A New Birth-Interval Approach to Estimating Demographic Parameters of Humpback Whales

A demographic model is developed based on interbirth intervals and is applied to estimate the population growth rate of humpback whales (Megaptera novaeangliae) in the Gulf of Maine. Fecundity rates in this model are based on the probabilities of giving birth at time t after a previous birth and on the probabilities of giving birth first at age x. Maximum likelihood methods are used to estimate these probabilities using sighting data collected for individually identified whales. Female survival rates are estimated from these same sighting data using a modified Jolly–Seber method. The youngest age at first parturition is 5 yr, the estimated mean birth interval is 2.38 yr (SE = 0.10 yr), the estimated noncalf survival rate is 0.960 (SE = 0.008), and the estimated calf survival rate is 0.875 (SE = 0.047). The population growth rate (l) is estimated to be 1.065; its standard error is estimated as 0.012 using a Monte Carlo approach, which simulated sampling from a hypothetical population of whales. The simulation is also used to investigate the bias in estimating birth intervals by previous methods. The approach developed here is applicable to studies of other populations for which individual interbirth intervals can be measured.

Using Genetics to Assess Differentiation Among Raccoons in an Area with Variable Rabies Status in Alabama

The western spread of raccoon rabies in Alabama has been slow and even appears to regress eastward periodically. While the disease has been present in the state for over 30 years, areas in northwest Alabama are devoid of raccoon rabies. This variation resulting in an enzootic area of raccoon rabies primarily in southeastern Alabama may be due to landscape features that hinder the movement of raccoons (i.e., gene flow) among different locations. We used 11 raccoon-specific microsatellite markers to obtain individual genotypes to examine gene flow among areas that were rabies free, enzootic with rabies, or had only sporadic reports of the disease. Samples from 70 individuals were collected from 5 sampling localities in 3 counties. The landscape feature data were collected from geographic information system (GIS) data. We inferred gene flow by estimating FST and by using Bayesian tests to identify genetic clusters. Estimates of pairwise FST indicated genetic differentiation and restricted gene flow between some sites, and an uneven distribution of genetic clusters was observed. Of the landscape features examined (i.e., land cover, elevation, slope, roads, and hydrology), only land cover had an association with genetic differentiation, suggesting this landscape variable may affect gene flow among raccoon populations and thus the spread of raccoon variant of rabies in Alabama.