REU: Autumn Thoyre
 
PATTERNS OF PACKSTOCK IMPACTS
IN ALPINE MEADOWS IN THE SIERRA NEVADAS

ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
CONCLUSIONS
REFERENCES

POWER POINT

ABSTRACT

In response to a court mandate to assess and monitor pack stock impacts to alpine meadows in the Sierra Nevadas, the US Forest Service has developed a labor- and expertise-intensive method of surveying meadows. In response to the difficulties the Forest Service has had in reaching so many meadows on a regular basis and monitoring them with objectivity, this study approached the monitoring from a more quantitative methodology with quadrats run across the meadow to pick up vegetation patterns and belt transects to capture impact patterns. For Duck and Ram meadows, the impact sod fragmentation is the most common and least severe impact, while rills/gullies are the least common and most severe impact, with trails falling in between in abundance and severity. The data suggest that wet areas are the most sensitive to impact presence, and that mesic and hydric areas are significantly less sensitive. Data from Ram meadow suggests that water sources are more sensitive to impacts than meadow-proper, but this was not supported by data from Duck meadow. Both findings have implications for further studies and for the assessment and monitoring of these alpine meadows.

INTRODUCTION

Despite representing less than 10% of the Sierra Nevadan subalpine and montane regions, alpine meadows are prized for recreational purposes, for their forage for pack stock, and for their high levels of biodiversity and ecosystem services (Moore 2000). Only 14% of all wilderness areas prohibit the use of pack stock, and 11% of visitors to wildernesses arrive on pack stock (McClaran and Cole 1993). There is believed to have been light to moderate grazing from deer, bighorn sheep, and small mammals in the Sierra Nevadas prior to the arrival of colonists from Spain and Mexico (Ratliff 1985). Grazing of livestock (e.g. sheep and cattle) on the slopes began in the 1860s and 1870s following a severe drought (Ratliff 1985). In the late 1800s to early 1900s many impacts had been observed in the Sierra Nevadan meadows due to overgrazing by livestock (Ratliff 1985). Currently, livestock grazing is prohibited from most of the USFS Wilderness areas of the Sierra Nevada. All stock use in these areas is for carrying supplies and most pack stock use is by the commercial pack stock outfitters, with some use by Forest Service employees for work purposes (Moore 2000).

In 2002, the US Forest Service was sued by both conservation organizations and commercial pack stock outfitters for allowing either too much or too little (respectively) pack stock use in the Ansel Adams and John Muir wildernesses in the Inyo and Sierra National Forests (Berlow 2004). The Wilderness Act of 1964 states that “wilderness areas…shall be administered for the use and enjoyment of the American people in such a manner as will leave them unimpaired for future use and enjoyment of wilderness…” (88 th US Congress 1964), which can cause some conflicts due to difficulties in defining this balance.

Conservation groups such as the High Sierra Hikers Association stated that the Forest Service is required by the NEPA (National Environmental Policy Act) to assess the environmental impacts of actions such as pack stock use before it gave special use permits to commercial outfitters (LaPorte 2002). They cited evidence of threats to sensitive species such as the Mountain Yellow Legged Frog and the Yosemite Toad, and other impacts such as the particular sensitivity of high alpine meadows due to their short growing season and other factors as reasons the use is too much (LaPorte 2002). The commercial pack stock outfitters stated that it would hurt the local economies, hurt children's education programs, and would keep some people from enjoying the wilderness areas if pack stock use were decreased (LaPorte 2002). The judge ruled in favor of the conservation groups, and ordered a “cumulative analysis” of pack stock policy in both wilderness areas, roughly 3,280 km 2 (Berlow 2004). The judge also ordered a 20% reduction in pack nights, a limit of 12 people and 20 stock for any overnight trip, and a phase-in of trailhead quotas (LaPorte 2002).

Pack Stock Impacts

While much has been studied about the impacts of livestock on various habitats, much less is known about the impacts of pack stock on any habitats, particularly on alpine meadows, and Moore (2000) points out that “…few quantitative studies exist to support management decisions.” Most of the studies that do address this question focus on a few specific impacts, such as grazing, trampling, and trails; little is known about rills and gullies and the effects on aquatic habitats have not been studied extensively. The following areas have been studied:

Grazing: The effects of grazing on meadows, particularly on productivity levels of the remaining vegetation is one of the most well-studied impacts. Clipping grass to simulate grazing on high-elevation plots in Yosemite has been shown to reduce productivity after two years of the treatment (Moore 2000). When horses were picketed in southwestern Montana in an alpine meadow, the short-term consequences for grasses and forbs were quantified, but no long-term consequences were identified (Olson-Rutz 1996).

Trampling: Trampling is considered the result of horse hooves hitting the ground or horses rolling in the dust (McClaran and Cole 1993). It can lead to hoof punches in the sod and multiple trails, as well as soil compaction and bare areas and holes, which in turn can lead to erosion and changes in plant composition (Ratliff 1985). Trampling can lead to bare ground, which Morgan (1986) points out is vulnerable to erosion (as cited in Pellant 2000).

Trails: Among the impacts of trail use to the meadows are soil compaction, erosion, the creation of bare ground, and effects on plant composition (Leung and Marion 2000). In a study comparing the trail effects of humans, horses, motorcycles, and off-road bicycles, horse use of trails tended to increase erosion more than other users because they kicked up more sediment that could then be washed away by rain (Wilson and Seney 1994). In 1999, Leung and Marion studied trails in the Great Smoky Mountains National Park, trails used frequently by horses were “significantly wider, muddier, and had more multiple treads” (as cited in Leung and Moore 2000).

Rills/Gullies: Pellant (2000) defines a “gully” as “a channel that has been cut into the soil by moving water” and Ratliff (1985) notes that they “characteristically move up a stream from the lower end.” Pellant (2000) defines “rills” as “small erosional rivulets that are generally linear and do not necessarily follow the microtopography as flow patterns do.” Higher slopes and lowered cover from disturbance are two factors that can cause an increase in rills (Pellant 2000).

Water Sources: Little is known about the specific impacts of pack stock on water sources, despite the potential for high use when pack stock drink from them. Cole and Landres (1996) note, “our understanding of recreational impacts on aquatic systems in wilderness is so rudimentary that a simple assessment of the prevalence and intensity of such impacts is a top research priority.” Considering that meadows are valuable in a strictly anthropogenic sense for their filtering of water for humans and for fish (Ratliff 1985), threats to water sources should be important to any assessment of pack stock impacts. Possible threats to streams and spring channels include channel degradation, sedimentation, and changes in vegetation that could affect wildlife (Allen-Diaz 1998). Despite the sometimes localized nature of contact with water sources, and the relative rareness of these habitats, impacts to lakes, ponds, streams, and spring channels can be more widespread than soil and vegetation impacts (Cole and Landres 1996).

Soil Moisture: Several studies have been done that note correlations between soil moisture and impacts from grazing, trampling, and trails; however, few studies directly look at pack stock. In a study of grazing effects of sheep and cattle, Murray (1997) found that drier meadows were less likely to be impacted than wetter meadows, but recovered slower when impacted, which he attributes to the mat of vegetation in drier meadows that can withstand punching-through, but which has a lower productivity from which to draw to recover when impacted. He found that an intermediate moisture level was the most likely to avoid impact, that meadows with drier soils are more vulnerable to erosion, and that wetter soils are more vulnerable to trampling and soil compaction.

Strand (1979) studied trampling on wet and dry soils and found that trampling lasted longer and was more extensive in a wet meadow than in a xeric site (as cited in Ratliff 1985), in contrast with Murray's (1997) study. A few studies have been done on the association between soil moisture and human trampling that suggest patterns for horse trampling but do not confirm them. In a study on trampling by humans on alpine tundra vegetation, a much smaller amount of walking created damage to wetter areas, such as snowbeds and marshes, in contrast to drier areas such as grassy turfs (Palmer 1979). However, Palmer's (1979) study on human trampling in a dry, intermediate, and wet meadow found that the plants in the drier area were most vulnerable to damage, and that the wet meadow recovered faster than the intermediate-moisture meadow.

Weaver and Dale (1978) note that trails in areas that are poorly drained (i.e. wetter) tended to be more severe (wider and deeper) than trails in well-drained soils (as cited in Wilson and Seney 1994).

Research Gaps: Clearly there is a lack of research on pack stock impacts in particular on alpine meadows. In much of the literature, pack stock impacts are considered qualititatively, but little is known about the quantitative impacts. There is a clear need for research to clarify these conflicting predictions on how different vegetation types might respond. In addition, few studies have considered the abundance of impacts in different habitats taking into account the amount of each habitat available in a meadow, to look at habitat vulnerability more clearly. There do not seem to be any guidelines for what is an acceptable amount of impact, since there are not many long-term studies. There is a need to know what the best predictors of impacts are (such as water sources or vegetation types) and what can be measured to best get at these predictors in order to streamline assessment and monitoring of meadows. Finally, the lawsuit against the Forest Service focused on physical impacts, rather than grazing, which have been studied much less extensively. In response to this lack of guidelines, the Forest Service has come up with a specific approach to monitoring and assessing alpine meadows for pack stock impacts.

The Forest Service Approach

In 2001, the Forest Service began collecting data to monitor and assess meadows in the Inyo National Forest (Interdisplinary-Team 2003a). They sent a group of experts in hydrology, botany, range conservation, and soil science, what they termed an “Interdisciplinary Team,” or “IDT,” to each meadow to evaluate various attributes they deemed important to the sensitivity of that meadow to impacts (Interdisciplinary-Team 2003a). They also looked specifically at certain factors they believed were important to assessing the degree to which each meadow had been impacted by pack stock (Interdisciplinary-Team 2003a). Some of the factors they rated were pack stock use levels; trail attributes; sod fragmentation; hummocking; soil compaction; plant composition change; soil erosion and moisture; and many aspects of impacts to water sources. After these factors were gathered at each meadow, the group reached a consensus on whether the meadow was suitable, partial, snacking, or unsuitable for commercial grazing (Interdisciplinary-Team 2003b).

In assessing each meadow, the team walked the entire meadow and gave a rating for each category based on the meadow as a whole (Lutrick 2004b). In three very full field seasons of field surveys (2001-2003) the IDT assessed over 180 meadows with this approach. The information they collected on meadow condition, stock impacts, and suitability for use was unprecedented in quantity, quality, and spatial extent. However, the IDT also noted potential problems with this method. For one thing, with hundreds of meadows in the Inyo National Forest alone (Lutrick DB 2004a), it is not feasible to repeat this process on a reasonable time scale. With the Forest Service's method, every time they want an updated assessment of a meadow, they need to send all the experts in the IDT to the meadow because none of the assessments can be done by a layperson. This is a large expenditure of valuable time for the Forest Service, and because many of the assessments require some expert judgment, any change in the makeup of the IDT may mean a change in the data. Thus there appear to be many reasons to explore other options of assessment and monitoring.

An Alternative Approach

To meet some of the challenges with assessing and monitoring such an expansive area, Berlow et al. (2004) have proposed a multi-tiered approach to make the process more objective and scientific, and hopefully simple enough for rangers or small teams of field technicians to apply without specialized training. They note that there is evidence that physical impacts and actual overgrazing amount do not correlate directly; thus there must be some other factors other than simply use amount that affect how much impact the use might have (Berlow 2004). The approach seeks to explain the difference between overgrazing amounts and physical impact concerns at a broad scale, using remote sensing, and moving down in scale so that in the end the number of meadows that actually have to assessed at the ground level individually might be much reduced (Berlow 2004).

Details of our Study

In this study, we seek to address what factors within a meadow (in terms of patch-scale habitats) best predict impact presence or severity. We measured vegetation type in terms of soil moisture (xeric, mesic, wet, and hydric) and water source type. We then examined the pattern of these factors against the spatial pattern and severity of impacts, in order to see if and how impacts occur in a predictable manner. From our preliminary findings, we can see that there are certain factors that rangers would want to focus on in assessing and monitoring alpine meadows in order to capture impacts. They also might be able to analyze these factors from a distance, through, for example, remote sensing or aerial photographs, in order to analyze the sensitivity of a meadow without having to go on-site, thus drastically reducing the time necessary to assess and monitor these meadows.

Through discussions with IDT member Erin Lutrick (2004b), a hydrologist with the US Forest Service, we decided to measure only a handful of the many impacts and impact attributes that might occur in a meadow, with the goal of streamlining the process without losing the quality of our data. Of particular interest were physical disturbances to the meadow that are a source of bare soil within the existing matrix of meadow vegetation, because erosion is a main concern in the court case due to its possible effects on water quality. We decided to focus on five main impacts: sod fragmentation, trails, bare banks, rills and gullies, and hummocking. However, no hummocking occurred in either meadow. We measured the extent of these impacts based on their occurrence within a belt transect and their severity based on a few key attributes of each (see Methods). We then were able to ask the following questions of our data to get at what might be some of the underlying patterns and associations with the impacts' presence and severity and the surrounding broad-scale habitat features such as soil moisture and water source presence.

Questions Addressed

1)   What patterns can be seen in the relative abundances of impacts within and between meadows?

2)  What patterns can be seen in the severities of impacts within and between meadows?

3)  What is the association between impact presence and water sources such as lakeshores, pond shores, streams, and spring channels?

4)  What is the association between impact severity and these water sources for each impact?

5)  What is the association between impact presence and broad vegetation types such as xeric, mesic, wet, and hydric soil moisture ratings?

6)  What is the association between impact severity and these broad vegetation types for each impact?

7)  What patterns can be seen in the spatial distribution of impact presence and severity?

METHODS

Site Selection

The two meadows chosen for this study are located in the Fish Creek drainage of the John Muir Wilderness of the Eastern Sierra Nevadas. Duck meadow skirts Duck Lake at 10,500 feet elevation, with an area of 0.377 acres (Lutrick 2004a), and is located roughly five miles from well-used campsites and parking near Mammoth, California. Ram meadow is actually two meadows that generally receive pack stock use from the same trips and in similar amounts, which is why they are usually considered as one meadow unit. They will be considered one meadow except in the spatial analysis. The Ram meadows are located at 10,150 feet elevation, with an area of 0.691 acres (Lutrick 2004a), located along the Pacific Coast and John Muir Trails around ten miles from the same campsites in Mammoth. These two sites were chosen for convenience of location and because the Forest Service had found a variety of impacts at these meadows, although they had differing levels of use.

According to the Forest Service's assessment of the meadows (Lutrick 2004a and Interdisciplinary-Team 2003a), Duck meadow received 12 pack stock nights in 2001 and 14 in 2002 (and an unknown number in 2003), while Ram meadow received 164 pack stock nights in 2001, 0 in 2002, and 0 in 2003. The IDT said both meadows had “moderate” trampling or chiseling of spring channels, with no headcuts and only “localized” changes in water flow. They said Ram had no stream impacts, and that Duck had no streams at all. They said Duck had one or more trails, which were changing local water flow, and that there were signs of incision, headcuts, widening, or multiple trailing. They said Ram's trails were more severe, with one or more trails affecting water flow locally and outside the local region of the trail, with signs of incision, headcuts, widening, or multiple trailing, with the potential of lowering the water table of the meadow. Both were deemed “partially” suitable, meaning, “suitable for commercial grazing allocation over some of the meadow, with major areas unsuitable for any entry by stock.” The IDT also gave the meadows an estimated capacity rating of 16 pack stock nights for Duck and 15 for Ram meadow. Other details about their evaluation of impacts are not as clear.

Field Methods

Our first task was to design a protocol for collecting data on vegetation and on impacts of mountain meadows. Our goal was a protocol that would be objective, repeatable, and straightforward enough that a non-expert could follow it and be reasonably accurate. We decided to collect our data on parallel transects laid out starting in the southwest corner of each meadow. For half of Duck Meadow, we physically laid out transects, but for the second half, as well as for Ram Meadow, we simply took a GPS point (Trimble GeoExplorer 3) at the start point and sighted the transect in a Northerly direction using a compass, and marking every five meters along it with flags. Our data was entered into PalmPilots (Palm m125 and HandSprings) for efficiency, with our forms designed using Pendragon software.

Regarding vegetation, we collected data on vegetation type (xeric, mesic, wet, or hydric) based on the soil moisture and the plants present. We designed the vegetation protocol as described by G. Collignon (2004). As such, we decided to collect vegetation data with 1 m by 1 m quadrats every ten meters on transects laid out every ten meters, starting in the southwest corner of each meadow. We only collected data in areas we defined as meadow in that they were more than fifty percent “meadow,” i.e. they were less than fifty percent shrub or rock. By defining the meadow in this way, our meadow boundary was smaller than that defined by the Forest Service in their aerial photos, which included some areas of the meadow that were more than fifty percent willow shrubs within their meadow boundaries.

For impacts, we decided to collect data on five different categories of impacts along a belt transect. For each category, we had set options for rating the severity and extent of each impact, usually using categories for cover class using the Daubenmire (1959) scale, and categories for expressing depth or length. Daubenmire's cover classes are defined as 0, <1, 1-5, 5-25, 25-50, 50-75, 75-95, and 95-100. When depths were measured, we used the centimeter categories of 0, <5, 5-10, 10-20, and >20, where 10 cm tends to correspond roughly to the primary rooting depth of many herbaceous meadow plants. Finally, when lengths were measured, we used the centimeter categories of 0, <30, 30-60, and >60. For each impact we also had a category for whether a clear horse sign such as a hoof punch or dung occurred.

Our five impact categories were: sod fragmentation, trails, bare bank, rills and gullies, and hummocking. We defined sod fragmentation as bare soil that appeared to be caused by humans or by pack stock (i.e.: we did not count sod fragmentation caused by rodents in this category), and rated its severity using cover classes and depth. We defined a trails as a clear, relatively linear break in the sod that was continued beyond several meters. We measured the number of trails, the length, and the depth. We defined bare bank as a section of the edge of a body of water such as a pond, spring, stream, or lake, which tended to be bare from the top of the edge down to the water. A healthy water bank has vegetation growing nearly down into the water, and along a stream or spring channel the channel is wider near the water level than at the top of the bank, and the vegetation tends to grow along this curve down to the water (Lutrick 2004b). We measured the length and depth of each bare bank, as well as noting if the bare bank was associated with a trail. We defined rills and gullies as erosion that tends to occur along a stream or spring channel upstream from a disturbance and tends to appear as if a second stream or spring channel is cutting alongside the original one, somewhat like a finger of erosion jutting out in an upstream direction. We measured the number of the rills or gullies, their width and depths, and whether they were associated with a stream or trail. Finally, we defined hummocking as an uneven ground with mini hills and valleys caused by trampling, and measured its cover class and depth (although we did not find any hummocking).

Unlike the vegetation data which was quantified with a regularly-spaced grid of quadrats, we measured the impact data using belt transects; that is, we walked along the transects set up in the same way as the vegetation transects and looked for impacts along the entire length of the transect on the eastern side of it. We decided to use a belt transect for impacts because they are much more rare than vegetation types and we wanted to be sure that we captured enough impacts to be able to analyze them. As Figure 1 illustrates, it would have been difficult to run statistical analyses on so few impacts that would have been captured using the quadrat method, thus the belt transects were necessary for answering our questions more completely. Taking data every 10 meters for the vegetation data made more sense because the patch scale of the vegetation data was significantly larger than that of the impacts.

Figure 1. A comparison of using 10 m x 10 m quadrats and belt transects to capture impact frequencies. The total impacts captured using the quadrat technique was only 42, compared to 278 impacts captured using the belt transect technique. Impacts captured were SF (Sod fragmentation), TR (Trails), BB (Bare bank), and RG (Rill/Gully).

When we found an impact, we put down a one-meter by one-meter quadrat at the nearest and lowest meter to the impact and measured cover classes, depths, lengths, and widths of the part of the impact that fell within that quadrat. In Ram Meadow, we changed the protocol so we measured the width of the trail itself, not just the part that fell within the quadrat, as we had in Duck Meadow. When we were unsure that an impact was natural or caused by humans or pack stock, we tended to err on the side of not including that area in our data. Finally, we also performed a belt transect on other rare features, such as the presence of ponds, springs, streams, and lakes, noting them whenever we came across them along our transects (see Figure 2 for a comparison of the quadrats and belt transects techniques for capturing these features). When we analyzed our data, all rare features collected in the belt transects were considered to be found only where we noted them, and all other meters along the transect were considered to be free of these features.

Figure 2. A comparison of using 10 m x 10 m quadrats and belt transects to capture water source frequencies. The total water sources captured using the quadrat technique was only 18, compared to 152 water sources captured using the belt transect technique.

Statistical Analysis

1) To calculate the relative abundances of the different impacts within and between meadows, a histogram was created showing the relative frequencies of each impact out of all the impacts to show which were most and least frequent and general trends.

2) The process of calculating the mean severity of each impact was more complicated because we had measured different attributes of each impact because they each appeared to us at the time to manifest themselves in different ways. Thus we measured cover class and depth for sod fragmentation, length and depth for bare bank, and number, length, and depth for trails and rills/gullies. In addition, cover classes, depths, and widths were all recorded as classes (ranges of values, as outlined above), while lengths and numbers were recorded as integers when measured. Therefore, to calculate severities for a given impact, we assigned classes the middle integer in their range, rounding up (for example, a cover class of “1-5%” was reclassified as “3”). Then, to compare the severities of each impact class, we decided to compare by “volumes” of impact, that is, to imagine that each impact was a different way of taking a “chunk” of soil or vegetation out of the ground. This approach was used to convert the severity of each impact type into a “common currency” to facilitate comparison. For sod fragmentation, “volume” was calculated by converting cover class to an integer, multiplying by 100 to account for cm 2 , and then multiplying it by the reclassified depth. Trail and rill/gully “volumes” were calculated by multiplying the number of the trails that fell in the quadrat by the reclassified width and depth, and then multiplying by 100 (since it was assumed that the trail length would be at least 100 cm). Since we only measured length and depth of bare banks, and width is not as clear-cut as the lengths we assumed for trails and rills/gullies, bare bank severities were not included in the severity calculations. To compare the severities for different impacts, a standard least squares ANOVA was run, followed by a Tukey HSD test to explore significance.

3) To examine the association between impact presence and water sources such as lakeshores, pond shores, streams, and spring channels, the proportions of the measured area that were “meadow-proper” and “water” were calculated and considered the “expected” values of the impact frequencies. Then a Chi-Squared test was run on the actual proportion of impacts that fell within “meadow-proper” and “waters” to see if the difference was significant. Finally, the same process was done for the categories of water within the “water sources” category (i.e.: lakeshores, pond shores, streams, and spring channels) to determine if there was a link on this level, with a correspond Chi-Squared test. This second process was not possible for Duck meadow because we did not collect data on whether impacts occurred in “meadow-proper” or “water.”

4) To explore the association between impact severity and water sources, a least squares ANOVA was run to explore the strength of the connection between severity of impacts and which type of water source they fell in, followed by a Tukey HSD test. Again, the comparison could only be made with the Ram meadow data for lack of Duck meadow data for this question.

5) To explore the association between impact presence and broad vegetation types, Chi-Squared tests were run on each impact type to compare its spread of vegetation types to that expected by the abundance of that vegetation type in the meadow. This test could also only be done with the Ram meadow data due to a lack of relevant data for Duck meadow.

6) To calculate the association between impact severity and the broad vegetation types, a least squares ANOVA was run to explore the strength of the connection between severity of impacts and which type of vegetation source they fell in, followed by a Tukey HSD test. Again, the comparison could only be made with the Ram meadow data for lack of Duck meadow data for this question.

Spatial Analysis

To approach a spatial analysis of the meadows, both sections of Ram meadow (Ram 1 and Ram 2) were brought into the spatial software ArcView by assigning UTM units to each quadrat that held data. Since the UTMs were only recorded for the starting point of each transect, that meant adding a meter to the northing for every meter farther along the transect we walked. Four broad vegetation types, mesic, wet, hydric, and a fourth category corresponding to lakes, ponds, streams, and springs, were reclassified in ArcView as the numbers one through four, respectively (a higher number corresponded to a higher moisture class). When this file was then kriged, it created a surface of vegetation types that was continuous. To make this surface discrete, the range of values from one to four were formed into four discrete categories, cutting them off within a range of values that was then considered to be mesic, wet, hydric, or lake/pond/stream/spring. Finally, since mesic was the greatest in quantity, it was made clear, so that the orthographic photo in the background could be seen.

Next, the impacts were entered into ArcView and given UTM units in the same way. Using the categories in ArcView of northing, easting, and severity, each impact was layered on top of the kriged vegetation type map and given a distinct color and shape. Then each was also given a range of sizes of the shape to correspond to increasing severity. Finally, a polygon surrounding the edge of the meadow was layered on top of all of these layers to outline where the meadow stopped.

RESULTS

1) What patterns can be seen in the relative abundances of impacts within and between meadows?

For both meadows, sod fragmentation is the most common and rills/gullies are the most rare impacts, with trails and bare banks falling in between (Fig. 3 and Table 1). In both meadows, more than half of the impacts were sod fragmentation, (78.0% and 54.5% in Ram and Duck meadows, respectively). In Duck meadow, trails represent 42.6% of the impacts, while this proportion is much lower at 7.9% in Ram meadow. Ram meadow has a higher proportion of impacts that are bare bank than Duck meadow (11.5% and 1.9%, respectively), but both meadows have less than 3% of impacts as rills/gullies, which are the rarest impacts overall.

Table 1. Relative Impact Abundances in Ram and Duck Lakes

Impact

Ram Meadow

Duck Meadow

Sod Fragmentation

0.78

0.55

Trail

0.079

0.43

Bare bank

0.12

0.019

Rill/Gully

0.025

0.0093

Figure 3. Each impact's proportion of the total impacts. Impacts include: SF (Sod fragmentation), TR (Trail), BB (Bare bank), and RG (Rill/Gully).

2) What patterns can be seen in the severities of impacts within and between meadows?

In both meadows, the trend is the inverse of that of abundance: mean impact severities increase from sod fragmentation to trails to rills/gullies (Fig. 4). Bare bank was not included in this comparison because of the difficulties in describing its severity as noted above. In each category, Duck meadow had a higher mean severity, and the difference was greatest in the rill/gully impact category. For both meadows, sod fragmentation had the lowest severity by far. For Ram meadow, there is a significant difference between the impact types in terms of mean severities (F = 49.1, DF = 2/245, p < 0.0001). Using a Tukey HSD test, all three impact types were shown to be different and sod fragmentation was significantly lower in mean severity, with rills/gullies as the significantly higher mean severity of the three impact types (LSMeans Tukey HSD < 0.05). For Duck meadow, there is also a significant difference between the impact types in terms of mean severities (F = 15.1, DF = 2/211, p < 0.0001). Using a Tukey HSD test, all three impact types were shown to be different and sod fragmentation was significantly lower in mean severity, with rills/gullies as the significantly higher mean severity of the three impact types (LSMeans Tukey HSD < 0.05). In Fig. 4, the different letters, A, B, C, indicate a significant difference in the mean severities of the three impact types. Between meadows, Duck meadow had higher severities in each category, with the greatest difference occurring in the rill/gully mean severity.

Figure 4. Mean severities calculated in cm 3 (“volumes”). Impacts: SF (Sod fragmentation), TR (Trail), and RG (Rill/Gully). The difference between the three impact categories is significant to the 0.05 level because the Tukey test showed three distinct levels for each meadow, as indicated by the letters A, B, and C.

3) What is the association between impact presence and water sources such as lakeshores, pond shores, streams, and spring channels?

For both meadows, the proportions of the meadow-proper vs. water sources (pond, lake, stream, spring channel) that are impacted are very close for observed and expected (Fig. 5). However, for Ram meadow, there is a significant difference (Pearson X 2 = 8.52, DF = 1/31, p <0.0035) between the observed and expected values, in other words, there is a greater proportion of water impacted than would be expected by chance alone, because a greater proportion of the impacts fall in water than expected from the amount of water available in the meadow. For Duck meadow, in contrast, there is no significant difference between the expected and observed values of impacts for the water vs. the meadow-proper (Pearsons X 2 = 1.87, DF = 1/4, p < 0.1718).

When the difference between observed and expected proportions of impacts are examined between water sources in Ram meadow (data is not available to perform the same test for Duck meadow), there are not enough data for a significant difference to be detected (since there were only four impacts in water sources, and 3 of them occur in streams and 1 in spring channels).

Figure 5. Expected impacts refer to the proportion of Ram or Duck meadow that is meadow-proper or water sources. Observed impacts are the proportion of impacts that are meadow-related vs. water source-related for each meadow.

4) What is the association between impact severity and these water sources for each impact?

Within Ram, looking at the severity of the impact bare bank for water the water sources spring channels, streams, pond shores, and lakeshores, there is a trend (Fig. 6). The severest impacts by far occur in spring channels, followed by lakeshores, with pond shores and streams having similar mean impact severities. According to the Tukey HSD test, there was a significant difference between spring channels and streams and between spring channels and pond shores (F = 3.16, DF = 3/30, p < 0.0406); however, the difference between any other pair of water sources was not significant.

Figure 6. Mean severities of impacts that fall in each of four water sources found in Ram meadow. The difference between mean severities is significant if two water sources are not connected by the same letter, with 0.05 significance according to the Tukey test. In other words, there is no significant difference between spring and lake, because they share the letter A, or between lake, pond, and stream, because they share the letter B. However, there is a significant difference between spring and pond and between spring and stream because they do not share letters.

5) What is the association between impact presence and broad vegetation types such as xeric, mesic, wet, and hydric soil moisture ratings?

This comparison was made on the Ram meadow data only due to a lack of coherent Duck meadow data for the purpose. For all four impact types, there is a significant difference between the expected and observed values of the impact proportions in each vegetation type (Fig. 7). Sod fragmentation, bare banks, and rills/gullies tended to occur at a lower than expected proportion in mesic and hydric areas, and a higher than expected proportion in wet areas; trails only occurred in mesic areas. For sod fragmentation, there is a significant difference between the observed proportion of sod fragmentation in each vegetation type and the value expected by the proportion of the meadow that is that vegetation type (Pearsons X 2 = 72.68, DF = 2/217, p < 0.0001). In sod fragmentation, impacts tended to occur less than expected in mesic and hydric areas and more than expected in wet areas. Trails only occurred in mesic areas, which is clearly a significantly higher proportion than expected, and a significantly lower proportion of occurrence in wet and hydric areas than expected. For the impact bare bank, there is significantly less impacts than would be expected in mesic and hydric areas, and significantly more in wet areas (Pearsons X 2 = 38.19, DF = 1/28, p < 0.0001). Rills/Gullies significantly did not occur in hydric areas, and only occurred in mesic and wet areas, however the difference between mesic and wet areas was not significant.

Figure 7. Black boxes refer to the proportion of Ram meadow that is mesic, wet, or hydric. Gray boxes refer to the proportion of each impact (sod fragmentation, trail, bare bank, or rill/gully) that falls in mesic, wet, or hydric areas.

6) What is the association between impact severity and these broad vegetation types for each impact?

This question was only evaluated for Ram meadow due to a lack of coherent Duck meadow data. There appears to be a trend (Fig. 8) with wet vegetation having the highest impact severities, but the difference is not statistically significant (F = 1.119, DF = 2/27, p < 0.328).

Figure 8. Mean severity of impacts found in the vegetation types mesic, wet, and hydric in Ram meadow. According to the Tukey test, the difference between the three mean severities is not significant.

7) What patterns can be seen in the spatial distribution of impact presence and severity?

When Ram 1 was kriged (Fig. 9), it was first a question of whether the kriging corresponded well to the underlying vegetation types. Looking at the orthographic photo underneath the kriged map it can be seen that a large pond in the lower right corner was captured, as well as a pond in the upper left corner that does not appear in the photo but was present when we ran transects. Several points along the stream that is visible in the orthographic photo were captured, although much of the stream was not captured.

From the spatial distribution of impacts across the meadow, there appear to be large areas of mesic that are not impacted (for example, the upper left corner of the meadow), and the pond in the lower right corner is not impacted within it. Otherwise, there appear to be a high concentration of impacts along the edge of the pond and along the left edge of the meadow leading into a wet area. Few hydric areas appear to be impacted. The majority of the impacts, instead, appear to affect mesic areas and to a lesser degree wet areas (which represent a significantly smaller portion of the meadow).

The kriged map of Ram 2 was not included because due to the odd shape of the meadow and the fewer data points, the kriged map did not lend itself well to illustrating spatial patterns. This demonstrates the limitations of using kriging for showing spatial patterns because with fewer data points or a meadow that is laid out in a less clumped area does not show patterns well.

Figure 9. Kriged map of Ram 1 meadow, showing vegetation types and the four impacts with their severities in equal-interval categories of low, medium, and high.

DISCUSSION

From the results, it is clear that there are some preliminary patterns in the abundances and severities of impacts, and where they fall in the meadow. However, there are many opportunities for improvement upon the approach in the future.

Abundance Patterns

There is a clear pattern of impact abundance, and that sod fragmentation was the most common and rills/gullies and hummocking the least common. Previous research has not identified the most abundant impacts within meadows; however, it has tended to focus on several impacts disproportionately: grazing, trampling, and trails, which we might be able to hypothesize is because previous studies have considered these the most important impacts for some reason, perhaps because they were the most common. Our study supported the unstated position of previous research that the process of hooves hitting the ground and horses rolling in the dirt, a result we measured as sod fragmentation, is one of the most abundant impacts of pack stock. Duck also had a high proportion of trail impacts, which is another impact more widely studied in the literature than bare banks and rills/gullies. The rarest impacts in both meadows were, of course, hummocking (which was not found at all), and rills/gullies, which have been studied proportionately very little.

Severity Patterns

The data support the idea that some rarer impacts have a higher severity. No studies have been done to compare the severities of various impacts within meadows using a common currency. Interestingly, the impact severity tends to be the inverse of the abundance: that is, in these two meadows, impacts such as sod fragmentation that had high abundances had low severities, and impacts such as rills/gullies that had low abundances tended to have high severities. This suggests a strong need for more research into these impacts, because although they may be rare, they tend to be significantly more severe than more common impacts, perhaps because they tend to be very localized, such as at a point along a spring where pack stock cross, causing a gully to form upstream because the crossing acts as a sort of funnel, bringing impacts to a peak at the stream. The data seem to support the idea that more common impacts might be less intense because they are more spread out across the meadow. Alternatively, the data could support the idea that the impacts are a continuum of bare ground (i.e. erosion), in other words, that more impacts to an area can cause sod fragmentation to become trails, which with more impacts could become rills or gullies.

One reason that impact severity has not been compared may be because of the difficulties in comparing disparate impacts that do not appear to scale to each other. However, it is possible that this comparison may be able to be made because some impacts are similar to each other in process. The strongest case for a comparison is sod fragmentation and trails since the process of using a trail or a trail forming is similar to the trampling, rolling, and grazing that can cause sod fragmentation. This study considered all impacts to be variations on a “chunk” of sod/vegetation being taken off the surface of the land due to disturbance; however, this assumption may be one of the weakest points of the comparison, due to the different processes at work between sod fragmentation/trails and rills/gullies. Due to our lack of data for a third dimension of bare banks, it was not possible to include this impact in the comparison.

Interestingly, Duck meadow had higher severities in each category, which appears to run contrary to the use levels of the recent past (which showed Ram meadow with a significantly higher number of pack stock nights per year in the past three years). It is possible that this is due to slight differences in the data collection approach for each meadow. It is also possible that Duck meadow is still showing signs of historically high use, which is impossible to quantify because no records were kept. It is also significant that Duck had a significantly higher level of trails than Ram, which could be because of its location so close to a main trail head. Therefore it is suggested that that the Forest Service could also focus on quantifying not only the number of pack stock nights at each meadow, but also day traffic that could be causing the majority of the impacts at Duck.

When the Forest Service surveyed these two meadows, they found that both meadows had trailing, and noted that Ram's trails were more severe. Their analysis of the sod fragmentation and rills/gullies were not as clear-cut. However, our data suggest that Duck meadow had more severely impacted trails, although the difference was not large.

Impacts and Water Sources

The idea that there is a strong association between impact presence and water sources is only supported by data from Ram meadow. Past studies have suggested the sensitivity of water sources, but no studies have quantified the effects of pack stock on water sources. We looked at one major impact that affects lakeshores, pond shores, streams, and spring channels: bare banks, a form of erosion. Looking at impact presence and these water sources, there was a significant association in Ram meadow only; the difference was not significant in Duck meadow. This means that in Ram meadow there was data to support the idea that there might be a higher proportion of water-related impacts than might be expected from the proportion of water sources in a meadow; however, Duck meadow does not support this idea. Thus it supports the idea that water sources might be more sensitive to having a higher abundance of impacts than meadow-proper. However, a vast majority of the observed stock disturbances were located in the meadow vegetation itself. Thus future monitoring should not focus only on stream, spring, and lakeshore disturbances.

The idea that there is a strong association between impact severity and specific water sources was supported by the data. Looking at impact severity and different water sources for each impact, the data support the idea that the most impact-sensitive areas of water (as shown by a higher mean severity) are spring channels, followed by lakeshores. Unfortunately, there is not data to compare the severities of bare bank in different water sources for Duck meadow. We hypothesized that areas easily approachable by pack stock for drinking might be especially susceptible to having more severe impacts, but it is impossible to see from this data if this idea is supported. It may support the idea that spring channels are especially sensitive to having severe impacts, but there is not enough data to make more than a preliminary hypothesis. Although the data were not conducive to this comparison for Duck meadow, it was observed that the majority of severe impacts to streams and spring channels in this meadow were associated with trails running across or near these water sources.

When the Forest Service looked at impacts to water sources in these two meadows, they noted that both meadows had moderately trampled or chiseled spring channels. They also found that Ram had no stream impacts; however, our data suggest that there were stream impacts, although they were less severe than spring and lake shore impacts.

Impacts and Vegetation Types

The idea that there is a strong association between impact presence and broad vegetation types was supported, but not in the linear way expected. It was expected that the wetter the vegetation type, the more impacts would occur. Instead, more than the expected proportion of impacts occurred in wet areas, while less than expected occurred in mesic and hydric areas for sod fragmentation, bare banks, and rills/gullies, while all trails occurred in mesic areas. Past studies that looked at impacts and grazing and trampling found that wetter soils were more vulnerable to trampling, but that an intermediate soil moisture level often meant less impacts. One study suggested that wetter soils recovered faster but drier soils were less likely to be impacted. However, it is difficult to tell resistance from resilience in our meadows because our data was not looking at long-term patterns. It may be that the wet areas are most sensitive because they are closest to where a horse might walk if it were trying to drink from a water source, but that it would not enter hydric areas by its nature, and that mesic areas because they were drier would show less impacts.

The fact that all trails occurred in mesic areas could suggest several ideas. The trails could have been built by humans to avoid wet areas, or created over time by people avoiding wet areas. On the other hand, trails by their very nature could tend to dry out any wetter areas by exposing bare soil to the elements. Thus for all four impacts examined, a better knowledge of human and horse behavior could shed some light on the questions. For example, from our data, it is not clear if impacts are more severe in wet vegetation because pack stock visit these areas more often, or because these areas are simply more likely to show strong impacts even with very little visitation. However, since there is still a high proportion of sod fragmentation that occurs in mesic areas, the data also support the idea that although pack stock may spend a relatively proportional (with regards to the amount of that vegetation type available in the meadow) amount of time in each vegetation type, wet areas may be more likely to show impacts, to have impacts last longer, or be more severe.

The idea that there is a strong association between impact severity and broad vegetation types was not supported by the data. The highest mean severity occurred in wet areas, and the lowest in mesic areas, with hydric areas receiving an intermediate level of impact severity; however, this pattern was not statistically significant. More studies must be done to draw significant conclusions about the relationship between impact severity and vegetation types.

Spatial Patterns of Impacts

The hypothesis that most impacts are associated with wetter vegetation types and water sources is supported in some ways. From the kriged map of Ram 1 vegetation overlaid with impacts with their severities, it appears that there is some pattern around water sources and wetter areas with more impacts. There are few blocks of wet that do not have some impact near them, and it appears that hydric areas have few impacts. There are large areas of mesic that do not have any impacts near them. All of these observations support the general trend that a higher proportion and more severe impacts than expected occur in wet areas, and that hydric and mesic areas are proportionally less affected.

Shortcomings of Approach

There were many shortcomings of our approach to surveying the meadows to look for patterns that have affected that broadness with which we can apply our results. By only surveying two meadows, and for several of our questions, only one meadow, our data was skewed toward incompletely answering some of our questions. For example, there was no xeric vegetation in Ram meadow, which meant that we could not fully assess the higher wetness-higher impacts idea. Neither meadow had any hummocking, so we could not assess this impact at all. Also, because they were only two meadows, and they were five miles apart and similar in elevation, we cannot account for many variations in meadows that may occur throughout the Sierra Nevadas. Therefore, it cannot be assumed that most meadows in this area of the Sierra Nevadas are primarily mesic or that the most common impact was sod fragmentation.

The attributes of impacts that we measured were not the same in Ram and Duck meadows, which led to some difficulties in calculating severities. These attributes were not very conducive to comparing severities, either. The “volumes” method of comparing severities may be applicable, but it needs to be tested further and run past some “experts” before it can be used as a truly reliable measurement of severity.

Important Modifications for Further Study

To truly approach the questions asked in this study, many repetitions of the study across a much greater gradient of meadow environmental and impact factors need to be performed. To be able to compare severities better, a few things should be measured differently. For sod fragmentation and trails and rills/gullies, the cover class and length/width measures need to scale better, since cover class could account for up to 100% of a quadrat, while the trail and rill/gully measurements only went up to a width of 60 cm. This is easily fixed by allowing trail and rill/gully measurements to range from 0 to 100 cm, and the assumption that trails are always at least as long as a quadrat seems to make sense. For bare bank, both the width and length should be measured so it can be included in severity calculations. To approach the idea of severity, a way to scale depth vs. cover measurements should be approached from the literature and from experts in the field to determine if a “volume” approach makes sense. The impact “rills/gullies” could also be split up, since all of what we called this category was gully and it seems clear at the end of the study that rills and gullies are two distinct impacts caused by different processes.

CONCLUSIONS

The results of this study, although preliminary, have some implications for the assessment, monitoring, and protection of alpine meadows in the Sierra Nevadas. The most sensitive areas in a meadow seem to be wet areas, but not necessarily hydric areas. There is some evidence to support the idea that water sources may be especially vulnerable, but it was not supported in Duck meadow. The rarest impacts in these two meadows were the most severe in nature, so it may be that only a few changes in behaviors of pack stock to meadows could make a large difference, especially since some of the worst impacts are bare bank and rills/gullies which are often associated with pack stock seeking out water. It seems disproportionately important, then, to monitor places where pack stock drink and wet areas in general when surveying meadows.

To approach these questions with a more thorough background, there are several main research needs outside the scope of this particular study. A behavior study of humans and pack stock on where they tend to go in meadows and how these impacts are being formed would help explain several of the patterns. A long-term study on the same impacts in various meadows to look at resistance versus resilience to impacts would also be relevant and put certain questions in perspective. There is a clear need for studies that address pack stock impacts in particular in alpine meadows.

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