IN F O R M A T IO N TO U S E R S T h e m o s t a d va n ce d te c h n o lo g y has been u se d to p h o to ­ g ra p h a n d rep rod uce th is m a n u s c rip t fro m th e m ic r o film m aste r. U M I f ilm s th e t e x t d ir e c t ly fr o m th e o r ig in a l o r copy s u b m itte d . T h u s , some th e s is a n d d is s e rta tio n copies are in ty p e w r ite r face, w h ile o th e rs m a y be fro m a n y ty p e o f c o m p u te r p rin te r. T h e q u a lit y o f t h is re p r o d u c tio n is d e p e n d e n t u p o n th e q u a lity o f th e copy s u b m itte d . B ro k e n o r in d is tin c t p r in t , colore d o r p o o r q u a lit y illu s t r a t io n s a n d p h o to g ra p h s , p r in t b le e d th ro u g h , s u b s ta n d a rd m a rg in s , a n d im p ro p e r a lig n m e n t can a d v e rs e ly a ffe ct re p ro d u c tio n . I n th e u n lik e ly e ve n t th a t th e a u th o r d id n o t send U M I a com plete m a n u s c rip t a n d th e re are m is s in g pages, these w i l l be n o te d . A ls o , i f u n a u th o riz e d c o p y r ig h t m a t e r ia l had to be rem oved, a n o te w i l l in d ic a te th e d e le tio n . O versize m a te ria ls (e.g., m aps, d ra w in g s , c h a rts ) a re re ­ p ro d u ce d b y s e c tio n in g th e o r ig in a l, b e g in n in g a t th e u p p e r le ft-h a n d c o rn e r a n d c o n tin u in g fro m le ft to r ig h t in eq ua l sections w it h s m a ll overlaps. E ach o r ig in a l is also photographed in one exposure an d is in c lu d e d in reduced fo rm a t th e back o f th e book. These are also a v a ila b le as one exposure on a s ta n d a rd 3 5 m m slid e o r as a 17" x 23" b la c k a n d w h it e p h o to g r a p h ic p r i n t f o r a n a d d it io n a l charge. P h o to g ra p h s in c lu d e d in th e o r ig in a l m a n u s c r ip t have been re p ro d u c e d x e r o g r a p h ic a lly in t h is copy. H ig h e r q u a lit y 6" x 9" b la c k a n d w h ite p h o to g ra p h ic p r in t s a re a va ila b le fo r a n y p h o to g ra p h s o r illu s tr a tio n s a p p e a rin g in th is copy fo r a n a d d itio n a l charge. C o n ta c t U M I d ir e c tly to order. University Microfilms International A Bell & Howell Information C om pany 300 North Zeeb Road, Ann Arbor, Ml 48106-1346 USA 313/761-4700 800/521-0600 O rder N u m b er 9011 9 6 8 Effects o f deer and elk brow sing on aspen regeneration and nu tritional qualities in M ichigan Campa, Henry, III, Ph.D. Michigan State University, 1989 UMI 300 N. Zeeb Rd. Ann Arbor, M I 48106 EFFECTS OF DEER AND ELK BROWSING ON ASPEN REGENERATION AND NUTRITIONAL QUALITIES IN MICHIGAN By Henry Campa, III A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Fisheries and Wildlife 1989 ABSTRACT EFFECTS OF DEER AND ELK BROWSING ON ASPEN REGENERATION AND NUTRITIONAL QUALITIES IN MICHIGAN By Henry Campa, III The Pigeon River Country State Forest (PRCSF) and surrounding lands in Michigan are managed for multiple use benefits. Two primary objectives are the production of timber products and supply of wildlife recreational opportunities. White-tailed deer (Odocoileus virqinianus) and especially elk (Cervus elaphus canadensis) have been exerting increased foraging pressure on vegetation in recent years. Concern exists that browsing may be restricting aspen (Populus spp.) regeneration. This study was initiated to determine the extent and severity of the problem, and to suggest management alternatives. Aspen clearcuts 1-6 growing seasons old were sampled for browse utilization from 1983-1986. Effects of various intensities of ungulate browsing on aspen stand charac­ teristics and nutritional qualities were studied with simulated browsing experiments. Replicated exclosures were constructed on bigtooth (P. grandidentata) and quaking aspen (P. tremuloides) clearcuts during their first growing season. The area within exclosures was separated into treatment plots by severing aspen root systems. The effects of 5 browsing intensities and 3 schedules were investigated. Ungulate effects on vegetation composition and structure were determined with replicated exclosures. Eighteen exclosures were constructed in stands of bigtooth and quaking aspen of 3 post-clearcut age classes. Areas of similar composition and structure open to ungulate browsing were also delineated in each clearcut. Stem densities, frequencies of herbaceous species, and vegetative cover were sampled. Results indicate ungulates browsed bigtooth aspen significantly more than quaking aspen. Utilization of both species significantly declined with age after harvesting. The selective browsing pressure on bigtooth aspen may be explained by the chemical constituent values obtained from simulated browsing samples. Bigtooth aspen twigs had significantly more crude protein than quaking aspen and less ether extract. Compounds within the ether extract constituent may have inhibited quaking aspen utilization. Stem densities were not impaired by the intensities of simulated browsing applied. Tree height, number of twigs available, and amount of woody annual productivity was impaired with simulated browsing, primarily at intensities > 50%. Current browsing pressures on bigtooth aspen, of some age classes, exceeded the intensity in which stand characteristics and nutritional qualities were altered with simulated browsing. Current browsing intensities indicate ungulates are affecting plant composition and structure by decreasing stem densities and cover and increasing the frequencies of some herbaceous species. Despite these significant results, no effects on timber production can be identified to date. Effects on habitat quality for other wildlife species would appear to be occurring. Management solutions to heavy browsing pressure on aspen shoots involve both silvicultural methods and herd manipulations. ACKNOWLEDGEMENTS This project was supported by the Federal Aid in Wildlife Restoration Act under Pittman-Robertson project W127-R and the Michigan Agricultural Experiment Station. I would like to thank Dr. Jonathan Haufler for serving as my major advisor, and for his guidance, friendship, and patience. Appreciation is also extended to Dr. Duane Ullrey, Dr. Kurt Pregitzer, Dr. Peter Murphy, and Mr. Carl Bennett, Jr. for serving as graduate committee members and for their helpful suggestions in completing this project. I would also like to thank Dean Beyer, Tod Herblet, Jim Brown, Dave Luukkonen, Scott Decker, Scott Laudenslager, and Tim Bills for their assistance with field work. Assistance with chemical analyses was provided by Dr. Phu Nguyen, Ed Olexa, Gina Ballard, and Nina Chambers. Their help was very much appreciated. Thanks are also extended to the personnel at the Pigeon River Country State Forest: Rita Rennie. Ned Caveney, Arch Reeves, and Their assistance and support was very much appreciated. I would also like to thank fellow graduate students and friends Tom Kulowiec (Holechek), Brian Gray, Carolyn Mehl, Paul Padding, Laura Grantham, Jim Ruhl, and Larry Gigliotti for making graduate school a memorable and stimulating experience. ii Special thanks are due to Dean Beyer and Dave Woodyard who are not only good friends but were also roommates, office mates, and critical consultants. Our arguments, discussions, and interactions I'm sure have made me a better biologist. To my parents, Henry Campa, Jr. and Jeanette Campa, this dissertation is dedicated to you. You have given me alot over the years and I thank you for everything. Finally, I would like to thank my wife, Sue, for her assistance in the field, patience, support, and love while conducting this study. iii TABLE OF CONTENTS Pacre LIST OF TABLES.............................. V LIST OF FIGURES...................... xii INTRODUCTION..................... ............ 1 STUDY AREA DESCRIPTION. . ........ ................... 6 BROWSE UTILIZATION OF ASPEN CLEARCUTS BY WHITE-TAILED DEER AND ELK ........... Introduction...................................... Methods........................................... Experimental Design............................ Clearcut Measurements.......................... ..... Data Analyses Results and Discussion. ............ 12 12 16 16 16 17 19 EFFECTS OF SIMULATED BROWSING ON ASPEN MORPHOLOGY, ANNUAL PRODUCTIVITY, AND CHEMICAL CONSTITUENTS ........ Introduction. .............. Methods ........ Experimental Design...................... ... Sample Collection and Measurements....... . Nutritional Analyses. ..... Data Analyses.................................. Results and Discussion. ............ ..... Stand Characteristics Nutritional Analyses. ...... 28 28 30 30 30 32 34 35 35 44 EFFECTS OF DEER AND ELK BROWSING ON THE COMPOSITION AND STRUCTURE OF REGENERATING ASPEN FOLLOWING CLEARCUTTING.......... Introduction ........................... Methods............... Experimental Design. ................. Vegetative Measures. ............. Data Analyses. ..... Results and Discussion. ....... 67 67 70 70 70 72 73 MANAGEMENT RECOMMENDATIONS . ...... 81 APPENDIX...... 84 LITERATURE CITED. ......... 113 iv LIST OF TABLES Table 1 2 3 4 5 6 7 8 Page Mean percent browsing (and standard error) of bigtooth (BT) and quaking (Q) aspen for 6 age classes since clearcutting, sampled 1983-1986.................................... 20 Significant differences (P<0.10) in browse utilization between bigtooth (BT) and quaking (Q) aspen clearcuts of various age classes.... 21 Comparisons of mean percent browse utilization (standard error) of bigtooth (BT) and quaking (Q) aspen between whole-tree harvested and conventional clearcuts, sampled in 1986. No significant differences (P>0.10) between harvesting methods. ..... 23 Variation in the measurements of 7 variables from 53 aspen clearcuts in the Pigeon River Country State Forest, 1986. . ...... 24 Clipping and vegetation collection schedule for simulated browsing. .................... 31 Mean standing height (cm) (and standard error) of bigtooth and quaking aspen trees subjected to various simulated browsing treatments. Values are from measurements taken in year 3 of the study, with the exception of plots clipped in year 1 and sampled in year 2.......... 36 Mean number (and standard error) of bigtooth and quaking aspen current annual growth twigs available per hectare under various simulated browsing treatments. Values are from samples taken in year 3 of the study, with the exception of plots clipped in year 1 and sampled in year 2 ..... .......... 38 Mean length (cm) (and standard error) of big­ tooth and quaking aspen current annually produced twigs clipped under various simulated browsing treatments. Values are from samples clipped in year 3 of the study, with the exception of plots clipped in year 1 and sampled in year 2 ................. 40 V Table 9 10 11 12 13 14 Page Mean stem density per hectare (and standard error) of bigtooth and quaking aspen under various simulated browsing treatments. Values are from year 3 of the study, with the exception of plots clipped in year 1 and sampled in year 2. No significant differences (P>0.10)......................... 42 Mean annual productivity (kg/ha) (and standard error) of bigtooth and quaking aspen twigs under various simulated browsing treatments. Values are from samples clipped in year 3 of the study, with the exception of plots clipped in year 1 and sampled in year 2. 43 Significant differences between bigtooth (BT) and quaking (Q) aspen stand characteristics under various simulated browsing treatments.......................... 45 Mean percent ash, on dry-matter basis, (and standard error) of bigtooth and quaking aspen twigs clipped under various simulated browsing treatments. Values are from samples clipped in year 3 of the study, with the exception of plots clipped in year 1 and sampled in year 2. ........ No significant differences (P>0.10) 46 Mean percent crude protein, on dry-matter basis, (and standard error) of bigtooth and quaking aspen twigs clipped under various simulated browsing treatments. Values are from samples clipped in year 3 of the study, with the exception of plots clipped in year 1 and sampled in year 2 ..... 48 Mean percent phosphorus, on dry-matter basis, (and standard error) of bigtooth and quaking aspen twigs clipped under various simulated browsing treatments. Values are from samples clipped in year 3 of the study, with the exception of plots clipped in year 1 and sampled in year 2............................ 50 vi Mean percent ether extract, on dry-matter basis, (and standard error) of bigtooth and quaking aspen twigs clipped under various simulated browsing treatments. Values are from samples clipped in year 3 of the study, with the exception of plots clipped in year 1 and sampled in year 2 ....... ............... Mean percent cell-soluble material, on drymatter basis, (and standard error) of bigtooth and quaking aspen twigs clipped under various simulated browsing treatments. Values are from samples clipped in year 3 of the study, with the exception of plots clipped in year 1 and sampled in year 2. No significant differences (P>0.10) ..... .................. Mean percent cellulose, on dry-matter basis, (and standard error) of bigtooth and quaking aspen twigs clipped under various simulated browsing treatments. Values are from samples clipped in year 3 of the study, with the exception of plots clipped in year 1 and sampled in year 2. No significant differences (P>0.10)... .................................. Mean percent hemicellulose, on dry-matter basis, (and standard error) of bigtooth and quaking aspen twigs clipped under various simulated browsing treatments. Values are from samples clipped in year 3 of the study, with the exception of plots clipped in year 1 and sampled in year 2 ....... ................. Mean percent lignin, on dry-matter basis, (and standard error) of bigtooth and quaking aspen twigs clipped under various simulated browsing treatments. Values are from samples clipped in year 3 of the study, with the exception of plots clipped in year 1 and sampled in year 2. No significant differences (P>0.10)..................................... Mean percent in vitro dry matter digestibility (and standard error) of bigtooth and quaking aspen twigs clipped under various simulated browsing treatments. Values are from samples clipped in year 3 of the study, with the exception of plots clipped in year 1 and sampled in year 2 ............................ Significant differences between bigtooth (BT) and quaking (Q) aspen chemical constituent levels in twigs and leaves under various simulated browsing treatments................ Mean percent ash, on dry-matter basis, (and standard error) of bigtooth and quaking aspen leaves removed from twigs subj ected to various simulated browsing treatments. Values are from samples collected the summmer following the respective twig clipping....... Mean percent crude protein, on dry-matter basis, (and standard error) of bigtooth and quaking aspen leaves removed from twigs subj ected to various simulated browsing treatments. Values are from samples collected the summer following the respective twig clipping. No significant differences (P>0.10) .......................... ........ Mean percent phosphorus, on dry-matter basis, (and standard error) of bigtooth and quaking aspen leaves removed from twigs subj ected to various simulated browsing treatments. Values are from samples collected the summer following the respective twig clipping. No significant differences (P>0.10).................. ................... Mean percent ether extract, on dry-matter basis, (and standard error) of bigtooth and quaking aspen leaves removed from twigs subj ected to various simulated browsing treatments. Values are from samples collected the summer following the respective twig clipping. ............................. viii Mean percent cell-soluble material, on drymatter basis, (and standard error) of bigtooth and quaking aspen leaves removed from twigs siobj ected to various simulated browsing treatments. Values are from samples collected the summer following the respective twig clipping. No significant differences (P>0.10)..................... .............. Mean percent cellulose, on dry-matter basis, (and standard error) of bigtooth and quaking aspen leaves removed from twigs subjected to various simulated browsing treatments. Values are from samples collected the summer following the respective twig clipping. No significant differences (P>0.10)............. Mean percent hemicellulose, on dry-matter basis, (and standard error) of bigtooth and quaking aspen leaves removed from twigs subjected to various simulated browsing treatments. Values are from samples collected the summer following the respective twig clipping. No significant differences ..... ...................... (P>0.10) Mean percent lignin, on dry-matter basis, (and standard error) of bigtooth and quaking aspen leaves removed from twigs subj ected to various simulated browsing treatments. Values are from samples collected the summer following the respective twig clipping. No significant differences (P>0.10) .......... Mean percent in vitro dry matter digestibility (and standard error) of bigtooth and quaking aspen leaves removed from twigs subjected to various simulated browsing treatments. Values are from samples collected the summer following the respective twig clipping. No significant differences (P>0.10)......... . Mean stem densities per hectare (and standard error) of trees (0-0.5m, 0.5-2.0m, and >2.0m in height) in exclosures and areas open to browsing on 4-year-old bigtooth aspen clearcuts (1986)............................. Table 32 33 34 35 36 37 38 39 Page Mean stem densities per hectare (and standard error) of trees (0-0.5m, 0.5-2.0m, and >2.0m in height) in exclosures and areas open to browsing on 5-year-old bigtooth aspen clearcuts (1986)............................. 95 Mean stem densities per hectare (and standard error) of trees (0-0.5m, 0.5-2.0m, and >2.0m in height) in exclosures and areas open to browsing on 6-year-old bigtooth aspen clearcuts (1986). No significant differences (P>0.10)... .................................. 97 Mean stem densities per hectare (and standard error) of trees (0-0.5m, 0.5-2.0m, and >2.0m in height) in exclosures and areas open to browsing on 4-year-old quaking aspen clearcuts (1986)............................. .......... 98 Mean stem densities per hectare (and standard error) of trees (0-0.5m, 0.5-2.0m, and >2.0m in height) in exclosures and areas open to browsing on 5-year-old quaking aspen clearcuts (1986). No significant differences (P>0.10).. 99 Mean stem densities per hectare (and standard error) of trees (0-0.5m, 0.5-2.0m, and >2.0m in height) in exclosures and areas open to browsing on 6-year-old quaking aspen clearcuts (1986). No significant differences (P>0.10).. 101 Mean percent vegetative cover (and standard error) for height strata in exclosures and areas open to ungulate browsing on 4-, 5-, and 6-year-old bigtooth and quaking aspen clearcuts (1986)............................. 76 Significant differences in horizontal cover for height strata between exclosures and areas open to ungulate browsing on 4-, 5-, and 6-year old bigtooth and quaking aspen clearcuts (1986)........ ............................... 78 Mean absolute (AF) and relative frequencies (RF) and standard errors (SE) of herbaceous species in exclosures and areas open to browsing on 4-year-old bigtooth aspen clearcuts (1986)............................. x 103 Table 40 41 42 43 44 Page Mean absolute (AF) and relative frequencies (RF) and standard errors (SE) of herbaceous species in exclosures and areas open to browsing on 5-year-old bigtooth aspen clearcuts (1986). No significant differences (P>0.10)..................................... 105 Mean absolute (AF) and relative frequencies (RF) and standard errors (SE) of herbaceous species in exclosures and areas open to browsing on 6-year-old bigtooth aspen clearcuts (1986). No significant differences (P>0.10)........................ ............. 107 Mean absolute (AF) and relative frequencies (RF) and standard errors (SE) of herbaceous species in exclosures and areas open to browsing on 4-year-old quaking aspen clearcuts (1986)................... .................... 108 Mean absolute (AF) and relative frequencies (RF) and standard errors (SE) of herbaceous species in exclosures and areas open to browsing on 5-year-old quaking aspen clearcuts (1986). No significant differences (P>0.10).. 109 Mean absolute (AF) and relative frequencies (RF) and standard errors (SE) of herbaceous species in exclosures and areas open to browsing on 6-year-old quaking aspen clearcuts (1986). No significant differences (P>0.10).. 111 xi LIST OF FIGURES Figure 1 2 3 4 Page Location of the Pigeon River Country State Forest in Michigan.......................... 7 Mean monthly temperatures at Vanderbilt, MI during years of the study (1983-86) and the long term average (1940-69)............ 9 Mean monthly precipitation at Vanderbilt, MI during years of the study (1983-86) and the long term average (1940-69)............ 10 Physiographic distribution of plant associations in the Pigeon River Country State Forest................................ 11 xil INTRODUCTION Bigtooth and quaking aspen (Populus qrandidentata and P.tremuloides) are considered important tree species in Michigan because of their economic importance to the pulp industry, as an energy resource, and their value to wildlife for food and cover (Barnes 1966, Young 1974). Because of these factors, land managers have implemented various silvicultural practices in an attempt to intensify the productive capacity of the aspen resource. Researchers have documented that aspen regeneration is greatest when the overstory is removed and if scarification occurs. This management strategy allows less understory competition for aspen sucker development after mature trees are harvested (Perala 1972, Schier and Smith 1979). To obtain optimum aspen regeneration, land managers have used clearcutting as the primary method of harvesting (Gysel 1957, Farmer 1962, Perala 1972, Schier and Smith 1979). This silvicultural practice has 3 benefits: 1) it stimulates the production of aspen shoots from the root pericycle of parent trees as they are harvested, thus producing relatively pure stands of aspen, 2) mechanized harvesting is more economically attractive and efficient for loggers by enabling aspen to be cut in large extensive stands, and 3) it is a means of habitat improvement for 1 2 wildlife, such as ungulates, by producing early successional stages and forests of various age classes (Schneider 1972). Clearcutting has been documented to be the most effective method of regenerating extensive stands of aspen (Schier and Smith 1979). The large number of shoots produced by clearcutting provide important cover for a variety of wildlife species, such as ruffed grouse (Bonasa umbellus), and nutritional food for ungulates. Because of the nutritive qualities of aspen, white-tailed deer (Odocoileus virqinianus) and/or elk (Cervus elaphus) may browse heavily on new shoots. This browsing removes the apical meristem of developing aspen and thus stimulates lateral buds on both suckers and roots (Farmer 1962). Therefore, effects of heavy browsing may include: 1) failure of suckers to attain maximum tree height or form (Weinstein 1979), 2) adverse impacts on populations of wildlife species, such as deer, elk, and ruffed grouse, which depend on aspen for food and cover, and 3) the development of aspen stands which are not able to produce merchantable timber for various wood products. Although there has recently been a significant increase in the understanding of evolutionary and ecological impacts of herbivory, the effects of herbivory remain poorly understood. Studies of the effects of ungulates on their habitat have mainly concentrated on plant species composition, structure, and productivity. Herbivory, 3 however, also has potential implications for changes in plant chemistry (Feeny 1976, Levin 1976). Mammalian herbivores have been known to discriminate between plants with high and low concentrations of nutrients (Arnold 1964) and digestion-inhibiting compounds (Longhurst et al. 1968, Radwan and Crouch 1978). Selective herbivory may result in intraspecific changes in the chemical composition of some plant communities (McNaughton and Tarrants 1983). At what use levels these chemical changes occur and still permit sustained production are not known for many important browse species, such as aspen. Because little is known, researchers have conducted experiments simulating various levels of browsing on tree species (Julander 1937, Garrison 1953, Marshall et al. 1955, Krefting et al. 1966, Shepard 1971, Willard and McKell 1978, Bergstrom and Danell 1987). Studies simulating browsing intensities on vegetation are usually conducted by constructing small exclosures and then clipping predetermined intensities of current annual growth from a number of individual trees within the exclo­ sures . Unfortunately, Julander's (1937) study is the only published simulated browsing study completed on the effects of clipping and utilization of aspen. He documented that quaking aspen regeneration in the Kaibab National Forest would deteriorate if utilized at an intensity of 75% or greater. However, if clipping intensities were within 65 to 70%, a net improvement was noted in both tree height and shoot production. Julander, however, did not monitor changes in the nutritional qualities of aspen. The effects that various levels of utilization have on the composition and stucture of aspen clearcuts have been documented by researchers through vegetative measurements conducted in both exclosures and areas open to ungulates. Gaffney (1941) estimated that elk browsing in clearcuts in Montana killed at least 50% of the young aspen between the heights of 38 cm and 1.8 m. Grimm (1939) using exclosures and control areas to quantify the effects of aspen utilization by ungulates, documented a difference between the 2 areas. The mortality of aspen was 50.7% greater among trees in control areas than within exclosures. Trees within exclosures also increased in height by 20% while trees in control areas decreased 24.2%. Similar results have been noted by other authors for aspen and hardwood species regeneration (Gaffney 1941, Marquis 1974, 1981). Because bigtooth and quaking aspen are important forest resources in the Pigeon River Country State Forest (PRCSF) and heavy browsing by deer and elk may be inhibiting regen­ eration, the effects of ungulates on aspen regeneration were investigated. Results of this study will assist resource managers in solving potential problems which may exist between aspen regeneration and ungulate use. Therefore, results may be important to determine whether modifications in current habitat and/or ungulate population management 5 practices might be necessary to alleviate any existing problems. The objectives of the study were to: 1) quantify browse utilization of bigtooth and quaking aspen, 2) determine the effects of various levels of simulated browsing on aspen clearcut productivity, stand characteristics, and nutritional qualities, and 3) determine the effects of deer and elk browsing on the composition and structure of regenerating aspen following clearcutting. STUDY AREA DESCRIPTION This study was conducted within the PRCSF in the northcentral lower peninsula, approximately 21 km east of Vanderbilt, Michigan. The forest includes approximately 39,000 ha and occupies portions of Cheyboygan, Montmorency, and Otsego Counties (Fig. 1). The study area lies within the Presque Isle Rolling Plain Emmet-Alcona Hill Land, and Huron Lake-Border Plain physiographic regions (Sommers 1977). The PRCSF is within the watersheds of the Sturgeon, Pigeon, and Black rivers which originate in the coniferous swamps on the southern edge of the forest and flow northward (Moran 1973). The surface formations of the area range from outwash plains of dry and sandy soils to swampy regions of highly fertile soils. Medium-high fertility soils are located on the till plains and moraines (Moran 1973). These materials were deposited in the Pleistocene epoch (Sommers 1977). The climate alternates between continental-type and semi-marine (Moran 1973). Although the interior location of the PRCSF helps to minimize the climatic influences of the Great Lakes, increased cloudiness, associated with prevailing westerly winds during the fall and winter months does occur. The area is characterized by large daily, monthly, and seasonal temperature changes. Mean (1940-1969) annual temperature and precipitation for this area is 5.6°C 6 7 SCALE 3.2km CHEBOYGAN OTSEGO MONTMORENCY PRCSF Fig. 1. Location of the Pigeon River Country State Forest in Michigan. 8 and 74.9 cm, respectively (Michigan Weather Service 1974). Mean monthly temperatures were similar to the long term averages (Fig. 2). Mean monthly precipitation, however, was more varied from 1983-1986 (Fig. 3) (National Oceanic and Atmospheric Administration 1983-1986). Due to the diversity of soil types, drainage, and exposure, in addition to perturbations such as logging, burning, and limited farming, a diversity of vegetation types have developed within the PRCSF. Spiegel et al. (1963) first classified the vegetation types into 5 categories with Moran (1973) adding a coniferous swamp category (Fig. 4). * 1983 1940-69] +16- - 8 - J F M A M J J A S O N 0 S O N D MONTH -4 1984 +16- 1940-69 4- TEMPERATURE (°C ) + J F M A M J J A MONTH 4 19@5 + 16- O 1940-69 + 4- J F M A M J J A S O N D N D MONTH A 1986 O 1940-69 + 16- + 4- -8 J F M A M J MONTH J A S O Fig. 2 . ilean monthly temperatures at Vanderbilt, MI during years of the study (1983-86) and the long term average (1940-69). 10 20 & 1983 1940-69, 12- MONTH 20 - 1984 1940-69 PRECIPITATION (cm ) 12- MONTH 20 1985 01940-69 * 12 - MONTH 20 - * 1986 0 1 9 4 0 -6 9 12 - MONTH Fig. 3. Mean monthly precipitation at Vanderbilt, MI during years of the study (1983-86) and the long term average (1940-63). Elevation 366 m iu 274 m Coniferous Swamp Riverbanks & Bottomlands Sandy Outwash Plain OutwashPlain Morainic Ecotone Steep Morainic Slopes Morainic Uplands White cedar Speckled alder Juneberry Red maple Aspens White elm Balsam fir Dogwoods Jack pine Aspens Oak Basswood Black spruce Willows Cherry Juneberry Red maple Sugar maple Balsam poplarWhite cedar W illows White birch White pine Hemlock Ash Red pine Red elm Fig. 4. Physiographic distribution of plant associations in the Pigeon River Country State Forest (Moran 1973). BROWSE UTILIZATION OF ASPEN CLEARCUTS BY WHITE-TAILED DEER AND ELK Introduction In the last decade much concern has been expressed over the decline of the aspen forest type. The primary cause for decline being succession to other forest types (Byelich et al. 1972, McGuire 1972). Heavy browsing by ungulates has been cited as the predominant cause for a loss of aspen in some regions of the United States. This was the traditional thought of researchers investigating the relationship of elk and aspen in Jackson Hole, Wyoming. Gruel1 and Loope (1974), however, suggested that this hypothesis neglected the consideration of other biotic and abiotic influences on aspen. Schier (1975) concluded that the amount of area in the aspen type had been previously reduced by the policy of fire suppression rather than ungulate browsing. He stated that the absence of fires had allowed plant succession to proceed uninterrupted, reducing the amount of available forage and resulting in intense browsing pressures on accessible vegetation. Gruel1 and Loope (1974) hypothesized that in the past, extensive fires produced enough forage to overcome effects of browsing and allow successful aspen regeneration. Under present management policies, in some regions of the United States, the role of natural disturbances, such as 12 13 fire, in determining forest cover types has been reduced. Therefore, the potential effects of ungulate browsing on aspen regeneration have to be considered. Typically, following clearcutting, an abundance of forage is produced and is available to ungulates. Schier and Smith (1979) compared aspen regeneration after clearcutting to other silvicultural practices and concluded that clearcutting resulted in the greatest number of suckers. Many researchers in the Lake States, Canada, and the West have made similar conclusions stating that clearcutting aspen results in regeneration with a minimum of gaps and the best possible growth (Weigle and Frothingham 1911, Sampson 1919, Baker 1925, Zehngraff 1947, 1949, Curtis 1948, Sandberg 1951, Perala 1972, Brinkman and Roe 1975). Schier (1976) stated that clearcutting produced more aspen shoots than other silvicultural methods due to the removal of all stems, reducing apical control to a minimum and enabling the species to grow in full sunlight where it could attain its1 maximum height. Producing large numbers of suckers, by techniques such as clearcutting, ensures the development of aspen stands because less vigourous suckers will die during the first 2 years post-harvest. Jones (1976) stated that approximately 40% of the suckers produced on plots in Arizona died within the first 4 years after clearcutting. In addition to natural thinning which occurs the first few 14 years after clearcutting, there are also continuous losses of suckers to browsing and trampling by ungulates (Crouch 1981). In heavily stocked stands, such as those produced by clearcutting, these losses are negligible (Smith et al. 1972, Jones 1976). These stands may provide a "browsing buffer" against ungulate browsing the first 3 to 4 years after clearcutting unless deer and/or elk numbers are exceptionally high (Sampson 1919, Packard 1942, Westell 1956, Larson 1959, Jones 1967, 1976, Smith et al. 1972) or locally concentrated. Other studies have documented a problem of inadequate aspen regeneration leading ultimately to a reduction in merchantable timber. Some researchers have attributed this problem to elk browsing (Gaffney 1941, Murie 1944, Beetle 1962). Heavy browsing of species such as aspen, sugar maple (Acer saccharum), red maple (A. rubrum), and black cherry fPrunus serptina) has often reduced the height and altered tree form. Westell (1954) documented that deer browsing in bigtooth aspen clearcuts removed up to 4,595 kg/ha of aspen twigs and leaves from suckers as tall as 1.65 m. This browsing impact resulted in no evidence of aspen reproduction even 3-5 years after clearcutting. Spiegel et al. (1963) noted that of 1,729 bigtooth and quaking aspen shoots examined in a new pulpwood clearcut in northern Michigan, all stems were severely browsed by deer and elk. 15 They projected that continued damage to this area would prevent the development of a new stand and the area would result in a type conversion to grassland. Gaffney (1941) made similar conclusions concerning effects of elk browsing on young aspen in Montana. The heavy browsing of aspen which has been documented to occur following clearcutting, throughout the country, may primarily occur due to the abundance of an easily attainable food source. Other factors which may contribute to the utilization of aspen include: 1) new sprouts charac­ teristically having a higher nutritional quality than more mature plants, 2) the type of clearcut (conventional, roundwood cut vs. whole-tree harvested) 3) location of clearcuts, and 4) clearcut size. These factors singly or in some combination could contribute to why aspen is heavily browsed after clearcutting and thus cause potential regeneration problems for resource managers. The objective for this portion of the study was to evaluate ungulate use of bigtooth and quaking aspen clearcuts in relation to surrounding cover types, stand age, clearcut size, and method of harvest. 16 Methods Experimental Design To evaluate the extent of browsing that bigtooth and quaking aspen clearcuts of various age classes received from ungulates, browse estimates were conducted in 53 aspen clearcuts within PRCSF. Browse counts were conducted in early spring, before development of current annual growth and leaf-out, in order to quantify the utilization of aspen twigs during fall and winter, the predominant seasons in which woody material is browsed by ungulates. Counts were conducted in 1983, 1984, 1985, and 1986. All clearcuts in PRCSF less than 3 growing seasons in age were classified as bigtooth and/or quaking aspen and sampled (if clearcuts contained both species of aspen, sampling was stratified according to species). Additional clearcuts were sampled in later years as they became available. Only clearcuts up to 6 growing seasons old were sampled the last year of the study as older clearcuts have generally grown beyond the reach of ungulates (Westell 1954). Any damage done to older stands by ungulates was primarily due to bending and breaking of trees, and thus took a different form than the browsing of shoots in younger age classes. Clearcut Measurements Percent browse utilization was determined as the number of stems browsed of the first 100 stems counted < 2.0 m 17 in height using 2.0 m wide randomly located belt transects (Gysel and Lyon 1980). A height limit of 2.0 m was used as it was assumed primary production occurring above this height was unavailable for normal browsing by deer and elk. Additional variables for each clearcut included distance to the nearest swamp conifer edge, stand age, stand size, and type of clearcut, as well as the percentage of area clearcut within the mean daily movement distance of Michigan elk. The movement distance used, 1.22 km, was based on data gathered from radio-collared elk in PRCSF (Beyer 1987). Clearcut size, straight line distances from clearcuts to swamps, and percentages of areas clearcut were measured using the Michigan State Forest Operations Inventory System (MSFOI 1982) compartment maps. Clearcut age was determined by the number of complete growing seasons post-harvest. Clearcut type was classified as whole-tree harvest or conventional, roundwood cut. Quality control of field sampling was assured by determining statistically adequate sample sizes (Freese 1978). A 90% confidence level was used to determine sample sizes. Allowable error was set at 10% of the mean. Data Analyses Data sets were tested for equality of variances with an F test (Steel and Torrie 1980). Browse utilization was compared between species, age classes, and type of clearcuts 18 using 1-way analysis of variance (Steel and Torrie 1980) and the randomization test (Siegel 1956). Because of the lack of some age classes of clearcuts, within harvesting methods and species, clearcuts were grouped into classes 1 and 2, 3 and 4, and 5 and 6 growing seasons old for comparisons between whole-tree harvested and conventional clearcuts. The influence of variables on browse utilization was analyzed using multiple regression methods (Draper and Smith 1966). Percent browse utilization was the dependent variable, and the other variables measured were treated as independent variables. Species of aspen and type of clearcut were coded as 0 or 1 for regression analysis. The computer program Number Cruncher Statistical System (NCSS) (Hintze 1986) was used to perform regression calculations. The best regression model, incorporating only the most influential independent variables, was calculated using the backward elimination procedure described by Draper and Smith (1966). The regression model was tested by analysis of variance techniques. Residuals of the regression model were plotted to assure data did not violate the assumptions of linear regression. The regression coefficient (R2) was calculated for the model to estimate the amount of variation in the dependent variable that was explained by the regression (Draper and Smith 1966). 19 Results and Discussion The percentage of browse utilization of bigtooth and quaking aspen clearcuts was greater in younger age classes than older classes for most years of the study (Table 1). These results may be attributed to 2 factors. One, ungulates tend to forage more heavily on vegetation which is younger and thus of a higher nutritional quality than more mature plants. It has been documented by various researchers that as plant tissue ages, protein content typically declines while fiber constituents increase. These chemical constituent changes have been shown to deter herbivore browsing (Kozlowski and Keller 1968). Secondly, as trees mature the amount of annual productivity available for ungulate consumption declines as trees grow beyond their reach. Crouch (1983) also documented a decline in aspen use by ungulates with age post-harvesting, as observed in the PRCSF. The percentage of utilization in his study, however, was substantially less than that observed in the PRCSF. Comparisons of browse utilization between species (bigtooth vs. quaking) within age classes and years showed bigtooth was browsed significantly more than quaking aspen for all age classes and years except 1-year-old bigtooth aspen clearcuts in 1985 (Table 2). Bigtooth aspen clearcuts did receive considerable browsing pressure from ungulates. Differences in browse utilization between species may be due 20 Table 1. Mean percent browsing (and standard error) of bigtooth (BT) and quaking (Q) aspen for 6 age classes since clearcutting, sampled 1983-1986. # of growing seasons Year Sp. 1 2 3 4 5 6 1983 BT 97. OA (0.8) 88.0B (2.0) — — — — Q 75. OA (7.0) 42.0B (3.0) 20. 0C (1.0) _~ —— — BT 85. OA (1.1) 86. 0A (4.2) 45.OB (3.9) — — — Q 50. OA (4.1) 39.0B (6.8) 26.4C (5.2) — —— BT 70. OA (14.0) 85. 0A (5.0) 91. OA (3.0) 44. OB (5.6) — — Q 42.4AB 51. 4A (12.9) (17.0) 28.2AB (4.5) 14.0BC (4.0) 12. OC (1.0) — 68. 5B (4.7) 58.1C (3.4) 18. 9D (7.3) — 9.3AB (2.1) 5.2B (0.4) 6.3B (0.5) 1984 1985 1986 BT Q (2.8) 42. 4A (11.0) 11.9A (1.0) 9.9A (1.6) 22.IK 34.4ABC (16.0) 4.9B (0.2) 1 Any 2 means within the same row with different letters indicate a significant difference (P<0.05). Table 2. Significant differences (P < 0.10) in browse utilization between bigtooth (BT) and quaking (Q) aspen clearcuts of various age classes. # of growing seasons Year 1 2 3 4 5 — — — — — 1983 BT > Q BT > Q 1984 BT > Q BT > Q BT > Q 1985 NSD1 BT > Q BT > Q BT > Q 1986 BT > Q BT > Q BT > Q BT > Q 1 No significant differences (P>0.10). — BT > < 22 to the differences in nutritive qualities of the 2 species. Comparisons of 8 chemical constituents between bigtooth and quaking aspen were conducted in the simulated browsing portion of this study and will be discussed in the later chapter. Comparisons of browse utilization between whole-tree harvested and conventional clearcuts indicated there were no significant differences in the level of use between methods, for either bigtooth or quaking aspen (Table 3). Therefore, one method of harvesting cannot be recommended over another to hinder ungulate movement into clearcuts and thus deter browsing. The ranges of measurements made of all variables on clearcuts are presented in Table 4 . The best regression model identified 3 variables that contributed 77% of the variation in ungulate use of aspen clearcuts in the PRCSF. These variables included species of aspen (P<0.01), clearcut age (P<0.10), and distance to the nearest swamp conifer stand (P<0.10). Therefore, multiple regression analysis indicated that a combination of these 3 variables may be influencing the utilization of some aspen clearcuts. As discussed by Beyer (1987), regenerating deciduous stands, primarily aspen, receive a great deal of use by elk during mild winter conditions or if stands are adjacent to good thermal cover in severe winter conditions. He stated 23 Table 3. Comparisons of mean percent browse utilization (standard error) of bigtooth (BT) and quaking (Q) aspen between whole-tree harvested and conventional clearcuts, sampled in 1986. No significant differences (P > 0.10) between harvesting methods. Harvesting method # of growing seasons Sp. WT1 1 & 2 BT 36.4(8.9) 46.6(21.9) Q 11.0(0.9) 9.6(2.4) BT 67.0(4.9) 60.8(5.0) 8.8(2.3) 5.9(0.5) 3 & 4 Q 5 & 6 BT CC2 12.0(2.8) _3 6.3(0.9) 7.1(1.2) Q 1 Whole-tree harvested clearcuts. 2 Conventional clearcuts. 3 Only 1 conventional clearcut in this age class. 24 Table 4. Variation in the measurements of 7 variables from 53 aspen clearcuts in the Pigeon River Country State Forest, 1986. Variables X Range SE % browsing 23.7 4.1-85.8 3.4 species of aspen CV1 — — type of clearcut (method of harvest) CV — — 1-6 0.2 age (growing seasons) size (ha) distance to nearest swamp conifer edge (m) % area clearcut within daily movement distance of Michigan elk 3.5 10. 0 2.0-19.0 0.7 444.5 0-1709 75.9 5.9 2-17.2 0.5 1 Coded variable - variable could not be measured and therefore was assigned a value of 0 or 1 for the respective species and type of clearcut. 25 that heavy use of thermal cover by the radio-collared elk he monitored in 1984 in the PRCSF, was primarily due to use of 1 stand. High use of this stand was partially attributed to it being adjacent to 3 young aspen stands. To minimize deer and elk use of aspen clearcuts close to good thermal cover, managers may cut aspen in long, narrow "strips", radiating away from wintering areas, if possible. Although elk may continue to browse on stems close to cover, they may not travel away from thermal cover edges, especially if snow exceeds 40 cm (Sweeney and Steinhoff 1976, Sweeney and Sweeney 1984). Reynolds (1966) and Harper (1969) documented that most elk use of either forage or cover areas occurred within 183 m of forest/cover edge. Hall and Thomas (1979) recommended that distances across clearcuts should be < 366 m to insure maximum use by ungulates. Although clearcutting aspen in strips wider than 366 m is not practical in the PRCSF, interspersing various age classes of clearcut strips around wintering areas may minimize intense browsing on specific stands. In addition, harvesting other tree species in areas where ungulates are locally abundant may relieve some browsing pressure on aspen. By implementing these strategies, aspen production for wood products and use by other wildlife species may be achieved. 26 A variety of other factors, however, may be instrumental in influencing ungulate use of clearcuts in the PRCSF. Because ungulate habitat use is a function of the inter­ relationships of behavioral and environmental variables, additional habitat factors may lead to different conclusions than the simultaneous effects of the variables considered in this study (Grover and Thompson 1986). This makes it difficult to prescribe habitat management techniques which will maintain or enhance ungulate habitat because the interactions of variables specific to a population are generally unknown in relation to habitat use for a given year (Skovlin 1982). In some forest types the distribution of cover and the presence of roads have also been found to affect elk use of clearcuts. Lyon and Jensen (1980) documented that in the absence of hiding cover inside clearcuts, cover at the edge became the deciding variable of elk use. This security cover was particularly important when clearcuts were accessible to vehicles. Leege and Hickey (1977) documented elk preferred brush fields without roads over nearby clear­ cuts with abundant forage and roads. Perhaps these 2 additional variables need to be considered in predicting ungulate use of clearcuts within the PRCSF. For example, whole-tree harvesting bigtooth aspen stands in close proximity to roads may help minimize intense browsing on 27 this species by providing less cover for ungulates and more disturbance from motor vehicles. Wildlife biologists and foresters should realize that in order to meet the objectives of management plans a variety of habitat management techniques may be implemented. The use of these techniques to achieve and maintain optimal habitat conditions for ungulates should be weighed to assure that they are complementary and help meet herd objectives (Lyon and Ward 1982). EFFECTS OF SIMULATED BROWSING ON ASPEN MORPHOLOGY, ANNUAL PRODUCTIVITY, AND CHEMICAL CONSTITUENTS Introduction Plants have adapted to herbivory in 4 general ways. First, they have developed various types of physical protection such as toughness, thorns, or spines (Schultz 1988). Second, they may be protected by the development of chemical compounds which may deter browsing by making plants less palatable or digestible (Rhodes 1979). Third, plant energy reserves may be funneled into growth, instead of the development of toxins, so that individuals may grow beyond the reach of herbivores before they are browsed (Coley et al. 1985). And lastly, the distribution of plants throughout space and time may also affect their potential as a food supply for herbivores (Feeny 1975). Individual plants may be either so abundant at one point in time that the relative amount of plant tissue browsed is negligible and thus some individuals will survive or plants may be distributed sparsely and may have such slow growth they may go undetected by herbivores. After some initial browsing, however, these strategies may alter the probability and intensity of future browsing as plants undergo chemical and/or physical changes (Haukioja and Niemela 1976, Rhodes 1979, Danell et al. 1985). 28 29 Various field studies have demonstrated that forage plants differ greatly in their ability to withstand browsing. A review of the literature, however, reveals a lack of knowledge regarding the amount of use important browse plants can withstand and still produce food on a sustained yield basis. Unfortunately, only a few studies have been based on clipping experiments where effects of repeated browsing or clipping on plant morphology, productivity, and chemical composition were monitored (Julander 1937, Aldous 1952, Bergstrom 1984, Danell et al. 1985, Bergstrom and Danell 1987). Removal of plant tissue over consecutive years or during critical years of plant development may have significant impacts on; 1) the amount of available wildlife forage, 2) timber production, 3) plant reproduction by the removal of reproductive parts or indirectly by altering plant physiology (Katsma and Rusch 1980), and 4) wildlife habitat through changes in stand composition or structure. This experiment was conducted to determine the potential effects of deer and elk browsing on aspen productivity, stand characteristics, and nutritional qualities. To study this objective, various levels of simulated browsing were used. 30 Methods Experimental Design Exclosures (40 m x 40 m x 2.1 m) were constructed on new bigtooth and quaking aspen clearcuts during the summer, 1984. The exclosures were replicated 3 times for each species, for a total of 6 exclosures. The area within the exclosures was divided into 10 m x 10 m blocks for each of the 3 clipping schedules (clipped in year 1, clipped in year 2, and clipped in years 1 and 2) and browsing intensities (no clipping-0%, 25%, 50%, 75%, and 100%) (Table 5) by severing the root systems between each block and around the perimeter of exclosures to a depth of 30.5 cm. Schier et al. (1985) reported that the maximum depth of aspen parent roots in the Lake States is less than 28 cm. Severing roots to this depth, therefore, eliminated the effects of aspen clones among treatments (B. Barnes, pers. comm.). Blocks were randomly selected for treatments of individual clipping schedules and intensities. Within exclosures, stand characteristics and aspen nutritional qualities were monitored with respect to each clipping intensity and schedule. Sample Collection and Measurements Data collected for each treatment included: oven-dried weights of woody current annual growth, stem densities, total number of twigs available within each treatment block, 31 Table 5. Clipping and vegetation collection schedules for simulated browsing. Simulated browsing intensities (%) Years Control 0 25 50 75 100 1 1 2 3 yi* N2 Y* Y* N Y* Y* N Y* Y* N Y* 2 1 2 3 N Y* Y* N Y* Y* N Y* Y* N Y* Y* H to Clipping schedule 1 2 3 Y Y* Y* Y Y* Y* Y Y* Y* Y Y* Y* 3 1 2 3 N N Y* 1 Denotes (Y) current annual growth was clipped. 2 Denotes (N) current annual growth was not clipped. * Samples were collected for nutritional analyses. 32 number of stems clipped per treatment, overall tree height, and length of woody current annual growth. Leaf samples were also collected since they are considered a valuble summer food for ungulates (Nelson and Leege 1982, DeByle 1985) and to assess effects of simulated browsing on chemical constituent levels of leaves. Twig and leaf samples collected from within exclosures were used to assess changes in the nutritive qualities of both species of aspen. Collection of vegetation coincided with the time various plant parts are utilized by ungulates. Leaf samples were collected during late summer and twig samples during early winter. Clipping of aspen twigs was conducted by removing only the designated percentage of current annual growth within each treatment with pruning shears. While simulated browsing is designed to be similar to actual ungulate browsing, it cannot exactly duplicate what may occur (stands which are heavily used by ungulates probably sustain a greater amount of injuries due to ungulate trampling). The clipping, however, does allow for a standardized method to be conducted among treatments. Nutritional Analyses To assess the impact various levels of simulated browsing had on the nutritional qualities of both species of aspen, vegetation collected was analyzed for percent dry matter, ash, crude protein, phosphorus, ether extract, in 33 vitro dry matter digestibility, neutral detergent fiber (NDF), acid detergent fiber (ADF), and acid detergent lignin (ADL). Cellulose, hemicellulose, and cell-soluble material were calculated as described by Goering and Van Soest (1970). All chemical constituent values are reported on a dry matter basis. Percent dry matter and ash content were determined by methods described in A.O.A.C. (1980). Total nitrogen and phosphorus was determined with a Kjeldahl digestion procedure using a Tecator Block Digestor, Model DS-40 (Tecator, Inc., Boulder, CO). Once samples were digested, nitrogen and phosphorus values were obtained using a Technicon Autoanalyzer II (Technicon Industrial Systems, Tarrytown, NY). Percent crude protein was then calculated as described by A.O.A.C. (1980) using total nitrogen values. Methods for NDF, ADF, and ADL analyses are those described by Goering and Van Soest (1970) with NDF procedures modified as discussed by Mould and Robbins (1981). In vitro dry matter digestibility was determined using the Tilley and Terry (1963) method modified by Michigan State University, Department of Dairy Science. Modifications included the use of a phosphate-carbonate buffer solution and a ratio of 12 ml of rumen fluid to 10 ml buffer solution. Inoculum for digestibility trials was obtained from a fistulated, nonlactating Holstein cow owned by Michigan State University, 34 Department of Dairy Science. The cow was maintained on a diet of good quality alfalfa hay. Percent ether extract (crude fat) was determined by methods stated in A.O.A.C. (1980) modified by weighing vegetation samples into tared filter paper '•packets” instead of extraction thimbles. This modification enabled a larger number of samples to be analyzed per run. A 3:1 ratio of anhydrous ethyl ether to methanol was used for ether extract analysis. Percent ether extract was calculated as the weight loss in samples after extraction. Data Analyses All data sets were tested for homogeneity of variance using the Fmax-test (Sokal and Rohlf 1981). Arcsin transformations were made to achieve homogeneity, if necessary. To test for differences in nutritional qualities and stand characteristics betweeen clipping intensities and schedules, 2-way analysis of variance was used. Comparisons of nutritional qualities and vegetative characteristics between clipping intensities and controls were made using Dunnett1s test (Steel and Torrie 1980). Significant differences among clipping intensities within individual schedules were identified using Duncan1s new multiple range test. Comparisons between aspen species were made using 1- way analysis of variance and the randomization test (Siegel 1956, Steel and Torrie 1980). The acceptance level of statistical significance for all tests was at o(= 0.10. 35 Results and Discussion Stand Characteristics Initially, (year 1) there were no differences in stand characteristics (standing height, number of current annual growth twigs available, stem density, length of annuallyproduced twigs clipped, and annual productivity) between treatment groups for any of the variables. Therefore, it was assumed that differences which occurred between treatments throughout the study were due to effects of clipping. Data collected the first year of the study, prior to any treatment, were considered baseline data and are not presented in the following tables. None of the clipped bigtooth aspen trees attained heights equal to or greater than those attained by control trees (Table 6). Bergstrom and Danell (1987) conducted simulated browsing studies on birch (Betula spp.) and documented shorter trees only on plots with 100% of the annual productivity clipped. After 3 years of clipping in their study, there were no significant differences in tree height between control groups and the 25%, 50%, and 75% treatments. Julander (1937), who investigated effects of ungulate utilization and clipping of quaking aspen on tree height and production, documented results similar to Bergstrom and Danell (1987). He stated that trees browsed or clipped greater than 75% showed a loss in maximum height. 36 Table 6. Mean standing height (cm) (and standard error) of bigtooth and quaking aspen trees subjected to various simulated browsing treatments. Values are from measurements taken in year 3 of the study, with the exception of plots clipped in year 1 and sampled in year 2. Simulated Intensities (% brows incr trtmt. NO (Year sampled) clipping 25 of annual productivity clipped) 50 75 100 1 (3) 203.8A1 (12.9) 160.4B (14.1) 177.4AB (8.7) 167.8AB (7.9) 156.3B (11.2) 2 (3) 203.8A (12.9) 161.7A (16.2) 190.1A (3.1) 191.8A (18.3) 168.9A (16.1) 1 (2) 156.5A (9.5) 142.0A (10.3) 130.2A (16.0) 128.8A (4.1) 140.7A (4.0) 1,2 (3) 203.8A (12.9) 179.6AB (5.8) 158.2AB (18.0) 160.2AB (19.8) 139.4B (18.0) 1 (3) 174.OAB (7.1) 186.9AB (10.7) 212.2A (1.1) 178.1AB (18.2) 157.8B (14.0) 2 (3) 174.0A (7.1) 173.7A (10.0) 186.2A (11.0) 171.0A (21.1) 172.0A (10.3) 1 (2) 187.7A (13.9) 169.7A (22.3) 167.7A (4.4) 161.4A (1.0) 148.2A (12.4) 1,2 (3) 174.0A (7.1) 172.4A (25.8) 168.9A (12.1) 147.0A (9.0) 144.0A (13.2) 1 Means within a row with different letters indicate a significant difference (P<0.10). 37 Similar results were documented in this study for bigtooth aspen clipped 100% the last year of the study. Unlike bigtooth aspen, quaking aspen did not show any significant differences in tree height between clipped trees and controls (Table 6). Results may be attributed to quaking aspen being more resistant to the effects of browsing by replacing lost biomass more quickly than bigtooth aspen. The number of bigtooth aspen twigs available the third year in all simulated browsing intensities was never greater than that of control trees (Table 7). Significantly fewer twigs were available in all 100% clipping treatments, except on plots clipped in year 1 and sampled in year 2. Fewer twigs were also found on plots clipped at 75% in years 1 and 2. Because trees clipped at lower intensities had less plant tissue removed, they had a greater chance of becoming larger and producing more lateral shoots than those clipped at higher intensities. Bergstrom and Danell (1987) documented similar results with birch as those obtained with bigtooth aspen. They noted that clipped birch, compared to controls, showed a decline in the number of shoots available. Sampson (1919) also investigated the influence of browsing on aspen reproduction following clearcutting. He documented that sprouting was vigorous, abundant, and widespread the first 2 growing seasons. The sprouts 38 Table 7. Mean number (and standard error) of bigtooth and quaking aspen current annual growth twigs available per hectare under various simulated browsing treatments. Values are from samples taken in year 3 of the study, with the exception of plots clipped in year 1 and sampled in year 2. Simulated Intensities (% browsina trtmt. No (Year sampled) clipping 25 1 (3) 278271A1 137695AB (128148) (83309) 2 (3) 278271A (128148) 1 (2) 47469A (21851) 1,2 (3) 278271A (128148) of annual productivity clipped) 50 234444AB (145061) 75 100 179876AB (51358) 93333B (30617) 132 098AB (29601) 251604AB 22 0370AB (66913) (136419) 73333B (38148) 35432A (22345) 23333A (16419) 16296A (6296) 14691A (2222) 170823AB (80860) 101604AB (80123) 69506B (46296) 54567B (6419) uai^xxiy aspen-1 (3) 196419AB 254814A (16296) (18024) 2 (3) 196419A (16296) 1 (2) 1,2 (3) 192098AB (32222) 181234AB (37407) 125555B (16913) 190246A (77777) 176913A (71975) 120617A (48518) 111234A (44444) 194629A (149321) 141604A (35185) 110740A (6419) 90123A (21111) 54938A (7407) 196419A (16296) 221604A (82469) 119506A (22098) 114814A (14444) 75802A (3827) 1 Means within a row with different letters indicate a significant difference (P<0.05). 39 produced each year, however, were extensively browsed. The third season sprouts were not as abundant, they lacked vigor, and tended to be in clumps instead of evenly distributed as previously documented. The implications of Sampson1s work are perhaps carbohydrate root reserves of healthy clones were depleted after 3 years of intense browsing (Olmstead 1979). Similar conclusions may be made for bigtooth aspen in the PRCSF. Intense clipping (>75%) in consecutive years or at an early growth stage may have depleted carbohydrate reserves and therefore reduced the number of twigs which could be produced. Clipping quaking aspen, however, did not seem to impair the number of twigs available since no significant diffe­ rences were observed between clipped trees and controls (Table 7). A significant difference was observed between plots clipped at 25% and 100% in year 1 but this may be attributed to random chance because no other differences were observed. The only significant differences observed in twig lengths among clipping intensities occurred on bigtooth and quaking aspen plots clipped in year 2. Trees clipped at 100% had significantly longer twigs than control trees (Table 8). This type of trend, however, was observed for 63% and 81% of the bigtooth and quaking aspen treatments, respectively. Greater twig lengths on clipped plots, than 40 Table 8. Mean length (cm) (and standard error) of bigtooth and quaking aspen current annually produced twigs clipped under various simulated browsing treatments. Values are from samples clipped in year 3 of the study, with the exception of plots clipped in year 1 and sampled in year 2. Simulated Intensities (% browsing trtmt. (Year No sampled) clipping 25 . of annual productivity clipped) 50 75 100 ca.speiir 1 (3) 21.5A1 (2.0) 13 .4A (1.6) 27. 6A (5.7) 16.3A (2.8) 24 .3A (6.0) 2 (3) 21. 5A (2.0) 22. 6A (3.2) 25.0AB (1.9) 22. 5A (2.1) 36.0B (5.2) 1 (2) 43. 6A (6.2) 42 .5A (3.5) 42. 6A (1.9) 44. 9A (7.0) 55. 9A (5.3) 1,2 (3) 21. 5A (2.0) 18. 3A (1.0) 18. 2A (2.1) 21.7A (4.2) 33. 7A (8.4) ---------- --- — -- - ■--- -— Quaking aspen- --------------- ---- ------- 1 (3) 18. 2A (3.8) 16.8A (1.4) 21.9A (2.5) 20.1A (1.7) 15. 2A (1.0) 2 (3) 18. 2A (3.8) 15, 3A (1.0) 18.8AB (2.1) 22.0AB (l.D 26. 9B (3.7) 1 (2) 48. 7A (3.1) 48. 8A (9.3) 54. 2A (4.6) 57. 9A (6.0) 59.1A (5.5) 1,2 (3) 18. 2A (3.8) 20.5A (5.3) 19. 4A (1.1) 21.4A (1.6) 21.5A (4.0) 1 Means within a row with different letters indicate a significant difference (P<0.05). 41 controls, (Table 8) may be attributed to less shading from adjacent stems which can impair growth.. Farmer (1963) stated that light is an essential factor for good aspen growth. Although no significant differences in stem densities were observed among clipping intensities for bigtooth and quaking aspen, bigtooth aspen control plots tended to have more stems per hectare than clipped plots (Table 9). This trend was observed for 92% of the treatments the third year of the study. Only 33% of the quaking aspen plots demon­ strated this type of trend. Effects of simulated browsing on bigtooth aspen twigs showed that clipping tended to impair stem productivity. Significantly less annual production was observed on plots clipped at 25%, 50%, and 75% than controls the second year of the 1,2 year treatment. This trend was observed on 75% of the bigtooth aspen treatments (Table 10). Similar significant differences between clipped plots and controls were observed with quaking aspen (Table 10). No trend was noted, however, since half of the clipped plots had less productivity than controls and half more productivity. Less woody annual productivity on clipped bigtooth aspen plots than controls may be attributed to clipped trees also being shorter and having fewer twigs available. The presence of shorter trees with fewer twigs on clipped plots Table 9. Mean stem density per hectare (and standard error) of bigtooth and quaking aspen under various simulated browsing treatments. Values are from year 3 of the study, with the exception of plots clipped in year 1 and sampled in year 2. No significant differences (P>0.10). Simulated Intensities (% browsina trtmt. (Year No sampled) clipping 25 of annual productivity clipped) 50 75 100 ---- .-- ---— -— -— -— — -— Bigtooth aspen- -------- ---- ---------1 (3) 9630 (2901) 7000 (5172) 7494 (3333) 9296 (4061) 5592 (2567) 2 (3) 9630 (2901) 7074 (2901) 8926 (2346) 12061 (5814) 6666 (3951) 1 (2) — — — 6172 (3234) 5098 (1061) 1,2 (3) 9630 (2901) — 6630 (3209) — 3790 (3790) --------- --- -.Quaking aspen- -------------------------1 (3) 14814 (2074) 18851 (3716) 18975 (2271) 12592 (2333) 11888 (4333) 2 (3) 14814 (2074) 16703 (4839) 14938 (2864) 16333 (5753) 16136 (4346) 1 (2) — — — 11395 (3444) 15469 (3914) 1,2 (3) 14814 (2074) — 11851 (2419) — 15555 (3519) 43 Table 10. Mean annual productivity (kg/ha) (and standard error) of bigtooth and quaking aspen twigs under various simulated browsing treatments. Values are from samples clipped in year 3 of the study, with the exception of plots clipped in year 1 and sampled in year 2. Simulated Intensities (% browsing trtmt. No (Year sampled) clipping 25 of annual productivity clipped) 50 -------- ----- ---- -•--- Bigtooth aspen- 75 — 100 ------------ -— 1 (3) 124A1 (65) 43A (25) 171A (82) 62A (14) 67A (20) 2 (3) 124A (65) 88A (33) 162A (40) 118A (101) 140A (81) 1 (2) 49A (19) 13B (7) 13B (2) 18B (3) 50A (8) 1,2 (3) 124A (65) 76A (35) 48A (40) 46A (21) 104A (53) aspen*" 1 (3) 33A (12) 37A (9) 38A (7) 44A (16) 18A (1) 2 (3) 33A (12) 24A (8) 42A (5) 45A (21) 53A (25) 1 (2) 214A (99) 56B (36) 120B (31) 166AB (15) 175AB (61) 1,2 (3) 33A (12) 42A (21) 21A (3) 29A (5) 35A (11) 1 Means within a row with different letters indicate a significant difference (P<0.05). 44 allowed the twigs to grow longer than those on control plots. Twigs on control plots were subjected to more shading from adjacent twigs and therefore growth was impaired. Comparisons of stand characteristics between species showed quaking aspen had significantly more twigs available, greater stem densities, and standing heights than bigtooth aspen (Table 11). Perala (1981) also documented quaking aspen clearcuts had greater stem densities than bigtooth aspen. Bigtooth aspen, however, tended to produce more mass (kg/ha) of twigs annually than quaking aspen (Table 11). This may be attributed to bigtooth aspen also producing significantly longer, and perhaps thicker stems than quaking aspen. The significant differences observed between species were primarily within the 50% and 100% clipping treatments. Nutritional Analyses No significant differences were observed in the ash content of either bigtooth or quaking aspen twigs among simulated browsing intensities (Table 12). The ash content of these samples comprised very little of the total chemical composition (<6%) of aspen. This chemical constituent is composed of all the inorganic elements present in samples and does not identify specific elements present. Because each inorganic element comprises a minute part of the total plant composition any increase in concentrations would have 45 Table 11. Significant differences between bigtooth (BT) and quaking (Q) aspen stand characteristics under various simulated browsing treatments. Aspen stand characteristics Years clipped-% CAG1 HTS2 PRO3 LEN4 Q>BT7 1-50 1-100 DEN5 Q>BT7 BT>Q6 2-25 BT>Q6 2-50 BT>Q7 BT>Q6 1,2-50 1,2-100 Q>BT7 Q>BT7 Q>BT7 1 Mean number of current annual growth twigs available. 2 Mean standing height of trees. 3 Mean annual productivity of woody current annual growth. 4 Mean length of woody current annual growth. 5 Mean stem density. 6 Significantly different (P<0.10). 7 Significantly different (P<0.05). 46 Table 12. Mean percent ash, on dry-matter basis, (and standard error) of bigtooth and quaking aspen twigs clipped under various simulated browsing treatments. Values are from samples clipped in year 3 of the study, with the exception of plots clipped in year 1 and sampled in year 2. No significant differences (P>0.10). Simulated Intensities (% of annual productivity clipped) browsing __________________________________________________ trtmt. (Year No sampled) clipping 25 50 75 100 Bigtooth aspen1 (3) 4.8 (<1) 5.5 (1.0) 4.6 (1.0) 5.3 (1.0) 5.5 (1.0) 2 (3) 4.8 (<1) 4.8 (0.10). Simulated Intensities (% browsing trtmt. (Year No sampled) clipping 25 of annual productivity clipped) 50 75 100 1 (3) 39.3 (0.4) 43.5 (3.4) 38.3 (2.3) 42.9 (1.2) 42.2 (1.3) 2 (3) 39.3 (0.4) 42 .1 (1.4) 40.1 (1.8) 40.9 (1.3) 40.7 (2.9) 1 (2) 37.4 (2.6) 38.7 (1.4) 34.9 (1.3) 36.9 (1.9) 36.6 (0.9) 1,2 (3) 39.3 (0.4) 43.0 (1.9) 39.8 (2.6) 39.1 (1.0) 37.8 (3.2) 1 (3) 46.7 (2.3) 47.1 (0.9) 49.2 (0.6) 43.5 (2.9) 45.8 (1.2) 2 (3) 46.7 (2.3) 45.4 (2.5) 50.0 (2.1) 42.2 (2.4) 44.2 (2.0) 1 (2) 42.4 (1.7) 44.8 (2.4) 42.5 (0.3) 43.3 (2.7) 42.0 (0.4) 1,2 (3) 46.7 (2.3) 48.8 (2.6) 46.9 (3.3) 44.5 (1.5) 43.7 (1.0) 56 Table 17. Mean percent cellulose, on dry-matter basis, (and standard error) of bigtooth and quaking aspen twigs clipped under various simulated browsing treatments. Values are from samples clipped in year 3 of the study, with the exception of plots clipped in year 1 and sampled in year 2. No significant differences (P>0.10). Simulated Intensities (% of annual productivity clipped) browsing __________________________________________________ trtmt. (Year No sampled) clipping 25 50 75 100 1 (3) 29.1 (1.3) 24 .9 (3.0) 30.8 (2.6) 27.1 (2.4) 26.7 (3.8) 2 (3) 29.1 (1.3) 26.4 (1.4) 28.4 (1.7) 27.8 (1.0) 30.0 (2.1) 1 (2) 32.6 (1.2) 32.6 (1.3) 33.7 (1.0) 33.8 (1.9) 34.8 (1.0) 1,2 (3) 29.1 (1.3) 24.9 (2.2) 28.4 (2.0) 27.9 (1.0) 33.8 (3.0) 1 (3) 21.0 (6.4) 22.9 (3.8) 22.5 (1.0) 25.1 (5.0) 21.4 (1.4) 2 (3) 21.0 (6.4) 24.6 (3.7) 21.0 (1.3) 24.8 (7.1) 27.0 (3.4) 1 (2) 29.8 (2.0) 30.7 (2.6) 34.6 (1.5) 31.8 (2.6) 32.4 (1.0) 1,2 (3) 21.0 (6.4) 19.7 (3.6) 23.7 (2.1) 23.2 (3.0) 26.0 (2.3) 57 Table 18. Mean percent hemicellulose, on dry-matter basis, (and standard error) of bigtooth and quaking aspen twigs clipped under various simulated browsing treatments. Values are from samples clipped in year 3 of the study, with the exception of plots clipped in year 1 and sampled in year 2. Simulated Intensities (% browsing trtmt. (Year No sampled) clipping 25 of annual productivity clipped) 50 75 100 1 (3) 10.4A1 (2.1) 9.2AB (2.0) 10.2AB (1.1) 6.7B (1.0) 9.1AB (1.0) 2 (3) 10. 4A (2.1) 10.1A (1.0) 9.6A (1.0) 9.1A (1.1) 10. 0A (1.4) 1 (2) 11. 9A (1.8) 12.1A (1.2) 11.2A (2.8) 11. 8A (1.1) 12. 6A (1.1) 1,2 (3) 10. 4A (2.1) 9.6A (1.9) 8.7A (1.2) 11. 5A (2.1) 8.8A (1.9) 1 (3) 7.6A (1.9) 13.1A (2.0) 5.7A (1.3) 6.8A (2.5) 8.6A (2.0) 2 (3) 7.6A (1.9) 5.4A (2.0) 7.1A (1.3) 5.3A (1.3) 9.6A (1.0) 1 (2) 9.6A (2.0) 8.4A (2.2) 9.8A (2.3) 8.7A (1.9) 11. 7A (1.0) 1,2 (3) 7.6A (1.9) 5.6A (1.2) 6.5A (2.0) 8.1A (1.8) 9.1A (1.4) 1 Means within a row with different letters indicate a significant difference (P<0.10). 58 Lignin content of bigtooth and quaking aspen showed no significant differences among clipping intensities throughout the study (Table 19). However, the lignin contents of twigs on clipped plots tended to be lower than on controls for 75% and 88% of the bigtooth and quaking aspen treatments, respectively. Results of fiber analyses (cellulose, hemicellulose, and lignin) show that clipping aspen may enhance the nutritional quality of twigs. New shoots of tree species characteristically have higher contents of cell-soluble material and lower fiber values than mature trees. Although twig removal has been shown to stimulate tree production and increase nutritional quality, results from past studies indicate that clipping can become a devitalizing process if conducted too long at too great an intensity. Many species in good condition when subjected to high intensities of browsing or clipping may not show evidence of degradation for several years (Garrison 1953). Therefore, the benefits received by clipping (or browsing) trees should be monitored over time. In quaking aspen, in vitro dry matter digestibility was significantly less on plots clipped at 75% in years 2 and 1,2 than on controls (Table 20). The trend of lower digest­ ibility occurring on clipped plots than on control plots was observed for 81% of the treatments. No differences in the 59 Table 19. Mean percent lignin, on dry-matter basis, (and standard error) of bigtooth and quaking aspen twigs clipped under various simulated browsing treatments. Values are from samples clipped in year 3 of the study, with the exception of plots clipped in year 1 and sampled in year 2. No significant differences (P>0.10). Simulated Intensities (% browsing trtmt. (Year No sampled) clipping 25 of annual productivity clipped) 50 75 100 1 (3) 22.5 (2.0) 22.4 (2.2) 20.7 (1.8) 23.3 (2.2) 21.8 (2.5) 2 (3) 22.5 (2.0) 21.5 (1.0) 21.9 (1.0) 22.2 (1.7) 19.3 (1.5) 1 (2) 18.5 (1.6) 16.4 (1.0) 20.2 (1.6) 17.6 (1.6) 16.0 (1.4) 1,2 (3) 22.5 (2.0) 22 .5 (1.5) 23.3 (2.0) 21.7 (3.2) 19.3 (1.2) 1 (3) 24.7 (5.0) 22.1 (3.9) 22.6 (2.2) 22.4 (3.0) 24.2 (1.6) 2 (3) 24.7 (5.0) 24.6 (2.9) 22.4 (2.6) 28.0 (5.8) 19.3 (1.3) 1 (2) 18.6 (3.1) 16.1 (2.0) 13.1 (1.0) 16.0 (1.0) 14.0 (1.4) 1,2 (3) 24.7 (5.0) 25.9 (3.8) 23.0 (1.0) 24.3 (3.6) 21.2 (1.0) 60 Table 20. Mean percent in vitro dry matter digestibility (and standard error) of bigtooth and quaking aspen twigs clipped under various simulated browsing treatments. Values are from samples clipped in year 3 of the study, with the exception of plots clipped in year 1 and sampled in year 2. Simulated Intensities (% browsing trtmt. No (Year sampled) clipping 25 50 75 100 (<1) 38.3A (3.4) 35. 5A (2.7) 37. 6A (1.9) 37. 2A (2.3) 37.3A (<1) 35.8A (3.3) 33.1A 35. 0A (1.9) 21 .IK (Q9 2-50 LG7 BT>gl° BT>Q9 CM8 Q>BT3-1 Q>BT9 BT>Q9 BT>Q9 Q>BT 10 BT>Q10 Q>BT9 BT>Q9 2-75 2-100 Q>BT10 1,2-75 Q>BT9 BT>Q9 1,2-100 Q>BT9 BT>Q10 _ 1-25 | a a » » « Q>BT 10 r k i ■■ q >BT10 Q>BT9 1-50 1-75 HM6 BT>Q9 BT>Q9 1-100 BT>Q10 2-25 CE5 BT>Q10 BT>Q9 BT>Q9 Q>BT10 1-100 b t >q !° 2-25 Q>BT9 Q>BT9 1,2-25 1,2-50 q >b t 1;l 1,2-75 Q>BT10 1,2-100 Q>BT9 63 Table 21. (cont'd.) 1 Mean percent crude protein 2 Mean percent phosphorus 3 Mean percent ether extract 4 Mean percent in vitro dry matter digestibility 5 Mean percent cellulose 6 Mean percent hemicellulose 7 Mean percent lignin 8 Mean percent cell-soluble material 9 Significantly different (P<0.10). 10 Significantly different (P<0.05). 11 Significantly different (P<0.01). 64 bigtooth aspen leaves was significantly greater on plots with 25% of the woody current annual growth clipped than on those clipped at 50% (Table 22 Appendix). The ether extract of bigtooth aspen leaves was also significantly greater on plots clipped at 50% than those clipped at 75% and 100% (Table 25 Appendix). The few differences which were detected were probably due to random chance at the probability level used. The study was not initially designed to investigate effects of simulated browsing on leaf production and nutritive quality so control plots for this treatment were unavailable. Significant differences in chemical constituent levels of leaves between species were similar to those observed with twigs (Table 21). Quaking aspen had greater concentrations of ether extract, cell-soluble material, and lignin than bigtooth aspen. Results of chemical analyses indicate that aspen leaves were generally of good nutritional quality. Tew (1970) investigated the nutritional quality of aspen leaves and documented summer crude protein, fat, and ash contents of 13.2%, 7.8%, and 6.2%, respectively, similar to values observed in this study. Ullrey et al. (1967) documented that adequate protein levels of white-tailed deer fawns after weaning was 14-22% (dry matter basis). The protein content of leaves from both aspen species are within the range required by fawns. 65 Results indicate that simulated browsing intensities > 50% did change some stand characteristics, of primarily bigtooth aspen. Browsing intensities of this magnitude are occurring on some bigtooth aspen clearcuts in the PRCSF. The importance of these changes to some aspen stands must be evaluated relative to the various multiple use demands for the forest. Although results from the simulated browsing experi­ ments are only from the first 3 years post-harvest, it is during these initial years that twigs are most susceptible to ungulates (Westell 1954). Long-term effects of browsing pressures on aspen stand characteristics should be monitored to determine if aspen production for timber products is impaired. At this time, detrimental, long-term changes have not been shown. Simulated browsing information indicates that "browsing" of aspen did not appear to decrease the nutritional quality of aspen browse. The selective browsing which occurred on bigtooth aspen may be attributed to its nutritional quality. One of the primary chemical constituents responsible for the differential browsing between species may be the ether extract component. Future research should investigate the composition of the ether extract component of each species especially with regards to secondary plant compounds and if their concentrations change with respect to browsing intensities. It is also unknown how heavily aspen leaves are utilized by ungulates in PRCSF. Future research may address this question in addition to quantifying effects of ungulate foraging on leaf production and nutritive qualities. Researchers have documented increased concentrations of phenolic compounds in leaf extracts of Populus x euroamericana ramets with leaf tissues damaged and in control plants (Baldwin and Schultz 1983). They suggested that an airborne cue originating in damaged tissues may stimulate biochemical changes in surrounding plants. plant response of this type may influence how heavily ungulates forage on aspen leaves. A EFFECTS OF DEER AND ELK BROWSING ON THE COMPOSTION AND STRUCTURE OF REGENERATING ASPEN FOLLOWING CLEARCUTTING Introduction The PRCSF and surrounding lands in Michigan are managed by the Michigan Department of Natural Resources for multiple use benefits. Two primary objectives are the production of timber products and the supply of wildlife recreational opportunities. The PRCSF, comprising an area of 39,000 ha, includes approximately 12,000 ha of aspen-dominated vegetation, an elk herd of approximately 300 animals, and an estimated white-tailed deer density of 10 per sg. km (D. Whitcomb, pers. comm.). Aspen is not only valuable because of its economic importance to the wood products industry and as an energy resource, but also for the forage and cover it provides to a variety of wildlife species (Barnes 1966, Young 1974). The highest production of white-tailed deer in Michigan has typically been found in aspen dominated areas (Byelich et al. 1972) . In the Lake States, aspen provides food and/or cover for white-tailed deer, elk, ruffed grouse, snowshoe hare, and a host of nongame species. Both white-tailed deer and elk are currently managed within the PRCSF by manipulating population sizes and structure, and through management of habitat. In the early 1960's the elk herd had grown to a density of 5-10 animals 67 68 per sq mi. and was responsible for damage to forest regeneration on parts of the Pigeon River, Black Lake, Hardwood, and Thunder Bay state forests. Browsing and breakage of aspen sprouts by elk and deer were observed in winter, 1963-64 and were considered to represent poor range conditions (Moran 1973). Spiegel et al. (1963) noted that at the existing browsing intensities, young aspen clearcuts would be converted to grasslands. In 1964 and 1965 controlled elk hunts were conducted in an effort to reduce the population and alleviate depredation problems. These hunting seasons were successful in reducing crop and forest damage complaints (Elk Management Plan 1984). The elk population, however, continued to decline reaching a low in 1975. Increased protection from hunting, poaching, and an increase in habitat management during the 1970!s produced an increase in the elk herd to approximately 850 animals by the winter of 1984. Once again, concerns of crop damage and forest regeneration problems, primarily due to elk foraging, started occurring. Of the total number of elk, however, only approximately 308 occurred in the PRCSF (T. Carlson, pers. comm.). Large mammalian herbivores, such as deer and elk, can strongly impact the structure, composition, and rate of succession in plant communities (Dinesman 1967, Adams 1975, 69 Crawley 1983, Risenhoover and Maass 1987). Therefore, these effects are of great importance, and many times a problem, to ecologists and land managers responsible for the management of natural resources. The objective of this experiment was to quantify the effects of ungulates on the composition and structure of various age classes of bigtooth and quaking aspen clearcuts. 70 Methods Experimental Design To assess the impacts of deer and elk browsing on the composition and structure of regenerating bigtooth and quaking aspen, ungulate-proof exclosures were constructed in stands of both aspen species of 3 different post-clearcut age classes. post-harvest. The age classes studied were 1, 2, and 3 years Exclosures were replicated for each species and stand age, so a total of 18 exclosures were constructed. All exclosures were constructed on sites within each clearcut which most represented the composition and structure of the stand at that time. Each exclosure was constructed using 16-3.7 m cedar posts and light gauge mesh wire. Two strands of 9 gauge wire were placed around each exclosure, 1 at the bottom and 1 at approximately 1.5 m for support. The dimensions of each exclosure were 20 m x 20 m x 2.1 m. Control areas, open to ungulate browsing, of similar vegetative composition and structure as within the exclosures, were also delineated on each clearcut. Comparisons could then be made between similar areas in each clearcut. This allowed the impact of ungulate browsing on the composition and structure of vegetation to be identified. Vecretative Measures To estimate the influences deer and elk had on the composition and structure of aspen clearcuts, appropriate 71 sampling techniques were used to measure vegetation within exclosures and on respective areas open to browsing. The line intercept method (Canfield 1941) was used to measure vertical cover above line intercepts within 3 height strata. The height strata used were 0-0.5 m, 0.5-2.0 m, and >2.0 m. The location of each line transect was randomly selected and for each stratum the intercept of any vegetation was recorded. centimeter. All intercepts were measured to the nearest Gaps in vertical cover <10 cm were ignored. Horizontal cover estimates were made with a profile board as described by Gysel and Lyon (1980). The height strata used were 0-0.5 m, 0.5-1.0 m, 1.0-1.5 m, 1.5-2.0 m, and 2.0-2.5 m. The locations of all profile board sampling points were randomly located within the exclosures and browsed areas. The height strata selected for vertical and horizontal cover estimates were chosen based on the growth forms of vegetation and structural requirements of deer and elk. The density of aspen and other primary browse species was determined by conducting complete counts of each species within the exclosures and delineated areas open to browsing. The densities of additional woody species and frequencies of herbaceous species were determined using nested quadrats. These were randomly located within the exclosures and browsed areas. Densities of woody species were determined 72 for each of the 3 size classifications used to measure vertical cover. Sample sizes were determined to provide a 90% confidence level with a 10% allowable error around the mean (Freese 1978). Data Analyses Equality of variances was tested with an F test (Steel and Torrie 1980) and, if necessary, arcsin transformations were conducted. Measures of vegetative composition and structure were compared between exclosures and areas open to browsing using paired t-tests (Steel and Torrie 1980) or the nonparametric sign test (Siegel 1956), depending on the scale of measurement. 73 Results and Discussion Mean stem densities of 63% of the woody species > 0.5m in quaking and bigtooth aspen clearcuts tended to be greater in exclosures than in areas open to ungulate browsing. Stems of 63% of the woody species < 0.5m in height tended to be greater in areas open to browsing than within exclosures (Tables 31 - 36 Appendix). The most significant differences in stem densities between exclosures and browsed areas occurred in the youngest clearcuts (4 growing seasons) of both quaking and bigtooth aspen (Tables 31 and 34 Appendix). The majority of significant differences in stem densities occurring in this age class of clearcuts may be attributed to greater browsing pressure (Table 1). Exclosures were constructed on these clearcuts during their first growing season, whereas on 6-year-old clearcuts, exclosures were constructed after their second growing season. By constructing exclosures on stands at an earlier age, suckers were protected during the time of greatest utilization and therefore, demonstrated the most differences in stem densities. Ideally, more exclosures should have been constructed the first year of the study and monitored for 6 years. Significantly greater stem densities of aspen and red maple in the upper 2 height strata (0.5-2.0m and >2.0m) of exclosures than in browsed areas were caused by these 74 species being protected from browsing (Tables 31, 32, and 34 Appendix). Significantly greater stem densities of juneberry, black cherry, and beech in areas open to browsing in the lowest stratum may be attributed to the more open canopy allowing for the development of these species. An important question for wildlife biologists and foresters, if multiple use of a specific area is desirable, is: What is the allowable browsing intensity in young stands of aspen? In very dense stands tree growth and development may decrease with age because of intense competition, especially in stands not subjected to ungulate browsing. Jones (1976) documented that 40% of the aspen suckers in his Arizona plots died within 4 years. Bartos and Mueggler (1982) reported a decline of stems from 44,000/ha at 2 years to 25,000/ha at 3 years. in stem density in 1 year. This represented a 44% reduction In order for ungulate browsing to impact the final stocking density of stands at harvest, browsing must reduce stem density below that of natural thinning. Therefore, a large amount of aspen reproduction may be available to ungulates on some clearcuts without causing injury to future forest products. DeByle (1985) stated that even-aged stands of aspen can withstand considerable tree loss during the early years, as long as a minimum of 1,000 well-formed stems/ha reach 4 m in height. Graham et al. (1963) suggested a minimum initial stocking of 2,429 suckers/ha to be necessary to produce a mature, fully stocked stand. If 243 trees/ha reach 10 cm dbh, a fully stocked stand will generally result (Westell 1954). Crouch (1983) concluded that 2,834 stems/ha after 7 growing seasons would provide enough for a new commercial stand. After 6 growing seasons bigtooth aspen and quaking aspen had 3 and 7 times the stems, respectively, recommended by Crouch (1983) on areas open to browsing. If the current trend of reduced browsing with increase age continues, it seems that the current ungulate browsing in northern Michigan may not adversely affect the density of stems in older stands. However, this conclusion should be viewed with caution since the potential long-term effects of mortality due to increased incidence of disease due to elk damage has not been quantified in the PRCSF (Hart et al. 1985, Hart et al. 1986). As with stem densities, 4-year-old clearcuts had the greatest number of significant differences in vertical cover between exclosures and areas open to browsing (Table 37). Cover > 0.5 m in height was significantly greater in ex­ closures than areas open to browsing for both aspen species. In 5-year-old quaking aspen clearcuts, cover > 2.0 m was also significantly greatest in exclosures. No differences were observed between treatments for the <0.5 m stratum. Horizontal cover > 0.5 m, like vertical cover, was significantly greater for bigtooth and quaking aspen in 76 Table 37. Mean percent vegetative cover (and standard error) for height strata in exclosures and areas open to ungulate browsing on 4-, 5-, and 6-year-old bigtooth and quaking aspen clearcuts (1986). Stratum Age classes Exclosures Browsed Bigtooth aspen-< 0.5m 4 5 6 95.5(1.0) 85.5(12.5) 95.4(3.0) 96.2(1.0) 93.5(5.8) 96.3(1.2) 0.5-2.0m 4 5 6 86.2(6.3) A 90.6(5.2) 87.6(7.1) 55.9(9.2) 83.1(1.5) 82.8 (2.8) > 2. 0m 4 5 6 33.9(10.0) A 37.0(12.5) 40.5(11.0) 4.4 (2.6) 30.0(3.5) 36.4(3.8) < 0. 5m 4 5 6 81.8(1.9) 94.0(2.6) 99.2(0.3) 82.6(3.2) 95.7(1.2) 96.8(1.7) 0.5-2.0m 4 5 6 89.2(1.6) B 84.4(6.8) 86.7(4.5) 58.2 (2.2) 72.9(2.0) 79.8(2.0) >2. 0m 4 5 6 34.8(3.9) B 36.0(8.4) A 62.6(7*9) 4.0(1.3) 14.7(4.0) 43.1(15.4) A Significantly different (P<0.10) from browsed. B Significantly different (P<0.05) from browsed. 77 exclosures than in browsed areas (Table 38). Six-year-old quaking aspen clearcuts had the least significant differences between treatments and 6-year-old bigtooth aspen clearcuts the most. These results may be attributed to bigtooth aspen being selectively browsed more than quaking aspen (Table 2) and thus having a greater impact on vegetative structure. No differences in horizontal cover <0.5 m were observed between exclosures and areas open to browsing (Table 38). Absolute and relative frequency estimates showed few significant differences in vegetative composition between exclosures and browsed areas (Tables 39 - 44 Appendix). Frequencies of some herbaceous species tended to be lower in exclosures than in areas open to browsing. In 1984, 37% of the herbaceous species occurring in all age classes of bigtooth and quaking aspen clearcuts tended to be more frequent in browsed areas than in exclosures. In 1985, this percentage increased to 50% of all species observed in clearcuts of both bigtooth and quaking aspen. years after most exclosures were constructed, In 1986, 4 the percentage of herbaceous species that had greater frequencies in browsed areas increased to 52%. Similar results have been documented by Edgerton (1987) who concluded that deer and elk browsing in clearcuts did prevent shrub establishment and favored the development of herbaceous species. These 78 Table 38. Significant differences in horizontal cover for height strata between exclosures and areas open to ungulate browsing on 4-, 5-, and 6-year-old bigtooth and quaking aspen clearcuts (1986). Age classes Stratum 4 5 6 -------------- ---------— Bigtooth aspen-- *— --- ------------< 0. 5m NSD1 0.5-1. Orn NSD NSD NSD Excl > Br3 Excl > Br3 1.0-1.5m Excl > Br4 NSD Excl > Br4 1.5-2.0m Excl > Br4 Excl > Br2 Excl > Br2 2.0-2.5m Excl > Br4 NSD Excl > Br2 aspen-"**"””"""< 0.5m NSD NSD NSD 0.5-1.0m NSD NSD NSD 1.0-1.5m Excl > Br2 Excl > Br3 NSD 1.5-2.0m Excl > Br3 Excl > Br4 NSD 2.0-2.5m Excl > Br2 Excl > Br3 Excl > Br4 1 No significant differences (P>0.10) between exclosures and areas open to browsing. 2 Significantly different (P<0.10). 3 Significantly different (P<0.05). 4 Significantly different (P<0.01). 79 effects have been documented by various researchers to be important in influencing the composition of the understory of later successional stages (Ratcliff 1941). As stated by DeByle (1985) the physiological effect of browsing on woody plants differs if they are repeatedly browsed during the growing season than if browsed while dormant. Removal of significant portions of plants during the growing season has the greatest impact on young trees. Carbohydrate reserves are at their lowest at this time (Schier and Zasada 1973). In contrast, browsing during the winter, or dormant season, may affect growth form and size but is less likely to kill trees. be a pruning process. Winter browsing tends to This browsing, however, may cause shrubby growth forms to develop. Such results were displayed in simulated browsing studies conducted in the PRCSF. Clipping woody current annual growth in the winter significantly affected tree height, number of twigs available, and the amount of woody annual productivity. Stem densities, however, were not significantly affected by clipping. Beyer (1987) stated that radio-collared elk used 0-5year-old regenerating stands, primarily aspen, relatively little in the PRCSF except for in 1985. During this year, cows spent approximately 9% of their time in 0-5-year-old aspen stands. Of these locations, 81% were found within 3 80 stands. All 3 were 1-year-old or less and were located within the home ranges of several radio-collared elk cows. He concluded that elk were able to utilize a majority of the available browse in these stands in a relatively short period of time. Due to the time of year that ungulates, primarily elk, utilize aspen, it does not appear that browsing within the PRCSF is impacting overall aspen stem density. Ungulate use may, however, be impacting stand structure and/or resulting tree form and herbaceous species composition on many new clearcuts. The greater vertical and horizontal cover in exclosures was probably attributable to protection of vegetation from ungulate browsing. The development of vegetation in the upper height strata within exclosures may have shaded understory vegetation and thus impaired its development. McConnell and Smith (1970) demonstrated that the production of herbaceous understory vegetation does vary inversely with overstory. This type of overstory-understory relationship is considered a typical ecological habitat response. MANAGEMENT RECOMMENDATIONS Evaluations of deer and elk use of aspen clearcuts were conducted to assess ungulate - aspen interactions so both quality habitat for ungulates and other multiple use objectives could be achieved. Identified problems can then be addressed through the formulation or modification of management plans. Habitat use by elk on managed forest lands includes using forage areas close to vegetation types that moderate climatic conditions and provide security needs. Silvi­ cultural techniques may be implemented to provide these requirements and simultaneously minimize heavy browsing on aspen shoots. Such alternatives may be to alter clearcut shape, size, number, and distribution, particularly for bigtooth aspen stands. Clearcutting various age classes of aspen in "strips" radiating away from wintering areas may minimize ungulate use on stands in some areas. Managers may also choose to minimize slash or heavy cover on the edges of clearcuts close to roads to reduce the amount of available cover. By providing less cover on the edges, ungulates may feel more vulnerable to traffic and be less apt to travel into clearcuts and forage. In addition, managers should monitor browsing intensities in clearcuts throughout the elk range. Where browsing pressures exceed 50%, managers need to consider the 81 82 potential effects of this browsing on stand composition and structure. If expected effects are felt to conflict significantly with other multiple use objectives, management alternatives can be considered. Cutting additional aspen or creating early successional stages in other vegetation types in the area could reduce browsing intensities. Creating favorable habitat in other areas through management for early successional stages may also disperse ungulate foraging pressures and reduce browsing damage on stands where regeneration problems may occur. In addition to silvicultural methods, harvest strategies to achieve ungulate populations of desired size and distribution can be developed. This may be accomplished by restricting hunters to areas where browsing damage is occurring. However, herd densities within the PRCSF at the time of this study were not considered to be excessively high. In addition, elk move considerable distances in the PRCSF. Because of these factors, decisions on further herd reductions must be weighed with other management priorities and with herd objectives. Reducing present ungulate numbers may not substantially reduce browsing pressure in some localized areas and may produce a conflict with other herd management objectives. In these areas, increased attention towards silvicultural options is warranted. On forested lands where managers wish to maintain ungulate populations they may have to accept heavy browsing 83 pressure on some stands. Even with low populations of deer and elk the composition and structure of some stands may be affected by ungulate concentrations. Although these animals may have significant impacts on specific stands the effects they have on the entire forest may be negligible. Quaking and bigtooth aspen are important for multiple resource benefits in the PRCSF. Browsing is influencing stand composition and structure, especially for bigtooth aspen in some areas. However, at this time, browsing pressure does not appear to be heavy enough to reduce stem densities below levels needed to produce marketable timber products except in a few local areas. Stands should continue to be monitored for browsing intensities and vegetation responses. The effects of ungulates on aspen should be considered when developing habitat and population management recommendations. The ultimate solution in the PRCSF must be a combination of silvicultural options and the management of herd sizes. Without carefully considering both options, maximum multiple use benefits will not be realized. APPENDIX 84 Table 22. Mean percent ash, on dry-matter basis, (and standard error) of bigtooth and quaking aspen leaves removed from twigs subjected to various simulated browsing treatments. Values are from samples collected the summer following the respective twig clipping. Intensities (% of woody annual productivity clipped) Years clipped 50 25 --------------- .— 75 — .— ..- Bigtooth aspen----- -— — 100 _ _ ------------- 1 6 .9(0.3) A2 5.8 (0.2)B 6.4(0.1)AB 6.3(0.1)AB 2 7 .1 (0 .2) A 6.4(0.1)A 6.5(0.4)A 7.3 (0.5)A 1, SNA1 2 7.2(0.4)A SNA SNA 6.2 (0.2)A V u c ijv j n i y 6.5(0.1)A a s p SNA 6 .1 (0 .5) A e n 1 5.7(0.3)A 6.7(1.5)A 5 .7 (1. 6) A 5.7(0 .3)A 2 6 .6(0.5)A 6.8(0.3)A 6.7(0.1)A 6.3(0.4)A If 2 SNA 6.3(0.2)A SNA 7.0(0.2)A SNA 7.0(0.8)A SNA 6.7(0.2)A 1 Samples not analyzed. 2 Means within a row with different letters indicate a significant difference (P<0.05). 85 Table 23. Mean percent crude protein, on dry-matter basis, (and standard error) of bigtooth and quaking aspen leaves removed from twigs subjected to various simulated browsing treatments. Values are from samples collected the summer following the respective twig clipping. No significant differences (P>0.10). Intensities (% of woody annual productivity clipped) Years clipped 25 50 75 100 a&j^cir 1 14.8(1.0) 14.3(0.6) 15.1(0.2) 14.4(0.2) 2 16.4(2.1) 15.6(2.2) 14.8(1.1) 15.5(1.8) SNA SNA SNA 1/ SNA1 2 15.6(0.3) 14.2(1.2) 15.2(0.9) 15.1(1.1) 1 13.3 (1.4) 12.8(1.4) 13.2(0.8) 13.2(1.4) 2 13.7(1.0) 14.7(1.9) 13.7(0.8) 14.3(0.6) If 2 SNA 15.2(1.1) SNA 16.5(1.0) 1 Samples not analyzed. SNA 15.7(0.9) SNA 14.3(1.8) 86 Table 24. Mean percent phosphorus, on dry-matter basis, (and standard error) of bigtooth and quaking aspen leaves removed from twigs subjected to various simulated browsing treatments. Values are from samples collected the summer following the respective twig clipping. No significant differences (P>0.10). Intensities (% of woody annual productivity clipped) Years Clipped 25 50 --------------------- 75 100 Bigtooth aspen— — -------------- 1 0.20(0.03) 0.20(0.02) 0.22(0.03) 0.21(0.04) 2 0.34(0.08) 0.32(0.08) 0.27(0.05) 0.28(0.01) SNA SNA SNA 0.30(0.04) 0.31(0.06) 0.33(0.05) 1, 2 SNA1 0.33(0.05) ------------------------Quaking aspen--------------------1 0.16(0.01) 0.17(0.02) 0.17(0.02) 0.17(0.01) 2 0.26(0.02) 0.28(0.05) 0.27(0.01) 0.28(0.03) 1, 2 SNA 0.31(0.03) SNA 0.34(0.03) 1 Samples not analyzed. SNA 0.30(0.03) SNA 0.30(0.03) 87 Table 25. Mean percent ether extract, on dry-matter basis, (and standard error) of bigtooth and quaking aspen leaves removed from twigs subjected to various simulated browsing treatments. Values are from samples collected the summer following the respective twig clipping. Intensities (% of woody annual productivity clipped) Years clipped 25 ------- --------- 50 75 100 — - Bigtooth aspen---------- — ---------- 1 1. 2 (0 .1) A2 5. 5 (1. 7) A 4.9 (0.7)A 4 .0(2 .0) A 2 5 .9(1.8)AB 9.8(0.6)A 4.1(1.7)B 3.9(1. 6) B If SNA1 SNA 2 3.3(1.2)A 2 .8(0.2)A —— SNA SNA 2.9(0.7)A 2 .8 (1. 4) A yUaKlIi^ * 1 5.2(1.0)A 5.4(1.4)A 4.0(0.8)A 6 .0 (0 .7) A 2 6 .6(1. 0) A 6 .8 (2 .3 )A 7 .1 (0 .5) A 8 .8 (2 .8) A 1, 2 SNA 3 .9(1.1) A SNA 5.9(0.9)A SNA 6.3(0.9)A SNA 4 .7 (0 .1) A 1 Samples not analyzed. 2 Means within a row with different letters indicate a significant difference (P<0.10). 88 Table 26. Mean percent cell-soluble material, on dry-matter basis, (and standard error) of bigtooth and quaking aspen leaves removed from twigs subjected to various simulated browsing treatments. Values are from samples collected the summer following the respective twig clipping. No significant differences (P>0.10). Intensities (% of woody annual productivity clipped) Years clipped 25 50 75 100 1 56.0(2.6) 49.4(0.6) 51.9(1.7) 51.7(1.0) 2 59.0(1.1) 58.0(2.4) 55.8(1.8) 56.0(1.4) 1/ SNA1 SNA SNA SNA 2 56.8(1.4) 56.6(0.5) 56.9(0.5) 56.7(2.4) 1 57.8(1.2) 59.1(1.9) 59.2(2.3) 58.4(1.4) 2 55.9(2.9) 58.9(2.4) 54.6(2.5) 53.5(1.0) 1/ SNA SNA SNA SNA 2 56.0(1.1) 55.1(1.7) 55.1(1.3) 54.1(3.4) 1 Samples not analyzed. 89 Table 27. Mean percent cellulose, on dry-matter basis, (and standard error) of bigtooth and quaking aspen leaves removed from twigs subjected to various simulated browsing treatments. Values are from samples collected the summer following the respective twig clipping. No significant differences (P>0.10). Intensities (% of woody annual productivity clipped) Years clipped 25 50 -— ■ Bigtooth 75 100 aSpeir"“ " " " " “ ' 1 16.8(0.4) 18.6(0.7) 16.9(0.8) 16.6(0.1) 2 14.6(1.2) 15.0(0.7) 16.2(1.5) 13.9(1.1) SNA SNA SNA 14.1(0.9) 14.8(0.3) 15.9(0.2) If 2 SNA1 15.0(1.2) clJs.i ny HSpGn—“ " 1 15.8(0.9) 16.5(1.2) 16.3(0.9) 16.5(0.7) 2 14.3(0.6) 15.6(0.4) 16.0(0.7) 14.8(1.1) 1/ SNA SNA SNA SNA 2 15.3(1.1) 14.1(0.5) 1 Samples not analyzed. 14.7(0.9) 14.3(2.3) 90 Table 28. Mean percent hemicellulose, on dry-matter basis, (and standard error) of bigtooth and quaking aspen leaves removed from twigs subjected to various simulated browsing treatments. Values are from samples collected the summer following the respective twig clipping. No significant differences (P>0.10). Intensities (% of woody annual productivity clipped) Years clipped 25 50 75 100 — — Bigtooth as p e r n —— 1 8.6(2.0) 8.7(2.5) 7.4(0.8) 8.4(0.4) 2 5.5(1.0) 4.7(0.8) 3.2(1.2) 4.0(0.9) 1, SNA1 SNA SNA 2 4.5(0.9) 4.1(1.2) 3.1(1.0) SNA 3.9(2.1) aspen---- ■-1 8.7(1.8) 7.8(1.0) 6.5(1.6) 6.4(2.0) 2 1.4(0.3) 3.0(1.1) 2.9(1.2) 2.4(0.4) If SNA SNA SNA SNA 2 3.0(1.1) 4.2(0.9) 5.3(0.7) 1.6(0.6) 1 Samples not analyzed 91 Table 29. Mean percent lignin, on dry-matter basis, (and standard error) of bigtooth and quaking aspen leaves removed from twigs subjected to various simulated browsing treatments. Values are from samples collected the summer following the respective twig clipping. No significant differences (P>0.10). Intensities (% of woody annual productivity clipped) Years clipped 25 50 75 100 -- Bigtooth asperr""“ " “ “ “ 1 22.3(3.2) 23.4(2.1) 23.8(2.0) 24.1(1.0) 2 20.8(0.1) 22.3(2.0) 25.0(2.5) 26.1(3.4) SNA SNA SNA 25.7(1.3) 24.2(1.4) 24.4(1.7) 1/ 2 SNA1 23.7(0.8) d s p e n " ” ” ""*” "’" 1 17.9(0.4) 16.6(0.2) 18.3(0.6) 19.2(2.0) 2 27.9(2.5) 24.9(4.2) 26.5(2.2) 29.3(2.9) 1/ SNA SNA SNA SNA 2 25.8(0.5) 27.3(0.5) 24.8(2.1) 31.9(5.3) 1 Samples not analyzed. 92 Table 30. Mean percent in vitro dry matter digestibility (and standard error) of bigtooth and quaking aspen leaves removed from twigs subjected to various simulated browsing treatments. Values are from samples collected the summer following the respective twig clipping. No significant differences (P>0.10). Intensities (% of woody annual productivity clipped) Years clipped 50 25 75 100 — -Bigtooth aspen----1 40.0(3.2) 37.9(1.8) 38.2(1.2) 35.9(2.6) 2 33.4(0.7) 33.5(2.2) 37.8(2.4) 38.9(2.1) SNA SNA SNA 30.9(1.0) 34.4(8.7) 36.4(3.3) 1/ 2 SNA1 36.3(2.8) yu.Qk iny aspen------1 43.4 (4.9) 43.1(1.8) 42.9(2.4) 44.2(5.2) 2 33.6(3.5) 38.8(1.7) 39.1(2.4) 37.2(1.1) 1, SNA SNA SNA SNA 2 33.9(3.0) 33.8(2.8) 35.9(2.0) 31.2(1.4) 1 Samples not analyzed. 93 Table 31. Mean stem densities per hectare (and standard error) of trees (0-0.5m, 0.5-2.Om, and >2.0m in height) in exclosures and areas open to browsing on 4-year-old bigtooth aspen clearcuts (1986). Treatments Species Stratum(m) Exclosures Browsed Bigtooth aspen Pooulus crrandidentata 0-0.5 0.5-2.0 >2.0 130(67) 6867(1716) 7400(1750) A Red maple Acer rubrum 0-0.5 0.5-2.0 >2.0 1867(898) 533(176) 200(116) June berry 0-0.5 Amelanchier soo. 0.5-2.0 >2.0 733(353) 400(200) 67(67) 133(67) 9230(5133) 1950(1098) 1317(421) 767(385) 0(0) A 1783(631) 217(117) 0(0) Quaking aspen P. tremuloides 0-0.5 0.5-2.0 >2.0 330(330) 1667(1473) 667(667) 550(347) 5133(4000) 1867(1398) Pin cherry Prunus oensvlvanica 0-0.5 0.5-2.0 >2.0 400(306) 267(267) 133(67) 133(67) 0(0) 0(0) Red oak Ouercus rubra 0-0.5 0.5-2.0 >2.0 267(67) 67(67) 0(0) 850(293) 83(83) 67(67) Speckled alder Alnus rucrosa 0-0.5 0.5-2.0 >2 .0 67(67) 667(667) 0(0) 0(0) 0(0) 0(0) Sugar maple A. saccharum 0-0.5 0.5-2.0 >2.0 0(0) 667(667) 0(0) 67(67) 0(0) 0(0) Common witch-hazel 0-0.5 0.5-2.0 Hamamelis >2.0 viroiniana 67(67) 133(133) 0(0) 67(67) 133(133) 0(0) 0-0.5 0.5-2.0 >2.0 330(176) 1200(504) 0(0) Black cherry P. serotina B 1233(318) 433 (234) 0(0) 94 Table 31. (cont'd.) Treatments Species Stratum(m) White birch 0-0.5 Betula oaovrifera 0.5-2.0 >2.0 Exclosures Browsed 133(133) 133(133) 0(0) 0(0) 0(0) 0(0) Hawthorn Crataecrus soo. 0-0.5 0.5-2.0 >2.0 0(0) 67(67) 0(0) 0(0) 0(0) 0(0) White pine Pinus strobus 0-0.5 0.5-2.0 >2.0 0(0) 67(67) 0(0) 0(0) 83 (83) 0(0) A B Significantly different (P<0.10) from browsed. Significantly different.(P<0.05) from browsed. 95 Table 32. Mean stem densities per hectare (and standard error) of trees (0-0.5m, 0.5-2.0m, and >2.0m in height) in exclosures and areas open to browsing on 5-year-old bigtooth aspen clearcuts (1986). Treatments Species Stratum(m) Bigtooth aspen Pooulus arandidentata 0-0.5 0.5-2.0 >2 .0 Red maple Acer rubrum 0-0.5 0.5-2.0 >2.0 Exclosures 67(67) 9800(1060) 16267(5580) Browsed 67(67) 11067(6397) 13133(2578) 2867(334) 267(154) A 200(200) 2667(1464) 2000(1156) 133(133) 0-0.5 June berry Amelanchier son. 0.5-2.0 >2.0 1933(942) 600(200) 133(133) 933(521) 2000(1156) 0(0) 0-0.5 Beech Faaus arandifoliaO.5-2.0 >2.0 2267(1977) A 533(533) 0(0) 67(67) 0(0) 0(0) 0(0) 0(0) 0(0) 0(0) 0(0) 0(0) Pin cherry Prunus pensvlvanica 0-0.5 0.5-2.0 >2 .0 Red oak Ouercus rubra 0-0.5 0.5-2.0 >2.0 Sugar maple A. saccharum 0-0.5 0.5-2.0 >2.0 0(0) 0(0) 0(0) 67(67) 0(0) 0(0) White oak 0. alba 0-0.5 0.5-2.0 >2.0 333(333) 0(0) 0(0) 200(116) 267(154) 0(0) Black cherry P. serotina 0-0.5 0.5-2.0 >2.0 2533(1836) 3800(3039) 67(67) 2933(1880) 1867(1079) 0(0) 667(481) 200(116) 200(116) A 1467(812) 67(39) 0(0) 96 Table 32. (cont'd.) Treatments Species Stratum(m) Exclosures Browsed White birch 0-0.5 Betula papvriferaO.5-2.0 >2.0 0(0) 0(0) 0(0) 67(67) 0(0) 0(0) Hawthorn Crataecms sod. 0-0.5 0.5-2.0 >2.0 0(0) 0(0) 0(0) 267(267) 67(39) 0(0) White pine Pinus strobus 0-0.5 0.5-2.0 >2.0 67(67) 267(176) 0(0) 0(0) 67(39) 0(0) A Significantly different (P<0.10) from browsed. 97 Table 33. Mean stem densities per hectare (and standard error) of trees (0-0.5m, 0.5-2.0m/ and >2.0m in height) in exclosures and areas open to browsing on 6-year-old bigtooth aspen clearcuts (1986). No significant differences (P>0.10). 1 Treatments Species Stratum(m) Bigtooth aspen Ponulus crrandidentata 0-0.5 0.5-2.0 >2.0 0(0) 3467(787) 7867(1624) 67(67) 4000(462) 8467(752) Red maple Acer rubrum 0-0.5 0.5—2.0 >2 .0 0-0.5 0.5-2.0 >2.0 1000(417) 533(176) 0(0) 1667(353) 1133(353) 0(0) 933 (467) 733(372) 67(67) 1800(347) 667(241) 0(0) Red oak Ouercus rubra 0-0.5 0.5-2.0 >2.0 1600(644) 133(67) 200(200) 1867(467) 67(67) 0(0) Black cherry Prunus serotina 0-0.5 0.5-2.0 >2.0 3733(2547) 1200(504) 200(200) 2800(438) 7333 (2469) 67(67) Hawthorn Crataecrus 0-0.5 0.5—2.0 >2.0 0(0) 0(0) 0(0) 0(0) 67(67) 0(0) 0-0.5 0.5-2.0 >2.0 0(0) 0(0) 0(0) 0(0) 67(67) 0(0) June berry Amelanchier son. sod White pine Pinus strobus . Exclosures Browsed 98 Table 34. Mean stem densities per hectare (and standard error) of trees (0-0.5m, 0.5-2.0m, and >2.0m in height) in exclosures and areas open to browsing on 4-year-old quaking aspen clearcuts (1986). Treatments Exclosures Species Stratum(m) Quaking aspen 0-0.5 0.5—2.0 >2.0 200(200) B 7800(970) 7200(2400) B 0-0.5 0.5-2.0 >2.0 0-0.5 0.5-2.0 >2.0 3200(800) 200(200) 0(0) 0(0) 800(380) B 0(0) 857(460) 142(142) 0(0) 143(143) 0(0) 0(0) Black cherry Prunus serotina 0-0.5 0.5-2.0 >2.0 600(400) 800(200) A 0(0) B 1857(739) 2143(801) 428(298) Bigtooth aspen P. crrandidentata 0-0.5 0.5-2.0 >2.0 200(200) 200(200) 0(0) P o d u Iu s tremuloides Red maple Acer rubrum June berry Amelanchier sod . A Significantly different (P<0.10) from browsed. B Significantly different (P<0.05) from browsed. Browsed 714(280) 5857(1058) 2714(1065) 0(0) 0(0) 0(0) 99 Table 35. Mean stem densities per hectare (and standard error) of trees (0-0.5m, 0.5-2.0m, and >2.0m in height) in exclosures and areas open to browsing on 5-year-old quaking aspen clearcuts (1986). No significant differences (P>0.10). Treatments Species Stratum(m) Quaking aspen Pooulus tremuloides 0-0.5 0.5-2.0 >2.0 200(200) 5200(873) 9667(2717) Red maple Acer rubrum 0-0.5 0 o5—2•0 >2.0 867(438) 467(372) 267(267) 1023(177) 177(96) 167(167) 0-0.5 0.5-2.0 >2 .0 933(200) 400(231) 0(0) 1323(953) 533(533) 0(0) Beech Facms arandifolia 0-0.5 0.5-2.0 >2.0 933(933) 1533(1533) 133(133) 510(248) 400(400) 0(0) White ash Fraxinus americana 0-0.5 0.5-2.0 >2.0 0(0) 400(400) 0(0) 67(67) 533(533) 0(0) Red oak Ouercus rubra 0-0.5 0.5-2.0 >2.0 67(67) 0(0) 0(0) 177(96) 0(0) 0(0) Sugar maple A. saccharum 0-0.5 0.5-2.0 >2.0 333(333) 467(467) 0(0) 267(267) 67(67) 0(0) Balsam fir Abies balsamea 0-0.5 0.5-2.0 >2.0 0(0) 868(868) 0(0) 400(400) 67(67) 0(0) Flowering dogwood 0-0.5 0. 5-2.0 Cornus florida >2.0 200(200) 133(133) 0(0) 0(0) 0(0) 0(0) June berry Amelanchier sod. Exclosures Browsed 177(96) 8477(2182) 5657(1924) 100 Table 35. (cont'd.) Treatments Species Stratum(m) White birch 0-0.5 Betula oanvrifera 0.5-2.0 >2.0 Exclosures 0(0) 0(0) 0(0) Browsed 67(67) 0(0) 0(0) Hawthorn Crataecrus son. 0-0.5 0.5-2.0 >2.0 0(0) 67(67) 0(0) 123(62) 0(0) 0(0) White pine Pinus strobus 0-0.5 0.5-2.0 >2.0 0(0) 67(67) 0(0) 277(160) 0(0) 0(0) Common witch-hazel 0-0.5 Hamamelis 0. 5—2.0 >2.0 vircriniana 200(200) 0(0) 0(0) 0(0) 57(57) 0(0) Speckled alder Alnus rucfosa 67(67) 400(306) 0(0) 133(133) 133(133) 0(0) 0(0) 0(0) 0(0) 400(400) 0(0) 0(0) 0-0.5 0.5-2.0 >2.0 0-0.5 Red-osier dogwood 0.5-2.0 C. stolonifera >2.0 Others 0-0.5 0.5-2.0 >2.0 0(0) 67(67) 0(0) 67(67) 57(57) 0(0) 101 Table 36. Mean stem densities per hectare (and standard error) of trees (0-0.5m, 0.5-2.0m, and >2.0m in height) in exclosures and areas open to browsing on 6-year-old quaking aspen clearcuts (1986). No significant differences (P>0.10). Treatments Species Stratum(m) Exclosures Browsed 0-0.5 0.5-2.0 >2.0 67(67) 7667(1858) 15730(3842) 333(333) 8733(4567) 9933(5050) 0-0.5 0.5-2.0 >2.0 4400(4105) 1200(612) 400(231) 9133(8544) 800(462) 133(67) 0-0.5 June berry Amelanchier son. 0.5-2.0 >2.0 333(133) 600(306) 67(67) 467(267) 600(400) 0(0) Beech Faaus arandifolia 0-0.5 0.5-2.0 >2 .0 67(67) 333(333) 0(0) 267(267) 67(67) 0(0) White ash Fraxinus americana 0-0.5 0.5—2•0 >2.0 67(67) 0(0) 0(0) 0(0) 0(0) 0(0) Red oak Ouercus rubra 0-0.5 0.5-2.0 >2.0 333 (241) 67(67) 0(0) 733(637) 0(0) 0(0) Sugar maple A. saccharum 0-0.5 0.5-2.0 >2.0 0(0) 0(0) 67(67) 133(77) 67(67) 67(67) Balsam fir Abies balsamea 0-0.5 0.5-2.0 >2.0 200(200) 267(267) 0(0) 1067(970) 333 (333) 0(0) 0(0) 67(67) 0(0) 0(0) 0(0) 0(0) Quaking aspen PODUlUS tremuloides Red maple Acer rubrum Flowering dogwood 0-0.5 0.5-2.0 Cornus florida >2.0 102 Table 36. (cont'd.) Treatments Stratum(m) Species Exclosures Browsed 600(0) 1133(570) 0(0) Black cherry Prunus serotina 0-0.5 0.5-2.0 >2.0 400(200) 1333(1036) 67(67) Hawthorn Crataecrus 0-0.5 0.5—2 .0 >2.0 0(0) 0(0) 0(0) 200(200) 133(133) 0(0) 0-0.5 0.5-2.0 >2.0 0(0) 67(67) 0(0) 467(467) 333 (333) 0(0) 0(0) 0(0) 0(0) 0(0) 67(67) 0(0) 0(0) 333 (333) 0(0) 67(67) 0(0) 0(0) sod White pine Pinus strobus . Common witch-hazel 0-0.5 Hamamelis 0.5-2.0 >2.0 vircriniana Others 0-0.5 0.5-2.0 >2.0 103 Table 39. Mean absolute (AF) and relative frequencies (RF) and standard errors (SE) of herbaceous species in exclosures and areas open to browsing on 4-year-old bigtooth aspen clearcuts (1986). Exclosures Species Browsed AF (SE) RF (SE) AF (SE) RF (SE) Bracken fern Pteridium acruilinum 95.7 (4.3) 18.6(1.5) 97.7 (2.3) 19.2(<1) Rubus spp. 62.3 (21.1) Orange-hawkweed Hieracium aurantiacium 3.3 (3.3) Carex spp. Blueberry Vaccium ancrustifolium 38.0(17.4) 7.3(3.4) 10.0(1.7) 1.9(<1) 62.3 (19.0) 11.8(3.2) 95.3 (2.3) 18.7(d) 60.0(25.2) 5.6(4.8) 22.3(13.6) 4.6(3.0) Wild strawberry 50.0(5.8) Fractaria virainiana 9.8(1.6) 50.0(21.5) 9.8(4.2) Yellow-hawkweed H. pratense 1.2(1.2) 2.3 (2.3) <1(<1) 0(0) 0(0) 6.7 (6.7) St. John1s wart 2.3 (2.3) Hypericum perforatum Wintergreen Pyrola spp. 16.7(8.8) Wild lettuce 3.3 (3.3) Lactuca canadensis Violet Viola spp. 12.4(4.8) <1(<1) <1(<1) 3.0(1.6) 31.0(24.8) <1(<1) 7.7(3.9) 77.7(13.9)B 14.8(2.2)B 38.0(16.0) Long-leafed aster 0(0) Aster macrophvllus 0(0) 2.3 (2.3) 5.8(4.5) 1.5(d) 7.5(3.1) d(d) 104 Table 39. (cont.) Exclosures Browsed Species AF (SE) RF (SE) AF (SE) RF (SE) Bearberry Arctostaphvlos uva-ursi 16.7(16.7) 3.5(3.5) 6.7(6.7) 1.3(1.3) Grass 75.7(7.2)A 14.6(1.2)A 95.7(4.3) Sweet fern 15.7(15.7) Comptonia pereqrina 2.9(2.9) 11.0(11.0) A Significantly different (P<0.10) from browsed. B Significantly different (P<0.05) from browsed. 18.7(<1) 2.3(2.3) 105 Table 40. Mean absolute (AF) and relative frequencies (RF) and standard errors (SE) of herbaceous species in excloures and areas open to browsing on 5-year-old bigtooth aspen clearcuts (1986). No significant differences (P>0.10). Exclosures Species Bracken fern Pteridium aquilinum AF (SE) 100.0(0) RF (SE) 20.9(2.9) Browsed AF (SE) 100.0(0) RF (SE) 19.0(1.0) Rubus spp 40.0(11.6) 7.7(1.4) 66.7(18.6) 12.4(3.2) Orange-hawkweed Hieracium aurantiacium 16.7(8.8) 3.7 (2.3) 33.3(18.6) Carex spp. 96.7(3.3) 20.3(3.4) 80.0(15.3) 14.9(2.5) Blueberry Vaccium anqustifolium 43.3(17.0) 7.7(4.0) 56.7(26.1) 10.4(4.9) 20.0(20.0) Wild strawberry Fraqaria virqiniana 3.3 (3.3) 0(0) 0(0) 6.7(<1) Lilly Lilium spp, 6.7(6.7) 1.3(1.3) 0 (0 ) 0 (0 ) Bunchberry Cornus canadensis 3.3 (3.3) <1(<1) 0 (0 ) 0(0) 6.7(3.3) 1.2(d) 13.3(13.3) 2.8(2.8) Wintergreen Pvrola spp. Wild lettuce Lactuca canadensis Violet Viola spp. 36.7(21.9) 0 (0 ) 7.4(4.4) 0 (0 ) 70.0(25.2) 13.3(4.4) Long-leafed aster 10.0(6.7) Aster macrophvllus 2.3(1.6) 70.0(17.3) 13.1(3.2) 3.3(3.3) d(d) 106 Table 40. (cont.) Exclosures Browsed Species AF (SE) RF (SE) Wood betony Pedicularis canadensis 6.7(6.7) 1.1(1.1) 0(0) 0(0) 43.3(23.4) 9.8(6.3) 43.3(26.1) 8.6(5.6) 3.3(3.3) <1(<1) 16.7(12.0) 3.3(2.6) Grass Sheep sorrel Rumex acetosella AF (SE) RF (SE) Smooth aster Aster laevis 0(0) 0(0) 3.3(3.3) <1(<1) Honeysuckle Lonicera spp. 0(0) 0(0) 3.3 (3.3) <1(<1) 107 Table 41. Mean absolute (AF) and relative frequencies (RF) and standard errors (SE) of herbaceous species in exclosures and areas open to browsing on 6-year-old bigtooth aspen clearcuts (1986). No significant differences (P>0.10). Exclosures Species AF (SE) Bracken fern Pteridium acruilinum Rubus son. Orange-hawkweed Hieracium aurantiacium Carex sod . Blueberry Vaccium ancmsti folium 100.0(0) RF (SE) 27.1(2.1) AF (SE) 100.0(0) RF (SE) 29.0(2.4) 10.0(10.0) 2.3(2.3) 3.3(3.3) 1.1(1.1) 3.3 (3.3) 1.0(1.0) 6.7(3.3) 1.8(<1) 66.7(3.3) 18.5(5.4) 63.3(17.7) 18.4(5.9) 90.0(5.8) 24.2(<1) 86.7(8.8) 25.2(3.6) <1(<1) 0(0) 0(0) Wild lettuce 3.3 (3.3) Lactuca canadensis 6.4(5.1) Wintergreen Pvrola s o d . 26.7(21.9) Grass 60.0(15.3) 16.0(4.0) Sheep sorrel Rumex acetosella Browsed 0(0) 0(0) 33.3 (28.5) 8.4(7.0) 50.0(28.9) 14.2(9.0) 3.3(3.3) 1 .0(1.0) 3.3 (3.3) 1 .0(1.0) 0(0) 0(0) Yellow-hawkweed 6.7(6.7) Hieracium pratense 1.8(1.8) 0(0) 0(0) Sweet fern 3.3 (3.3) Comotonia perecrrina <1(<1) Smooth aster Aster laevis 3.3 (3.3) 1 .0(1.0) 108 Table 42. Mean absolute (AF) and relative frequencies (RF) and standard errors (SE) of herbaceous species in exclosures and areas open to browsing on 4-year-old quaking aspen clearcuts (1986). Exclosures Species AF (SE) RF (SE) 23.8(2.8) Browsed AF (SE) RF (SE) Bracken fern Pteridium acruilinum 100(3.3) Rubus spo. 60.0(6.1)A 14.3(2.4)A Orange-hawkweed Hieracium aurantiacium 90.0(3.0) Carex son. 20.0(3.8) 4.8(1.8) Blueberry Vaccium anaustifolium 20.0(3.8) 4.8(2.5) 0(0) 0(0) Wild strawberry 20.0(3.8) Fracraria vircriniana 4.8(1.5) 30.0(12.0) 6.9(4.5) 21.4(<1) 100(0) 23.3 (3.7) 90.0(1.6) 20.9(2.0) 80.0(8.8) 18.6(1.5) 20.0(3.4) 4.7(4.4) 0(0) 0(0) 10.0(3.3) 2.3(<1) Grass 80.0(8.5) 19.0(5.6) 90.0(1.6) 20.9(3.9) Ground cedar Lvconodium comolanatum 20.0(5.8) 4.8(1.8) 10.0(3.3) 2.3(<1) Starflower 10.0(3.3) Trientalis borealis 2.4(1.3) Wild lettuce Lactuca canadensis A 0(0) Significantly different (P<0.10) from browsed. 0(0) 109 Table 43. Mean absolute (AF) and relative frequencies (RF) and standard errors (SE) of herbaceous species in exclosures and areas open to browsing on 5--year-old quaking aspen clearcuts (1986). No significant differences (P>0.10). Exclosures Browsed AF (SE) RF (SE) Bracken fern Pteridium acruilinum 96.7(3.3) 17.6(2.8) 73.3(14.5) 12.7(3.7) Rubus spp. 93.3(6.7) 16.8(2.4) 80.0(11.6) 13.4(2.0) Species Orange-hawkweed Hieracium aurantiacium 3.3(3.3) <1(<1) AF (SE) 16.7(8.8) RF (SE) 2.7(1.5) Carex spp. 66.7 (33.3) 11.1(5.8) 76.7(23.4) 13.0(4.4) Blueberry Vaccium anqustifolium 30.0(17.3) 4.7 (2.5) 40.0(23.1) Wild strawberry 50.0(15.3) Fraqaria virqiniana 8.4(1.5) 83.3(12.0) 13.8(1.7) 13.3(13.3) 1.9(1.9) 13.3(8.8) 1.9(1.2) 23.4 (23.4) Bunchberry Cornus canadensis 3.2(3.2) 23.4(23.4) 3.2(3.2) 26.7(26.7) 5.1(5.1) 30.0(30.0) 6.1(6.1) 1.5(1.5) 3.3(3.3) Lilly Lilium spp. Wintergreen Pvrola spp. 6.7(6.7) Wild lettuce Lactuca canadensis 6.3 (3.3) <1(<1) Violet Viola spp. 73.0(16.7) 13.0(3.4) 63.3(17.7) 10.4(2.8) Bedstraw Galium spp. 13.3(8.8) 16.7(12.0) 2.6(2.0) 2.8(2.1) 110 Table 43. (cont'd.) Exclosures Species AF (SE) RF (SE) Browsed AF (SE) RF (SE) Thistle Carduus spp. 0(0) 0(0) 6.7(6.7) 1.1(1.1) Wood betony Pedicularis canadensis 0(0) 0(0) 3.3(3.3) <1(<1) <1(<1) 3.3(3.3) <1(0.10). Exclosures Species AF (SE) RF (SE) Browsed AF (SE) RF (SE) Bracken fern 93.3(6.7) Pteridium aauilinum 15.2(2.4) 93.3 (6.7) 16.0(2.0) Rubus spp. 83.3 (8.8) 13.9(3.2) 86.7(6.7) 14.8(1.8) Orange-hawkweed Hieracium aurantiacium 13.3(8.8) 2.4 (1.8) 13.3(13.3) 2.0(2.0) Carex spp. 90.0(5.8) 14.5(1.8) 90.0(5.8) 15.4(1.8) 10.4(1.9) 46.7(18.6) 7.8 (3.2) Wild strawberry 66.7(14.5) Fraqaria virqiniana Lilly Lilium spp. 36.7(18.6) 5.2(2.6) 36.7(20.3) 5.8(3.1) Bunchberry Cornus canadensis 36.7(13.3) 5.4(1.8) 26.7(21.9) 4.1(3.2) Wintergreen Pvrola spp. 33.4 (33.4) 4.3 (4.3) violet Viola spp. 96.7(3.3) 15.5(1.4) 6.7(3.3) <1(<1) Bedstraw Galium spp. Long-leafed aster Aster macrophvllus False Solomon's seal Smilacing racemosa 0(0) 6.7(6.7) Ground cedar 0(0) Lvcopodium complanatum 0(0) 1.0(1.0) 0(0) 33.4(33.4) 6.0(6.0) 90.0(5.8) 15.2(<1) 0(0) 3.3(3.3) 0(0) 3.3 (3.3) 0(0) <1(<1) 0(0) <1(<1) 112 Table 44. (cont'd.) 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