Classification of West Creek Cliff: Analysis Based on Dimensional Data and Sedimentary Features, Connor Newman

CLASSIFICATION OF WEST CREEK CLIFF: AN ANALYSIS BASED ON DIMENSIONAL DATA AND SEDIMENTARY FEATURES

Abstract

 Sandstone bodies of varying size and internal architecture comprise many cliff-forming outcrops in the Douglas Creek Arch of the Piceance basin in north-western Colorado. The goal of this study is to characterize the depositional environment of one of these sandstone outcrops (West Creek Cliff) based on its dimensions and on sedimentary features observed in the field. This was accomplished using a synthesis of classification systems set out in Gibling (2006), Cole and Cumella (2005) and Pranter et al. (2009). Dimensional data was interpreted using photomosaics incorporated with outcrop data, while sedimentary features were noted and subsequently compared with similar features of known facies associations in the literature. The results of this study suggest that the depositional setting of West Creek Cliff was a low energy sinuous fluvial environment. Dimensional data reveals several separate sandstone bodies with apparent widths ranging from 85.6 ft. (26.1 m) to 96.5 ft. (29.4 m) and average thicknesses ranging from 4 ft. (1.22 m) to 11.6 ft. (3.53 m). Further analysis of this data gives apparent width vs. thickness (W:T) ratios ranging from 7.4 to 24.1. Using this dimensional data and interpreted sedimentary features associations the separate sandstone bodies that make up West Creek Cliff were classified. This classification allows for greater understanding of the different types of sandstone bodies that can be modeled, although WCC itself was not modeled due to questionable subsurface analogy and outcrop exposure.

 

 

 

Introduction

The interpretation of depositional environment of sedimentary bodies is usually conducted using the internal architecture of the body only (Gibling, 2006). This may yield results which are not as accurate as can be achieved by using multiple data sets to understand the depositional setting of a sedimentary body. For this reason, the aim of this paper is to classify the depositional environment of sandstone bodies based off of two data sets; the dimensions of outcrop surfaces and the sedimentary features present. This method was applied to one specific sandstone outcrop in the Douglas Creek Arch of the Piceance Basin in north-western Colorado (Figures 1 & 2). This cliff was named West Creek Cliff and will subsequently be referred to as WCC.       

WCC is located along West Creek approximately one mile west of Colorado State Highway 139 at mile marker 46. WCC is composed primarily of silty-sandstone and is 29.8 ft. (9.1 m) high with varying widths depending on vertical position (Figure 3). WCC is a member of the sandstone-poor lower Williams Fork formation (Figure 4). WCC was chosen to be studied due to the ease of access to all areas of the outcrop and due to the interesting geometry at both the outcrop scale and internal surfaces scale. By identifying the separate sandstone bodies that make up WCC the changes in depositional environments between sandstone body deposition can be examined. This is important because sandstone comprises significant reservoirs of hydrocarbons that make the Piceance Basin economically valuable (Pranter 2009).

One of the primary goals of previous studies based on dimensional analysis is to use outcrop data to correlate and map sandstone bodies within the subsurface. This is not attempted in this discussion as the outcrop is relatively small and isolated (Figure 5) and subsurface analogy is questionable. The primary use of dimensional data analyzed here is to add to the data set used in modeling the dimensions of similar depositional style bodies.

 

 

 

 

Figure 1: Map of Piceance Basin, roughly outlined with Mesa Verde outcrops shown in green. Douglas Creek Arch is in upper left (northwest) corner of map with study area of West Creek highlighted by yellow rectangle. Modified from Pranter et al. (2009).

 

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Figure 2: Location of WCC along Colorado State Highway 139. Location denoted by blue dot.  Waypoint data obtained using a Trimble Geo HX 2008 Series Global Positioning System.

 

       
 
   

= 5 ft. (1.5 m)

 

 

 

 

Figure 3: Photomosaic of WCC with separate sandstone bodies outlined. Jacob Staff just left of center of sandstone body three is 5 ft. (1.5 m) tall for scale.

 

 

 

 

 

 

 

Figure 4. General stratigraphic column showing nomenclature for Douglas Creek Arch and surrounding basins. Study area for WCC lies in the Kmvc member, shown in yellow box. Modified from Cole (2009).

 

 

 

Figure 5. WCC circled in red with scale denoted by arrow bar. This shows the degree to which WCC is isolated from other, larger sandstone bodies.

 

 

 

 

 

 

Geologic History

The Piceance basin is an asymmetrical northwest-southeast trending elongated sedimentary basin formed due to uplifts corresponding to the Laramide orogeny (Pranter et al. 2009). During the upper Cretaceous, the basin was part of the much larger Rocky Mountain foreland basin before later being isolated by uplift. During this time the basin was on the western shore of the Cretaceous Interior Seaway (Johnson and Flores, 2003). This alluvial plain environment represents the most likely depositional setting for WCC (shown in Figure 6). As the Laramide orogeny progressed during the early Paleocene, uplifts (such as the Park and Sawatch ranges) began to isolate various parts of the Rocky Mountain foreland basin and to cause drainage patterns to change from predominantly northeastern direction to a northern direction (Johnson and Flores, 2003). The earlier northeastern flow direction suggests that the White River Uplift had not yet occurred. This indicates that the main river system during this time period may have been to the east of the Piceance Basin (Johnson and Flores, 2003).

In the late Paleocene the Piceance Basin was dominated by a low energy paludal environment. This environment persisted until the early Eocene when the White River and Uncompahgre uplifts increased the basin’s relief and sediment transport energy (Johnson and Flores, 2003). This uplift caused the drainage source of the Piceance Basin to shift westward, further into the trough of the main Piceance Basin.            

            According to Johnson and Flores (2003) the early Eocene brought a freshwater lacustrine environment to dominate the Piceance Basin, and the Douglas Creek Arch in particular. The early development of Lake Uinta in this time period may be directly linked to the White River uplift as the uplift caused rapid subsidence to occur on its western flank, deepening the basin as a result. This lake and subsequent freshwater and saline lakes in the area account for the most abundant oil-shale deposits in the world (Johnson and Flores, 2003).

Figure 6: Paleogeographic map showing depositional environments of the Piceance Basin in latest Cretaceous. Approximate study area of WCC given by yellow box. Modified from Johnson and Flores (2003).

Methods

In determining the dimensions of sandstone bodies it is important to define the terms used to describe sandstone bodies and the term sandstone body itself. For the purposes of this analysis a “sandstone body” is defined as a three dimensional volume of sandstone with interbedded mudstone that has distinct sedimentary features and recognizable contacts from surrounding sedimentary beds. The term “apparent width” is defined as the measurable linear horizontal distance between one above ground termination or loss to diving into subsurface of the sandstone body in question to another above ground termination/loss to subsurface. The term “thickness” is defined as the measurable vertical distance from the apparent lower terminus to apparent upper terminus of the sandstone body, measured orthogonal to the local ground surface. This means that the thickness value used is also “apparent” as the true dimensions cannot be known.

             To define the edges of sandstone bodies the program Microsoft PowerPoint was used in conjunction with field notes. A photomosaic was created by merging three photos taken from one location. Using the Jacob Staff in the photomosaic for scale, a ratio was obtained relating distances in PowerPoint to real-world distance. This allowed for the comparison of field notes including recorded distance with visual inspection and distances computed with PowerPoint. Apparent width and thickness were both measured using this same method. Apparent width was obtained by measuring the maximum width from one end of a sandstone body to the other in PowerPoint and the ratio previously mentioned. Thickness again used this ratio and the average of five different thicknesses measured in PowerPoint at varying horizontal position within the sandstone body in question. The varying horizontal positions used for this computation were regularly spaced. There is some error inherent in this method as the “outcrop slice” of WCC is not known. The outcrop as it is preserved today may be a view perpendicular to paleoflow or may be in some way oblique to paleoflow. This would cause the apparent width to differ from the actual width of the fluvial channel which formed WCC. All paleocurrent measurements were taken using a Brunton compass and rose diagrams were created using the program Oriana. The location of WCC as given on Figure 2 was taken from global positioning system measurements using a Trimble Geo HX 2008 Series GPS device. All gamma ray measurements were taken using a RS-125 Super Spec scintillometer and are reported in counts per second (cps).

 

Figure 6: Stratigraphic column to which WCC belongs. WCC lies in the Kmvc member. Modified from Cole (2009).

Results

 

The aforementioned methods yield three separate sandstone bodies that make up WCC. These sandstone bodies show distinct sedimentary features and sharp contacts with each other. The dimensional data for these sandstone bodies is given in Table 1. The net to gross percentage of the interval containing WCC is approximately 43.31 % sandstone and 56.69 % siltstone, mudstone or claystone (Harper, 2011).

Sandstone body one lies above a 2.5-3.3 ft. (0.75-1 m) thick (depending on horizontal position) layer of mudrock that separates it from sandstone body two. The surface between sandstone body one and the underlying mudrock appears to be erosional and sharp. Sandstone body one contains the most well developed sedimentary structure present in WCC in the form of small-scale trough cross stratification (Figure 7). This trough stratification appears in a view perpendicular to paleoflow, in a view parallel to paleoflow this would appear as ripple stratification. The paleocurrent values for these and all other structures are shown in Figure 8, with corresponding data given in Table 2. Sandstone body one is made up of fine sand.

Sandstone body two lies above an erosional surface that caps sandstone body three. Sandstone body two displays a darker color than sandstone body three, which one of its distinguishing characteristics. Sandstone body two is also more structured than sandstone body

 

 

Sandstone Body Number

Apparent Width ft. (m)

Thickness ft. (m)

Apparent Width to Thickness Ratio (W:T)

1

96.45 (29.39)

4.00 (1.22)

24.09

2

88.02 (26.83)

4.33 (1.32)

20.32

3

        85.64 (26.12)

11.58 (3.53)

7.39

 

Table 1. Dimensional data for sandstone bodies contained within WCC.

 

 

 

Data Type:

All Cross Stratification

Trough Cross Stratification

Number of Observations:

5

4

Mean Vector (azimuth):

144.214  ͦ

156.223  ͦ

Circular Standard Deviation:

29.014  ͦ

12.965  ͦ

 

Table 2.  Paleocurrent data for all types of cross stratification and for trough cross stratification only. Both the mean vector and the standard deviation are affected by the presence of one measurement. This measurement is from sandstone body three, which differs in fluvial body type from sandstone bodies two and one; this explains the different paleoflow direction.°

 

 

 

 

Figure 7: Small-scale trough cross stratification within sandstone body one. Several                 paleocurrent measurements were taken from this sandstone body. Lens cap is 0.22 ft. (7 cm) for scale.

 

 

 

 

 

 

 

A.)

B.)

                                        Figure 8. A.) Paleocurrent rose diagram for all cross stratification. B.) Paleocurrent rose diagram for trough cross stratification only.

three as it contains wavy bedding and trough cross stratification throughout. Sandstone body two is made up of fine sand much like sandstone bodies three and one but contains a smaller percentage of mud than sandstone body three, making it more resistant to erosion and causing it to protrude out from the outcrop and form a small overhang (Figure 3). Unlike sandstone body three there are no dipping surfaces within sandstone body two.

Sandstone body number three is the largest in volume, due to its greater thickness than other sandstone bodies. Sandstone body three appears to have an erosional contact with the surrounding mudrocks, but topsoil largely hides this contact from view. Sandstone body three is made up of fine sand intermixed with mud. Sandstone body three contains numerous fine grained organic drapes, ranging in thickness from millimeters to several centimeters (Figure 9). There are multiple lenticular bodies within sandstone body three (Figure 10) that display dips of ≈10 degrees (the lenticular body in Figure 10 has a dip of 11 degrees). Sandstone body three is largely structureless although it rarely displays ripple foresets, wavy laminations and planar laminations.

All sandstone bodies contain prominent calcareous concretions (most likely siderite). These concretions commonly form at erosional boundaries but are also found within beds. Figure 11 shows one example of a large concretion at the erosional surface between sandstone bodies two and three.      

 

                                                                                                                                                

 

 

 

Figure 9: Organic laminations within sandstone body three. Laminations are millimeters thick to the right of the lens cap while they are several centimeters thick in the bottom left corner. Lens cap is 0.22 ft. (7 cm) for scale.

 

 

 

 

 

 

Figure 10: Lenticular body within sandstone body three. This particular body has a dip of 11 degrees. Lens cap is 0.22 ft. (7cm) for scale.

 

 

 

 

 

 

 

Figure 11: Calcareous concretion (most likely siderite) at erosional surface between sandstone bodies two and three. Grain size card is 0.32 ft. (10 cm) for scale.

 

 

 

Discussion

Following the recognition and subdivision of WCC into separate sandstone bodies it is possible to assign each of these sandstone bodies to a specific depositional environment. In this pursuit both the sedimentary features present within sandstone bodies and the dimensions of the sandstone bodies were used.

            Sandstone bodies one and two fit into the same model for depositional styles, and therefore will be discussed concurrently. The presence of small-scale trough stratification, grain size of fine sand and W:T ratios of 24.1 (sandstone body one) and 20.3 (sandstone body two) support the conclusion that these sandstone bodies most likely represent crevasse-splay deposits. Both of these sandstone bodies display prominent small-scale trough cross stratification (Figure 7). The position of this trough stratification can be seen on the completed measured section (Figure 12). This was noted by both Cole and Cumella (2005) and by Pranter et al. (2009) as being present in what were identified as crevasse-splay deposits. Gibling (2006) discusses the dimensions of crevasse splay deposits and notes that they commonly display W:T ratios between 5 and 20 but that there are modern examples of river systems with avulsion deposits with W:T ratios over 20 (sandstone body 1). The grain size of fine sand noted also agrees with established grain size of crevasse-splay deposits (Cole and Cumella 2005, Pranter et al. 2009). Worth noting is that both sandstone bodies one and two lack the bioturbation that was noted in Cole and Cumella (2005) and Pranter et al. (2009) as being associated with crevasse-splay deposits. This may be due to increased aggradation rate or due to the transient nature of avulsion deposits (Gibling, 2006). All paleocurrent measurements corresponding to trough cross stratification were taken from these two sandstone bodies. These paleocurrent observations may not represent the paleoflow direction of the river system as a whole. This is due to the position of avulsion channels within in the main river channel. Near the edges of

 

 

 

Figure 12: Measured section of WCC.

 

 

 

 

 

 

the channel (where avulsion channels form) the paleocurrent measurements tend to be oblique to paleoflow (Bridge, 2006).

The sedimentary features including ripple foresets, wavy laminations and planar laminations, grain size of fine sand, and W:T ratio of 7.4 suggest that sandstone body three most likely represents a low energy sinuous river deposit. Sandstone body three displays poorly defined lateral accretion sets (evident from dipping surfaces seen in Figure 3) which show aggradation from left to right. These lateral accretion sets were noted by Cole and Cumella (2005) and Pranter et al. (2009) as being associated with sinuous rivers that did not develop meander belts. The lack of similar deposits close in proximity to WCC supports this possibility. The dimensional data for sandstone body three also supports the formation through a sinuous river system. The common range of W:T for channel deposits of this type is 5-50 but with the majority of deposits below 15 (Gibling, 2006). The relatively rare sedimentary structures within sandstone body three (ripple forests, wavy laminations and planar laminations) is puzzling. This may be due to the fact that sandstone body three contains a large fraction of mud. This mud would make the outcrop surface of sandstone body three less resistant to erosion and therefore may result in structures being harder to identify. The paleocurrent measurement taken from sandstone body three off of a ripple foreset most likely represents a direction closer to the mean transport direction of the main river channel as it was not near the margin of the channel (Bridge, 2006). This paleocurrent value of 90 degrees agrees with the drainage pattern of the Douglas Creek Arch during the latest Cretaceous, as seen from rose diagrams on Figure 6. The grain size (silt to fine sand) of sandstone body three also agrees with the range of grain sizes given as being associated with sinuous river systems in Cole and Cumella (2005) and Pranter et al. (2009). The organic laminations found in sandstone body three suggest multiple changes in flow velocity during deposition, allowing for grading from fine sand to mud sized organic particles.

Another possible interpretation for sandstone body three is a tidally influenced fluvial system. This conclusion is supported by the fine grained organic laminations. Other evidence of tidal influence is lacking however. One example of this is the lack of paleocurrent observations in the opposite direction of the average flow direction as was noted by Bridge (2006) as being found in tidally influenced fluvial systems.

            The presence of calcareous clasts within all sandstone bodies unfortunately does not restrict the depositional environment, as these may form in a range of depositional settings. Mozley and Wersin (1992) suggest that the isotopic composition of siderite may be used as an indicator of depositional environment. This analysis was not conducted in this research as isotopic composition of clasts was not available. The conditions under which siderite is formed in continental settings is in a reducing environment (Mozley and Wersin, 1992). This supports the interpretation of a low energy environment, as stagnant water represents a reducing environment.

            It has been previously noted in this paper that many analyses concerning dimensional data of sandstone bodies have been used for modeling purposes. Data obtained in this study may or may not be used in this way; it is useful to discuss the reasons for this. Bridge (2006) discusses problems in using outcrop as an analog for subsurface conditions. One such problem is that outcrops are rarely extensive enough to determine the overall geometry of the complete deposit. This is true of WCC as only one side of the deposit outcrops on the surface, meaning the true subsurface orientation is not known. Porosity and permeability are also important inputs to modeling programs (Gibling, 2006). These values are lacking for WCC as the rocks in outcrop have been too extensively weathered to give reliable subsurface values. The final reason that modeling has not been attempted is that channel body type changes as one moves upward in section. This has been identified by Gibling (2006) as a major mistake in many models. This is due to the different climatic and geographic conditions under which these channel bodies likely existed.

 

Conclusion

Through the use of both dimensional data and sedimentary features it is possible to gain a better understanding of depositional environments of sandstone outcrops. By using this method the depositional environment of the different sandstone bodies which make up WCC have been interpreted. These interpretations are that sandstone bodies one and two most likely represent crevasse-splay deposits and that sandstone body three most likely represents a low energy sinuous river deposit. Dimensional data of the separate sandstone bodies yields ranges of apparent width of 85.6-96.5 ft. (26.1-29.4 m) and average thickness values ranging from 4-11.6 ft. (1.22-3.53 m). The results of this study show that WCC was most likely once part of an alluvial plain which was crossed by low energy sinuous rivers. These rivers most likely did not develop large meander belts. Avulsion events which created crevasse-splay deposits were common in the area as almost half of the preserved outcrop at WCC displays this type of fluvial body. The implications of this study are that accurate modeling of such sandstone bodies and outcrops would be furthered by subsurface knowledge gained from well core data and from more completely exposed outcrops.

 

 

 

References

Bridge, J. S., 2006, Fluvial facies models: Recent developments, in Posamentier, H. W. and Walker, R. G., eds., Facies models revisited: SEPM Special Publication 84, p. 85-170.

Cole R.C. and Cumella S.P., 2005, Sandstone-Body Architecture in the Lower Williams Fork Formation (Upper Cretaceous), Coal Canyon, Colorado, with Comparison to the Piceance Basin Subsurface, The Mountain Geologist, v. 42, no. 3, p. 85-107.

Gibling M. R., 2006, Width and Thickness of fluvial channel bodies and valley fills in the geological record: A literature compilation and classification, Journal of Sedimentary Research, v. 76, p. 731-770.

Harper, E. S., 2011, Stratigraphic variability of sandstone-body types and dimensions in the Mesaverde Group, Douglas Creek Arch, Colorado: Implications for sandstone-body connectivity in Piceance Basin reservoirs: M.S. thesis (in prep), University of Colorado, Boulder, p. 150.

Johnson R.C., Flores R.M., 2003, History of the Piceance Basin from latest Cretaceous through early Eocene and the characterization of lower Tertiary sandstone reservoirs, in K. M. Peterson, T. M. Olson, and D. S. Anderson, eds., Piceance basin 2003 guidebook: Rocky Mountain Association of Geologists, p. 21-62.

Mozley P.S., Wersin P., 1992, Isotopic Composition of siderite as an indicator of depositional environment, Geology, v. 20, p. 817-820.

Pranter et al., 2009, Sandstone-body dimensions in a lower coastal-plain depositional setting: Lower Williams Fork Formation, Coal Canyon, Piceance Basin, Colorado, AAPG Bulletin, v. 93, no. 10, p. 1379-1401.

 

Bromus Tectorum Soil Conditioning, James O’Connor

Bromus tectorum Soil Conditioning

 

 

 

 

 

A thesis submitted to the

University of Colorado at Boulder

In partial fulfillment to receive

Honors designation in

Environmental Studies

December 2011

 

 

 

 

 

 

 

Thesis Advisors:

Timothy Seastedt, Ecology and Evolutionary Biology, Committee Chair

Dale Miller, Environmental Studies

William Bowman, Ecology and Evolutionary Biology

 

 

 

All rights reserved

Table of Contents

Abstract------------------------------------2

 

Author’s Note ----------------------------2

 

Introduction -------------------------------4

 

Background -------------------------------5

 

Materials and Methods -----------------21

 

Results ------------------------------------30

 

Discussion -------------------------------39

 

Appendices ------------------------------48

 

Bibliography ----------------------------52

 

 

 

 

 

Abstract

 

            The exotic grass, Bromus tectorum, commonly known as cheatgrass, is a highly damaging, ubiquitous invader. Cheatgrass has proven to be a very proficient competitor, frequently forcing out native plants, forming monocultures and reducing biodiversity in the landscape which they invade. This experiment tested the importance of soil conditioning on the growth and dominance of cheatgrass. Productivity of Bromus tectorum and a native grass, Pascopyrum smithii, were compared by harvesting aboveground biomass after two simulated growing seasons in combinations of invaded and native conditioned soils. These preconditioned soils were gathered from monocultures found on the Colorado Front Range. Results indicated that Bromus tectorum does not inhibit the productivity of natives and shows signs of increasing its own fertility. Future research should examine the specific mechanisms that cheatgrass may employ to alter soil properties.

 

Author’s Note

         I am an Environmental Studies major with an Ecology and Evolutionary Biology minor. As my academic career has progressed I have begun to hone my interest in onto field ecology. I am taking on this project to get more specific, professional experience in this field which may evolve into my career path. This project will largely be a learning experience with a unique opportunity to also bring some new knowledge into the field. The research I will be conducting will be within the University of Colorado at Boulder’s East Campus Greenhouse off of 30th street, soil samples will be originating from Timothy Seastedt’s field site in Lefthand Canyon. My research will be supervised largely by my Honors Thesis mentor, Janet Prevey, a graduate student of Timothy Seastedt and by professor Seastedt himself.

            I would like to thank a number of people who have all been crucial to the development of this thesis. I would like to thank Professor Bowman for first making Ecology interesting, my first semester at the University of Colorado Boulder. Professor Bowman also provided me with a welcoming and friendly experience working in his lab. Professor Seastedt for continuing to provide a great and inspiring set of upper level Ecology classes, along with directing my specific interests as I advanced through my education at Boulder. Professor Seastedt also provided me with the most important knowledge and expertise which helped to create the very foundations of the design of my experiment, also his knowledge and resources were crucial to the caliber of this thesis. I would not have even considered the idea of writing an Honor’s Thesis if it were not for Kallin Tea. Kallin exposed me to the realm of actual field ecology working with native and invasive grasses on the Colorado Front Range. This experience was crucial in directing my focus and interest in the field of Ecology. From before the beginning of this thesis to the very last steps Janet Prevey has been my guide and mentor. When I was still unsure of what to do for and Honors Thesis Janet helped realize the subject that merged my interests with relevant current issues in local ecology. Janet helped me with every aspect of the actual experiment providing direction and an undue amount of hands on help. Professor Miller has provided me with his extensive experience in the writing of Honors Theses. Thanks to Professor Miller this arduous process has been smooth and motivating, not oppressive. Professor Miller’s guidance has helped create a document I am proud of. 

 

Introduction

            The competition between native and non-native plants is already an issue in Colorado, costing the state and farmers billions of dollars (Pimentel et al. 2000). Non-native grasses are very effective and tenacious invaders that have a variety of traits which will interact in novel ways with the changing climate. As our environment changes, it is important that we try to more fully understand the penetration of non-natives if we are to secure the future health of our ecosystems. I am conducting this research to help explain how invasive species become successful in the environments they invade.                    

            I investigated Bromus tectorum (cheatgrass); a particularly successful invasive grass which is widely present in Colorado. Its success is due in part to its ability to form large monocultures. I hope to provide some information on how it does this, focusing on the importance of soil conditioning in cheatgrass’ ability to form monocultures and force out native species. Soil conditioning is the change that occurs in a soil when a new species is grown on that soil. This conditioning can include a number of changes from physical properties such as texture and pH to altering the microbial community. My hypothesis is that cheatgrass will be significantly more productive in soil which it had previously conditioned, and that this soil will inhibit the growth of native species. My experiment to test this hypothesis will involve growing Bromus tectorum and Pascopyrum smithii (a native grass) in their own soils and in subsequent generations, in soils from their own and each other’s predecessors (Figure 1). When these growing seasons are complete, net primary productivity will be measured, and various chemical analyses will be conducted to gain a greater understanding of cheatgrass modifications of the soils that it invades. Given that light is not a limiting resource to the short grass steppe, belowground competition dynamics are very important (Nelson et al 2003). Previous research studying the impacts on soil of cheatgrass and Lehmann lovegrass found significant changes in soil texture and soil fungi communities (Belnap and Philips, 2001) (Huxman et al. 2001). Those who will benefit from the results of my experiment will largely be the grassland ecosystem and invasive species ecologists and, I hope, land managers. If I get significant results which may explain how cheatgrass modifies its soil environment for greater success, land managers may be able to preemptively modify native soils to make them less suitable for cheatgrass invasion, or attack cheatgrass monocultures with greater knowledge and effectiveness. Land managers may include ranchers and farmers as well as local and state governments which have an imperative to protect public lands from exotic species. Ecologists also stand to benefit from my research as it may suggest additional mechanisms for success of invaders and shed light on further research to extend my findings.

 

Background

Invasive species

An invasive species is an alien species whose introduction and spread causes environmental or economic harm. Invasive species are a severe threat to native species, second only to habitat destruction and conversion in the United States (Levine et al. 2003). When considering endangered species and their future one often thinks of habitat loss and climate change. However, the impact of invasive species is underestimated: 400 of the 958 endangered or threatened species are at risk primarily due to pressures from invasive species (Pimentel et al. 2000). In a little over the last century, invasives are estimated to have caused $97 billion dollars in damages (Pimentel et al. 2000). The severity of this threat has been recognized by the United States. In 1999 Executive Order #13112 directed relevant federal agencies “to prevent the introduction of invasive species and provide for their control and to minimize the economic, ecological, and human health impacts that invasive species cause" (Sakai et al. 2001). Although it may seem like invaders are a superior force compared to native species, it is important to note that only a small proportion of exotic species become dominant over the locals in the landscapes they invade (Reinhart and Callaway 2006).          

Perhaps the most common and inclusive theory regarding the success of invaders is that they are no longer constrained by the biota in their home range which previously limited their competitive ability (Callaway and Aschehoug 2000). There are a number of factors and pathways involved in an exotic species becoming invasive. A successful invader may dominate a community as a “driver” through mechanisms where interaction with native species is quite important; where they can outcompete native species for limiting resources (Macdougall and Turkington 2005). Or interaction with native species may not actually be the most important factor; as mentioned earlier, the exotic species may become dominant not through direct competition over native species but through not being limited by the same factors which restrict native species, such as not being susceptible to certain predators which restrict native species (Macdougall and Turkington 2005). An important temporal factor which can lead to the success of an invader is when the introduction of an exotic species coincides with habitat change. This can be through disturbance, such as fire, or anthropogenic change, such as conversion of grassland to agricultural land (Mack 1981). 

 

Invasive Plants

            Invasive plants across the globe have already had a great impact and are increasing in abundance. In many areas, 25% of species present are exotic, and on islands the case is even more extreme. In Hawaii up to 70% of vegetation is non-native (Dukes and Mooney 1999).  Currently nearly 5,000 exotic plant species have successfully established themselves in the United States (Pimentel et al. 2000). This is a significant number when compared to the 17,000 native plants that have evolved here over millennia (Pimentel et al. 2000). In Colorado, exotic plants have displaced 130 species of native plants across over 550,000 acres (Pimentel et al. 2000).

            These changes in species composition have negative effects on ecosystem health but they also come at great cost to humans. When certain species die back because they are being out-competed, or when invasive species act as a novel vector for disease, this will cause a temporal window of decreased biomass which in many areas will increase the danger of avalanches and landslides (Krauchi and Kienast 2003) (Dukes and Mooney 1999). Invasive weed species cost $23.4 billion a year in crop losses alone (Pimentel et al. 2000).  Spending to deal with invasives in croplands of developing countries is especially difficult, as these communities have very small margins in which to make a living, and as crop yields decline they will be even less able to deal with the invasives (Dukes and Mooney 1999) (Omasa and Nouchi 2004).

            Exotic plants may be anthropogenically introduced into a landscape any number of ways. They are frequently brought to a new environment purposely to be used as forage, fiber, medicine, erosion control, timber or ornamentals (Sakai et al. 2001). There are examples where species introduced with scientific forethought became harmful invasives. Lehman lovegrass was introduced into the Southwest on sites that were grazed bare by cattle, and could not be reestablished by natives. This was a great example of scientists and land managers working together as early as the 1930s. This very same species, however, now is spreading and causing a loss in native biodiversity (McPherson 2004). It is crucial to understand that not only do plant species have different attributes, but they may have diverse effects on the various ecosystems that they invade.

            To better understand the features and mechanisms by which invasive plants succeed, research needs to isolate the effects of human actions from the natural plant characteristics. A powerful indicator of the general impact and success of invaders in an area is assessment of the species composition in parks and preserves. Where there is great human disturbance near roads or in drainage ditches there will always be a plethora of invasive species. If one makes observations in parks and preserves, greater insight can be gained into the species’ success in the natural environment competing with the natives (Dukes and Mooney 1999). 

 

Invasive plants: comparative advantages

            Invaders frequently are found to have competitive advantages. Exotic species which become invaders often have higher standing biomass, higher net primary productivity, faster growth rates, faster decomposing litter, and can even increase nitrogen availability compared to natives in the same ecosystems (Ehrenfeld 2003). These plants usually are a larger burden on their invaded habitat than their native habitat. In its native range, Diffuse Knapweed for instance, reduces surrounding grass biomass by 50% while in the United States it decreases biomass of native grasses by 85% (Callaway and Aschehoug 2000). And the very basic interactions an invasive plant may have with soil biota can differ dramatically between home and invaded ranges. The soil biota associated with diffuse knapweed in Europe has a negative effect on its proliferation, helping control its growth and spread. In North American soils, the soil biota which live in association with diffuse knapweed actually have positive growth effects (Callaway et al. 2004). This sort of differentiation leads many invasive species to grow in much higher densities, more frequently creating monocultures in invaded ranges compared to their native ranges (Broennimann et al. 2007).

            In broad studies involving many species across a multitude of regions, invasive species are generally more efficient than their native counterparts at using limiting resources (water, phosphorus etc.) (Funk and Vitousek 2007). Because the invaders studied had high rates of carbon assimilation, this allowed them to have a higher light, nitrogen and instantaneous energy use efficiency in systems limited by light and nutrients (Funk and Vitousek 2007). In the long run this advantage dwindles, but in the short run their ability to be much more efficient users of energy means that they will outcompete their neighbors quickly, which will not be around to see the long run.

            As habitats become increasingly fragmented by human infrastructure, this opens more opportunities for invaders, as they quickly move into disturbed zones and show an ability to take up human-created habitat niches such as along roadsides and in irrigation ditches.

Invaders compete with their native counterparts through direct resource competition, by changing rates of resource supply, local geomorphology (changing erosion patterns), and microclimate (increasing litter that changes soil temperature) and through disturbance effects (increasing fire frequency; D'Antonio and Vitousek 1992).

            Exotics may also quickly evolve to become even better competitors. As mentioned previously, one reason for invader’s success is that they are no longer limited by certain factors which may have existed in their home range. This means that over time, a species may evolve to no longer allocate resources to defense from herbivory. Instead it may allocate these resources to increasing its seed bank (Callaway and Ridenour 2004).

 

 

Invasive grasses: comparative advantages

Although grasslands do not receive as much public and scientific attention as areas of high biodiversity such as tropical rainforests, they occupy 15 million km2 and are about as productive as tropical rainforests (Parton et al. 1993). Exotic grasses are invading agricultural land and reducing forage and viable cropland. Of the weeds which invade cropland, 73% are nonindigenous (Pimentel et al. 2000).

            Traits that make grasses successful weeds are the ability to reproduce sexually and asexually, rapid growth from seedling to sexual maturity, and the ability to rapidly adapt to environmental stressors (Sakai et al. 2001). These invasive grasses can have widespread effects that have a noticeable impact on human communities. Through loss of suitable wildlife habitat, altering watershed functioning, loss of tourist appeal, increasing fire intensity and frequency, and promoting further invasions, local economies and public safety can be adversely affected (Brooks et al. 2004). 

            Invasive grasses such as cheatgrass are especially important to study in Colorado as historically, invasive grasses have had the largest success in the semiarid west (D'Antonio and Vitousek 1992). The basic types of grassland invasions are: the spread of exotic grasses into undisturbed native vegetation, the spread of grasses into disturbed vegetation, and the long-term persistence of exotic grasses where they were originally seeded by humans (D'Antonio and Vitousek 1992). Although some will die out, it is predicted more will successfully invade and outcompete natives in the future (Hellman 2008).                

           

 

 

Invasive plants, ecosystem effects

Invasive species do not always succeed by monopolizing resources; they may also have a variety of indirect effects on native vegetation. Invaders may alter soil stability, promote erosion, affect the accumulation of litter, salt and other resources and promote or suppress fire (Brooks et al. 2004). The effects of invasives on fires are especially relevant because fire has tangible effects on humans and is already an important issue in the arid west of the United States (Brooks et al. 2004). Invasives often affect the fire return interval (the historical average amount of time before a fire reburns an area), fire seasonality (the annual window for fire activity in an area), fire cycle (average time for a fire to burn an area), fire extent (the size and spatial characteristics of a fire), fire type (crown, surface ground) and fire intensity (amount of heat released in a given amount of time) (Brooks et al. 2004). 

            Invasives also can affect native vegetation by increasing the availability of limiting resources such as nitrogen (Brooks et al. 2004). A well-known example of nitrogen alteration was the introduction of Myrica faya into Hawaii. This plant, along with root symbionts, is capable of fixing nitrogen very efficiently in a very nitrogen-limited community. This crucial alteration has radically changed primary succession in this volcanic landscape (Wolfe and Klilronomos 2006).   

             This variety of effects can make restoring a habitat to its original form exceptionally difficult as the spatial and temporal status of soil nutrients may be completely altered compared to their original form (Brooks et al. 2004).

Exotic grasses are particularly effective at changing their environments in ways that increase their chances of reproduction at the expense of natives. Exotic grasses can alter ecosystem processes from nutrient cycling to regional microclimate and many species of grasses can tolerate fire or even speed up fire frequency, and many respond to fire with rapid growth (D'Antonio and Vitousek 1992).  Grass litter can affect seedling growth and germination by exuding harmful compounds, altering microclimates, and creating a physical barrier to shoot extension (Olson and Wallander 2002). Litter can affect species throughout their life cycle as litter can alter light penetration, humidity, soil and air temperatures and even air movement close to the surface (Olson and Wallander 2002).

            The alteration of soils by invasive grasses can be both a cause and an effect. As invasives push out natives and form monocultures and change the community composition, the species composition of soil biota changes as well. In some cases, the invasive can actively change soil properties (Wolfe and Klilronomos 2006). Many species native to North America have negative feedbacks associated with soil microbes. This trait makes dominance by a single species more difficult and promotes biological diversity (Callaway et al. 2004). Exotics often have positive feedback with soil microbes which reduce biological diversity (Callaway et al. 2004). Over time these feedbacks become stronger and compound leading to chronic problems in trying to remove monocultures and reintroduce native species (Perkins, Johnson and Nowak 2011). The traits which invaders possess and the following feedbacks, however, their ability to dominate soil dynamics may still be controlled by the characteristics of the soil on a geological time scale, as invasives and native plants have shown differing levels of carbon accumulation on soils from different geologic eras (Huxman et al. 2004). 

 

Climate change

The effects of climate change are complex and far reaching. Although there are still many specifics to be determined, simulations and models have shown that global warming will cause drastic changes in the species composition of ecosystems (Krauchi and Kienast 2003). In addition, the most direct effects studied are those related to increased CO2 in the atmosphere. In many biomes, increased CO2 will create a warmer and wetter climate, which leads to an increase in land carbon storage (Thornton et al. 2011). Increased CO2 in the atmosphere is predicted to result in a decrease in Net Ecosystem Exchange by 1.1 Pg/Year (Thornton et al. 2011). If this reduction in NEE does take place it will lead to a positive feedback loop; less CO2 would be taken from the atmosphere, which would lead to greater warming which would further reduce NEE (Cain et al. 2008).

            Climate change will create challenges to our understanding of invasive species. Changes of which we will include: altered transport and introduction mechanisms (through changes in commerce and tourism and in the danger of transport); establishment of new invasive species; altered impact of existing invasives; shifts in distribution of existing invasives; and

altered effectiveness of control strategies (Hellman 2008).  

 

Climate change, benefits to invasive plants

            Climate change is largely predicted to exacerbate the effects of invasive plants and facilitate their spread and dominance.  Invaders find a habitat suitable when there are available resources. If an ecosystem has a very tight nutrient cycle, where the natives are using all of the available resources, than an invasion is unlikely to occur. But a broad range of events fed by climate change may create this opening: an increase in nutrients from disturbance (fires from increased drought), a decrease in native demand for nutrients due to pathogen outbreaks, or timing shifts in the availability of nutrients and growth limiting factors (Weltzin et al 2003).  When an ecosystem is disturbed, it is one of the optimal times for invasive plant species to establish themselves. Studies have shown that increased CO2 concentration may slow the successional recovery of ecosystems in response to these changes, which would allow a longer window for alien species to invade.

            Many of the most basic changes will result simply from the expected change in temperature. There have been widespread scientific observations recording that invasives have been able to shift their ranges as climate changes (Broennimann et al. 2007). For instance, in the southeast United States, as temperatures rise, an incredibly damaging weed, Kudzu, is expected to increase its range northward, as its spread is currently being limited by cold temperatures (Weltzin et al 2003). While observing the change in spotted knapweed’s range across the American continent, it was discovered that an invasive can occupy climatically novel niches after it has been introduced to an area (Broennimann 2007). And in Colorado, by the time temperatures have risen 3° Celsius; deciduous trees will no longer be constrained by the same cold alpine temperatures, and may press into the subalpine belt, eliminating the conifers there. The conifers may then invade the alpine zone, simply eliminating whatever species that are there and have no vector of escape (Krauchi and Kienast 2003).

            An increase in CO2 will have many more direct effects on plant life compared to the warming that humans and animals will feel. Returning to Kudzu, in experiments it has been shown that Kudzu produces more and longer stems along with a substantial increase in biomass under conditions of increased CO2 (Weltzin et al 2003). Elevated CO2 in the atmosphere greatly increases the photosynthetic rates of plants with the C3 photosynthetic pathway.  In some areas, however, temperature increases may offset this effect, as C3 plants are much inferior to C4 plants in very hot environments (Vitousek 1994). In Colorado one of our most noxious weeds, Bromus tectorum (cheatgrass), is even more responsive to elevated CO2 than its native C3 counterparts (Vitousek 1994).

            When in an environment of elevated CO2, plants do not need as much water because they can keep their stomatal openings closed more than they would be able to otherwise. Because they will lose less water from their stomata, this may lead to an increase in soil moisture (Weltzin et al. 2003). This is another factor which may provide an opportunity for invaders, as nutrient rich habitats are more prone to invasion than resource poor habitats (Funk and Vitousek 2007).

            Another possible effect of climate change that is being studied is an increase in atmospheric nitrogen deposition. An increase in nitrogen availability has been predicted to generate higher growth response rates in invasive species compared to most natives (Lowe, Lauenroth and Burke 2003).             

            As ecosystems change as result of these invasive plants there will likely be positive feedback effects. For example, if the soil organic matter and water holding capacity change (as a result of increased fire frequency) this would create further changes in plant composition, the chemistry of the plant litter and rates of decomposition, which will further affect the frequency of fire (Weltzin et al. 2003).

 

Climate change, benefits to invasive grasses

            Invasive grasses have demonstrated strong adaptability to some alterations that climate change will bring. Compared to natives, they frequently have a quicker time to maturity, low seed mass and rapid growth rates. These traits have been found to be conducive to quickly adapting to elevated levels of CO2 (Vitousek 1994) (Hellman 2008). In addition to adapting quickly, certain species have a very sustained response to an increase in CO2, maintaining high growth rates for a much longer period of time than that of natives (Bazzaz et al. 1994). Although this does not hold true on a global level, in North America, the plants species which are most responsive to nitrogen deposition are alien grass species. Thus increased nitrogen deposition from industrial sources and the coupling of the nitrogen and carbon cycle may favor invasive grass species on Colorado’s Front Range. 

            It may be hard to create global and regional models predicting the species composition outcome, but because of specific knowledge such as this, it should be easier to predict the changes in range that individual species may take.

 

Colorado

The effects of climate change on the hydrologic cycle will be most important in the western United States. Snowmelt is a crucial aspect of hydrology in Colorado, and melt timing and quantity have proven to be very sensitive to even small shifts in temperature (Vanrheenen et al. 2004). Under most Parallel Climate Models, an increase of 2.2C by around 2090, combined with reductions in winter and spring precipitation could cut the spring snowpack available for melt in half by the end of this century (Vanrheenen et al. 2004). As a regional average, 67% of plant biomass across the Short Grass Steppe is below ground (Kuske et al. 2002) (Nelson et al. 2003). Given the importance of the water source in the Colorado Plateau and its ecosystem’s sensitivity to environmental changes, a decline of this magnitude will have massive effects which will cascade through the biome (Kuske et al. 2002). Soil bacteria are also crucial agents in promoting plant growth in arid ecosystems. These organisms are not very tolerant of environmental changes and may also have large unpredictable effects on Colorado vegetation as the climate changes (Kuske et al. 2002).

Competition particularly for water in an arid landscape can be seen through the spatial distribution of the two major Colorado bunchgrasses. Stipa hymenoides and Hilaria jamesii are widely spaced, covering no more than 30% of the land surface. The invader Bromus tectorum has not evolved in this habitat, however, and is able to cover great tracts of land (Kuske et al. 2002).

 

Bromus tectorum history

            Currently Bromus tectorum or cheatgrass is the most ubiquitous exotic grass in the steppe of the intermountain west (Mack 1981). The first record of its invasion dates back to 1889 in Washington, where it was first observed in cultivated fields and meadows (Mack 1981). The main theory for its introduction is that Bromus tectorum was a grain contaminant, though its spread was likely assisted by livestock. Where Bromus tectorum evolved in the Mediterranean, its spread was influenced by cattle sheep and goats (Knapp 1996). In the American West, it also is likely that its seeds attached themselves to the coats of livestock. Cheatgrass was observed continuously growing in the same area even as it was converted from grazing land to crop land, an early indicator of its resilience (Mack 1981). Prior to the 1850’s, remoteness and topography made the intermountain west unsuitable and undesirable for development. As silver and gold strikes become more frequent and profitable, these areas become more developed. The surrounding plains were converted to open grazing ranges, which were subsequently overgrazed (Mack 1981). Cattle were driven through these mining regions as far north as the mining districts of Northern Idaho, putting them in direct contact with the expanding agriculture of Washington (Mack 1981). This disturbance, development and transport was likely what allowed cheatgrass to invade the intermountain steppe region.

 

 

Bromus tectorum and fire

            An important factor that interacts with Bromus tectorum is fire; it may even be considered the most vital factor in assuring the survival of Bromus tectorum in a landscape (Knapp 1996). Cheatgrass benefits from fire because it is an early successional species; in post- burn sites, cheatgrass is able to occupy the limited resource niche that most natives are unable to fill (Knapp 1996). Once it is established on a burned site, it prevents other species that were present from reestablishing. Cheatgrass helps perpetuate this benefit by reducing fire return intervals. In Utah and Idaho, fire historically burned a landscape every 60-110 years; now sites burn as frequently as every 3 to 5 years (Pimentel et al. 2000). When looking at a 31-year fire record for Southern Idaho, 90% of acres burned were areas where cheatgrass was dominant (Knapp 1996). Fire attributes are largely determined by fuel. Bromus tectorum affects fuel loads by increasing the surface to volume ratio of litter (exposing more to embers), increasing horizontal fuel continuity (areas are more completely covered with fuel (Perkins, Johnson and Nowak 2011)), and creating a fuel-packing ratio that facilitates easier ignition (Brooks et al. 2004).

            This increase in fire frequency and intensity has a plethora of harmful effects. The frequency is sufficient to prevent native shrub recovery and they have become locally absent. Many species require shrubland for forage and cover, including ground dwelling birds like the sage grouse, and rodent species like the Paiute Ground Squirrel (Brooks et al. 2004). The effects of altered fire regimes further cascade as the Golden Eagle and Prairie Falcon rely on the above mentioned species as a food source (Brooks et al. 2004). Studies have shown that the loss of some of these ground dwelling prey species results in an environment with high population fluctuations, which makes these populations of both prey and predator more extinction prone (Knapp 1996).

            Although feedbacks make many of these landscapes hard to restore, there is some effort being made. Other alien species, such as Agropyron desertorum, have been introduced immediately after a site has been burned to suppress the growth of cheatgrass, and to reduce litter loads to try to interrupt the feedbacks between cheatgrass and fire (Brooks et al. 2004). This may be an effective method to control cheatgrass as mowing has proven to be unsuccessful--if one mows too early the seed simply resprouts, and if mowed too late, the seeds on the plant are frequently mature enough to produce new plants (Hulbert 1955).

 

Bromus tectorum, previous results

Given its large and wide-scale impact, Bromus tectorum has been the focus of a comparatively large amount of research. Although litter has been observed to have important effects on the fire regime, litter effects on soil is less studied. The only study to look primarily at the effects of cheatgrass litter on germination was in a forest ecosystem which differs greatly from that of the Colorado steppe (Pierson and Mack 1990). Litter is also an important driver for nutrient cycling as it has been observed that cheatgrass litter can have a detectable effect on nutrient cycling at a site in as little as 2 years (Perkins, Johnson and Nowak 2011). Another study looked at litter quality (nitrogen concentration) of cheatgrass in comparison with some Colorado natives. This study did not find significant differences between most species but did observe a significant difference in quality of cheatgrass litter when compared to Pascopyrum smithii (western wheatgrass) (Nosshi et al. 2006). Although not all of the mechanisms may be known, several studies looked at the effects of Bromus tectorum on soils. The most obvious and important nutrient to study is what is most limiting to plants in the communities it invades--nitrogen. As has been documented for several invasives, cheatgrass biomass gain is greater when exposed to increases in nitrogen levels than the response of natives. Cheatgrass showed biomass gains at every increase in nitrogen level; while a native (Bouteloua gracilis) stopped responding at an early level of increase (Lowe, Lauenroth and Burke 2003). The importance of the macronutrient phosphorus also has been observed. Bromus tectorum grown on silty soils (common in Colluvial soils in the foothills) tended to have a higher phosphorus content (0.16%) compared to that grown on loam soils (0.13%) (Grings et al. 1996). This may partially explain why areas most prone to cheatgrass invasion had silty soils and a high level of litter (Belnap and Phillips 2001). This second characteristic points to a positive feedback which cheatgrass perpetuates. Bromus tectorum has been observed to create 2.2 times more ground litter than the native Hilaria jamesii and 2.8 times more than the native Stipa comata (Belnap and Phillips 2001). These changes have cascading effects, as varying nutrients in the soils have effects on soil biota. Invaded soils showed lower soil biota species richness in comparison to non-invaded, similar levels of soil invertebrate and fungi, greater bacterial activity and silt levels, and a more continuous layer of dead plant material (Belnap and Phillips 2001). These changes in soil community, of course, alter the functioning of these systems (Wolfe and Klilronomos 2006). These soil feedbacks, in combination with decreasing water to other plants (Levine et al. 2003), naturally result in a decrease in biomass and in the competitive ability of native plants in the same plots (Lowe, Lauenroth and Burke 2003). Cheatgrass has proven to be a very successful invader as these feedbacks and self-fertile characteristics accumulate. Differences in soils, and therefore in native species, can become pronounced in only a few growing seasons (Perkins et al. 2011) (Hulbert 1955).

 

 

 

Pascopyrum smithii: previous results

            Pascopyrum smithii (western wheatgrass) is a perennial grass species native to the Colorado steppe. Unfortunately for its competition with cheatgrass, climate change will likely have direct negative effects on Pascopyrum smithii. Under elevated CO2, many grass species showed an increase in mycorrhizal colonization, but it had no effect on western wheatgrass even after 4 years (Monz et al. 1994). An increase in temperature also decreased Pascopyrum smithii colonization more significantly than that of its neighbors (Monz et al. 1994). When compared directly to Bromus tectorum, Pascopyrum smithii had lower C/N (Nosshi et al. 2006).

 

My Research

            The existing literature certainly emphasizes the need to understand the dominance of exotics, and any possible methods to halt their encroachment. My study hopes to increase the knowledge of how Bromus tectorum is able to so easily form monocultures and dominate communities. I am hypothesizing that Bromus tectorum is able to condition soils in a way that enhances its own production while simultaneously inhibiting the growth of native species, specifically Pascopyrum smithii in this study.

 

 

Materials and Methods

My experiment tested the effects of native conditioned-soil and soil conditioned by Bromus tectorum on the native grass Pascopyrum smithii and the invader Bromus tectorum. For adequate replication I began the experiment with 24 pots of native soil and 24 pots of soil conditioned by cheatgrass (see Figure 1). Then cheatgrass seeds and western wheatgrass seeds were planted throughout these pots.

For the experiment, we collected soil from local Bromus tectorum and Pascopyrum smithii monocultures. Soils were collected from a Ponderosa savanna/ grassland matrix in Lefthand Canyon CO, USA, 40.127064,-105.308461. Lefthand Canyon is approximately 15 km Northwest of Boulder, Colorado and lies at around 6,200 ft. (Knochel, 2010).  This site was chosen because there are already a number of experiments running in the area so there is an abundance of data regarding the site available. 

 

 

Site and soil characteristics

            This area receives a mean annual precipitation of six to ten inches, and this small level of rain is combined with a drainage class which is considered excessively drained. The frost free period for Lefthand canyon is generally between 80-100 days. The basic land type is considered Colluvial (USDA 2001). Colluvial soil, or colluvium, refers to soil which is mostly composed of loose sediment deposited at the base of low angle slopes. The difference between colluvium and the more commonly known alluvium is that colluvium is transported by only gravity, not water. The site has a somewhat variable but low slope between 9-25% with lithic bedrock no farther than 60 inches below. From the surface layer to 3 inches the soil is classified as gravelly sandy loam, from 3 inches to 60 inches it is gravelly sand, very gravelly sand and gravelly loamy sand. Loam is considered a high quality soil with reasonable quantities of humus and a somewhat even distribution between sand, silt, and clay, 40-40-20% (Kaufman 2008). This classification of the soils means that the soil at the site is a low quality loam, with decreasing quality further beneath.         The maximum calcium carbonate content is around 10%. The amount of calcium carbonates has a direct effect on the pH of the soil and plant nutrient availability. Calcium carbonates are associated with alkaline soils and are commonly used to neutralize acidic soils. Acidic soils have less calcium which is a crucial macro nutrient. Calcium is key to proper cell division, cell wall development, nitrate uptake, enzyme activity and the ability to metabolize starch (spectrumanalytic.com). The gypsum rating for this soil is given as 0%, which is the percent in weight of hydrated calcium sulfates in the fraction of soil less than 20mm in size (USDA 2001). Gypsum acts primarily as a structural stabilizer in soils. In soils with a high clay content, when the amount of water in the soil changes the clay expands and contracts drastically, which has a variety of negative effects. Gypsum helps alleviate this effect and minimizes the amount of erosion in an area (Graber at al. 2006). The lack of gypsum in this site may be explained by the lack of clay in these soils; gypsum is less important here and most likely leaches through the porous soils. The clay percentage in these soils is 6.9%, this basic soil particle type, which is defined by its size of less than .002mm, has great influence on a variety of other soil metrics to be discussed (USDA 2001). In great contrast the sand percentage for this area is 88.5%, sand is defined as a soil particle that is between .5 – 2mm in diameter (USDA 2001). Silt lies between these two soil types and has a rating of 4.7% (USDA 2001). Organic matter content, which is defined as plant or animal litter which is still in various stages of decomposition is .34% (USDA 2001). The average pH over this area is 7.9 although I will give a pH rating at a more specific scale further along (USDA 2001). This measurement defines the soil as slightly to moderately alkaline. This is logical, given the calcium carbonate concentrations. Basic soils have certain negative and positive effects which depend on the plant species, however, one of the two most important nutrients to plants, phosphorus, is most available is soils with a pH of around 6.5. This pH promotes the most nutrient availability to plants (USDA 2001) (Bickelhaupt, 2011). The liquid limit of the soil is 22.5 percent. This is the percent water by weight that a soil holds before the soil enters a liquid state. A soil with a high liquid limit is able to retain a greater amount of plant available water while retaining a solid state (USDA 2001).

These soils have a plasticity index of 2.5. The plasticity index is the difference between the liquid limit and plastic limit of the soil; it is the range of water content which makes the soil behave as a plastic solid. The number 2.5 then describes the percentage range in the soil’s moisture content that results in a plastic soil (USDA 2001). The water availability supply rating of 0.72 cm from the surface down to 50 cm. This is the volume of water available to plants when the water is at field capacity. This is calculated by multiplying the water capacity of the soil by the thickness of each soil horizon to the specified depth of 50cm (USDA 2001). The water content at 15 Bar is 3% of the soil volume. This is the amount of water by percent weight that is retained in the soil at a tension of 15 Bar. The water retained at 15 Bar is an estimation of the wilting point of the soil. The water content at 1/3 Bar is 14.5%. This measurement is commonly used to describe the amount of water content at field capacity (USDA 2001). At this same water tension the density of the soil is 1.57 grams per cubic centimeter. This is the weight of dried soil material, less than 2mm so gravel and rocks are not included, per unit of soil volume. A bulk density of more than 1.4 can restrict water storage and root penetration. So at the rating of 1.57 the soil is denser than is beneficial to plants (USDA 2001). The linear extension the soil has a rating of 1.5%. This refers to the change in length that a clod of soil undergoes when the soil is reduced from a moist to dry state, the change in states is from 1/3 Bar to ovendry. The very small difference in size is indicative of the very low clay content as described earlier, clay rich soils expand and contract greatly when moisture is added and subtracted (USDA 2001).

The Cation Exchange Capacity has a rating of 3.9 milliequivalents per 100 grams. This number represents the concentration of extractable cations held in the soil at a pH of 7. This is an important number to demonstrate how much nutrients a soil can holds for plant use (USDA 2001). The saturated hydraulic conductivity of the soil has a rating of 79.0622 micrometers per second. This metric describes the ability of pores in the soil to transmit water; it is a numerical value to describe the soil texture (USDA 2001). The K Factor in a rock free soil has a value of .28; this describes the susceptibility of the soil to erosion by water. The values range from .02 to .69, the closer your value is to .69 the more prone the soil is to erosion (USDA 2001). The soils in Lefthand Canyon are in Wind Erosion Group 3. There are groups one through eight, the lower the value the more susceptible the site is to wind erosion. The more detailed rating describing the wind erosion potential of this area is 86 tons per acre per year. This is the amount of soil to be expected to be eroded per year; this is largely determined by surface soil texture (USDA 2001).  

 

Soil collection methods

            On May 9th 2011, Janet Prevey and I drove to Lefthand Canyon to collect soils for the pots. We surveyed approximately 3 acres looking for patches of growth which were close to 100% western wheat (Pascopyrum smithii), or cheatgrass (Bromus tectorum). We collected soil from two patches, digging no deeper than 20 cm to use soil that was most directly impacted by the plant growth above. Digging at this depth, however, led to collection of excess plant litter and roots. We did a preliminary removal of the largest and most obvious litter and roots. On the non-native site (cheatgrass dominated soils) the most abundant species was Bromus tectorum. Also present were: Sisymbrium altissimum, Lactuca serriola, and Ambrosia psilostachya var. coronopifolia. This site had no bare ground and an abundance of litter. The native soil site (wheatgrass dominated soils) was primarily Pascopyrum smithii. Also present were: Bouteloua gracilis, Poa compressa, Artemisia ludoviciana and Lomatium orientale. This site had significant bare ground. Neither site had any large rocks or shade. 

           

Experiment

The collected soil was taken to the CU Greenhouse on 30th Street to begin potting on the 15th of May. An 80:20 mix of the soil collected from the field to perlite was mixed. Perlite is a volcanic glass which is used to increase oxygen content and water retention properties of soils (mii.org). It was also used to prevent the soils from clumping and bricking up too much. The soils were mixed with perlite in large tubs, during this process more litter and biomass was removed.           

To observe how soil conditioning affected growth of western wheatgrass and cheatgrass, a 2 X 2 factorial design was developed using soil type (cheatgrass or wheatgrass) and seed type (cheatgrass or wheatgrass). Twenty-four pots were filled with wheatgrass soil, and 24 pots with cheatgrass soil.  Then 12 pots of each soil type were filled with either 6 cheatgrass or 6 wheatgrass seeds for 12 replicates of each factorial treatment (Figure 1).

 

 

Figure 1 Experimental planting sequence

 

 

Every three days each pot received 300ml of water. About once per month, all of the pots on the table were shuffled to help ensure small variations in microclimate did not result in any stunting or improved growth. These variations may be caused by the exact air paths created by the fans, and some small variations in sunlight as may be caused by various pipes and apparatuses above the pots.

From 5/24/2011 to 7/15/2011 the average daytime lumens per square feet recorded by a data logger was 2069.9. By May 24th there were a couple unwanted dicots sprouting; Eroduim cicutarium, and Convolvulus arvensis. These were removed as they sprouted, so there was no chance that their root activity should have affected the soil of the grass’ growth. By June 27th it was apparent that some pots had more individuals growing in them than there were seeds planted. The soils from the field were not sterilized so some of this growth may have been from seeds from the field site. At this point many of the grasses were too large to be uprooted without disturbing the other grasses. In pots with more than six individuals, excess individuals were trimmed to the ground. This reduced their competitive ability so that within two weeks those individuals who were trimmed largely did not regrow. Pots that did not have more than two individuals were reseeded in an amount that should result in 6 individuals.

On July 29th the first growing season was ended. The number of individuals in the each pot was counted. All aboveground biomass was cut and placed in individually-labeled paper bags. The roots of every individual in every pot were removed. To help ensure that there were no survivors from season one; I checked the pots every day for a few days to pull up any more individuals that resprouted. The paper bags containing the biomass were taken to INSTAAR and dried at 60 degrees Celsius for a minimum of 62 hours. After this drying period, each sample was emptied into a Styrofoam bowl which weighed 4.51 grams or for very small samples, a coffee filter weighing .91 grams. Most samples were weighed on a Denver Instruments XE-510 which was sensitive to a thousandth of a gram. Very light samples were weighed with the Mettler Toledo which measures down to a ten thousandth of a gram, when using this scale coffee filters were used. 

The second part of the experiment was designed to test how different generations of native or non-native grass may influence conditioning effects of soil. For example, would wheatgrass-dominated soil that had experienced one generation of cheatgrass growth be more beneficial to further cheatgrass growth than wheatgrass? To test this, the potted soils from the original four treatment groups (western wheat soil- western wheat seed, western wheat soil– cheatgrass seed, cheatgrass soil– cheatgrass seed, cheatgrass soil – western wheat seed), were planted into eight groups. WW-> W, WW-> C, WC-> C, WC -> W, CW->W, CW-> C, CC-> C, CC-> W (see figure 1). On August 2, six seeds were planted in each pot. By August 27th, many pots still had very moist soil by the next scheduled watering period. This resulted in some algae and moss developing on the surface of many of the pots, which is not a normal condition found in the shortgrass steppe. After watering on the 27th, the next watering was delayed until September 3rd. The plants handled the dry period very easily and showed no sign of water stress, while at the same time the algae and moss seemed to have been dried up. From this point onward the plants were watered every four days, as opposed to three. This slight decrease in watering did not create any visible signs, such as wilting, from water stress. A strange occurrence in season two is that a common unwanted dicot, clover, sprouted although that species had no presence in season one. 

To collect additional data regarding the soils from our site, Janet and I drove to Lefthand Canyon to collect soils to be analyzed from more specific locations given that our pots were filled with soils from only two spots. We picked 18 locations from either cheatgrass or wheat monocultures. We separated each sampling location by around 30 meters to ensure the most complete picture of the site as possible. At each of these locations we collected soil from 10 cm depth for a total of 9 cheatgrass and 9 wheatgrass dominated soils.  First, we measured soil moisture for each sample by comparing moist and dry weight of the soil. The soils from each of the 18 spots were removed from their zip lock bags, where moisture was retained, weighed for their initial weight and then placed into an oven to dry. One week later inorganic nitrogen content the soil was measured. This is done via KCl (2M) extractions. From the sixteen samples around 10 grams was weighed out after all litter was removed, recorded and then placed into a 250ml flask. 50ml of KCl was added into each flask and then parafilm was applied to seal the top of the flask. These samples were then placed onto a rotating plate which was set to 200rpm and left for 24 hours. When this process has finished flasks with side nozzles were inserted in the pump system, and funnels with filters are placed onto the top of these flasks. After moistening the filter paper the pump was turned on, and 8 vials of KCl were poured into 8 flasks. After all the KCl has been sucked through the filter paper, this process was continued until all 18 samples were filtered.

            After the 18 soil samples were oven dried they were also prepped for CHN analysis. Using a highly precise scale that measures up to 1/10,000 of a milligram, a tin capsule was placed onto the scale and zeroed, then within 1 mg of 20 mg was measured out and placed into the capsule and its weight recorded. The capsule was then z and double folded and placed into a 96 well plate. Samples were analyzed for % C and % N on a CHN analyzer.

 

Statistical Analysis

            For basic data entry, aboveground biomass (g) and surviving individuals were entered in Excel tables. In Excel, averages were calculated for the various treatments along with standard error, standard deviation, and square root transformation of the biomass results for better results in the statistical analysis software R. Excel was also used to create bar graphs which showed the respective average biomass for each treatment.                                                                                      The various data tables were then loaded into R. A Shapiro-Wilk normality test was performed on the biomass data. This test shows the probability that the data came from a normally-distributed population. The data were not normally-distributed (Shapiro-Wilk p <0.01), so data were square-root transformed to better approximate a normal distribution before analysis. Biomass data were analyzed with two-way ANOVAs.  The use of a two-way ANOVA in this experiment compares two experimental factors (seeds and soil) across the 4 and then 8 treatments; it tells whether there was a statistically significant difference in the means of these groups. R was also used to create interaction plots to easily visualize the interactions between the variables.

 

 

Results

Season 1

The data collected from the first season of growing were largely above ground biomass weights, which are a direct representation of Net Primary Productivity. In this way the productivity between the various treatments were compared for statistical significance.

 

Table 1.  Average weights of above-ground biomass for plants in the four initial treatments.

Treatment

Average Weight (g)

Standard Deviation

Standard Error

Wheat Soil Wheat Seeds

0.2743

0.1616

0.0466

Wheat Soil Cheat Seeds

0.4175

0.3918

0.1131

Cheat Soil Wheat Seeds

0.5808

0.4373

0.1262

Cheat Soil Cheat Seeds

2.3433

0.8291

0.2393

Average Across All Treatments

0.9040

 

Biomass of cheatgrass was significantly greater in cheatgrass-conditioned soil than in wheatgrass-conditioned soil (p< 0.001, Table 1, Fig. 2). Biomass of wheatgrass was much lower in all treatments, and contrary to our hypothesis, slightly greater in cheatgrass-conditioned soil than wheatgrass-conditioned soil (Table 1, Fig. 2).

 

 

 

Figure 2. Average above-ground biomass weights for each treatment

 

 

             

 

 

 

 

 

Figure 3

 

 

 

 

 

 

 

 

 

 

 

Df

Sum Sq

Mean Sq

F Value

P Value

Soil

1

14.951

14.951

56.513

2.008e-09

Seeds

1

10.8956

10.8956

41.184

8.205e-08

Soil  Seeds

1

7.8659

7.8659

29.732

2.135e-06

Residuals  

44

11.6407

0.2646

 

 

 

 

The next important visualization of my results is the Interaction Plot (Figure 3). This plot shows that there is an important relationship between the variables; the results are not simply a result of one of the variables independently. If there was not interaction between the variables the lines would be parallel or close to parallel to each other. Figure 3 specifically shows a heightened response in biomass between when cheatgrass is grown in its previously conditioned soil compared to in native soils. The response shown from the native Western wheatgrass is less pronounced.

 

 

Table 2. ANOVA Results, Season 1

 

 

 

 

Table 3 End of season individuals

Treatment

 

Individuals

Average Across All Treatments

5.08

Wheat Soil Wheat Seeds Average

5.17

Wheat Soil Cheat Seeds Average

3.17

Cheat Soil Wheat Seeds Average

3.83

Cheat Soil Cheat Seeds Average

8.17

 

There were too many variations and less strictly controlled factors to properly test survival rates between the populations.  It is apparent, however, that at the end of the first season, cheatgrass conditioned soil and cheatgrass seeds both led to more productive pots with higher numbers of individuals. The specific number of individuals per pot can be found in Table A-1. Individuals per pot showed a weak predictive power for the biomass of the pot                                  (R-squared = 0.18) (Figure A-6).

 

 

 

 

 

 

Season 2

Table 4 and Figure 4 show the average biomass across the second season of treatments. With this number of treatments, the results are slightly more difficult to visualize. Figure 4 does easily shows that cheatgrass grown on its own soil for the length of the experiment did prove to have the highest level of productivity.

 

 

Table 4 Above-ground biomass weights, cheatgrass and wheatgrass, season 2

 

 

 

Treatment

Average Weight (g)

Standard Deviation

Standard Error

WWW

0.1283

0.0679

0.0277

WWC

0.5783

0.1158

0.0473

WCC

0.451

0.2641

0.1078

WCW

0.1195

0.0836

0.0341

CWW

0.2302

0.3001

0.1225

CWC

1.0967

0.5392

0.2201

CCC

1.28

0.2718

0.1110

CCW

0.3383

0.1283

0.0524

Total Average

0.52779

 

 

 

 

Figure 4 Average above-ground biomass weights for each treatment

 

 

 

Table 5  ANOVA Results, Season 2

 

 

 

                 

Df

Sum Sq

Mean Sq

F value   

Pr(>F)   

Soil              

1

0.84630

0.84630

21.5390

3.688e-05

Seeds             

1

0.01059

0.01059 

0.2695  

0.60655   

Seeds2            

1

2.57297

2.57297

65.4844

5.930e-10

Soil:Seeds        

1

0.14086

0.14086 

3.5851  

0.06555 

Soil:Seeds2       

1

0.15160

0.15160 

3.8585  

0.05647 

Seeds:Seeds2      

1

0.01926

0.01926 

0.4901  

0.48792   

Soil:Seeds:Seeds2 

1

0.00483

0.00483 

0.1228  

0.72783   

Residuals        

40

1.57165

0.03929                     

 

 

 

 

 

 

 

 

 

Table 5 shows the statistical significance of the various treatments and their interaction. Soil type (cheatgrass or wheatgrass, “soil”) and the type of seeds sown in the second season (cheatgrass or wheatgrass, “seeds2”) both significantly affected biomass (Table 5, p <0.001). Soil-conditioning over only one season of growth (“seeds”) did not significantly influence second-season growth of cheatgrass or wheatgrass (Table 5, p > 0.05).

 

Figure 5

 

 

Figure 5 is provided for more information regarding the distribution of season 2 data. The mean is within boxes which also contain the upper and lower quartile. Lines extending from the box represent the uppermost and lowermost limits of the data with data points considered to be outliers represented by small circles. One can see that although there is a little more range in middle portions of the graph the cheatgrass conditioned soils have more biomass than treatments with wheatgrass plants and soils.

 

 

 

Table 6 End of season individuals

 

 

 

Treatment

Average Individuals

Across All Treatments

3.020833

WWW

3.6667

WWC

2.8333

WCC

1.8333

WCW

3.5

CWW

3.33

CWC

2.33

CCC

2.833

CCW

3.833

 

 

 

 

 

 

 

 

 

 

Again real extrapolation regarding individual survivorship cannot be done due to frequency of data collection and the inability to compare to the previous season. The specific number of individuals per pot can be found in Table A-2. Individuals per pot were not a significant predictor of biomass (R-squared = -0.02) (Figure A-6).

 

 

 

 

 

Discussion

Results

Season 1

The data presented in Table 1 are very striking and obvious conclusions can be observed. Pascopyrum smithii on its own soil had the smallest amount of growth while Bromus tectorum on soil it had previously been grown on had the largest productivity. Cheatgrass grows significantly better on soil which it had previously occupied compared to native soil. The difference in soils is also strong enough that even though it is clear that cheatgrass has a higher level of productivity, wheatgrass grown on cheatgrass soil manages to still produce more biomass than cheatgrass on native soil. Table 2 shows the statistical significance of the results. The p-value for each variable is well below .05. This confirms that data easily seen in Table 1 and Figure 2 are in fact significant. Soil, plant species and the interaction between the plants and the grass are all significant factors in determining the resulting biomass.

The season 1 results clearly reject the second portion of my hypothesis that cheatgrass dominated soils decrease the production of the native western wheatgrass. At this stage it cannot be stated conclusively that cheatgrass conditions soils in a way that promotes its own growth. Although cheatgrass had much higher productivity on soils from which we found cheatgrass monocultures, this does not prove that the soils were more fertile because of the cheatgrass. The soils which cheatgrass was found to dominate at the field site may have been more fertile previous to cheatgrass invasion. Cheatgrass may have invaded the particular sites that it did due to this fertility. There are some initial differences in soil which may allow some theorizing of mechanisms. The cheatgrass pots and the western wheatgrass pots are very easy to differentiate based simply on appearances. The soil collected from under plots of Pascopyrum smithii was much lighter and denser and claylike in texture. The soil collected from under monocultures of Bromus tectorum was much darker and loser in texture. The drastic difference in soil color is an initial indicator of a higher level of organic matter in the soil. This reason for this higher level of organic material could be from a variety of interacting factors. The most obvious hypothesis that can be supported by this experiment and literature is that the higher amount of biomass produced by cheatgrass results in a higher quantity of litter on Bromus tectorum soils (Belnap and Phillips 2001). This plant material contributes to organic carbon in the soil. The available carbon in turn may feed a richer and more robust population of soil biota. This may create a positive feedback as the increased number of soil heterotrophs themselves will also provide additional carbon and other essential nutrients into the soil (Chapin et al. 2011). The mechanisms for soil conditioning can only be hypothesized at this point. When the full array of soil analyses has been completed, we will be closer to understanding these mechanisms.

 

Season 2

Easily visualizing the data for season two is more difficult and the exact results we are looking for to address my hypothesis are also more complicated. Overall, it seems that one season of growth by either species is not enough to change soil conditions drastically. The most important comparisons to make to test my hypotheses are comparing WCC to WWC and CCW to CWW. The difference I am hoping to see to prove my hypothesis correct is wheat to cheat to cheat should have a higher biomass than first generation cheat being grown on wheatgrass soil. Table 4 shows, however, that not only is this not the case but that WWC actually has a slightly higher level of biomass compared to WCC. Given the results of season one however, this is not likely due to actual correlation, but to random variation. When comparing CCW to CWW we are interested in seeing the effect of cheatgrass colonization on western wheatgrass. To support my original hypothesis I would be looking for lower growth in cheat to cheat to wheat compared to cheat to wheat to wheat. But since that aspect of my hypothesis was clearly rejected in season 1 we would expect to see higher growth in CCW given that western wheatgrass seems to also prefer cheatgrass conditioned soil. In this case the results of biomass in season 2 (Table 4) are what one would expect given season 1; the CCW treatment had an average biomass of 0.33 grams while CWW had a biomass of 0.23 grams. The last two treatments to compare are WWW to WCW and CCC to CWC. Given the results of season 1 it would be expected wheat to cheat to wheat may have a slightly higher biomass than 2 generations of wheatgrass alone. Table 4 however shows no real difference between these two groups. We would expect purely invaded soil to result in slightly higher biomass compared to invaded soil with western wheat grown in the interim. The difference observed here does align with the initial hypothesis that cheatgrass grows better on soil that it has conditioned.

However when one looks at Table 5 we see that there are no statistically significant interactions between the seeds of season 1 and the seeds of season 2. It is very tempting though to look at the relationship between the soil type and the season 2 plants; the confidence interval is just short of 95%.

 

Implications

The results of my study have three main implications which can be stated with confidence. One is that neither Bromus tectorum nor Pascopyrum smithii alter soil conditions in any significant manner within one season. Secondly, as can be seen in Figure 3, cheatgrass does have a heightened response to more fertile soils, which may help explain the ability of cheatgrass to outcompete natives. The third is that Bromus tectorum does not condition soils in a way that inhibits the growth of natives. Even if the reasons for soil fertility cannot be stated be stated at this point, if cheatgrass did exude harmful compounds or alter the soil microbial community in a fashion that would have negative impacts on western wheatgrass, a decrease in western wheatgrass productivity would have been seen in this experiment.

            This, for one, points towards cheatgrass not acting in an allelopathic function, where it may be exuding harmful chemicals which directly inhibit the growth of neighbors. Given that western wheatgrass was planted into cheatgrass soils immediately after the removal of cheatgrass, if cheatgrass exuded any growth inhibiting compounds we would certainly see lower success for wheatgrass compared to in its own soils. But the very opposite was found. Although all of its functions in the landscape are not known, this experiment may suggest that suppression of its competitors, such as Pascopyrum smithii, through soil conditioning, is not the most important reason for its success. Cheatgrass may have the ability to create soils that are simply more fertile for a variety of plants. There are two main possibilities regarding how an increase in soil fertility allows cheatgrass to outcompete its neighbors. As cheatgrass becomes more productive on soil which it has conditioned, its heightened response allows it to outcompete grasses that are on the edge of its conditioned soil, and so the cheatgrass conditioned soil, along with cheatgrass spreads. The ability of invasives to take advantage of more nutrient rich environments compared to natives has been observed in a range of literature (Weltzin et al 2003) (Vitousek 1994) (Lowe, Lauenroth and Burke 2003).The other possibility is that cheatgrass is able to form relationships with soil biota which thrive on the highly productive soils that western wheatgrass is not able to. An example of the mechanism is spotted knapweed; an invader which has been able to create beneficial relationships with local soil biota which have a negative effect on native plants (Callaway et al. 2004).

            The primary usefulness of this paper to ecologists will be to better steer and direct future research efforts. My research shows the importance of soil conditioning to cheatgrass growth. This should direct research efforts to more closely examine the interaction between cheatgrass and soil biota, nutrient qualities and structure.

            Land managers within the Colorado Front Range may be able to use the results to better understand the spread and dominance of cheatgrass. Areas which have very poor nutrient-limited soils may be more susceptible to cheatgrass invasion as it may be able to establish more beneficial relationships with soil biota. As cheatgrass is able to create more fertile soil it will quickly outcompete the stunted natives. Areas may be less susceptible to cheatgrass invasion where soils are already fertile. The natives in these landscapes will already be adapted to taking advantage of the highly fertile soils, and cheatgrass will not be as able take advantage of its ability to condition soils. Examining soil properties of susceptible regions could help managers prepare and prioritize their efforts to eliminate the spread and introduction of cheatgrass.    

 

Further Research

There are two main areas in which cheatgrass management needs to be further refined: further scientific research, and merging science and management. Science seeks to create laws, predictions, to explain phenomena. Management, in contrast, is site specific, species specific; management has very specific objectives. Management also deals with economic realities and qualitative factors such as human values.

Restoration efforts using exotic species such as Agropyrom desertorum must be very carefully monitored as there have been countless past examples of non-natives making matters worse in the long run. Constant monitoring is a must and a thorough understanding of the potential cascading effects that changes in population dynamics and species composition may bring. An important note to make in regards to restoration and monitoring is the importance of belowground biota. Frequently observations are only made for above ground biota. But as my results help illustrate what happens below ground is at least as important. As restoration projects continue there should be a stronger emphasis on surveying the effects and progress that are occurring in soil nutrient dynamics and biota.

Although my results show significance in soil conditioning in soils from the Colorado Front Range, Bromus tectorum has a massive range. With this range comes the possibility of varying effects based on the exact ecosystem that cheatgrass has invaded. This means that studies should be conducted throughout cheatgrass’ range to test for variation in effects dependent on location.

            Evolutionary biology is an aspect of biology which should play a larger role in the study on invasive species. Although species such as Bromus tectorum have been present in the United States, or more broadly outside of its native range, for some time. As exotic species enter new habitats it is inevitable that over time they will take a different evolutionary path than they took in their home range. If an exotic suddenly is not restricted by the same competitors or herbivores, over time individuals which allocate resources towards these past limitations will no longer be the fittest and will not be selected for. A greater understanding of genetics and traits of invasives may also help the source be identified. This may prove to be useful information to identify the vectors of invasions to help minimize the possibility of further invasions in the future.

 

 

Experiences and Continuation

            This being the first experiment of this level of rigor I have conducted, I noticed areas for improvement. My primary concern is that although when analyzing soil from the site we had nine cheatgrass locations and nine wheatgrass locations, for potting the grasses there were only one location from each soil type. This means that the results do have a greater chance of being affected by a particular anomaly that may have been present in one of those two sites. If four locations were chosen from native and nonnative soils, each would have three pots, and I would be more confident in the ability to extrapolate from my results.                                                         The next small oversight has less effect on my actual results but did limit the scope of results that had significance. Planting, recording, and managing individuals could have been conducted with more rigor. Janet and I both planted seeds in season one. We certainly had differences between the patterns in which we planted along with depth. Cheatgrass seeds come clumped and I had trouble planting the correct number in each pot. This was observed as some pots had many more than six individuals. The opposite problem also occurred as after weeks of growing some pots had too few individuals and we were forced to plant more seeds after the growing process was already well underway. In season two of the experiment, I was less concerned about counting individuals because most pots had ample growth but not more than the prescribed number of seeds. This lead to a frequency of individual counts in season two that could not be compared to season one. This combination of issues essentially results in me not being able to analyze survivorship data. As mentioned this should not affect the importance of my Net Primary Productivity finding, but if controlled better I could have additional results looking at the survivorship of the cheatgrass and wheatgrass seeds where I would then be able to hypothesize competition and germination effects. 

            Other than these two issues I observed no real shortcomings to the experimental design or its execution. There is always room for improvement, but I feel that experiment was conducted carefully and consistently to a degree that I confident in the significance of my results.

            Although there were certain time constraints for finishing this research and displaying the results comparing NPP, the current materials still remaining provide ample opportunity for further research. As the results from the KCl extraction come in, the plant available nitrogen will be able to be compared across native and cheatgrass conditioned soils. In addition CHN analysis has already been prepared for the 18 sites at Lefthand canyon. CHN analysis can also be conducted on the 48 pots whose soil is still in the greenhouse. Soil texture analysis will also be a readily available method of analysis which can be conducted on the 18 field sites and the 48 experimental pots. The prime importance of these tests is to shed light on possible mechanisms for the significant change in NPP observed in this experiment. These analyses will be conducted in the following months.  

            As for a separate follow up experiment the most appropriate ideas would be to increase the number of sites that soil would be drawn from as mentioned earlier and the potential for a field experiment. Given the very widespread nature of Bromus tectorum a similar experiment could be run but with soils from Bromus tectorum across multiple states and choosing a native which frequently is outcompeted in the range of that particular population of cheatgrass. This would require a much larger investment of time and materials. However, looking for similar results and conducting soil analyses to test for mechanisms would give a much broader view and allow for more extensive and relevant extrapolation. A field experiment that would be very interesting to conduct is to observe the effects of soil type on the competition between Bromus tectorum and Pascopyrum smithii. A number of sites could be picked along the Colorado Front Range, each site with soils of different ages and/or parent material. Plots in this landscape would be cleared and then planted with even number of cheatgrass and wheatgrass in the same plot. The purpose of this experiment would be to see what soils are more or less susceptible to invasion by cheatgrass.

 

 

 Appendices

Figure A -1 Greenhouse Temperatures, May 24 to June 17

 

 

 

 

 

 

 

Figure A -2 Greenhouse Temperatures, May 22 to July 16

Table A-2 Season 2 Individual Count

Table A-1 Season 1 Individual Count

                                          

 

 Figure A-3 Season 1 Treatment and Pot Biomass

 

Figure A-4 Season 1 Individual Count and Biomass Relationship

P value = 0.00124                               Adjusted R-Squared: 0.1875

Figure A-5 Season 2 Treatment and Pot Biomass

 

Figure A-6 Season 2 Individual Count and Biomass Relationship

P Value = .9922                                               Adjusted R-Squared: -0.02174

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Is Erosion Helping the Himalayas Grow? River Incision and Mountain Uplift, Brooke Marston

River Incision and Mountain Uplift
648
1
Is Erosion Helping the Himalayas Grow?
A Literature Review of River Incision and Uplift in
the Himalayas
“The Roof of the World,” the Himalayan Mountains,
is home to some of the highest
peaks in the world. The Himalayan Mountains formed
from the subduction of continental
plates that continues today to increase mountain el
evations. High-altitude climates have an
increasing effect on erosional denudation, transfor
ming landscapes and altering
geomorphic processes that govern orogeny. Unprecede
nted rapid uplift rates in the
Himalayan Mountains are perplexing scientists. It i
s hypothesized that erosion may actually
be responsible for growth of Himalayan Mountains. R
iver valleys continually gouged out of
the mountainous terrain by fluvial erosion create t
he potential for rising mountain peaks.
Molnar and England (1990) began by looking at the d
riving forces of mountain
uplift and the influence of climate change on mount
ain geomorphologic processes. The
highly concentrated weight of mountain ranges cause
s isostatic depression of the crust and
mantle. As a result, continental crust thickens und
er mountain ranges. However, Molnar
and England noted that the mountain ranges borderin
g the Tibetan Plateau increased in
elevation at a rate so fast as to be unaccountable
solely by crustal thickening. The evidence
Molnar and England found for the accelerated uplift
did not necessarily reflect a general
surface uplift from crustal thickening, but rather
it was the result of isostatic compensation
of rapid erosion and bedrock unroofing. Erosion by
both rivers and glaciers lowered mean
elevations and thus, underlying crust thinned. Isos
tatic compensation then raised the
remaining peaks on the sides of the incised valleys
to greater heights than before (Fig. 1).
While some scientists believe tectonic uplift and c
hemical weathering from uplift and
erosion triggered the Quaternary ice ages (Cornwell
et al. 2003), Molnar and England

 
River Incision and Mountain Uplift
2
concluded that it was the Cenozoic climate change t
hat increased valley incisions and
induced mountain peak uplift in mountain ranges all
over the world. Molnar and England’s
findings spurred a deeper exploration into further
explaining why and how mountain uplift
is related to isostatic response to valley incision
.
Figure 1.
Illustration of isostatic uplift of mountain peaks
in response to isostatic compensation. (A) Erosion
of deep valleys in an initially level plateau leads
to (B) a landscape with lower mean elevation with
mountain
peaks rising about the elevation of the original pl
ateau. Source: Montgomery, D. (1994). Valley incisi
on and
the uplift of mountain peaks.
Journal of Geophysical Research, 99,
13,914.
Nanga Parbat, the ninth highest mountain on Earth,
resides at the western end of
the Himalayas in Pakistan. It lies just south of th
e Indus River, which is responsible for
mass fluvial erosion and valley incision that forms
some of the steepest relief on the planet
(Cornwell et al. 2003). As the slopes of Nanga Parb
at steepen, they become less stable and
eventually fail under gravitational forces. The den
uding of the Nanga Parbat massif occurs
through a process coined “unroofing.” Schroeder and
Bishop (2000) attribute the unroofing
of the massif to geomorphologic erosional processes
having occurred over millions of
years. The gravitational collapse of Nanga Parbat’s
oversteepened slopes exhibited
outward as mass movement. Much of the debris from r
ockslides and landslides fell into the
river, creating a partial barrier that narrowed and
obstructed the river’s natural flow. As a

 
River Incision and Mountain Uplift
3
result, the river gradient and velocity increased a
nd effectively removed the debris,
equating to high rates of denudation. Landslides, s
uch as the Liachar-Indus landslides of
1840-1841, may dam a river for several months, resu
lting in catastrophic floods that carry
large, eroded sediment loads downstream. Torrential
rains from orographic precipitation,
rapid snow melt, avalanches, and glacial erosion al
l contribute to erosion of mountain
slopes. Much of the Nanga Parbat landscape’s major
alteration is attributed to major
glaciations, mass movement, and running water from
glacial meltwater streams during the
late Quaternary. The erosion-initiated uplift of Na
nga Parbat’s peak into high, permafrost
zones where colder temperatures increased rock stre
ngth through joint freezing and
produced cold-ice glaciers, thus resulted in less m
ass-movement based denudation. The
denudation that continues to occur is responsible f
or unroofing the Nanga Parbat
Himalaya, while at the same time produces steep rel
ief and deep valley gorges.
As important as erosive processes such as landslide
s, rockslides, and glacial scour,
may be to uplift by removing weight from the underl
ying crust, downstream surface uplift
from fluvial incision is an additional influential
factor. Montgomery (1994) concurs with
the assessment that climate change from the late Ce
nozoic accelerated valley erosion,
which may be responsible for up to twenty to thirty
percent, 1500 meters, of the present
elevation of the Himalayan peaks. But of the proces
ses contributing to valley incision,
Montgomery states that transport laws for erosion b
y fluvial processes have the strongest
basis. Erosion for fluvial incision is proportional
to stream power, which is proportional to
water discharge and valley slope. Montgomery modele
d the downstream pattern of river
incision in the Himalaya based on a plateau edge, m
imicking the Tibetan Plateau that
borders the Himalayan Mountains. Montgomery found t
hat calculated profiles showed

 
River Incision and Mountain Uplift
4
significant uplift of mountain peaks at the edge of
the plateau, where the Karnali River is
incised up to 4500 meters, and a decreasing relief
downstream. Montgomery’s findings
supported the hypothesis that the great height of t
he Himalayas is due to river incision.
River incision, such as the Indus Gorge that runs t
hrough the Nanga Parbat massif,
has a profound effect on mass wasting and erosion,
but also effects the structuring of the
crust and lithosphere. Zeitler et al. (2001) produc
ed a study examining the advective heat
flow in crust and its ensuing role in mountain upli
ft. Crust will weaken and thin as the
upper crust is eroded away or incised by rivers. As
valley incision weakens the crust,
advective heat flow from deep inside the earth is a
ttracted to the weakening area as the
potential energy attempts to reestablish equilibriu
m between the highlands and the
lowlands. The increasing topographic gap between th
e valley gorge and mountain peak
causes the geothermal gradient to increase. In resp
onse to the differential geothermal
gradient, crustal flow is diverted from the isother
mally compressed weak crust to the
mountain massif to prevent strain from further weak
ening the already-compromised crust.
The diversion of the advective heat flow in the cru
st results in mountain uplift as well as a
production of weaker crust under the massif. The do
wncutting river and high topographic
relief provide the rapid erosion required to keep t
he system in place. This thermal-
mechanical-erosional process, termed a “tectonic an
eurysm” (Fig. 2), is one of the driving
mechanisms of Nanga Parbat’s, and many other Himala
yan mountain massifs’, growing
elevation from river incision and erosion.
In addition to the rate of river incision, climate
is one of the most significant
factors in determining the amount of erosion. The a
nnual, summer monsoon season occurs

 
River Incision and Mountain Uplift
5
Figure 2.
Cartoon illustrating dynamics of a tectonic aneurys
m. Source: Zeitler, P., Meltzer, A., Koons, P., Cra
w,
D., Hallet, B., Chamberlain, C., Kidd, W., Park, S.
, Seeber, L., Bishop, M., & Shroder, J. (2001). Ero
sion, Himalayan
Geodynamics, and the Geomorphology of Metamorphism.
GSA Today,
7.
when air masses, tracking over the Bay of Bengal, p
ick up moisture, causing tropical
depressions, and, unable to pass over the Himalayas
, drop tremendous amounts of
precipitation over the Himalayas. Hodges (2006) pro
posed that monsoon rainfall
influences how energy transfer takes place within t
he depths of the Himalayan-Tibetan
system. Much like the “tectonic aneurysm” theory, w
here advective heat flows towards the
weakest crust, the lower crustal flow of Tibet is f
lowing southward in the direction of least
resistance towards the Himalayan front range, which
has experienced extreme surface
erosion due to high monsoon rainfall. The flow of c
rust towards the front range results in
uplift, which in turn results in more erosion, thus
creating a positive feedback system.
Hodges discovered that rapid uplift is correlated w
ith high topographic relief and steep
river gradients, producing a large change in elevat
ion over a short horizontal distance. High
rates of erosion are responsible for the steepening
slopes of Himalayan massifs; current
erosion in the Himalayan range is largely driven by
monsoons. To establish that channel

 
River Incision and Mountain Uplift
6
extrusion has been responsible for the unusually ra
pid uplift of the Himalayan Mountains,
upwards of a few millimeters per year, Hodges measu
red uplift and erosion rates based on
cosmogenic dating. To support rapid uplift, Hodges
found that the annual rate of uplift,
mean hillslope angle, and relative stream channel s
teepness all increased over millennia
timescales (Fig. 3). Hodges also found that annual
monsoon precipitation increased over
the zone of unusually rapid uplift, further support
ing his hypothesis that there exists a
significant relationship between local climate and
deformation. Furthermore, the
correspondence of the region of high monsoon precip
itation to the zone of channel
extrusion is consistent with the hypothesis that ch
annel extrusion is caused by range-front
erosion in response to monsoon. As the “tectonic an
eurysm” theory postulates, the
extrusion activated by rapid erosion results in the
diversion of crustal flow to the front
range, which in turn causes uplift of the mountains
so that the peaks can more readily
intercept the monsoon as it tracks northward. Glaci
al erosive processes primarily drove
past erosion of the Himalayas, but much of today’s
erosion is climate-induced and has a
notably strong correlation to the erosion driving s
teepening channel extrusion and
mountain uplift.
While inertia-driven tectonic activity is still pre
sent in the Himalayas, the
resulting thickening crust is insufficient in expla
ining the unparalleled rapid rates of uplift.
Scientists looked to erosive processes to explain t
he phenomenon. River incision is a
boundary condition for hillslope erosion. As the in
cision steepens, the mountain slope will
become less stable and will erode at a higher rate,
primarily through mass movement. The
incising river channel coupled with upland glacial
erosion of mountain tops lowers the
mean elevation and weakens the underlying crust, al
lowing advective heat flow from the

 
River Incision and Mountain Uplift
7
crust to move upward, into the mountain massif, res
ulting in mountain uplift. The rate of
fluvial erosion, correlated to the rate of uplift,
is directly affected by stream power, which is
proportional to water discharge and valley slope; t
herefore, as the slope angle increases so
does the rate of fluvial erosion and vice versa. Ma
ny of the erosive processes in the
Himalayas today are driven by climate and are adver
sely affected by climate change. The
main mechanism causing the rapid uplift in the Hima
layas is increasing river incision, thus
resulting in some of the world’s highest peaks, ste
epest slopes, and deepest valley gorges in
the world
River Incision and Mountain Uplift
8
Figure 3.
Relationship of
annual rate of uplift, mean hillslope angle, relati
ve stream channel steepness, and
annual monsoon precipitation to uplift. Hodges, K.
(2006, August). Climate and the Elution of Mounta
ins:
New studies of the Himalaya and the Tibetan Plateau
suggest a deep relation between climate and Scientific Ameri