Abstract. Wildlife managers are often asking for reliable information of population density across larger spatial scales. In this study, we examined the spatiotemporal relationships between moose density as estimated by cohort analysis and the density indices (1) harvest density (HD; hunter kills per km 2 ), (2) moose seen per unit effort (SPUE), seen moose density (SMD; seen moose per km 2 ), and density of moosevehicle accidents (MVA density; e.g., traffic kills per km 2 ) in 16 areas in Norway with 13-42 years of data. HD showed a close positive relationship with moose density both within and between regions. However, the temporal variation in HD was best explained as a delayed reflection of moose density and tended to overestimate its growth and decline. Conversely, SMD and SPUE were unable to predict the spatial variation in moose density with high precision, though both indices were relatively precise temporal reflectors of moose density. However, the SPUE tended to underestimate population growth, probably because of a decrease in searching efficiency with increasing moose density. Compared to the other indices, MVA density performed poor as an index of moose density within regions, and not at all among regions, but may, because of its independent source of data, be used to cross-check population trends suggested by other indices. Our study shows that the temporal trends in moose density can be surveyed over large areas by the use of cheap indices based on data collected by hunters and local managers, and supports the general assumption that the number of moose killed per km 2 provides a precise and isometric index of the variation in moose density at the spatial scale of our study.

Carrying capacity is 1 driver of wildlife population dynamics. Although in previous studies carrying capacity was considered to be a fixed entity, it may differ among locations due to environmental variation. The factors underlying variability in carrying capacity, however, have rarely been examined. Here, we investigated spatial heterogeneity in the carrying capacity of Japanese sika deer ( Cervus nippon ) from 2005 to 2014 in Yamanashi Prefecture, central Japan (mesh with grid cells of 5.5×4.6 km) by state-space modeling. Both carrying capacity and density dependence differed greatly among cells. Estimated carrying capacities ranged from 1.34 to 98.4 deer/km 2 . According to estimated population dynamics, grid cells with larger proportions of artificial grassland and deciduous forest were subject to lower density dependence and higher carrying capacity. We conclude that population dynamics of ungulates may vary spatially through spatial variation in carrying capacity and that the density level for controlling ungulate abundance should be based on the current density level relative to the carrying capacity for each area.

Abstract. Cohort analysis (also known as virtual population analysis) is a method of population reconstruction from age-specific harvest data. Because cohort analysis requires data over a whole life span to reconstruct a population for a single year, this method is impracticable for longer-lived animals. Three models are routinely combined by fisheries scientists to make cohort analysis more cost effective and to provide real-time estimates of population size; these models may be applied to large terrestrial mammal harvest data. Each model has unique assumptions about hunting mortality rates or age distributions, and the reliability of estimates depends on meeting these assumptions. In this study, we first tested previously used assumptions for these models through an analysis of longterm moose (Alces alces) harvest data, followed by an examination of the robustness of estimates for each moose age class. We developed practical ways to achieve more realistic assumptions for two of three models and showed that meeting these assumptions was more important in estimations of large terrestrial mammal population parameters than for fish population parameters. Therefore, we recommend compliance with assumptions of the three models for more reliable population estimates of large terrestrial mammals.

: Wildlife managers often manipulate hunting regulations to control deer populations. However, few empirical studies have examined the level of hunting effort (hunter‐days) required to limit population growth and demographic effects through harvesting of females. Moreover, the relative importance of density effects on population growth has not been quantified. We reconstructed a sika deer [Cervus nippon] population over a period of 12 years (1990–2001) using age‐ and sex‐specific harvest data. Using cohort analysis, we analyzed population dynamics, focusing on 1) the relationship between hunting effort and hunting‐induced mortality rate, 2) relative contributions of hunting mortality and recruitment of yearlings to annual changes in population growth rate, and 3) annual variation in recruitment rate. Population size increased until 1998 and declined thereafter. The population growth rate changed more in response to annual changes in recruitment rate than hunting mortality rate. Temporal variation in recruitment rate was not controlled by birth rate alone; direct density dependence, intensities of hunting mortality for fawns, and for females (≥2 yr of age), which accounted for the fawn survival rate, were required as factors to explain temporal variation. Density effects on the recruitment rate were not strong enough to regulate the population within the study period; high hunting mortality, with intensive female harvesting, was necessary to prevent population growth. Hunting effort was a good predictor of the hunting mortality rate, and female harvest had a negative effect on the recruitment rate through fawn survival. We suggest that >3,500 hunter‐days and prioritization of female harvesting are required to prevent increases in this deer population.

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