The growing demand for efficient and effective mosquito control requires a better understanding of vector population dynamics and how these are modified by endogenous and exogenous factors. A long-term (ll-year) monitoring data set describing the relative abundance of the saltmarsh mosquito (Aedes vigilax) in the greater Darwin region, northern Australia, was examined in a suite of Gompertz-logistic (GL) models with and without hypothesized environmental correlates (high tide frequency, rainfall, and relative humidity). High tide frequency and humidity were hypothesized to influence saltmarsh mosquito abundance positively, and rainfall was hypothesized to correlate negatively by reducing the availability of suitable habitats (moist substrata) required by ovipositing adult female mosquitoes. We also examined whether environmental correlates explained the variance in seasonal carrying capacity (K) because environmental stochasticity is hypothesized to modify population growth rate (r), carrying capacity, or both. Current and lagged-time effects were tested by comparing alternative population dynamics models using three different information criteria (Akaike's Information Criterion [corrected; AICJ, Bayesian Information Criterion [BIC], and cross-validation [C-V]). The GL model with a two-month lag without environmental effects explained 31 % of the deviance in population growth rate. This increased to >70% under various model combinations of high tide frequency, rainfall, and relative humidity, of which, high tide frequency and rainfall had the highest contributions. Temporal variation in Kwas explained weakly by high tide frequency, and there was some evidence that the filling of depressions to reduce standing water availability has reduced Aedes vigilax carrying capacity over the study period. This study underscores the need to consider simultaneously both types of drivers (endogenous and exogenous) when predicting mosquito abundance and population growth patterns. This work also indicates that climate change, via continued increases in rainfall and higher expected frequencies and intensities of high tide events with sea level rise, will alter mosquito abundance trends in northern Australia.

This paper re-examines the characteristics and assumptions of current remoteness/accessibility classifications in Australia and proposes a simple and easily understandable alternative measure for remoteness. In this study, remoteness is redefined simply as the average distance between two nearest people within an appropriate spatial unit where population distribution is assumed to be homogenous. By definition, the most straightforward remoteness and incapacity index (RII) would be remoteness times a measure of the incapacity for social and commercial interaction, where remoteness is gauged by the square root of the area divided by the population, and incapacity is measured by the reciprocal of population. Australian Bureau of Statistics Statistical Local Area (SLA) level population data and digital boundaries have been utilised for assessment of this index. The utility of the RII is demonstrated with two examples of activity measures for general practitioner services and businesses. At the State/Territory level, RIIs are negatively related to both general practitioner services per person (Pearson correlation coefficient r=−0.873), and the number of businesses per person (r=−0.546). The correlation can be further enhanced by normalising the distributions of the remoteness scores with a simple logarithmic function. The strong correlations confirm that remoteness has a substantial inverse impact on daily activities. Greater distance means longer time and higher costs for travelling, diseconomy of scale, and higher personnel costs. The RII provides an alternative measure of remoteness that is both intuitive and statistically straightforward and, at an SLA level, closely coincides with the commonly used but complex Accessibility/Remoteness Index of Australia Plus (ARIA+). Significantly, the RII is free of the service specific and policy sensitive adjustments justified by accessibility that have been introduced into existing measures.