Effects of forest spatial structure on insect outbreaks: insights from a host-parasitoid model.

Understanding how cycles of forest-defoliating insects are affected by forest destruction is of major importance for forest management. Achieving such an understanding with data alone is difficult, however, because population cycles are typically driven by species interactions that are highly nonlinear. We therefore constructed a mathematical model to investigate the effects of forest destruction on defoliator cycles, focusing on defoliator cycles driven by parasitoids. Our model shows that forest destruction can increase defoliator density when parasitoids disperse much farther than defoliators because the benefits of reduced defoliator mortality due to increased parasitoid dispersal mortality exceed the costs of increased defoliator dispersal mortality. This novel result can explain observations of increased outbreak duration with increasing forest fragmentation in forest tent caterpillar populations. Our model also shows that larger habitat patches can mitigate habitat loss, with clear implications for forest management. To better understand our results, we developed an approximate model that shows that defoliator spatial dynamics can be predicted from the proportion of dispersing animals that land in suitable habitat. This approximate model is practically useful because its parameters can be estimated from widely available data. Our model thus suggests that forest destruction may exacerbate defoliator outbreaks but that management practices could mitigate such effects.

How to measure the impacts of antibiotic resistance and antibiotic development on empiric therapy: new composite indices.

OBJECTIVES: We aimed to construct widely useable summary measures of the net impact of antibiotic resistance on empiric therapy. Summary measures are needed to communicate the importance of resistance, plan and evaluate interventions, and direct policy and investment. DESIGN, SETTING AND PARTICIPANTS: As an example, we retrospectively summarised the 2011 cumulative antibiogram from a Toronto academic intensive care unit. OUTCOME MEASURES: We developed two complementary indices to summarise the clinical impact of antibiotic resistance and drug availability on empiric therapy. The Empiric Coverage Index (ECI) measures susceptibility of common bacterial infections to available empiric antibiotics as a percentage. The Empiric Options Index (EOI) varies from 0 to 'the number of treatment options available', and measures the empiric value of the current stock of antibiotics as a depletable resource. The indices account for drug availability and the relative clinical importance of pathogens. We demonstrate meaning and use by examining the potential impact of new drugs and threatening bacterial strains. CONCLUSIONS: In our intensive care unit coverage of device-associated infections measured by the ECI remains high (98%), but 37-44% of treatment potential measured by the EOI has been lost. Without reserved drugs, the ECI is 86-88%. New cephalosporin/ß-lactamase inhibitor combinations could increase the EOI, but no single drug can compensate for losses. Increasing methicillin-resistant Staphylococcus aureus (MRSA) prevalence would have little overall impact (ECI=98%, EOI=4.8-5.2) because many Gram-positives are already resistant to ß-lactams. Aminoglycoside resistance, however, could have substantial clinical impact because they are among the few drugs that provide coverage of Gram-negative infections (ECI=97%, EOI=3.8-4.5). Our proposed indices summarise the local impact of antibiotic resistance on empiric coverage (ECI) and available empiric treatment options (EOI) using readily available data. Policymakers and drug developers can use the indices to help evaluate and prioritise initiatives in the effort against antimicrobial resistance.

Ecology and the Evolution of Biphasic Life Cycles.

Sexual eukaryotes undergo an alternation between haploid and diploid nuclear phases. In some organisms, both the haploid and diploid phases undergo somatic development and exist as independent entities. Despite recent attention, the mechanisms by which such biphasic life cycles evolve and persist remain obscure. One explanation that has received little theoretical attention is that haploid-diploid organisms may exploit their environments more efficiently through niche differentiation of the two ploidy phases. Even in isomorphic species, in which adults are morphologically similar, slight differences in the adult phase or among juveniles may play an important ecological role and help maintain haploid-diploidy. We develop a genetic model for the evolution of life cycles that incorporates density-dependent growth. We find that ecological differences between haploid and diploid phases can lead to the evolution and maintenance of biphasic life cycles under a broad range of conditions. Parameter estimates derived from demographic data on a population of Gracilaria gracilis, a haploid-diploid red alga with an isomorphic alternation of generations, are used to demonstrate that an ecological explanation for haploid-diploidy is plausible even when there are only slight morphological differences among adults.