On the Potts model partition function in an external field

We study the partition function of Potts model in an external (magnetic) field, and its connections with the zero-field Potts model partition function. Using a deletion-contraction formulation for the partition function Z for this model, we show that it can be expanded in terms of the zero-field partition function. We also show that Z can be written as a sum over the spanning trees, and the spanning forests, of a graph G. Our results extend to Z the well-known spanning tree expansion for the zero-field partition function that arises though its connections with the Tutte polynomial

Safeguarding pollinators and their values to human well-being

Wild and managed pollinators provide a wide range of benefits to society in terms of contributions to food security, farmer and beekeeper livelihoods, social and cultural values, as well as the maintenance of wider biodiversity and ecosystem stability. Pollinators face numerous threats, including changes in land-use and management intensity, climate change, pesticides and genetically modified crops, pollinator management and pathogens, and invasive alien species. There are well-documented declines in some wild and managed pollinators in several regions of the world. However, many effective policy and management responses can be implemented to safeguard pollinators and sustain pollination services.Environmental Biolog

Assessing recovery from acidification of European surface waters in the year 2010: Evaluation of projections made with the MAGIC Model in 1995

In 1999 we used the MAGIC (Model of Acidification of Groundwater In Catchments) model to project acidification of acid-sensitive European surface waters in the year 2010, given implementation of the Gothenburg Protocol to the Convention on Long-Range Transboundary Air Pollution (LRTAP). A total of 202 sites in 10 regions in Europe were studied. These forecasts can now be compared with measurements for the year 2010, to give a "ground truth" evaluation of the model. The prerequisite for this test is that the actual sulfur and nitrogen deposition decreased from 1995 to 2010 by the same amount as that used to drive the model forecasts; this was largely the case for sulfur, but less so for nitrogen, and the simulated surface water [NO3-] reflected this difference. For most of the sites, predicted surface water recovery from acidification for the year 2010 is very close to the actual recovery observed from measured data, as recovery is predominantly driven by reductions in sulfur deposition. Overall these results show that MAGIC successfully predicts future water chemistry given known changes in acid deposition

Optimising the use of bio-loggers for movement ecology research

1.The paradigm‐changing opportunities of bio‐logging sensors for ecological research, especially movement ecology, are vast, but the crucial questions of how best to match the most appropriate sensors and sensor combinations to specific biological questions, and how to analyse complex bio‐logging data, are mostly ignored. 2.Here, we fill this gap by reviewing how to optimise the use of bio‐logging techniques to answer questions in movement ecology and synthesise this into an Integrated Bio‐logging Framework (IBF). 3.We highlight that multi‐sensor approaches are a new frontier in bio‐logging, whilst identifying current limitations and avenues for future development in sensor technology. 4.We focus on the importance of efficient data exploration, and more advanced multi‐dimensional visualisation methods, combined with appropriate archiving and sharing approaches, to tackle the big data issues presented by bio‐logging. We also discuss the challenges and opportunities in matching the peculiarities of specific sensor data to the statistical models used, highlighting at the same time the large advances which will be required in the latter to properly analyse bio‐logging data. 5.Taking advantage of the bio‐logging revolution will require a large improvement in the theoretical and mathematical foundations of movement ecology, to include the rich set of high‐frequency multivariate data, which greatly expand the fundamentally limited and coarse data that could be collected using location‐only technology such as GPS. Equally important will be the establishment of multi‐disciplinary collaborations to catalyse the opportunities offered by current and future bio‐logging technology. If this is achieved, clear potential exists for developing a vastly improved mechanistic understanding of animal movements and their roles in ecological processes, and for building realistic predictive models

Characterization factors to assess land use impacts on pollinator abundance in life cycle assessment

While wild pollinators play a key role in global food production, their assessment is currently missing from the most commonly used environmental impact assessment method, Life Cycle Assessment (LCA). This is mainly due to constraints in data availability and compatibility with LCA inventories. To target this gap, relative pollinator abundance estimates were obtained with the use of a Delphi assessment, during which 25 experts, covering 16 nationalities and 45 countries of expertise, provided scores for low, typical, and high expected abundance associated with 24 land use categories. Based on these estimates, this study presents a set of globally generic characterization factors (CFs) that allows translating land use into relative impacts to wild pollinator abundance. The associated uncertainty of the CFs is presented along with an illustrative case to demonstrate the applicability in LCA studies. The CFs based on estimates that reached consensus during the Delphi assessment are recommended as readily applicable and allow key differences among land use types to be distinguished. The resulting CFs are proposed as the first step for incorporating pollinator impacts in LCA studies, exemplifying the use of expert elicitation methods as a useful tool to fill data gaps that constrain the characterization of key environmental impacts.Industrial EcologyEnvironmental Biolog

Post-acute COVID-19 neuropsychiatric symptoms are not associated with ongoing nervous system injury

A proportion of patients infected with severe acute respiratory syndrome coronavirus 2 experience a range of neuropsychiatric symptoms months after infection, including cognitive deficits, depression and anxiety. The mechanisms underpinning such symptoms remain elusive. Recent research has demonstrated that nervous system injury can occur during COVID-19. Whether ongoing neural injury in the months after COVID-19 accounts for the ongoing or emergent neuropsychiatric symptoms is unclear. Within a large prospective cohort study of adult survivors who were hospitalized for severe acute respiratory syndrome coronavirus 2 infection, we analysed plasma markers of nervous system injury and astrocytic activation, measured 6 months post-infection: neurofilament light, glial fibrillary acidic protein and total tau protein. We assessed whether these markers were associated with the severity of the acute COVID-19 illness and with post-acute neuropsychiatric symptoms (as measured by the Patient Health Questionnaire for depression, the General Anxiety Disorder assessment for anxiety, the Montreal Cognitive Assessment for objective cognitive deficit and the cognitive items of the Patient Symptom Questionnaire for subjective cognitive deficit) at 6 months and 1 year post-hospital discharge from COVID-19. No robust associations were found between markers of nervous system injury and severity of acute COVID-19 (except for an association of small effect size between duration of admission and neurofilament light) nor with post-acute neuropsychiatric symptoms. These results suggest that ongoing neuropsychiatric symptoms are not due to ongoing neural injury

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

Carbon revenues and economic breeding objectives in Eucalyptus globulus pulpwood plantations

This paper investigates the integration of carbon revenues into production system models used to define economic breeding objectives for the genetic improvement of Eucalyptus globulus pulp-wood plantations. A model was used to estimate that carbon dioxide equivalent accumulation in biomass in the Australian Eucalyptus globulus plantation estate established between 2004 and 2012 was in the order of ~146 t CO₂e ha⁻¹, of which 62 t CO₂e ha⁻¹ were tradable in 2012 and a further 30 t CO₂e ha⁻¹ were tradable in 2016. By considering a system where revenues for carbon sequestration are directly dependant upon biomass production in a plantation, it was possible to determine whether economic breeding objectives for the genetic improvement of E. globulus will be sensitive to the revenue from carbon sequestration. The correlated response of breeding objectives with and without carbon ( ΔcGH₁ ) never fell below 0.86 in sensitivity analysis, and the mean was 0.93. As such, where economic breeding objectives for the genetic improvement of Eucalyptus globulus for pulpwood plantations are based on maximizing NPV by increasing biomass production, the consideration of carbon in economic breeding objectives will provide no significant gains in NPV