversity values

probably due to the presence of livestock and other anthropogenic

activities. Herbivory of aquatic vegetation and nutrient inputs

via urine and fecal deposition and trampling of sediments which

was a common phenomenon in these sites (Abrehet Kahsay Mehari

personal observations), have direct impacts on the macro-

invertebrate communities in streams (Griffith et al., 2005).

Hilsenhoff Family-level Biotic Index indicates organisms’

tolerance to low dissolved oxygen or high organic pollution. High

values are indicative of organic pollution while low values are

indicative of clean water. Average HFBI values at head water

station E1 indicated a fair water quality, but the more downward

stations all showed poorer water quality: fairly poor (E2), poor

(E3) and very poor (E4), respectively.

4.3. Correlations between physico-chemical parameters and macro-

invertebrate metrics

16

The correlation that exists between physico-chemical parameters

and the macro-invertebrates’ metrics indicate that physico-

chemical parameters regulate the distribution of the different

macro-invertebrate taxa, i.e. affect community structure. This

was also observed by Ogbogu (2001) for a stream-reservoir system

in Nigeria.

4.4 Conclusions

Land use strongly affected oxygen concentrations, macro-

invertebrate community structure and biodiversity based on the

relative abundance of the macro-invertebrate taxa. Biodiversity

indices indicated poor and very poor water quality at the down

stream stations. We conclude that the Enfranz River downstream is

severely affected by land use of the local people. Mitigating

management measures are urgently needed to restore the quality of

this river.

5. Acknowledgements

This research was carried out under the Agriculture and

Environmental Science College and Fisheries, Wetlands and

Wildlife program. We are thankful for the practical and mental

support of colleagues and friends during the course of the

research. The financial support from the Bahir Dar University and

17

Amhara regional Agricultural Research Institute (ARARI) is highly

acknowledged.

6. References

Adakole, J.A. and Annue, P.A. (2003).BenthicMacroinverteberates as indicators of Environmentalquality of an urban stream, Zaria, Northern Nigeria. J.Aquat. Sci. 18: 85-92.

Afonso, A.D.O., Henry, R., Rodella, R., and Maimoni, C. S.(2000). Allochthonous matter input in two differentstretches of a headstream. Braz. Arch. Biol. Tec. 43: 335–343.

Barbour, M. T., Gerritsen, J., Snyder, B. D., and Stribling,J. B. (1999). Rapid bio-assessment protocols for use instreams and wadeable rivers: periphyton, benthic macroinvertebrates and fish, 2nd ed. EPA 841-B-99-002. U.S.Environmental Protection Agency; Office of Water;Washington D.C.

Bode, R. W., Novak, M. A., and Abele, L. E. (1996). Qualityassurance Work plan for Biological Stream Monitoring inNew York State. NYS department of EnvironmentalConservation, Albany, NY.

Bouchard, R.W. (2004). Guide to aquatic macroinvertebrates ofthe Upper Midwest. Water C.E.M. Bicudo, T. Matsumura-Tundisi (Eds.), Limnology in Brazil. pp. 365-371.ABC/SBL. Rio de Janeiro: Graftex Comunicação Visual.

Boulton, A. J. (2003). Parallels and contrasts in the effectsof drought on stream macro-invertebrate assemblages.Freshwater Biology. 48: 1173-1185.

Bradt, P., Urban, M., Goodman, N., Bissell, S. and Spiegel, I.(1999). Stability and resilience in benthic macro-invertebrate assemblages. Hydrobiologia. 403: 123-133.

18

Callisto, M., Moreno, P., and Barbosa, F.A.R. (2001). Habitatdiversity and benthic functional trophic groups at SerraDo Cipo, Southeast Brazi. Rev. Brasil. Biol. 61: 259-266.

CSA. (2007). Statistical Abstract 2007. Central Statistical Agency,Addis Ababa.

Dallas, H. F., and Mosepele, B. (20007). A Preliminary Surveyand Analysis of the Spatial Distribution of AquaticInvertebrates in the Okavango Delta. African journal of aquaticscience. 32: 1-11.

Davis, S., Vellids, G., and Pringle, C. M. (2003). Macroinvertebrates Biomonitoring in Interminant Coastal PlainStreams Impacted by Animal Agriculture, Journal ofEnvironmental Quality. 32:1036-1043.

Dudgeon, D., Arthington, A. H., Gessner, M. O., Kawabata, Z.,Knowler, D. J., Leveque, C., Naiman, R. J., Prieur-Richard, A., Soto, D., Stiassny, M. L. J., andSullivan, C.A. (2006). Freshwater Biodiversity:importance threats, status and conservation challenges.Biological Reviews. 81:163-182.

Edmondson, W. T. (1959). Fresh water biology. 2nd ed. JohnWiley and Sons Inc. New York, USA.

Edokpayi C.A., Okenyi, J.C., Ogbeibu, A.E. and Osimen, E.C.(2000). The effect of Human activities on themacrobenthic Invertebrates of Ibiekuma stream, Ekpoma,Nigeria. Biosc. Res. Comm.. 12: 79-87.

Findlay, S., Schoeberl, K., and Wagner, B. (1989).Abundance,Composition, and Dynamics of the Invertebrate Fauna of aTidal Freshwater Wetland. Journal of the North AmericanBenthological Society, 8: 140-148.

Gooderham, J. and Tysrlin, E. (2002). The water bug book. Aguide to the freshwater macro-invertebrates of temperateAustralia. Csiro publishing.

19

Griffith, M. B., Hill, B., Mccormick, H., Kaufmann, R.,Herlihy, T., Selle, A. R. (2005). Comparative applicationof indices of biotic integrity based on periphyton,macro-invertebrates, and fish to southern Rocky Mountainstreams. Journal of ecology and natural environment, 5: 117- 136.

Grubh, A. R., and Mitsch, W. J. (2004). Distribution andabundance of macro-invertebrates in created wetlandecosystems. 2003 Annual report (Olentangy River WetlandResearch Park).

Hilsenoff, W. L. (1988). Rapid field assessment of organicpollution with a family-level biotic index. Journal of theNorth American Benthological Society, 7: 65-68.

Hooper, H. L., Sibly, R. M., Hutchinson, T. M., and Maund, S.J. (2003). The in uence of larval density, foodflavailability and habitat longevity on the life historyand population growth rate of the midge Chironomusriparius. Oikos, 102: 515–524.

Jessup, B. K., Markowitz, A., and Stribling, J. B. (1999).Family-level key to the stream invertebrates of Marylandand surrounding areas. Maryland department of naturalresources Chesapeake Bay and watershed program resourceassessment service monitoring and non-tidal assessmentdivision CBWP-MANTA-EA-99-2.

Kassahun, G. (2008). Physico-chemical and BacteriologicalDrinking Water Quality Assessment of Bahir Dar town watersupply from source to yard connection (NorthWesternEthiopia). M.Sc Thesis, Addis Ababa University, AddisAbaba.

Kidan, W.G. (2009).Biodiversity assessment/Majorvegetation/and land use impacts of Enfranz Riverinewetland in Lake Tana watershed, Northern BahirDar,Ethiopia. MSc thesis, School of Graduate Studies, BahirDar University.

20

Kostecke, M. R., Smith, M. L., and Hands, M. H. (2005). Macro-invertebrate Responses to Cattail Management at CheyenneBottoms. Wetlands journal, 23: 758-763.

LaBonte, J. R., Scott, D. W., McIver, J. D., and Hayes, J. L.(2001).Threatened, endangered and sensitive insects inEastern Oregon and Washington forests and adjacent lands.Northwest Science, 75:185-198.

Lake, P. S. (2003). Ecological effects of perturbation bydrought in owing waters. fl Freshwater Biology, 48: 1161-1172.

Mandaville, S. M. 2002. Benthic macro-invertebrates infreshwaters-taxa tolerance values, metrics, andprotocols. Project H-1. Soil and Water conservationsociety of metro Halifax.Environmental protection agency:Office of research and development, Washington D.C.

Marques, M. M., and Barbosa, F. (2001). Biological quality ofwaters from an impacted tropical watershed (middle RioDoce basin, southeast Brazil), using benthic macro-invertebrate communities as an indicator. Hydrobiologia,457: 69–76.

Matthaei, C. D., Arbuckle, C. J., Townsend, C .R. (2000).Stable surface as refugia for invertebrates duringdisturbance in a New Zealand stream. Journal of North AmericanBenthological societies, 19: 82-93.

Merritt, R. W., and Cummins, K. W. (1988). An introduction tothe aquatic insects of North America. Kendall, Hunt Pub.Co., Dubuque, Iowa, 722p.

Neill, C., Deegan, L. A., Thomas, S. M., Haupert, C. L.,Krusche, A. V., Ballester, V. M., and Victoria, R .L.(2006). Deforestation alters the hydraulic andbiogeochemical characteristics of small lowland Amazonianstreams: Hydrological Processes, 20: 2563-2580.

21

Ogbeibu, A. E. (2001). Distribution, density, and diversity ofdipterans in a temporary pond in Okomu forest reserve,southern Nigeria. Nigeria Journal of Aquatic Sciences, 16: 43-52.

Ogbogu, S. S. (2001) .Assessment of water quality and macroinvertebrates’ abundance in Opa-stream Reservoir system,Ile-Ife. Journal of Pure Applied Sciences, 17: 517-521.

Pielou, E. C. (1966). An introduction to mathematical ecology.Wiley, New York.

Reece, F.P., and Richardson, S.J. (2000).Biomonitoring withthe Reference Condition Approach for the Detection ofAquatic Ecosystems at Risk. Proceedings of a conferenceon the Biology and Management of species and habitats atrisk.

Sitotaw, B. (2006). Assessment of Benthic-Macro-invertebratestructures in relation to environmental degradation insome Ethiopian rivers. Biological Reviews, 81: 163-182.

Strayer, D. L. (2006). Challenges for freshwater invertebrateconservation. Journal of the North American Benthological Society,25:271–287.

USEPA (2002). Summary of biological assessment programs andbio-criteria development for states, tribes, territories,and interstate commissions: Streams and wadeable rivers.EPA 822-R-02-048. Washington, D.C.: U.S. Environmentalprotection agency, office of environmental informationand office of water.

Uwadiae, R. E. (2009). An ecological study on the macrobenthicinvertebrate community of Epe lagoon, Lagos. PhD. ThesisUniversity of Lagos, Akoka, Lagos. 253 p.

Vannote, R. L., Minshall, G. W., Cummins, K. W., Sedell, J.R., and Cushing, C. E. (1980). The River ContinuumConcept. Canadian Journal of Fisheries and Aquatic Sciences, 37: 130-137.

22

Victor, R., and Onomivbori, O. (1996). The effects of urbanperturbation on the benthic macro-invertebrates of asouthern Nigeria stream. In: SPB Academic PublishingAmsterdam, the Netherlands. 223-238pp.

Victor, R and Ogbeibu, A.E. (1985). Macrobenthic invertebratesof a stream flowing through farmland in Southern Nigeria.Environmental Pollution series A. 39:333-347.

Vinson, M. R., and Hawkins, C. P. (1998). Biodiversity ofstream insects: variation at local, basin and regionalscale s. Annual Review of Entomology 43:271-193.Northwest Science.Voelz, N.J., and Mcarthur, J.V. 2000.An exploration of factors influencing lotic insectspecies richness. Biodiversity and Conservation, 9,1543–1570.

Voelz, N.J., and Mcarthur, J.V (2000). An exploration offactors influencing lotic insect species richness.Biodiversity and Conservation, 9, 1543–1570.Wallace, J.B., Grubaugh, J. W., and Whiles, M. R. (1996). Bioticindices and stream ecosystem processes: Results from anexperimental study. Ecological Applications, 6: 140-151.

Xie, Z., Tang, T., Ma, k., Liu, R., Qu, X., Chen, J., and Ca,I. (2006). Effect of plant Architecture on the structureof Epiphytic macro-invertebrates in a Chinese Lake.Journal of fresh water ecology, 21:132-137.

23

Table 1. Description of sampling sites in the Enfranz River (see

also Figure 1).

Site

Name

Coordinates Altitude Descriptions

E1 11.600659N

37.279893E

1833 Head of the river, sides covered

with patchy grasses and few

shrubs. More than 10 springs join

here to create the river.

E2 11.622792N

37.289684E

1805 River sides surrounded by

riparian vegetation.

E3 11.639711N

37.299492E

1791 River sides surrounded by big

trees. Used by local people to

cultivate crops and for washing

and bathing site.

E4 11.647443N

37.310901E

1789 Mouth of the river. Agriculture,

cattle grazing and fisheries

dominate.

24

Table 2. Mean (± SE) values of physico-chemical parameters per site and season along the Enfranz River (2010-2011). SE = Standard error.

ParametersDO (mg

l-1)

Temp

(oC)

TDS (ppm) Cond

(μS/cm)

pH

Sampling sitesE1 6.08±0.14

a

20.33±0.6

2a

94.75±15.77ab 207.18±9.09

ab

7.12±0.

02aE2 5.16±0.07

b

21.12±0.9

7a82.78±10.51bc

165.50±21.0

4bc

7.16±0.

03aE3 4.19±0.12

c

19.17±0.5

0a96.70±3.05ac

192.03±7.46

ac

7.16±0.

01aE4 3.27±0.23

d

21.88±0.2

5a

146.50±

20.04a

246.75±17.8

1a

7.14±0.

01a

Sampling seasonWet 4.66±.45

a

19.98±.66

a92.45±11.41a

192.04±16.26

a

7.14±.

03aDry 4.69a±.3

9a

21.26±.36

a117.91±12.62a

213.69±11.89

a

7.15±.

01a

25

Table 3. Total number of collected macro-invertebrates per familyat each sampling site and per season in the Enfranz River (2010-2011).

FamilyTolerance value

Sampling sites and seasons E1 E2 E3 E4 Wet Dry Total

Ephemeroptera

Baetidae 5 329 243 66 0 305 327 632

Caenidae 6 205 106 63 7 171 210 381

Heptageniidae 4 76 0 0 0 28 48 76

Potomanthidae 3 25 0 0 0 7 18 25

TrichopteraHydropsychidae 4 166 101 0 0 152 115 267Hydroptilidae 4 55 0 0 0 33 22 55Philoptotamidae 3 34 0 0 0 29 5 34Phryganeidae 4 67 0 0 0 52 15 67Rhyacophilidae - 10 0 0 0 9 1 10OdonataAeshnidae 3 83 49 0 0 88 44 132Coenagrionidae 9 12 77 381 636 426 686 1106Libellulidae 9 17 60 503 1960 888 1652 2540Calopterygidae 5 26 0 0 0 6 20 26HemipteraBelostomatidae 9 150 288 124 573 451 684 1135Corixidae 8 57 122 211 285 271 404 675Gerridae 6 189 350 47 64 276 374 650Naucoridae 8 81 102 57 0 107 133 240Nepidae 7 74 133 55 0 104 158 262Notonectidae 9 43 65 143 319 229 341 570Pleidae 8 0 69 57 78 96 108 204Veliidae 7 63 113 66 61 127 176 303ColeopteraDytiscidae 5 121 85 0 0 77 129 206Elmidae 4 295 84 78 0 216 241 457Gyrinidae 4 227 87 80 123 285 232 517Haliplidae 5 67 65 65 58 123 132 255Hydrophilidae 5 70 71 53 66 124 136 260Dipterans Ceratopogonidae 6 25 116 175 345 289 372 661Chironomidae 8 66 255 595 831 743 1004 1747Culicidae 8 28 21 198 431 255 423 678MolluscsPhysidae 8 0 71 0 180 135 116 251Planorbidae 7 0 0 69 180 95

4154 249

Lymnaeidae 6 0 9 0 0 5 9Sphaeriidae 8 0 37 0 0 37 37 37Arachnida Pisauridae 8 0 63 71 146 114 166 280

26

Tetragnatidae 4 15 61 0 51 60 67 127Water mites 6 14 34 0 19 60 7 67Hirudinae 10 0 0 35 60 40 55 95Total Individuals 2690 2909 3192 6473 6512 8774 15286

27

Table 4. Mean + 1 SE of macro-invertebrate metrics per site and season in the Enfranz River (2010-2011). H′ = Shannon-Wiener Diversity Index, HFBI = Hilsenhoff Family-level Biotic Index. Different letters within the same column show significant differences (P <0.05). SE = Standard error.

28

H′ HFBI % Ephem %

Trichop

%

Dipterans

E1 2.97±.03

3a

5.38±.14

a

23.59±.4

6a

12.59±2.

8a4.29±1.58a

E2 3.02±.03

1a

6.61±.11

b

11.92±.5

8b

3.60±0.5

b

13.24±1.44

b

E3 2.70±.02

6b

7.78±.03

c

3.84±.24

c

0.00±0.0

c

29.77±1.15

c

E4 2.39±.06

5c

8.19±.08

d

0.12±.12

d

0.00±0.0

c

25.57±2.16

c

Wet 2.80±.08

a

6.86±.44

a

9.84±3.3

9a

5.39±2.6

8a

17.59±4.40

a

Dry 2.74±.11

a

7.13±.39

b

9.89±3.4

3a

2.70±1.2

9b

18.85±3.44

a

Table 5. Pearson’s correlation coefficients between physico-chemical parameters and macro-invertebrate metrics. H′ = Shannon-Wiener Diversity Index, HFBI = Hilsenhoff Family-level Biotic Index.

Metrics Physico-chemical parameters

R P-value

Dissolved oxygen 0.824

0.00

H′

Temperature -0.203

0.452

TDS -0.672

0.004

Conductivity -0.636

0.008

pH -0.008

0.975

HFBI

Dissolved oxygen -0.944

0.000

Temperature 0.067

0.804

TDS 0.507

0.045

Conductivity 0.338

0.201

pH 0.294

0.269

Dissolved oxygen 0.94

0.000

29

8Temperature -

0.065

0.811

%Ephem

TDS -0.441

0.087

Conductivity -0.252

0.346

pH -0.295

0.267

Dissolved oxygen 0.814

0.000

Temperature -0.006

0.982

% Trichop

TDS -0.415

0.110

Conductivity -0.187

0.488

pH -0.384

0.143

Dissolved oxygen -0.868

0.000

Temperature -0.104

0.701

% Dipterans

TDS 0.378

0.149

Conductivity 0.27

0.309

30

1pH

0.284

0.287

31

Figure 1. Map of study area, Enfranz River with sampling

stations E1 (head of river), E2, E3, E4 (mouth of river) and

Lake Tana.

32