A predictive model of avian natal dispersal distance provides prior information for investigating response to landscape change

Abstract

Summary1. Informative Bayesian priors can improve the precision of estimates in ecological studies or estimate parameters for which little or no information is available. While Bayesian analyses are becoming more popular in ecology, the use of strongly informative priors remains rare, perhaps because examples of informative priors are not readily available in the published literature. 2. Dispersal distance is an important ecological parameter, but is difficult to measure and estimates are scarce. General models that provide informative prior estimates of dispersal distances will therefore be valuable. 3. Using a world-wide data set on birds, we develop a predictive model of median natal dispersal distance that includes body mass, wingspan, sex and feeding guild. This model predicts median dispersal distance well when using the fitted data and an independent test data set, explaining up to 53% of the variation. 4. Using this model, we predict a priori estimates of median dispersal distance for 57 woodlanddependent bird species in northern Victoria, Australia. These estimates are then used to investigate the relationship between dispersal ability and vulnerability to landscape-scale changes in habitat cover and fragmentation. 5. We find evidence that woodland bird species with poor predicted dispersal ability are more vulnerable to habitat fragmentation than those species with longer predicted dispersal distances, thus improving the understanding of this important phenomenon. 6. The value of constructing informative priors from existing information is also demonstrated. When used as informative priors for four example species, predicted dispersal distances reduced the 95% credible intervals of posterior estimates of dispersal distance by 8-19%. Further, should we have wished to collect information on avian dispersal distances and relate it to species' responses to habitat loss and fragmentation, data from 221 individuals across 57 species would have been required to obtain estimates with the same precision as those provided by the general model.

Comparative Tests of Birds Support a Link between Sex-Biased Dispersal and Body Size

“…Our comparative tests support the prediction that sex-biased dispersal is related to body size [9,10,12]. Specifically, we find that larger species have more male-biased dispersal, that distance is increasing more rapidly in males than in females, and that female and male distances are both positively correlated with their sex-specific masses (Tables 1 and 2; Figure 1; Supplemental Table 3).…”

“…Conversely, previous studies of species-specific dispersal have focused instead on the potential effects of other life history traits such as body size and territory area [9][10][11]. In particular, prior species-specific investigations have found that the natal dispersal distances (hereafter, referred to as distances) of a group are positively correlated with body size [12,13]. In animals, one explanation for this positive correlation is that the mass-specific energy cost of transport (COT) decreases with body size, thereby making it relatively cheaper for larger species to move farther [14,15].…”

“…The sex-biased dispersal of birds was then scored as three continuous characters that were obtained from the separate female and male median or average distances of Sutherland et al [9], Garrard et al [12], and Mabry et al [7]. These two sets of binary and continuous characters were chosen as complementary and were therefore analyzed separately throughout our study.…”

“…Female and male median distances (in meters) were obtained from Sutherland et al [9], Garrard et al [12], and Mabry et al [7] for 44 species from 10 orders (Supplemental Table 1). Following Mabry et al, these sex-specific median distances for 44 species were supplemented with the female and male average distances (in meters) for another 18 species that represented an additional three orders.…”

“…The significance of each correlation was tested with Pearson's r. These correlation analyses were complemented with ordinary least squares regressions whose y intercept was set to 0 [22]. Characters of mass are routinely taken in regression analyses as the independent variables [9][10][11][12][13], because body size imposes physical constraints on the variation of many biological traits [14]. Thus, the mass and mass ratio characters were treated as the independent variables in their regressions with distance and distance ratio.…”