Estimating moose population parameters from aerial surveys

Successful moose management depends on knowledge of population dynamics. The principal parameters required are size, rate of change, recruitment, sex composition, and mortality. Moose management in Alaska has been severely hampered by the lack of good estimates of these parameters, and unfortunately, this lack contributed to the decline of many Alaskan moose populations during the 1970s (e.g., Gasaway et al. 1983). The problems were: (1) population size not adequately estimated, (2) rapid rates of decline not acknowledged until populations were low, (3) meaningful recruitment rates were not available in the absence of good population estimates, and (4) calf and adult mortality rates were grossly underestimated. Frustration of moose managers working with inadequate data led to development of aerial survey procedures that yield minimally biased, sufficiently precise estimates of population parameters for most Alaskan moose management and research. This manual describes these procedures. Development of these procedures would have been impossible without the inspiration, support, advice, and criticism of many colleagues. We thank these colleagues for their contributions. Dale Haggstrom and Dave Kelleyhouse helped develop flight patterns, tested and improved early sampling designs, and as moose managers, put these procedures into routine use. Pilots Bill Lentsch and Pete Haggland were instrumental in developing and testing aerial surveying techniques. Their interest and dedication to improving moose management made them valuable allies. Statisticians Dana Thomas of the University of Alaska and W. Scott Overton of Oregon State University provided advice on variance approximations for the population estimator. Warren Ballard, Sterling Miller, SuzAnne Miller, Doug Larsen, and Wayne Kale tested procedures and provided valuable criticisms and suggestions. Jim Raymond initially programmed a portable calculator to make lengthy calculation simple, fast, and error-free. Angie Babcock, Lisa Ingalls, Vicky Leffingwell, and Laura McManus patiently typed several versions of this manual. John Coady and Oliver Burris provided continuous moral and financial support for a 3-year project that lasted 6 years. Joan Barnett, Rodney Boetje, Steven Peterson, and Wayne Regelin of the Alaska Department of Fish and Game provided helpful editorial suggestions in previous drafts. Finally, we thank referees David Anderson of the Utah Cooperative Wildlife Research Unit, Vincent Schultz of Washington State University, and James Peek, E. "Oz" Garton, and Mike Samuel of the University of Idaho whose comments and suggestions improved this manual. This project was funded by the Alaska Department of Fish and Game through Federal Aid in Wildlife Restoration Projects W-17-9 through W-22-1

DISPERSAL OF SUBADULT MOSOE FROM A LOW DENSITY POPULATION IN INTERIOR ALASKA

Dispersal of 1- to 3-year-old moose from a low density, but rapidly growing, moose population was investigated. Radio-collars were placed on 17 offspring of previously radio-collared adult cows. Comparison of home ranges of independent offspring and their respective dams indicates a close spatial relationship between home ranges. No long distance dispersal resulting in the formation of a home range separate from that of the dam’s was observed. Winter home ranges of offspring tended to deviate more from that of their dams’ than did summer home ranges. Thus, this moose population demonstrated a very slow rate of dispersal. For managers this conclusion has important consequences: 1) newly created habitat will not be rapidly located and occupied by dispersing moose; 2) locally overhunted areas will be repopulated primarily by offspring of the areas surviving moose; 3) since declining moose populations adjacent to low density populations derive few new members by immigration, each population must be managed with respect to its individual potential growth rates

PRECISION OF MOOSE DENSITY ESTIMATES DERIVED FROM STRATIFICATION SURVEY DATA

Stratified random block (SRB) surveys are commonly used to monitor moose abundance. However, SRB surveys are expensive and time consuming, hence few areas can be surveyed annually and successive surveys in an area are infrequent. We investigated the potential for using only the stratification portion of the SRB survey technique to monitor moose abundance. Our objective was to determine how precisely moose density could be predicted from stratification data. Densities predicted from stratification data were compared with densities estimated from SRB surveys. A simple regression model demonstrated that moose seen per minute on the stratification surveys explains 81% of the variance in moose density. When applied to new data, the regression model predicted moose density with a 90% confidence interval of ± 72 moose per 1,000 km2. Changes in predicted moose density in excess of about 120 moose per 1,000 km2 are statistically significant (P < 0.05). Moose densities predicted from stratification data were not significantly different from SRB estimates in 6 test cases (P > 0.05), but fell outside the 90% confidence intervals of the SRB estimates in 4 of the 6 test cases. Management applications for moose density estimates derived from stratification survey data are discussed

PRELIMINARY REPORT ON ACCURACY OF AERIAL MOOSE SURVEYS

Sample quadrats were established around radiocollared moose and each quadrate was surveyed with a search intensity of approximately 4 to 5 min/mi2 using transect/contour searches similar to standard Alaska Department of Fish and Game surveys. A second, more intensive search of 10 to 13 min/m2 was then made of each quadrat. Substantially more moose were seen during the intensive search than during transect/contour surveys in all three physiographic areas. Habitat selected by moose was the most critical environmental factor affecting sightability of 45 radiotagged moose. During early and late winter, 84 and 61 percent, respectively of the radiocollared moose selected habitat types with low canopies (herbaceous, low shrub, and tall shrub). Moose using these open habitats were easier to see regardless of search intensity. Moose using forest habitats were often missed during the initial transect/contour survey but were usually seen later during the intensive search. Spruce-dominated quadrats were the only areas in which uniformly high sightability could not be achieved with intensive search effort. Activity of moose also affected sightability. Lying moose were missed more frequently than standing moose during transect/contour surveys and intensive searches. Snow condition was identified as having considerable influence upon sightability, but the adverse effects of poor snow condition were largely overcome by intensive search effort. The application of these data to moose trend surveys and censuses is discussed

ANTLER SIZE RELATIVE TO BODY MASS IN MOOSE: TRADEOFFS ASSOCIATED WITH REPRODUCTION

Body size and age are highly correlated with antler size, fighting ability, and reproductive success in male cervids. Production of antlers requires energy above that for maintenance of basal functions, and is especially demanding of minerals. In addition to producing antlers, young cervids also incur the cost of completing body growth. Large-bodies males with large antlers invest more in antler development and reproduction at the expense of body condition than do young males. Young males are constrained by the need to complete body growth to attain the body size necessary to compete effectively for females when mature and, hence, invest less in antlers. We tested the hypothesis that adult male moose (Alces alces) produced larger antlers relative to body mass than did younger males. We used regression to compare the ratio of antler length per unit body mass (antler length: body mass) with age. Regression analysis indicated a strong curvilinear relationship (Ra2 = 0.961) between antler length per unit body mass and age. Young males invested less in antlers than older males that had reached a sufficient size to compete effectively for mates; consequently, there was a tradeoff between body growth and antler size. Young males must produce antlers to gain experience in aggressive encounters and establish dominance relationships among their cohort, although investment in antlers is less than that of mature adults. Delaying investment in mating until physically mature and able to compete for females with other large-antlered males is the most successful strategy for maximizing mating success and achieving the greatest fitness in male moose, as well as among other cervids

GEOGRAPHICAL VARIATION IN ANTLER MORPHOLOGY OF ALASKAN MOOSE: PUTATIVE EFFECTS OF HABITAT AND GENETICS

We assessed antler size of Alaskan moose (Alces alces gigas) with respect to the geographic region and dominant vegetation community (taiga or tundra) from which they were harvested from 1968 to 1983. Our retrospective analysis indicated that moose from the Copper River Delta and Alaska Peninsula possessed the largest antlers, whereas those from southeast Alaska, USA, had the smallest antlers. Delta flood plains of the Copper River offer a rich food supply for moose, and browse on the Alaska Peninsula also is plentiful; both areas have mild maritime climates and longer growing seasons than tundra and taiga habitats in interior Alaska—large antlers in those moose populations likely were the result of superior nutrition. After controlling for age, antlers of moose from tundra communities were significantly larger than those inhabiting taiga. Willows (Salix spp.), which are an important food for moose, dominate braided rivers and associated riparian areas in tundra habitat, and provide a high-quality and stable food supply over time. Fire and subsequent successional changes dominate taiga landscapes, which results in a variable food supply that is sometimes low in quality and quantity. Again, forage abundance and quality likely play important roles in determining antler size for populations of Alaskan moose inhabiting those plant communities. Nonetheless, antlers of A. a. gigas from taiga regions in Alaska, USA, were larger than those of A. a. andersoni from similar habitat in northeastern Minnesota, USA, and Saskatchewan, Canada. In addition, moose from tundra habitat on the Seward Peninsula, Alaska, which have colonized that area within the last ~30 years from the boreal forest, possessed antlers intermediate in size between moose inhabiting taiga and tundra. Moreover, moose from forested areas of southeast Alaska, which have a unique mitochrondial DNA haplotype from other subspecies of moose, also had comparatively smaller antlers than other moose in Alaska. Those outcomes indicated that differences in antler size likely have a genetic in addition to a nutritional basis. We hypothesize that differences in antler size of Alaskan moose in relation to habitat may have genetic as well as nutritional underpinnings related to openness of habitat, but more research is needed. Finally, our results on antler morphology, in concert with information on pelage coloration and recent data on genetics, do not support hypotheses concerning a double migration, or eastern and western races of moose, forwarded to explain morphological variation in moose inhabiting the New World. Likewise, we reject the hypothesis that ecotypical differences are primarily responsible for morphological variation in subspecies of moose inhabiting North America