scispace - formally typeset
Search or ask a question
Author

Alexander L. Wild

Bio: Alexander L. Wild is an academic researcher from University of Texas at Austin. The author has contributed to research in topics: Linepithema & Argentine ant. The author has an hindex of 16, co-authored 24 publications receiving 1657 citations. Previous affiliations of Alexander L. Wild include University of Arizona & University of Illinois at Urbana–Champaign.

Papers
More filters
Journal ArticleDOI
TL;DR: A phylogeny of beetles based on DNA sequence data from eight nuclear genes, including six single‐copy nuclear protein‐coding genes, for 367 species representing 172 of 183 extant families provides a uniquely well‐resolved temporal and phylogenetic framework for studying patterns of innovation and diversification in Coleoptera.
Abstract: © 2015 The Authors. Systematic Entomology published by John Wiley & Sons Ltd on behalf of Royal Entomological Society This is an open access article under the terms of the Creative Commons AttributionߚNonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

419 citations

Journal ArticleDOI
TL;DR: The draft genome sequence of a particularly widespread and well-studied species, the invasive Argentine ant, is reported, which was accomplished using a combination of 454 and Illumina sequencing and community-based funding rather than federal grant support.
Abstract: Ants are some of the most abundant and familiar animals on Earth, and they play vital roles in most terrestrial ecosystems. Although all ants are eusocial, and display a variety of complex and fascinating behaviors, few genomic resources exist for them. Here, we report the draft genome sequence of a particularly widespread and well-studied species, the invasive Argentine ant (Linepithema humile), which was accomplished using a combination of 454 (Roche) and Illumina sequencing and community-based funding rather than federal grant support. Manual annotation of >1,000 genes from a variety of different gene families and functional classes reveals unique features of the Argentine ant's biology, as well as similarities to Apis mellifera and Nasonia vitripennis. Distinctive features of the Argentine ant genome include remarkable expansions of gustatory (116 genes) and odorant receptors (367 genes), an abundance of cytochrome P450 genes (>110), lineage-specific expansions of yellow/major royal jelly proteins and desaturases, and complete CpG DNA methylation and RNAi toolkits. The Argentine ant genome contains fewer immune genes than Drosophila and Tribolium, which may reflect the prominent role played by behavioral and chemical suppression of pathogens. Analysis of the ratio of observed to expected CpG nucleotides for genes in the reproductive development and apoptosis pathways suggests higher levels of methylation than in the genome overall. The resources provided by this genome sequence will offer an abundance of tools for researchers seeking to illuminate the fascinating biology of this emerging model organism.

279 citations

Journal ArticleDOI
TL;DR: A dataset of over 1000 occurrences of the Argentine ant, one of the world's worst invasive alien species, was assembled to assess the species' potential geographical and ecological distribution, and to examine changes in its distributional potential associated with global climate change, using techniques for ecological niche modelling.
Abstract: Determining the spread and potential geographical distribution of invasive species is integral to making invasion biology a predictive science. We assembled a dataset of over 1000 occurrences of the Argentine ant (Linepithema humile), one of the world's worst invasive alien species. Native to central South America, Argentine ants are now found in many Mediterranean and subtropical climates around the world. We used this dataset to assess the species' potential geographical and ecological distribution, and to examine changes in its distributional potential associated with global climate change, using techniques for ecological niche modelling. Models developed were highly predictive of the species' overall range, including both the native distributional area and invaded areas worldwide. Despite its already widespread occurrence, L. humile has potential for further spread, with tropical coastal Africa and southeast Asia apparently vulnerable to invasion. Projecting ecological niche models onto four general circulation model scenarios of future (2050s) climates provided scenarios of the species' potential for distributional expansion with warming climates: generally, the species was predicted to retract its range in tropical regions, but to expand at higher latitude areas.

206 citations

Journal ArticleDOI
TL;DR: The concatenated data reconstruct the test phylogeny with high support in both Bayesian and parsimony analyses, indicating that combining data from multiple nuclear loci will be a fruitful approach for assembling the beetle tree of life.

203 citations

Journal Article
TL;DR: The earliest known Linepithema humile records for 95 geographic areas (countries, island groups, major islands, and US states) were found in this paper, including several for which they found no previously published records.
Abstract: The Argentin e ant, Linepithema humile (MAYR, 1868), originally from subtropical South America, is an important pest in many parts of the world. To evaluate its worldwide distribution and potential for further spread, we mapped records of L. humile from > 2100 sites. Because several South and Central American Linepithema species have been often misidentified as L. humile, we excluded all unconfirmed South and Central American records. We documented the earliest known L. humile records for 95 geographic areas (countries, island groups, major islands, and US states), including several for which we found no previously published records. We could not confirm any L. humile records from several South and Central American countries with published reports. Most records of L. humile come from the subtropics, particularly from regions with Mediterranean-like climates (i.e., warm dry summers and cool moist winters), including its native range in South America and exotic populations in California, the Mediterranean, southern Africa, Australia, New Zealand, and Japan. In more humid subtropical areas, such as the southeast US, L. humile rarely dominates outside urban areas. In tropical latitudes, L. humile dominates only at higher elevations, most notably in Hawaii. In temperate areas, L. humile is almost exclusively an indoor pest. Linepithema humile has already spread to most subtropical lowland regions with Mediterranean-like climates, but is not known yet from most tropical highland areas with suitable climates. In the past, L. humile probably arrived in tropical regions by sea accompanying human commerce and had to survive coastal lowland conditions before spreading to higher, cooler elevations. Nowadays air travel allows L. humile to stowaway in cargo delivered almost anywhere in the world. Therefore, a wider spread of this pest is expected in the future.

116 citations


Cited by
More filters
Journal ArticleDOI
TL;DR: A novel jackknife validation approach is developed and tested to assess the ability to predict species occurrence when fewer than 25 occurrence records are available and the minimum sample sizes required to yield useful predictions remain difficult to determine.
Abstract: Aim: Techniques that predict species potential distributions by combining observed occurrence records with environmental variables show much potential for application across a range of biogeographical analyses. Some of the most promising applications relate to species for which occurrence records are scarce, due to cryptic habits, locally restricted distributions or low sampling effort. However, the minimum sample sizes required to yield useful predictions remain difficult to determine. Here we developed and tested a novel jackknife validation approach to assess the ability to predict species occurrence when fewer than 25 occurrence records are available. Location: Madagascar. Methods: Models were developed and evaluated for 13 species of secretive leaf-tailed geckos (Uroplatus spp.) that are endemic to Madagascar, for which available sample sizes range from 4 to 23 occurrence localities (at 1 km2 grid resolution). Predictions were based on 20 environmental data layers and were generated using two modelling approaches: a method based on the principle of maximum entropy (Maxent) and a genetic algorithm (GARP). Results: We found high success rates and statistical significance in jackknife tests with sample sizes as low as five when the Maxent model was applied. Results for GARP at very low sample sizes (less than c. 10) were less good. When sample sizes were experimentally reduced for those species with the most records, variability among predictions using different combinations of localities demonstrated that models were greatly influenced by exactly which observations were included. Main conclusions: We emphasize that models developed using this approach with small sample sizes should be interpreted as identifying regions that have similar environmental conditions to where the species is known to occur, and not as predicting actual limits to the range of a species. The jackknife validation approach proposed here enables assessment of the predictive ability of models built using very small sample sizes, although use of this test with larger sample sizes may lead to overoptimistic estimates of predictive power. Our analyses demonstrate that geographical predictions developed from small numbers of occurrence records may be of great value, for example in targeting field surveys to accelerate the discovery of unknown populations and species. © 2007 The Authors.

2,647 citations

Journal ArticleDOI
TL;DR: Modelling approaches are explored that aim to minimize extrapolation errors and assess predictions against prior biological knowledge to promote methods appropriate to range‐shifting species.
Abstract: Summary 1. Species are shifting their ranges at an unprecedented rate through human transportation and environmental change. Correlative species distribution models (SDMs) are frequently applied for predicting potential future distributions of range-shifting species, despite these models’ assumptions that species are at equilibrium with the environments used to train (fit) the models, and that the training data are representative of conditions to which the models are predicted. Here we explore modelling approaches that aim to minimize extrapolation errors and assess predictions against prior biological knowledge. Our aim was to promote methods appropriate to range-shifting species. 2. We use an invasive species, the cane toad in Australia, as an example, predicting potential distributions under both current and climate change scenarios. We use four SDM methods, and trial weighting schemes and choice of background samples appropriate for species in a state of spread. We also test two methods for including information from a mechanistic model. Throughout, we explore graphical techniques for understanding model behaviour and reliability, including the extent of extrapolation. 3. Predictions varied with modelling method and data treatment, particularly with regard to the use and treatment of absence data. Models that performed similarly under current climatic conditions deviated widely when transferred to a novel climatic scenario. 4. The results highlight problems with using SDMs for extrapolation, and demonstrate the need for methods and tools to understand models and predictions. We have made progress in this direction and have implemented exploratory techniques as new options in the free modelling software, MaxEnt. Our results also show that deliberately controlling the fit of models and integrating information from mechanistic models can enhance the reliability of correlative predictions of species in non-equilibrium and novel settings. 5.Implications. The biodiversity of many regions in the world is experiencing novel threats created by species invasions and climate change. Predictions of future species distributions are required for management, but there are acknowledged problems with many current methods, and relatively few advances in techniques for understanding or overcoming these. The methods presented in this manuscript and made accessible in MaxEnt provide a forward step.

2,013 citations

Journal ArticleDOI
TL;DR: MAKER2 is the first annotation engine specifically designed for second-generation genome projects, which scales to datasets of any size, requires little in the way of training data, and can use mRNA-seq data to improve annotation quality.
Abstract: Second-generation sequencing technologies are precipitating major shifts with regards to what kinds of genomes are being sequenced and how they are annotated. While the first generation of genome projects focused on well-studied model organisms, many of today's projects involve exotic organisms whose genomes are largely terra incognita. This complicates their annotation, because unlike first-generation projects, there are no pre-existing 'gold-standard' gene-models with which to train gene-finders. Improvements in genome assembly and the wide availability of mRNA-seq data are also creating opportunities to update and re-annotate previously published genome annotations. Today's genome projects are thus in need of new genome annotation tools that can meet the challenges and opportunities presented by second-generation sequencing technologies. We present MAKER2, a genome annotation and data management tool designed for second-generation genome projects. MAKER2 is a multi-threaded, parallelized application that can process second-generation datasets of virtually any size. We show that MAKER2 can produce accurate annotations for novel genomes where training-data are limited, of low quality or even non-existent. MAKER2 also provides an easy means to use mRNA-seq data to improve annotation quality; and it can use these data to update legacy annotations, significantly improving their quality. We also show that MAKER2 can evaluate the quality of genome annotations, and identify and prioritize problematic annotations for manual review. MAKER2 is the first annotation engine specifically designed for second-generation genome projects. MAKER2 scales to datasets of any size, requires little in the way of training data, and can use mRNA-seq data to improve annotation quality. It can also update and manage legacy genome annotation datasets.

1,504 citations

Journal Article
TL;DR: The author wished to relate the three phases of research on insects and to express insect sociology as population biology in this detailed survey of knowledge of insect societies.
Abstract: In his introduction to this detailed survey of knowledge of insect societies, the author points out that research on insect sociology has proceeded in three phases, the natural history phase, the physiological phase and the population-biology phase. Advances in the first two phases have permitted embarkation in the third phase on a more rigorous theory of social evolution based on population genetics and writing this book, the author wished to relate the three phases of research on insects and to express insect sociology as population biology. A glossary of terms, a considerable bibliography and a general index are included. Other CABI sites 

1,394 citations

Journal ArticleDOI
TL;DR: Insects are model systems for studying aberrant mt genomes, including truncated tRNAs and multichromosomal genomes, and greater integration of nuclear and mt genomic studies is necessary to further the understanding of insect genomic evolution.
Abstract: The mitochondrial (mt) genome is, to date, the most extensively studied genomic system in insects, outnumbering nuclear genomes tenfold and representing all orders versus very few. Phylogenomic analysis methods have been tested extensively, identifying compositional bias and rate variation, both within and between lineages, as the principal issues confronting accurate analyses. Major studies at both inter- and intraordinal levels have contributed to our understanding of phylogenetic relationships within many groups. Genome rearrangements are an additional data type for defining relationships, with rearrangement synapomorphies identified across multiple orders and at many different taxonomic levels. Hymenoptera and Psocodea have greatly elevated rates of rearrangement offering both opportunities and pitfalls for identifying rearrangement synapomorphies in each group. Finally, insects are model systems for studying aberrant mt genomes, including truncated tRNAs and multichromosomal genomes. Greater integration of nuclear and mt genomic studies is necessary to further our understanding of insect genomic evolution.

910 citations