Predicting local and non-local effects of resources on animal space use using a mechanistic step selection model

1. Predicting space use patterns of animals from their interactions with the environment is fundamental for understanding the effect of habitat changes on ecosystem functioning. Recent attempts to address this problem have sought to unify resource selection analysis, where animal space use is derived from available habitat quality, and mechanistic movement models, where detailed movement processes of an animal are used to predict its emergent utilization distribution. Such models bias the animal's movement towards patches that are easily available and resource-rich, and the result is a predicted probability density at a given position being a function of the habitat quality at that position. However, in reality, the probability that an animal will use a patch of the terrain tends to be a function of the resource quality in both that patch and the surrounding habitat. 2. We propose a mechanistic model where this non-local effect of resources naturally emerges from the local movement processes, by taking into account the relative utility of both the habitat where the animal currently resides and that of where it is moving. We give statistical techniques to parametrize the model from location data and demonstrate application of these techniques to GPS data of caribou in Newfoundland. 3. Steady-state animal probability distributions arising from the model have complex patterns that cannot be expressed simply as a function of the local quality of the habitat. In particular, large areas of good habitat are used more intensively than smaller patches of equal quality habitat, whereas isolated patches are used less frequently. 4. Whilst we focus on habitats in this study, our modelling framework can be readily used with any environmental covariates and therefore represents a unification of mechanistic modelling and step selection approaches to understanding animal space use

Opportunities and challenges for monitoring terrestrial biodiversity in the robotics age

With biodiversity loss escalating globally, a step change is needed in our capacity to accurately monitor species populations across ecosystems. Robotic and autonomous systems (RAS) offer technological solutions that may substantially advance terrestrial biodiversity monitoring, but this potential is yet to be considered systematically. We used a modified Delphi technique to synthesize knowledge from 98 biodiversity experts and 31 RAS experts, who identified the major methodological barriers that currently hinder monitoring, and explored the opportunities and challenges that RAS offer in overcoming these barriers. Biodiversity experts identified four barrier categories: site access, species and individual identification, data handling and storage, and power and network availability. Robotics experts highlighted technologies that could overcome these barriers and identified the developments needed to facilitate RAS-based autonomous biodiversity monitoring. Some existing RAS could be optimized relatively easily to survey species but would require development to be suitable for monitoring of more ‘difficult’ taxa and robust enough to work under uncontrolled conditions within ecosystems. Other nascent technologies (for instance, new sensors and biodegradable robots) need accelerated research. Overall, it was felt that RAS could lead to major progress in monitoring of terrestrial biodiversity by supplementing rather than supplanting existing methods. Transdisciplinarity needs to be fostered between biodiversity and RAS experts so that future ideas and technologies can be codeveloped effectively

Opportunities and challenges for monitoring terrestrial biodiversity in the robotics age

With biodiversity loss escalating globally, a step-change is needed in our capacity to accurately monitor species populations across ecosystems. Robotic and autonomous systems (RAS) offer technological solutions that may significantly advance terrestrial biodiversity monitoring, but this potential is yet to be considered systematically. We used a modified Delphi technique to synthesise knowledge from 98 biodiversity and 31 RAS experts who identified the major methodological barriers that currently hinder monitoring, and explored the opportunities and challenges that RAS offer to overcome these barriers. Biodiversity experts identified four barrier categories: site access, species/individual identification, data handling/storage and power/network availability. Robotics experts highlighted technologies that could overcome these barriers and identified the developments needed to facilitate RAS-based autonomous biodiversity monitoring. Some existing RAS could be optimised relatively easily to survey species, but would require development to monitor more ‘difficult’ taxa and be robust enough to work in uncontrolled conditions within ecosystems. Other nascent technologies (e.g., novel sensors, biodegradable robots) need accelerated research. Overall, it was felt that RAS could lead to major progress in monitoring terrestrial biodiversity by supplementing, rather than supplanting, existing methods. Transdisciplinarity needs to be fostered between biodiversity and RAS experts, so future ideas and technologies can be co-developed effectively

Altered TMPRSS2 usage by SARS-CoV-2 Omicron impacts infectivity and fusogenicity

The SARS-CoV-2 Omicron BA.1 variant emerged in 20211 and has multiple mutations in its spike protein2. Here we show that the spike protein of Omicron has a higher affinity for ACE2 compared with Delta, and a marked change in its antigenicity increases Omicron’s evasion of therapeutic monoclonal and vaccine-elicited polyclonal neutralizing antibodies after two doses. mRNA vaccination as a third vaccine dose rescues and broadens neutralization. Importantly, the antiviral drugs remdesivir and molnupiravir retain efficacy against Omicron BA.1. Replication was similar for Omicron and Delta virus isolates in human nasal epithelial cultures. However, in lung cells and gut cells, Omicron demonstrated lower replication. Omicron spike protein was less efficiently cleaved compared with Delta. The differences in replication were mapped to the entry efficiency of the virus on the basis of spike-pseudotyped virus assays. The defect in entry of Omicron pseudotyped virus to specific cell types effectively correlated with higher cellular RNA expression of TMPRSS2, and deletion of TMPRSS2 affected Delta entry to a greater extent than Omicron. Furthermore, drug inhibitors targeting specific entry pathways3 demonstrated that the Omicron spike inefficiently uses the cellular protease TMPRSS2, which promotes cell entry through plasma membrane fusion, with greater dependency on cell entry through the endocytic pathway. Consistent with suboptimal S1/S2 cleavage and inability to use TMPRSS2, syncytium formation by the Omicron spike was substantially impaired compared with the Delta spike. The less efficient spike cleavage of Omicron at S1/S2 is associated with a shift in cellular tropism away from TMPRSS2-expressing cells, with implications for altered pathogenesis

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

Incidence of diabetes mellitus following hospitalisation for COVID-19 in the United Kingdom: A prospective observational study

Background People hospitalised for coronavirus disease 2019 (COVID-19) have elevated incidence of diabetes. However, it is unclear whether this is due to shared risk factors, confounding or stress hyperglycaemia in response to acute illness. Methods We analysed a multicentre prospective cohort study (PHOSP-COVID) of people ≥18 years discharged from NHS hospitals across the United Kingdom following COVID-19. Individuals were included if they attended at least one research visit with a HbA1c measurement within 14 months of discharge and had no history of diabetes at baseline. The primary outcome was new onset diabetes (any type), as defined by a first glycated haemoglobin (HbA1c) measurement ≥6.5% (≥48 mmol/mol). Follow-up was censored at the last HbA1c measurement. Age-standardised incidence rates and incidence rate ratios (adjusted for age, sex, ethnicity, length of hospital stay, body mass index, smoking, physical activity, deprivation, hypertension, hyperlipidaemia/hypercholesterolaemia, intensive therapy unit admission, invasive mechanical ventilation, corticosteroid use and C-reactive protein score) were calculated using Poisson regression. Incidence rates were compared with the control groups of published clinical trials in the United Kingdom by applying the same inclusion and exclusion criteria, where possible. Results Incidence of diabetes was 91.4 per 1000 person-years and was higher in South Asian (incidence rate ratios [IRR] = 3.60; 1.77, 7.32; p < 0.001) and Black ethnic groups (IRR = 2.36; 1.07, 5.21; p = 0.03) compared with White ethnic groups. When restricted to similar characteristics, the incidence rates were similar to those in UK clinical trials data. Conclusion Diabetes incidence following hospitalisation for COVID-19 is high, but it remains uncertain whether it is disproportionately higher than pre-pandemic levels

Long COVID and cardiovascular disease: a prospective cohort study

Background Pre-existing cardiovascular disease (CVD) or cardiovascular risk factors have been associated with an increased risk of complications following hospitalisation with COVID-19, but their impact on the rate of recovery following discharge is not known. Objectives To determine whether the rate of patient-perceived recovery following hospitalisation with COVID-19 was affected by the presence of CVD or cardiovascular risk factors. Methods In a multicentre prospective cohort study, patients were recruited following discharge from the hospital with COVID-19 undertaking two comprehensive assessments at 5 months and 12 months. Patients were stratified by the presence of either CVD or cardiovascular risk factors prior to hospitalisation with COVID-19 and compared with controls with neither. Full recovery was determined by the response to a patient-perceived evaluation of full recovery from COVID-19 in the context of physical, physiological and cognitive determinants of health. Results From a total population of 2545 patients (38.8% women), 472 (18.5%) and 1355 (53.2%) had CVD or cardiovascular risk factors, respectively. Compared with controls (n=718), patients with CVD and cardiovascular risk factors were older and more likely to have had severe COVID-19. Full recovery was significantly lower at 12 months in patients with CVD (adjusted OR (aOR) 0.62, 95% CI 0.43 to 0.89) and cardiovascular risk factors (aOR 0.66, 95% CI 0.50 to 0.86). Conclusion Patients with CVD or cardiovascular risk factors had a delayed recovery at 12 months following hospitalisation with COVID-19. Targeted interventions to reduce the impact of COVID-19 in patients with cardiovascular disease remain an unmet need

A study of the distribution and ecology of the macrobenthic communities in Eckerts Bayou on Galveston Island, Texas.

205 p., ThesisBiological, hydrological, and geological samples were collected monthly for twelve months, from August 1976 through July 1977, at twenty stations in Eckerts Bayou, Galveston, Texas. A total of 130 species, including 53 polychaetous annelids, 35 crustaceans, 14 bivalves, and 10 gastropods, were collected during the study. The most abundant organism was the polychaete Streblopio benedicti, while the most ubiquitous species were the polychaetes Streblopio benedicti and Mediomastus californiensis, and the amphipods Ampelisca abdita and Corophium louisianum. Two-dimensional analyses were utilized to delineate site and species groups. Two site and five species groups were constructed from the two-dimensional data. An assemblage of 48 species was grouped which exhibited no apparent site restrictions. The Shannon-Wiener diversity index was indicative of a within-habitat situation where species composition did not fluctuate widely, but where H'(= sum of Pi log2 pi) was affected by the seasonal variation of the number of individuals of a few species.http://gbic.tamug.edu/request.ht

Acetamiprid fate in a sandy loam with contrasting soil organic matter contents: A comparison of the degradation, sorption and leaching of commercial neonicotinoid formulations

The impacts of neonicotinoids have generally focussed on the responses of the pure active ingredient. Using a selection of two commercial formulations and the active ingredient, we ran three laboratory studies using 14C-labelled acetamiprid to study the leaching, sorption and mineralisation behaviours of the commercially available neonicotinoid formulations compared to the pure active ingredient. We added 14C-spiked acetamiprid to a sandy loam soil that had received long-term additions of farmyard manure at two rates (10 t/ha/yr and 25 t/ha/yr) and mineral fertilisers, as a control. We found significant differences in acetamiprid mineralisation across both the SOM and chemical treatments. Sorption was primarily impacted by changes in SOM and any differences in leachate recovery were much less significant across both treatment types. The mineralisation of all pesticide formulations was comparatively slow, with <23 % of any given chemical/soil organic matter combination being mineralised over the experimental period. The highest mineralisation rates occurred in samples with the highest soil organic matter levels. The results also showed that 82.9 % ± 1.6 % of the acetamiprid applied was leached from the soil during repeated simulated rainfall events. This combined with the low sorption values, and the low rates of mineralisation, implies that acetamiprid is highly persistent and mobile within sandy soils. As a highly persistent neurotoxin with high invertebrate selectivity, the presence of neonicotinoids in soil presents a high toxicology risk to various beneficial soil organisms, including earthworms, as well as being at high risk of transfer to surrounding watercourses