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The Asian bush mosquito (Aedes japonicus japonicus, Theobald 1901) is an invasive culicid species which originates in Asia but is nowadays present in northern America and Europe. It is a competent vector for several human disease pathogens. In addition to the public health threat, this invasive species may also be an ecological threat for native container-breeding mosquitoes which share a similar larval habitat. Therefore, it is of importance to gain knowledge on ecological and eco-toxicological features of the Asian bush mosquito. However, optimal laboratory feeding conditions have not yet been established. Standardized feeding methods will be needed in assessing the impact of insecticides or competitional strength of this species. To fill this gap, we performed experiments on food quality and quantity for Ae. j. japonicus larvae. We found out that the commercial fish food TetraMin (Tetra, Melle, Germany) in a dose of 10 mg per larva is the most suitable food tested. We also suggest a protocol with a feeding sequence of seven portions for all larval stages of this species.
The forest, savanna, and grassland biomes, and the transitions between them, are expected to undergo major changes in the future due to global climate change. Dynamic global vegetation models (DGVMs) are very useful for understanding vegetation dynamics under the present climate, and for predicting its changes under future conditions. However, several DGVMs display high uncertainty in predicting vegetation in tropical areas. Here we perform a comparative analysis of three different DGVMs (JSBACH, LPJ-GUESS-SPITFIRE and aDGVM) with regard to their representation of the ecological mechanisms and feedbacks that determine the forest, savanna, and grassland biomes, in an attempt to bridge the knowledge gap between ecology and global modeling. The outcomes of the models, which include different mechanisms, are compared to observed tree cover along a mean annual precipitation gradient in Africa. By drawing on the large number of recent studies that have delivered new insights into the ecology of tropical ecosystems in general, and of savannas in particular, we identify two main mechanisms that need improved representation in the examined DGVMs. The first mechanism includes water limitation to tree growth, and tree–grass competition for water, which are key factors in determining savanna presence in arid and semi-arid areas. The second is a grass–fire feedback, which maintains both forest and savanna presence in mesic areas. Grasses constitute the majority of the fuel load, and at the same time benefit from the openness of the landscape after fires, since they recover faster than trees. Additionally, these two mechanisms are better represented when the models also include tree life stages (adults and seedlings), and distinguish between fire-prone and shade-tolerant forest trees, and fire-resistant and shade-intolerant savanna trees. Including these basic elements could improve the predictive ability of the DGVMs, not only under current climate conditions but also and especially under future scenarios.
This article was republished on October 14, 2015, to correct the order of Figs 8–13. The publisher apologizes for the error. Please download this article again to view the correct version. The originally published, uncorrected article and the republished, corrected article are provided here for reference.