Non-invasive sampling reveals low mitochondrial genetic diversity for an island endemic species: The critically endangered Grenada Dove Leptotila wellsi.

As an island endemic with a decreasing population, the critically endangered Grenada Dove Leptotila wellsi is threatened by accelerated loss of genetic diversity resulting from ongoing habitat fragmentation. Small, threatened populations are difficult to sample directly but advances in molecular methods mean that non-invasive samples can be used. We performed the first assessment of genetic diversity of populations of Grenada Dove by (a) assessing mtDNA genetic diversity in the only two areas of occupancy on Grenada, (b) defining the number of haplotypes present at each site and (c) evaluating evidence of isolation between sites. We used non-invasively collected samples from two locations: Mt Hartman (n = 18) and Perseverance (n = 12). DNA extraction and PCR were used to amplify 1751 bps of mtDNA from two mitochondrial markers: NADH dehydrogenase 2 (ND2) and Cytochrome b (Cyt b). Haplotype diversity (h) of 0.4, a nucleotide diversity (π) of 0.00023 and two unique haplotypes were identified within the ND2 sequences; a single haplotype was identified within the Cyt b sequences. Of the two haplotypes identified, the most common haplotype (haplotype A = 73.9%) was observed at both sites and the other (haplotype B = 26.1%) was unique to Perseverance. Our results show low mitochondrial genetic diversity and clear evidence for genetically isolated populations. The Grenada Dove needs urgent conservation action, including habitat protection and potentially augmentation of gene flow by translocation in order to increase genetic resilience and diversity with the ultimate aim of securing the long-term survival of this critically endangered species.

Non-territorial GPS-tagged golden eagles Aquila chrysaetos at two Scottish wind farms: Avoidance influenced by preferred habitat distribution, wind speed and blade motion status.

Wind farms can have two broad potential adverse effects on birds via antagonistic processes: displacement from the vicinity of turbines (avoidance), or death through collision with rotating turbine blades. These effects may not be mutually exclusive. Using detailed data from 99 turbines at two wind farms in central Scotland and thousands of GPS-telemetry data from dispersing golden eagles, we tested three hypotheses. Before-and-after-operation analyses supported the hypothesis of avoidance: displacement was reduced at turbine locations in more preferred habitat and with more preferred habitat nearby. After-operation analyses (i.e. from the period when turbines were operational) showed that at higher wind speeds and in highly preferred habitat eagles were less wary of turbines with motionless blades: rejecting our second hypothesis. Our third hypothesis was supported, since at higher wind speeds eagles flew closer to operational turbines; especially-once more-turbines in more preferred habitat. After operation, eagles effectively abandoned inner turbine locations, and flight line records close to rotor blades were rare. While our study indicated that whole-wind farm functional habitat loss through avoidance was the substantial adverse impact, we make recommendations on future wind farm design to minimise collision risk further. These largely entail developers avoiding outer turbine locations which are in and surrounded by swathes of preferred habitat. Our study illustrates the insights which detailed case studies of large raptors at wind farms can bring and emphasises that the balance between avoidance and collision can have several influences.

Scenario-Led Habitat Modelling of Land Use Change Impacts on Key Species.

Accurate predictions of the impacts of future land use change on species of conservation concern can help to inform policy-makers and improve conservation measures. If predictions are spatially explicit, predicted consequences of likely land use changes could be accessible to land managers at a scale relevant to their working landscape. We introduce a method, based on open source software, which integrates habitat suitability modelling with scenario-building, and illustrate its use by investigating the effects of alternative land use change scenarios on landscape suitability for black grouse Tetrao tetrix. Expert opinion was used to construct five near-future (twenty years) scenarios for the 800 km2 study site in upland Scotland. For each scenario, the cover of different land use types was altered by 5-30% from 20 random starting locations and changes in habitat suitability assessed by projecting a MaxEnt suitability model onto each simulated landscape. A scenario converting grazed land to moorland and open forestry was the most beneficial for black grouse, and 'increased grazing' (the opposite conversion) the most detrimental. Positioning of new landscape blocks was shown to be important in some situations. Increasing the area of open-canopy forestry caused a proportional decrease in suitability, but suitability gains for the 'reduced grazing' scenario were nonlinear. 'Scenario-led' landscape simulation models can be applied in assessments of the impacts of land use change both on individual species and also on diversity and community measures, or ecosystem services. A next step would be to include landscape configuration more explicitly in the simulation models, both to make them more realistic, and to examine the effects of habitat placement more thoroughly. In this example, the recommended policy would be incentives on grazing reduction to benefit black grouse.

Seasonality of Plasmodium falciparum transmission: a systematic review.

BACKGROUND: Although Plasmodium falciparum transmission frequently exhibits seasonal patterns, the drivers of malaria seasonality are often unclear. Given the massive variation in the landscape upon which transmission acts, intra-annual fluctuations are likely influenced by different factors in different settings. Further, the presence of potentially substantial inter-annual variation can mask seasonal patterns; it may be that a location has "strongly seasonal" transmission and yet no single season ever matches the mean, or synoptic, curve. Accurate accounting of seasonality can inform efficient malaria control and treatment strategies. In spite of the demonstrable importance of accurately capturing the seasonality of malaria, data required to describe these patterns is not universally accessible and as such localized and regional efforts at quantifying malaria seasonality are disjointed and not easily generalized. METHODS: The purpose of this review was to audit the literature on seasonality of P. falciparum and quantitatively summarize the collective findings. Six search terms were selected to systematically compile a list of papers relevant to the seasonality of P. falciparum transmission, and a questionnaire was developed to catalogue the manuscripts. RESULTS AND DISCUSSION: 152 manuscripts were identified as relating to the seasonality of malaria transmission, deaths due to malaria or the population dynamics of mosquito vectors of malaria. Among these, there were 126 statistical analyses and 31 mechanistic analyses (some manuscripts did both). DISCUSSION: Identified relationships between temporal patterns in malaria and climatological drivers of malaria varied greatly across the globe, with different drivers appearing important in different locations. Although commonly studied drivers of malaria such as temperature and rainfall were often found to significantly influence transmission, the lags between a weather event and a resulting change in malaria transmission also varied greatly by location. CONCLUSIONS: The contradicting results of studies using similar data and modelling approaches from similar locations as well as the confounding nature of climatological covariates underlines the importance of a multi-faceted modelling approach that attempts to capture seasonal patterns at both small and large spatial scales.

Interpreting predictive maps of disease: highlighting the pitfalls of distribution models in epidemiology.

The application of spatial modelling to epidemiology has increased significantly over the past decade, delivering enhanced understanding of the environmental and climatic factors affecting disease distributions and providing spatially continuous representations of disease risk (predictive maps). These outputs provide significant information for disease control programmes, allowing spatial targeting and tailored interventions. However, several factors (e.g. sampling protocols or temporal disease spread) can influence predictive mapping outputs. This paper proposes a conceptual framework which defines several scenarios and their potential impact on resulting predictive outputs, using simulated data to provide an exemplar. It is vital that researchers recognise these scenarios and their influence on predictive models and their outputs, as a failure to do so may lead to inaccurate interpretation of predictive maps. As long as these considerations are kept in mind, predictive mapping will continue to contribute significantly to epidemiological research and disease control planning.

The anatomy of population change in a black grouse population 1992-2008.

We interrogate an 18-year-long dataset containing counts of displaying male black grouse Tetrao tetrix and incidental counts of females within an 800-km(2) region of Perthshire, Scotland. We examine the trends in the population and investigate how different components of the population might act as signposts of different stages of overall population change. We found statistical evidence for a decline in black grouse numbers between 1992 and 2000, and then a recovery from 2002 to 2008, but little evidence for a link between population change and weather during the decline phase. There was some evidence for a positive relationship between male and female counts. The two main components of male population size, lek size and lek frequency followed the overall population trend while it was increasing, but during the earlier decline, the two became uncoupled, to expose a complex structure within the data. During the decline, when black grouse numbers were approaching their minimum, mean lek size was actually increasing. Small leks lost proportionally more birds than did large leks, and lek longevity was positively correlated with lek size, indicating that maintenance of large leks is crucial in buffering the population against serious declines. During the decline, the spatial arrangement of leks changed, with remnant leks showing tight clustering at larger spatial scales, before expanding out to fill the large areas of unoccupied landscape during the population increase. We discuss these findings in terms of species monitoring and suggest that counts of young males may add much useful demographic information with little extra effort.