MOUNTAIN SHEEP HABITAT EVALUATION in MOJAVE DESERT SCRUB Louis R
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sert Bighorn Council 1992 Transactions A Compilation of Papers Presented and Submitted at the 36th Annual Meeting 8-1 1 April 1992, Bullhead City, Arizona Copies Available for $15.00 to members Paul R. Krausman, Editor ($20.00 plus postage to nonmembers) Walter M. Boyce, Associate Editor by writing the Desert Bighorn Council Mark C. Wallace, Associate Editor 1500 N. Decatur Blvd. Raymond M. Lee, Associate Editor Las Vegas, NV 89108 TABLE OF CONTENTS TECHNICAL REPORTS MEASURING VISUAL OBSTRUCTION CAUSED BY DISCRETE OBJECTS IN BIGHORN SHEEP HABITATS Craig W. McCarty and James A. Bailey ..................................................... 1 EVALUATION OF MOUNTAIN SHEEP HABITAT IN ZION NATIONAL PARK, UTAH Tom S. Smith and Jerran T. Flinders ....................................................... 4 MOUNTAIN SHEEP HABITAT EVALUATION IN MOJAVE DESERT SCRUB Louis R. Berner and Paul R. Krausman ...................................................... 10 HABITAT SELECTION BY MOUNTAIN SHEEP IN MOJAVE DESERT SCRUB Louis R. Berner, Paul R. Krausman, and Mark C. Wallace ....................................... 13 RESOURCE USE BY MOUNTAIN SHEEP IN A LARGE ENCLOSURE Matthew J. Zine, Paul R. Krausman, Mark C. Wallace, and Louis R. Berner .......................... 23 MORTALITY OF MOUNTAIN SHEEP IN THE BLACK CANYON AREA OF NORTHWEST ARIZONA Stan C. Cunningham and James C. deVos .................................................... 27 THE HEALTH OF MOUNTAIN SHEEP IN THE SAN ANDRES MOUNTAINS, NEW MEXICO Richard K. Clark and David A. Jessup ...................................................... 30 COMPOSITION AND QUALITY OF MOUNTAIN SHEEP DIETS IN THE SUPERSTITION MOUNTAINS, ARIZONA Bryon S. Holt, William H. Miller, and Brian F. Wakeling ........................................ 36 AN ANALYSIS OF FORAGE USED BY MOUNTAIN SHEEP IN THE EASTERN MOJAVE DESERT, CALIFORNIA Vernon C. Bleich, R. Terry Bowyer, Deborah J. Clark, and Thomas 0. Clark ......................... 41 COMMENTS, PANEL DISCUSSIONS, AND STATUS REPORTS THE USE OF DESERT BIGHORN COUNCIL TRANSACTIONS PaulR.Krausman ...................................................................... 48 ACTUAL COSTS OF BIGHORN SHEEP WATER DEVELOPMENTS Rodney J. Mouton and Raymond M. Lee. .................................................... 49 PROBLEMS ASSOCIATED WITH HEART RATE TELEMETRY IMPLANTS Mark C. Wallace, Paul R. Krausman, Donald W. DeYoung, and Mara E. Weisenberger .................. 51 IMPLICATIONS OF CAPTIVE BREEDING PROGRAMS FOR THE CONSERVATION OF DESERT BIGHORN SHEEP Lee F. Elliott and Walter M. Boyce ......................................................... 54 PANEL: STRESS AND BIGHORN SHEEP Walter Boyce, Tom Bunch, Stan Cunningham, Jim DeForge, David Jessup, and John Wehausen ........... 58 PANEL: WHAT IS MINIMUM VIABLE POPULATION SIZE? Paul R. Krausman, James Bailey, Vernon Bleich, Don Armentrout, and Rob Ramey ..................... 68 STATUS OF BIGHORN SHEEP IN ARIZONA, 1991 RaymondM.Lee ...................................................................... 75 STATUS OF BIGHORN SHEEP IN CALIFORNIA, 1991 Vernon C. Bleich, Steven G. Torres, David A. Jessup, and Gerald Mulcahy ........................... 76 STATUS OF BIGHORN SHEEP IN TEXAS, 1991 Robert L. West and Michael D. Hobson ..................................................... 78 STATUS OF BIGHORN SHEEP IN NEVADA, 1991 William R. Brigham and Daniel E. Delaney ................................................... 79 STATUS OF BIGHORN SHEEP IN NEW MEXICO. 1991 Amy S. Fisher ............................................................................ 80 RECENT DESERT BIGHORN SHEEP LITERATURE ........................................ 81 OBITUARY: DANIEL E. DELANEY, 1951-1992 ............................................. 82 DESERT BIGHORN COUNCIL MEMBERSHIP LIST - 1992 ................................... 83 jective evaluation of visual obstruction, permit inter-observer differ- ences, and perhaps observer expectancy bias (Balph and Balph 1983), MEASURING VISUAL that may be important when evaluating visual obstruction. We offer a method based on computer simulation for measuring visual OBSTRUCTION CAUSED obstruction ofhabitats that (1) minimizes the importance ofdetermining the "center" of an area to be evaluated; (2) is based upon objectively BY DISCRETE OBJECTS IN measured densities and widths of trees or other discrete objects; and (3) allows estimation in the field or, in some habitats, from aerial photo- BIGHORN SHEEP graphs. The method is especially applicable to pinyon/juniper habitats on relatively smooth slopes where visibility is not obstructed by abrupt HABITAT changes in topography, such as across a plot of 20 m radius. We also used this method to investigate relationships between distributions and densities of discrete vision-obstructing objects and resulting visibility CRAIG W. MCCARTY, Department of Fishery and Wildlife Biology, data. Colorado State University, Fort Collins, CO 80523 This study was part of a larger project funded by the U. S. Bureau of Land Management, the Colorado Division of Wildlife, the Rocky Moun- JAMES A. BAILEY, Department of Fishery and Wildlife Biology, Col- tain Bighorn Society, the Foundation for North American Wild Sheep, orado State University, Fort Collins, CO 80523 and the Colorado Wildlife Heritage Foundation. Desert Bighorn Counc. Trans. 36:l-3. METHODS Program TSIM (Appendix) is a mathematical algorithm that calcu- lates the visual obstruction produced by simulating a random placement Abstract: Methods for measuring visual obstruction in bighorn sheep of a given number of vision-obstructing objects in a circle of given (Ovis canadensis) habitats are not clearly described in the literature, radius. It applies when visual obstruction in a habitat is produced pri- permit inter-observer differences and observer-expectancy bias, and may marily by objects of similar diameter (i.e., trees and/or boulders). Pro- produce data with poor statistical properties. We propose solutions for gram TSIM was developed for measuring visual obstruction in pinyon some of these problems in measuring visibility in pinyon (Pinus edulis)/ pine/juniper/rock habitats in the Dolores River Canyon near Slickrock, juniper (Juniperus spp.) habitats. Colorado. It specifies that the center of the circle, for which visual Key words: bighorn sheep, computer simulation, habitat evaluation, obstruction is being measured, be at least a given distance from the Ovis canadensis, visibility. nearest vision-obstructing object. In the Dolores River Canyon, 6 m was used. This was the mean distance from the nearest visual obstruction > 1 m tall for bighorn sheep observed in the Canyon during 1990-9 1 Visibility, or lack of visual obstruction by tall trees, shrubs, or rocks, (n = 177). is an important habitat characteristic for bighorn sheep. Bighorn be- Program TSIM will accommodate study areas with different visibility havior has been related to visibility (Risenhoover and Bailey 1980, characteristics. Use of a circle >20 m is suggested for comparing es- 1985; Hansen 1982) and the value of visibility is recognized in habitat- pecially open habitats. If there is important variation in the sizes of evaluation models (Hansen 1980, Holl 1982, Armentrout and Brigham vision-obstructing objects, TSIM may be modified to use a frequency 1988). In research and management applications (e.g., habitat evalua- distribution of object diameters. tion) it may be necessary to measure visibility in the field or from aerial Program TSIM uses the average width at 1 m high of vision-ob- photographs of vegetation. structing objects, and a frequency distribution of the number of objects, The method of Risenhoover and Bailey (1 985) is commonly used for within circles of a given radius. The program calculates expected percent quantifying visual obstruction in bighorn habitats (Armentrout and visual obstruction values (Fig. 2) from successive random placings of Brigham 1988, Dunn 199 1, Haas 199 1). Risenhoover and Bailey (1 985) the given number of objects in the circle. The densities of vision-ob- measured percent visual obstruction subjectively by standing in the structing objects may be measured from plots in the field or from aerial center of an area to be evaluated and estimating the percent of the photographs. The average width of objects at 1 m above the ground surrounding 360 degrees for which an object 90 cm tall and 40 m away may be measured in the field; and perhaps from aerial photographs, could not be seen. The area to be evaluated was either the center of a depending upon the shapes of the objects. patch of habitat or the center of an area used by a group of sheep. We randomly located 2-22 points within each of 4 habitats in the Risenhoover and Bailey (1985) did not specify how they selected the Dolores River Canyon (Table 1). From each point, we estimated the center of this area; however, they avoided standing very close to, or percent of each quarter of the compass over which an object 1 m tall within the crowns of, trees (J. Bailey, pers. commun.). Varying the degree and 20 m away could not be seen. We ignored visual obstructions within to which trees are avoided can produce large effects upon resulting 6 m of the observers, and above or below 1 m tall. The average of 4 estimates of visibility. An alternative for selecting plot centers is to use percentages was the visual obstruction for the plot. We also counted the location of one bighorn chosen at random from a band of sheep. the number of trees in each plot. This method cannot be used for