Habitat sustainability of white bellied heron at Adha Lake in relation to anthropogenic eutrophication of lake.
Karma Lhundup
Submitted in partial fulfillment of the requirements of B.Sc. in Forestry
15 June 2017
College of Natural Resources Royal University of Bhutan Lobesa: Punakha
Plagiarism Declaration Form
I declare that this is an original work and I have not committed, to my knowledge, any academic dishonesty or resorted to plagiarism in writing the dissertation. All the sources of information and assistance received during the course of this study are duly acknowledged.
Student’s Signature: Date: 15/07/2017
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Abstract Lentic water bodies are among the most threatened wetland habitat types, mainly due to anthropogenic disturbances, which have significant influence over the structure and function of aquatic ecosystems. The objectives of the study were to evaluate the relationship between macroinvertebrate and physicochemical parameters to assess the influence of surrounding landuse on lake ecosystem. The macroinvertebrates presence in the lake were used as an indicator to assess the effect of surrounding landuse, especially the impact of agriculture runoff into lake. The lake were categorized into major zones based on the surrounding landuse as agriculture zone, forest east zone, catchment zone and forest west zone. The sampling was carried out along the littoral zone of the lake. Beside macroinvertebrates, the physicochemical variable such as pH, salinity, conductivity, water temperature and TDS were attributed for both the seasons. The Chironomidae and Baetidae families were the dominant macroinvertebrates in the lake. The least families encountered were Acrididae, Aeshnidae, Tabanidae, Hydrophilidae, and Libellulidae during monsoon season, and Simuliidae and Culicidae for post monsoon season. There was no significant difference in Shannon Wiener’s Diversity for monsoon and post monsoon season. The pH, salinity, conductivity, TDS and water temperature have negative correlation with taxon diversity and richness; however, TDS, water temperature and pH have positive association with taxon evenness. There were significant differences in water pH for monsoon (8.7) and post monsoon (6.6) season including water temperature. The water quality at the lake were assessed as per the Nepal Lake Biotic Index tolerance score system of macroinvertebrates. The lake were heavily polluted with poor water quality. Bhutan still has a gap to be filled in the field of macroinvertebrates and wetlands, including the development of basic Lake biotic scoring system and identification guidelines for macroinvertebrates.
Keywords: Adha lake, conductivity, diversity, evenness, macroinvertebrate, pH, physicochemical parameter, richness, salinity, seasons, taxa, taxon, TDS, temperature.
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Acknowledgement I would like to thank the Royal University of Bhutan and College of Natural Resources for providing in-service degree program. I would like to sincerely thank Mr. Ugyen Dorji, Lecturer, for guiding and giving me quintessential supports from the very beginning of my dissertation workflow. I am ever grateful for the guidance and reaching his helping hand in every nook and corner of my research works. I also would like to acknowledge Mrs Thinley Choden, Officer In- charge, Agroforestry Technology Sub- Center, Darla, Chukha for the peer review and recommendation. I thank the BTFEC and RSPN for the fund. This study would not have been possible without the financial support. I am truly thankful to my comrade, Choney Dorji, Lha Tshering, Rinchen Dorji, Karma Choden and Sonam Yangden in-service forestry 6th cohort for their continuous support. In addition, I would like to express my deep appreciation to Mr. Sangay Tshewang and Mr. Wangchuck Dorji of Adha Range Office, Jigme Singye Wangchuck National Park for their indispensible support without which the research would be incomplete within the time frame. I would also like to extend my gratitude to the management of Ugyen Wangchuck Institute of Conservation and Environmental Research for the research approval on time and Watershed Management Division, Ministry of Agriculture and Forest, for the water testing kits. I would also like to affectionately acknowledge my daughter Quentsho Yoedbum Lhundup for bearing my absence for these two long years of my study. Finally, i would like to thank all the individuals, organisations and the local communities who were involved for the successful implementation of this study.
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Dedication
This piece of work is dedicated to the entire nature lovers, who are tirelessly dedicating their full time, beyond their boundaries in making the earth a very beautiful place to live.
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Abbreviation and Acronyms ANOVA Analyze of Variance df Degree of Freedom
EH Shannon Evenness EIA Environment Impact Assessment FADA Freshwater Animal Diversity Assessment GPS Global Positioning System H’ Shannon Wiener Diversity Index HKH Hindu Kush Himalaya IUCN International Union for Conservation of Nature and Nature resources JSWNP Jigme Singye Wangchuck National Park LWQC Lake Water Quality Class M Monsoon M.a.s.l Meters above sea level NLBI Nepal Lake Biotic Index NGO’s Non Governmental Organization P Probability pH Potential of Hydrogen PM Post monsoon PPM Parts Per Million Ppt Parts per thousand rs Spearman’s Correlation coefficient R² Regression coefficient RA Relative Abundance Sig Significant SPSS Statistical Package for Social Science
SR Species richness TDS Total Dissolved Salt Ugyen Wangchuck Institute for Conservation and Environment UWICER Research x̅ Mean μm Micrometer μS/cm Micro-Siemens per centimeter
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Contents Plagiarism Declaration Form ...... i Abstract …………………………………………………………………………………………...ii Acknowledgement ...... iii Dedication ...... iv Abbreviation and Acronyms ...... v List of figures ...... viii List of tables ...... ix Chapter One ...... 1 Introduction ...... 1 1.1 Background ...... 1 1.2 Problem Statement ...... 2 1.3 Objectives ...... 4 Chapter Two...... 5 Literature review ...... 5 2.1 Status of macroinvertebrate in the world and in Bhutan...... 5 2.2 Conservation significance of macroinvertebrates ...... 6 2.3 Habitats of macroinvertebrates ...... 7 2.4 Relationship between macroinvertebrates diversity and landuse types ...... 8 2.5 Physicochemical factors and macroinvertebrates ...... 9 2.6 Macroinvertebrates as a bio-indicator ...... 10 2.7 Threats of macroinvertebrates...... 11 2.8 Common source of contamination on water body and the impact ...... 12 2.9 Water quality assessment and Nepal Lake Biotic Index ...... 12 Chapter Three...... 14 Materials and method ...... 14 3.1 Study area...... 14 3.1.1 Major zone description ...... 15 3.1.2 Agriculture Zone ...... 15 3.1.3 Forest East Zone ...... 15 3.1.4 Catchment Zone ...... 15 3.1.5 Forest West Zone ...... 16 3.2 Survey Method ...... 16 3.2.1 Sampling of Macroinvertebrates ...... 16 3.2.2 Macroinvertebrate preservation and identification ...... 18 vi
3.2.3 Recording of physicochemical Variables...... 18 3.3 Data Analysis ...... 18 3.3.1 Comparing diversity of macroinvertebrates in Adha Lake between monsoon and post monsoon season; ...... 18 3.3.2 The relationship between macroinvertebrates and physicoparameter...... 19 3.3.3 Evaluate the status of macroinvertebrates diversity with every 15 meter increase in distance away from agriculture zone in Adha lake; ...... 19 3.3.4 Water quality assessment:...... 19 Chapter Four ...... 20 Result and Discussion ...... 20 4.1 Macroinvertebrates diversity in the study area ...... 20 4.2 Composition of macroinvertebrates in major zone for monsoon and post monsoon seasons. ……………………………………………………………………………………………...22 4.3 Macroinvertebrates diversity among monsoon and post monsoon seasons...... 25 4.4 Macroinvertebrate diversity among zone for monsoon and post monsoon seasons ...... 26 4.5 Relationship between macroinvertebrates and physicochemical parameters ...... 28 4.6 Physicochemical variables among monsoon and post monsoon season ...... 30 4.7 Relationship between macroinvertebrate diversity with the distance away from Agriculture Zone...... 31 4.8 Lake Water quality...... 33 4.9 Water quality of different seasons ...... 34 Chapter Five ...... 36 Conclusion ...... 36 Recommendation ...... 37 Reference ...... 38 Annexure I: Physicochemical parameters recording sheet in different habitat zone ...... 48 Annexure II: Recording data sheet for macroinvertebrates in the field ...... 48 Appendices I: Taxa with their respective tolerance score for calculating the NLBI, macroinvertebrates are ranked based on ten point scoring system with high scores indicating high sensitivity...... 49 Appendice II: Major zones and the families with relative abundance for monsoon and post monsoon seasons ………………………………………………………………………………………….53
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List of figures Figure 3.1: Map showing study area (Adha village) ...... 14 Figure 3.2: Sampling layout in Adha Lake (Study area) ...... 17 Figure 4.1 (a): Composite graph showing relative abundance of taxon with major zone in the study area for monsoon and post monsoon season ...... 23 Figure 4.1 (b): Cluster analysis of major zones using dendrogram based on relative abundance for monsoon and post monsoon season ...... 24 Figure 4.2: Shannon Wiener Diversity, Evenness and Richness of macroinvertebrates in monsoon and post monsoon seasons ...... 25 Figure 4.3: Shannon Wiener diversity indices within and between, zone of monsoon and post monsoon ...... 27 Figure 4.4: Linear regression test between taxa diversity and the distance away from Agriculture Zone for monsoon (a) and post monsoon (b) season ...... 32 Figure 4.5: Regression test between taxa evenness and the distance away from Agriculture Zone for monsoon(a) and post monsoon(b) season ...... 32 Figure 4.6: Regression test between taxa richness and the distance away from Agriculture zone for monsoon(a) and post monsoon(b) season ...... 33 Figure 4.7: Shannon Wiener Diversity index with Distance away from Agriculture Zone ...... 33
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List of tables Table 4.1: Order, families and relative abundance of macroinvertebrates for the whole study area ...... 21 Table 4.2: Mann-Whitney test for diversity indices among monsoon and post monsoon season 26 Table 4.3: Kruskal Wallis test for Shannon Wiener indices among major zone for monsoon and Post monsoon ...... 27 Table 4.4: Physicochemical parameters for catchment zone in monsoon and post monsoon season ...... 27 Table 4.5: Spearman’s correlation between diversity indices and physicoparameters...... 30 Table 4.6: Mann-Whitney test for physicoparameters between monsoon and post monsoon seasons...... 31 Table 4.7: Taxon biotic score, according to Nepal Lake Biotic Scoring system ...... 34 Table 4.8: Transformation scale of NLBI to LWQC, degree of pollution and colour code ...... 34 Table 4.9: Lake water quality for monsoon and post monsoon season ...... 35
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Chapter One Introduction 1.1 Background The White bellied heron is classified as critically endangered (IUCN, 2008), because it has an extremely small and rapidly declining population. The decline is projected to increase in the near future because of degradation of lowland forest and wetlands, and through direct exploitation and disturbance. The white-bellied heron (Ardea insignis Hume 1878) belongs to the order Ciconiiformes and family Ardeidae (Wildscreen Arkive, 2015). It is a very large bird with long neck that measures 160 cm (RSPN, 2011). Mostly, it has a dark grayish colour with contrasting white coloration on the throat, belly and vent, and white-streaked scapulars, fore-neck and upper breast (RSPN, 2011; Wildscreen Arkive, 2015). In Bhutan the bird is found along the Punatshangchu river basin and Adha lake in western part of the country and Mangduechu river basin in central Bhutan. According to Pradhan (1997), of the 60 individuals, 28 are found in Bhutan, 23 in Myanmar and 7-8 in India, making White bellied heron (WBH) even more critically endangered than previously thought. Due to change in landuse system around the world as well as in Bhutan, many critical habitats are under direct threat. Similarly, Adha lake which is one of the primary feeding ground, located in western part of Bhutan are in direct threat due to contamination from surrounding landuse. The lake was primary feeding ground for WBH during monsoon season until recently, when the endangered bird are rarely seen. Therefore, this study is going to evaluate the status of lake water quality through evaluating macroinvertebrates and physicochemical parameters. Fresh water lakes are important sensors of environmental changes such as acidification, eutrophication and climate change (Bian et al., 2006). Their sediments and macroinvertebrates are historical archives providing information about physical, chemical and biological changes in lake ecosystems and their catchments (Gurung, 2012). Macroinvertebrates are the animals without backbone and lives in freshwater bodies such as lake, streams, ponds, and rivers for some or entire life cycle but their life cycle or transformation either go complete (egg, larva, pupa and adult) or incomplete (eggs, nymph, and adult) (Voshell, 2002). They are often said to be used in paleoecological studies to assume past environmental conditions. These lakes are good indicators of changes in the environment including those related to climate change because of their sensitivity to anthropogenic activities (Bian et al., 2006).
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Although lake ecosystems are pristine, studies in the Europe and the Himalaya have shown that they are susceptible to changes in the environment, altering the physicochemical properties that affect the flora and fauna (Gurung, 2012). She also mentioned that, many lakes in Europe have suffered changes in their chemical composition due to enhanced weathering rates caused by rising air temperature, where the biological activity of lake are increased (Gurung, 2012). Many lakes are affected by deposition of pollutants such as nitrogen, for example in the European Alps (Thaler and Tait, 2014). The macroinvertebrates dwelling in the lake are excellent indicators of human impacts, especially contamination (Sharma et al., 2010). They have narrow ecological requirements and are very useful as biological indicators in determining the characteristics of aquatic environments (Fernandez-Diaz and Benetti, 2008; Benetti and Garrido., 2010). This is because they are found in all aquatic habitats, have generally limited mobility, are quite easy to collect by well established sampling techniques (Barbour et al., 1999). Macroinvertebrate in lentic (flow less) water system plays very crucial role in maintaining the health and freshness of the lake. They are the key decomposer in the container of the lake where high deposition take place and have significant ecological role in aquatic food chain and ecosystem (Stubbington et al., 2009). Most macroinvertebrates are important components of stream ecosystems. They graze periphyton (aquatic plants), assist in the breakdown of organic matter and cycling of nutrients, acts as intermediate predator and, in turn, become food for predators (Sharma et al., 2010).
1.2 Problem Statement According to Wangchuk (2016), fishes mainly composed their primary diet and heron being non- swimmer it feeds along the shallow water. Bhutan mostly being composed of rugged terrain, river flows with relatively high turbidity. Due to seasonal flooding during monsoon, their fooding ground are regularly been destroyed. The problem of not having large stretch of still and clean water is bigger concern. However, in western part of its habitat, adha lake have been the solution until recently when heron are rarely seen. Adha lake has been suffering from immense contamination and eutrophication from surround ding landuse till date, which makes water more dirty and unclear for WHB to fish.
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Fresh water lakes are among the most threatened habitat types in the world (Kasangaki et al., 2008), illustrated most expressively in a 50% decline in the Living Planet Index for freshwater ecosystems between 1970 and 2000 (Millennium Ecosystem Assessment, 2005). Anthropogenic land disturbance continues to increase worldwide. The aquatic scientists and the conservationist are faced with the challenge of determining how human activities influence the structure and function of aquatic ecosystems and the potential for restoration of impacted waters (Sutherland et al., 2002). Key to the above problems is to understanding the functional links between large scale land use, changes in the physicochemical conditions and biotic assemblages of rivers. Adha Lake is a typical low altitude lake (1300 m.a.s.l) harboring significant wild animals of conservation importance beside socio-cultural values. It is located in the sub-Himalayas of Bhutan under Jigme Singye Wangchuck National Park (JSWNP) administration. This study will be the first limnological investigation ever conducted on it. Adha Lake (90° 6' 32.49"E, 27°17' 32.92"N) has the following morphometric properties: maximum length 216 meter, maximum width 99.3 meter, with surface area of 2.38 hectare (extracted from Google Earth pro). Four major landuse types surround the lake, the agriculture paddy terrace towards north of lake, forest tree cover on east and west side of lake, and catchment area feeding the lake from southeast direction. With increasing age, most lakes naturally undergo a gradual eutrophication with a concomitant increase in productivity. In large lakes, this is a slow process, but it can be accelerated by pollution (Robertson, 2004). Similarly, Adha lake is no difference, during monsoon and agriculture cultivation season, the nutrient rich water overflows from paddy terrace into the lake. This is worrisome if it is not intervened. This may result to enrichment and eutrophication of lake and might change its ecological significance in long run. This process is accelerated with the contamination and degradation of lake catchment area by the free cattle grazing near the lake. This action if not intervened, will have significant impact on the ecosystem as a whole, especially the critically endangered white bellied heron and rare keystone species like mountain hawk inhabiting the lake for easy food (JSWNP, 2014). The lake also function as a water hole for other mammals like samber deer, guar, wild pig during their migratory period, since the area fall under semi arid region of chirpine forest and cool broad leave forest of Jigme Singye Wangchuck National Park.
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Beside this, in Bhutan macroinvertebrate studies and conservation program are concentrated more towards lotic water body by research institution, national parks, nongovernmental organization (NGO’s) and individual researcher. Less interest have been shown in conserving of lentic water bodies until date. These drawbacks have also pondered in losing many fresh water lakes especially the low altitude lake, which had social-economic function in terms of drinking, irrigation and socio-cultural values for local communities (National Environment Commission, 2001). Therefore, it is very crucial and timely to conserve the few remaining low altitude lake like Adha, which are having significant conservation importance. This study is going to evaluate the environment impact (EIA) of lake for monsoon and post monsoon season through bio- monitoring of macroinvertebrates present and by correlating with physicochemical parameter in relation to distance from paddy field. This study has potential to inform the relevant agencies on the importance to intervene fresh water lake ecosystem and aquatic animals for sustainable conservation and management. This research will be of immense help for Jigme Singye Wangchuck National Park management in formulating conservation policy and action plan that have been missing until now.
1.3 Objectives Compare diversity of macroinvertebrates between monsoon and post monsoon seasons. Study the correlation between macroinvertebrates and physicochemical parameter. Evaluate the influence of agriculture zone to the macroinvertebrates diversity in Adha lake. To assess the water quality through bio-indicator.
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Chapter Two Literature review Freshwater pollution increase water shortage problem for daily use. Freshwater such as lake, river and streams are open to anthropogenic pollution (Chatzinikolaou and Lazaridou, 2007). Agriculture, industrialization and construction along the water bodies can pollute and change its ecosystem (Dudgeon, 2000). The types of the creatures that can survive, such as aquatic macroinvertebrate reflect the quality of water (Oller and Goitia, 2005). In Bhutan, lake ecology is weakly explored and due to their strong, socio-cultural and religious beliefs associated with it. Since from the ancestral, the people of Bhutan have been worshiping and restricting any direct interference to the lake. Due to this tradition, many wild creatures found their safe habitat near and within the lake for their daily survival. However, the lake at the current study site is under serious threats due to contamination from agriculture field runoff and the other surface runoff draining into the lake. Pollution of lake and river by domestic waste and agriculture discharge is growing problems in many countries. The pollution degrades the fresh water resources including the biological productivity not only of lake and of river themselves but also of the costal water, they drain (Chatzinikolaou and Lazaridou, 2007). Indeed, some nongovernment organization maintain that with increasing pollution together with growing demand for water, the world fresh water resources will be fully utilized within the next 50 to 60 years (Oller and Goitia, 2005).
2.1 Status of macroinvertebrate in the world and in Bhutan According to Allen et al. (2010), the global fresh water diversity is continuous to be relatively high compared to the terrestrial and marine ecosystem. The International Union for Conservation of Nature (IUCN) has estimated 126,000 described species that rely on freshwater habitats, including fishes, molluscs, reptiles, insects, plants and mammals (IUCN, 2010). According to the checklist data base recorded by the Freshwater Animal Diversity Assessment (FADA), there are about 3,141 named species of Ephemeroptera (Barber et al., 2010), 2000 species of Plecoptera (Skeel, 2009), 14,000 species of described Trichopetra, 158,000 species of Diptera known worldwide with approximately 6,500 Odonata till 2009 as increase of 500 numbers from 2001 to 2009 (Allen et al., 2010).
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In Bhutan few studies have been carried out on lotic water bodies by authors like Mitra (2006); Maclicky and Moog (2008); Wangyel et al. (2011); Giri and Singh (2013); Wangchuk and Eby (2013); Dorji (2014); Dorji et al. (2014); Gurung and Dorji (2014), however, no single study on lentic water bodies has been carried out so far. Moreover, most of the studies on lotic macroinvertebrates are concentrated in western part of the country focusing more in the field of assessing water quality through evaluating biological indicator and correlation between physicoparameter and macroinvertebrates. According to Moog et al. (2008), during the three week trip in Bhutan, they had recorded 166 species of macroinvertebrates’ diversity. The diversity assessment of macroinvertebrates in Teobrongchuu stream recorded 20 species of macroinvertebrates belonging to 13 different orders (Wangyel et al., 2011). There are 51 taxa comprising of 51 families, recorded from the four streams in Punakha dzongkhag namely Dorokna, Jinchulum, Teobrongchuu and Metsina (Dorji, 2014). Bhutan has 17 sub families, 24 genera and 31 species of Odonata recorded in the country. These numbers includes the study of Odonata in the eastern Bhutan that added four new discoveries (Mitra, 2006). The study on biomonitoring of water quality through benthic macroinvertebrates of river Singyechu, Pasakha under Chukha dzongkhag recorded 7order and 33 families (Giri and Sigh, 2012). Though many research has been carried out with recommendation to protect and conserve the fresh water for sustainable utilization in Bhutan, least have been done to incorporate the recommendation and finding for conservation and management. Therefore assessing the macroinvertebrates in Adha lake will be first of its kind and it is necessary and significant for recording the checklist of macroinvertebrates further. This information generated will help relevant agencies working for the fresh water to plan and implement their programs.
2.2 Conservation significance of macroinvertebrates Macroinvertebrates have been remained as a key indicator of changes in the physical, biological and chemical conditions of aquatic ecosystems (Fernandez-Diaz and Benetti, 2008). They have significant key role in many major functional groups, as a grazers, shredders, gatherers, filterers, and predators, in aquatic ecosystem processes. Many stream-dwelling insects exploit the physical characteristics of streams to obtain their foods. As consumers at intermediate trophic levels,
6 macroinvertebrates are influenced by both bottom-up and top-down forces in streams and serve as the channel by which these process are propagated (Wallace and Webster, 1996). Different groups of macroinvertebrates are excellent indicators of human impacts, especially contamination (Sharma et al., 2010). Most of them have quite narrow ecological requirements and are very useful as biological indicators in determining the characteristics of aquatic environments (Fernandez-Diaz and Benetti, 2008; Benetti and Garrido, 2010). It helps to identify the segments of a polluted river where self-purification of organic inputs is under process (Chatzinikolaou and Lazaridou, 2007). They play an important role in maintaining healthy ecosystems and they are useful indicators of water quality and the overall health of aquatic ecosystems (Giri and Singh, 2013).
2.3 Habitats of macroinvertebrates Macroinvertebrates lives in many different places in a water body. They live on the water’s surface, in the sediment, on submerged rocks, logs, and leaf litter (Richards and Host, 1994). Each type of habitat provides spaces within which macroinvertebrates can live. The most important feature around a water body is surrounding vegetation. Aquatic plants, particularly rushes and sedges, provide a space on which macroinvertebrates can live (Pedersen and Friberg, 2007). In addition, they balance the water flow, light availability and temperature around them (Nakano et al., 2008). Logs, branches, bark and leaves that fall into the water provide habitat for aquatic organisms. Leaf litter forms an important part of a food web for macroinvertebrates, which feed, on this material, or on the bacteria and fungi that cause it to decay (Dudgeon and Wu, 1999). In lotic water bodies such as the upland streams, the bed consists of large rocks and stones where macroinvertebrates are adapted to fast flowing water by having powerful gripping legs and, in lentic water bodies such as lowland rivers, lake or wetlands, the bed are sandy and muddy with increased light penetration (Johnson et al., 2004). In both lotic and lentic water bodies, predators are said to be found where their preferred preys are located. According to Weatherhead and James (2001), the collectors (feeds on aquatic residual remains) and scrapers (feed on residual remains on rocks, logs) dominate the macroinvertebrate community in all aquatic system. Collectors burrow into the sediment or filter their food directly from the water column. Grazers were found on rocks, snags and woody debris or aquatic plants.
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Freshwater macroinvertebrates are divided into various groups based on feeding habits, called functional feeding groups. The classification of a functional feeding group is based on food preference and how an organism eats (Richards and Host, 1994). For example, predators feed by either eating prey whole or by piercing into their prey. Collectors feed on small bits of organic matter by either gathering deposits from the substrate or by filtering particles out of flowing water. In some instances there is more than one functional feeding group listed for a certain family. This means that not all genera in this family have the same food preferences (Weatherhead and James, 2001). Most insects that land on water are trapped by the water surface tension, and tiny ones can even drown inside a water droplet, unable to break out of the bubble surface. Aquatic insects cope by having waterproofed skin so large amounts of freshwater do not diffuse into the body. Many are covered with a water-repellent waxy layer (Johnson et al., 2004). They also usually have hairy or waxy legs, which repel water so they are not trapped by the water surface tension. Many of these insects are strong swimmers or crawlers as nymphs or larvae and as adults can also fly, although the degree to which they use their ability to fly varies quite a bit. Insects either go through complete metamorphosis or incomplete metamorphosis but most insects go through complete metamorphosis (Erica, 2011).
2.4 Relationship between macroinvertebrates diversity and landuse types Macroinvertebrate diversity depends on particular physical and chemical environmental conditions (temperature, salinity, turbidity, metal concentrations, and nutrient levels) (Metcalfe, 1989; Freund, 2007). This diversity is influenced by the land use within the catchment. In lakes, the habitat use of macroinvertebrates is strongly influenced by vegetation characteristics, depth and complexity of the substrate (Efiter et al., 2001). Beside these, substratum composition, complexity and particle size also affects the distribution, structure and composition of macroinvertebrate communities. The surface runoff due to degradation of vegetation affects hydrological discharge regimes in the lake. This increases temperature, sedimentation and affects the existence of benthic rheophilic and their interstitial habitats (Sutherland et al., 2002). These include insect groups like the Ephemeroptera, Plecoptera, and Trichoptera. Macroinvertebrates community is also affected by change in the water quality, due to pollution entering into the lake. Although the abundance of certain species are said to be
8 increasing in low quality water, the diversity and species richness are said to be decreasing (Stubbington et al., 2009). A common result of deforestation and other anthropic activities in aquatic ecosystems is a reduction in the number of taxa that are less tolerant to modifications in the water quality. It leads to increase in the number of pollution-tolerant taxa, often resulting in the local extinction of native species (Smith and Lamp, 2008). In a study carried out in southern Brazil, Hepp and Santos (2009) evaluated the impact of different land uses on local benthic communities and mentioned that there were significant differences in organism density and taxonomic richness in the streams in urbanized and pasture areas.
2.5 Physicochemical factors and macroinvertebrates Macroinvertebrates are driven by the type and conditions of physicochemical parameters present in that locality. Different macroinvertebrates have different tolerances to pollution. Highly sensitive macroinvertebrates can only live in water with high water quality where as tolerant and very tolerant macroinvertebrates can withstand lower water quality. A healthy waterway has higher biodiversity (Erica, 2011). Their survival is related to the water quality and environmental variables as they live in the water for all or part of their lives. Macroinvertebrates are sensitive to different chemical and physical conditions. If there is a change in the water quality, perhaps because of a pollutant entering the water, or a change in the flow downstream of a dam, then the macroinvertebrate community will also change (Freund, 2007). The study by Yap et al. (2006) on Oligochateas class found out positive correlation with conductivity, nitrate, ammonia and dissolved concentrations of copper and zinc. They are negatively correlated with the pH and dissolved oxygen, which mean that these families are pollution tolerant. While an appropriate concentration of salts is vital for aquatic plants and animals, salinity that is beyond the normal range for any species of organism will cause stress or even death to that organism. The crustaceans family are highly tolerant to rising salinity than other aquatic macroinvertebrates (Le and Haffner, 2000). Similarly, temperature affects the metabolic rate of aquatic animals, timing and success of reproduction, and the sensitivity of organisms to toxins, parasites and disease. At the lowest temperature, the amount of dissolve oxygen is said to be high and vice versa (Weatherhead and James, 2001). Temperature being one of the most important ecological factors is intimately related to latitude, altitude, season, and in spring fed or lake fed streams to the distance from the
9 source. The benthic macroinvertebrates have evolved to live within a specific temperature range, which limits their distribution and affects the community structure their emergence patterns, growth rates, metabolism, reproduction and body size (Benetti and Garrido, 2010).
2.6 Macroinvertebrates as a bio-indicator Macroinvertebrates have characteristics that are related to water bodies’ alteration and due to their high sensitiveness to changes in water environment, they are appropriate for the determination of water qualities. Generally, water quality can be categorized based on sensitiveness of macroinvertebrates to pollution: species such as stonefly, caddisfly, water penny, dobsonflies, mayflies all indicates that the water is in very good to excellent conditions. Whereas water consisting of macroinvertebrates such as crayfish, sow bugs, mussels, dragonfly larvae, crane fly larvae, damselfly larvae, scuds and whirligig beetles indicates the water of intermediate quality. Midge fly, leeches, snails and black fly larvae presence in river indicates water of polluted quality (Clements, 1994). The aquatic life spans of macroinvertebrates range from several weeks to several years. This long life span provides an indication of stream quality over a period. As long as water quality is good enough, macroinvertebrates can be found in any aquatic habitat (Maralidharan et al., 2010). Their life initially begins in the water and transform as terrestrial insects upon maturity (Mitchell et al., 1996; Voshell, 2002; Edelstein, 2014). Depending on the water characteristics such as depth, width, chemical contents and velocity, diverse macroinvertebrates will be seen inhabiting the water bodies accordingly to their tolerance level (Kantzaris et al., 2002). The invertebrates, which live on, in, or near the substratum of running water, include representatives of almost every taxonomical group that occurs in freshwater. There are indeed remarkably few freshwater groups, which are not regularly represented in rivers. In contrast, there are several groups that occur only in running water, and many that reach their maximum development and diversity there. This is undoubted by the permanence of streams as compared with lakes and ponds. Many river systems have been in continuous existence from far back into the geological time, whereas lakes persist for relatively short periods and give little opportunity for the development of purely lacustrine fauna (Robertson, 2004).
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2.7 Threats of macroinvertebrates Macroinvertebrates require favorable various physicochemical conditions to survive as well as specific micro and meso habitat features to build sustainable populations (Erica, 2011). The constant constructions and contamination from agriculture runoff throughout the world have caused much interference in the macroinvertebrates due to change in water pH and siltation (Chatzinikolaou and Lazaridou, 2007). Beside contamination from anthropogenic activities, the vegetation along the water bodies are said to be influencing the macroinvertebrate population. For example, the functional feeding group composition of macroinvertebrate assemblages shift from the shredder-dominated headwaters via scraper dominated middle reaches to the collector- dominated lower reaches of large rivers (Dorji, 2014). Not only the vegetation within the stream channels but also the riparian vegetation also greatly affects the structure and function of macroinvertebrates (Fernandez-Diaz and Benetti, 2008). It has been recorded that streams with forests in their riparian corridors are about two and half times wider than streams whose riparian zones have been deforested and have more benthic surface area in the form of inorganic (sand, gravel, cobble) and organic (tree roots, leaf litter, wood, etc.) substrates for macroinvertebrate colonization. The streamside forests have been shown to affect the food quality and quantity for macroinvertebrates directly through inputs of particulate food (leaf litter, soils, wood, etc.). Which indirectly affects the structure and productivity of microbial (algae, bacteria) food web through shading and modifying the levels of dissolved organic carbon and nutrients (Giri and Singh, 2013). Climate change is said to be one of the natural factors that pose threats to its population. Changes in the natural hydrology of streams and rivers have contributed to the decline of aquatic macroinvertebrates (Erica, 2011). Droughts are very common features in temporary lotic systems. Barbour et al. (1999) defined these systems as natural watercourses that experience recurrent dry phases of variable duration. The biota in these systems is exposed to a suite of adverse environmental conditions and alterations in the biotic interactions during the dry period. Drought conditions frequently lead to intolerable thermal stress and/or low dissolved oxygen levels for macroinvertebrates before the entire stream dries up (Mitra, 2006). When the disturbance is strong enough, habitats can be restricted to isolated pools where interactions can be enhanced. Consequently, species richness decreases before the total drying up of the channel (Robertson, 2004). The constant mudslide, sewerage disposal into rivers, natural disaster
11 management activities alongside riverbanks are some of the frequent factors that configure the demographic status of the macroinvertebrates (Kantzaris et al., 2002).
2.8 Common source of contamination on water body and the impact Pollution from agricultural areas and non-point sources is largely uncontrolled, and domestic wastewater treatment is limited (Dudgeon, 2000). These disturbances produce alterations in the chemical composition of water and in the structure of the communities of organisms living in that environment (Oller and Goitia, 2005). Nutrient enrichment of streams, rivers, lakes and estuaries can cause reduction of plant and animal diversity, development of toxic algal blooms, lowered oxygen concentrations, fish kills, loss of aquatic plant communities and coral reefs (Carpenter et al., 1998). Aquatic fauna are impacted by nutrient enrichment primarily because of changes in primary production and in the chemistry of water column and sediment. These changes potentially lead to reduced diversity and abundance, shifts in community composition, physiological changes, and mass mortality (Bernharelt and Likans, 2004). Sediment, nutrients and pesticides are the most common pollutants from agriculture. Sedimentation represents the largest volume of aquatic contaminant (Gurung, 2012). A freshwater benthic community may consist of the immature stages of many flies, beetles (adults and immature), mayflies, caddisflies, stoneflies, dragonflies, aquatic worms, snails, leeches and numerous other organisms which makes them fragile and vulnerable to environmental changes, especially those related to disturbances of anthropogenic origin, which often imply irreversible degradation of their biota (Beasley and Kneale, 2003; Dahl, 2004). As these animals live in the water for all or part of their lives, good water quality is an indispensible prerequisite for their survivals.
2.9 Water quality assessment and Nepal Lake Biotic Index The health and well-being of the human race is closely tied up with the quality of water used. Due to change in landuse and non point source pollution, the fresh water ecosystem have been rampantly deteriorating. Today, countries with vast water resources are also threatened with deteriorating water quality (Sharma et al., 2005). The ecologist around the world have been constantly developing different biotic index to assess the quality of fresh water.
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One such method developed to assess water quality is Hindu Kush Himalayan biotic scoring system (HKHbios-Hindu Kush-Himalayan biotic score), which is the new ranking and weighting system of macroinvertebrates in himalayan region, developed by Ofenböck et al. (2010), to assess the ecological status of lotic water bodies . It help to determines the quality of water and reflect not only organic pollution but also environmental degradation like river damming, industrial effect and effects of river engineering (Sharma et al., 2010). However, there is no specific lake biotic index for assessing lentic water bodies for Bhutan other than to use Nepal Lake Biotic Index (NLBI), which have similar agroecological zone with equal altitude. The only limnological study carried out in Bhutan by UWICE for assessing ecological and social economic significant of high altitude wetland (Wangdi and Sherub, 2013) does not reflect on biotic index used in assessing lentic water quality. According to Shah et al. (2011), for development of NLBI, Benthic samples was collected from reference and impaired lakes during year 2006 and 2009 from two ecological zones; Lowland (500 m.a.s.l) and Mid-Hills (2,999 m.a.s.l). They used a tolerance score based on a ten- point scoring system ranging from very pollution sensitive to very pollution tolerant taxa to calculate the NLBI. In reference to the transformation scale, the calculated NLBI describes the lake water quality as high, good, fair, poor and bad. Fifty-five lakes (both natural and man- made) and one reservoir were selected with size ranging from 2 hectare to 443 hectare. The classification criteria were based on point source pollution, lake morphology, water abstraction, flow regulation, riparian zone vegetation, fisheries, and recreational use.
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Chapter Three Materials and method
3.1 Study area Adha Lake (90° 6' 32.49"E and 27°17' 32.92"N) is a low altitude lake (1300 m.a.s.l) located in the Sub-Himalayas of Bhutan. The lake falls under Wangdue District, Adha block and under the conservation jurisdiction of JSWNP (figure 3.1). The lake has the following morphometric properties: maximum length 216 meter, maximum width 99.3 meter, with surface area 2.38 hectare.
Figure 3.1: Map showing study area (Adha village) The lake is home to many wild animals, water birds and aquatic organism such as dragonfly and damselfly. The lake caters the endangered white bellied heron and rare crested eagle, the
14 lake also served as a water hole for many wild cats and ungulates thriving in western part of protected area (JSWNP, 2014). 3.1.1 Major zone description In lakes, the habitat use of macroinvertebrates is strongly influenced by the vegetation characteristics, depth and complexity of the substrate (Efiter et al., 2001; Korte et al., 2010). For example, substrate types such as cobble, pebble and gravel exhibit greater diversity of macroinvertebrate taxa than substrates that are smaller in (Metcalfe, 1989; Freund, 2007). Which are very much influenced by the surrounding land use, where degradation of vegetation affect hydrological discharge regimes in the lake, which increase temperature, sedimentation and affects the existence of benthic rheophilic and their interstitial habitats (Sutherland et al., 2002). These include insect groups like the Ephemeroptera, Plecoptera, and Trichoptera. Accordingly, in this study, the descriptions of four sampling sites are presented below (figure 3.2). 3.1.2 Agriculture Zone This zone consist of agriculture paddy terrace located towards the north of lake, where surface runoff from all categories of farming practices from the uphill terrace drains into the lake during rainy season. At the site, the substrates were composed of coarse gravel, sandy bottom, boulder rocks, cobbles, and aquatic grass (i.e. monsoon season). Agriculture was the main land use in the surrounding area, though there were some grassland areas. 3.1.3 Forest East Zone This zone was located along eastern side of the lake. The leaf litters mainly dominated the substrates and woody logs with few patchy grasses. The surrounding riparian vegetation is composed of closed canopy woody shrubs and trees of cool broad leaved forest. The soil were mostly composed of humus and loamy texture. 3.1.4 Catchment Zone Feeding water to the lake, the catchment zone was located along the southeast aspect of the lake. The soil were mostly composed of sandy loam dominated Ageratina adenophora and the surrounding riparian vegetation is composed of open canopy woody shrubs and trees like Alnus nepalensis. The area was highly degraded due to uncontrolled grazing by domesticated cattle.
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3.1.5 Forest West Zone The riparian vegetation was mainly dominated by Quercus griffithii and other cool broadleaved species. Leaf litters mainly composed the substrate in this zone. The zone was located along the western aspect of the lake where Lake outlet was located. The zone have relatively more influence by the human where the activities like worshiping and local religious ceremony site were located including tradition trail connecting villages runs parallel to the lake.
3.2 Survey Method
3.2.1 Sampling of Macroinvertebrates Based on the landuse types around the lake, which was categorized into four major zones. The Agriculture Zone with agriculture paddy terrace towards north of lake, Forest East with nature forest cover towards the east of lake and Forest West with nature forest cover on the western direction of lake, and Catchment area feeding the lake from South East direction with transect length of 120 meters each. The sampling plots were laid out along the littoral zone of lake within four major landuse zones. Within each stretch of 120 meter, first sampling plot was systematically laid out exactly at the center of 120 meter transect line (at 60 meter) and subsequent sample plots were laid every 15 meter towards left and right of first sample plot (figure 3.2) for sampling physicochemical, macroinvertebrate and other parameters of the lake (Efitre et al., 2001). The process was replicated to all other zones. The sampling were carried out once in monsoon season from July 2016 to September 2016 and once in post monsoon season between December 2016 to February 2017. The following steps/techniques were followed while performing the macroinvertebrate sampling. Sampling techniques on habitats, such as bedrocks and boulders, were performed by kicking, brushing and rubbing the surface and then gently sweeping the animals into the net. In habitats with course cobble, cobbles and stones, the sampling was performed by gently sweeping the surface within the targeted area by hand to dislocate surface dwelling animals and sweeping them into the net. The cobbles and larger stones were disturbed by hands while brushing and scratching the surfaces to remove clinging and sessile animals into the net.
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In woody debris and leaf litter habitat, samples collected were washed thoroughly into the net and the animals were recovered by hand using fine forceps. The habitat with greater depth of lake water where disturbed with poles and leg and the sample where collected using sampling gear and poured into bucket to sort the macroinvertebrates. .
AGRICULTURE ZONE
FOREST EAST
FOREST WEST
CATCHMENT ZONE
Legend Catchment area sampling unit Forest West Zone sampling unit Agriculture zone sampling unit Forest East sampling unit
Adha lake Figure 3.2: Sampling layout in Adha Lake (Study area)
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3.2.2 Macroinvertebrate preservation and identification The sample containers were appropriately labeled with major zone name and site code, date of sampling, investigators name and the number of the sample unit. All macroinvertebrates from each sample were picked up with the help of fine forceps and put into sample containers containing 70% ethanol. Macroinvertebrates that could be identified on the spot were recorded and released back after taking picture and the unidentified species were collected and were taken to the laboratory and kept in the refrigerator until laboratory sorting and identification began. These samples were identified in the laboratory using high power microscope (45-100X) and other macroinvertebrate’s identification manual and field guides. The macroinvertebrates were identified to operational taxonomic level i.e. down to family level using available HKH identification keys such as the HKH field key for selected Benthic macroinvertebrates from the HKH Region (Hartmann, 2006) and based on other key guideline of Bosquet (1990); Choate (1999); Pescador et al. (2000); Nesemann, et al. (2011); Throp and Rogers (2011). According to Chessman et al. (2007), family level identification is sufficient for detecting distresses on the aquatic macroinvertebrate community with low cost and timely completion of the project. A more detailed level of identification is generally required for ecological interpretation, though such studies require significantly more time, and the availability of an appropriate laboratory and facilities.
3.2.3 Recording of physicochemical Variables The physical and chemical parameters were recorded in the developed format as attached in annexure I and annexure II. The physicochemical parameters such as temperature, pH, conductivity, total dissolved salt and salinity were measure in the field with the help of soil and water testing kits (Pcs tester) at every sampling unit before sampling of macroinvertebrates. The geographical elements like altitude, easting and northing coordinates were recorded in the field using Global Positioning System (GPS etrex).
3.3 Data Analysis 3.3.1 Comparing diversity of macroinvertebrates in Adha Lake between monsoon and post monsoon season; Macroinvertebrates diversity between seasons as well as between major zones was computed using Shannon Wieners Diversity Index (Hˈ =-ΣPi*lnPi). The taxon richness were computed
18 using R=(S-1)/LogN (Wilson, 1992) and Evenness using Pielou evenness formula E = H’ / Hmax (McGinley, 2014). The diversity, richness and evenness were compared in the IBM SPSS statistics 21 program, using Mann-Whitney U test between seasons and Kruskal Wallis test among major zones. The excel function and PC ORD were used to analyze the major zone for monsoon and post monsoon.
3.3.2 The relationship between macroinvertebrates and physicoparameter. Spearman’s rho correlation test was used to see the association between macroinvertebrates diversity, evenness and richness with the physicochemical parameter. The Mann-Whitney U test was used to see the significances between environmental variables within the seasons and Kruskal Wallis test among the major zone in study area.
3.3.3 Evaluate the status of macroinvertebrates diversity with every 15 meter increase in distance away from agriculture zone in Adha lake; The objectives were assessed using Linear Regression test.
3.3.4 Water quality assessment: The water quality at each sampling site was assessed using Nepal Lake Biotic Index computed n here: NLBI= Σ i TTSi . (Shah et al., 2011). n This method was used because the HKHbios that was developed to be used in himalayan region including Bhutan was applicable only for running water bodies and not for lentic water bodies (Ofenböck et al., 2010). Having advantages of Bhutan sharing same himalayan range with similar agroecological zone of Nepal, this biotic index was used. On top of that, Adha lake (study area) with altitude 1300 m.a.s.l fall within the range of NLBI study range, which is 500 m.a.s.l to 2,999 m.a.s.l.
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Chapter Four Result and Discussion 4.1 Macroinvertebrates diversity in the study area Total of 1,009 numbers of macroinvertebrates belonging to eight taxonomic order and two sub- order comprised of twenty families (table 4.1) were recorded from the study area. Taxa belonging to the Chironomidae (n=413, RA=40.93) were the most common and were observed in all sites followed by the Baetidae (n=173, RA=17.15) (table 4.1). This could be because, the lake’s littoral zone was degraded and polluted with high disposal of leave litters, twigs, small logs from surrounding vegetation. Moreover, the surface runoff from surrounding landuse during rainy season leads to siltation with fragile top soil and nutrients. These probably might have led to low oxygen level, which could have made the Chironomidae and Baetidae to be most abundant in the area. This could indicate that the aquatic habitat is polluted. This finding accord with Coffman and Ferrington Jr (1996), where these families were found to be distributed in low oxygen level habitat or relatively heavily polluted area and feeds on small particles of organic debris. Soldner (2006) also found that chironomidae were very common in almost 50% of the sampling sites studied in Dominican Republic. The species were found to be very much common in mud or silt or other soft sediments build tubes or tunnels as refuges (Foote, 1987). Earlier studies on high altitude lakes in the Sagarmatha National Park (Manca et al., 1998), and in mountain ranges of Europe such as the Alps (Boggero et al., 2006) also reported that chironomidae were the most dominant taxa. Baetidae are scraper, which feeds on algae and detritus. They are said to be very common in polluted and low oxygenated waters. Moreover, they are tolerant to temperature fluctuation (Morihara and McCafferty, 1979). There were many taxa with minimal percentage within the study area suggesting high λ - diversity within the study area such as Acrididae (RA= .10), Aeshnidae (RA = .10), Tabanidae (RA =.10), Hydrophilidae (RA =.10), and Libellulidae (RA =.10) during monsoon season and Simuliidae (RA =.10), and Culicidae (RA =.20) during post monsoon season (table 4.1). Taxa Aeshnidae, and Simuliidae were found in the catchment zone. These indicate that the water being relatively less polluted in the catchment zone (Das et al., 2013). The catchment zone have continues water flow sourced from nearby forest, which was relatively clean. Moreover, the marshy landuse in the catchment zone, probably filtered all the surface runoff entering the lake
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(Burkett and Kusler, 2000). These macroinvertebrates are said to be sensitive to the degradation of stream habitats (Lautenschlager and Kiel, 2005; Das et al., 2013).
Table 4.1: Order, families and relative abundance of macroinvertebrates for the whole study area.
Order Sub-order Family Count RA % Odonata Zygoptera Protoneuridae 17 1.68 Synlestidae 150 14.87 Anisoptera Gomphidae 10 0.99 Libellulidae 1 0.1 Macromiidae 4 0.4 Aeshnidae 1 0.1 Haplotaxida Naididae 117 11.6 Ephemeroptera Baetidae 173 17.15 Hemiptera Gerridae 44 4.36 Coleoptera Noteridae 7 0.69 Hydrophilidae 1 0.1 Dytiscidae 30 2.97 Diptera Tabanidae 1 0.1 Chironomidae 413 40.93 Culicidae 2 0.2 Simuliidae 1 0.1 Trichoptera Helicopsychidae 11 1.09 Lepidostomatidae 18 1.78 Philopotamidae 7 0.69 Orthoptera Acrididae 1 0.1 Total 1009 100
Libellulidae was found in the forest east zone. The few large riparian trees along the forest east zone must have probably provided good habitat for Libellulidae larvae to breed and feed. Das et al. (2013) mentioned that they habits still to slow flowing water. The larvae of the taxa
21 occupy tree holes of evergreen and semi-evergreen forests to breed (Das et al., 2013). Hydrophilidae, Acrididae and Tabanidae were found in agriculture zone. This could be because the surface runoff from agriculture zone favors the growth of riparian grasses, which indirectly provides habitats for Acridadae (grasshopper), Tabanidae (Horse fly) and preying ground for Hydrophilidae (beetle). The taxa Hydrophilidae preferred habitat with marshy and heavily weeded shallow areas (Arribas et al., 2012) which agriculture zone provides. Tabanidae famously known as horse fly are said to live mostly in wet soil in marshes/bogs and at margins of streams and ponds (Thorsteinson et al., 1965), while Acrididae (grasshopper family) preferred grasses (forbivorous and graminivorous) (Mcclenaghan et al., 2015). The agriculture zone provides the perfect habitat for the taxa Tabanidae and Acrididae.
4.2 Composition of macroinvertebrates in major zone for monsoon and post monsoon seasons. During monsoon season, in agriculture zone, the most dominant order encountered was Diptera (55.30%) and the least order recorded was Anisoptera (3.79%) (figure 4.1, (a)). The families which were prevalent to agriculture zone were acrididae, Protoneuridae, Noteridae, Hydrophilidae, Tabanidae and Gomphidae (appendices II). Similarly, the dominant order in forest east zone was Diptera (42.28%) and the least encountered order was Anisoptera (1.34 %) (figure 4.1, (a)). The only endemic family in the forest east zone was Libellulidae (appendices II). In catchment zone and forest west zone, the dominant order were Diptera, 49.38% and 35.35% respectively and the least encountered order were Coleoptera (1.23%) and Ephemoptera (1.01%) (figure 4.1, (a)). The family particularly prevalent to catchment zone was Aeshnidae. Similarly, for post monsoon season in all major zones, order Diptera dominated with 47.52% for agriculture zone, 39.86% for forest east, and 38.31% for catchment zone except forest west, where Zygoptera dominated with 27.27% (figure 4.1, (a)). Families such as Culicidae, Simuliidae and Macromiidae were only found in catchment zone and Gerridae Was only found in forest east zone (appendices II).
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A_PM
F_E_PM
F_W_PM
A_M
C_PM
F_E_M
C_M
F_W_M
0 10 20 30 40 50 60 70 80 90 100 Anisoptera Coleoptera Diptera Ephemeroptera Haplotaxida Hemiptera orthoptera Trichoptera zygoptera
*A=Agriculture Zone, *F_E=Forest East Zone, *F_W=Forest West Zone, *M= Monsoon, *PM= Post Monsoon.
Figure 4.1 (a): Composite graph showing relative abundance of taxon with major zone in the study area for monsoon and post monsoon season
The cluster analysis based on the relative abundance of taxa found in eight major zones for two seasons showed the major zones grouped into two major clade. The dendrogram showed that the forest east zone and forest west zone of monsoon season and forest west of post monsoon have similar family composition with more than 50% similarity in dendrogram scale. The dominant families were Chironomidae, Synlestidae, Naididae and Gerridae (figure 4.1 (b)). The similarity among these zones could be due to similarity in riparian vegetation, mostly dominated by large growth trees, and the geographic location of surrounding landuse with probable of high nutritious surface runoff into lake during rainy season. The surrounding vegetation cover provides similar substrate composition in the lake, where macroinvertebrates distribution was strongly influence by complexity of substrate, depth and vegetation characteristic (Efiter et al., 2001). The finding also accord with Dorji (2014), where similar riparian vegetation was mentioned to have same influence over the aquatic habitat and macroinvertebrates distribution.
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Similarly, catchment zone monsoon and agriculture zone monsoon were indicated as sister clade with 50% similarity in relative macroinvertebrates abundance and catchment zone post monsoon and agriculture zone post monsoon having very closer, 100% similarity (figure 4.1, (b)). This was probably because of similar influence of surrounding landuse of lake. The nutrients rich surface runoff from the agriculture paddy field during monsoon season and the surface runoff from cattle grazing ground near catchment zone could have persuade in having similar habitat in these two zones, having similar macroinvertebrates abundance. These indicate that, these zones have similar water physicochemical parameters such as pH, salinity, conductivity, TDS and water temperature, which made the habitat suitable for that particular macroinvertebrates. Sutherland et al. (2002) accorded that the substratum composition, complexity and particle size affects the distribution, structure and composition of macroinvertebrate communities, where surface runoff due to degradation of vegetation affect hydrological discharge regimes in the lake. This increases the temperature, sedimentation and affects the existence of benthic macroinvertebrates and the habitat.
Figure 4.1 (b): Cluster analysis of major zones using dendrogram based on relative abundance for monsoon and post monsoon season
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4.3 Macroinvertebrates diversity among monsoon and post monsoon seasons There were minute differences between monsoon and post monsoon seasons on macroinvertebrate diversity as indicated by Shannon diversity index (H’=1.72) Evenness (EH=
1.43) and taxon richness (SR=5.63) for monsoon season and diversity (H’=1.73), Evenness
(EH=1.55) and richness (SR= 4.38) for post monsoon season (figure 4.2). However there were no significant seasonal difference as indicated by Mann-Whitney test for diversity (U=6, p =.567), (x̄ =1.5±.14), Evenness (U=8, p =.1), (x̄ =1.7±.24) and Richness (U=8, p =.1), (x̄ =8.02±2.34) for monsoon and post monsoon season (table 4.2). The finding were in contradiction to Arunachalam et al. (1991) where diversity was mentioned to be relatively more in pre monsoon season in the Europe, however Negi and Mamgain (2013) found that the diversity of macroinvertebrates were more during post monsoon season in Garhwal Himalaya Uttarakhand. Dorji (2016) also found higher values of macroinvertebrate abundance in the post season at Samtse district, Bhutan. The difference among these three finding could be because, the diversity of macroinvertebrates are directly correlated and influenced by the surrounding landuse which in turn is influenced by the rate of physicoparameters like water pH, temperature, salinity and dissolved oxygen (Dhakal, 2006). Beside this Dorji (2016) found that during high flow season (monsoon), diversity of macroinvertebrates decrease and vice versa. Where as in current study area the lake being perennial throughout the season, the volume of lake remain almost same, which could have render unaltered habitat for macroinvertebrate and diversity may have remain same.
Richness
Evenness Post Monsoon Monsoon
Diversity Shannon Wieners Index Wieners Shannon
0.000 1.000 2.000 3.000 4.000 5.000 6.000 Indices
Figure 4.2: Shannon Wiener Diversity, Evenness and Richness of macroinvertebrates in monsoon and post monsoon seasons
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Table 4.2: Mann-Whitney test for diversity indices among monsoon and post monsoon season Evenness Richness Diversity Mann-Whitney U 8.000 8.000 6.000 Z .001 .001 -.577 Asymp. Sig. (2-tailed) 1.000 1.000 .564
4.4 Macroinvertebrate diversity among zone for monsoon and post monsoon seasons There were no significant differences within as well as between zones for monsoon and post monsoon seasons as indicated by Kruskal Wallis test for diversity (χ2=.333, p=.564), (x̄ =1.5±.14), taxa evenness (χ2=.001, p=.1), (x̄ =1.7±.24) and taxa richness (χ2=.001, p=.1), (x̄ =8±2.34) (table 4.3). However as expected there were relatively high taxon richness indicated by Shannon Wiener biodiversity index (SR=12.54) (figure 4.3) at the catchment zone during post monsoon season as compare to other zones. The high taxon richness in catchment zone may be due to edge effect, where lake meets with running stream that ends into lake, which is another different habitat with different physicochemical properties (Heino et al., 2007; Soininen et al., 2015). These two different habitat with different physicoparameter may have provided stability and optimum environmental factor for taxa to thrive. In addition, in catchment area, the physicochemical parameters for monsoon and post monsoon varies greatly (table 4.4), which showed significant difference between monsoon and post monsoon seasons by Mann-Whitney test (table 4.6). Study by Kłonowska-Olejnik and Skalski (2014) at Pieniny Mountains, West Carpathians found that, macroinvertebrates varied significantly in different seasons of the year, which are influenced by environmental variability such as water temperature, flow velocity, stream width and depth. These factors are mainly determined by the season, and are essential driving variables for altering macroinvertebrate community structure by both direct and indirect effects on habitat conditions, and on variables such as pH and pollution loads. However, Spearman’s correlation test indicated that there was weak negative correlation between taxa richness and physicochemical parameter (table 4.5). The test was not significant (p>.05).
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14.00 4.50 12.00 4.00 3.50 10.00 3.00 8.00 2.50 6.00 2.00 1.50 4.00 1.00 2.00 0.50
Taxon Richness Richness Taxon indices 0.00 0.00
Catchment Zone Post Post ZoneCatchment
Forest west Post Post Forest west
Agriculture Zone Post Post ZoneAgriculture
Forest East Post Forest Post East ZoneCatchment
Forest west Monsoon Forest west
Agriculture ZoneAgriculture
Forest Forest Eastmonsoon
Diveristy, Evenness Diveristy,Evenness Indices
Monsoon
Monsoon
Monsoon
Monsoon
Monsoon Monsoon Richness Evenness Diversity
Major Zones
Figure 4.3: Shannon Wiener diversity indices within and between, zone of monsoon and post monsoon Table 4.3: Kruskal Wallis test for Shannon Wiener indices among major zone for monsoon and Post monsoon Diversity Evenness Richness Chi-Square .333 .001 .001 df 1 1 1 Asymp. Sig. .564 1.000 1.000
Table 4.4: Physicochemical parameters for catchment zone in monsoon and post monsoon season pH Temperature Salinity TDS Conductivity M PM M PM M PM M PM M PM 8.7 6.4 24.90 15.60 45.70 46.30 45.00 48.90 63.60 68.80 8.8 6.3 24.80 15.80 45.70 45.70 43.50 48.10 61.00 67.30 8.7 6.5 24.90 15.80 45.50 46.10 44.50 49.00 62.40 69.00 8.6 6.5 25.00 16.70 45.50 46.10 44.50 48.70 62.50 68.30 8.6 6.7 25.40 15.70 44.70 48.80 43.60 48.90 60.70 68.70 8.7 6.5 29.90 15.80 46.50 45.90 45.50 49.00 64.10 69.10 8.7 6.5 25.10 15.70 46.40 46.40 46.10 49.10 64.40 69.10 8.8 6.3 25.20 15.30 47.90 46.10 47.30 49.00 66.60 69.00 Mean 8.7 6.5 25.65 15.80 45.99 46.43 45.00 48.84 63.16 68.66
*M=Monsoon, *PM=Post Monsoon.
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4.5 Relationship between macroinvertebrates and physicochemical parameters Spearman’s correlation indicated weak negative correlations between diversity indices and physicoparameters with pH (rs=-.17, p=.69), temperature (rs=-.55, p=.16) salinity (rs=-.69, p=.06) TDS (rs=-.55, p=.594) and conductivity (rs=-.19, p=.65) (table 5). Similarly there were weak negative correlation between taxon richness and physicoparameter, pH (rs=-.21, p=.61), temperature (rs=-.29, p=.49), salinity (rs=-.45, p=.26), TDS (rs=-.45, p=.26) and conductivity
(rs=-.05, p=.91) (table 4). However, the correlation was not significant (p>.05) (table 4.5). Macroinvertebrates have certain optimum range to survive and breed. The negative correlation could be due to the surrounding landuse pattern influencing the optimum range of physicoparameters required for macroinvertebrates. The surface runoffs during monsoon season from surrounding landuse could have enriched the lake, increased its turbidity and changed the optimum range of physicoparameters requirements. This could have modified the habitats making it unsuitable for macroinvertebrates. According to Negi and Mamgain (2013), the physicoparameter such as temperature have suppressing effect on macroinvertebrates. With the temperature of 30 degree Celsius, the macroinvertebrates were found be less in diversity and richness. Clenaghan et al. (1998) and his team pointed out that temperature increase in linear correlation with increase in pH. The optimum pH required for all benthic macroinvertebrates to thrive is in between 5.0 and 9.0 (Yuan, 2004). The macroinvertebrates like Ephemeroptera, Pleocoptera and Tricoptera are very sensitive to pollution and siltation. These insects have an external respiratory gills located thoracic, abdominal, caudally or at the base of their legs, which could be easily clog with suspended solid (colloid or small particle that suspension in the water). Once it is clogged the gills cannot function. It cannot extract oxygen from the water, and this could be lethal to the aquatic insects (Budin et al., 2007). The dissolved oxygen is vital for survival and growth of all aerobic organism. The Spearman’s correlation indicated that pH, temperature and salinity in the study area had significant positive correlation to each other (p<.05) (table 4.5). The salinity concentration was found to be more during monsoon season as compared to post monsoon. It could be due to dissolving of nature salt and high siltation from surrounding land use, which increases salinity
28 concentrated of the lake where it help to trap the heat and increase temperature during monsoon making water slightly alkaline. The Spearman’s correlation indicated that there was negative correlation between the taxa diversity and the Salinity, TDS and conductivity of the study area (table 4.5). This may be because, the taxa faces osmotic stress due to salt concentration which wipes the taxa out from the habitat (Zinchenko and Golovatyuk, 2013), nevertheless the negative correlation between taxa diversity and salinity was not significant (p>.05). Dunlop et al. (2008) mentioned that the taxa, Ephemeroptera, Gastropoda, Hemiptera, Diptera, Zygoptera, Coleoptera and Isopoda are highly tolerant to salinity however, it depends species to species within the taxa (Timpano et al., 2010). Dunlop et al. (2005) also mentioned that salt and turbidity have pronounced direct toxic effects and indirect ecological effects on freshwater biota above certain thresholds. The recent study by Brraich and Kaur (2017) in Nangal wetland, India also found that water temperature, electrical conductivity, TDS, alkalinity and salinity are negatively correlated with macrobenthic organisms. The findings were in contradiction with the study by Faith and Norris (1989), where they found strong positive correlation between environment variables with rare and common taxon richness and diversity in central Australia. It was also found that diversity of aquatic macroinvertebrate were strongly associated to differences in geographical position, altitude, slope, catchment area and current velocity beside physicoparameter (Skoulikidis et al., 2009).
The Spearman’s correlation test also indicated that the pH (rs=.19, p=.65), temperature
(rs=.05, p=.91) and TDS (rs=.05, p=.91) have positive association with taxa evenness while salinity (rs=-.02, p=.96) and conductivity (rs=-.26, p=.53) showed negative association (table 4.5). The pH, temperature and TDS have positive correlation with taxa evenness because these physicoparameter suppresses the diversity and richness of taxa leading to uniform and even distribution with the habitat (Sutclifee and Hildrew, 1989). However, salinity and conductivity have negative correlation with taxa evenness. This could be because, the evenly distribution of taxa within the habitat are hampered by salt concentration where it make the habitat unsuitable for taxa to thrive. However, to contrary, Uwadiae (2009) found that, mean salinity of >0.34ppt has higher taxa evenness, while mean salinity <0.09ppt have low taxa evenness.
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Table 4.5: Spearman’s correlation between diversity indices and physicoparameters. pH Temperature Salinity TDS Conductivity Diversity Evenness Richness pH 1.0 .762* 0.67 0.33 -0.24 -0.17 0.19 -0.21 0.03 0.07 0.42 0.57 0.69 0.65 0.61
Temperature 1.00 .786* 0.24 -0.17 -0.55 0.05 -0.29
0.02 0.57 0.69 0.16 0.91 0.49
Salinity 1.00 0.57 0.29 -0.69 -0.02 -0.45
0.14 0.49 0.06 0.96 0.26
TDS 1.00 0.48 -0.55 0.05 -0.45
0.23 0.16 0.91 0.26
Conductivity 1.00 -0.19 -0.26 -0.05
0.65 0.53 0.91
Diversity 1.00 0.21 0.43
0.61 0.29
Evenness 1.00 -.762*
0.03 Richness 1.00
4.6 Physicochemical variables among monsoon and post monsoon season There was significant differences in temperature (U=.001, p=.001), (x̄ =20.73±5.41), pH (U=.001, p=.001), (x̄ =7.6±1.13), salinity (U=271, p=.001), (x̄ =47.2±1.89), TDS (U=304.5, p=.005), (x̄ =48.7±3.92) and conductivity (U=258, p=.001), (x̄ =68±2.7) between monsoon and post monsoon seasons (table 4.6). Similar findings were made by Alagoa and Aleleye-Wokoma (2012), where they revealed that there was a significant seasonal difference in physicochemical parameters of temperature, turbidity, pH. The difference in these physicochemical parameter variables especially pH and salinity in the study area could be, due to high turbidity surface runoff from surrounding landuse into lake in the monsoon season, in particular agriculture land where nutrient rich water during paddy cultivation season drains into lake making water slightly alkaline and fit for the bloom of floating algae. In addition the edges of lake in two other zones (Forest East and West) were covered with debris like leaf litters, twigs and rotten log fallen directly into lake. Beside this, the strategic location of lake within the bottom of valley collects all the organic surface runoff from surrounding landuse. During post monsoon season, the surrounding agriculture land were left
30 uncultivated and on top of that, the area receives less to no precipitation, which reduces the surface runoff entering lake from surrounding landuse. The water is slightly acidic during post monsoon. Chatzinikolaou and Lazaridou (2007) mentioned that constant constructions together with contamination from agriculture runoff have direct relation with the water pH and siltation. Beside contamination from anthropogenic activities, the vegetation along the water bodies were said to have maximum influences on physicoparameter including water pH (Fernandez-Diaz and Benetti, 2008; Dorji, 2014). The study by Zinabu (2002) also made a similar finding where salinity and total ions seemed to increase during the wet seasons in some of the lakes.
Table 4.6: Mann-Whitney test for physicoparameters between monsoon and post monsoon seasons. pH Temperature Salt TDS Conductivity Mann-Whitney U .001 .001 271.000 304.500 258.000 Z -6.879 -6.878 -3.248 -2.793 -3.418 Asymp. Sig. (2- .001 .001 .001 .005 .001 tailed)
4.7 Relationship between macroinvertebrate diversity with the distance away from Agriculture Zone. The association between diversity index of macroinvertebrates presence with every 15 meter away from agriculture zone along the forest east zone was tested using linear regression analysis for monsoon and post monsoon seasons. The linear Regression test showed weak positive associations between diversity and agriculture zone with every 15 meter increase in distance away from it, for monsoon (R² = .1266) and post monsoon season (R² = .0072) (figure 4.4). There were also weak positive associations between taxa evenness and agriculture zone for monsoon (R² = .112) and post monsoon (R² = .001) seasons (figure 4.5). The regression test of taxa richness and agriculture zone also indicated a weak positive association for monsoon (R² = 0.054) and post monsoon (R² = 0.054) (figure 4.6). The regression test indicated that, the agriculture zone have lesser influence on the diversity index of macroinvertebrates for monsoon as well as post monsoon seasons. The finding indicates that agriculture has less influence over the macroinvertebrates in adha lake (figure 4.7). According to Stubbington et al. (2009), there is a significant impact on lake due to change in
31 landuse, although the abundance of certain species are said to increase, the diversity and species richness are said to be decreasing (Efiter et al., 2001).
2.00 1.60 y = -0.0006x + 0.8703 1.40 R² = 0.0072 1.50 1.20 r=.0848 1.00 1.00 0.80 y = 0.0056x + 0.5111 0.60 0.50
R² = 0.1266 0.40 Diversity Diversity indices 0.00 r=0.355 0.20 0.00
Diversity Diversity indices 0 15 30 45 60 75 90 105 120 0 15 30 45 60 75 90 105 120 Distance in meter Distance in meter
Figure 4.4: Linear regression test between taxa diversity and the distance away from Agriculture Zone for monsoon (a) and post monsoon (b) season 2.50 2.50 2.00 2.00 1.50 1.50
1.00 y = 0.008x + 0.8517 1.00 y = 0.0002x + 1.5169 R² = 0.001
0.50 R² = 0.1126 0.50 Evennessindices Evenness indices r=0.335 r=.031 0.00 0.00 0 15 30 45 60 75 90 105 120 0 15 30 45 60 75 90 105 120 Distance in meter Distance in meter
Figure 4.5: Regression test between taxa evenness and the distance away from Agriculture Zone for monsoon(a) and post monsoon(b) seasons
3.50 3.50 y = -0.0058x + 2.5309 3.00 3.00 R² = 0.0504 2.50 2.50 r=0.224 2.00 2.00 1.50 y = 0.008x + 1.376 1.50 1.00 R² = 0.0548 1.00
Richness indicesRichness 0.50 r=0.232 indicesRichness 0.50 0.00 0.00 0 15 30 45 60 75 90 105 120 0 15 30 45 60 75 90 105 120 Distance in meter Distance in meter
32
Figure 4.6: Regression test between taxa richness and the distance away from Agriculture zone for monsoon(a) and post monsoon(b) seasons
4.50 4.00 3.50 3.00 2.50 2.00
Indices 1.50 Diversity 1.00 Evenness 0.50 0.00 Richness 15 30 45 60 75 90 105 120 15 30 45 60 75 90 105 120 m m m m m m m m m m m m m m m m
Monsoon Post Monsoon Season
Figure 4.7: Shannon Wiener Diversity index with Distance away from Agriculture Zone
4.8 Lake Water quality. The overall water quality of adha lake computed through the tolerance score of macroinvertebrates presence (table 4.7) following the Nepal lake biotic index (appendices I) indicated that lake was heavily polluted with poor water quality (LWQC=3.15) (table 4.8). The poor water quality owes to the stagnant and small volume of inflow and out flow of water. Moreover, the lake receive immense inorganic surface runoff from surrounding land beside agriculture paddy field during monsoon, which enrich water nutrient concentration making fit for water surface algae bloom (Chatzinikolaou and Lazaridou, 2007; Benetti and Garrido, 2010). The leaf litters and vegetative parts like twigs and logs were seen fallen inside the lake from surrounding vegetation cover (Forest East and West zone) which also aids in making water high in productivity (Hepp and Santos, 2009; Dorji, 2014).
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Table 4.7: Taxon biotic score, according to Nepal Lake Biotic Scoring system Order Sub-order Family Tolerance score Odonata Zygoptera Protoneuridae 8 Synlestidae Anisoptera Gomphidae 4 Libellulidae 3 Macromiidae Aeshnidae 6 Haplotaxida Naididae 6 Ephemeroptera Baetidae 6 Hemiptera Gerridae Coleoptera Noteridae 5 Hydrophilidae 6 Dytiscidae 5 Diptera Tabanidae 4 Chironomidae 1 Culicidae 2 Simuliidae Trichoptera Helicopsychidae Lepidostomatidae 7 Philopotamidae Orthoptera Acrididae Total score 63 LWQC 3.15
Table 4.8: Transformation scale of NLBI to LWQC, degree of pollution and colour code NLBI LWQC Degree of pollution Colour code 6.10–10.00 High None to minimal Blue 4.91–6.09 Good Slightly Green 4.00–4.90 Fair Moderately Yellow 2.00–3.99 Poor Heavily Orange 0.00–1.99 Bad Extremely Red
4.9 Water quality of different seasons The Nepal lake biotic index indicated that the water qualities for both monsoon (LWQC= 3.375) and post monsoon (LWQC= 3) (table 4.9) fall both within poor quality with heavily polluted category (table 4.8). The high surface runoff from the surrounding landuse into lake could have favored the algal bloom during monsoon season. Moreover, the leave litters and broken twigs
34 falling into the lake from riparian vegetation during dry post monsoon season could have aided in polluting the lake.
Table 4.9: Lake water quality for monsoon and post monsoon season Tolerance Tolerance Order Family score Order Family score Protoneuridae 8 Protoneuridae 8 Synlestidae Synlestidae Zygoptera Zygoptera Haplotaxida Naididae 6 Ephemeroptera Baetidae 6 Ephemeroptera Baetidae 6 Culicidae 2 Hemiptera Gerridae Chironomidae 1
Noteridae 5 Diptera Simuliidae Hydrophilidae 6 Macromiidae Coleoptera Dytiscidae 5 Anisoptera Gomphidae 4 Tabanidae 4 Hemiptera Gerridae Diptera Chironomidae 1 Lepidostomatidae 7 Gomphidae 4 Trichoptera Philopotamidae Libellulidae 3 Coleoptera Dytiscidae 5 Macromiidae Haplotaxida Naididae 6 Anisoptera Aeshnidae 6 Trichoptera Helicopsychidae Orthoptera Acrididae Total score 54 39 LWQC 3.4 3
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Chapter Five Conclusion Assessing macroinvertebrates diversity and water quality in Adha lake was crucial as it habits many endangered animals and the socio-religious believe associated with it. Evaluating the rate of influence of surrounding landuse on lake water quality and eutrophication was timely. The fresh waters bodies are among the most threatened habitat types in the world. As anthropogenic land disturbance continues to increase worldwide, great difficulties are been faced with the challenge of determining the influence over the structure and function of aquatic ecosystems. However, macroinvertebrate in lentic water system plays important role in maintaining the condition and structure of the lake by decomposing the high deposition taking place in the container of the lake. Eight orders and twenty families were identified within different major zones of Adha lake. Chironomidae family were the dominant in all major zone followed by Baetidae family. The least family present were Acrididae, Aeshnidae, Tabanidae, Hydrophilidae, Libellulidae, Simuliidae and Culicidae. There was no significant difference in diversity between monsoon and post monsoon season, however there was relatively high taxon richness in catchment zone as compared to other zones. There were weak negative correlations between taxon diversity and richness with physicoparameters, and positive correlation between pH, temperature and TDS with taxon evenness, both of which were not significant. The significant differences were found between the physicoparameters of two seasons. There was significant negative influence of surrounding landuse on water quality. According to the Nepal Lake Biotic Index the water quality was categorized as poor and heavily polluted. It is timely to design prevention and remedial measure to revive significant Adha lake, which was once a habitat for critically endangered white bellied heron and other significant fauna.
36
Recommendation The low altitude limnological study is first of its kind in Bhutan. It can be used as reference baseline data to study low altitude lake located at the zone of chirpine forest and cool broadleaved forest in future (1300 m.a.s.l). Similar study could be carried out in the future, taking in consideration all the season, despite two season (monsoon and post monsoon) since physicoparameters such as pH, dissolved oxygen varies significantly among season. Beside HKHbios index and NLBI scoring system, there is need for rigorous taxonomic investigations, that can provide guidelines for correct identifications required for the development of monitoring methods, purely focused in freshwater biota of Bhutan. There is scope in developing Bhutan Lake Biotic Index. Due to non availability of biotic index for lake dwelling macroinvertebrates, the only index that could be use in Bhutan for low altitude lake was NLBI. NLBI is focused within the altitude range of 500 m.a.s.l to 2999 m.a.s.l in Nepal. Although this study was restricted to Adha lake only, 1009 taxa were found which could not be identified to species level. Specific taxonomic studies on macroinvertebrates are still very limited and comprehensive keys are not yet available but should be developed. Further studies with regards to assessment of relationship between bryophyte and macroinvertebrates in adha lake together with Physicoparameters could give the overall snap shot status of lake in terms of ecology.
37
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Annexure I: Physicochemical parameters recording sheet in different habitat zone Records of the physicochemical parameters in different habitat zone Catchment Major Zone Agri_ zone Forest East Forest West zone Sampling Site 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 Parameters pH Temperature Salt TDS Conductivity Dissolved oxygen
Annexure II: Recording data sheet for macroinvertebrates in the field
Name of Major Zone: Major habitat Sampling unit number: 1 Zone ID Sl.no Order Family Count Remarks Agri_land zone AZ Forest East FE Forest West FW Catchment zone CZ
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Appendices I: Taxa with their respective tolerance score for calculating the NLBI, macroinvertebrates are ranked based on ten point scoring system with high scores indicating high sensitivity. Taxon Tolerance score Ephemeroptera Baetidae 6 Caenis sp. 3 Trichoptera Ecnomidae 3 Lepidostomatidae 7 Leptoceridae 6 Molannidae 6 Coleoptera Chrysomelidae 8 Curculionidae 5 Dryopidae 10 Dytiscidae 5 Gyrinidae 7 Hydrophilidae 6 Noteridae 5 Scirtidae 10 Odonata Aeshnidae 6 Coenagrionidae 5 Corduliidae 5 Gomphidae 4 Libellulidae 3 Protoneuridae 8 Heteroptera Belostomatidae 7 Corixidae 2 Gerridae 4 Helotrephidae 9 Hydrometridae 6 Mesoveliidae 6 Micronectidae 3
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Nepidae 4 Notonectidae 3 Pleidae 4 Veliidae 8 Diptera Ceratopogonidae 5 Chironomidae (red) 1 Chironomidae not red 5 Culicidae 2 Diamesinae (Chironomidae) 8 Microtendipes sp. (Chironomidae) 4 Polypedilum sp. (Chironomidae) 4 Dolichopodidae 2 Ephydridae 1 Limoniidae 8 Muscidae 2 Sciomyzidae 8 Stratiomyidae 4 Tabanidae 4 Tipulidae 7 Lepidoptera Pyralidae 8 Decapoda Atyidae 6 Caridina (cf. nilotica) 7 Palaemonidae 6 Macrobrachium spec. 6 Isopoda Corallanidae 7 Tachaea spongillicola 7 Mysidacea Mysidae 8 Gangemysis assimilis 8 Decapoda Potamidae 9 Himalayapotamon spec. 9 Parathelphusidae 6 Amphipoda Talitridae 8 Platorchestia platensis 8 Araneae Hydracarina sp. 7 Spinicaudata Cyclestheriidae 7 Cyclestheria hislopi 7
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Haplosclerida Spongillidae 7 Cheilostomata Lophopodidae 8 Lophopodilla carteri 8 Plumatellidae 7 Tricladida Planariidae, Dugesia sp. 6 Nematoda 2 Haplotaxida Naididae 6 Aulophorus v 7 Aulophorus flabelliger 8 Aulophorus furcatus 7 Aulophorus hymanae 8 Aulophorus indicus 7 Aulophorus michaelseni 7 Aulophorus tonkinensis 8 Chaetogaster limnaei bengalensis 5 Dero nivea 6 Nais bretscheri 6 Nais communis 6 Nais pardalis 7 Nais simplex 5 Pristina cf. biserrata 6 Pristina breviseta 6 Pristinella acuminata 6 Pristinella jenkinae 6 Pristinella menoni 6 Pristina synclites 6 Stylaria fossularis 6 Tubificidae 2 Aulodrilus limnobius 9 Aulodrilus pigueti 6 Aulodrilus pluriseta 4 Branchiodrilus hortensis 5 Branchiodrilus semperi 6 Branchiura sowerbyi 2 Limnodrilus claparedeanus 4 Limnodrilus hoffmeisteri 2 Limnodrilus profundicola 3 Limnodrilus udekemianus 4 Enchytraeidae 7 Megascolecidae 7 Amynthas corticis 7
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Lumbriculida Lumbriculidae 8 Lumbriculus variegatus 8 Arhynchobdellida Salifidae 3 Barbronia weberi 4 Salifa (herpobdelloidea) lateroculata 5 Haemadipsidae 8 Haemadipsa sylvestris 8 Hirudinidae 7 Hirudinaria manillensis 8 Poecilobdella granulosa 8 Rhynchobdellida Glossiphoniidae 4 Alboglossiphonia heteroclita 4 Alboglossiphonia pahariensis 5 Alboglossiphonia weberi 4 Batracobdelloides reticulatus 4 Placobdelloides multistriatus 7 Placobdelloides fulvus 4 Bivalvia Unionidae 6 Lamellidens jenkinsianus jenkinsianus 6 Lamellidens marginalis 8 Lamellidens narainporensis 6 Corbiculidae 5 Corbicula striatella Sphaeriidae 5 Musculium indicum 4 Pisidium annandalei 9 Pisidium atkinsonianum 8 Pisidium clarkeanum dhulikhelensis 6 Pisidium clarkeanum 4 Pisidium nevllianum 5 Amblemidae 7 Radiatula caerulea 6 Radiatula lima 7 Radiatula occata 7 Gastropoda Bithyniidae 5 Digoniostoma cerameopoma 5 Digoniostoma pulchella 5 Gabbia orcula 5 Lymnaeidae 4 Galba truncatula 8
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Lymnaea acuminata 4 Radix luteola 4 Radix ovalis 4 Thiaridae 4 Brotia costula 7 Melanoides pyramis 4 Melanoides tuberculatus 4 Thiara lineata 4 Thiara scabra 5 Planorbidae: Planorbinae 4 Gyraulus convexiusculus 4 Gyraulus euphraticus 4 Gyraulus labiatus 5 Hippeutis umbilicalis 4 Segmentina calatha 4 Segmentina trochoidea 5 Planorbidae: Bulininae Camptoceras lineatum 7 Indoplanorbis exustus 4 Physidae 2 Physa (Haitia) mexicana 2 Viviparidae 6 Bellamya bengalensis 6 Idiopoma dissimilis 6 Ampullariidae 4 Pila globosa 4
Appendice II: Major zones and the families with relative abundance for monsoon and post monsoon seasons
Monsoon season Family Forest West Zone Catchment Zone Forest East Zone Agriculture Zone Synlestidae 30.3030303 22.22222222 14.76510067 13.63636364 Naididae 20.2020202 3.703703704 21.47651007 8.333333333 Baetidae 1.01010101 9.87654321 7.382550336 Gerridae 10.1010101 5.369127517 Dytiscidae 3.03030303 1.234567901 5.369127517 4.545454545 Chironomidae 35.35353535 49.38271605 42.28187919 54.54545455 Macromiidae 2.469135802 0.67114094 Aeshnidae 1.234567901
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Helicopsychidae 9.87654321 2.013422819 Libellulidae 0.67114094 acrididae 0.757575758 Protoneuridae 7.575757576 noteridae 5.303030303 Hydrophilidae 0.757575758 Tabanidae 0.757575758 3.787878788 Gomphidae 100 100 100 100
Post Monsoon Season
Forest West Catchment Forest East Agriculture Order Family Zone Zone Zone Zone Haplotaxida Naididae 16.36363636 3.246753247 13.98601399 5.673758865 Zygoptera Synlestidae 27.27272727 9.74025974 3.496503497 8.510638298 Ephemeroptera Baetidae 16.36363636 31.16883117 30.06993007 31.20567376 Diptera Chironomidae 20.90909091 36.36363636 39.86013986 47.5177305 Trichoptera Lepidostomatidae 9.090909091 1.948051948 2.797202797 0.709219858 Hemiptera Gerridae 10 2.597402597 7.692307692 Zygoptera protoneuridae 1.948051948 2.097902098 0.709219858 Diptera Culicidae 1.298701299 Diptera Simuliidae 0.649350649 Anisoptera Macromiidae 0.649350649 Anisoptera Gomphidae 2.597402597 0.709219858 Trichoptera Philopotamidae 3.896103896 0.709219858 Coleoptera Dytiscidae 3.896103896 4.255319149 100 100 100 100
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