Assessment of day-to-day functioning in prodromal and early Huntington disease

The Functional Rating Scale Taskforce for pre-Huntington Disease (FuRST-pHD) is a multinational, multidisciplinary initiative with the goal of developing a data-driven, comprehensive, psychometrically sound, rating scale for assessing symptoms and functional ability in prodromal and early Huntington disease (HD) gene expansion carriers. The process involves input from numerous sources to identify relevant symptom domains, including HD individuals, caregivers, and experts from a variety of fields, as well as knowledge gained from the analysis of data from ongoing large-scale studies in HD using existing clinical scales. This is an iterative process in which an ongoing series of field tests in prodromal (prHD) and early HD individuals provides the team with data on which to make decisions regarding which questions should undergo further development or testing and which should be excluded. We report here the development and assessment of the first iteration of interview questions aimed to assess functional impact in day-to-day activities in prHD and early HD individuals.

An objective, niche-based approach to indicator species selection

1. Species-based indices are frequently employed as surrogates for wider biodiversity health and measures of environmental condition. Species selection is crucial in determining an indicators metric value and hence the validity of the interpretation of ecosystem condition and function it provides, yet an objective process to identify appropriate indicator species is frequently lacking. 2. An effective indicator needs to (i) be representative, reflecting the status of wider biodiversity; (ii) be reactive, acting as early-warning systems for detrimental changes in environmental conditions; (iii) respond to change in a predictable way. We present an objective, niche-based approach for species' selection, founded on a coarse categorisation of species' niche space and key resource requirements, which ensures the resultant indicator has these key attributes. 3. We use UK farmland birds as a case study to demonstrate this approach, identifying an optimal indicator set containing 12 species. In contrast to the 19 species included in the farmland bird index (FBI), a key UK biodiversity indicator that contributes to one of the UK Government's headline indicators of sustainability, the niche space occupied by these species fully encompasses that occupied by the wider community of 62 species. 4. We demonstrate that the response of these 12 species to land-use change is a strong correlate to that of the wider farmland bird community. Furthermore, the temporal dynamics of the index based on their population trends closely matches the population dynamics of the wider community. However, in both analyses, the magnitude of the change in our indicator was significantly greater, allowing this indicator to act as an early-warning system. 5. Ecological indicators are embedded in environmental management, sustainable development and biodiversity conservation policy and practice where they act as metrics against which progress towards national, regional and global targets can be measured. Adopting this niche-based approach for objective selection of indicator species will facilitate the development of sensitive and representative indices for a range of taxonomic groups, habitats and spatial scales.

Strengthening the link between climate, hydrological and species distribution modeling to assess the impacts of climate change on freshwater biodiversity

To understand the resilience of aquatic ecosystems to environmental change, it is important to determine how multiple, related environmental factors, such as near-surface air temperature and river flow, will change during the next century. This study develops a novel methodology that combines statistical downscaling and fish species distribution modeling, to enhance the understanding of how global climate changes (modeled by global climate models at coarse-resolution) may affect local riverine fish diversity. The novelty of this work is the downscaling framework developed to provide suitable future projections of fish habitat descriptors, focusing particularly on the hydrology which has been rarely considered in previous studies. The proposed modeling framework was developed and tested in a major European system, the Adour-Garonne river basin (SW France, 116,000 km(2)), which covers distinct hydrological and thermal regions from the Pyrenees to the Atlantic coast. The simulations suggest that, by 2100, the mean annual stream flow is projected to decrease by approximately 15% and temperature to increase by approximately 1.2 °C, on average. As consequence, the majority of cool- and warm-water fish species is projected to expand their geographical range within the basin while the few cold-water species will experience a reduction in their distribution. The limitations and potential benefits of the proposed modeling approach are discussed. Copyright © 2012 Elsevier B.V. All rights reserved.

The REFLEX project: Comparing different algorithms and implementations for the inversion of a terrestrial ecosystem model against eddy covariance data

We describe a model-data fusion (MDF) inter-comparison project (REFLEX), which compared various algorithms for estimating carbon (C) model parameters consistent with both measured carbon fluxes and states and a simple C model. Participants were provided with the model and with both synthetic net ecosystem exchange (NEE) of CO2 and leaf area index (LAI) data, generated from the model with added noise, and observed NEE and LAI data from two eddy covariance sites. Participants endeavoured to estimate model parameters and states consistent with the model for all cases over the two years for which data were provided, and generate predictions for one additional year without observations. Nine participants contributed results using Metropolis algorithms, Kalman filters and a genetic algorithm. For the synthetic data case, parameter estimates compared well with the true values. The results of the analyses indicated that parameters linked directly to gross primary production (GPP) and ecosystem respiration, such as those related to foliage allocation and turnover, or temperature sensitivity of heterotrophic respiration, were best constrained and characterised. Poorly estimated parameters were those related to the allocation to and turnover of fine root/wood pools. Estimates of confidence intervals varied among algorithms, but several algorithms successfully located the true values of annual fluxes from synthetic experiments within relatively narrow 90% confidence intervals, achieving >80% success rate and mean NEE confidence intervals <110 gC m−2 year−1 for the synthetic case. Annual C flux estimates generated by participants generally agreed with gap-filling approaches using half-hourly data. The estimation of ecosystem respiration and GPP through MDF agreed well with outputs from partitioning studies using half-hourly data. Confidence limits on annual NEE increased by an average of 88% in the prediction year compared to the previous year, when data were available. Confidence intervals on annual NEE increased by 30% when observed data were used instead of synthetic data, reflecting and quantifying the addition of model error. Finally, our analyses indicated that incorporating additional constraints, using data on C pools (wood, soil and fine roots) would help to reduce uncertainties for model parameters poorly served by eddy covariance data.

Changing climate and the Irish landscape

The impacts of current and future changes in climate have been investigated for Irish vegetation. Warming has been observed over the last two decades, with impacts that are also strongly influenced by natural oscillations of the surrounding ocean, seen as fluctuations in the North Atlantic Oscillation and the Atlantic Multidecadal Oscillation. Satellite observations show that vegetation greenness increases in warmer years, a feature mirrored by increases in net ecosystem production observed for a grassland and a plantation forest. An ensemble of general circulation model simulations of future climates indicate temperature rises over the twenty-first century ranging from 1°C to 7°C, depending on future scenarios of greenhouse gas emissions. Net primary production is simulated to increase under all scenarios, due to the positive impacts of rising temperature, a modest rise of precipitation and rising carbon dioxide concentrations. In an optimistic scenario of reducing future emissions, CO2 concentration is simulated to flatten from about 2070, although temperatures continue to increase. Under this scenario Ireland could become a source of carbon, whereas under all other emission scenarios Ireland is a sink for carbon that may increase by up to three-fold over the twenty-first century. A likely and unavoidable impact of changing climate is the arrival of alien plant species, which may disrupt ecosystems and exert negative impacts on native biodiversity. Alien species arrive continually, with about 250 dated arrivals in the twentieth century. A simulation model indicates that this rate of alien arrival may increase by anything between two and ten times, dependent on the future climatic scenario, by 2050. Which alien species may become severely disruptive is, however, not known.

Natal nest locations of the Asian house rat (Rattus tanezumi) in lowland rice–coconut cropping systems: a coconut penthouse or rice bunds with water frontage?

CONTEXT. Rattus tanezumi is a serious crop pest within the island of Luzon, Philippines. In intensive flood-irrigated rice field ecosystems of Luzon, female R. tanezumi are known to primarily nest within the tillers of ripening rice fields and along the banks of irrigation canals. The nesting habits of R. tanezumi in complex rice–coconut cropping systems are unknown. AIMS. To identify the natal nest locations of R. tanezumi females in rice–coconut systems of the Sierra Madre Biodiversity Corridor (SMBC), Luzon, during the main breeding season to develop a management strategy that specifically targets their nesting habitat. METHODS. When rice was at the booting to ripening stage, cage-traps were placed in rice fields adjacent to coconut habitat. Thirty breeding adult R. tanezumi females were fitted with radio-collars and successfully tracked to their nest sites. KEY RESULTS. Most R. tanezumi nests (66.7%) were located in coconut groves, five nests (16.7%) were located in rice fields and five nests (16.7%) were located on the rice field edge. All nests were located above ground level and seven nests were located in coconut tree crowns. The median distance of nest sites to the nearest rice field was 22.5m. Most nest site locations had good cover of ground vegetation and understorey vegetation, but low canopy cover. Only one nest location had an understorey vegetation height of less than 20 cm. CONCLUSIONS. In the coastal lowland rice–coconut cropping systems of the SMBC, female R. tanezumi showed a preference for nesting in adjacent coconut groves. This is contrary to previous studies in intensive flood-irrigated rice ecosystems of Luzon, where the species nests mainly in the banks of irrigation canals. It is important to understand rodent breeding ecology in a specific ecosystem before implementing appropriate management strategies. IMPLICATIONS. In lowland rice–coconut cropping systems, coconut groves adjacent to rice fields should be targeted for the 20 management of R. tanezumi nest sites during the main breeding season as part of an integrated ecologically based approach to rodent pest management.

Restoring species-rich grassland: principles and techniques

Grassland restoration is the dominant activity funded by agri-environment schemes (AES). However, the re-instatement of biodiversity and ecosystem services is limited by a number of severe abiotic and biotic constraints resulting from previous agricultural management. These appear to be less severe on ex-arable sites compared with permanent grassland. We report findings of a large research programme into practical solutions to these constraints. The key abiotic constraint was high residual soil fertility, particularly phosphorus. This can most easily be addressed by targeting of sites of low nutrient status. The chief biotic constraints were lack of propagules of desirable species and suitable sites for their establishment. Addition of seed mixtures or green hay to gaps created by either mechanical disturbance or herbicide was the most effective means of overcoming these factors. Finally, manipulation of biotic interactions, including hemiparasitic plants to reduce competition from grasses and control of mollusc herbivory of sown species, significantly improved the effectiveness of these techniques.

Reading comprehension in autism spectrum disorders: The role of oral language and social functioning

Reading comprehension is an area of difficulty for many individuals with autism spectrum disorders (ASD). According to the Simple View of Reading, word recognition and oral language are both important determinants of reading comprehension ability. We provide a novel test of this model in 100 adolescents with ASD of varying intellectual ability. Further, we explore whether reading comprehension is additionally influenced by individual differences in social behaviour and social cognition in ASD. Adolescents with ASD aged 14-16 years completed assessments indexing word recognition, oral language, reading comprehension, social behaviour and social cognition. Regression analyses show that both word recognition and oral language explain unique variance in reading comprehension. Further, measures of social behaviour and social cognition predict reading comprehension after controlling for the variance explained by word recognition and oral language. This indicates that word recognition, oral language and social impairments may constrain reading comprehension in ASD.

The benefits of a compute cluster approach to high spatial resolution biodiversity richness modelling: projecting the impact of climate change on Mediterranean flora

High spatial resolution environmental data gives us a better understanding of the environmental factors affecting plant distributions at fine spatial scales. However, large environmental datasets dramatically increase compute times and output species model size stimulating the need for an alternative computing solution. Cluster computing offers such a solution, by allowing both multiple plant species Environmental Niche Models (ENMs) and individual tiles of high spatial resolution models to be computed concurrently on the same compute cluster. We apply our methodology to a case study of 4,209 species of Mediterranean flora (around 17% of species believed present in the biome). We demonstrate a 16 times speed-up of ENM computation time when 16 CPUs were used on the compute cluster. Our custom Java ‘Merge’ and ‘Downsize’ programs reduce ENM output files sizes by 94%. The median 0.98 test AUC score of species ENMs is aided by various species occurrence data filtering techniques. Finally, by calculating the percentage change of individual grid cell values, we map the projected percentages of plant species vulnerable to climate change in the Mediterranean region between 1950–2000 and 2020.

Reconciling biodiversity and carbon conservation

Climate change is leading to the development of land-based mitigation and adaptation strategies that are likely to have substantial impacts on global biodiversity. Of these, approaches to maintain carbon within existing natural ecosystems could have particularly large benefits for biodiversity. However, the geographical distributions of terrestrial carbon stocks and biodiversity differ. Using conservation planning analyses for the New World and Britain, we conclude that a carbon-only strategy would not be effective at conserving biodiversity, as have previous studies. Nonetheless, we find that a combined carbon-biodiversity strategy could simultaneously protect 90% of carbon stocks (relative to a carbon-only conservation strategy) and > 90% of the biodiversity (relative to a biodiversity-only strategy) in both regions. This combined approach encapsulates the principle of complementarity, whereby locations that contain different sets of species are prioritised, and hence disproportionately safeguard localised species that are not protected effectively by carbon-only strategies. It is efficient because localised species are concentrated into small parts of the terrestrial land surface, whereas carbon is somewhat more evenly distributed; and carbon stocks protected in one location are equivalent to those protected elsewhere. Efficient compromises can only be achieved when biodiversity and carbon are incorporated together within a spatial planning process.