Host Range Expansion of an Endemic Insect Herbivore is Associated With High Nitrogen and Low Fibre Content in Exotic Pasture Plants.

Endemic moth species of the genus Wiseana spp. (Hepialidae) have become serious pests of introduced pasture plants in New Zealand. The original native host plants of these moths have not been confirmed. This study investigated the performance (survival, development time, weight gain) of three Wiseana species on seven putative host plants: five native and two exotic species. The aim was to identify native hosts for the three Wiseana species and to compare their performance on native plants and exotic pasture plants. The chemical composition of the seven putative host plants was investigated to compare native and exotic plant chemistries, and to test for associations between plant characteristics and performance of selected Wiseana species. Carbon, nitrogen, silica and fibre contents were measured for each plant species; primary metabolite composition was determined by gas chromatography-mass spectrometry. For the three moth species, increased survival and weight gain were significantly associated with high nitrogen and low fibre contents in one exotic host plant, white clover (Trifolium repens), although one species, W. umbraculata, did not complete development to adult on any of the plants tested, including clover. Two exotic plants (T. repens, Lolium perenne × Lolium multiflorum), and two native plants (Aciphylla squarrosa and Festuca actae) supported W. copularis development to the adult stage, but only one exotic (T. repens) and one native (F. actae) species supported complete development of W. cervinata. Exotic and native plant species had distinct metabolite profiles, but there was no significant association between metabolite composition and Wiseana performance. We conclude that W. copularis and W. cervinata, but not W. umbraculata, have expanded their host range, because of their ability to use both native and new hosts. No evidence was found for a host shift, i.e., a loss of performance on the ancestral host compared with the new host.

Multi-Scenario Species Distribution Modeling.

Correlative species distribution models (SDMs) are increasingly being used to predict suitable insect habitats. There is also much criticism of prediction discrepancies among different SDMs for the same species and the lack of effective communication about SDM prediction uncertainty. In this paper, we undertook a factorial study to investigate the effects of various modeling components (species-training-datasets, predictor variables, dimension-reduction methods, and model types) on the accuracy of SDM predictions, with the aim of identifying sources of discrepancy and uncertainty. We found that model type was the major factor causing variation in species-distribution predictions among the various modeling components tested. We also found that different combinations of modeling components could significantly increase or decrease the performance of a model. This result indicated the importance of keeping modeling components constant for comparing a given SDM result. With all modeling components, constant, machine-learning models seem to outperform other model types. We also found that, on average, the Hierarchical Non-Linear Principal Components Analysis dimension-reduction method improved model performance more than other methods tested. We also found that the widely used confusion-matrix-based model-performance indices such as the area under the receiving operating characteristic curve (AUC), sensitivity, and Kappa do not necessarily help select the best model from a set of models if variation in performance is not large. To conclude, model result discrepancies do not necessarily suggest lack of robustness in correlative modeling as they can also occur due to inappropriate selection of modeling components. In addition, more research on model performance evaluation is required for developing robust and sensitive model evaluation methods. Undertaking multi-scenario species-distribution modeling, where possible, is likely to mitigate errors arising from inappropriate modeling components selection, and provide end users with better information on the resulting model prediction uncertainty.

A modeling framework for the establishment and spread of invasive species in heterogeneous environments.

Natural and human-induced events are continuously altering the structure of our landscapes and as a result impacting the spatial relationships between individual landscape elements and the species living in the area. Yet, only recently has the influence of the surrounding landscape on invasive species spread started to be considered. The scientific community increasingly recognizes the need for broader modeling framework that focuses on cross-study comparisons at different spatiotemporal scales. Using two illustrative examples, we introduce a general modeling framework that allows for a systematic investigation of the effect of habitat change on invasive species establishment and spread. The essential parts of the framework are (i) a mechanistic spatially explicit model (a modular dispersal framework-MDIG) that allows population dynamics and dispersal to be modeled in a geographical information system (GIS), (ii) a landscape generator that allows replicated landscape patterns with partially controllable spatial properties to be generated, and (iii) landscape metrics that depict the essential aspects of landscape with which dispersal and demographic processes interact. The modeling framework provides functionality for a wide variety of applications ranging from predictions of the spatiotemporal spread of real species and comparison of potential management strategies, to theoretical investigation of the effect of habitat change on population dynamics. Such a framework allows to quantify how small-grain landscape characteristics, such as habitat size and habitat connectivity, interact with life-history traits to determine the dynamics of invasive species spread in fragmented landscape. As such, it will give deeper insights into species traits and landscape features that lead to establishment and spread success and may be key to preventing new incursions and the development of efficient monitoring, surveillance, control or eradication programs.

Global threat to agriculture from invasive species.

Invasive species present significant threats to global agriculture, although how the magnitude and distribution of the threats vary between countries and regions remains unclear. Here, we present an analysis of almost 1,300 known invasive insect pests and pathogens, calculating the total potential cost of these species invading each of 124 countries of the world, as well as determining which countries present the greatest threat to the rest of the world given their trading partners and incumbent pool of invasive species. We find that countries vary in terms of potential threat from invasive species and also their role as potential sources, with apparently similar countries sometimes varying markedly depending on specifics of agricultural commodities and trade patterns. Overall, the biggest agricultural producers (China and the United States) could experience the greatest absolute cost from further species invasions. However, developing countries, in particular, Sub-Saharan African countries, appear most vulnerable in relative terms. Furthermore, China and the United States represent the greatest potential sources of invasive species for the rest of the world. The analysis reveals considerable scope for ongoing redistribution of known invasive pests and highlights the need for international cooperation to slow their spread.

Preference of a native beetle for "exoticism," characteristics that contribute to invasive success of Costelytra zealandica (Scarabaeidae: Melolonthinae).

Widespread replacement of native ecosystems by productive land sometimes results in the outbreak of a native species. In New Zealand, the introduction of exotic pastoral plants has resulted in diet alteration of the native coleopteran species, Costelytra zealandica (White) (Scarabaeidae) such that this insect has reached the status of pest. In contrast, C. brunneum (Broun), a congeneric species, has not developed such a relationship with these 'novel' host plants. This study investigated the feeding preferences and fitness performance of these two closely related scarab beetles to increase fundamental knowledge about the mechanisms responsible for the development of invasive characteristics in native insects. To this end, the feeding preference of third instar larvae of both Costelytra species was investigated using an olfactometer device, and the survival and larval growth of the invasive species C. zealandica were compared on native and exotic host plants. Costelytra zealandica, when sampled from exotic pastures, was unable to fully utilise its ancestral native host and showed higher feeding preference and performance on exotic plants. In contrast, C. zealandica sampled from native grasslands did not perform significantly better on either host and showed similar feeding preferences to C. brunneum, which exhibited no feeding preference. This study suggests the possibility of strong intraspecific variation in the ability of C. zealandica to exploit native or exotic plants, supporting the hypothesis that such ability underpins the existence of distinct host-races in this species.

Novel three-step pseudo-absence selection technique for improved species distribution modelling.

Pseudo-absence selection for spatial distribution models (SDMs) is the subject of ongoing investigation. Numerous techniques continue to be developed, and reports of their effectiveness vary. Because the quality of presence and absence data is key for acceptable accuracy of correlative SDM predictions, determining an appropriate method to characterise pseudo-absences for SDM's is vital. The main methods that are currently used to generate pseudo-absence points are: 1) randomly generated pseudo-absence locations from background data; 2) pseudo-absence locations generated within a delimited geographical distance from recorded presence points; and 3) pseudo-absence locations selected in areas that are environmentally dissimilar from presence points. There is a need for a method that considers both geographical extent and environmental requirements to produce pseudo-absence points that are spatially and ecologically balanced. We use a novel three-step approach that satisfies both spatial and ecological reasons why the target species is likely to find a particular geo-location unsuitable. Step 1 comprises establishing a geographical extent around species presence points from which pseudo-absence points are selected based on analyses of environmental variable importance at different distances. This step gives an ecologically meaningful explanation to the spatial range of background data, as opposed to using an arbitrary radius. Step 2 determines locations that are environmentally dissimilar to the presence points within the distance specified in step one. Step 3 performs K-means clustering to reduce the number of potential pseudo-absences to the desired set by taking the centroids of clusters in the most environmentally dissimilar class identified in step 2. By considering spatial, ecological and environmental aspects, the three-step method identifies appropriate pseudo-absence points for correlative SDMs. We illustrate this method by predicting the New Zealand potential distribution of the Asian tiger mosquito (Aedes albopictus) and the Western corn rootworm (Diabrotica virgifera virgifera).

Threat of invasive pests from within national borders.

Predicting and ranking potential invasive species present significant challenges to researchers and biosecurity agencies. Here we analyse a worldwide database of pest species assemblages to generate lists of the top 100 insect pests most likely to establish in the United States and each of its 48 contiguous states. For the United States as a whole, all of the top 100 pest species have already established. Individual states however tend to have many more 'gaps' with most states having at least 20 species absent from their top 100 list. For all but one state, every exotic pest species currently absent from a state's top 100 can be found elsewhere in the contiguous United States. We conclude that the immediate threat from known invasive insect pests is greater from within the United States than without. Our findings have potentially significant implications for biosecurity policy, emphasizing the need to consider biosecurity measures beyond established national border interventions.