Simulating detection of cattle-fever tick ( Boophilus spp.) infestations in rotational grazing systems

Abstract

To evaluate the relative influence of ecological and management factors on the probability of detecting cattle-fever tick ( Boophilus microplus and Boophilus annulatus) infestations in rotational grazing systems, we adapted a simulation model of Teel et al. [J. Range Manage. 51 (1998) 501] that examines interactions among Boophilus ticks, cattle, and habitat type under rotational grazing systems developed for semi-arid shrublands of south Texas. We added a submodel that estimates probability of inspectors detecting Boophilus-tick infestations when examining 1, 20, 40, or 80 cows in a tick-infested herd of 80 cattle. Results indicate that probability of detecting infestations depends most on season of initial infestation; less heavily on rotational grazing strategy, habitat type, and number of cows inspected; and only moderately on initial number of infesting tick larvae. Results showed high detection probabilities (≥0.95) usually exist as temporal windows of opportunity during brief but definite periods; outside these windows, detection of existing infestations becomes poor. Each halving of the number of cows inspected tended to shorten duration of these windows by approximately 40%. Probability of detecting tick infestations, however, also depends strongly on inspector training, cow behavior, and weather, factors that we set as implicit constants. Models such as this one can indicate gaps in knowledge about the influence of biophysical and human factors on detection efforts in tick eradication or control programs, estimate magnitude and duration of Boophilus-tick infestations, and indicate potentially favorable inspection periods.