Experimentally assessing the effect of search effort on snare detectability

Reducing threats to biodiversity is the key objective of ranger patrols in protected areas. However, efforts can be hampered by rangers' inability to detect threats, and poor understanding of threat abundance and distribution in a landscape. Snares are particularly problematic due to their cryptic nature and limited selectivity with respect to captured animals' species, sex, or age. Using an experimental approach, we investigated the effect of search effort, habitat, season, and team on rangers' detection of snares in a tropical forest landscape. We provide an effort-detection curve, and use our findings to make preliminary predictions about snare detection under different scenarios of patrol effort. Results suggest that the overall probability of a searcher detecting any given snare in a 0.25/km2 area, assuming 60 min (or approximately 2 km) of search effort is 20% (95% CI ± 15–25%), with no significant effect of season, habitat or team. Our models suggested this would increase by approximately 10% with an additional 30mins/1 km of search effort. Our preliminary predictions of the effectiveness of different patrolling scenarios show that detection opportunities are maximised at low effort levels by deploying multiple teams to a single area, but at high effort levels deploying single teams becomes more efficient. Our results suggest that snare detectability in tropical forest landscapes is likely to be low, and may not improve dramatically with increased search effort. Given this, managers need to consider whether intensive snare-removal efforts are the best use of limited resources; the answer will depend on their underlying objectives

Multiplatform Analysis of 12 Cancer Types Reveals Molecular Classification within and across Tissues of Origin

Recent genomic analyses of pathologically-defined tumor types identify “within-a-tissue” disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head & neck, and a subset of bladder cancers coalesced into one subtype typified by TP53 alterations, TP63 amplifications, and high expression of immune and proliferation pathway genes. Of note, bladder cancers split into three pan-cancer subtypes. The multi-platform classification, while correlated with tissue-of-origin, provides independent information for predicting clinical outcomes. All datasets are available for data-mining from a unified resource to support further biological discoveries and insights into novel therapeutic strategies

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Frameworks for risk communication and disease management: the case of Lyme disease and countryside users

Management of zoonotic disease is necessary if countryside users are to gain benefit rather than suffer harm from their activities, and to avoid disproportionate reaction to novel threats. We introduce a conceptual framework based on the pressure–state–response model with five broad responses to disease incidence. Influencing public behaviour is one response and requires risk communication based on an integration of knowledge about the disease with an understanding of how publics respond to precautionary advice. A second framework emphasizes how risk communication involves more than information provision and should address dimensions including points-of-intervention over time, place and audience. The frameworks are developed by reference to tick-borne Lyme borreliosis (also known as Lyme disease), for which informed precautionary behaviour is particularly relevant. Interventions to influence behaviour can be directed by knowledge of spatial and temporal variation of tick abundance, what constitutes risky behaviour, how people respond to information of varying content, and an understanding of the social practices related to countryside use. The frameworks clarify the response options and help identify who is responsible for risk communication. These aspects are not consistently understood, and may result in an underestimation of the role of land-based organizations in facilitating appropriate precautionary behaviou

The size and migratory origins of the population of Hen Harriers Circus cyaneus wintering in England

Capsule: The majority of Hen Harriers Circus cyaneus that spend the winter in England are derived from the British breeding population. Aims: To investigate the popular hypothesis that Hen Harriers which over-winter in England are derived principally from breeding populations in mainland Europe. Methods: Demographic data were used to estimate numbers of Hen Harriers in Britain at the end of the breeding season. This figure was used, together with data from winter (October-March inclusive) recoveries of Hen Harriers ringed in Britain during the breeding season, to estimate the number of birds from the British breeding population wintering in England and in other parts of Europe. Results: It was estimated that Hen Harriers wintering in England are derived primarily from British breeding populations. Published winter population figures for British Hen Harriers may be significant underestimates. Conclusion: The link between breeding and wintering populations of Hen Harriers in Britain is closer than previously thought. Conservation action should be spread more equally between the environmental factors which limit populations in different seasons. The winter population in Britain, as monitored by the Hen Harrier Winter Roost Survey, may provide a good indication of the status of the breeding population

Lyme disease ecology in a changing world:consensus, uncertainty and critical gaps for improving control

Lyme disease is the most common tick-borne disease in temperate regions of North America, Europe and Asia, and the number of reported cases has increased in many regions as landscapes have been altered. Although there has been extensive work on the ecology and epidemiology of this disease in both Europe and North America, substantial uncertainty exists about fundamental aspects that determine spatial and temporal variation in both disease risk and human incidence, which hamper effective and efficient prevention and control. Here we describe areas of consensus that can be built on, identify areas of uncertainty and outline research needed to fill these gaps to facilitate predictive models of disease risk and the development of novel disease control strategies. Key areas of uncertainty include: (i) the precise influence of deer abundance on tick abundance, (ii) how tick populations are regulated, (iii) assembly of host communities and tick-feeding patterns across different habitats, (iv) reservoir competence of host species, and (v) pathogenicity for humans of different genotypes of Borrelia burgdorferi. Filling these knowledge gaps will improve Lyme disease prevention and control and provide general insights into the drivers and dynamics of this emblematic multi-host–vector-borne zoonotic disease