Estimating the frequency of Cry1F resistance in field populations of the European corn borer (Lepidoptera: Crambidae).

BACKGROUND: Transgenic corn hybrids that express toxins from Bacillus thuringiensis (Bt) have suppressed European corn borer populations and reduced the pest status of this insect throughout much of the US corn belt. A major assumption of the high-dose/refuge strategy proposed for insect resistance management and Bt corn is that the frequency of resistance alleles is low so that resistant pests surviving exposure to Bt corn will be rare. RESULTS: The frequency of resistance to the Cry1F Bt toxin was estimated using two different screening tools and compared with annual susceptibility monitoring based on diagnostic bioassays and LC50 and EC50 determinations. An F1 screening approach where field-collected individuals were mated to a resistant laboratory strain and progeny were assayed to determine genotype revealed that resistance alleles could be recovered even during the first year of commercially available Cry1F corn (2003). Estimates of frequency from 2003-2005 and 2006-2008 indicated that, although allele frequency was higher than theoretical assumptions (0.0286 and 0.0253 respectively), there was no indication that the frequency was increasing. Similar estimates in 2008 and 2009 using an F2 screening approach confirmed the presence of non-rare resistance alleles (frequency ≈ 0.0093 and 0.0142 for 2008 and 2009, respectively). The results of both screening methods were in general agreement with the observed mortality in diagnostic bioassays and LC50 and EC50 determinations. CONCLUSIONS: These results are consistent with previous modeling results, suggesting that the high-dose/refuge strategy that is in place for Bt corn may be effective in delaying resistance evolution even when a relatively high frequency of resistance alleles exists.

Disturbance frequency and vertical distribution of seeds affect long-term population dynamics: a mechanistic seed bank model.

Seed banks are critically important for disturbance specialist plants because seeds of these species germinate only in disturbed soil. Disturbance and seed depth affect the survival and germination probability of seeds in the seed bank, which in turn affect population dynamics. We develop a density-dependent stochastic integral projection model to evaluate the effect of stochastic soil disturbances on plant population dynamics with an emphasis on mimicking how disturbances vertically redistribute seeds within the seed bank. We perform a simulation analysis of the effect of the frequency and mean depth of disturbances on the population's quasi-extinction probability, as well as the long-term mean and variance of the total density of seeds in the seed bank. We show that increasing the frequency of disturbances increases the long-term viability of the population, but the relationship between the mean depth of disturbance and the long-term viability of the population are not necessarily monotonic for all parameter combinations. Specifically, an increase in the probability of disturbance increases the long-term viability of the total seed bank population. However, if the probability of disturbance is too low, a shallower mean depth of disturbance can increase long-term viability, a relationship that switches as the probability of disturbance increases. However, a shallow disturbance depth is beneficial only in scenarios with low survival in the seed bank.

Demography in an increasingly variable world.

Recent advances in stochastic demography provide unique insights into the probable effects of increasing environmental variability on population dynamics, and these insights can be substantially different compared with those from deterministic models. Stochastic variation in structured population models influences estimates of population growth rate, persistence and resilience, which ultimately can alter community composition, species interactions, distributions and harvesting. Here, we discuss how understanding these demographic consequences of environmental variation will have applications for anticipating changes in populations resulting from anthropogenic activities that affect the variance in vital rates. We also highlight new tools for anticipating the consequences of the magnitude and temporal patterning of environmental variability.