Spatially explicit analyses of environmental and health data to determine past, emerging and future threats to child health.

BACKGROUND: Dire forecasts predict that an increasingly hostile environment globally will increase the threats to human health. Infants and young children are especially at risk because children are particularly vulnerable to climate-related stressors. The childhood diseases most affected, the breadth and magnitude of future health problems and the time frame over which these problems will manifest remain largely unknown. OBJECTIVES: To review the possibility that spacially explicit analyses can be used to determine how climate change has affected children's health to date and whether these analyses can be used for future projections. METHODS: As an example of whether these objectives can be achieved, all available Australian environmental and health databases were reviewed. RESULTS: Environmental and health data in Australia have been collected for up to 30 years for the same spatial areas at 'Statistical Area level 1' (SA1) scale. SA1s are defined as having a population of between 200 and 800 people and collectively they cover the whole of Australia without gaps or overlap. Although the SA1 environmental and health data have been collected separately, they can be merged to allow detailed statistical analyses that can determine how climate change has affected the health of children. CONCLUSIONS: The availability of environmental and health datasets that share the same precise spatial coordinates provides a pathway whereby past and emerging effects on child health can be measured and predicted into the future. Given that the future health and well-being of children is one of society's greatest concerns, this information is urgently needed.

Relative demographic susceptibility does not explain the extinction chronology of Sahul's megafauna.

The causes of Sahul's megafauna extinctions remain uncertain, although several interacting factors were likely responsible. To examine the relative support for hypotheses regarding plausible ecological mechanisms underlying these extinctions, we constructed the first stochastic, age-structured models for 13 extinct megafauna species from five functional/taxonomic groups, as well as 8 extant species within these groups for comparison. Perturbing specific demographic rates individually, we tested which species were more demographically susceptible to extinction, and then compared these relative sensitivities to the fossil-derived extinction chronology. Our models show that the macropodiformes were the least demographically susceptible to extinction, followed by carnivores, monotremes, vombatiform herbivores, and large birds. Five of the eight extant species were as or more susceptible than the extinct species. There was no clear relationship between extinction susceptibility and the extinction chronology for any perturbation scenario, while body mass and generation length explained much of the variation in relative risk. Our results reveal that the actual mechanisms leading to the observed extinction chronology were unlikely related to variation in demographic susceptibility per se, but were possibly driven instead by finer-scale variation in climate change and/or human prey choice and relative hunting success.

Combining agent-based, trait-based and demographic approaches to model coral-community dynamics.

The complexity of coral-reef ecosystems makes it challenging to predict their dynamics and resilience under future disturbance regimes. Models for coral-reef dynamics do not adequately account for the high functional diversity exhibited by corals. Models that are ecologically and mechanistically detailed are therefore required to simulate the ecological processes driving coral reef dynamics. Here, we describe a novel model that includes processes at different spatial scales, and the contribution of species' functional diversity to benthic-community dynamics. We calibrated and validated the model to reproduce observed dynamics using empirical data from Caribbean reefs. The model exhibits realistic community dynamics, and individual population dynamics are ecologically plausible. A global sensitivity analysis revealed that the number of larvae produced locally, and interaction-induced reductions in growth rate are the parameters with the largest influence on community dynamics. The model provides a platform for virtual experiments to explore diversity-functioning relationships in coral reefs.

Experimental comparison of aerial larvicides and habitat modification for controlling disease-carrying Aedes vigilax mosquitoes.

BACKGROUND: Microbial and insect-growth-regulator larvicides dominate current vector control programmes because they reduce larval abundance and are relatively environmentally benign. However, their short persistence makes them expensive, and environmental manipulation of larval habitat might be an alternative control measure. Aedes vigilax is a major vector species in northern Australia. A field experiment was implemented in Darwin, Australia, to test the hypotheses that (1) aerial microbial larvicide application effectively decreases Ae. vigilax larval presence, and therefore adult emergence, and (2) environmental manipulation is an effective alternative control measure. Generalised linear and mixed-effects modelling and information-theoretic comparisons were used to test these hypotheses. RESULTS: It is shown that the current aerial larvicide application campaign is effective at suppressing the emergence of Ae. vigilax, whereas vegetation removal is not as effective in this context. In addition, the results indicate that current larval sampling procedures are inadequate for quantifying larval abundance or adult emergence. CONCLUSIONS: This field-based comparison has shown that the existing larviciding campaign is more effective than a simple environmental management strategy for mosquito control. It has also identified an important knowledge gap in the use of larval sampling to evaluate the effectiveness of vector control strategies.