Synthesising acid mine drainage to maintain and exploit indigenous mining micro-algae and microbial assemblies for biotreatment investigations

The stringent regulations for discharging acid mine drainage (AMD) has led to increased attention on traditional or emerging treatment technologies to establish efficient and sustainable management for mine effluents. To assess new technologies, laboratory investigations on AMD treatment are necessary requiring a consistent supply of AMD with a stable composition, thus limiting environmental variability and uncertainty during controlled experiments. Additionally, biotreatment systems using live cells, particularly micro-algae, require appropriate nutrient availability. Synthetic AMD (Syn-AMD) meets these requirements. However, to date, most of the reported Syn-AMDs are composed of only a few selected heavy metals without considering the complexity of actual AMD. In this study, AMD was synthesised based on the typical AMD characteristics from a copper mine where biotreatment is being considered using indigenous AMD algal-microbes. Major cations (Ca, Na, Cu, Zn, Mg, Mn and Ni), trace metals (Al, Fe, Ag, Na, Co, Mo, Pb and Cr), essential nutrients (N, P and C) and high SO₄ were incorporated into the Syn-AMD. This paper presents the preparation of chemically complex Syn-AMD and the challenges associated with combining metal salts of varying solubility that is not restricted to one particular mine site. The general approach reported and the particular reagents used can produce alternative Syn-AMD with varying compositions. The successful growth of indigenous AMD algal-microbes in the Syn-AMD demonstrated its applicability as appropriate generic media for cultivation and maintenance of mining microorganisms for future biotreatment studies.     

Delivering an accredited non-invasive prenatal diagnosis service for monogenic disorders and recommendations for best practice

The identification of cell-free fetal DNA circulating in maternal blood combined with technological developments, in particular next-generation sequencing, is enabling the development of safer prenatal diagnosis. While this technology has been widely applied as a highly sensitive screening test for aneuploidy, there has been relatively little clinical application for the diagnosis of monogenic disorders. In the UK, we have established non-invasive prenatal diagnosis (NIPD) as a clinical service for a range of inherited disorders. The results from NIPD do not require confirmation by invasive testing and are welcomed by patients and health professionals alike. Here, we describe the technical approaches used, current practice and outline recommendations for best practice when delivering an NIPD service from an accredited laboratory. © 2017 John Wiley & Sons, Ltd.     

Evaluation and classification of severity for 176 genes on an expanded carrier screening panel

Background

Disease severity is important when considering genes for inclusion on reproductive expanded carrier screening (ECS) panels. We applied a validated and previously published algorithm that classifies diseases into four severity categories (mild, moderate, severe, and profound) to 176 genes screened by ECS. Disease traits defining severity categories in the algorithm were then mapped to four severity-related ECS panel design criteria cited by the American College of Obstetricians and Gynecologists (ACOG).

Methods

Eight genetic counselors (GCs) and four medical geneticists (MDs) applied the severity algorithm to subsets of 176 genes. MDs and GCs then determined by group consensus how each of these disease traits mapped to ACOG severity criteria, enabling determination of the number of ACOG severity criteria met by each gene.

Results

Upon consensus GC and MD application of the severity algorithm, 68 (39%) genes were classified as profound, 71 (40%) as severe, 36 (20%) as moderate, and one (1%) as mild. After mapping of disease traits to ACOG severity criteria, 170 out of 176 genes (96.6%) were found to meet at least one of the four criteria, 129 genes (73.3%) met at least two, 73 genes (41.5%) met at least three, and 17 genes (9.7%) met all four.

Conclusion

This study classified the severity of a large set of Mendelian genes by collaborative clinical expert application of a trait-based algorithm. Further, it operationalized difficult to interpret ACOG severity criteria via mapping of disease traits, thereby promoting consistency of ACOG criteria interpretation.

     

An Experiment Testing whether Condition and Survival are Limited by Food Supply in a Reintroduced Hihi Population

Abstract: The Hihi (Stitchbird, Notiomystis cincta ) is an endemic New Zealand honeyeater that after European colonization survived on only one offshore island. Attempts to reintroduce Hihi to other islands have been unsuccessful, with populations slowly declining. The main hypothesis for these declines was an inadequate year-round supply of carbohydrate food (nectar and fruit) due to human impacts on the forest habitat. When Hihi were reintroduced to Mokoia, another island with regenerating forest, we tested whether survival was limited by carbohydrate food in the year after release. We conducted an "on-off" experiment in which ad libitum sugar water was available to birds for 2 out of every 4 weeks. We compared the masses of individual birds at the end of on and off periods to identify times when birds lost condition with no supplementary food and would be likely to starve. We also used mark-recapture analysis of resighting data to test whether mortality rates were higher when supplementary food was unavailable. The only effect of the supplementary food was that Hihi spent less time foraging for nectar and fruit and more time foraging for invertebrates. There was no time of year when birds lost mass when the food was taken away, and survival rates were not significantly lower when supplementary food was absent. The low (38%) annual survival rate could not be accounted for by shortage of carbohydrate food, and population viability analysis suggests that the population is likely to slowly decline. Our experiment shows that declines of reintroduced Hihi populations may be unrelated to food supply and that alternative hypotheses should be developed and tested. Our results also show the importance of using experimental methods, when possible, to test hypotheses about factors thought to be limiting reintroduced populations.     

Potential climate change impacts on Atlantic cod (Gadus morhua) off the northeastern USA

We examined the potential impacts of future climate change on the distribution and production of Atlantic cod (Gadus morhua) on the northeastern USA’s continental shelf. We began by examining the response of cod to bottom water temperature changes observed over the past four decades using fishery-independent resource survey data. After accounting for the overall decline in cod during this period, we show that the probability of catching cod at specified locations decreased markedly with increasing bottom temperature. Our analysis of future changes in water temperature was based on output from three coupled atmosphere–ocean general circulation models under high and low CO₂ emissions. An increase of <1.5°C is predicted for all sectors under the low emission scenario in spring and autumn by the end of this century. Under the high emission scenario, temperature increases range from ～2°C in the north to >3.5°C in the Mid-Atlantic Bight. Under these conditions, cod appear vulnerable to a loss of thermal habitat on Georges Bank, with a substantial loss of thermal habitat farther south. We also examined temperature effects on cod recruitment and growth in one stock area, the Gulf of Maine, to explore potential implications for yield and resilience to fishing. Cod survival during the early life stages declined with increasing water temperatures, offsetting potential increases in growth with warmer temperatures and resulting in a predicted loss in yield and increased vulnerability to high fishing mortality rates. Substantial differential impacts under the low versus high emission scenarios are evident for cod off the northeastern USA.     

Spatial and temporal variability of greenhouse gas emissions from rural development land use operations

Climate change objectives of mitigation and adaptation are being mainstreamed into many policies and strategies around the world. In Europe, this has included the Rural Development Programme, which aims to tackle multiple social, economic and environmental objectives in rural areas, and the integration of climate change objectives adds another strand of complexity to the decision making process. When formulating policies determining the likely effectiveness of any particular measure can be challenging, especially with respect to the spatial and temporal variability of greenhouse gas emissions. This is a challenge faced by all countries and regions around the world. This study uses Europe as an example to explore this issue. It highlights the variability in emissions from land use operations that may be encountered under different conditions and time horizons and considers this in the context of policy formulation. The Optimal Strategies for Climate change Action in Rural Areas software has been adapted to derive net greenhouse gas emissions for rural development operations for all regions in Europe. Operations have been classified into five categories based on their benefit/burden over different time horizons. The analysis shows that it is important to understand the time period over which benefits or burdens are realised and determine how this fits with policy instruments, such as land management agreements and the permanency of actions. It also shows that in some regions an operation can have benefits, but in other regions it has burdens; thus, location can be critical. Finally, in the context of developing operations to meet multiple social, economic and environmental objectives, it is important to acknowledge that seeking options that only reduce emissions may not always be practical or possible. In some instances, we may have to accept an increase in emissions in order to meet other objectives. It is important that we evaluate the net greenhouse gas emissions of all operations, not just those aimed at climate change mitigation. We can then select those with the least burden in the process of developing optimal solutions to meet multiple objectives.     

Economic-based projections of future land use in the conterminous United States under alternative policy scenarios

Land-use change significantly contributes to biodiversity loss, invasive species spread, changes in biogeochemical cycles, and the loss of ecosystem services. Planning for a sustainable future requires a thorough understanding of expected land use at the fine spatial scales relevant for modeling many ecological processes and at dimensions appropriate for regional or national-level policy making. Our goal was to construct and parameterize an econometric model of land-use change to project future land use to the year 2051 at a fine spatial scale across the conterminous United States under several alternative land-use policy scenarios. We parameterized the econometric model of land-use change with the National Resource Inventory (NRI) 1992 and 1997 land-use data for 844 000 sample points. Land-use transitions were estimated for five land-use classes (cropland, pasture, range, forest, and urban). We predicted land-use change under four scenarios: business-as-usual, afforestation, removal of agricultural subsidies, and increased urban rents. Our results for the business-as-usual scenario showed widespread changes in land use, affecting 36% of the land area of the conterminous United States, with large increases in urban land (79%) and forest (7%), and declines in cropland (-16%) and pasture (-13%). Areas with particularly high rates of land-use change included the larger Chicago area, parts of the Pacific Northwest, and the Central Valley of California. However, while land-use change was substantial, differences in results among the four scenarios were relatively minor. The only scenario that was markedly different was the afforestation scenario, which resulted in an increase of forest area that was twice as high as the business-as-usual scenario. Land-use policies can affect trends, but only so much. The basic economic and demographic factors shaping land-use changes in the United States are powerful, and even fairly dramatic policy changes, showed only moderate deviations from the business-as-usual scenario. Given the magnitude of predicted land-use change, any attempts to identify a sustainable future or to predict the effects of climate change will have to take likely land-use changes into account. Econometric models that can simulate land-use change for broad areas with fine resolution are necessary to predict trends in ecosystem service provision and biodiversity persistence.