We used 38,709 fixes collected from December 2003 through June 2006 from 44 elk (Cervus elaphus) fitted with Global Positioning System collars and hourly traffic data recorded along 27 km of highway in central Arizona, USA, to determine how traffic volume affected elk distribution and highway crossings. The probability of elk occurring near the highway decreased with increasing traffic volume, indicating that elk used habitat near the highway primarily when traffic volumes were low (<100 vehicles/hr). We used multiple logistic regression followed by model selection using Akaike's Information Criterion to identify factors influencing probability of elk crossings. We found that increasing traffic rates reduced the overall probability of highway crossing, but this effect depended on both season and the proximity of riparian meadow habitat. Elk crossed highways at higher traffic volumes when accessing high quality foraging areas. Our results indicate that 1) managers assessing habitat quality for elk in areas with high traffic‐volume highways should consider that habitat near highways may be utilized at low traffic volumes, 2) in areas where highways potentially act as barriers to elk movement, increasing traffic volume decreases the probability of highway crossings, but the magnitude of this effect depends on both season and proximity of important resources, and 3) because some highway crossings still occurred at the high traffic volumes we recorded, increasing traffic alone will not prevent elk‐vehicle collisions. Managers concerned with elk‐vehicle collisions could increase the effectiveness of wildlife crossing structures by placing them near important resources, such as riparian meadow habitat.

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Bird abundance trends have been correlated with habitat changes in urban developed areas but have seldom been associated with specific patterns of urban‐related habitat changes. We examined breeding bird–habitat relationships in 334 random plots ranging from undisturbed natural to highly developed land in Tucson, Arizona. In each plot we quantified 19 variables describing three land cover patterns (habitat physiognomy, floristics, and spatial relationships of native habitat fragments) and correlated them with abundances of 21 bird species. Abundances of 17 bird species were associated with variables describing land cover pattern. In addition, we correlated abundance, species richness, and evenness for three bird guilds (non‐natives, natives, and a native indicator guild) with land cover variables. Housing density best explained the variation in species richness for both the non‐native (r2 = 0.79) and the indicator guilds (r2 = −0.69), whereas area of Upland Sonoran vegetative cover (r2 = 0.56) and distance from undisturbed washes (r2 = −0.56) correlated most strongly with the native‐bird group. Finally, we developed and tested regression models predicting species richness for each bird guild. The following variables loaded into the predictive models: house density; percentage cover of paved areas; exotic, Upland Sonoran, and undisturbed riparian vegetation; and distance from undisturbed washes. The models explained 71% of the variation in non‐native bird species richness, 56% of the variation in native bird species richness, and 60% of the variation in species richness for the indicator guild of birds. The correlations and regression models can be used to predict species richness responses to future residential development in the Tucson area.

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