Entomofauna associated with the olive tree in southern Portugal

Since 2004 several studies have been carried out in order to identify the main insect species that usually inhabiting the olive ecosystem. The field trials have taken place in two olive groves, one situated in Olhão and the other one in Loulé, both in Algarve and also under Integrated Pest Management (IPM). The sampling techniques used differ according to their purpose (sticky traps, pheromone traps, pitfall traps and samples of aerial parts of the trees such as inflorescences, leaves, fruits and branches). Results showed that the main insect pests of olive tree in southern Portugal were the olive fruit fly Bactrocera oleae Gmelin (Diptera: Tephritidae) and the olive moth Prays oleae Bernard (Lepidoptera: Hyponeumetidae). Other insect pests were also found in our olive groves namely the olive psyllid Euphyllura olivina Costa (Homoptera: Psyllidae), the olive dark beetle Phloeotribus scarabaeoides Bernard (Coleoptera: Curculionidae), the mediterranean black scale Saissetia oleae (Olivier) (Homoptera: Coccidae) and the olive thrip Liothripes oleae Costa (Thysanoptera: Phlaeothripidae). Concerning the auxiliary insects that were found in our olives groves they belong to the following orders and families: Diptera (Syrphidae), Coleoptera (Carabidae, Coccinelidae and Staphylinidae), Hemiptera (Anthocoridae and Miridae), Neuroptera (Chrysopidae) and Hymenoptera (Braconidae, Encyrtidae, Eulophidae, Formicidae and Trichogrammatidae).

Conifer defence against insects: microarray gene expression profiling of Sitka spruce (Picea sitchensis) induced by mechanical wounding or feeding by spruce budworms (Choristoneura occidentalis) or white pine weevils (Pissodes strobi) reveals large

Conifers are resistant to attack from a large number of potential herbivores or pathogens. Previous molecular and biochemical characterization of selected conifer defence systems support a model of multigenic, constitutive and induced defences that act on invading insects via physical, chemical, biochemical or ecological (multitrophic) mechanisms. However, the genomic foundation of the complex defence and resistance mechanisms of conifers is largely unknown. As part of a genomics strategy to characterize inducible defences and possible resistance mechanisms of conifers against insect herbivory, we developed a cDNA microarray building upon a new spruce (Picea spp.) expressed sequence tag resource. This first-generation spruce cDNA microarray contains 9720 cDNA elements representing c. 5500 unique genes. We used this array to monitor gene expression in Sitka spruce (Picea sitchensis) bark in response to herbivory by white pine weevils (Pissodes strobi, Curculionidae) or wounding, and in young shoot tips in response to western spruce budworm (Choristoneura occidentalis, Lepidopterae) feeding. Weevils are stem-boring insects that feed on phloem, while budworms are foliage feeding larvae that consume needles and young shoot tips. Both insect species and wounding treatment caused substantial changes of the host plant transcriptome detected in each case by differential gene expression of several thousand array elements at 1 or 2 d after the onset of treatment. Overall, there was considerable overlap among differentially expressed gene sets from these three stress treatments. Functional classification of the induced transcripts revealed genes with roles in general plant defence, octadecanoid and ethylene signalling, transport, secondary metabolism, and transcriptional regulation. Several genes involved in primary metabolic processes such as photosynthesis were down-regulated upon insect feeding or wounding, fitting with the concept of dynamic resource allocation in plant defence. Refined expression analysis using gene-specific primers and real-time PCR for selected transcripts was in agreement with microarray results for most genes tested. This study provides the first large-scale survey of insect-induced defence transcripts in a gymnosperm and provides a platform for functional investigation of plant-insect interactions in spruce. Induction of spruce genes of octadecanoid and ethylene signalling, terpenoid biosynthesis, and phenolic secondary metabolism are discussed in more detail.

Spatially stratified sampling using auxiliary information for geostatistical mapping

This paper presents a method of spatial sampling based on stratification by Local Moran’s I i calculated using auxiliary information. The sampling technique is compared to other design-based approaches including simple random sampling, systematic sampling on a regular grid, conditional Latin Hypercube sampling and stratified sampling based on auxiliary information, and is illustrated using two different spatial data sets. Each of the samples for the two data sets is interpolated using regression kriging to form a geostatistical map for their respective areas. The proposed technique is shown to be competitive in reproducing specific areas of interest with high accuracy.

Host selection in phytophagous insects: a new explanation for learning in adults

Insect learning can change the preferences an egg laying female displays towards different host plant species. Current hypotheses propose that learning may be advantageous in adult host selection behaviour through improved recognition, accuracy or selectivity in foraging. In this paper, we present a hypothesis for when learning can be advantageous without such improvements in adult host foraging. Specifically, that learning can be an advantageous strategy for egg laying females when larvae must feed on more than one plant in order to complete development, if the fitness of larvae is reduced when they switch to a different host species. Here, larvae benefit from developing on the most abundant host species, which is the most likely choice of host for an adult insect which increases its preference for a host species through learning. The hypothesis is formalised with a mathematical model and we provide evidence from studies on the behavioural ecology of a number of insect species which demonstrate that the assumptions of this hypothesis may frequently be fulfilled in nature. We discuss how multiple mechanisms may convey advantages in insect learning and that benefits to larval development, which have so far been overlooked, should be considered in explanations for the widespread occurrence of learning.

A general model for host plant selection in phytophagous insects

We develop a general theoretical framework for exploring the host plant selection behaviour of herbivorous insects. This model can be used to address a number of questions, including the evolution of specialists, generalists, preference hierarchies, and learning. We use our model to: (i) demonstrate the consequences of the extent to which the reproductive success of a foraging female is limited by the rate at which they find host plants (host limitation) or the number of eggs they carry (egg limitation); (ii) emphasize the different consequences of variation in behaviour before and after landing on (locating) a host (termed pre- and post-alighting, respectively); (iii) show that, in contrast to previous predictions, learning can be favoured in post-alighting behaviour--in particular, individuals can be selected to concentrate oviposition on an abundant low-quality host, whilst ignoring a rare higher-quality host; (iv) emphasize the importance of interactions between mechanisms in favouring specialization or learning.

High efficiency auxiliary power converters

The auxiliary load DC-DC converters of the Sunshark solar car have never been examined. An analysis of the current design reveals it is complicated, and inefficient. Some simple measures to greatly improve the efficiency are present which will achieve an overall worthwhile power saving. Two switch-mode power supply DC-DC converter designs are presented. One is a constant current supply for the LED brake and turn indicators, which allows them to be powered directly from the main DC bus, and switched only as necessary. The second is a low power flyback converter, which employs synchronous rectification among other techniques to achieve good efficiency and regulation over a large range of output powers. Practical results from both converters, and an indication of the overall improvement in system efficiency will be offered.

Bayesian indirect inference using a parametric auxiliary model

Indirect inference (II) is a methodology for estimating the parameters of an intractable (generative) model on the basis of an alternative parametric (auxiliary) model that is both analytically and computationally easier to deal with. Such an approach has been well explored in the classical literature but has received substantially less attention in the Bayesian paradigm. The purpose of this paper is to compare and contrast a collection of what we call parametric Bayesian indirect inference (pBII) methods. One class of pBII methods uses approximate Bayesian computation (referred to here as ABC II) where the summary statistic is formed on the basis of the auxiliary model, using ideas from II. Another approach proposed in the literature, referred to here as parametric Bayesian indirect likelihood (pBIL), we show to be a fundamentally different approach to ABC II. We devise new theoretical results for pBIL to give extra insights into its behaviour and also its differences with ABC II. Furthermore, we examine in more detail the assumptions required to use each pBII method. The results, insights and comparisons developed in this paper are illustrated on simple examples and two other substantive applications. The first of the substantive examples involves performing inference for complex quantile distributions based on simulated data while the second is for estimating the parameters of a trivariate stochastic process describing the evolution of macroparasites within a host based on real data. We create a novel framework called Bayesian indirect likelihood (BIL) which encompasses pBII as well as general ABC methods so that the connections between the methods can be established.

Small RNA viruses of insects : expression in plants and RNA silencing

Interest in insect small RNA viruses (SRVs) has grown slowly but steadily. A number of new viruses have been analyzed at the sequence level, adding to our knowledge of their diversity at the level of both individual virus species and families. In particular, a number of possible new virus families have emerged. This research has largely been driven by interest in their potential for pest control, as well as in their importance as the causal agents of disease in beneficial arthropods. At the same time, research into known viruses has made valuable contributions to our understanding of an emerging new field of central importance to molecular biology-the existence of RNA-based gene silencing, developmental control, and adaptive immune systems in eukaryotes. Subject to RNA-based adaptive immune responses in their hosts, viruses have evolved a variety of genes encoding proteins capable of suppressing the immune response. Such genes were first identified in plant viruses, but the first examples known from animal viruses were identified in insect RNA viruses. This chapter will address the diversity of insect SRVs, and attempts to harness their simplicity in the engineering of transgenic plants expressing viruses for resistance to insect pests. We also describe RNA interference and antiviral pathways identified in plants and animals, how they have led viruses to evolve genes capable of suppressing such adaptive immunity, and the problems presented by these pathways for the strategy of expressing viruses in transgenic plants. Approaches for countering these problems are also discussed. © 2006 Elsevier Inc. All rights reserved.

Approximate Bayesian computation using auxiliary model based estimates

We present a novel approach for developing summary statistics for use in approximate Bayesian computation (ABC) algorithms using indirect infer- ence. We embed this approach within a sequential Monte Carlo algorithm that is completely adaptive. This methodological development was motivated by an application involving data on macroparasite population evolution modelled with a trivariate Markov process. The main objective of the analysis is to compare inferences on the Markov process when considering two di®erent indirect mod- els. The two indirect models are based on a Beta-Binomial model and a three component mixture of Binomials, with the former providing a better ¯t to the observed data.

Evolution of New Zealand insects : summary and prospectus for future research

Knowledge on the evolution of the New Zealand insect fauna is reviewed and outstanding questions are highlighted. The New Zealand insect fauna is a composite of old and recent lineages and many spectacular examples of evolutionary processes are evident, including species radiations, hybridisation and unusual adaptations. We discuss the origins and evolution of four prominent communities within the insect fauna: terrestrial lowland insects, alpine insects, aquatic insects and insect communities from offshore islands. Within each of these communities, significant lineages are discussed, and in particular the crucial adaptations that enable these lineages to thrive and diversify. Glacial history has had a dramatic impact on the New Zealand insects, and the effects on different lineages are discussed. The New Zealand insects are unique, yet many are threatened with extinction, and efforts to preserve the fauna are reviewed. Despite the accumulating knowledge, major gaps still exist and these are outlined, as are opportunities to address key questions. The review concludes with a synthesis and a discussion of how systematics, new technologies and integrative approaches have the promise to improve dramatically our understanding of New Zealand insect evolution.

Virtual 3D models of insects for accelerated quarantine control

We learn from the past that invasive species have caused tremendous damage to native species and serious disruption to agricultural industries. It is crucial for us to prevent this in the future. The first step of this process is to identify correctly an invasive species from native ones. Current identification methods, relying on mainly 2D images, can result in low accuracy and be time consuming. Such methods provide little help to a quarantine officer who has time constraints to response when on duty. To deal with this problem, we propose new solutions using 3D virtual models of insects. We explain how working with insects in the 3D domain can be much better than the 2D domain. We also describe how to create true-color 3D models of insects using an image-based 3D reconstruction method. This method is ideal for quarantine control and inspection tasks that involve the verification of a physical specimen against known invasive species. Finally we show that these insect models provide valuable material for other applications such as research, education, arts and entertainment. © 2013 IEEE.

Accelerating entomology with Web3D insects

Capturing high-quality 3D models of insects is challenging - they are usually too small for laser or depth camera based systems, and techniques such as CT scanning do not record color. We have developed a prototype system that generates unprecedentedly high-quality natural-color 3D models of various insects from 3mm to 30 mm in length. Through the use of 3D web standards we are able to use these models to develop novel applications for entomologists and ensure wide accessibility. © 2014 Authors.

Capturing natural-colour 3D models of insects for species discovery and diagnostics

Collections of biological specimens are fundamental to scientific understanding and characterization of natural diversity - past, present and future. This paper presents a system for liberating useful information from physical collections by bringing specimens into the digital domain so they can be more readily shared, analyzed, annotated and compared. It focuses on insects and is strongly motivated by the desire to accelerate and augment current practices in insect taxonomy which predominantly use text, 2D diagrams and images to describe and characterize species. While these traditional kinds of descriptions are informative and useful, they cannot cover insect specimens "from all angles" and precious specimens are still exchanged between researchers and collections for this reason. Furthermore, insects can be complex in structure and pose many challenges to computer vision systems. We present a new prototype for a practical, cost-effective system of off-the-shelf components to acquire natural-colour 3D models of insects from around 3 mm to 30 mm in length. ("Natural-colour" is used to contrast with "false-colour", i.e., colour generated from, or applied to, gray-scale data post-acquisition.) Colour images are captured from different angles and focal depths using a digital single lens reflex (DSLR) camera rig and two-axis turntable. These 2D images are processed into 3D reconstructions using software based on a visual hull algorithm. The resulting models are compact (around 10 megabytes), afford excellent optical resolution, and can be readily embedded into documents and web pages, as well as viewed on mobile devices. The system is portable, safe, relatively affordable, and complements the sort of volumetric data that can be acquired by computed tomography. This system provides a new way to augment the description and documentation of insect species holotypes, reducing the need to handle or ship specimens. It opens up new opportunities to collect data for research, education, art, entertainment, biodiversity assessment and biosecurity control. © 2014 Nguyen et al.