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Forest structure associated with ruffed grouse abundance
Forest Ecology and Management, 49 ( 1992 ) 2 ! 1-218
211
Elsevier Science Publishers B.V., Amsterdam
Forest structure associated with ruffed grouse abundance Ernie P. Wiggers a, Murray K. Laubhan a and David A. Hamilton b aSchool of Natural Resources, 112 Stephens Hall, Universityof Missouri. Cnlumbia, MO 65211, USA bMissouri Department of Conservation, Research Center, 11lO S. CollegeAve.. Columbia, MO 65201. USA (Accepted 28 March 1991 )
ABSTRACT Wiggers, E.P., Laubhan, M.K. and Hamilton, D.A., 1992. Forest structure associated with ruffed grouse abundance. For. Ecol. Manage., 49:211-218. We identified and described the occurrence and structure of habitats related to ruffed grouse (Bonasa umbellus) abundance on 11 study areas in the oak (Quercus spp.) and hickory (Carya spp.) forest association of the central US. The percent occurrence of 7- to 15-year-old hardwood regeneration was the only habitat correlated with grouse density. Structural characteristics that influenced the quality of this habitat for grouse were basal area and percent canopy closure. Basal area exhibited a positive linear relationship, whereas percent canopy closure exhibited a curvilinear relationship with grouse density. Highest grouse densities occurred where 7- to 15-year-old hardwood regeneration habitat comprised greater than 14% of the area; basal area was greater than 16.9 m 2 ha - j and canopy closure was between 70 and 89% in this habitat. Management strategies for enhancing habitat for grouse should include maintaining more than 14% of a forest in 7- to 15-year-old hardwood regeneration and maintaining a balance between partial canopy closure and high basal area within this habitat. Hardwood regeneration stands occurring on the most productive or highest quality sites probably have the greatest potential to provide habitat for grouse.
INTRODUCTION
Forest attributes such as the occurrence of different aged stands and diverse structure within and among these stands are thought to influence habitat suitability and abundance of forest-dwelling wildlife species. However, there is a paucity of information that identifies and quantifies the relationships between the amount and structure of habitats with animal abundance. One wildlife species that is dependent upon forest as habitat is the ruffed grouse (Johnsgard, 1973). The southern periphery of this bird's range includes the oak and hickory forests of the central US. Research suggests that extensively cut deciduous woodlands and even-aged regenerating stands are important habitats for ruffed grouse (White and Dimmick, 1978; Stoll et al., © 1992 Elsevier Science Publishers B.V. All rights reserved 0378-1127/92/$05.00
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1979; Thompson et al., 1987). However, neither the optimum amounts nor structural characteristics of these forest habitats have been quantified, nor have the relationships between forest structure and grouse abundance been determined. This information is essential to understand how changes in forest structure, whether by natural processes or man induced, impact grouse populations. The purpose of our study was to identify and describe habitats and structures important for ruffed grouse on areas that differentially supported grouse populations and to determine the relatit, nship between the occurrence and structure of these habitats and ruffed grouse abundance. S T U D Y A R EA S
Selection of study areas was restricted to areas where ruffed grouse releases and forest disturbance had not occurred for at least 3 years. During 1985 and 1986, we collected information on forest structure and ruffed grouse densities on 11 study areas that met these criteria. These areas ranged from 200 to 528 ha in size and were distributed within the River Hills, Ozark, and Ozark Plateau regions of Missouri (Krusekopf, 1962 ). All areas were extensively forested, and the oak and hickory association represented the dominant overstory vegetation (Laubhan, 1987 ). Topography ranged from deep hollows with narrow ridges and steep slopes in the River Hills region to hilly plateaus with deep hollows and moderate to steep slopes in the Ozark Plateau region. METHODS Ruffed grouse populations were surveyed by complete area counts of drumming males during April. Drumming count data were collected for 2 years on ten areas and for 1 year on three areas. Because forest conditions were dynamic as a result of natural succession, we restricted population surveys to years when vegetation measurements were conducted. Survey routes were established on ridges and in hollows on each area so drumming by grouse could be detected at the greatest distance and in as many directions as possible. Personnel paused and listened for drumming for 4 min every 200 paces along these routes. Upon detection, observers located the position of the bird and recorded it on a map. Counts began 30 min before sunrise and continued for 4 h on mornings of no precipitation and wind speed less than 15 km h (Bump et al., 1947 ). To account for variation in individual drumming behavior, three counts were conducted on each area annually. Density estimates for each study area were calculated based on an assumed 1 : 1 sex ratio of drumming males to females (Bezdek, 1944 ). Each area was stratified by habitat according to overstory composition, stand age and stem size. Habitats were: ( 1 ) young regeneration m stands of
FOREST STRUCTURE ASSOCIATED WITH RUFFED GROUSE ABUNDANCE
2|3
clearcut hardwood regeneration less than 7 years of age with stems less than 5.1 cm average dbh; (2) 7-to 15-year-old hardwood r e g e n e r a t i o n - stands of clearcut hardwood regeneration between 7 and 15 years of age with stems between 5.1 and 10.2 cm dbh; (3) mixed cedar-hardwood - - stands o f red cedar (Juniperus virginiana) and hardwoods including persimmon (Diospyros virginiana), American plum (Prunus americana), and Japanese multiflora rose (Rosa multiflora) with variable stem dbh (5.1-25.4 cm dbh; (4) hardwood saplings - - hardwood regeneration stands greater than 15 years of age with stems between 10.2 and 15.2 cm average dbh; (5) open f i e l d s fields with less than 50% woody canopy coverage; (6) upland s a w t i m b e r stands greater than 50% oak and hickory with stems greater than 22.9 cm average dbh; ( 7 ) upland poletimber-- stands greater than 50% oak and hickory with stems between 15.2 and 22.9 cm average dbh; (8) pine sawtimber m stands greater than 50% pine (Pinus spp.) with stems greater than 22.9 cm average dbh; (9) pine poletimber - - stands greater than 50% pine with stems between 10.2 and 22.9 cm average dbh; (10) bottomland poletimber-- stands greater than 50% ash (Fraxinus spp.), birch (Betula spp.), elm ( Ulmus spp.), and sycamore (Platanus occidentalis) with stems 10.2-22.9 cm average dbh; ( 11 ) bottomland sawtimber - - stands greater than 50% ash, birch, elm, and s,.:camore with stems greater than 22.9 cm average dbh. Habitat composition of each study area was obtained from stand maps generated from compartment examinations performed by the Missouri Department of Conservation (MDC) and Mark Twain National Forest (MTNF) personnel. A minimum of 40, stratified-random sampling plots was used to determine the vegetation structure on each study area. The number ofsample plots measured in each habitat on a study area was proportional to its occurrence. To reduce spurious relationships, we only measured variables that had been identified in other investigations as important or potentially important indicators of grouse habitat. Variables measured at each plot were: basal area (m 2 h a - ~) using a 10-factor prism; density (no. h a - i ) o f deciduous and coniferous stems less than 2.54 cm diameter and greater than 1 m in height using four 2 m × 8 m belt transects; density (no. h a - ' ) of stems greater than 2.54 cm dbh counted on a 0.02 ha circular plot; horizontal cover (%) using a density board (Nudds, 1977); total canopy closure (%), shrub canopy closure (%), and ground cover (%) by measuring the proportion of a 30 m line transect intercepted by the different canopies. Mean values of vegetative variables within each habitat were calculated for each area and used in all analyses. Pearson's correlation analysis and scatter diagrams were used to detect relationships between habitat occurrence (%) and grouse density. For habitats associated with grouse density, we used the same analyses to determine specific structural features related to grouse density. Study areas also were categorized as supporting high or low grouse densities; the median density of our study areas was used as the separating value. We used t-tests to determine if
214
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the mean grouse density on areas categorized as supporting high grouse density differed from areas categorized as supporting low grouse densities. We also used t-tests to determine if mean values for habitat structure differed between areas supporting high and lcw grouse densities. We used SAS-GLM to examine the relationships between the occurrence of habitats and structural features within habitats and grouse density (Statistical Analysis Systems, 1988). We used SAS-DISCRIM analysis to determine the accuracy of classifying study areas into high and low grouse density using variables determined to be related to grouse density in regression analysis. RESULTS
Six areas were classified as supporting high grouse densities (3.3 or more birds 100 h a - i ) and five as supporting low densities (less than 3.3 birds 100 h a - I ) . Mean grouse density on the high density areas (4.3 birds 100 ha -I ) was significantly different (t = 5.1 l, P = 0.0006) than on the low density areas ( 1.0 birds 100 h a - i ). The occurrence of only one habitat, stands of 7- to 15year-old hardwood regeneration, was correlated (r=0.7 l, P = 0 . 0 2 ) with grouse density (Fig. l). The mean percent occurrence of 7- to 15-year-old hardwood regeneration was greater ( t = 2.7 l, P = 0.02 ) on areas supporting high grouse densities compared with areas supporting low grouse densities (.g= 14.3% and 2.7%, respectively). Stands of 7- to 15-year-old hardwood regeneration comprised greater than 14% of four areas with high grouse densities, whereas all areas with low grouse densities contained less than 7%. Using percent occurrence of 7- to 15-year-old hardwood regeneration in discriminate analysis resulted in 82% (nine out of 11 ) of the study areas being correctly classified into low or high grouse density categories. The two misclassified areas supported high grouse densities but contained 7% or less of this habitat. Basal area and percent canopy closure were the only two structural attributes within the 7- to 15-year-old hardwood regeneration habitat related to grouse density. Basal area exhibited a positive linear relationship ( r = 0 . S l , P=0.01 ) (Fig. l ). Moor. basal area did not differ (t=2.33, P = 0 . 0 6 ) on high ( X = 19.2 m E h a - i ) and low ( , ( = 12.5 m E h a - i ) grouse density areas. Basal area was 16.9 m E ha -I, or greater, on five areas supporting high grouse densities, whereas only one area supporting a low grouse density had a mean basal area greater than 16.9 m 2 h a - i. Discriminate analysis correctly classified 88% (seven out of eight ) of the areas containing 7- to 15-year-old hardwood regeneration habitat into low or high grouse density categories. The one misclassification was a low grouse density area that had a basal area of 18.7 m 2 h a - i. Percent canopy closure in the 7- to 15-year-old hardwood regeneration habitat exhibited a curvilinear relationship with grouse density (Fig. l ). A significant relationship between percent ,:anopy closure and grouse density was
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Fig. 1. Relationshipsbetweenruffedgrousedensityand the percentoccurrenceof 7- to 15-yearold hardwoodregenerationhabitat, and basal area and percent canopyclosurewithin 7- to ! 5year-old hardwoodregenerationon 11 study areas in the oak and hickoryforests of Missouri, 1985-1986. determined in regression analysis when percent canopy closure was used in a quadratic equation (r2=0.81, P--0.01 ). Mean percent canopy closure did not differ ( t = - 0 . 2 2 , P--0.84) between high (X=78%) and low (X--80%) grouse density areas. Five out of six areas supporting high grouse densities had between 70 and 89% canopy closure, whereas all areas supporting low grouse densities had either a lower or higher percentage of canopy closure. Discriminate analysis correctly classified 63% (five out of eight) of the areas containing the 7- to 15-year-old hardwood regeneration habitat into high or low grouse density categories using percent canopy closure. Two areas supporting high grouse densities and one area supporting a low density were misclassified. DISCUSSION Grouse densities on our study areas were positively related to the percent of the area comprised of hardwood regeneration stands between 7 and 15
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years of age. Highest grouse populations tended to occur on areas where stands of this habitat made up greater than 14% of the area. Even-aged regeneration stands have been identified in other studies as important ruffed grouse habitat (Stoll et al., 1979; Thompson et al., 1987). In Tennessee, grouse using 9to 12-year-old hardwood regeneration stands had higher survivorship than in other habitats (White and Dimmick, 1978). In the Great Lakes region, young stands of aspen (Populus slap.) provided optimum drumming and winter habitat (Gullion, 1977). Our data did not indicate an upper level beyond which an increase in the occurrence of 7- to 15-year-old hardwood regeneration failed to increase ruffed grouse populations. In Wisconsin, management recommendations for ruffed grouse included having 30-35% of aspen stands in sapling size stems (Kubisiak, 1985 ). Gullion (1972) reported that higher sustained grouse densities in Minnesota occurred on areas where aspen regeneration comprised at least 50% of the area. Although 7- to 15-year-old hardwood regeneration can be maintained in forests at levels exceeding 14%, regulations that restrict timber harvest may limit the occurrence of this habitat below optimum levels for grouse habitat. Further, guidelines established to enhance multi-use objectives on forested lands may also limit the extent and location of timber harvest and thus limit the occurrence of 7- to 15-year-old hardwood regeneration below levels desirable for ruffed grouse. Other studies have indicated that high stem densities are important structural attributes of grouse habitat (Hale ct al., 1982; Thorapson et al., 1987 ). However, on our study areas mean stem density in 7- to 15-year-old hardwood regeneration was not related to grouse density, but was related to basal area. Basal area is influenced by both stem density and diameter. Stem diameter is a function of age and site quality factors such as soil fertility. We believe the correlation between grouse densities and basal areas indicates that 7- to 15-year-old hardwood regeneration stands occurring on the most productive or highest quality sites have the greatest potential as habitats for ruffed grouse The larger stems and shrubs provide resources such as overhead protection and vertical screening cover from avian predation (Moulton, 1968; Boag, 1976). High grouse densities also occurred where canopy closure in the 7- to 15year-old hardwood regeneration was between 70 and 89%. Partial canopy closure may afford overhead cover, and allow penetration of solar radiation and development of ground vegetation. This ground vegetation may be important either as browse or as a substrate that supports other forage such as insects (Korschgen, 1966). Overhead cover also is important in spring when males use this habitat for drumming sites and are more exposed to predation than during any other season (Bump et al., 1947; Hale et al., 1982; Thompson et al., 1987). Regeneration stands that develop canopies that are either too open or too
FOREST STRUCTURE ASSOCIATED WITH RUFFED GROUSE ABUNDANCE
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closed m a y not provide suitable habitat for grouse. Management actions designed solely to produce regeneration stands with high basal areas m a y not be successful if the high basal area results in a closed canopy. Habitat management plans should therefore include strategies for maintaining a balance between partial canopy closure and high basal areas. ACKNOWLEDGMENTS We thank E.L. Brunson, W.D. Dijak, M.E. Reed, and G.D. Zenitsky for assistance in collecting much o f t h e vegetation data. Personnel from the MDC, M T N F and the N o r t h Central Forest Experiment Station also assisted in various aspects o f data collection. Funding support for this study was p r o v i d e d by the MDC, the Missouri Agricultural Experiment Station, the N o r t h Central Forest Experiment Station, the E. Sidney Stephens Fellowship, and the Missouri Cooperative Fish a n d Wildlife Research U n i t (U.S. Fish a n d Wildlife Service, Missouri D e p a r t m e n t o f Conservation P-R Project W-I 3-R, University o f Missouri-Columbia, a n d Wildlife M a n a g e m e n t Institute, cooperating). This is contribution 11 441 o f the Missouri Agricultural Experiment Station Project 275.
REFERENCES Bezdek, H., 1944. Sex ratios and color phases in two races of ruffed grouse. J. Wildl. Manage., 8: 85-88. Boag, D.A., 1976. Influence of changing grouse density and forest attributes on the occupancy of a series of potential territories by male ruffed grouse. Can J. Zool., 54: 1727-1736. Bump, G., Darrow, R.W., Edminster, F.C. and Crissey, W.F., 1947. Ruffed Grouse; Life History, Propagation, Management. Holling Press, Buffalo, NY, 915 pp. Gullion, G.W., 1972. Improving your forested lands for ruffed grouse. Ruffed Grouse Soc. North Am., 134 pp. Gullion, G.W., 1977. Forest manipulation for ruffed grouse. Trans. N. Am. Wildl. Nat. Resour. Conf., 42: 449-458. Hale, P.E., Johnson, A.S. and Landers, J.L., 1982. Characteristics of ruffed grouse drumming sites in Georgia. J. Wildl. Manage., 46:115-123. Johnsgard, P.A., 1973. Grouse and quail of North America. Univ. of Nebraska Press, Lincoln, NE, 553 pp. Korschgen, L.J., 1966. Food and nutrition of ruffed grouse in Missouri. J. Wildl. Manage., 30: 86-100. Krusekopf, H.H., 1962. Major soil areas of Missouri. Univ. of Missouri Agric. Exp. Stn., Columbia, Me, 25 pp. Kubisiak, J.F., 1985. Ruffed grouse habitat relationships in aspen and oak forests of central Wisconsin. Wis. Dept. Nat. Resour. Tech. Bull. 151, 22 pp. Laubhan, M.K., 1987. Development and evaluation of pattern recognition habitat models for the ruffed grouse, gray squirrel, and fox squirrel in Missouri. M.S. Thesis., Univ. of Missouri, Columbia, Me, 128 pp.
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Moulton, J.C., 1968. Ruffed grouse habitat requirements and management opportunities. Res. Rep. No. 36. Wisconsin Dept. Nat. Resour., Madison, WI, 32 pp. Nudds, T., 1977. Quantifying the vegetation structure of wildlife cover. Wildl. Soc. Bull., 5: i!3-117. Statistical Analysis Systems, 1988. User's Guide, Release 5.0. SAS Institute Inc., Cary, NC, 1028 pp. Stoll, Jr., R.J., Milford, M.W., Boston, P.L. and Hanchur, G.P., 1979. Ruffed grouse drumming site characteristics in Ohio. J. WildL Manage., 43: 324-333. Thompson, III, F.R., Freiling, D.A. and Fritzell, E.K., 1987. Drumming, nesting, and brood habitat of ruffed grouse in an oak-hickory forest. J. Wildl. Manage., 51: 568-575. White, D. and Dimmick, R., 1978. Survival and habitat use of northern ruffed grouse introduced into west Tennessee. Proc. Annu. Conf. Southeast. Assoc. Fish and Wildl. Agencies, 32: 1-7.
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Forest structure associated with ruffed grouse abundance Ernie P. Wiggers a, Murray K. Laubhan a and David A. Hamilton b aSchool of Natural Resources, 112 Stephens Hall, Universityof Missouri. Cnlumbia, MO 65211, USA bMissouri Department of Conservation, Research Center, 11lO S. CollegeAve.. Columbia, MO 65201. USA (Accepted 28 March 1991 )
ABSTRACT Wiggers, E.P., Laubhan, M.K. and Hamilton, D.A., 1992. Forest structure associated with ruffed grouse abundance. For. Ecol. Manage., 49:211-218. We identified and described the occurrence and structure of habitats related to ruffed grouse (Bonasa umbellus) abundance on 11 study areas in the oak (Quercus spp.) and hickory (Carya spp.) forest association of the central US. The percent occurrence of 7- to 15-year-old hardwood regeneration was the only habitat correlated with grouse density. Structural characteristics that influenced the quality of this habitat for grouse were basal area and percent canopy closure. Basal area exhibited a positive linear relationship, whereas percent canopy closure exhibited a curvilinear relationship with grouse density. Highest grouse densities occurred where 7- to 15-year-old hardwood regeneration habitat comprised greater than 14% of the area; basal area was greater than 16.9 m 2 ha - j and canopy closure was between 70 and 89% in this habitat. Management strategies for enhancing habitat for grouse should include maintaining more than 14% of a forest in 7- to 15-year-old hardwood regeneration and maintaining a balance between partial canopy closure and high basal area within this habitat. Hardwood regeneration stands occurring on the most productive or highest quality sites probably have the greatest potential to provide habitat for grouse.
INTRODUCTION
Forest attributes such as the occurrence of different aged stands and diverse structure within and among these stands are thought to influence habitat suitability and abundance of forest-dwelling wildlife species. However, there is a paucity of information that identifies and quantifies the relationships between the amount and structure of habitats with animal abundance. One wildlife species that is dependent upon forest as habitat is the ruffed grouse (Johnsgard, 1973). The southern periphery of this bird's range includes the oak and hickory forests of the central US. Research suggests that extensively cut deciduous woodlands and even-aged regenerating stands are important habitats for ruffed grouse (White and Dimmick, 1978; Stoll et al., © 1992 Elsevier Science Publishers B.V. All rights reserved 0378-1127/92/$05.00
212
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1979; Thompson et al., 1987). However, neither the optimum amounts nor structural characteristics of these forest habitats have been quantified, nor have the relationships between forest structure and grouse abundance been determined. This information is essential to understand how changes in forest structure, whether by natural processes or man induced, impact grouse populations. The purpose of our study was to identify and describe habitats and structures important for ruffed grouse on areas that differentially supported grouse populations and to determine the relatit, nship between the occurrence and structure of these habitats and ruffed grouse abundance. S T U D Y A R EA S
Selection of study areas was restricted to areas where ruffed grouse releases and forest disturbance had not occurred for at least 3 years. During 1985 and 1986, we collected information on forest structure and ruffed grouse densities on 11 study areas that met these criteria. These areas ranged from 200 to 528 ha in size and were distributed within the River Hills, Ozark, and Ozark Plateau regions of Missouri (Krusekopf, 1962 ). All areas were extensively forested, and the oak and hickory association represented the dominant overstory vegetation (Laubhan, 1987 ). Topography ranged from deep hollows with narrow ridges and steep slopes in the River Hills region to hilly plateaus with deep hollows and moderate to steep slopes in the Ozark Plateau region. METHODS Ruffed grouse populations were surveyed by complete area counts of drumming males during April. Drumming count data were collected for 2 years on ten areas and for 1 year on three areas. Because forest conditions were dynamic as a result of natural succession, we restricted population surveys to years when vegetation measurements were conducted. Survey routes were established on ridges and in hollows on each area so drumming by grouse could be detected at the greatest distance and in as many directions as possible. Personnel paused and listened for drumming for 4 min every 200 paces along these routes. Upon detection, observers located the position of the bird and recorded it on a map. Counts began 30 min before sunrise and continued for 4 h on mornings of no precipitation and wind speed less than 15 km h (Bump et al., 1947 ). To account for variation in individual drumming behavior, three counts were conducted on each area annually. Density estimates for each study area were calculated based on an assumed 1 : 1 sex ratio of drumming males to females (Bezdek, 1944 ). Each area was stratified by habitat according to overstory composition, stand age and stem size. Habitats were: ( 1 ) young regeneration m stands of
FOREST STRUCTURE ASSOCIATED WITH RUFFED GROUSE ABUNDANCE
2|3
clearcut hardwood regeneration less than 7 years of age with stems less than 5.1 cm average dbh; (2) 7-to 15-year-old hardwood r e g e n e r a t i o n - stands of clearcut hardwood regeneration between 7 and 15 years of age with stems between 5.1 and 10.2 cm dbh; (3) mixed cedar-hardwood - - stands o f red cedar (Juniperus virginiana) and hardwoods including persimmon (Diospyros virginiana), American plum (Prunus americana), and Japanese multiflora rose (Rosa multiflora) with variable stem dbh (5.1-25.4 cm dbh; (4) hardwood saplings - - hardwood regeneration stands greater than 15 years of age with stems between 10.2 and 15.2 cm average dbh; (5) open f i e l d s fields with less than 50% woody canopy coverage; (6) upland s a w t i m b e r stands greater than 50% oak and hickory with stems greater than 22.9 cm average dbh; ( 7 ) upland poletimber-- stands greater than 50% oak and hickory with stems between 15.2 and 22.9 cm average dbh; (8) pine sawtimber m stands greater than 50% pine (Pinus spp.) with stems greater than 22.9 cm average dbh; (9) pine poletimber - - stands greater than 50% pine with stems between 10.2 and 22.9 cm average dbh; (10) bottomland poletimber-- stands greater than 50% ash (Fraxinus spp.), birch (Betula spp.), elm ( Ulmus spp.), and sycamore (Platanus occidentalis) with stems 10.2-22.9 cm average dbh; ( 11 ) bottomland sawtimber - - stands greater than 50% ash, birch, elm, and s,.:camore with stems greater than 22.9 cm average dbh. Habitat composition of each study area was obtained from stand maps generated from compartment examinations performed by the Missouri Department of Conservation (MDC) and Mark Twain National Forest (MTNF) personnel. A minimum of 40, stratified-random sampling plots was used to determine the vegetation structure on each study area. The number ofsample plots measured in each habitat on a study area was proportional to its occurrence. To reduce spurious relationships, we only measured variables that had been identified in other investigations as important or potentially important indicators of grouse habitat. Variables measured at each plot were: basal area (m 2 h a - ~) using a 10-factor prism; density (no. h a - i ) o f deciduous and coniferous stems less than 2.54 cm diameter and greater than 1 m in height using four 2 m × 8 m belt transects; density (no. h a - ' ) of stems greater than 2.54 cm dbh counted on a 0.02 ha circular plot; horizontal cover (%) using a density board (Nudds, 1977); total canopy closure (%), shrub canopy closure (%), and ground cover (%) by measuring the proportion of a 30 m line transect intercepted by the different canopies. Mean values of vegetative variables within each habitat were calculated for each area and used in all analyses. Pearson's correlation analysis and scatter diagrams were used to detect relationships between habitat occurrence (%) and grouse density. For habitats associated with grouse density, we used the same analyses to determine specific structural features related to grouse density. Study areas also were categorized as supporting high or low grouse densities; the median density of our study areas was used as the separating value. We used t-tests to determine if
214
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the mean grouse density on areas categorized as supporting high grouse density differed from areas categorized as supporting low grouse densities. We also used t-tests to determine if mean values for habitat structure differed between areas supporting high and lcw grouse densities. We used SAS-GLM to examine the relationships between the occurrence of habitats and structural features within habitats and grouse density (Statistical Analysis Systems, 1988). We used SAS-DISCRIM analysis to determine the accuracy of classifying study areas into high and low grouse density using variables determined to be related to grouse density in regression analysis. RESULTS
Six areas were classified as supporting high grouse densities (3.3 or more birds 100 h a - i ) and five as supporting low densities (less than 3.3 birds 100 h a - I ) . Mean grouse density on the high density areas (4.3 birds 100 ha -I ) was significantly different (t = 5.1 l, P = 0.0006) than on the low density areas ( 1.0 birds 100 h a - i ). The occurrence of only one habitat, stands of 7- to 15year-old hardwood regeneration, was correlated (r=0.7 l, P = 0 . 0 2 ) with grouse density (Fig. l). The mean percent occurrence of 7- to 15-year-old hardwood regeneration was greater ( t = 2.7 l, P = 0.02 ) on areas supporting high grouse densities compared with areas supporting low grouse densities (.g= 14.3% and 2.7%, respectively). Stands of 7- to 15-year-old hardwood regeneration comprised greater than 14% of four areas with high grouse densities, whereas all areas with low grouse densities contained less than 7%. Using percent occurrence of 7- to 15-year-old hardwood regeneration in discriminate analysis resulted in 82% (nine out of 11 ) of the study areas being correctly classified into low or high grouse density categories. The two misclassified areas supported high grouse densities but contained 7% or less of this habitat. Basal area and percent canopy closure were the only two structural attributes within the 7- to 15-year-old hardwood regeneration habitat related to grouse density. Basal area exhibited a positive linear relationship ( r = 0 . S l , P=0.01 ) (Fig. l ). Moor. basal area did not differ (t=2.33, P = 0 . 0 6 ) on high ( X = 19.2 m E h a - i ) and low ( , ( = 12.5 m E h a - i ) grouse density areas. Basal area was 16.9 m E ha -I, or greater, on five areas supporting high grouse densities, whereas only one area supporting a low grouse density had a mean basal area greater than 16.9 m 2 h a - i. Discriminate analysis correctly classified 88% (seven out of eight ) of the areas containing 7- to 15-year-old hardwood regeneration habitat into low or high grouse density categories. The one misclassification was a low grouse density area that had a basal area of 18.7 m 2 h a - i. Percent canopy closure in the 7- to 15-year-old hardwood regeneration habitat exhibited a curvilinear relationship with grouse density (Fig. l ). A significant relationship between percent ,:anopy closure and grouse density was
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100
CANOPY CLOSURE (%)
Fig. 1. Relationshipsbetweenruffedgrousedensityand the percentoccurrenceof 7- to 15-yearold hardwoodregenerationhabitat, and basal area and percent canopyclosurewithin 7- to ! 5year-old hardwoodregenerationon 11 study areas in the oak and hickoryforests of Missouri, 1985-1986. determined in regression analysis when percent canopy closure was used in a quadratic equation (r2=0.81, P--0.01 ). Mean percent canopy closure did not differ ( t = - 0 . 2 2 , P--0.84) between high (X=78%) and low (X--80%) grouse density areas. Five out of six areas supporting high grouse densities had between 70 and 89% canopy closure, whereas all areas supporting low grouse densities had either a lower or higher percentage of canopy closure. Discriminate analysis correctly classified 63% (five out of eight) of the areas containing the 7- to 15-year-old hardwood regeneration habitat into high or low grouse density categories using percent canopy closure. Two areas supporting high grouse densities and one area supporting a low density were misclassified. DISCUSSION Grouse densities on our study areas were positively related to the percent of the area comprised of hardwood regeneration stands between 7 and 15
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years of age. Highest grouse populations tended to occur on areas where stands of this habitat made up greater than 14% of the area. Even-aged regeneration stands have been identified in other studies as important ruffed grouse habitat (Stoll et al., 1979; Thompson et al., 1987). In Tennessee, grouse using 9to 12-year-old hardwood regeneration stands had higher survivorship than in other habitats (White and Dimmick, 1978). In the Great Lakes region, young stands of aspen (Populus slap.) provided optimum drumming and winter habitat (Gullion, 1977). Our data did not indicate an upper level beyond which an increase in the occurrence of 7- to 15-year-old hardwood regeneration failed to increase ruffed grouse populations. In Wisconsin, management recommendations for ruffed grouse included having 30-35% of aspen stands in sapling size stems (Kubisiak, 1985 ). Gullion (1972) reported that higher sustained grouse densities in Minnesota occurred on areas where aspen regeneration comprised at least 50% of the area. Although 7- to 15-year-old hardwood regeneration can be maintained in forests at levels exceeding 14%, regulations that restrict timber harvest may limit the occurrence of this habitat below optimum levels for grouse habitat. Further, guidelines established to enhance multi-use objectives on forested lands may also limit the extent and location of timber harvest and thus limit the occurrence of 7- to 15-year-old hardwood regeneration below levels desirable for ruffed grouse. Other studies have indicated that high stem densities are important structural attributes of grouse habitat (Hale ct al., 1982; Thorapson et al., 1987 ). However, on our study areas mean stem density in 7- to 15-year-old hardwood regeneration was not related to grouse density, but was related to basal area. Basal area is influenced by both stem density and diameter. Stem diameter is a function of age and site quality factors such as soil fertility. We believe the correlation between grouse densities and basal areas indicates that 7- to 15-year-old hardwood regeneration stands occurring on the most productive or highest quality sites have the greatest potential as habitats for ruffed grouse The larger stems and shrubs provide resources such as overhead protection and vertical screening cover from avian predation (Moulton, 1968; Boag, 1976). High grouse densities also occurred where canopy closure in the 7- to 15year-old hardwood regeneration was between 70 and 89%. Partial canopy closure may afford overhead cover, and allow penetration of solar radiation and development of ground vegetation. This ground vegetation may be important either as browse or as a substrate that supports other forage such as insects (Korschgen, 1966). Overhead cover also is important in spring when males use this habitat for drumming sites and are more exposed to predation than during any other season (Bump et al., 1947; Hale et al., 1982; Thompson et al., 1987). Regeneration stands that develop canopies that are either too open or too
FOREST STRUCTURE ASSOCIATED WITH RUFFED GROUSE ABUNDANCE
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closed m a y not provide suitable habitat for grouse. Management actions designed solely to produce regeneration stands with high basal areas m a y not be successful if the high basal area results in a closed canopy. Habitat management plans should therefore include strategies for maintaining a balance between partial canopy closure and high basal areas. ACKNOWLEDGMENTS We thank E.L. Brunson, W.D. Dijak, M.E. Reed, and G.D. Zenitsky for assistance in collecting much o f t h e vegetation data. Personnel from the MDC, M T N F and the N o r t h Central Forest Experiment Station also assisted in various aspects o f data collection. Funding support for this study was p r o v i d e d by the MDC, the Missouri Agricultural Experiment Station, the N o r t h Central Forest Experiment Station, the E. Sidney Stephens Fellowship, and the Missouri Cooperative Fish a n d Wildlife Research U n i t (U.S. Fish a n d Wildlife Service, Missouri D e p a r t m e n t o f Conservation P-R Project W-I 3-R, University o f Missouri-Columbia, a n d Wildlife M a n a g e m e n t Institute, cooperating). This is contribution 11 441 o f the Missouri Agricultural Experiment Station Project 275.
REFERENCES Bezdek, H., 1944. Sex ratios and color phases in two races of ruffed grouse. J. Wildl. Manage., 8: 85-88. Boag, D.A., 1976. Influence of changing grouse density and forest attributes on the occupancy of a series of potential territories by male ruffed grouse. Can J. Zool., 54: 1727-1736. Bump, G., Darrow, R.W., Edminster, F.C. and Crissey, W.F., 1947. Ruffed Grouse; Life History, Propagation, Management. Holling Press, Buffalo, NY, 915 pp. Gullion, G.W., 1972. Improving your forested lands for ruffed grouse. Ruffed Grouse Soc. North Am., 134 pp. Gullion, G.W., 1977. Forest manipulation for ruffed grouse. Trans. N. Am. Wildl. Nat. Resour. Conf., 42: 449-458. Hale, P.E., Johnson, A.S. and Landers, J.L., 1982. Characteristics of ruffed grouse drumming sites in Georgia. J. Wildl. Manage., 46:115-123. Johnsgard, P.A., 1973. Grouse and quail of North America. Univ. of Nebraska Press, Lincoln, NE, 553 pp. Korschgen, L.J., 1966. Food and nutrition of ruffed grouse in Missouri. J. Wildl. Manage., 30: 86-100. Krusekopf, H.H., 1962. Major soil areas of Missouri. Univ. of Missouri Agric. Exp. Stn., Columbia, Me, 25 pp. Kubisiak, J.F., 1985. Ruffed grouse habitat relationships in aspen and oak forests of central Wisconsin. Wis. Dept. Nat. Resour. Tech. Bull. 151, 22 pp. Laubhan, M.K., 1987. Development and evaluation of pattern recognition habitat models for the ruffed grouse, gray squirrel, and fox squirrel in Missouri. M.S. Thesis., Univ. of Missouri, Columbia, Me, 128 pp.
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Moulton, J.C., 1968. Ruffed grouse habitat requirements and management opportunities. Res. Rep. No. 36. Wisconsin Dept. Nat. Resour., Madison, WI, 32 pp. Nudds, T., 1977. Quantifying the vegetation structure of wildlife cover. Wildl. Soc. Bull., 5: i!3-117. Statistical Analysis Systems, 1988. User's Guide, Release 5.0. SAS Institute Inc., Cary, NC, 1028 pp. Stoll, Jr., R.J., Milford, M.W., Boston, P.L. and Hanchur, G.P., 1979. Ruffed grouse drumming site characteristics in Ohio. J. WildL Manage., 43: 324-333. Thompson, III, F.R., Freiling, D.A. and Fritzell, E.K., 1987. Drumming, nesting, and brood habitat of ruffed grouse in an oak-hickory forest. J. Wildl. Manage., 51: 568-575. White, D. and Dimmick, R., 1978. Survival and habitat use of northern ruffed grouse introduced into west Tennessee. Proc. Annu. Conf. Southeast. Assoc. Fish and Wildl. Agencies, 32: 1-7.