The design of a non-lethal fish monitoring program for rivers in Bhutan

by

Karma Tenzin B.Sc. University of Delhi, Sherubtse College (Tashigang, Bhutan), 2000

A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF

Master of Science

In the Graduate Academic Unit of Biology

Supervisor: Kelly Munkittrick, PhD, Canadian Rivers Institute, UNB Saint John

Examining Board: John Johnson, PhD, Biology, UNB Saint John - Chair Keith Dewar, PhD, Business, UNB Saint John

This thesis is accepted by the

Dean of Graduate Studies

THE UNIVERSITY OF NEW BRUNSWICK

March, 2006

© Karma Tenzin, 2006

ABSTRACT

Bhutan is a small country in the Himalayas that started modernization in the

1960s with a series of five-year plans focused on the sustainable use of renewable natural resources. The development of large-scale hydroelectric facilities and the lack of any existing data on fisheries resources have increased concerns about the river ecosystems. Any monitoring program needs to focus on non-lethal sampling protocols in keeping with Bhutanese cultural philosophy.

To test the hypothesis that growth in fish can be assessed using non-lethal sampling, 350 yellow perch (Perca flavescens) were collected from 10 sites on the Saint John River, NB, Canada. Growth rates were compared within and among sites using size at age, linear growth profile obtained through back- calculation, increments of growth at age, and size at a standard back-calculated age. The smallest size, lowest condition, oldest fish and slowest growth were observed at two reservoir sites (Tobique and Nackawic), and faster growth was observed at sites with nutrient inputs (Edmundston and Fredericton). The

Nackawic site has previously been identified as a site of concern, but this is the first study suggesting that the Tobique reservoir is impacted by stress. The techniques and experiences gained in the Saint John River Study permitted the designing of a relevant fish monitoring program suited for Bhutan. Data from

Bhutan were reviewed and factors affecting study design were taken into account with respect to selection of sentinel species, sampling sites, sampling

ii time and identification and selection of endpoints for assessment of river health and fish performance in Bhutan. The suggested program will monitor relative species abundances, growth rates, age distributions, and condition of fish. The designed framework will strengthen Bhutan’s capability to monitor and manage their fisheries resources during the next phase of development.

iii ACKNOWLEDGMENTS

I am very much indebted to great many people who helped me both professionally and personally in various ways and taught me a lot during the course of pursuing this degree. I owe much of what I achieved to all these people who took me through the right direction and helped me when I did not have the means to get there. I owe special thanks especially to my father Jochu

Dorji and mother Sherub Zangmo for always believing in me.

First and foremost I would like to thank my supervisor Dr. Kelly Munkittrick for everything he has done for me; I could never thank him enough. Every meeting with him has been greatly enriching and his support and advice invaluable. I have in many ways learnt a great deal about life from Kelly and you are truly my mentor. I am what I am, only due to your untiring push and pull throughout my uphill struggle. I could always recount on you and your family as my guardians during my stay in Canada. I found a home away from home in you and your family and I am very thankful to you and your family for taking care of me throughout my stay.

I would also like to thank Dr. Allen Curry and Dr. Deborah MacLatchy for agreeing to be my co-supervisors. I learned a lot as your student and I am always grateful for everything that was taught to me. I would like to thank Dr.

Deb MacLatchy for helping me with my admission to UNB, finding me a place to stay and picking me up at the airport when I first came to Canada and especially

iv for asking Kelly to be my supervisor. I would like to thank Dr. Allen Curry for all your kind assistance.

Much thanks goes to Dr. Brendan Galloway for taking me to the numerous field trips, I learned a lot about field research from you. The field trips were great learning experiences and through these trips I was able to see much of New

Brunswick. I am also grateful to Chad Doherty and Sandra Brasfield for taking me to field trips and teaching me about sampling on a lot of occasions. I would like to thank Mark Gautreau for going with me to sample. I gathered much of my field research experiences through Kelly Munkittrick, Lisa Peters, Brendan

Galloway, Chad Doherty, Sandra Brasfield, Mark Gautreau and Kirk Roach.

In no certain order I would like to thank: Kelly Munkittrick, Deb MacLatchy,

Allen Curry, Lisa Peters, Sandra Brasfield, Brendan Galloway, Steve Currie,

Michelle Gray, Jonathan Freedman, Genevieve Vallieres, Frank, Lottie Vallis,

Jennifer Peddle, Mark Gautreau, Karen Gormley, Eric Chernoff ,Jennifer Shaw,

Kirk Roach, Megan, my family, and many others for being kind and supportive towards me. If it would not have been you all, I would not have been here today.

Thank you all.

Last but not the least I would like to thank the Royal Government of

Bhutan, Ministry of Agriculture, Bhutan Trust Fund for Environmental

Conservation, and Royal Civil Service Commission for enabling me to pursue my degree. I am also very indebted to National Environment Commission and

Hydromet Services Division for giving me permission to use their data in this thesis.

v TABLE OF CONTENTS

ABSTRACT ...... ii ACKNOWLEDGMENTS...... iv TABLE OF CONTENTS ...... vi LIST OF TABLES...... viii LIST OF FIGURES ...... x CHAPTER 1 1 GENERAL INTRODUCTION...... 1 1 Overview ...... 1 1.1 Bhutan: Background Information ...... 2 1.2 Need for an Aquatic Effects Framework for Bhutan ...... 4 1.3 Hydropower in Bhutan...... 5 1.3.1 Impacts of Hydroelectric Dams ...... 8 1.3.2 Other Potential Impacts on Rivers of Bhutan...... 10 1.4 Design of Monitoring Studies ...... 12 1.4.1 Focus of Monitoring Studies...... 15 1.4.2 Non-lethal Sampling Methodology ...... 16 1.4.3 Back-calculating growth ...... 19 1.5 Statement of Problem ...... 20 1.6 Objectives and Outline of Thesis...... 21 CHAPTER 2 23 BACK-CALCULATIONS OF GROWTH OF YELLOW PERCH ALONG THE SAINT JOHN RIVER ...... 23 2 Introduction ...... 23 2.1 The Saint John River, New Brunswick ...... 24 2.1.1 Recent Studies - Saint John River...... 26 2.1.2 Hydroelectric dams on the Saint John River (history and location) ...... 30 2.1.3 Objective of this Chapter ...... 32 2.2 Materials and Methods ...... 33 2.2.1 Study Area – the upper Saint John River ...... 33 2.2.2 Sample Collection...... 36 2.2.3 Age Reading...... 38 2.3 Results ...... 41 2.3.1 Raw Fish Data ...... 42 2.3.2 Effects of Sex on Size of Perch ...... 46 2.3.3 Size-at-age comparisons...... 46 2.3.4 Length Frequency Data and Ford-Walford Plots...... 50 2.3.5 Back-Calculating Growth ...... 55 2.3.6 Weight Back-Calculation...... 63 2.4 Discussion...... 69 2.4.1 Relevance of the findings to Bhutan...... 74 CHAPTER 3 76 A FRAMEWORK FOR MONITORING FISH IN BHUTAN’S RIVERS ...... 76 3 Ecology of Bhutan’s Rivers Systems...... 76

vi 3.1 Designing the Framework: Ecosystem Definition...... 80 3.1.1 Physiographic Zones of Bhutan ...... 82 3.1.2 Climate...... 87 3.1.3 Hydrogeology...... 91 3.1.4 Physical Structure of Rivers ...... 97 3.1.5 Water Chemistry of Rivers ...... 98 3.1.6 Land Use...... 102 3.1.7 Dams and Reservoirs ...... 108 3.2 Factors Affecting Sampling Design...... 109 3.3 Site Selection...... 112 3.4 Selection of Sampling Design...... 113 3.4.1 Development of Methods and Approach ...... 117 3.4.2 Baseline Data for Reference Sites...... 118 3.4.3 Among River Reference Comparisons ...... 119 3.4.4 Altitudinal Reference Sites ...... 119 3.4.5 Longitudinal Comparisons of Developed Sites...... 120 3.5 Endpoint Selection...... 120 3.6 Selection of Sentinel Species ...... 125 3.6.1 Life History Characteristics of Native Species...... 130 3.6.2 Sample Size Requirements ...... 131 3.7 Final Study Design: A Fisheries Assessment Program for Bhutan 132 3.7.1 Schedule of Sampling ...... 132 3.7.2 Selection of Species ...... 134 3.7.3 Sampling Considerations...... 134 3.7.4 Monitoring Program...... 136 3.8 Conclusion...... 137 References...... 139 4 References...... 139 5 Appendix A ...... 153 Curriculum Vitae

vii LIST OF TABLES

Table 1-1 Mega hydropower stations power generation...... 7 Table 1-2 A comparison of stressor-based, effects-based and values- based approaches to environmental assessment (modified from Dubé and Munkittrick, 2001)...... 13 Table 1-3 Endpoints relevant for non-lethal evaluation of fish performance in an effects-based approach (modified from Environment Canada, 2005b)...... 19 Table 2-1 Fish community study sites, their characteristics and human impacts (from Curry & Munkittrick 2005) ...... 25 Table 2-2 Summary statistics for all perch captured. Data sharing an alphabetical letter are not statistically different (within a column)...... 44 Table 2-3 Length and weight data for perch used in back-calculation of length and weight respectively ...... 45 Table 2-4 Summary statistics for perch captured at St. Hilaire, Edmundston and Nackawic by sex. Values are mean ± SE (n), and values sharing an alphabetical superscript are not significantly different within a site ...... 47 Table 2-5 Regression table of length at age for all sites, and the rank of sites based on slope of the regression line...... 50 Table 2-6 Summary table of Ford-Walford plots for fork length (linear growth) at Edmundston (EDMN) and St. Hilaire (SHIL) by sex...... 51 Table 2-7 Scale width (mm) calculated using Ford-Walford plots (the plot was limited to age 1-5 fish) ...... 53 Table 2-8 Distance of annuli (mm) from origin derived from Ford- Walford plots at individual sites ...... 53 Table 2-9 Fork length at age increments (cm) derived from Ford- Walford plots ...... 54 Table 2-10 Summary table of Ford-Walford plots for fork length (linear growth) ...... 54 Table 2-11 Scale increments for Edmundston females (mm)...... 58 Table 2-12 Comparisons of year classes of males and females at St. Hilaire and Edmundston sites...... 59 Table 2-13 Back-calculated fork length at age (cm) ...... 64 Table 2-14 Number of fish aged per year class per site for the Saint John River sites. All fish were collected in 2001, except Nackawic, which includes fish captured in 2004, and Edmundston, which were collected in 2003...... 68 Table 2-15 Averages for four-year-olds at all sites ...... 68 Table 2-16 Summary of rankings of size or growth rates for yellow perch ... 70 Table 3-1 Discharge and runoff (source Baillie and Norbu, 2004) ...... 77

viii Table 3-2 Water quality tests for Wang chhu River System (NWWFCC, 2001) ...... 79 Table 3-3 Summary of fish species recorded in Bhutan (Petr, 1999) ...... 81 Table 3-4 List of Introduced fish species (Petr, 1999) ...... 82 Table 3-5 Physiographic zones within the North-South Valleys and Ridges of Bhutan (recreated from Norbu et al. 2003)...... 85 Table 3-6 Mean annual rainfall in Bhutan (modified from Baille and Norbu, 2004)...... 90 Table 3-7 Discharge and specific runoff from rivers during 2003 (source data from Hydrology Section, 2005) ...... 95 Table 3-8 Water quality survey 2003 by NEC (source data provided by NEC, 2005)...... 100 Table 3-9 Minerals and location of mines in Bhutan (compiled from USGS, 2006) ...... 105 Table 3-10 Influence of system characteristics on design for fisheries studies ...... 111 Table 3-11 Potential sites for development fisheries studies in Bhutan...... 114 Table 3-12 Potential stresses associated with hydroelectric development (created from Greig et al., 1992; CEA, 2001; DFO, 2005)...... 122 Table 3-13 Generalized response patterns of fish populations to changes in populations (from Munkittrick et al., 2000)...... 123 Table 3-14 Indicators that should be addressed in the monitoring program (adapted from Ribey et al., 2002)...... 126 Table 3-15 Sentinel species characteristics for optimizing effects-driven assessment of aquatic environmental health using fish populations (modified from Munkittrick et al., 2000) ...... 128 Table 3-16 Sample sites and schedule for studies on Bhutan’s rivers (refer to 2.16 for site locations),...... 133 Table 3-17 Recommended fish survey measurements to determine effects in fish growth, reproduction, condition and survival (adapted from Ribey et al., 2002) ...... 135 Table 5-1 Life-history characteristics for fish species of Bhutan: most information collected from Fishbase– www.fishbase.org and Petr, 1999 (* valid scientific name from Fishbase)...... 154 Table 5-2 Life-history characteristics for introduced fish species of Bhutan: most information collected from Fishbase– www.fishbase.org and Petr, 1999 (* valid scientific name from Fishbase)...... 157

ix LIST OF FIGURES

Figure 2-1 Map of the Saint John River basin (from Curry and Munkittrick 2005) ...... 28 Figure 2-2 Two year old fish (file: Edm_DS_F_2Yr_864) ...... 40 Figure 2-3 Two year old fish scale sample (file: Aroostook_023)...... 40 Figure 2-4 Fork length-at-age within sites for females and males at: (A) St. Hilaire (B) Edmundston ...... 48 Figure 2-5 Fork length-at-age among sites at Edmundston (EDMN) and St. Hilaire (SHIL): (A) Females (B) Males...... 48 Figure 2-6 Weight-at-age within sites for females and males at: (A) St. Hilaire (B) Edmundston ...... 49 Figure 2-7 Weight-at-age among sites at Edmundston (EDMN) and St. Hilaire (SHIL): (A) Females (B) Males ...... 49 Figure 2-8 Ford-Walford plot for fork length for Edmundston female yellow perch...... 52 Figure 2-9 Scale length at age comparison within site between males and females at: (A) Edmundston (B) St. Hilaire...... 56 Figure 2-10 Scale width at age comparison within site between males and females at: (A) Edmundston (B) St. Hilaire...... 56 Figure 2-11 Scale length at age comparison among sites at Edmundston (EDMN) and St. Hilaire (SHIL): (A) Females (B) Males ...... 57 Figure 2-12 Scale width at age comparison among sites at Edmundston (EDMN) and St. Hilaire (SHIL): (A) Females (B) Males ...... 57 Figure 2-13 Scale length to width ratio at age for male (A) and female (B) perch at Edmundston ...... 58 Figure 2-14 Comparison of average scale increment (Edmundston) versus Daily Temperature Unit (DTU) >10C for the year of hatching. Scale increment represents the average increment for 4-year-old fish for that year; temperature was obtained from temperature records from Mactaquac Fish Hatchery...... 60 Figure 2-15 Distance of annuli from origin for male (A) and female (B) perch at Edmundston ...... 61 Figure 2-16 Percent scale increment to total scale length for male (A) and female (B) perch at Edmundston...... 61 Figure 2-17 Scale growth profile for all sites back-calculated from Ford- Walford plots ...... 62 Figure 2-18 Fork length versus scale length for yellow perch from Saint John River ...... 65 Figure 2-19 Back-calculated fork length at age for yellow perch from the Saint John River ...... 65 Figure 2-20 Length increments at age derived from Ford-Walford plots...... 66 Figure 2-21 Back-calculated weight at scale length for yellow perch...... 66 Figure 2-22 Back-calculated weight at age for yellow perch...... 67 Figure 2-23 Weight increments at age derived from Ford-Walford plots...... 67

x Figure 2-24 Relative abundance of yellow perch as compared to other fish species at sites along the Saint John River (from Curry and Munkittrick, 2005) ...... 73 Figure 2-25 Fish species richness at sites along the upper Saint John River from upstream of the Canadian border at Moody Bridge to Fredericton (from Curry and Munkittrick, 2005)...... 73 Figure 3-1 Major river systems of Bhutan ...... 78 Figure 3-2 Provisional physiographic zonation of Bhutan (recreated from Norbu et al., 2003)...... 84 Figure 3-3 Geological map of Bhutan showing bedrock composition (sourced from Daniel et al. 2003) ...... 88 Figure 3-4 Average temperature and rainfall for the Lingmuteychu watershed, Bhutan (from RNRRC, 2002) ...... 89 Figure 3-5 Total annual rainfall in 2004 (source data from Hydrology Section, 2005) ...... 91 Figure 3-6 Topography map of Bhutan ...... 93 Figure 3-7 Examples of river gradients and physiographic profiles in Bhutan (modified from Norbu et al., 2003)...... 94 Figure 3-8 Location of river flow data collection stations (source data from Hydrology Section, 2005) ...... 96 Figure 3-9 Flow comparisons among the hydrological monitoring stations (source data from Hydrology Section, 2005). Letters on x axis refer to the stations in Figure 3-8...... 96 Figure 3-10 Water quality survey 2003 by NEC (source data provided by NEC, 2005): (A) Calcium (B) Magnesium (C) Silicon Oxide (D) Total hardness (Calcium Carbonate)...... 101 Figure 3-11 Land use of Bhutan (from Karan, 1987) ...... 102 Figure 3-12 Protected Areas of Bhutan (recreated from DOE, 2004) ...... 104 Figure 3-13 Map of Bhutan with location of industries, mines, sewage treatment plants, dams, major towns, water sampling stations, roads and rivers ...... 107 Figure 3-14 River systems of Bhutan with location of large hydropower development sites (includes existing developed sites and future planned development to 2023)...... 110 Figure 3-15 Proposed fish sampling sites and location of current and proposed development ...... 116

xi CHAPTER 1

GENERAL INTRODUCTION

1 Overview

Bhutan is a small, pristine country with little industrial development, located in the Himalayan Mountains. Bhutan started modernization in the 1960s with a series of five-year plans focused on the sustainable use of the natural resources. Watershed management will provide the foundation for development.

At the same time Bhutan is undertaking a number of large hydropower initiatives that will impact most of the major river systems in the country. The lack of any existing monitoring program or any data on existing fish populations have increased concerns about the fishery resources. There is an increasing interest in understanding the impacts of development on the river ecosystems, but it has been difficult due to lack of scientific data available on the fish communities and the rivers within Bhutan (Rajbanshi and Csavas, 1982).

There have been a few studies on Bhutan’s rivers that have been focused on the establishment of aquaculture facilities along the southern foothills of

Bhutan near the Indian border. These studies documented 41 fish species in the warmwater rivers and lakes (Dubey, 1978; Petr, 1999), but there have been no studies conducted in the cooler water systems where most of the hydroelectric development will take place. The development of a fish monitoring program for rivers in Bhutan is further complicated by the lack of available personnel trained to conduct such studies. There is also the added factor that few people will be interested to pursue such studies if it involves sacrificing a large number of

1 fishes for research purposes. It is a sentiment among the Bhutanese population to avoid unnecessary killing of animals.

The main objective of this thesis was to develop a framework for a fish monitoring program that would be usable in Bhutan. The current scenario in

Bhutan means that the most suitable method would be adapting non-lethal techniques for field research purposes. Such a program would require the sacrifice of few, if any, fish to get the required data. Non-lethal techniques have the added advantage of heeding to conservation principles, which Bhutan holds very high in its development principles.

Initial field work was conducted on the Saint John River, New Brunswick,

Canada, to develop the techniques to be used for non-lethally assessing the growth and health of fish populations. The Saint John River study focused on assessing differences among populations of yellow perch (Perca flavescens) from upstream and downstream sites near a series of hydroelectric dams along the Saint John River. A comparison was conducted among a variety of methods to examine the growth rates of fish, applicable to a monitoring program for the rivers of Bhutan.

1.1 Bhutan: Background Information

Bhutan is bordered by China in the north and India in the south, east and west. It has a total surface area of 46,500 km2, a population of 672,425 (OCC,

2005), and an annual growth rate of 2.5% (NSB, 2004). Agriculture is the main occupation of Bhutanese people, with 69.1% of the population living in rural

2 agricultural areas and 30.9% in urban areas (OCC, 2005). The majority of the population are followers of Mahayana Buddhism. Buddhism has influenced the

Bhutanese outlook in every aspect of life. Many Buddhist beliefs are pro- environmental in nature. This results in high compliance in implementing the government’s policy towards environmental conservation.

Bhutan started on the path of modern development with phased five-year plans, which have a major goal of developing the country through the sustainable use of natural resources. The plans place particular importance on the conservation of natural resources and preservation and promotion of cultural heritage. The development goal of Bhutan has further been refined in the concept of Gross National Happiness, conceptualised by His Majesty the King of Bhutan.

In recent years, the government has given much impetus to achieving its goal of Gross National Happiness. Three policy strategies were identified to achieve this goal (DOP, 1999): a) the protection and conservation of the environment through sustainable use of its renewable natural resources, b) the preservation and promotion of its rich and unique cultural heritage, and c) the promotion of good governance through efficiency, transparency and accountability. The three strategies stand out as Bhutan’s pillars of existence and as an example to the world at large. With these priorities, the government has framed policies based on principles of the middle path to development

(NEC, 1998), wherein it strives to achieve maximum development without compromising its natural resources and cultural heritage. These policies have

3 proved to be valuable in bringing Bhutan to the front line in terms of its richness in biological diversity and cultural heritage and in its efforts for conservation of these rich resources.

1.2 Need for an Aquatic Effects Framework for Bhutan

Bhutan has an abundant supply of water resources in most parts of the country and they play an important role in development. Water has been used in

Bhutan for agriculture, drinking, domestic and industrial uses, and for generation of hydroelectricity. Increased land use and development of industries, construction and urban settlements, agriculture, forestry and mining results in a growing number of adverse effects to the existing water bodies. The effects are in the form of point and non-point sources of pollution, increasing sediment load due to erosion, and inputs from mining sites.

The development of water resources to harness electricity contributes one of the most significant impacts. These developments undermine the water quality and cause impacts on the health of the ecosystem. These effects cannot be

(understood or mitigated if baseline data is not available) if early studies are not initiated; in time the impacts could lead to degradation of the available water quality. It is, therefore, necessary to develop proper study designs to assess the health of these water bodies for management strategies.

Water quality assessments can be conducted in many ways. Some assessments carried out in the past in Bhutan were based solely on measuring physical characteristics and water chemistry. These assessments are not able to detect stress present in the ecological systems and water quality criteria for

4 chemicals have not been defined for Bhutan’s rivers. Furthermore, there can be ecological consequences of hydroelectric developments without dramatically altering water chemistry (Greig et al., 1992).

The purpose of this document will be to develop guidelines for a framework for future fish monitoring programs in Bhutan. Bhutan has stated that watershed management is the single most important strategy to maintain the resource base needed to support its national economy (Bhutan 2020 document; DOP,

1999). The use of fish has been a common choice for assessment of impacts on water bodies in many research studies around the world and has been shown to be effective in indicating the presence of stress in the system. The current lack of any efficient methods for monitoring the water bodies and lack of any database on existing fish populations makes a compelling argument to begin studying the fishery resources in the country. As in most studies, it is necessary to collect data that can correctly identify the health of the system and that can be used in monitoring studies. Any fishery monitoring program will operate out of the Ministry of Agriculture, but will require the cooperation of various government departments associated with land use, hydrological monitoring and industrial development.

1.3 Hydropower in Bhutan

The high gradient of the mountain river systems has endowed Bhutan with enormous potential for hydropower development. Hydroelectricity is the cleanest source of large-scale energy production in Bhutan and the power sector has

5 been the major revenue earner for the country since the commissioning of the first hydropower project at Chukha (336 MW) in 1986. The development of hydropower is guided by the Hydropower Development Master Plan (1990-

2010) and aims to harness 20,000 MW of power by the end of the 10th Five

Year Plan (2012) and 25,000 MW of power by the end of the 11th Five Year

Plan (2017) (DOP, 1999). Currently, four mega hydro projects remain commissioned: Chukha, Baso chhu Phase I, Kuri chhu and Baso chhu Phase 2, with a total generation capacity of 460 MW (Table 1-1).

Though the current development represents only 1.5% of the estimated

30,000 MW potential (DOP, 2002), power generation remains the major contributor to the country’s external revenue earnings. The soon to be commissioned Tala Hydro Power Station (2006) has a generation capacity

(1020 MW) that exceeds the combined power output of the four previous mega projects. It is expected to boost the country’s development with unprecedented economic earnings and accelerate development projects in Bhutan.

The construction of power projects not only produces electricity for export, but also enhances other avenues of development, and provides Bhutan with the much needed cheap source of power for industrialization. The Kuri chhu power station was constructed to allow the establishment of two other mega projects, the Dungsam Cement Project in Nganglam and the Ferro Silicon Project in

Matanga. These projects are expected to consume 25 MW and 20 MW, respectively, of the 60 MW generated. The remaining 15 MW will be distributed for supply to the six eastern Dzongkhags (Districts) and will also supplement the

6 Table 1-1 Mega hydropower stations power generation Hydro Power Power River Project State Other details Stations Output (MW) *Chukha 336 Wang chhu *Commissioned 1986 First Mega Hydro Project *Baso chhu Phase I 24 Baso chhu *Commissioned 2002 Run-of-the-river *Baso chhu Phase 40 Tailrace from Baso *Commissioned 2004 73,000 m3 water storage II chhu I + Ruri chhu *Kuri chhu 60 Kuri chhu *Commissioned 2002 15.7 million m3 water storage Tala 1020 Wang chhu Completion in 2006 Puna Tsang chhu 1002 Puna Tsang chhu **Planned Completion 2011 4.9 million m3 water storage Mangde chhu 670 Mangde chhu **Planned Completion 2013 1.1 million m3 water storage Puna Tsang chhu II 992 Puna Tsang chhu **Planned completion 2015 5.2 million m3 water storage Chamkhar chhu 671 Chamkhar chhu **Planned Completion 2019 1.8 million m3 water storage Chamkhar chhu 568 Chamkhar chhu **Planned Completion 2022 1.6 million m3 water storage 7 Kholong chhu 486 Kholong chhu **Planned Completion 2023 1.4 million m3 water storage Amo chhu 499 Amo chhu **Planned Feasibility Study 2010 2.4 million m3 water storage Chukha II 500 Wang chhu Sunkosh 4060 Puna Tsang Chhu at Study completed Dam 1: power generation Multipurpose Sarbang Dam 2: 141 KM Irrigation Project Canal Digala 670 Proposed study during 9th Plan Shemgang Shingkhar 570 Khoma chhu 326 Nika chhu 210 Rothpashong 401 Kuri chhu Bunagu 180 Proposed study during 9th Plan

(* Currently Operational, ** Power System Master Plan –Bhutan 2003-2022)

western power grid. In view of the value of the power projects, additional projects have been identified as the main avenue for future development.

Furthermore, the potential for development of aquaculture at the dam sites is currently being examined.

The development of hydropower proves beneficial to the South Asian region as a whole. The current projects export almost 90% of the generated power to

India, thus reducing the immediate need for India to finance coal and nuclear generating plants. This way it effectively checks the release of large amounts of greenhouse gases, which might otherwise have resulted from such power plants. The building of dams is further seen as an effective means of flood control downstream of the dams and the Indian plains during the monsoons. It is also anticipated that the development will lead to the development of irrigation systems by using canals from the dams.

1.3.1 Impacts of Hydroelectric Dams

Hydroelectric dams can impact a river system in a number of ways. There are two main types of hydroelectric facilities, the run-of-the-river station type and the peaking station. The run-of-the-river station generates electricity by letting water pass through turbines without blocking the flow of the river, so the river continuum is maintained. The peaking station blocks the river and stores a large amount of water above the dam to release water regularly to generate electricity. The different types of operation impact river systems differently. The peaking stations tend to have more impact than do the run-of-the-river stations

8 which have localised impact (Greig et al., 1992). Most dams in Bhutan are a combination of both types.

The initial effects on river ecosystems would invariably be caused during the construction of the dam. The effects during construction would include a large amount of erosion and sedimentation due to the clearing of forests, the movement of large amounts of earth and construction materials, the paving of access roads, and the diversion of water flow for construction downstream

(Greig et al., 1992). A peaking station progressively starts flooding a large amount of land upstream, changing the ecosystem from terrestrial to aquatic.

The flooding of land upriver with increasing depth causes associated changes in thermal regime (Greig et al., 1992). In comparison, decreasing and fluctuating water levels would be observed downstream with associated changes in thermal regimes (Greig et al., 1992). The sediment-free water released from peaking stations also causes higher erosion downstream, potentially resulting in destruction of fish habitat (Greig et al., 1992). The sporadic release of water from peaking stations also results in high mortality of fish eggs and younglings downstream (Greig et al., 1992). The regulation of water flow also results in more turbulence causing destruction of habitat and food sources downstream.

There have been specific cases where poor management and operational strategies of dams have led to extinction of particular fish species from a river system (Penczak et al., 1998). The existence of a dam on a river results in the modification of the river’s physical, chemical and biological attributes (Duthie and Ostrofsky, 1975; Kanehl and Lyons, 1997; Penczak et al., 1998;

9 Schmetterling and McEvoy, 2000; Gido et al., 2002; Greig et al., 1992) and this causes wide changes in the response of fish and an overall change in community structure of fish (Munkittrick et al., 2000; Jager et al., 2001; Gido et al., 2002). The construction of dams breaks the continuity of the river and blocks the migratory route of fishes to their spawning habitats (Penczack et al., 1998;

Schmetterling and McEvoy, 2000), and also affects the spawning sites downstream due to their operations (Panczack et al., 1998; Hanna et al., 1999).

Fish blocked off from their spawning habitat by dams were reported to be reabsorbing their eggs (Schmetterling and McEvoy, 2000), raising concerns about the persistence of the species concerned.

In a peaking station the response to a dam can be seen in the fish community changing from a river-based environment to an ecosystem that resembles a lake (lacustrine) (Greig et al., 1992). The study of impacts of hydroelectric dams is important in evaluating the extent of their effects on fishes, other than those effects caused by discharge of effluents (Munkittrick et al.,

2000). There is a need to achieve greater understanding of the impacts of dams on the river ecosystem to come up with proper mitigation measures (Efford,

1975; Schmetterling and McEvoy, 2000).

1.3.2 Other Potential Impacts on Rivers of Bhutan

Bhutan is a mountainous country with few flatlands available for settlement, putting lots of pressure on the narrow river valleys for urban settlement and agricultural farmlands. The population growth in these river valleys has led to

10 the loss of riparian zones for the adjacent water bodies. This trend is most noticeable in Thimphu, the capital city of Bhutan, located at the headwaters of

Wang chhu (river). The location of industrial estates within the municipal boundary further compounds the problem as the industrial runoff ends up in the river along with non-point sources of pollution. The government does have regulations which prohibit the input of industrial inputs into rivers and streams.

However, this regulation has seen little success in implementation due to constraints in the number of personnel available for enforcement (NWFCC,

2001).

There are two large wastewater sewage treatment plants in Bhutan. The treatment plant at Thimphu (population of 27,000) discharges its effluent into

Wang chhu and has a fecal coliform count of 1500FC/100ml (Charlton, 1997).

The other plant discharges into Amo chhu at Pheuntsholing (population of

12,000) and the effluent is calculated to contain 55FC/100ml (Charlton, 1997).

These are two visible point sources of effluent in Bhutan and with the development of other townships there will be the development of more sewage plants.

The establishment of large manufacturing industries, quarrying of stones and sand, mining and construction has also added stress to the rivers through various types of effluents. Although the effects of these point and non-point sources of effluents on the biota of affected rivers have been studied and known in many developed countries, effects have not been studied in Bhutan. It is vital that studies be conducted to establish baseline data of changes that might be

11 stressing the river systems at this early stage of development. Specific management plans to mitigate the causes of these effects can then be implemented.

1.4 Design of Monitoring Studies

Although there have been concerns about the environmental consequences of development for several decades, the assessment methodologies for predicting, mitigating, and assessing impacts have varied considerably (SCS,

2000). There are three main strategies to assessing or monitoring environmental impacts: stressor-based, values-based, and effects-based (Table

1-2). In a stressor-based monitoring program, the stressors (such as sedimentation, thermal change or altered flow) are defined based on the development and linked to probable impacts on identified Valued Ecosystem

Components (VEC) through the construction of theoretical stress-response pathways (Dubé and Munkittrick, 2001). The probable impacts are evaluated and used to identify potentially significant stressors to develop potential mitigation measures. For a hydroelectric development, a stressor-based assessment would focus (for example) on identifying the impacts of changes in flow on spawning migrations of fish (Grieg et al., 1992).

This approach may prove to be successful in systems exposed to a single stressor but proves difficult when examining a complex system with multiple stressors (Munkittrick et al., 2000). Stressor-based monitoring fails to detect

12 effects of subtle stressors which might already be present in the system before any development has taken place.

Table 1-2 A comparison of stressor-based, effects-based and values-based approaches to environmental assessment (modified from Dubé and Munkittrick, 2001)

Stressor Effects Values Focus Stressor-response Performance Ecosystem uses or pathways and indicators of benefits valued ecosystem ecosystem status components Boundaries Related to Related to Related to human development biological uses components Use of existing data Library searches Field studies Use and opinion surveys Follow-up Traditionally very little Ongoing monitoring Opinion surveys requirements and adaptive management Advantages Are often based on Site-specific focus Focused on user previous assessments and experience Disadvantages Ignores unidentified Time and expense Not based on interactions and of baseline ecosystem cumulative effects monitoring properties or responses Question How do I mitigate What are the How do I protect potentially important factors that are the uses that are impacts? limiting energy important? flow?

A values-based assessment involves active participation of community stakeholders in an assessment of the value of potential development, or of a potential resource worth protecting. This approach is the main approach that has been used to date in Bhutan. The value of the hydroelectric power

13 development has been the main focus, in terms of export potential, and in terms of driving other potential developments. A values-based approach does not usually focus on determining ecosystem-level impacts. Since the fishery value in Bhutanese rivers is low, and the value of the electricity has been high, the focus has been on the development of the hydroelectric potential.

In an effects-based monitoring program, the performance of the system is identified as the unit for protection. In the absence of a hydroelectric development, there are environmental constraints on the performance of the system. The effects-based approach seeks to focus on the limiting factors, and utilize them to drive the risk assessment process (Munkittrick et al., 2000; Dubé and Munkittrick, 2001). There no current understanding of the health of Bhutan’s rivers, or an adequate understanding of their ecology that can be used to drive an effects-based assessment. The main advantage of an effects-based approach, within the context of developing a monitoring program for Bhutan, is that it allows an iterative development of baseline information on the ecology of the system.

Several critical data gaps (Munkittrick et al., 2000) will challenge the development of an effects-based approach in Bhutan, including an inadequate understanding of the natural variability of performance indicators and concerns about reference sites. A standardized and easy to apply assessment framework is needed that will determine whether future development will adversely affect a system (Dubé and Munkittrick, 2001). In Canada, the effects-based approach has been used to develop the Environmental Effects Monitoring (EEM)

14 requirements for pulp and paper mills (Walker et al., 2002), metal mines (Ribey et al., 2002) and sewage treatment outfalls (Kilgour et al., 2005). It is applicable to situations with hydroelectric development (Munkittrick et al., 2000), and can be adapted to help develop an assessment framework for Bhutan’s river systems.

The sequential steps in the effects-based approach are to define the geographical limitations of the study, develop the key performance indicators of the system, develop the performance assessment, and identify the impaired aspects, the limiting factors and the critical stressors (Munkittrick et al., 2000).

Effects-driven approaches will drive the collection of focused baseline data prior to the construction of new facilities, and more widespread adoption of post- development monitoring programs (Dubé and Munkittrick, 2001). The existence of baseline data providing information on the growth, reproductive performance and survival of organisms, and on stressors limiting the performance of the system will make prediction and risk assessments more accurate.

1.4.1 Focus of Monitoring Studies

It is possible to define indicators at multiple levels of organization

(physiological, individual, population and community) and at multiple ecological levels (bacterial, algal, invertebrate, fish, etc). The monitoring program of interest to Bhutan is related to a fisheries assessment, so it is not necessary at this time to deal further with other taxonomic levels. However, it is important to

15 remember that other levels of organization can provide valuable information

(Munkittrick et al., 2000).

As far as the level of organization is concerned, there are compromises between measures with a rapid response time (physiological) and those with ecological relevance (population, community); between responses that are easy to reverse (physiological) and those that are difficult (community); and between those that are easy to link to the cause of changes (physiological, chemical) and those that are relevant to stakeholders (population) (Munkittrick et al., 2000).

The Canadian EEM program operates at the individual/population level as a compromise to these trade-offs, and this is probably most relevant to the situation in Bhutan. Physiological measurements will be difficult due to the isolation of many field areas and equipment limitations. Community measures will be difficult in large, high gradient rivers, especially when there is no baseline of data against which to judge. The most promising approach is an iterative, sentinel-species driven approach to develop the baseline data, focusing on the individual/population level endpoints.

1.4.2 Non-lethal Sampling Methodology

Study designs for fish surveys have been evolving over the past few years, and there has been increased emphasis on the use of small-bodied fish species

(Munkittrick et al., 2000). Fish resident in a system can be naturally stressed before any additional changes, which result in additional stress, are made to the system. This requires any assessment to take into consideration the initial

16 performance of fish populations in the system (Munkittrick et al., 2000).

Changes in performance of fish populations can be assessed by measuring endpoints such as maturity, lifespan, age-specific mortality rates, recruitment, growth rates and abundance (Ruemper, 1998). Endpoints which are critical to assessing the impacts of stressors include estimates of age distributions and indicators of energy use and energy storage (Munkittrick et al., 2000). Recent attention has focused on developing non-lethal approaches for collecting these types of data for environmental assessments (Gray et al., 2002, Environment

Canada, 2005b). These kinds of data will be critical for developing baseline data on fish populations in Bhutan’s river systems. As opposed to large lethal sampling applied in traditional assessment methods (Munkittrick et al., 2000), the application of non-lethal assessment of populations (as in Gray et al., 2002;

Environment Canada, 2005b) can be seen as a better alternative in light of its adherence to Bhutan’s conservation principles and cultural sensitivity to lethal sampling.

The most important endpoints are those reflecting information on growth, reproduction, energy storage and survival (Environment Canada, 2005a) (Table

1-3). Non-lethal information on condition and length frequencies are relatively straightforward, and are a function of the number of individuals sampled.

Reproductive information, in terms of non-lethal data, will be dependent on the collection method and timing, and will vary with the species being examined. In many cases, these methods will need to be developed site-specifically once more information is available on the life history of Bhutanese fishes. Once this

17 information has been developed, a standardized approach to estimate abundance or density will be possible. The initial information needed to evaluate species suitability will be related to relative abundance, life history and longevity. Obviously, there will be significant differences in sampling programs to evaluate fish that live for a single year, for three years, or for several decades.

The initial information that needs to be developed is associated with relative abundance, distribution, age distributions, and growth rates of fishes in the rivers of Bhutan. Comparing the distributions of ages of fish in a population can be conducted through direct measurement of the ages of fish by enumerating growth zones in calcified tissues, or indirectly by assessing size-frequency plots

(Gray et al., 2002). The most commonly used method is the analysis of the growth zones found in otoliths (inner ear bones), external scales, fin rays, vertebrae, or cheek bones such as the cleithrum or operculum (Bagenal and

Tesch, 1978). With the exception of fin rays and scales, the removal of aging structures is lethal.

Scales can be read relatively accurately during the early years in most species, however, reliability diminishes near maturity in the majority of species

(Beamish and McFarlane, 1987). The accuracy of aging based on these structures depends on a variety of factors including the presence of distinct growth seasons (as experienced by most northern and temperate species), proper storage and preparation of tissues and structures, and validation of the particular method. In most species, internal bony tissues are the most accurate

18 aging tissue, though methods can be age- and species-specific (Beamish and

McFarlane, 1987).

Table 1-3 Endpoints relevant for non-lethal evaluation of fish performance in an effects-based approach (modified from Environment Canada, 2005b).

Endpoint Non-destructive Growth Size (length and weight) of young-of year (Age 0) at end of growth period Size of 1+ fish Size at age (if possible) Reproduction Relative abundance of young-of-the year (% composition of young of year) Young-of-year survival Condition Body weight relative to length (k)x Survival Length:frequency distribution Age frequency distribution (if possible)

Growth can be measured through a variety of methods, including size distributions and incremental analysis, size-at-age, tracking of a cohort over time, biochemical methods, and back-calculation. The focus of this study is to evaluate methodologies for back-calculating growth, within the context of developing a fisheries monitoring program for rivers in Bhutan.

1.4.3 Back-calculating growth

Back-calculation of fish growth with the use of scales or bony structures is seen to have wide potential in its application to ecological studies. Fish scales

19 give important information regarding fish size at different ages by back- calculation (Johal et al., 2001). In general, the annuli on an aging structurse are marked, and the distances between annuli are proportional indicators of the relative growth of a fish during different periods of its life history.

Horppila et al. (1999) examined three hypotheses regarding back-calculation of fish growth. They concluded that the body proportional hypothesis gives the most reliable estimate for back-calculated age for roach as compared with the scale proportional hypothesis and the Fraser-Lee method. It is anticipated that the use of any method, if used consistently to back-calculate age, will not affect the results (i.e., detection of differences in performance of fish between reference and exposed sites).

Major variations in environmental conditions influence the formation of annuli on scales of fish and consequently scales are shown to be accurate in predicting life history characteristics (Fabré et al., 1998; Machias et al., 1998).

Information on growth rates obtained can be used to detect differences between upstream and downstream sites of dams.

1.5 Statement of Problem

The lack of any information regarding the extent of stress on a river system undermines understanding the impacts of continued development on the health of the river ecosystem. The recognition of the carrying capacity due to existing natural stressors of a river system is important in assessing the extent of stress that can be incurred due to development activities (Munkittrick et al., 2000).

20 Information that can help establish the amount of development that can take place without significantly degrading the river system can support good management strategies for the river system.

Information on the health and growth of existing populations of fish in a system can yield important information regarding carrying capacity of the system. Since no background information on fish exists for rivers of Bhutan regarding the carrying capacity of its rivers, it is important to begin such studies before more development takes place. Immediate attention must be given to gathering information regarding existing fish populations. The present study on the Saint John River is to specifically design a non-lethal sampling protocol suitable to the Bhutanese scenario in order to develop information for a fisheries assessment.

1.6 Objectives and Outline of Thesis

The primary objective of the thesis is to develop a framework for a fish monitoring program for Bhutan that can be used to evaluate potential impacts of hydroelectric development on Bhutan’s river systems. This objective will be developed by determining a protocol for back-calculating fish growth rates using fishes of the Saint John River that can be applied to help manage Bhutan’s fisheries and maintain river quality.

The specific objectives are:

21 1. Define the factors that need to be considered in developing a species-

specific growth profile, and develop a sampling strategy for yellow

perch (Perca flavescens) in the Saint John River.

2. Determine the performance of fish upstream and downstream of dams

along the Saint John River system.

3. Develop a protocol that could be transferred to monitor the status of

fish populations in Bhutan (based on Munkittrick et al., 2000).

The thesis is arranged into three chapters. After this introductory chapter,

Chapter 2 describes the development of the data, and evaluation of growth of yellow perch in the Saint John River, Chapter 3 examines the relevant data available for Bhutan, and describes a framework for initiating a fisheries assessment project for Bhutan’s rivers. A final discussion makes some recommendations about the best path forward.

22 CHAPTER 2

BACK-CALCULATIONS OF GROWTH OF YELLOW PERCH ALONG THE

SAINT JOHN RIVER

2 Introduction

There is a need to evaluate different methodologies for non-lethally determining growth in fish to focus the monitoring program and framework for

Bhutan. Therefore, evaluation was undertaken using fish collected from the

Saint John River, New Brunswick, Canada, along a continuum of development that includes a series of hydroelectric dams. As mentioned in earlier chapters, it is expected that hydroelectric dams will influence fish distributions, abundance and performance. The growth of fish is an output related to factors including the availability, quality and quantity of food, and can be influenced by other energy outputs, including reproductive development and movement (Munkittrick et al.,

2000).

There are a number of ways to examine size of fish that will be important to evaluate for a non-lethal sampling program: the size of fish captured, the size-at age, the length-frequency and age-frequency distributions, Ford-Walford plots to estimate maximum length, back-calculations of the rates of fish growth, and the average back-calculated size of fish at a pre-determined age. Each of these will be examined to determine the differences in information that can be obtained and to evaluate the relative strengths and weaknesses of different approaches.

This is important for understanding the relative strengths of information that will

23 be obtained through a non-lethal sampling program. The focus of this part of the thesis is to describe a protocol which will minimize variability while increasing the power by using back-calculation methods for assessment.

2.1 The Saint John River, New Brunswick

The Saint John River is a 7th order river (river order reflects the relative size and complexity of a river basin) and runs a length of 700 km from its head waters to the Bay of Fundy and has a mean annual discharge of 1110 m3/s

(Curry and Munkittrick, 2005; Munkittrick et al., 2005). It has a vertical descent of 481 m from head waters to the mouth at the Bay of Fundy (Munkittrick et al.,

2005). The Saint John River Basin covers 55,000 km2 (Curry and Munkittrick,

2005; Munkittrick et al., 2005). It runs approximately 50 km through Northern

Maine in the United States and then flows through the province of Quebec and

New Brunswick in Canada to drain into the Bay of Fundy at Reversing Falls,

Saint John (Munkittrick et al., 2005).

It is a highly impacted river with numerous stressors along major part of its length (Table 2-1) (Curry and Munkittrick, 2005). The Saint John River is impacted due to effluents from pulp mills, wastewater sewage treatment plants, and other industrial discharges. These effluents were shown to have adverse effects on fish populations in other river systems (Munkittrick et al., 2000). Many studies have been either completed or undertaken recently to understand the river’s assimilative capacity (capacity to absorb wastes) in view of the developments taking place. By understanding the extent to which the river can

24 Table 2-1 Fish community study sites, their characteristics and human impacts (from Curry & Munkittrick 2005)

Location Elevation Site Type Stressors Comments (km upstream) (m a.s.l.) Priestly, Main stem Forestry, recreation >475 – 625 338 Moody Bridge Baker Brook Main stem Sewage, poultry processing 447 295 Edmundston Main stem Pulp mill, paper mill, sewage treatment plants, piggeries 420 136

Grand Falls Main stem Potato agriculture, potato processing Hydroelectric dam, no 360 135 (reservoir) fish passage

Tobique Tribut ary Forestry Hydroelectric dam, 325 100 (reservoir) with fish passage Aroostook Main stem Potato farming and processing, sewage treatment Hydroelectric dam no 329 80

25 facilities, de - commissioned air force base. fish passage

Florenceville Main stem Two food processing plants, potato farming, and sewage Hydroelectric dam 275 55 treatment facilities

Hartland Main stem Presque Isle tributary has starch production industries 255 50 and potato production fields

Woodstock Main stem Large municipal sewage tre atment facility, intense potato The head of the 233 48 production, Meduxnekeag River drains urban and potato flooded reservoir production created by the Mactaquac Hydroelectric Dam Nackawic Main stem Pulp mill 185 45 (reservoir)

Fredericton Main stem Downstream of the 135 9 Mactaquac Dam, no fish passage *m. a. s. l. – meters above sea level withstand development (assimilative capacity), we can maintain its water quality and protect the aquatic ecosystem (Munkittrick et al., 2005).

2.1.1 Recent Studies - Saint John River

There have been a variety of recent studies taking place on the Saint John

River, including the upper (Culp et al., 2003; Galloway et al., 2003; Flanagan

2003; Gray et al., 2005; Curry and Munkittrick, 2005) and middle basins

(Doherty et al., 2004; Luiker et al., 2004, 2005), and at the river mouth (Dubé and MacLatchy, 2000, 2001; Vallis et al., 2006; Vallieres et al., 2006). There are concerns about the continuing impacts of nutrients from industry and municipal outfalls, and the impacts of agriculture and food processing plants in the upper basin, although the situation is improving (Cunjak and Newbury,

2004).

Studies on the Saint John River included the investigation of effects of pulp and paper mill effluents (Galloway et al., 2003), agricultural inputs (Gray et al.,

2002), and sewage effluents (Doherty et al., 2004) on fish communities. The studies involved use of both lethal (Doherty et al., 2004; Galloway et al., 2003) and non-lethal (Gray et al., 2002) techniques to access the effects of effluents on fish populations (Munkittrick et al., 2005) and communities (Curry and

Munkittrick, 2005). There are a variety of changes in the fish community in the middle reaches of the river associated with the presence of large hydroelectric dams (Curry and Munkittrick, 2005). These dams offer no fish passage upstream.

26 Curry and Munkittrick (2005) compared the fish community at 12 sites across

300 km of the upper basin, and found that relatively few fish species were sufficiently widespread; only 3/21 species were found at 10 or more sites along the river – white sucker (Catostomus commersoni), common shiner (Luxilus cornutus) and yellow perch (Perca flavescens).

Galloway et al. (2003, 2004) evaluated the performance of fish in the

Edmundston reach of the river, sampling fish from the Canadian border downstream to Riviere Vert (approximately 40 km upstream of Grand Falls)

(Figure 2-1). Several fish species were used in this part of the river, including white sucker, yellow perch, slimy sculpin (Cottus cognatus) and blacknose dace

(Rhinichthys atratulus). The study focused on the potential impacts near

Edmundston, where there is a pulp mill, a paper mill, multiple sewage outfalls and inputs from farming and a food processing plant. Additional studies examine the relative inputs of the sewage and pulp mill effluents on invertebrates (Culp et al., 2003), and potential responses of fathead minnow

(Pimephales promelas) to concentrations of effluent higher than those found in the river.

Among the field studies using fish, white sucker were not found to be sensitive to point source shoreline discharges in this section of the river, probably because water column mixing is relatively poor and they stay towards the middle of the river. This species has been widely used in other studies on other rivers (Munkittrick et al., 2002). Slimy sculpin have been shown to have a

27 N r e iv R e c n re Edmundston w a Tobique River L Baker t. S Brook

Grand Falls Aroostook

C E B Caribou E U Priestly Aroostook Dam NEW BRUNSWICK Q Tobique Presque Beechwood Dam Isle Moody Aroostook Florenceville Bridge River Hartland

Nackawic Fredericton MAINE

SAINT JOHN RIVER Woodstock DRAINAGE BASIN Mactaquac Watershed boundary Dam Sample site Large Urban 100 km Saint Dam John BayBAY of of FundyFUNDY

Figure 2-1 Map of the Saint John River basin (from Curry and Munkittrick 2005)

very small home range (Gray et al., 2002; Cunjak et al., 2005) and respond strongly to effluent inputs (Galloway et al., 2003, 2004). However, this species was only found in large numbers in the upper river basin (above Grand Falls;

Curry and Munkittrick, 2005) and in tributaries (Gray et al., 2005). The yellow perch did show some responses (Galloway et al., 2004) and has previously

28 been used as an indicator species in this part of the river (BAR, 1996) and elsewhere (McMaster et al., 2002).

Further downstream, Doherty et al. (2005) evaluated white sucker in the vicinity of Florenceville and Woodstock. This study was initiated because the fish community surveys (Curry and Munkittrick, 2005) had identified lesions on white sucker in the upper portion of this reach of the river. Radiotracking of the white sucker showed that outside of the spawning season, the home range was relatively small for this species in this part of the river (Doherty et al., submitted).

The fish showed the largest size and condition near the upstream part of this reach at Florenceville (Doherty et al., 2005). This area is immediately downstream of the Beechwood hydroelectric dam. Daily water level fluctuations resulting from upstream dam discharge may change habitat availability and/or diversity, thereby altering the fish community (Doherty et al., 2005). The area is also adjacent to a large potato processing plant that has been associated with significant nutrient inputs to the river (Luiker et al., 2004, 2005).

Freedman (2005) evaluated the fish community in the Nackawic reach of the river to determine mobility and potential suitability of species as sentinels over small distances. His study was associated with the pulp mill and sewage discharges of the town of Nackawic, and his analyses of stable isotopes of carbon and nitrogen suggested that yellow perch showed high home-range fidelity. He also showed that significant differences in body size and organ sizes could be seen over a small range (<1 km) (Freedman, 2005), as had been previously reported with yellow perch in the Ottawa River (McMaster et al.,

29 2002). While the abundance of yellow perch did not appear to be affected by pulp mill effluent near Nackawic, changes in their trophic positions and carbon sources suggest there is an impact (Freedman, 2005). The utility of the species does depend on sampling seasons, and similar to white sucker (Doherty et al.,

2005), yellow perch do show more mobility at spawning times.

Except for the upper 200 km of the river basin, yellow perch are widely distributed all along the length of the Saint John River, (Curry and Munkittrick,

2005). This, as well as their high site fidelity, and the relative ease of aging of their scales, makes them a good species to select to examine the size distributions and growth rates to evaluate non-lethal sampling methods to examine the impacts of hydroelectric dams on fish performance in the Saint

John River.

2.1.2 Hydroelectric dams on the Saint John River (history and location)

Hydroelectric facilities continue to impose significant obstacles to upstream passage and no opportunity for safe downstream passage. Much of the earlier knowledge about the health of the Saint John River ecosystem came from assessments of the dramatic decline in populations of Atlantic salmon (Salmo salar) that have occurred over the past 50 years (Cunjak and Newbury, 2004).

Their declining numbers, from tens of thousands to a few thousand in recent years, are strongly correlated with the construction of dams, particularly the farthest downstream dam which allows no free passage of fishes. A major study of the biology and socioeconomics of the river occurred in the late 1960s

30 and early 1970s (Meth, 1972). High summer water temperatures, especially in the impoundments, stress the fish and restrict growth for many species. Altered flow regimes may affect in-river movements and the abundance of non-native piscivorous species (e.g., smallmouth bass (Micropterus dolomieu), chain pickerel (Esox niger), muskellunge (Esox masquinongy)), provides additional constraints to juvenile salmon production in the river (Cunjak and Newbury,

2004).

There are in total 11 dams in existence on the river system (Cunjak and

Newbury, 2004; Munkittrick et al. 2006). The current study involves the investigation of effects of five major dams located on the mainstem (Grand

Falls, Beechwood and Mactaquac) or on major tributaries near the mainstem

(Tobique, Aroostook).

The Grand Falls hydroelectric facility (66 MW) is the first facility as you go down river from the head waters. It is located at a 23 m natural barrier, and was first operated in 1928-1931. The next two major hydroelectric dams on the river are located on major tributaries. The Tinker dam is located on the Aroostook

River, just upstream of the US-Canada border. The 34 MW station is described as a run-of-the-river facility with five generators that began operation at various times between 1925 and 1965 (WPS Power Development, 2000). Although it is constructed as a run-of-the-river facility, there are large variations in downstream flow in the Aroostook River (unpubl. observations). The Aroostook

River enters the Saint John about 30 km below Grand Falls, and about 4 km upstream of the Tobique River.

31 The Tobique Narrows Dam (20 MW) was built in 1953 on the Tobique River near the confluence of the main Saint John River about 35 km upriver from

Beechwood Dam and 39 km downstream of Grand Falls. The Beechwood Dam

(113 MW), built in 1957, has a head of 17 m and is located 130 km upriver of

Mactaquac Dam. It has a fish collection gallery and a mechanical skip-hoist which lifts fish over the dam into the headpond.

Mactaquac dam, built in 1967, has a head of up to 35 m. Fish passage is provided through a fish collection facility situated in the base of the dam, which is comprised of a collection gallery, holding pool, crowder and hopper. The hopper lifts upstream migrants into tank trucks for upriver distribution. All adult salmon captured in the migration channel at the Mactaquac Main Salmon

Hatchery are sorted for broodstock and for transportation upriver where they are released for natural spawning and angling. The Mactaquac reservoir is 100 km in length and covers an area of approximately 87 km2. It is operated as a peaking station with a daily cycle throughout the entire year (low discharge overnight and high during the day). Both the Beechwood and Mactaquac facilities have limited and selective active fish passage (only Atlantic salmon and alewife (Alosa pseudoharengus involving upstream transport by truck, and act as barriers to upstream movement for other fishes.

2.1.3 Objective of this Chapter

The objective of this chapter is to develop a protocol for back-calculating fish growth rates in the Saint John River in the vicinity of five hydroelectric dams that

32 can be applied to help manage Bhutan’s fisheries and maintain river quality. The specific hypothesis tested is that there are no differences in the growth performance of yellow perch at various sites along the Saint John River.

The specific objectives are listed below:

1. Define the factors that need to be considered in developing a species-

specific growth profile, and develop a sampling strategy for yellow

perch in the Saint John River.

2. Determine the performance of fish upstream and downstream of dams

along the Saint John River system.

3. The second part of this chapter will test the hypothesis that similar

information about the effects of dams on life history characteristics of

fish can be obtained using non-lethal and lethal sampling techniques

2.2 Materials and Methods

Yellow perch were collected and measured from 10 sites in the upper Saint

John River near the hydroelectric dams to examine their growth and condition.

2.2.1 Study Area – the upper Saint John River

In the headwater reaches (>km 400), where river width and depth average

50 m and 2 m, respectively, summer and winter low discharge averages 135 m3/s. At Fredericton (135 km), low water discharge averages 250 m3/s

(average width = 750 m and depth = 3 m) (Curry and Munkittrick, 2005).

33 Yellow perch were collected using a standardized protocol of gillnetting and electrofishing at 10 sites by Curry and Munkittrick (2005) during late July and

August, 2000 and 2001 (Table 2-1). Additional detailed samples were collected at St. Hilaire and Edmundston by angling during the summer of 2002 (Galloway et al., 2004) and by Tenzin in the summer of 2004 by angling. Further detailed sampling was undertaken by angling in the Mactaquac headpond (Tenzin in summer of 2004) and by Freedman (2005) by electrofishing near Nackawic.

The main study sites along the main stem (Table 2-1) spanned a variety of human-impacted reaches, and included areas with reservoirs, forestry operations, dam/flow regulation, potato farming, pulp mills, paper mill, urban sewage treatment discharge, food processing, and pig/poultry production. The sites at Florenceville, Hartland, and Fredericton experience substantial fluctuations in water levels owing to the hydroelectric facilities. There is no fish passage at the Mactaquac Dam and thus it is the upstream limit for at least 10 anadromous species of fishes (Curry and Munkittrick, 2005).

Existing samples for aging and comparison exist from previous studies conducted at a number of sites on the river. These include a) St. Hilaire – the furthest site upstream with significant perch populations.

Although there are some sewage and food processing effluents upstream,

the inputs are relatively minor. The upper 200 km of the basin lies within

the Maine Northwoods – an industrial forest area where there are few

people or inputs outside of forestry operations.

34 b) Edmundston – this area of the river receives significant input of sewage

from an area including approximately 20,000 people. Inputs also include

a large pulp mill, a paper mill, and some local agricultural activity. Both

the pulp mill and the paper mill have secondary waste treatment facilities.

The town sewage input includes both treated and untreated sewage. c) Grand Falls – in addition to a natural 23 m waterfall that is now blocked by

a hydroelectric facility, the Grand Falls area (population approximately

6000) is the start of the potato growing area of New Brunswick, and the

site of a large potato processing plant than employs more than 250

people. d) Aroostook – this area has fewer than 500 people, but is the site of a

hydroelectric facility on the Aroostook River at the US-Canada border.

Upstream of the dam, there are historical issues with agricultural activities

and PCB contamination from a closed US air force base. e) Tobique – The Tobique area is home to about 2500 people, and the

Tobique River drains an area of active forestry. The tributary is blocked

by a hydroelectric facility near its confluence with the Saint John River. f) Florenceville – is located a few km below a large hydroelectric facility that

blocks the Saint John River. It is home to <1000 people, but is the site of

a very large potato processing facility that is a major contributor of

nutrients to the Saint John River (Luiker et al., 2004, 2005). The river

fluctuates approximately 2 m several times a day, as the peaking

hydroelectric facility alters flow with the hydroelectric demand. The food

35 processing plant produces primarily frozen french fries and has been in

operation since 1957. The processing plant built a tertiary treatment plant

involving an aerobic digester in 1996 (Jacques Whitford Environment

Limited, 1996). g) Hartland – is a town of <1000 people located 20 km downstream of

Florenceville. The Presque Isle tributary to the river drains agricultural

and food processing activities. h) Woodstock – is a town of over 5000 people located near the southern end

of the potato growing belt for New Brunswick. Treated sewage is

released into the Saint John River, and the Meduxneakeag River also

drains some potato growing areas. i) Nackawic – is the site of a large pulp mill that was closed for parts of 2004

and 2005. The city’s population is approximately 1000 people at the

upper end of the Mactaquac headpond. The headpond was not cleared

at the time of the construction of the dam, and the deeper water areas

near Nackawic have some issues with hypoxia during the summer. j) Fredericton – is the lowermost site sampled as part of this project. It is 20

km below Mactaquac dam, has a population of about 80,000 people, and

the main discharges to the river are related to secondary-treated sewage

inputs.

2.2.2 Sample Collection

To evaluate the performance of sampled fish upstream and downstream of dams, the fish collected were examined for external lesions, and sex was

36 determined. Scales were collected for aging. Fish were measured for weight (±

0.1 g) and fork length (±0.1 cm), and lateral scales were collected, dried in paper envelopes, and examined for the measurement of annuli. Scale samples were collected for aging. More than 350 perch were collected from 10 sites on the Saint John River, from Saint Hilaire to Fredericton. All fish were aged, but some fish were removed from the data set for back-calculating growth. In total,

318 fish were retained for back-calculations.

Fish were removed in some cases because the Ford-Walford plots (see below) suggested that the fit of the data with the ages was not consistent, and the differences were not easily resolved. In other cases, some data were missing from individual fish and these were removed. Most fish that were removed (>60%) were from Nackawic and other sites had few fish that were confusing.

2.2.2.1 Scale Cleaning and Mounting

Scales were removed from the scale envelopes and soaked in distilled water in a Petri dish. With aid of a binocular microscope, five scales were selected and initially cleaned with forceps. Care was taken not to subject the scales to corrosive pressure to preserve the rings. In the later stages, forceps were used only to hold the scales and paint brushes with clipped tips were used to scrape dirt off the scales. The paint brushes performed comparatively better at cleaning without damaging the rings on the scales. The scales were then rinsed again and put on paper towels for drying. Five dry scales were mounted between two microscope slides with the ends secured together by paper tape. All the scales

37 were mounted with the curved side facing up and with the same alignment. The sample identity was written with markers on the paper tapes, which also helped in identifying which side faced up.

2.2.2.2 Scale Digitization

Scales were digitized with the use of an Olympus BX40 (UNB ID 05927) microscope equipped with Sony Ex Wave HAD digital color video camera,

Model No. SSC-DC54A (Serial No. 101266). Media Cybernetics Optimas 6 (S/N

30N65000-11391) imaging software was used to capture images to the computer. The images were captured at 2X and 4X magnification and all the images were saved according to their site and the magnification at which the images were captured. The imaging software was calibrated with the aid of an image micrometer taken at 2X and 4X magnifications. This allowed for two configurations to be loaded to measure the scale images, which were also captured under 2X and 4X magnifications.

From the five scales mounted on each slide, only the best one was used to capture images. The use of five scales during mounting also allowed rejection of regenerated scales observed at higher magnification without diminishing the actual number of samples.

2.2.3 Age Reading

Age determination using scales formed the most important aspect of this thesis. Jearld (1983) indicates errors in age determination include missing the first annulus, the crowding of rings and reabsorption in old scales, and over-

38 estimation of age due to anomalous rings. A detailed list of criteria was developed by Jearld (1983) to correctly identify fish ages. Refinement of the criteria over iterative readings reduced variability among consecutive readings.

The scales of yellow perch show distinct growth rings due to a higher rate of growth in the warmer months and slow growth during the winter. The differences in rate of growth are reflected in the formation of rings on the scales with summer growth rings spaced widely apart and the winter growth rings concentrated closely together, resulting in distinct formation of alternating light and dark bands when observed under the microscope (Figure 2-2 and Figure

2-3).

The edge of the dark band shows the end of winter season for that growth year and each dark band was counted as an annulus. The absence of distinct focus was treated as regenerated scales and these regenerated scales were filtered out from the samples. The centers of regenerated scales tend to be without any distinct circuli and are clear. New growth rings crossing over or cutting winter growth rings were determined to be the start of new summer growth. Many false rings or anomalous rings could be eliminated using such observations in the ring formation, preventing overestimation of age.

39 Radial Line

2nd Annulus

Cutting over (new growth)

No Cutting over

1st Annulus

Cutting over (new growth)

Origin

Figure 2-2 Two year old fish (file: Edm_DS_F_2Yr_864)

2nd Annulus

1st Annulus

Figure 2-3 Two year old fish scale sample (file: Aroostook_023)

40 2.2.3.1 Ford- Walford plots

The ages were examined by plotting size at age of one year L(t+1) against size at age of the previous year ( Lt) (with the t values pertaining to constant time intervals, e.g., a year). Two values derived from this exponential function are important in characterising growth in fish populations: maximum possible size (L∞) and rate of growth to maximum possible size (K). Ford-Walford plots are typically used to derive L∞ and K.

2.2.3.2 Back-Calculation

Back-calculation was used to estimate fish length at the time of each annulus formation. It used the relative distance between annuli to approximate the growth of the fish over time by an assumed relationship between the current size of the structure and the current overall size of the fish. It requires that the growth of the aging structure be compared to a consistent landmark and to the size of the fish. The successive measurements on the same fish are not independent and the number of animals represents the replication, not the measurements.

2.3 Results

More than 350 perch were collected from 10 sites on the Saint John River, from Saint Hilaire to Fredericton. The largest perch were captured at the two most upstream sites (St. Hilaire and Edmundston), and were smallest at the

Tobique site (Table 2-2). Among sites, there was no significant relationship

41 between weight of fish and average age (r2=0.02), and the Tobique and

Nackawic fish were among the oldest and smallest fish. Condition factor also varied significantly between sites, and Nackawic and Tobique also had the skinniest fish (Table 2-2).

2.3.1 Raw Fish Data

Scales were examined from 355 fish. All fish were aged, but some fish were removed from the data set for back-calculating growth. In total, 318 fish were retained for back-calculations. Fish were removed in some cases because the

Ford-Walford plots suggested that the fit of the data with the ages was not consistent, and the differences were not easily resolved. In other cases, some data were missing from individual. Most fish that were removed (>60%) were from Nackawic and other sites had few fish that were confusing; Nackawic fish were the oldest and thinnest fish suggesting some stress was present. The fish retained for analysis were significantly shorter (p=0.009), lighter (p=0.008), and older (p<0.001) than the entire data set for Nackawic, but there was no difference in condition factor (p=0.38).

Five scales per fish were cleaned and mounted on slides for digitizing.

During digitization the scale which showed the best detail under the microscope was used to capture the image, resulting in 354 images. Thirty-one scales were not used due to difficulty in aging caused either by fish being too old or the scales being very unclear. Eleven scale images were not used due to them being from regenerated scales. In the second round of measurement, five

42 additional scales were used which were not used in the first round of measurement. Data were collected and analysed for only 307 scale samples in the first part of measurement and 312 scale samples were used in the second part resulting in 80% to 88% useable samples from the total collected. Over

44% of the bad scales turned out to be from Nackawic. Hartland and

Fredericton each accounted for 16% of the bad scales; 26% of the bad scales were regenerated, of which 82% turned out to be from Nackawic samples. The rest of the bad scales were either too old or were very unclear samples. The site differences in size of perch were consistent with the reduced data set (Table

2-3).

Perch collected from St. Hilaire were observed with the highest growth in length and weight and condition (Table 2-3). The lowest growth in length and weight was observed in perch collected from Tobique, and the lowest condition was observed in perch collected from Nackawic. The results for mean age changed here as compared to the ones reported in Table 2-2 because of the removal of fish. The highest and lowest mean age were reported from

Florenceville and Woodstock, respectively (Table 2-3).

43 Table 2-2 Summary statistics for all perch captured. Data sharing an alphabetical letter are not statistically different (within a column)

Site* Length (cm) Weight (g) Age (years) Condition SHIL 20.7 ± 0.8 (25) abcde 146.4 ± 15.7 (25) bcdg 4.4 ± 0.3 (25) abce 1.52 ± 0.03 (25) ab EDMN 20.4 ± 0.4 (101) abd 135.7 ± 8.2 (101) bcdg 5.2 ± 0.2 (101) abe 1.44 ± 0.02 (101) ab GRFA 15.2 ± 0.9 (18) defgh 59.6 ± 12.6 (18) acefh 2.8 ± 0.4 (18) ace 1.39 ± 0.04 (18) abd ARST 17.6 ± 0.7 (26) acdefg 85.5 ± 12.1 (26) acdef 3.8 ± 0.3 (26) abce 1.39 ± 0.04 (26) abd TOBQ 13.5 ± 0.8 (15) efgh 32.6 ± 7.1 (15) eh 4.9 ± 0.5 (15) abcde 1.18 ± 0.04 (15) acd FLOR 17.3 ± 1.7 (11) acdefgh 101.3 ± 26.0 (10) abcdefg 3.8 ± 0.7 (11) abce 1.33 ± 0.05 (10) abd HART 17.7 ± 0.6 (25) abcdefg 81.8 ± 7.9 (25) acdef 4.2 ± 0.3 (25) abce 1.39 ± 0.04 (25) abd

44 WOOD 15.7 ± 0.7 (22) cdefgh 57.6 ± 8.0 (22) acefh 3.5 ± 0.3 (22) ace 1.34 ± 0.03 (22) abd NACK 18.0 ± 0.4 (68) acdef 67.9 ± 4.7 (68) acef 6.3 ± 0.3 (68) de 1.08 ± 0.03 (68) cd FRED 18.3 ± 0.4 (44) abcde 103.4 ± 10.1 (38) abcdg 4.4 ± 0.3 (42) abce 1.49 ± 0.06 (38) ab A A highest value AAAA lowest value

*SHIL = St. Hilaire, EDMN = Edmundston, GRFA = Grand Falls, ARST = Aroostook, TOBQ = Tobique FLOR = Florenceville, HART = Hartland, WOOD = Woodstock, NACK = Nackawic, FRED = Fredericton

Table 2-3 Length and weight data for perch used in back-calculation of length and weight respectively

Site Length (cm) Weight (g) Age (years) Condition SHIL 21.0 ± 0.7 (23) 147.9 ± 15.6 (23) 4.5 ± 0.3 (23) 1.51 ± 0.04 (23) EDMN 20.2 ± 0.4 (98) 133.7 ± 8.2 (98) 5.2 ± 0.2 (98) 1.45 ± 0.02 (98) GRFA 15.2 ± 0.9 (18) 59.6 ± 12.6 (18) 4.8 ± 0.8 (18) 1.39 ± 0.04 (18) ARST 17.3 ± 0.7 (25) 77.7 ± 9.7 (25) 4.3 ± 0.4 (25) 1.38 ± 0.04 (25) TOBQ 12.8 ± 0.5 (14) 26.2 ± 3.4 (14) 4.9 ± 0.5 (14) 1.19 ± 0.04 (14) FLOR 18.0 ± 1.7 (10) 101.3 ± 26.0 (10) 8.5 ± 1.5 (10) 1.33 ± 0.05 (10) HART 17.0 ± 0.5 (18) 68.0 ± 5.8 (18) 6.1 ± 0.6 (18) 1.37 ± 0.05 (18)

45 WOOD 15.2 ± 0.6 (21) 51.5 ± 5.4 (21) 3.2 ± 0.2 (21) 1.33 ± 0.03 (21) NACK 17.1 ± 0.4 (45) 56.7 ± 3.6 (45) 6.8 ± 0.3 (45) 1.05 ± 0.02 (45) FRED 17.4 ± 0.3 (37) 83.8 ± 4.7 (31) 4.3 ± 0.3 (31) 1.46 ± 0.04 (31) AAA highest value AAAA lowest value

2.3.2 Effects of Sex on Size of Perch

Sex was only identified in fish collected by angling at St. Hilaire and

Edmundston (Tenzin, unpubl. data), and those collected at Nackawic (Freedman,

2005) because these were lethally sampled. Female perch were always longer and heavier than male fish (Table 2-4), but were not significantly different in age or condition. For the purposes of this thesis, the detailed data analyses will first be presented by sex for the furthest upstream sites because of sample size and the availability of information on sex of fish. The following set of analyses is presented for combined analyses of fish non-lethally sampled for which sex was not known.

Comparisons among sites will subsequently be conducted and compared.

2.3.3 Size-at-age comparisons

The size of fish was examined based on size-at-age data, which show differences between females and males at both Edmundston and St. Hilaire for both length (Figure 2-4) and weight (Figure 2-6). In a site-by-site comparison, both length (Figure 2-5) and weight (Figure 2-7) give similar results, and interpretation was similar to the interpretation of data based on weight; females at S. Hilaire showed a faster increase in size-at-age than females at Edmundston, but males were similar.

In an examination of all sites on the river, pooled sexes were compared for length-at-age (Table 2-5). Tobique fish had the slowest growth, followed by

46 Nackawic, and the slope of the line was highest at Grand Fall and Florenceville, followed by St. Hilaire.

Table 2-4 Summary statistics for perch captured at St. Hilaire, Edmundston and Nackawic by sex. Values are mean ± SE (n), and values sharing an alphabetical superscript are not significantly different within a site

Site Sex Length (cm) Weight (g) Age (years) Condition SHIL F 22.1 ± 0.9 (17) 172.1 ± 19.4 (17) 4.3 ± 0.3 (17) 1.51 ± 0.04 (17) a a a a M 18.8 ± 0.5 (7) 101.9 ± 9.1 (7) 5.0 ± 0.5 (17) 1.52 ± 0.04 (7) b b a a EDMN F 21.4 ± 0.5 (60) 155.0 ± 10.8 (60) 5.4 ± 0.3 (60) 1.46 ± 0.02 (60) a a a b M 18.9 ± 0.6 (41) 107.5 ± 11.3 (41) 4.8 ± 0.3 (41) 1.42 ± 0.03 (41) b b a b NACK F 18.5 ± 0.4 (54) 72.8 ± 5.5 (54) 6.6 ± 0.3 (54) 1.07 ± 0.04 (54) a a a a M 16.2 ± 0.6 (13) 51.0 ± 6.1 (13) 5.3 ± 0.4 (13) 1.13 ± 0.03 (13) b b b a AAA highest value AAAA lowest value

47 35 A 35 B n=23 n=98 30 y = 2.7233x + 10.181 30 y = 1.3079x + 14.351 2 R = 0.9022 R2 = 0.8366 25 25

20 20 Females Females Males Males 15 y = x + 13.757 15 y = 1.5785x + 10.782 R2 = 0.9727 R2 = 0.9482 Fork Length (cm) Fork Length (cm)Fork Length 10 10

5 5

0 0 024681012 024681012 Age Age

48 Figure 2-4 Fork length-at-age within sites for females and males at: (A) St. Hilaire (B) Edmundston

35 A 35 B

y = 2.7233x + 10.181 30 30 y = 1.5785x + 10.782 R2 = 0.9022 R2 = 0.9482 25 25

20 20 EDMN EDMN SHIL 15 y = 1.3079x + 14.351 y = x + 13.757 SHIL 2 15 R = 0.8366 R2 = 0.9727 Fork Length (cm) Length Fork Fork Length (cm) Length Fork 10 10

5 5

0 0 024681012 024681012 Age Age

Figure 2-5 Fork length-at-age among sites at Edmundston (EDMN) and St. Hilaire (SHIL): (A) Females (B) Males

A 400 B 400 n=98 n=23 350 350

y = 60.371x - 92.287 300 y = 28.762x - 0.3462 300 2 R2 = 0.9447 R = 0.7912 250 250 Females Females 200 200 Males Males Weight (gm) 150 Weight (gm) 150 100 100 y = 28.258x - 35.899 y = 16.667x + 18.524 50 50 R2 = 0.8423 R2 = 0.9671 0 0 024681012 024681012 Age Age

49 Figure 2-6 Weight-at-age within sites for females and males at: (A) St. Hilaire (B) Edmundston

400 A 400 B

350 y = 60.371x - 92.287 350 R2 = 0.9447 300 300 y = 28.258x - 35.899 R2 = 0.8423 250 250 EDMN 200 EDMN 200 SHIL SHIL Weight (gm) Weight (gm) 150 150

100 100

y = 28.762x - 0.3462 y = 16.667x + 18.524 50 50 R2 = 0.7912 R2 = 0.9671 0 0 024681012 024681012 Age Age

Figure 2-7 Weight-at-age among sites at Edmundston (EDMN) and St. Hilaire (SHIL): (A) Females (B) Males

Table 2-5 Regression table of length at age for all sites, and the rank of sites based on slope of the regression line SITES R2 Slope Intercept Correlation n Slope Intercept Rank Rank SHIL 0.4649 1.7783 12.9200 0.6818 23 5 1 EDMN 0.8116 1.4411 12.7830 0.9009 98 7 3 GRFA 0.9171 2.3787 8.5759 0.9576 18 1 9 ARST 0.9079 2.0978 9.5431 0.9528 26 3 6 TOBQ 0.9318 0.9482 8.2192 0.9653 14 10 10 FLOR 0.9477 2.2434 8.8120 0.9735 10 2 8 HART 0.9077 1.5294 11.3120 0.9527 25 6 4 WOOD 0.9043 1.7847 9.4127 0.9510 23 4 7 NACK 0.9139 0.9789 10.4400 0.9560 45 9 5 FRED 0.9063 1.2458 12.4210 0.9520 37 8 2

2.3.4 Length Frequency Data and Ford-Walford Plots

Ford-Walford plots were used to generate back-calculated length, weight, scale length, and scale width for comparison among sites and within sites. The

Ford-Walford plot was chosen due to its easy applicability to generate a linear growth profile (Ruemper, 1998; Sparre, 1998) and the rationale that the use of one method of back-calculation consistently for all the data collected would generate growth profiles that would be comparable among and within sites.

The measured growth parameters (fork length1, weight, scale length and scale width) for aged fish were averaged into a single reading per year for each age group. It was possible to generate tables for each of these averaged values in t (year the data were collected) and t+1 (the next year, using the value for fish a year older than the current one) (Sparre, 1998). These two values, t and t+1,

1 Fork length is the length from the most anterior part of the fish to the tip of the median caudal fin rays (Anderson et al., 1983).

50 were plotted to generate the regression line (Figure 2-8). Another line was generated at 45º from the origin. The intercept of the regression line generated from the plots and the 45º line was taken as the maximum growth for that parameter (Sparre, 1998) (Figure 2-8). The intercept of the regression line on the Y-axis is taken as the value of the parameter at age-1 (Figure 2-8). This method was used consistently for all the parameters among and within sites to generate linear growth profile for the parameters investigated (Table 2-7, Table

2-8, Table 2-9). The equation of the line (linear growth profile) was used to back-calculate all the values for each growth parameter linearly and could be used to compare the parameters by site and by sex.

For the Ford-Walford plots, the largest intercepts (fork length at age 1) were found at St. Hilaire, followed by Grand Falls and Woodstock. The smallest was

Tobique, followed by Florenceville, and Fredericton (Table 2-10).

Table 2-6 Summary table of Ford-Walford plots for fork length (linear growth) at Edmundston (EDMN) and St. Hilaire (SHIL) by sex

Sites Sex R2 Intercept (size at Slope n Two line intercept age-1) (max growth) SHIL F 0.9227 5.3306 0.8708 16 41.26 SHIL M 0.9602 4.7794 0.7970 7 23.54 EDMN F 0.9537 3.6106 0.8942 60 34.13 EDMN M 0.9361 3.2065 0.9071 38 34.52

51

40 y = 0.8942x + 3.6106 35 R2 = 0.9537 n = 60 30 ) 25 t+1 fork-length at age-1 20 Intercept = 3.6106 (cm)

15 Max growth (two line

Length at ( intercept) = 34.13 10

5

0 0 5 10 15 20 25 30 35 40 Length at t (cm)

Figure 2-8 Ford-Walford plot for fork length for Edmundston female yellow perch.

52 Table 2-7 Scale width (mm) calculated using Ford-Walford plots (the plot was limited to age 1-5 fish)

Sites Age 1 Age 2 Age 3 Age 4 Age 5 Age 6 Age 7 Age 8 Age 9 Age 10 Max.

SHIL 1.1729 1.5393 1.6538 1.6895 1.7007 1.7042 1.7053 1.7056 1.7057 1.7058 1.7058 EDMN 0.2046 0.3981 0.5810 0.7540 0.9176 1.0723 1.2185 1.3569 1.4876 1.6113 3.7610 GRFA 0.8907 1.2532 1.4008 1.4608 1.4852 1.4952 1.4992 1.5009 1.5016 1.5018 1.5020 ARST 0.8299 1.3233 1.6166 1.7910 1.8946 1.9563 1.9929 2.0147 2.0276 2.0353 2.0466 TOBQ* 1.8690 1.1016 1.4167 1.2873 1.3404 1.3186 1.3276 1.3239 1.3254 1.3248 1.3250 FLOR* -0.8181 -2.5112 -6.0154 -13.2675 -28.2765 -59.3392 0.7649 HART 1.3001 1.6795 1.7902 1.8225 1.8319 1.8346 1.8355 1.8357 1.8358 1.8358 1.8358 WOOD 0.8193 1.3639 1.7259 1.9665 2.1264 2.2327 2.3034 2.3504 2.3816 2.4023 2.4435 NACK* 3.4792 0.4085 3.1187 0.7266 2.8379 0.9745 2.6191 1.1676 2.4487 1.3180 1.8481 FRED 1.2989 1.7925 1.9800 2.0513 2.0784 2.0887 2.0926 2.0941 2.0947 2.0949 2.0950

53 Table 2-8 Distance of annuli (mm) from origin derived from Ford-Walford plots at individual sites

Sites Annulus Annulus Annulus Annulus Annulus Annulus Annulus Annulus Annulus Annulus 1 2 3 4 5 6 7 8 9 10 SHIL 0.5685 1.0872 1.5605 1.9923 2.3862 2.7457 3.0737 3.3729 3.6460 3.8951 EDMN 0.5264 0.9792 1.3686 1.7035 1.9916 2.2394 2.4525 2.6358 2.7934 2.9290 GRFA 0.6998 1.2621 1.7139 2.0769 2.3686 2.6030 2.7913 2.9426 3.0642 3.1619 ARST 0.4683 0.8943 1.2819 1.6344 1.9551 2.2469 2.5123 2.7537 2.9734 3.1732 TOBQ 0.3366 0.6505 0.9432 1.2161 1.4706 1.7080 1.9293 2.1356 2.3281 2.5075 FLOR 0.5487 1.0032 1.3798 1.6917 1.9501 2.1642 2.3415 2.4884 2.6101 2.7109 HART 0.5862 1.0785 1.4919 1.8391 2.1307 2.3755 2.5812 2.7539 2.8989 3.0207 WOOD 0.9661 1.6696 2.1819 2.5550 2.8266 3.0245 3.1685 3.2734 3.3498 3.4054 NACK 0.4592 0.8450 1.1691 1.4413 1.6701 1.8622 2.0236 2.1593 2.2732 2.3689 FRED 0.8335 1.5249 2.0984 2.5741 2.9687 3.2961 3.5676 3.7928 3.9796 4.1346

* indicates problems obtaining good plot

Table 2-9 Fork length at age increments (cm) derived from Ford-Walford plots

Sites Age Age Age Age Age Age Age Age Age Age 1 2 3 4 5 6 7 8 9 10 SHIL 9.95 2.70 2.46 2.24 2.05 1.87 1.71 1.56 1.42 1.30 EDMN 8.68 3.18 2.73 2.35 2.02 1.74 1.50 1.29 1.11 0.95 GRFA 7.08 2.80 2.25 1.81 1.45 1.17 0.94 0.75 0.61 0.49 ARST 7.50 2.75 2.50 2.27 2.07 1.88 1.71 1.56 1.42 1.29 TOBQ 6.19 1.71 1.60 1.49 1.39 1.29 1.21 1.13 1.05 0.98 FLOR 4.41 3.11 2.58 2.14 1.77 1.47 1.21 1.01 0.83 0.69 HART 8.47 2.17 1.82 1.53 1.28 1.08 0.91 0.76 0.64 0.54 WOOD 0.86 6.35 4.62 3.37 2.45 1.78 1.30 0.95 0.69 0.50 NACK 4.98 2.88 2.42 2.03 1.71 1.43 1.21 1.01 0.85 0.71 FRED 9.42 2.69 2.23 1.85 1.54 1.27 1.06 0.88 0.73 0.60

Table 2-10 Summary table of Ford-Walford plots for fork length (linear growth)

Sites R2 Intercept Slope n Slope Intercept Two line (length of age- Rank Rank intercept 1 fish in cm) (max growth in cm) SHIL 0.1968 12.5120 0.4554 2310 7 22.97 EDMN 0.9580 2.8606 0.9300 98 5 2 40.87 GRFA 0.9953 10.6740 1.9899 18 1 9 -10.78 ARST 0.8470 4.1272 0.8876 26 7 3 36.72 TOBQ 0.9034 -0.4501 1.1212 14 2 8 3.71 FLOR 0.8401 2.6122 1.0052 10 4 10 -502.35 HART 0.9409 2.3427 0.9569 25 3 1 54.35 WOOD 0.9915 5.2808 0.7941 23 9 5 25.65 NACK 0.9762 2.9673 0.8802 45 8 6 24.77 FRED 0.9882 2.7698 0.9152 37 6 4 32.66

54 2.3.5 Back-Calculating Growth

There are a variety of techniques that can be used for back-calculating growth rates. The simplest technique is measuring the length and width of the scales, but it is also possible to examine the size of growth increments (the growth rate of fish back-calculated from the information in the increments) and to also examine growth by back-calculating the size of fish at a specific age.

2.3.5.1 Scale Width and Length by Age

It is also possible to compare growth by examining changes in the length and width of scales by ages (Table 2-8, Table 2-7). The relationships between scale length and scale width are similar to size versus age for both male and female perch (Figure 2-9, Figure 2-10, Figure 2-11, Figure 2-12), and the ratio between scale length and width is independent of age (Figure 2-13).

2.3.5.2 Scale Increments

The annular increments on the scales provide a history of growth, with the differences in distances between annuli proportional to the growth obtained in different years. The scale increment data for Edmundston females (Table 2-11) included fish that were captured from 10 year classes from 1991 to 2001 (Table

2-12).

55

5 A 5 B

4.5 4.5 y = 0.4425x + 0.8807 y = 0.1548x + 1.6731 4 4 R 2 = 0.6021 R 2 = 0.5975 3.5 3.5 3 3 Females Females 2.5 2.5 Males Males 2 2 y = 0.1498x + 1.3848

Scale Length (mm) 2 1.5 ScaleLength (mm) 1.5 R = 0.6973 y = 0.1924x + 1.271 1 1 R 2 = 0.7707 0.5 0.5

0 0 024681012 024681012 Age Age

Figure 2-9 Scale length at age comparison within site between males and females at: (A) Edmundston (B) St. 56 Hilaire

A B 5 5 4.5 4.5 4 4

3.5 3.5 y = 0.3294x + 0.3957 y = 0.2007x + 0.9 R 2 = 0.6672 3 R 2 = 0.5911 3 Females Females 2.5 2.5 Males Males 2 2 Scale Width (mm) Scale Width(mm) 1.5 1.5

1 1 y = 0.1108x + 1.0522 y = 0.1262x + 0.8553 2 2 0.5 R = 0.6502 0.5 R = 0.6517

0 0 024681012 024681012 Age Age Figure 2-10 Scale width at age comparison within site between males and females at: (A) Edmundston (B) St. Hilaire

A B 5 5 y = 0.4425x + 0.8807 4.5 4.5 R2 = 0.6021 4 4 y = 0.1924x + 1.271 3.5 3.5 2 R = 0.7707 3 3 EDMN EDMN 2.5 2.5 SHIL SHIL 2 2 Scale Length (mm) Scale (mm) Length y = 0.1548x + 1.6731 y = 0.1498x + 1.3848 1.5 1.5 2 R2 = 0.5975 R = 0.6973 1 1

0.5 0.5 0 0 024681012 024681012 Age Age

57 Figure 2-11 Scale length at age comparison among sites at Edmundston (EDMN) and St. Hilaire (SHIL): (A) Females (B) Males

5 A 5 B

4.5 4.5

4 4

3.5 y = 0.3294x + 0.3957 3.5 2 3 R = 0.6672 3 EDMN y = 0.1262x + 0.8553 EDMN 2.5 2.5 SHIL R2 = 0.6517 SHIL 2 2

Scale Width (mm) Scale Width (mm) 1.5 1.5

1 y = 0.1108x + 1.0522 1 R2 = 0.6502 y = 0.1364x + 0.7844 0.5 0.5 R2 = 0.7859 0 0 024681012 024681012 Age Age Figure 2-12 Scale width at age comparison among sites at Edmundston (EDMN) and St. Hilaire (SHIL): (A) Females (B) Males

2 A 2 B 1.8 1.8 1.6 1.6 1.4 1.4 1.2 1.2 1 1

L/W Ratio 0.8

L/W Ratio 0.8 0.6 0.6 y = -0.0061x + 1.5644 0.4 y = -0.0062x + 1.5603 2 0.4 R = 0.0091 R2 = 0.0155 0.2 0.2 0 0 024681012 024681012 Age Age Figure 2-13 Scale length to width ratio at age for male (A) and female (B) perch at Edmundston

58

Table 2-11 Scale increments for Edmundston females (mm) Age Increments 1st 2nd 3rd 4th 5th 6th 7th 8th 9th 10th 11th 2 0.5185 0.8683 3 0.5578 0.5395 0.5868 4 0.5202 0.5919 0.48900.5160 5 0.4542 0.4279 0.47450.4910 0.3804 6 0.4491 0.3644 0.41580.4902 0.5423 0.4693 7 0.4561 0.2618 0.4662 0.3798 0.3528 0.3232 0.2915 8 0.3581 0.3165 0.3499 0.2679 0.3626 0.3349 0.2646 0.3037 9 0.3915 0.2872 0.4254 0.3395 0.3038 0.4135 0.3749 0.3095 0.2060 10 0.3781 0.2296 0.2754 0.2645 0.2491 0.2749 0.2394 0.3061 0.3170 0.2029 11 0.5107 0.1725 0.3486 0.3452 0.2884 0.2388 0.2495 0.2579 0.2414 0.2064 0.2018

Table 2-12 Comparisons of year classes of males and females at St. Hilaire and Edmundston sites

Site Sex Year Class Total Per Site 1993 1994 1995 1996 1997 1998 1999 2000 2001 SHIL M 1 2 1 2 1 7 F 2 3 8 2 1 16

EDMN M 1 2 2 2 6 7 5 8 5 38 F 1 5 2 7 5 8 13 8 7 60

One of the challenges with increment data is that the growth per year is not equal in all years, and the amount of growth will also vary with water temperature for that year. A significant relationship between water temperature and scale increment exists (Figure 2-14). This data can also be used to examine relative growth rates between sexes and sites (Figure 2-15, Figure 2-

16).

For comparisons among sites, measurements of distance of annuli obtained from image analysis were pooled for each site irrespective of the age of the fish in the group to obtain a single value of growth for each annulus at each site. The resulting data were used on a Ford-Walford plot to obtain a linear growth profile for scale growth for the particular site. The growth profiles obtained were compared among sites (Table 2-8; Figure 2-17). Maximum scale growth was obtained from fish collected at Fredericton and St. Hilaire and was lowest among the fish collected from Tobique and Nackawic (Figure 2-17).

59

0.4

0.35 y = -0.0004x + 1.5278 R2 = 0.8145 0.3

0.25

Females 0.2 Males

0.15

Scale Increment (mm) Increment Scale y = -0.0001x + 0.6955 0.1 R2 = 0.4556

0.05

0 2700 2800 2900 3000 3100 3200 Yearly DTU Contribution (C)

Figure 2-14 Comparison of average scale increment (Edmundston) versus Daily Temperature Unit (DTU) >10C for the year of hatching. Scale increment represents the average increment for 4-year-old fish for that year; temperature was obtained from temperature records from Mactaquac Fish Hatchery.

60 A B 3.5 3.5

3 3 Age 2 A Age 2 2.5 2.5 Age 3 Age 3 Age 4 Age 4 Age 5 2 Age 5 2 Age 6 Age 6

(mm) Age 7 Age 7 1.5 Distance 1.5 Age 8

Distance (mm) Distance Age 8 Age 9 Age 9 1 1 Age 10 Age 10 Age 11 0.5 0.5

0 0 024681012 024681012 Age Age

61 Figure 2-15 Distance of annuli from origin for male (A) and female (B) perch at Edmundston

45 A 50 B

40 45

35 40 Age 2 Age 2 35 Age 3 Age 3 30 Age 4 Age 4 30 Age 5 25 Age 5 Age 6 Age 6 25 Age 7 20 Age 7 20 Age 8 % Increment Age 8 % Increment Age 9 15 Age 9 15 Age 10 Age 10 10 10 Age 11 5 5 0 0 024681012 024681012 Age Age

Figure 2-16 Percent scale increment to total scale length for male (A) and female (B) perch at Edmundston

4.5 4.0

3.5 SHIL EDMN 3.0 GRFA 2.5 ARST TOBQ 2.0 FLOR HART WOOD

Distance (mm) Distance 1.5 NACK 1.0 FRED 0.5 0.0 01234567891011 Annuli

Figure 2-17 Scale growth profile for all sites back-calculated from Ford-Walford plots

2.3.5.3 Back-Calculating Sizes at a Standard Age

A different approach to back-calculate length and weight was taken here as compared to the previous one. The average fork length for each age group was correlated with the distance of annuli obtained from Ford-Walford plot (Table

2-8). The data were used to linearly derive the back-calculated length of fish at age for each site (Table 2-13).

The fork length at scale length was compared among sites (Figure 2-18).

The ratio of fork length to scale length decreased in the order: Edmundston,

62

Aroostook, Woodstock, St. Hilaire, Florenceville, Nackawic, Tobique, Grand

Falls, Hartland and Fredericton.

The back-calculated fork length was also compared among sites by age

(Figure 2-19). Perch collected at St. Hilaire and Edmundston and Aroostook were found to have the highest growth and the lowest growth was seen among the fish at Tobique, Nackawic, Florenceville, Hartland and Grand Falls. The fork-length increments at age were also obtained from back-calculated fork lengths (Table 2-13) and were plotted to observe comparative differences among sites (Figure 2-20).

2.3.6 Weight Back-Calculation

The scale growth profile (Table 2-8) was used again to correlate with the average weight of each age group of fish by site to obtain weight-of-fish-at-age.

The resulting data were used to back-calculate weight. The data obtained were used to plot the weight-at-scale-length for each site (Figure 2-21). The weight gained to scale growth was highest for fish collected at Edmundston and the lowest among fish collected at Fredericton, Tobique, Hartland and Grand Falls

(Figure 2-22). The back-calculated weight at age was also compared among sites (Figure 2-23). The fish collected at St. Hilaire and Edmundston gained the most weight and the fish at Tobique, Nackawic, Hartland, Florenceville and

Grand Falls gained the lowest (Figure 2-24).

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Table 2-13 Back-calculated fork length at age (cm)

Sites Age 1 Age 2 Age 3 Age 4 Age 5 Age 6 Age 7 Age 8 Age 9 Age 10 SHIL 9.9500 12.6500 15.1100 17.3500 19.4000 21.2700 22.9800 24.5300 25.9500 27.2500 EDMN 8.6800 11.8600 14.5900 16.9400 18.9600 20.7000 22.2000 23.4800 24.5900 25.5400 GRFA 7.0800 9.8800 12.1300 13.9300 15.3900 16.5500 17.4900 18.2500 18.8500 19.3400 ARST 7.5000 10.2400 12.7400 15.0100 17.0800 18.9600 20.6700 22.2300 23.6400 24.9300 TOBQ 6.1900 7.9000 9.4900 10.9800 12.3700 13.6700 14.8700 16.0000 17.0500 18.0300 FLOR 4.4100 7.5200 10.1000 12.2400 14.0100 15.4700 16.6900 17.6900 18.5200 19.2100 HART 8.4700 10.6400 12.4600 13.9900 15.2700 16.3500 17.2500 18.0100 18.6500 19.1900 WOOD 0.8600 7.2000 11.8300 15.1900 17.6400 19.4300 20.7300 21.6700 22.3600 22.8700 64 NACK 4.9800 7.8600 10.2800 12.3100 14.0200 15.4500 16.6600 17.6700 18.5200 19.2300 FRED 9.4200 12.1100 14.3400 16.1900 17.7300 19.0000 20.0600 20.9300 21.6600 22.2600

50

40

SHIL 30 EDMN GRFA ARST 20 TOBQ FLOR HART WOOD 10

Fork Length (cm) Fork Length NACK FRED

0 01234567 -10 Scale Length (mm)

Figure 2-18 Fork length versus scale length for yellow perch from Saint John River

30

25

SHIL EDMN 20 GRFA ARST 15 TOBQ FLOR HART

10 WOOD

Fork Length (cm) Length Fork NACK FRED 5

0 01234567891011 Age

Figure 2-19 Back-calculated fork length at age for yellow perch from the Saint John River

65

11 10 9 8 SHIL EDMN 7 GRFA ARST 6 TOBQ 5 FLOR HART

Length (cm) 4 WOOD NACK 3 FRED 2 1 0

01234567891011 Age

Figure 2-20 Length increments at age derived from Ford-Walford plots

800 700

600 SHIL 500 EDMN GRFA 400 ARST TOBQ 300 FLOR HART

Weight (g) 200 WOOD 100 NACK FRED 0

-100 01234567

-200 Scale Length (mm)

Figure 2-21 Back-calculated weight at scale length for yellow perch

66

350

300

250 200 SHIL EDMN 150 GRFA ARST 100 TOBQ 50 FLOR HART (g) Weight 0 WOOD NACK -50 01234567891011FRED -100 -150 -200 Age

Figure 2-22 Back-calculated weight at age for yellow perch

100

90 80 SHIL 70 EDMN GRFA 60 ARST 50 TOBQ FLOR

40 HART WOOD 30 NACK FRED Weight Increments (g) 20 10

0 01234567891011 Age

Figure 2-23 Weight increments at age derived from Ford-Walford plots

67

Table 2-14 Number of fish aged per year class per site for the Saint John River sites. All fish were collected in 2001, except Nackawic, which includes fish captured in 2004, and Edmundston, which were collected in 2003

Year 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 Total Class Per Site SHIL 3 2 4 10 3 1 23 EDMN 4 2 7 4 9 11 15 18 16 12 98 GRFA 2 3 3 7 3 18 ARST 1 2 2 1 7 7 6 26 TOBQ 1 1 2 2 5 3 14 FLOR 1 1 3 1 1 1 2 10 HART 1 1 3 2 7 10 1 25 WOOD 1 3 6 5 7 22 NACK 3 5 4 3 9 8 6 3 4 45 FRED 1 2 5 4 4 12 8 6 42 TOTAL 323

Table 2-15 Averages for four-year-olds at all sites

Site Weight Length Annuli Distance SHIL 171.00 22.20 2.30 EDMN 155.86 21.77 2.40 GRFA 81.50 17.55 2.87 ARST 72.63 16.98 2.51 TOBQ 23.44 12.39 1.57 FLOR 68.00 18.20 2.62 HART 79.17 17.75 2.24 WOOD 69.14 17.14 2.55 NACK 75.22 18.70 2.08 FRED 85.00 17.73 2.63 AAA highest value AAAA lowest value

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2.4 Discussion

The size and growth of yellow perch were evaluated at 10 sites along the

Saint John River. The largest fish were captured at the site furthest upstream

(St. Hilaire), and were four times as heavy as those collected at the site with smallest fish (Tobique). The condition factor was almost 50% higher at St.

Hilaire than it was at Nackawic and 30% higher than at Tobique. Data from the

Canadian EEM program have suggested that changes in sizes and growth rates in excess of 30% are ecologically relevant (Munkittrick et al., 2002; Lowell et al.,

2004; Munkittrick et al., 2006). For condition factor, differences in excess of

10% are thought to be important (Munkittrick et al., 2002).

In general, growth was consistently fastest at St. Hilaire, Edmundston and

Fredericton, and slowest at Tobique, Nackawic and Woodstock (Table 2-16).

Condition factor is an indicator of energy reserves and commonly correlates with growth rate (Lowell et al., 2003). St. Hilaire, Edmundston and Fredericton also had the highest condition factors, and Tobique and Nackawic had the lowest condition factors.

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Table 2-16 Summary of rankings of size or growth rates for yellow perch

Site Raw data Adjusted Data Length-at-age Ford-Walford Back-calculated Size Weight K Weight k Slope Intercept Slope Intercept Final Size Age 4 SHIL 1 1 1 1 5 1 10 7 4 2 EDMN 2 3 2 3 7 3 5 2 6 7 GRFA 8 4 7 4 1 9 1 9 3 5 ARST 5 4 5 5 3 6 7 3 8 4 TOBQ 10 9 10 9 10 10 2 8 10 9 FLOR 4 8 3 7 2 8 4 10 7 8 HART 6 4 6 6 6 4 3 1 5 6 WOOD 9 7 9 7 4 7 9 5 2 3 NACK 7 10 8 10 9 5 8 6 9 10 70 FRED 3 2 4 2 8 2 6 4 1 1

The lowest slope for size-at-age was also evident at Nackawic and Tobique, and were less than half of that seen at the fastest growing sites; the steepest slopes were at Florenceville and Grand Falls. Both of these sites are reservoirs upstream of hydroelectric facilities. However, the slope of the regression lines for length or weight-at-age did not correlate as strongly with fish size or condition as did intercept for the regressions. It is possible to estimate growth performance a number of ways, and there was good agreement in rankings between the body weight and condition of fish, and the length-at-age intercept, and estimated sizes at age 4 and age 10 using back-calculation (Table 2-16).

There was poor agreement of the slopes of length-at-age, or Ford-Walford slopes or intercepts with the other rankings. There was also not good agreement within the slopes of length-at-age or Ford-Walford plots. The size-at- age and body size at capture give good information on an integrated response of the fish over its life span. But, the back-calculated information provides a complete picture of the growth history, and enables an analysis of the growth performance of younger fish.

In terms of impacts, enrichment is mild near Edmundston (Culp et al., 2003;

Galloway et al., 2003), and nitrogen and phosphorus are elevated near

Florenceville associated with a potato processing plant discharge (Luiker et al.,

2004, 2005). A similar potato processing plant discharges effluent upstream of

Grand Falls, but elevated levels of nutrients further downstream are associated with agricultural inputs near Hartland and Woodstock. Increased size and condition have been reported in white sucker near the Florenceville area

71

(Doherty et al., 2005), and faster growth has been seen in slimy sculpin downstream of Edmundston (Galloway et al., 2003). We would expect that elevated nutrients would be associated with improved performance near

Edmundston and Florenceville, and yellow perch were larger here with higher condition factors than at many other sites. Grand Falls, Florenceville and

Aroostook also had the largest slopes for length-at-age and had higher than average condition factors.

The abundance of perch has been shown to increase in the Saint John River with distance downstream (Figure 2-24; Curry and Munkittrick, 2005). Diversity also increases (Figure 2-25), especially after the dam at Mactaquac, upstream of Fredericton. This dam acts as a barrier to 10 anadromous fish species in the river (Curry and Munkittrick, 2005).

The poorest performance of yellow perch occurred near Tobique and

Nackawic. Nackawic has been the subject of previous studies (Freedman,

2005). The river reach near Nackawic, receives effluent from a large pulp mill, and is influenced to varying degrees by both upstream and downstream hydroelectric facilities. In the first cycle of EEM studies at the St. Anne-

Nackawic Pulp Mill (in 1995) yellow perch and white sucker were used as the sentinel species (BEAK, 1996), while the Cycle 2 study (in 1999) assessed only yellow perch (BEAK, 2000). These earlier studies found decreased body size, condition and liver size in fish near Nackawic. Freedman (2005) showed that the yellow perch showed relatively high site fidelity, and that both pulp mill- and

72

2.5

2

1.5 All fishes 1 Yellow perch

0.5 Relative Abundance Relative

0

k n lle nd k c ge o to i a d ro s took toc awi cev s k Bri Priestlyr B nd os n d c y e u Tobique Hartl k m Aro re Na od Grand Falls lo Woo Fredericton o Ba Ed F M Site

Figure 2-24 Relative abundance of yellow perch as compared to other fish species at sites along the Saint John River (from Curry and Munkittrick, 2005)

25

20

15

10

Species richness (n) 5

0

k e d e tly n lls le k ic ok oo qu il w ro Fa t i icton B cev stoc r Bridg r ndsto d d Pries u Tob en Hartlan dy m an Aroos Nacka d Gr Woo Frede Bake E Flor Moo Site

Figure 2-25 Fish species richness at sites along the upper Saint John River from upstream of the Canadian border at Moody Bridge to Fredericton (from Curry and Munkittrick, 2005)

73

sewage effluent-exposed sites in this reach had lower species richness, abundance, and diversity. Fishes that are present show marked differences in trophic position and dietary sources than those at non-exposed reference sites

(Freedman, 2005).

The poor performance at Tobique was not expected. While Luiker et al.

(2004) found elevated chlorophyll a near Tobique, nutrients were not elevated.

The yellow perch were sampled from the headpond and, therefore, this is an area of the river where further study is required.

2.4.1 Relevance of the findings to Bhutan

This study on the Saint John River identified methodology that can be used in non-lethal sampling programs to assess the effects of hydroelectric activities on fish health. There are a number of advantages of using fish age in monitoring studies. The accurate interpretation of fish age can allow for back- calculation of fish growth to describe the period years before any monitoring was ever initiated at the site of interest and indicate if a history of effects is present. These methodologies are of particular value in a country such as

Bhutan, in which little monitoring has been initiated to date and in which development of non-lethal sampling methods are imperative.

There are also a number of limitations in using fish age in monitoring studies as the precision and accuracy of the age interpretation can have considerable influence on the results. Accuracy and precision in age interpretation can be increased by increasing the number of samples and also by validating by

74

different age interpreters repeatedly until consistency among readers can be reached. Older fish can be harder to age due to slow growth in their latter years.

It is important during the baseline studies to evaluate variability; this information will be needed to determine appropriate sample sizes. The impacts of temperature and age on growth rate in most species means that power will be increased with a sampling design that focuses the sampling strategy on fish of a similar age at comparable sites. It is probable that the suitability of different indicators will need to be evaluated for each species in initial monitoring programs in Bhutan. It is also difficult to generalize which indicators are most accurate estimates of growth.

The sampling program for Bhutan must evaluate the impacts of sex on growth rates. If there is an effect due to sex, it is possible with some species to separate the sexes non-lethally by secondary sex characteristics or by condition factor (when there are large differences between male and female gonad sizes) when the fish can not be easily sexes externally.

The various measures of growth need to be evaluated for Bhutanese species to determine the most sensitive and culturally-appropriate sampling design. Calculations similar to those in this chapter need to be undertaken. It is also important that the sampling design include other endpoints. Information on abundance, fish community structure, and stable isotopes will all play an important role in understanding impacts.

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CHAPTER 3

A FRAMEWORK FOR MONITORING FISH IN BHUTAN’S RIVERS

3 Ecology of Bhutan’s Rivers Systems

Bhutan has has five major glacial-fed perennial river systems, Amo chhu2,

Wang chhu3, Puna Tsang chhu4, Manas and the Nyere Ama chhu flowing from north to south (Table 3-1; Figure 3-1). The total length of the rivers and tributaries are estimated to be 7200 km (Petr, 1999). All the rivers drain into the

Brahmaputra River Basin in the Indian Plains, and most of the rivers originate within Bhutan with a few exceptions. The headwaters of the Amo chhu and two tributaries of the Manas River System, the Kuri chhu and the Gongri-Twang chhu (which continues as Dangme chhu) originate on the Tibetan plateau. All the rivers differ greatly due to extreme altitudinal gradients among flow beds

(Baillie and Norbu, 2004). The rivers have a very high gradient, resulting in very high water velocities; the Wang chhu descends from almost 3600 meters at

Thimphu to 500 meters at the Southern Himalayan, within a span of approximately 200 km.

The rivers have maximum flow during the monsoons, with the flow rate increasing up to 20-50 times during the monsoons (Charlton, 1997). This results in intermittent flooding of the foothills; flooding has become more frequent in the

2 Toorsa in India

3 Raidak in India

4 Sankosh in India

76

recent years, possibly due to climate change. The flooding is more severe as one proceeds north to south due to heavier rainfall experienced in the south and the funnelling effect of the converging rivers. The effect of flooding has also become more noticeable in the recent years, which might be due to expanding and new settlements in flood- prone areas.

The water temperatures for Wang chhu river system ranged from 11-18°C in the upper reaches (NWWFCC, 2001). Shrestha (1991) conducted water quality tests for the winter of 1990-1991 and a similar study was conducted in summer by NWWFCC in 2001. The findings of the two studies are shown in Table 3-2.

Table 3-1 Discharge and runoff (source Baillie and Norbu, 2004)

River Catchment Mean Mean area (km2) annual specific discharge runoff (mm (m3/s) p.a.) Wang chhu 3550 102 906

Puna Tsang 8050 384 1504 chhu Mangde chhu 3200 149 1469

Kuri chhu 8600 291 1067

Gongri chhu 8560 262 965

Manas chhu 20925 784 1182

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Key China Bhutan Rivers

u h h Mo C Ch o Nepal hu h P T h India i K m u ri

P C Ch C

Bangladesh a hu h C h

C D h h h

h o

u a u C

h C m

h u h

k h

h a

u u r

u C h h M h 78 o h as a u B C n u g g h hu d h HaC Ch n e C u h a Chh h D Ch e u h m a u g m n A

ChhuChhu a A e D r m e g y N o n N C a W h s

T h a

u n M g a WE n a C u n hhu P a s

50 km S

Figure 3-1 Major river systems of Bhutan

Table 3-2 Water quality tests for Wang chhu River System (NWWFCC, 2001)

Parameters Alkalinity CO2 DO Total Hardness pH (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) Tributaries 1991 2001 1991 2001 1991 2001 1991 2001 1991 2001 Thim chhu 45-66 86-120 1.0-5.8 5.0-6.0 9.1-13.5 7.5-8.0 43-66 51-120 8.0-9.4 7.7-8.0 Paro chhu 48-65 51-103 4.5-8.9 3.0-6.0 7.5-11.5 7.0-8.7 53-66 51-68 8.0-8.3 7.8-8.3 Ha chhu 13-57 34.20 2.2-5.5 2.0-4.0 7.5-11.2 7.5-8.4 12-63 17-34 7.0-8.5 7.2-7.3

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There have been 41 species of fish documented in rivers and lakes of

Bhutan (Table 3-3 and Table 3-4) (Day, 1873; Dubey, 1978; Dhendup and

Boyd, 1994; Petr, 1999). The snow trout or asla (Schizothorax progastus) and

Himalayan trout (Barilus spp.) are common in all rivers (Petr, 1999). Brown trout

(Salmo trutta) were introduced in 1930 (Petr, 1999), and are also very abundant in most rivers. Other species of interest are katle (Acrossocheilus hexagonolepis) and mahseer (Tor tor and T. puititora) (Petr, 1999). Specific details on the population, density and distribution of species remain unknown at this time due to lack of studies.

With the exception of snow trout and brown trout (NWWFCC, 2001), all other species have only been recorded in warmer waters on the southern plains (Petr,

1999). There is no information on the distribution of other species within the area of Bhutan influenced by existing and potential hydropower development.

3.1 Designing the Framework: Ecosystem Definition

Munkittrick et al. (2000) outlined a framework for an effects-based approach for monitoring impacts of hydroelectric development. The effects-based approach uses the performance of fish to provide an integrated signal about the status of the system, and follow-up studies can be used to identify factors limiting performance in the system (Hewitt et al., 2005). The characteristics of the system are important for defining the most sensitive study design for detecting impacts. For the purpose of this discussion, the relevant characteristics will be described in terms of the physical environment and

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Table 3-3 Summary of fish species recorded in Bhutan (Petr, 1999) Family Species Common name River/stream (pond) Cyprinidae 1 Schizothorax progastus Dinnawah Sankosh; Chamkhar; Kuru; Manas; Ha; snowtrout/asla Mangdi 2 Schizothorax Manas molesworthii 3 Acrossocheilus Copper mahseer Manas; Mangdi; Phepso; Gaylegphug; hexagonolepis Sarbhang Khola; Kuru; Chanchi; Phuntsholing 4 Crossocheilus latius Manas; Sarbhang Khola; Gaylegphug 5 Tor putitora Mahseer Manas; Sarbhang Khola; Gaylegphug 6 Tor tor Mahseer; jantura Manas; Sarbhang Khola; Gaylegphug; Phepsu 7 Barilius barna Manas; Sarbhang Khola; Gaylegphug; Phepsu; Sankosh; Khalikhola; Phuntsholing; Magdi 8 Barilius bendelisis Sarbhang Khola; Gaylegphug 9 Barilius bola Phepsu 10 Puntius macropogon Gaylegphug 11 Puntius sophore Gaylegphug 12 Puntius ticto Ticto barb Gaylegphug; Sarbhang Khola 13 Puntius titius Swamp barb Sankosh; Sarbhang Khola 14 Cirrhinus lata Sankosh 15 Barbus spp. Gaylegphug 16 Labeo dero Manas 17 Labeo dyocheilus Manas; Phepsu 18 Labeo pangusia Sankosh 19 Garra annandalei Gaylegphug; Sarbhang Khola; Phepsu 20 Garra gotyla Sankosh; Sarbhang Khola; Phepsu; Magdi 21 Danio aequipinnatus Giant danio Manas; Sarbhang Khola 22 Danio dangila Manas; Sarbhang Khola 23 Brachydanio rerio Zebra danio Sarbhang Khola 24 Botia Dario Bengal loach Gaylegphug 25 Semiplotus semiplotus Assamese kingfish Phepsu 26 Rasbora daniconius Slender rasbora Gaylegphug Cobitidae 27 Noemacheilus botia Mottled loach Sarbhang Khola Siluridae 28 Batasio batasio Gaylegphug 29 Mystus bleekeri Day’s mystus Gaylegphug 30 Mystus vittatus Striped dwarf Gaylegphug catfish 31 Ompok pabda Pabdah catfish Gaylegphug Sisoridae 32 Bagarius bagarius Dwarf goonch/ Manas Bagarid catfish 33 Nangra punctata Manas Belonidae 34 Xenentodon cancila Freshwater garfish Phepsu Channidae 35 Channa gachua Phepsu 36 Channa striatus Snakehead murrel Gaylegphug Nandidae 37 Badis badis Badis Manas 38 Nandus nandus Gangetic leaffish Gaylegphug Mastacem- 39 Mastacembelus Zig-zag eel Sarbhang Khola; Kalikhola belidae armatus

81

Table 3-4 List of Introduced fish species (Petr, 1999)

Family/Species Common Name River/stream (pond) Salmonidae 1 Salmo trutta fario Brown trout Ha; Paro; Thimphu 2 Salmo trutta trutta Sea trout Ha; Paro; Thimphu Cyprinidae 3 Cyprinus carpio Common carp Gaylegphug – ponds 4 Catla catla Catla Gaylegphug – ponds 5 Cirrhinus mrigala Mrigal Gaylegphug – ponds 6 Labeo rohita Rohu Gaylegphug – ponds 7 Aristichthys nobilis Bighead carp Gaylegphug – ponds 8 Ctenopharyngodon idella Grass carp Gaylegphug – ponds 9 Hypophthalmichthys molitrix Silver carp Gaylegphug – ponds

stresses, factors affecting the selection of sampling sites, and characteristics of the biota that can increase the sensitivity of monitoring programs.

It is necessary to consider background information to tailor a study design for the specific region of interest. The basic requirements of the background information include understanding the geology, hydrogeology, local climate, industrial development, physical structure, water chemistry and resident biota

(Munkittrick et al., 2000). This information will help define the scope and magnitude, and limitations, of the study design.

3.1.1 Physiographic Zones of Bhutan

Norbu et al. (2003) have proposed a classification of physiographic zones for

Bhutan based on altitude, climate, bedrock geology, surface drift, landforms, hydrology, soils and natural vegetation. Norbu et al. (2003) have divided

82

Bhutan into three main zones: High Himalaya, North-South Valleys and Ranges, and Southern (Figure 3-2). Each of these main zones is further subdivided into multiple zones. The High Himalayas will not be considered within the context of a fisheries monitoring program as they are outside proposed development sites.

Furthermore, much of the water in this zone is presently in glaciers and lakes, and there is limited surface runoff that would support fish.

Most of the settlements and industrial development in the Southern Region are near the border with India, and downstream reaches would be outside

Bhutan’s boundaries. Studies in the Southern Region will be limited in range towards the downstream sites. The high occurrence of landslides and high sediment loads in the Southern Region might prompt the study of sediment loads on fish populations, and there are some opportunities for examining industrial impacts that will be considered. But future hydroelectric development is the major concern, and it will primarily occur in the North-South Valleys and

Ranges.

According to Norbu et al. (2003), the North-South Valleys can be further classified as: Northern Valleys, Inner Valleys and Passes, Southern Mountains and Gorges, Deep Eastern Valleys, and the Merak-Sakten-Block (Table 3-5).

The Northern Valleys include much of the protected areas and have seen little development. There will be little opportunity to sample within these protected areas, and most of the monitoring designs will consider areas outside of the Nature Reserves.

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Key Region: High Himalaya N Zone 1: Trans-Himalayan Plateau WE Zone 2: High Himalayan Peaks u h h Mo C S C o Zone 3: High Himalayan Plateau hh h u P Region: North-South valleys T h i K m u Zone 4: Northern valleys ri

P

C C Ch C

a hu

h h C h

C D

h h h h

h o

u u

a u

C C

Zone 5: Inner valleys & passes h C m

h h u h

k

h h

h a

u u

u r Zone 6: Southern Mountains u C h M h o h h as a u 84 & gorges B C n u u g g h Ha hh n d h C C a eC C hhu Zone 7: Deep Eastern valleys h D e C h h u h m a u g m n A

ChhuChhuChhu a A Zone 8: Merak-Sakten block D re m ye

o ng N C a W h s

T Region: South h a u n M g a n a Zone 9: Front hills C u n hhu P a s Zone 10: Southeastern Bhutan

50 km Zone 11: Piedmont (Duars) Physiographic Region

Figure 3-2 Provisional physiographic zonation of Bhutan (recreated from Norbu et al., 2003)

A

Table 3-5 Physiographic zones within the North-South Valleys and Ridges of Bhutan (recreated from Norbu et al. 2003)

Zone Altitude range Bedrock Landforms Hydrology (m a.s.l.) Northern valleys 2000 – 4500 Gneiss, schist, High N–S* ranges; deep U- valleys Moderate runoff & ranges in W & quartzite & upstream, more V- downstream C* limestone with Inner valleys & 1100 – 4000 intrusions; some High N–S ranges; wide alleys with river Moderate runoff from mid passes in W & C Tethyan terraces & large side valley fans & upper slopes but low from valley floor & lower slopes.

Eastern valleys & 500 – 4000 Gneiss, schist, High N–S ranges; deep, narrow V – Moderate runoff from mid

85 ranges quartzite & valleys; few terraces or fans & upper slopes but low limestone with from valley floor & lower intrusions; some slopes. Lesser Himalayan Rocks

Southern 400 – 5100 Gneiss, schist, High N–S ranges, with plateau High runoff from lower mountains & quartzite & remnants; deep, narrow & steep valleys slopes; moderate from gorges limestone with & gorges higher altitudes intrusions

Merak-Sakten 1500 – 4500 Tethyan High E-W* block; upstream valleys wide Moderate runoff block metasediments with terraces & fans; valleys downstream deeper & steeper

* N-S is North-South, W & C is West and Central, E-W is East-West

The Inner Valleys and Passes include most of the major cities of Bhutan and also have lots of agricultural development. Most of the agricultural development consists of small farms with limited mechanization. This area also has considerable industrial and mining development in some small regions.

The Southern Mountains and Gorges include one of the most developed sites for hydroelectricity in the west, as well as the area for potential hydroelectric development sites. They have also seen development of settlements due to hydroelectricity, and these can be considered to be sites with multiple constructions in new settlements. As well, there has been considerable road development for these settlements.

The Deep Eastern Valleys are the location of major towns in Eastern Bhutan.

Most of the towns tend to be small and are located away from rivers due to the absence of flatlands in the valleys, and the population tends to be sparsely distributed as compared to western Bhutan. One of the biggest hydroelectric projects in terms of water storage lies here on the Kuri chhu. The Merak-Sakten

Block can also be excluded from immediate assessments due to the absence of major development in terms or settlements, agriculture or industries.

As mentioned above, Norbu et al.’s (2003) classification of regions was based on similarity of altitude, climate, bedrock geology, surface drift, landforms, hydrology, soils and natural vegetation. Background geology, soils and surface drift contributes to baseline water chemistry and limitations on the resident fish biota. Altitude, climate and hydrology all affect the quantity and quality of water in the system, and these will be described in the following sections.

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The basic understanding of bedrock geology is a requirement for assessment in terms of its influence on water chemistry and related changes in resident fish (Munkittrick et al., 2000). Each of the zones proposed by Norbu et al. (2003) can be identified with a particular type of bedrock geology. According to Baille and Norbu (2004), much of Bhutan is underlain by high-grade metamorphic rocks and gneiss forms the dominant portion (Figure 3-3). The bedrock is composed mostly of thick sheets of metamorphosed geneisses, quartzites, schists and marbles (Daniel et al., 2003; Baillie et al., 2004). Tethyan metasediments dominate in the higher altitudes in the northern mountains and southern hills and gradually shift towards being dominated by gneiss, schist, quartzite and limestone towards the lower valleys (Table 3-5, Figure 3-3). Baillie et al. (2004) notes that almost 70% of the country is dominated by gneisses.

3.1.2 Climate

The country can be classified into mainly three distinct climatic zones. The southern foothills and the plains, with an altitude of less than 2000 m, have a hot humid climate with temperatures ranging from 15 to 30ºC throughout the year and annual rainfall ranging from 2500 to 5000 mm. The central inner Himalayas, with altitudes ranging from 2000 to 3000 m, have a comparatively cooler temperate climate with an annual average rainfall of about 1000 mm. The

Greater Himalayas, with altitudes ranging from 3000 to 7500 m, have an alpine climate with an annual rainfall of around 400 mm.

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N

W A

88

Figure 3-3 Geological map of Bhutan showing bedrock composition (sourced from Daniel et al. 2003)

The rainfall is heaviest at the onset of the monsoon in the summer during the months of June, July and August (Figure 3-4). This is mainly due to Bhutan being in the Eastern Himalayas, which is among the first to receive the monsoon winds. The south-western and south-central parts receive the highest amount of rainfall in the country with mean annual rainfall well over 4000 mm, sometimes reaching 5000 mm as in the case of Pheuntsholing (Table 3-6). The 2004 rainfall data show the highest rainfall occurring in Sarpang in the south-central part of Bhutan, with total annual recorded rainfall of over 7000 mm (Figure 3-5).

Eastern Bhutan comparatively receives lesser rainfall than western Bhutan due to it lying in the rain shadow of Meghalaya plateau in India (Baille and Norbu,

2004). All of these factors culminate in the presence of various ecological niches within the country, resulting in its rich biodiversity.

Figure 3-4 Average temperature and rainfall for the Lingmuteychu watershed, Bhutan (from RNRRC, 2002)

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Table 3-6 Mean annual rainfall in Bhutan (modified from Baille and Norbu, 2004).

Station Longitude (°E) Altitude n (years) Mean (meters annual above sea rainfall level) (mm) Chengmari 89°03' 430 6 4160 Samtse 89°06' 430 14 4200 Pugli 89°14' 300 6 4270 Phuntsholing 89°23' 420 15 4940 Gedu 89°31' 1980 17 3450 Darla 89°34' 1750 12 3380 Lhamoizingkha 89°51' 170 17 4570 Sarpang 90°16' 330 14 4480 Bhur 90°26' 375 7 4070 Panbhang 90°58' 220 13 4150 Dechenling 91°13' 1000 14 3250 Nanglam 91°14' 550 11 3280 Deothang 91°29' 800 6 3310 Bakuli 91°42' 240 7 3270 Daifam 92°05' 280 10 2830 Ha 89°17' 2620 8 910 Paro 89°20' 2410 16 660 Wang 89°33' 2450 10 740 Thim 89°34' 2210 17 610 Puna Tsang 89°52' 1250 11 762 Mangde 90°31' 2120 14 1321 Chamkhar 90°45' 2590 11 719 Kuri 91°10' 700 13 944 Kholong 91°30' 1830 12 1176 Gongri 91°33' 830 10 890

90

8000

7000

6000 5000

4000

3000

2000 Total Annual Rainfall (mm) 1000

0

e r o g ay r ng aa se khar shel Pa pan ga H ongsa glung angdi tokha n Sipsoo m Lhunts agat Tr Mongar DaganaW Tsirang Sar Yangt a Khat PunakhaKa Jongkha Si Chamas Zhem hi G Pem Pheuntsholing Tas

Samdrup Rain Guageing Stations

Figure 3-5 Total annual rainfall in 2004 (source data from Hydrology Section5, 2005)

3.1.3 Hydrogeology

Hydrogeology has a major influence on local fish habitat. All the rivers of

Bhutan flow from north to south and are mainly 4th or 5th order rivers. There are five major river systems, with a total length of 7200 km (Petr, 1999). All the rivers originate within Bhutan with exception of the Kuri chhu and the Gongri

Twang chhu (Baille and Norbu, 2004).

Baille and Norbu (2004) concluded the river profiles to be effectively different even among the tributaries of the same river system and it is not possible to

5 Hydrology Section: Hydromet Services Division, Department of Energy, Ministry of Trade and Industries,Royal Government of Bhutan, Thimphu, Bhutan

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generate a single generalised profile even within the same river system. The mountainous terrain (Figure 3-6) offers variation in the altitudinal profile of river beds even along the same latitude (Figure 3-7). The terrain also results in very steep descents with multiple waterfalls for some of the rivers offering vast potential for hydropower development. The Kholong chhu in eastern Bhutan is among the steepest, rising at 5000 m and joining Gongri at 1000 m (Baille and

Norbu, 2004). The differences among the river profiles demonstrate the need to develop unique assessments on all the rivers.

The Wang chhu receives discharge from the Thim chhu, Paro chhu, Do chhu and Ha chhu and has a mean discharge of 60 m3/s (Table 3-7). The Mo chhu and Pho chhu together form the Puna Tsang chhu with a mean discharge of over 300 m3/s. Discharge rates for other rivers have been similarly collected and maintained by the Hydromet Services Division, Department of Energy (Figure

3-8) and have been shown in Table 3-7. Figure 3-9 shows the river flow at the main gauging stations previously set up by the Hydromet Services Division. The increasing discharge with high current and unstable soil conditions towards southern Bhutan result in a high amount of sediment load in the rivers when reaching the southern foothills. The sediment load is further compounded by heavier rainfall in the south with associated sediment-laden runoff and flooding.

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N

W E

93

Figure 3-6 Topography map of Bhutan6

6 Map source from http://www.southasianfloods.org/graphic/maps/bhutan/topo.html (Accessed March 15, 2006)

Stepped high valley & low pass in W & C Bhutan

6000 Kang Bum

Dagala 4000

Dochula

(m.a.s.l) Altitude

Thim chhu 2000

Wang chhu

27 N 28 N

Deep valley & high ridge in E Bhutan

6000

4000 Thrumsingla

(m.a.s.l) Altitude

2000

Kuri chhu Manas

27 N 28 N

Figure 3-7 Examples of river gradients and physiographic profiles in Bhutan (modified from Norbu et al., 2003).

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Table 3-7 Discharge and specific runoff from rivers during 2003 (source data from Hydrology Section, 2005)

River Guageing Elevation Mean Maximum Minimum Runoff Stations (ft) (m3/s) (m3/s) (m3/s) (mm) Thimphu chhu Lungtenphug 7473 22.99 37.21 15.55 91.61 Wang chhu Tamchu 6994 60.95 102.20 41.37 63.87 Mo chhu Yebesa 4130 126.83 196.70 84.10 144.35 Puna Tsang chhu Wangdi 3996 303.91 483.80 203.93 127.98 Mangde chhu Dobani 1056 361.27 571.21 251.03 111.00 Mangde chhu Bjizam 6356 72.43 119.45 45.65 137.59 Mangde chhu Tingtibi 1786 135.84 194.00 99.63 112.18 Chamkhar chhu Kurjey 8598 52.95 87.80 33.60 103.53

95 Kuri chhu Kurizampa 1997 466.57 976.86 309.42 143.56 Gongri chhu Uzorong 2103 353.09 554.65 236.31 108.84 Kholong chhu Muktirap 5530 78.29 144.65 39.29 228.35

Key N Hydromet Water Sampling Stations WE Roads u h h Rivers Mo C C o S hhu h P

T h K im H ur C i

P C Ch C

a hu h F C h

C D h h h

h o

u a u C

h C m

h u h

k

h h

ar K u u A D u C h M h o h h as a u B C n u u g g h Ha hh n d h C C a e C hhu h D C e C h h u h m J a g u m I n A

Chhu a A B G D re m e g y

o n N

C a W h s

T h a

u n E M g a n a u n Ch P a hu s

50 km

Figure 3-8 Location of river flow data collection stations (source data from Hydrology Section, 2005)

1000 900 800 700 /s) 3 600 Mean Flow 500 Maximum Minimum 400 River Flow (m Flow River 300

200

100

0

ABCDEFGH I JK Data Collection Stations

Figure 3-9 Flow comparisons among the hydrological monitoring stations (source data from Hydrology Section, 2005). Letters on x axis refer to the stations in Figure 3-8 96

The timing of sampling will be affected by flows, and fish will be most concentrated and easiest to capture during the periods of lower flow. The difference between maximum and minimum river flow in monsoon and dry months is as much as 50 times (Charlton, 1997). It will be important to avoid sampling during the monsoons from June to August, as 90 - 97% of the sediment transport occurs during this season (Sharma, 2002), and flow will be very high. Sediment transport issues are huge, over 4800 t km-2 in some areas

(in Sharma, 2002)

3.1.4 Physical Structure of Rivers

All the rivers (excepting the Manas and Lhobhrak) flow from the Himalayas to the Brahmaputra River. The rivers have a confined channel in narrow valleys and are not navigable (Dubey, 1978). The Amo chhu, Wang chhu and Mo chhu drain western Bhutan and the Manas and its tributaries to the east. The Amo chhu is one of the principal rivers in western Bhutan and begins in Tibet. The river flows rapidly and follows a confined valley between steep mountains, with an average depth of at least 1 m. As it leaves the foothills and enters the Duar plain, it widens into a braided channel. The minimum annual flow of the river is

11.75 m3/s and the river and its tributaries measure a total of 310 km (Dubey,

1978).

The Wang chhu and its tributaries cover a total length of nearly 610 km in

Bhutan (Dubey, 1978). The main river is a rapid stream, running over a bed of large boulders. Between Thimphu and the confluence with the Paro chhu, the

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course of the river is not severely confined but, after leaving the confluence, it runs through a narrow defile between very steep cliffs (Dubey, 1978).

The Paro chhu flows southeast through a comparatively open valley with large boulders. It is joined by several small tributaries flowing from nearby mountains. The Ta chhu, which flows in just above Paro Dzong, joins it from the left. To the west, the Ha chhu drains into the Wang chhu. At Tashichho Dzong the bed of the river is about 2,121 m above sea level and at the point of its exit in the Duar its elevation is only 90 m (Dubey, 1978).

The Mo chhu drains a basin of 9,900 km2, has a total length of 1,810 km, including all its tributaries, and has a minimum annual flow of 53.8 m3/s (Dubey,

1978). At Punakha, it is joined by the Pho chhu and 20 km further downstream at Wangdi Phodrang, by the Tang chhu.

The Manas is the largest river system in Bhutan, with a total length of 3,200 km (Dubey, 1978). Just before reaching Tashigang, the Manas is joined by the

Kulong chhu. At Tashigang the Manas is about 50 m wide, and its waters flow rapidly over a bed of boulders. The river bed near Tashigang is about 606 m above sea level; it is only about 121 m above sea level where it joins the

Tongsa chhu.

3.1.5 Water Chemistry of Rivers

Water quality is determined by the geological conditions the river flows through and by inputs of various effluents from human activities (Munkittrick et al., 2000). Sharma et al. (2005) have classified Nepalese rivers into seven

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classes of river quality based on ecological integrity and water quality. The collection of water quality data is essential in identifying the associated stresses if any were detected during the assessment. The available data from the

National Environment Commission water quality survey of 2003 are reflected in

Table 3-8.

Thim chhu, Amo chhu and Paro chhu showed the highest amounts of E.coli as these rivers flow through the most populated towns and receive inputs from water and sewage treatment plants (Thim chhu and Amo chhu). Highest turbidity was seen in Thim chhu, Paro chhu and Kuri chhu. Dissolved oxygen and pH ranged from 8.3-11.0 (mg/l) and 7.7 to 8.4, respectively. Dissolved ammonium, phosphates and nitrates did not show much variation among the surveyed rivers. Comparative charts for dissolved calcium, magnesium, silicon oxide and total hardness are shown in Figure 3-10 (A, B, C, D). In terms of water quality, hydroelectric development would be expected to have impacts on sediments, nutrients, physical parameters and inorganic contaminants (Greig et al., 1992). Impacts on major ions would be expected to be relatively low, with some influence on biological oxygen demand (BOD), and organic parameters.

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Table 3-8 Water quality survey 2003 by NEC (source data provided by NEC7, 2005)

River Alt Pressure Flow Turbidity pH Dissolved Electrical E.Coli Chemical Ammonia Nitrate Phos- m hPa m3/s NTU Oxygen Conductivity count Oxygen mg/l mg/l phorus mg/l at org/ml Demand mg/l 25˚C µS/cm mg/l Amo 165.0 994.0 52.0 5.5 7.8 9.5 144.5 22.5 2.5 0.2 0.2 0.0 chhu Thim 2340.9 785.2 72.0 28.5 8.2 9.4 200.7 53.9 7.2 0.2 0.2 0.0 chhu Wang 1740.0 847.8 167.3 16.3 8.3 9.5 158.7 15.5 4.3 0.2 0.2 chhu Paro 2370.0 775.0 12.0 8.4 9.0 142.0 26.0 6.0 0.2 0.2 0.0 chhu

100 Ha chhu 3020.0 742.0 2.0 1.7 8.3 8.3 64.7 0.0 2.7 0.2 0.2 0.0 Puna 1033.3 935.9 178.0 9.3 7.9 9.5 104.4 3.0 4.0 0.3 0.2 1.3 Tsang chhu Mangde 1790.0 865.0 16.0 7.0 7.8 11.0 128.0 0.0 1.0 0.2 0.2 0.0 chhu Kholong 1013.3 951.3 56.5 8.7 7.7 10.3 114.7 0.0 1.0 0.2 0.2 0.0 chhu + Gongri chhu Kuri chhu 857.0 960.0 46.5 22.0 8.1 11.0 277.0 2.0 1.0 0.2 0.2 0.0 Chamkar 2575.0 772.5 16.0 3.0 8.0 9.5 108.0 1.0 1.5 0.2 0.2 0.0 chhu

7 NEC: National Environment Commission, Royal Government of Bhutan, Thimphu, Bhutan

A B 30.0 10.0

9.0

25.0 8.0

7.0 20.0 6.0

15.0 5.0

Calcium (mg/l) 4.0 Magnesium (mg/l) Magnesium 10.0 3.0

2.0 5.0

1.0

0.0 0.0 Amo Chhu Thim Chhu Wang Paro Chhu Haa Chhu Punatsang Mangde Kholong Kuri Chhu Chamkar Amo Chhu Thim Chhu Wang Paro Chhu Haa Chhu Punatsang Mangde Kholong Kuri Chhu Chamkar Chhu Chhu Chhu Gongri Chhu Chhu Chhu Chhu Gongri Chhu Chhu Chhu Rivers Rivers

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C 120.0 D 8.0

7.0 100.0

6.0

80.0 5.0

4.0 60.0

Silicon OxideSilicon (mg/l) 3.0

Calcium Carbonate (mg/l) 40.0

2.0

20.0 1.0

0.0 0.0 Amo Chhu Thim Chhu Wang Paro Chhu Haa Chhu Punatsang Mangde Kholong Kuri Chhu Chamkar Amo Chhu Thim Chhu Wang Paro Chhu Haa Chhu Punatsang Mangde Kholong Kuri Chhu Chamkar Chhu Chhu Chhu Gongri Chhu Chhu Chhu Chhu Gongri Chhu Chhu Chhu Rivers Rivers Figure 3-10 Water quality survey 2003 by NEC (source data provided by NEC, 2005): (A) Calcium (B) Magnesium (C) Silicon Oxide (D) Total hardness (Calcium Carbonate)

3.1.6 Land Use

Agricultural activities make up about 5% of land use, and almost all of it occurs within the North-South Valleys (Figure 3-11). Forested land constitutes almost 75% of the surveyed land and 46% of the surface area (Karan, 1987).

This forest cover is the highest among South Asian countries (Sharma, 2002).

Deforestation and mismanagement of forest resources near road areas and overgrazing have resulted in significant soil erosion in numerous areas, and in general sedimentation in rivers is a significant issue.

N

W E

S

Figure 3-11 Land use of Bhutan (from Karan, 1987)

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3.1.6.1 Protected Areas and Parks

Bhutan has currently set aside 26.23% of its land as protected areas (Figure

3-12). It has four national parks, four wildlife sanctuaries and one nature reserve. All are connected by biological corridors to enable migration or movement of fauna among these protected areas. All the river basins run along one or more protected areas along the course of their flow.

3.1.6.2 Industrial Development

Industries in Bhutan can be classified into forest- or wood-based, agro- based, mineral-based and service-based. The development of forest-based industries at the expense of exploiting the forests has been reduced with the government restricting the export of timber. This is due to the government’s realization that forests offer vital ecological benefits and the forestry act states that Bhutan will maintain 60% forest coverage for all time. The restriction on timber exports has seen substantial reduction in deforestation with aggressive reforestation; forest coverage is thought to be increasing. There still exist cottage industries for wooden products such as wooden masks, traditional bowls and cups. The making of traditional paper (daysho), bamboo products, and traditional herbs for medicine also exist as cottage industries for non-wood products. Large non-wood based industries include particle board industries.

Softwood-based industries export broom and tool handles to European countries and tea boxes and wooden shoe heels to India.

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Key

Protected Areas N Biological Corridors Forest Management Units WE Jigme Dorji Wangchuk Roads u National Park h h Rivers Mo C S C o hh h u P Bumdeling Wildlife T h K Sanctuary im u ri

P

C C Ch C

a hu

h h C h

C D

h h h h

h o

u u

a u

C C

h C m

h h u h

k

h h

h a

u u u r 104 Toorsa Sakteng u ThrumshinglaC Strict h M h Wildlife o h h as a Nationalu Park Nature B C n u Sanctuary u g g h Ha hh n d h Reserve C C a e C hu h D C e Ch h Jigme Singye h u h m a g Wangchuk u m n A

ChhuChhuChhu a A National Park e D r m e g y

o n N

C a W h s

T h a u n M g a n a C u n hh P a u s Khaling National Wildlife Sanctuary Royal Manas Phibsoo Wildlife National Park Sanctuary 50 km

Figure 3-12 Protected Areas of Bhutan (recreated from DOE, 2004)

The Department of Geology and Mines provides mapping, resource exploration and technical services in Bhutan and also regulates the mines so that their functioning is environmentally friendly (DGM, 2005). Bhutan’s mined mineral resources consist of gypsum, limestone, marble quartzite, coal, slate and talc (Table 3-9) (USGS, 2006). Almost all of the mining is carried out in southern Bhutan, except that of marble slate and dolomite (Figure 3-13). Marble is mined in Gidakom near Thimphu and slate is mined in Wangdiphodrang.

Dolomite, gypsum and limestone are used in the cement and calcium carbide factories; most of the manufactured product is exported to India. Quartzite is used in the manufacture of ferrosilicon, which is exported to India and Japan.

Table 3-9 Minerals and location of mines in Bhutan (compiled from USGS, 2006)

Minerals Mine Location

Gypsum Khotakpa, Pemagatsel

Coal Bhangtar, Chenangri, Deothang

Dolomite Samtse, Mongar, Samdrupjongkhar, Shemgang

Marble Gidakom

Slate Wangdiphodrang

Talc Kalapani

Limestone Haurie Khola and Rongri, Pugli, Duarpani, Kalesore and Titi

Quartzite Tintali, Suktikhola and at Kamji

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The by-product of manufacturing ferrosilicon, microsilica, is also exported.

Quarrying of boulders and sand is carried out in river beds during the dry season in some parts, mainly for construction. The existing mining industries and mineral-based industries are strictly required to conduct proper environmental impact assessments both before initiation of a project and on a periodic basis afterwards, to prevent any detrimental effects on the surrounding environment.

Agricultural industries such as food processing plants (fruit juices, fruit jams, pickles, dairy, and distillery) exist mainly in southern Bhutan (Figure 3-13). The progress of the agro-based industries inherently depends on the performance of the agriculture sector. Though there has not been much expansion in agricultural lands due to limited availability of agricultural land, intensification programs initiated by the government in the existing agricultural lands (by educating the farmers and providing subsidies for agricultural tools, such as machinery and quality seeds) have resulted in sustaining agro-industries fairly well within the regional market.

A recent boost in service industries such as construction and tourism has helped Bhutan to mitigate unemployment. The increase in employment has been due to initiation of construction of mega-projects such as the Tala and Kuri chhu hydropower plants as well as increases in tourism. Though the construction of hydropower plants is perceived as being a benefit to Bhutan’s economy in the coming decades, environmental damages during construction

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Key Large Hydropower Sites (2006) Mines (Gypsum, coal, Cement Factories dolomite, marble, slate, Large Hydropower Sites (1012) Food Processing limestone, talc, quartzite) industries (Fruit Large Hydropower Sites (2017) Water and Sewage products, distilleries, Large Hydropower Sites (2023) Treatment Plants dairies, beverages, etc) Major towns with road access u h h Chemical Industries Hydromet Water Sampling Mo C C o (Calcium Carbide, Stations hh h u P Ferrosilicon, candle, Roads plastic, polythene, Th etc) Rivers K im u ri

P C Ch C

a hu h C h

C D h h h

h o

u a u C

h C m

h u h

k h

h a

107 u u r u C h M h o h h as a u B C n u u g g h Ha hh n d h C C a e C hhu h D C e C h h u h m a g u m n A

ChhuChhu a A D re m e g y

o n N

C a Wa h s N h T u n M g a n a u n C a hhu P WE s

50 km

S

Figure 3-13 Map of Bhutan with location of industries, mines, sewage treatment plants, dams, major towns, water sampling stations, roads and rivers

and during operation are unavoidable. These types of projects will call for more environmental vigilance; other similar projects are likely to be launched in the future.

3.1.7 Dams and Reservoirs

Many of the rivers of Bhutan have seen fast development of run-of-the-river stations, peaking stations, or hybrids of both in the past two decades. The power sector aims to generate 20,000 MW of power by the end of the 10th Five

Year Plan (2012) and add another 5,000 MW by the end of the 11th Five Year

Plan (2017) (DOP 1999). The first major dam, Chukha (336 MW), was commissioned in 1986 and currently the major hydropower dams include Baso chhu Phase I, Kuri chhu and Baso chhu Phase 2 with total generation capacity of 460 MW (Figure 3-14). The newest mega hydropower station at Tala will be commissioned in June 2006. Additionally, smaller dams affecting rivers and streams have been constructed since the 1960s.

The most impacted river, by number of dams, is the Wang chhu. The Wang chhu already has two major dams at Chukha (336 MW) and at Tala (1020 MW).

Another dam, Chukha II (500 MW), is also planned (DOP, 1999). In the east, the

Kuri chhu has seen the development of a major dam with a high-capacity peaking facility generating 60 MW. The Baso chhu (24 MW) is a run-of-the-river type station on the Baso chhu, a tributary of Puna Tsang chhu. The Baso chhu I

(40 MW) located further downstream has water flow from the tailrace of Baso chhu and Ruri chhu.

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3.2 Factors Affecting Sampling Design

The previous overview has examined the basic background information to tailor a study design for the specific region of interest. This information will help define the scope and magnitude, and limitations, of the study design. The main focus of the monitoring program for Bhutan, based on the geographic information, will be related to monitoring of the North-South valleys where the hydroelectric development will take place (Figure 3-14). The geology, physical structure, local climate, hydrogeology, industrial development, and water chemistry place restrictions and offer opportunities to optimize study designs

(Table 3-10).

There will not be many confounding factors in the North-South Valleys because of low population densities and low development of agriculture, and most of the industry and mining take place in the southern plains. However, the systems will be largely forested, prone to high sediment inputs, and road access will be limited. The inability to travel the rivers in boats will largely restrict sampling to areas with road access. Consequently, sampling in some future areas of development will need to wait for road access to the areas.

Sampling should avoid the monsoon season in June-August because of high flows and high sediment transport during these periods. Sampling should not use fish that spawn in the fall after these periods, as impacts of water flow regulation and fluctuations will probably be largest prior to the monsoon season.

Therefore, it will probably be best to sample between March and May.

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Key Large Hydropower Sites (2006) N Large Hydropower Sites (2012) Large Hydropower Sites (2017) WE Large Hydropower Sites (2023) u h Rivers h S Mo C Ch o Roads h h u P

T h K im u ri

P C Ch C

a hu h Ch h

C D h

h o h

u a u C

h C m

h u h

k h

h a u u r u Ch h M hu aso h a B C ngde 110 u u g h Ha hh n h C C a C hhu h D C e C h hhu u m a g m n A

ChhuChhu a A D re m e g y

o n N

C a W h s

T h a u n M g a n a u n Ch P a hu s

50 km

Figure 3-14 River systems of Bhutan with location of large hydropower development sites8 (includes existing developed sites and future planned development to 2023)

8 Location of Hydropower sites taken from “The 2003-2022 Power System Master Plan Final Report – Executive Summary” (DOE

2004)

Table 3-10 Influence of system characteristics on design for fisheries studies

Characteristic Restriction Rationale or Consequences Physiographic zones Restrict studies primarily to North-South central Location for hydroelectric valleys development

Climate Avoid monsoon season in June-August Avoid high flow, high sediment deposition Hydrogeology Probably sample March-May

Physical Structure of Not navigable, high flow Will restrict sampling gear types Rivers

111 Land Use Largely forested, small agriculture, road system Restricted access poorly developed

Protected Areas and Not available for sampling Parks

Industrial Industrial development and mining towards Not a lot of confounding factors in Development southern plain North-South Valleys

Dams and reservoirs Series of existing, proposed and planned Allows development of tiered, and developments sequential sampling

The fish species that offer the most sensitivity will be ones that are spawning or preparing to spawn in the time periods leading up to the monsoon season. At least two species should be examined, one that spawns in the nearshore area prior to or at the start of the monsoon season, and a second that is preparing to spawn during this time period.

The fish capture techniques will have to consider the fast current, in systems that are not navigable; these factors will restrict sampling gear types. The most suitable sampling options will include angling, long-lining and cast-netting.

Back-pack electroshocking should be used to examine potential small-bodied species, and to examine growth rates and size-distributions of juveniles. The most sensitive designs will include species in which the juvenile stages are spent in the mainstream of the river systems.

Considering these limitations on the sampling design, the next phases of the sampling design are to select the study sites, design the sampling schedule, select the relevant endpoints, and select the sentinel species.

3.3 Site Selection

Proper sample site selection is very important for monitoring studies. In the case of Bhutan, most of the rivers are experiencing very fast development, either through hydropower construction on the river or growth of urban and industrial areas near the rivers. Therefore, it becomes necessary to prioritize sampling schedules for specific sites to keep pace with development and to

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identify specific effects associated with these developments, or the nature of questions asked during assessments (Munkittrick et al., 2000).

Greig et al. (1992) examined study design needs for hydroelectric development, and recommended that researchers:

1. Study existing sites on regulated rivers with upstream (reference), reservoir

and downstream sites,

2. Study reference sites on a) unregulated rivers, b) sites during different

periods of operation to understand how changes in operation affect habitat,

and c) future development areas before, during and after development, and

3. Establish experimental sites to conduct detailed studies.

Relevant sites are available in Bhutan for all of these options (Table 3-11).

3.4 Selection of Sampling Design

Bhutan presents a complex system, whereby rivers differ even along the same latitude due to the changing altitude and difference in river sizes. It is important in this case for reference sites to be selected for river size and altitude; until more is known about the distribution of fishes in the study area it is not possible to have a final study site selection.

However, some preliminary designs can be stated. It is important to have study sites on as many rivers as possible, and study designs sometimes use both local reference sites that have closely matched conditions, and regional reference sites to provide information about regional changes. The regional,

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Table 3-11 Potential sites for development fisheries studies in Bhutan

Goal Focus Potential Rivers Priority Background Data Available Establish Development of methods, baseline Upper tributaries of 1 NWWFCC, 2001 experimental sites information of fish biology Wang chuu to conduct detailed studies

Monitoring Studies Existing sites on regulated rivers with Wang chhu 2 Flow data only upstream (reference), reservoir and Kuri chhu downstream sites

Study sites on unregulated rivers Dangme chhu* 4 Flow data only 114 Study sites during difference periods Wang chhu 2 Flow data only of operation to understand how changes in operation affect habitat Study future sites before, during and Puna Tsang chhu 3 Flow data only after development Mangde chhu Chamkar chhu

Examine potential Examine potential future confounding Thim chhu 3 Charlton, 1997 for industrial or factors (sewage) sewage (Thim chhu and sewage impacts Amo chhu) Pa chhu (agriculture) None for agriculture input Amo chhu (urban) Petr, 1999 for Amo chhu

* Additional sampling on future development sites will contribute to understanding variability in unregulated rivers

long-term study site should be selected at an area with good accessibility, and the upper tributaries of the Wang chhu make the most sense.

It is also necessary to examine sites that are exposed to sewage and industrial waste, so that an understanding can be developed about potential future impacts associated with expanding stresses (Table 3-11).

It may also be necessary to take into consideration the wide changes in water temperatures between north and south or rivers at higher and lower altitudes. This may be a factor that results in different fish communities even along the same river. A provisional line depicting warm and cold water has been shown (Figure 3-15), but the line does not take into consideration the low rivers which are also warm above the line. Identification of divisions among fish communities due to water temperature or altitude may be refined during subsequent sampling.

Baseline fish community surveys are important for Bhutanese rivers as the community structure of fish in these rivers remains unstudied. These baseline studies can be used to identify the types of fish present in the system (seasonal or non-seasonal), the types suitable for monitoring studies (sentinel species), and the selection of reference sites. Community studies may involve using various means to catch fish and techniques for monitoring studies may be refined during these studies for different rivers.

In monitoring studies, it is important to study the residency of the fish to make sure they are not moving between affected and reference sites

(Munkittrick et al., 2000). In the case of Thim chhu (Figure 3-15), monitoring

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Key

Large Hydropower Sites (2006) Proposed Fish Mines (Gypsum, coal, Cement Factories Sampling Sites dolomite, marble, slate, Large Hydropower Sites (2012) Food Processing limestone, talc, quartzite) industries (Fruit Large Hydropower Sites (2017) Water and Sewage products, distilleries, Large Hydropower Sites (2023) Treatment Plants dairies, beverages, etc) Major towns with road access Chemical Industries Hydromet Water Sampling u h (Calcium Carbide, Stations h Mo C Ferrosilicon, candle, C o hh h Roads u P plastic, polythene, etc) Rivers T h K im u ri

P A Ch Ch F Ch a hu C

C D h N E h h

h o

u

D a u C

116 h C m F h

u h H

k h

A h a

u WE u A2 r E u C h M h A o h h as a u G S B C ng u u g h H hh n de h aC C a F C u h D hh 1 D C e H C h A hhu u m a g m n A

ChhuChhu a A E D re m e B g y

o n D N

C a 1 W h s G 1 T h a u n B Cold Water M g a n a C u n Warm Water hhu P a s C C1 50 km

Figure 3-15 Proposed fish sampling sites and location of current and proposed development

studies between site A1 (effected by urban and sewage effluent) and site A

(reference site above settlement) may yield inconclusive results if fish moved between the sites due to absence of barriers. In this case it may be necessary to study the residency of fish through techniques such as mark and recapture techniques or by using stable isotope analysis to identify residency issues.

3.4.1 Development of Methods and Approach

The top priority for sampling will be conducted on the Wang chhu river system. The Wang chhu is probably one of the most developed rivers and is undergoing further development at the present time. The Wang chhu river system is made up of three main tributaries, the Thim chhu, Pa chhu and the Ha chhu. All the tributaries and the main river are in turn fed by many smaller rivers and streams offering good fish spawning habitat. A detailed study was conducted to survey the water quality and status of fish populations in these rivers in 2001 (NWWFCC, 2001). Although observations were made by the study team regarding water quality and the occurrence of illegal fishing, the team conducted sampling entirely with throw/cast nets, which isn’t suitable for fishing in these types of rivers. Therefore, the population survey of fish would be inconclusive.

Initial sampling would involve refining fish sampling techniques in these rivers with the use of various methods such as long-lines, angling, electro- fishing and gill netting in some parts of the rivers for community surveys. Angler

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surveys should also be considered for increasing sample sizes, as information on length, weight and age could be easily obtained.

3.4.2 Baseline Data for Reference Sites

Multiple sites can be selected on the Wang chhu river system. Munkittrick et al. (2001) notes that selecting multiple reference sites can strengthen the study by improving the understanding of differences among reference sites outside the influence of stress. Multiple reference sites on the Wang chhu river will be selected upstream of development and urban settlements (Figure 3-15, Site A) based on prior knowledge of developments on the rivers. As there are no barriers restricting fish movement, it may be necessary to understand how far fish move within the system by mark-recapture methods and stable isotope methods. Use of various types of fishing methods will be necessary to understand the community composition and structure in these rivers. The

NWWFCC (2001) survey was able to confirm only two types of fish, the brown trout (Salmo trutta) and the snow trout (Schizothorax progastus). Iterative sampling during all seasons have to be initiated to understand the life-history pattern of these fish and to know if there are occurrences of other fish in the system, as well as their life history.

The comparison of reference sites on Thim chhu, Pa chhu and Ha chhu will yield important information on differences among sites and rivers on the same system.

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3.4.3 Among River Reference Comparisons

There is the possibility to sample upstream areas of all major river systems, upstream from existing and potential developments, to collect comparative information. Sites that are comparable to the Wang chhu (Sites A) could be selected in the upper reaches of the Mo chhu, Mangde chhu, Changku chhu and Dangme chhu (sites D, E, F and H; Figure 3-15) to assess inter-river differences in fish community composition among the systems. It may be possible to detect differences between Wang chhu, which experienced repeated brown trout introductions, and some of the other rivers, which may have native fish populations.

3.4.4 Altitudinal Reference Sites

Altitudinal comparisons can be made among rivers on the same latitude using GPS navigation. The most powerful sampling designs are designs that can sample the same sites before and after developments occur (Environment

Canada, 2005a), and future hydroelectric developments will occur on the Amo chhu (planned feasibility study 2010), Puna Tsang chhu (Site D; 2011, 2015),

Mangde chhu (Site E; 2013), Chamkhar chhu (Site F; 2019, 2022), and Kholong chhu (Site G; 2023) (Figure 3-15). Sites should be selected upstream and downstream of the proposed developments. Baseline data collected prior to development will be useful in understanding species distribution patterns, and in helping develop mitigation plans to reduce the impacts of potential

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developments. Continued monitoring after development at these sites will be required.

In some cases, road access would currently limit sampling, but sampling should be initiated as soon as access becomes possible.

3.4.5 Longitudinal Comparisons of Developed Sites

There are existing sites with hydroelectric development on the Wang chhu

(sites A1, B1), Amo chhu (C1) and Kuri chhu (G1). As soon as methods are developed and refined, sampling should be initiated at upstream and downstream sites in these locations (Figure 3-15).

3.5 Endpoint Selection

There has been considerable in Canada over the last decade related to endpoint selection as the environmental effects monitoring (EEM) programs have developed. EEM programs exist for point source effluents associated with pulp and paper mills (Walker et al., 2002), metal mining operations (Ribey et al.,

2002), and sewage treatment plants (Kilgour et al., 2005). There has been some discussion of developing similar monitoring programs for hydroelectric facilities

(Munkittrick et al., 2000), and recent recommendations for monitoring techniques for species abundance and species composition near hydroelectric facilities (DFO, 2005).

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The river systems available in Bhutan offer opportunities for the development of tiered, and sequential sampling programs. The focus of this study design will be specifically to understand the impacts of hydroelectric development on fisheries resources, because hydroelectric development is the biggest potential impact facing Bhutan’s rivers.

The focus of the study designs for Bhutan need to focus on the specific stresses associated with development and operation of hydroelectric facilities.

The main impacts of hydroelectric development include changes in quantity, quality and distribution of fish habitat, shifts in species composition, spawning failures in shorelines, spawning species affected by drawdowns, initial increases in productivity, changes in harvesting and use of fish, physical damage to fisheries resources, confinement and restriction of fish, and changes in migration patterns and access to habitat, with a fragmentation of populations

(Table 3-12).

Fish populations can show a variety of responses to these kinds of stresses, and these have been analyzed and summarized by Munkittrick et al. (2000).

The responses associated with a hydroelectric development would usually be confined to impacts on food and habitat, and would be analogous (depending on the species) to exploitation responses (increased food), recruitment failure

(disruption of spawning habitat) and food limitations (loss of food resources)

(Table 3-13).

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Table 3-12 Potential stresses associated with hydroelectric development (created from Greig et al., 1992; CEA, 2001; DFO, 2005)

Potential Potential Stress Potential Impact Development Action Reservoir Deforestation, erosion, decomposition of waste Changes in habitat clearing plant material, exposing soils Reservoir Change in depth, morphometry, erosion and Changes in habitat, shifts in species flooding sedimentation, potential mobilization of mercury, composition, shoreline spawning affected by changes in ground water reserves, changes in drawdowns, initial increase in productivity primary production and energy flow Transmission Deforestation, road access Changes in habitat and harvesting of fish

122 line construction Road Deforestation, road access Changes in habitat and harvesting of fish construction Construction Changes in access, water use and recreational Potential impacts on fish populations camps fishing Extraction of Erosion, sedimentation Impacts on habitat, feeding construction materials Dam Redistribution of energy, change in flow, change Changes in quantity, quality and distribution operation in temperature, nutrients and sediments of fish habitat, Turbines, Changes in water velocity, oxygenation Physical damage to fisheries resources, spillways confinement and restriction of fish Diversions Changes in water depths, velocities, Changes to habitat Fish Changes in migration patterns and access to passage habitat, fragmentation of populations

Table 3-13 Generalized response patterns of fish populations to changes in populations (from Munkittrick et al., 2000) Generalized Cause of Changes Follow-up study Age Energy Energy Pattern Distribution Utilization Storage

Exploitation Decreased competition between Examine food resource Shift to Increased Increased adults associated with mortality or availability and population density younger eutrophication

Recruitment Shift to older age classes associated Detailed examination of spawning Shift to older No change No change Failure with decreased reproductive success habitat, utilization and reproductive development

Multiple Simultaneous impacts on food Detailed studies of reproductive Shift to older Decreased Decreased Stressors availability and reproductive success development and food resources

123 Food Increased competition associated with Examine food resource No change Decreased Decreased Limitation increased reproductive success or availability and population density decreased food availability

Niche Shift Modest increase in competition for Examine food base and No change Decreased No change forage base competition aspects

Metabolic Inability to maximally utilize available Detailed physiological studies of Shift to Mixed Mixed Redistribution food resources energetics younger

Chronic Shift to small population of older Detailed study of reproductive Shift to older Increased Increased Recruitment individuals performance or Failure decreased

Null response No obvious changes Check population size data to see No change No change No change if carrying capacity of the system has changed A shift in age distribution can be indicated by mean age or larger samples for ages of the population. Energy utilization can be reflected in growth rate, reproductive rates or age at maturity. Energy storage can be reflected in condition factors, liver size or in lipid storage levels.

The type of recruitment failure associated with hydroelectric development would either be because of dewatering of nearshore spawned eggs, or blockage of migratory routes and access to spawning sites. Both recruitment failure and increased productivity and habitat result in the same kinds of changes in fish – there are fewer fish and more resources so the fish grow faster, reproduce more, are fatter (higher condition) and mature younger (Munkittrick et al., 2000).

The patterns can be differentiated by an increase in the abundance of younger fish for increased habitat, and a decrease in terms of recruitment failures. Food limitation reduces the growth rates of fish, and the fish have lower condition.

The expected stresses affect the abundance, diversity of fish species, age distributions and growth. The impacts will be associated with habitat alterations, changes in productivity and in sedimentation. So the main types of responses that should be associated with hydroelectric development would be relatively easy to detect during standardized monitoring by measuring relative species abundances, growth rates, age distributions and condition (a function of length and weight of fish).

Greig et al. (1992) summarized the specific information needs related to hydroelectric development as: a) understanding distributions and abundance of fish species in the region, b) determining baseline fish habitat needs, including information on temperature, substrate composition, depth, cover, oxygen, pH, suspended solids and food availability, c) predicting changes in habitats associated with development – information on flow, water quality, and sediment

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transport, and d) developing models that predict impacts of habitat change on changes in fisheries resources.

The sampling program should also include information on water quality, temperature, sediment load, and mercury, which would all be expected to be affected by hydroelectric development. Baseline surveys of other heavy metals should also be investigated in water samples. A key issue will also be the flow of energy, and the mobility of fish, which can both be tracked using stable isotopes (Gray et al., 2004; Cunjak et al., 2005). The fish issues of importance will be parameters that will respond to habitat, movements and spawning and abundance (Table 3-14).

The key aspect of information that will need to be developed once sampling begins in Bhutan will be the measurements that will be used to document growth and energy use in fish. The next chapter will examine these issues using fish collected from the Saint John River near hydroelectric developments.

3.6 Selection of Sentinel Species

The life-history characteristics and biology of fish species can dramatically affect their suitability as sentinel species for monitoring programs (Munkittrick et al., 2000). A long-lived species that does not mature sexually until they are 15 to 20 years old, and spawns only every 2 to 3 years, would not be as sensitive to impacts associated with reproductive toxicity as one that matures rapidly, has a high fecundity, and spawns regularly. The main factors for selecting any

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sentinel species are that they are present in abundance, they are exposed to the stressors of interest, and the endpoints that are desired can be acquired

(Environment Canada, 1997). For instance, in a non-lethal sampling program, a fish that can be easily aged (e.g., by scales or length-frequency analysis) is more desirable than one that is difficult to age.

Table 3-14 Indicators that should be addressed in the monitoring program (adapted from Ribey et al., 2002)

Concern Endpoints Indicators Initial Periodic (historical data) Monitoring Monitoring Community Community Presence/absence Relative composition Abundance of abundance species CPUE* of Rare/endangered species species Population Abundance Abundance Size vs. Age Size vs. Age Growth Average age Average age Reproduction Relative year Relative year class strength class strength

Health Condition Condition Condition Physical Factor Factor abnormalities Physical Physical abnormalities abnormalities Exposure/ Stable isotopes Stable Residency isotopes Fish Contaminant Metals levels in Tissue Tissue usability levels tissues concentrations concentration of mercury s of mercury

* CPUE: Catch Per Unit Effort

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For fish that are abundant, can be measured, and are exposed, there are a variety of other life-history characteristics that are important for sensitivity.

These include longevity, food preference, reproductive investments and growth rates, and spawning time (Table 3-15). The factors need to be examined site- specifically for study designs. For Bhutan, and for a non-lethal sampling program, response time and sensitivity will be shorter for a short- to medium- lived species. In very old fish, aging from non-lethal structures becomes more difficult as growth slows in older fish.

Capture success for non-lethal sampling may be higher for piscivorous fish, as angling success will be higher, although these species commonly have a larger home range. It will be useful to examine multiple species; the Canadian

Environmental Effects Monitoring (EEM) program recommends at least two species (Environment Canada, 2005).

Fish with a high reproductive rate and early maturity will respond more quickly to changes in energy use. With concerns about dewatering associated with fluctuating flows, it will be useful to use a fish that spawns nearshore as at least one species. Fish with a fast growth rate will be easier to age, so fish with a larger size and a lifespan of <10-15 years would be preferred for at least one sentinel species.

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Table 3-15 Sentinel species characteristics for optimizing effects-driven assessment of aquatic environmental health using fish populations (modified from Munkittrick et al., 2000)

Characteristics Fisheries Health Human Comments Point Non-point Health Source Source Residency (in Local Wide Issue- For non-point source impacts, need a species that will integrate the signals from absence of ranging specific the area. barriers) Abundance High High Issue- For human health, there may be local concerns associated with food preferences specific and consumption that outweigh all other factors. Longevity Short- Short- Long For fisheries health issues, long-lived species will decrease the likelihood of medium medium detecting changes. For human health, long-lived species increase the body burdens and possible consequences of exposure. 128 Food Benthic Issue- Piscivorous For human health, want a species that is at the top of the food chain. For other preference specific issues, this would be associated with (usually) increased mobility. Fecundity and High High Low High energetic requirements are preferred, so that changes in food availability or growth rate quality will be detected quickest. For human health, retaining body burdens by slow growth and reproduction would be preferred. Age to Short Short Long For impacts on fisheries health, species that need energy for initiation of spawning, maturation while retaining needs for fast growth will show impacts sooner; for human health, delayed maturity reduces the clearance of contaminants in females associated with spawning. Spawning time Site- Site- Site- The relationship between exposure and spawning time will vary with the issue. In specific specific specific prairie systems, spring spawning fish develop eggs over-winter, during maximum exposure from point-sources. In other systems, maximum exposure occurs during the late summer or fall. Food chain Yes Yes Yes Always want a species with an aquatic-based diet, and not one depending involvement predominantly on terrestrial-based foods.

Spawning time is a site-specific and issue-specific criterion. As mentioned above, a fish that spawns near-shore would be preferred in at least one species.

The preferred sampling time is March to May (Table 3-15), so selecting a fish species that is in the process of investing energy in reproductive development would be sampled. It is easiest to detect disruptions of food availability during this time period. An exception would be species for which young-of-the-year could be easily sampled prior to the onset of the monsoon season’s high turbidity and flows.

As there is very little baseline data available on Bhutan’s fish species, the sentinel species for monitoring studies should be selected through initial community surveys. This is similar to the pre-design sampling component of the

EEM programs in Canada, where the focus of the community data is the determination of potential sentinel species and relative abundances. Data on abundance from catch is highly variable (see Munkittrick et al., 2000), and are difficult to use for decision-making.

The usefulness of small-bodied fish in monitoring assessments has been shown in studies conducted on the Saint John River in Canada (Gray et al.,

2002). There is a lack of knowledge on occurrence of small-bodied fish in

Bhutanese rivers. Community surveys using different techniques could yield information on existence of such small bodied fish and their life history could be looked at for monitoring purposes.

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3.6.1 Life History Characteristics of Native Species

Bhutan currently lacks any detailed survey and baseline information on the distribution and abundance of its aquatic fauna. The current knowledge of fish of

Bhutan is a documented list of 41 species found in rivers and lakes of southern

Bhutan (Day, 1873; Dubey, 1978; Dhendup and Boyd, 1994; Shrestha, 1998;

Petr, 1999). This survey used chemical sampling (Petr, 1999), which is not suitable in the fast-moving rivers in the North-South Valleys. Most of the species found in Petr’s (1999) survey are warm-water species which may not be present in the hydroelectric development area.

There are no background data on fish in the North-South Valleys other than the survey conducted by NWWFCC (2001). They found snow trout and brown trout in the Wang chhu system. From that study, snow trout have a ventral mouth, a long digestive tract (2.5 X body length) and stomach contents of algae and some aquatic insects. Brown trout stomach contents included aquatic insects, small crustaceans and small fish (NWWFCC, 2001). The current importance of the aesthetic value placed on snow trout by the government and communities (NWWFC, 2001) may make it a possible candidate for sentinel species after its abundance, mobility and response to stressors are known.

A detailed survey is needed to identify species which may be suitable as sentinels. Snow trout may not be an ideal candidate species. They spawn in

September or October, and migrate to small tributaries. Although the migration means that they may be captured in higher numbers at spawning time, their growth and reproductive characteristics will be a function of the location where

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they are resident. Detailed studies would need to be conducted on the home range and behaviour of the species to understand its suitability as an indicator.

However, because of its high aesthetic value, it should be part of the monitoring program. It is assumed that the information integrated by the trout would encompass a relatively large geographic area, but they would be sensitive to issues surrounding mobility and access to limited habitats.

Local community and government concerns also sometimes play a role in indicator selection. However, stakeholders may not always select the species that are the most sensitive or responsive to changes. One criterion that is important is the presence of rare, threatened or endangered species. The

Bhutanese government has shown concern about the decreasing population of snow trout (NWWFCC, 2001). It also stopped stocking brown trout in Wang chhu based on its possible effect on the snow trout population. Evaluation of performance and recruitment data of specific fish species on each river will be necessary to determine the state of the population. Community surveys on selected sites can give a clear picture of the status of fish populations in rivers of Bhutan and it may be possible to identify any endangered species.

3.6.2 Sample Size Requirements

The Canadian EEM program uses a minimum sample size of 20 adult males and 20 adult females for monitoring (Environment Canada, 2005a) and a sample size of 100 for non-lethal estimates of size distributions (Environment

Canada, 2005b). If back-calculations of growth are used, sample sizes need to

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focus on relatively large numbers of fish (n=12) of a single cohort to increase the power of comparisons between sites (Ruemper, 1998).

Sampling designs are better if they are based on local information, but there are no baseline data available for any species in Bhutan other than for the ranges of length of snow trout and brown trout captured by cast-netting

(NWWFCC, 2001). Sampling size calculations require information on variability, power (1-β), levels for statistical significance (α) and effect size. Variability information is not available for Bhutanese species. The Canadian EEM program recommends that β and α levels be set equally (0.05 or 0.10) (Environment

Canada, 2005a), and recent advice for effect sizes recommends goals of detecting a difference of 25% for growth and 10% for condition (Munkittrick et al., 2006).

3.7 Final Study Design: A Fisheries Assessment Program for Bhutan

The lack of any existing monitoring program and lack of any data on existing fish populations have increased concerns about fishery resources in Bhutan.

The following study design meets the criteria set out in this thesis.

3.7.1 Schedule of Sampling

A preliminary sampling schedule has been framed depending on the importance placed on the phase of development on the rivers (Table 3-16). The schedule takes into consideration current developments and known potential

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Table 3-16 Sample sites and schedule for studies on Bhutan’s rivers (refer to 2.16 for site locations), lethal sampling monitoring studies

Site River Site Type 2007 2008 2009 2010 A Thim chhu, Reference sites, Pa chhu, Ha (upstream of chhu settlements and development)

A1 Thim chhu Sewage effluent & below urban area

A2 Pa chhu Below agricultural area

B Wang chhu Reference site

B1 Wang chhu Below dam site

C Amo chhu Reference site

C1 Amo chhu Sewage effluent & below urban area

D Puna Tsang Baseline community chhu survey, future development

E Mangde chhu Baseline community survey, future development

F Chamkhar Baseline community chhu survey, future development

G Kuri chhu Reference site

G1 Kuri chhu Below dam site

H Dangme chhu Baseline community survey

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future developments affecting the river systems of Bhutan. The schedule may be altered and refined as and when necessary based on urgency due to unforeseen development during the designing process or during the study period. In monitoring studies, iterative follow-up studies can be conducted to verify conclusions from earlier studies.

3.7.2 Selection of Species

Much of the validity of monitoring results is based on the choice of sentinel species. The potential sentinel species for monitoring purpose must be selected correctly during the initial community baseline studies. The evaluation of the requirements of its responsiveness to stress, site fidelity and other life-history characteristics may be further refined during iterative follow-up studies. To get detailed and complete performance data on the fish it is necessary to lethally sample the fish on the selected sites until baseline data have been collected

(Table 3-17).

3.7.3 Sampling Considerations

The initial surveys should be focused on studying the structure of the fish communities in Bhutan. The studies for building a baseline performance database would include collecting important information regarding: body weight, fork length or total length, liver weight and gonad weight. The community database would include information on distribution and abundance of fish

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Table 3-17 Recommended fish survey measurements to determine effects in fish growth, reproduction, condition and survival (adapted from Ribey et al., 2002)

Measurements Expected Recommended Reporting Precision Length (fork or total or standard)* +/- 1mm Individual measurements, mean, standard deviation Total body weight (fresh) +/- 1.0% Individual measurements, mean, standard deviation Age +/- 1 year (10% to be Individual measurements, mean, independently standard deviation confirmed) External condition NA Obvious abnormalities, prevalence of lesions, tumours, parasites, etc. Sex NA Male, female, immature * If caudal fin forked, use fork length. Otherwise, use total length. In cases where fin erosion is prevalent, standard length should be used

species in the studied sites. Aging structures (scales, opercula, spines, vertebrae, and otoliths) may also be collected lethally and non-lethally for basic understanding of the potential for applying aging techniques for monitoring studies in Bhutan.

The use of scales in back-calculating growth of yellow perch along the Saint

John River has shown that site differences in performance of fish can be detected non-lethally. Aging and back-calculating growth of fish can give important information on effects of development on fish population on a chronological basis. The effectiveness of aging techniques of fish selected for monitoring should be considered for detecting effects of developments on fish populations in the rivers of Bhutan. The available non-lethal aging techniques for monitoring fish performance have significant value as they comply with the conservation principles of the government. Other non-lethal methods such as

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site comparison of body size can also yield important information on performance of fish in a system (Table 3-17).

3.7.4 Monitoring Program

The underlying significance of this research lies in its contribution toward development of non-lethal techniques for ecological studies. Non-lethal techniques are increasingly gaining importance in ecological field studies due to their adherence to conservation policies. This research will promote understanding of important aspects of fish growth characteristics upstream and downstream of dams. The knowledge of detailed life-history characteristics of fish in affected systems is vital for identification of effective mitigation measures.

In addition, the project will assist in delimiting the impacts of hydroelectric dams from those of other stressors caused mainly by discharge of various effluents in the Saint John River system.

There are a number of ways to examine size of fish that will be important to evaluate effectiveness of a non-lethal sampling program: size of fish captured, size-at age, length-frequency, and back-calculations of the rates of fish growth.

The sampling program will strengthen Bhutan’s capability to monitor and manage its fisheries resources during the next phase of development.

It will be important to coordinate essential information on water flows, water chemistry, temperature, flow data and the fisheries assessments. Many of these functions currently rest in different government departments, and

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discussions will need to take place regarding the best mechanism to coordinate this information.

3.8 Conclusion

The primary objective of the thesis was to develop a framework for a fish monitoring program for Bhutan that could be used to evaluate potential impacts of hydroelectric development on Bhutan’s river systems. The study reviewed different growth measurements using yellow perch collected on the Saint John

River, in New Brunswick, Canada. Obvious differences in performance of fish were detected, and were consistent with other ongoing studies in the areas using other fish species and other parameters.

The comparisons of growth measurements will need to be repeated using

Bhutanese fish species, as the optimal measurement for growth may be different for different species. Bhutan’s geology, physical structure, local climate, hydrogeology, industrial development, and water chemistry were reviewed as they place restrictions on potential study designs. Potential study sites were selected, the sampling schedule was evaluated and a review of impacts examined potential endpoints for a monitoring program.

There is not very much information on fish species distributions, abundances and biology in Bhutan’s North-South Valleys, where most of the hydroelectric development will take place. A priority has been placed on developing some of the background information, and on conducting comparative sampling projects

137

within developed rivers, on undeveloped rivers, and during the development phases at proposed sites.

138

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5 Appendix A

Summary of background information on species found in Bhutan

153

Table 5-1 Life-history characteristics for fish species of Bhutan: most information collected from Fishbase– www.fishbase.org and Petr, 1999 (* valid scientific name from Fishbase) Species Food Tail Spawning Temperature Present in study Length preference areas (cm) Schizothorax progastus Zoobenthos, algae, aquatic 50.0 September Cold Breeds upstream, plants, fish eggs/larvae to October benthopelagic, potamodromous Schizothorax molesworthi 20.5 (SL) Subtropical Benthopelagic Schizothorax richardsonii Algae, aquatic plants and 60.0 March to Cold Spawns upstream detritus May and September to October Acrossocheilus Zoobenthos, phytoplankton, 120.0 April to Warm, Migrates upstream

154 hexagonolepis plants, insects, crustaceans October Tropical during spawning *Neolissochilus (peak hexagonolepis August to September) Crossocheilus latius 12.4 (SL) Warm, Benthopelagic, Tropical potamodromous Tor putitora Fish, zooplankton, dipteran 275.0 Warm Benthopelagic, larvae, plant matter potamodromous Juveniles – plankton Tor tor Plankton, chironomid 52.0 March to Warm Moves upstream larvae, water beetles, (150 cm September during rainy crustaceans reported) season, Benthopelagic, potamodromous Barilius barna Nekton, insects, fish 15.0 Warm, Benthopelagic Tropical Barilius bendelisis 22.7 Warm Benthopelagic, potamodromous

Barilius bola 35.0 Warm Dermersal, *Raiamas bola potamotromous Puntius macropogon 50.0 Warm Benthopelagic (Misspelling for Puntius micropogon) *Hypselobarbus periyarensis Puntius sophore 18.0 Warm, Benthopelagic, Tropical amphidromous Puntius ticto Crustaceans, insects, 10.0 Warm Benthopelagicm plankton potamordomous Puntius titius Worms, crustaceans, 15.0 Warm Benthopelagic, *Puntius chola insects, plant matter potamodromous Cirrhinus lata ?? Warm

155 Barbus spp. ?? Warm Labeo dero Detritus 75.0 May to June Warm, Hill streams, *Sinilabeo dero tropical migrates to warmer waters, shallow Labeo dyocheilus 90.0 Warm Benthopelagic, potamodromous Labeo pangusia Algae, diatoms 90.0 Warm Benthopelagic, potamodromous Garra annandalei 23.0 Warm Benthopelagic Garra gotyla gotyla Algae, plants, detritus 14.5 Warm Benthopelagic Danio aequipinnatus Exogenous insects, worms, 15.0 Warm Pelagic crustaceans Danio dangila 8.3 (SL) Warm Benthopelagic Brachydanio rerio Worms, small crustaceans, 3.8 Warm Benthopelagic *Danio rerio insect larvae Botia Dario 15.1 Warm Demersal Semiplotus semiplotus 60.0 Warm Benthopelagic *Cypribion semiplotum

Rasbora daniconius Nekton, zoobenthos, 15.0 Warm Benthopelagic, zooplankton, fish, potamodromous crustaceans, insects Noemacheilus botia Zoobenthos, insects 11.0 May to June Warm Dermersal *Acanthocobitis botia 100-150 eggs Batasio batasio 10.0 Warm Demersal Mystus bleekeri 15.5 Warm Demersal, potamodromous Mystus vittatus Nekton, zoobenthos, fish, 21.0 Warm Demersal crustaceans, insects Ompok pabda 30.0 Warm Demersal, potamodromous Bagarius bagarius Nekton, zoobenthos, fish, 200.0 Before flood Warm Benthopelagic, crustaceans, insects potamodromous

156 Nangra punctata 8.5 Warm Demersal, *Gogangra viridescens potamodromous Xenentodon cancila Nekton, zoobenthos, fish, 40.0 Warm Pelagic, crustaceans, insects amphidromous Channa gachua Nekton, fish, insects 20.0 (SL) March to Warm Benthopelagic, August potamodromous Channa striatus Detritus, nekton, 100.0 June to July Warm Benthopelagic, *Channa striata zoobenthos, zooplankton, potamodromous herps, crustaceans, insects, worms, Badis badis Zoobenthos, crustaceans, 8.0 Warm Benthopelagic insects, worms Nandus nandus Nekton, zoobenthos, fish, 20.0 300 eggs Warm Benthopelagic insects Mastacembelus armatus Nekton, plants, zoobenthos, 90.0 April to June Warm Demersal, zooplankton, fish, potamodromous crustaceans, insects, worms

Table 5-2 Life-history characteristics for introduced fish species of Bhutan: most information collected from Fishbase– www.fishbase.org and Petr, 1999 (* valid scientific name from Fishbase) Species Food Spawning time Tail Length Other (male/ information unsexed) (cm) Salmo trutta fario Nekton, zoobenthos, fish, herps, January to May and 100 Demersal, non- ??? insects, mollusks, benthic October to December migratory invertebrates Salmo trutta trutta Nekton, zoobenthos, April to July and July 140 Pelagic, zooplankton, fish, insects, to November anadromous terrestrial invertebrates, crustaceans, mollusks, worms

157 Cyprinus carpio Detritus, nekton, plants, Spring and summer 120 Benthopelagic, carpio zoobenthos, zooplankton, fish, potamodromous insects, worms Catla catla Plants, zoobenthos, May to September 182 Benthopelagic, phytoplankton, insects potamodromous Cirrhinus mrigala Detritus, phytoplankton, 100 Benthopelagic, *Cirrhinus cirrhosus zooplankton, crustaceans potamodromous Labeo rohita Detritus, plants, zooplankton, April to August 200 Benthopelagic, invertebrates potamodromous Aristichthys nobilis Zooplankton April to June 112 Benthopelagic, potamodromous Ctenopharyngodon Higher aquatic plants, April to September 150 Demersal, idella submerged grass, detritus, potamodromous insects, invertebrates Hypophthalmichthys Plants, phytoplankton April to September 105 Benthopelagic, molitrix potamodromous

CURRICULUM VITAE

Candidate’s Full Name: Karma Tenzin

Universities Attended

1997- 2000 Sherubtse College, University of Delhi, Tashigang, Bhutan (B. Sc.,

2000)

Publications

Tenzin K, Dorji L, 2000. A Study of Butterfly and Moth Species in Eastern Bhutan. Sherubtse College, Tashigang, Bhutan

NWWFCC. 2001. Survey on water quality and status of fish in the rivers of Thimphu, Paro and Haa Dzongkhags. Report. National Warm Water Fish Culture Centre, Ministry of Agriculture, Royal Government of Bhutan. Gelephu. 35p

Conference Presentations

Tenzin K, 2006, Potential developmental challenges in rivers of Bhutan. Linking Watersheds Workshop: February 26- March 1, Fredericton, New Brunswick