Modelling Pollinator and Nonpollinator Selection on Flower Colour Variation

1. Flower colour variation is ubiquitous within and between populations, which is why it has long been a focal point for studies of natural selection. This body of work has uncovered a wide range of selective agents, including pollinators, herbivores, and various abiotic factors. Nevertheless, we lack an integrative framework for predicting the phenotypic outcome in terms of floral pigmentation when these forces act collectively and often in opposition. 2. We here present such a framework through a model that incorporates selection on pigmentation at the vegetative phase (i.e., through survival to reproduction) and at the flowering phase (i.e., on pollinator attraction). We focus on anthocyanins as common class of pigments, although the model is equally applicable to any compounds that can be jointly expressed in vegetative tissue and in flowers. We explore the dynamics of our model in a theoretical context and in four scenarios based on classic systems for studying selection on flower colour. 3. Our model predicts that pollinators are the main driver for flower colour evolution, but selection on seedling survival plays a major role in the absence of pollen limitation, that is, if pollinator abundance is sufficiently high, or if pollinator preference is absent or weak (high variance in colour preference). In each of the case studies, our model recovered the predicted patterns of fitness for each floral morph given the strength and nature of selection. 4. This work suggests that selection at the vegetative phase must act alone or be exceptionally strong to negate pollinator preference for particular colours. Nevertheless, the influence of differential survival associated with anthocyanin production leaves a clear signature on the fitness curves, suggesting that nonpollinator agents of selection can often be detected from empirical data. 5. Synthesis: Overall, the application of this model to empirical systems will be key for understanding how flower colour diversity evolves and for predicting how changes in climate and pollinator communities may jointly alter evolutionary trajectories

STABILIZATION BY ADAPTIVE FEEDBACK CONTROL FOR POSITIVE DIFFERENCE EQUATIONS WITH APPLICATIONS IN PEST MANAGEMENT

An adaptive feedback control scheme is proposed for stabilizing a class of forced nonlinear positive difference equations. The adaptive scheme is based on so-called high-gain adaptive controllers and contains substantial robustness with respect to model uncertainty as well as with respect to persistent forcing signals, including measurement errors. Our results take advantage of the underlying positive systems structure and ideas from input-to-state stability from nonlinear control theory. Our motivating application is to pest or weed control, and in this context the present work substantially strengthens previous work by the authors. The theory is illustrated with examples

Improving precision and reducing bias in biological surveys: estimating false-negative error rates

The use of presence/absence data in wildlife management and biological surveys is widespread. There is a growing interest in quantifying the sources of error associated with these data. We show that false-negative errors (failure to record a species when in fact it is present) can have a significant impact on statistical estimation of habitat models using simulated data. Then we introduce an extension of logistic modeling, the zero-inflated binomial (ZIB) model that permits the estimation of the rate of false-negative errors and the correction of estimates of the probability of occurrence for false-negative errors by using repeated. visits to the same site. Our simulations show that even relatively low rates of false negatives bias statistical estimates of habitat effects. The method with three repeated visits eliminates the bias, but estimates are relatively imprecise. Six repeated visits improve precision of estimates to levels comparable to that achieved with conventional statistics in the absence of false-negative errors In general, when error rates are less than or equal to50% greater efficiency is gained by adding more sites, whereas when error rates are >50% it is better to increase the number of repeated visits. We highlight the flexibility of the method with three case studies, clearly demonstrating the effect of false-negative errors for a range of commonly used survey methods

Modelling radiation-induced cell cycle delays

Ionizing radiation is known to delay the cell cycle progression. In particular after particle exposure significant delays have been observed and it has been shown that the extent of delay affects the expression of damage such as chromosome aberrations. Thus, to predict how cells respond to ionizing radiation and to derive reliable estimates of radiation risks, information about radiation-induced cell cycle perturbations is required. In the present study we describe and apply a method for retrieval of information about the time-course of all cell cycle phases from experimental data on the mitotic index only. We study the progression of mammalian cells through the cell cycle after exposure. The analysis reveals a prolonged block of damaged cells in the G2 phase. Furthermore, by performing an error analysis on simulated data valuable information for the design of experimental studies has been obtained. The analysis showed that the number of cells analyzed in an experimental sample should be at least 100 to obtain a relative error less than 20%.Comment: 19 pages, 11 figures, accepted for publication in Radiation and Environmental Biophysic

Inferring transient dynamics of human populations from matrix non-normality

This is the final version of the article. Available from Springer Verlag via the DOI in this record.In our increasingly unstable and unpredictable world, population dynamics rarely settle uniformly to long-term behaviour. However, projecting period-by-period through the preceding fluctuations is more data-intensive and analytically involved than evaluating at equilibrium. To efficiently model populations and best inform policy, we require pragmatic suggestions as to when it is necessary to incorporate short-term transient dynamics and their effect on eventual projected population size. To estimate this need for matrix population modelling, we adopt a linear algebraic quantity known as non-normality. Matrix non-normality is distinct from normality in the Gaussian sense, and indicates the amplificatory potential of the population projection matrix given a particular population vector. In this paper, we compare and contrast three well-regarded metrics of non-normality, which were calculated for over 1000 age-structured human population projection matrices from 42 European countries in the period 1960 to 2014. Non-normality increased over time, mirroring the indices of transient dynamics that peaked around the millennium. By standardising the matrices to focus on transient dynamics and not changes in the asymptotic growth rate, we show that the damping ratio is an uninformative predictor of whether a population is prone to transient booms or busts in its size. These analyses suggest that population ecology approaches to inferring transient dynamics have too often relied on suboptimal analytical tools focussed on an initial population vector rather than the capacity of the life cycle to amplify or dampen transient fluctuations. Finally, we introduce the engineering technique of pseudospectra analysis to population ecology, which, like matrix non-normality, provides a more complete description of the transient fluctuations than the damping ratio. Pseudospectra analysis could further support non-normality assessment to enable a greater understanding of when we might expect transient phases to impact eventual population dynamics.This work was funded by Wellcome Trust New Investigator 103780 to TE, who is also funded by NERC Fellowship NE/J018163/1. JB gratefully acknowledges the ESRC Centre for Population Change ES/K007394/1

Conserved Odorant-Binding Proteins from Aphids and Eavesdropping Predators

Background: The sesquiterpene (E)-ß-farnesene is the main component of the alarm pheromone system of various aphid species studied to date, including the English grain aphid, Sitobion avenae. Aphid natural enemies, such as the marmalade hoverfly Episyrphus balteatus and the multicolored Asian lady beetle Harmonia axyridis, eavesdrop on aphid chemical communication and utilize (E)-ß-farnesene as a kairomone to localize their immediate or offspring preys. These aphidpredator systems are important models to study how the olfactory systems of distant insect taxa process the same chemical signal. We postulated that odorant-binding proteins (OBPs), which are highly expressed in insect olfactory tissues and involved in the first step of odorant reception, have conserved regions involved in binding (E)-ß-farnesene. Methodology: We cloned OBP genes from the English grain aphid and two major predators of this aphid species. We then expressed these proteins and compare their binding affinities to the alarm pheromone/kairomone. By using a fluorescence reporter, we tested binding of (E)-ß-farnesene and other electrophysiologically and behaviorally active compounds, including a green leaf volatile attractant. Conclusion: We found that OBPs from disparate taxa of aphids and their predators are highly conserved proteins, with apparently no orthologue genes in other insect species. Properly folded, recombinant proteins from the English grain aphid, SaveOBP3, and the marmalade hoverfly, EbalOBP3, specifically bind (E)-ß-farnesene with apparent high affinity. For the firs

Microorganisms from aphid honeydew attract and enhance the efficacy of natural enemies

Aphids are one of the most serious pests of crops worldwide, causing major yield and economic losses. To control aphids, natural enemies could be an option but their efficacy is sometimes limited by their dispersal in natural environment. Here we report the first isolation of a bacterium from the pea aphid Acyrthosiphon pisum honeydew, Staphylococcus sciuri, which acts as a kairomone enhancing the efficiency of aphid natural enemies. Our findings represent the first case of a host-associated bacterium driving prey location and ovipositional preference for the natural enemy. We show that this bacterium has a key role in tritrophic interactions because it is the direct source of volatiles used to locate prey. Some specific semiochemicals produced by S. sciuri were also identified as significant attractants and ovipositional stimulants. The use of this host-associated bacterium could certainly provide a novel approach to control aphids in field and greenhouse systems

Confirmation of a non-synonymous SNP in PNPLA8 as a candidate causal mutation for Weaver syndrome in Brown Swiss cattle

Background: Bovine progressive degenerative myeloencephalopathy (Weaver syndrome) is a neurodegenerative disorder in Brown Swiss cattle that is characterized by progressive hind leg weakness and ataxia, while sensorium and spinal reflexes remain unaffected. Although the causal mutation has not been identified yet, an indirect genetic test based on six microsatellite markers and consequent exclusion of Weaver carriers from breeding have led to the complete absence of new cases for over two decades. Evaluation of disease status by imputation of 41 diagnostic single nucleotide polymorphisms (SNPs) and a common haplotype published in 2013 identified several suspected carriers in the current breeding population, which suggests a higher frequency of the Weaver allele than anticipated. In order to prevent the reemergence of the disease, this study aimed at mapping the gene that underlies Weaver syndrome and thus at providing the basis for direct genetic testing and monitoring of today's Braunvieh/Brown Swiss herds. Results: Combined linkage/linkage disequilibrium mapping on Bos taurus chromosome (BTA) 4 based on Illumina Bovine SNP50 genotypes of 43 Weaver-affected, 31 Weaver carrier and 86 Weaver-free animals resulted in a maximum likelihood ratio test statistic value at position 49,812,384 bp. The confidence interval (0.853 Mb) determined by the 2-LOD drop-off method was contained within a 1.72-Mb segment of extended homozygosity. Exploitation of whole-genome sequence data from two official Weaver carriers and 1145 other bulls that were sequenced in Run4 of the 1000 bull genomes project showed that only a non-synonymous SNP (rs800397662) within the PNPLA8 gene at position 49,878,773 bp was concordant with the Weaver carrier status. Targeted SNP genotyping confirmed this SNP as a candidate causal mutation for Weaver syndrome. Genotyping for the candidate causal mutation in a random sample of 2334 current Braunvieh animals suggested a frequency of the Weaver allele of 0.26 %. Conclusions: Through combined use of exhaustive sequencing data and SNP genotyping results, we were able to provide evidence that supports the non-synonymous mutation at position 49,878,773 bp as the most likely causal mutation for Weaver syndrome. Further studies are needed to uncover the exact mechanisms that underlie this syndrome