Diurnal defecation rate of moose in southwest Finland

An accurate measure of defecation rate is essential for application of pellet group counts in moose (Alces alces) population estimates. We measured the wintertime, diurnal defecation rate of moose by tracking 7 GPS-collared and 22 uncollared moose in southwest Finland. The mean defecation rate was 23.5 ± 4.2 pellet groups/d, one of the highest values reported. The mean defecation rate did not differ between the tracking methods (GPS vs. uncollared moose); limited sample size precluded conclusions about sex and age differences. The defecation rate was not correlated with calendar week, length of accumulation period, or number of diurnal beds. Our results are appropriate for use in southwest Finland when using the pellet group method to assess moose population density

The effect of snow depth on movement rates of GPS-collared moose

During deep snow conditions, wildlife must balance between minimizing movements to conserve energy while seeking high amounts of browse to gain the energy. Knowledge of how snow begins to hinder their movements is therefore vital when predicting their wintertime behavior. We assessed the phenomenon with moose. Movement data from 122 GPS-collared moose were integrated with snow depth data from designated measurement stations. The effects of increasing snow depths on moose movement rates were then modeled with spline regression. The study was conducted in Finland, between 2009 and 2011. The moose were known for their sex and for the presence of calf at heel. On average, the movement rates decreased sharply until snow depths of ca. 30–40 cm, after which further significant decreases were not seen. The movement rates decreased from several kilometers per day to less than 500 m per day. Moose in the northernmost study area with the deepest snow covers moved as much as the moose in the other areas with less snow. Although we saw differences in the movement rates between males and females, differences between individuals were markedly higher than those caused by sex or a calf at heel. Moose are keystone species whose heavy browsing, especially during winter, can have profound effects on vegetation and forest regeneration. As snow covers in large parts of the boreal zone are predicted to decrease due to warming climate, the wintertime movements of moose and how they affect the local vegetation will remain relevant questions

Using allocative efficiency analysis to inform health benefits package design for progressing towards Universal Health Coverage: Proof-of-concept studies in countries seeking decision support

Background: Countries are increasingly defining health benefits packages (HBPs) as a way of progressing towards Universal Health Coverage (UHC). Resources for health are commonly constrained, so it is imperative to allocate funds as efficiently as possible. We conducted allocative efficiency analyses using the Health Interventions Prioritization tool (HIPtool) to estimate the cost and impact of potential HBPs in three countries. These analyses explore the usefulness of allocative efficiency analysis and HIPtool in particular, in contributing to priority setting discussions. / Methods and findings: HIPtool is an open-access and open-source allocative efficiency modelling tool. It is preloaded with publicly available data, including data on the 218 cost-effective interventions comprising the Essential UHC package identified in the 3rd Edition of Disease Control Priorities, and global burden of disease data from the Institute for Health Metrics and Evaluation. For these analyses, the data were adapted to the health systems of Armenia, Côte d’Ivoire and Zimbabwe. Local data replaced global data where possible. Optimized resource allocations were then estimated using the optimization algorithm. In Armenia, optimized spending on UHC interventions could avert 26% more disability-adjusted life years (DALYs), but even highly cost-effective interventions are not funded without an increase in the current health budget. In Côte d’Ivoire, surgical interventions, maternal and child health and health promotion interventions are scaled up under optimized spending with an estimated 22% increase in DALYs averted–mostly at the primary care level. In Zimbabwe, the estimated gain was even higher at 49% of additional DALYs averted through optimized spending. / Conclusions: HIPtool applications can assist discussions around spending prioritization, HBP design and primary health care transformation. The analyses provided actionable policy recommendations regarding spending allocations across specific delivery platforms, disease programs and interventions. Resource constraints exacerbated by the COVID-19 pandemic increase the need for formal planning of resource allocation to maximize health benefits

What is the potential for replacing monocultures with mixed-species stands to enhance ecosystem services in boreal forests in Fennoscandia?

The boreal forests of Fennoscandia are largely dominated by Norway spruce and Scots pine. Conifer monocultures have been favoured in forest management during the last decades. Recently, concern has risen that forests consisting of only one tree species could be vulnerable to biotic damage. Additionally, environmental and societal changes are placing new demands on forest utilization, thus shifting the focus to alternative forest management options providing a wider scale of ecosystem services. It has been proposed that mixed forests are better than monocultures with respect to biodiversity, risk management and recreational value. By synthesising research studies, we provide an overview of current knowledge on how to combine wood production and other ecosystem services in mixed boreal forests in Fennoscandia. We addressed the following questions in more detail: what are the effects of mixed forests on soil properties, understorey vegetation, biodiversity, wildlife, resistance to and resilience against damage, forest productivity and the multiple use of forests? Furthermore, what are the silvicultural possibilities for establishing and managing mixed forests?Based on this review, mixed forests appear to provide a higher output of most ecosystem goods and services, including higher biodiversity and improved risk management, soil properties and multiple-use values. The most serious challenge is the browsing by cervids, which damages sapling stands. There is potential to establish single-storied mixed forests with current regeneration methods and material. Further research is particularly needed on the silvicultural practices suited for mixed boreal forests

Preeclampsia prediction with blood pressure measurements: A global external validation of the ALSPAC models

Objective: The prediction of preeclampsia in pregnancy has resulted in a plethora of prognostic models. Yet, very few make it past the development stage and most fail to influence clinical practice. The timely identification of high-risk pregnant women could deliver a tailored antenatal care regimen, particularly in low-resource settings. This study externally validated and calibrated previously published models that predicted the risk of preeclampsia, based on blood pressure (BP) at multiple time points in pregnancy, in a geographically diverse population. Methods: The prospective INTERBIO-21st Fetal Study included 3,391 singleton pregnancies from Brazil, Kenya, Pakistan, South Africa, Thailand and the UK, 2012–2018. Preeclampsia prediction was based on baseline characteristics, BP and deviation from the expected BP trajectory at multiple time points in pregnancy. The prediction rules from the Avon Longitudinal Study of Parents and Children (ALSPAC) were implemented in the INTERBIO-21st cohort. Results: Model discrimination was similar to the development cohort. Performance was best with baseline characteristics and a BP measurement at 34 weeks’ gestation (AUC 0.85, 95 % CI 0.80–0.90). The ALSPAC models largely overestimated the true risk of preeclampsia incidence in the INTERBIO-21st cohort. Conclusions: After recalibration, these prediction models could potentially serve as a risk stratifying tool to help identify women who might benefit from increased surveillance during pregnancy

Pyrolysis of medium-density fiberboard: optimized search for kinetics scheme and parameters via a genetic algorithm driven by Kissinger's method

The pyrolysis kinetics of charring materials plays an important role in understanding material combustions especially for construction materials with complex degradation chemistry. Thermogravimetric analysis (TGA) is frequently used to study the heterogeneous kinetics of solid fuels; however, there is no agreed method to determine the pyrolysis scheme and kinetic parameters for charring polymers with multiple components and competing reaction pathways. This study develops a new technique to estimate the possible numbers of species and sub-reactions in pyrolysis by analyzing the second derivatives of thermogravimetry (DDTG) curves. The pyrolysis of a medium-density fiberboard (MDF) in nitrogen is studied in detail, and the DDTG curves are used to locate the temperature of the peak mass-loss rate for each sub-reaction. Then, on the basis of the TG data under multiple heating rates, Kissinger’s method is used to quickly find the possible range of values of the kinetic parameters (<i>A</i> and <i>E</i>). These ranges are used to accelerate the optimization of the inverse problem using a genetic algorithm (GA) for the kinetic and stoichiometric parameters. The proposed method and kinetic scheme found are shown to match the experimental data and are able to predict accurately results at different heating rates better than Kissinger’s method. Moreover, the search method (K–K method) is highly efficient, faster than the regular GA search alone. Modeling results show that, as the TG data available increase, the interdependence among kinetic parameters becomes weak and the accuracy of the first-order model declines. Furthermore, conducting TG experiment under multiple heating rates is found to be crucial in obtaining good kinetic parameters

COVID-19 in non-hospitalised adults caused by either SARS-CoV-2 sub-variants Omicron BA.1, BA.2, BA.4/5 or Delta associates with similar illness duration, symptom severity and viral kinetics, irrespective of vaccination history

BACKGROUND: SARS-CoV-2 variant Omicron rapidly evolved over 2022, causing three waves of infection due to sub-variants BA.1, BA.2 and BA.4/5. We sought to characterise symptoms and viral loads over the course of COVID-19 infection with these sub-variants in otherwise-healthy, vaccinated, non-hospitalised adults, and compared data to infections with the preceding Delta variant of concern (VOC). METHODS: In a prospective, observational cohort study, healthy vaccinated UK adults who reported a positive polymerase chain reaction (PCR) or lateral flow test, self-swabbed on alternate weekdays until day 10. We compared participant-reported symptoms and viral load trajectories between infections caused by VOCs Delta and Omicron (sub-variants BA.1, BA.2 or BA.4/5), and tested for relationships between vaccine dose, symptoms and PCR cycle threshold (Ct) as a proxy for viral load using Chi-squared (χ2) and Wilcoxon tests. RESULTS: 563 infection episodes were reported among 491 participants. Across infection episodes, there was little variation in symptom burden (4 [IQR 3-5] symptoms) and duration (8 [IQR 6-11] days). Whilst symptom profiles differed among infections caused by Delta compared to Omicron sub-variants, symptom profiles were similar between Omicron sub-variants. Anosmia was reported more frequently in Delta infections after 2 doses compared with Omicron sub-variant infections after 3 doses, for example: 42% (25/60) of participants with Delta infection compared to 9% (6/67) with Omicron BA.4/5 (χ2 P < 0.001; OR 7.3 [95% CI 2.7-19.4]). Fever was less common with Delta (20/60 participants; 33%) than Omicron BA.4/5 (39/67; 58%; χ2 P = 0.008; OR 0.4 [CI 0.2-0.7]). Amongst infections with an Omicron sub-variants, symptoms of coryza, fatigue, cough and myalgia predominated. Viral load trajectories and peaks did not differ between Delta, and Omicron, irrespective of symptom severity (including asymptomatic participants), VOC or vaccination status. PCR Ct values were negatively associated with time since vaccination in participants infected with BA.1 (β = -0.05 (CI -0.10-0.01); P = 0.031); however, this trend was not observed in BA.2 or BA.4/5 infections. CONCLUSION: Our study emphasises both the changing symptom profile of COVID-19 infections in the Omicron era, and ongoing transmission risk of Omicron sub-variants in vaccinated adults. TRIAL REGISTRATION: NCT04750356

Influences of Forest Structure, Climate and Species Composition on Tree Mortality across the Eastern US

Few studies have quantified regional variation in tree mortality, or explored whether species compositional changes or within-species variation are responsible for regional patterns, despite the fact that mortality has direct effects on the dynamics of woody biomass, species composition, stand structure, wood production and forest response to climate change. Using Bayesian analysis of over 430,000 tree records from a large eastern US forest database we characterised tree mortality as a function of climate, soils, species and size (stem diameter). We found (1) mortality is U-shaped vs. stem diameter for all 21 species examined; (2) mortality is hump-shaped vs. plot basal area for most species; (3) geographical variation in mortality is substantial, and correlated with several environmental factors; and (4) individual species vary substantially from the combined average in the nature and magnitude of their mortality responses to environmental variation. Regional variation in mortality is therefore the product of variation in species composition combined with highly varied mortality-environment correlations within species. The results imply that variation in mortality is a crucial part of variation in the forest carbon cycle, such that including this variation in models of the global carbon cycle could significantly narrow uncertainty in climate change predictions