Takayoshi Ikeda

Relative roles of climatic suitability and anthropogenic influence in determining the pattern of spread in a global invader

Because invasive species threaten the integrity of natural ecosystems, a major goal in ecology is to develop predictive models to determine which species may become widespread and where they may invade. Indeed, considerable progress has been made in understanding the factors that influence the local pattern of spread for specific invaders and the factors that are correlated with the number of introduced species that have become established in a given region. However, few studies have examined the relative importance of multiple drivers of invasion success for widespread species at global scales. Here, we use a dataset of >5,000 presence/absence records to examine the interplay between climatic suitability, biotic resistance by native taxa, human-aided dispersal, and human modification of habitats, in shaping the distribution of one of the worlds most notorious invasive species, the Argentine ant (Linepithema humile). Climatic suitability and the extent of human modification of habitats are primarily responsible for the distribution of this global invader. However, we also found some evidence for biotic resistance by native communities. Somewhat surprisingly, and despite the often cited importance of propagule pressure as a crucial driver of invasions, metrics of the magnitude of international traded commodities among countries were not related to global distribution patterns. Together, our analyses on the global-scale distribution of this invasive species provide strong evidence for the interplay of biotic and abiotic determinants of spread and also highlight the challenges of limiting the spread and subsequent impact of highly invasive 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).

Insulin-like growth factor 2 and insulin-like growth factor binding protein 2 expression in hepatoblastoma.

The expression of insulin-like growth factor 2 (IGF2) and insulin-like growth factor binding protein 2 (IGFBP2) in 11 cases of hepatoblastoma was studied by means of in situ mRNA hybridization using digoxigenin (DIG)-labeled riboprobes. The results showed that both IGF2 and IGFBP2 transcripts are present in hepatoblastoma and that their expression is inversely correlated with the degree of tumor cell differentiation. The data suggested that IGF2 and IGFBP2 gene expression could be regarded as a marker for assessment of the degree of differentiation in hepatoblastoma.

Climate Variability, Weather and Enteric Disease Incidence in New Zealand: Time Series Analysis

Background Evaluating the influence of climate variability on enteric disease incidence may improve our ability to predict how climate change may affect these diseases. Objectives To examine the associations between regional climate variability and enteric disease incidence in New Zealand. Methods Associations between monthly climate and enteric diseases (campylobacteriosis, salmonellosis, cryptosporidiosis, giardiasis) were investigated using Seasonal Auto Regressive Integrated Moving Average (SARIMA) models. Results No climatic factors were significantly associated with campylobacteriosis and giardiasis, with similar predictive power for univariate and multivariate models. Cryptosporidiosis was positively associated with average temperature of the previous month (β =  0.130, SE =  0.060, p <0.01) and inversely related to the Southern Oscillation Index (SOI) two months previously (β =  −0.008, SE =  0.004, p <0.05). By contrast, salmonellosis was positively associated with temperature (β  = 0.110, SE = 0.020, p<0.001) of the current month and SOI of the current (β  = 0.005, SE = 0.002, p<0.050) and previous month (β  = 0.005, SE = 0.002, p<0.05). Forecasting accuracy of the multivariate models for cryptosporidiosis and salmonellosis were significantly higher. Conclusions Although spatial heterogeneity in the observed patterns could not be assessed, these results suggest that temporally lagged relationships between climate variables and national communicable disease incidence data can contribute to disease prediction models and early warning systems.

Junior doctor skill in the art of physical examination: a retrospective study of the medical admission note over four decades

Objectives To investigate the hypothesis that junior doctors’ examination skills are deteriorating by assessing the medical admission note examination record. Design Retrospective study of the admission record. Setting Tertiary care hospital. Methods The admission records of 266 patients admitted to Wellington hospital between 1975 and 2011 were analysed, according to the total number of physical examination observations (PEOtot), examination of the relevant system pertaining to the presenting complaint (RelSystem) and the number of body systems examined (Nsystems). Subgroup analysis proceeded according to admission year, level of experience of the admitting doctor (registrar, house surgeon (HS) and trainee intern (TI)) and medical versus surgical admission notes. Further analysis investigated the trend over time in documentation with respect to cardiac murmurs, palpable liver, palpable spleen, carotid bruit, heart rate, funduscopy and apex beat location and character. Results PEOtot declined by 34% from 1975 to 2011. Surgical admission notes had 21% fewer observations than medical notes. RelSystem occurred in 94% of admissions, with no decline over time. Medical notes documented this more frequently than surgical notes (98% and 86%, respectively). There were no differences between registrars and HS, except for the 2010s subgroup (97% and 65%, respectively). Nsystems declined over the study period. Medical admission notes documented more body systems than surgical notes. There were no differences between registrars, HSs and TIs. Fewer examinations were performed for palpable liver, palpable spleen, cardiac murmur and apex beat location and character over the study period. There was no temporal change in the positive findings of these observations or heart rate rounding. Conclusions There has been a decline in the admission record at Wellington hospital between 1975 and 2011, implying a deterioration in local doctors’ physical examination skills. Measures to counter this trend are discussed.

What will it take to get to under 5% smoking prevalence by 2025? Modelling in a country with a smokefree goal

Background New Zealand has a goal of becoming a smokefree nation by the year 2025. Smoking prevalence in 2012 was 17%, but is over 40% for Māori (indigenous New Zealanders). We forecast the prevalence in 2025 under a business-as-usual (BAU) scenario, and determined what the initiation and cessation rates would have to be to achieve a <5% prevalence. Methods A dynamic model was developed using Census and Health Survey data from 1981 to 2012 to calculate changes in initiation by age 20 years, and net annual cessation rates, by sex, age, ethnic group and time period. Similar parameters were also calculated from a panel study for sensitivity analyses. ‘Forecasts’ used these parameters, and other scenarios, applied to the 2011–2012 prevalence. Findings Since 2002–2003, prevalence at age 20 years has decreased annually by 3.1% (95% uncertainty interval 0.8% to 5.7%) and 1.1% (−1.2% to 3.2%) for non-Māori males and females, and by 4.7% (2.2% to 7.1%) and 0.0% (−2.2% to 1.8%) for Māori, respectively. Annual net cessation rates from the dynamic model ranged from −3.0% to 6.1% across demographic groups, and from 3.0% to 6.0% in the panel study. Under BAU, smoking prevalence is forecast to be 11% and 9% for non-Māori males and females by 2025, and 30% and 37% for Māori, respectively. Achieving <5% by 2025 requires net cessation rates to increase to 10% for non-Māori and 20% for Māori, accompanied by halving or quartering of initiation rates. Conclusions The smokefree goal of <5% prevalence is only feasible with large increases in cessation rates.

Ecological Informatics for the Prediction and Management of Invasive Species

Ecologists face rapidly accumulating environmental data form spatial studies and from large-scale field experiments such that many now specialize in information technology. Those scientists carry out interdisciplinary research in what is known as ecological informatics. Ecological informatics is defined as a discipline that brings together ecology and computer science to solve problems using biologically-inspired computation, information processing, and other computer science disciplines such as data management and visualization. Scientists working in the discipline have research interests that include ecological knowledge discovery, clustering, and forecasting, and simulation of ecological dynamics by individual-based or agent-based models, as well as hybrid models and artificial life. In this chapter, ecological informatics techniques are applied to answer questions about alien invasive species, in particular, species that pose a biosecurity threat in a terrestrial ecological setting. Biosecurity is defined as the protection of a regionʼs environment, flora and fauna, marine life, indigenous resources, and human and animal health. Because biological organisms can cause billions of dollars of impact in any country, good science, systems, and protocols that underpin a regulatory biosecurity system are required in order to facilitate international trade. The tools and techniques discussed in this chapter are designed to be used in a risk analysis procedure so that agencies in charge of biosecurity can prioritize scarce resources and effort and be better prepared to prevent unexpected incursions of dangerous invasive species. The methods are used to predict, (1) which species out of the many thousands might establish in a new area, (2) where those species might establish, and, (3) where they might spread over a realistic landscape so that their impact can be determined.