Nicolas L. Ziebarth

The evolution of resistance to two‐toxin pyramid transgenic crops

Pyramid transgenic crops that express two Bacillus thuringiensis (Bt) toxins hold great potential for reducing insect damage and slowing the evolution of resistance to the toxins. Here, we analyzed a suite of models for pyramid Bt crops to illustrate factors that should be considered when implementing the high dose-refuge strategy for resistance management; this strategy involves the high expression of toxins in Bt plants and use of non-Bt plants as refuges. Although resistance evolution to pyramid Bt varieties should in general be slower, resistance to pyramid Bt varieties is nonetheless driven by the same evolutionary processes as single Bt-toxin varieties. The main advantage of pyramid varieties is the low survival of insects heterozygous for resistance alleles. We show that there are two modes of resistance evolution. When populations of purely susceptible insects persist, leading to density dependence, the speed of resistance evolution changes slowly with the proportion of refuges. However, once the proportion of non-Bt plants crosses the threshold below which a susceptible population cannot persist, the speed of resistance evolution increases rapidly. This suggests that adaptive management be used to guarantee persistence of susceptible populations. We compared the use of seed mixtures in which Bt and non-Bt plants are sown in the same fields to the use of spatial refuges. As found for single Bt varieties, seed mixtures can speed resistance evolution if larvae move among plants. Devising optimal management plans for deploying spatial refuges is difficult because they depend on crop rotation patterns, whether males or females have limited dispersal, and other characteristics. Nonetheless, the effects of spatial refuges on resistance evolution can be understood by considering the three mechanisms determining the rate of resistance evolution: the force of selection (the proportion of insects killed by Bt), assortative mating (deviations of the proportion of heterozygotes from Hardy-Weinberg equilibrium at the total population level), and male mating success (when males carrying resistance alleles find fewer mates). Of these three, assortative mating is often the least important, even though this mechanism is the most frequently cited explanation for the efficacy of the high dose-refuge strategy.

Analysis of ecological time series with ARMA(p,q) models.

Autoregressive moving average (ARMA) models are useful statistical tools to examine the dynamical characteristics of ecological time-series data. Here, we illustrate the utility and challenges of applying ARMA (p,q) models, where p is the dimension of the autoregressive component of the model, and q is the dimension of the moving average component. We focus on parameter estimation and model selection, comparing both maximum likelihood (ML) and restricted maximum likelihood (REML) parameter estimation. While REML estimation performs better (has less bias) than ML estimation for ARMA (p,q) models with p = 1 (as has been found previously), for models with p > 1 the performance of the estimators is complicated by multimodal likelihood functions. The resulting difficulties in estimation lead to our recommendation that likelihood functions be routinely investigated when applying ARMA (p,q) models. To aid this investigation, we provide MATLAB and R code for the ML and REML likelihood functions. We further explore the consequences of measurement error, showing how it can be explicitly and implicitly incorporated into estimation. In addition to parameter estimation, we also examine model selection for identifying the correct model dimensions (p and q). Finally, we estimate the characteristic return rate of the stochastic process to its stationary distribution, a quantity that describes a key property of population dynamics, and investigate bias that results from both estimation and model selection. While fitting ARMA models to ecological time series with complex dynamics has challenges, these challenges can be surmounted, making ARMA a useful and broadly applicable approach.

Weak population regulation in ecological time series

How strongly natural populations are regulated has a long history of debate in ecology. Here, we discuss concepts of population regulation appropriate for stochastic population dynamics. We then analyse two large collections of data sets with autoregressive-moving average (ARMA) models, using model selection techniques to find best-fitting models. We estimated two metrics of population regulation: the characteristic return rate of populations to stationarity and the variability of the stationary distribution (the long-term distribution of population abundance). Empirically, longer time series were more likely to show weakly regulated population dynamics. For data sets of length > or = 20, more than 35% had characteristic return times > 6 years, and more than 29% had stationary distributions whose coefficients of variation were more than two times greater than would be the case if they were maximally regulated. These results suggest that many natural populations are weakly regulated.

Did the National Industrial Recovery Act Foster Collusion? Evidence from the Macaroni Industry

We use plant-level data from the Census of Manufactures to study collusion in the United States macaroni industry during the Great Depression. The National Industrial Recovery Act was passed in 1933 to promote recovery through industry coordination of economic activity. While there is no change in the price-cost margin after the law is passed, a variety of markers of anti-competitive conduct suggest that collusion indeed increased. Prices became less responsive to changes in cost, the dispersion of prices decreased, and the persistence in prices increased.

A Troublesome Statistic: Traders and Coastal Shipments in the Westward Movement of Slaves

We analyze all slave manifests housed at the National Archives—some 24,400 documents involving approximately 135,000 slaves who were transported in the coastwise trade from 1810 to 1861. The manifests list the name of the owner or shipper, which allows us to match names with traders found in other sources. We also utilize demographic characteristics of the manifests to estimate the probability that a trader organized the shipment. Commercial transactions increased over the antebellum period, and on average were responsible for approximately 55 percent of slaves who migrated from Atlantic to Gulf coast ports. “No one has ever suggested a method for finding what proportion of the slaves transported from one state to another were taken by their original masters or their heirs for their own use.†Bancroft 1931, p. 397

Economic Development and the Demographics of Criminals in Victorian England

We use a data set consisting of felony trials in London from 1835 to 1913 to analyze changing demographic patterns in the commission of crimes. We find that the average age of offenders in London increased substantially more than can be explained through increases in longevity or jurisdictional changes. Moreover, this increase is larger for crimes committed for economic gain than for crimes of violence. We build a model to explain the increase in the number of older offenders. As industrialization proceeded, older workers increasingly found their human capital unsuitable to the technology level, which forced some into crime. We then complement this time-series analysis with cross-sectional data from England and Wales from 1870, 1883, and 1910. In the cross sections, areas with higher rates of urbanization and industrialization had higher average ages of criminals and disproportionately more criminals from medium-skilled, artisan occupations.

The Great Depression Through the Eyes of the Census of Manufactures

Abstract The author discusses a very rich resource for studying the Great Depression: the Censuses of Manufactures from 1929, 1931, 1933, and 1935. He highlights the strengths and weaknesses of this source in terms of the information available on the schedules and the quality of the data. In terms of information collected, these censuses compare favorably with the modern Census of Manufactures with some limitations. The author also draws on some published studies to argue that the records held at the National Archives are (in general) complete enumerations of the establishments existing at the time. He then conducts tests for the presence of measurement error and finds a limited role.

Trader Selectivity and Measured Catch-Up Growth of American Slaves

Critics who doubt the sources and meaning of some four inches of catch-up growth claim that market-based distortions created by slave traders biased measured heights of children and adolescents. Here we analyze this possible bias using a new database of all slave manifests available at the National Archives. Employing procedures to match names of shippers with known or suspected professional traders, we find that biases in height by age due to trader selectivity were negligible relative to the four inches of catch-up growth.

Estimation of Models with Multiple-Valued Explanatory Variables

We study estimation and inference when there are multiple values (“matches”) for the explanatory variables and only one of the matches is the correct one. This problem arises often when two dataset...

The Role of Local Labor Supply in Response to Oil Price Shocks

We separate changes in labor supply and demand through changes in higher-order moments of the wage distribution. We illustrate this idea in a study of the effects of oil price shocks, which generate a predictable labor demand adjustment across regions. Empirically, oil price shocks decrease average wages, particularly skilled wages, and increase wage dispersion, particularly unskilled wage dispersion. In a model with spatial energy intensity differences and nontradables, labor demand shifts, while explaining the response of average wages to oil price shocks, have counterfactual implications for the response of wage dispersion. Only shifts in labor supply can explain this latter fact.