Crop dominance exerts specific effects on foliage‐dwelling arthropods in Bacillus thuringiensis cotton

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The complete mitochondrial genome of Biston panterinaria (Lepidoptera: Geometridae), with phylogenetic utility of mitochondrial genome in the Lepidoptera

The complete mitochondrial genome (mitogenome) of the Chinese pistacia looper Biston panterinaria was sequenced and annotated (15,517 bp). It contains the typical 37 genes of animal mitogenomes and a high A + T content (79.5%). All protein coding genes (PCGs) use standard ATN initiation codons except for cytochrome c oxidase 1 (COX1) with CGA. Eleven PCGs use a common stop codon of TAA or TAG, whereas COX2 and NADH dehydrogenase 4 (ND4) use a single T. All transfer RNA (tRNA) genes have the typical clover-leaf structure with the exception of tRNA^Ser(AGN). We reconstructed a preliminary mitochondrial phylogeny of six ditrysian superfamilies and performed comparative analyses of inference methods (Bayesian Inference (BI), Maximum Likelihood (ML), and Maximum Parsimony (MP)), dataset compositions (including and excluding 3rd codon positions), and alignment methods (Muscle, Clustal W, and MAFFT). Our analyses indicated that inference methods and dataset compositions more significantly affected the phylogenetic results than alignment methods. BI analysis consistently revealed uncontroversial relationships with all dataset compositions. By contrast, ML analysis failed to reconstruct stable phylogeny at two nodes, whereas MP analysis had more difficulties in the tree resolution and nodal support. Distinct from most previous studies, our analyses revealed that Geometroidea had a closer lineage relationship with Bombycoidea than Noctuoidea. Similar to previous molecular studies, our analyses revealed that Hesperiidae were nested in the Papilionoidea clade, providing further evidence to the previous concept that Papilionoidea was paraphyletic, and none of the butterflies were associated with the Macroheterocera.     

Robustness and uncertainty in estimates of butterfly abundance from transect counts

Many butterfly populations are monitored by counting the number of butterflies observed while walking transects during the butterfly’s flight season. Methods for estimating population abundance from these transect counts are appealing because they allow rare populations to be monitored without capture–recapture studies that could harm fragile individuals. An increasingly popular method for estimating abundance from transect counts relies on strong assumptions about the counting process and the processes that govern butterfly population dynamics. Here, we study the statistical performance of this method when underlying model assumptions are violated. We find that estimates of population size are robust to departures from underlying model assumptions, but that the uncertainty in these estimates (i.e., confidence intervals) is substantially underestimated. Alternative bootstrap and Bayesian methods provide better measures of the uncertainty in estimated population size, but are conditional upon knowledge of butterfly detectability. Because of these requirements, a mixed approach that combines data from small capture–recapture studies with transect counts strikes the best balance between accurate monitoring and minimal injury to individuals. Our study is motivated by monitoring studies for St. Francis satyr (Neonympha mitchelli francisci), a rare and relatively immobile butterfly occurring only in the sandhills region of south-central North Carolina, USA.     

Floristic homogenization by native ruderal and alien plants in north-east Spain: the effect of environmental differences on a regional scale

Aim To evaluate the relative potential contribution of native ruderals and aliens to plant homogenization at a regional scale, after taking into account the effect of diverse environmental distances. Location Catalonia (north‐east Spain) Methods We have used the flora module of the BDBC project (Catalonian Database of Biodiversity), which provides information on plant species distribution per 10 × 10 km Universal Transverse Mercator (UTM) cell. Pairwise floristic similarities of: (1) total, (2) native non‐ruderal, (3) native ruderal, and (4) alien vascular plant species have been calculated for a particularly well‐sampled subset of UTM cells, using a modified version of the Simpson index. These similarities have been compared per UTM pair using Mantel tests, before and after considering their relative association with geographical, climatic and landscape distances from linear regression models. The floristic similarity of both total and native non‐ruderal species was also correlated with the proportion of alien and native ruderal species after discounting the effects of environmental distances. Results The proportion of variance explained by environmental correlates was highest for the floristic similarity of native non‐ruderal plants and lowest for that of aliens. In all plant groups, climatic distance was the main significant variable of species similarity. Geographical distance was only significant for total and native non‐ruderal species and was of secondary importance in both cases. Landscape distance was not significant in any case. Similarities among both aliens and native ruderals were significantly higher than among native non‐ruderals, but these differences disappeared after removing the effect of environmental distances. Main conclusions Species similarity between sites may depend on differences in environmental factors other than geographical distance. This has to be taken into account when exploring the implications for biotic homogenization. In the case of Catalonian flora, the potentially homogenizing effect of native ruderal and alien species seems to be associated with their lower dependence on geographical distance and climatic factors compared with those of native, non‐ruderal species.     

Tapered empirical likelihood for time series data in time and frequency domains

We investigate data tapering in two formulations of empiricallikelihood for time series. One empirical likelihood is formedfrom tapered data blocks in the time domain and a second isbased on the tapered periodogram in the frequency domain. Limitingdistributions are provided for both empirical likelihood versionsunder tapering. Theoretical and simulation evidence indicatesthat a data taper improves the coverage accuracy of empiricallikelihood confidence intervals for time series parameters,such as means and correlations.     

Calculating bootstrap probabilities of phylogeny using multilocus sequence data

Phylogeny estimation is extremely crucial in the study of molecular evolution. The increase in the amount of available genomic data facilitates phylogeny estimation from multilocus sequence data. Although maximum likelihood and Bayesian methods are available for phylogeny reconstruction using multilocus sequence data, these methods require heavy computation, and their application is limited to the analysis of a moderate number of genes and taxa. Distance matrix methods present suitable alternatives for analyzing huge amounts of sequence data. However, the manner in which distance methods can be applied to multilocus sequence data remains unknown. Here, we suggest new procedures to estimate molecular phylogeny using multilocus sequence data and evaluate its significance in the framework of the distance method. We found that concatenation of the multilocus sequence data may result in incorrect phylogeny estimation with an extremely high bootstrap probability (BP), which is due to incorrect estimation of the distances and intentional ignorance of the intergene variations. Therefore, we suggest that the distance matrices for multilocus sequence data be estimated separately and these matrices be subsequently combined to reconstruct phylogeny instead of phylogeny reconstruction using concatenated sequence data. To calculate the BPs of the reconstructed phylogeny, we suggest that 2-stage bootstrap procedures be adopted; in this, genes are resampled followed by resampling of the sequence columns within the resampled genes. By resampling the genes during calculation of BPs, intergene variations are properly considered. Via simulation studies and empirical data analysis, we demonstrate that our 2-stage bootstrap procedures are more suitable than the conventional bootstrap procedure that is adopted after sequence concatenation.     

Once a Batesian mimic, not always a Batesian mimic: mimic reverts back to ancestral phenotype when the model is absent

Batesian mimics gain protection from predation through the evolution of physical similarities to a model species that possesses anti-predator defences. This protection should not be effective in the absence of the model since the predator does not identify the mimic as potentially dangerous and both the model and the mimic are highly conspicuous. Thus, Batesian mimics should probably encounter strong predation pressure outside the geographical range of the model species. There are several documented examples of Batesian mimics occurring in locations without their models, but the evolutionary responses remain largely unidentified. A mimetic species has four alternative evolutionary responses to the loss of model presence. If predation is weak, it could maintain its mimetic signal. If predation is intense, it is widely presumed the mimic will go extinct. However, the mimic could also evolve a new colour pattern to mimic another model species or it could revert back to its ancestral, less conspicuous phenotype. We used molecular phylogenetic approaches to reconstruct and test the evolution of mimicry in the North American admiral butterflies (Limenitis: Nymphalidae). We confirmed that the more cryptic white-banded form is the ancestral phenotype of North American admiral butterflies. However, one species, Limenitis arthemis, evolved the black pipevine swallowtail mimetic form but later reverted to the white-banded more cryptic ancestral form. This character reversion is strongly correlated with the geographical absence of the model species and its host plant, but not the host plant distribution of L. arthemis. Our results support the prediction that a Batesian mimic does not persist in locations without its model, but it does not go extinct either. The mimic can revert back to its ancestral, less conspicuous form and persist.     

Assessing variation in life‐history tactics within a population using mixture regression models: a practical guide for evolutionary ecologists

Mixed models are now well‐established methods in ecology and evolution because they allow accounting for and quantifying within‐ and between‐individual variation. However, the required normal distribution of the random effects can often be violated by the presence of clusters among subjects, which leads to multi‐modal distributions. In such cases, using what is known as mixture regression models might offer a more appropriate approach. These models are widely used in psychology, sociology, and medicine to describe the diversity of trajectories occurring within a population over time (e.g. psychological development, growth). In ecology and evolution, however, these models are seldom used even though understanding changes in individual trajectories is an active area of research in life‐history studies. Our aim is to demonstrate the value of using mixture models to describe variation in individual life‐history tactics within a population, and hence to promote the use of these models by ecologists and evolutionary ecologists. We first ran a set of simulations to determine whether and when a mixture model allows teasing apart latent clustering, and to contrast the precision and accuracy of estimates obtained from mixture models versus mixed models under a wide range of ecological contexts. We then used empirical data from long‐term studies of large mammals to illustrate the potential of using mixture models for assessing within‐population variation in life‐history tactics. Mixture models performed well in most cases, except for variables following a Bernoulli distribution and when sample size was small. The four selection criteria we evaluated [Akaike information criterion (AIC), Bayesian information criterion (BIC), and two bootstrap methods] performed similarly well, selecting the right number of clusters in most ecological situations. We then showed that the normality of random effects implicitly assumed by evolutionary ecologists when using mixed models was often violated in life‐history data. Mixed models were quite robust to this violation in the sense that fixed effects were unbiased at the population level. However, fixed effects at the cluster level and random effects were better estimated using mixture models. Our empirical analyses demonstrated that using mixture models facilitates the identification of the diversity of growth and reproductive tactics occurring within a population. Therefore, using this modelling framework allows testing for the presence of clusters and, when clusters occur, provides reliable estimates of fixed and random effects for each cluster of the population. In the presence or expectation of clusters, using mixture models offers a suitable extension of mixed models, particularly when evolutionary ecologists aim at identifying how ecological and evolutionary processes change within a population. Mixture regression models therefore provide a valuable addition to the statistical toolbox of evolutionary ecologists. As these models are complex and have their own limitations, we provide recommendations to guide future users.     

Estimation in Bayesian disease mapping

Recent work on Bayesian inference of disease mapping models discusses the advantages of the fully Bayesian (FB) approach over its empirical Bayes (EB) counterpart, suggesting that FB posterior standard deviations of small-area relative risks are more reflective of the uncertainty associated with the relative risk estimation than counterparts based on EB inference, since the latter fail to account for the variability in the estimation of the hyperparameters. In this article, an EB bootstrap methodology for relative risk inference with accurate parametric EB confidence intervals is developed, illustrated, and contrasted with the hyperprior Bayes. We elucidate the close connection between the EB bootstrap methodology and hyperprior Bayes, present a comparison between FB inference via hybrid Markov chain Monte Carlo and EB inference via penalized quasi-likelihood, and illustrate the ability of parametric bootstrap procedures to adjust for the undercoverage in the "naive" EB interval estimates. We discuss the important roles that FB and EB methods play in risk inference, map interpretation, and real-life applications. The work is motivated by a recent analysis of small-area infant mortality rates in the province of British Columbia in Canada.