Management of game animals requires understanding of factors that affect harvest levels. Although influenced by international law, bobcat (Lynx rufus) management is the responsibility of state or provincial agencies, and jurisdictional environmental, ecological, and regulatory differences may alter which variables influence harvest. Consequently, our understanding of the factors driving bobcat harvest should be at a scale similar to that at which they are managed. We associated 32 years of bobcat harvest data from Minnesota with socioeconomic (e.g., pelt prices, license sales) and ecological variables (e.g., prey abundance, bobcat-specific index of winter severity) to determine what variables most strongly influenced annual bobcat harvest. We constructed candidate negative binomial generalized linear models based on an information–theoretic approach and used quasi-likelihood Akaike's Information Criterion adjusted for small sample size to assess the relative performance of each model. Our best model suggested that annual bobcat harvest in Minnesota was positively related to the proportion of scent stations visited by bobcats and season length, and negatively related to the proportion of days when the maximum temperature did not exceed the bobcat's lower critical temperature. Our results differ from those of other studies examining factors influencing furbearer harvest that have suggested furbearer harvest is driven primarily by pelt price, and suggest that managers can influence the annual harvest of bobcats by changing season length. © 2011 The Wildlife Society.