Effective population density and intergenerational dispersal distance are key aspects of population biology, but obtaining empirical estimates of these parameters can be difficult. This is especially true for my study taxa, wild bees. In this paper, I apply and evaluate an existing but underutilized method to estimate the effective density and dispersal distance of bumble bees (Bombus, Apidae). Specifically, using 10 datasets of bumble bees in North America, I use the relationship between genetic isolation-by-distance and Wright’s neighborhood size to define a density-dispersal isocline—that is, a curve describing pairs of density and dispersal values consistent with observed rates of isolation-by-distance. These parameters are inversely related; as one increases, the other decreases. I then use outside estimates of bumblebee dispersal distances to make more specific estimates of effective colony density. Compared to some prior estimates of census density (100s to 1000s colonies/km2), my estimated effective colony densities were very low (1–41 effective colonies/km2). I also hypothesize, however, that these estimates are affected by the spatial extent of sampling, due to scale-dependent patterns in the distribution of individuals. To test this hypothesis, I subsampled each dataset to simulate varying study extent, and repeated my analysis. Within populations, effective densities tended to decrease when measured across larger spatial extents. Altogether, I demonstrate a useful and under-appreciated tool for studying population biology, especially of small, mobile animals like bees, but also show that researchers must interpret their results carefully within the context of their study design.

Habitat is a key aspect of any species’ niche and can affect populations at multiple spatial scales. Basic ecology and effective conservation thus require understanding which habitats matter and at which scales. Yet, habitat studies are rarely scale-optimized and what determines the scale(s) at which populations are affected by surrounding habitat (the “scale of effect”) is poorly understood. In this study, we test the “mobility hypothesis,” which predicts that species with larger foraging ranges should have larger scales of effect. The mobility hypothesis is the most popular explanation of what determines species’ scales of effect but empirical support is mixed. We test the mobility hypothesis using wild bee species and, in doing so, also assess landscape-scale habitat associations of 84 bee species. We collected 30,376 specimens of 84 bee species from 165 sites in the northeastern USA and used linear models to determine landcover associations and scales of effect for each species. To test the mobility hypothesis, we asked whether scales of the effect varied with two mobility-related traits - body size or sociality, which are the strongest known predictors of bee foraging ranges. Controlling the false discovery rate at 5%, we found 193 significant species-landcover associations across 60 (of 84) species. Scales of effect ranged from 100 to 8000 m (mode = 200 m; median = 1000 m) and – counter to the mobility hypothesis – were not associated with body size or sociality. As a result, we argue that ecologists should reconsider making assumptions about species’ scales of effect and should instead explicitly measure scales of effect for their particular study organism and system. Considering the landcover associations themselves, we found these were broadly explained by phenology, with spring-flying bees being associated with forests and summer-flying bees being associated with more open, non-forested habitats.

A zip file containing data and R scripts to reproduce all results and figures

A zip file containing data and R scripts to reproduce all results and figures

A zip file containing data and R scripts to reproduce all results and figures