Diversity and Distribution of Aquatic Insects in Streams of the Mae ...

Hindawi Publishing Corporation Psyche Volume 2015, Article ID 912451, 7 pages http://dx.doi.org/10.1155/2015/912451

Research Article Diversity and Distribution of Aquatic Insects in Streams of the Mae Klong Watershed, Western Thailand Witwisitpong Maneechan and Taeng On Prommi Faculty of Liberal Arts and Science, Kasetsart University, Kamphaeng Saen Campus, Nakhon Pathom 73140, Thailand Correspondence should be addressed to Taeng On Prommi; [email protected] Received 27 July 2015; Revised 26 October 2015; Accepted 29 October 2015 Academic Editor: Nguya K. Maniania Copyright © 2015 W. Maneechan and T. O. Prommi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The distribution and diversity of aquatic insects and water quality variables were studied among three streams of the Mae Klong Watershed. In each stream, two sites were sampled. Aquatic insects and water quality variables were randomly sampled seven times in February, May, September, and December 2010 and in January, April, and May 2011. Overall, 11,153 individuals belonging to 64 families and nine orders were examined. Among the aquatic insects collected from the three streams, the order Trichoptera was most diverse in number of individuals, followed by Ephemeroptera, Hemiptera, Odonata, Coleoptera, Diptera, Plecoptera, Megaloptera, and Lepidoptera. The highest Shannon index of diversity of 2.934 and 3.2 was recorded in Huai Kayeng stream and the lowest was in Huai Pakkok stream (2.68 and 2.62). The high diversity of insect fauna in streams is an indication of larger microhabitat diversity and better water quality conditions prevailing in the streams. The evenness value was recorded as high in most sites. The high species diversity and evenness in almost all sites indicated good water quality.

1. Introduction In lotic environments, aquatic insects are important elements in the ecological dynamics [1], playing an important role in the cycle of materials and in trophic transfers [2–5]. The understanding of distribution patterns in communities is one of the main aims in ecology [6]. A multiplicity of factors regulates the occurrence and the distribution of aquatic insects, the most important being the current (velocity), temperature, altitude, season, total suspended solids, and vegetation [7]. Other factors which affect the occurrence of these benthic fauna include substrates, pH, dissolved oxygen, availability of food, turbidity, conductivity, and competition [8]. Changes of these environmental factors in streams can be used in biomonitoring and degraded aquatic environments [9, 10]. Thus, the nature of this distribution provides an initial insight into the types of ecological processes that regulate populations and assemblages. For example, the distribution of aquatic insects among stream habitats reflects, to some degree, the distribution of benthic resources (e.g., food, oxygen, and predators) and provides information about how communities might respond to changes in environmental

parameters such as increased sedimentation and changes in flow [11]. In this work, three streams in the Mae Klong Watershed were selected. These streams are used for domestic activities including drinking, cooking, bathing, and fisheries. It is therefore important to preserve these water resources and maintain the biotic integrity of these ecosystems. Such management requires basic knowledge such as the distribution of the aquatic communities among stream habitats. The aim of this study was to describe the composition of aquatic insects at different stations of the studied streams. The identification of species and their distribution patterns provide more information for monitoring and conserving these ecosystems.

2. Materials and Methods 2.1. Study Area. The Mae Klong Watershed is the most important watershed in western Thailand. The upstream watershed area consists of two main rivers, namely, Khwae Noi and Khwae Yai. The rivers run into the Khao Laem and Srinagarind Dam located in the upper region of Mae Klong

2

Psyche

Site

Stream Mae Klong River Boundary of Thailand 8 1

Number 1 2 3 4 5 6 7 8 9 10 11

Mae Klong Watershed

6

2 4

Boundary of Province

5

(km) 10 0 10 20 30

7 3

Site name Huai Pakkok 1 Huai Pakkok 2 Huai Kayeng 1 Huai Kayeng 2 Huai U long 1 Huai U long 2 Pilok Wire Wachiralongkorn Dam Mae Klong Dam Ratchaburi Samut Songkhram

N

9

10 11

Figure 1: Map of Mae Klong Watershed showing the sampling sites, namely, Huai Pakkok, PK1 = 1 and PK2 = 2; Huai Kayeng, KY1 = 3 and KY2 = 4; and Huai U Long, UL1 = 5 and UL2 = 6.

Watershed. The rivers joint in Kanchanaburi Province, which is considered downstream, flow through Ratchaburi Province and enter the Gulf of Thailand in Samut Songkhram Province. Six sampling sites in three streams (upper and lower in each stream) were chosen in this study. These streams were in the upstream section of Khwae Noi River before flowing into Khao Laem Dam (Figure 1). These three streams are, namely, Huai Pakkok, PK1 and PK2; Huai Kayeng, KY1 and KY2; and Huai U Long, UL1 and UL2. 2.2. Sampling and Identification of Aquatic Insects. To determine the distribution of aquatic insect taxa, six sampling sites in three streams (upper and lower in each stream) were chosen in this study. Seven samplings were performed in February, May, September, and December 2010 and in January, April, and May 2011. Aquatic insects were collected using aquatic D-frame aquatic kick net (30 × 30 cm frame,

250 𝜇m mesh). At each sampling site, a stretch of approximately 50 m was chosen for collection of samples from the three target habitats: riparian vegetation, leaf litter, and low gradient riffles and pools. The sampling time at each habitat was 3 min. In each sampling period, three replicate samples were collected at each station and placed in white trays for sorting. The content of each sample was transferred into properly labelled plastic containers, preserved in 80% ethanol, and taken back to the laboratory for analysis. In the laboratory, aquatic insects were sorted and identified to the family level using taxonomic keys [12–14]. All the sorted samples were kept in properly labelled vials containing 80% ethanol. 2.3. Environmental Variables. Three replicates of selected physicochemical water quality parameters were recorded directly at the sampling sites including pH, air temperature

Psyche

3 Diptera 5.81%

Trichoptera 33.98%

Lepidoptera 0.26% Megaloptera Coleoptera 0.30% 8.77%

Ephemeroptera 19.66% Odonata 11.30%

Plecoptera 4.61% Hemiptera 15.31%

Figure 2: Composition of aquatic insect orders of the three streams in the Mae Klong Watershed during a period of seven months.

(AT), water temperature (WT), dissolved oxygen (DO), total dissolved solid (TDS), and electrical conductivity (EC). Water samples from each collecting period were stored in polyethylene bottles (500 mL). Ammonia-nitrogen (NH3 -N), orthophosphate (PO4 3− ), nitrate-nitrogen (NO3 -N), sulfate (SO4 2− ), and turbidity (TUB) were determined in accordance with the standard method procedures (APHA et al., 1992) [15]. Alkalinity (ALK) was measured by titration. 2.4. Data Analyses. The aquatic insect abundance and taxonomic richness (𝑆) were estimated for each sample. Ecological indices, including the Shannon-Wiener diversity (𝐻󸀠 ), Simpson’s diversity index (𝐷), and Evenness (𝐸) indices, were determined for each sampling site [16]. A principle component analysis (PCA) was performed using environmental variables to determine the abiotic typology of sampling stations. This analysis was performed with the matrix consisting of 42 samples (6 stations × 7 campaigns) and 12 environmental variables. Analyses were conducted using PCORD.

3. Results and Discussion A total of 11,153 individuals of aquatic insects representing 64 families from 9 orders were collected and identified from three streams in February, May, September, and December 2010 and in January, April, and May 2011. Table 1 and Figure 2 show the overall composition and distribution of aquatic insect communities in the three streams. More aquatic insects were recorded in Huai Pakkok (PK1 and PK2) (2,054 and 2,726 individuals) than in Huai Kayeng (KY1 and KY2) (2,202 and 1,234 individuals) and Huai U Long (UL1 and UL2) (969 and 1,968 individuals). However, the total number of individuals recorded in the three streams was significantly different (One-Sample Test = 7.022, 𝑃 < 0.05). Trichoptera (3,790 individuals; 33.98% of total abundance) was the most dominant order with the highest number of individuals in the three streams. It was followed by Ephemeroptera

(2,193 individuals; 19.66% of total abundance), Hemiptera (1,707 individuals; 15.31% of total abundance), Odonata (1,260 individuals; 11.30% of total abundance), Coleoptera (978 individuals; 8.77% of total abundance), Diptera (648 individuals; 5.81% of total abundance), Plecoptera (514 individuals; 4.61% of total abundance), Megaloptera (34 individuals; 0.30% of total abundance), and Lepidoptera (29 individuals; 0.26% of total abundance) (Figure 2; Table 1). The aquatic insects of Huai Pakkok stream (PK1 and PK2) constituted 50 families and 46 families, while 49 families and 46 families were recorded in Huai Kayeng stream (KY1 and KY2). The aquatic insects recorded from Huai U Long stream (UL1 and UL2) were represented by 41 and 49 families, respectively (Table 1). Table 1 showed the species diversity indices. The highest Shannon index of diversity of 2.934 and 3.2 was recorded in Huai Kayeng stream (KY1 and KY2) and the lowest was in Huai Pakkok stream (HK1 and HK2) (2.68 and 2.62), indicating the presence of a higher diversity of aquatic insects in lotic ecosystems. The diversity of insects in aquatic ecosystems tends to increase with increased nutrients and these optimum environmental conditions favour their abundance in this habitat [17]. The high diversity of insect fauna in streams is an indication of larger microhabitat diversity and better water quality conditions prevailing in the streams (Table 2) [18]. Their abundance has been associated with the presence of high food quality, stable water flow, and stable substrata common in these habitats [17]. The evenness value in the present study was recorded as high in almost all the sites, indicating a relatively even distribution of taxa in the stream. The highest species diversity and evenness in almost all the sites are an indication of good water quality [18]. The high scores of diversity indices, such as those of the Shannon-Wiener index and Simpson’s index, indicate that clean or unpolluted rivers support more diverse taxa, thus making them useful for detecting organic pollution [19]. Higher numbers of taxa (family) collected from a habitat imply a richer community that usually lives in a healthier environment. Based on the scores, all streams in the Mae Klong Watershed supported relatively rich aquatic insect fauna, but their composition and abundance were significantly different between rivers. The differences in the physical habitat and hydrological conditions of streams could contribute to the observed dissimilarities in the aquatic insect compositions. This may be due to the multiplicity of microhabitats along with a combination of several other environmental factors that varied between streams [20]. Usually, similar richness of aquatic insects is recorded from streams with similar habitat structures, stream geomorphologies, and hydrological conditions [21]. By composition, Trichoptera and the Ephemeroptera dominated the study sites, accounting for almost 54% of all the total individuals that were sampled at the three streams. Heptageniidae (Ephemeroptera) and Hydropsychidae (Trichoptera) were found in all sampling sites because they are able to colonize waters with low oxygen concentration. Similar low numbers of Plecoptera in tropical waters have been reported [22, 23].

4

Psyche Table 1: The composition and total abundance of aquatic insect communities in Mae Klong Watershed.

Taxa Ephemeroptera Pothamanthidae Oligoneuriidae Caenidae Heptageniidae Leptophlebiidae Ephemerellidae Neoephemeridae Ephemeridae Baetidae Prosopistomatidae Odonata Lestidae Chlorocyphidae Protoneuridae Gomphidae Libellulidae Euphaeidae Corduliidae Aeshnidae Platycnemididae Coenagrionidae Calopterygidae Plecoptera Perlidae Peltoperlidae Nemouridae Hemiptera Aphelocheiridae Gerridae Veliidae Nepidae Hydrometridae Helotrephidae Naucoridae Pleidae Notonectidae Micronectidae Coleoptera Noteridae Hydrophilidae Hydraenidae Gyrinidae Elmidae Psephenidae Dytiscidae Scirtidae Megaloptera Corydalidae Lepidoptera Pyralidae

Abbv.

PK1

PK2

KY1

Potha Oligo Caeni Hepta Leptp Ephem Neoep Ephee Baeti Proso

1

1 2 1 266 218 97 1

1 3 91 58 17 6

118

75

26 8 61 33 26 14 31 1 1 39 20

Lesti Chlor Proto Gomph Libel Eupha Cordu Aeshn Platy Coena Calop

5 88 247 20 2 57

24 53 43 20 29 42 12 62 16

KY2

UL1

UL2

1

1

4 110 40 50 8 9 41 2

1 79 65 20

7 1 7 113 76 94

33

5 51

8 6 58 15 16 31 68

15 9 59 9 34 20

1 53 46

3 24 4

3 9 20 4 14 12 1 3 8 13

4 8 37 19 28 32 1 2 2

Perli Pelto Nemou

60 3 1

99 22

63

39

75 21

130 1

Aphel Gerri Velii Nepid Hydrm Helot Nauco Pleid Noton Micro

13 69 19 13 1 24 125 13 6

15 128 10 16 1 17 289 1 2

32 50 23 15

33 52 13 12

4 24 3 1

12 171 2

1 52

9 63 5

28 40 16 4 2 10 262

Noter Hydrp Hydra Gyrin Elmid Pseph Dytis Scirt

1 1 8 1 21 91 26 10 5

12 2 17 79 23

8 1 12 29 9

Coryd

6

6

10

Pyral

2

5

4

5

10

19

19 46 20 41

4 299 9 9

3 4 75 50 12 3

3

9

3

15

Psyche

5 Table 1: Continued.

Taxa Trichoptera Polycentropodidae Hydroptilidae Odontoceridae Leptoceridae Calamoceratidae Hydropsychidae Helicopsychidae Philopotamidae Lepidostomatidae Goeridae Diptera Athericidae Tipulidae Simuliidae Tabanidae Ceratopogonidae Stratiomyidae Culicidae Psychodidae Sciomyzidae Chironomidae Abundance Richness Evenness Shannon-Wiener diversity Simson’s diversity index

Abbv.

PK1

Polyc Hydrt Odont Lepto Calam Hydrs Helic Philo Lepid Goeri

2 1 1 6 6 727

Ather Tipul Simul Taban Cerat Strat Culic Psych Sciom Chiro

2 12 21 4 1 5

4

PK2

KY1

KY2

UL1

UL2

8 809 2 2

30 4 76 522 324 37 1 3

8 5 145 130 91 13 2

1 1 26 96

1 52 8 60 578

1 3 34 6 1

1 4 5 2 1

3 3 1

3

1

40 1,234 46 0.836 3.2 0.9441

1 2 969 41 0.712 2.643 0.8683

16 195

6

3 2

47 2,054 50 0.685 2.68 0.8461

55 2,726 46 0.684 2.62 0.8709

62 2,202 49 0.754 2.934 0.9031

2 5 1 5 15 23 5 7

50 1,968 49 0.712 2.771 0.8775

Table 2: Mean values (±SD) of environmental variables in each sampling site. Parameter/station AT WT pH DO EC TDS TUB ALK NH3 -N PO4 3− NO3 -N SO4 2−

PK1 31.35 ± 3.03 28.45 ± 3.02 8.05 ± 0.85 4.16 ± 2.08 74.08 ± 21.95 37.02 ± 10.56 3.33 ± 1.37 58.33 ± 22.32 0.18 ± 0.18 0.13 ± 0.06 1.35 ± 0.42 1.2 ± 6

PK2 33.73 ± 1.73 29.82 ± 2.67 8.15 ± 0.9 4.45 ± 1.98 104.1 ± 30.72 55.03 ± 13.5 3.57 ± 3.36 70 ± 20.40 0.14 ± 0.16 0.09 ± 0.06 1.57 ± 0.24 2 ± 10

KY1 31.87 ± 2.66 29.03 ± 2.17 8.15 ± 0.59 3.79 ± 1.63 275.38 ± 111.73 135.44 ± 55 9 ± 16.67 106.67 ± 35 0.24 ± 0.19 0.11 ± 0.06 1.52 ± 0.29 2.2 ± 11

PCA ordination for data of aquatic insects can be separated into two groups (Figure 3). The first group was located in the Huai Pakkok stream (PK1 and PK2) and the second group was located in the Huai Kayeng stream (KY1 and KY2) and the Huai U Long stream (UL1 and UL2). PCA analysis

KY2 30.04 ± 4.36 28.58 ± 2.57 7.99 ± 0.99 5.0 ± 1.67 325.49 ± 91.15 163.15 ± 43.27 12.43 ± 24.53 170.71 ± 33.76 0.22 ± 0.18 0.07 ± 0.05 1.87 ± 0.81 2.33 ± 14

UL1 30.57 ± 1.86 27.83 ± 1.15 8.43 ± 0.64 3.86 ± 0.65 119.68 ± 16.94 58.3 ± 15.22 5.0 ± 2.65 132 ± 24.98 0.19 ± 0.19 0.09 ± 0.08 1.47 ± 0.06 5 ± 15

UL2 29.97 ± 3.68 28.11 ± 2.72 8.19 ± 0.53 6.35 ± 2.51 158.62 ± 69.67 92.92 ± 33.39 5.17 ± 4.96 136.17 ± 24.33 0.18 ± 0.16 0.14 ± 0.22 1.45 ± 0.16 1.83 ± 11

revealed a correlation between the aquatic insect family and water quality (Figure 3). Aquatic insects in families Baetidae, Heptageniidae, Protoneuridae, Gerridae, Helotrephidae, Notonectidae, Nepidae, Leptoceridae, and Simuliidae were related to the concentration of orthophosphate and water

Psyche ALK TDS DO UL2

Axis 2

6

References

KY2

TUR EC

Calam Dytis Proso Ephee Lepid NO3-N Odont Micro Aphel Neoep Eupha Philo Gyrin Cerat Leptc Sciom Caeni Goeri Helic SO4 Ather Potha Elmid Gomph KY1 NH3-N Pyral Taban Scirt Noter Pseph Culic Hydrp Hydra Velii EphemAeshn Perli Hydrt Calop Hydrm Cordu Chlor Chiro Coryd PO4 Platy Oligo Polyc Strat Pelto Pleid Nauco Nepid Tipul Nemou Hepta Coena Simul Lesti Libel Baeti Noton Hydrs Psych Gerri Proto WT Helot Lepto PK1 pH

UL1

Axis 1

PK2

Figure 3: Biplot of the PCA ordination diagram for the data set between aquatic insect taxa, sampling sites, and environmental variables in the three streams. Abbreviations of taxa are shown in Table 1.

temperature. Aquatic insects in families Calopterygidae, Chlorocyphidae, Coenagrionidae, Lestidae, Platycnemididae, Peltoperlidae, Pleidae, Culicidae, and Hydropsychidae had relationships with pH of water. Water quality variables such as alkalinity, total dissolved solids, dissolved oxygen, turbidity, electrical conductivity, sulfate, nitratenitrogen, and ammonia-nitrogen affected aquatic insect families Neoephemeridae, Ephemeridae, Elmidae, Dytiscidae, Calamoceratidae, Helicopsychidae, and Philopotamidae.

4. Conclusions The results obtained in the present study indicate that, of the aquatic insects collected from the three streams, the order Trichoptera was most diverse in number of individuals, followed by Ephemeroptera, Hemiptera, Odonata, Coleoptera, Diptera, Plecoptera, Megaloptera, and Lepidoptera. The highest Shannon index of diversity was recorded in Huai Kayeng stream and the lowest was in Huai Pakkok stream. The evenness value was recorded as high in almost all sites. PCA analysis can expose the correlation between aquatic insect family and water quality with water temperature, orthophosphate alkalinity, total dissolved solids, dissolved oxygen, turbidity, electrical conductivity, sulfate, nitratenitrogen, and ammonia-nitrogen.

Conflict of Interests The authors declare that there is no conflict of interests regarding the publication of this paper.

Acknowledgment Financial support for this research was given through a scholarship of the Graduate School, Kasetsart University, year 2014, to Witwisitpong Maneechan.

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