Development and Application of a Geospatial Database of Sierra Nevada Lakes and Reservoirs

ABSTRACT

DEVELOPMENT AND APPLICATION OF A GEOSPATIAL DATABASE OF SIERRA NEVADA LAKES AND RESERVOIRS

by Molly Gail Mehling

High-elevation, mountain regions, such as the Sierra Nevada, are characterized as extremely heterogeneous and ecologically fragile. The Sierra Nevada has been recognized for its high conservation value, but historical and predicted tourism and development threaten the ecological resources of the region. Assessment and monitoring of the Sierra Nevada’s aquatic resources and their catchments is crucial to their balanced management. Using a digital geospatial database, landscape-scale variables of morphometry, land cover and human activities were quantified for 20 assessment sites and their catchments in the most rapidly developing area of the ecoregion, the central Sierra Nevada. Landscape-scale variables revealed ecological and anthropogenic heterogeneity among the sites. These measurements were incorporated into a multi-level index of ecological integrity and were analyzed with multivariate statistical methods to objectively assess similarity among sites. It is expected that these metrics will be incorporated into a multi-level assessment protocol.

DEVELOPMENT AND APPLICATION OF A GEOSPATIAL DATABASE OF SIERRA NEVADA LAKES AND RESERVOIRS

A Practicum Report

Submitted to the Faculty of Miami University In partial fulfillment of the Requirements for the degree of Master of Environmental Science Institute of Environmental Sciences

By Molly Gail Mehling Miami University Oxford, Ohio 2006

Advisor: ______

Dr. James Oris

Reader: ______

Dr. Gene Willeke

Reader: ______

Dr. William Renwick

TABLE OF CONTENTS

Table of Contents ...... ii List of Figures ...... iii List of Tables ...... iv List of Plates...... v Acknowledgments...... vi Chapter 1: Introduction...... 1 Chapter 2: Assessment Site Descriptions...... 6 Chapter 3: Development of a Geospatial Database...... 21 Chapter 4: Quantification of Landscape-scale Characteristics...... 25 Chapter 5: Application of Landscape-scale Characteristics...... 45 Chapter 6: Conclusions ...... 52 Literature Cited ...... 54

LIST OF FIGURES

Figure Page 1. Locations of assessment sites ...... 7 2. Examples of varying degrees of shoreline development...... 29 3. Index of ecological integrity ...... 47

ii i

LIST OF TABLES

Table Page 1. General descriptive characteristics of assessment sites...... 8 2. GIS layers and their respective sources ...... 24 3. Ecological characteristics of assessment sites...... 33 4. Relative percentages of USGS NLCD 1992 land cover classes ...... 36 5. Human activity within assessment site catchments...... 39 6. Variable groups and variables for multi-level index of ecological integrity ...... 46 7. Rescaled PCA eigenvectors for morphological, land cover, and human activity comparison ...... 49

LIST OF PLATES

Plate Page 1. Upper Angora Lake ...... 9 2. Donner Lake ...... 12 3. Eagle Lake ...... 13 4. Sand Harbor, Lake Tahoe...... 15 5. Marlette Lake...... 17 6. Spaulding Reservoir...... 18 7. Stampede Reservoir ...... 19 8. Tahoe Keys, Lake Tahoe: Shoreline Development...... 42

ACKNOWLEDGMENTS

It is a pleasure to thank the many people who inspired, supported and assisted me on the path to my practicum’s completion. It is difficult to overstate my gratitude to my adviser, Dr. James Oris, for this opportunity. With his patience and guidance I was able to refine many skills and develop novel ones while contributing to a valuable research project. I must also extend sincere gratitude to Dr. Avram Primack who provided me with GIS shortcuts and suggestions throughout the project.

I am indebted to my many student colleagues for providing a stimulating and fun environment in which to learn and grow. Collaboration with Carrie Smith and Scott McClain enhanced this research significantly. I am especially grateful to Tom Arbour, Dana Thomas, and Nathan Moyer for many hours of intellectually stimulating discussions. Lastly, I’d like to thank my husband, Los, for his selfless contributions to this practicum. I am not only eternally grateful for his support of my career, but for the many mind-bending conversations about tourism and the environment. I look forward to our collaborations, both personal and professional.

I am extremely grateful to be a part of the Miami University Institute of Environmental Sciences (IES) family. Drs. Gene Willeke, Sandy Woy-Hazelton, and Vincent Hand have always been intrigued and supportive of my research endeavors providing valuable constructive criticism along every step of the way. IES has provided me with the strongest of foundations on which to build my environmental career. I will always be grateful for the interdisciplinary, collaborative, problem- solving framework in which I was trained. I dedicate this practicum to my IES mentors.

Chapter 1

INTRODUCTION

SIERRA NEVADA ECOREGION

The Sierra Nevada, located in the western United States, is the longest, unbroken chain of mountains in North America, spanning 400 miles north to south. Recreational opportunities and breath-taking scenery attract tourists year round as well as an ever-increasing population of permanent residents. Between 1970 and 1990, the human population in the Sierra Nevada doubled from 300,000 to 650,000, most of which was concentrated in three counties (Nevada, Placer, and El Dorado) (Davis, 1996). The population is expected to reach nearly 2 million by 2040. The growing population has not come without taking an ecological toll on the region. One of the most publicized of these impacts is the eutrophication of Lake Tahoe. Lake Tahoe, one the nation’s largest, clearest, and deepest lakes, is the most popular natural attraction of the Sierra Nevada. However, over the last 50 years a measured loss of water clarity has sparked concern among stakeholders, those parties interested in the condition and fate of Lake Tahoe (Goldman, 1988; Tarnay et al., 2001).

The Sierra Nevada ecoregion, once thought to be pristine, is now recognized for its fragility. A thorough environmental assessment of the ecoregion, the Sierra Nevada Ecosystem Project (SNEP), was conducted in the mid 1990s, and a comprehensive report was submitted to Congress in 1996 (Davis, 1996). In 1997, the Lake Tahoe Presidential Forum was held in Incline Village, NV. At the forum, President Clinton pledged $50 million to protect and restore Lake Tahoe and its basin. The region is also recognized by the World Wildlife Fund as a “globally outstanding ecoregion requiring immediate protection or restoration” (Ricketts et al., 1999). More recently, the United Nations designated 2002 as the International Year of Mountains to celebrate and bring recognition to the world’s ecologically and culturally diverse

regions. A result of this recognition prompted the completion of the first Mountain Watch report, completed by the United Nations Environment Programme (UNEP) and many partners (2002). The report identifies three mountainous areas of particular concern for global conservation based on high biodiversity and severe environmental pressures. One of those areas was the montane ecoregions of California (UNEP et al., 2002: 8) and the other two regions identified were the North-Western Andean moist forest and Magdeleña Valley of South America and the Caucasus mixed forests ecoregion.

High-elevation, mountainous regions, such as the Sierra Nevada, are characterized as extremely spatially heterogeneous, high in biodiversity, relatively low in productivity, and particularly sensitive to environmental stressors (Heinonen et al., 2000). These systems are topographically complex with a high degree of variation in slope and altitude within a small area. Ecological resistance, the ability to withstand change after a disturbance, and ecological resilience, the ability of an ecosystem to recover after a disturbance, are both characteristically low in mountainous regions. The spatial complexity of mountains has been suggested to contribute to the low resilience of these systems (Haslett, 1997), but also the biodiversity (Peterson et al., 1997). Mountain ecosystems have short growing seasons, less than 180 days, which limits growth, reproduction, and survival of inhabiting organisms. The short growing season also limits recovery from environmental disturbance, in other words, reduces resilience. There is evidence that these systems are slow to recover following environmental disturbance, and some disturbed areas have not yet recovered to their initial conditions (Wang et al., 2003; Whinam & Chilcott, 2003; Knapp et al., 2001). However, there is conflicting evidence regarding resistance and resilience of high- elevation ecosystems. With regard to fish introductions into historically fishless lakes, Knapp et al. (2005) found that lakes and ponds in the Sierra Nevada had low resistance, but high resilience. The lake’s food webs were quickly and drastically altered upon introduction of fish, but recovered quickly once fish were removed.

The Sierra Nevada is not only altitudinally diverse with elevations reaching over 4400 2

m, but the orographic effect, resulting from the north to south orientation of the range and the west to east prevailing weather pattern, moistens the western half of the range, leaving the eastern half with much drier conditions. In addition, the Sierra Nevada spans 400 miles, thus the north and south latitudinal gradient adds another layer of ecological complexity. Furthermore, the region is geologically diverse with an abundance of granite, sedimentary, volcanic and metamorphic rocks. The Sierra Nevada has been sculpted largely by a combination of uplift and glaciation and is currently one of the most tectonically active regions in the world.

SIERRA NEVADA AQUATIC RESOURCES

It has been stated that the Sierra Nevada’s aquatic resources are the most negatively impacted habitats of the ecoregion (Davis, 1996). Direct impacts from atmospheric deposition of pollutants (Heyvaert et al., 2000; Tarnay et al. 2001; Zhang et al., 2002), residential and recreational activity (Adams & Minor, 2000), water diversion/damming, non-native fish introductions (Knapp and Matthews, 2000; Schindler et al., 2001), and an increase in UV-B radiation (Sommaruga, 2001) are among the many issues of concern. Logging, mining, transportation development, fire suppression and grazing have left only 25% of the natural terrestrial habitat intact indirectly impacting the aquatic resources of the region via catchment impacts (Ricketts et al., 1999).

Lakes in the Sierra Nevada are typically small water bodies that may be biologically isolated. These lakes tend to be oligotrophic with small catchments and short growing seasons. The vulnerability of these ecosystems and the increasing threats to their integrity have sparked a substantial effort to increase research and conservation efforts in the Sierra Nevada. Most lakes and reservoirs in the region serve multiple purposes. A lake may be recreational, wild/scenic, and also serve as a reservoir for irrigation, drinking water supply or to maintain downstream flow. Many naturally formed lakes have been dammed for regulation of water levels. Reservoirs in the region are man-made water bodies. The overall environmental goal is to balance the ecological integrity of these systems with economic and recreational development. 3

An assessment protocol is essential for the protection and management of these resources. The US EPA-funded research project “Multilevel indicators of ecological integrity of Sierra Nevada alpine lakes” sought to develop a multi-metric assessment protocol for these fragile ecosystems (Oris, 1999). Between 1999 and 2002, many indicators were assessed including molecular biomarkers of contaminant exposure, fish community structure, population genetics, littoral benthic invertebrate assemblages, water chemistry, physical habitat, and sediment cores. While many aspects of these systems were measured, the potential impacts of human disturbance within the catchments have not yet been assessed. This practicum specifically addressed this need to expand the assessment to include landscape-scale measurements.

RESEARCH GOALS AND OBJECTIVES

The overall goal of this study was to contribute to the development of protocols for environmental assessments of lakes and reservoirs in the Sierra Nevada with a range of ecological characteristics and of human activities. More specifically, this study sought to address ecological characteristics and human activities at the landscape-scale that may be incorporated into an environmental assessment protocol to be used by agencies for management of lakes, reservoirs and their catchments in the Sierra Nevada ecoregion. Agencies that would benefit from this research include the US EPA, US Geological Service, NOAA, and various State and Regional authorities, all of which have exposure assessment and monitoring programs.

To accomplish this goal, there were three main research objectives:

1) To develop a geospatial database by:

a. acquiring readily-available, digital, spatially referenced data and

b. formatting the acquired data files into a user-friendly file format.

2) To quantify landscape-scale characteristics applicable to:

a. the morphometry of the assessment sites and catchments,

b. land cover within assessment catchments, and

c. human activities within the assessment catchments.

3) To incorporate the landscape-scale characteristics into:

a. a first-cut, multilevel index of site integrity and

b. a multivariate statistical analysis of morphometry, catchment land cover, and human activity.

It was expected that the use of readily available digital data would provide an efficient, cost-effective method to preliminarily assess the lake/reservoir and catchment condition. This would allow for prioritization of at-risk systems and would allow local, state, and federal resource managers to focus efforts in these areas. Furthermore, assessment of lakes and reservoirs of the Sierra Nevada was expected to contribute to the knowledgebase of the ecology of these systems. The similarities and differences among the lakes and reservoirs should serve to better understand and manage the lakes for their desired uses. A more thorough understanding of the relationships among ecological characteristics, anthropogenic impacts and measured response variables will be of significant importance to the future of lakes and reservoirs of the Sierra Nevada. This landscape-scale assessment was part of a comprehensive multilevel assessment of these systems, which provide a solid foundation for more focused research in the region.

Chapter 2

ASSESSMENT SITE DESCRIPTIONS

The study area for this research was limited to the catchments of 20 assessment lakes and reservoirs in the Sierra Nevada. The majority of these sites are located within the three fastest developing counties: Nevada, Placer and El Dorado. Due to its size and variability, three subsites were selected on Lake Tahoe and the 17 remaining sites were lakes and reservoirs in the surrounding area (Figure 1). Hence, these are referred to collectively as lakes or assessment sites. All assessment sites were located within the Sierra Nevada ecoregion with the exception of Castle Lake, which is located in the Klamath ecoregion of northern California. Topaz Reservoir, Upper Twin Lake and Lower Twin Lake are located on the border of the Sierra Nevada ecoregion and the Basin and Range ecoregion. The sites were selected and classified a priori (low, moderate and high) to represent a gradient of human impact based on knowledge of recreational activity and shoreline structures. The assessment sites were also intended to represent the ecological diversity of lentic ecosystems in the ecoregion. However, all assessment sites selected for this study were accessible by vehicle or within a day by foot. More remote lakes were not included in this study. General ecological characteristics of the assessment lakes are described in Table 1. Descriptions of each of the sites are provided that include information about the site’s location, accessibility, and usage.

GOL

JAC STA

BOC IND PRO SPA DON SAN TCM Lake MAR Tahoe

CAS CSD EAG TKS FAL UAN

TOP

LTW UTW

Figure 1. Assessment sites were distributed throughout the Sierra Nevada ecoregion. Castle Lake (CAS) is located in the Klamath Mountain ecoregion in northwest California. Topaz Reservoir (TOP), Upper and Lower Twin Lakes (UTW & LTW) border the Basin and Range ecoregion.

Table 1. Assessment sites (lakes and reservoirs), their respective codes and available general descriptive information. A priori human activity classification was based primarily on observed in-lake recreational activity. A priori N Latitude W Longitude Maximum Elevation Maximum Site Code Human (decimal (decimal Storage Capacity Storage Range (AF) (m) Depth (m) Activity degrees) degrees) (AF) Boca Reservoir BOC High 39.41917 120.08611 1708 40,800 4,000 – 40,000 Cascade Lake* CSD - 39.30333 120.43861 1965 Castle Lake CAS Low 41.22675 122.38458 1657 35 Donner Lake DON High 39.32261 120.27208 1808 9,500 3,500 – 9,500 100 Eagle Lake EAG Low 38.94214 120.12278 2128 25 Fallen Leaf Lake FAL Moderate 38.88392 120.06592 1943 Gold Lake GOL Moderate 39.68342 120.64703 1953 33 Independence Lake* IND - 39.43500 120.32200 2117 17,500 Jackson Meadows Reservoir* JAC - 39.50408 120.55344 1840 33 Lower Twin Lake* LTW - 38.17056 119.32889 2158 Marlette Lake MAR Low 39.17417 119.90417 2384 11 Prosser Creek Reservoir PRO Moderate 39.37944 120.14083 1750 29,800 4,000 – 29,800 33 Sand Harbor, Lake Tahoe SAN Moderate 39.20114 119.93186 1898 122,160,000 500 Spaulding Reservoir SPA Moderate 39.32789 120.34158 1527 75,100 91 Stampede Reservoir STA Moderate 39.47500 120.11472 1813 226,500 100,000 – 150,000 21 Tahoe City Marina, Lake Tahoe TCM High 39.32789 120.34158 1898 122,160,000 500 Tahoe Keys, Lake Tahoe TKS High 39.14839 119.88886 1898 122,160,000 500 Topaz Reservoir TOP Moderate 39.16903 120.13514 1526 59,500 23 Upper Angora Lake UAN Low 38.86236 120.06867 2269 29 Upper Twin Lake UTW Moderate 38.14833 119.36808 2162 32 * These lakes were added later in the study, therefore there are missing data points (e.g., these sites were not included in the a priori classification, but are considered to have moderate human activity levels).

ANGORA LAKE (UPPER)

Upper Angora Lake is the highest of the glacial cirque Angora Lakes. They are located a short, steep hike from a public parking. Upper Angora Lake is on U.S. Forest Service property and is privately owned by the Angora Lakes Resort. The resort consisted of summer rental cabins, a food stand, non-motorized boat rental and a managed beach. A trail winds around the entire lake providing access to cliffs for diving (Plate 1). Fishing is permitted, but motorized boating is not. The resort is very busy during the summer; according to the U.S. Forest Service the lake has experienced an increase in usage over the last 10-15 years (Ridley, 2005). Upper Angora Lake was classified a priori as low.

Plate 1. The sheer granite cliffs of Upper Angora Lake’s catchment.

BOCA RESERVOIR

Boca Reservoir is located in the Tahoe National Forest and is easily accessible as it is 1 mile north of Interstate 80, only 4 miles northeast of Truckee, CA. Boca Reservoir 9

is part of the Truckee Storage Project that provides irrigation to Truckee Meadows surrounding Reno and Sparks, NV and maintains flow in the Truckee River. A small private dam was built in 1920, and in 1939 the current dam was completed. Boca Reservoir is now operated by the Washoe County Water Conservation District.

The primary activities on Boca are boating and water skiing, but other activities consist of fishing, swimming, camping, and picnicking. There are many put-ins, but one main boat ramp and parking area. Boca is open for fishing year-round with ice fishing when the reservoir is frozen. Fish include kokanee salmon, rainbow, brook, and brown trout. Boca Reservoir was classified a priori as high.

CASCADE LAKE

Cascade Lake is located near Fallen Leaf Lake on the southwestern side of Lake Tahoe. It is located within the Lake Tahoe basin. The accessible portion of the lake is private property; otherwise it is a hike and still a difficult scramble to the far end of the lake. Common activities in and around the lake include fishing (Lahontan cutthroat and brown trout) and horseback riding. The Lahontan cutthroat trout are thriving in Cascade Lake; the food web is said to resemble the historical food web of Lake Tahoe (Vander Zanden et al., 2003). Cascade Lake was not included in the original 16 assessment sites and therefore does not have an a priori classification.

CASTLE LAKE

Castle Lake has been the focus of limnological research (Park et al., 2004; Elser et al., 1995; Higly et al., 2001); therefore, the information about the small lake is more detailed than other lakes in this study. Castle Lake is a small dimictic, oligomesotrophic, subalpine glacial cirque lake formed in a granite basin. The mean depth of Castle Lake is 11.4 meters (Park et al., 2004). The lake is located in northern California 12 miles southwest of Mt. Shasta. Recreational activities on Castle Lake include fishing (golden shiners, brook trout, and rainbow trout), swimming, picnicking, camping and hiking. Castle Lake was classified a priori as low.

DONNER LAKE

Donner Lake is located in the Truckee River watershed. The first dam was built in 1877, while the current dam was completed in the 1930s. Once impassable and made infamous by the misfortune of the Donner Party, Donner Pass is now very well traveled and is likely the most accessible lake in the region. A mixture of private and public land surrounds the lake. Donner Memorial State Park and Museum is located on the west end of the lake with a campground and beach. The north side of the lake is lined with 1.5 shoreline miles of public docks and a public boat ramp (Plate 2). The east end houses hotels, resorts condominiums and a private beach. The east and southern sides of the lakes are dotted with high-end real estate (1,500 full-time residents) with both developed and undeveloped lots. The development regulations around Donner Lake are less strict than those in the Lake Tahoe basin.

Boating is one of the most popular activities on Donner Lake, but a 35 speed limit is imposed. Swimming, sailing, water skiing, diving and fishing (Mackinaw, rainbow trout, German brown trout, and kokanee salmon) are also common. During the winter the water level of Donner Lake is lowered by 8-12 feet to provide a catch basin for spring runoff, thus reducing the flood risk downstream. Donner Lake was classified a priori as high.

Plate 2. Northern shore of Donner Lake.

EAGLE LAKE

Eagle Lake (Plate 3) is a small glacial cirque located about a 1 mile scenic hike from the Eagle Falls Picnic Area off Rt. 89 near Emerald Bay on the south end of Lake Tahoe. Waterfalls line the hike up to the lake. Trails surround the lake, while fishing from shore and rock climbing is available are common activities as well as backpacking on trails that continue into the backcountry above Eagle Lake. Eagle Lake was classified a priori as low.

Plate 3. Eagle Lake, surrounded by granite peaks, is located southwest of Lake Tahoe.

FALLEN LEAF LAKE

Dammed in 1934, Fallen Leaf Lake is the largest lake in the Lake Tahoe basin. Tahoe Regional Planning Agency’s boating regulation for lakes in the Tahoe region, including Fallen Leaf Lake, do not allow engines that do not meet the U.S. EPA 2006 or the California Air Resources Board (CARB) 2001 standards, including electronic fuel injected and two-stroke engines. Boating and fishing (rainbow trout, Mackinaw, brown trout) are popular activities on the lake. A marina (boat launch and boat rentals) is located on the western end. The lake has also been established as a Lahontan Cutthroat trout reintroduction site (Vander Zanden et al., 2003) and fishing within 250 ft. of the dam is prohibited.

Rental homes are also located on the western end, but access is a narrow, bumpy road. Also, from this end are the trailheads for trails leading into Desolation Wilderness. A campground is located on the east end with beach access. Fallen Leaf Lake was classified a priori as moderate.

GOLD LAKE

Gold Lake lies on the border of Tahoe National Forest and Plumas National Forest in the Lakes Basin Recreation Area (LBRA) 40 miles north of Tahoe and 75 miles northwest of Reno. It is the largest of 20 lakes in the area. Gold Lake’s dam was first built in 1858 out of Frazier Creek. The lake has a boat ramp and dock, but no motor size or speed restrictions. Fishing (Mackinaw trout, rainbow and eastern brook trout) is common, as well as hiking, backpacking, picnicking, and camping. Gold Lake was classified a priori as moderate.

INDEPENDENCE LAKE

Independence Lake is also located in the Truckee River watershed. It is relatively less accessible that other lakes of its size. There is no boat launch and no motorized watercraft allowed. Camping, hiking and fishing (brown trout, brook trout, kokanee salmon, and a catch-and-release Cutthroat trout fishery) frequent activities in and around the lake. Independence was not included in the original 16 assessment sites and therefore does not have an a priori classification.

JACKSON MEADOWS RESERVOIR

Jackson Meadows Reservoir is located 17 miles north of Truckee, California. Several campgrounds have been built around the reservoir; the Jackson Point Campground is accessible only by boat. Recreational activities include camping, fishing, swimming, boating, and a self-guided nature tour. Jackson Meadows Reservoir was not included in the original 16 assessment sites and therefore does not have an a priori classification.

LAKE TAHOE SUBSITES

Lake Tahoe is the second deepest lake in the United States and the tenth deepest in the world with a maximum depth near 500 m. Lake Tahoe is famous for its depth of clarity, reaching 33 m, due to its size and low nutrient inputs. However, a loss of clarity, decreasing at a rate of 0.3 m/year, has been an issue of concern for over two decades (Goldman, 1988). Due to the shear size and complexity of Lake Tahoe, 14 three subsites were chosen on the lake to include in the assessment: Sand Harbor, Tahoe City Marina and Tahoe Keys.

Sand Harbor

Sand Harbor was an assessment subsite located on the northeast shore of Lake Tahoe (Plate 4). The site is within the most popular of the Lake Tahoe – Nevada State Parks experiencing significant traffic for its beaches, boat launch, picnicking and group facilities. The site includes long sandy beaches, lakeside hiking trails leading to rocky coves. The rock formations around Sand Harbor are used for swimming and scuba diving. Sand Harbor was classified a priori as moderate.

Plate 4. The sandy and rocky beaches of Sand Harbor subsite, Lake Tahoe.

Tahoe City Marina

The Tahoe City Marina subsite is located on the north shore of Lake Tahoe in Tahoe City. The marina is one of the oldest on the lake offering boat docks, rentals,

sales, fuel and sport fishing charters. Also, at the marina is a three-story mall with shops and restaurants. Tahoe City Marina was classified a priori as high.

Tahoe Keys

Tahoe Keys is a 750-acre private resort community and marina on the southern shore of Lake Tahoe. Homes are located on winding canals that connect directly to Lake Tahoe. The marina is full-service and open year-round offering boat launch, storage, rentals, fuel and sport fishing charters. Tahoe Keys was classified a priori as high.

MARLETTE LAKE

Marlette Lake is located on the northeast side of Lake Tahoe (Plate 5). It is one of three lakes that make up the Marlette-Hobart Water System; the other two are Spooner Lake and Hobart Reservoir. Marlette Lake, technically a reservoir, was born when a dam was built in 1873 to help feed logs down a flume, to Carson City. The flume is now a well-traveled hiking and mountain biking trail commonly called The Flume Trail. Water from the lake was also sent to Virginia City and Gold Hill; these communities still receive water from Marlette Lake.

Popular activities in and around Marlette Lake include hiking, mountain biking, picnicking, some overnight backpacking and limited equestrian usage. The lake is surrounded by scenic trails through aspen stands. Motorized boating and fishing are not allowed on the lake as it is also used as a spawning location for Lahontan Cutthroat trout. Marlette Lake was classified a priori as low.

Plate 5. A view of Marlette Lake and a portion of the lake’s catchment.

PROSSER CREEK RESERVOIR

Prosser Creek Reservoir is located 3 miles north of Truckee, CA in the Truckee River watershed and within the Tahoe National Forest. The dam was built in 1962 as part of the Washoe Project. Prosser is accessible by a paved road, but there is a 5 mph speed limit on the lake.

Like many of the reservoirs in this region, Prosser is used for fishing and boating, with camping and hiking around the perimeter. Since year-round access to the reservoir is possible ice fishing is another recreational activity on the lake. Prosser Creek Reservoir was classified a priori as moderate.

SPAULDING RESERVOIR

Spaulding Reservoir, more commonly called Lake Spaulding or Spaulding Lake, is located just 3 miles off of Interstate 80. It is distinct from the other reservoirs since it was created in a glacially carved granite basin with steep forested shorelines. Spaulding was dammed on the upper reached of the South Yuba River in 1912 for hydraulic mining purposes. Today the reservoir is operated by the Pacific Gas &

Electric Co. and experiences extreme drawdown late in the summer when water is released (Plate 6).

Recreational activity is also prevalent on the lake: boating, fishing (brown and rainbow trout), swimming, picnicking, hiking, camping and backpacking are available in the area, but only during the summer months. Spaulding Reservoir was classified a priori as moderate.

Plate 6. Spaulding Reservoir after drawdown. Tree line indicates early season lake level.

STAMPEDE RESERVOIR

Stampede Reservoir is a large reservoir located in the Truckee River catchment on in the Tahoe National Forest (Plate 7). It was dammed in 1970. A three lane boat launch is located on the reservoir commendable fishing and boating, as well as swimming, camping and picnicking. Fishing (kokanee salmon, rainbow trout, brook trout, lake (mackinaw) trout, and brown trout) is allowed year round with ice fishing during the winter. Stampede Reservoir was classified a priori as moderate.

Plate 7. Stampede Reservoir shoreline with indications of drawdown, partially newly vegetated and partially barren shoreline.

TOPAZ RESERVOIR

Topaz Reservoir, once called Alkali Lake and more commonly called Topaz Lake, is located on the California-Nevada border on CA State Route 395. It is a large reservoir, 700 hectares, created in 1922 on the West Walker River for irrigation purposes in the Walker River Irrigation District. The maximum depth of Topaz during the winter is about 30 m, but this is decreased substantially during summer periods when water is removed for irrigation.

Topaz is popular with boaters, water skiers, and jet skiers, and fisherman, but also gamblers as there are casinos just off the shore. There are no boating restrictions on the reservoirs. Fish present in the reservoir include brown trout, rainbow trout, tiger trout, cutbow trout, largemouth bass, bullhead catfish, carp, and white fish. Picnicking, camping and RVing is also common in the vicinity. A few homes are located on the north and west sides of the reservoir. Topaz Reservoir was classified a priori as moderate.

TWIN LAKES (UPPER & LOWER)

Upper and Lower Twin Lakes are two glacial trough lakes bounded by glacial moraines and separated by a 150 ft. long stream and a small private home community. These two lakes are located just north of Yosemite National Park near Bridgeport, California on Rt. 395. Boating and fishing (brown trout, rainbow trout, and kokanee salmon) are prevalent on both lakes; however, speed on Lower Twin Lake is restricted to 5 mph and water skiing is prohibited. Upper Twin Lake is the more developed, active lake of the two with a recreational community, Mono Village, that includes a café, market, cabins, RV spaces, campground, motel rental boats, launch, marina and gift shop. Lower Twin Lake Resort is located on the shore of Lower Twin Lake and consists of housekeeping cottages, a trailer park, marina, boat launch and rentals, and a grocery store. Additional recreational facilities in the area include several hot springs and more primitive campgrounds. Lastly, trailheads for mountain biking, horseback riding and backpacking are located in Mono Village. Lower Twin was not included in the original 16 assessment sites and therefore does not have an a priori classification. Upper Twin Lake was classified a priori as moderate.

Chapter 3

DEVELOPMENT OF A GEOSPATIAL DATABASE

INTRODUCTION

The influence of the catchment on a lake’s water chemistry and ecology has long been recognized (Wetzel, 1983). However, the web of biogeochemical processes that occur between precipitation and catchment export into lakes is still being teased apart. The onset of the digital age has brought about many cost-effective tools that have assisted in the field of catchment biogeochemistry. The combination of geographic information systems (GIS) and remote sensing (RS) allows for the storage, analysis and display of large amounts of geospatial information. Higher resolution spatial and temporal data can be collected, stored, distributed and analyzed efficiently. The vast amount of available digital information and mainstream software has facilitated intricate temporal and spatial modeling to describe and predict natural and anthropogenically altered processes (Lucas and Curran, 1999; Viedma et al., 1997; Mann et al., 1999; Lathrop and Bognar, 1998; Inyan and Williams, 2001). These advances have allowed for more informed ecological and political decision making for management of lakes and their catchments.

Advances in computer technology, hardware and software, have enabled the mainstream application of geographic information systems (GIS) in many fields of study. These systems have increased the efficiency of storage, retrieval and analysis of spatially explicit data. In addition, the data types available are ever increasing and many are readily available for download.

A GIS was appropriate for this research for many reasons. The large spatial extent of this study was regional, spanning most of northern and central California. Some of the field sites were relatively difficult to access due to the mountainous terrain. Many

data types were synthesized for an integrated assessment. Lastly, it was expected that similar work would be conducted on all lakes and reservoirs of the Sierra Nevada; therefore, data collected at regular intervals that are consistent across the region is necessary to expand this research. As Soranno et al. (1999) suggest, lakes must be considered as a network, not as independent entities. By using a GIS, the spatial relationships between the assessment lakes can be examined, and eventually the analysis will be expanded to include all lakes in the ecoregion.

Many regional-scale projects rely heavily on large geospatial databases for the continued monitoring and assessment of ecosystems. Two examples include the Great Lakes GIS (http://www.glfc.org/glgis/other_pages/main.htm) and the Lake Tahoe Data Clearinghouse (http://tahoe.usgs.gov/). In addition, as part of the Sierra Nevada Ecosystem Project (SNEP), Moyle and Randall (SNEP, 1996, pg. 975) characterized 100 Sierra Nevadan catchments based on their biotic integrity incorporating metrics such as native frogs and native fishes.

This study examined a small number, 20, of the lakes and reservoirs in the Sierra Nevada. It is expected that processes similar to that undertaken in this study will be replicated on all lakes and reservoirs in the region. Data and methods were selected with this in mind. In addition, since the goal of the research was to develop monitoring protocols, the cost and efficiency of data acquisition must be considered in the context of the limitations of managers and/or monitoring crews. This would be important when considering the cost of the various remotely sensed data, preprocessing requirements, error and accuracy, ground-truthing required, and personnel/equipment required. Only readily available, inexpensive GIS and remotely sensed data were selected for analyses. A geospatial database was developed by (1) acquiring readily available digital spatially reference data and (2) formatting the acquired data files into a user-friendly file format.

METHODS

Acquisition of readily-available digital data

ESRIs ArcView 8.3, ArcINFO, and ArcGIS were used to store, analyze and display geospatial data about the assessment sites and their catchments. Data layers were acquired from three sources:

1. the United States Geological Survey (USGS) National Land Cover Dataset 1992 (http://landcover.usgs.gov/natllandcover.asp),

2. the California Spatial Information Library (CaSIL) (http://gis.ca.gov/), and

3. and the GIS Data Depot (http://data.geocomm.com/).

Data pre-processing

Each data layer was downloaded, reformatted, if necessary, and imported into the GIS software. All layers, except USGS NLCD 1992, were reprojected into NAD 1983 Universal Transverse Mercator (UTM) 11. USGS NLCD 1992 was downloaded as a TIFF, imported into ArcView 8.3, then converted into a grid. USGS NLCD 1992 was not reprojected in UTM 11. Instead, the catchment layer was re-projected to match the land cover layer for analysis. Three regions encompassing all 20 lakes and their catchments were generated. USGS NLCD 1992 was cut into the three regions and DEMs were stitched into the three regions to speed up processing.

RESULTS

The resulting data layers used for subsequent landscape-scale characteristic quantification are summarized in Table 2. Most of the layers were available from GIS Data Depot since this site provides an abundance of data with national extents. Two layers with California extent, political boundaries and hydrography DLGs (1:20,000), were retrieved from CaSIL. Lastly, USGS NLCD 1992 was downloaded directly from the publishing USGS site.

Table 2. GIS data layers incorporated into geospatial database, their sources and relevant notes. Data Layer Source Notes 7minute quandrant index GIS Data Depot State and county boundaries CaSIL Ecoregion boundaries GIS Data Depot Digital Elevation Models (DEMs) GIS Data Depot 10 m resolution Digital Line Graphs (DLGs) - Hydrology CaSIL Blue line streams and coarse polygons of lakes Digital Ortho Quarter Quads (DOQQs) GIS Data Depot USGS National Land Cover Data (1992) USGS NLCD Site 30 m resolution US Census files GIS Data Depot

DISCUSSION

A few difficulties with data availability were encountered. The border of California and Nevada runs through the center of the northern Sierra Nevada causing inconsistency in some of the available data sources. Data for California are more abundant than for Nevada. Also, there is an abundance of data for the Lake Tahoe catchment, but significantly less data of lower quality for the much of the remaining Sierra Nevada ecoregion. For these reasons national data sets were used for the analysis to maintain data consistency across the study region. Furthermore, a detailed soil layer was available for the Lake Tahoe catchment, but not for the remaining area within the Sierra Nevada. In addition, a generalized geology map was not found, but would be useful to the regional classification of Sierra Nevada lakes.

Although the USGS NLCD 1992 was available for the entire country, the temporal resolution may not be fine enough for certain assessment requirements. The time lag between the first USGS NLCD 1992 layer and the second to be released will be in the range of 10 years. If assessment needs require detection of land cover changes that occur from year-to-year another data layer would need to be substituted for the USGS NLCD 1992 layer. Otherwise, the USGS NLCD data sets provide high quality land cover data for the entire Sierra Nevada ecoregion.

Chapter 4

QUANTIFICATION OF LANDSCAPE-SCALE CHARACTERISTICS

INTRODUCTION

Limnological measures of lake and catchment morphometry, the land cover within the lake’s catchment and measures of within-catchment human activity can be useful for developing an ecological framework for lake assessment as well as estimating human impact to a lentic ecosystem. As stated earlier, the catchment’s influence on a lake’s water chemistry and ecology has long been recognized especially with regard to nutrient cycling (Wetzel, 1983: 223). However, the web of biogeochemical processes that occur between precipitation and catchment export into lakes is still being teased apart. The importance of within lake processes that depend on broad-scale measures of lake morphometry have also been long recognized (Wetzel, 1983: 17). The drive behind using these two forces to predict and manage lake health are the primary tributaries that converge at the base of research for lake management. Lake management requires both strength in knowledge of the ecological processes and associated deviations due to human activity to successfully maintain ecological integrity in the face of increasing human pressures.

The morphometry of a lake’s basin is often closely related to the lake’s productivity (Wetzel, 1983: 17). There are many processes that result in the birth of a lake; those most common in the Sierra Nevada include tectonics, volcanic activity, landslides, glacial activity and human intervention. Tectonic basins are typically deep and oligotrophic. Glacial cirque lakes are usually small and shallow (<50 m) (Wetzel, 1983: 22). The origin of many lakes is multifaceted including more than one of the abovementioned processes. For example, Lake Tahoe originated when tectonic activity caused a fault slip and then was dammed by volcanic flow (Hill, 1984: 96). Morphometrics quantified for any given lake reflect the lake’s origin. Tectonic

25 graben lakes, such as Lake Tahoe, Lake Baikal, and Lake Tanganyika, are of particular interest because of their depth and large number of endemic species (Wetzel, 1983: 17). Glacial cirque lakes are amphitheater-like basins shaped by freezing and thawing of glacial ice. They tend to be small, shallow lakes located at snow line (Wetzel, 1983: 22). Man-made reservoirs tend to be shallow and contain large areas conductive to aquatic vegetation (Wetzel, 1983: 30). Many morphometric measures (lake surface area, catchment area, lake perimeter) can be derived from maps or aerial photos.

The composition and configuration of land cover are also essential descriptors of catchment processes. The land cover composition, relative coverage of each land cover type, has been correlated to water quality measures such as stream solute export (Inyan and Williams, 2001; Meixner et al., 2000; Basnyat et al., 2000; Holloway and Dahlgren, 2001; Griffith, 2002), and sediment transport (Adams and Minor, 2002; Richards et al., 1996). For example, the contribution of methyl mercury to streams is greater from catchments with a greater proportion of forest- wetland than those with agriculture-forest or primarily agriculture (Hurley et al., 1995). The land cover configuration, the spatial orientation of land cover patches within the catchment, may also be used to predict variability in water quality parameters (Griffith, 2002). Furthermore, detailed vegetation classification can provide information regarding nutrient and hydrologic cycling. For example, France & Peters suggest forest litter can contribute 15% of an oligotrophic lake’s carbon input and 10% of phosphorus input in lakes with high catchment area: surface area ratio (1994). Research on Castle Lake showed the importance of riparian mountain alder to the lake’s nitrogen (N) input (Goldman, 1961). The methods available for land cover and vegetation classification are abundant, but regional differences will determine the most appropriate classification method for the application at hand. Most related research has been focused in the eastern United States, but more recently, western catchment biogeochemical studies have been conducted, especially in the Lake Tahoe Basin (Williams & Melack, 1997; Tarnay et al., 2001; Huff et al., 2002). As part of US EPA’s Environmental Monitoring and Assessment Program

(EMAP), an integrated assessment of aquatic resource condition and landscape characteristics is underway in the western United States (Jones et al., 2000).

One of the main objectives of the current research was to quantify landscape-scale characteristics of assessment lakes and reservoirs, and their respective catchments, in order to (1) provide an ecological framework for the assessment of Sierra Nevada lake/reservoirs and (2) to compare human activity levels.

METHODS

Landscape-scale characteristics quantified were grouped into three categories, measures of morphometry, land cover and human activity. Measured morphometry variables included lake/reservoir surface area, catchment area, lake/reservoir perimeter, mean catchment slope, and lake/reservoir surface elevation. The shoreline development index and catchment area: surface area were calculated from the above measurements. In addition, relative percent areas of land cover classes were determined for each of the catchments. Lastly, measures of human activity within the catchments were quantified. These included percent urban land use (derived from two sources), weighted road density, mean population density, and mean housing density.

Morphometry

Morphometric variables quantified included lake/reservoir surface elevation, lake/reservoir surface area, catchment area, lake/reservoir perimeter, and mean catchment slope. These variables were generated from two data sources, digital elevation models (DEMs) and digital ortho quarter quads (DOQQs). The shoreline development index and catchment area: surface area were calculated from the above measurements.

Lake Surface Elevation

Lakes at higher elevation are considered to be more sensitive than those at lower elevation due to the reduced growing season and lower productivity. The surface elevation (m) was determined from locating the lake’s surface on the DEMs.

Lake Surface Area

Lake surface area from the hydrography digital line graphs (DLGs) were too coarse to capture the shoreline detail desired, therefore lake surface area polygons were manually digitized from DOQQs. The digitization was performed on each of the lakes using the same viewing scale (1:5000). The resulting files were not reprojected to match the other data files, but were created only to quantify lake surface area. However, the polygons were manually moved to their correct position for visualization purposes.

Catchment Area

The area of each lake’s catchment was determined by a series of steps performed using the DEMs. Catchments were first estimated manually from topographic maps. Euclidean sub-catchments of appropriate sizes, those smaller than the catchments, were calculated using ArcView 8.2 Spatial Analyst. Sub-catchments were selected and compared to and used to refine the manually-derived catchment for each of the assessment sites. The sub-catchments were combined to yield one catchment polygon for each of the assessment catchments, the area was determined and catchments were used in subsequent analyses.

Catchment Area: Lake Surface Area

The ratio of a lake’s catchment size to its surface area is a broad-scale, unitless metric used to describe the morphometry of the lake ecosystem. The greater the ratio (larger catchment, smaller lake), the more productive the lake is expected to be. In addition, with regard to atmospheric deposition of pollutants, such as nitrogen,

smaller ratios can indicate an increased importance of N atmospheric deposition relative to catchment sources of N. Lake Tahoe is an extreme example of a small catchment area: lake surface area ratio.

Shoreline Development

Shoreline development (DL) is a descriptor of the potential for the littoral community’s relative importance to the entire lake metabolism (Wetzel, 1983). Contribution of the littoral zone to the lake’s productivity will differ from lake to lake, depending on other factors, including the morphometry of the lake basin and climatic variables. However, the length of shoreline relative to the area of the lake’s surface is a gross measure of littoral importance. A higher littoral importance suggests a more productive system.

Shoreline development describes the ratio of lake perimeter, shoreline length, to lake surface area. A perfect circle’s shoreline development is 1; the further a lake deviates from a circle the greater the shoreline development (Figure 2). Shoreline development is calculated as:

L DL = 2 πA0 where L = shoreline length and A = lake surface area.

(A) (B) (C)

Figure 2. Three examples of lake shape and shoreline development (DL). (A) DL = 1, no shoreline

development; (B) low DL, and (C) high DL.

Shoreline development for the three Lake Tahoe subsites was calculated by using the expected length of the site’s shoreline, 10 m, as the denominator and the actual shoreline length, L.

Mean Catchment Slope

Catchments with lower mean slopes are expected to be prone to more commercial and residential development. They are also expected to have more soil development and potentially contribute to the productivity of the lake. Catchments with higher mean slopes are more difficult to develop, will have less vegetative cover and less soil development. To quantify slope, DEMs were cut using the catchments of each assessment lake/reservoir. Slope grids were generated for each of the assessment catchments using ArcView’s Spatial Analyst; means were calculated for each of the catchments to summarize the slope profile.

Catchment Land Cover

Relative percent land cover was quantified for each lake’s catchment from USGS National Land Cover Data (NLCD) from 1992. It was generated by an unsupervised classification of Landsat TM (Thematic Mapper) imagery from 1992 with ancillary data sources (topography, census, agricultural statistics, soil characteristics, other land cover maps, and wetlands data). The overall accuracy of this product is approximately 70% (http://landcover.usgs.gov/accuracy/index.asp#results). The development of an updated data set is underway, but completion is not anticipated until 2006.

USGS NLCD 1992 is a raster, or grid, representation of the land use and land cover on the surface of the earth. The grid consists of 30 meter X 30 meter squares. A number is associated with each square (pixel), which corresponds to a particular land cover class. The grid is displayed as an image for illustration and visual analysis. Since each square is 30 m X 30 m the total and relative proportions of land cover types within each catchment can be calculated. For example, if there are 100 pixels of deciduous forest within a catchment, 30 X 30 = 900 (one pixel represents 900m2 of 30

deciduous forest), 900 m2 X 100 pixels = 90,000 m2 of deciduous forest, 0.09 square km2 or 22.24 acres. USGS NLCD was cut using the assessment lake/reservoir catchments. Summaries of total area for each land cover class were generated. Since the catchments are variable in size among assessment sites, relative land cover area was calculated.

Human Activity

Measures of human activity within the catchments were quantified. These included percent urban land use (from both USGS NLCD 1992 and US Census 2000 data), road density, mean population density, and mean housing density.

Percent Urban Land Cover within Catchments

The percent of human activity with the catchments was quantified in two ways. First, human-related land cover classes from USGS NLCD 1992 were combined to obtain a total percent of human activity. The land cover classes that were included in this measure were low intensity residential, commercial/industrial/transportation, quarries/strip mines/gravel pits, and pasture/hay. Although the grasslands/herbaceous land cover class included public parks and golf courses, it was not incorporated into the human activity measure to avoid overestimation. Secondly, U.S. Census Bureau census blocks were classified as “urban” or “rural” in the acquired data layer. The percent of “urban” land cover was determined for each of the catchments.

Weighted Road Density

The density of roads is indicative of the amount of development, accessibility and degree of human activity within a catchment. Weighted road density was calculated for the assessment catchments using the 2000 Tiger road layer available from the U.S. Census Bureau. Roads were weighted higher the closer they were located to the lakeshore. Buffers were used to determine appropriate weights.

Population Density and Housing Density

One of the most direct ways to measure human impact is to quantify the population density within a given area. One benefit to using this information is that it is collected on a regular basis and there is reliable historical data. Human population density (people/mi2) and housing unit density (houses/mi2) were quantified using U.S. Census data from 2000. Polygons of census blocks and the corresponding census data were acquired. When blocks were cut along catchment boundaries the proportion of original block was used to calculate the number of residents and housing units in the remaining proportion of the block.

RESULTS

Morphometry

The morphometry of the assessment sites and catchments revealed extreme differences between some of the assessment sites. The results from quantification of morphometric variables are presented in Table 3. Upper Angora Lake and Topaz Reservoir were the most different of the sites. Eagle Lake and Upper Angora Lake are small, high elevation systems, while Topaz Reservoir is a large reservoir located at a low elevation. Castle Lake, while small like Eagle Lake and Upper Angora Lake, is positioned at a much lower elevation. Furthermore, although all three assessment sites are small, Upper Angora Lake and Castle Lake have small catchments while Eagle Lake has a very large catchment relative to the lake’s surface area.

Table 3. Morphometrics quantified from a geospatial database for the Sierra Nevada assessment sites. ) L ) 2 ) 2 (m) Elevation Surface Surface Area (km Surface Perimeter (km) Catchment Area (km Mean Catchment Slope (degrees) Mean Catchment Catchment Area: Surface Area Area: Surface Catchment Shoreline Development (D BOC 1708 2.43 14.71 446 184 2.66 37.5 CSD 1965 0.86 4.12 11.7 13.6 1.25 33.5 CAS 1657 0.2 2.11 1.4 7.00 1.33 30 DON 1808 3.28 10.75 31.6 9.63 1.67 31.5 EAG 2128 0.07 1.13 12.9 184 1.21 33.5 FAL 1943 5.67 12.1 52.1 9.19 1.43 35.5 GOL 1953 2 8.4 9.84 4.92 1.68 30.5 IND 2117 2.77 9.62 19.8 7.15 1.63 30.5 JAC 1840 4.03 17.58 96.3 23.9 2.47 33.5 LTW 2158 1.64 6.44 101 61.6 1.42 39.5 MAR 2384 1.57 7.47 7.32 4.66 1.68 25.5 PRO 1750 1.24 10.18 130 105 2.58 35.5 SAN 1898 499 115 966 1.94 1.42 36.5 SPA 1527 2.44 15.75 307 126 2.85 35.1 STA 1813 11.73 36.8 352 30.0 3.03 35 TCM 1898 499 115 966 1.94 1.04 36.5 TKS 1898 499 115 966 1.94 20.30 36.5 TOP 1526 7 13.85 1060 151 1.48 40.5 UAN 2269 0.05 1.05 0.86 17.2 1.32 26.5 UTW 2162 1.22 6.78 80.3 65.8 1.73 39.5

The surface elevation of the assessment sites ranged from 1526 to 2384 m. Lakes above 2000 m in elevation include Marlette Lake, Upper Angora Lake, Upper and Lower Twin Lakes, Eagle Lake and Independence Lake, in order from highest to lowest. The lowest elevation lakes were Boca Reservoir, Castle Lake, Spaulding Reservoir and Topaz Reservoir, in order of decreasing elevation. The surface areas of the lakes ranged greatly between 0.05 to 499 km2. Upper Angora Lake is the smallest of the assessment sites. Cascade Lake, Castle Lake, Eagle Lake are also lakes with surface areas less than 1 km2. Sites with the largest surface areas include the Lake Tahoe subsites (499 km2) since these measures are for the entire lake, while

the next largest is Stampede Reservoir with a surface area of 11.73 km2, 40 times smaller than that of Lake Tahoe. Topaz Reservoir is close behind at 7 km2 followed by Fallen Leaf Lake at 5.67 km2. To synthesize surface elevation and surface area, the two smallest, highest lakes are Eagle Lake and Upper Angora Lake, while the largest, lowest site is Topaz Reservoir.

As with the surface areas, the catchment areas also ranged greatly from 0.86 to 1060 km2. Upper Angora Lake (0.86 km2) and Castle Lake (1.4 km2) are at the small end of the spectrum while Topaz Reservoir (1,060 km2) and Boca Reservoir (446 km2) are at the large end. The mean catchment slope measurements ranged from approximately 25 to 40 degrees. Marlette Lake and Upper Angora Lake catchments were the flattest, 25.5 and 26.5 degrees, respectively. Upper and Lower Twin Lakes and Topaz Reservoir were the steepest, with mean slopes of 39.5 and 40.5 degrees, respectively. Again, Upper Angora Lake and Topaz Reservoir are found at opposite extremes of the gradient.

The two morphological metrics calculated from measured variables were catchment area: lake area and shoreline development. Lake Tahoe’s catchment area is only twice that of the lake’s surface area, a ratio of 1.94. Marlette Lake and Gold Lake have catchments that are just less than 5 times the size of the lake’s surface. Boca Reservoir, Eagle Lake and Topaz Reservoir have catchments that are over 150 times larger the surface of the lake. The shoreline development of the assessment lakes varied from 1.21 to 20.3. Eagle Lake, Cascade Lake and Upper Angora Lake had the lowest shoreline development while Spaulding Reservoir, Stampede Reservoir, and Tahoe Keys had the highest shoreline development. Tahoe Keys shoreline development (20.3) was nearly 7 times greater than Stampede Reservoir.

USGS National Land Cover Data 1992

The most common land cover types were evergreen forest, shrubland, and grassland/herbaceous, which were present in varying degrees among the catchments. For a complete description of all land cover types and their relative percentages in

each of the catchments see Table 4. A few land cover trends are apparent with the common land cover classes. Sites north of Lake Tahoe (CAS, GOL, JAC, STA, IND, BOC, SPA, DON, TCM, SAN, MAR, PRO) had significantly more evergreen than sites south of Lake Tahoe (EAG, CAS, FAL, TKS, UAN, TOP, UTW, LTW) (P<0.001). Shrubland and grasslands/herbaceous land covers were most abundant in lakes south of Lake Tahoe (DON, EAG, LTW, UTW, UAN, TOP). Bare rock/sand/clay was found primarily in high elevation assessment sites (EAG, IND, MAR, UAN, LTW, UTW). Deciduous forests comprised no more than 2.7% of any of the 20 catchments. Marlette Lake and Upper Angora Lake had the most deciduous forest with 1.97% and 2.70%, respectively.

The less common land cover types were often present in only a subset of the catchments. Wetlands occur only in Tahoe Keys, Boca Reservoir, Jackson Meadows Reservoir, Stampede Reservoir and Topaz Reservoir catchments. The catchment with the most wetland was Tahoe Keys. Wetlands did not correspond with low slope catchments; instead, the catchments with wetlands had the highest slopes. Although 13 catchments had detectable quantities of perennial ice and snow, only Eagle Lake and Fallen Leaf Lake had >1% of this land cover class. All catchments contained a detectable proportion of open water; the percent cover ranged from 0.9% in Topaz Reservoir’s catchment to 24.11% in Gold Lake’s catchment.

Table 4. Percent land cover within assessment catchments derived from USGS National Land Cover Data 1992. eous Wetlands and ergent Herbac ergreen Forest v m Open Water Perennial Ice/Snow Bare Rock/Sand/Clay Transitional Deciduous Forest E Mixed Forest Shrubl Grasslands/Herbaceous Pasture/Hay Woody Wetlands E Low Intensity Residential Commercial/Industrial/Transportation Quarries/Strip Mines/Gravel Pits Urban and recreational grasses BOC 3.21 0.04 0.13 0.06 0.84 68.40 1.83 18.69 6.68 0.00 0.01 0.10 0.00 0.00 0.06 0.00 CSD 8.70 0.91 3.28 0.00 0.53 42.65 1.72 35.25 6.95 0.00 0.00 0.00 0.00 0.00 0.00 0.00 CAS 14.29 0.06 5.24 0.00 0.00 56.82 4.40 5.17 14.03 0.00 0.00 0.00 0.00 0.00 0.00 0.00 DON 10.55 0.00 0.90 0.00 1.45 63.16 4.39 13.05 2.26 0.00 0.00 0.00 1.86 2.38 0.00 0.00 EAG 5.21 2.47 3.69 0.00 0.50 37.97 0.74 44.10 5.31 0.00 0.00 0.00 0.00 0.00 0.00 0.00 FAL 16.89 1.77 4.68 0.00 0.65 36.72 1.02 33.23 5.03 0.00 0.00 0.00 0.01 0.00 0.00 0.00 GOL 24.11 0.00 0.37 0.00 0.19 40.88 1.55 30.73 2.18 0.00 0.00 0.00 0.00 0.00 0.00 0.00 IND 13.70 0.13 1.98 0.00 0.75 61.38 3.03 13.35 5.68 0.00 0.00 0.00 0.00 0.00 0.00 0.00 JAC 4.12 0.00 0.49 0.13 1.48 74.97 2.97 12.00 3.65 0.00 0.02 0.16 0.00 0.00 0.13 0.00 LTW 3.37 0.13 14.67 0.00 0.94 23.07 0.93 43.86 13.00 0.00 0.00 0.00 0.02 0.00 0.00 0.00 MAR 20.74 0.00 0.21 0.00 1.97 48.52 1.71 17.01 9.84 0.00 0.00 0.00 0.00 0.00 0.00 0.00 PRO 1.25 0.12 0.69 0.00 1.10 65.68 4.02 19.30 6.50 0.00 0.00 0.00 1.32 0.02 0.00 0.00 SAN 1.11 0.00 0.50 0.00 0.22 84.78 0.33 11.08 1.98 0.00 0.00 0.00 0.00 0.00 0.00 0.00 SPA 2.91 0.02 1.86 0.00 1.56 68.06 2.90 18.92 3.08 0.00 0.00 0.00 0.17 0.51 0.00 0.00 STA 3.17 0.05 0.15 0.08 0.74 69.08 2.14 16.98 7.47 0.00 0.01 0.13 0.00 0.00 0.08 0.00 TCM 0.14 0.00 0.02 0.00 0.47 88.69 1.25 3.12 0.38 0.00 0.00 0.00 4.88 0.53 0.00 0.53 TKS 0.05 0.00 0.46 0.00 0.49 62.39 0.39 6.42 5.62 0.00 0.25 2.70 19.29 1.96 0.00 0.00 TOP 0.90 0.03 2.82 0.00 1.12 29.25 0.98 47.10 12.39 5.11 0.01 0.14 0.12 0.06 0.00 0.00 UAN 6.02 0.21 4.98 0.00 2.70 27.10 3.12 29.60 26.27 0.00 0.00 0.00 0.00 0.00 0.00 0.00 UTW 2.15 0.16 18.18 0.00 1.07 22.21 1.06 41.53 13.63 0.00 0.00 0.00 0.01 0.00 0.00 0.00

Human Activity

Human activity in the assessment catchments was quantified with the percent cover of human-related USGS NLCD, the percent urban as classified by the U.S. Census Bureau, weighted road density, mean population density and mean housing density. These data are summarized in Tables 4 and 5. Overall, sites with the most human activity within their catchments included Tahoe Keys, Tahoe City Marina, and Donner Lake. The sites with the least human activity included Eagle Lake, Castle Lake, Independence Lake and Sand Harbor. The only activity in the catchments of Castle Lake, Marlette and Sand Harbor was minimal road density.

Over half of the catchments contained human-related USGS NLCD (Table 4). Those that had greater than 1% included Tahoe Keys (21.25%), Tahoe City Marina (5.94%), Topaz Reservoir (5.29%), Donner Lake (4.24%), and Prosser Creek Reservoir (1.34%). With regard to human-related cover types, Topaz Reservoir was the only catchment with the pasture/hay land cover class. Tahoe Keys, Tahoe City Marina, Donner Lake, and Prosser Creek Reservoir catchments contained more than 1% low intensity residential while five other catchments had less than 1%. All but six catchments did not have any commercial/industrial/transportation land cover; Donner Lake was the highest for this class at 2.38%, Tahoe Keys had 1.96%, while Spaulding Reservoir, Prosser Creek Reservoir and Topaz Reservoir had less than 1%. Lastly, the catchments of Boca Reservoir, Jackson Meadows Reservoir and Stampede Reservoir had negligible area of quarries/strip mines/gravel pits, all around 0.1%.

Donner did not stand out morphometrically or with regard to USGS NLCD, but was ranked very high for human activity. This was also the case for Tahoe City Marina and Tahoe Keys. Percent urban land from the 2000 U.S. Census data showed that the two Lake Tahoe subsites ranked in the three catchments with the highest human activity (Table 5). Tahoe Keys had 40.8% urban, Donner Lake had 18.9% urban and Tahoe City Marina had 16.7% urban land. Similarly, Tahoe Keys, Donner Lake and Tahoe City Marina ranked as the top three for weighted road density with

37 densities of 939, 818, and 709 m/acre, respectively. Mean population and housing density results showed that the catchments of Castle Lake, Jackson Meadows Reservoir, Marlette Lake, and Sand Harbor did not have any residents nor did they contain houses. Tahoe Keys had the densest population (1226 people/mi2) and the highest housing density (770 houses/ mi2). Also, worthy of mention are Tahoe City Marina and Donner Lake. Tahoe City Marina’s catchment had a mean population density of 201 and a housing density of 191 houses/mi2, while Donner Lake’s catchment had a population density of 83 people/mi2 and contains 124 houses/mi2.

Table 5. Human activity measurements quantified from a geospatial database for Sierra Nevada assessment sites. ) 2 ) 2

Mean Housing Density (houses/mi % Human Land Use (NLCD 1992) % Urban Land Use (US Census 2002) Weighted Road Density (m/acre) Mean Population Density (people/mi BOC 0.06 0.00 - 0.62 0.42 CSD 0 0.00 - 0.21 6.54 CAS 0 0.00 15.33 0.00 0.00 DON 4.24 18.89 818.50 83.30 123.57 EAG 0 0.00 0.00 0.00 4.44 FAL 0.01 0.00 249.35 6.97 19.37 GOL 0 0.00 198.57 0.10 0.24 IND 0 0.00 - 0.00 0.16 JAC 0.13 0.00 287.32 0.00 0.00 LTW 0.02 0.00 - 0.75 4.35 MAR 0 - 128.40 0.00 0.00 PRO 1.34 1.43 392.87 55.60 51.35 SAN 0 - 49.14 0.00 0.00 SPA 0.68 0.00 107.61 2.24 5.40 STA 0.08 0.00 251.41 0.11 0.11 TCM 5.94 16.36 709.65 201.24 191.73 TKS 21.25 40.79 939.79 1226.82 770.09 TOP 5.29 0.00 230.58 - - UAN 0 0.00 0.00 0.98 19.78 UTW 0.01 0.00 364.15 0.44 3.43

Several major conclusions can be drawn from site morphometric, land cover and human activity variable quantification. The morphometry of the assessment sites and catchments revealed extreme differences between some of the assessment sites. Upper Angora Lake and Topaz Reservoir were the most dissimilar of the sites. The most common USGS NLCD land cover types within the assessment site catchments during the early 1990’s were evergreen forest, shrubland, and grassland/herbaceous. Sites north of Lake Tahoe had significantly more evergreen forest than sites south of Lake Tahoe. Catchments south of Lake Tahoe contained significantly more

shrubland and grasslands/herbaceous land cover than those sites north of Lake Tahoe. Bare rock/sand/clay land cover was found primarily in high-elevation catchments. Overall, the sites with the most human activity within their catchments included Tahoe Keys, Tahoe City Marina and Donner Lake. The catchments with the lowest human activity included Eagle Lake, Castle Lake and Sand Harbor.

DISCUSSION

Morphometry

Measures of morphometry showed the extreme variability in the 20 assessment sites although the sites are distributed within the central Sierra Nevada ecoregion with the exception of Castle Lake. The assessment sites are located within montane and subalpine ecosystems on both the eastern and western slopes of the range. Smaller lakes tend to be located at high elevations (i.e., Upper Angora Lake and Eagle Lake) while larger lakes are found at moderate and lower elevations. This is likely because the lakes at higher elevations are small glacial cirques or tarns resulting from glacial processes, whereas the larger lakes are either glacial troughs from receded glaciers and their respective moraines or man-made reservoirs.

Catchment sizes of the assessment sites also varied greatly with respect to lake surface area. It is well known that Lake Tahoe is unique because of its unusually small catchment area: surface area ratio (1.94). This property results in Lake Tahoe receiving relatively higher amounts of input from atmospheric sources when compared to catchment sources (Tarnay et al., 2001, Zhang et al., 2002), as well as a long residence time of 650 years (Jassby et al., 2003). Most assessment sites had moderate ratios, while Eagle Lake and Topaz Reservoir had extremely large catchments relative to their surface areas. The two systems may receive more nutrients than lakes of similar sizes with smaller catchments. That being said, nutrient inputs from catchments also depend greatly on other catchment characteristics such as land cover, slope, and human activity.

The mean slope of the catchments revealed the differences in elevational profile between assessment sites in the north of the study region, north of Lake Tahoe, and the assessment sites in the south of the study region. The topography of the region surrounding Lake Tahoe is moderately steep with granite cliffs near Lake Tahoe and less steep volcanic deposition north of the lake. South of Lake Tahoe, the terrain is dominated by granite cliffs that drop suddenly to the flat Great Basin ecoregion in the east. The assessment catchments in the north were found to be flatter than the catchments in the south. Implications for this variability might be differences in productivity due to more soil development in flatter catchments, thus more nutrient input to the lake, as compared to steeper catchments with little soil development, more bare rock and ultimately nutrient inputs closer to that of precipitation.

Also, with respect to nutrient inputs and the productivity of lakes, the measures of shoreline development showed that small, high elevation lakes, Eagle Lake and Upper Angora Lake, have very low shoreline development. This is also an indication that they are glacial cirque lakes, as these tend to be very circular in shape. Shoreline development can be used to estimate the importance of littoral zone, the more important the littoral zone the higher the expected productivity of the lake. However, given these 20 assessment sites, the lakes with the lower shoreline development are also lakes that are very small and shallow. Depth is a more important factor influencing a lake’s ecological processes and trophic status. The sites with highest shoreline development were two of the reservoirs, Spaulding and Stampede, and the marina community of Tahoe Keys. Reservoirs tend to have high shoreline development because these lentic water bodies were dammed in a once lotic-eroded landscape in which the reservoirs fill in stream channels and result in finger-like projections from the dam. Tahoe Keys is an extreme example of high shoreline development. Once a wetland, Tahoe Keys was channelized into a marina community of shallow channels connected directly to Lake Tahoe (Plate 8).

Plate 8. An aerial view of Tahoe Keys and its high shoreline development.

With regard to measurements of lake surface area, a resolution finer than 30 m was needed, which was possible using aerial photography (DOQQs). However, the availability of DOQQs is limited and they are not acquired at regular intervals. Although reservoir levels are monitored on a regular basis, lakes are not, therefore, another source of this information would be very useful for future work on Sierra Nevada lakes. On a related note, for future analysis of a significant number of catchments, it is recommended that a script be used to determine catchment polygons from the lake polygons. This was first attempted, but errors in processing caused the script to become more time consuming than running the steps individually and manually selecting the polygons that should be included in each catchment.

USGS NLCD

USGS NLCD 1992 within each of the catchments suggest major geographic and elevational patterns among the assessment sites. The difference in land cover between lakes north of Lake Tahoe and lakes south of Lake Tahoe suggests a strong north to south ecological gradient as would be expected in such a large north to south trending mountain range. However, the sites are not distributed across the entire Sierra Nevada, but are centrally located within the ecoregion. This suggests either strong ecological differences between the north and south of the assessment range, due to factors such as geology, or it supports a strong north to south climatic gradient that would require further work by expanding the assessment region to the extreme 42

ends of the region. Either possibility is plausible, as it is known that the geology north of Lake Tahoe is quite different than that south of Lake Tahoe. The northern end of the region is flatter and contains large areas of volcanic substrate while the southern end is steeper and is dominated more by glaciated granite.

Furthermore, the wetlands were unexpectedly located in steeper catchments, which can be explained by the variation in topography within the catchments that is not captured when slopes are averaged. Although Topaz Reservoir’s catchment had the highest mean slope, its catchment contains areas of sheer cliffs (near 90 degree slopes) and areas of flat, irrigated agriculture (near 0 degree slope). To account for the variability, standard deviations or slope profiles could be used to represent the catchments.

Human Activity

The sites that were ecologically distinct were not the same sites that stood out with respect to human activity. Most sites tended to have moderate to low human activity in their catchments while activity within the catchments of Tahoe Keys, Tahoe City Marina and Donner Lake had human activity several times greater than the other sites. These three sites are extremely accessible to many visitors and each also supported permanent residents.

Although measures of road density, housing density and population density are related, comparison among human activity measurements suggests road density is an appropriate measure to compare activity that may otherwise not be detected with housing density or population density. Also, while population density provides a measure of permanent residents or homeowners, housing density estimates the transient population of summer renters.

Comparison of catchment human activity to a priori human activity classification

For most sites, the quantified human activities closely matched the a priori classification; however, there are a few exceptions to this pattern. Tahoe Keys,

Tahoe City Marina and Donner Lake were all classified as high impact a priori and human activity within their catchments was found to be the highest of all the assessment sites. Upper Angora, Castle Lake and Eagle Lake were classified a priori as low and quantification of catchment human activities were supportive. Most other sites, those classified a priori and those not classified a priori, fall somewhere in between the two extremes as moderate. The exceptions to this pattern include Boca Reservoir, Sand Harbor, Topaz Reservoir and Marlette Lake. Boca Reservoir was classified as high impact a priori, but catchment human activity does not support this extreme. Sand Harbor was classified as moderate a priori, but catchment activity would be considered low. Topaz Reservoir was previously thought to be moderate in human activity, but it could be argued that this reservoir should be classified as high. Lastly, a priori classification of Marlette Lake was low, but catchment activity, specifically road density, could qualify a moderate ranking.

In conclusion, measures of morphometry showed the extreme variability in the 20 assessment sites. Morphometric measurements could be used to estimate lake type and can be used to develop an ecological framework for site assessment. Since the landscape is heterogeneous in the Sierra Nevada ecoregion, the combination of several metrics is recommended to encapsulate the variability of morphometry. USGS NLCD 1992 data suggest geographic and elevation patterns among the assessment sites. Patterns of human activity indicate three sites with severe catchment human activity (Tahoe Keys, Tahoe City Marina and Donner Lake) and several sites with much lower activity. Finally, for most sites, catchment human activity closely matched the a priori classification, with a few exceptions.

Chapter 5

APPLICATION OF LANDSCAPE-SCALE CHARACTERISTICS

The application of the quantified landscape-scale characteristics involved (1) their incorporation into a first-cut, multilevel index of site integrity and (2) the multivariate statistical comparison of morphometry, land cover and human activity within site catchments.

INCORPORATION OF LANDSCAPE-SCALE VARIABLES INTO A MULTILEVEL INDEX OF ECOLOGICAL INTEGRITY

The first application of the quantified landscape-scale variables was a collaborative project conducted by incorporating measures of catchment morphometry and human activity into an index of site ecological integrity. This work was presented via poster at the 2002 Annual Society of Environmental Toxicology and Chemistry Meeting in Salt Lake City, UT (Smith, et al., 2002). This was completed in order to begin to summarize the multilevel dataset that had been collected over a period of three years, from 1999 to 2002, the landscape-scale variables being only a portion of the dataset’s entirety.

Five variable groups were included in the index: water chemistry, shoreline habitat, molecular biomarkers, human impact and lake/watershed morphometry. The human activity measurements, as described in earlier chapters, were included in the human impact variable group along with human activity measured in the field. Human activity measured in the field included number of human structures along the shoreline and in-lake recreational activity. Morphometric variables as described in earlier chapters were included in the lake/catchment morphometry variable group.

Principal components analysis (PCA) is a multivariate statistical procedure commonly used for data exploration and data reduction. PCA was used to eliminate variables

from each group that had little variation among lakes, that were co-linear, or that were redundant or extraneous. The remaining variables are presented in Table 6. Values for the remaining variables were ranked from lowest to highest, 1-16, in the direction of presumed ecological integrity. For example, the lake with the lowest value for % low intensity residential would receive a rank of 16, while the highest would receive a rank of 1.

Table 6. Variable groups and variables remaining after PCA reduction that were consolidated into the index of ecological integrity. Variable Group Variable

Water Chemistry NH4 Soluble Reactive Phosphorous Barium Dissolved Oxygen Secchi Depth

Shoreline Habitat Fish Structure Canopy Shoreline Vegetation

Molecular Biomarkers CYP1A1 (gill) Metallothinein (liver) MXR (liver) Activin (gill)

Human Impact Riparian Human Structures Observed In-lake Recreation % Low Intensity Residential (USGS NLCD 1992)

Lake/Catchment Morphology Shoreline Development Catchment Area: Surface Area

Ranks were consolidated within variable groups to generate a group rank for each lake within each variable group. In other words, lakes were ranked from lowest to highest in each of the variable groups by summing the variable ranks, then repeating the ranking procedure. A lake with the highest integrity for fish structure, canopy, and shoreline vegetation would be ranked 16 in the shoreline habitat variable group. The index of ecological integrity was determined by taking the average of the five group ranks for each lake. Figure 3 illustrates the index of ecological integrity.

Figure 3. Final index of ecological integrity for 16 of the 20 assessment sites. Topaz Reservoir (TO), Prosser Creek Reservoir (PC), Tahoe Keys (TK), Jackson Meadows Reservoirs (JM), Spaulding Reservoir (SP), Tahoe City Marina (TC), Donner Lake (DO), Upper Angora Lake (UA), Upper Twin Lake (TW), Stampede Reservoir (ST), Castle Lake (CA), Sand Harbor (SH), Gold Lake (GO), Marlette Lake (MA), Fallen Leaf Lake (FL), Eagle Lake (EA). Lake codes are colored according to their a priori human activity classification where red = high, green = moderate, and blue = low.

The most obvious trend apparent was the segregation of lakes classified high and low a priori. Those sites that had high human activity ranked in the lower half of the index, while those that were classified as having low human activity a priori ranked in the upper half of the index. The a priori moderately ranked lakes were spread out evenly across the index of ecological integrity. Topaz Reservoir ranked the lowest while Eagle Lake ranked the highest. This was consistent when compared with the catchment human activity levels alone. However, Upper Angora Lake and Donner Lake were positioned adjacent to one another with moderate ecological integrity. This was inconsistent when compared to the result from catchment human activity alone. Also, Castle Lake had the highest standard deviation among group ranks, which may be related to its geographic distance from the other 15 lakes.

Although landscape-scale characteristics derived from digital data can be a cost- effective source of information about ecosystems, these variables combined with variables from multiple levels of ecological organization can reveal a very different representation of ecosystem integrity. For example, while for majority of the catchment characteristics, Donner Lake and Upper Angora Lake were found at opposing ends of the gradients, these two lakes are located next to one another mid- gradient when in-lake measurements are included in the multi-level index of ecological integrity.

MULTIVARIATE STATISTICAL ANALYSIS OF MORPHOMETRY, LAND COVER, AND HUMAN ACTIVITY

The second application of the quantified landscape-scale variables was conducted to elucidate the most important morphological, catchment land cover, and human activity variables for describing the variation among the original 16 assessment sites. A multivariate statistical approach was used.

PCA was used to reduce and compare the sites according to their morphology, catchment land cover and human activity. Land cover variables included percent land cover from USGS NLCD 1992 from non-human related classes. Included in human activity were those variables discussed in previous chapters as well as a combined variable of riparian structure and in-lake recreational activity. Important variables were those that remained after variables had been removed iteratively until the first principal component of the remaining variables explained over 75% of the variation. This was conducted on each of the three categories of variables. The tables of remaining variables were then transposed and PCA was applied again, but this time in a way that the variables within each of the three categories were combined into one value for each of the lakes (i.e., the values comprised the first eigenvector of the three categories). These values were then used to compare the relationships among lakes within each of the variable categories. Lakes that are more similar will be closer along the vector while dissimilar lakes will be farther apart. Eigenvectors were rescaled from to range from 0-10 for ease of comparison (Table 7).

Important morphometry variables included catchment area (m2), mean slope (degrees), lake surface area (km2), and lake perimeter (km), which explained 80.8% of the morphological variation among assessment sites. Important USGS NLCD 1992 land cover classes included bare rock/sand/clay, evergreen forest, and shrubland. These explained 77.5% of the variation among catchment land cover of the assessment sites. Finally, important human activity variables included weighted road density (m/acre), mean population density (people/mi2), mean housing density (houses/mi2), and % low intensity residential, which explained 90.2% of the human activity variation among assessment sites.

Table 7. Multivariate relationships among lakes within morphological, catchment land cover, and human activity categories. Lakes are ranked in order of similarity; similar values indicate lakes are similar within the category. (a) Morphometry (b) USGS NLCD 1992 (c) Human Activity CAS 0.00 UTW 0.00 UAN 0.00 UAN 0.03 TOP 4.73 EAG 0.14 MAR 0.99 EAG 6.99 TKS 5.35 GOL 1.39 UAN 7.34 TCM 9.77 EAG 3.02 FAL 8.53 DON 9.96 DON 7.08 CAS 9.14 PRO 9.98 FAL 8.82 GOL 9.21 FAL 9.99 TCM 9.29 TCM 9.27 SPA 10.00 TKS 9.30 TKS 9.48 TOP 10.00 SAN 9.31 SAN 9.57 UTW 10.00 UTW 9.41 JAC 9.65 CAS 10.00 JAC 9.81 DON 9.75 GOL 10.00 PRO 9.91 STA 9.86 JAC 10.00 STA 9.97 SPA 9.89 MAR 10.00 TOP 9.99 PRO 9.93 SAN 10.00 SPA 10.00 MAR 10.00 STA 10.00

Using PCA for variable reduction and consolidation revealed several trends. Morphological characteristics of lakes/reservoirs and their catchments nearly fall into groups that can be described by four lake types – glacial cirques (CAS, UAN, EAG), glacial troughs (DON, FAL, UTW), Lake Tahoe subsites (TCM, TKS, SAN) and reservoirs (JAC, PRO, STA, TOP, SPA). Marlette Lake and Gold Lake are similar to the glacial cirque lakes due to their small size.

PCA of USGS NLCD 1992 distinguishes the geographic outliers that border the Basin and Range ecoregion, Topaz Reservoir and Upper Twin Lake, from the remaining sites. Castle Lake in the Klamath Mountain ecoregion seems to be similar to most of the sites in the Lake Tahoe region with regard to the USGS NLCD 1992 classification types and resolution.

PCA analysis of human impact in the catchments did not produce expected patterns. However, a general relationship between morphological groupings and human impacts is worth noting. Glacial cirque lakes are relatively small and inaccessible, thus human impacts are limited. Glacial trough lakes are larger and more accessible, thus they tend to be fishing and boating destinations. The reservoirs large sizes and accessibility also draw more boating and fishing activity.

Most of the sites had moderately low to very low impact, while only a few have very high impacts. In addition, the USGS NLCD 1992 data contained a large number of zeros since many of the catchments did not contain similar land cover classes. These two characteristics make PCA a less than ideal ordination method for this data set. PCA is ideal when using data that has linear relationships among the variables (McCune & Grace, 2002: 125). PCA also interprets zeros as a positive relationship between variables (McCune & Grace, 2002: 115). When plotting the 1st and 2nd principle components against one another, heterogeneous ecological data sets tend to result in an arch of points that resembles a horseshoe (McCune & Grace, 2002: 115). This horseshoe pattern was observed when PCA was applied to the human activity data.

For the aforementioned reasons, future work should be conducted using another multivariate statistical method, non-metric multidimensional scaling (NMDS). NMDS is more appropriate for regional-scale, or wide gradient, datasets. NMDS performs well when beta diversity is high, and is appropriate for data that is non- normal discontinuous or on a questionable scale (McCune & Grace, 2002: 125). NMDS does not assume linear relationships exist between variables, relieves the problem of zeros, and allows the use of any distance measure or relativization, such 50 as percent catchment land cover (McCune & Grace, 2002: 125) and is therefore more appropriate for future work on heterogeneous ecological regional data sets, such as the variables describing Sierra Nevada lakes and catchments.

Chapter 6

CONCLUSIONS

The geospatial database provided a cost-effective tool to estimate ecological and human activity variables for several sites across a large ecoregion. The morphological measurements describe the range of physical variation among the assessment sites. These measures could be used to estimate lake type, a general description of the lake’s origin and morphology, for use as an ecological stratification method for future assessments in the region. Morphological measures could also be used to predict expected productivity and sensitivity to environmental stressors. Although morphological variables provide a broad overview of the lakes’ physical structure, GIS-derived measures of morphometry do not replace detailed bathymetric maps from which lake volume can be calculated. In the case of Sierra Nevadan lakes and reservoirs, their water levels, and thus their surfaces and volumes, fluctuate at varying time scales. Drawdown is an important process to consider during an environmental assessment. While reservoir levels are monitored regularly, these data are not readily available for many of the lakes in the Sierra Nevada. Therefore, GIS-derived measures of lake morphometry should be coupled with as much ancillary information as possible.

USGS National Land Cover Data 1992 also revealed variation among the assessment sites, primarily highlighting geographic outliers and displaying a north-south difference in catchment land cover likely due to climatic or geologic variation. The USGS NLCD 1992 human activity within the catchments was very similar to both the a priori classification and other measures of catchment human activity despite the time difference between data sources. In addition, other measures of human activity in the site catchments were very similar to the a priori classification of activity in and around the lakes.

Applications of the GIS-derived landscape-scale characteristics illustrated the differences between catchment activity and in-lake processes. Further work will need to be done to tease these relationships apart. As suggested by the multivariate analysis, the four groups of lakes (Lake Tahoe subsites, reservoirs, glacial trough lakes, and glacial cirque lakes) can be used as an ecological framework for future analyses of these 20 assessment sites. From an environmental management perspective, the glacial trough lakes of the Sierra Nevada should be a high priority for monitoring and management due to their ecological value and degree of anthropogenic impacts.

This study contributed to the development of an assessment protocol for western lakes. The analysis performed also contributed to the expanding body of knowledge on landscape indicators of ecological condition and effects of human activities in the Sierra Nevada lentic aquatic resources. Region specific information will be useful to decision makers for the future protection and management.

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