At high densities, moose can do extensive damage to forests by over browsing - altering forest composition and forest succession. One moose may consume 30 kg of vegetation per day. Fundy National Park conducts aerial censuses of the moose population every 5 years.

A moose population survey was conducted on the Yukon Flats in November/December 2018. This was the first fall survey since 2015. Moose were counted in 97 of 421-5.3mi2 units, of which 63 were stratified high moose density and 34 low moose density. The estimate for the 2,269 mi2 survey area in the western Yukon Flats (Alaska Game Management Unit [GMU] 25D) was 1123 total observable moose (95% CI; 895-1351). Density of moose was 0.49/mi2 or 0.19/km2. The population was comprised of an estimated 908 adults (95% CI; 698-1118) and 199 calves (148-251). Search time averaged 6.0 minutes/mi2. The estimate of total observable moose increased from the lows of 2004-2010. Improved calf survival may have contributed to the population increase in some years. It is unlikely that public harvest of wolves and bears contributed, as harvest intensity is light. Thus, moose density increased in the presence of lightly harvested wolf and bear populations, suggesting that the dynamics of this low density population may sometimes be more complex than previously thought. Moose numbers can fluctuate naturally within a low density equilibrium over a period of approximately a decade, and this fluctuation can be detected with the current survey method.

The population estimate for the western Yukon Flats in Game Management Unit (GMU) 25D (2,269 square miles) was 632 moose (Alces alces) with a certainty of +1- 20% (758/506) at the 90% confidence level. Estimated population density in the high and low density areas was 0.57 and 0.19 moose per square mile, respectively, with an average density estimate of 0.28 moose per square mile. Calves comprised 15% of the estimated total population. Search times averaged 6.2 minutes per square mile.

Moose habitat and movement throughout Colorado.

A moose population survey was conducted on the Yukon Flats in November 2015. This was the first fall survey since 2010 due to a lack of sufficient snow in early winter that caused surveys in 2012-2014 to be cancelled. Moose were counted in 100 of 421-5.3mi2 units, of which 59 were stratified high moose density and 41 low moose density. The estimate for the 2,269 mi2 survey area in the western Yukon Flats (Alaska Game Management Unit [GMU] 25D) was 790 total observable moose (95% CI; 600-980). Density of moose was 0.35/mi2 or 0.13/km2. The population was comprised of an estimated 609 adults (95% CI; 460-759) and 191 calves (126256. Search time averaged 6.7 minutes/mi2. The estimate of total observable moose increased from 2010 to 2015. Improved calf survival may have contributed to the population increase in some recent years. It was unlikely that public harvest of wolves and bears contributed, as harvest intensity was light. Thus, moose density increased in the presence of lightly harvested wolf and bear populations, suggesting that the dynamics of this low density population may sometimes be more complex than previously thought.

What? An aerial wildlife population survey is used in Cape Breton Highlands National Park to estimate moose (Alces alces) population density. When? Monitoring frequency for this measure occurs every two to three years. Surveys take place in early March when there is snowpack present, the weather is stable, and sightability is increased by sun angle and day length. How? The population survey uses a random stratified design. The study area is Cape Breton Highlands National Park (950km2) and is divided up into Survey Units (SU’s) or “blocks”. Survey units are numbered sequentially in rows running from west to east, beginning in the north. Stratification lines are flown along transects running through the center point of each survey unit, and cluster analysis is used to assign all survey units a moose density stratum: High, Medium or Low. Survey units are randomly selected from each stratum to be flown in the block survey. 50 survey units are initially selected (35 Low, 10 Medium, 5 High), with more survey units added as necessary to obtain a population estimate with a 90% confidence interval. Why? Moose are the top herbivore in Cape Breton Highlands National Park. Benefiting from favourable conditions following a spruce budworm outbreak and, having no significant natural predators, the moose population has become hyperabundant, resulting in negative impacts to the parks forest ecosystem. This survey every helps to monitor changes in moose density in the park, and determine if it is at a sustainable level (ie. within the natural range of variability observed in predator controlled populations).

Moose distribution, season of habitat use, and habitat values are determined by local wildlife biologist relying on observations, surveys, and radio/satellite data. For use in large-scale planning and reporting.Habitat definitions:Crucial value - habitat on which the local population of a wildlife species depends for survival because there are no alternative ranges or habitats available. Crucial value habitat is essential to the life history requirements of a wildlife species. Degradation or unavailability of crucial habitat will lead to significant declines in carrying capacity and/or numbers of wildlife species in question.Substantial value - habitat used by a wildlife species but is not crucial for population survival. Degradation or unavailability of substantial value habitat will not lead to significant declines in carrying capacity and/or numbers of the wildlife species in question.

A moose population survey was conducted on the Yukon Flats National Wildlife Refuge in March 2013. Moose were counted in 101 of 421-5.3 mi2 units, of which 68 were stratified high moose density and 33 low density. The estimate for the 2,269 mi2 survey area in the western Yukon Flats (Alaska Game Management Unit [GMU] 25D) was 460 total observable moose (95% CI; 345-575). Density of moose was 0.20/mi2 or 0.08/km2. The population was comprised of 364 adults (95% CI; 269-458) and 103 calves (63-143). Search time averaged 6.3 minutes/mi2. The number of calves was high relative to other spring surveys, but the reasons for this are not known. There was no detectable trend in spring numbers of total observable moose. Moose on the Yukon Flats continue to persist at low densities, which has been documented for >50 years. Continued conservative management of harvest is recommended.

Updated December, 2024CONCENTRATION AREA: That part of the range of a species where densities are 200% higher than the surrounding area during a specific season. OVERALL RANGE: The area which encompasses all known seasonal activity areas within the observed range of a population of moose. SUMMER RANGE: That part of the overall range where 90% of the individuals are located during the summer months. This summer time frame will be delineated with specific start/end dates for each moose population within the state (ex: May 1 to Sept 15). Summer range is not necessarily exclusive of winter range. WINTER RANGE: That part of the overall range where 90 percent of the individuals are located during the winter months. This winter time frame will be delineated with specific start/end dates for each moose population within the state (ex: November 15 to April 1).This information was derived from Colorado Parks and Wildlife field personnel. Data was captured by digitizing through a SmartBoard Interactive Whiteboard using topographic maps and NAIP imagery at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35). These data are updated on a four year rotation with one of the four Colorado Parks and Wildlife Regions updated each year. These data are not updated on a statewide level annually.

Introduced Moose, lacking natural predators in Gros Morne, are causing widespread damage in park forests. Park-wide Moose density will be monitored using aerial surveys and estimated using the Gasaway (1986) stratified random block method. Bull, cow, calf and unknown Moose are counted in randomly-selected blocks expected to have extremely high, high and low moose density. Survey occurs in late February or March, with sufficient snow cover to see tracks.

At high densities, moose can do extensive damage to forests by over browsing - altering forest composition and forest succession. One moose may consume 30 kg of vegetation per day. Fundy National Park conducts aerial censuses of the moose population every 5 years.

In 2014, we initiated an investigation into the role of wolf (Canis lupus) and brown bear (Ursus arctos) predation in regulating the population dynamics of moose (Alces alces) on Togiak National Wildlife Refuge (Refuge), BLM Goodnews Block, and adjacent areas. We will relate the predation impact by wolves and bears on moose at varying levels of moose population density. We will use existing population estimates for brown bears, and through the use of radio telemetry, we will estimate the number and composition of wolf packs on the Refuge. We will model wolf and bear predation on moose based on the quantity of wolves and bears and diet composition of both species determined through analysis of carbon (13C) and nitrogen (15N) stable isotopes. To date, we have gathered demographic and isotopic data on 25 wolves from nine wolf packs, and have collected approximately 400 brown bear hair samples. Genetic and isotopic analyses have been successfully performed on 139 bear samples. This reports our progress to date, and identifies the remaining data gaps.

Monitoring widely distributed species on a budget presents challenges for the spatio-temporal allocation of survey effort. When there are multiple discrete units to monitor, survey alternatives such as model-based estimates can be useful to fill information-gaps but may not reliably reflect biological complexity and change. The spatio-temporal allocation of survey effort that minimizes uncertainty for the greatest number of units within a budget can help to ensure monitoring efforts are optimized. We used aerial survey-based population estimates of moose (Alces alces) across 30 Wildlife Management Units (WMUs) in Ontario, Canada to parameterize simulated populations and test the performance of different monitoring scenarios in capturing WMU-specific annual variation and trends. Firstly, we tested scenarios that prioritized conducting a survey for a unit based on one of three management criteria: population state, population uncertainty, or number of years between surveys. Also incorporated in the decision framework were WMU-specific costs and annual budget constraints. Secondly, we tested how using model-based estimates to fill information-gaps improved population and trend estimates. Lastly, we assessed how the utility (based on minimizing population uncertainty) of using a model-based estimate rather than conducting a survey was impacted by population density, severity of environmental stressors, and years since the last survey. Interval-based monitoring that minimized the number of years between surveys captured accurate trends for the highest number of WMUs, but annual variation was poorly captured regardless of management criteria prioritized. Using model-based estimates to fill information gaps improved trend estimation. Further, the utility of conducting a survey increased with time since the last survey and was greater for populations with low densities when the severity of environmental stressors was high, while being greater for populations with high densities when environmental severity was low. Overall, the utility of aerial survey monitoring was strongly associated with WMU-specific monitoring precision and the predictive power of model-based estimates. If long-term trends are evident then there is greater value in using alternatives such as model-based predictions to replace surveys, but model-based estimates may be a poor substitute when there is strong annual variation and when using a simple model. This file includes moose density (moose/km2) estimates for 30 Wildlife Management Units (WMUs) derived from plot-based aerial-surveys conducted by the Ministry of Northern Development, Mines, Natural Resources, and Forestry (formerly called the Ontario Ministry of Natural Resources and Forestry, OMNRF) over 25 years (1991 – 2015). The data presented here represents derived estimates per WMU and year. The original moose aerial inventory data are available upon request from the Ministry of Northern Development, Mines, Natural Resources, and Forestry.

The relative effect of top-down versus bottom-up forces in regulating and limiting wildlife populations is an important theme in ecology. Untangling these effects is critical for a basic understanding of trophic dynamics and effective management. We examined the drivers of moose (Alces alces) population growth by integrating two independent sources of observations within a hierarchical Bayesian population model. This analysis used one of the largest existing spatiotemporal datasets on ungulate population dynamics globally. We documented a 20% population decline over the period examined. Moose population growth was negatively density-dependent. Although the mechanisms producing density-dependent suppression of population growth could not be determined, the relatively low densities at which moose populations were documented suggests it could be due primarily to density-dependent predation. Predation primarily limited population growth, except at low density, where it was regulating. Harvest appeared to be largely additive and contributed to population declines. Our results, highlight how population dynamics are context dependent and vary strongly across gradients in climate, forest type, and predator abundance. These results help clarify long-standing questions in population ecology and highlight the complex relationships between natural and human-caused mortality in driving ungulate population dynamics. Data is found here on Dryad (moose_data_dryad.RData), but the R scripts (run_jags_model.R and gompertz_jags.R) are found on Zenodo (https://doi.org/10.5281/zenodo.6030027). See the README.txt for a description of all 3 files. See the manuscript for details on how the dataset was collected and processed.

This report summarizes a study done on Kenai National Wildlife Refuge to determine which habitats moose prefer to calve in. The majority of observations of female moose,(Alces alces) with recently-born calves have been in open, bog-meadow, black spruce, (Picea mariana), habitats on the Kenai National Moose Range, but many moose probably calve in other areas where they are more difficult to observe. Frequent aerial surveys over the Moose-Chickaloon River Area during the calving period from 1957 to 1970 revealed maximum numbers of observed cows in the calving area in 1964, or 17 years after a major wildfire burned through the area. Numbers of observed cows declined after several years of antlerless seasons and several severe winters but increased again after antlerless seasons were suspended and winters moderated. Numbers of observed calves paralleled numbers of observed cows. Maximum twinning rates declined from a high of 46 percent in 1962 to 7 percent in 1966 but increased to 48 percent in 1969. Twinning rates appeared related to forage conditions, mild winters and moose density. General observations and observed numbers of calves suggest two birth peaks may have occurred in the 1960's, one in early June and another in early July. Population estimates suggest generally less than 20 percent of the refuge's moose population calve in the Moose-Chickaloon River Area.

Parameter estimates after model averaging from the most parsimonious models (ΔAICc < 4, Table 2) predicting the selection of roe deer (1) over moose (0) as kills for wolves in Scandinavia, in relation to roe deer density (Roe deer) and moose density (Moose).

Wolf territory is included as a random factor and the number of parameters in the model is indicated by K, AIC corrected for small sample size AICc, differences between models ΔAIC, the model weights AICcWt, and the log likelihood value for each model LL.

Moose aerial surveys are conducted approximately every 5 years by helicopter, subject to snow and weather conditions or to coincide with a survey being done in the adjacent Wildlife Management Unit. The dataset includes surveys conducted during the winters of 1996, 1999, 2003, 2008, 2009, 2011 and 2017. Plots to be surveyed are randomly selected from the ninety-seven 25 km² plots within the park and flown with rotary wing aircraft. Prior to the 2017 survey, paper maps and data sheets were used to record information. In 2017, Avenza software and geoPDF maps on an android tablet were used and data were transferred to paper after landing. The objectives of the survey are to monitor moose density, productivity and sex ratio.

Maps of Nova Scotia showing distribution of (Fig. A1) moose populations and protected areas; (Fig. A2) moose habitat suitability values; (Fig. A3) road density and moose pellet presence/absence; (Fig. A4) contiguous areas of natural cover 10,000 ha; (Fig. A5) roadless areas; (Fig. A6) uneven-aged forest stands; (Fig. A7) combined cover for contiguous natural cover 10,000 ha, roadless areas, and uneven-aged forest stands; (Fig. A8) areas of primary priority combining natural areas, 10,000 ha, uneven-aged forest stands, and roadless areas; (Fig. A9) species at risk globally or provincially; (Fig. A10) highest rarity-weighted richness values; (Fig. A11) significant ecosites; (Fig. A12) signigficant old and unique forest stands; (Fig. A13) areas of primary priority for special elements; highest habitat suitability and population densities for (Fig. A14) American moose, (Fig. A15) American marten, and (Fig. A16) Northern Goshawk; (Fig. A17) 47 core areas selected by priority sites for representation, special elements, and focal species; (Fig. A18) cost-surface for American marten; and (Fig. A19) least-cost paths for American marten.

For each area and period, we provide the estimated deer abundance (N), 95% confidence interval (CI), coefficient of variation (CV), and ΔAIC.