Role of Diadegma semiclausum (Hymenoptera: Ichneumonidae) in controlling Plutella xylostella (Lepidoptera: Plutellidae): Cage exclusion experiments and direct observation

We evaluated the role of the larval parasitoid, Diadegma semiclausum Hellen (Hymenoptera: Ichneumonidae), in controlling Plutella xylostella (L.) (Lepidoptera: Plutellidae) by cage exclusion experiments and direct field observation during the winter season in southern Queensland, Australia. The cage exclusion experiment involved uncaged, open cage and closed cage treatments. A higher percentage (54-83%) of P. xylostella larvae on sentinel plants were lost in the uncaged treatment than the closed (4-9%) or open cage treatments (11-29%). Of the larvae that remained in the uncaged treatment, 72-94% were parasitized by D. semiclausum , much higher than that in the open cage treatment (8-37% in first trial, and 38-63% in second trial). Direct observations showed a significant aggregation response of the field D. semiclausum populations to high host density plants in an experimental plot and to high host density plots that were artificially set-up near to the parasitoid source fields. The degree of aggregation varied in response to habitat quality of the parasitoid source field and scales of the manipulated host patches. As a result, density-dependence in the pattern of parasitism may depend on the relative degree of aggregation of the parasitoid population at a particular scale. A high degree of aggregation seems to be necessary to generate density-dependent parasitism by D. semiclausum . Integration of the cage exclusion experiment and direct observation demonstrated the active and dominant role of this parasitoid in controlling P. xylostella in the winter season. A biologically based IPM strategy, which incorporates the use of D. semiclausum with Bt, is suggested for the management of P. xylostella in seasons or regions with a mild temperature.

Host-dependent Anopheles flavirostris larval distribution reinforces the risk of malaria near water

Malaria control strategies are more likely to be successful if groups at high risk can be accurately predicted. Given that mosquitoes have an obligate aquatic phase we were interested in determining how vector larval abundance relates to the spatial distribution of human malaria infection. We examined the relationship between malaria parasite prevalence and distance from vector larval habitat, and vector larval abundance and distance from human habitation, in separate studies in rural, low-endemic areas of the Philippines. Parasite prevalence among symptomatic patients was significantly higher among those living in proximity ( less than or equal to 50 m) to potential larval habitats of the major vector, Anopheles flavirostris (adjusted odds ratio [AOR] 2.64, P = 0.02 and AOR 3.43, P = 0.04). A larval survey of A. flavirostris revealed a higher density of early and late instars near human habitation (adjusted P < 0.05). The results suggest that larvae are associated with human habitation, thereby reinforcing malaria risk in people living close to larval habitats. This has implications for understanding the interaction between vectors, hosts, and parasites, and the potential for success of localized malaria control measures.

Exposing extinction risk analysis to pathogens: Is disease just another form of density dependence?

In the United States and several other countries., the development of population viability analyses (PVA) is a legal requirement of any species survival plan developed for threatened and endangered species. Despite the importance of pathogens in natural populations, little attention has been given to host-pathogen dynamics in PVA. To study the effect of infectious pathogens on extinction risk estimates generated from PVA, we review and synthesize the relevance of host-pathogen dynamics in analyses of extinction risk. We then develop a stochastic, density-dependent host-parasite model to investigate the effects of disease on the persistence of endangered populations. We show that this model converges on a Ricker model of density dependence under a suite of limiting assumptions, including. a high probability that epidemics will arrive and occur. Using this modeling framework, we then quantify: (1) dynamic differences between time series generated by disease and Ricker processes with the same parameters; (2) observed probabilities of quasi-extinction for populations exposed to disease or self-limitation; and (3) bias in probabilities of quasi-extinction estimated by density-independent PVAs when populations experience either form of density dependence. Our results suggest two generalities about the relationships among disease, PVA, and the management of endangered species. First, disease more strongly increases variability in host abundance and, thus, the probability of quasi-extinction, than does self-limitation. This result stems from the fact that the effects and the probability of occurrence of disease are both density dependent. Second, estimates of quasi-extinction are more often overly optimistic for populations experiencing disease than for those subject to self-limitation. Thus, although the results of density-independent PVAs may be relatively robust to some particular assumptions about density dependence, they are less robust when endangered populations are known to be susceptible to disease. If potential management actions involve manipulating pathogens, then it may be useful to. model disease explicitly.