Investigating Calving Areas for Rocky Mountain Elk on the Plumas National Forest:

Implications for Land Management

By Abigail Marshall

A case study submitted to Oregon State University in partial fulfillment of the requirements for the degree of

Masters of Natural Resources

Presented: March 27, 2020

Commencement: June 13, 2020

Marshall Case Study

Abstract Sustainable elk (Cervus canadensis) habitat management on U.S. Forest Service (USFS) lands involves a complex relationship between management practices and ecological processes. A relatively novel Rocky Mountain elk population (Cervus canadensis nelsoni) on the Plumas National Forest (PNF) in northeastern California became established in the early 2000s, but there is little information on the current number of individuals or the extent of land used by elk on the PNF. Elk populations are highly influenced by cow and calf survival and disturbances during the calving period are associated with reduced calf:cow ratios. Taking advantage of the fact that cows and calves have limited mobility during the first few weeks after birth, I developed a survey method that can be utilized by the PNF to identify and conserve key areas where calving activity occurs. Vegetative conditions and management histories will be documented for positively identified calving areas on two scales to begin gathering data related to site selection. The monitoring program will enhance the USFS’s ability to manage elk habitat, as well as food resources for the threatened gray wolf (Canis lupus), and domestic grazing on the PNF. The information will also benefit collaboration with partners as part of multi-stakeholder adaptive management effort.

Acknowledgements

Thank you to Brenda McComb (Graduate Advisor, Dean Emeritus OSU), Cristina Eisenberg (Graduate Committee Member, Courtesy Faculty, College of Forestry, Oregon State University), Matthew Jedra (Graduate Committee Member, USFS PNF District Ranger), Rachel Bauer (USFS PNF District Wildlife Biologist), Kelly Mosinski (USFS PNF Wildlife Biologist), and Debbie Bliss (USFS PNF Wildlife Biologist, Retired) for all of your guidance and assistance. Thank you to The Plumas National Forest and Oregon State University. Thank you to my family and friends for supporting me during the development of this Case Study; Jeff Lees, Bob, Besty, Maddie, and Jack Marshall, and Jenn Cossaboon.

Table of Contents Introduction ...... 1 Study Questions ...... 3 Significance of study ...... 3 Study Site Ecology ...... 4 Rocky Mountain Elk Life History ...... 4 Climate ...... 6 Topography and Geology ...... 7 Hydrology ...... 7 Vegetation ...... 8 Fire ...... 10 Historical, Social, and Economic Conditions ...... 12 California Department of Fish and Wildlife Elk Efforts in Plumas County ...... 12 Traditional Ecological Management ...... 12 Post-Euro-American Settlement Vegetation and Fuels Management ...... 13 Livestock Grazing Management ...... 14 Hunting ...... 15 Additional human dimensions and elk management ...... 15 Temporal and Spatial Considerations ...... 16 Recommendations ...... 17 Minimizing Disturbances in Calving Areas ...... 18 Identification of Important Calving Areas ...... 19 Schedule ...... 21 Funding ...... 21 Additional Recommendations ...... 22 Conclusions ...... 24 References ...... 25 Appendix A: Calving Area Monitoring Protocols…………………………………………………30

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List of Figures

Figure 1: Map of the case study area within the Plumas National Forest in Northeastern California. Map Credit: Abigail Marshall...... 1 Figure 2: CDFW (2018) graph of elk population growth in California from 1965 to 2017...... 5 Figure 3: CDFW (2108) map of elk distribution in California as of 2018...... 5 Figure 4: NOAA (2019) image demonstrating the difference in snowpack in the Sierra Nevadas in 2011 (on the left) and 2014 (on the right) after three relatively dry years. Trace snow is represented by dark purple and deep snow is light blue or white...... 6 Figure 5: Map of the springs and perennial (p), intermittent (i), and ephemeral (e) streams within the case study area. Map Credit: Abigail Marshall ...... 8 Figure 6: Map of vegetation cover types in the case study based on PNF vegetation models. Map credit Abigail Marshall...... 9 Figure 7: Fire History Map of the case study area from the early 1900s to 2019. All prescribed fires within the case study area took place between 2006-2009. Walker Fire burn severity is indicated on a scale of 0->90% of the loss of total basal area within a pixel. Basal area is the cross-sectional area of all tree stems at breast height. Map Credit: Abigail Marshall...... 11 Figure 8: Diagram of Sustainability Issues relating to Elk Habitat Management on the PNF. Site ecology, societal values, economics, policy, and institutions all influence one another. Diagram Credit: Abigail Marshall...... 16 Figure 9: Elk calf nursing at a spring site within the case study area. Elk cows and calves formed a sub-herd after the isolation period. This photograph was captured by Matthew Jedra on a game camera within the case study area...... 20

List of Tables

Table 1: Miles of each stream type within the case study area...... 7 Table 2: Acres of each vegetation cover type within the case study area...... 9 Table 3: Potential annual cost of implementing the Elk Calving Area Monitoring Program in 2019 USFS GS-5 wages...... 22 Table 4: Elk management issues and recommended actions to improve elk habitat management and sustainability...... 23

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Introduction The Plumas National Forest (PNF) lies in northeastern California, along the northernmost crest of the Sierra Nevadas. It makes up more than 70% of the total land in Plumas County, covering more than 1.2 million acres of mountains, forests, meadows, and streams. It stretches from the California foothills to the west and the Great Basin to the east, with the high alpine landscapes in between. Local resource-related industries, including its products, and the private, non- governmental, and governmental organizations, rely on the PNF, and it plays a major part in supporting the local economy (USDA 1988). The case study area is centered around the area formerly known as Squaw Valley (which is currently in the process of being renamed under consultation with local indigenous tribes), north of Lake Davis in the eastern portion of the PNF (Figure 1). It has an area of approximately 30,000 acres (12,140 hectares). Squaw Queen Creek flows in the middle of the valley, surrounded by meadow and sagebrush (Artemisia tridentata) communities, with coniferous forests and occasional aspen (Populus tremuloides) stands on the surrounding hillsides. Livestock grazing, hunting, recreation, forestry, and foraging all take place within the case study area by the USFS, the Maidu and Washoe tribes, and members of the public. In 2019, the Walker Fire burned 54,608 acres (22,099 hectares) within the Plumas National Forest and 12,480 acres (5,050 hectares) burned within the case study area.

Figure 1: Map of the case study area within the Plumas National Forest in Northeastern California. Map Credit: Abigail Marshall.

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A small population of Rocky Mountain elk (Cervus canadensis nelsoni) roams over the eastern Plumas National Forest (PNF). Herds of elk on the PNF are relatively novel. There were sporadic observations of individual elk on the PNF throughout the 1980s and ‘90s, but since the mid-2000s there have been numerous incidental sightings of elk that indicate that the population is quickly growing on the PNF. However, there is little information regarding elk abundance, including the numbers of bulls, cows, and calves, or the area used by the elk. The largest reported observation is up to 20 individuals observed at one time (in 2012 and twice in 2018); however, observations of subherds up to 10 individuals are becoming increasingly common. The California Department of Fish and Wildlife’s (CDFW) Final Elk Conservation and Management Plan, released in 2018, excludes the PNF’s group from the closest Elk Management Unit. Additionally, since no elk were present during the last Plumas National Forest Land and Resource Management Plan (LRMP) revision in 2004, there is no management direction specific for elk or their habitat currently on the PNF. The United States Forest Service (USFS) desires to create elk habitat management guidelines for the PNF and to gather information that can be shared with partners as part of a multi-stakeholder adaptive management effort. Elk conservation and habitat management can be enhanced on the PNF through the identification and protection of important calving areas. Pregnant female elk that are about to give birth may separate from the herd, give birth, and then raise the young independently before rejoining the herd (Skolvin et al. 2002, p. 545). Different studies have documented this isolation behavior lasting from several days up to one month, if it occurs (Innes 2011, Vore and Schmidt 2001, Skolvin et al. 2002, p. 545). There are two incidental observations of calving sites with some degree of isolation behavior occurring on the PNF, and 3 to 4 weeks is typical for Rocky Mountain elk farther north in California (Communications with Stacy Anderson, CDFW Biologist, 2019). Elk often return to the same calving areas to have young in subsequent years (Vore and Schmidt 2011). However, this isolation behavior is not observed in many parts of the central U.S. and the degree of isolation may be related to the dominant type of predation on elk in a given area (Communications with Cristina Eisenberg, Courtesy Faculty, College of Forestry, Oregon State University, 2019), and may change over time depending on predation and herd densities. Disturbances during the calving period, such as domestic cattle grazing or mechanical equipment conducting vegetation treatments, can cause cows and calves to move, expending resources and potentially exposing them to predation (Innes 2011, Pitman et al. 2014). Disturbances are associated with reduced calf:cow ratios (Innes 2011). However, if isolation behavior is not occurring, then disturbance may not negatively impact the calves to the same degree (Communications with Cristina Eisenberg, Courtesy Faculty, College of Forestry, Oregon State University, 2019). As of 2020, there are multiple grazing allotments that are actively grazed by cow:calf pairs during the summer months. There are also two planned landscape-scale vegetation treatment projects overlapping the study area, and implementation of the projects should take place between 2020-2030. Identifying important calving areas would allow the USFS to avoid disturbances to these areas during the calving period and gather information on elk reproductive behaviors. Based on the data gathered from this study, there is potential for domestic cattle grazing, various vegetation management activities, and other activities to be deferred until a later time in these areas. Additionally, the PNF can identify areas where elk habitat improvement projects would be most beneficial and provide information to guide management prescriptions to meet desired conditions for calving habitat.

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Study Questions 1. How can the USFS identify calving areas and calving behavior (such as isolation patterns) for a small and novel elk population in the Sierra Nevadas using non-invasive techniques? 2. How can the USFS detect patterns of calving area selection or begin to identify important habitat elements through both spatial data and site visits? 3. How can the USFS minimize disturbances to positively identified calving areas? I conducted research and tested methods and to identify calving areas using cameras and pellet searches. Taking advantage of the fact that cows often have calving area fidelity and that cows and calves have limited mobility during the first few weeks after birth, I developed a monitoring method that can be utilized by the PNF to try to identify key areas where calving activity occurs and begin gathering data related to site selection utilizing motion-activated cameras at springs, as they are perennial water sources which are associated with calving area selection (Skovlin 2002, p. 544). The USFS plans to begin the monitoring program in 2020. I also reviewed the literature on different strategies used by the USFS and other land management organizations that conserve occupied calving areas and discuss those recommendations, such as limiting recreation activities within calving areas during the critical calving period to minimize disturbances. This report has two major components. The main body of the Case Study explores the elk habitat management context within the study area, focused on ecological, social, economic, spatial, and temporal considerations. Within this Case Study, there are recommendations for the USFS to identify calving areas. The second component is a stand-alone document located in the Appendix that provides context and guidance for implementing a calving area monitoring program on the PNF. There is some redundancy between the documents, as the introduction within protocols summarizes some of the body of the case study for context, particularly the introduction and recommendations section. However, the protocols are designed to be able to function as a stand-alone document, to be read separate from the rest of the case study. Significance of study The Elk Calving Area Monitoring Program will enable the USFS to improve sustainable forest management on the PNF. According to the PNF’s LRMP (1988) and the Forest Service Manual (USFS 2005), wildlife management objectives on the PNF include (1) maintaining minimal viable populations of all species; (2) minimizing negative impacts of management activities on wildlife species; and (3) enhancing habitat for a variety of species. Maintaining robust elk populations, which are greatly influenced by reproduction and survival of cows and calves, helps achieve these goals. This program also increases the USFS’s ability to improve certain management practices, such as grazing allotments rotations and vegetation improvements. Because elk calving habitat varies throughout their range (Innes 2011), once a significant number of used calving areas are identified (the exact number of which is to be determined, see protocols for more information), data gathered from used and unused sites can provide a point of comparison and may allow prediction of calving areas based on vegetation conditions within the PNF. Information on calving behavior by cow elk, including the degree of isolation behavior, can help inform the PNF of the potential for management to impact calving, either positively through habitat conservation and improvement, or negatively through disturbances, and contribute to a greater understanding of

3 Marshall Case Study reproductive behavior by elk throughout their geographic range. Additionally, incidental observations of elk throughout the year can provide preliminary data on the elk population, herds, and sub-herds, and identify areas where elk congregate, which could facilitate the collaring of individuals for future research (Communications with Stacy Anderson, CDFW Biologist, 2019). Sustainable elk management also contributes to sustainable wolf (Canis lupus) management (Cooperider 2002, p. 518). Federally threatened, wolves are moving back into its historical range on the PNF. As they are a secondary consumer, one important aspect of effectively managing wolf habitat involves management of their prey base, including elk (Cooperider 2002, p.518). Additionally, multiple cattle grazing allotments overlap the elk herd's current territory. Locating elk calving sites can allow the PNF to mitigate potential conflicts between elk and domestic cattle as they compete for food, water, and cover by identifying key areas important to the elk (Lyon and Christensen 2002, p. 571). Elk calving information can also be shared with partners as part of a multi-stakeholder adaptive-management effort. Gathering preliminary information can enable the USFS to facilitate and guide future research on elk for the PNF. Finally, the USFS will be updating the PNF’s Land and Resource Management Plan, and this program is intended to help inform management direction. In addition to developing a calving area monitoring program, I desired to increase public involvement on the PNF. I initiated a media campaign whereby the general public could submit photos and locations of elk captured on game cameras placed throughout the case study area. This will help the USFS identify areas to survey, gain a better understanding of the phenology of calving activities, and identify areas for elk habitat restoration and conservation. Study Site Ecology

Rocky Mountain Elk Life History Elk, also known as Waipati, are the second largest member of the Cervidae (deer) family in North America (CDFW 2018). There is some debate over elk taxonomy in North America. The CDFW recognizes four subspecies of elk (Cervus canadensis) in North America, with three occurring in California: Tule elk (C. c, nannodes), Roosevelt elk (C. c. roosevelti), and Rocky Mountain elk (C. c. nelsoni) (Figure 3). However, the IUCN Redlist does not recognize C. c. nelsoni as a subspecies (Brook et al. 2018). Additionally, some reports use C. elaphus rather than C. canadensis. To maintain consistency with the CDFW, this report recognizes Rocky Mountain elk as C. c. nelsoni; however, the principles of habitat management are likely to be similar regardless of Rocky Mountain elk taxonomy. Elk population dynamics can vary geographically. Typically, bulls (adult males), cows (adult females), and calves (young) form various herds and sub-herds (groups) throughout the year. Bulls frequently separate from cow and calf groups during the spring and summer, however, there are multiple documented instances of sub-herds of bulls, cows, and calves on the PNF (photographs submitted to the PNF). The rut (breeding season) often lasts August through November (CDFW 2018). Single calves, or twins on rare occasions, are born after a gestation of 244 to 265 days and are approximately 35 pounds (16 kilograms) at birth. There are occasional observations of migrant Roosevelt elk or Tule elk that pass through the PNF (information from the National Resources Information System, or NRIS), however, the resident elk populations are primarily Rocky Mountain elk. Rocky Mountain elk have a lifespan around 14 years. Predators for either adult or calf elk on the

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PNF include black bears (Ursus americanus), gray wolves (Canis lupus), mountain lions (Puma concolor) and coyotes (Canis latrans) (CDFW 2018). Elk are generally opportunistic foragers. They can consume forbs, grasses, sedges, shrubs, and woody stems; however, diet composition can vary widely depending on the season, digestible energy content, protein content, availability, snow depth, and predator avoidance (Cook 2002, p. 281). In very general terms, during the spring, summer, and autumn, elk eat primarily grasses, forbs, and shrubs; winter diet is often woody browse or grasses when available (Cook 2002, p. 281). Nutritional demands can also be highly variable; for example, lactating cows have 2 to 3 times the energetic needs during gestation (Beck and Peek 2004). Euro-American settlement led to drastic declines of elk populations throughout their range, and by the turn of the 20thcentury they were completely extirpated in some areas (Morris 1956), due competition from livestock, overharvesting, agriculture and land development, and introduced diseases (Innes 2011). From 8-10 million elk (of all CDFW-recognized subspecies) were estimated to be in the U.S. before European settlement, and 500,000 elk were estimated to exist in California (CDFW 2018, Thompson 2004). By 1890, only 100,000 elk were estimated in North America, most of which resided in Yellowstone National Park (Innes 2011). State, federal, hunting, and conservation organizations worked to restore elk across the western landscape (CDFW 2018). Now there is likely 1 million elk in the U.S. (USFWS 2014). Translocations of Rocky Mountain elk in California occurred in 1913 and 1967 in Kern and Shasta counties (CDFW 2018). In California, the CDFW estimates that there are approximately 1,500 Rocky Mountain elk, with populations that are relatively stable, however, their range is expanding (Figure 3, Figure 3).

Figure 2: CDFW (2018) graph of elk population growth in California from 1965 to 2017.

Figure 3: CDFW (2108) map of elk distribution in California as of 2018.

There is debate over whether the elk ever historically existed within the case study area before the late 1990s, which contributes to controversies regarding human-elk conflicts (CDFW 2018,

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Thompson 2004). The CDFW (2018) historic range map does not include the PNF, however, the Nevada Division of Wildlife (1997) reported two unverified hunting reports from the Lake Tahoe and Honey Lake area from before local extinction in Nevada at the turn of the 19th century. I spoke with a representative from the Maidu tribe (Trina Cunningham) who did not recall an oral history of elk within the area. Before Euro-American colonization, predators such as wolves and grizzly bears (Ursus arctos) existed in the case study area, but it is unlikely that elk populations in the case study area (or within the PNF) were very high before Rocky Mountain elk populations were extirpated in most of the west (CDFG 2011, CDWF 2018, Thompson 2004). Climate The case study area lies within the transition between the northern Sierra Nevadas, southern Cascades and the Great Basin. It has hot, dry summers and cool, snowy winters (CDFG 2003). Summer thunderstorms help contribute to overall precipitation rates (USDA 1988). Over the last 10 years, the average temperatures in the summer have highs of 82ºF and lows of 39ºF, with winter highs of 49ºF and lows of 17ºF (Iowa Environmental Mesonet 2019). During the development of the Land and Resource Management Plan in 1988, the snowpack was estimated to range from 5-10ft during the winter, and snow was typically present from December to May (USDA 1988). The case study area, as well as the rest of California, experienced severe drought from 2011-2017 (Lund et al. 2018). The drought resulted in reduced snowpacks through the Sierra Nevada during the drought period (Figure 4).

Figure 4: NOAA (2019) image demonstrating the difference in snowpack in the Sierra Nevadas in 2011 (on the left) and 2014 (on the right) after three relatively dry years. Trace snow is represented by dark purple and deep snow is light blue or white. Subsequently, there are lingering aftereffects of the drought, such as severe tree mortality from drought-related stress (Lund et al. 2018). After the drought, the total precipitation in Thompson

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Valley within the case study area was 35.2 inches in 2017 and 18.9 in 2018 (Iowa Environmental Mesonet 2019). Although the 2011-2016 drought may be over, climatic projections for the study area show that decreased precipitation, earlier snowmelts, increased proportion of precipitation as rain, periods of drought, and extreme weather patterns are likely to occur (Diffenbaugh et al. 2015). Climate changes can impact elk habitat. While reduced snowloads might allow for increased elk winter survival (Poole and Mowat 2005), drought conditions are overall negatively associated with elk habitat suitability as it decreases plant growing seasons and can contribute to winter starvation, reduced survival, and reduced elk calf recruitment (Vucetich et al. 2005, Middleton et al. 2013). Therefore, if periodic droughts increase in frequency, elk habitat in the case study area is likely to be negatively impacted (Vucetich et al. 2005). Topography and Geology The case study area includes the valley formerly known as Squaw Valley, which is approximately 4,000 acres (1,618 hectares). It rests near 5,500ft (1,676m) in elevation and the surrounding mountains rise up to 6,800 ft elevation. Rocky cliffs occur along the northern ridge of the mountains surrounding Squaw Valley, and volcanic outcrops occur within the case study area. The Sierra Nevada was formed by faulting and uplifting processes, which created diverse rock and soil types across the PNF (USDA 1998). The general bedrock type is volcanic (CDFG 2003). Soil types can provide various growing conditions and influence water availability and nutrients, influencing resource growth and availability. There are 100 soil types within the case study area based on PNF soil surveys. Approximately half of the land is comprised of only 7 soil types. These types include very gravely loam (Soil Code 10), cobbly loam with unweathered bedrock below (Soil Code 170), and gravely sandy clay loam (Soil Code 232). Hydrology The case study area is within the United Stated Geological Survey (USGS) 18020122 Hydrologic Unit (HUC 8, Level 4). It is part of the headwaters of the Feather River, which feeds into the California Central Valley and the Sacramento River and provides the majority of the drinking water for California (USDA 1988). The main hydrologic features include Squaw Queen Creek and spring-fed tributaries. According to the PNF Streams database, there are 321 miles (517km) of ephemeral streams, 123 miles (199km) of intermittent streams, and 37 miles (60km) of perennial streams in the case study area, for a total of 482 miles (776km) of streams (Table 1, Figure 5). There are 86 springs within the study area. Table 1: Miles of each stream type within the case study area. Stream Type Length in mi Length in km Ephemeral 321 517 Intermittent 123 198 Perennial 37 60 Total 482 776

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Figure 5: Map of the springs and perennial (p), intermittent (i), and ephemeral (e) streams within the case study area. Map Credit: Abigail Marshall Elk typically prefer areas located within 0.25 miles (0.41 km) of permanent water sources (Skovlin 2002 p. 544). While there are 37 miles (60 km) of perennial water within the case study area, springs play an important role in the hydrology of the case study area. Springs are natural water sources where subterranean water emerges from a land surface and are unique features on the landscape that act as natural concentration areas due to the limited presence of permanent water within the case study area (Simpson et al. 2011). Springs will be utilized for survey sites in this case study. There are also occasional guzzlers, human-installed water retainers that are generally placed in areas without other sources of water, present within the study area (exact the number of which is unknown), however, these are often hydrologically removed from the landscape and can lack the plant communities associated with elk forage (Simpson et al. 2011), and are not used as study sites. However, information on nearby guzzlers will be captured for positively identified calving areas. Vegetation Forests within the case study area are generally classified as climatically temperate and are within the Sierra Nevada Forest Ecoregion (Ricketts et al. 1999). This ecoregion is known for its remarkable biological diversity. The case study area is the most northern section of this ecoregion. The majority of the acres within the case study area are comprised of conifers, followed by shrub types and then herbaceous types (Figure 6, Table 2). Conifers typically found within the study area include Jeffrey pine (Pinus jeffreyi, and for the purposes of this case study, Jeffrey pine and ponderosa

8 Marshall Case Study pine, Pinus ponderosa, are both classified as Jeffrey pine), Incense-cedar (Calocedrus decurrens), white fir (Abies concolor), and Curl-leaf mountain mahogany (Cercocarpus ledifolius), and quaking aspen (Populus tremuloides) are the prominent hardwoods.

Table 2: Acres of each vegetation cover type within the case study area.

Hectares Cover Type Acres Conifer 28743 11632 Shrub 12785 5174 Herbaceous 6783 2745 Bare ground 195 79 Hardwood 71 29 Water 3 1 Grand Total 48580 19660

Figure 6: Map of vegetation cover types in the case study based on PNF vegetation models. Map credit Abigail Marshall. Typically, elk habitat is broken into temporal ranges: summer range, spring/fall range, winter range, and calving range (Skovlin et al. 2002, p. 532). The calving period overlaps with the spring range. Horizontal complexity of vegetation within an elk herd’s home range is critical, as it provides forage in areas without dense forest canopies, while denser forest provide hiding and thermal cover.

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Ecotones are important elk habitat elements as they provided increased forage diversity and quantity available to elk than the adjacent individual communities (Innes 2011). Beck and Peek (2004) found elk use of mountain meadows is highest when adjacent to forest cover and excluded from roads. Thomas et al. (1979, p. 121) formulated that spring ranges are ideally “20% hiding cover, 10% thermal cover, 10% hiding or thermal cover, and 60% forage areas.” However, habitat selection is greatly influenced by predator hunting tactics, forage conditions, and human disturbance (Pitman et al. 2014). The habitat requirements for calving areas must incorporate the needs of cows and calves immediately before, during, and for several weeks after birth. Elk typically select aspen sites over conifer sites for calving grounds (Barbknecht et al. 2011). Young quaking aspen stands are a likely food source, while mature aspen stands provide cover (Holland 2005). In areas without wolves, canopy covers above 70% may be suitable for adult elk hiding cover (Thomas et al. 1979, p. 114), but conifers with high canopy closures may not be suitable for newborn elk due to lack of sunlight, which causes thermal stress (Barbknecht et al. 2011). Multistoried conifer stands tend to be better thermal cover than single-aged stands (Thomas et al. 1979, p. 115). Shrubs and downed logs within forest stands can be important elements to hide newborn elk calves, however, they can also impede adult escape from wolves (Thomas et al. 1979, p. 120, Halofsky and Ripple 2008). The Calving Area Monitoring Program can help refine and identify vegetative habitat variables that are specific to the case study area, which can allow the PNF to gear management prescriptions to benefit calving habitat. Fire The main disturbance regime within the case study area is fire. Fire in the northern Sierras was typically frequent and low to moderate intensity. According to McKelvey et al. (1996), fires ranged from small, isolated incidents to large-scale fires covering vast areas, but were generally less than 250 acres (101 hectares) in size, with a return interval ranged between 5-50 years. Fires were of a low enough severity that they rarely lead to crown fires or kill large-sized tree. Historically, forests were not only resilient and resistant to these types of disturbances, but these fires helped regulate forest insects and disease, soil nutrients and productivity, understory plant communities, forest stand densities, forest vertical structure and complexity, and early successional, unique, or riparian habitat types such as meadows, aspen stands, and springs (Graham et al. 2004; McKelvey et al. 1996). Additionally, many plants within the Sierra Nevadas have fire-dependent growth patterns (McKelvey et al. 1996). All of these habitat elements are important for maintaining suitable elk habitat, as diverse successional stages increase forage and cover available to elk (Innes 2011). The Maidu and Washoe tribes would often intentionally ignite fires within the case study area (Lake 2013, Correspondence with Trina Cunningham, representative of the Maidu Tribe, 2020). After European colonization, the designation of the US Forest Service, and several devastating fires that occurred in 1910, complete fire suppression became the main fire management direction in land management agencies for human- or naturally-ignited fires, including the case study area (Agee and Skinner 2005). Over time, fire suppression created forests that had higher stand densities, shifted forests to a species mix that was less fire tolerant, increased ground fuel accumulations, and resulted in a more homogenous landscape (Beaty and Taylor 2008; Parsons and Debenedetti 1979). Without these fires, we experience cascading impacts including: reduced biodiversity, declines in water yield, decreased forbs and grasses, and an increase in understory fuel that ultimately leads to an increased risk of large high-severity fires (also referred to as catastrophic fires) (McKelvey et al. 1996). The vast majority of the case study area is far outside the historic fire interval (5-50 years) (Figure 7). In September 2019, the Walker fire burned through the 12,480 acres in the western section of the case study area. While the Walker Fire burned at high severity within the majority of its

10 Marshall Case Study footprint (approximately 55,000 acres), the fire burned largely at mixed-severity within the case study area (Figure 7). The Walker Fire likely impacted elk habitat. Burned areas often provide for increased graminoids available to elk, allow for increased aspen availability, and elk can be highly attracted to burned areas (Bond 2015).

Figure 7: Fire History Map of the case study area from the early 1900s to 2019. All prescribed fires within the case study area took place between 2006-2009. Walker Fire burn severity is indicated on a scale of 0->90% of the loss of total basal area within a pixel. Basal area is the cross-sectional area of all tree stems at breast height. Map Credit: Abigail Marshall. Elk herbivory can have varying impacts in post-burned landscapes. Intensive elk herbivory can negatively impact aspen regeneration in burned areas (Bailey and Whitham 2002). However, reseeding grasses post-fire may reduce woody plant herbivory by elk (Biggs et al. 2010) and large fires may “swamp” effects from herbivory from increased amounts available biomass (Bond 2015). Bailey and Whitham (2002) found an interesting relationship between arthropod richness, fire severity, and elk herbivory; areas with intermediate fire severity and moderate browsing by elk had increased richness and abundance of arthropods, while areas with high severity fire and high levels of elk browsing had much lower arthropod richness and abundance. A mosaic of different fire severity and elk browsing rates led to the greatest diversity in arthropod community types. Elk impact on post-fire landscapes can vary greatly depending on scale, geographic range, fire severity, and elk range and population (Biggs et al. 2010).

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Historical, Social, and Economic Conditions Management conditions influence site ecology. This can occur as activities impact hydrologic patterns, vegetation composition, disturbance regimes, species interactions, and wildlife species populations (Figure 8). Management objectives are often influenced by societal values, economics, policy, and the constraints of the area’s ecological factors (Christensen et al. 1996). In turn, land management institutions, policy, and access shape how people interact with the environment, which can influence social structures and values (Bell and Ashwood 2016, p. 46). California Department of Fish and Wildlife Elk Efforts in Plumas County The CDFW has attempted to study elk within Plumas County since the mid-2000s. Collaring attempts from 2012 to 2018 failed to yield any positive results, either through inability to locate elk during collaring events or from tranquilized elk waking before collars could be placed (Communications with Stacy Anderson, CDFW Biologist, on May 30, 2019). Helicopter surveys also failed to identify elk due to the forested environment of the case study area (Email communications between Terri Weist (former CDFW Biologist) and Russell Nickerson (former USFS PNF Biologist) on January 31, 2018). Similar to the methods used on the Elk Calving Monitoring Program, since 2013 the CDFW has attempted to gather public observations, conduct pellet surveys, and use cameras to try and estimate elk populations in Plumas County, however, the Elk Calving Monitoring Program is targeted at natural wildlife concentration features and focused primarily on identifying important calving areas. The data gathered from the program can be shared with the CDFW to help identify areas where collaring attempts may be successful (Communications with Stacy Anderson, CDFW Biologist, in July 27, 2019). In 2012, a lone bull elk in Sierra Valley, approximately 12.5 miles (20 kilometers) south of the case study area, reportedly killed multiple domestic cattle calves, chased domestic cows, and was destroying private property on a ranch. The ranchers worked with the CDFW to attempt to relocate the elk, rather than kill the elk, as it had a positive public following (Multiple email communications from Terri Weist, former CDFW Biologist, to Russell Nickerson, former USFS biologist, in September 2012). In September of 2012, CDFW biologists, veterinarians, and multiple other biologists trapped, collared, and attempted to transport the elk. A reversal agent (to counter the tranquilizer) was given to the elk and it became extremely agitated during transportation, thrashing in the trailer, and died before reaching the relocation destination. Traditional Ecological Management The case study area is the historic homeland of the Maidu and Washoe Tribes. The Maidu prolifically used the case study area for a range of purposes before being systematically killed or forcibly removed from much of their homeland in the late 1800s by Euro-American settlers. However, many tribal members continue to use the lands within the case study area for hunting, foraging, and spiritual experiences. Traditional ecological management involves utilizing practices that help to shape ecologically complex systems in sustainable methods (Turner et al. 2000). Historically, the case study area was home to village sites and different areas were also used for sacred ceremonial uses (Communications with Trina Cunningham, representative of the Maidu Tribe, 2020). There are also sacred areas within the case study area that are currently used for gathering or prayer, which can vary with the time of year. Cultural burning was a widespread practice throughout the case study area, which stimulates

12 Marshall Case Study the growth of vegetation. Mountain mahogany (Cercocarpus ledifolius) and western juniper (Juniperus occidentalis) was often burned and pruned to facilitate growth conducive with making tools. Tending root vegetables also helps prevent soil compaction and increases the quality of forage such as wild potatoes (Periderida parishii, also known as Yampah), onions (multiple Allium species), and carrots (Sanicula sp.); however, active cultivation has become more difficult due to colonization and land accessibility issues, leading to soil compaction that reduced the quality of forage items (Communications with Trina Cunningham, representative of the Maidu Tribe, 2020). Elk are an important cultural component of many indigenous tribes in California, and those tribes managed elk populations and their habitats (CDFW 2018). The CDFW is trying to work closely with different tribes to incorporate Traditional Ecological Knowledge (TEK) in elk and habitat management (CDFW 2018). Working with tribal organizations in areas that were previously occupied before mass-extermination efforts by Euro-American settlers helps to increase tribal influence and management of ancestral lands. Further, the TEK held by Indigenous people locally can be very effectively applied within an adaptive management strategy to create more effective ecological restoration and increase stakeholder engagement (Eisenberg et al. 2019). Accordingly, the Maidu and Washoe Tribes will continue to be an important partner throughout the adaptive management process. Post-Euro-American Settlement Vegetation and Fuels Management The forests in the case study area have been logged extensively since the late 1800s (Laudenslayer and Herman 1990). Deforestation practices impacted the case study area by altering species compositions and creating stands with trees that are younger and smaller than previously existed (Laudenslayer and Herman 1990). Based on vegetation models utilized by the PNF, 52% of the case study area, and 88% of the forested area, is dominated by trees between 11-24” (28-61 cm) in diameter at breast height (dbh), while only 1.2% of the forested area is comprised of old-growth sized trees (>24” dbh, >61 cm) (SNFPA 2004). Additionally, the amount of understory grasses has declined (Laudenslayer and Herman 1990). There is an inverse relationship between increasing pine canopy and the yield in grasses, forbs, and shrubs (Thomas et al. 1979, p. 116). Forests dominated by small and densely stocked trees negatively impact elk habitat, as multi-storied stands provide better thermal cover than single-aged stands and openings within forested stands provide opportunities for the growth of forbs and grasses (Thomas et al. 1979, p. 116). The USFS currently manages the land for multi-use purposes. Vegetation and fuels management is a prominent use of the land within the case study area. As of 2020, the USFS is planning a large-scale fuels reduction project, titled the Mapes Project, which encompasses 90,000 acres (36,422 hectares) and extends beyond the borders of the case study area. The objectives and actions include ecological restoration, fuels reduction, and timber sales through uneven-aged forest management (Personal communications with PNF staff 2019). One of the goals for the Pacific Southwest Region (Region 5, which includes the PNF) is “to retain and restore ecological resilience of the National Forest lands to achieve sustainable ecosystems that provide a broad range of services to humans and other organisms. Ecologically healthy and resilient landscapes, rich in biodiversity, will have greater capacity to adapt and thrive in the face of natural disturbances and large-scale threats to sustainability” (USDA 2013). Additionally, the Land and Resources Management Plan (USDA 1988, p. 4.29) has standards and guidelines specific for wildlife that apply throughout the case study area. The USFS will “assure adequate protection for wildlife and fish resources.” The

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USFS will also “provide a diversity of vegetation types and habitat to support viable populations of all fish, wildlife, and plant species.” Proposed forest health projects would likely improve elk habitat due to the increase of light available to the understory. There is some ability to mimic historic fire regimes through tree removal, prescribed fire, or managed fire (Weatherspoon and Skinner,1996). Prescribed fires are planned within the case study area through the Mapes Project (in planning as of 2020) to attempt to return fire regimes to the area and reduce biomass, however, it is unlikely that the entire footprint of the case study area will receive underburning (USDA 2004). Returning fire to the landscape will likely improve elk habitat. Dense conifer canopy cover that resulted from fire suppression can lead to shading out understory plants, which lowers plant cover, forage, and species diversity available to elk, while also being vulnerable to high-intensive crown fires (Shepperd et al. 2006. p. 67). Livestock Grazing Management Livestock grazing in the Sierra Nevada was widespread in the late 1800s and throughout the 1900s (Allen-Diaz et al. 1999). Livestock grazing is currently managed by the USFS on the PNF. The vast majority of the case study area resides within active cattle grazing allotments (as of 2020). Domestic cattle cow and calf pairs graze within allotments from late spring or early summer through September. One of the most polarizing issues with elk involves domestic cattle management and grazing concerns, as stakeholders are often pursuing different goals (Beck and Peek 2004). The elk/livestock relationship is complex. In some cases, the presence of both livestock and elk can improve habitat of the other (Sheehy and Vavra 1996) and there may be a large enough difference between preferred forage that there may not be direct competition (Beck and Peek 2004). However, cattle can greatly reduce winter forage for elk, and elk foraging during the winter can decrease summer forage for cattle (Smallidge et al. 2015). Elk typically prefer pastures and resting areas that are not utilized by cattle (Yeo et al. 1993, Smallidge et al. 2015). Competition for forage can be particularly concentrated in riparian areas where cattle congregate, particularly in the late season when forage is most limited (Treadaway et al. 1997, Smallidge et al. 2015, Shepperd et al. 2006, p. 67). Competitive interactions for forage increase with rising elk or cattle populations (Beck and Peek 2004). Elk presence on rangelands managed by the USFS may negatively impact permittees in multiple ways. Elk and cattle can transmit certain diseases to one another, such as chronic wasting disease, brucellosis, and various gastrointestinal parasites, and increased populations of elk could increase opportunities for disease transmittance (Pruvot et al. 2020). Elk can damage fences that permittees are required to maintain (Smallidge et al. 2015). Increased ungulate presence may impact post-season monitoring results of grazing utilization (Treadway et al. 1997). Additionally, private property incentives or compensation programs available on private lands, such as money or assistance to maintain fences, are not offered on federal lands (Smallidge et al. 2015). These issues can lead to further negative associations of elk for grazing permittees. There are rare occasions where conflict between elk and cattle take place, however, the majority of conflict around elk and domestic cattle arises between societal groups who feel as though their values are not being addressed (Smallidge et al. 2015). For example, seasonal closures, such the ones I recommend to the USFS (see Recommendations below) are controversial as they can restrict desired human activities in certain areas during certain time periods (Phillips and Alldredge 2000). However, there are a variety of mitigation measures that can be enacted that increase the amount of

14 Marshall Case Study forage for both livestock and elk, such as restoring meadows, riparian areas, forest densities, and fire regimes (Smallidge et al. 2015). Rest-rotation strategies can also improve forage for both cattle, elk, and other wildlife (Frisina 1992). Anticipating conflict and utilizing creative strategies can mitigate some of the social concerns surrounding cattle and elk management. Hunting In addition to cattle, elk can compete with other large mammals that can be important to hunters. Mule deer (Odocoileus hemionus) hunting is regulated within the case study area by the CDFW. Deer and elk have moderate levels of dietary overlap, and increased elk populations have the potential to lead to competitive interactions between the two species (Beck and Peek 2004). However, forage competition is also increased due to cattle grazing, so there are multiple factors to consider. Elk hunting is not currently permitted within the case study area but is a widespread practice throughout much of the Rocky Mountain elk’s range (CDFW 2018). Elk hunting can provide local economic boosts during the hunting seasons (Smallidge et al. 2015). Increased elk populations may allow for possible hunting opportunities in the future. Funding from hunting through the Pittman-Robertson Act and hunting organizations were critical in the recovery of elk across the western landscape (CDFW 2018). Additionally, funding from hunting licenses, hunting tags, the Pittman-Robertson Act, hunting conservation organizations, and other hunting-related sources funds a large portion of the CDFW elk program and ungulate habitat restoration programs (CDFW 2018). Additional human dimensions and elk management Management activities that influence cow and calf survival, food availability, and human- inflicted stress, are driven by science and policy, which in turn are developed or implemented based on the dominant values of people at any given time or place (Christensen et al. 1996, Bell and Ashwood 2016, p. 46, Figure 8). These management activities and societal values can therefore have large impacts on elk populations. Decision-making and conservation efforts can be more effective when they integrate the needs of wildlife, the environment, and humans, as well as increase the positive public responses to decisions (CDFW 2018). Open dialogue is necessary to find solutions that work among various committed parties (Smallidge et al. 2015). Many wildlife, agricultural, game management, and ecosystem management interests are intertwined and can have common pursuits that are not mutually exclusive when managed properly (Smallidge et al. 2015).

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Figure 8: Diagram of Sustainability Issues relating to Elk Habitat Management on the PNF. Site ecology, societal values, economics, policy, and institutions all influence one another. Diagram Credit: Abigail Marshall.

Temporal and Spatial Considerations Spatial considerations are important when considering elk habitat management, as habitat selection takes place over various scales. Douglas Johnson (1980) identified the four levels of habitat selection; within Johnson’s framework, elk habitat selection would be considered as 1) across the broad geographic range, 2) a home range, 3) a patch within that home range, and 4) individual resources within the patch. Across the landscape level, elk ranges are frequently shifting as they continue to recover from population declines post-Euro-American settlement (CDFW 2018). The Elk Calving Monitoring Program primarily focuses on levels 3 and 4; the calving area habitat is a patch within the greater home range of elk, and the microsite habitat variables are the individual resources utilized by cows and calves within that patch. Studying these components can help contribute to a greater understanding of overall elk habitat selection, as elk vary in calving habitat selection across their broader range (Innes 2011). Temporal considerations can also vary by scale. The calving monitoring program focuses on a particular time period within the elk’s reproductive cycle. Calving takes place during the spring, typically in May and June (USFS 2010). While the monitoring program I developed will capture elk use of study sites year-round, the focus of the program is aimed at the critical calving period. The study can refine our understanding of local calving phenology, as there can be slight variation over different areas of the elk’s range due to receding snowlines and plant availability (USFS 2010, Shively et al. 2005, Skovlin et al. 2002, p. 545). Over a broad temporal scale, calving activities can influence elk populations over much longer periods of time. Populations of elk can grow due to birth, death,

16 Marshall Case Study immigration, and emigration rates (Johnson et al. 2004). Elk population growth can be slow for extended periods of time before rising quickly and exponentially depending on the constraints of the site (NDOW 1997). Factors that influence these include food availability, disease, predation, climate, population density, and human-inflicted stress (Johnson et al. 2004). Population growth over time is frequently dependent on cow and calf survival (Lehman et al. 2018). Identifying calving areas is the first step in conserving these areas and increasing cow and calf survival. In addition to calving phenology, behavior, and habitat, there are numerous other temporal considerations that should be studied to better understand elk and elk habitat management (Table 4). For example, efforts to understand winter ranges can influence management objectives. If the herd regularly overwinters within the case study area, it is important to ensure adequate browse to allow populations to survive the winter. The Elk Calving Monitoring Program is the first step in establishing an Adaptive Management program at the PNF for elk. In adaptive management, researchers and land managers work together to develop and interpret data and re-evaluate management methods based on that data (Johnson et al. 2004). The USFS, California Department of Fish and Wildlife, hunting, tribal, and conservation organizations, and other stakeholders and partners can work together to study and manage both elk populations and the landscapes they depend upon. Gathering preliminary data on the elk herd’s population and range is the first step in this adaptive management process. Recommendations Summary Currently, there is no specific management direction) in the Land and Resource Management Plan (USDA 1988) or Sierra Nevada Forest Plan Amendment (USDA 2004) for protection of calving areas on the PNF or within Region 5 of the USFS. Mitigations to conserve calving areas are handled on a case by case basis. While elk populations on the PNF appear to have steadily increased in the last 20 years, there are numerous complicating factors that could influence elk populations and suitable elk habitat in the future, including changes in predation pressure and climate change. If the USFS desires to increase or maintain elk calving habitat and elk populations, particularly under uncertain future conditions, I recommend that the PNF identify and conserve positively identified calving areas to prevent reduced cow:calf ratios and improve calving habitat. I developed a study to conduct intensive monitoring of spring sites in order to identify important calving areas and gather incidental population information for this elusive elk population. This study can contribute to a greater understanding of elk habitat use in the PNF through the identification of calving areas and habitat variables within those areas. Data on calving area locations and site management is immediately helpful to the USFS in determining future actions at or near the sites, such as identification of areas for potential elk habitat improvement projects and opportunities to minimize disturbances to these areas during the critical calving period. Data on site selection will be helpful for long-term habitat management as a significant number of sites are identified. To prevent disturbances, the USFS should limit management activities during the critical calving period from April 15 to July 15 at these sites. The buffer around the calving areas where the seasonal closure should be maintained is site dependent. Detailed protocol methods are located in the Appendix, however, a brief summary of the techniques are provided here. There are four major components to the program: 1) a camera survey at study sites (springs that are perennial water sources) to identify areas utilized by cow/calf pairs, 2) a walking survey to search for pellets to help validate the camera data, 3) site vegetation data

17 Marshall Case Study gathered for on the microsite scale, 4) site management history and vegetation data at a larger macrosite scale. The objective of this study is to conduct intensive monitoring of spring sites in order to identify important elk calving areas and gather incidental population information. Springs are buffered by 984-ft (300-m) to create a study site. Study sites that have more than one spring may be larger than those without as they will be grouped due to close proximity. A camera will be placed at only one of the springs within the study site, but a transect pellet survey will be conducted throughout the study site. The microsite is a 984-ft (300-m) radius around whichever spring was surveyed using a camera and will contain four plots to sample vegetation. The macrosite will be a 3280-ft (1-km) radius plot centered on the spring that was surveyed using a camera. Once a significant number of calving areas are identified, the micro- and macrosite data can be analyzed using discriminant function analysis or cluster analysis to determine which site characteristics appear to differentiate sites that were used for calving compared to those for which no use was detected. The number of sites needed to be able to document selection will be dependent on the number of microsite variables measured and on the desired confidence with which differentiation can be detected (effect size). The pilot studies I conducted in 2019 (see below) did not gather enough information to run a power analysis to identify the desired sample size where further study of the calving habitat variable could be successful. A power analysis would need to be conducted to estimate the desired sample size to detect biologically meaningful differences in the variables gathered between sites used as calving areas and sites that are unused. Minimizing Disturbances in Calving Areas Disturbances during the calving period, such as domestic cattle grazing or mechanical equipment conducting vegetation treatments, can cause cows and calves to move, expending resources and potentially exposing them to predation (Innes 2011). Disturbances are associated with reduced calf:cow ratios (Innes 2011). Occasional incidental disturbances may not result in increased mortality and elk can become habituated to disturbance if it is continuous and predictable; however, high levels of disturbance, either through intensity in interaction or through duration, can negatively impact cows and calves (Phillips and Alldredge 2000). Elk cows also have a relative degree of site fidelity; Vore and Schmidt (2001) found that four out of five study elk reused calving areas in subsequent years. Delaying disturbances in key calving areas until mid to late summer can also prevent displacement of elk cows and calves from areas that meet forage and hiding cover requirements (Pitman et al. 2014). Different National Forests have various seasonal closures at important calving areas, and closures are also recommended by the CDFW on the PNF (Email communications between Terri Weist (former CDFW Biologist) and Russell Nickerson (former USFS PNF Biologist)). Currently, there is no specific direction for protection of calving areas on the PNF or within Region 5 of the USFS (California), and mitigations on the PNF are determined on a case-by-case basis and by working with livestock permittees to try to keep livestock out of calving areas as long as possible. In Region 5 (California), the Klamath National Forest has specified limited operating periods for logging activities within calving areas for certain projects but did not specify specific dates (USDA 1989). Outside of California, the White River National Forest in Colorado maintains closures in calving areas from April 25 to June 21 (USDA 2006), the Deschutes National Forest in Oregon maintains closures from January 1 to August 15 (USDA 1996), and the Carson National Forest in New Mexico maintains closures from May 1 to June 25 (USDA 1999). Starting a closure at April 15

18 Marshall Case Study allows for a buffer to mitigate disturbances to elk cows scouting sites before parturition and to account for the variations in geographic range until further phenology is identified. Additionally, there is incidental information of isolation behavior of a cow and calf within a calving area through early July captured on cameras by PNF biologists in 2012, but photographs from 2019 indicate that by July 16, the isolation period had ended. Due to calving area fidelity and sensitivity to disturbance, I recommend using similar strategies as the national forests listed above by implementing a seasonal closure at positively identified calving areas from April 15-July 15, where disturbing activities should be limited, as an interim recommendation until further data are collected. These time periods can be refined as we collect data on calving phenology within the study area and the degree to which isolation behavior by the cow and calf are occurring. Mitigation strategies used by different national forests during these periods include delayed vegetation treatments and temporary road or recreational trail closures (USDA 1989, USDA 1996, USDA 1999). The buffer around calving areas where the seasonal closure should apply is site dependent. In 2012, PNF biologists placed a camera at a spring site during the critical calving period and successfully identified an important calving area. The CDFW used cameras to successfully confirm that the area was still utilized as a calving area in 2015 and created a 470-acre polygon to indicate the critical calving area. The Klamath Tribes (Johnson et al. 2008) create a quarter mile buffer to prevent disturbances to calving areas from May 1-June 30. On the PNF, the extent of the buffer may depend on the type of disturbance, the topography of the site, and the ability of sound to carry. Identification of Important Calving Areas There are numerous challenges to identifying important calving areas. First, there are no collared elk within the study area that facilitate studies of GPS movement patterns of cows or calves, or allow for trapping and insertion of vaginal transmitters in pregnant cows, which are traditional methods for identifying parturition locations (Barbknecht et al. 2016). These are costly, risky to cows and calves and there is no large sum of money and personnel to enact a widespread study. Second, the dense forest canopy within the study area makes helicopter studies and other methods infeasible to studying elk within the study area. Third, actions are taking place on the forest currently; livestock grazing, vegetation management projects, and recreational activities could be affecting calving areas currently, both positively and negatively, and there is no information available to the USFS about where those areas may be. Working within this framework, I worked to create a survey that could facilitate the USFS to identify areas important to elk cows and calves during critical time periods that fit into the larger program of work without greatly increasing costs to the PNF. I developed a monitoring plan that outlines methods for locating calving areas (Appendix A). It is not currently feasible to determine the exact parturition sites without widespread collaring efforts; however, as cows and calves have limited mobility during the first few weeks after birth, the USFS can identify key areas where calving activity occurs and begin gathering data related to site selection. The monitoring program will allow the USFS to monitor calving areas each year using cameras and stand searches to document evidence of use by cows and their calves at springs located within the study area. Areas that are located along intermittent waterways that may be flowing during the calving season will not be surveyed due to feasibility issues. Vegetative conditions and management histories will be documented for study sites on both micro- (the immediate spring vicinity) and macro-scales to begin identifying patterns in land use.

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Pilot Studies In effort to create the methodology, I conducted various pilot studies from the end of 2018 and through 2019. I created datasheets for each component of the program and methods for selecting sites for survey (summarized below), tracking surveyed sites, maintaining collected data, and interpreting photo results (Appendix A). Other PNF biologists and I placed cameras at one developed spring and one xeric site from November 2018 to May 2019, and one camera at a small meadow adjacent to a spring within a known calving area from November 2018 to July 20, 2019. No calving activity was observed, however, this may be due to the placement or angle of the camera within the site. All camera batteries and SD cards lasted throughout the survey period. Four cameras are being tested at four study sites from November 2019 to July 2020 to further refine any issues. Two PNF biologists and I placed three cameras at a study spring and known calving area to test optimal placement of cameras within a study site, from August 7, 2019 to October 1, 2019; however, one camera malfunctioned and stopped recording on September 9. We placed two cameras at the top of the springhead at two different angles, and one camera at a pool within the spring channel approximately 330ft (100 meters) from the springhead. The camera that was at the springhead (and functioned the entire survey period) detected only two elk observations (and captured 15 photos of elk), while the camera at the pool detected six observations at the spring channel (with 30 photos of elk). See the protocols located in the Appendix for further information. I determined transect spacing for pellet surveys after conducting variable-width transects spaced 330ft (100m) apart within two different study sites, walking a total of 3.9 mi (6.1 km). I encountered 62 pellet groups for a detection rate of 15.9 pellet groups/mile (10.1 groups/km). This was a higher detection rate than anticipated, however this is likely due to the sites being located at natural elk concentration areas. The objective of the pellet survey is to detect presence, not changes in population density, and with an encounter rate of 330ft/pellet group (100m/pellet group), 1.694mi ( 2,727 meters) per site (for sites with single springs) allows for high confidence that surveyors will encounter pellet groups if they are present at the site. Because the sites vary in size, this provides a baseline; larger study sites will have proportionately larger coverage. The Pellet Survey segment of the protocols detail how I determined the appropriate length of transects. I workshopped the microsite protocols over the two known calving areas during site visits. I conducted preliminary tests with the assistance of two other biologists at one calving area and then refined the protocols. Another biologist and I conducted two out of four plot surveys at the other known calving area and refined the protocols again. Four biologists tested various canopy cover methods over a plot in a test site to determine optimal methods. See the Microsite and Macrosite Protocols, Figure 9: Elk calf nursing at a spring site within the case study located in the Appendix, for more area. Elk cows and calves formed a sub-herd after the isolation information on the methods used. period. This photograph was captured by Matthew Jedra on a game camera within the case study area.

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Additionally, I initiated a media campaign in the local newspaper and on Facebook, whereby members of the public can submit observations or photographs of elk to the Plumas National Forest. The public media campaign resulted in 14 different observations of elk, including one observation of an adult cow elk that indicates isolation behavior and a potential calving area near the sighting. I also analyzed emails from previous biologists on the PNF and the CDFW to better synthesize known information, which is presented throughout this document. Incidental observations from the public and the CDFW demonstrate elk presence outside the study area, however, the study area still presents the highest concentration of elk observations on the Beckwourth Ranger District of the PNF. These observations indicate that the Elk Calving Area Monitoring Program should be enacted wherever elk calving could occur, not just within the study area. Any existing observations made by PNF wildlife personnel, the CDFW, and members of the public, tracked in the National Resource Information System (NRIS), can be used to identify areas that may warrant survey outside of the initial study area. These observations begin in 2012. Schedule The USFS is planning to begin implementing the plan during the summer of 2020. Cameras will be placed at study sites beginning in August to gather data throughout the fall and ensure that cameras are in optimal position before the winter, as many of the sites may not be accessible until the spring and into the critical calving period. Therefore, cameras should be able to be deployed from November to mid-July without being checked so surveyors do not disturb cows and calves if the site is a calving area. During pilot tests (see above), cameras utilizing 32G SD cards and lithium batteries were still operational at test sites in the summer after being deployed in early November. Further tests to refine protocols are being tested currently. If the sites are accessible November through March, cameras should be checked to optimize photo data. Funding The program costs to the PNF will vary depending on the number of sites that will be monitored in a given year. For the purposes of analysis, I estimated the program costs per year if five sites are monitored, and the number of person days was estimated using times encountered during field tests. The only equipment costs would be slight wear and tear on cameras and various field equipment The estimated personnel costs of implementing the Elk Calving Area Monitoring Program are approximately $4,000 per year (Table 3). Deploying and inspecting cameras could take approximately eight person days per year; two days for deployment and one day every 2-3 weeks to check cameras. At GS-5 seasonal wildlife technician wages, this amounts to $1,044.56. Pellet surveys would take another 2 person days at the same wages, amounting to $262.14. The majority of the costs will occur during the filling out datasheets and entering the data into the database. Camera data analysis, such as inspecting photos, filling out the data sheets, and entering the data into the database, will likely take approximately 1.5 days per site for a total of 7.5 person days (rounded to 8 person days), costing $1,044.56 of GS-5 wages. Each microsite was designed to take two people less than one day to travel to and from the site and conduct the assessment. If two calving areas are identified, this would equate to 10 person days (2 people per site per day), resulting in $1,305.70. The macrosite assessment should take one person approximately half a day per site, or $362.50. The PNF has limited resources (i.e. cameras, surveyors, or time) available to dedicate to monitoring of calving sites, however, this program should be feasible to complete within the program of work and allows for survey of multiple species over multiple years, as springs serve as

21 Marshall Case Study natural concentration areas for wildlife activity. There is also potential for partnerships with Oregon State University, Feather River Community College, Portola High School, the Rocky Mountain Elk Foundation, the Maidu tribe, University of Nevada Reno, and the Mule Deer Foundation to assist with managing photo data and documentation.

Table 3: Potential annual cost of implementing the Elk Calving Area Monitoring Program in 2019 USFS GS-5 wages. Item Expense Cost Deploying and inspecting five cameras 8 person days $1,044.56 Pellet surveys 2 person days $262.14 Data analysis 8 person days $1,044.56 Microsite data gathering 10 person days $1,305.70 Macrosite data gathering 2.5 person days $362.50 Total $4,019.46 Additional Recommendations If increasing the elk herd is a USFS goal, then in addition to limiting management actions at calving areas, the USFS should consider closing roads that are within or adjacent to calving areas to help prevent disturbances from public vehicles and enhance elk habitat overall. The presence of roads is adversely related to elk habitat (Thomas et al. 1979, p. 122). Elk generally avoid areas within 656ft (200m) of major roads (Rost and Baily 1979). There are some cases that document otherwise, such as Beck and Peek (2004) who noted that road densities were high in areas selected by elk, but that may be due to the fact that roads are often placed in aspen and sagebrush, areas highly utilized by elk, due to ease of movement across the terrain. Yet the evidence to support the impacts of roads on elk habitat is well documented (Thomas et al. 1979, p. 112, Beck and Peek 2004). In addition to improving elk use of certain areas, road closures and restoration can improve watershed health (Beck et al. 1996, p. 65). To enhance elk habitat under current predation levels, the USFS should implement aspen stand and small meadow restoration whenever feasible to increase forage available to elk and increase horizontal complexity across the landscape. As wolf populations increase, the strategies to improve habitat may need to evolve, as high wolf populations can lead to a lack of uniform or expected elk responses to predation risk factors when compared to areas with moderate wolf presence (Eisenberg et al. 2014). Additionally, the filtered light available to the understory in aspen stands results in high plant diversity and contributes to forage, soil, and water protection (Shepperd et al. 2006). Increased elk populations could have large impacts on aspen by limiting aspen regeneration, particularly in the absence of abundant predators (Shepperd et al. 2006, p. 43). This is compounded by the absence of natural fires and active management (p. 49) and through livestock grazing (p. 67). Options to promote aspen regeneration include removal of competing vegetation (such as conifers), protection from browsing (through permanent or temporary fencing), prescribed fire, or a combination of the above (Shepperd et al. 2006, p. 81-86). Utilizing partners like the Maidu and Washoe tribes to aid in the design and implementation of restoration projects helps to increase the use of TEK in land management decisions, increase tribal management of ancestral lands, and increase the diversity of restoration perspectives in land management. There are numerous other recommendations to improve the sustainability of elk management on the Plumas National Forest (Table 4).

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Table 4: Elk management issues and recommended actions to improve elk habitat management and sustainability.

Management Issue Impacts to Actions to Potential Level sustainability Increase Results Sustainability Herd Research Unknown There can be Study the abundance A better population competition between over time and track understanding of size livestock and elk for demographic changes. potential grazing forage that may conflicts, forage, negatively impact and potential both species. impacts to deer populations. Unknown It is difficult to Study the current range A better range and manage the landscape and track changes, understanding of distribution for elk without track signs of use, land use by elk can understanding their collar individuals. inform management distribution. actions for elk habitat management and other spatial considerations. Unknown Elk need woody Study where elk spend Increased winter important browse in the winter time during the winter survival by elk winter use to prevent starvation. months. through improved areas Grazing can reduce vegetation the amount of forage management available to elk during the winter, and elk can reduce the amount of forage available to cattle during the summer. Unknown Elk can be pushed out Study changes in elk Better management movement of suitable forage due movement and of when, how, and responses due to presence of cattle behavior when how many cattle to livestock and expend energy. domestic cattle grazing should be interactions season begins. introduced to the area. Unknown There may be human Place GPS collar on Improved ability to movement disturbance during multiple elk, overlay mitigate disturbance patterns and management this information with during management forest habitat activities, the USFS vegetation data. activities, improved use can improve elk vegetation habitat. management. Local Habitat Conifer Reducing Remove conifers Increased Management encroachment opportunities for (particularly western opportunities for at springs water sources and juniper) from springs, water, increased important forage in reintroduce fire to the stream flow. these areas. Creating area. concentration areas for elk and cattle conflicts.

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Management Issue Impacts to Actions to Potential Level sustainability Increase Results Sustainability Conifer Elk select aspen Aspen stand Improved winter encroachment stands over conifer improvement projects forage, calving sites, in aspen stands for many within the range of the and other elk stands activities and utilize elk herd, reducing habitat. aspen for winter conifers, and forage. Aspen stands reintroducing fire to are shrinking or the stand. disappearing from the case study area. High road Road densities are Reduce road densities Expansion of area densities negatively associated by closing and utilized by elk. with elk habitat and restoring roads to use. prevent use by the public.

Available Potential to over- Study the carrying Reduced impact to forage for utilize forage capacity of forage herbaceous, aspen, cattle and elk resources available to available to elk and and other forage these and other cattle, similar to Beck resources on the species. and Peek (2004). PNF. Social or Climate Reduced forage and Climate change policy Improved water Economic change water availability to and mitigation. availability to elk, elk domestic cattle, and all other species. Reduced Reduced capacity to Increased funding and Improved elk funding for understand and personnel to research habitat, improved research and manage elk habitat. elk habitat habitat for species habitat relationships, pursue that depend on the improvement elk habitat elk, such as the projects improvement projects. federally threatened wolf (Canis lupis).

Conclusions Robust populations of elk are relatively novel in the study area, at least in recent history. Previously, the PNF did not need to account for the habitat requirements of another large ruminant land mammal when managing the landscape for a variety of species and resource objectives. Elk habitat management is complex; effective management must account for ecological, social, economic, temporal, and spatial considerations involved. One of the ways the PNF can enhance its management of the landscape and elk habitat is to identify and protect calving areas. The Elk Calving Area Monitoring Program may be a feasible method to begin identifying these areas, but it is only the first step in increasing adaptive management in an area that is changing in wildlife and plant species composition, climate, and societal values.

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References Agee, James K. and Carl N. Skinner. 2005. Basic principles of forest fuel reduction treatments. Forest Ecology and Management 211 (1-2): 83-96. https://www.fs.fed.us/psw/publications/skinner/psw_2005_skinner(agee)001.pdf Allen-Diaz, Barbara; Barrett, Reginald; Frost, William; Huntsinger, Lynn; Tate, Ken. 1999. Sierra Nevada Ecosystems in the Presence of Livestock. A report to the Pacific Southwest Station and Region 5 USDA Forest Service. Rangeland Science Team Anderson, Stacy. CDFW Wildlife Biologist for Plumas and Sierra Counties. Personal Communications May 30, 2019. Bailey, J. K., & Whitham, T. G. 2002. Interactions among fire, aspen, and elk affect insect diversity: reversal of a community response. Ecology, 83(6): 1701-1712. https://doi.org/10.1890/0012- 9658(2002)083[1701:IAFAAE]2.0.CO;2 Barbknecht, A.E., Fairbanks, W.S., Rogerson, J.D., Maichak, E.J., Scurlock, B.M. and Meadows, L.L. 2011. Elk parturition site selection at local and landscape scales. The Journal of Wildlife Management, 75: 646-654. doi:10.1002/jwmg.100 Beaty, Matthew R. and Alan H. Taylor. 2008. Fire history and the structure and dynamics of a mixed conifer forest landscape in the northern Sierra Nevada, Lake Tahoe Basin, California, USA. Forest Ecology and Management 255 (3-4): 707-719. https://doi.org/10.1016/j.foreco.2007.09.044 Beck, J. L., and J. M. Peek. 2004. Jarbidge elk herd habitat evaluation: Nevada Department of Wildlife hunt unit 072. Final research report. Department of Fish and Wildlife Resources, University of Idaho, Moscow, Idaho, USA. 172 pp. Beck, J. L., Flinders, J. T., Nelson, D. R., Clyde, C. L., Smith, H. D., & Hardin, P. J. 1996. lk and domestic sheep interactions in a north-central Utah aspen ecosystem. United States Department of Agriculture, Research Paper INT-RP-491.

Bell, M.M, and L.L. Ashwood. 2016. An Invitation to Environmental Sociology (5th ed). Thousand Oaks, California: Sage. Biggs, J. R., VanLeeuwen, D. M., Holechek, J. L., & Valdez, R. (2010). Multi-scale analyses of habitat use by elk following wildfire. Northwest Science, 84(1): 20-32. https://doi.org/10.3955/046.084.0103 Bond, Monica L. 2015. Chapter 4 - Mammals and Mixed- and High-severity Fire. In The Ecological Importance of Mixed-Severity Fires. Elsevier. 89-117. Brook, S.M., Pluháček, J., Lorenzini, R., Lovari, S., Masseti, M., Pereladova, O. & Mattioli, S. 2018. Cervus canadensis (errata version published in 2019). The IUCN Red List of Threatened Species 2018: e.T55997823A142396828. https://dx.doi.org/10.2305/IUCN.UK.2018- 2.RLTS.T55997823A142396828.en. Downloaded on 17 March 2020. California Department of Fish and Game. 2003. Atlas of the Biodiversity of California. California Department of Fish and Game:United States. California Department of Fish and Game. 2011. Gray Wolves in California: An evaluation of historical information, current conditions, potential natural recolonization, and management implications. https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=76636&inline California Department of Fish and Wildlife. 2018. Elk Conservation and Management Plan. https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=162912&inline

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Christensen, N.L., Bartuska, A.M., Brown, J.H., Carpenter, S., D'Antonio, C., Francis, R., Franklin, J.F., MacMahon, J.A., Noss, R.F., Parsons, D.J., Peterson, C.H., Turner, M.G. and Woodmansee, R.G. 1996, The Report of the Ecological Society of America Committee on the Scientific Basis for Ecosystem Management. Ecological Applications, 6: 665-691. doi:10.2307/2269460 Cook, John. 2002. Chapter 5: Nutrition and Food. In North American Elk: Ecology and Management. Washington D.C.: Smithsonian Institution Press. Cooperider, Allen. 2002. Chapter 11: Elk and Ecosystem Management. In North American Elk: Ecology and Management. Washington D.C.: Smithsonian Institution Press. Diffenbaugh, N. S., Swain, D. L., & Touma, D. 2015. Anthropogenic warming has increased drought risk in California. Proceedings of the National Academy of Sciences, 112(13): 3931-3936. Eisenberg, C., Hibbs, D. E., Ripple, W. J., & Salwasser, H. 2014. Context dependence of elk (Cervus elaphus) vigilance and wolf (Canis lupus) predation risk. Canadian journal of zoology, 92(8): 727-736. Eisenberg, Cristina. 2019. Courtesy Faculty, College of Forestry, Oregon State University. Eisenberg, C., Anderson, C. L., Collingwood, A., Dunn, C. J., Meigs, G. W., Hibbs, D. E., ... & Little Bear, L. 2019. Out of the Ashes: Effects of Extreme Wildfire, Prescribed Burns, and Indigenous Burning on Ecosystem Structure and Diversity. Frontiers in Ecology and Evolution, 7: 436. Frisina, M. R. 1992. Elk habitat use within a rest-rotation grazing system. Rangelands Archives, 14(2): 93-96. Graham, Russell T., Sarah McCaffrey, and Theresa B. Jain. 2004. Science basis for changing forest structure to modify wildfire behavior and severity. USDA Forest Service, Rocky Mountain Research Station, General Technical Report RMRS-GTR-120. Holland, Tom. 2005. Rocky Mountain Elk Species Assessment. Grand Mesa, Uncompahgre, and Gunnison National Forests. Halofsky, J. S., & Ripple, W. J. 2008. Fine-scale predation risk on elk after wolf reintroduction in Yellowstone National Park, USA. Oecologia, 155(4): 869-877. Innes, Robin J. 2011. Cervus elaphus. In: Fire Effects Information System. U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fire Sciences Laboratory (Producer). Available: www.fs.fed.us/database/feis/mammal/ceel/all.html Iowa Environmental Mesonet. 2019. Coyote-Thompson Valley Station Data and Metadata. https://mesonet.agron.iastate.edu/sites/monthlysum.php?station=CYVC1&network=CA_DCP Johnson, Douglas. 1980. The comparison of usage and availability measurements for evaluating resource preference. Ecology 61: 65-71. Johnson, Bruce K.; Wisdom, Michael J.; Cook, John G. 2004. Issues of elk productivity for research and management. In: Transactions of the 69th North American Wildlife and Natural Resources Conference: 551- 571 Johnson, K.N., Franklin, J.F., Johnson, D.L. 2008. A plan for the Klamath Tribes’ management of the Klamath Reservation Forest. http://klamathtribes.org/documents/Klamathtribes_forestmanagement_plan.pdf Lake, Frank. 2013. Historical and Cultural Fires, Tribal Management and Research Issue in Northern California: Trails, Fires, and Tribulations. Occasion: Interdisciplinary Studies in the Humanities, 5(5). https://www.fs.usda.gov/treesearch/pubs/44867

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Laudenslayer, William F.; Darr, Herman H. 1990. Historical effects of logging on forests of the Cascade and Sierra Nevada ranges of California. 1990 Transactions of the Western Section of the Wildlife Society. pp 12- 23. Lehman, C. P., Rota, C. T., Raithel, J. D. and Millspaugh, J. J. 2018. Pumas affect elk dynamics in absence of other large carnivores. Jour. Wild. Mgmt., 82: 344-353. doi:10.1002/jwmg.21392 Sheehy, Dennis P, and Martin Vavra. 1996. Ungulate Foraging Areas On Seasonal Rangeland In Northeastern Oregon. Journal of Range Management 49(1): 16. Web. Journal Of Range Management. Lund, J., Medellin-Azuara, J., Durand, J., & Stone, K. 2018. Lessons from California’s 2012–2016 drought. Journal of Water Resources Planning and Management, 144(10), 04018067. Lyon, L. Jack, and Christensen, Alan G. 2002. Chapter 13: Elk and Land Management. In North American Elk: Ecology and Management. Washington D.C.: Smithsonian Institution Press. Mayer, Kenneth and Laudenslayer, William. 1988. A Guide to Wildlife Habitats of California. Department of Fish and Game: Sacramento, CA. McKelvey, K.S., Skinner, C.N., Chang, C., Erman, D.C., Husari, S.J., Parsons, D.J., van Wagtendonk, J.W., Weatherspoon, C.P.. 1996. An overview of fire in the Sierra Nevada. In Sierra Nevada Ecosystem Project: Final report to Congress, vol. II: Assessments and scientific basis for management options. Water Resources Center Report No. 37. Centers for Water and Wild- land Resources, University of California, Davis, pp. 1033–1040. Middleton, A. D., Kauffman, M. J., McWhirter, D. E., Jimenez, M. D., Cook, R. C., Cook, J. G., ... & White, P. J. 2013. Linking anti‐predator behaviour to prey demography reveals limited risk effects of an actively hunting large carnivore. Ecology Letters, 16(8): 1023-1030. Morris, M.S., 1956. Elk and livestock competition. Journal of Range Management, 9(1), pp.11-14. Nevada Division of Wildlife. 1997. Elk Species Management Plan. National Oceanic and Atmospheric Administration. 2019. California Drought 2011-2017: A Story Map. https://www.arcgis.com/apps/Cascade/index.html?appid=0307d687789c4d1cbec397d0abc2fffc. Accesssed October 2019. Parsons, David J. and Steven H. DeBenedetti. 1979. Impact of fire suppression on a mixed-conifer forest. Forest Ecology and Management. 2: 21-33. https://doi.org/10.1016/0378-1127(79)90034-3 Phillips, Gregory, and Willian Alldredge. 2000. Reproductive success of elk following disturbance by humans during calving season. The Journal of Wildlife Management 64(2): 521-530. https://www.jstor.org/stable/3803250 Pitman, James; Cain III, James; Liley, Stewart; Gould, William; Quintana, Nicole; and Ballard, Warren. 2014. Post-parturition habitat selection by elk calves and adult female elk in New Mexico. The Journal of Wildlife Management 78(7): 1216-1227. Poole, K. G., & Mowat, G. 2005. Winter habitat relationships of deer and elk in the temperate interior mountains of British Columbia. Wildlife Society Bulletin, 33(4): 1288-1302. Pruvot, M., Musiani, M., Boyce, M. S., Kutz, S., & Orsel, K. 2020. Integrating livestock management and telemetry data to assess disease transmission risk between wildlife and livestock. Preventive veterinary medicine 174: 104846.

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Ricketts, T.H., Dinerstein, E., Olson, D.M., Eichbaum, W., Loucks, C.J., Kavanaugh, K., Hedao, P., Hurley, P., DellaSalla, D., Abell, R. and Carney, K. 1999. Terrestrial Ecoregions of North America: A Conservation Assessment. Island Press: Covelo, California. Rost, G., & Bailey, J. 1979. Distribution of Mule Deer and Elk in Relation to Roads. The Journal of Wildlife Management, 43(3), 634-641. doi:10.2307/3808741 Shively, Kirk, Alldredge, A. William, and Phillips, Gergory E. 2005. Reproductive response to removal of calving season disturbance by humans. The Journal of Wildlife Management 69(3): 107-1080. https://www.jstor.org/stable/3803346 Shepperd, W., Rogers, P., Burton, D., and Bartos, D. 2006. Ecology, Biodiversity, Management, and Restoration of Aspen in the Sierra Nevada. United States Department of Agriculture General Technical Report RMRS-GTR-178. Simpson, N.O., Stewart, K.M., Bleich, V.C.. 2011. What have we learned about water developments for wildlife? Not enough!. California Fish and Game 97(4): 190-209. Skovlin, Jon M.; Zager, Peter; and Johnson, Bruce K. 2002. Chapter 12: Elk Habitat Selection and Evaluation. In North American Elk: Ecology and Management. Washington D.C.: Smithsonian Institution Press. Smallidge, S. T., Halbritter, H. J., Baker, T. T., Ashcroft, N. K., Cram, D. S., & Fowler, J. M. 2015. Elk and Livestock in New Mexico. New Mexico State University, Cooperative Extension Service and Agricultural Experiment Station. Thompson, Don. 2004. Rocky Mountain Elk make tracks in California. Los Angeles Times. Accessed April 27, 2019. https://www.latimes.com/archives/la-xpm-2004-aug-29-adme-elk29-story.html Thomas, Jack Ward; Black, Hugh; Scherzinger, Richard; Pedersen, Richard. 1979. Chapter 8: Deer and Elk. In Wildlife Habitats in Managed Forests for the Blue Mountains of Oregon and Washington, ed. Jack Ward Thomas. USDA Agricultural Handbook No. 553. https://www.srs.fs.usda.gov/pubs/misc/agh553.pdf Treadaway, Michael ; Howard, V.W. Jr.; Allison, Chris D.; and Boren, Jon C. 1997. Elk vs. Livestock: Forage utilization study in portions of the Gila National Forest. Great Plains Wildlife Damage Control Workshop Proceedings. 379. United States Department of Agriculture. 1988. Land and Resources Management Plan. Plumas National Forest. United States Department of Agriculture. 1989. Draft Environmental Impact Statement, King-Titus Fire Recovery Project, Klamath National Forest. Unites States Department of Agriculture. 1996. Upper Deschutes Wild and Scenic River Record of Decision, Final Environmental Impact Statement. Unites States Department of Agriculture. 1999. Draft Environmental Impact Statement for Proposed Agua/Caballos Projects. United States Department of Agriculture. 2004. Sierra Nevada Forest Management Plan, Record of Decision. United Stated Forest Service, Pacific Southwest Region, 046. United States Department of Agriculture. 2006. White River National Forest Travel Plan: Environmental Impact Statement. United Stated Department of Agriculture. 2013 Ecological Restoration Implementation Plan. United States Forest Service, Pacific Southwest Region R5-MB-249.

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United States Fish and Wildlife Service. 2014. Rocky Mountain Elk. Cold Springs National Wildlife Refuge. Accessed January 29, 2020. https://www.fws.gov/refuge/Cold_Springs/Wildlife_Habitat/Elk.html United States Forest Service. 2005. FSM 2600 – Wildlife, Fish, and Sensitive Plant Habitat Management. Forest Service Manual. Vore, J. M., & Schmidt, E. M. 2001. Movements of female elk during calving season in northwest Montana. Wildlife Society Bulletin 29(2): 720-725. Vucetich, J. A., Smith, D. W., & Stahler, D. R. 2005. Influence of harvest, climate and wolf predation on Yellowstone elk, 1961-2004. Oikos, 111(2): 259-270. Weatherspoon, C. P., & Skinner, C. N. 1996. Fire-silviculture relationships in Sierra forests. In Sierra nevada ecosystem project: final report to congress (2): 1167-1176. Yeo, J., Peek, J., Wittinger, W., & Craig T. Kvale. 1993. Influence of Rest-Rotation Cattle Grazing on Mule Deer and Elk Habitat Use in East-Central Idaho. Journal of Range Management, 46(3), 245-250. doi:10.2307/400261

29

Appendix A: Elk Calving Area Survey Protocols Plumas National Forest, United States Forest Service

Developed by Abigail Marshall Oregon State University Graduate Student USFS Wildlife Technician

With guidance and input from Brenda McComb, Cristina Eisenberg, Matthew Jedra, Rachel Bauer, Kelly Mosinski, and Debbie Bliss.

Elk Calving Protocols

1

Elk Calving Protocols

Table of Contents

Summary ...... 1 Site Selection ...... 8 Sites with more than one spring present ...... 8 Springs outside the SIA ...... 9 Adding new sites to the Survey Layer ...... 9 Camera Deployment, Setup, and Monitoring ...... 10 Timing of Survey ...... 10 Pre-field equipment checklist ...... 10 Camera deployment ...... 11 Pellet Surveys After the Calving Period ...... 13 Creating Transects in ArcMap ...... 15 Walking variable-width transects ...... 16 Camera Survey Results Data Sheet Instructions ...... 19 Data storage ...... 22 Photo storage ...... 22 File organization ...... 22 Data entry ...... 22 Microsite Data ...... 23 Canopy Cover, Downed Logs, and Herbaceous Cover ...... 24 Tree Species, DBH, Basal Area, and Trees per Acre ...... 25 Aspen Condition Form: ...... 27 Macrosite Data ...... 30 Appendices ...... 32 Appendix B: Site Selection Methodologies ...... 32 Appendix C: Camera Survey Results ...... 35 Appendix D: Elk Program Pellet Survey ...... 37 Appendix E: Calving Micro-Site Condition ...... 39 Appendix F: Calving Macrosite Condition Form ...... 44

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Elk Calving Protocols

Summary Introduction A small population of Rocky Mountain elk (Cervus canadensis nelsoni) roams over the eastern Plumas National Forest (PNF). Elk on the PNF are relatively novel; while there are sporadic observations of individual elk on the PNF throughout the 1980s and 90s, there have been numerous incidental sightings since the mid-2000s that indicate that the elk population is quickly growing on the PNF. However, there is little information regarding elk abundance, including the numbers of bulls, cows, and calves, or the area used by the elk. This study should contribute to a greater understanding of elk habitat use in the PNF through the identification of calving areas and calving habitat variables related to site selection. According to the PNF’s Land and Resource Management Plan (LRMP) (USDA 1988) and the Forest Service Manual (USFS 2005), wildlife management objectives on the PNF include (1) maintaining minimal viable populations of all species, (2) minimizing negative impacts of management activities on wildlife, and (3) enhancing wildlife habitat for a variety of species. Maintaining stable or growing elk populations helps to achieve these goals and is greatly influenced by reproduction and survival of cows and calves. Sustainable elk management also contributes to sustainable wolf management (Cooperider 2002, p.518). The federally-threatened wolf (Canis lupus) is moving back into its historical range on the PNF. As wolves are a secondary consumer, one important aspect of effectively managing wolf habitat involves management of their prey base, including elk (Cooperider 2002, p. 518). Elk conservation and habitat management can be enhanced on the PNF through the identification and protection of important calving areas. Pregnant female elk that are about to give birth may separate from the herd, give birth, and then raise the young independently before rejoining the herd (Skovlin 2002 p. 545). Disturbances during the calving period, such as livestock grazing or mechanical equipment conducting vegetation treatments, can cause cows and calves to move, expending resources and potentially exposing them to predation, and disturbances are associated with reduced calf:cow ratios (Innes 2011). There are multiple grazing allotments that are grazed annually and a landscape-scale vegetation treatment project overlapping the study area that is in the planning phase in 2020 and will likely be implemented between 2020-2030. Identifying important calving areas would allow the USFS to avoid disturbances to these areas during the calving period and gather information on elk reproductive behaviors within the study area. Based on the data gathered from this study, there is potential for livestock grazing, various vegetation management activities, and other activities to be deferred until after the critical calving period in these areas. Additionally, the PNF can identify areas where elk habitat improvement projects would be most beneficial and provide information to guide management prescriptions to meet desired conditions for calving. Information on calving behavior of cow elk, including the degree of isolation behavior, can help inform the PNF of management impacts and contribute to a greater understanding of reproductive behavior by elk throughout their geographic range. Additionally, incidental observations of elk throughout the year can provide preliminary data on the herd’s population and identify areas where elk congregate, which could facilitate the collaring of individuals for future research (Anderson 2019). Calving information can also be shared with partners as part of a multi-

1

Elk Calving Protocols stakeholder adaptive management effort. Gathering preliminary information can enable the USFS to facilitate and guide future research on elk for the PNF. Study Area The initial study area used to develop these methods is approximately 30,000 acres (12,141 hectares) on the Beckwourth Ranger District of the Plumas National Forest, north of Red Clover Valley. I determined this area based on a high number of incidental elk observations (42 observations from various sources at the time of delineation) and because elk reproduction on the forest has known to occur here, gathered as incidental information by both the USFS and CDFW. Because the range of elk on the PNF is more amorphous than previously believed, these methods can be utilized throughout the eastern PNF in areas where elk occur or are suspected to occur. Any existing observations made by PNF wildlife personnel, the CDFW, and members of the public, tracked in the National Resource Information System (NRIS), can be used to identify areas that may warrant survey outside of the initial study area. These observations begin in 2012. Water is usually found within 1000ft (305 meters) of calving sites (Thomas et al. 1979, p. 120) and elk typically have a high preference for habitat areas located within 0.25 miles (0.41 km) of permanent water sources (Skovlin 2002 p. 544). Within the Study Area, springs comprise the majority of the perennial water available to elk. The monitoring program will allow the USFS to monitor potential calving areas that are in active grazing allotments or are within planned project areas, using cameras and stand searches to document evidence of use by elk cows and their calves at springs. Areas that are located along intermittent waterways that may be flowing during the calving season will not be surveyed due to feasibility issues.

Figure 1: Map of the initial Study Area in the PNF in 2019.

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Elk Calving Protocols

There are four major components to the program: 1) a camera survey at study sites (springs that are perennial water sources) to identify areas utilized by cow/calf pairs, 2) a walking survey to search for pellets to help validate the camera data, 3) site vegetation data gathered on the microsite scale, 4) site management history and vegetation data at a larger macrosite scale. The objective of this study is to conduct intensive monitoring of spring sites in order to identify important calving areas and gather incidental population information for an elusive elk population. Springs are buffered by 984-ft (300-m) to create a study site. Study sites that have more than one spring may be larger than those without as they will be grouped due to the close proximity. A camera will be placed at only one of the springs within the study site, but a transect pellet survey will be conducted throughout the study site. The microsite is a 984-ft (300-m) radius around whichever spring was surveyed using a camera and will contain four plots to sample vegetation. The macrosite will be a 3280-ft (1-km) radius plot centered on the spring that was surveyed using a camera.

Figure 2: Map of the general survey layout. In this example, sites 6 and 7 would be due for survey. Cameras would be placed near a spring within the site from August 1 to July 15. When surveyors pick up the cameras, they will walk transects throughout the study site to search for pellets. Additional data will be gathered over two scales: 1) surveyors will establish plots within the microsite where they will collect data that can be used to describe calving habitat for elk and 2) surveyors will identify site characteristics within the macrosite spatially using GIS.

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Elk Calving Protocols

Identification of calving areas has immediate benefit to the USFS. There are opportunities to minimize disturbances to these areas during the critical calving period and data can contribute to analysis of vegetation treatments on wildlife species, as well as identify areas for potential elk habitat improvement projects. Once a significant number of calving areas are identified, the micro- and macrosite data can be analyzed using discriminant function analysis or cluster analysis to determine which site characteristics appear to differentiate sites that were used for calving compared to those for which no use was detected. The number of sites needed to be able to document selection will be dependent on the number of microsite variables measured and on the desired confidence with which differentiation can be detected (effect size). The pilot studies I conducted in 2019 (see below) did not gather enough information to run a power analysis to identify the desired sample size where further study of the calving habitat variable could be successful. A power analysis would need to be conducted to estimate the desired sample size to detect biologically meaningful differences in the variables gathered between sites used as calving areas and sites that are unused. Camera Surveys While telemetry and GPS studies may offer more information on elk calving and movements, there are vast logistical and financial constraints that prevent the PNF from being able to implement this type of project. However, as cows and calves have limited mobility during the first few weeks after birth, the PNF can identify key areas where calving activity occurs and begin gathering data related to site selection. Photographs of a cow and calf pair at a study site can help to identify these areas. Camera surveys will be conducted at springs each year, the number of which correspond to the type of project and abilities of the PNF. Each site will be surveyed for up to one year. During the summer and fall seasons, the cameras will be checked every 2-3 weeks to gather photo data and check the camera status, adjusting the angle or other settings to ensure optimal detections while minimizing triggers by vegetation or light. The cameras will remain through winter and spring before being picked up in mid-July after the calving period (as soon as possible after July 15). At that time pellet searches (see below) will be conducted. All of the cameras in the Beckwourth Wildlife Department are Bushnell Trophy Cam Aggressor infrared cameras. I completed all pilot study work (see section on Pilot Studies below) with these cameras. Once triggered, one 8-megapixel photograph will be taken every 3 seconds as long as what triggered the camera remains in the view. While the camera is capable of higher resolution photos, keeping the megapixels lower saves space on the SD card. Pellet Surveys Pellet searches will be conducted after the calving period to help verify photo data. Typical pellet surveys cover large areas and are used to estimate population size; that is not the goal of the protocols and there is too much bias to gather it as incidental information due to deviation from random habitat patterns and by having variable study site sizes (Dobrowski and Murphy 2006). This study uses variable-width transect pellet surveys to detect presence of fresh elk pellets (based on decay class, see Table 4 on page 16) at the site to help validate camera data. If there are no elk detections on the camera placed at the site, but there are fresh elk pellets, then the camera data may not be representative of the site use, particularly if there is more than one spring within the study site. Calf pellets that may be observed during the stand search can act as a secondary way to understand use of the site by a cow and calf. If there are photographs of elk, but no pellets are

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Elk Calving Protocols identified, then the pellet survey methodology may need to be adjusted. While it is difficult to prove absence of elk at the site, if there are no camera detections of elk and no pellets are identified, biologists at the PNF can be highly confident that the site was not used as a calving area. Between the camera data and the stand searches, there are several indicators that may denote a positive identification of an important calving area during the critical calving period (see Page 10): 1. A single adult female elk and a single calf are captured on camera. a. Record in the notes on the data sheet the frequency by which the observations take place. 2. A single elk calf is observed on camera. 3. A single adult female elk is observed at the spring multiple times and no elk calf is observed. a. Calves may hide within the study site and may not captured on camera, so isolation behavior of the cow elk can act as an indicator. b. While there are not definitive ways of ensuring that it is the same cow, rather than different single females visiting the spring, this isolation behavior would still indicate that calving had occurred and that the area is suitable for calving. 4. Multiple adult female elk and multiple calves are observed at the spring in May or June. a. Not all Rocky Mountain elk demonstrate isolation behavior, such as those in the Rocky Mountains. This type of behavior on the PNF would be notable. 5. Calf pellets of decay class 1 or 2 observed during the stand search (Jung and Kukka 2016).

Microsite Data Microsites are 984ft (300m) radius circles will be created around the spring that was camera surveyed. Surveyors will return to the site, measure vegetation and site characteristics and complete a Microsite datasheet. Surveyors will install four plots, one centered on the springhead and three others that are randomly located within the microsite. Canopy cover, herbaceous cover, aspen (Populus tremuloides) stand condition, and tree composition, size, and density will be measured. Macrosite Data Macrosites are 3,280ft (1km) radius circles created around the spring that was camera surveyed. This buffer allows for multiple days of estimated cow movements within a site (Vore and Schmidt 2001), allows for incorporation and investigation of connectivity based on the number of springs and other water features present, and places the calving area within a larger context of site selection. For positively identified calving areas, vegetation information, road and stream densities, and management histories will be gathered spatially through GIS and by contacting rangeland, archeology, fuels, and timber specialists in the PNF. The macrosite allows for a biologist or land manager to quickly assess the rangeland and vegetation management opportunities. Program Folders The program folder and photo data will be kept on Pinyon, a USFS cloud-storage program, with backups of photographs on an external hard drive. Shapefiles are kept in a folder on the T- drive (also cloud-based storage). Pilot Studies In 2012, PNF biologists placed a camera at a spring site during the critical calving period by and successfully identified an important calving area. The CDFW used cameras to successfully

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Elk Calving Protocols confirm that the area was still utilized as a calving area in 2015. Throughout 2019, I conducted various pilot projects to optimize survey results. Further pilot studies in 2020 could help refine the protocols. Another PNF biologist and I put cameras at two test sites from November 2018 to May 2019; one xeric site with mountain mahogany (Cercocarpus ledifolius) and one developed spring. The xeric site had 3,542 photos, 26 wildlife photos, and no observations of elk (vegetation movement triggered the camera frequently). The developed spring had 286 photos, with 6 events of elk visits (64 total photos), and a total of 31 wildlife observation events (163 photos). We also placed a camera at a small meadow adjacent to a spring within a known calving area from November 2018 to July 20, 2019. At this site, 212 photos were taken, with 4 elk events (16 photos total) and 18 general wildlife events (52 photos). While no calving activity was observed, this may be due to the placement or angle of the camera within the site. All camera batteries and SD cards lasted throughout the survey period. Four cameras are being tested at four study sites from November 2019 to July 2020 to further refine any issues. Two PNF biologists and I placed three cameras at a study spring and known calving area to test optimal placement of cameras within a study site, from August 7, 2019 to October 1, 2019; however, one camera malfunctioned and stopped recording on September 9. We placed two cameras at the top of the springhead at two different angles, and one camera at pool within the spring channel approximately 330ft (100 meters) from the springhead. The camera that was at the springhead (and functioned the entire survey period) detected only two elk observations (and captured 15 photos of elk), while the camera at the pool detected six events at the spring channel (with 30 photos of elk). See “Camera deployment” on page 11 for further information. I determined transect spacing for pellet surveys after conducting variable-width transects spaced 330 ft (100 m) apart within two different study sites, walking a total of 3.9 mi (6.1 km). I encountered 62 pellet groups for a detection rate of 15.9 pellet groups/mile (10.1 pellet groups/km). The objective of the pellet survey is to detect presence, not changes in population density, and with an encounter rate of 330 ft/pellet group (100 m/pellet group), 1.694mi ( 2,727 meters) per site (for sites with single springs) allows for high confidence that surveyors will encounter pellet groups if they are present at the site. Because the sites vary in size, this provides a baseline; larger study sites will have proportionately larger coverage. See page 13 for more information on transect spacing. I workshopped the microsite protocols over the two known calving areas. I conducted preliminary tests with the assistance of two other biologists at one calving area and then refined the protocols. Another biologist and I conducted two out of four plots at the other known calving area and refined the protocols again. Four biologists tested various canopy cover methods over a plot in a test site to determine optimal canopy cover methods.

References Anderson, Stacy. CDFW Wildlife Biologist for Plumas and Sierra Counties. Personal Communications May 30, 2019. Innes, Robin J. 2011. Cervus elaphus. In: Fire Effects Information System. U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fire Sciences Laboratory (Producer). Available: www.fs.fed.us/database/feis/mammal/ceel/all.html

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Jung, Thomas S.; Kukka, Piia M. 2016. Influence of habitat type on the decay and disappearance of elk Cervus canadensis pellets in boreal forest of northwestern Canada. Wildlife Biology, 22(4), 160-166. Thomas, Jack Ward; Black, Hugh; Scherzinger, Richard; Pedersen, Richard. 1979. Chapter 8: Deer and Elk. In Wildlife Habitats in Managed Forests for the Blue Mountains of Oregon and Washington, ed. Jack Ward Thomas. USDA Agricultural Handbook No. 553. https://www.srs.fs.usda.gov/pubs/misc/agh553.pdf Cooperider, Allen. 2002. Chapter 11: Elk and Ecosystem Management. In North American Elk: Ecology and Management. Washington D.C.: Smithsonian Institution Press. United States Department of Agriculture. 1988. Land and Resource Management Plan. United Stated Forest Service, Pacific Southwest Region. United States Forest Service. 2005. FSM 2600 – Wildlife, Fish, and Sensitive Plant Habitat Management. Forest Service Manual.

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Site Selection The initial study area focused on spring sites within a core area of use by elk, where there have been frequent observations of multiple subherds and where reproduction has been known to occur. I determined the initial study area (also known as the survey inference area or SIA) based on observations of elk (found in NRIS, the National Resource Information System), PNF boundaries, and topography such as large cliff faces or ridgetops. As new potential study sites are identified, the layer can be edited to include the new study sites. I clipped the Beckwourth Ranger District shapefile for Springs, located within the T-Drive, to the SIA. Elk generally avoid areas within 656 ft (200 m) of major roads (Rost and Baily 1979). Springs that are within 656 ft (200 m) of major roads (such as the Dixie Valley road or the Janesville Grade) or private homes are not likely to be suitable calving sites due to the number of vehicles and should be removed from the survey schedule. Additionally, spring sites that do not have standing water should be removed from the survey schedule. Suitable springs are perennial water features have surface water available. Sites that are in large open meadows without cover or trees on which to place cameras will not be surveyed due to camera security issues. Once the Beckwourth Ranger District can purchase supplies to better secure camera equipment they may be surveyed. Fortunately, the wide-open meadows are not likely to be optimal calving areas due to the lack of hiding and thermal cover for both the cow and calf, at least until wolf populations indicate changes in elk behavior. Springs that are in close proximity to one another will be grouped into one study site (see Appendix A for methods). Any springs with overlapping 984 ft (300 m) buffers will be merged into one study site (see Figure 3 under Pellet Surveys). When the site is due for survey, choose at random which spring within the site will have a camera, however, all springs within the site will be surveyed for pellets using transects after the calving period, starting mid-July. I identified 86 springs over a total of 44 study sites within the initial study area, but the exact number of springs may vary by the project area. Each study site will be assigned a tracking number and name unique to the project. The attribute table should contain a list of the number of springs located within the site, as well as comments for other known site names (if the spring has a name on the map). Determining the order of sites to be surveyed depends on project needs. For long-term monitoring within grazing allotments, a random number can be generated within a new field of the attribute table which can then be sorted by ascending, giving a random survey order. Sites that are to be monitored before vegetation treatment projects may require a more targeted approach; sites that will be implemented sooner than others may have a higher priority. A more in-depth breakdown of the methods used in ArcMap to generate the list of sites is provided in Appendix B. Sites with more than one spring present There are instances where there may be more than one spring within the study site (as they have been grouped together due to overlapping 984-ft or 300-m buffers). Not all springs within the PNF Springs layer have drinkable surface water for elk; if there are multiple springs identified within a site but only one has drinkable surface water, then survey the spring where water is available. If there are multiple suitable sites to survey, randomly select which spring will be surveyed. If the site

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Elk Calving Protocols was positively identified to be an important calving area (based on the criteria on page 5), then base the microsite and macrosite buffers around the spring that was camera surveyed. Springs outside the SIA It is beneficial to survey springs outside the SIA in areas where there are no previously reported observations to search for evidence of use by elk. Visiting these springs every 3 years can help track changes in distribution of elk. Buffer the SIA by 3,280 ft (1 km) and visit any springs within this buffer. Use the “Pellet Surveys Protocol” when visiting the site. If a spring is identified to be used by elk, continue to visit springs in this direction, in 1-km increments, until encountering a spring with no observations. Edit the SIA to include any springs that should be added to the schedule. Adding new sites to the Survey Layer • “Draw” a point over the new site and convert this to a feature. • Buffer the new feature by 300 m and dissolve all. • Use the Update Tool with the input as Survey_Sites and then select the new feature. Label this SurveySites_MonthYear so it is clear which version the most recent update. Save this shapefile in the project folder. • Edit the feature and add the next sequential Site_No. Add any other name associations. • Add the site to the survey schedule excel sheet. • Edit the Study Springs layer to add a new feature at the spring’s location. References: Rost, G., & Bailey, J. 1979. Distribution of Mule Deer and Elk in Relation to Roads. The Journal of Wildlife Management, 43(3), 634-641. doi:10.2307/3808741

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Camera Deployment, Setup, and Monitoring Timing of Survey The critical period for calving appears to be between April 15 – July 15. These time periods can be refined as we collect data on calving phenology within the study area and the degree to which isolation behavior by the cow and calf are occurring. the White River National Forest in Colorado maintains closures in calving areas from April 25 to June 21 (USDA 2006), the Deschutes National Forest in Oregon maintains closures from January to August 15 (USDA 1996), and the Carson National Forest in New Mexico maintains closures from May 1 to June 25 (USDA 1999). Starting a closure at April 15 allows for a buffer to mitigate disturbances to elk cows scouting sites before parturition and to account for the variations in geographic range until further phenology is identified. Additionally, there is incidental information of isolation behavior of a cow and calf within a calving area through early July captured on cameras by PNF biologists in 2012 and photographs from 2019 indicate that by July 16, the isolation period had ended. When a site is due for survey, cameras will be deployed in August of the survey year and remain at the site until after July 15 of the next year. During August – December (which may be variable depending on weather), cameras should be visited every 2-3 weeks to make adjustments to cameras or adjust vegetation that may be triggering the camera. Data gathered during this period can inform us on site use during the fall season, but is not critical for capturing information on calving, so if cameras cannot be deployed until September or October, this may still be acceptable. Sites may or may not be accessible once the snow falls during the winter months or into the spring before calving, so it is important to make sure the cameras are in optimal position before the winter to prevent the SD cards from filling up and to make the batteries last throughout the survey period. Pre-field equipment checklist • Cameras – as many as are intended to set that day/session. Bring a spare if possible. All of the BKRD’s cameras are “Bushnell Trophy Cam Aggressor” • Compass – To help position cameras away from direct sunlight • Data entry sheets • Batteries – Spares for replacing during site follow ups. Lithium batteries are preferred. • GPS device – To find the way to the initial camera location and mark the actual position. • Memory cards – One per camera for initial set up or and one per camera during follow ups, at least 32GB. • Camera (handheld) – To test memory cards and camera position • Notebook and pens • Gloves – to prevent scent transference • Locks, straps, and safety boxes – bring extra locks and straps to attach cameras to large diameter trees if necessary. • Camera straps – to attach cameras to trees • Hand saw – To help cut vegetation in front of camera • GPS locations of springs and map of area • Protocols

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Camera deployment • Camera placement: After identifying which spring will be surveyed put the camera as close to the springhead as makes logical sense, where there is surface water available for drinking and vegetation does not inhibit elk movement (that stays with the site). The objective is to maximize potential for elk observations while minimizing bias. In the additional comments portion, write why the camera placement was chosen. o There may be specific instances where the camera placement may not be at the springhead. In the case of Lava Spring, I placed cameras at the springhead and at a pool approximately 984 ft (100 m) down the channel with the assistance of two other PNF biologists. There was an abundance of vegetation at the springhead that frequently triggered the camera and hindered access by elk to the water. The number of elk observations (as well as other wildlife observations) at the pool in the channel was much higher than at the springhead, and there was much less triggering of the camera by vegetation. • Camera direction: Point camera northwards to prevent sunlight triggers whenever possible. • Camera height: Approx. 4-5 ft (1.2-1.5 m) off the ground (shoulder height for an elk calf) • Camera distance to target: ideally 15-30 feet (4.5-9 meters) o Measure the distance between the camera and the target and record this information for the data sheet. • Attach camera to a tree or similar surface using the straps. Adjust camera angle when necessary by using local materials wedged between camera and mounting surface. • Clear vegetation between camera and spring, or any vegetation that may trigger the camera. • Camera settings o Sensor Level: High o Number of photos per event (Capture Number in Menu): 1 photo per event o Time between photos: 3 seconds o Image size: 8 megapixels o Time: 24 hr mode o LED Control: Medium (<30 ft from lure), High (>30ft from lure) o NV Shutter: High o Field scan: Off o Check data and time with every deployment, after changing batteries, and at regular intervals when checking the cameras. o Camera Name: Ensure that the camera name corresponds to the label on the outside of the photo. ! This ensures that the camera setting and location will match, negating the need for a whiteboard to clarify the camera location and site name within a photo. • Record the date, time of deployment, camera name, and GPS the camera location. Testing the camera Place camera to “On” and put camera into case. Walk in front of camera several times, leaving the frame occasionally and visiting and leaving the spring. Then return to camera. Remove SD card and enter into handheld digital camera. Go through the photos to ensure that the trail

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Elk Calving Protocols camera is angled properly. Delete test photos. Test as many times and necessary until satisfied with the placement and angle. Return SD card to the trail camera and place camera on “On” before leaving the site. When finished testing the camera, use the lock around the camera and case to prevent theft. If the camera is placed in a position that may be difficult to find, take a photograph of the camera on the tree with the surrounding vegetation to make it easier to find in the future. Checking the camera Cameras should be checked every 2-3 weeks. Turn camera to off and remove SD card. Put SD card into handheld digital camera and ensure that camera is still at proper angle and has not been moved. If it is apparent that vegetation is making the camera deploy frequently, then remove the necessary vegetation or adjust the camera placement. Place a new SD card in the trail camera. Place old SD in a case and label the case with the date and time of pick up and camera number/site number. Ensure that cameras have at least 60% battery. If battery is low, replace all of the batteries. Ensure that the date is correct after changing batteries. Change the batteries in November or December to prepare for being unable to check the cameras until the following summer if necessary due to snow. Data sheets • Fill out camera location, deployment date and start time, camera distance to spring, and all other relevant information on the data sheet when returning from the field. References: Shively, Kirk, Alldredge, A. William, and Phillips, Gergory E. 2005. Reproductive response to removal of calving season disturbance by humans. The Journal of Wildlife Management 69(3): 107-1080. https://www.jstor.org/stable/3803346 United States Department of Agriculture. 1988. Land and Resources Management Plan. Plumas National Forest. Unites States Department of Agriculture. 1996. Upper Deschutes Wild and Scenic River Record of Decision, Final Environmental Impact Statement. United States Department of Agriculture. 2006. White River National Forest Travel Plan: Environmental Impact Statement.

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Pellet Surveys After the Calving Period Surveyors will walk transects throughout the study site. This is used to help validate camera data and gather information on pellet detection rates. The surveys will occur upon picking up the cameras as soon as possible after July 15. I conducted a pilot study to estimate the length of transects needed to sample the study sites. I walked variable width transects spaced 328 ft (100 m) apart at two different study sites. Surveying additional sites could help improve encounter rate averages over a greater range of sites; however, an active wildfire prevented visiting more sites at the time of the pilot study. I surveyed 3.9 miles (6.139 km) of transects, detecting 62 pellet groups, giving a detection rate of 15.9 pellet groups/mile (10.1 pellet groups/km) within the study sites. The following formula from Maisels and Aba’s (2010) allows us to estimate the length of transects needed:

3 � � = �! �

Where L is the total length of transect needed to survey per study site in order to detect population trends greater than Z percent (within the study sites) using X km surveyed during the pilot study and Y number of pellets encountered. Table 1 demonstrates the length of transects that would be required to survey to detect population changes larger than the given percentage. The objective of these pellet survey is to detect presence, not changes in population density, however, I chose 33% in order to utilize the formula as this should allow the PNF to detect presence with high levels of confidence while maintaining efficiency in survey efforts.

Table 1: Total survey lengths required for different values of Z, or population change, within the study sites.

% population Transect length Transect length change to survey (in km) to survey (in mi) 0.25 4.8 3.0 0.30 3.3 2.1 0.33 2.7 1.7 0.35 2.4 1.5 0.40 1.9 1.2 0.45 1.5 0.9 0.50 1.2 0.7

According to the formula, the single-spring sites should have at least 1.7 mi (2.7 km) of transect walked in order to cover the site. With an encounter rate of 330 ft/pellet group (100 m/pellet group), 1.7mi (2.7 km) per site allows for high confidence that surveyors will encounter pellet groups if they are present at the site. Because the sites vary in size, this provides a baseline; larger study sites will have proportionately larger coverage. I tested the following methods identified below at four different single-spring (and therefore same size) sites to estimate variations in total transect lengths per site.

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Table 2. Total miles of survey transect within 4 different sites based on the spacing between transects encountered using the fishnet method described below.

Test Site 295ft (150m) 410ft (125m) 328ft (100m) 246ft (75m) 1 1.2mi (2.0km) 1.3mi (2.1km) 1.7mi (2.7km) 2.3mi (3.734km) 2 1.1mi (1.8km) 1.3mi (2.1km) 1.7mi (2.7km) 2.3mi (3.731km) 3 1.1mi (1.9km) 1.4mi (2.3km) 1.8mi (2.8km) 2.4mi (3.8km) 4 1.2mi (1.9km) 1.3mi (2.1km) 1.7mi (2.8km) 2.4mi (3.8km) Mean 1.2mi (1.9km) 1.3mi (2.1km) 1.7mi (2.8km) 2.3mi (3.8km) SD 0.04mi (0.07km) 0.06mi (0.10km) 0.03mi (0.04km) 0.03mi (0.05km)

At a 328-ft (100-m)-transect spacing, total transect lengths averaged at 1.7 mi (2.8 km) with a standard deviation of 0.04mi (0.04km) (Table 2). Therefore, transects spaced at 330ft (100m) apart should provide adequate coverage to meet the requirements above. Additionally, I checked the ratios of transect lengths to acreage for two different sites of varying size to ensure that the method provided proportional coverage (Table ). In Figure 3 below, Site 1 had an area of 146 acres (59 hectares) and a transect length of 3.7 mi (6.0 km); while Site 2 had an area of 69 acres (28 hectares) and a transect length of 1.8 mi (2.9 km). The area of coverage is proportional to the transect length.

Table 3: Total transect length compared to area surveyed for five different study sites.

Site Transect Length Area (acres) Number of Springs 1 3.7mi (6.0km) 146 (59ha) 4 2 1.8mi (2.9km) 69 (28ha) 1 3 4.1mi (6.7km) 166 (67ha) 6 4 3.9mi (6.2km) 156 (63ha) 3 5 3.5mi (5.6km) 141 (57ha) 4

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Figure 3: Representation of transect configuration for two different sites, one with a single springhead and one with four springheads. Surveyors will walk the transects and record any pellet groups observed. For Site 1, the total transect length is 3.7mi (6.0km). For Site 2, the total transect length is 1.8mi (2.9 km). Creating Transects in ArcMap To create transects in ArcMap using the Fishnet Method: • Using the Study Sites layer, select the sites that will be surveyed and export these sites into a new layer named “PelletSurveySites_Year”. • In the toolbox, under Data Management Tools, select Sampling and “Create Fishnet.” • The output feature class can be named “PelletSurveyFishnet_Year.” • The Template Extent can be “Same as PelletSurveySites_Year” layer. • Under Cell Size Width put 50 and under Cell Height put 100. • Two new layers will appear. Under Under Analysis Tools choose Extract and then “Clip.” The input feature is the PelletSurveysFishnet_Year” (the grid, not the points), and save the new layer as “PelletSurveysTransects_Year.” Then, edit this new shapefile, open the attribute table, and delete the vertical lines within the grid. • Upload this shapefile onto a GPS unit. • Note: If walking north/south, rather than east/west, is desired due to topography, make the Cell Size Width 100 and the Cell Height 100, then delete the horizontal lines after clipping the fishnet to the site.

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Walking variable-width transects The variable-width transects refer to the width of the “belt” around the transect line itself, or the sight distance of the observer to the pellets. In areas lacking dense ground vegetation, observers can visibly detect pellets farther from the transect line than in areas where there is dense vegetation, such as the herbaceous vegetation along the spring channel, where there is a lower detection rate of pellets and a higher amount of observer bias (Dobroski and Murphy 2006). In areas of dense ground vegetation, to reduce detection bias, move some vegetation out of the way while walking to increase the visibility of pellets. Pellets are typically found in clumps or scattered groups depending on the movement of the elk while it defecated. There are also occasions where multiple pellet groups may be in close proximity, making it difficult to determine the exact number of pellet groups present. Try to determine the general center of a pellet group based on the densest area to differentiate between groups. Record any pellet groups (or a single pellet if only one is observed) from the transect line. Upon locating a pellet group, record the perpendicular distance between the transect line and the closest pellet (within the pellet group), the vegetation type where the pellet group was located, the height of the vegetation (if it is located in herbaceous vegetation), and the decay class of the pellets (Table 4). In addition to elk pellet groups, record any observations of deer pellet groups, using the same distance and decay class protocols. This incidental information could be used to help analyze elk and deer interactions at spring sites in the future. Record if fresh domestic cattle scat is present at the site, which can also offer insights into interactions between elk and cows, and record any other important scat or tracks, such as wolves, bears, or mountain lions. Searches should be conducted at a leisurely pace, allowing for ample time to scan the ground and vegetation for signs of elk use. Careful attention to location of adjacent observers and GPS units are important to maintain consistent spacing of individual transects. At the end of each transect the observers will stop and move to the start point of the next transect. Classifying vegetation Herbaceous vegetation can be classified into grasses, sedges, or rushes. In areas lacking herbaceous cover, record the substrate, such as litter (for open forest floors), rocks, bare soil, or if there is notable bitterbrush or sagebrush between the pellet group and transect. Estimating decay class The following table was taken from Jung and Kukka (2016). Table 4: How to determine decay class for pellets identified during the survey

Decay Class Pellet color shade Pellet cracking 1 Dark and wet, with a glossy Smooth surface patina 2 Dark but dry on surface, without Light cracking thinner than a hair patina 3 Dull Wider cracks (<1mm wide) 4 Grey Deep cracks (>1mm wide)

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A B

C D

Figure 4: Photographs of elk pellets and tracks taken in 2019. A) Adult elk pellets at one of the study sites (with inch scale) at decay class 2. B) Calf pellets at a known calving area on the PNF (with cm scale) at decay class 1. Pellets were located near adult pellets. C) Elk pellets at decay class 4 (with cm scale). D) Fresh calf tracks on a xeric site (with cm scale).

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Elk Calving Protocols

Other signs of use While not necessarily indicative of calving, note any additional use of the site by elk, including tracks and antler scrapings. Tracks can be difficult to detect in green vegetation. Additionally, antler scrapings from bulls do not help track calving, however, it is important to note all signs of use to help understand elk’s use of the site.

References: Jung, Thomas S.; Kukka, Piia M. 2016. Influence of habitat type on the decay and disappearance of elk Cervus canadensis pellets in boreal forest of northwestern Canada. Wildlife Biology, 22(4), 160-166. Dobrowski, S; and Muprhy, S. 2006. A practical look at the variable area transect. Ecology 87(7): 1856-1860. https://scholarworks.umt.edu/forest_pubs/30 Mandujano, S. 2014. PELLET: An Excel®-based procedure for estimating deer population density using the pellet-group counting method. Tropical Conservation Science Vol.7 (2): 308-325.. Available online: www.tropicalconservationscience.org

Maisels, F., and Aba'a R. 2010. Section 3: Survey design. M. Kühl H., F., Ancrenaz, M., and Williamson, E.A., editor. Best Practice Guidelines for Surveys and Monitoring of Great Ape Populations. IUCN Ape Species Specialist Group.

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Camera Survey Results Data Sheet Instructions I designed these data sheets to be utilized for a variety of camera surveys on the PNF. These data sheets are modified from several different carnivore camera datasheets currently utilized by the PNF. The NRIS carnivore data only applies to carnivore surveys and will not be utilized for the Elk Calving Program. Project • Enter the name of the project associated with the survey. o Examples: Elk Calving Program, Frenchman Forest Health Carnivore Surveys, etc… Station Information • Enter the project-specific site name or number and the camera name deployed at the site (which should be visible in every photo). • Enter the vegetation at the site. Use the vegetation descriptions listed in A Guide to Wildlife Habitats of California by Mayer and Laudenslayer (1988) as a guide. o Examples: ! “Aspen and wet meadow vegetation” ! “Aspen and western juniper” ! “Jeffrey pine and wet meadow vegetation” ! “Aspen and bitterbrush” • Enter the Lat/Long Locations of the camera where the photos were taken. • Enter the township, range, section, and ¼ section of the site. NRIS Carnivore Naming Convention (for data entry into NRIS) • When entering the data into NRIS, use the Carnivore Survey naming convention. • Project ID: Write the name of the project. • Unit ID.: o Upload the grid shapefile into ArcMap. ! Pathway on the T Drive: T:\FS\NFS\Plumas\Program\2600Wildlife\GIS\Data\BaseData\Beckwo urthRD\WildlifeSpecies\carnivores_nad83.mdb ! Use SAMPLE2 to determine Unit ID • Station ID: Find the highest number station already existing in that grid. Name the stations after the next available station number. • In NRIS, the naming convention for each site goes as follows: o Project Name (Unit ID ______) Station ____ o Example: Red Clover DFPZ Project (Unit ID 251307) Station 04 Survey Details • Enter the name of the person(s) physically visited the site to deploy the camera or changed SD cards • Enter the name of the person(s) who is is filling out the photo results in the data sheet. • Enter the survey period start date and time. • Enter the survey period end data and time.

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Elk Calving Protocols

• Spring/lure/bait/feature: whatever is being used to attract the wildlife to the camera, such as “Gusto” (the scent lure) or “guzzler” or “spring” or “game trail” o The elk calving project will only use natural or developed springs as the attracting feature. o Record if the spring is developed (if it has a springbox) • Write the species (such as elk) or species group (such as carnivore) that is the purpose of the camera study. Camera Settings • Height: The height above the ground at which the camera was placed • Distance to spring: The distance between the camera and the lure, spring, guzzler, etc… • Sensitivity: Low, medium, or high • Photos per trigger: How many photos were taken per triggering event • Delay: Time that restricts triggering events after the initial event • Camera Type: As of 2019, Cameras BkWild 1-8 are all “Bushnell Trophy Cam Aggressor” Results • If the survey period takes place during the winter, start with the first frame when the camera was deployed, which will not necessarily be the first photo visible in the folder if the folder sorts the data by image number. The first four numbers of the photo correspond to the month and day. Start filling the results chronologically. o For example, if a camera is left out from October 2018 to May 2019, the folder may open with the first photo from January first, as the file name would start with “0101…” instead of October. Double check that datasheets are filled in a chronologic order. • Write down the data for the first available frame and write “First Frame” in the contents section. • When finished capturing all the photo data on the sheet, for the final photo, write the photo information and “Final Frame” in the content section. • Enter the date and time of the observation, the photo ID number (to allow someone to find that photo in the folder) and any observations of wildlife or what triggered the camera. Do not record photos where it appears that light changes or vegetation set off the photo. • If there are an abundance of photos that are obviously from one individual or group staying in front of the camera for an extended period, without any gaps in time, write the time the observation started, then write the time the observation ended. If there is any uncertainty that it is not one continuous observation, then break the observation up into continuous observations and the events will be determined afterwards, per project specific protocols. • Save all wildlife photos captured in the secondary photo folder in Pinyon. Create a highlights folder within this folder, and copy any particularly notable photos, especially those of calves. • Write the location of where the photos are being stored.

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Table 5: Example of data sheet information. Date Start End Species Image IDs Comments Time Time 10/12/2018 1000 1000 Gray squirrel 10120322 Ran towards spring 10/12/2018 1020 1050 Black bear 10120323- Wallows in spring and scratches 10120356 on tree 10/12/2018 1130 1130 Steller’s jay 10120391 Steller’s jay flies to spring. 10/12/2018 1315 ____ Final Frame 10120450 Final Frame

Interpreting Photo Data Criteria for determining whether an observation indicates that the site is an important calving area may change as more information is gathered during the survey. Future efforts to survey positively identified sites multiple years in a row and examining nearby sites could help validate the importance of the site as a calving area and inform movement patterns. Some indicators that denote a positive identification of an important calving area could include: 1. A single adult female elk and a single calf are captured on camera. a. Record in the notes on the data sheet the frequency by which the observations take place. 2. A single elk calf is observed on camera. 3. A single adult female elk is observed at the spring multiple times and no elk calf is observed. a. Due to the isolation behavior of cow elk during the calving period, and the ability of calves to hide within the study site, calves may not be captured the calf on camera. Isolation behavior of the cow elk can act as an indicator. b. While there are not definitive ways of ensuring that it is the same cow, rather than different single females visiting the spring, this isolation behavior would still indicate that calving had occurred and that the area is suitable for calving. 4. Multiple adult female elk and multiple calves are observed at the spring in May or June. a. Not all Rocky Mountain elk demonstrate isolation behavior, such as those in the Rocky Mountains. This type of behavior on the PNF would be notable. 5. Calf pellets of decay class 1 or 2 observed during the stand search (Jung and Kukka 2016).

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Data storage

The program folder will be kept on the cloud in Pinyon. Photo storage Raw photo data should be stored in both an external hard drive and in Pinyon (a cloud-based platform used by the USFS). Upon retrieval of the SD cards, the photos will be uploaded onto an external hard drive as well as the designated site folder in Pinyon. The SD cards can then be reformatted and used again. Additionally, photos referenced in the camera results data sheet will be stored on the T-Drive to allow them to be uploaded into NRIS. File organization Within the program folder for elk in Pinyon there are three subfolders:

• Folder for keeping track of study sites and a backup of the shapefiles used in ArcMap o There is a study site tracker excel sheet that can be filled out to keep track of when and what sites have been surveyed and the results of the survey. o All shapefiles will be kept on the T-Drive, but back them up within this folder as well. • Site folders to keep photos and data sheets tied to each site o Within the site folders there will be a folder for photos and a folder for data sheets or other information o Within the photo folder, there will be two folders one for all photos and one for photos referenced on the data sheets that will be copied into the T-Drive. o Within the forms folder, place a copy of the site visit/pellet survey form and a folder for any data sheets. • Data on positively identified calving areas o Store any data sheets, excel files, or other components in site specific folders within the Positively Identified Calving Areas With the T-Drive there is a folder for each site’s photos and a folder for shapefiles necessary to complete the survey. Data entry • All species observed will be entered into NRIS • The survey is titled the “Elk Calving Program” o If a new site is surveyed, associate the site by adding a sample point to the project and place the sample point at the correct location. Enter the site visit as dates specified on the data sheet. o Right-click on the site/sample point and hit “rapid data entry mode.” ! Click the tab for “observations” and begin entering the observations specified on the data sheet. Upload photos to the observation as warranted.

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Microsite Data

Introduction The Microsite is a 300-meter radius surrounding the springhead where the camera was placed (if there was more than one spring in a study site). General data about the site will be gathered. Four 1/10th acre (0.04 hectare) vegetation plots will be conducted. Additionally, if aspen is present, additional data on the status of the aspen stand will be gathered.

Figure 5: Visualization of 0.10-acre plot points randomly placed within the microsite. Generating Random Points The first plot will be centered on the springhead and the next three plot points will be randomly placed within the microsite. To generate three random plot points in ArcMap:

• Select the microsite and export the site into a new shapefile. • Open the Data Management Toolbox, open Sampling, and select Create Random Points. • Choose a folder to store the random points. Select the exported microsite layer as the constraining feature. • Enter 3 for the number of points under the “Long” option. Hit okay. • Export the three randomized plot points and the springhead location onto a GPS unit. Alternatively, the same method can be used in X-tools Pro.

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Tools Needed: • Diameter Tape (inches) • Ten-factor prism • Pin flags • Long measuring tape (>50ft or 15 meters) • Compass • Clinometer (to measure slope in percentage to the nearest 5%) • Bags for collecting biomass • Moosehorn • 1-meter string with weight tied to the end (such as a pen or deadlock, nothing larger than 1”x1” • GPS Unit

Site Information

• Site Name: Enter the project-specific site name or number • Enter the Lat/Long Location of the microsite center (the spring head). • Enter the township, range, section, and ¼ section of the site. • Elevation: Enter the elevation of the spring head. • Slope: Enter the slope percentage at the spring head using a clinometer. • Aspect: Enter the aspect based off the spring head on the slope using a compass. • Spring Name: Record if the spring is named on the map, such as “Rocky Point Spring” • Vegetation types: Mark more than one if applicable. If aspen are present within the microsite, fill out the back side of the form, and do the same for conifers. Use the descriptions in A Guide to Wildlife Habitats of California by Mayer and Laudenslayer (1988) to help record vegetation types.

Site condition Describe the general status of the site in order to paint the best representation of the area and conditions of vegetation, any human impacts, and other notable components. Is the spring channel becoming downcut? Is there a railroad grade bisecting the site? Is the aspen stand narrow along the spring channel and surrounded by dense conifers? Are there dead aspen but no live aspen observed? Are there large Jeffrey pines in the overstory with an open understory? Some of this may be captured in the plots and aspen forms, but it helps to create a representative picture here and present any information that may otherwise be missed. See below for calculating the site totals. Canopy Cover, Downed Logs, and Herbaceous Cover The following methods are based on or taken from those described in “Chapter 9: Techniques for Sampling Habitat” in Monitoring Animal Populations and Their Habitats: A Practitioners Guide (McComb et al. 2010). Plot Selection Plot 1 will always be taken from the center of the microsite, which is the springhead, and three other plots will be taken randomly within the stand. Navigate to the center of each plot point using a GPS unit. Mark the plot center with a pin flag, then measure 37.2 feet (11.3 meters) out in the four

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Elk Calving Protocols cardinal directions (N, S, E, W), marking the edge with pin flags. Complete the canopy cover, herbaceous cover, and downed wood components while measuring the transects so the measuring tape is visible and can be used to maintain proper distances. The pin flags on the edge of the circle create a tenth acre plot. Canopy Cover Use the four 37.2-ft (11.3-m) radii as transects. Walk along each transect with the measuring tape visible and stop at 6.5 ft (2 m), 13 ft (4 m), 19.6 ft (6 m), 29.5 ft (8 m), and 32.8 ft (1 0m). At each of the five points look up using the moosehorn and see if vegetation is visible overlapping the dot in the mirror when the levels are in the proper position. Record “1” for vegetation and “0” for sky. At these same points record herbaceous cover (see below). Repeat for all transects. Tally the number of “1’s” recorded and divide by 20 to estimate the canopy cover within the plot and write this on page 3 of the data sheet. Herbaceous Cover Percentage of the plot covered by herbaceous vegetation will be estimated based on but modified from the techniques used by the PNF Rangeland Management department to measure cover at Fens.. At the same points along the cardinal transects as used for tree canopy cover (2, 4, 6, 8, and 10 meters), dangle the weighted string against the measuring tape and lower under the weight touches the ground. If herbaceous vegetation touches the string/weight at any point mark a “1.” If no herbaceous vegetation touches the string/weight at any point than mark a “0.” Repeat this at each of the five points on each of the four transects. Tally the number of “1’s” within the plot and divide by 20 to estimate the herbaceous cover within the plot and write this on page 3. Dead wood Large downed logs provide hiding cover for elk calves. Walking along the cardinal direction transects, record the diameter (using the diameter tape) of the downed log where it intercepts the line, but only for logs greater than 20in (51cm) in diameter at any point (based on SNFPA 2004 guidelines for large woody debris). Diameters of elliptically-shaped logs should be measured in two dimensions and then averaged to get a single value. Remark if there is a significant blowdown of logs <20” creating a jackstraw area within the plot that may provide other hiding cover.

Calculate the surface area in m2/ha of logs >20” dbh, where transect length is in meters (and should be 11.3m) and log diameter is in centimeters: Surface area = ((50* π2)/transect length) * ∑(log diameters), Convert this to feet per acre using the ratio of 1 m2/ha = 4.356 ft2/acre.

Notes Put any remarks about the plots here. Record incidentally observed elk pellets in any plot. Record if there are any notable vegetation types or features that may not have been captured in any of the plots. Record any other relevant information that is not otherwise documented. Tree Species, DBH, Basal Area, and Trees per Acre Take multiple copies of page 4 into the field and use as necessary. Using a diameter tape, record the species and dbh for all live trees and greater than 6 inches within the 0.10-acre plot at 4.5ft (1.3

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Elk Calving Protocols meters) above the ground. Trees, saplings, and shrubs between 1-6” dbh are measured in a 0.01-acre plot (centered on the center pin flag), so only count these size-class trees after measuring out 11.8ft (3.6 meters) from the center pin flag. Seedlings and small shrubs are only measured in a 0.001-acre plot, so measure out 3.7ft (1.1 meters) 3.7ft and record the diameter at the root collar (rather than dbh) and species of any tree seedlings and shrubs <1” dbh. For the purposed of this study, Jeffrey pine (Pinus jeffreyi) and Ponderosa pine (Pinus ponderosa) should be classified only as Jeffrey pine. Four letter species codes can be used as a shorthand when filling in the data sheet. Some common species are included in Table below.

Table 6: Common species codes for trees and shrubs surveyors may encounter during the microsite plots

Code Species Common name JUOC Juniperus occidentalis Western juniper PICO Pinus contorta Lodgepole pine PILA Pinus lambertiana Sugar pine PSME Pseudotsuga menziesii Douglas-fir PIJE Pinus jeffreyi Jeffrey pine ABCO Abies concolor White fir POTR Populus tremuloides Quaking aspen CADE Calocedrus decurrens Incense-cedar CELE3 Cercocarpus ledifolius Curl-leaf mountain mahogany

Calculating the totals for Microsite Average the canopy cover, herbaceous cover, and surface area covered by downed logs by adding each of the four plot totals (after determining each plot’s average using the methods described above) and dividing the number by 4. Put these totals on the first page of the Microsite data sheet. This can also be done in excel. If a tree takes up a high percentage of the basal area, but a low percentage of the trees per acre, then there are likely a small number of larger trees. If a species takes up a smaller amount of the basal area but a large amount of the trees per acre, it is mostly a large number of small trees. Calculate the average dbh, trees per acre, and basal area in excel spreadsheets • Average dbh o Start a new page of the excel sheet. Enter the species and dbh information. Select the data and use a pivot table to gather information on average dbh per species and over the entire plot. ! Place Plot in the row field and dbh in the values field but select Average in the field settings. Record dbh by plot on page 3 of the data sheets. Add the averages and divide by 4 to record the overall average dbh page 1 of the data sheet. Remove Plot from the row field and place Species in the field. Record the average dbh by species on page one of the data sheets. • Trees per acre o Create another a pivot table with Plot in the column, species in the row, and a count of the tree numbers in the values field. Multiply all totals by 10 to get average trees per acre based on the plot, record this information on page 3, and by species on page 26

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1. Average the trees per acre over the entire site by summing the average per plot and dividing by four. • Basal area per acre (CFRP 2009). o Start a new column for Basal Area Per Tree in the data sheet containing the tree data. The dbh is in inches, and the basal area will be in square feet per acre. o In row 2 of Column E (Basal Area Per Tree) type: =(D2*D2)*0.005454 ! It will look like this in Excel:

o Put the cursor on the bottom right edge of the completed cell (on the green square) and drag it down to the bottom to continue the formula throughout the tree numbers. o In the Basal Area Per Acre column, type: =E2*10 to find the basal area per acre (in square feet).

o Drag the formula down the column as before. o Use a pivot table to sort by tree species to find out how much each species is contributing to the basal area by summing the basal area per acre by species and plot. o Record the information by plot on page 3, then average the four plots and place the total on page 1 of the data sheet. • Save this excel sheet in the site folder.

Aspen Condition Form: The Aspen Condition Form is based off the Aspen Risk Assessment form created by David Burton for the 2002 Aspen Delineation Project for the USFS Region 5, but are slightly modified to better capture project goals. More information about this protocol can be located from Burton (2004).

The Aspen Condition Form is based on the entire stand, which is a contiguous area occupied by aspen, not necessarily the components that are only located in the Microsite. Walk the perimeter of the area where aspen are present, and include the areas where any aspen is present, even those dominated by conifers. Record tracks while walking the perimeter using the GPS unit, which can be

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Elk Calving Protocols used to estimate aspen stand acreage. Information gathered from this form can help identify aspen stands that are at-risk and may warrant treatment.

Definitions • Overtopping: Growing taller than another species, thus shading that species • Dominate: To be taller • Co-dominant: Equal or the same (in this case the number of the tallest conifers in this level is equal to the number of the tallest aspens) • Browse: Eating of bud, leaf, or stem • Terminal bud (terminal leader): Growth at the tip of the primary stem • Cohort: Stems of the same age. In the case of evaluating aspen regeneration >500 stems/acre is the lowest number of stems/acre used to indicate significant regeneration. Overstory Conifers have overtopped (>50%) aspen (majority of aspen are shaded). Indicate if there are more conifers overtopping (>50%) aspen in the overstory canopy level than there are aspen overtopping conifers. Also indicate whether that ratio is approximately 10:0, 8:2, or 6:4. For example, 8:2 means that for every 8 conifers dominating the overstory there are only 2 aspen dominating the overstory. Conifers are co-dominant with aspen, (aspen canopy = conifer canopy cover). Indicate if the tallest conifers and the aspen in this canopy level are at the same height. The ratio of Conifer to Aspen at this level should be 5:5, indicating that there is an equal mix of the tallest conifers and aspens. Aspen dominate over conifers (aspen canopy >conifer canopy cover). Indicate if the aspen in this canopy level are dominant over the conifers which are in this canopy level. The ratio of Conifer to Aspen should be 4:6, 2:8, or 0:10. Aspen stand structure is decadent. Indicate whether the stand is in a state of decline or decay, if there are more dead overstory or mid-level stems present than live stems and sucker regeneration <500 stems/acre. Dominant conifer species. Indicate what species of conifer is the most dominant in this canopy level. Mid-Story Mid-level conifer canopy has overtopped (>50%) mid-level aspen canopy. Indicate if there are more mid-level conifers overtopping (>50%) aspen in the canopy level than there are mid-level aspen overtopping conifers. Also indicate whether the ratio of conifers to aspen in this level is 10:0, 8:2, or 6:4. For example: 8:2 means that for every 8 conifers dominating the mid-story there are only 2 aspen dominating the mid-story. Mid-level conifers are co-dominant with mid-level aspen. Indicate whether the tallest mid-level conifers and mid-level aspen in this canopy level are at the same height. The conifer to aspen ratio at this point should be 5:5, where the mix of mid-level conifers and mid-level aspen are equal. Mid-level aspen dominate over mid-level conifers. Indicate if the aspen in this canopy level are dominant over the conifers which are in this canopy level. Indicate whether the Conifer:Aspen ratio is 4:6, 2:8, or 0:10. >50% Mid-level aspen dominated (shaded) by conifers located in overstory canopy. Indicate what effect the conifer overstory is having on the mid-level aspen

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Understory There is a distinctive (>500 stems/acre) regeneration stem age class present. Indicate if stand has a regeneration cohort. Aspen regeneration is poor (<500 stems/acre). Indicate if stand has does not have a regeneration cohort (<500 stems/acre) Young conifers seedlings present (>500 per acre). Identify presence of conifers <1" dbh. Browsing intense (current terminal leader growth is completely removed on > 20% of stems). Indicate if > 20% of current terminal leader growth has been browsed. Note: This percentage standard is based on standards and guidelines found in the SNFPA 2004 (Sierra Nevada Forest Plan Amendment). Browsing light to moderate (current terminal leader growth is completely removed on < 20% of stems). Indicate if < 20% of current terminal leader growth has been browsed. Aspen suckers (>20%) have multiple leaders or are “hedged." This is a key indicator that browsing has been an ongoing problem in stand. Other Insect Damage (>20% of stems). Indicate if >20% of stems show signs of any signs of damage from insect species Disease damage (>20% of stems). Indicate if >20% of stems show signs of any one pathogen pattern (conks, etc.) Blowdown. Indicate if >25% of the stand has suffered significant wind damage--i.e., stems fallen in a consistent direction Sagebrush. Indicate of >20% of stand contains sagebrush. Corn Lilies. Corn lilies will indicate a high water table (>25% of stand). Gully Cuts. Indicate any significant erosion (bare soil cuts) greater than three feet Beaver Presence. Indicate signs of beaver--current or past

References: Burton, David. 2004. Development of a Protocol for the Ecological Assessment of a Special Species. USDA Forest Service Preceedings. RMRS-P-34. https://www.fs.fed.us/rm/pubs/rmrs_p034/rmrs_p034_164_170.pdf Collaborative Forest Restoration Program (CFRP). 2009. Monitoring Data Analysis Tutorial. New Mexico Forest and Watershed Restoration Institute. McComb, B., Zuckerberg, B., Vesely, D., & Jordan, C. 2010. Monitoring animal populations and their habitats: a practitioner's guide. CRC Press.

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Macrosite Data

Macrosites will be a 1km radius around the springhead that was camera-surveyed. Site Information All macrosites are approximately 776 acres (314 hectares) in size. All the site information will be gathered using ArcGIS and existing Beckwourth Ranger District (RD) shapefiles. Road Density Within the program folder on the T-Drive, select the roads layer. Clip the roads to the macrosite. Using X-tools Pro, calculate the geometry of the newly clipped layer to get the length in meters. Open the attribute table, go to length, and hit “Summarize” to get the total meters of road within the macrosite. Spring Density Using the Springs layer (within the project folder), count the number of springs. Stream Density The Beckwourth RD stream layer is located within the 2600 folder on the T-Drive. Clip the layer to the macrosite. Using either X Tools Pro or the attribute table, recalculate the geometry to get the length of streams within the macrosite in meters. Then run a query on the layer to show only perennial streams (which has a P under “Type”). Open the attribute table and gather the sum of the perennial stream length within the site. Repeat with a new query to get the intermittent stream density within the macrosite. Guzzlers Check the guzzler shapefile in the 2600 folder in the T-Drive to see if any guzzlers are located in the macrosite. Slope and Elevation Locate the Aspen_Slope layer within the project folder. Clip the layer to the macrosite and calculate the geometry in X Tools Pro similar to the stream and roads layers, but ensure that acres will be recalculated. Copy the attribute table into an excel sheet and click “insert pivot table.” Put aspect in the rows and acres in the values fields. Format the values so that it does not show any decimal places by clicking the “Sum of Acres” and editing the Value Field Settings. Calculate the proportion of each value’s contribution to the total acreage. Remove aspect from the row and repeat with slope. Excel will occasionally rewrite 06-15% as June 15, so change this manually if necessary. Vegetation Composition Until LIDAR becomes available, utilize PNF_veg located within the 2600 Wildlife Folder on the T- Drive.

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• Note: Once LIDAR becomes available, all sites that have completed Macrosite Data should be redone using the newly available layers. Save these and the older sites in the project folder. Clip the vegetation layer to the Macrosite. Recalculate the geometry using X-tools Pro. Open the attribute table, select all, and copy selected into a new excel sheet. Use pivot tables to gather acres of each vegetation type (WHRTYPE), tree size composition (WHRSIZE), canopy cover class (WHRDENSITY), and land cover type (COVERTYPE). For the tree size and canopy cover classifications, change the codes used to reflect the content using the CWHR classifications. Site Management History Gathering this information will likely require assistance from other specialists at the Beckwourth RD. Contact Archeology, Range, Fuels, and Ecosystem Operations to gather the information if necessary. There is an allotment shapefile in the program folder, however, there may be changes that are not up to date with current grazing numbers. Fire and Vegetation Treatments Examples for the type of fire include: prescribed, wildfire, or managed fire. Examples for the type of prescriptive treatment include mechanical, hand thins, aspen release, etc.... Record in the notes the extent of the treatments. Record if treatments occurred at the spring itself or within portions of the macrosite. Record the extent of treatments, such as if it covered the entire macrosite or estimate a percentage of the site treated.

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Appendices Appendix B: Site Selection Methodologies To locate springs within the study area: • The first step is to draw a Survey Inference Area (SIA) as a polygon, based on observations of elk, forest boundaries, and topography. Convert the graphic to a feature and label the polygon as the SIA. o Current observations can be found in NRIS (National Resource Information System) under the Wildlife Observations layer. o Boundaries exclude private land, particularly Red Clover Valley. o Topographic features include such as large cliff faces or ridgetops. • Then, use the Clip tool, with the PNF’s “Springs” layer (located on the T Drive) as the input and the SIA being the boundary. Name the new layer “Survey_Springs.” To merge sites that have multiple springs into one site and generate the list of sites to be surveyed: • Using the Buffer Tool, buffer each spring by 300m and Dissolve All. • Under Data Management Tools, select Features and then Multipart to Singlepart and label this “Survey_Sites” • Move the Survey_Springs layer above Survey_Sites. • Open the Attribute Table for the Survey_Sites layer and create a new field labeled “Num_Spring” • Start editing the Survey_Sites layer. Navigate to each site using the map and select each site so that the site become highlighted in the attribute table. Type the number of springs that are inside each polygon. • Save edits and stop editing. • Labeling Sites o Create a new short integer field named “Site_No” ! Right-click the new field and select Field Calculator. ! Set the Parser to Python. ! Check the check box for Show Codeblock. ! Paste the following into the Pre-Logic Script Code:

rec=0 def autoIncrement(): global rec pStart = 1 pInterval = 1 if (rec == 0): rec = pStart else: rec += pInterval return rec

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! Paste the following code in the smaller box below the Pre-Logic Script Code:

autoIncrement()

! Click Okay ! Source: https://support.esri.com/en/technical-article/000011137 o The Site Numbers will be used to track all sites. o Create a new text field titled “Other_Name” ! Highlight each Site No and see if the spring is named on the forest or topo maps. Type in the name used on a map. This layer should be updated if other names are identified. To randomly select the survey order: • Open the attribute table for Survey_Sites o To generate random values in a new field: ! Create a new Float field and name it “RandomNum” ! Right-click the new field header and click Field Calculator. ! Change the parser to Python. ! Check the Show Codeblock check box. ! Copy the following code and paste to the Pre-Logic Script Code text box: import random def rand(): return random.random() ! Type rand() in the RandomNumb text box. ! Click OK. Random numbers are generated in the new field. o Right click on the RandomNumb field and sort by ascending. This is the order in which springs will be surveyed. o Copy and paste the attribute table into an excel sheet labeled “Site Survey Schedule” ! Create columns to track when sites were surveyed as well as general elk observations. More detailed elk observation data will be stored in another table. Surveying springs outside the SIA to see if they should be added: • Start with 1km and visit sites within this range. If a spring is identified to be used by the elk, continue to visit springs in this direction until locating a spring with no observations. If a spring does not have detections, it should be resurveyed every 3 years. • Open ArcToolbox, select Analysis tools, Proximity, and then finally, Buffer. o Select 1 mile as the buffer width and name the new file “SIA_Buff_1mile” • Under Analysis tools, select Overlay and select Erase. o The input feature is the SIA_Buff_1mile” and the erase feature is “SIA” o Label the new layer “SIABuff1mile_EraseSIA” • Under Analysis tools, select Extract and select Clip. o The input feature is the Beckwourth RD Springs Layer, and the clip feature is the “SIABuff1mile_EraseSIA”

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o Label the new layer “SpringsWithin1Mile” • If necessary, Edit the layer to delete any springs that are located on private property. • When visiting the sites: o Follow the protocol for walking transects outlined in the “Pellet Surveys Post- Calving” to look for sign of use by any elk. ! Enter this data into the table. Any springs that have evidence of use will be added to the SIA. o This should be done at least every 3 years to account for herd changes, land management, disturbances, and other factors.

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Appendix C: Camera Survey Results United States Forest Service, Plumas National Forest, Beckwourth Ranger District (2020) Project:______Station Information Site Name/Number: Camera Number: Latitude: Longitude: ______Site Vegetation: Township, Range, Section, and ¼ Section: ______NRIS (Using Carnivore Naming Conventions) Project ID: Unit ID No.: Station ID.: ______Survey details Name of person(s) who set up camera: Survey period start date and time: ______Name of observer of photos: Survey period end date and time: ______Lure/Bait/Feature: Target species or species group: ______Camera Settings Height: Distance to spring: Sensitivity: Photos/trigger: Delay: Camera Type: ______

Additional Comments ______Results Date Start End Species Image IDs Comments Time Time

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Date Start End Species Image IDs Comments Time Time

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Appendix D: Elk Program Pellet Survey United States Forest Service, Plumas National Forest, Beckwourth Ranger District (2020)

Date: ______Visit Time: Begin ______End ______Surveyors:______

Site Information Site Name/Number: Lat/Long of spring: Township, Range, Section: Site Size (acres) ______Site Vegetation: ______Spring Condition: ______Detections: Elk individuals observed Adult elk pellets Elk calf pellets Rack rubbings on trees Wallows Other: None

Number of elk pellet groups:______Number of deer pellet groups: _____

Other Observations & Comments:

Entered into NRIS:______

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Transect Pile Species Distance Veg type Veg height Decay (cm) (cm) Class

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Appendix E: Calving Micro-Site Condition Plumas Elk Calving Monitoring Program (2020) Date: ______Visit Time: Begin ______End ______Surveyors: ______Site Information Site Name/Number: Latitude: Longitude: Township, Range, Section: ______Elevation (ft): Slope %: Aspect: Spring name on map (if applicable): ______Vegetation Types Present: Aspen Juniper: Other Conifer: Wet Meadow Bitterbrush Other: ______If aspen is present, complete the additional aspen condition portion of the data sheet.

General Comments About Site Condition: (Describe the condition of the spring head, spring channel, human structures, evidence of use by cattle, railroad grades or old roads that bisect the spring channel, and any other conditions of note). ______Totals based on data gathered from the four plots: Averages Tree/Shrub Percentage Percentage Average Canopy Cover (%): ______Species of total of total trees dbh Herbaceous Cover (%): ______basal area per acre Downed wood: ______

Basal Area (per acre): ______

Average dbh: ______Average trees per acre: ______

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Cardinal Transects Datasheet Plot Transect Point Canopy Herbaceous Logs (1=veg, Cover (diameters at intersect 0=no (1=veg, of transect) veg) 0=no veg) 1 N 1 1 N 2 1 N 3 1 N 4 1 N 5 1 E 1 1 E 2 1 E 3 1 E 4 1 E 5 1 S 1 1 S 2 1 S 3 1 S 4 1 S 5 1 W 1 1 W 2 1 W 3 1 W 4 1 W 5 2 N 1 2 N 2 2 N 3 2 N 4 2 N 5 2 E 1 2 E 2 2 E 3 2 E 4 2 E 5 2 S 1 2 S 2 2 S 3 2 S 4 2 S 5 2 W 1 2 W 2 2 W 3 2 W 4 2 W 5 3 N 1 3 N 2 3 N 3 3 N 4 3 N 5 3 E 1 3 E 2 3 E 3 3 E 4

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3 E 5 3 S 1 3 S 2 3 S 3 3 S 4 3 S 5 3 W 1 3 W 2 3 W 3 3 W 4 3 W 5 4 N 1 4 N 2 4 N 3 4 N 4 4 N 5 4 E 1 4 E 2 4 E 3 4 E 4 4 E 5 4 S 1 4 S 2 4 S 3 4 S 4 4 S 5 4 W 1 4 W 2 4 W 3 4 W 4 4 W 5

Notes: ______

Totals: Averages over the Plot Plot 1 Plot 2 Plot 3 Plot 4 Canopy Cover (%) Herbaceous Cover (%) Downed wood (surface area) Basal Area (per acre) Average dbh (inches) Trees per acre

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Tree Species and DBH Data Plot Tree Species DBH (in Number inches)

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Aspen Condition Form

Aspen Stand Acreage Estimate(Total) <1/4 1/4-1/2 >1/2-2 >2-10 >10

Overstory Canopy Level (Aspen >8"dbh) Conifers have overtopped (>50%) aspen (majority of aspen are shaded) Ratio Conifer:Aspen 10:0 8:2 6:4 Conifers are co-dominant with aspen , (aspen canopy cover = conifer canopy cover) Ratio Conifer:Aspen 5:5 Aspen dominate over conifers (aspen canopy >conifer canopy cover) Ratio Conifer:Aspen 4:6 2:8 0:10 Mature aspen stand structure is decadent Dominant conifer species:______

Mid-level Aspen Canopy (Aspens 1" dbh to 8" dbh) Mid-level conifers have overtopped (>50%) mid-level aspen Ratio Conifer:Aspen 10:0 8:2 6:4 Mid-level conifers are co-dominant with mid-level aspen Ratio Conifer:Aspen 5:5 Mid-level aspen dominate over mid-level conifers Ratio Conifer:Aspen 4:6 2:8 0:10 >50% Mid-level aspen dominated (shaded) by conifers located in overstory canopy

Aspen Understory (Aspen <1 " dbh) There is a distinctive (>500 stems/acre) regeneration stem age class present Aspen regeneration is poor (<500 stems/acre) or none Young conifers (<4.5ft') present (>500 per acre) BROWSING ISSUES: • Browsing intense: current terminal leader growth is completely removed on > 20% of stems(<4.5') • Browsing light to moderate: current terminal leader growth is completely removed on < 20% stems(<4.5') Aspen suckers (<4.5') have multiple leaders or are “hedged"(indicating history of intense browsing)

Other Insect damage (>20% of stems) Disease damage (>20% of stems) Blowdown Sagebrush (covers >20% of stand) Corn lilies: (covers >20% of stand) Conifer ≥30” dbh Gully Erosion: Beaver Presence:

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Appendix F: Calving Macrosite Condition Form Plumas Elk Calving Monitoring Program (2020)

Site Name/Number: Spring Lat/Long: Township, Range, Section: ______

Form compiled by: Date: ______

Macrosite Information Road Density Spring density Perennial stream Intermittent stream Guzzlers within (meters): ______(number): ______density (meters): _____ density (meters): ____ Site (Y/N): ___

Proportion (%) of aspect N: ____ NW:____ NE:_____S: ____ SW: ____ SE: _____E: ____ W: ____

Proportion (%) of slope 0-5%:____ 6-15%:_____ 16-25%:____ 26-35%:_____ 36-45%: _____ >45%:____

Vegetation Data

Vegetation Acres % of Tree Size Acres % of Canopy Acres % of Type site Class (dbh) site Cover site

Land Cover Acres % of Notes:

Type site ______

______

______

______

______

______

______

______

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Site Management History

Archeological Site (Y/N): _____ Type(s) of Arch site:______Notes: ______

Grazing Allotment (Y/N): ______Name of grazing allotment: ______

Number of Cow/Calf pairs per year: ______Dates of allotment use: ______Notes: ______

Year of last fire within the site: ______Type of fire: ______Notes: ______

Year of last prescriptive treatment: ______Type of treatment: ______Notes: ______

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