AN ABSTRACT of the DISSERTATION of Asako M. Yamamuro

AN ABSTRACT OF THE DISSERTATION OF

Asako M. Yamamuro for the degree of Doctor of Philosophy in Zoology presented on December 17, 2009.

Title: Aquatic Insect Adaptations to Different Flow Regimes

Abstract approved:

David A. Lytle

My thesis explored the effects of environmental variability on population dynamics and community composition of aquatic insects. Environmental variability in the form of flow regime in streams can limit the distribution and life-history traits of aquatic insects. I used tributaries to the McKenzie River in Oregon with dramatically different flow regimes to compare aquatic insect community composition (Chapter 2).

Runoff-dominated streams were responsive to precipitation events and had high flow events in the winter and dried down in the summer. Spring-fed streams had a relatively steady flow regime year round. Streams categorized as runoff-dominated had distinctly different taxonomic composition of aquatic insects compared to streams designated as having a spring-fed flow regime. Larval Ameletus (order

Ephemeroptera) and Calineuria (order Plecoptera) were prominent indicator genera for runoff-dominated streams while Caudatella (order Ephemeroptera) and Yoraperla

(order Plecoptera) were prominent indicator genera for spring-fed streams.

Additionally, life-history trait indicators for spring-fed streams included semivoltinism, poorly synchronized emergence, and slow seasonal development.

These analyses suggested that there were community level differences between seasonally fluctuating and relatively constant flow regimes.

My thesis investigated population-level differences in life-history traits of an aquatic insect species that is found in both runoff-dominated and spring-fed streams

(Chapter 3). Cohort patterns of Yoraperla nigrisoma were distinctly different between both stream types. At the end of the summer, spring-fed streams had three distinct cohorts, while runoff-dominated streams had two distinct cohorts present. Yoraperla nigrisoma in spring-fed streams have a more consistent growth rate year round, and they emerge at a larger size and have more cohorts present than in runoff-dominated streams. These analyses suggest that flow regime type is highly associated with these life-history differences.

My thesis explored whether life-history trait differences at the population level are phenotypically plastic to environmental conditions in the short term (Chapter 4).

The variability in sources of phenotypic variation may be due to the presence or lack of phenotyically plastic factors. I conducted a reciprocal transplant experiment to quantify the effects of environment on life-history traits of Yoraperla nigrisoma.

Insects from the spring-fed stream that were transferred to the runoff-dominated stream sped up their development, which was measured by change in head width over time. Also, newly-emerged adults showed differences in head width and biomass between treatments, but the small sample sizes associated with these results should be considered. Overall, both phenotypically plastic factors and factors lacking

phenotypic plasticity affect life-history traits between the runoff-dominated and spring-fed stream.

Aquatic Insect Adaptations to Different Flow Regimes

by Asako M. Yamamuro

A DISSERTATION

submitted to

Oregon State University

in partial fulfillment of the requirements for the degree of

Doctor of Philosophy

Presented December 17, 2009 Commencement June 2010

Doctor of Philosophy dissertation of Asako M. Yamamuro presented on December 17, 2009.

APPROVED:

Major Professor, representing Zoology

Chair of the Department of Zoology

Dean of the Graduate School

I understand that my dissertation will become part of the permanent collection of

Oregon State University libraries. My signature below authorizes release of my dissertation to any reader upon request.

Asako M. Yamamuro, Author

ACKNOWLEDGEMENTS

First, I’d like to thank my advisor, Dave Lytle. He’s a passionate scientist with a very strong connection to field work. Dave’s given me great freedom and opportunities to explore my questions of interest in the field. Also, I greatly appreciate Dave’s talent for picking fantastic lab members. I’ve been very fortunate to be able to intimately interact with this great group over the last five years. Thanks,

Dave, for giving me the opportunity to join your lab and grow as a stream ecologist.

I’d really like to acknowledge the assistance that my committee has provided for me. Michael Blouin, Stanley Gregory, and Gordon Grant have been very supportive of my research and approachable when I wanted to meet with them. I’ve learned a lot from them and my dissertation is improved by their insight. Susan

Tornquist has been the ideal graduate representative. She is highly responsive and has been so nice to me.

I have to thank my personal support group. Without these folk, I’m not sure if

I could have gotten through the gauntlet of my Ph.D. adventure. My mom has always been my soft place to land. She is my personal cheerleader and harshest critic. I should never feel like no one ever cares about me, because she does on a daily basis.

Mom, thanks for being my friend for longer than anyone else. I obviously need to thank my roommate and closest friend, Ivan Phillipsen. If he hasn’t been there the instant that I needed him, he’s been there for me a few moments later. We’ve waxed and waned from sharing our intimate thoughts to bickering over washing dishes. But, whatever happens, we fundamentally and genuinely care about each other and I hope

that we’ll remain close friends for the rest of our lives. Ivan, you’re one of the best listeners I know and I appreciate every kindness you’ve given me. I also need to thank

Laura McMullen. She’s my officemate, labmate, and one of my closest friends. Even though I think of her as my little sister, she has taught me many things. Conceptually,

I embrace her “what ev’s” attitude but I still need to work on its practice. Laura has many passions and she’s shown me that there’s no reason to be demure about them. I can shout them out for all of the world to hear and without any self-centered modesty.

Laura has been a great companion and has consistently encouraged me in my pursuits.

Laura, thanks for being a generous gem. If Laura’s my little sister, then Marshall

Knoderbane is my little brother. I haven’t been as close to him for as long, but he’s really added a lot of fun into my life. I will never get tired of his flattery or our random conversations. Marshall has been enormously supportive and encouraging.

Marshall, thanks for making me laugh loudly and frequently. I also want to thank

Dafne Eerkes-Medrano. I started to get to know her after she invited me to join her for a hip-hop dance class. That says a lot about her. Dafne is both super sweet and open-minded (a great combination). Besides being like a unique snowflake, I see her as a huge, three dimensional, glittery, memorable snowflake. She’s very special and has been a very supportive friend. I feel like I can talk to her about anything. Dafne, thanks for being such a great person. She invited me to Newport for a weeklong writing retreat that turned out to be a great success. Additionally, I really want to thank Sylvia Chung. She is one of my closest and oldest friends. Sylvia has always been there for me and I really appreciate how she gives me the non-grad. student

perspective that helps me stay grounded. I always enjoy our long phone conversations. Thanks, Sylvia, for being so good to me for all of these years. I also want to thank Joe Cannon for being a good friend and introducing me to new things. I had never heard of the verb “botanize” before I met him. I’ve also gained a great appreciation for bonsai, lichens, mushrooms, and even a greater appreciation for beavers. Additionally, I’m very grateful for my pet rat, Rigobeartoe. He really puts a smile on my face multiple times a day, no matter what is going on (which is exactly what I need most of the time).

My lab members have been so supportive. Mike Bogan provided me with an indulgent writing retreat at his home in Arizona. Everyday, there were so many fantastic experiences. I was treated to gourmet meals, great coffee, leisure bird watching, hikes set in really soothing colors, and phenomenal sunsets. Plus, I was productive. Mike (a.k.a. Golden Boy) is super talented and industrious and I’m lucky that he’s my friend. My other labmate, Kate Boersma, has been the “rock” in my life during these last handful of months. Kate has made time for me whenever I randomly see her and she also generously helped me edit part of this thesis. Kate, thanks for being so supportive, encouraging, and sympathetic. Thanks for making time for me.

Also in our lab, Deb Finn has been an exceptionally great post-doc and our lab is lucky to have her. Deb helped me on my Sigma Xi grant and it paid off! Deb’s also a great tough chick role model for me. She’s a hardworker and still has tons of friends and a balanced life. She’s never too serious and has a great chuckle. I also admire

Deb’s openmindedness. Temporarily in our lab, Morgan Hannaford has also been a

great help. He’s been so easy to talk to and I like his sense of humor. Morgan has helped me a number of times in brainstorming ideas and with field work. I’d like to thank Morgan for also being a great role model.

My home for my first three summers in Oregon had been the H. J. Andrews

Experimental Forest. I’d like to thank Kathy Keable and Kari O’Connell for helping to make my research go more smoothly and comfortably. I had nice labspace and storage. They ran a nice, tight ship. Plus, it was always fun to talk with Kathy on a regular basis.

I’d also like to thank Anne Jefferson. Many of my study sites overlap with hers and Anne has been so generous with her time and research. Anne basically got me started on the right foot and I really appreciate all of her help. I also want to thank everyone who has helped me in the field, including Edwin Price, Ashley Timko,

Morgan Hannaford, Nick Chambers, Jacob Tennessen, Deb Finn, Ivan Phillipsen,

Laura McMullen, and Joe Cannon. I especially would like to thank Eddy for helping me. I could not have done this by myself. I’d also like to thank Andy Moldenke for generously letting me use his emergence traps. They were so well built that they were very easy to use. I’d also like to thank Norm Anderson for being such an approachable and knowledgeable expert in this field. His passion is truly inspiring.

I’ve been able to bounce numerous ideas off of him. Bruce McCune has helped me with multivariate statistics. Thanks for a big help. I’d also like to thank Judy Li. I’m very fortunate that I’ve gotten to know her and her lab. Judy has been so encouraging and generous in giving me opportunities. I had a blast working in her lab. Judy runs a

great lab group. I’d like to thank Bill Gerth and Rich Van Driesche. I had a great time chitchatting while looking at bugs under the scope. You guys crack me up. Thanks for letting me be loud and unruly.

I’d also like to thank all of my friends in the Zoology Department. This includes, in no particular order, Sarah Eddy, Josef Uyeda, Elyse Vaccaro, Paul

Bradley, Julia Buck, Steph Gervasi, Lindsay Biga, Catherine Searle, Angela Brandt,

Sean Moore, Margot Hessing-Lewis, Orissa Moulton, Phoebe Zarnetske, Mark Albins,

Tim Pusack, Sarah Close, Alison Iles, Jeremy Rose, Joe Tyburczy, Chris Friesen,

Rocky Parker, Angela Poole, Chrisy Schnitzler, Karen Kiemnec-Tyburczy, Darren

Johnson, Arlo Pelegrin, Betsy Bancroft, Barbara Han, John Romansic, Laura Petes,

Luis Vinueza, and Liz Martin (not in Zoology, but she was my writing buddy). I’d also especially like to thank my other Cordley fourth floormates. Thanks Mark

(Hammerpants) Christie, Kaitlin Bonner, and Jacob Tennessen for all of the conversations and socializing. The zo-grads are a great group that have helped me with their encouragement and parties.

I’d also like to thank those who have helped me with their expertise. Thank you Adry Clark, Carlos Toloya, A. J. Williams, Elizabeth Lazaroff, and Vicki Tolar

Burton. Thanks for all of your help when I really needed it.

Lastly, I’d like to thank the Zoology Department staff. Thanks Tara

Bevandich, Torri Givigliano, Traci Durrell-Khalife, and Mary Crafts. All of you have made this experience a smooth one.

CONTRIBUTION OF AUTHORS

David A. Lytle contributed to funding, editing, and revising Chapters 2, 3, & 4.

TABLE OF CONTENTS

Page

CH. 1. GENERAL INTRODUCTION………………………………………... 1

Importance of freshwater biodiversity………………………………… 2

Flow regime variation and life-history traits………………………….. 4

Study system…………………………………………………………... 6

Flow regime variation on community structure……………………….. 6

Flow regime variation and population dynamics……………………… 7

Flow regime variation and short term phenotypic plasticity………… 8

References……………………………………………………………... 10

CH. 2. AQUATIC INSECT COMMUNITY COMPOSITION IN STREAMS WITH STABLE VS. VARIABLE FLOW REGIMES...... 19

Abstract………………………………………………………………... 20

Introduction……………………………………………………………. 21

Methods………………………………...... 24

Results ………………………………………………………………… 29

Discussion …………………………………………………………….. 31

Acknowledgements...... 37

References...... 38

TABLE OF CONTENTS (Continued)

Page

CH. 3 POPULATION LIFE-HISTORY DIFFERENCES BETWEEN RUNOFF-DOMINATED AND SPRING-FED STREAMS………...... 49

Abstract………………………………………………………………... 50

Introduction……………………………………………………………. 51

Methods………………………………...... 58

Results ………………………………………………………………… 63

Discussion …………………………………………………………….. 65

Acknowledgements……………………………………………………. 70

References…………………………………………………………… 71

CH. 4. STONEFLY LIFE-HISTORY DIFFERENCES BETWEEN RUNOFF-DOMINATED AND SPRING-FED STREAMS: A RECIPROCAL TRANSPLANT EXPERIMENT……………………... 82

Abstract………………………………………………………………... 83

Introduction……………………………………………………………. 83

Methods………………………………...... 89

Results ………………………………………………………………… 93

Discussion …………………………………………………………….. 96

Acknowledgements……………………………………………………. 101

References……………………………………………………………... 101

TABLE OF CONTENTS (Continued)

Page

CH. 5. CONCLUSIONS……………………………………………………... 114

BIBLIOGRAPHY………………………………………………………...... 120

APPENDICES…………………………………………………………………. 131

LIST OF FIGURES

Figure Page

1.1 Figure 1.1. Map of study sites on tributaries to the upper section of the McKenzie River , Willamette National Forest, Oregon. White represents the High Cascades and gray shading represents the Western Cascades………………………………………………………………… 16

1.2 Lava bed located in the High Cascades of the Willamette National Forest, Oregon …………………………………………………………... 17

1.3 Ventral view of Yoraperla nigrisoma larvae……………………………. 18

2.1 Schematic of the nested stream study design for our 10 study streams in the Cascade Mountains of Oregon, U.S.A………………………………. 44

3.1 Conceptual diagram of research organization and predictions………….. 75

3.2 Change in cohort head width patterns overtime. The axes represent head width modes (in mm) per cohort (x-axis = cohort 1, y-axis = cohort 2, z- axis = cohort 3). Each dot represents all cohorts for one stream. Solid dots represent runoff-dominated streams and open dots represent spring- fed streams..………………………………………………………………. 76

3.3 Frequency distribution of head widths for different months in a (a) runoff-dominated and a (b) spring-fed stream. Lines connect modes of presumptive cohorts……………………………………………………... 77

3.4 Life cycle diagram comparing cohort 1(C1), cohort 2 (C2), cohort 3 (C3), and cohort 4 (C4) for runoff-dominated and spring-fed streams for Yoraperla nigrisoma…………………………………………………….. 78

3.5 Daily growth rate of larval Yoraperla nigrisoma cohorts between different months. Black bars represent runoff-dominated streams and gray bars represent spring-fed streams. Error bars are one standard deviation…………………………………………………………………... 79

3.6 Average head width differences of emerging Yoraperla nigrisoma adults from each stream (n = 5). Black dots represent runoff-dominated streams and white dots represent spring-fed streams. Error bars are one standard deviation…………………………………………………………………... 80

LIST OF FIGURES (Continued)

Figure Page

3.7 Average proportion of adult Yoraperla nigrisoma emerged per date out of total emerged from each stream (n = 5). Black dots represent runoff- dominated streams and white dots represent spring-fed streams. Error bars are standard deviations………………………………………………. 81

4.1 Theoretical patterns of a reciprocal transplant experiment between a runoff-dominated and spring-fed stream when (a) development is directly related to growth rate and (b) growth is directly measured as mass………………………………………………………………………. 103

4.2 Reciprocal transplant experimental design showing random ordering of replicate enclosures across the two stream types…………………………. 104

4.3 View of (a) inside of enclosure and (b) outside of the enclosure………… 105

4.4 Frequency histogram of head width sizes of insects collected prior to the experiment from a) the runoff-dominated stream and b) the spring-fed stream. n = 200 for each stream type…………………………………….. 106

4.5 Reciprocal transplant growth rate differences between larvae in four treatments: runoff-dominated native (RO-N), spring-fed transplant (SF- T), spring-fed native (SF-N), and runoff-dominated transplant (RO-T)…. 107

4.6 Reciprocal transplant head width differences between emerged adults from four treatments: runoff-dominated native (RO-N), spring-fed transplant (SF-T), spring-fed native (SF-N), and runoff-dominated transplant (RO-T)…………………………………………………………. 108

4.7 Reciprocal transplant experiment differences between recently emerged female vs. male adults in (a) head width, (b) biomass, and (c) wing length. Each symbol represents an individual…………………………… 109

4.8 Reciprocal transplant biomass differences between emerged adults from four treatments: runoff-dominated native (RO-N), spring-fed transplant (SF-T), spring-fed native (SF-N), and runoff-dominated transplant (RO-T)……………………………………………………………………. 110

LIST OF FIGURES (Continued)

Figure Page

4.9 Reciprocal transplant wing length differences between emerged adults from four treatments: runoff-dominated native (RO-N), spring-fed transplant (SF-T), spring-fed native (SF-N), and runoff-dominated transplant (RO-T)…………………………………………………………. 111

4.10 Reciprocal transplant days to emerge differences between emerged adults from four treatments: runoff-dominated native (RO-N), spring-fed transplant (SF-T), spring-fed native (SF-N), and runoff-dominated transplant (RO-T)…………………………………………………………. 112

4.11 Reciprocal transplant percent survival differences between larvae plus emerged adults from four treatments: runoff-dominated native (RO-N), spring-fed transplant (SF-T), spring-fed native (SF-N), and runoff- dominated transplant (RO-T)……………………………………………... 113

LIST OF TABLES

Table Page

2.1 Nested perMANOVA results to determine differences in community taxonomic composition and community life-history trait composition. Sitereps = averaged riffle samples specific to a single site……………… 45

2.2 Significant indicator taxa for runoff-dominated and spring-fed streams. Numbers represent indicator values (IV). Within a column the first value is for 2005, second value is for 2006. An IV of 100 refers to perfect indication, while zero refers to no indication. Genera towards top of table have higher IV for runoff-dominated streams, while those towards the bottom have a higher IV for spring-fed streams……………. 46

2.3 Diversity measures for community taxonomic composition and community life-history trait composition. S = richness, E = evenness, H = Shannon diversity, D = Simpson’s index of diversity for an infinite 47 population…..

2.4 Significant indicator life-history traits for spring-fed streams. No significant indicator traits found for runoff-dominated streams. Numbers represent indicator values (IV). An IV of 100 refers to perfect indication, while zero refers to no indication……………………………. 48

LIST OF APPENDICES

Appendix Page

A Physical features of ten study streams…………………………………… 132

B Temperature measurements of ten study streams……………………… 136

C Size frequency distributions of Yoraperla nigrisoma larvae collected from ten study streams…………………………………………………... 147

LIST OF APPENDIX FIGURES

Figure Page

A1 Discharge measurements for five runoff-dominated streams (solid line) and five spring-fed streams (dashed line)…………………………….. 134

B1 Boulder Creek, a runoff-dominated stream, temperature measurements for two time intervals………………………………………………….. 137

B2 Sweetwater Creek, a spring-fed stream, temperature measurements for two time intervals…………………………………………………….. 138

B3 Florence Creek, a runoff-dominated stream, temperature measurements for two time intervals………………………………………………….. 139

B4 Fritz Creek, a runoff-dominated stream, temperature measurements for two time intervals……………………………………………………… 140

B5 Ice Cap Creek, a spring-fed stream, temperature measurements for two time intervals………………………………………………………….. 141

B6 Kink Creek, a runoff-dominated stream, temperature measurements for two time intervals……………………………………………………….. 142

B7 Olallie Creek, a spring-fed stream, temperature measurements for two time intervals…………………………………………………………….. 143

B8 Payne Creek, a spring-fed stream, temperature measurements for two time intervals…………………………………………………………….. 144

B9 Scott Creek, a runoff-dominated stream, temperature measurements for two time intervals………………………………………………………. 145

B10 Anderson Creek, a spring-fed stream, temperature measurements for two time intervals………………………………………………………. 146

C1 Frequency graphs of Yoraperla nigrisoma larval head widths for ten study streams in August 2005. Y-axis is count. Left column graphs are runoff-dominated streams and right column graphs are spring-fed streams…………………………………………………………………… 148

LIST OF APPENDIX FIGURES (Continued)

Figure Page

C2 Frequency graphs of Yoraperla nigrisoma larval head widths for ten study streams in April 2006. Y-axis is count. Left column graphs are runoff-dominated streams and right column graphs are spring-fed streams…………………………………………………………………….. 149

C3 Frequency graphs of Yoraperla nigrisoma larval head widths for ten study streams in May 2006. Y-axis is count. Left column graphs are runoff-dominated streams and right column graphs are spring-fed streams…………………………………………………………………… 150

C4 Frequency graphs of Yoraperla nigrisoma larval head widths for ten study streams in July 2006. Y-axis is count. Left column graphs are runoff-dominated streams and right column graphs are spring-fed streams…………………………………………………………………… 151

C5 Frequency graphs of Yoraperla nigrisoma larval head widths for ten study streams in August 2006. Y-axis is count. Left column graphs are runoff-dominated streams and right column graphs are spring-fed streams…………………………………………………………………… 152

C6 Frequency graphs of Yoraperla nigrisoma larval head widths for ten study streams in September 2006. Y-axis is count. Left column graphs are runoff-dominated streams and right column graphs are spring-fed streams……………………………………………………………….. 153

LIST OF APPENDIX TABLES

Table Page

A1 Study stream location coordinates, elevations, and watershed areas. First five streams listed are runoff-dominated streams and last five streams listed are spring-fed streams.………………………………… 133

A2 Table of substrate composition based on a Wolman pebble count for each stream. Wood = sticks & logs. Sand = substrates less than 2 mm. Pebble = substrates between 2 to 63 mm. Cobble = substrates between 64 to 255 mm. Boulder = substrates 256 to 4096 mm. First five streams listed are runoff-dominated streams and last five streams listed are spring-fed streams…………………………………………………….. 135

DEDICATION

I dedicate this dissertation to all of the aquatic insects

that I’ve killed on this Ph.D. seeking adventure.

Aquatic Insect Adaptations to Different Flow Regimes

CHAPTER 1: GENERAL INTRODUCTION

Environmental variability determines population dynamics and community structure, and distinct disturbance regimes may impact populations and communities differently, even within an ecosystem type. Cases of disturbance regime variability influencing populations and communities include fire in grasslands (Parsons and

Stohlgren 1989, Vogel 1974, Whelan 1995), drought (Gould et al. 1999, Price et al.

1984), insect outbreaks (Ayres and Lombardero 2000, Logan and Powell 2001), ice storms (Hauer et al. 1996, Simpson 1999), wind storms in forests (Lawton and Putz

1988, Nowacki and Kramer 1998), and flow on aquatic organisms (Bunn and

Arthington 2002, Lytle and Poff 2004, Poff et al. 1997). The final example, flow regime variability, is especially appropriate for the study of how environmental variability affects population dynamics and community structure. Some researchers consider flow regime to be the ultimate driving force for all abiotic conditions in streams (Frissell et al. 1986, Kondolf 1997, Poff et al. 1997). Flow is a major force in shaping biotic composition (Poff and Allan 1995, Ward et al. 1999) because it directly affects physical habitat, including sediment movement, water chemistry, discharge rate, and temperature regime (Frissell et al. 1986, Newbury and Gaboury 1993), and it limits the distribution of aquatic organisms (Harper and Everard 1998, Lytle and Poff

2004, McElravy et al. 1989, Power et al. 1995, Soluk 1985, Statzner et al. 1988).

Importance of freshwater biodiversity

Streams and rivers provide a rapid turnover of essential freshwater while sustaining unique habitats and biota even though they only occupy one-thousandth of the planet’s total land surface (Hynes 1970). Increasing knowledge of streams will allow for better preservation of these often overused and vulnerable ecosystems (Poff et al. 2003, Richter et al. 2003). The endangerment of life and health through flooding, drought, water contamination, etc. of those dependent on this resource increases the importance of streams as increasing human-induced pressures – road building, channel straightening, dam installation, water withdrawal – are placed on these systems (Baron et al. 2002, Ebersole et al. 1997).

Natural streams are complex, and researchers often have difficulty explaining study findings. Streams respond to external variables like regional climate, watershed, soil quality and geology type, regional vegetation, and nearby land-use and internal variables like water chemistry, temperature, organic matter retention rates, flow rates, sediment size, and hyporheic influence (Frissell et al. 1986, Hynes 1975, Richards et al. 1996, Ward 1989). Besides this, characteristically different subwatersheds are often dendritically connected (Vannote et al. 1980, Ward and Stanford 1983). Within the stream channel, variability can occur in water chemistry, temperature, organic matter retention rates, flow rates, sediment size, and hyporheic influence, and streams tend to be naturally dynamic over different scales and levels of biological organization

(Anderson et al. 2006). This natural complexity of streams also provides unique biological interactions.

Habitat loss or alteration is a major cause of biodiversity loss (e.g., Wilcove et al. 1998). Stream ecologists and managers who aim to quantify, preserve, and understand community composition in different ecosystem types are interested in biodiversity (Dallmeier et al. 2002, Linke et al. 2007, Naiman et al. 1993, Richter et al. 2003). The degradation of freshwater habitat has led to many extinctions, including fish, mussels, and crayfish (Carlson and Muth 1989, Master 1990, Williams and Miller 1990). Much work has been done on fish and amphibians in freshwater systems, yet there is a paucity of studies on aquatic insects, which are essential to food webs that include fish and amphibians and are commonly used to assess overall stream health (Cairns et al. 1993).

Aquatic insects are an important component of overall river productivity and provide important ecosystem functions, such as organic matter processing and major food resources for fish. Aquatic insects are excellent study organisms for comparing population and community structure between environments differing in flow variability because they are abundant and diverse and because they live in almost every body of water. Indeed, the U.S. has a greater number of the economically- important and often-sensitive species of stoneflies, mayflies, and caddisflies than any other country (Master et al. 1998); regrettably, 43% of stonefly species in the U.S. are threatened or extinct (Stein et al. 2000). Understanding effects of disturbance in the form of flow variation on the adaptations of stream-dwelling insects will lead to a better understanding of stream ecosystems.

Flow regime variation and life-history traits

Flow regime is considered to be a primary variable influencing the distribution of aquatic biota (Poff et al. 1997, Power et al. 1995, Resh et al. 1988). There are five specific aspects of the flow regime that affect river-dwelling organisms: magnitude, frequency, duration, timing, and rate of change. Magnitude is the amount of water passing a fixed point per unit time (Poff et al. 1997). Frequency refers to the number of occurrences of flow above a specific magnitude per unit time. Duration is the length of time that a certain flow condition occurs. Timing of hydrologic conditions refers to the regularity of flows of a specific magnitude. Rate of change is a measure of the flashiness or the amount of change from one magnitude flow to another per unit time. The movement of water and sediment within the channel and between floodplains leads to physical habitat alterations. Floods can transport fine sediments, import large woody debris, and connect the stream channel to the floodplain depending on the magnitude and frequency of flows. Flow regime can dictate the spatial and temporal patterns of habitats which in turn can affect species distribution and abundance and ecosystem function.

Lotic ecosystems are principally characterized by their flow regime. Flow regime describes the distribution of floods, droughts, and baseflow conditions through time (Poff et al. 1997). Streams with runoff-dominated and spring-fed flow regimes characterize two extremes of flow variability (Tague and Grant 2004). Runoff- dominated streams are responsive to precipitation events and can flood from heavy precipitation or dry down during extended dry periods. Water temperature regimes are

5 influenced by local atmospheric conditions in runoff-dominated streams (Tague et al.

2007). As a result, runoff-dominated streams tend to be seasonally variable in flow and temperature. At the other extreme of flow variability, spring-fed flow regimes are relatively stable and buffered from the effects of precipitation (Jefferson et al. 2006).

Water levels and discharge remain relatively constant regardless of precipitation events in spring-fed streams. Additionally, the groundwater source for spring-fed streams maintains a relatively constant temperature year-round (Tague et al. 2007). In contrast to runoff-dominated streams, spring-fed streams tend to lack seasonal variability in flow and temperature.

Flow variability can affect aquatic insect life-history traits, such as development, and influence both population dynamics and community structure (Lytle

2002, Resh et al. 1988). Flow variability can act as an environmental filter to eliminate taxa that cannot tolerate extreme conditions like floods, droughts, and temperature variability (Gray 1981). Also, flow variability modifies life-history traits by limiting the time available for seasonal growth and development. Trade-offs may prevent organisms from thriving in more than one environment. For example, a variable environment could place more time constraints on organisms than a relatively steady environment. Time constraints could lead to adaptations in time-related events in an organism’s life cycle, such as life-history traits. Organisms better adapted to dealing with time constraints may be more successful with temporal heterogeneity than others better adapted to temporal homogeneity.

Study system

We used two stream groups – runoff-dominated and spring-fed – to investigate community and population level differences in insects inhabiting streams with either a highly varying or slightly varying flow regime and to experimentally address the driving force of the observed population level differences (Fig. 1.1). The flow regimes of these streams have been well-characterized (Jefferson 2006). For geologic reasons, the upper McKenzie River, OR has both runoff-dominated, thus relatively unstable, tributaries and spring-fed, thus stable, tributaries (Fig. 1.2). All the streams are located within a small geographic area of 110 km2 and band of elevation, 550 to

730 m, therefore minimizing environmental differences aside from flow type.

Since streams are diverse, researchers have difficulty finding similar streams to conduct studies with statistically robust results (Carter and Resh 2001), and the common lack of adequate sample sizes in stream studies makes interpreting results and finding general patterns difficult (Townsend et al. 1997). My research, though, will take advantage of this ideal system for conducting a natural study to achieve strong scientific inference.

Flow regime variation on community structure

One focus of my research is on aquatic insect community taxonomic composition between streams with different flow regimes. Temporal variations in flow patterns affect insect diversity patterns (Vannote et al. 1980, Ward and Stanford

1983, Yamamuro 2009). Other studies focusing on flow regime have not considered aquatic insects or used grouped streams (Bain et al. 1988, Bell and Barnes 2000,

Freeman et al. 2001, Leland 2003, Leonard et al. 1998, Marchetti and Moyle 2001,

Peterson 1987, Schlosser 1985, Stevenson 1983, Travnichek et al. 1995). We ask whether there are aquatic insect community composition differences between runoff- dominated and spring-fed streams in three areas: (1) community taxonomic composition, (2) community life-history trait composition, and (3) diversity measures.

Addressing these questions allows us to reassess the importance of the flow regime on stream biota and whether or not general patterns can be observed.

We predict that aquatic insect community taxonomic composition will differ between runoff-dominated and spring-fed streams. We reason that streams with different flow regime types will have different available habitats because flow regime is a major force in shaping habitats. In turn, habitat-specific genera will occupy these different habitats in different densities between the two stream types. Specifically, we focused on life-history traits because we believe that differences in a fluctuating vs. a constant environment will influence how an individual allocates energy towards fitness-related life-history strategies like growth, development, and reproduction.

Insects inhabiting streams with fluctuating flow regimes may have different life- history strategies than those inhabiting streams with stable flow regimes (Townsend et al. 1997).

Flow regime variation and population dynamics

We investigated whether population differences exist between a seasonally- fluctuating and a relatively steady environment. Across populations, life-history differences may result from responses to differing environmental conditions and/or

8 differences in genetic composition (Arnold 1994). An environment with both seasonal cues and time constraints refers to habitats where seasonal fluctuations tend to be predictable and the probability of increased stressors or mortality risk is seasonally dependent (Rowe and Ludwig 1991). Very little is known about the impacts of flow regulation at the population level (Bunn and Arthington 2002, Lytle and Poff 2004,

Poff et al. 1997). My research will fill this void by investigating population level differences among insects inhabiting streams with characteristically different natural flow regimes.

First, we will quantify population-level differences in the developmental patterns of insects inhabiting different stream types (Fig. 1.3). Insects in runoff- dominated streams might be expected to mature and emerge prior to summer droughts or spring floods in order to avoid mortality from these deteriorating environmental conditions. By contrast, stable conditions and limited flow variability in spring-fed streams provide neither a cue nor a mortality risk. Temporally heterogeneous environments such as runoff-dominated streams may induce synchronous emergence in aquatic insects due to seasonal cues related to time constraints. Spring-fed streams that lack both seasonal cues and time constraints may allow for a wider range in timing of emergence, which would result in a less synchronous emergence pattern.

Flow regime variation and short term phenotypic response

We examined whether life-history differences between aquatic insect populations in different flow regimes have short term phenotypic responses induced by the environment. We predict that if life-history trait differences are largely under

9 factors that are not phenotypically plastic, then insect life histories may not be able to adjust to a different flow regime. However, if life-history trait differences are induced by environmental cues, then insect life histories may be able to respond to a change in flow regime.

Life-history traits are genetically-driven or plastic responses to environmental conditions, or a combination of both. The variability in sources of phenotypic variation may be due to tradeoffs between genetic and environmental drivers. Local adaptation, or genetic divergence caused by natural selection, may give a population a home-site survival advantage. However, local adaptation can be disadvantageous if the rate of environmental change is faster than the organism’s response to selection

(Bennington and McGraw 1996, Billington and Pelham 1991, Blows and Hoffmann

2005, Etterson and Shaw 2001, Roff 1996). For example, an organism that is genetically constrained to hatch once a certain temperature is reached in a variable environment would be at a disadvantage if the environment stabilizes and never approaches that threshold hatching temperature.

Distinguishing the extent to which the genotype or the environment influences phenotypic differences is crucial to understanding the ecology and evolution of the organism. Despite this fundamental premise, very little empirical research addressing this topic has been conducted with animals. Aquatic insects are well suited to address the extent to which local genotype determines life-history trait differences between a seasonally variable and a relatively steady environment because they are abundant, diverse, and live in almost every body of freshwater. A reciprocal transplant

10 experiment determines how different phenotypes from two distinct environments, runoff-dominated and spring-fed streams, respond to living in either their native or a transplanted environment.

Efficiently describing population dynamics and community structure is especially important today because a majority of stream ecologists and managers lack the time or funding to understand the details of a system before the habitat has changed due to global warming, dam installation, or other factors, rendering the data irrelevant (Dallmeier et al. 2002, Ebersole et al. 1997, Simberloff 2004). My research will provide much-needed empirical evidence that environmental variability significantly affects biota, depending on whether the environment is highly variable or relatively stable.

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Figure 1.1. Map of study sites on tributaries to the upper section of the McKenzie River , Willamette National Forest, Oregon. White represents the High Cascades and gray shading represents the Western Cascades. Map prepared by I. Phillipsen.

Figure 1.2. Lava bed located in the High Cascades of the Willamette National Forest, Oregon.

Figure 1.3. Ventral view of Yoraperla nigrisoma larvae. Photo taken by A. Pelegrin.

CHAPTER 2: AQUATIC INSECT COMMUNITY COMPOSITION IN STREAMS WITH STABLE VS. VARIABLE FLOW REGIMES

Asako M. Yamamuro and David A. Lytle

In preparation for submission to the journal Ecology Ecological Society of America Publications, Ithaca, New York

Abstract

Flow regime is important to understanding stream ecosystem biodiversity. We sampled and identified the Ephemeroptera, Plecoptera, and Trichoptera from five runoff-dominated and five spring-fed streams over the course of two years.

Community-level taxonomic, life-history trait, and biodiversity measures differed between seasonally fluctuating and relatively constant streams. We found differences in community taxonomic composition between runoff-dominated and spring-fed streams, which provide strong evidence that by simply grouping streams by flow regime type, distinct community differences can be detected. We identified reliable indicator taxa, which may have a preference or specialization, for both flow regime types. We found that Ameletus (order Ephemeroptera) and Calineuria (order

Plecoptera) were prominent indicator genera for runoff-dominated streams and that

Caudatella (order Ephemeroptera) and Yoraperla (order Plecoptera) were prominent indicator genera for spring-fed streams. We found significant life-history differences between communities inhabiting the two stream types. Semivoltine, poorly synchronized emergence and slow seasonal development traits were indicators for spring-fed streams. We found that biodiversity measures were higher in runoff- dominated streams than in spring-fed streams. However, the differences were not large, so this may imply that disturbance is not the only factor influencing diversity.

Overall, these differences between grouped streams of both types located in similar proximity support the hypothesis that flow regime is a primary driver in differentiating stream ecosystems.

Introduction

Variability in disturbance regime across habitats can lead to dramatic differences in both community composition and population structure. Examples of this have been documented in grasslands that experience fire (Parsons and Stohlgren

1989, Vogel 1974, Whelan 1995), drought on islands (Gould et al. 1999, Price et al.

1984), insect outbreaks in forest ecosystems (Ayres and Lombardero 2000, Logan and

Powell 2001), ice storms in forests (Hauer et al. 1996, Simpson 1999), wind storms in forests (Lawton and Putz 1988, Nowacki and Kramer 1998), and flow variability in river and stream habitats (Bunn and Arthington 2002, Lytle and Poff 2004, Poff et al.

1997). The latter, flow regime variability, is especially well suited for the study of environmental variability affecting population dynamics and community structure because flow regimes are often predictable and therefore easier to study than more sporadic regimes such as fire.

Lotic ecosystems are fundamentally characterized by their flow regime. Flow regime describes how floods, droughts, and baseflow conditions are distributed through time (Poff et al. 1997). Because flow regimes can differ greatly among streams, flowing-water ecosystems are a valuable model system for understanding generally how environmental variation affects population dynamics and community.

Flow variability can act as an ecological filter to taxa that cannot tolerate extreme conditions (floods, droughts, temperature variability)(Gray 1981). Also, flow variability can limit time available for seasonal growth and development. Aquatic insects are ideal study organisms for comparing population dynamics and community

22 structure between environments differing in flow variability because they are abundant, diverse, and live in almost every body of water. For example, during seasonal floods and droughts, taxa with a one year generation time (univoltinism) may be favored to escape unfavorable conditions especially if they transition between the aquatic and terrestrial environment (a complex life cycle sensu Wilbur 1980) (Lytle

2000, 2002). On the other hand, a stable stream environment may favor taxa with a two year generation (semivoltine) that can grow larger and secure more mates

(Plaistow and Tsubaki 2000). Trade-offs may prevent taxa from thriving in more than one environment. For example, fast growing species may do well in seasonally variable environments but may spend more time foraging and risking predation in a stable stream environment.

Runoff-dominated and spring-fed streams represent two extremes of flow variability (Tague and Grant 2004). Streams with runoff-dominated flow regimes are highly responsive to precipitation events; heavy precipitation events result in floods, and stream drying can result from a lack of precipitation events. Water temperature regimes also reflect local atmospheric conditions in runoff-dominated streams due to a lack of groundwater influence (Tague et al. 2007). Consequently, runoff-dominated streams tend to be seasonally variable in both flow and temperature. At the other end of the spectrum, streams with spring-fed flow regimes are relatively stable and buffered from precipitation events due to a several year lag time of precipitation traveling through groundwater storage to the surface stream (Jefferson et al. 2006).

During dry seasons, spring-fed streams maintain a similar water level and discharge as

23 during wet periods. In streams with spring-fed flow regimes, the stored groundwater source keeps the water temperature relatively constant year round, which prevents freezing during the winter (Tague et al. 2007). Unlike runoff-dominated streams, spring-fed streams tend to lack seasonality attributable to a stable flow and temperature regime.

We used grouped streams (5 runoff-dominated and 5 spring-fed) to test the following questions: are there aquatic insect community composition differences between streams with a variable vs. constant environment in (1) taxonomic composition, (2) life-history trait composition, and (3) community diversity?

Addressing these questions allows us to reassess the importance of the flow regime on stream biota and determine whether general patterns can be observed. We studied community trait composition to increase the universality of our study of community composition between the two disturbance regimes. Specifically, we focused on life- history traits because we believe that differences in a fluctuating vs. constant environment will influence how an individual allocates energy towards fitness related life-history strategies (i.e. growth, development, reproduction) (Townsend et al. 1997).

While a number of studies have focused on the importance of flow regime in determining aquatic and riparian communities (Bain et al. 1988a, Bell and Barnes

2000, Boulton et al. 1992, Freeman et al. 2001a, Leland 2003, Leonard et al. 1998,

Marchetti and Moyle 2001a, Peterson 1987a, Puckridge et al. 1998, Schlosser 1985a,

Stevenson 1983, Stromberg 2001, Travnichek et al. 1995), studies with multiple streams are needed to allow greater generalization of patterns. Our study, on the other

24 hand, spanned two years and used multiple streams with distinct flow regimes located in the same vicinity. The close proximity of these streams allows all aquatic insects to disperse to either stream type, producing a common species pool across sites. We predicted that trade-offs will favor some traits in a given stream type over the other, resulting in consistent community composition differences between a seasonally variable vs. steady environment.

Methods

Study system

The McKenzie River, in the Cascade Mountain Range in Oregon, has both runoff-dominated and spring-fed tributaries due to local differences in geology. The

Western Cascades (greater than 8 Myr old) have well-drained, highly conductive soils which overlie layers with low permeability, resulting in shallow subsurface flow (Harr

1977). The High Cascades (less than 2 Myr old) have poorly-developed soils overlying permeable layers which charge a deeper groundwater system during storm events (Tague and Grant 2004). Eighty percent of annual precipitation falls in the winter in both Western and High Cascades, which results in distinct high precipitation and low precipitation seasons in the terrestrial environment. However, geological differences ultimately cause differences in stream flow dynamics due to different routes of precipitation to the stream channel. Streams of the Western Cascades are generally runoff-dominated and thus relatively variable in their flow regime (winter floods, summer droughts; temperature fluctuations). Streams of the High Cascades are generally spring-fed and thus stable (constant flow and temperature). Our study

25 consisted of five runoff-dominated and five spring-fed tributaries to the upper

McKenzie River. Both study stream types were distributed in a relatively small geographic area (110 km2) and band of elevation (550 to 730 m). Similar reaches

(width, substrate, canopy, channel shape) were chosen for study sites.

Field work and study design

Streams were characterized as spring-fed or runoff-dominated based on the hydrogeomorphic work of Jefferson (2006) and by directly recording flow and temperature regime from June to August 2005. We took multiple discharge measurements from each stream (spanning wet and dry seasons) to determine flow variability. We installed water temperature data loggers (iButton from Maxim

Integrated Products, and HOBO H8 from Onset Computer Corporation) to characterize water temperature regimes during the study period.

This study had a nested design (Fig. 2.1). In July 2005 and 2006, we collected insect community samples from 10 streams total (five from each of the two stream types). We sampled six separate haphazardly-chosen riffles (n = 6) within each stream. We schematically divided up the entire area of a riffle into nine equally sized sections of a 3X3 sectioned matrix, and collected one benthic insect sample from one of the nine sections (randomly determined) of six separate riffles. We sampled sixty riffles each year (6 riffles from 10 streams). We sampled for two years and a total of

120 riffles using a kicknet (500 µm mesh) to collect insects dislodged from a standardized area (841 cm2). After picking all aquatic insect larvae in the field, we preserved them in 70% ethanol.

Lab methods

We separated and identified Ephemeroptera, Plecoptera, and Trichoptera to genus and calculated densities per genus for each riffle sample (# of individuals per m2). We categorized individuals by life-history traits specified for each genus (Vieira et al. 2006). Our study included eight traits: semivoltine (<1 generation/yr), univoltine

(1 generation/yr), bi- or multivoltine (>1 generation/yr), fast seasonal development, slow seasonal development, nonseasonal development, poorly-synchronized emergence (week), and well-synchronized emergence (day).

Statistical analyses

Quantitative multivariate analyses were conducted on two matrices: (1)

Ephemeroptera, Plecoptera, Trichoptera genera and (2) life-history traits. The genus abundance matrix contained 120 sample units and 47 genera. Likewise, the data for the life-history trait matrix contained 120 riffle sample units and 8 traits. The environmental matrix was composed of 120 riffle sample units and three categorical variables (flow regime type, location, year).

All statistical analyses were performed in PC-ORD version 6.91 (McCune and

Mefford 2009). For all analyses involving distance measures, Euclidean distances were used. Ephemeroptera, Plecoptera, and Trichoptera community densities were log

(x+1) transformed to lower the average skewness of columns and row and column total coefficient of variation. The log-transformed matrices improved adherence to methodological assumptions, therefore these were used for all analyses.

We ran a nested perMANOVA, a nonparmetric test, to determine how riffle samples should be combined (averages taken) with factors (site, year, stream type).

Significance values were calculated from 4999 randomizations. Program limitations only allowed two factors to be analyzed at a given time. Ideally, we would have year nested within site while site was nested within stream type. We ran a perMANOVA with stream type as the fixed effect and collection year as the random effect to determine whether communities differed between years within a stream type.

Taxonomic composition and life-history differences

Significant differences between collection years within a stream type for the taxon abundance matrix would not allow us to combine the riffle samples per site for both years. Therefore, we averaged our riffle samples (n = 6) from a given site separately for each year sampled. No significant differences between collection years within a stream type for the life-history density matrix allowed for riffle samples to be combined for both years per site, so we averaged riffle samples (n = 12) from a given site for both years.

We ran nested perMANOVAs on the taxon abundance and life-history trait matrices to determine whether there were differences in community composition between runoff-dominated and spring-fed streams. Stream type was a fixed effect and the averaged riffle samples specific to a single site was a random effect for the three matrices (2005 genera, 2006 genera, 2005 & 2006 life-history).

Indicator Species Analysis (ISA) was run on the abundance matrices for

Ephemeroptera, Plecoptera, and Trichoptera and life-history traits to contrast taxa in

28 our a priori flow regime groups (runoff-dominated or spring-fed streams). ISA allows for the calculation of an observed indicator value (IV), which takes into account both relative abundance and stream-type fidelity for each genus and life-history trait. An IV of 100 represents perfect indication, meaning that the presence of a taxon indicates a particular group without error. When IV is high, the genus is considered a good indicator of a particular flow regime type (max. group). A low IV indicates that the genus is a poor indicator of a particular flow regime type (other stream type). An IV of zero represents no indication. A Monte Carlo test gives a p-value for the significance of the observed maximum IV for each genus based on 1000 randomizations. ISA was run on the two 10 rows X 47 columns genus composition matrices separated by year and the 10 rows X 8 columns life-history trait composition matrix.

Diversity differences

We analyzed the community diversity differences between the two stream types using four diversity measures: richness, evenness, Shannon diversity, and

Simpson’s index. Diversity measures were determined for all three matrices: genera

2005, genera 2006, and trait 2005 and 2006. Richness (S) measures the number of taxa present (Hurlbert 1971). Evenness (E) calculates diversity by accounting for abundance and richness (Hill 1973). Shannon diversity (H) takes into account both abundance and evenness of the taxa present (Hill 1973, Hurlbert 1971). Simpson’s index of diversity for an infinite population (D) accounts for both richness and evenness (Hill 1973).

Results

Stream type effect on generic community composition

We identified a total of 47 genera for both 2005 and 2006. Community taxonomic composition differed between sites, and within a site differences depended on the year the samples were collected (nested perMANOVA; Table 2.1). A nested perMANOVA run for each year separately determined that community taxonomic composition significantly differed between stream types (runoff-dominated or spring- fed) when site was nested within stream type (Table 2.1). Based on our perMANOVA results, we kept years separate for the ISA and used community log-transformed generic abundance averages (n = 6 riffle samples collected per site per year) to identify the taxa that were driving these community differences at the level of site.

In 2005, 11 significant indicator taxa were strongly associated with either spring-fed or runoff-dominated streams (Table 2). For the 2006 data set, we determined 14 significant indicator taxa of the 47 identified (Table 2.2). In 2006, one ephemeropteran, five plecopteran, and one trichopteran genera indicated runoff- dominated streams, while three ephemeropteran, two plecopteran, and two trichopteran genera indicated spring-fed streams (Table 2.2). Eight taxa (Ironodes,

Cinygmula, Ameletus, Caudatella, Doroneuria, Calineuria, Yoraperla, Pteronarcys) overlapped as indicator taxa for both years. Prominent indicator taxa (genera that overlap between the two years with IV > 50 and p-value < 0.02) were Ameletus and

Calineuria for runoff-dominated streams and Caudatella and Yoraperla for spring-fed.

For all community composition diversity measures for both years, values were higher

30 for runoff-dominated streams than spring-fed streams (Table 2.3). Of the prominent indicator taxa in 2005 and 2006, Calineuria had the highest IV (100 and 87 respectively) followed by Ameletus (71 and 90) for runoff-dominated streams, while

Caudatella had the highest IV (77 and 76) followed by Yoraperla (67 and 74) for spring-fed streams. Additionally, runoff-dominated streams had a lower abundance of total Epheroptera, Plecoptera, and Trichoptera than spring-fed streams (p < 0.05).

Stream type effect on community life-history trait composition

Vieira et al.’s (2006) traits table omitted life-history traits for the genus

Yoraperla (order Plecoptera) and explicit traits were not found in the literature, so we assigned Yoraperla the life-history traits semivoltine, slow seasonal development, and poorly synchronized emergence based on previous observations (Yamamuro 2009).

Community life-history trait composition between sites differed significantly, but year nested within site did not (nested perMANOVA; Table 2.1). Another nested perMANOVA indicated that community trait composition significantly differed between stream types when sites are nested within type (Table 2.1).

No life-history traits were indicators for runoff-dominated streams (Table 2.4).

Three out of eight life-history traits (semivoltinism, poor synchronization of emergence, slow seasonal rate of development) significantly indicated spring-fed streams (Table 4). All significant indicator values ranged between 53 and 56, with semivoltinism having the highest value. Also, significant p-values associated with the

ISA ranged between 0.02 and 0.04, with slow seasonal development having the lowest value. The diversity measures, richness (S) and Shannon diversity (H), were higher in

31 runoff-dominated streams than spring-fed streams, but evenness (E) and Simpson’s index of diversity for an infinite population (D) were very similar in both stream types.

Discussion

Community taxonomic composition

Our findings suggest that flow regime is important in understanding stream ecosystem biodiversity. First, we found differences in taxonomic composition between runoff-dominated and spring-fed streams. This supports our prediction that flow regime is important in affecting biotic composition of communities. This may occur because flow regime directly impacts habitats by affecting sediment sorting, temperature regime, water chemistry, interactions with the riparian zone, the disturbance regime, and nutrient and organic matter cycling and retention (Poff et al.

1997). Alternatively, some taxa may be unable to complete their life cycle in one habitat due to incorrect environmental cues for development, emergence, or avoidance of disturbance (Lytle 2008). Our study provides evidence that simply grouping streams by flow regime type, without considering other possibly relevant variables

(e.g., substrate size, habitat volume, water quality, or food availability), provides a robust means of identifying community differences among streams.

Like other studies in aquatic systems, our study found differences in community composition based on flow regime. Previous studies on organisms other than aquatic insects (i.e. fish, diatom, phytoplankton, sponges) have found differences in community composition in habitats with different flow regimes (Bain et al. 1988,

Bell and Barnes 2000, Freeman et al. 2001, Leland 2003, Leonard et al. 1998,

Marchetti and Moyle 2001, Peterson 1987, Schlosser 1985, Stromberg 2001,

Travnichek et al. 1995). Studies focusing on aquatic insect communities studies have found community differences between different flow regime types (e.g., Delucchi

1988). However, unlike these studies, we used a grouped stream study design with data for two separate years, which allowed for stronger statistical power to support the hypothesis that flow regime affects biotic community composition. Our study design allowed us to identify indicator taxa for both stream types. Two studies that also used grouped streams to demonstrate that flow regime is related to ecological patterns include Puckridge et al. (1998) which examined fish communities and Stevenson

(1983) which found differences in diatom immigration across stream types.

Indicator taxa for a stream type have a preference for a given flow regime instead of another, but the mechanism producing this affinity is not always clear. For example, we found that larval Ameletus (order Ephemeroptera) and Calineuria (order

Plecoptera) are prominent indicator taxa for runoff-dominated streams. Ameletus are typically found in the margins of streams, adjacent to but not in fast waters (Hafele &

Hughes 2004). They rest on stones, vegetation, or debris in stream margins and feed on algae or other plant material. These marginal habitats are generally more abundant in runoff-dominated streams, where they are generated by channel widening and scouring during high discharge events. Calineuria tend to prefer fast riffles broken by rocks and boulders (Hafele and Hughes 1981, Stewart and Stark 2002). Spring-fed streams are generally more imbricated than runoff dominated streams, and so lack the large emergent cobbles that Calineuria require. In runoff-dominated streams, the

33 unstable nature of rain-soaked slopes leads to more slope failure and other erosion events, resulting in higher rates of larger sediment input to the channel than in spring- fed streams. Fast riffles are created during high flow events in runoff-dominated streams when finer substrates are washed downstream or to the side, while larger substrates are confined to the thalwag (fastest flowing part of the stream)(Gordon et al.

2004). In contrast, spring-fed streams usually lack larger substrates because there is less erosion into the stream. Therefore spring-fed streams often have moderate riffles with little turbulence. Also, Calineuria prefer the undersides of rocks; they have easier access to this habitat in runoff-dominated vs. spring-fed streams because of the sediment scouring and sorting that occurs during high flow events. Spring-fed streams have more embedded substrates because finer substrates fill the interstitial spaces but are not regularly flushed out by larger discharge events.

Caudatella (order Ephemeroptera) and Yoraperla (order Plecoptera) were prominent indicator taxa for spring-fed streams, possibly due to a preference for slow to moderate currents. Caudatella is a crawler and has a stout, blocky body shape

(Hafele & Hughes 1981), which makes them prone to accidental dislodgement into the drift.

It is possible that Caudatella prefer spring-fed to runoff-dominated streams because a lower frequency of disturbances produces less flow variability. The stability of spring-fed streams may also offer more of the preferred slow to moderate currents than runoff-dominated streams which tend to have a larger range of currents that vary seasonally.

Yoraperla are often found in spring-fed streams, usually in mountainous or hilly regions (McCafferty 1998, Stewart and Oswood 2006). Yoraperla are shredder- detritivores (Harper et al. 1984) and also commonly inhabit leaf packs. They are small and may lack cold-hardiness related to tolerating prolong freezing of water and substrates. A low tolerance to prolonged freezing makes them more likely to be found in spring-fed streams which have little temperature fluctuation compared to runoff- dominated streams that can freeze during the winter. Yoraperla are found in high densities in submerged moss habitats; spring-fed streams tend to have more submerged moss than in runoff-dominated streams, where moss would be scoured off during larger discharge events.

Community life-history trait composition

As predicted we found significant life-history differences between the two stream types. The life-history traits that we found to be indicators for spring-fed streams (semivoltine, poorly synchronized emergence, slow seasonal development) were descriptive of Yoraperla, but only matched Caudatella in slow seasonal development. Both were prominent indicator taxa for spring-fed streams. Caudatella are univoltine, well-synchronized emergers, and slow seasonal developers. Yoraperla are semivoltine, poorly synchronized emergers, and slow seasonal developers. The presence of semivoltine taxa may indicate a spring-fed stream because in this stable environment, insects inhabiting the stream for more than one year will experience few mortality and emergence-related time constraints. Our results also show that the presence of taxa with poorly synchronized emergence traits may indicate spring-fed

35 streams because the aseasonality and stability indicative of spring-fed streams increases the range of suitable emergence times. The presence of insects with slow seasonal development may be an indicator trait for spring-fed streams because the lack of seasonality favors spending more energy on growth, rather than on development in order to mature before unfavorable conditions (spring floods, summer droughts) arrive

(Lytle 2001, Rowe and Ludwig 1991). Runoff-dominated streams with seasonally fluctuating flow regimes have more available niches than spring-fed streams and therefore have a higher variation in life-history traits. Runoff-dominated streams may not have any indicator traits due to the high variation in life-history traits. Trait studies can be difficult to interpret at the genus level because this can mask among- species differences in trait values. However, our results are supported by evidence from other life-history studies on aquatic insects that also found differences between flow regime types. Cereghino and Lavandier (1998) found that a species of stonefly had different growth strategies depending on whether they were upstream or downstream of a hydroelectric dam, which caused differences in flow regime that are similar to our spring-fed (upstream) and runoff-dominated (downstream with intermediate hydropeaking with hypolimnetic releases) stream types. Pardo et al.

(1998) found that a mayfly species had different life cycles depending on whether they were downstream from a dam that produced near-constant flows vs. in a tributary with a natural flow regime that experienced seasonal floods and droughts.

Biodiversity measures

We found that biodiversity measures were higher in runoff-dominated than in spring-fed streams. However, the differences were not large, so this may imply that disturbance is not the only factor influencing diversity (Doak et al. 1998). Usually, biodiversity is related to the number of specialized habitats available because more specialized adaptations yield higher biotic variety. We speculate that runoff- dominated streams have more habitat variability than spring-fed streams due to higher variation in flow, which includes floods that often form new habitats. However, spring-fed streams are more tolerable to aquatic insects as a result of constant temperature and oxygen concentrations despite having less variability in habitats than runoff-dominated streams. These pros and cons may have led to comparable diversity measures between both flow regime types. Even though it was not part of the study, we found abundance differences between the two flow regime types. Runoff- dominated streams had a lower abundance of total Epheroptera, Plecoptera, and

Trichoptera than spring-fed streams. Abundance differences based on flow regime provide additional evidence that a more variable environment may be less tolerable than a steady environment.

Broader implications

Our study provides evidence to ecologists and stream managers that flow regime type can be used to predict community taxonomic composition in streams.

Our findings support using flow regime type to classify community taxonomic composition. Flow regimes are constantly being changed due to dams, channel

37 manipulations, climate change, riparian zone alterations, groundwater withdrawal, forestry and agricultural practices, and urbanization. This study supports the potential for focusing on flow regime to allow stream ecologists and managers to document generalizable community differences efficiently. Streamlining research will enable stream ecologists and managers to better understand how changes in flow regime can lead to changes in community structure and biodiversity. For example, if dams are placed on runoff-dominated streams of the western slope of the Cascades range, making them more like spring-fed streams (with regulated discharge and hypolimnetic flow which is a colder temperature), we predict that based on flow regime changes,

Ameletus and Calineuria may be lost; proportions of semivoltine, poorly synchronized emergers and slow seasonal developers will increase; and overall diversity will decrease.

Virtually all major rivers and streams worldwide have been altered by humans, yet little is known about how alteration of the natural flow regime affects stream- dwelling organisms. We emphasize the importance of understanding and predicting changes in biota associated with the sudden shift in flow regimes to provide needed guidance on emerging conservation and management issues.

Acknowledgements

Anne Jefferson and David Kretzing helped to confirm stream classifications. David

Bickford helped with fish habitat identification. Edwin Price assisted with field work.

Bruce McCune, Michael Bogan, and Laura McMullen provided statistical guidance.

Partial funding came from National Science Foundation grants (IIS-0326052, IIS-

0705765, and DEB-0445366).

References

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Type Runoff-dominated Spring-fed

Stream

Riffle X 2 For two years

Figure 2.1. Schematic of the nested stream study design for our 10 study streams in the Cascade Mountains of Oregon, U.S.A.

Table 2.1. Nested perMANOVA results to determine differences in community taxonomic composition and community life-history trait composition. Sitereps = averaged riffle samples specific to a single site.

Matrix Year Source F p Genera 2005 & 2006 Site 4.3 0.0002 Year 1.8 0.0002

Genera 2005 Type 5.3 0.0084 Sitereps 3.3 0.0002

Genera 2006 Type 7.0 0.0056 Sitereps 2.6 0.0002

Trait 2005 & 2006 Site 7.6 0.0002 Year 1.2 0.2740

Trait 2005 & 2006 Type 6.9 0.0084 Siterep 5.4 0.0002

Table 2.2. Significant indicator taxa for runoff-dominated and spring-fed streams. Numbers represent indicator values (IV). Within a column the first value is for 2005, second value is for 2006. An IV of 100 refers to perfect indication, while zero refers to no indication. Genera towards top of table have higher IV for runoff-dominated streams, while those towards the bottom have a higher IV for spring-fed streams.

Stream Type Genus Runoff-dominated Spring-fed Calineuria* 100, 87 0, 5 Doroneuria* 78, 100 4, 0 Ameletus* 71, 90 23, 2 Pteronarcys* 100, 80 0, 0 Despaxia 61, 87 9, 3 Polycentropus 80, 60 0, 0 Kathroperla 40, 80 0, 0 Lepidostoma 51, 72 39, 2

Ironodes* 41, 41 59, 59 Cinygmula* 37, 42 63, 58 Sweltsa 37, 48 63, 52 Ecclicoesmoecus 0, 4 60, 82 Megarcys 8, 3 64, 69 Neothremma 0, 0 60, 80 Epeorus 24, 32 70, 61 Yoraperla* 27, 21 67, 74 Caudatella* 14, 19 77, 76 * = taxa that are significant indicator genera consistently for both years bold = prominent indicator genera that overlap for both years, IV>50, p<0.02

Table 2.3. Diversity measures for community taxonimic composition and community life-history trait composition. S = richness, E = evenness, H = Shannon diversity, D = Simpson’s index of diversity for an infinite population.

Matrix Year Stream Type S E H D Genera 2005 Runoff-dominated 27.2 0.97 3.201 0.9553 Spring-fed 24.8 0.965 3.091 0.9499

Genera 2006 Runoff-dominated 25.6 0.976 3.16 0.9542 Spring-fed 23.4 0.963 3.034 0.9471

Trait 2005 & 2006 Runoff-dominated 7.2 0.989 1.951 0.8565 Spring-fed 7 0.999 1.944 0.8566

Table 2.4. Significant indicator life-history traits for spring-fed streams. No significant indicator traits found for runoff-dominated streams. Numbers represent indicator values (IV). An IV of 100 refers to perfect indication, while zero refers to no indication.

Life-history trait Stream type Spring-fed Runoff-dominated Semivoltine (< 1 generation /y) 56 44 Poorly synchronized emergence (wk) 53 47 Slow seasonal development 55 45

CHAPTER 3: POPULATION LIFE-HISTORY DIFFERENCES BETWEEN RUNOFF-DOMINATED AND SPRING-FED STREAMS

Asako M. Yamamuro and David A. Lytle

In preparation for submission to the Journal of the North American Benthological Society North American Benthological Society, Lawrence, Kansas

Abstract

Our population-level study provided detailed differences between runoff- dominated and spring-fed streams. We sampled larval and adult Yoraperla nigrisoma

(Plecoptera: Peltoperlidae) from five runoff-dominated and five spring-fed streams over the spring and summer of 2006. We found that within a population of Yoraperla nigrisoma, individual size within a cohort is larger towards the end of summer in spring-fed streams than in runoff-dominated streams. This finding supports our hypothesis that a lack of seasonality in spring-fed streams removes seasonal time constraints on growth and development. We also found that cohorts in both stream types showed semivoltine patterns; however, the patterns were different between stream types. At the end of the summer, spring-fed streams had three distinct cohorts, while most runoff-dominated streams had only two distinct cohorts. Consistent with the pattern of larger larvae, spring-fed streams had reliably larger adults emerging from the end of June to the end of August 2006. However, we found no difference in the proportion of adults emerging or timing of emergence between the two stream types. Population patterns for Yorperla nigrisoma living in runoff-dominated streams were distinctly different from those living in spring-fed streams. Since we grouped streams by flow regime type, our findings support that flow regime is highly associated with these life-history differences. It appears that time constraints and seasonal environmental changes characteristic of runoff-dominated streams produced distinct life-history patterns compared to those found in spring-fed streams. Y. nigrisoma in spring-fed streams have a more consistent growth rate year round, and

51 they emerge at a larger size and have more cohorts present than in runoff-dominated streams.

Introduction

Disturbances such as floods and droughts can lead to evolutionary responses in stream-dwelling biota (Lytle 2001, Lytle and Poff 2004, Poff and Allan 1995, Resh and Solem 1996, Ward et al. 1999). In particular, the frequency, severity, and predictability of disturbance events can be a strong determinant of an aquatic insect’s life history strategy (Lytle 2008). The selective pressures experienced by aquatic insects may differ greatly among populations because floods and droughts are common in some streams and nearly-absent in others (Poff 1996). Few studies have directly examined the influence of flow regime across populations of aquatic insects

(Lytle and Poff 2004, Poff et al. 1997; but see Lytle 2008). This is surprising because many key life history attributes of aquatic insects, such as life-cycle duration, body size, and timing of development, may evolve in response to flow regime (Lytle 2002,

Resh et al. 1988). Understanding the effects of disturbance, in the form of flow variation, on the adaptations of stream-dwelling insects could lead to a better understanding of stream ecosystems. Currently, little is known especially at the population level (Lytle and N. L. Poff 2004, N. L. Poff et al. 1997; but see Lytle

2008).

Life-history strategies involve optimizing the allocation of energy towards growth, development, and reproduction (Bernardo 1993, Stearns 1992). Insect populations inhabiting streams with fluctuating flow regimes may face different

52 selective pressures than populations inhabiting streams with stable flow regimes.

While floods may remove >90% of insects inhabiting the stream during their larval stage (Fisher et al. 1982, Lamberti et al. 1991, Lytle 2000), insect life histories may be adjusted to the seasonal distribution of floods so that many individuals are present as aerial adults during the flood season (Gray 1981, Lytle 2002). An environment with both seasonal cues and time constraints refers to habitats where seasonal fluctuations tend to be predictable and the probability of increased stressors or mortality risk is seasonally dependent (Rowe and Ludwig 1991). Insects inhabiting streams with seasonal flooding may have a fast life cycle that entails rapid development, earlier emergence in the flood season, and consequent emergence at a smaller size, in order to decrease flood encounters and reduce mortality risk (Lytle 2000, 2002). In streams with stable flow regimes, insects may lack specific adaptations to flood events because of their rarity (Lytle and White 2007). Theory suggests that predictable floods can lead to adaptations to a flow regime, whereas unpredictable floods hinder adaptations to a flow regime (Junk et al. 1989, Lytle 2001). Insects that rarely experience floods may be less seasonally constrained and able to develop more slowly, exhibit variable emergence times, and emerge at a larger final body size. Similarly, insect development tends to be more synchronized in streams with seasonal flooding than in streams with rare flood events (Bunn 1988). For example, aquatic insects in seasonably-unpredictable New Zealand streams tend to have unsynchronized life histories (Winterbourn et al. 1981), while predictable seasonal flow fluctuations provide cues for life-cycle events such as emergence in some desert stream insects

(Lytle 2002). These ideas can readily be tested by comparing population level life- history differences between seasonally fluctuating and relatively stable streams.

Runoff-dominated and spring-fed streams characterize two extremes of flow variability (Tague and Grant 2004). Streams with runoff-dominated flow regimes respond to precipitation events. Heavy precipitation events can result in floods.

Stream drying often results from a lack of precipitation events. Additionally, water temperature regimes tend to reflect local atmospheric conditions in runoff-dominated streams (Tague et al. 2007). Therefore, runoff-dominated streams are often seasonally variable in flow and temperature. Towards the opposite end of the spectrum, streams with spring-fed flow regimes are comparably stable and buffered from precipitation events due to a several year lag time of water traveling through groundwater storage to the surface stream (Jefferson et al. 2006). Spring-fed streams maintain similar water levels and discharge during dry periods as during wet periods. The stored groundwater source keeps the water temperature relatively constant year round, which prevents freezing during the winter in streams with spring-fed flow regimes (Tague et al. 2007). Spring-fed streams tend to lack seasonality due to a stable flow and temperature regime, unlike runoff-dominated streams. Previously, we found community structure differences between runoff-dominated and spring-fed streams

(Yamamuro 2009), so investigating population life-history differences will provide further evidence that flow variation affects stream-dwelling biota.

Larval growth strategies

Body size is a key determinant of fitness in most insects, so it is likely to play an important role in the evolution of life-history strategies. Body size is positively correlated with both the number and quality of eggs produced by females in many aquatic insect species, and thus presents a significant fitness gradient within insect populations (Lytle 2008). It has been found that larger individuals have a competitive advantage for securing a wider range of food and territory than smaller individuals

(Cohen et al. 1993, Formanowicz 1986, Hart 1987). In a dynamic stream environment, larger individuals, compared to smaller individuals, may better withstand being swept downstream to a less favorable habitat (Poff et al. 1991).

Furthermore, optimizing growth is a favored strategy because larger females are associated with higher egg production (Blanckenhorn 2000). More eggs can result in more offspring, which would increase the mother’s fitness (Risch et al. 2007). Also, larger parents may have larger, and therefore higher quality eggs than smaller eggs from smaller parents. Higher quality eggs may result in higher quality offspring, which may increase the mother’s fitness (Fox et al. 1997). On the other hand, allocating a significant amount of energy towards growth may have disadvantages.

Larger larvae stay in the stream environment longer while smaller larvae allocate a higher proportion of energy towards development to emerge into the terrestrial environment (Lytle 2002). Allocating more energy towards development sooner allows for faster offspring production (Arendt 1997). Larger individuals must find more food and therefore increase foraging time than individuals that are smaller, but at

55 the same stage of development (Stoks et al. 2006). Increasing foraging time may increase exposure risks to predation (Kuparinen and Merilä 2007, Savage et al. 2004).

Overall, there are a variety of environment dependent growth strategies because there are tradeoffs to investing more energy into growth than development or reproduction.

Larval development strategies

Sweeney & Vannote (1978) drew a distinction between larval growth and development as is it relates to temperature. They investigated whether a species specific optimal temperature regime for larvae results in maximum adult size and fecundity. For example, if the temperature is warmer than the optimal temperature, the larvae will allocate more energy towards metabolism, reducing resource allocation towards growth. Additionally, warm temperatures stimulate development of adult tissues which result in smaller adults that are less fecund. Larvae in seasonal, runoff- dominated streams may evolve to allocate less energy to growth and more to development due to time constraints and suboptimal water temperatures, which would result in emerging at a smaller size than in spring-fed streams. Seasonal cues for ensuing intolerable conditions may induce this strategy and result in emergence from the stream to escape mortality (Fig. 3.1). Inevitably, an organism will experience a gradient of intolerable to favorable conditions in an environment with seasonal fluctuations. Once cues for seasonally predictable patterns are recognized, the organism may react to the cues and allocate more energy into development to escape increasingly harsher conditions and decrease mortality. Aquatic larval insects are known to increase survival from ensuing intolerable conditions by increasing

56 development rates and emerging from the water prior to reaching their tolerance limit

(Peckarsky et al. 2001). Decreasing water volume is a common seasonal cue in regions with distinct dry seasons and can result in triggering a developmental response in the entire population at the same time, resulting in a synchronized emergence event

(Jackson 1988). Compared to environments with seasonal fluctuations and time constraints, environments with more stable conditions are expected to have lower environmentally-related survival risks. Thus, we predict that the same species inhabiting both runoff-dominated and spring-fed streams will have different environment –dependent growth, development, and emergence strategies.

We predict that stream-dwelling larvae will allocate more energy towards development than growth in runoff-dominated compared to spring-fed streams because of prevalent seasonal time constraints related to summer stream drying and warmer water temperatures. Interconnectedly, we predict that insect larvae will allocate more energy to growth than development in spring-fed compared to runoff- dominated streams because of a lack of seasonal constraints on time spent in the stream. Additionally, a lack of time pressure in spring-fed streams may result in larger clutch size because larger females have more provisions for eggs. Besides a difference in development and growth strategies, we predict that there will be voltism differences in aquatic insects inhabiting runoff-dominated vs. spring-fed streams. A univoltine trait (one year generation) may be advantageous for insects in runoff- dominated streams that experience harsh seasonal conditions on a yearly basis that larvae can avoid by emerging as adults and fleeing the intolerable instream

57 environment. On the other hand, a semivoltine trait (two year generation) may be better suited for insects in spring-fed streams because there are no harsh conditions to be avoided, enabling insects to optimize their growth and developmental period.

Thirdly, we predict that related to the previous two predictions, adult insects will be smaller in runoff-dominated streams compared to those in spring-fed streams. If larvae distribute more resources towards development than growth and additionally are univoltine, they should emerge at a smaller size than if they allocated more energy towards growth and were semivoltine as predicted for spring-fed streams.

Resulting voltinism differences

Insects in seasonally fluctuating environments with time constraints are more likely to be univoltine because seasonal deterioration of the environment entrains them into an annual life cycle. By contrast, semivoltinism (generation time of >1 year) is a viable strategy in more stable environments because there are fewer disturbances. If growth rates remain high relative to within-stream mortality risks, stable environments will favor maturation to a larger body size over a longer time period. Thus, we predict that final body size at emergence and time spent during the larval stages will be greater for populations in spring-fed vs. runoff-dominated streams.

Adult size and timing of emergence strategies

In runoff-dominated streams, the seasonal cues and worsening conditions lead larvae to emerge. Aquatic insects will emerge in synchrony to reduce mortality and escape to a more tolerable terrestrial environment. In spring-fed streams, the temporally homogeneous environment and lack of seasonal cues and time constraints

58 allows for longer time spent in the stream environment to grow prior to emerging as adults to the terrestrial environment. Since escaping is not their strategy, like in runoff-dominated streams, spring-fed stream inhabitants are more likely to capitalize on growth and development due to a lack of time constraints, which would result in unsynchronized emergence patterns.

We predict that in a seasonally-fluctuating environment, the combination of both tolerable and intolerable conditions will lead to fluctuations in growth rate and attempts to escape the intolerable environment by emerging as an adult at a smaller size (Figure 1). We predict that in a relatively stable environment, a lack of time constraints will allow for a more even allocation of energy towards growth, development, and reproduction. Results may include a steady growth rate year round and emergence at a larger size compared to a fluctuating environment.

Methods

Study sites

We chose to compare stream dwelling insects living in runoff-dominated and spring-fed streams to test the prediction that population level differences exist between inhabitants of seasonally fluctuating vs. steady environments. Our study streams are tributaries to the upper McKenzie River in the Cascade Range of Oregon, which has a distribution of both runoff-dominated and spring-fed streams. We had a total of ten study streams; five were categorized as runoff-dominant and five were categorized as spring-fed streams, based on their flow regimes. Runoff-dominated streams are seasonally variable in the Cascade Range, where over 80% of the precipitation falls

59 between October and March during long duration events (12-72 hours) of low intensity in the form of rain (below 400 m), snow (> 1500 m), or a mixture of rain and snow (between 400 & 1500 m)(Tague and Grant 2004, Vanderbilt et al. 2003). There is an average annual precipitation of 2400 mm (Morrison and Swanson 1990). These precipitation patterns result in greater discharge and higher probabilities of flooding during the fall and winter and dry downs in the spring and summer. Additionally, in the Cascades, runoff-dominated streams have water temperature regimes that reflect atmospheric temperatures and result in cold streams in the winter and warm water in the summer (Tague et al. 2007). In contrast, spring-fed streams in this area are characteristically stable in flow and temperature regime regardless of season. For this population level study, we chose similar reaches (width, substrate, canopy, channel shape) for both stream types.

Study organism

We collected a species of stonefly to test the prediction that there are population level differences in life history between runoff-dominated and spring-fed streams. Yoraperla nigrisoma (Plecoptera: Peltoperlidae) was our target taxon, which was found in all of our study sites. Not much is known about this species, much less this genus (Stewart and Stark 1993). There is very little natural history data on this taxon. However, it has been documented that the genus is found in small springs and seeps and that Peltoperlidae are shredder-detritivores (Stewart and Stark 1993). Also, one study found that a different Yoraperla species is semivoltine in the Rocky

Mountains (Hughes et al. 1999). Previously, we found that at the community level,

60 there are differences in life-history trait composition (Yamamuro 2009). In a stable environment, there were more slow developers, unsynchronized emergers, and semivoltine individuals than in a seasonally fluctuating environment.

Field sampling

Larvae

We collected Yoraperla nigrisoma larvae to test the prediction that there are larval life-history differences depending on whether they inhabit runoff-dominated or spring-fed streams. In August 2005, and on a monthly basis during peak growth periods (April-September 2006), we collected larval samples of Yoraperla nigrisoma at our ten study sites. A kicknet (500 µm-mesh) was used to collect insects that were manually dislodged from rocks. We focused on collecting peltoperlids, which are associated with moss habitat and leaf packs. Since Yoraperla are associated with submerged moss habitats (personal observation), collecting efforts focused on rocks and logs with moss, but riffles were also sampled. This allowed for a higher diversity of collection locations and reduced the risk of collecting individuals from a single microhabitat which may not represent the reach-wide population. Two collectors were always involved, and collected from separate stream sections to get a better representation of the stream site. We live-picked larvae until we had more than 100 specimens per site, or until three hours had passed, while making sure that a kick sample that we started picking from was completely devoid of peltoperlid larvae (to reduce any size bias in sampling). Larvae were preserved in 70% ethanol.

Adults

We collected Yoraperla nigrisoma adults to test the prediction that there are life-history trait differences between adults emerging from either runoff-dominated or spring-fed streams. Every two weeks from June to August 2006, we collected adult aquatic insects in emergence traps to determine timing of emergence. The traps covered an area of 0.5 m2. The traps had a PVC frame, shaped like a pyramid, and were covered with green cloth with mesh at the top. The mesh had a Velcro flap to allow easy insertion and removal of a plastic container filled with a preservative, antifreeze (ethylene glycol). Once insects emerge from the stream, they move to the highest point of the trap and end up falling into the preservative. Five emergence traps were placed in each stream. The emergence traps were placed to target moss covered habitats because peltoperlid larvae tend to associated with moss habitats (personal observation). Traps were checked every two weeks; adult insects were removed from antifreeze and preserved in 70% ethanol.

Sample processing and data analyses

Larvae

We compared Yoraperla nigrisoma larval head widths to test the prediction that size distribution and growth rates would differ between those inhabiting runoff- dominated and spring-fed streams. We used a dissecting microscope and a Yoraperla key (Stark and Nelson 1994) to distinguish Yoraperla nigrisoma larvae from the other peltoperlids we collected in the field. We measured head capsule width (associated with size) with an ocular micrometer to determine frequency at different head widths for each site at a given time. First, we examined frequency histograms for each month

62 for each stream to determine cohorts (unimodal distribution) using head width on the x-axis. Once cohorts were determined, we determined the mode head width for that cohort’s distribution. We ran a nonparametric Wilcoxon rank-sum test (S-plus 8.0) for each collection month with mode of head width for each cohort grouped by stream type (5 sample sites) to determine whether there are pattern differences in cohort head width between runoff-dominated or spring-fed streams.

Growth rate was determined by subtracting the measured head width modes of the same cohort between months and divided by the difference by the number of days between collection dates (mm/day). Growth rate differences were compared between runoff-dominated and spring-fed streams by running a nonparametric Wilcoxon rank- sum test (S-Plus 8.0) because sample sizes were small. Analyses on cohorts were run separately.

Adults

We compared Yoraperla nigrisoma adult emergence patterns and head widths to test our prediction that adults from runoff-dominated streams would emerge smaller, earlier, and in synchrony compared to adults emerging from spring-fed streams. Timing of emergence of insects was determined by date of collection from traps. We identified Yoraperla nigrisoma (Stark and Nelson 1994) found in both stream types. We measured head capsules of individuals to determine relative sizes.

Sex of adults was also determined.

We ran a perMANOVA to determine whether there were differences in size of adults between runoff-dominated and spring-fed streams. We used stream type as the

63 grouping variable and sex as the nested variable. We also ran a nonparametric

Wilcoxon rank-sum test for each sampling period with proportion of emerged individuals over the total emerged per stream to determine whether there were differences in timing and synchrony of emergence depending on stream type (n = 5).

Results

Patterns differences between larval cohorts of runoff-dominated and spring-fed streams

In August 2005, Y. nigrisoma in spring-fed streams were consistently larger in cohort 1 (cohort 2 occurred in only one runoff-dominated stream and all spring-fed streams, and cohort 3 was not present in runoff-dominated streams) than those in runoff-dominated streams (Fig. 3.2, 3.3, & 3.4). However, in April and May 2006, no differences were detected between head widths of all cohorts in runoff-dominated and spring-fed streams. By July, most of cohort 1 had emerged from runoff-dominated streams (July, n = 2; August, n = 0; September, n = 0), while in spring-fed streams cohort 1 continued emerging until September (July, n = 4; August, n = 4; September, n

= 1). Thus, the adult emergence period was longer in spring-fed vs. runoff-dominated streams. In July and August, cohort 2 had a larger head width in spring-fed streams compared to runoff-dominated streams, but differences were not significant in

September. Cohort 3 starts becoming present in April, but is absent in most runoff- dominated streams (April, May, July, August, September, n = 1), but present in most spring-fed streams in July (n = 4), August (n = 5), and September (n = 5). Therefore,

64 as we predicted, there are different patterns of size distribution between runoff- dominated and spring-fed streams.

Growth rate differences within a larval cohort of runoff-dominated and spring-fed streams

In cohort 1, Y. nigrisoma had a consistently higher growth rate between August

2005 and April 2006 in runoff-dominated streams compared to spring-fed streams

(Fig. 3.5). Growth rates between April to May, and May to July, were not significantly different between cohort 1 for either stream type. In cohort 2, growth rates were faster in runoff-dominated streams compared to spring-fed streams between

August 2005 and April 2006, but this difference was not significant (p = 0.057).

Growth rates for all other intervals for cohort 2 were not significantly different between runoff-dominated and spring-fed streams. Growth rates for cohort 3 could not be compared between the two stream types because from August 2005 to April

2006, only one runoff-dominated stream and one spring-fed stream had been present.

For all other intervals of growth rates measured, cohort 3 was detected in only 1 runoff-dominated stream but in all five spring-fed streams so comparisons could not be made. Consequently, we found that growth rates differed between both stream types during fall and winter.

Size at emergence between runoff-dominated and spring-fed streams

We ran a nested perMANOVA and found that size at emergence differed according to stream type (runoff-dominated or spring-fed), but sex was not a factor contributing to the differences (Fig. 3.6). There were no significant differences in

65 head widths between stream type for all sample dates. Emerging adults were trapped in two to five of the spring-fed streams whereas only zero to three runoff-dominated streams had trapped Y. nigrisoma adults throughout the sampling period. Therefore, in addition to size at emergence differences, there was a difference in trapping capacity.

Emergence timing and synchrony between runoff-dominated and spring-fed streams

Proportion of emergence did not differ between the stream types for the days adults were collected (Fig. 3.7). Based on this finding, there are no differences in emergence timing and synchrony between runoff-dominated and spring-fed streams.

Discussion

Pattern differences between larval cohorts of runoff-dominated and spring-fed streams

Evidence supports our hypothesis that seasonally fluctuating flow regimes influence life-history tradeoffs between growth and development when conditions become less tolerable. Increasing water temperature and decreasing water volume may stress insects in runoff-dominated streams to trade growth for development.

Spring-fed streams had larger sized individuals towards the end of the summer in spring-fed streams compared to runoff-dominated streams. A lack of seasonal cues in spring-fed streams may allow insects release from seasonal time constraints. In other words, spring-fed stream larvae can strategize to grow to reach a large adult size, instead of sacrificing some growth due to pressures for developing to escape a gradually intolerable environment that the runoff-dominated stream larvae experience.

One observation that we didn’t expect was for the presence of more than two cohorts in spring-fed streams. Typically, a two-year generation time is detected from a bimodal distribution if size is on the x-axis and frequency is plotted on the y-axis.

However, at the end of the summer, spring-fed streams have three cohorts present while most runoff-dominated streams have two cohorts. This pattern may be explained by cohort splitting in spring-fed streams but not in runoff-dominated streams. Cohort splitting is often associated with bet-hedging in life-history strategies

(Kiss and Samu 2005). One cohort will lay eggs that undergo two or more developmental pathways. In the spring-fed streams, it appears as though some of the eggs oviposited in the spring and summer hatch and grow as larvae right away, while the third cohort is lagging in growth between the egg and larval stage. Y. nigrisoma in spring-fed streams don’t appear to be multivoltine or to have a three-year life cycle.

Our study provides evidence that adults in runoff-dominated streams lay eggs that diapause since detectable larvae are not apparent until much later than in spring-fed streams, even though adults have similar emergence times in both stream types. This may occur because stream conditions in runoff-dominated streams towards the end of summer are inhospitable towards developing larvae (warm and small water volume).

Elwood and Cushman (1975) found that a different Peltoperlidae species, Peltoperla maria, grew at a steady rate in a small spring-fed stream and had a two-year life cycle like Yoraperla nigrisoma in our streams. They also found that Peltoperla maria distribution was associated with leafpacks and detritus. O’Hop et al. (1984) also detected a synchronized emergence in May and since they the smallest larvae are

67 detectable in November, they suggest a six-month diapause for Peltoperla maria eggs.

Grubbs and Cummins (1996) found that Tallaperla maria is semivoltine and had fall and/or winter growth. Yokum et al. (1995) found that two peltoperlid species

(Peltoperla arcuata & Tallaperla maria) in streams flowing through mixed deciduous forest in West Virginia were both semivoltine, had a six-month egg diapauses, followed by an 18-month larval period, including approximately 14 or 15 instars, with emergence between May and July.

Our measured differences in growth rates provide evidence that between the fall and spring, conditions may be better for growth compared to other seasons for Y. nigrisoma in runoff-dominated streams. Another study in Western Cascades found that a Lepidostoma species in a warmer stream may need highly conditioned food to compensate for higher respiration rates compared to the same species that can feed on less conditioned, lower quality food in a colder stream (Grafius and Anderson 1980).

The Western Cascades are dominated by conifers and it is assumed that needles enter the stream in the fall when higher lateral flows increase debris input. The longer the needles and other debris are in the water, the more conditioned and higher quality it becomes for an aquatic insect. In the fall, there is leaf fall to provide nutrients. The winter rainy season provides more water, increasing habitat volume.

Growth rates

We found life-history differences in Y. nigrisoma between runoff-dominated and spring-fed streams. Our findings support our hypothesis that the seasonal fluctuations in flow regime in runoff-dominated streams provide seasonal cues

68 signaling time constraints, but are absent in spring-fed streams. Our analyses show that in runoff-dominated streams, growth rates are higher in the fall and winter compared to later spring and summer. By contrast, growth rates were more seasonally-constant in spring-fed streams. This difference may be caused by autumn leaf fall producing a seasonally abundant food source for Y. nigrisoma, which is a shredder-detrivore. This seasonal food source would allow for a faster growth rate during that time period. However, during spring and summer, leaf input is lacking and additionally, in runoff-dominated streams conditions become increasingly harsh as the water temperature rises and the volume of water in the stream decreases. These seasonal conditions may cause Y. nigrisoma in runoff-dominated streams to take advantage of growing in the fall and winter, when conditions are favorable and having a decreased growth rate in the harsher spring and summer.

Towards the end of the summer 2005, Y. nigrisoma in spring-fed streams were larger in cohort 1 than in runoff-dominated streams possibly because summer growth rates were higher in spring-fed streams. In runoff-dominated streams, Y. nigrisoma grows faster in the fall and winter months (between August and April). This may occur because growing conditions are better during these seasons. In Oregon, the precipitation is high during the months of October to March, and experiences drought like conditions during the months of April to September. Y. nigrisoma in the spring- fed streams may grow at a steady rate year round, growth rates fluctuate in runoff- dominated streams.

The presence of cohort 3 in all of the spring-fed streams in August 2006, while lacking in most of the runoff-dominated streams, seems to be the most profound life- history difference between the two stream types (Fig. 3.3 & 3.4). This pattern is probably due to the timing of oviposition and/or diapauses. In all streams, we were unable to collect eggs or very young larvae due to mesh size of our nets. Therefore, if they were not detected, Y. nigrisoma is either an emerged adult, an egg, or a very young larvae. Since a third cohort is detected in spring-fed streams, this may indicate that adults are ovipositing faster and more frequently and/or eggs are diapausing less frequently in spring-fed streams compared to runoff-dominated streams. This result further supports the hypothesis that seasonal fluctuations put more constraints on biota living in runoff-dominated streams than in spring-fed streams that lack seasonality, because diapauses is generally reserved for avoiding harsh conditions.

The higher growth rates for cohort 1 and marginally higher growth rate for cohort 2 in runoff-dominated streams compared to spring-fed streams between August

2005 to April 2006 further supports that this time period is seasonally important for growth, as mentioned previously. Since cohort 3 was only present in one out of five runoff-dominated streams, but in all of the spring-fed streams, faster growth rates were obvious between July and August in spring-fed streams.

Pattern differences in adult emergence between runoff-dominated and spring-fed streams

Our prediction that emerging adults would be larger in spring-fed than in runoff-dominated streams was not supported. A clear pattern was not detected with

70 our conservative nonparametric analyses. Also, our hypothesis regarding differences in timing and synchrony of emergence was not supported since we found no difference in proportion of adults emerged and timing of emergence between the two stream types. It may be that this population of Y. nigrisoma have a high level of genetic mixing and are highly phenotypically plastic. Similar timing of emergence would explain a higher potential for interbreeding between individuals emerging from either stream type. This may perpetuate a genetic constraint for timing of emergence. Plus, both stream types are in somewhat close proximity to each other and are intermingled.

Our larval data support that larvae in spring-fed streams are larger compared to those in runoff-dominated streams. These findings support our hypothesis that seasonal fluctuations in runoff-dominated streams provide less tolerable conditions that negatively affect optimal life-history strategies. However, our findings on emergence timing and synchrony did not support our hypothesis. We predicted that Y. nigrisoma in runoff-dominated streams would emerge earlier and more synchronized than those in spring-fed streams. In contrast, we found no differences in timing and synchrony of emergence between the two stream types. Emerging around the same time and for about the same interval may increase chances of finding mates if adults disperse among stream sites.

Acknowledgements

Edwin Price, Jacob Tennessen, Debra Finn, Ryan Craig, Laura McMullen, and

Ivan Phillipsen helped with field work. Michael Bogan, William Gerth, Darren

Johnson, and Michael Blouin provided statistical guidance. Andrew Moldenke

71 provided emergence traps. The Zoology Research Fund of the Zoology Department of

Oregon State University awarded to A. M. Yamamuro provided funding. Partial funding also came from National Science Foundation grants (IIS-0326052, IIS-

0705765, and DEB-0445366).

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Figure 3.1. Conceptual diagram of research organization and predictions.

Figure 3.2. Change in cohort head width patterns overtime. The axes represent head width modes (in mm) per cohort (x-axis = cohort 1, y-axis = cohort 2, z-axis = cohort 3). Each dot represents all cohorts for one stream. Solid dots represent runoff-dominated streams and open dots represent spring-fed streams

0.5 0 .5 a. F lo re n c e n = 1 8 b P a y n e n = 7 8 0.4 0 .4 . 0.3 0 .3 Aug. 0 .2 0.2 Frequency 2005 0.1 0 .1

0 0 .0 0 .5 0.5 n = 3 2 n = 1 2 4

0.4 0 .4 0.3 0 .3 Apr.

0.2 Frequency 0 .2 2006

0 .1 0.1

0 .0 0 0 .5 n = 4 1 n = 1 0 0 0.5 0.4 0 .4

0.3 0 .3 May

0.2 Frequency 0 .2 2006

0.1 0 .1 Frequency

0 0 .0 0.5 0 .5 n = 3 7 n = 1 3 1 0.4 0 .4 0.3 0 .3 Jul.

0 .2 0.2 Frequency 2006 0.1 0 .1

0 0 .0 0.5 0 .5 n = 1 0 4 n = 1 7 1

0.4 0 .4

0.3 0 .3 Aug.

0 .2 0.2 Frequency 2006

0.1 0 .1

0 0 .0 0 .5 0.5 n = 4 1 n = 1 1 8 0.4 0 .4

0.3 0 .3 Sep.

0.2 Frequency 0 .2 2006

0.1 0 .1 0 0 .0 0 .2 0 .4 0 .6 0 .8 1 .0 1 .2 1 .4 1 .6 0 .2 0 .4 0 .6 0 .8 1 .0 1 .2 1 .4 1 .6 Head width (mm) Head width (mm)

Figure. 3.3. Frequency distribution of head widths for different months in a (a) runoff-dominated and a (b) spring-fed stream. Lines connect modes of presumptive cohorts. 78

Runoff- Spring-fed dominated

C1 emerge C2 C1 C1 emerge C2

summer Lays C1 C2 C2 eggs Lays diapausing eggs fall C2 C1 emerge C3 C2

Lays eggs C3 C2 C3 C2 spring

C3 C2 emerge C3 C2 emerge C2

Lays summer C3 Lays C3 eggs C2 diapausing eggs

fall C3 C3 C4 C2 emerge

Lays eggs C3 C4 C3 C4 spring

C3 emerge C4 C3 emerge C4

Lays diapausing Lays

summer eggs eggs C4 C4

Figure 3.4. Life cycle diagram comparing cohort 1(C1), cohort 2 (C2), cohort 3 (C3), and cohort 4 (C4) for runoff-dominated and spring-fed streams for Yoraperla nigrisoma.

0.012 COHORT1 0.010 Col 7 0.008 Col 9

0.006

0.004

mm/day * 0.002

0.000

-0.002 Aug-Apr Apr-May May-Jul Jul-Aug Aug-Sep

0.012 COHORT2 0.010

0.008

0.006

0.004 mm/day 0.002

0.000

-0.002 Aug-Apr Apr-May May-Jul Jul-Aug Aug-Sep

0.012 COHORT3 0.010

0.008

0.006

0.004 mm/day 0.002

0.000

-0.002 Aug-Apr Apr-May May-Jul Jul-Aug Aug-Sep

Figure 3.5. Daily growth rate of larval Yoraperla nigrisoma cohorts between different months. Black bars represent runoff-dominated streams and gray bars represent spring-fed streams. Error bars are one standard deviation.

1.45

1.40

1.35

1.30

1.25 Headwidth (mm) 1.20

1.15

1.10 Jun Jul Aug Sep

Figure 3.6. Average head width differences of emerging Yoraperla nigrisoma adults from each stream (n = 5). Black dots represent runoff- dominated streams and white dots represent spring-fed streams. Error bars are one standard deviation.

0.8

0.6

0.4

Proportion 0.2

0.0

-0.2 1Jun 27Jun 10Jul 24Jul 7Aug 21Aug

Figure 3.7. Average proportion of adult Yoraperla nigrisoma emerged per date out of total emerged from each stream (n = 5). Black dots represent runoff-dominated streams and white dots represent spring-fed streams. Error bars are standard deviations.

CHAPTER 4: STONEFLY LIFE-HISTORY DIFFERENCES BETWEEN RUNOFF- DOMINATED AND SPRING-FED STREAMS: A RECIPROCAL TRANSPLANT EXPERIMENT

Asako M. Yamamuro and David A. Lytle

In preparation for submission to Freshwater Biology Wiley-Blackwell, Malden, Massachusetts

Abstract

Environmental variability can limit available time for life history processes, thereby affecting development and growth. We conducted a reciprocal transplant experiment to determine whether life-history differences in an insect population between a runoff-dominated and spring-fed stream were due to phenotypically plastic responses induced by the environment. Y. nigrisoma transplanted from the spring-fed stream to the runoff-dominated stream grew at a faster rate than those native to the runoff-dominated stream, and they grew faster than those that stayed in the spring-fed stream. This result may support the Thermal Equilibrium Hypothesis that aquatic insects in warmer environments, like runoff-dominated streams during the summer, will allocate more energy towards development while those in cooler environments, like spring-fed streams, will allocate more energy to growth. Therefore, when insects from the spring-fed stream are transferred to the runoff-dominated stream, they speed up their development, which is measured by change in head width over time. We also found differences between treatments for newly-emerged adults, but the small sample sizes associated with these results should be considered.

Introduction

Life-history traits, or the allocation of energy to growth, development, and reproduction, can have both genetically-fixed and phenotypically-plastic components.

The variability in sources of phenotypic variation may be due to trade-offs arising from underlying genetic variation or from direct environmental effects on the phenotype. Local adaptation, or genetic divergence caused by natural selection, gives

84 the population a home-site survival advantage. However, local adaptation can be disadvantageous if the rate of environmental change is faster than the organism’s response to selection (Bennington and McGraw 1996, Billington and Pelham 1991,

Blows and Hoffmann 2005, Etterson and Shaw 2001, Roff 1996). Distinguishing the extent to which the genotype or the environment influences phenotypic differences is crucial to understanding the ecology and evolution of the organism. Aquatic insects are well suited to address the extent to which local genotype determines life-history trait differences between a seasonally variable and a relatively steady environment because they are abundant, diverse, and live in almost every body of freshwater. A reciprocal transplant experiment determines how different phenotypes from two distinct environments respond to living in either their native or transplanted environment. Environmental variability can lead to two distinct environments which affect population dynamics including life-history traits. Variability in flow regime, or how floods, droughts, and baseflow conditions are distributed through time, is especially well suited for the study of environmental variability affecting population dynamics (Bunn and Arthington 2002, Lytle and Poff 2004, Poff et al. 1997).

Flow variability can affect the population dynamics of stream-dwelling organisms by acting as an ecological filter to taxa unable to tolerate extreme events such as floods, droughts, and temperature variability (Townsend and Hildrew 1994).

Also, flow variability can directly affect life-history traits by limiting time available for seasonal growth and development. While the effect of flow variability on aquatic insect communities has been studied (Vannote et al. 1980, Ward and Stanford 1983,

Yamamuro 2009), population-level studies are less common (Lytle and Poff 2004,

Poff et al. 1997). For stream insects, variation in life history patterns such as life- cycle length, strategies for development, and seasonal life history stages may have evolved in response to flow regimes (Lytle 2002, Resh et al. 1988). Previously, we found that Yoraperla nigrisoma (Plecoptera: Peltoperlidae) have different life-history traits between environmentally variable and environmentally stable streams

(Yamamuro 2009). Depending on the season, we found differences in the number of larval cohorts present, larval growth rates, and size at emergence of Y. nigrisoma between runoff-dominated and spring-fed streams. These observed life-history differences between seasonally-variable and steady streams makes Y. nigrisoma ideal for answering questions about the driver of these patterns at the population level.

Streams with runoff-dominated and spring-fed flow regimes represent two extremes of flow variability (Tague and Grant 2004). Runoff-dominated streams are responsive to precipitation events. Runoff-dominated streams can flood from heavy precipitation events, and may dry down from extended dry periods. Water temperature regimes often correspond to local atmospheric conditions in runoff- dominated streams (Tague et al. 2007). Therefore, runoff-dominated streams tend to be seasonally variable in flow and temperature. At the other extreme of flow variability, streams with spring-fed flow regimes are relatively stable and buffered from precipitation events due to a several year lag time of water traveling as rain/snow through groundwater storage to the surface stream (Jefferson et al. 2006). Water levels and discharge remain relatively constant during both wet and dry periods in

86 spring-fed streams. Also, the groundwater source maintains a relatively constant temperature year round (Tague et al. 2007). Unlike runoff-dominated streams, spring- fed streams tend to lack seasonal variability in flow and temperature.

In addition to floods and droughts, warm water temperature may also negatively affect stream-dwelling biota in runoff-dominated streams. Water temperature directly affects development of ectotherms (Clarke & Fraser 2004).

Therefore, an organism exposed to a different range of temperatures from another can develop differently. In the stream environment, Vannote and Sweeney (1980) have presented the Thermal Equilibrium Hypothesis that focuses on the idea that rapid shifts of energy use occur in response to thermal variation. Essentially, they divide metabolism up into two parts: 1) the conversion of nutrients into tissue (constructive metabolism), and 2) the release of energy from nutrients to be used for activity

(maintenance metabolism). When temperatures are high, overall metabolism is high for an individual, but maintenance metabolism is proportionately increased relative to constructive metabolism. Therefore, individuals will develop sooner and mature at a smaller size since growth is compromised compared to inhabitants of optimal thermal conditions. On the other hand, inhabitants of streams cooler than optimal thermal conditions will have lower overall metabolism, with even distribution between constructive and maintenance metabolism. Under constructive metabolism, the result of lower temperatures would favor development over growth, leading to a reduced size at maturity. For our stream types (runoff-dominated and spring-fed), the Thermal

Equilibrium Hypothesis would predict that insects living in runoff-dominated streams

87 would develop faster and emerge at a smaller size because water temperature is warmer than the optimal thermal conditions for optimal size and fecundity. Also, insects in spring-fed streams would develop more slowly and mature at a larger size because we believe the cooler water temperatures are closer to optimal thermal conditions. In other words, an insect native to runoff-dominated streams would develop faster than a spring-fed native (Fig. 4.1a). If an insect from a spring-fed stream is transplanted to a runoff-dominated stream, it will increase its development, while an insect from a runoff-dominated stream transplanted into a spring-fed stream will continue developing at the same rate (Fig. 4.1a). When considering growth, an insect native to a runoff-dominated stream would have a lower mass than a spring-fed native (Fig. 4.1b). However, an insect transplanted from a runoff-dominated stream to a spring-fed stream would be larger than if it had stayed in the runoff-dominated stream (Fig. 1b).

We conducted our research in natural streams to evaluate life-history traits of

Y. nigrisoma. Insect experiments are more commonly run in labs than in nature, often due to the difficulty of maintaining controls and manipulating treatments. However, results from lab experiment are difficult to translate to a natural environment.

Therefore, it is ideal that we conduct an instream experiment since we are interested in patterns influenced by nature. Ideally, a reciprocal transplant experiment determines how different phenotypes from two distinct environments (runoff-dominated vs. spring-fed) respond to living in either their native or transplanted environment.

However, the short term nature of our experiment only allowed for distinguishing the

88 effect of the environment, not genetics. Therefore, we were only able to investigate the short term phenotypic response induced by the environment. This study design allows us to address why Yoraperla nigrisoma is an indicator for spring-fed streams, but not for runoff-dominated streams.

Our objective was to examine short term phenotypic response of life-history traits of aquatic insect populations induced by different environments. We had four treatments: 1) runoff-dominated native, 2) spring-fed transplant, 3) spring-fed native, and 4) runoff-dominated transplant. We hypothesized that differences between the runoff-dominated native and spring-fed transplant treatments and/or the spring-fed native and runoff-dominated transplant treatments will indicate a lack of phenotypic response in the measured trait. Differences between the runoff-dominated native and transplant treatments or the spring-fed native and transplant treatments will indicate a phenotypically plastic response in the measured life-history trait. We predict that if life-history trait differences are governed primarily by genetics, then insect life histories may not be able to adjust under a different flow regime. However, if life- history trait differences are due to environmental cues, then insect life histories may be able to respond to a change in flow regime. An interaction of genetic and environmental drivers for life-history trait differences may produce novel life histories in insects as a response to experiencing a drastically different flow regime.

We predict that the adults emerging from the runoff-dominated stream will emerge smaller and earlier than those in the spring-fed stream in correspondence with the Thermal Equilibrium Hypothesis. We also predict that those inhabiting the spring-

89 fed stream will be more massive than those inhabiting the runoff-dominated stream.

We also predict that the insects transplanted from the spring-fed stream to the runoff- dominated stream will develop faster than those remaining in the spring-fed stream, while there will be no difference in development between insects native to or transplanted from the runoff-dominated stream to the spring-fed stream. Additionally, we predict that insects transplanted from the runoff-dominated stream to the spring-fed stream will have a higher biomass than those that remained in the runoff-dominated stream. Also, we predict that insects will not have biomass differences regardless of whether they remained in or were transplanted from the spring-fed stream to the runoff-dominated stream.

Methods

Relationship between geology and flow regime

The western slope of the Cascades mountain range in Oregon has two types of geology known as the Western Cascades and the High Cascades (Tague and Grant

2004). The Western Cascade geology is associated with runoff-dominated streams while the High Cascade geology is associated with spring-fed streams. The Western

Cascades has an older geology that reflects erosional volcanism, while the High

Cascades represents recent constructional volcanism. The Western Cascades are classified as having high drainage efficiency with shallow subsurface flow paths through soils one to three meters in depth. Precipitation travels through the soil layer to the stream channel resulting in runoff-dominated streams which are highly responsive to precipitation events. In contrast, the High Cascades has poor soil

90 development due to its young age and low drainage efficiency, but has exceptionally high hydraulic conductivities from the highly porous volcanic layers resulting in a deep groundwater system. Relative to the Western Cascades, the High Cascades has a newer geology that is more porous. Higher porosity allows rain to infiltrate directly to the underlying aquifer which drives spring-fed streams.

Experimental setup

We set up the reciprocal transplant experiment between Boulder Creek, a runoff-dominated stream (seasonally fluctuating flow and temperature) and

Sweetwater Creek, a spring-fed stream (constant flow and temperature) (Fig. 4.2).

Both streams are located in close proximity in the Willamette National Forest, OR, at the foothills of the western slope of the Cascades Mountain Range. We made enclosures out of 19-liter buckets, from which we cut out 12 windows, each measuring

7.5-cm high and 9-cm wide and covered with 500-micrometer Nitex mesh (Fig. 4.3).

The enclosures were topped with an emergence trap that we made fitted to the bucket lid (Fig. 4.3). They contained soapy water to entrain the emerging adults. We placed foam floats on the enclosures so the water level was comparable among all enclosures within a given stream type. In the spring-fed stream, enclosure water level was approximately 30 cm deep in all enclosures for the duration of the experiment. In the runoff-dominated stream, in the beginning of July water levels averaged 23 cm deep, at the end of July water levels averaged 16 cm deep, and in mid August water levels averaged 15 cm deep within the enclosures. We secured the enclosures downstream of each other by tethering them to stable rocks and logs. A wooden dowel was placed

91 in each enclosure to help the larvae climb out of the water to emerge. We placed two moss covered rocks in each enclosure. Yoraperla nigrisoma are highly associated with moss covered rocks (personal observation). We collected rocks from a downstream reach of Sweetwater Creek and used dry ice (CO2) to kill animals living on the rocks before placing them in the enclosures. We collected 200 larvae from each stream over two days and measured head width of all individuals streamside. We placed 20 individuals randomly into each of 20 enclosures (five enclosures per treatment with two treatments per stream). Enclosures were placed in the stream in a randomly determined order (Fig. 4.2). The exact location within the stream took into consideration distance from the road (to discourage vandalism) and suitability based on water depth, flow, and anchor points for the enclosures.

Each day over the 95 day study period we brushed the mesh windows on all of the enclosures to remove trapped debris and keep water flowing through the enclosure.

We also checked for emerged adults. When material appeared to accumulate on the bottom of the enclosures, we used a turkey baster to suck out smaller particles of all enclosures in both streams to clean them out. A 500-micometer mesh sieve was used to make sure that no insects were sucked out of the enclosure.

Sample processing and analyses

Larval data

For the larval data, we first looked at the initial head-width size frequency distribution of the 20 Y. nigrisoma in each enclosure. We then categorized whether the initial distribution contained one or two cohorts (Yamamuro 2009). Similarly, we

92 determined whether one or two cohorts were apparent in the final head-width size frequency distribution of the remaining Y. nigrisoma larvae that survived until the end of our experiment. We calculated a growth rate of final minus initial mean head width size for comparable cohorts and divided by the number of days the larvae were kept in the enclosures (mm/day). We decided to use nonparametric statistical tests because we were comparing low sample sizes of five samples per treatment. We used a nonparametric Kruskal-Wallis Rank Sum test to determine whether growth rates differed between treatments. When differences were found, we compared treatments using a nonparametric Mann-Whitney U test.

Emerged adults

We ran a Kruskal-Wallis test with k = 4 treatments to determine whether there were differences in head width, biomass, wing length, and/or days to emerge between treatments. Similarly, we ran a nonparametric Wilcoxon Rank Sum test to determine whether there were differences in head width, biomass, wing length, and/or days to emerge between sexes. If significant differences were found among treatments, we used a Mann-Whitney U test to determine treatment differences. If differences were found between sexes, we used a Kruskal-Wallis or Wilcoxon Rank Sum test to determine how emerged adults differed between treatments for each sex separately.

Survival

To estimate larval survival we first determined the number of survivors per enclosure by adding the final number of larvae plus the number of adults that emerged from the enclosure. We assumed that unaccounted individuals were mortalities. We

93 performed a Kruskal-Wallis Rank Sum test to determine differences between treatments in percent survival and compared treatments using a Mann-Whitney U test.

Results

Larvae

Growth rate

We found that our prediction was supported that insects transplanted from the spring-fed stream to the runoff-dominated stream would have a higher growth rate than if they had remained in the spring-fed stream. Our prediction that there would be no difference in growth rate between insects that remained in the runoff-dominated stream and those transplanted to the spring-fed stream was also supported. However, our prediction that insects in the runoff-dominated native treatment would have a higher growth rate than those in the spring-fed native treatment was not supported.

We compared growth rate of larvae between treatments to determine whether our prediction was supported that development would be faster in runoff-dominated natives than spring-fed natives, and that spring-fed transplants would increase their development in the runoff-dominated stream. Focusing on cohort 2, on average, larvae originally collected from the spring-fed stream were larger at the beginning of the experiment compared to larvae collected from the runoff-dominated stream (Fig.

4.4). Of all four treatments, only spring-fed natives had a measurable growth rate for cohort 1 (originally larger sized individuals). Therefore, we could not compare cohort

1 growth rates, and only compared cohort 2 growth rate differences between treatments. Larvae in the spring-fed transplant treatment grew faster than those in the

94 runoff-dominated native, spring-fed native, or runoff-dominated transplant treatments

(Fig. 4.5). However, detectable differences in larval growth were not found between runoff-dominated native, runoff-dominated transplant, and spring-fed native treatments (Fig. 4.5).

Emerged adults

Head widths

Our prediction that insects experiencing the runoff-dominated environment would be smaller at emergence than those experiencing the spring-fed environment was not supported. Among all treatments, a total of 28 individuals emerged for the entire duration of the experiment (runoff-dominated native & spring-fed transplant =

94 days, spring-fed native & runoff-dominated transplant = 95 days). Three adults emerged from the runoff-dominated native treatment, 13 emerged from the spring-fed transplant treatment, 11 emerged from the spring-fed native treatment, and one emerged from the runoff-dominated transplant treatment. We found that emerged adults from the spring-fed native treatment had smaller head widths than those from the spring-fed transplant treatment (Fig. 4.6). However, we didn’t detect any head width differences between the other combinations of runoff-dominated native, spring- fed transplant, runoff-dominated transplant, and spring-fed native treatments (Fig.

4.6). Head widths of emerged females were larger than those of males (Fig. 4.7).

Biomass and wing length

Our prediction that biomass would be higher in insects exposed to the spring- fed flow regime than those that experienced the runoff-dominated flow regime was not

95 supported. Patterns of biomass and wing length were similar. Emerged adults had higher biomass in the runoff-dominated native treatment than either the spring-fed native or transplant treatments (Fig. 4.8 & 4.9). We did not detect differences between the runoff-dominated native or transplant treatments and spring-fed native or transplant treatments. Also, we did not find biomass differences between the runoff- dominated transplant and spring-fed native or transplant treatments.

Emergence timing

Our prediction that insects experiencing the runoff-dominated flow regime would emerge in a shorter amount of time than insects exposed to the spring-fed flow regime was partially supported. We found that the runoff-dominated native treatment emerged in less time than the spring-fed native and transplant treatments (Fig. 4.10).

However, runoff-dominated natives and transplants did emerge at the same time. The runoff-dominated transplant treatment was not different compared to the spring-fed native and transplant treatments. We did not detect any differences in emergence timing between the spring-fed native and transplant treatments.

All life stages

Survivorship

Our prediction that insects transplanted to the spring-fed stream from the runoff-dominated stream and the insects native to the spring-fed stream would have a higher survivorship than the insects experiencing the runoff-dominated flow regime was partially supported. The percent of individuals surviving over the duration of the experiment was lower in the runoff-dominated native compared to the spring-fed

96 native treatment, but not significantly different in other comparisons (Fig. 4.11). All other treatment combinations did not differ in survival.

Discussion

Larval growth patterns

Larval growth rate patterns provide evidence that this trait has both phenotypically plastic factors and factors lacking phenotypic plasticity contributing to differences between runoff-dominated and spring-fed streams. Within both environments, larvae originating from the spring-fed stream grew faster than those originating from the runoff-dominated stream. This may indicate that spring-fed individuals grow more efficiently in general, or it could be due to the fact that individuals originating in spring-fed streams were larger at the start of the experiment and therefore had a growth advantage. We predicted that the insects from the spring- fed stream would increase their development activity, while those from the runoff- dominated stream would increase their growth activity when transplanted in the other environment type (Fig. 4.1). Our results support the first prediction when we assume that development is analogous to growth rate (with each molt to a larger size, larvae are maturing), and head width (proxy for size) is related to the age of an individual in the context of the population that they came from. We claim that growth is measured by mass (individuals fatten up and increase their mass to grow while their head width can remain the same)(Fig. 4.1). Individuals with larger rates of change in head width are predicted to have invested more energy towards development (typical of runoff- dominated (warmer) stream inhabitants) while more massive individuals have invested

97 more energy towards growth (typical of spring-fed (cooler) stream inhabitants)(Fig.

1). In May 2007, daytime temperatures ranged from7.5 to 8.5 degrees C in runoff- dominated streams and 4.2 to 6.5 degrees C in spring-fed streams. Also, of all the treatments, spring-fed transplants grew fastest, which may indicate that the warmer water temperatures of their new environment may have sped up their metabolic and therefore developmental rates. However, we were unable to test the second prediction related to growth because we were not able to measure individual larval biomass at the beginning of the experiment. We wanted to reduce handling time and stress related to removing them from the water to weigh them.

Emerged adult patterns

Our results for emerging adults are affected by having a small sample size

(runoff-dominated native = 3, runoff-dominated transplant = 1, spring-fed native = 11, spring-fed transplant = 13). Therefore, we acknowledge that forming conclusions from these results should be done with small sample sizes in mind. Additionally, some sexual dimorphic characteristics (Fig. 4.7) may have disproportionately affected our results since we were dealing with small sample sizes. We found the same pattern of larger biomass, longer wing length, and earlier emergence in the runoff-dominated native treatment compared to the spring-fed native and transplant treatments.

Generally, size is proportional to wing length and larger size is related to early emergence. Our findings support the pattern found by Vannote and Sweeney (1980) that found that size at emergence is greater earlier on in the emergence period.

Additionally, it appears that regardless of local adaptation, survivorship is higher for

98 spring-fed natives than for runoff-dominated natives. This supports our prediction that a seasonally variable environment is harsher to live in than a relatively steady environment.

Adult head width and biomass at emergence showed different patterns.

Patterns in head width support environmental variation having a greater influence in size differences between treatments than genotypic differences. In contrast, biomass patterns indicate that more factors that lack phenotypic plasticity than phenotypically plastic factors influence the differences between treatments. Larger head widths in emerged adults from the spring-fed transplant than the native treatment support larval evidence that growth rates were highest in the spring-fed transplant treatment.

Our results partially support the Thermal Equilibria Hypothesis presented by

Vannote and Sweeney (1980), which states that rapid shifts of energy use occur in response to thermal variation. They found that aquatic insects in warmer than optimal environments partition more resources towards maintenance metabolism than constructive metabolism causing faster development at the cost of growth. On the other hand, aquatic insects in optimal temperature conditions allocate more resources towards constructive metabolism than maintenance metabolism enabling more growth and larger adults than in suboptimal temperature environments. Based on Vannote and Sweeney’s (1980) findings, we predicted that (Fig. 4.1) in their native environment, those from the runoff-dominated stream would be better at developing than those from the spring-fed stream. Likewise, those from the runoff-dominated stream would be worse at growing than those from the spring-fed stream in their

99 native environment. We took these temperature related resource partitioning strategies into consideration.

Maternal effects (e.g., egg size) could have affected our findings because larvae were collected in the field (Bernardo 1996, Mousseau and Fox 1998). Maternal effects may influence the organism’s phenotype in addition to a combination of the individual’s genotype plus effects of the environment during development. Studies on animals generally attempt to prevent maternal effects from factoring as a driver of phenotypic variation by starting a reciprocal transplant experiment with eggs of the F2 generation gathered from each environment type and raised in the same laboratory environment (Conover and Schultz 1995). While attempting to eliminate the influence of maternal effects, such an experimental design does not consider that these effects are important in shaping offspring differences between different environments

(Bernardo 1994). Additionally, rearing generations of test organisms in an artificial environment prior to placing offspring in a native or transplant environment may influence phenotypic variation in the experiment differently than if they were directly moved to the environments of interest (Bernardo 1996). For example, eggs produced in a controlled lab environment have qualities far different to those found in nature.

Specifically, in the runoff-dominated streams, in a previous study, we found evidence supporting diapausing eggs, while eggs in spring-fed streams did not appear to diapause (Yamamuro 2009). Thirdly, attempting to neutralize maternal effects in an artificial environment by pooling individuals of the same size class may prevent proper analysis regarding drivers of phenotypic variation in nature because there are

100 natural size frequency distribution differences depending on stream type (Yamamuro

2009).

An ideal experiment would keep each egg separately to keep track of individual results, and ultimately increase the power of statistical analyses. If feasible, this technique would lead to simpler and more interpretable analyses.

However, that experimental design would not address whether phenotypically plastic factors or factors lacking phenotypic plasticity affect life-history traits better for a natural population than our study design. Y. nigrisoma are often found in dense groups (personal observation), therefore placing individuals in their own enclosure may affect their life-history traits so they are not representative of a naturally occurring population. Also, placing many enclosures in one stream, no matter how small, will likely affect the flow within the enclosures, which may negatively alter our treatments. Additionally, placing many enclosures in one stream will involve a large longitudinal area which may make longitudinal environmental variation a confounding variable.

In conclusion, we found that both phenotypically plastic factors and factors lacking phenotypic plasticity affect life-history traits between the runoff-dominated and spring-fed stream. Our findings indicate that an organism’s reaction to being placed in drastically different flow regimes may be very specific to their starting and ending environments. Also, in the event that a stream with a runoff-dominated flow regime is changed to a spring-fed flow regime (dam with steady hypolimnetic flow release), the aquatic insect may develop a distinct phenotype that is different from

101 organisms adapted to either a runoff-dominated or spring-fed flow regime. A potential loss of phenotypic diversity may occur.

Acknowledgements

Edwin Price and Ashley Timko assisted with field and lab work. Edwin Price and Nick Chambers helped with enclosure construction. A Grant-in-Aid of Research was awarded to A. M. Yamamuro by Sigma Xi. Partial funding also came from

National Science Foundation grants (IIS-0326052, IIS-0705765, and DEB-0445366).

References

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Lytle, D. A. 2002. Flash floods and aquatic insect life-history evolution: evaluation of multiple models. Ecology 83:370–385. Lytle, D. A., and N. L. Poff. 2004. Adaptation to natural flow regimes. Trends in Ecology & Evolution 19:94–100. Mousseau, T. A., and C. W. Fox. 1998. The adaptive significance of maternal effects. Trends in Ecology & Evolution 13:403–407. Poff, N. L., J. D. Allan, M. B. Bain, J. R. Karr, K. L. Prestegaard, B. D. Richter, R. E. Sparks, and J. C. Stromberg. 1997. The natural flow regime. BioScience 47:769–784. Resh, V. H., A. V. Brown, A. P. Covich, M. E. Gurtz, H. W. Li, G. W. Minshall, S. R. Reice, A. L. Sheldon, J. B. Wallace, and R. C. Wissmar. 1988. The role of disturbance in stream ecology. Journal of the North American Benthological Society 7:433–455. Roff, D. A. 1996. The evolution of genetic correlations: an analysis of patterns. Evolution 50:1392–1403. Tague, C., M. Farrell, G. Grant, S. Lewis, and S. Rey. 2007. Hydrogeologic controls on summer stream temperatures in the McKenzie River basin, Oregon. Hydrological Processes 21:3288–3300. Tague, C., and G. E. Grant. 2004. A geological framework for interpreting the low- flow regimes of Cascade streams, Willamette River Basin, Oregon. Water Resources Research 40:W04303. Townsend, C. R., and A. G. Hildrew. 1994. Species traits in relation to a habitat templet for river systems. Freshwater Biology 31:265–276. Vannote, R. L., G. W. Minshall, K. W. Cummins, J. R. Sedell, and C. E. Cushing. 1980. The river continuum concept. Canadian Journal of Fisheries and Aquatic Sciences 37:130-137. Vannote, R. L. and B. W. Sweeney. 1980. Geographic analysis of thermal equilibria: a conceptual model for evaluating the effect of natural and modified thermal regimes on aquatic insect communities. The American Naturalist 115:667-695. Ward, J. V. and J. A. Stanford. 1983. The serial discontinuity concept. Pages 29-42 in Dynamics of lotic ecosystems. T. D. Fontaine III and S. M. Bartell (eds.). Ann Arbor Science, Ann Arbor, Michigan. Yamamuro, A. M. 2009. Aquatic insect adaptations to different flow regimes. Ph.D. dissertation. Corvallis, OR. Oregon State University.

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Figure 4.1. Theoretical patterns of a reciprocal transplant experiment between a runoff-dominated and spring-fed stream when (a) development is directly related to growth rate and (b) growth is directly measured as mass.

104

Runoff-dominated origin Spring-fed origin

Runoff-dominated stream

Spring-fed stream

Figure 4.2. Reciprocal transplant experimental design showing random ordering of replicate enclosures across the two stream types.

105

Figure 4.3. View of (a) inside of enclosure and (b) outside of the enclosure.

106

Boulder

30 Cohort 2

15 frequency Frequency Cohort 1

Sweetwater

0 30 0.475 0.6 0.725 0.85 0.975 1.1 1.225 1.35 1.475 headwidth (mm)

Cohort 2 20

15 frequency Cohort 1

10 Frequency

0 0.475 0.6 0.725 0.85 0.975 1.1 1.225 1.35 1.475 headwidth (mm)

Head width (mm) Figure 4.4. Frequency histogram of head width sizes of insects collected prior to the experiment from a) the runoff-dominated stream and b) the spring-fed stream. n = 200 for each stream type.

107

0.0025

SF-T 0.0020

0.0015 SF-N

RO-N

growth growth rate (mm/day) RO-T 0.0010

0.0005 Runoff-dominated Spring-fed

Figure 4.5. Reciprocal transplant growth rate differences between larvae in four treatments: runoff-dominated native (RO-N), spring-fed transplant (SF-T), spring-fed native (SF-N), and runoff-dominated transplant (RO-T).

108

1.50

1.45

1.40

RO-N 1.35 RO-T

SF-T

Headwidth(mm) 1.30

1.25 SF-N

1.20 Runoff-dominated Spring-fed

Figure 4.6. Reciprocal transplant head width differences between emerged adults from four treatments: runoff-dominated native (RO-N), spring-fed transplant (SF-T), spring-fed native (SF-N), and runoff-dominated transplant (RO-T).

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1 .6 a. Runoff-dom inated native Runoff-dom inated transplant Spring-fed native Spring-fed transplant

1 .4

head head width(mm) 1 .2

1 .0 b. 0 .0 2 4

0 .0 2 0

0 .0 1 6

0 .0 1 2 biomass (g)

0 .0 0 8

0 .0 0 4

9 .5 c.

9 .0

8 .5

8 .0

wing length wing (mm) 7 .5

7 .0

6 .5

Female Male Figure 4.7. Reciprocal transplant experiment differences between recently emerged female vs. male adults in (a) head width, (b) biomass, and (c) wing length. Each symbol represents an individual.

110

0.020

0.018

0.016 RO-N RO-T 0.014

0.012 Biomass (g)Biomass

0.010 SF-T SF-N 0.008

0.006 Runoff-dominated Spring-fed

Figure 4.8. Reciprocal transplant biomass differences between emerged adults from four treatments: runoff-dominated native (RO-N), spring-fed transplant (SF-T), spring-fed native (SF-N), and runoff- dominated transplant (RO-T).

111

9.5 RO-T

9.0 RO-N

8.5

8.0 Wing length (mm)

7.5 SF-T SF-N

7.0 Runoff-dominated Spring-fed

Figure 4.9. Reciprocal transplant wing length differences between emerged adults from four treatments: runoff-dominated native (RO-N), spring-fed transplant (SF-T), spring-fed native (SF-N), and runoff-dominated transplant (RO-T).

112

SF-T SF-N

50 RO-T

40 Days to emergeDays to

30 RO-N

20 Runoff-dominated Spring-fed

Figure 4.10. Reciprocal transplant days to emerge differences between emerged adults from four treatments: runoff-dominated native (RO-N), spring-fed transplant (SF-T), spring-fed native (SF-N), and runoff- dominated transplant (RO-T).

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100

80 SF-N

SF-T 60 RO-T Survival (%)Survival

40 RO-N

20 Runoff-dominated Spring-fed

Figure 4.11. Reciprocal transplant percent survival differences between larvae plus emerged adults from four treatments: runoff-

dominated native (RO-N), spring-fed transplant (SF-T), spring-fed native (SF-N), and runoff-dominated transplant (RO-T).

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CHAPTER 5: CONCLUSIONS

This dissertation documented how environmental variation shapes population and community patterns of aquatic organisms. We learned more about aquatic insect adaptations to variation in flow regimes. A seasonally variable flow regime compared to a relatively steady flow regime may affect aquatic insects differently depending on tolerance characteristics. For example, an insect that cannot tolerate low oxygen levels may be more likely to be found in a cool, steady spring-fed stream and not in a runoff-dominated stream that heats up and dries down in the summer since cooler and more turbulent water has higher oxygen concentration than warmer, slower-flowing water. We compared aquatic insect community (Chapter 2) and population (Chapter

3) differences between runoff-dominated and spring-fed streams. Additionally, we tested the mechanism for these differences by conducting a reciprocal transplant experiment to determine whether life-history traits responded with phenotypic plasticity induced by the environment (Chapter 4).

Community taxonomic composition

My dissertation provides further evidence that flow regime is important in understanding stream ecosystem biodiversity (Vannote et al. 1980, Ward and Stanford

1983). In Chapter 2, we found differences in community taxa composition between runoff-dominated and spring-fed streams, which provides strong evidence that by simply grouping streams by flow regime type, distinct community differences can be detected.

115

Unlike similar studies (Boulton et al. 1992), we used a grouped stream study design with data from two separate years, which allowed for stronger statistical power to support the hypothesis that flow regime affects biotic community composition. We identified reliable indicator taxa, which may have a preference or specialization, for either stream type. In our study, indicator taxa may be adapted to live in either a runoff-dominated or spring-fed stream. We found that larval Ameletus (order

Ephemeroptera) and Calineuria (order Plecoptera) were prominent indicator genera for runoff-dominated streams and that Caudatella (order Ephemeroptera) and

Yoraperla (order Plecoptera) were prominent indicator genera for spring-fed streams.

Our study was not designed to identify the mechanism for patterns in prominent indicator genera for runoff-dominated and spring-fed streams.

Community life-history trait composition

We found significant life-history differences between the two stream types.

Semivoltine, poorly synchronized emergence and slow seasonal development traits were indicators for spring-fed streams. Trait studies are often difficult to interpret because data that categorize traits at the genus level may not accurately capture the diversity within a genus and even within a species because phenotypic plasticity is not usually taken into account.

Biodiversity measures

We found that biodiversity measures were higher in runoff-dominated streams than in spring-fed streams. However, the differences were not large, so this may imply that disturbance is not the only factor influencing diversity (Doak et al. 1998).

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To summarize Chapter Two, community genera and life-history trait composition and biodiversity measures differed between seasonally fluctuating and relatively constant streams. These differences between grouped streams of both types located in similar proximity support the hypothesis that flow regime is a primary driver in differentiating stream ecosystems.

Pattern differences between larval cohorts of runoff-dominated and spring-fed streams

Our population-level study provided detailed differences in addition to our community study of differences between runoff-dominated and spring-fed streams

(Chapter 3). We found that within a population of Yoraperla nigrisoma, individual size within a cohort is larger towards the end of summer in spring-fed streams than in runoff-dominated streams. This finding supports our hypothesis that a lack of seasonal cues in spring-fed streams allows insects to avoid trading off growth for development.

We also found that cohorts in both stream types showed semivoltine patterns; however, the patterns were distinctly different between stream types. Both streams had generation patterns of two years. At the end of the summer, spring-fed streams had three distinct cohorts, while four out of five runoff-dominated streams had two distinct cohorts present. Cohort splitting in spring-fed streams may cause the differences in the number of cohorts present at the end of the summer. The adults in runoff-dominated streams may lay eggs that diapause, since larvae are not apparent until much later than in spring-fed streams, even though adults have similar emergence

117 times in both stream types. This may occur because stream conditions in runoff- dominated streams towards the end of summer are inhospitable towards developing larvae due to warmer water and smaller water volume. In cohort 1, Y. nigrisoma had a consistently higher growth rate between August 2005 and April 2006 in runoff- dominated streams than in spring-fed streams. In runoff-dominated streams, higher growth rates between fall and spring may coincide with better conditions for Y. nigrisoma growth compared with other seasons. In the fall, there is leaf fall to provide nutrients. The winter rainy season provides more water and increasing habitat volume.

Pattern differences in adult emergence between runoff-dominated and spring-fed streams

Consistent with the pattern of larger larvae, spring-fed streams had reliably larger individuals emerging from the end of June to the end of August 2006 (Chapter

3). However, we found no difference in the proportion of adults emerging or timing of emergence between the two stream types.

To summarize Chapter Three of my dissertation, population patterns for

Yorperla nigrisoma living in runoff-dominated streams were distinctly different from those living in spring-fed streams. Since we grouped streams by flow regime type, our findings support that flow regime is highly associated with these life-history differences. It appears that time constraints and seasonal environmental changes characteristic of runoff-dominated streams produced distinct life-history patterns compared to those expected in spring-fed streams. Y. nigrisoma in spring-fed streams

118 have a more consistent growth rate year round, and they emerge at a larger size and have more cohorts present than in runoff-dominated streams.

Larval growth rate patterns compared in a reciprocal transplant experiment

Y. nigrisoma transplanted from the spring-fed stream to the runoff-dominated stream grew at a faster rate than those native to the runoff-dominated stream, and they grew faster than those that stayed in the spring-fed stream. This result may support the Thermal Equilibrium Hypothesis that aquatic insects in warmer environments, like runoff-dominated streams during the summer, will allocate more energy towards development while those in cooler environments, like spring-fed streams, will allocate more energy towards growth (Vannote & Sweeney 1980). Therefore, when insects from the spring-fed stream are transferred to the runoff-dominated stream, they speed up their development, which is measured by change in head width over time.

We also found differences between treatments for newly-emerged adults, but the small sample sizes associated with these results should be considered. The results seem to reflect that in this experiment, adult females were larger and have longer wings than males.

Broader implications

Our study provides evidence to ecologists and stream managers that flow regime type can be used to predict community taxonomic composition in streams. Our findings support using flow regime type to classify community taxonomic composition.

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Flow regimes are constantly being changed by dams, droughts, floods, rerouted paths, climate change, groundwater removal, and other factors, and we advocate finding general and consistent patterns by analyzing community genera and life- history trait composition in relation to flow regime. This study supports the potential for focusing on flow regime to allow stream ecologists and managers to properly document accurate and broad community differences efficiently. Streamlining research will enable stream ecologists and managers to better communicate to other scientists and the public how communities are changing. Broad-spectrum knowledge and increased confidence in the data will facilitate biodiversity conservation efforts and predict biodiversity losses in stream ecosystems that are undergoing flow regime changes. For example, if dams are placed in the runoff-dominated streams of the western slope of the Cascades range, making them more like spring-fed streams with regulated discharge and hypolimnetic flow, which is a colder temperature, we predict that based on flow regime changes, Ameletus and Calineuria may be lost, proportions of semivoltine, poorly synchronized emergers, and slow seasonal developers will increase, and overall diversity will decrease.

Virtually all major rivers and streams worldwide have been altered by humans, yet little is known about how alteration of the natural flow regime affects stream-dwelling organisms. We emphasize the importance of understanding and predicting changes in biota associated with the sudden shift in flow regimes to provide necessary guidance on emerging conservation and management issues.

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APPENDICES

132

APPENDIX A. Physical features of ten study streams

133

APPENDIX A

Table A1. Study stream location coordinates, elevations, and watershed areas. First five streams listed are runoff-dominated streams and last five streams listed are spring- fed streams.

Watershed Creek Latitude (°) Longitude (°) Elevation (m) Area (km2) Florence 44.18119 122.18792 447 6.975 Scott 44.19751 122.03822 524 21.986 Boulder 44.20485 122.03795 533 23.496 Fritz 44.26843 122.07118 685 4.777 Kink 44.29566 122.02701 696 6.964 Olallie 44.27215 122.01825 754 4.005 Sweetwater 44.2829 122.02443 732 2.425 Payne 44.28759 122.02898 693 0.274 Ice Cap 44.34263 121.99917 831 0.077 Anderson 44.26428 122.04046 637 2.719

134

APPENDIX A

0.5

-0.5

-1

-1.5 (m³/s) logdischarge -2

-2.5 Jul-05 Oct-05 Jan-06 Apr-06 Jul-06

Figure A1. Discharge measurements for five runoff-dominated streams (solid line) and five spring-fed streams (dashed line).

135

APPENDIX A

Table A2. Table of substrate composition based on a Wolman pebble count for each stream. Wood = sticks & logs. Sand = substrates less than 2 mm. Pebble = substrates between 2 to 63 mm. Cobble = substrates between 64 to 255 mm. Boulder = substrates 256 to 4096 mm. First five streams listed are runoff-dominated streams and last five streams listed are spring-fed streams.

Creek % Wood % Sand % Pebble % Cobble % Boulder Florence 7.6 0.6 18.1 37.4 36.3 Scott 10.4 0.0 21.7 47.0 20.8 Boulder 3.7 0.7 15.5 32.0 48.0 Fritz 8.5 2.3 14.1 28.5 46.7 Kink 11.4 3.5 27.1 41.9 16.2 Olallie 29.8 3.1 43.5 19.9 3.7 Sweetwater 25.0 14.3 43.9 12.4 4.4 Payne 41.8 13.6 24.5 16.4 3.6 Ice Cap 54.5 6.3 18.0 16.9 4.2 Anderson 9.2 3.8 54.3 30.8 1.9

136

APPENDIX B. Temperature measurements of ten study streams

137

APPENDIX B

Figure B1. Boulder Creek, a runoff-dominated stream, temperature measurements for two time intervals.

138

APPENDIX B

Figure B2. Sweetwater Creek, a spring-fed stream, temperature measurements for two time intervals.

139

APPENDIX B

Figure B3. Florence Creek, a runoff-dominated stream, temperature measurements for two time intervals.

140

APPENDIX B

Figure B4. Fritz Creek, a runoff-dominated stream, temperature measurements for two time intervals.

141

APPENDIX B

Figure B5. Ice Cap Creek, a spring-fed stream, temperature measurements for two time intervals.

142

APPENDIX B

Figure B6. Kink Creek, a runoff-dominated stream, temperature measurements for two time intervals.

143

APPENDIX B

Figure B7. Olallie Creek, a spring-fed stream, temperature measurements for two time intervals.

144

APPENDIX B

Figure B8. Payne Creek, a spring-fed stream, temperature measurements for two time intervals.

145

APPENDIX B

Figure B9. Scott Creek, a runoff-dominated stream, temperature measurements for two time intervals.

146

APPENDIX B

Figure B10. Anderson Creek, a spring-fed stream, temperature measurements for two time intervals.

147

APPENDIX C. Size frequency distributions of Yoraperla nigrisoma larvae collected from ten study streams

148

APPENDIX C

60 60 SCOTT ANDERSON

30 30 AUG05

0 600 60 OLALLIE KINK

30 30

0 60 600 FLORENCE PAYNE

30 30

0 600 60 ICE CAP FRITZ

30 30

0 600 60 BOULDER SWEETWATER

30 30

0 0 0.3 0.55 0.8 1.05 1.3 1.55 0.3 0.55 0.8 1.05 1.3 1.55 head width (mm) head width (mm)

Figure C1. Frequency graphs of Yoraperla nigrisoma larval head widths for ten study streams in August 2005. Y-axis is count. Left column graphs are runoff-dominated streams and right column graphs are spring-fed streams.

149

APPENDIX C

60 60 SCOTT ANDERSON

30 30 APR06

600 600 KINK OLALLIE

30 30

600 600 PAYNE FLORENCE

30 30

600 600 ICE CAP FRITZ

30 30

0 600 60 BOULDER SWEETWATER

30 30

0 0 0.3 0.55 0.8 1.05 1.3 1.55 0.3 0.55 0.8 1.05 1.3 1.55 head width (mm) head width (mm)

Figure C2. Frequency graphs of Yoraperla nigrisoma larval head widths for ten study streams in April 2006. Y-axis is count. Left column graphs are runoff-dominated streams and right column graphs are spring-fed streams.

150

APPENDIX C

90 90

SCOTT ANDERSON 60 60

30 May06 30

0 0 90 90 OLALLIE

60 KINK 60

30 30

0 0

90 90

PAYNE 60 FLORENCE 60

30 30

0 0 90 90 ICE CAP 60 FRITZ 60

30 30

0 0 90 90

BOULDER SWEETWATER 60 60

30 30

0 0 0.3 0.55 0.8 1.05 1.3 1.55 0.3 0.55 0.8 1.05 1.3 1.55 head width (mm) head width (mm)

Figure C3. Frequency graphs of Yoraperla nigrisoma larval head widths for ten study streams in May 2006. Y-axis is count. Left column graphs are runoff-dominated streams and right column graphs are spring-fed streams.

151

APPENDIX C

60 60 SCOTT ANDERSON

30 30 JUL06

0 0 60 60 KINK OLALLIE

30 30

0 60 0 60 FLORENCE PAYNE

30 30

0 60 600 FRITZ ICE CAP

30 30

600 600 BOULDER SWEETWATER

30 30

0 0 0.3 0.55 0.8 1.05 1.3 1.55 0.3 0.55 0.8 1.05 1.3 1.55 head width (mm) head width (mm)

Figure C4. Frequency graphs of Yoraperla nigrisoma larval head widths for ten study streams in July 2006. Y-axis is count. Left column graphs are runoff-dominated streams and right column graphs are spring-fed streams.

152

APPENDIX C

90 90

60 60 Aug06 30 30

0 0 90 90

60 60

30 30

0 0 90 90

60 60

30 30

0 0 90 90

60 60

30 30

0 0 90 90

60 60

30 30

0 0 0.3 0.55 0.8 1.05 1.3 1.55 0.3 0.55 0.8 1.05 1.3 1.55 head width (mm) head width (mm)

Figure C5. Frequency graphs of Yoraperla nigrisoma larval head widths for ten study streams in August 2006. Y-axis is count. Left column graphs are runoff-dominated streams and right column graphs are spring-fed streams.

153

APPENDIX C

60 60 SCOTT ANDERSON

30 30 Sep06

0 0 60 60 KINK OLALLIE

30 30

0 60 600 FLORENCE PAYNE

30 30

0 60 0 60 FRITZ ICE CAP

30 30

0 60 0 60 BOULDER SWEETWATER

30 30

0 0 0.3 0.55 0.8 1.05 1.3 1.55 0.3 0.55 0.8 1.05 1.3 1.55 head width (mm) head width (mm)

Figure C6. Frequency graphs of Yoraperla nigrisoma larval head widths for ten study streams in September 2006. Y-axis is count. Left column graphs are runoff- dominated streams and right column graphs are spring-fed streams.