Herbicide resistances in Amaranthus tuberculatus: a call for new options

Amaranthus tuberculatus is a major weed of crop fields in the midwestern United States. Making this weed particularly problematic to manage is its demonstrated ability to evolve resistance to herbicides. Herbicides to which A. tuberculatus has evolved resistance are photosystem II inhibitors, acetolactate synthase inhibitors, protoporphyrinogen oxidase inhibitors, and glyphosate. Many populations of A. tuberculatus contain more than one of these resistances, severely limiting the options for effective herbicide control. A survey of multiple-herbicide resistance in A. tuberculatus revealed that all populations resistant to glyphosate contained resistance to acetolactate synthase inhibitors, and 40% contained resistance to protoporphyrinogen oxidase inhibitors. The occurrences of multiple-herbicide resistances in A. tuberculatus illustrate the need for continued herbicide discovery efforts and/or the development of new strategies for weed management.     

Multi-scale environmental heterogeneity as a predictor of plant species richness

Ecological theory predicts a positive influence of local-, landscape-, and regional-scale spatial environmental heterogeneity on local species richness. Therefore, knowing how heterogeneity measured at a variety of scales relates to local species richness has important implications for conservation of biological diversity. We took a statistical modeling approach to determine which metrics of heterogeneity measured at which scales were useful predictors of local species richness, and whether the heterogeneity-local richness relationship was always positive. Local plant species richness data came from 400-m² vegetation plots in North and South Carolina, USA. At each of four scales from within plots to across regions, we used either GIS or field data to calculate measures of heterogeneity from abiotic environmental variables, vegetation productivity data, and land cover classifications. Among all predictors at all scales, we found that no measure of heterogeneity was a better predictor of local richness than mean pH within plots. However, at scales larger than within plots, measures of heterogeneity were correlated most strongly with local richness, and each of the three classes of variables we used had a distinct scale at which it performed better than the others. These results highlight the fact that ecological processes occurring across multiple scales influence local species richness differently. In addition, relationships between heterogeneity and richness were usually, though not always, positive, underscoring the importance of processes that occur at a variety of scales to local biodiversity conservation and management.     

The crossbred sire: experimental results for cattle

Results comparing crossbred bulls relative to straightbred bulls for various reproduction traits (such as puberty, sperm concentration, pregnancy rate and weaning rate) and progeny growth traits (birth and weaning weight) were summarized separately for Bos taurus X Bos taurus (Bt X Bt) and Bos indicus X Bos taurus (Bi X Bt) crosses. The Bt X Bt and Bi X Bt crossbred bulls were 1.8 and 5.0% younger, respectively, at puberty than straightbred bulls. Also, sperm concentration of Bt X Bt and Bi X Bt crossbred bulls was greater than straightbred bulls by 36.4 and 56.0%, respectively. Pregnancy rate and weaning rate of cows exposed to straightbred and crossbred bulls indicated advantage values of .2 and 4.0%, respectively, for Bt X Bt crossbred bulls. Corresponding advantage values for Bi X Bt crossbred bulls over straightbred bulls were 1.4 and 3.7%, respectively, for these two traits. Birth and weaning weights were similar for calves sired by straightbred and Bt X Bt crossbred bulls as well as for calves sired by straightbred and Bi X Bt crossbred bulls.     

The North American Animal Disease Spread Model: a simulation model to assist decision making in evaluating animal disease incursions

The North American Animal Disease Spread Model is a stochastic, spatial, state-transition simulation model for the spread of highly contagious diseases of animals. It was developed with broad international support to assist policy development and decision making involving disease incursions. User-established parameters define model behavior in terms of disease progression; disease spread by animal-to-animal contact, contact with contaminated personnel or equipment, and airborne dissemination; and the implementation of control measures such as destruction and vaccination. Resources available to implement disease control strategies, as well as the direct costs associated with these strategies, are taken into consideration. The model records a wide variety of measures of the extent of simulated outbreaks and other characteristics. The graphical interface and output visualization features also make it a useful tool for training and preparedness exercises. This model is now being used to evaluate outbreak scenarios and potential control strategies for several economically important exotic animal diseases in the United States, Canada, and elsewhere. NAADSM is freely available via the Internet at http://www.naadsm.org.     

Kernel Intensity Estimation of 2-Dimensional Spatial Poisson Point Processes From k-Tree Sampling

To estimate the spatial intensity (density) of plants and animals, ecologists often sample populations by prespecifing a spatial array of points, then measuring the distance from each point to the k nearest organisms, a so-called k-tree sampling method. A variety of ad hoc methods are available for estimating intensity from k-tree sampling data, but they assume that two distinct points of the array do not share nearest neighbors. However, nearest neighbors are likely to be shared when the population intensity is low, as it is in our application. The purpose of this paper is twofold: (a) to derive and use for estimation the likelihood function for a k-tree sample under an inhomogeneous Poisson point-process model and (b) to estimate spatial intensity when nearest neighbors are shared. We derive the likelihood function for an inhomogeneous Poisson point-process with intensity λ(x,y) and propose a likelihood-based, kernel-smoothed estimator \(\hat{\lambda}(x,y)\) . Performance of the method for k=1 is tested on four types of simulated populations: two homogeneous populations with low and high intensity, a population simulated from a bivariate normal distribution of intensity, and a “cliff” population in which the region is divided into high- and low-intensity subregions. The method correctly detected spatial variation in intensity across different subregions of the simulated populations. Application to 1-tree samples of carnivorous pitcher plants populations in four New England peat bogs suggests that the method adequately captures empirical patterns of spatial intensity. However, our method suffers from two evident sources of bias. First, like other kernel smoothers, it underestimates peaks and overestimates valleys. Second, it has positive bias analogous to that of the MLE for the rate parameter of exponential random variables.     

Tidal modulation of nonvolcanic tremor

Episodes of nonvolcanic tremor and accompanying slow slip recently have been observed in the subduction zones of Japan and Cascadia. In Cascadia, such episodes typically last a few weeks and differ from "normal" earthquakes in their source location and moment-duration scaling. The three most recent episodes in the Puget Sound/southern Vancouver Island portion of the Cascadia subduction zone were exceptionally well recorded. In each episode, we saw clear pulsing of tremor activity with periods of 12.4 and 24 to 25 hours, the same as the principal lunar and lunisolar tides. This indicates that the small stresses associated with the solid-earth and ocean tides influence the genesis of tremor much more effectively than they do the genesis of normal earthquakes. Because the lithostatic stresses are 10(5) times larger than those associated with the tides, we argue that tremor occurs on very weak faults.     

Mitochondrial genome sequences illuminate maternal lineages of conservation concern in a rare carnivore

Background  

Science-based wildlife management relies on genetic information to infer population connectivity and identify conservation units. The most commonly used genetic marker for characterizing animal biodiversity and identifying maternal lineages is the mitochondrial genome. Mitochondrial genotyping figures prominently in conservation and management plans, with much of the attention focused on the non-coding displacement ("D") loop. We used massively parallel multiplexed sequencing to sequence complete mitochondrial genomes from 40 fishers, a threatened carnivore that possesses low mitogenomic diversity. This allowed us to test a key assumption of conservation genetics, specifically, that the D-loop accurately reflects genealogical relationships and variation of the larger mitochondrial genome.