Diversity, Seasonality, and Context of Mammalian Roadkills in the Southern Great Plains

Thousands of mammals are killed annually from vehicle collisions, making the issue an important one for conservation biologists and environmental managers. We recorded all readily identifiable kills on or immediately adjacent to roads in the southern Great Plains from March 2004–March 2007. We also recorded distance traveled, whether a road was paved or divided, the number of lanes, and prevailing habitat. Surveys were opportunistic and were conducted by car during conditions of good visibility. Over our 239 surveys and >16,500 km traveled, we recorded 1412 roadkills from 18 different mammal species (size ranged from Sciurus squirrels to the white-tailed deer, Odocolieus virginianus). The overall kill rate was 8.50 / 100 km. Four species were prone to collisions: the Virginia opossum (Didelphis virginiana), nine-banded armadillo (Dasypus novemcinctus), striped skunk (Mephitis mephitis), and northern raccoon (Procyon lotor). Together they accounted for approximately 85% (1198) of all roadkills. Mortality rate differed significantly between 2- and 4-lane roads (8.39 versus 7.79 / 100 km). Kill rates were significantly higher on paved versus unpaved roads (8.60 versus 3.65 / 100 km), but did not depend on whether a road was divided. Roadkills were higher in spring than in fall (1.5×), winter (1.4×), or summer (1.3×). The spring peak (in kills / 100 km) was driven chiefly by the armadillo (2.76 in spring/summer versus 0.73 in autumn/winter) and opossum (2.65 versus 1.47). By contrast, seasonality was dampened by a late winter/early spring peak in skunk mortalities, for which 41% occurred in the 6-week period of mid-February through March. The raccoon did not exhibit a strong seasonal pattern. Our data are consistent with dispersal patterns of these species. Our results underscore the high rate of highway mortality in the southern plains, as well as differences in seasonality and road type that contribute to mortality. Conservation and management efforts should focus on creating underpasses or using other means to reduce roadkill rates.     

Predictors of occupancy trend across spatial scale

Many explorations of extinction probability have had a global focus, yet it is unclear whether variables that explain the probability of extinction at large spatial extents are the same as those at small spatial extents. Thus, we used nearly annual presence-absence records for the most recent 40 years of a 110-year data set from Palenque, Mexico, an area with ongoing deforestation, to explore which of >200 species of birds have probabilities of extirpation that are likely to increase. We assessed associations between long-term trends in species presence (i.e., detection in a given year) and body size, geographic range size, diet, dependence on forest cover, taxonomy, and ecological specialization. Our response variable was the estimated slope of a weighted logistic regression for each species. We assessed the relative strength of each predictor by means of a model ranking scheme. Several variables associated with high extinction probability at global extents, such as large body size or small geographic range size, were not associated with occurrence of birds over time at our site. Body size was associated with species loss at Palenque, but occurrence trends of both very large and very small species, particularly the latter, have declined, or the species have been extirpated. We found no association between declining occurrence trend and geographic range size, yet decline correlated with whether a species depends on forest (mean occupancy trend =-0.0380, 0.0263, and 0.0186 for, respectively, species with high, intermediate, or low dependence on forest) and with complex combinations of diet and foraging strata (e.g., occurrence of canopy insectivores and terrestrial omnivores has increased, whereas occurrence of mid-level frugivores and terrestrial granivores has decreased). Our findings emphasize that analyses of local areas are necessary to explicate extirpation risk at various spatial extents.