AN ABSTRACT OF THE THESIS OF Abe A. Clark for the degree of Master of Science in Animal Science presented on May, 4 th 2007. Title: Botanical Composition and Diet Quality of Beef Cattle Grazing at Three Stocking Rates Following Fuels Reduction in Mixed Conifer Forests Abstract approved: Timothy DelCurto ABSTRACT: An experiment was conducted to evaluate the influence of forest fuels reduction on the diet quality, botanical composition, relative preference, and foraging efficiency of beef cattle grazing at different stocking rates. A split plot factorial design was used, with the whole plots (3 ha) being fuel reduced or no treatment (control) and the split plots (1 ha) within grazed to three levels of forage utilization; (low) 3 heifers/ha, (mod) 6 heifers/ha, (high) 9 heifers/ha, with a 48 hour grazing duration. Grazing treatments were applied in August of 2005 and 2006. Cattle diet composition and masticate samples were collected during 20 minute grazing bouts using six ruminally cannulated cows in each experimental unit. Masticate samples were analyzed for crude protein (CP), acid detergent fiber (ADF), neutral detergent
fiber (NDF), and invitro dry matter digestibility (IVDMD). Relative preference indices (RPI) indicate a strong preference for grass regardless of treatment and stocking rate. Grass consumption was lower in the control pastures (p<.05) and tended (P<.95) to decrease with increased stocking rates. Shrub use was higher in control pastures displaying a quadratic effect (p<.05) due to stocking where shrub use increased stocking rate across all treatments. Cattle grazing control pastures consumed diets higher in crude protein compared to cattle grazing treated pastures (p<.05). IVDMD values were significantly lower (p<.05) in control sites and tended (p=.10) to decrease with increased stocking rates. In both control and treated pastures bites per minute and grams consumed per minute declined (p=.003) with increased stocking, indicating foraging efficiency of cattle decreases with increased stocking rates. Our data indicated that cattle grazing late season grand fir habitat types have a strong preference for grass regardless of treatment or stocking rate. However, as stocking rate increased in both control and treated pastures grass consumption decreased, shrub consumption increased and foraging efficiency decreased. Fuels reduction did not increase late season shrub consumption, however it could lower late season CP availability. Keywords: cattle, fuels reduction, diet quality, diet selection
Botanical Composition and Diet Quality of Beef Cattle Grazing at Three Stocking Rates Following Fuels Reduction in Mixed Conifer Forests by Abe A. Clark A Thesis submitted to Oregon State University In partial fulfillment of the requirements for the degree of Master of Science Presented May 4, 2007 Commencement June 2007
Master of Science Thesis of Abe A. Clark presented on May 4, 2007. APPROVED: Major Professor, representing Animal Science Head of the Department Animal Science Dean of the Graduate School I understand that my thesis will become part of the permanent collection of Oregon State University libraries. My signature below authorizes release of my dissertation to any reader upon request. Abe A Clark, Author
ACKNOWLEGEMENTS I would like to thank and acknowledge the Pacific Northwest Research Station and the Eastern Oregon Agriculture Research Station for funding this project. I would like to express my appreciation to all my family, friends and mentors. I can not thank you all enough for all your help. Tim, thanks for taking me on as one of your graduate students and for all your help along the way. Thanks, Brian, Ryan, Jack, Dennis, and Kristen for helping me with collections and hauling water and trailers. I also want to thank C.W. and Jenny for their help with collections, building fence, and hauling cows. Bryan and Bridgett your help with plant sampling was invaluable. In addition thank you Ken Walburger for all your help with my study, and with making the transition from an undergraduate to a graduate student. You all made this enjoyable endeavor.
CONTRIBUTION OF AUTHORS Dr. Tim DelCurto assisted with experimental design, data collections, and data interpretation. Dr. Marty Vavra assisted with experimental design and data collections. Dr. Daalkhaijav Damiran and Enkhjargal Darambazar assisted with data collections and laboratory analysis. Brian Dick assisted with data collections and general logistics throughout the study.
TABLE OF CONTENTS Page LITERATURE REVIEW………………………………………….. 1 Introduction………………………………………………….. 1 Fuels Reduction………………………………………............ 2 Post Treatment Management………………………………… 3 Diet Selection and Quality…………………………………… 4 Statement of the Problem…………………………………….. 6 Literature Cited……………………………………………….. 8 BOTANICAL COMPOSISTION AND DIET QUALITY OF BEEF CATTLE GRAZING AT THREE STOCKING RATES FOLLOWING FUELS REDUCTION IN MIXED CONIFER FORESTS…………… 12 Abstract…..…………………………………………………... 13 Introduction…………………………………………………... 14 Materials and Methods……………………………………….. Study Area……………………………………...………. Diet Composition….......................................................... Diet Quality……………………………………...……… Foraging Efficiency……………………………...……… Statistical Analysis……………….……………...……… 15 15 18 19 20 20 Results and Discussion……………………………………….. Diet Composition….......................................................... Diet Quality……………………………………...……… Foraging Efficiency……………………………...……… Implications................................................................…... 21 21 24 27 31 Literature Cited……………………………………………….. 32 SUMMARY…………….…………………………………………... Literature Cited……………………………………………….. 35 37
TABLE OF CONTENTS (Continued) Page BIBLIOGRAPHY……....………………………………………….. 38 APPENDICES………….………………………………………….. 43
LIST OF FIGURES Figure Page 2.1 Grams consumed per minute of cattle grazing at low, moderate, and high stocking rates in control and treated pastures at the Starkey Forest and Range, northeast Oregon (Data averaged over 2005 and 2006)……………………….. 29 2.2 Bites consumed per minute of cattle grazing at stocking rates of 0%, low, moderate, and high in control and treated pastures at the Starkey Forest and Range, northeast Oregon (Data averaged over 2005 and 2006)……………………….. 30
LIST OF TABLES Table Page 2.1 Percent diet composition by forage class of cattle grazing at stocking rates of 0%, low, moderate, and high in control and treated pastures at the Starkey Forest and Range, northeast Oregon (Data averaged over 2005 and 2006)……. 21 2.2 Relative preference index by forage class of cattle grazing at stocking rates of 0%, low, moderate, and high in control and treated pastures at the Starkey Forest and Range, northeast Oregon (Data averaged over 2005 and 2006)……. 23 2.3 Relative preference index for the dominant shrubs consumed within all shrubs consumed by cattle grazing at low, moderate, and high stocking rates in control and treated pastures at the Starkey Forest and Range, northeast Oregon (Data averaged over 2005 and 2006)………………. 23 2.4 Relative preference index for the dominant grasses consumed within all grasses consumed by cattle grazing at low, moderate, and high stocking rates in control and treated pastures at the Starkey Forest and Range, northeast Oregon (Data averaged over 2005 and 2006)………………. 24 2.5 Percent crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), and invirto dry matter digestibility (IVDMD) of masticate samples from cattle grazing at low, moderate, and high stocking rates in control and treated pastures at the Starkey Forest and Range, northeast Oregon (Data averaged over 2005 and 2006)……. 25 2.6 Percent crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), invirto dry matter digestibility (IVDMD), and % moisture of clipped and hand plucked forages by species in control and treated pastures at the Starkey Forest and Range, northeast Oregon (Data averaged over 2005 and 2006). …………………………….. 28
LIST OF APPENDICES Apendix Page A.2.1 Diet quality of cattle masticate samples at Starkey (2005,06)……….…………………………………….. ……. 44 A.2.2 Diet Quality of hand plucked forages by species at Starkey (2005,06)……………………………...……….…… 47 A.2.3 Percent diet composition by forage class of cattle at Starkey (2005,06)……………………………………...……. 48 A.2.4 Grams consumed per minute of cattle at Starkey (2005,06)……………………………………………………. 53 A.2.5 Bites consumed per minute of cattle at Starkey (2005,06)……………………………………………………. 57
LITERATURE REVIEW Introduction In recent years, the financial and ecological impacts of catastrophic wildfires in the Western United States have become a major issue in forest land management. Before the advent of fire control in the early 20 th century, fire was a major factor in forest disturbance. Wildfire suppression and selective logging are two of the primary changes that have altered the present day structure of many forest stands throughout the West, especially on the drier forest sites. On these sites, the removal of fire and the selective logging of large fire­resistant trees has lead to an increase in the establishment of smaller trees, understory fuels, and tree density (Agee and Skinner 2005). Changes in understory and ladder fuels (small trees) have increased the risk of large stand replacing wildfires because these fuels often assist a ground fire in reaching the forest canopy and becoming a crown fire. The increase in tree density has also allowed shade­tolerant species to establish in areas that were historically dominated by ponderosa pine (Tiedemann et al. 2000; Kerry and Fiedler 2006). Changes in species composition coupled with structural changes have created forest stands more susceptible to insect attack and disease (Tiedemann et al. 2000). Widespread outbreaks of western spruce budworm (Choristoneura occidentalis) and Douglas­fir beetle (Dendroctonus pseudotsugae) in the 1980’s and early 90’s have left dense stands of dead trees highly susceptible to stand replacing wildfires (Bull et al. 2005).
2 Fuels Reduction The importance of fire as a natural component of ecological systems is now recognized by scientist and managers who have developed methods, using prescribed fire and the mechanical removal of trees, to reduce fuel loads in forest stands. By reducing the fuel load, managers seek to reduce the intensity, size, and damage of wildfires as well as to help prevent insect outbreaks (Fernandes and Botelho 2004; Barbour et al. 2004). Mechanically removing trees (thinning) is primarily used to reduce large or coarse fuels (Hong et al. 2004). The reduction in overstory canopy cover has been shown to increase understory production (Kerry and Fiedler 2006; McConnell and Smith 1970) by reducing tree competition, resulting in an increase in resource availability to understory grasses, forbs, and shrubs (Covington 1997). Depending on the forest type and structural composition of the stand, prescribed fire may be implemented following the mechanical removal of trees to reduce the amount of surface fuels (Agee and Skinner 2005; Stephens and Moghaddas 2005). Stephens and Moghaddas (2005) suggested that removing surface fuels may reduce flame length and fireline intensity resulting in a decreased probability of crown fire and tree mortality. However, the potential ecological effects of prescribed fire are diverse and vary considerably depending on burning conditions and intensity of the fire (Tiedemann et al. 2000). Additional research is necessary in order to determine the effect of prescribed fire on other ecosystem components including wildlife, livestock, insects, soils, coarse woody debris, snag density, and live biomass accumulation (Stephens and Moghaddas 2005).
3 Post Treatment Management Research is also needed to determine how ecosystem components respond to different post fuels treatment management strategies (Riggs et al. 2000). Many studies have looked at vegetation response after fire (Johnson 1998; Rouse 1986; Conard and Radosevich 1982). However, few studies have included herbivory as a factor in post­fire vegetation response, even though the herbivory regime that follows can result in altered plant communities (Riggs et al. 2000). Typically in undisturbed forest stands, a low level of grazing is considered to have a positive impact on structure and species diversity (Mitchell and Kirby 1990). However, forest stands, and the plant communities within, vary considerably and managers face the challenge of maintaining sustainable grazing without undesirable vegetation changes (Heady 1964). Johnson (1998) suggested that prescribed fire creates early seral stages of vegetation resulting in improved plant vigor along with increased plant community diversity. He also suggested that ungulates would be attracted to the succulent emergent vegetation at these sites. Since ungulates feed selectively and can alter the plant species composition of a community (Augustine et al. 1998; Riggs et al. 2000), the subsequent effect may be species replacement and a change in the successional pathway. Therefore, it is important to understand how herbivory and utilization level can affect vegetation following fuels reduction treatments. Augustine and McNaughton (1998) suggested that the relationship between foraging selectivity and plant tolerance is the basic mechanism by which ungulate herbivory can change plant species composition. Selective herbivory can have
4 direct and indirect influences on forest communities (Riggs et al. 2004). Herbivores are capable of environmental change through altering the pathway of succession by accelerating seral vegetation to climax or altering the vegetation present at climax (Riggs et al. 2000; Hobbs 1996). Because there are dietary differences between species, large scale experiments that observe different species of herbivores at different densities are needed in order to document these changes in successional pathways (Riggs et al. 2000). As part of this documentation, the changes in herbivore diet selection and diet quality after fuel reduction treatments need to be recognized. These dietary changes should be measured seasonally, at different levels of utilization, as well as over time. Diet Selection and Quality Cattle have been shown to be very selective grazers (Beck 1975; Cruz and Ganskopp 1998). Diet selection and the diet quality of the forage consumed are affected by the chemical composition and the physical characteristics of the forage (Kothmann 1992) as well as the species composition and amount of available forage present at the site (Walburger et al. 2007). The inherent heterogeneous vegetative composition of forest ecosystems allows grazing animals the opportunity to select from a variety of plant species within a pasture. Since different plant species can vary significantly in nutritive quality (Provenza et al. 2007), fuel reduction and the level of forage utilization may affect diet quality due to influences on the availability and structure of the vegetation present (Guevara et al. 1996).
5 Growth stage is another factor that may differ in fuels treated and untreated sites, which may also have an influence on the dietary quality of the available forage. Cruz and Ganskopp (1998) found that as plants reach senescence, forage quality tends to decline. Beck (1975) observed a decrease in cattle preference of some grasses with maturation. In addition Holecheck et al. (1982a) saw a decrease in forb consumption with maturation. As grasses and forbs senesce in late summer/early fall cattle often increase shrub consumption (Holechek et al. 1982a; Darambazar et al. 2003). In a study at the Starkey Experimental Forest and Range, Damiran (2006) reported that shrubs retained more crude protein than mature grasses or forbs in late summer. In a Northeast Oregon study, Darambazar et al. (2003) suggested that grass maturation and the subsequent decline in quality can occur in the first half of the late summer grazing season, while forbs and shrubs remain higher in quality. It was also suggested that cattle will increase shrub consumption with the maturation of grasses and the reduction in forb availability. Increased shrub use has also been attributed to a decline in grass availability (Holecheck et al. 1982a). An increase in shrub consumption has been reported in other studies when green grass is unavailable (Rosiere et al. 1975; Holechek et al. 1982a). Willms et al. (1980) reported an increase in shrub use with an increase in grazing intensity. Studies at the Starkey Experimental Forest and Range by Holechek et al. (1982a,b) have identified common snowberry as a preferred and important browse species late in the season. Darambazar et al. (2003) suggested that late summer grazing on riparian meadows should be light or avoided once grasses have reached senescence, in order to
6 prevent over utilization of shrubs. Since the early 1950’s managers have been concerned about over utilization of shrubs by cattle grazing Northeast Oregon forests, due to the importance of shrubs for wintering deer and elk (Mitchell 1951). Additionally, Mitchell and Rodgers (1985) stated that most Northwest forest/range managers believe that cattle and big game prefer shrub species occurring on open sites following logging or fire, and when stands approach climax the most prevalent shrubs are unpalatable and seldom utilized as forage. These relevant concerns justify the need for research that documents cattle diet selection after fuels reduction. Statement of the Problem The sustainability of livestock grazing has been under scrutiny in recent years due to an increase in social pressure to remove livestock from public lands (Wuerthner 1990). Public demand for non­grazing uses such as recreation and wildlife continue to increase with the ever­growing human population. Kosco and Bartolome (1985) believed that detailed inventories of land use capabilities and better management to minimize harmful interactions with conflicting uses is essential to the future of livestock on Federal lands. Holechek (1981) believed livestock grazing controlled by the use of scientific principles is compatible with other public rangeland resources and can also be used as a tool to enhance those resources. In addition Heitschmidt (2004) suggested that the employment of science­based rangeland grazing management strategies and tactics can ensure ecological sustainability. Research is a continual process and the foundation for
7 developing new and sound grazing management strategies. DelCurto et al. (2005) addressed the need for additional research that encourages the sustainable use of rangeland resources. Since elk, cattle, and deer share millions of acres of public and private forest and rangelands across the western United States and Canada (Coe et al. 2005), it is often important to manage for optimal interspecific performance. Understanding the spatial and dietary overlap between species is critical for successful forage allocation (Coe et al. 2005). In addition, Jensen et al. (1972) felt that the proper allocation of forage is the most critical factor in managing rangelands frequented by big game in the winter and domestic livestock during other times of the year. Interior Northwest forests are often prone to forage nutrient deficiencies in late summer due to dry summer conditions (Svejcar and Vavra 1985). Damiran (2006) suggested that prior grazing could create forage competition between cattle, deer, and elk utilizing late summer northeast Oregon rangelands due to an increased animal dietary overlap observed in early summer. He also suggested that monitoring productivity and use of key forage species, particularly in allotments containing shrubs communities, would compliment management objectives on shared mixed conifer rangelands. Knowledge of seasonal herbivore foraging behavior is essential to the sustainable management of forage resources. Walker (1995) believed diet selection is the most important aspect of foraging behavior relative to its impact on plant community structure. Additionally, he believed that stocking rate is the number one problem of grazing management. If stocking rate exceeds carrying
8 capacity, preferred plants are put at a competitive disadvantage to non­preferred plants, which generally results in a change in plant community composition along with a reduction in overall plant production and/or overall plant nutritive quality (Walker 1995). In addition, preferred species may be subjected to additional stress if herbivores are attracted to the early seral vegetation accompanying the secondary succession that follows fuels reduction treatments. Our study seeks to address concerns about the effects of cattle grazing and the influence of stocking rate on the plant community dynamics following fuels reduction through looking at cattle forage selection and forage preference. In addition we seek to document changes in cattle diet quality after fuels reduction at different stocking rates. The results of this study will be used as part of a larger, long­term study that will provide information and assist with modeling the interaction of ungulate herbivory and episodic disturbance on mixed conifer forests. Literature Cited Agee, J.K. and C.N. Skinner. 2005. Basic principles of forest fuel reduction treatments. Forest Ecology and Management. 211:83­96 Augustine, D.J. and S.J. McNaughton. 1998. Ungulate effects on the functional Species composition of plant communities: Herbivore selectivity and plant tolerance. J. Wildl. Manage. 62:1165­1183 Barbour, J.R., R.D. Fight, G.A. Christensen, G.L. Pinjuv, and R.V. Nagubadi. 2004. Thinning and prescribed fire and projected trends in wood product potential, financial return, and fire hazard in Montana. USDA­ Forest Service, Pacific Northwest Region. Gen. Tech. Rep. PNW GTR­606, Portland, OR Beck, R.F. 1975. Steer diets in southeastern Colorado. Range Manage. 28:48­51
9 Bull, E.L., A.A. Clark, and J.F. Shepherd. 2005. Short­term effects of fuel reduction on pileated woodpeckers in northeastern Oregon—a pilot study. U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. Res. Pap. PNW­RP­564. Coe, P. K., B. K. Johnson, K. M. Stewart, and J. G. Kie. 2005. Spatial and temporal interactions of elk, mule deer, and cattle. March 20, 2004. Transactions of the North American Wildlife and Natural Resources Conference 69. Conard, S.G. and S.R. Radosevich. 1982. Post­fire succession in white fir (Abies concolor) vegetation of the Northern Sierra Nevada. Madrono. 29:42­56 Covington, W.W., P.Z. Fule, M.M. Moore, S.C. Hart, T.E. Kolb, J.N. Mast, S.S. Sackett, and M.R. Wagner 1997. Restoring ecosystem health in ponderosa pine forests of the Southwest. Journal of Forestry 95:23­39 Cruz, R. and D. Ganskopp. 1998. Seasonal preferences of steers for prominent northern Great Basin grasses. J. Range Manage. 51:557­565 Damiran, Daalkhaijav. (2006) Influence of previous cattle and elk grazing on the subsequent diet quality and nutrient intake rate of cattle, deer, and elk grazing late­ summer mixed­conifer rangelands. Ph.D. Dissertation. Oregon State University., Corvallis. 119 p. Darambazar, E., T. DelCurto, C. Ackerman, G. Pulsipher, and D. Damiran. 2003. Changes in forage quantity and quality with continued cattle grazing in a mountain riparian pasture. In: Proceedings of the West. Sec. of Amer. Soc. Anim. Sci. 54:324­328. DelCurto, T., M. Porath, C.T. Parsons, and J.A. Morrison. (2005) Management Strategies for Sustainable Beef Cattle Grazing on Forested Rangelands in the Pacific Northwest. Rangeland Ecology & Management. 58:119– 127 Fernandes, P.M., and H.S. Botelho. 2004. A review of prescribed burning effectiveness in fire hazard reduction. International Journal of Wildland Fire. 12:117­128 Guevara, J.C., C. R. Stasi and O. R. Estevez. 1996. Seasonal specific selectivity by cattle on rangeland in the Monte Desert of Mendoza, Argentina. Journal of arid environments. 34:125­132 Heady, H.F. 1964. Palatability of herbage and animal preference. J. Range Manage. 17:76­82
10 Heitschmidt, R. K., L.T. Vermeire, and E.E. Grings. 2004. Is rangeland agriculture sustainable? J. Anim Sci. 82:138­146 Hobbs, N.T. 1996. Modification of ecosystems by ungulates. J. Wildl. Manage. 60:695­713 Holechek, J.L. 1981. Livestock grazing impacts on public lands: a viewpoint J. Range Manage. 34:251­254 Holechek, J.L., M. Vavra, J. Skovlin, and W.C. Krueger. 1982a. Cattle diets in the Blue Mountains of Oregon. II. Forests. J. Range Manage. 35:239­242 Holechek, J.L., M. Vavra, and J. Skovlin. 1982b. Cattle Diet and Daily Gains on a Mountain Riparian Meadow in Northeastern Oregon. J. Range Manage. 35:745­ 747 Hong, S.E, B.Z. Shang, T.R. Crow, E.J. Gustafson, and S.R. Shifley. 2004. Simulating forest fuel and fire risk dynamics across landscapes—LANDIS fuel module design. Ecological Modelling. 180:135­151 Jensen, C.H., A.D., Smith and G.W. Scotter. 1972. Guidelines for grazing sheep on rangelands used by big game in winter. J. Range Manage. 25: 346­352 Johnson, C.G. 1998. Vegetation Response after wildfires in National Forests of Northeastern Oregon. USDA­ Forest Service, Pacific Northwest Region. R6­NR­ ECOL­TP­06­98. Kerry L.M., and C.E. Fiedler. 2006. Restoration treatment effects on the understory of ponderosa pine/Douglas­fir forests in western Montana, USA. Foresst Ecology and Management 222:355­369 Kosco, B.H., and J.W. Bartolome. 1985. Forest grazing: past and future. J. Range Manage. 34:248­251 Kothmann, M.M. (1992). Nutrition for livestock grazing rangelands and pasturelands. In: Howard, J.L. (Ed.), Current Veterinary Therapy 3: Food Animal Practice, pp. 285–293. McConnell B.R. and J.G. Smith. 1970. Response of understory vegetation to Pinus ponderosa thinning in eastern Washington, J. Range Manage. 23:208–212 Mitchell, F.J.G. and K.J., Kirby. 1990. The impact of large herbivores on the conservation of semi­natural woods in the British uplands. Forestry. 63:333­353 Mitchell, G.E. 1951. Status of browse on ranges of eastern Oregon and eastern Washington. J. Range Manage. 4:249­253
11 Mitchell, J.E., and R.T., Rodgers. 1985. Food habits and distribution of cattle on a forest and pasture range in northern Idaho. J. Range Manage. 38:214­220 Stephens, S.L., and J.J. Moghaddas. 2005. Experimental fuel treatment impacts on forest structure, potential fire behavior, and predicted tree mortality in a California mixed conifer forest. Forest Ecology and Management. 215:21­36 Svejcar, T., and M. Vavra. 1985. The influence of several range improvements on estimated carrying capacity and potential beef production. J. Range Manage. 38:395­399 Tiedemann, A.R., J.O. Klemmedson, and E.L. Bull. 2000. Solution of forest health problems with prescribed fire: are forest productivity and wildlife at risk? Forest Ecology and Management. 127:1­18 Riggs, R. A., A. R. Tiedemann, J. G. Cook, T. M. Ballard, P. J. Edgerton, M. Vavra, W. C. Krueger, F. C. Hall, L. D. Bryant, L. L. Irwin, and T. DelCurto. 2000. Modification of mixed­conifer forests by ruminant herbivores in the Blue Mountains Ecological Province. USDA­ Forest Service, Pacific Northwest Region. Research Paper PNW­RP­527. LaGrande, OR. Riggs, R. A., J. G. Cook, and L. L. Irwin. 2004. Management Implications of Ungulate Herbivory in Northwest Forest Ecosystems. Transactions of the North American Wildlife and Natural Resource Conference 69: in press. Rosiere, R.E., R.F. Beck, and J.D. Wallace. 1975. Cattle diets on semidesert grassland: botanical composition. J. Range Manage. 28:89­93 Rouse, C. 1986. Fire effects on Northeastern forests: Aspen. USDA­ Forest Service, North Central Forest Experiment Station, General Technical Report NC ­102 Walburger, K. J., M. Wells, M. Vavra, T. DelCurto, B. Johnson, and P. Coe. 2007. Influence of Cow Age on Grazing Distribution in a Mixed Conifer Forest. J. Range Ecol. Manage. (In press). Walker, J.W. 1995. Viewpoint: grazing management and research now and in the next millennium. J. Range Manage. 48:350­357 Willms, W., A. McLean, R. Tucker, and R. Ritcey. 1980. Deer and cattle diets on summer range in British Columbia. J. Range Manage. 33:55­59 Wuerthner, G. 1990. The Price is wrong. Sierra. 25:38­48
12 BOTANICAL COMPOSISTION AND DIET QUALITY OF BEEF CATTLE GRAZING AT THREE STOCKING RATES FOLLOWING FUELS REDUCTION IN MIXED CONIFER FORESTS Abe Clark(1), Tim DelCurto(1), Martin Vavra(2), Daalkhaijav Damiran(1), Enkhjargal Darambazar(1), and Brian L. Dick(2) (1) Eastern Oregon Agricultural Research Center, Oregon State University, Union. OR 97883 (2) United States Forest Service, Pacific Northwest Research Station, 1401 Gekeler Lane, La Grande, OR 97850, USA
13 ABSTRACT An experiment was conducted to evaluate the influence of forest fuels reduction on the diet quality, botanical composition, relative preference, and foraging efficiency of beef cattle grazing at different stocking rates. A split plot factorial design was used, with the whole plots (3 ha) being fuel reduced or no treatment (control) and the split plots (1 ha) within grazed to three levels of forage utilization; (low) 3 heifers/ha, (mod) 6 heifers/ha, (high) 9 heifers/ha, with a 48 hour grazing duration. Grazing treatments were applied in August of 2005 and 2006. Cattle diet composition and masticate samples were collected during 20 minute grazing bouts using six ruminally cannulated cows in each experimental unit. Masticate samples were analyzed for crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), and invitro dry matter digestibility (IVDMD). Relative preference indices (RPI) indicate a strong preference for grass regardless of treatment and stocking rate. Grass consumption was lower in the control pastures (p<.05) and tended (P<.95) to decrease with increased stocking rates. Shrub use was higher in control pastures displaying a quadratic effect (p<.05) due to stocking where shrub use increased stocking rate across all treatments. Cattle grazing control pastures consumed diets higher in crude protein compared to cattle grazing treated pastures (p<.05). IVDMD values were significantly lower (p<.05) in control sites and tended (p=.10) to decrease with increased stocking rates. In both control and treated pastures bites per minute and grams consumed per minute declined
14 (p=.003) with increased stocking, indicating foraging efficiency of cattle decreases with increased stocking rates. Our data indicated that cattle grazing late season grand fir habitat types have a strong preference for grass regardless of treatment or stocking rate. However, as stocking rate increased in both control and treated pastures grass consumption decreased, shrub consumption increased and foraging efficiency decreased. Fuels reduction did not increase late season shrub consumption, however it could lower late season CP availability. Key words: diet quality, diet selection, forage preference, fuels reduction Introduction Due to the increasing cost and concern of catastrophic wildfires in the Western United States, there is an increasing interest in fuels reduction projects. Fuel reduction treatments utilize various methods of thinning and/or prescribed fire to obtain desirable forest stand conditions (Barbour et al. 2004). However, the effects of fuels reduction on ecosystem function are not well known. Since both public and private timberlands are typically grazed by cattle in the Western United States, it is also essential to understand the effect of fuels reduction on cattle diets. Additionally, the interaction of stocking rate and fuels management on forest vegetation diversity and vigor has not been evaluated in the peer reviewed scientific literature. This information is not only important for cattle production but also for land management since selective herbivory can have direct and indirect influences on forest communities (Riggs et al. 2004). Herbivores are
15 capable of environmental change through altering the pathway of succession by accelerating seral vegetation to climax or altering the vegetation present at climax (Riggs et al. 2000; Hobbs 1996). If stocking rate exceeds carrying capacity, preferred plants are put at a competitive disadvantage to non­preferred plants, which generally results in a change in plant community composition along with a reduction in overall plant production and/or overall plant nutritive quality (Walker 1995). To explore the effects of fuel reduction, a series of studies have been developed. This study was designed to look at how cattle diets are affected by fuels reduction and stocking rate. The objective of this study was to evaluate the effect of fuels reduction on the botanical composition, forage preference, and diet quality of cattle grazing at different stocking rates in mixed conifer forests. MATERIALS AND METHODS Study Area The study was conducted at the Starkey Experimental Forest and Range located approximately 50 km southwest of La Grande Oregon. The elevation of the study area ranges between 1200m and 1500m. Average annual precipitation is approximately 400 mm (Bureau of Reclamation AgriMet). The dominant grasses include pinegrass (Calamagrostis rubescens), western fescue (Festuca occidentalis), Kentucky bluegrass (Poa pratensis), elk sedge (Carex geyeri), California brome (Bromus carinatus), and Idaho fescue (Festuca idahoensis). Common snowberry (Symphoricarpos albus), shinyleaf spiraea (Spiraea betulifolia lucida), twinflower (Linnaea borealis), bearberry (Arctostaphylos uva­ursi), big
16 huckleberry (Vaccinium membranaceum), and grouse huckleberry (Vaccinium scoparium) are the primary shrub species that are found in the study area. The most common forbs include western yarrow (Achillea millefolium), tall annual willowherb (Epilobium paniculatum), strawberry (Fragaria spp) and lupine (Lupinus spp.). From 2000 to 2003 fifty mature multilayered grand fir/Douglas­fir/larch (Larix occidentalis) stands (9 to 35 ha) were mechanically thinned and forty­two of those stands were broadcast burned between 2001 and 2003. Stands were thinned with a feller­buncher to reduce fuel loads to no more than 15­20 tons per acre (Vavra et al. 2004). The objective was to retain 18.4 m²/ha basal area of live trees, live green trees larger than 51cm diameter at breast height were not removed (Bull et al. 2005). Stands were ignited by hand with drip torches and burning occurred when the maximum daily temperature was between 12 and 24° C, and minimum relative humidity was 15 to 55 percent with the percentage of fuel moisture of 1­hour fuels between 4 and 11, of 10­hour fuels between 7 and 9, and of 1,000­hour fuels between 11 and 15 (Bull et al. 2005). In the summer of 2002, two (3­ha) exclosures were constructed in stands that were treated with mechanical tree removal (summer, 2001) and broadcast burning (fall, 2001). The locations of the treated exclosures were established at random within the available treated habitat types. These exclosures were built using 8 foot high game fence to ensure that no large herbivores would be allowed to graze the exclosures prior to the initiation of the grazing treatments. Two (3­ha) untreated (control) exclosures were built using electric fence in previously logged mixed conifer forest stands
17 which are currently grazed. These untreated exclosures were constructed early in the summers of 2005 and 2006 prior to cattle grazing each year. The locations of the untreated exclosures were selected at random on sites adjacent to the treated exclosures. Within each 3­ha exclosure were three experimental units (1­ha paddocks). Each unit was randomly assigned 1 of 3 levels of cattle grazing (light, moderate, or heavy stocking). In order to determine stocking rate we took the estimated biomass of forage available in each1­ha unit (approximately 450 kg) divided by the forage consumed per animal per day. The forage consumed per day was estimated by taking the mean daily intake rate (approximately 2.75% of body weight) divided by an average heifer weight (455 kg) resulting in 12.5 kg of forage consumed per cow per day. We tried to assimilate three levels of stocking (light, moderate, and heavy) where the moderate stocking was used to represent typical stocking on the majority of regional forest grazing allotments. Our moderate stocking rate was configured to result in approximately 33% utilization. Light stocking was configured to result in approximately 17% utilization, while heavy stocking resulting in approximately 50% utilization. To obtain approximately 17, 33, and 50% utilization, groups of heifers (3, 6, and 9) were placed in randomly selected experimental units for two full days to provide stocking rates equivalent to 6, 12 and 18 cattle days/ha. Post treatment utilization estimates were obtained by means of ocular estimates (60­per ha) similar to that described by Parsons et al. (2003) using regression to adjust for observer error. Grazing treatments were applied in August of 2005 and 2006. The month of August was selected with the objective of recording the effect the treatments
18 had on the selection for vulnerable shrubs and trees due to the senescence of herbaceous vegetation at that time. Heifers were preconditioned to the area for two days before grazing treatments began each year to account for the effect of previous experience on diet preference (Parsons et al. 1994). Cattle dietary composition and quality of diet were two of the response variables that were measured in regard to the treatment and level of herbivory. The order in which exclosures were sampled was randomly selected for the first year and exclosures were visited in the reverse order the second year. Diet Composition Data was collected on species frequency in mid­July, prior to initiation of grazing treatments. Vegetation was sampled along parallel transects located at 15 meter intervals within each experimental unit. Ten x ten centimeter square quadrats (n=30 per experimental unit) were located every 10 meters along each transect to measure plant frequency. Frequency was measured by recording the presence or absence of species within each plot. This information was used to determine the relative preference of species consumed by cattle in each treatment. Cattle dietary composition information was collected in mid­August from six heifers in each experimental unit (1 ha paddock) using bite­count methodology similar to that described by Wickstrom et al. (1984) and Canon et al. (1987). Diet composition data were collected at 0% utilization in all experimental units at the initiation of the grazing treatments each year and six, (6 animals and 1
19 bouts/animal) 20 minute grazing trials were conducted in each unit after the grazing treatment was applied. Each observer was assigned a heifer at random for each grazing bout. The animals were accustomed to observers in close proximity and observers had prior training in plant identification. Observers used a small hand­held tape recorder to record the number of bites of each plant species consumed (Findholt et al. 2004). These data were then transcribed from the tapes and placed in an excel file for analysis. Relative preference was calculated for grasses, shrubs, and forbs by dividing the percent bites consumed by the percent of plant frequency in the pasture. Diet Quality Cattle diet quality information was collected in mid­August from six ruminally cannulated heifers in each experimental unit (1 ha paddock). Collections occurred in each unit after the grazing treatment was applied. Each heifer’s ruminal contents were evacuated and the ruminal wall washed with a sponge to remove remaining digesta and ruminal fluid. Heifers were allowed to graze for 20 minutes and diet samples were obtained via the ruminal cannula. One rumen evacuation per heifer was preformed in each experimental unit. Ruminal samples were dried in a forced­air oven (55°C; 96 h) and ground to pass a 1­mm screen in a Wiley mill. Rumen samples were analyzed in duplicate for organic matter, invitro digestibility (Ankom Daisy II incubator, Ankom Co., Fairport, NY), nitrogen (Leco CN­2000; Leco Corporation, St. Joseph, MI), and NDF and ADF (Ankom 200 Fiber Analyzer, Ankom Co., Fairport, NY).
20 Clipped and hand plucked samples where collected from the major forage species consumed during grazing bouts in each main plot. Approximately 50 to 100 simulated bites were collected for each species. Samples were placed in paper bags, weighed, dried in a forced air oven at 55°C, and reweighed to determine dry matter. Samples were then ground to pass a 1­mm screen in a Wiley mill and analyzed in duplicate for organic matter, invitro digestibility (Ankom Daisy II incubator, Ankom Co., Fairport, NY), nitrogen (Leco CN­2000; Leco Corporation, St. Joseph, MI), and NDF and ADF (Ankom 200 Fiber Analyzer, Ankom Co., Fairport, NY). Foraging Efficiency Masticate samples were collected after each 20 minute bout. Samples were dried in a forced air oven at 50°C. The dried weight was divided by 20 to determine grams consumed per minute. Bites per minute were calculated by dividing the total number of bites per grazing bout by 20. Statistical Analysis Data were analyzed using GLM procedures of SAS (2002). Predetermined contrast statements (Steel and Torrie 1980) were used to determine significant differences. Contrast statements were as follows, Control vs. Fuels Treated, Linear, Quadratic, Linear Interaction, and Quadratic Interaction for both diet composition and quality. Differences were considered significant at p<.05.
21 Results and Discussion Diet Composition Diet composition by forage class is presented in Table 2.1. Grass made up the greatest proportion of all cattle diets, coinciding with other regional studies by Miller and Krueger (1976) and Walburger et al. (2007). Grass consumption was lower in the control pastures (p<.05) and tended (P=.095) to decrease with increased stocking rates. Shrub use was higher in control pastures (p<.05) with a significant quadratic effect (p<.05) due to stocking where shrub use tended to increase with increased stocking rate across all treatments. The higher shrub consumption in the control as well as the overall increase in shrub consumption with higher stocking rates maybe related to the availability of grasses within the pasture (Holechek et al. 1982a). Rosiere et al. (1975) observed an increase is shrub consumption when grass was unavailable. Forb consumption was similar (16% in diet) across all treatments. Table 2.1. Percent diet composition by forage class of cattle grazing at stocking rates of 0%, low, moderate, and high in control and treated pastures at the Starkey Forest and Range, northeast Oregon (Data averaged over 2005 and 2006). Control Fuels treated . 0% Low Mod High 0% Low Mod High SE % Grass 1, 2 68.8 74.1 80.1 56.5 82.0 86.5 83.9 81.9 7.2 % Shrub 1,3,4,5 6.1 3.5 6.2 23.5 2.6 2.2 4.5 5.4 3.5 % Forb 25.1 22.4 13.6 17.2 15.3 11.1 11.5 13.3 7.2 1 Main effect (p<.05) 2 Tendency for quadratic effect due to stocking rate (p<.095) 3 Linear effect due to stocking rate (p=.008) 4 Quadratic effect (p<.05) 5 Tendency for quadratic interaction (P=0.08)
22 Grass was preferred to forbs and shrubs across all treatments as determined using a relative preference index (RPI; Table 2.2). RPI values indicate a strong preference for grass regardless of treatment and stocking rate. Forbs and shrubs were never preferred as a forage class in any treatment, although there was a slight increase in shrub use with an increase in stocking rate. Table 2.3 shows the relative preference of the dominate shrub species that were consumed. Although cattle never preferred shrubs as a forage class, this table shows that there were individual shrub species that were preferred, including snowberry and shinyleaf spirea. Snowberry and shinyleaf spirea were also the dominate shrubs consumed in a study by Holechek et al. (1982a). Table 2.4 shows the relative preference of the grass species that were consumed. Pinegrass was the dominate grass occurring across all treatments and was preferred in each treatment. Elk sedge and Kentucky bluegrass were highly preferred in every treatment, while timothy and tall trisetum were preferred in the control pastures. Holechek et al. (1982a) also suggested that elk sedge was a preferred species, based on consumption and cover, in a study identifying important dietary constituents of cattle at the Starkey Experimental Forest and Range. Clark (2003) suggested that since elk sedge maintains at least moderate forage quality throughout the year it may help sustain herbivore diet quality when other forage species reach dormancy.
23 Table 2.2. Relative preference index by forage class of cattle grazing at stocking rates of 0%, low, moderate, and high in control and treated pastures at the Starkey Forest and Range, northeast Oregon (Data averaged over 2005 and 2006). Control Fuels treated . 0% Low Mod High 0% Low Mod High SE RPI Grass 1,2 2.5 3.0 2.5 2.1 4.1 6.1 3.5 3.7 0.43 RPI Shrub 1 0.2 0.2 0.2 0.8 0.4 0.9 0.7 0.5 0.17 RPI Forb 1 0.5 0.4 0.3 0.4 0.2 0.1 0.2 0.2 0.12 1 Main effect (p<.05) 2 Quadratic effect (p<.05) Table 2.3. Relative preference index for the dominant shrubs consumed by cattle grazing at low, moderate, and high stocking rates in control and treated pastures at the Starkey Forest and Range, northeast Oregon (Data averaged over 2005 and 2006). Control Fuels treated . Low Mod High Low Mod High SE . Bearberry 0.2 0.2 0.2 0.1 0.1 0.4 0.16 2 Twinflower 0.1 0.5 0.1 0.0 0.1 0.0 0.14 Oregon grape 0.1 0.9 3.1 0.3 0.2 0.2 0.70 Rose 1.1 0.6 1.6 0.3 0.1 0.7 0.70 Shinyleaf spirea 4.3 2.3 1.7 0.1 0.2 0.1 1.75 Snowberry 1.4 4.9 11.1 4.3 2.4 4.3 3.60 Grouse huckleberry 1 0.3 0.4 0.3 0.1 0.0 0.0 0.12 Big huckleberry 0.4 1.1 2.6 0.0 0.0 0.0 1.00 1 Main effect (p<.05) 2 Quadratic effect due to stocking rate (p<.05)
24 Table 2.4. Relative preference index for the dominant grasses consumed by cattle grazing at low, moderate, and high stocking rates in control and treated pastures at the Starkey Forest and Range, northeast Oregon (Data averaged over 2005 and 2006). Control Fuels treated . Low Mod High Low Mod High SE . California brome 1 1.5 1.5 1.2 3.6 1.6 7.3 1.2 Elk sedge 18.6 16.5 7.8 28.8 6.8 21.6 9.6 Pine grass 1 6.3 3.7 1.8 13.3 5.2 10.7 3.4 Orchard grass 0.6 0.1 0.9 0.0 0.6 0.0 0.4 Idaho fescue 1.9 0.5 1.2 0.2 1.3 1.2 0.9 Western fescue 0.7 1.0 2.4 0.3 0.5 0.8 0.8 Timothy 1 2.6 2.4 1.3 0.1 0.0 0.8 1.0 1 Kentucky bluegrass 12.7 8.4 19.1 5.8 1.9 5.8 3.3 Tall trisetum 1.5 2.0 0.8 0.1 0.1 0.0 0.9 1 Main effect (p<.05) Diet Quality Diet quality in terms of CP, NDF, ADF and IVDMD is presented in Table 2.5. CP values of masticate samples were higher (p<.05) in control sites than the fuels treated sites. Cattle grazing control pastures had an average CP value of 9.4% compared with 8.5% CP in treated pastures. Crude protein requirements for mature lactating beef cattle (545 kg; NRC, 1996) suggest that animals should consume 9.25% CP in their diets. Therefore, cattle grazing treated pastures may be faced with diets that are marginally deficient in protein content. Higher CP values in the control diets may be attributed to higher shrub consumption in those pastures. Holechek and Vavra (1983) suggested that shrubs retain higher CP levels than grasses and forbs in late summer. We found no significant differences in CP between stocking rates within control or treated pastures. No significant differences were found in ADF or NDF values. However there was a tendency for
25 a linear effect due to stocking rate (p=0.14) for NDF values. NDF values appeared to increase with increased stocking rates in both control and treated sites. IVDMD values were significantly lower (p<.05) in control sites and tended (p=.10) to decrease with increased stocking rates. The higher DMD values in the control pastures and the tendency for DMD values to decrease with increased stocking is likely due to a greater percent of shrubs in the diet. This relationship contradicts the high DMD values of hand plucked shrub samples (Table 2.6), however difficulties in collecting representative shrub bites may have produced observer bias. Cattle likely consumed more of the woody, less digestible, portion of the shrubs than observers collected from hand plucking. Table 2.5. Percent crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), and invirto dry matter digestibility (IVDMD) of masticate samples from cattle grazing at low, moderate, and high stocking rates in control and treated pastures at the Starkey Forest and Range, northeast Oregon (Data averaged over 2005 and 2006). Control Fuels treated . Low Mod High Low Mod High SE 1 CP 9.3 9.3 9.7 8.5 8.8 8.3 0.32 NDF 2 66.8 66.7 69.2 66.9 66.6 67.2 0.87 ADF 42.5 42.6 42.3 42.3 42.8 43.1 0.97 IVDMD 1,3 64.3 62.7 58.9 65.3 66.1 65.2 1.5 1 Main effect (p<.05) 2 Tendency for linear effect due to stocking rate (p=.14) 3 Tendency for quadratic interaction (p=.10) Overall grasses and forbs in the control pastures had greater nutritive values than grasses and forbs in the treated pastures, while shrubs were similar in nutritive value (Table 2.6). In both control and treated pasture grass had lower average CP than forbs and shrubs. Grass in the control pastures had higher
26 average CP levels (6.5%) than grass in treated pastures (4.9%), and CP values were always higher in the control pastures than the treated pastures where the same species were collected. Forb CP levels were also higher in the control pastures where the same species was collected and average CP was also higher in the control pastures, 12.8% CP opposed to 8.1% CP. Shrub CP was similar with slightly higher levels in the treated pastures, 8.8 opposed to 8.4 in the control pastures. Average grass and forb ADF, IVDMD, and percent moisture levels were higher and NDF values were lower in control pastures compared to treated pastures. The higher percent moisture and nutritive value in forage found in the control pastures may be due to differences in the growth stage of the forage present (Perez Corona et al. 1998; Cruz and Ganskopp 1998; Skovlin 1967). Growth stage may also explain the similarity in nutritive quality and moisture levels in shrubs since shrubs tend to reach senescence later in the year than forbs and grasses (Ganskopp et al. 1999). The earlier senescence of forbs and grasses in the treated pastures may be due to the decrease in the forest canopy closure and the reduction of course woody debris which in turn alters available soil water and soil temperature of the site (Svejcar and Vavra. 1985; Kruger and Bedunah 1988). Accelerated plant phenology due to a decrease in canopy cover was also reported by Long et al. (in review) in a study at the Starkey Experimental Forest and Range looking at the effects of fuels reduction on the quantity and quality of forage for elk.
27 Foraging Efficiency Foraging efficiency of cattle decreased with increased stocking rates in both control and fuels treated sites (Figure 2.1). Grams consumed per minute decreased in both control and treated pastures as stocking rate increased with a significant linear effect (p=0.003). Stocking rate also had a similar significant linear effect (p=0.003) on bites consumed per minute, with a decrease in bites per minute with increased stocking rate for both control and treated pastures. There were no significant differences between control and treated pastures. Foraging efficiency may have had an influence on the relationship between stocking rates and utilization. The anticipated percent utilization for low, moderate, and high stocked pastures were 16.7%, 33.3%, and 50%, however, average utilization estimates were 26%, 31%, and 35% for low, moderate, and high pastures. Low pastures were on average grazed 10% heavier than predicated. Moderate pastures were grazed to the approximate goal of 33% utilization. While high pastures were grazed 15% less than predicted
28 Table 2.6. Percent crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), invirto dry matter digestibility (IVDMD), and % moisture of clipped and hand plucked forages by species in control and treated pastures at the Starkey Forest and Range, northeast Oregon (Data averaged over 2005 and 2006). Forage Species Control Fuels Treated . CP NDF ADF IVDMD % Moisture CP NDF ADF IVDMD % Moisture Grasses California brome 8.8 60.4 34.1 68.0 53.1 4.1 72.9 44.4 51.8 16.0 Elk sedge 6.4 65.3 35.7 62.9 31.3 5.7 65.6 36.7 63.3 29.4 Pine grass 9.4 60.3 33.4 66.3 49.1 6.9 59.6 35.0 61.5 23.0 Orchard grass 5.5 66.2 41.1 52.2 51.0 ­­­­­ ­­­­­ ­­­­­ ­­­­­ ­­­­­ Idaho fescue 6.5 65.9 36.1 57.5 28.1 ­­­­­ ­­­­­ ­­­­­ ­­­­­ ­­­­­ Western fescue 4.0 71.3 41.2 49.9 6.7 3.6 79.7 48.6 36.0 7.8 Timothy 4.7 65.1 37.0 54.3 44.4 3.9 65.8 36.3 56.4 24.5 Kentucky bluegrass 7.0 64.4 36.0 59.5 36.6 5.7 64.8 36.6 61.8 21.8 Tall trisetum 6.2 65.4 39.5 56.1 26.2 4.7 73.9 45.6 51.9 15.0 Forbs Western yarrow ­­­­­ ­­­­­ ­­­­­ ­­­­­ ­­­­­ 6.6 45.5 33.8 69.0 9.7 Annual willowherb ­­­­­ ­­­­­ ­­­­­ ­­­­­ ­­­­­ 6.5 55.1 43.2 53.9 47.8 Birdsfoot­trefoil 15.4 30.6 21.7 77.1 67.7 ­­­­­ ­­­­­ ­­­­­ ­­­­­ ­­­­­ Lupine 10.6 30.5 21.4 84.6 47.3 10.9 36.8 25.2 75.4 13.9 Yellow salsify ­­­­­ ­­­­­ ­­­­­ ­­­­­ ­­­­­ 4.8 50.4 36.7 62.3 52.3 White clover 14.5 40.5 28.8 74.8 48.7 11.5 47.5 35.9 65.9 38.3 Stinging nettle 10.7 38.8 24.8 81.1 66.1 ­­­­­ ­­­­­ ­­­­­ ­­­­­ ­­­­­ Shrubs Twinflower 7.5 37.5 27.8 72.5 54.4 ­­­­­ ­­­­­ ­­­­­ ­­­­­ ­­­­­ Rose 8.6 37.1 18.1 82.6 22.2 9.1 30.3 15.2 79.9 22.7 Shinyleaf spirea 8.0 37.2 22.8 72.5 12.0 8.4 32.2 19.3 81.0 22.2 Snowberry 9.2 26.3 17.7 81.3 28.1 9.0 26.5 16.9 82.8 39.7 Grouse huckleberry 8.6 45 33.2 68.0 48.5 ­­­­­ ­­­­­ ­­­­­ ­­­­­ ­­­­­
29 18 Control Treated 16 14 Bites per Minute
12 10 8 6 4 2 0 Low Mod High Stocking Rate Figure 2.1. Grams consumed per minute of cattle grazing at low, moderate, and high stocking rates in control and treated pastures at the Starkey Forest and Range, northeast Oregon (Data averaged over 2005 and 2006). 30 16 Control Treated 14 Bites per Minute
12 10 8 6 4 2 0 0% Low Mod High Stocking Rate Figure 2.2. Bites consumed per minute of cattle grazing at stocking rates of 0%, low, moderate, and high in control and treated pastures at the Starkey Forest and Range, northeast Oregon (Data averaged over 2005 and 2006). 31 IMPLICATIONS Cattle grazing late season grand fir habitat types have a strong preference for grass regardless of treatment or stocking rate. In our study fuel reduction did not cause an increase in late summer/early fall shrub consumption or preference. Cattle did show an increase in shrub use as stocking rate increased, however, cattle never showed an overall preference for shrubs. The increase in shrub use seemed to be a function of grass availability. Snowberry in both the control and treated pastures and spirea in the control pastures were preferred species, therefore emphasizing the importance of balancing grazing pressure with plant species tolerance in order to prevent unwanted changes in plant composition. Cattle in this study did not select forage based solely on the nutritional quality of the plant species. Out of the dominate forage consumed, cattle showed the strongest preference for elk sedge. The preference for elk sedge in late summer/early fall could possibly be due in part to its evergreen type characteristics or nutrient density. The apparent acceleration of plant phenology in the fuels treated sites may have a negative effect on late season grass and forb nutritive quality and could lower crude protein availability for cattle grazing in late summer/early fall. However, managers may find protein supplementation to be a valid option for compensating for lower available CP in treated stands. Managers may also consider grazing fuels treated sites earlier in the year before grasses and forbs senesce or implanting fuels reduction in a portion of the stand to provide cattle
32 with increased early season forage while retaining higher quality late season forage in untreated portion. Fuels reduction occurs in many other plant communities and forest types. Season of use and stocking rates are variable within and across these habitat types. As a result, further research is needed to better understand the effects of fuels reduction and to develop proper stocking rates that coincide with season of use across various fuels treated stands. Literature Cited Barbour, J.R., R.D. Fight, G.A. Christensen, G.L. Pinjuv, and R.V. Nagubadi. 2004. Thinning and prescribed fire and projected trends in wood product potential, financial return, and fire hazard in Montana. USDA­ Forest Service, Pacific Northwest Region. Gen. Tech. Rep. PNW GTR­606, Portland, OR Bull, E.L., A.A. Clark, and J.F. Shepherd. 2005. Short­term effects of fuel reduction on pileated woodpeckers in northeastern Oregon—a pilot study. U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. Res. Pap. PNW­RP­564. Canon, S.K., P.J. Urness, and N.V. DeBule. 1987. Foraging behavior and dietary nutrition of elk in burned aspen forest. J. Range Manage. 40:433­438 Clark, P.E. 2003. Date and plant community effects on elk sedge forage quality. J. Range Manage. 56:21­26 Cruz, R. and D. Ganskopp. 1998. Seasonal preferences of steers for prominent northern Great Basin grasses. J. Range Manage. 51:557­565
33 Findolt, S. L., D. Damiran, B. K. Johnson, T. DelCurto, and J. G. Kie. 2004. Diet overlap among elk, mule deer, and cattle. March 20, 2004. Transactions of the North American Wildlife and Natural Resources Conference 69. Ganskopp, D., T. Svejcar, F. Taylor, J. Farstvedt, and K. Painter. 1999. Seasonal cattle management in 3 to 5 year old bitterbrush stands. J. Range Manage. 52:166­173 Ganskopp, D., and D. Bohnert. 2001. Nutritional dynamics of 7 northern Great Basin grasses. J. Range Manage. 54:640­647 Holechek, J.L., M. Vavra, J. Skovlin, and W.C. Krueger. 1982a. Cattle diets in the Blue Mountains of Oregon. II. Forests. J. Range Manage. 35:239­242 Holecheck, J.L., and M. Vavra. 1983. Drought effects on diet and weight gains of yearling heifers in Northeastern Oregon. J. Range Manage. 36:227­231 Krueger, J.K., and D.J., Bedunah. 1988. Influence of forest site on total nonstructural carbohydrate levels of pinegrass, elk sedge, and snowberry. J. Range Manage. 41:144­149 Long, R.A., J.L. Rachlow, J.G. Kie and M. Vavra. (in review). Fuels reduction in a western coniferous forest: Effects on quantity and quality of forage for elk. Miller, R.F., and W.C. Krueger. 1976. Cattle use on summer foothill rangelands in northeastern Oregon. J. Range Manage. 29:367­371 National Research Council, NRCS. 1996. Nutrient Requirements of Cattle. National Academy Press. Page 227. Parsons, A.J., J.A. Newman, P.D. Penning, A. Harvey and R.J. Orr. 1994. Diet preference of sheep: effects of recent diet, physiological state and species abundance, J. Anim. Ecol. 63 (1994), pp. 465–478. Parsons, C.T., P.A. Momont, T. DelCurto, M. McInnis, and M.L. Porath. 2003. Cattle distribution patterns and vegetation use in mountain riparian areas. J. Range Manage. 56:334­341 Perez Corona, M.E., B.R. Vazquez de Aldana, B. Garcia Criado, and A Garcia Ciudad. 1998. Variations in nutritional quality and biomass production of semiarid grasslands. J. Range Manage. 51:570­576
34 Skovlin, J.M. 1967. Fluctuations in forage quality on summer range in the Blue Mountains. Pacific Northwest Forest and Range Exp. Sta., USDA, Pacific Northwest 44. Steel, R.G., and J.H. Torrie. 1960 Principles and procedures of statistics. McGraw­Hill Book Co., INC. New York. Svejcar, T., and M. Vavra. 1985. The influence of several range improvements on estimated carrying capacity and potential beef production. J. Range Manage. 38:395­399 Rosiere, R.E., R.F. Beck, and J.D. Wallace. 1975. Cattle diets on semidesert grassland: botanical composition. J. Range Manage. 28:89­93 Vavra, M., M. J. Wisdom, J. G. Kie, J. G. Cook, and R. A. Riggs. 2004. The Role of Ungulate Herbivory and Management Ecosystem Patterns and Processes: Future Direction of the Starkey Project. Transactions of the North American Wildlife and Natural Resource Conference 69: in press. Walburger, K.J., T. DelCurto, and M. Vavra. 2007. Influence of forest management and previous herbivory on cattle diets. Rangeland Ecology & Manage. 60:172­178 Walker, J.W. 1995. Viewpoint: grazing management and research now and in the next millennium. J. Range Manage. 48:350­357 Wickstrom, M.L., C.T. Robbins, T.A. Hanley, D.E. Spalinger, and S.M. Parish. 1984. Food intakes and foraging energetic of elk and mule deer. J. Wildl. Manage. 48:1285­1301
35 SUMMARY This research was designed to look at late summer diets of cattle grazing fuels­treated and non­treated mixed­conifer forests in the interior Northwest. The influence of stocking rate on cattle diets was also evaluated within the context of the study. This study designed to look at the short term effects of fuels reduction, however, the data collected will be incorporated into a larger long term study. In addition to cattle diets, the diets of elk are also being studied in adjacent pastures with the objective of comparing dietary differences and herbivore specific long­ term impacts on vegetation. Our data indicated that cattle grazing late season grand fir habitat types have a strong preference for grass regardless of treatment or stocking rate. In our study elk sedge was the most preferred grass. Relative preference index values indicated that shrubs as a whole were never consumed in relation to availability in any pasture and were therefore generally avoided. However, we did see a slight increase in shrub consumption as stocking rate increased. In addition, snowberry in both the control and treated pastures and spirea in the control pastures were preferred species, therefore emphasizing the importance of balancing grazing pressure with plant species tolerance in order to prevent unwanted changes in plant composition. Due to a small sample size, and the inherent error associated with collecting samples that accurately represent the actual plant part consumed by animals, the diet quality of clipped and hand plucked forage species in this study
36 should be viewed as general examples and not absolute values. Overall, however these data do show relative trends, as well as relative differences in the diet quality of available forages growing in control versus treated pastures. These data also show relative differences in diet quality between forage classes within pastures. Forbs and grasses in the fuels treated pastures had lower overall moisture levels than forbs and grasses in the control pastures, a trend which was also noted by observers. Accompanying this observation, averaged diet quality data showed that forbs and grasses growing in the treated pastures had lower nutritive quality than forbs and grasses growing in control pastures, suggesting that fuel reduction may accelerate forb and grass phenology. The lower CP values (p<.05) observed in masticate samples from fuels treated pastures may be partially due to differences in phenology and the associated diet quality of the grasses and forbs in those pastures. Although, grass availability leading to an increase in shrub consumption may also be associated with higher masticate CP values in the control pastures. During data collections, all observers noted a decrease in grazing activity when animals were moved from lower stocked pastures to higher stocked pastures and an increase in grazing activity when animals were moved from higher stocked pastures to lower stocked pastures. This trend coincided with an observed decline in grazing efficiency, in terms of grams consumed per minute and bites consumed per minute, as stocking rate increased in both control and treated pastures. Cattle in this study did not compensate for decreased bite size (grams per minute) with bite rate (bites per minute). Due to the methods used for collecting our data we could not account for the time spent grazing. However, in general animals will
37 attempt to compensate for reduction in bite size with either bite rate, or grazing time, rarely both (Damiran 2006). Overall, fuels reduction appeared to accelerate plant phenology. In addition, fuels reduction could lower crude protein availability for cattle grazing in late summer/early fall. On average, the diets of cattle grazing fuels treated sites contained 83% grass, 13% forbs, and 4% shrubs. We did not see an increase in shrub use due to fuels reduction. On fuels treated sites cattle generally avoided shrubs. Snowberry was the highest preferred out of the dominate shrubs consumed. Increase stocking rates had a negative effect on foraging efficiency for both fuels treated and non­treated sites. In addition, increased stocking rates increased shrub consumption especially in the non­treated sites. Fuels reduction occurs in many other plant communities and forest types. Season of use and stocking rates are variable within and across these habitat types. As a result, further research is needed to better understand the effects of fuels reduction and to develop proper stocking rates that coincide with season of use across various fuels treated stands. Literature Cited Damiran, Daalkhaijav. (2006) Influence of previous cattle and elk grazing on the subsequent diet quality and nutrient intake rate of cattle, deer, and elk grazing late­ summer mixed­conifer rangelands. Ph.D. Dissertation. Oregon State University., Corvallis. 119 p.
38 BIBLIOGRAPHY Agee, J.K. and C.N. Skinner. 2005. Basic principles of forest fuel reduction treatments. Forest Ecology and Management. 211:83­96 Augustine, D.J. and S.J. McNaughton. 1998. Ungulate effects on the functional Species composition of plant communities: Herbivore selectivity and plant tolerance. J. Wildl. Manage. 62:1165­1183 Barbour, J.R., R.D. Fight, G.A. Christensen, G.L. Pinjuv, and R.V. Nagubadi. 2004. Thinning and prescribed fire and projected trends in wood product potential, financial return, and fire hazard in Montana. USDA­ Forest Service, Pacific Northwest Region. Gen. Tech. Rep. PNW GTR­606, Portland, OR Beck, R.F. 1975. Steer diets in southeastern Colorado. Range Manage. 28:48­51 Bull, E.L., A.A. Clark, and J.F. Shepherd. 2005. Short­term effects of fuel reduction on pileated woodpeckers in northeastern Oregon—a pilot study. U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. Res. Pap. PNW­RP­564. Canon, S.K., P.J. Urness, and N.V. DeBule. 1987. Foraging behavior and dietary nutrition of elk in burned aspen forest. J. Range Manage. 40:433­438 Clark, P.E. 2003. Date and plant community effects on elk sedge forage quality. J. Range Manage. 56:21­26 Coe, P. K., B. K. Johnson, K. M. Stewart, and J. G. Kie. 2005. Spatial and temporal interactions of elk, mule deer, and cattle. March 20, 2004. Transactions of the North American Wildlife and Natural Resources Conference 69. Conard, S.G. and S.R. Radosevich. 1982. Post­fire succession in white fir (Abies concolor) vegetation of the Northern Sierra Nevada. Madrono. 29:42­56 Covington, W.W., P.Z. Fule, M.M. Moore, S.C. Hart, T.E. Kolb, J.N. Mast, S.S. Sackett, and M.R. Wagner 1997. Restoring ecosystem health in ponderosa pine forests of the Southwest. Journal of Forestry 95:23­39 Cruz, R. and D. Ganskopp. 1998. Seasonal preferences of steers for prominent northern Great Basin grasses. J. Range Manage. 51:557­565 Damiran, Daalkhaijav. (2006) Influence of previous cattle and elk grazing on the subsequent diet quality and nutrient intake rate of cattle, deer, and elk grazing late­
39 summer mixed­conifer rangelands. Ph.D. Dissertation. Oregon State University., Corvallis. 119 p. Darambazar, E., T. DelCurto, C. Ackerman, G. Pulsipher, and D. Damiran. 2003. Changes in forage quantity and quality with continued cattle grazing in a mountain riparian pasture. In: Proceedings of the West. Sec. of Amer. Soc. Anim. Sci. 54:324­328. DelCurto, T., M. Porath, C.T. Parsons, and J.A. Morrison. (2005) Management Strategies for Sustainable Beef Cattle Grazing on Forested Rangelands in the Pacific Northwest. Rangeland Ecology & Management. 58:119– 127 Fernandes, P.M., and H.S. Botelho. 2004. A review of prescribed burning effectiveness in fire hazard reduction. International Journal of Wildland Fire. 12:117­128 Findolt, S. L., D. Damiran, B. K. Johnson, T. DelCurto, and J. G. Kie. 2004. Diet overlap among elk, mule deer, and cattle. March 20, 2004. Transactions of the North American Wildlife and Natural Resources Conference 69. Ganskopp, D., T. Svejcar, F. Taylor, J. Farstvedt, and K. Painter. 1999. Seasonal cattle management in 3 to 5 year old bitterbrush stands. J. Range Manage. 52:166­173 Ganskopp, D., and D. Bohnert. 2001. Nutritional dynamics of 7 northern Great Basin grasses. J. Range Manage. 54:640­647 Guevara, J.C., C. R. Stasi and O. R. Estevez. 1996. Seasonal specific selectivity by cattle on rangeland in the Monte Desert of Mendoza, Argentina. Journal of arid environments. 34:125­132 Heady, H.F. 1964. Palatability of herbage and animal preference. J. Range Manage. 17:76­82 Heitschmidt, R. K., L.T. Vermeire, and E.E. Grings. 2004. Is rangeland agriculture sustainable? J. Anim Sci. 82:138­146 Hobbs, N.T. 1996. Modification of ecosystems by ungulates. J. Wildl. Manage. 60:695­713 Holechek, J.L. 1981. Livestock grazing impacts on public lands: a viewpoint J. Range Manage. 34:251­254 Holechek, J.L., M. Vavra, J. Skovlin, and W.C. Krueger. 1982a. Cattle diets in the Blue Mountains of Oregon. II. Forests. J. Range Manage. 35:239­242
40 Holechek, J.L., M. Vavra, and J. Skovlin. 1982b. Cattle Diet and Daily Gains on a Mountain Riparian Meadow in Northeastern Oregon. J. Range Manage. 35:745­ 747 Holecheck, J.L., and M. Vavra. 1983. Drought effects on diet and weight gains of yearling heifers in Northeastern Oregon. J. Range Manage. 36:227­231 Hong, S.E, B.Z. Shang, T.R. Crow, E.J. Gustafson, and S.R. Shifley. 2004. Simulating forest fuel and fire risk dynamics across landscapes—LANDIS fuel module design. Ecological Modelling. 180:135­151 Jensen, C.H., A.D., Smith and G.W. Scotter. 1972. Guidelines for grazing sheep on rangelands used by big game in winter. J. Range Manage. 25: 346­352 Johnson, C.G. 1998. Vegetation Response after wildfires in National Forests of Northeastern Oregon. USDA­ Forest Service, Pacific Northwest Region. R6­NR­ ECOL­TP­06­98. Kerry L.M., and C.E. Fiedler. 2006. Restoration treatment effects on the understory of ponderosa pine/Douglas­fir forests in western Montana, USA. Foresst Ecology and Management 222:355­369 Kosco, B.H., and J.W. Bartolome. 1985. Forest grazing: past and future. J. Range Manage. 34:248­251 Kothmann, M.M. (1992). Nutrition for livestock grazing rangelands and pasturelands. In: Howard, J.L. (Ed.), Current Veterinary Therapy 3: Food Animal Practice, pp. 285–293 Krueger, J.K., and D.J., Bedunah. 1988 Influence of forest site on total nonstructural carbohydrate levels of pinegrass, elk sedge, and snowberry. J. Range Manage. 41:144­149 Long, R.A., J.L. Rachlow, J.G. Kie and M. Vavra. (in review). Fuels reduction in a western coniferous forest: Effects on quantity and quality of forage for elk. McConnell B.R. and J.G. Smith. 1970. Response of understory vegetation to Pinus ponderosa thinning in eastern Washington, J. Range Manage. 23:208–212 Miller, R.F., and W.C. Krueger. 1976. Cattle use on summer foothill rangelands in northeastern Oregon. J. Range Manage. 29:367­371 Mitchell, F.J.G. and K.J., Kirby. 1990. The impact of large herbivores on the conservation of semi­natural woods in the British uplands. Forestry. 63: 333­353
41 Mitchell, G.E. 1951. Status of browse on ranges of eastern Oregon and eastern Washington. J. Range Manage. 4:249­253 Mitchell, J.E., and R.T., Rodgers. 1985. Food habits and distribution of cattle on a forest and pasture range in northern Idaho. J. Range Manage. 38:214­220 National Research Council, NRCS. 1996. Nutrient Requirements of Cattle. National Academy Press. Page 227. Parsons, A.J., J.A. Newman, P.D. Penning, A. Harvey and R.J. Orr. 1994. Diet preference of sheep: effects of recent diet, physiological state and species abundance, J. Anim. Ecol. 63 (1994), pp. 465–478. Parsons, C.T., P.A. Momont, T. DelCurto, M. McInnis, and M.L. Porath. 2003. Cattle distribution patterns and vegetation use in mountain riparian areas. J. Range Manage. 56:334­341 Perez Corona, M.E., B.R. Vazquez de Aldana, B. Garcia Criado, and A Garcia Ciudad. 1998. Variations in nutritional quality and biomass production of semiarid grasslands. J. Range Manage. 51:570­576 Provenza, F. D., J.J. Villalba, J. Haskell, J.W. MacAdam, T.C. Griggs, and R.D. Wiedmeier, 2007. The Value to Herbivores of Plant Physical and Chemical Diversity in Time and Space. Crop Science 47: 382­398 Skovlin, J.M. 1967. Fluctuations in forage quality on summer range in the Blue Mountains. Pacific Northwest Forest and Range Exp. Sta., USDA, Pacific Northwest 44. Steel, R.G., and J.H. Torrie. 1960 Principles and procedures of statistics. McGraw­Hill Book Co., INC. New York. Stephens, S.L., and J.J. Moghaddas. 2005. Experimental fuel treatment impacts on forest structure, potential fire behavior, and predicted tree mortality in a California mixed conifer forest. Forest Ecology and Management. 215:21­36 Svejcar, T., and M. Vavra. 1985. The influence of several range improvements on estimated carrying capacity and potential beef production. J. Range Manage. 38:395­399 Tiedemann, A.R., J.O. Klemmedson, and E.L. Bull. 2000. Solution of forest health problems with prescribed fire: are forest productivity and wildlife at risk? Forest Ecology and Management. 127:1­18 Riggs, R. A., A. R. Tiedemann, J. G. Cook, T. M. Ballard, P. J. Edgerton, M. Vavra, W. C. Krueger, F. C. Hall, L. D. Bryant, L. L. Irwin, and T. DelCurto.
42 2000. Modification of mixed­conifer forests by ruminant herbivores in the Blue Mountains Ecological Province. USDA­ Forest Service, Pacific Northwest Region. Research Paper PNW­RP­527. LaGrande, OR. Riggs, R. A., J. G. Cook, and L. L. Irwin. 2004. Management Implications of Ungulate Herbivory in Northwest Forest Ecosystems. Transactions of the North American Wildlife and Natural Resource Conference 69: in press. Rosiere, R.E., R.F. Beck, and J.D. Wallace. 1975. Cattle diets on semidesert grassland: botanical composition. J. Range Manage. 28:89­93 Rouse, C. 1986. Fire effects on Northeastern forests: Aspen. USDA­ Forest Service, North Central Forest Experiment Station, General Technical Report NC ­102 Vavra, M., M. J. Wisdom, J. G. Kie, J. G. Cook, and R. A. Riggs. 2004. The Role of Ungulate Herbivory and Management Ecosystem Patterns and Processes: Future Direction of the Starkey Project. Transactions of the North American Wildlife and Natural Resource Conference 69: in press. Walburger, K. J., M. Wells, M. Vavra, T. DelCurto, B. Johnson, and P. Coe. 2007. Influence of Cow Age on Grazing Distribution in a Mixed Conifer Forest. J. Range Ecol. Manage. (In press). Walburger, K.J., T. DelCurto, and M. Vavra. 2007. Influence of forest management and previous herbivory on cattle diets. Rangeland Ecology & Manage. 60:172­178 Walker, J.W. 1995. Viewpoint: grazing management and research now and in the next millennium. J. Range Manage. 48:350­357 Wickstrom, M.L., C.T. Robbins, T.A. Hanley, D.E. Spalinger, and S.M. Parish. 1984. Food intakes and foraging energetic of elk and mule deer. J. Wildl. Manage. 48:1285­1301 Willms, W., A. McLean, R. Tucker, and R. Ritcey. 1980. Deer and cattle diets on summer range in British Columbia. J. Range Manage. 33:55­59 Wuerthner, G. 1990. The Price is wrong. Sierra. 25:38­48
43 APPENDICES
44 Table A.2.1. Diet quality of cattle masticate samples at Starkey(2005,06). Block Treatment CP NDF ADF IVDMD 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 2 2 2 2 2 2 1 1 1 1 1 1 6 6 6 6 6 6 5 5 5 5 5 5 4 4 4 4 4 4 3 3 3 3 3 3 2 2 2 2 2 2 1 8.2 8.5 8.1 7.7 7.7 8.1 7.8 9.0 8.0 8.8 7.7 8.7 6.9 6.6 7.7 7.1 8.1 8.0 9.1 9.1 9.3 8.2 9.6 10.8 8.3 8.9 10.7 8.2 11.5 11.8 10.0 11.0 9.9 9.3 10.0 12.0 9.5 6.9 8.9 6.3 7.3 8.3 11.7 7.5 8.7 6.7 7.9 8.7 9.7 68.3 61.1 68.3 66.8 67.9 69.4 62.5 64.6 64.6 65.1 71.6 68.1 68.3 66.7 67.9 65.1 68.0 68.1 67.9 66.8 66.5 65.1 67.3 63.3 70.9 66.1 69.9 64.6 69.7 60.7 68.7 68.9 69.5 65.9 69.3 62.8 61.1 66.0 64.8 66.1 66.1 64.2 61.8 68.3 67.3 67.8 67.5 69.3 66.9 42.1 39.0 42.6 42.0 40.8 42.6 38.5 39.7 42.8 41.1 43.7 43.1 41.2 41.0 44.7 40.9 39.2 43.6 45.3 46.2 46.7 47.1 45.2 44.2 46.1 44.3 50.0 43.0 45.0 44.2 43.6 44.9 49.0 41.6 47.7 43.6 41.4 42.4 43.1 39.3 40.9 40.3 42.0 44.6 44.0 43.4 40.7 41.7 45.6 64.8 71.0 66.3 70.5 68.7 65.3 68.5 69.1 64.3 63.0 64.0 63.0 66.5 64.1 63.9 66.0 66.7 67.2 62.3 64.1 61.3 63.8 59.7 60.0 59.3 62.3 56.0 60.4 53.9 63.7 57.2 60.1 54.9 60.4 55.9 55.8 68.7 66.1 63.5 65.5 64.9 63.5 64.8 64.6 66.9 65.0 63.2 61.9 63.9
45 Table A.2.1. (continued) Block Treatment CP 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 1 1 1 1 1 6 6 6 6 6 6 5 5 5 5 5 5 4 4 4 4 4 4 3 3 3 3 3 3 2 2 2 2 2 1 1 1 1 1 1 6 6 6 6 6 5 5 6.7 9.9 6.1 6.9 8.7 8.0 7.7 8.0 8.7 8.3 8.0 7.6 10.6 8.1 8.5 9.4 7.1 7.9 7.1 7.6 6.6 7.3 8.4 8.0 8.6 8.2 7.9 10.1 9.4 8.2 9.3 8.9 9.8 10.0 8.5 9.6 8.9 8.9 10.7 9.2 9.0 9.4 9.5 10.5 10.0 9.3 8.0 NDF ADF IVDMD 68.7 68.4 67.6 68.1 72.1 67.2 71.4 69.4 68.0 71.2 66.8 67.1 63.7 67.6 64.1 66.4 67.0 68.5 71.5 64.8 71.8 72.7 65.2 70.5 64.8 64.8 66.6 62.9 68.5 70.0 59.6 65.2 65.0 65.0 65.4 67.4 69.3 66.5 66.4 63.9 67.9 69.0 65.6 67.7 69.0 69.3 72.4 42.0 44.4 40.1 40.9 44.1 44.1 44.3 45.3 41.7 43.3 45.4 43.1 40.4 44.0 40.9 43.8 40.7 43.1 43.4 41.5 44.4 43.7 40.7 48.0 43.0 45.0 45.8 44.3 47.7 49.1 43.3 46.3 45.2 47.6 46.9 45.6 48.4 45.2 47.3 43.3 41.7 42.2 41.0 43.5 42.6 42.6 47.3 65.5 58.4 63.2 62.7 54.9 64.9 66.0 62.4 67.3 66.0 59.5 72.8 64.4 68.0 67.7 71.1 66.5 65.3 62.5 65.5 58.4 61.9 63.2 69.5 60.7 61.6 56.1 66.9 68.1 66.2 76.7 68.2 68.3 68.6 69.9 64.0 64.3 70.9 60.5 69.1 68.5 61.0 63.2 70.1 61.5 61.8 65.8
46 Table A.2.1. (continued) Block Treatment CP 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 4 4 4 4 4 4 3 3 3 3 3 3 2 2 2 2 2 2 1 1 1 1 1 1 6 6 6 6 6 6 5 5 5 5 5 5 4 4 4 4 4 7.7 11.6 12.0 8.2 10.2 10.0 11.4 11.3 8.7 9.7 8.2 8.7 10.7 10.2 8.9 9.4 8.2 9.0 9.9 9.3 8.5 8.3 8.3 8.7 9.2 8.7 9.2 9.4 10.5 10.8 9.8 9.9 10.1 9.9 8.3 9.6 10.3 8.4 8.8 10.0 10.6 11.6 9.6 12.4 NDF ADF IVDMD 69.0 67.7 63.3 67.6 72.5 75.5 68.4 71.3 65.8 72.3 72.9 66.3 71.4 73.2 62.6 67.0 71.0 68.5 66.2 69.8 68.2 69.8 70.7 64.4 65.5 60.8 66.1 66.4 63.8 66.2 62.0 62.8 63.5 60.0 64.2 67.0 63.4 69.0 68.5 69.0 72.0 74.4 66.2 69.1 43.5 40.5 36.7 39.3 43.3 46.7 42.0 42.7 41.3 39.1 40.7 39.4 44.1 43.3 39.1 39.3 41.8 41.1 40.1 41.9 39.8 47.4 40.1 38.1 44.9 41.2 38.0 36.8 37.3 38.6 40.8 37.8 36.8 39.0 38.1 46.7 37.2 41.3 41.8 40.6 45.6 44.4 40.3 42.7 63.9 65.9 66.9 64.7 54.3 59.7 58.2 62.9 62.7 66.6 65.0 65.9 61.7 59.6 67.6 69.0 66.7 63.0 65.2 67.0 60.4 70.9 66.1 67.9 69.7 62.0 65.9 63.5 64.8 67.2 69.4 66.6 64.1 60.6 70.3 45.6 64.2 53.0 54.9 61.8 56.8 42.0 60.7 54.1 Block: 1­Bally camp 05; 2­louis springs 05; 3­bally camp 06; 4­louis springs 06 Treatment: 1­treated high stocking; 2­treated mod stocking; 3­treated low stocking 4­control high stocking; 5­contol mod stocking; 6­control low stocking
47 Table A.2.2. Diet Quality of hand plucked forages by species at Starkey(2005,06) Treatment Forage Species CP NDF ADF IVDMD % Moisture Treated Treated Treated Treated Treated Treated Treated Treated Treated Treated Treated Treated Treated Treated Treated Control Control Control Control Control Control Control Control Control Control Control Control Control Control Control Control Control Control 1 1 1 1 1 2 2 2 2 2 2 2 3 3 3 1 1 1 1 2 2 2 2 2 2 2 2 2 3 3 3 3 3 Acmil Epcig Lupo2 Trdu Trre Brma Cage Caru Feoc Phpr Popr Trca Rogy Spbe Syal Loco Lupo2 Trre Urgr Brma Cage Caru Dagl Feid Feoc Phpr Popr Trca Libo2 Rogy Spbe Syal Vasc 6.6 6.5 10.9 4.8 11.5 4.1 5.7 6.9 3.6 3.9 5.7 4.7 9.1 8.4 9.0 15.4 10.6 14.5 10.7 8.8 6.4 9.4 5.5 6.6 4.0 4.7 7.0 6.2 7.5 8.6 8.0 9.2 8.6 45.5 55.1 36.8 50.4 47.5 72.9 65.6 59.6 79.7 65.8 64.8 73.9 30.3 32.2 26.5 30.6 30.5 40.5 38.8 60.4 65.3 60.3 66.2 65.9 71.3 65.1 64.4 65.4 37.5 37.1 37.2 26.3 45.0 33.8 43.2 25.2 36.7 35.9 44.4 36.7 35.0 48.6 36.3 36.6 45.6 15.2 19.3 16.9 21.7 21.4 28.8 24.8 34.1 35.7 33.4 41.1 36.1 41.2 37.0 36.0 39.5 27.8 18.1 22.8 17.7 33.2 68.9 53.9 75.4 62.3 65.9 51.8 63.3 61.5 36.0 56.4 61.8 51.9 79.9 81.0 82.8 77.1 84.6 74.8 81.1 68.0 62.9 66.3 52.2 57.5 49.9 54.3 59.5 56.1 72.5 82.6 72.5 81.3 68.0 9.7 47.8 13.9 52.3 38.3 16.0 29.4 23.0 7.8 24.5 21.8 15.0 22.7 22.2 39.7 67.7 47.3 48.7 66.1 53.1 31.3 49.1 51.0 28.1 6.7 44.4 36.6 26.2 54.5 22.2 12.0 28.1 48.5 Forage: 1­Forb; 2­Grass; 3­Shrub Species: alpha code follows the recommendations of the USDA Natural Resource Conservation Service (USDA, NRCS 2005)
48 Table A.2.3. Percent diet composition by forage class of cattle at Starkey(2005,06) Block Treatment % Grass % Shrubs % Forbs 1 4 78.5 5.8 15.7 1 4 90.3 4.0 5.7 1 4 89.6 5.0 5.4 1 4 92.7 0.0 7.3 1 4 82.9 2.4 13.3 1 3 61.0 26.3 11.4 1 3 89.0 3.9 6.6 1 3 79.7 11.1 9.2 1 3 97.4 1.3 1.3 1 3 89.1 7.6 3.4 1 3 92.3 3.2 4.5 1 2 95.4 1.1 3.5 1 2 81.0 5.4 12.3 1 2 93.6 1.8 4.5 1 2 93.0 1.0 6.0 1 2 74.0 0.0 26.0 1 2 87.9 1.5 10.6 1 8 23.0 37.8 39.2 1 8 13.0 50.0 33.3 1 8 59.7 25.4 0.0 1 8 37.4 48.5 5.1 1 8 33.0 36.9 3.9 1 7 68.0 28.4 3.6 1 7 58.9 7.5 31.8 1 7 53.2 21.1 25.7 1 7 91.0 4.0 5.0 1 7 36.5 2.0 61.1 1 6 54.4 2.6 43.1 1 6 45.2 0.3 54.5 1 6 23.8 2.9 73.3 1 6 78.9 1.1 20.0 1 6 48.3 0.0 51.7 1 6 15.5 9.5 75.0 2 4 98.3 0.0 1.7 2 4 98.8 0.0 1.2 2 4 94.8 3.2 1.9 2 4 65.7 0.0 34.3 2 4 73.2 8.5 18.3 2 4 97.6 1.2 1.2 2 3 91.7 1.0 7.3
49 Table A.2.3. (continued) Block Treatment % Grass % Shrubs % Forbs 2 3 84.3 2.3 13.4 2 3 65.3 0.8 34.0 2 3 88.7 2.6 8.7 2 3 85.3 0.0 14.7 2 2 97.7 1.4 0.5 2 2 87.3 0.6 10.9 2 2 92.8 3.1 3.6 2 2 63.2 4.8 32.0 2 2 72.0 0.0 28.0 2 2 84.8 0.5 14.8 2 8 93.2 1.9 4.9 2 8 92.7 0.7 6.5 2 8 93.9 2.4 3.7 2 8 76.1 1.1 22.7 2 8 76.8 0.0 23.2 2 7 77.1 0.4 22.5 2 7 81.8 4.1 14.0 2 7 95.9 1.3 2.8 2 7 88.2 1.2 10.2 2 7 85.8 1.3 12.8 2 7 96.7 0.0 3.3 2 6 95.6 1.1 3.3 2 6 85.6 0.8 13.6 2 6 99.2 0.8 0.0 2 6 55.6 1.2 43.1 2 6 47.8 0.0 52.2 2 6 40.8 1.7 57.5 3 4 73.0 4.7 22.3 3 4 72.3 3.6 24.1 3 4 34.6 53.8 11.5 3 4 84.7 12.2 3.1 3 4 87.3 4.4 8.3 3 4 67.5 4.0 28.5 3 3 87.8 2.8 9.4 3 3 87.0 6.8 6.1 3 3 79.7 2.5 17.8 3 3 52.7 6.2 41.1 3 3 60.7 7.0 32.2 3 3 93.2 0.0 6.8 3 2 95.4 0.0 4.6
50 Table A.2.3. (continued) Block Treatment % Grass % Shrubs % Forbs 3 2 94.2 0.8 5.0 3 2 97.6 0.3 2.0 3 2 73.7 6.2 20.1 3 2 95.5 0.6 3.8 3 2 97.4 0.0 2.6 3 8 58.9 21.9 19.2 3 8 18.3 67.3 14.4 3 8 53.6 44.2 2.2 3 8 81.5 11.1 7.4 3 8 24.1 55.6 20.4 3 7 65.0 2.5 32.5 3 7 48.7 25.0 26.3 3 7 96.9 2.9 0.2 3 7 83.8 10.8 5.4 3 7 94.5 3.4 2.1 3 6 83.9 10.2 5.9 3 6 93.7 0.3 6.0 3 6 93.8 2.9 3.3 3 6 96.2 1.3 2.6 3 6 96.8 0.8 2.5 3 6 92.8 5.9 1.3 4 4 78.7 0.0 21.3 4 4 91.8 5.2 3.0 4 4 76.0 0.0 24.0 4 4 73.9 3.9 22.2 4 3 95.1 4.9 0.0 4 3 85.9 0.4 13.7 4 3 90.5 8.6 0.9 4 3 92.5 0.0 7.5 4 2 91.9 1.6 6.5 4 2 58.5 10.6 30.9 4 2 99.5 0.0 0.5 4 8 86.2 0.0 13.8 4 8 6.5 3.2 90.3 4 8 80.0 13.3 6.7 4 8 64.0 36.0 0.0 4 7 96.3 0.0 3.7 4 7 94.7 0.0 5.3 4 7 79.3 9.3 11.4 4 7 100.0 0.0 0.0
51 Table A.2.3. (continued) Block Treatment % Grass % Shrubs % Forbs 4 7 97.2 0.0 2.8 4 6 93.4 1.2 5.4 4 6 88.5 7.7 3.8 4 6 92.4 2.3 5.3 4 6 79.2 13.1 7.7 4 6 84.5 15.5 0.0 4 6 92.8 0.0 7.2 2 1 87.6 6.0 6.4 2 1 84.4 1.9 13.6 2 1 92.3 0.0 7.7 2 1 86.1 0.0 13.9 2 1 37.7 0.0 62.3 2 1 29.2 0.8 70.1 2 5 81.1 0.0 18.9 2 5 50.0 0.0 50.0 2 5 91.1 0.0 8.9 2 5 93.1 0.0 6.9 2 5 17.5 1.6 80.9 2 5 32.8 26.6 40.7 1 1 80.1 9.4 10.5 1 1 70.1 0.0 29.9 1 1 91.2 0.9 7.9 1 1 92.8 6.7 0.5 1 1 91.7 1.0 7.3 1 1 95.4 0.8 3.8 1 5 35.8 44.2 20.0 1 5 21.9 34.4 43.8 1 5 32.5 9.3 58.1 1 5 21.0 9.8 69.2 1 5 79.9 2.2 17.9 1 5 47.5 5.9 46.5 4 1 98.7 0.0 1.3 4 1 88.6 0.0 11.4 4 1 82.5 0.0 17.5 4 1 91.8 0.0 8.2 4 1 65.4 3.8 30.8 4 1 86.5 1.2 12.3 4 5 52.6 0.0 47.4 4 5 90.9 0.0 9.1 4 5 96.3 0.0 3.7
52 Table A.2.3. (continued) Block Treatment % Grass % Shrubs % Forbs 4 5 98.7 0.0 1.3 4 5 98.5 1.1 0.4 4 5 98.0 0.0 2.0 3 1 98.9 0.0 1.1 3 1 91.4 5.0 3.2 3 1 69.0 10.9 20.1 3 1 79.6 11.8 8.7 3 1 97.8 0.7 1.4 3 1 79.5 1.9 18.5 3 5 93.0 3.8 3.3 3 5 94.5 1.8 3.7 3 5 76.2 0.0 23.8 3 5 77.8 6.3 16.0 3 5 74.8 0.0 25.2 3 5 96.5 0.0 3.5 Block: 1­Bally camp 05; 2­louis springs 05; 3­bally camp 06; 4­louis springs 06 Treatment: 1­treated 0% stocking; 2­treated low stocking; 3­treated mod stocking 4­treated high stocking; 5­contol 0% stocking; 6­control low stocking 7­control mod stocking; 8­control high stocking
53 Table A.2.4. Grams consumed per minute of cattle at Starkey(2005,06) Block Treatment gm / min 1 3 7.4 1 3 21.95 1 3 25.65 1 3 18.2 1 3 10.5 1 3 20 1 2 15.9 1 2 13.1 1 2 16.35 1 2 7.2 1 2 6.4 1 2 10.9 1 1 11.7 1 1 12.7 1 1 15.5 1 1 9.95 1 1 2 1 1 6.3 1 6 21.1 1 6 9.7 1 6 10.5 1 6 11.15 1 6 7.65 1 6 13 1 5 9.5 1 5 3.15 1 5 19 1 5 3.4 1 5 5 1 4 4.8 1 4 3.35 1 4 10.15 1 4 3.5 1 4 8.45 1 4 5.05 2 3 11.7 2 3 10.1 2 3 4.65 2 3 10.7
54 Table A.2.4. (continued) Block Treatment gm / min 2 3 4.2 2 3 15.7 2 2 10.1 2 2 7.7 2 2 10.25 2 2 9 2 2 6.25 2 1 5.4 2 1 7.15 2 1 2.4 2 1 8.2 2 1 5.1 2 1 2.45 2 6 16.05 2 6 13.1 2 6 24.55 2 6 15 2 6 11.8 2 6 11.85 2 5 16.05 2 5 7.15 2 5 21.35 2 5 14.05 2 5 17 2 5 24.35 2 4 9.9 2 4 4.7 2 4 7.95 2 4 7.45 2 4 5.55 3 3 22.825 3 3 28.375 3 3 26.475 3 3 20.075 3 3 18.775 3 3 18.825 3 2 21.425 3 2 17.175 3 2 13.225
55 Table A.2.4. (continued) Block Treatment gm / min 3 2 15.225 3 2 7.275 3 2 9.625 3 1 11.475 3 1 12.775 3 1 9.425 3 1 7.675 3 1 4.575 3 1 11.425 3 6 31.375 3 6 19.625 3 6 14.625 3 6 22.025 3 6 2.925 3 6 14.675 3 5 19.275 3 5 11.425 3 5 4.675 3 5 4.625 3 5 5.525 3 4 6.925 3 4 2.975 3 4 6.875 3 4 9.425 3 4 1.475 4 3 7.175 4 3 5.475 4 3 10.225 4 2 4.825 4 2 13.875 4 2 11.125 4 2 2.775 4 1 9.375 4 1 9.925 4 1 11.575 4 1 9.975 4 6 12.175 4 6 8.875 4 6 8.175
56 Table A.2.4. (continued) Block Treatment gm / min 4 6 9.975 4 6 2.475 4 6 6.075 4 5 18.475 4 5 10.775 4 5 6.875 4 5 1.575 4 5 15.425 4 4 3.325 4 4 2.525 4 4 0.775 Block: 1­Bally camp 05; 2­louis springs 05; 3­bally camp 06; 4­louis springs 06 Treatment: 1­treated high stocking; 2­treated mod stocking; 3­treated low stocking 4­control high stocking; 5­contol mod stocking; 6­control low stocking
57 Table A.2.5. Bites consumed per minute of cattle at Starkey(2005,06) Block Treatment Bites/Min 1 2 5.5 1 2 15.8 1 2 15.55 1 2 14.25 1 2 9.95 1 2 13.2 1 3 11.8 1 3 9.05 1 3 11.9 1 3 7.65 1 3 7.75 1 3 7.8 1 4 11.1 1 4 14.9 1 4 10.5 1 4 9.55 1 4 1.45 1 4 2.05 1 6 25.2 1 6 17.35 1 6 10.35 1 6 17.05 1 6 4.5 1 6 7.4 1 7 13.9 1 7 5.35 1 7 20.3 1 7 5.45 1 7 9.95 1 8 3.7 1 8 2.7 1 8 10.15 1 8 0.95 1 8 9.05 1 8 4.95 2 2 6.25 2 2 10.85 2 2 7.5 2 2 9.7
58 Table A.2.5. (continued) Block Treatment Bites/Min 2 2 8.25 2 2 21.35 2 3 13.1 2 3 13.25 2 3 10.8 2 3 10.25 2 3 7.15 2 4 3.35 2 4 7.75 2 4 3.55 2 4 8.1 2 4 5.8 2 4 4.25 2 6 17.9 2 6 17.75 2 6 24.35 2 6 6.25 2 6 22.85 2 6 12.45 2 7 10.7 2 7 6.05 2 7 18.7 2 7 12.9 2 7 16 2 7 12.25 2 8 18.85 2 8 4.4 2 8 13.75 2 8 20.55 2 8 4.75 3 2 14.8 3 2 27.05 3 2 18.95 3 2 17.55 3 2 21.1 3 2 15.65 3 3 14.65 3 3 16.9 3 3 9.85
59 Table A.2.5. (continued) Block Treatment Bites/Min 3 3 14.35 3 3 6.45 3 3 12.1 3 4 4.9 3 4 10.2 3 4 7.4 3 4 4.15 3 4 9.1 3 4 7.55 3 6 19.5 3 6 26.2 3 6 12 3 6 15.95 3 6 12.75 3 6 11.8 3 7 24.15 3 7 19 3 7 5.55 3 7 6 3 7 7.8 3 8 4.05 3 8 6.9 3 8 3.65 3 8 5.2 3 8 2.7 4 2 6.2 4 2 9.15 4 2 10.85 4 3 5.8 4 3 11.35 4 3 13.25 4 3 4.05 4 4 11.55 4 4 8.55 4 4 22.05 4 4 7.5 4 6 6.6 4 6 12.05 4 6 6.5
60 Table A.2.5. (continued) Block Treatment Bites/Min 4 6 8.4 4 6 6.5 4 6 6.95 4 7 17.6 4 7 7 4 7 5.35 4 7 4.7 4 7 11.3 4 8 1.5 4 8 2.9 4 8 1.55 4 8 1.25 2 1 21 2 1 12.85 2 1 3.25 2 1 1.8 2 1 6.9 2 1 19.7 2 5 14.8 2 5 5.1 2 5 24.8 2 5 21.6 2 5 22 2 5 14.5 1 1 9.55 1 1 9.7 1 1 11.4 1 1 10.4 1 1 15.05 1 1 11.95 1 5 6 1 5 4.8 1 5 12.3 1 5 7.15 1 5 18.45 1 5 10.1 4 1 11.25 4 1 13.25 4 1 1.65
61 Table A.2.5. (continued) Block Treatment Bites/Min 4 1 2.8 4 1 1.7 4 1 10.9 4 5 6.15 4 5 22.85 4 5 28.45 4 5 14.95 4 5 12.85 4 5 12.1 3 1 31.65 3 1 21.2 3 1 6.35 3 1 16.55 3 1 27.05 3 1 12.25 3 5 9.9 3 5 7.75 3 5 15.5 3 5 5.6 3 5 13.95 3 5 8.35 Block: 1­Bally camp 05; 2­louis springs 05; 3­bally camp 06; 4­louis springs 06 Treatment: 1­treated 0% stocking; 2­treated low stocking; 3­treated mod stocking 4­treated high stocking; 5­contol 0% stocking; 6­control low stocking 7­control mod stocking; 8­control high stocking
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