The biology and natural history of Tripogon loliiformis (Poaceae, Chloridoideae), an Australian resurrection grass

Tripogon loliiformis is a desiccation-tolerant grass that occurs throughout mainland Australia. There has been recent interest in this species as a model system for understanding desiccation tolerance in a native grass at the structural, molecular and physiological levels. However, not much is known about the biology and natural history of this species, despite its widespread geographic distribution and remarkable capability of withstanding prolonged drying. We provide an overview of the genus by consolidating information from a wide variety of sources. We report a variety of new and interesting observations on the general biology, ecology and desiccation response of T. loliiformis and conclude by highlighting areas for future research.

Projecting the impact of climate change on dengue transmission in Dhaka, Bangladesh

Weather variables, mainly temperature and humidity influence vectors, viruses, human biology, ecology and consequently the intensity and distribution of the vector-borne diseases. There is evidence that warmer temperature due to climate change will influence the dengue transmission. However, long term scenario-based projections are yet to be developed. Here, we assessed the impact of weather variability on dengue transmission in a megacity of Dhaka, Bangladesh and projected the future dengue risk attributable to climate change. Our results show that weather variables particularly temperature and humidity were positively associated with dengue transmission. The effects of weather variables were observed at a lag of four months. We projected that assuming a temperature increase of 3.3 °C without any adaptation measure and changes in socio-economic condition, there will be a projected increase of 16,030 dengue cases in Dhaka by the end of this century. This information might be helpful for the public health authorities to prepare for the likely increase of dengue due to climate change. The modelling framework used in this study may be applicable to dengue projection in other cities.