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Widespread use of pesticides has resulted in the evolution of resistance in many insect pests worldwide limiting their use in pest control. Effective pest and resistance management practices require understanding of the genetics of resistance and of the life history of the pest. Most models for pesticide resistance assume that resistance is monogenic, conferred by a single gene. However, resistance could evolve as a polygenic quantitative trait resulting from the action of several genes, especially when pesticide dose is low. Further, fitness of the pest could be density-dependent and might depend upon abiotic factors such as temperature. It is not known how these factors affect the evolution of polygenic resistance or pest population dynamics when resistance evolves. We use the western corn rootworm, Diabrotica virgifera virgifera, as a case study and use data on density-dependent survival, heritability and survival rates on the transgenic Cry3Bb1 toxin and corresponding LC50 values, to model polygenic resistance to Cry3Bb1. We found that LC50 increased rapidly even at doses that produced a mortality of less than 99.9%. However, survival reached 100% only when mortality was as high as 99.9%. Fast response to high selection pressure produced cyclical larval densities while lower selection pressures produced equilibrium densities. Interestingly we found that a relatively low density observed in a population may not be evidence for a low survival to the pesticide. As a consequence we found that larger refuges might not necessarily help in reducing pest densities especially when pesticide mortality is low. This effect, arising from the tradeoff between response to selection and density dependence, calls for careful assessment of the evolution of resistance based on change in survival as well as on pest densities. When selection pressure is low a lower initial density resulted in a larger response to selection. Finally, we showed that populations with shorter developmental times developed resistance faster initially irrespective of selection pressure. However, when selection pressure is low survival eventually became higher in populations with longer developmental times. Since developmental time depends on degree days spatio-temporal variation in temperature could be an important factor in polygenic resistance evolution.

Spatiotemporal variation in demographic rates can have profound effects for population persistence, especially for dispersal-limited species living in fragmented landscapes. Long-term studies of plants in such habitats help with understanding the impacts of fragmentation on population persistence but such studies are rare. In this work, we reanalyzed demographic data from seven years of the short-lived cactus Opuntia macrorhiza var. macrorhiza at five plots in Boulder, Colorado. Previous work combining data from all years and all plots predicted a stable population (deterministic log lamda approximately 0). This approach assumed that all five plots were part of a single population. Since the plots were located in a suburban-agricultural interface separated by highways, grazing lands, and other barriers, and O. macrorhiza is likely dispersal limited, we analyzed the dynamics of each plot separately using stochastic matrix models assuming each plot represented a separate population. We found that the stochastic population growth rate log lamdaS varied widely between populations (log lamdaS = 0.1497, 0.0774, -0.0230, -0.2576, -0.4989). The three populations with the highest growth rates were located close together in space, while the two most isolated populations had the lowest growth rates suggesting that dispersal between populations is critical for the population viability of O. macrorhiza. With one exception, both our prospective (stochastic elasticity) and retrospective (stochastic life table response experiments) analysis suggested that means of stasis and growth, especially of smaller plants, were most important for population growth rate. This is surprising because recruitment is typically the most important vital rate in a short-lived species such as O. macrorhiza. We found that elasticity to the variance was mostly negligible, suggesting that O. macrorhiza populations are buffered against large temporal variation. Finally, single-year elasticities to means of transitions to the smallest stage (mostly due to reproduction) and growth differed considerably from their long-term elasticities. It is important to be aware of this difference when using models to predict the effect of manipulating plant vital rates within the time frame of typical plant demographic studies.

a b s t r a c t When vital rates depend on population structure (e.g., relative frequencies of males or females), an important question is how the long-term population growth rate λ responds to changes in rates. For instance, availability of mates may depend on the sex ratio of the population and hence reproductive rates could be frequency-dependent. In such cases change in any vital rate alters the structure, which in turn, affect frequency-dependent rates. We show that the elasticity of λ to a rate is the sum of (i) the effect of the linear change in the rate and (ii) the effect of nonlinear changes in frequency-dependent rates. The first component is always positive and is the classical elasticity in density-independent models obtained directly from the population projection matrix. The second component can be positive or negative and is absent in density-independent models. We explicitly express each component of the elasticity as a function of vital rates, eigenvalues and eigenvectors of the population projection matrix. We apply this result to a two-sex model, where male and female fertilities depend on adult sex ratio α (ratio of females to males) and the mating system (e.g., polygyny) through a harmonic mating function. We show that the nonlinear component of elasticity to a survival rate is negligible only when the average number of mates (per male) is close to α. In a strictly monogamous species, elasticity to female survival is larger than elasticity to male survival when α < 1 (less females). In a polygynous species, elasticity to female survival can be larger than that of male survival even when sex ratio is female biased. Our results show how demography and mating system together determine the response to selection on sex-specific vital rates.

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:ThefrequencyofresistancetotheCry1FBttoxinwasestimatedusingtwodifferentscreeningtoolsandcomparedwith annual susceptibility monitoring based on diagnostic bioassays and LC50 and EC50 determinations. An F1 screening approach wherefield-collectedindividualswerematedtoaresistantlaboratorystrainandprogenywereassayedtodeterminegenotype 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:Theseresultsareconsistentwithpreviousmodelingresults,suggestingthatthehigh-dose/refugestrategythat is in place for Bt corn may be effective in delaying resistance evolution even when a relatively high frequency of resistance alleles exists. c � 2013 Society of Chemical Industry Supportinginformationmaybefoundintheonlineversionofthisarticle.

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.

Population size and population growth rate respond to changes in vital rates like survival and fertility. In deterministic environments change in population growth rate alone determines change in population size. In random environments, population size at any time t is a random variable so that change in population size obeys a probability distribution. We analytically show that, in a density-independent population, the proportional change in population size with respect to a small proportional change in a vital rate has an asymptotic normal distribution. Its mean grows linearly at a rate equal to the elasticity of the long-term stochastic growth rate λ S while the standard deviation scales as $\sqrt t$ . Consequently, a vital rate with a larger elasticity of λ S may produce a larger mean change in population size compared to one with a smaller elasticity of λ S. But a given percentage change in population size may be more likely when the vital rate with smaller elasticity is perturbed. Hence, the response of population size to perturbation of a vital rate depends not only on the elasticity of the population growth rate but also on the variance in change in population size. Our results provide a formula to calculate the probability that population size changes by a given percentage that works well even for short time periods.

The elasticities of long-run population growth rate with respect to vital rates are useful in studying selection on vital rates, and in evaluating management policy that aims to control vital rates. In temporally varying environments, elasticity is often calculated from simulations that assume a probability distribution for the environmental states. Here we develop a method to estimate elasticities directly from demographic data. Using a time-series of demographic matrices and age-structure we construct a consistent statistical estimator of elasticity that converges to the correct limiting value as the sample length increases. We also construct confidence intervals for elasticities from temporal data and suggest tools for testing hypotheses about the strength of selection. We use data on a natural population to show that our method can indeed accurately estimate elasticities using relatively short time series.

How does life history affects the short-term elasticities of population growth rate? We decompose short-term elasticity as a sum of (i) the effect of the perturbation in rates on the unperturbed population structure and (ii) the effect of the original vital rates on the difference in structure between the original and the perturbed population. We provide exact analytical formulas for these components. In a population at its stable stage distribution (SSD), short-term elasticity is determined mainly by the SSD and reproductive value. In a non-stable population, short-term elasticity depends also on the projection of initial structure on the SSD, equal to population momentum. Non-stable stage structures matter most to elasticity if stages are missing that take time to fill in. We show how the demographic damping rate of the original population determines the rate at which short-term elasticity converges to its limiting values.

For species in disturbance-prone ecosystems, vital rates (survival, growth and reproduction) often vary both between and within phases of the cycle of disturbance and recovery; some of this variation is imposed by the environment, but some may represent adaptation of the life history to disturbance. Anthropogenic changes may amplify or impede these patterns of variation, and may have positive or negative effects on population growth. Using stochastic population projection matrix models, we develop stochastic elasticities (proportional derivatives of the long-run population growth rate) to gauge the population effects of three types of change in demographic variability (changes in within- and between-disturbance-phase variability and phase-specific changes). Computing these elasticities for five species of disturbance-influenced perennial plants, we pinpoint demographic rates that may reveal adaptation to disturbance, and we demonstrate that species may differ in their responses to different types of changes in demographic variability driven by climate change.

How much does environmental autocorrelation matter to the growth of structured populations in real life contexts? Interannual variances in vital rates certainly do, but it has been suggested that between-year correlations may not. We present an analytical approximation to stochastic growth rate for multistate Markovian environments and show that it is accurate by testing it in two empirically based examples. We find that temporal autocorrelation has sizeable effect on growth rates of structured populations, larger in many cases than the effect of interannual variability. Our approximation defines a sensitivity to autocorrelated variability, showing how demographic damping and environmental pattern interact to determine a population's stochastic growth rate.

We consider a matrix model to describe the population dynamics of the Indian paper waspRopalidia marginata, a eusocial insect species of peninsular India. We obtain the stable class distribution of this model and apply it to compute the worker-brood genetic relatedness of the colony. Our results are compared with those obtained by observational studies. Further, we study the effect of changes in turnover rates and survival rates on the genetic relatedness coefficient with the help of the theoretical formulae.

Elasticities in stochastic matrix models are used to understand both population and evolutionary dynamics. We examine three such elasticities: stochastic elasticity \documentclass{aastex} \usepackage{amsbsy} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{bm} \usepackage{mathrsfs} \usepackage{pifont} \usepackage{stmaryrd} \usepackage{textcomp} \usepackage{portland,xspace} \usepackage{amsmath,amsxtra} \usepackage[OT2,OT1]{fontenc} \newcommand\cyr{ \renewcommand\rmdefault{wncyr} \renewcommand\sfdefault{wncyss} \renewcommand\encodingdefault{OT2} \normalfont \selectfont} \DeclareTextFontCommand{\textcyr}{\cyr} \pagestyle{empty} \DeclareMathSizes{10}{9}{7}{6} \begin{document} \landscape $E^{\mathrm{S}\,}_{ij}$ \end{document} with respect to the (i, j) matrix element, the elasticity \documentclass{aastex} \usepackage{amsbsy} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{bm} \usepackage{mathrsfs} \usepackage{pifont} \usepackage{stmaryrd} \usepackage{textcomp} \usepackage{portland,xspace...