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Currie, D.

Publications and source records attributed to Currie, D..

2 recordsLinked to original sources

A novel RNA virus, Macrobrachium rosenbergii Golda virus (MrGV), linked to mass mortalities of the larval giant freshwater prawn in Bangladesh

1Mass mortalities of the larval stage of the giant freshwater prawn, Macrobrachium rosenbergii, have been occurring in Bangladesh since 2011. Mortalities can reach 100% and have resulted in an 80% decline in the number of hatcheries actively producing M. rosenbergii. To investigate a causative agent for the mortalities, a disease challenge was carried out using infected material from a hatchery experiencing mortalities. Moribund larvae from the challenge were prepared for metatranscriptomic sequencing. De novo virus assembly revealed a 29 kb single-stranded positive-sense RNA virus with similarities in key protein motif sequences to yellow head virus (YHV), an RNA virus that causes mass mortalities in marine shrimp aquaculture, and other viruses in the Nidovirales order. Primers were designed against the novel virus and used to screen cDNA from larvae sampled from hatcheries in the South of Bangladesh from two consecutive years. Larvae from all hatcheries screened from both years were positive by PCR for the novel virus, including larvae from a hatchery that at the point of sampling appeared healthy, but later experienced mortalities. These screens suggest that the virus is widespread in M. rosenbergii hatchery culture in southern Bangladesh, and that early detection of the virus can be achieved by PCR. The hypothesised protein motifs of MrGV suggest that it is likely to be a new species within the Nidovirales order. Biosecurity measures should be taken in order to mitigate global spread through the movement of post-larvae within and between countries, which has previously been linked to other virus outbreaks in crustacean aquaculture.

molecular biology↗

Would conserving natural land cover in landscapes conserve biodiversity?

It is generally accepted that protecting natural land cover would protect biodiversity. This would only be true as a general statement if the relationship between richness and natural land cover were monotonic positive and scale- and method-independent. Assertions about habitat loss causing species losses often come from broad-scale assessment of richness (e.g., from range maps) combined with patterns of natural habitat conversion. Yet, the evidence about species loss following habitat loss or fragmentation typically comes from fine-scale experiments. Here, we test whether broad-extent relationships between avian species richness and natural land cover are independent of: 1) whether species distribution data come from systematic censuses (atlases) versus range maps, and 2) the grain size of the analysis. We regressed census-based and range map-based avian species richness against the proportion of natural land cover and temperature. Censused richness at the landscape level was obtained from Breeding Bird Atlases of Ontario and New York State. Range-map richness derived from BirdLife International range maps. Comparisons were made across different spatial grains: 25-km2, 100-km2, and 900-km2. Over regional extents, range-map richness relates strongly to temperature, irrespective of spatial grain. Censused species richness relates to temperature less strongly. Range-map richness is a negative function of the proportion of natural land cover, while realized richness is a peaked function. The two measures of richness are not monotonically related to each other. In conclusion, the data do not indicate that, in practice, landscapes with greater natural land cover in southern Ontario or in New York State have higher species richness. Moreover, different data types can lead to dramatically different relationships between richness and natural land cover. We argue that the argument that habitat loss is the main driver of species loss has become a panchreston. It may be misguiding conservation biology strategies by focusing on a threat that is too general to be usefully predictive.

ecology↗