We tested the prediction that home range area and dispersal distance in mammals are related when considered independently of body size. Regression of logtransformed data demonstrated that more variance in maximum dispersal distance could be explained by home range area (74%) than could be explained by body size (50%). The relationship between maximum dispersal distance and home range size was isometric (slope ϭ 1) when the square root of home range area (i.e., linear dimension of home range) was used. Thus, maximum dispersal distance was related to home range size by a single constant of 40. A linear relationship remained between these two variables after the effects of body size were removed (F ϭ 31.6, df ϭ 1, 32, P ϭ 3.2 ϫ 10 Ϫ6 , R 2 ϭ 0.50). A similar isometric relationship with home range size was found for median dispersal distance (related by a multiple of 7). This isometric relationship between dispersal distance and home range size was tested using a second data source: maximum movements made by mammals after translocation, which also was linearly related to home range area (F ϭ 94.5, df ϭ 1, 23, P ϭ 1.3 ϫ 10 Ϫ9 , R 2 ϭ 0.81). The slope and intercept of this relationship were not different from those of the relationship between maximum dispersal distance and home range area. We suggest that the vagility of mammals affected both home range size and dispersal distance (or movement after translocation) independently of body size, such that these movements could be predicted by home range area better than by body size alone. The resulting isometric relationship between dispersal distance and home range size has potential as a useful scaling rule for ecological practitioners.
ABSTRACT. Many habitat fragmentation experiments make the prediction that animal population density will be positively related to fragment, or patch, size. The mechanism that is supposed to result in this prediction is unclear, but several recent reviews have demonstrated that population density often is negatively related to patch size. Immigration behavior is likely to have an important effect on population density for species that do not show strong edge effects, for species that have low emigration rates, and during short-term habitat fragmentation experiments. We consider the effect that different kinds of immigration behaviors will have on population density and we demonstrate that only a minority of possible scenarios produce positive density vs. patch size relationships. More commonly, these relationships are expected to be negative. Our results demonstrate the importance of considering autecological mechanisms, such as immigration behavior, when developing the predictions that we test in habitat fragmentation or other experiments.
White-tailed deer (Odocoileus virginianus) exhibit a variety of migration strategies across northern portions of their range. Factors reported as being responsible for migration initiation have shown no consistent pattern. We monitored 186 radiocollared white-tailed deer from 1994 to 1998 in 2 areas of New Brunswick: a southern area with moderate and variable winter climate and a northern area with consistently severe winter climate. We determined that deer in the south contained a large proportion of conditional migrators (individuals that may or may not migrate to winter range in a given year, and may or may not remain until spring), whereas deer in the north consisted almost entirely of obligate migrators (those that annually migrate to winter range for the duration of winter). Occurrence of conditional migration appeared to be a function of climate variability, although distribution of the behavior among individual deer was influenced by migration distance. Initiation of autumn migration in the south was related to snow depth for most deer and represented a response to the proximate cue of the onset of limiting conditions. Autumn migration in the north appeared to be a response to seasonal cues, and the direct influence of snow depth was reduced. Initiation of spring migration in the 2 study areas showed a similar pattern. Migration distance may represent a factor influencing distribution of migrational cues among individual deer within a population. The effect of winter climate variability on deer migration behavior may account for the disparity in behavior reported in the literature. The differences in migration behavior have implications for deer management surveys in northern areas where deer yarding occurs. Managers have assumed that deer observed during winter surveys were on winter range, but this may not be a reasonable assumption in areas with variable winter climates.
Recent research shows that density dependence should result in predictable movements between habitats of different suitability, depending on whether population densities are increasing or decreasing. When population densities are increasing, habitats become filled in order of their suitability, resulting in a net flow from high suitability to low suitability. When populations decrease in density, the reverse can happen. These patterns suggest that genetic information can be used to infer habitat suitability since individual-based genetic assignment tests permit high resolution assessments of migration. We used replicated landscapes to study fishers (Martes pennanti ) during a population increase and predicted that there should be a net flow of individuals from areas of shallow to deep snow, since snow depth has previously been linked to fisher fitness. A total of 769 fishers were sampled from 35 different landscapes and profiled at 16 microsatellite loci. From assignment tests, we inferred five genetic populations. By assigning each of the 35 landscapes to one of these five populations, we were able to determine the proportion of immigrants to each. Consistent with our prediction, there was a positive relationship between the proportion of immigrants and snow depth. The best model of fisher habitat suitability was one with both snow depth and the proportion of coniferous forest in landscapes. Our findings suggest that where population trend is known, genetic information can be used to measure habitat suitability.
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