Martin H. Villet
Other affiliations: University of the Witwatersrand
Bio: Martin H. Villet is an academic researcher from Rhodes University. The author has contributed to research in topics: Genus & Forensic entomology. The author has an hindex of 35, co-authored 175 publications receiving 3941 citations. Previous affiliations of Martin H. Villet include University of the Witwatersrand.
Papers published on a yearly basis
TL;DR: In this paper, a correlative modelling technique that uses locality records (associated with species presence) and a set of predictor variables to produce a statistically justifiable probability response surface for a target species is presented.
Abstract: . We present a correlative modelling technique that uses locality records (associated with species presence) and a set of predictor variables to produce a statistically justifiable probability response surface for a target species. The probability response surface indicates the suitability of each grid cell in a map for the target species in terms of the suite of predictor variables. The technique constructs a hyperspace for the target species using principal component axes derived from a principal components analysis performed on a training dataset. The training dataset comprises the values of the predictor variables associated with the localities where the species has been recorded as present. The origin of this hyperspace is taken to characterize the centre of the niche of the organism. All the localities (grid-cells) in the map region are then fitted into this hyperspace using the values of the predictor variables at these localities (the prediction dataset). The Euclidean distance from any locality to the origin of the hyperspace gives a measure of the ‘centrality’ of that locality in the hyperspace. These distances are used to derive probability values for each grid cell in the map region. The modelling technique was applied to bioclimatic data to predict bioclimatic suitability for three alien invasive plant species (Lantana camara L., Ricinus communis L. and Solanum mauritianum Scop.) in South Africa, Lesotho and Swaziland. The models were tested against independent test records by calculating area under the curve (AUC) values of receiver operator characteristic (ROC) curves and kappa statistics. There was good agreement between the models and the independent test records. The pre-processing of climatic variable data to reduce the deleterious effects of multicollinearity, and the use of stopping rules to prevent overfitting of the models are important aspects of the modelling process.
TL;DR: In this paper, a case study of a coastal dune plant (Scaevola plumieri ) along the coast of South Africa, using a mechanistic model based on summer water balance (SWB), and two correlative models (a profile and a group discrimination technique).
Abstract: Models used to predict species’ potential distributions have been described as either correlative or mechanistic. We attempted to determine whether correlative models could perform as well as mechanistic models for predicting species potential distributions, using a case study. We compared potential distribution predictions made for a coastal dune plant ( Scaevola plumieri ) along the coast of South Africa, using a mechanistic model based on summer water balance (SWB), and two correlative models (a profile and a group discrimination technique). The profile technique was based on principal components analysis (PCA) and the group-discrimination technique was based on multiple logistic regression (LR). Kappa ( κ ) statistics were used to objectively assess model performance and model agreement. Model performance was calculated by measuring the levels of agreement (using κ ) between a set of testing localities (distribution records not used for model building) and each of the model predictions. Using published interpretive guidelines for the kappa statistic, model performance was “excellent” for the SWB model ( κ =0.852), perfect for the LR model ( κ =1.000), and “very good” for the PCA model ( κ =0.721). Model agreement was calculated by measuring the level of agreement between the mechanistic model and the two correlative models. There was “good” model agreement between the SWB and PCA models ( κ =0.679) and “very good” agreement between the SWB and LR models ( κ =0.786). The results suggest that correlative models can perform as well as or better than simple mechanistic models. The predictions generated from these three modelling designs are likely to generate different insights into the potential distribution and biology of the target organism and may be appropriate in different situations. The choice of model is likely to be influenced by the aims of the study, the biology of the target organism, the level of knowledge the target organism’s biology, and data quality.
TL;DR: A new predictive modelling technique called the fuzzy envelope model (FEM) is introduced, which can be used to predict species’ potential distributions that could be used for identifying regions at risk from invasion by alien species and in conservation planning in the case of native species.
Abstract: A new predictive modelling technique called the fuzzy envelope model (FEM) is introduced. The technique can be used to predict potential distributions of organisms using presence-only locality records and a set of environmental predictor variables. FEM uses fuzzy logic to classify a set of predictor variable maps based on the values associated with presence records and combines the results to produce a potential distribution map for a target species. This technique represents several refinements of the envelope approach used in the BIOCLIM modelling package. These refinements are related to the way in which FEMs deal with uncertainty, the way in which this uncertainty is represented in the resultant potential distribution maps, and the way that these maps can be interpreted and applied. To illustrate its potential use in biogeographical studies, FEM was applied to predicting the potential distribution of three invasive alien plant species (Lantana camara L., Ricinus communis L. and Solanum mauritianum Scop.), and three native cicada species (Capicada decora Germar, Platypleura deusta Thun. and P. capensis L.) in South Africa, Lesotho and Swaziland. These models were quantitatively compared with models produced by means of the algorithm used in the BIOCLIM modelling package, which is referred to as a crisp envelope model (the CEM design). The average performance of models of the FEM design was consistently higher than those of the CEM design. There were significant differences in model performance among species but there was no significant interaction between model design and species. The average maximum kappa value ranged from 0.70 to 0.90 for FEM design and from 0.57 to 0.89 for the CEM design, which can be described as ‘good’ to ‘excellent’ using published ranges of agreement for the kappa statistic. This technique can be used to predict species’ potential distributions that could be used for identifying regions at risk from invasion by alien species. These predictions could also be used in conservation planning in the case of native species.
TL;DR: The major elapoid and elapid lineages are identified, a phylogenetic classification system for the superfamily is presented, and results imply rapid basal diversification in both clades in the late Eocene of Africa and the mid‐Oligocene of the Oriental region.
Abstract: The snake superfamily Elapoidea presents one of the most intransigent problems in systematics of the Caenophidia Its monophyly is undisputed and several cohesive constituent lineages have been identified (including the diverse and clinically important family Elapidae), but its basal phylogenetic structure is obscure We investigate phylogenetic relationships and spatial and temporal history of the Elapoidea using 94 caenophidian species and approximately 2300–4300 bases of DNA sequence from one nuclear and four mitochondrial genes Phylogenetic reconstruction was conducted in a parametric framework using complex models of sequence evolution We employed Bayesian relaxed clocks and Penalized Likelihood with rate smoothing to date the phylogeny, in conjunction with seven fossil calibration constraints Elapoid biogeography was investigated using maximum likelihood and maximum parsimony methods Resolution was poor for early relationships in the Elapoidea and in Elapidae and our results imply rapid basal diversification in both clades, in the late Eocene of Africa (Elapoidea) and the mid-Oligocene of the Oriental region (Elapidae) We identify the major elapoid and elapid lineages, present a phylogenetic classification system for the superfamily (excluding Elapidae), and combine our phylogenetic, temporal and biogeographic results to provide an account of elapoid evolution in light of current palaeontological data and palaeogeographic models © The Willi Hennig Society 2009
TL;DR: Jo Whaley, perhaps drawing on her previous experience working in the theatre and taking inspiration from 16th and 17th century illustrators of natural history, has produced a collection of superb photographs of insects.
Abstract: Here is a book that is quite different from those we usually review. Jo Whaley, perhaps drawing on her previous experience working in the theatre and taking inspiration from 16th and 17th century illustrators of natural history, has produced a collection of superb photographs of insects. Each insect is set centre stage against a collage of man-made images or materials, which highlight its natural beauty and make us look again at the beauty of form and design. The book has been published to coincide with the photographic exhibition that is on show at several galleries across the USA from September 2008 to January2009. The recent South African Invertebrate Art Exhibition at Little Brenthurst in Johannesburg and at the 23rd International Congress of Entomology held at the Durban ICC has shown that there is a great interest and appreciation for insects as beautiful and visually interesting objects in art and craft works. The book is made up of 64 colour plates, and three short essays illustrated with colour photographs. The short essays, Spectacle of Nature by D. Klochko, Philosophy of Insects by L. Weiner and Notes from the Studio by J. Whaley provide easy to read background and food for thought. Butterflies and moths feature strongly amongst the insects chosen as subjects for the photographs but there are fascinating compositions using beetles, dragon flies and even millipedes as ‘honorary insects’. Scientific names are provided in most cases but no biological background. The first essay starts with the quote from von Schlegel (1797) ‘...every art should become science and every science should become art...’. In a world of entomological studies where accurate observation, description and scientific method dominate, it is refreshing to see insects from an artist’s perspective. This small coffee table book would be an ideal gift for anyone who is interested in using insects as a source of artistic inspiration. S.A. Hanrahan Animal Plant and Environmental Sciences University of the Witwatersrand Johannesburg, WITS 2050 firstname.lastname@example.org Medical Entomology for Students (4th Edition) by M.W. Service. Cambridge University Press, Cambridge. 2008. Pp. xvi + 289. Price R540 incl. VAT (paperback). ISBN 978-0 521-70928-6.
TL;DR: It is suggested that the natural selection against large insertion/deletion is so weak that a large amount of variation is maintained in a population.
Abstract: The relationship between the two estimates of genetic variation at the DNA level, namely the number of segregating sites and the average number of nucleotide differences estimated from pairwise comparison, is investigated. It is found that the correlation between these two estimates is large when the sample size is small, and decreases slowly as the sample size increases. Using the relationship obtained, a statistical method for testing the neutral mutation hypothesis is developed. This method needs only the data of DNA polymorphism, namely the genetic variation within population at the DNA level. A simple method of computer simulation, that was used in order to obtain the distribution of a new statistic developed, is also presented. Applying this statistical method to the five regions of DNA sequences in Drosophila melanogaster, it is found that large insertion/deletion (greater than 100 bp) is deleterious. It is suggested that the natural selection against large insertion/deletion is so weak that a large amount of variation is maintained in a population.
TL;DR: For the next few weeks the course is going to be exploring a field that’s actually older than classical population genetics, although the approach it’ll be taking to it involves the use of population genetic machinery.
Abstract: So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to
TL;DR: An overview of recent advances in species distribution models, and new avenues for incorporating species migration, population dynamics, biotic interactions and community ecology into SDMs at multiple spatial scales are suggested.
Abstract: In the last two decades, interest in species distribution models (SDMs) of plants and animals has grown dramatically. Recent advances in SDMs allow us to potentially forecast anthropogenic effects on patterns of biodiversity at different spatial scales. However, some limitations still preclude the use of SDMs in many theoretical and practical applications. Here, we provide an overview of recent advances in this field, discuss the ecological principles and assumptions underpinning SDMs, and highlight critical limitations and decisions inherent in the construction and evaluation of SDMs. Particular emphasis is given to the use of SDMs for the assessment of climate change impacts and conservation management issues. We suggest new avenues for incorporating species migration, population dynamics, biotic interactions and community ecology into SDMs at multiple spatial scales. Addressing all these issues requires a better integration of SDMs with ecological theory.
TL;DR: Twelve approaches to determining thresholds were compared using two species in Europe and artificial neural networks, and the modelling results were assessed using four indices: sensitivity, specificity, overall prediction success and Cohen's kappa statistic.
Abstract: Transforming the results of species distribution modelling from probabilities of or suitabilities for species occurrence to presences/absences needs a specific threshold. Even though there are many approaches to determining thresholds, there is no comparative study. In this paper, twelve approaches were compared using two species in Europe and artificial neural networks, and the modelling results were assessed using four indices: sensitivity, specificity, overall prediction success and Cohen's kappa statistic. The results show that prevalence approach, average predicted probability/suitability approach, and three sensitivity-specificity-combined approaches, including sensitivity-specificity sum maximization approach, sensitivity-specificity equality approach and the approach based on the shortest distance to the top-left corner (0,1) in ROC plot, are the good ones. The commonly used kappa maximization approach is not as good as the afore-mentioned ones, and the fixed threshold approach is the worst one. We also recommend using datasets with prevalence of 50% to build models if possible since most optimization criteria might be satisfied or nearly satisfied at the same time, and therefore it's easier to find optimal thresholds in this situation.