Printer Friendly

Physical and chemical variables influencing riverine biota in a tropical river of northern Mindanao Philippines.


In a riverine system, the physico-chemical variables, in addition to hydrological conditions are the pivotal factors for macroinvertebrate and microalgae communities. The abundance of these organisms is determined by the resource availability, biotic interactions, and prevailing water quality. Water quality parameters play a major role in aquatic ecosystem health. Any change in water quality can lead to variations in compositions of plants and animal species. The most important water quality parameters that impact on aquatic ecosystems include temperature, salinity [1] acidity, Total Dissolved Solids (TDS), Dissolved oxygen (DO), Biological Oxygen Demand (BOD), pH [2] and nutrients [3]. Nutrient input into the stream due to agricultural land use and removal of riparian vegetation led to degraded water quality and increased conductivity. Differentiation of the physico-chemical parameters in the stream between agricultural and forest areas affected the benthic macroinvertebrates [4] and the microalgae [5].

The relationship between biotic indices and water quality parameters proved to be a useful tool for water resource managers to assess the ecosystem status when only physicochemical properties of water are known [6, 7]. The use of riverine biota is based on the assumption that disturbances alter biotic communities, changing their density or causing functional changes in the ecosystem [8]. Findings of many studies on river habitats suggested that specific physical and chemical variables influence the distribution of organisms [9]. Families of macroinvertebrates vary in their sensitivity to disturbances such as pollution [10]. Moreover, their relative abundance is used to infer the severity of contamination [9, 11]. The species of algae that develop in an area depend on different environmental factors [12] making them good indicators of water quality [13]. Among the algae, diatoms have the advantage of being easy to collect and store due to their hard frustules. They also respond rapidly to changes in environmental variables such as light, pH, temperature and nutrients [14].

This study explored the assemblage of macroinvertebrates and benthic microalgae in a tropical river as influenced by environmental variables. These organisms are sensitive to changes in physical and chemical conditions of river systems. Certain physical and chemical conditions that existed at the time of field sampling were measured to make inferences on the influence of these conditions to the focused organisms. Our research incorporated both biotic and abiotic components of the lotic ecosystem of Cagayan de Oro River, a major river system of Cagayan de Oro City, Mindanao, Philippines. The river has its headwaters and tributaries in the central part of the province of Bukidnon. It flows northward towards Cagayan de Oro City traversing three municipalities at the same time picking up tributaries along the way. The river empties into Macajalar Bay of Misamis Oriental, stretching about 90 kilometers. The river has a catchment area of approximately 152,000 hectares, eighty percent is located in the province of Bukidnon, and the rest is in the province of Lanao del Norte and Cagayan de Oro City. The river serves as a boundary between the provinces of Bukidnon and Lanao del Norte, and between Bukidnon and Cagayan de Oro City. The river basin is of economic, social, and leisure activities. It is the major source of water for domestic, industrial, agricultural, and hydroelectric power generation of a progressing urban community.


Field samplings were done twice in 2010-2011 in seventeen (17) sites, 9 from the main channel and 8 from tributaries of Cagayan de Oro River, Mindanao Philippines (Figure 1). Biotic sampling were in 3 replicates per site at a sampling reach of 150 meters. Water samples for physico-chemical parameters were collected in the middle portion of the river channel where mixing of water mostly occurred. The physical profile of the river including channel width, depth and flow velocity were measured. Determination of elevation and coordinates used Global Positioning System (Magellan brand).

Field sampling of macroinvertebrates used the "kick" net method (mesh size of 0.3 mm) with net "kicks" duration of three minutes per sampling site. The samples collected per net "kicks" were pooled, and obtained three composite field samples from each site. Each field sample was added with equal volume of 95% ethyl alcohol for preservation. In the laboratory, macroinvertebrates were sorted and concentrated into 100 mL A sub-sample of 10 mL per sampling site was counted and identified with the aid of a stereo-binocular dissecting microscope.

Benthic microalgae assemblage were collected by picking ten stones with biofilm (20 cm or greater) from the river channel. The biofilm of the stone's upper surface was designated with a 1.5-inch delimiter which was brushed using a firm-bristled toothbrush. The brushed surfaces per site were rinsed with 50 mL river water and fixed in 10% formalin. A volume of 0.101 mL of sub-sample of microalgae was the basis for the counting and identification. Counting used the nanoplankton counting chamber, and genus identification used the 400x Leica light microscope.

Determination of nutrients such as nitrate, phosphate, nitrite, and silicate used spectrophotometry. The total dissolved solids (TDS) and the hydrogen potential (pH) were measured in situ using Sartorius pH-TDS meter. Temperature, conductivity and dissolved oxygen (DO) was measured in situ using DO-TemperatureConductivity meter (JENWAY). Total suspended solids (TSS) were determined using gravimetric method.

Encoding of data and descriptive statistics were determined using Microsoft EXCEL. The influence of physical and chemical variables on the biota assemblage used the multivariate data analysis software (CANOCO 4.5).


Macroinvertebrate Assemblage:

A total of one thousand nine hundred sixty two (1,962) individuals of macroinvertebrates were counted and identified. The macroinvertebrate assemblages comprised a total of 63 families, 30 of which were commonly found in both main channel and tributaries. Fifteen (15) families were exclusively observed in the main channel, and 18 families in the tributaries. Many of these families belonged to the orders Ephemeroptera (13 families), Trichoptera (11 families), Coleoptera (8 families) and Diptera (7 families).

Table 1 shows the relative abundance of the macroinvertebrate families. In the main channel, the ephemeropteran Family Baeticidae and the dipteran larvae of Family Chironomidae were almost equally abundant, 22.46% and 22.94%, respectively. These were followed by another two ephemeropterans Family Baetidae (9.78%) and Family Trichorythidae (9.19%). In the tributaries, Family Chironomidae was the most abundant (26.54%) followed by two ephemeropterans of the Family Baeticidae (15.57%) and Family Baetidae (11.02%). Baetids were consistently present in all sampling sites, both in the main channel and in the tributaries. Chironomids were almost always present in all sampling sites. About 48% of the comprising families represented the more sensitive orders Ephemeroptera (mayflies), Plecoptera (stoneflies), and Trichoptera (caddis flies) indicating that less sensitive taxa are more diverse than the more sensitive ones. Among these three orders, Plecoptera were very few and observed only in the upstream tributaries where sedimentation was minimal.

The abundance of a number of insect taxa decreased as the proportion of fine sediments of the river bed increased [15, 6]. The abundance of Baetidae and Caenidae decreased from the headwaters to low lying areas of the river and replaced by Chironomidae. Plecopterans develop only in cold, clear springs and are sensitive to low oxygen concentration and organic pollution [17]. Land use, slope and substratum were the effective variables for the assemblage of macroinvertebrates [18].

Benthic Microalgae Assemblage:

Benthic microalgae from tributaries and the main channel of the river (Table 2) consisted of thirty (30) genera belonging to five groups namely; Chlorophyceae (6), Euglenophyceae (2), Xanthophyceae (1), Bacillariophyceae (19) and Cyanophyceae (2). The Bacillariophyceae (also known as diatoms) had the highest number of genera. The genera Coscinodiscus, Diadismes, Rhizosolenia, Ankistrodesmus, Cladophora, Tribonema and Spirulina were present only in the tributaries. While density of Navicula was highest in both main channel and tributaries, Oscillatoria was exclusively densest in the main channel as Fragilaria was to the tributaries.

Benthic microalgae stabilize substrata and serve as habitat for many other organisms [19, 20]. These are attached to the substrate, and most likely affected by physical, chemical and biological factors occurring in the stream reach [21]. The abundance of the diatom group in this study, is similar to other works [20, 22, 23, 24, 25]. Diatoms are large and diverse group distributed throughout the world in nearly all types of aquatic systems, and are one of the most important food resources in freshwaters [22].

Species of the genus Navicula are known to crawl towards the upper surface if they are covered by silt [19]. The high density of Oscillatoria may indicate nitrogen enrichment because blue-green algae have a competitive edge over other algae if bioavailable nitrogenous radicals (nitrate and ammonia) are in short supply. Cocconeis density increases in response to general impairment in streams and rivers as well as to sediment, nutrient and metals impairment while Surirella increase in response to sediment impairment [26].

Physical and Chemical variables that significantly explain biological assemblage:

There is a wide range of measurements of each physical and chemical variables (Table 3) in every sampling site. The mean values of the variables measured, except for Total Suspended Solids (TSS), were within the acceptable level of Philippine water quality standards. The main channel of the river had high TSS and appeared turbid. The high TSS impacts water quality and deposition of sediments in downstream water bodies and reservoirs. Its high TSS concentration was attributed to accumulation of sediments from eroded tributaries. These water quality evaluation based on physical and chemical methods are only instantaneous measurements [27], and therefore restraining the knowledge of water conditions only to the moment when the measurements were taken.

The health of the water environment could be assessed most importantly by the abundance, distribution and diversity of the benthic macroinvertebrates and microalgae. At the regional scale, nutrient-rich water bodies can collectively host high species richness [28]. Species of diatoms are characteristics of small streams and benthic invertebrates are associated with larger stream types. The trend was likely the consequence of multiple anthropogenic pressures that have affected lowland rivers [29]. In environmental degradation, biodiversity loss also occurs [7].

Redundancy Analysis (RDA) of environmental variables with macroinvertebrates showed that the variance in axis 1 was 46.6% and 61.3% in axis 2 (Table 4). These support a highly significant impact of environmental variables to macroinvertebrate assemblage. The first ordination axis significantly showed that pH (r=-0.46) had negative relationship with macroinvertebrates, whereas positive for nitrate (r=0.03). The associations between macroinvertebrates and abiotic conditions can be river basin-specific and are not automatically applicable across river basins in the tropics [30]. For instance, Ephemeroptera, Plecoptera and Trichoptera had very strong negative correlation with pH, BOD, phosphate and TSS but were positively correlated with DO [31], temperature and pH and between ammonia and nitrates [32]. Benthic macroinvertebrates in general have negative correlation with pH, dissolved oxygen, Biological Oxygen Demand, alkalinity, chloride and phosphate [33].

RDA of environmental variables and microalgae showed that the variance in axis 1 was 47.6% and 73.3% in axis 2 (Table 4) indicating a highly significant influence on microalgae. The first ordination axis showed pH (r=-0.872), TDS (r=-0.254) and nitrite (r=-0.267) had a significant negative relationship with benthic microalgae while BOD (r=0.453) and temperature (r=0.053) were positively correlated. Other environmental variables in the data set, were total suspended solids (TSS), dissolved oxygen (DO), phosphate, nitrate and silicate did not show significant influence. Studies in urban and rural streams showed that variables such as total nitrogen, electrical conductivity, DO, BOD and velocity have the greatest influence on the assemblage structure of microalgae [34]. In karst springs microalgae assemblage was correlated positively with dissolved oxygen concentration and negatively with specific conductivity and nitrate concentration [35].

Among the physical and chemical conditions considered in the data set for the ordination analysis, only nitrate and pH significantly described the assemblage of the families of macroinvertebrates (Figure 2). The families preferring higher pH were Perlodidae, Dipseudopsidae and Ephemerellidae (axis 1). While families that increase their abundances with increasing nitrate (axis 2) were Lymnaedae, Planorbidae, Viviparidae, Pilidae and Philopotamidae.

The ordination diagram in Figure 3 showed that environmental variables significantly explained benthic microalgae assemblage. Certain benthic microalgae genera either increased or decreased their abundance in response to different environmental variables. Redundancy analysis (RDA) of benthic microalgae genera with 10 environmental variables of interest showed two axes that are predictors of water quality. The first axis was associated with autochthonous inputs of the river as indicated by the arrows of BOD and pH in the ordination diagram. The second axis revealed the importance of nitrite, Total Dissolved Solids (TDS), and temperature as the influencing variables. These variables are related to geologic and allochthonous inputs. In this study, the genera that favoured high concentrations of BOD (axis 1) were at the right quadrant of the diagram whereas those adapted to poor water quality such as low pH (axis 1), high temperature, low nitrite concentrations and high concentration of TDS (axis 2) are at the left quadrant.

The percentage variance that explained the relationship between macroinvertebrates and the environmental variables (46.6% in axis 1 and 61.3% in axis 2) was not as high as that of the benthic microalgae (47.6% in axis 1 and 73.3% in axis 2). This indicated that the number of macroinvertebrate individuals counted was not as robust as the standard counts. Results showed that only pH and nitrate are good predictors of the macroinvertebrate assemblage. Among the physical and chemical variables measured, only pH, TDS, nitrite, BOD and temperature significantly explained the variation of benthic microalgae assemblage. Certain genera of microalgae can be used as an indicator of low pH and nitrite, high TDS, temperature and BOD of the river or as bioindicators of water quality. Worldwide, diatoms are being used in monitoring the quality of rivers, but in the Philippines this is still not widely used. Currently, freshwater biomonitoring and assessment is being increasingly implemented in Southeast Asian countries such as China [36]. In running waters, where changes in hydrology are rapid and difficult to estimate, biological monitoring has proven to be very useful due to its integrating nature [27].


This study proved that certain families of macroinvertebrates and genera of benthic microalgae responded to riverine environmental variables in a tropical river. The families of Perlodidae, Dipseudopsidae and Ephemerellidae preferred higher pH while Lymnaedae, Planorbidae, Viviparidae, Pilidae and Philopotamidae thrived in increasing nitrate concentration. Benthic microalgae genera such as Rhopalodia, Epithemia and Melosira favored high oxygen demand. Pinnularia, Gyrosigma and Gomphonema required low pH. Surirella, Cymbella, Achnanthes and Fragilaria thrived in low nitrite and low total dissolved solids concentration. Dissolved oxygen (DO), phosphate, nitrate and silicate did not influence the biota studied. However, biological assemblage can be specific for certain environmental variable and may provide clues of the prevailing physical and chemical conditions of the river.


Article history:

Received 3 October 2015

Accepted 10 October 2015

Published Online 13 November 2015


The authors would like to thank the Kinaadman Research Center (KRC), Xavier University-Ateneo de Cagayan for funding the project. Dr. Hilly Ann Roa-Quiaoit and Fr. Mars P. Tan, SJ the Ridge to Reef (R3) project leaders for trusting our team (XUFBioT) to do the biology component and some physico-chemical parameters. Dr. Ester L. Raagas for generating statistical outputs and guidance on interpretation of statistical results. Engr. Dexter S. Lo and the Engineering Resource Center (XU-ERC) for providing us with GIS map of the study area.


[1] Kefford, Ben, E., Fields, C. Clay and D. Nugegoda, 2007. Salinity tolerance of riverine macroinvertebrates from the southern Murray-Darling Basin. Marine and Freshwater Research, 58: 1019-1031.

[2] Salman, J.M., J. Hassan, A. Jawad, J. Nassar and F.M. Hassan, 2013. A study of phytoplankton communities and related environmental factors in Euphrates river (between two cities: Al _Musayyab and Hindiya) Iraq. Journal of Environmental Protection, 4: 1071-1079.

[3] Bouwman, A.F., M.F.P. Bierkens, J. Griffioen, M.M. Hefting, J.J. Middelburg, H. Middelkoop and C.P. Slomp. 2013. Nutrient dynamics, transfer and retention along aquatic continuum from land to ocean: towards integration of ecological and biogeochemical models. Biogeosciences, 10: 1-23.

[4] Getwongsa, P., C. Hanjavanit and N. Sangpradub, 2010. Impacts of agricultural land use on stream benthic macroinvertebrates in tributaries of the Mekong River, northeast Thailand. AES Bioflux, 2(2): 97-112.

[5] Laine, M., S. Morin, J. Tison-Rosebery, 2014. A multicompartment approach--Diatoms, Macrophytes, Benthic Macroinvertebrates and Fish--To assess the impact of toxic industrial releases on the small French River. PloS One, 9(7): e102358.

[6] Yazdian, H., N. Jaafarzadeh, and B. Zaharaie, 2014. Relationship between benthic macroinvertebrateindices and physico-chemical parameters of water: a tool for water resource managers. J Environ Health Sci. Eng. 12: 30.

[7] Nkwoji, J.A., J.K. Igbo, A.O. Adeleye, J.A. Obienu and M.J. Tony-Obiagwu, 2010. Implications of bioindicators in ecological health: study of a coastal lagoon, Lagos, Nigeria. Agric. Biol. J. N. Am., 1(4): 683-689.

[8] Begon, M., C.R. Townsend and J.L. Harper, 2006. ECOLOGY: From Individuals to Ecosystem. Oxford Publishing Garsington Road, Oxford OX4 2DQ, UK, 50-58.

[9] Chang, F., J.E. Lawrence, B. Touma and V.H. Resh, 2014. Tolerance values of benthic macroinvertebrates for stream biomonitoring: assessment of assumptions underlying scoring systems worldwide. Environmental Monitoring and Assessment, 186: 2135-2149.

[10] Kenny, M.A., A.E. Robert, F. Smith, and S.E. Gresens, 2009. Benthic macroinvertebrates as indicators of water quality. Terrestrial Arthropod Reviews, 2: 99-128.

[11] Wen, C.L., 2008. Do freshwater macroinvertebrates reflect water quality improvements following the removal of point source pollution from Spen Beck, West Yorkshire? Earth and Environment, 3: 369-406.

[12] Martin, G. and M. Fernandez, 2012. Diatoms as indicators of water quality and ecological status: sampling, analysis and some ecological remarks. Ecological Water Quality-Water Treatment and Reuse, Dr. Voudouris (Ed.), ISBN:978-953-51-0508-4, InTech, available from: /books/ecological-water-quality-water-treatment-and-reuse/diatoms-as-indicatorsof-water-quality-andecological-status -sampling-analysis-and-some-ecological-r.

[13] Salmoni, S.E., O. Rocha, V.L. Callegaro and E.A. Lobo, 2006. Epilithic diatoms as indicators of water quality in the Gravatai River, Rio Grande do Sul, Brazil. Hydrobiologia, 559: 233-246.

[14] Triest, L.P., P. Kaur, S. Heylen and N. De Pauw, 2001. Comparative monitoring of diatoms, macroinvertebrates and macrophytes in Woluwwe River (Brussels, Belgium). Aquatic Ecology, 35(2): 183194.

[15] Buendia, C., C.N. Gibbins, D. Vericat, J.A. Lopez-Tarazon and R.J. Batalla, 2011. Influence of naturally high fine sediment loads on aquatic insect larvae in a montane river. Scottish Geographical Journal, 127(4): 315-334.

[16] Wagenhoff, A., C.R. Townsend and C.D. Matthaei, 2012. Macroinvertebrate responses along broad stressor gradients of deposited fine sediment and dissolved nutrients: a stream mesocosm experiment. Journal of Applied Ecology, 49(4): 892-902.

[17] Rada, R.B. and S. Puljas, 2010. Do karst rivers "deserve" their own Biotic index? A ten year study on macrobenthos in Croatia. International Journal of Speleology, 39: 137-147.

[18] Misrah, A.S. and P. Nautiyal, 2013. Longitudinal distribution of macrobenthic invertebrate asesmblages in a central highlands river, the Tons (Central India). Proc.Nat. Sci. India. Sect. B. Biol., 83(1): 47-51.

[19] Stevenson, R.J. and L.L. Bahls, 1999. Periphyton protocols. Pp 6-1 to 6-22 in: M. T. Barbour, J. Gerritsen, & B. D. Snyder (Eds.), Rapid bioassessment protocols for use in wadeable streams and rivers: periphyton, benthic macroinvertebrates, and fish. Second edition. EPA 841-B-99-002 United States Environmental Protection Agency, Washington, DC.

[20] Weilhoefer, C.L. and Y. Pan, 2006. "Diatom Assemblages and their Associations with Environmental Variables in Oregon Coast Range Streams, USA" Hydrobiologia, 56(1): 207-219.

[21] Hobbs W.O., R.J. Telford, H.J.B. Birks, J.E. Saros, R.R.O. Hazewinkel, B.B. Perren, E. Saulnier-Talbot and A. P. Wolfe, 2010 Quantifying recent ecological changes in remote lakes of North America and Greenland using sediment diatom assemblages. PLoS ONE, 5: e10026.

[22] Potapova, M.G. and D.F. Charles, 2002. Benthic diatoms in USA Rivers: distribution along spatial and environmental gradients. Journal of Biogeography, 29: 167-187.

[23] Potapova, M.G. and D.F. Charles, 2003. Benthic diatoms in U.S. rivers in relation to conductivity and ionic composition. Freshwater Biology, 48: 1311-1328.

[24] Potapova, M.G., D.F. Charles, K.C. Ponader and D.M. Winter, 2004. Quantifying species indicator values for trophic diatom indices: a comparison of approaches. Hydrobiologia, 517: 25-41.

[25] Wu, J. and L. Kow. 2010. Alteration of phytoplankton assemblages caused by changes in water hardness in Feitsui Reservoir, Taiwan. Botanical Studies, 51: 521-529.

[26] Teply M. and L. Bahls, 2006 Diatom biocriteria for Montana streams: Middle Rockie Ecoregions. A monitoring project of the Montana Department of Environmental Quality, 26.

[27] Resende, P., P. Resende, M. Pardal, S. Almeida and U. Azeiteiro, 2010. Use of biological indicators to assess water quality in the Ul River (Portugal). Environmental Monitoring and Assessment, 170: 535-544.

[28] Wezel, A., B. Oertli, V. Rosset, F. Arthaud, B. Leroy, R. Smith, S. Ange'libert, G. Bornette, D. Vallod and J. Robin, 2014. Biodiversity patterns of nutrient-rich fish ponds and implications for conservation. Limnology, 15: 213-223.

[29] Dohet, A., L. Ector, H. Cauchie, and L. Hoffmann.2008. Identification of benthic invertebrate and diatom indicator taxa that distinguish different stream types as well as degraded from reference conditions in Luxemborg. Animal Biology, 58: 419-472.

[30] Everaert, G., J. De Neve, P. Boets, L. Dominguez-Granda, S.T. Mereta, A. Ambelu, T. Hoang, P.L. Goethals and O. Thas. 2014. Comparison of the abiotic preferences of macroinvertebrates in tropical river basins. PLoS One, 9(10): e108898.

[31] Paparisto, A., P. Lazo, S. Duka, O. Locknori, L. Valja. B. Plepa, E. Hamzaraj and A. Fierza. 2012. Environmental assessment of water quality of the Mati River (Abania) based on the use of physicochemical parameters and aquatic insects as bioindicators. Macedonian Journal of Ecology and Environment, XIV 1(2): 27-33.

[32] Menbohan, F.S., S. Tchakonte, A.A. Gideon, Z. Togouet, C.F. Bilong, and T. Njine. 2013. Water quality assessment using benthic macroinvertebrates in a periurban stream (Cameroon). The International Journal of Biotechnology, 2(5): 91-104.

[33] Sharma, S., S. Dubey, and R. Chaurasia. 2013. Benthic macroinvertebrates abundance and its correlation with physico-chemical parameters from Kunda Rive, Khargone (M.P.), India. International Journal of Advanced Research 1(2): 8-13.

[34] Moresco, C., and L. Rodrigues. 2014. Periphytic diatom as bioindicators in urban and rural streams. Acta Scientarium. Biological Sciences Maringa, 36(1): 67-78.

[35] Wojtal, A.Z. and L. Sobezyk. 2012. The influence of substrates and physicochemical factors on the composition of diatom assemblages in karst springs and their applicability in water-quality assessment. Hydrobiologia, 695: 97-108.

[36] Qin, C. J., Y. Zhou, Y. Cao, R. Zhang, M. Huges, and B. Wang. 2014. Quantitative tolerance values for common stream benthic macroinvertebrates in the Yangtze River Delta, eastern China. Environmental Monitoring and Assessment, 186: 5883-5895.

(1,2) Astrid L. Sinco, (1) Leolinda L. Saab, (1) Judy P. Sendaydiego, (1) Geraldine R. Mojica, (1) Giovanni G. Tampus and (1) Adora S. Rondez

(1) Biology Department, Xavier University, Cagayan de Oro City, Philippines

(2) Kinaadman Research Center, Xavier University, Cagayan de Oro City, Philippines

Corresponding Author: Astrid L., Biology Department, Xavier University, Cagayan de Oro City, Philippines

Tel: +639178136262;

Table 1: Macroinvertebrate assemblage and % relative abundance
in the main channel and tributaries of Cagayan de Oro River,

Taxon                     Relative Abundance (%)

                        Main Channel    Tributaries

Lymnaedae                   0.24             Physidae
-            0.45
Pilidae                     0.97             Planorbidae
0.12             Viviparidae
0.36             Veneroida
Sphaeriidae                 0.12             Plecoptera
Perlidae                    0.15           0.76
Perlodidae                    -            0.18
Leuctridae                    -            0.07
Calamoceratidae               -            0.15
Brachycentridae             0.12             Dipseudopsidae
2.05           2.64
Glossomatidae               0.27           0.27
Hydroptilidae               1.40           3.30
Hydropsichidae              1.72           1.78
Limnephilidae                 -            0.35
Philopotamidae              1.47           0.67
Psychomyiidae               0.41           0.95
Rhyacophilidae              0.15             Phryganeidae
0.15             Ephemeroptera
Baeticidae                  22.46          15.57
Baetidae                    9.78           11.02
Caenidae                    2.32           2.73
Ephemerellidae              0.95           2.82
Heptageniidae               1.14           1.89
Leptophlebiidae               -            1.60
Neoephemeridae              0.87           1.28
Oligoneuridae               1.45           0.07
Polymitarcyidae             0.12             Potamanthidae
-            0.45
Prossopistomatidae            -            0.30
Teloganeliidae                -            0.32
Trychorythidae              9.19           4.14

Family                    Relative Abundance (%)

                        Main Channel    Tributaries

Carabidae                   0.12             Dysticidae
-            0.26
Elmidae                     4.44           4.52
Gyrinidae                   0.12             Haliplidae
0.12           0.07
Noteridae                   0.60             Psephenidae
3.69           1.65
Ptilodactylidae               -            0.09
Dixidae                     0.90           2.15
Empididae                   0.12           0.09
Ceratopogonidae             0.24             Simuliidae
2.88           2.23
Tipulidae                   0.58           3.19
Chironomidae                22.94          26.54
Culiicidae                    -            0.27
Belostomatidae                -            0.07
Gerridae                    0.97           1.83
Nepidae                       -            0.07
Pleidae                     0.36             Veliidae
0.95           0.77
Crambidae                   0.15           0.41
Pyralidae                   0.27           0.51
Sialidae                      -            0.15
Corduliidae                   -            0.09
Libelluidae                 0.12             Calopterygidae
0.12           0.35
Protoneuridae                 -            0.18
Nematomorphan family          -            0.07
Oligochaete family          0.48           0.39
Turbellaria family          0.60           0.07
Unidentified pupa           1.24           0.18

Table 2: Mean cell density (cells/[in.sup.2]) of benthic
microalgae in Cagayan de Oro River.

Taxa                  Main Channel   Tributary

Ankistrodesmus             -           0.04
Cladophora                 -           0.001
Cosmarium                 0.17         0.05
Nostoc                    1.99         0.15
Pediastrum                             0.01
Scenedesmus               0.15         0.15
Euglena                   0.05         0.06
Phacus                    0.05         0.01
Tribonema                  -           0.02
Achnanthes                0.81         0.95
Amphora                   0.04         0.29
Cocconeis                 2.48         1.26
Coscinodiscus              -           0.001
Cyclotella                0.11         0.10
Cymbella                  1.95         3.19
Diadismes                  -           0.03
Epithemia                 0.35         0.49
Fragilaria                3.95         7.32
Gomphonema                5.25         5.14
Gyrosigma                 0.64         0.49
Melosira                  1.43         2.37
Navicula                 17.92         19.66
Nitzschia                 0.77         0.55
Pinnularia                1.98         1.33
Rhizosolenia               -           0.01
Rhopalodia                0.21         0.13
Surirella                 0.84         1.17
Synedra                   0.35         0.35
Oscillatoria             10.24         5.28
Spirulina                  -           0.01

Table 3: Physical and chemical variables measured
in the nine sites from the main channel and eight
sites from the tributaries of Cagayan de Oro River.

Indicators of River's         Standard       Main Channel
Physical and Chemical          Values         Mean value

Total suspended solids         50mg/L           67.10
Total dissolved solids       1000 mg/L          175.21
Dissolved oxygen               5 mg/L            6.83
Conductivity                   600ms            345.22
Orthophosphate            Class A: 0.1mg/L       0.15
Nitrate                        10mg/L            0.31
Nitrite                       0.1mg/L            0.02
Silicate                       1-100            89.30
pH                           6.5 - 8.5           8.12
Temperature                26[degrees]C -       27.19
Velocity (m/s)              30[degrees]C         0.13

Indicators of River's     Tributaries      Minimum &
Physical and Chemical     Mean value    Maximum values

Total suspended solids       26.45       3.00 - 339.04
Total dissolved solids      127.68      43.67 - 511.50
Dissolved oxygen             6.04         5.27 - 9.17
Conductivity                240.98      82.57 - 1103.83
Orthophosphate               0.11         0.03 - 0.65
Nitrate                      0.25         0.02 - 1.05
Nitrite                      0.02         0.01 - 0.03
Silicate                    104.78      23.80 - 226.67
pH                           8.23         7.15 - 8.89
Temperature                  25.77       21.54 - 29.61
Velocity (m/s)               0.18         0.06 - 0.35

Table 4: Summary statistics on the relationship between biological
and physico-chemical variables using redundancy analysis and Monte
Carlo permutation test. Only environmental variables selected in
the forward selection procedure are presented in the ordination
(** highly significant at a < 0.01).

Biological Variables                    Axis 1   Axis 2   F value

Families of macroinvertebrates
Correlation between                      0.96     0.70
macroinvertebrates and environmental
Percentage of variance of
macroinvertebrates explained             20.8     27.3
in axes 1 & 2
Percentage of variance of
macroinvertebrates-environment           46.6     61.3    1.69 **
Weighted correlation of environmental
variables with macroinvertebrates
Nitrate                                  0.03    -0.06
                                        -0.46     0.10

Genera of benthic microalgae
Correlation between benthic              0.91     0.87
microalgae and environmental             28.0     43.2
variables Percentage of variance of
benthic microalgae explained
in axes 1 & 2
Percentage of variance of benthic
microalgae-environment relation          47.6     73.3
Weighted correlation of environmental
variables with benthic microalgae
pH                                      -0.87     0.19    3.01 **
TDS                                     -0.25     0.60
BOD                                      0.45     0.37
Nitrite                                 -0.27    -0.28
Temperature                              0.05     0.61
COPYRIGHT 2015 American-Eurasian Network for Scientific Information
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2015 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Sinco, Astrid L.; Saab, Leolinda L.; Sendaydiego, Judy P.; Mojica, Geraldine R.; Tampus, Giovanni G.
Publication:Advances in Environmental Biology
Article Type:Report
Geographic Code:9PHIL
Date:Oct 1, 2015
Previous Article:Estimate soil carbon stock in mixed deciduous forest at the Sirindhorn International Environmental Park, Thailand.
Next Article:The use of biotic indices to assess streams water quality in the Mae Klong watershed, western Thailand.

Terms of use | Privacy policy | Copyright © 2019 Farlex, Inc. | Feedback | For webmasters