New services of the EMBL Data Library.

The existing services of the EMBL Data Library for external users have been improved and extended in several ways. The EMBL File Server has been reorganised, and many new databases and other information relevant to biologists are now accessible via global computer networks. A broad range of software for molecular biology is freely available for different popular computer systems, including the EMBL enhancements to the Wisconsin (GCG) Package. The new Mail-Quicksearch and Mail-FastA services give access to the latest sequence data for database searches by ordinary electronic mail.     

Reptile responses to fire and the risk of post-disturbance sampling bias

Altered fire regimes are a driver of biodiversity decline. To plan effective management, we need to know how species are influenced by fire and to develop theory describing fire responses. Animal responses to fire are usually measured using methods that rely on animal activity, but animal activity may vary with time since fire, potentially biasing results. Using a novel approach for detecting bias in the pit-fall trap method, we found that leaf-litter dependent reptiles were more active up to 6 weeks after fire, giving a misleading impression of abundance. This effect was not discovered when modelling detectability with zero-inflated binomial models. Two species without detection bias showed early-successional responses to time since fire, consistent with a habitat-accommodation succession model. However, a habitat specialist did not have the predicted low abundance after fire due to increased post-fire movement and non-linear recovery of a key habitat component. Interactions between fire and other processes therefore must be better understood to predict reptile responses to changing fire-regimes. We conclude that there is substantial bias when trapping reptiles after fire, with species that are otherwise hard to detect appearing to be abundant. Studies that use a survey method based on animal activity such as bird calls or animal movements, likely face a similar risk of bias when comparing recently-disturbed with control sites.     

Information-Theoretic Analysis of Neural Coding

We describe an approach to analyzing single- and multiunit (ensemble) discharge patterns based on information-theoretic distance measures and on empirical theories derived from work in universal signal processing. In this approach, we quantify the difference between response patterns, whether time-varying or not, using information-theoretic distance measures. We apply these techniques to single- and multiple-unit processing of sound amplitude and sound location. These examples illustrate that neurons can simultaneously represent at least two kinds of information with different levels of fidelity. The fidelity can persist through a transient and a subsequent steady-state response, indicating that it is possible for an evolving neural code to represent information with constant fidelity.     

Replication and fine mapping of asthma-associated loci in individuals of African ancestry

Asthma originates from genetic and environmental factors with about half the risk of disease attributable to heritable causes. Genome-wide association studies, mostly in populations of European ancestry, have identified numerous asthma-associated single nucleotide polymorphisms (SNPs). Studies in populations with diverse ancestries allow both for identification of robust associations that replicate across ethnic groups and for improved resolution of associated loci due to different patterns of linkage disequilibrium between ethnic groups. Here we report on an analysis of 745 African-American subjects with asthma and 3,238 African-American control subjects from the Candidate Gene Association Resource (CARe) Consortium, including analysis of SNPs imputed using 1,000 Genomes reference panels and adjustment for local ancestry. We show strong evidence that variation near RAD50/IL13, implicated in studies of European ancestry individuals, replicates in individuals largely of African ancestry. Fine mapping in African ancestry populations also refined the variants of interest for this association. We also provide strong or nominal evidence of replication at loci near ORMDL3/GSDMB, IL1RL1/IL18R1, and 10p14, all previously associated with asthma in European or Japanese populations, but not at the PYHIN1 locus previously reported in studies of African-American samples. These results improve the understanding of asthma genetics and further demonstrate the utility of genetic studies in populations other than those of largely European ancestry.     

Animal movements in fire‐prone landscapes

Movement is a trait of fundamental importance in ecosystems subject to frequent disturbances, such as fire‐prone ecosystems. Despite this, the role of movement in facilitating responses to fire has received little attention. Herein, we consider how animal movement interacts with fire history to shape species distributions. We consider how fire affects movement between habitat patches of differing fire histories that occur across a range of spatial and temporal scales, from daily foraging bouts to infrequent dispersal events, and annual migrations. We review animal movements in response to the immediate and abrupt impacts of fire, and the longer‐term successional changes that fires set in train. We discuss how the novel threats of altered fire regimes, landscape fragmentation, and invasive species result in suboptimal movements that drive populations downwards. We then outline the types of data needed to study animal movements in relation to fire and novel threats, to hasten the integration of movement ecology and fire ecology. We conclude by outlining a research agenda for the integration of movement ecology and fire ecology by identifying key research questions that emerge from our synthesis of animal movements in fire‐prone ecosystems.     

Incentivising fire management in Pindan (Acacia shrubland): A proposed fuel type for Australia's Savanna burning greenhouse gas emissions abatement methodology

The Australian Government has sanctioned development of greenhouse gas emissions (GHG) abatement methodologies to meet international emissions reduction obligations. Savanna burning emissions abatement methodologies have been available since 2012, and there are currently 72 registered projects covering approximately 32 million ha. Abatement to date has exceeded 4 million tonnes of carbon dioxide equivalent (CO2‐e) principally through the application of low intensity early dry season fire management to reduce the amount of biomass combusted in higher intensity late dry season (LDS) fires. Savanna burning projects can only be conducted on areas with eligible fire‐prone vegetation fuel types where implementing the improved fire management regime is considered ecologically appropriate. This study assesses the suitability of including tall Acacia shrublands (‘Pindan’) as a new eligible fuel type. These shrublands make up 12% (~2 million ha) of the Kimberley region, Western Australia, where, on average, 32% is fire affected annually, mostly in the LDS. A standard assessment protocol was applied to describe vegetation fuel type structural and pyrolysis characteristics. We show that Pindan (i) can be identified and mapped as a unique tall Acacia shrubland vegetation fuel type, (ii) characterised by a significantly greater shrubby fuel load biomass, and (iii) the conservation status of which would benefit from imposition of strategic prescribed burning programme. Savanna burning projects in the Pindan fuel type could potentially abate up to 24.43 t.CO₂‐e/km² per year, generating significant income and employment opportunities for predominantly Indigenous land managers in the region.     

Priority effects: How the order of arrival of an invasive grass,Bromus tectorum,alters productivity and plant community structure when grown with native grass species

Theories and models attempt to explain how and why particular plant species grow together at particular sites or why invasive exotic species dominate plant communities. As local climates change and human‐use degrades and disturbs ecosystems, a better understanding of how plant communities assemble is pertinent, particularly when restoring grassland ecosystems that are frequently disturbed. One such community assembly theory is priority effects, which suggests that arrival order of species into a community alters plant–plant interactions and community assembly. Theoretically, priority effects can have lasting effects on ecosystems and will likely be altered as the risk of invasion by exotic species increases. It is difficult to predict how and when priority effects occur, as experimental reconstruction of arrival order is often difficult in adequate detail. As a result, limited experimental studies have explored priority effects on plant community assembly and plant invasions. To determine if and how priority effects affect the success of invasive species, we conducted a greenhouse study exploring how the arrival order of an invasive grass, Bromus tectorum, affects productivity and community composition when grown with native grasses. We found evidence for priority effects, as productivity was positively related to dominance of B. tectorum and was greater the earlier B. tectorum arrived. This suggests that priority effects could be important for plant communities as the early arrival of an invasive species drastically impacted the productivity and biodiversity of our system at the early establishment stages of plant community development.     

Closing the translation gap: AI applications in digital pathology

Recent advances in artificial intelligence show tremendous promise to improve the accuracy, reproducibility, and availability of medical diagnostics across a number of medical subspecialities. This is especially true in the field of digital pathology, which has recently witnessed a surge in publications describing state-of-the-art performance for machine learning models across a wide range of diagnostic applications. Nonetheless, despite this promise, there remain significant gaps in translating applications for any of these technologies into actual clinical practice. In this review, we will first give a brief overview of the recent progress in applying AI to digitized pathology images, focusing on how these tools might be applied in clinical workflows in the near term to improve the accuracy and efficiency of pathologists. Then we define and describe in detail the various factors that need to be addressed in order to successfully close the “translation gap” for AI applications in digital pathology.