A New Application of the Disturbance Index for Fire Severity in Coastal Dunes

Fires are a disturbance that can lead to short term dune destabilisation and have been suggested to be an initiation mechanism of a transgressive dune phase when paired with changing climatic conditions. Fire severity is one potential factor that could explain subsequent coastal dune destabilisations, but contemporary evidence of destabilisation following fire is lacking. In addition, the suitability of conventional satellite Earth Observation methods to detect the impacts of fire and the relative fire severity in coastal dune environments is in question. Widely applied satellite-derived burn indices (Normalised Burn Index and Normalised Difference Vegetation Index) have been suggested to underestimate the effects of fire in heterogenous landscapes or areas with sparse vegetation cover. This work assesses burn severity from high resolution aerial and Sentinel 2 satellite imagery following the 2019/2020 Black Summer fires on Kangaroo Island in South Australia, to assess the efficacy of commonly used satellite indices, and validate a new method for assessing fire severity in coastal dune systems. The results presented here show that the widely applied burn indices derived from NBR differentially assess vegetation loss and fire severity when compared in discrete soil groups across a landscape that experienced a very high severity fire. A new application of the Tasselled Cap Transformation (TCT) and Disturbance Index (DI) is presented. The differenced Disturbance Index (dDI) improves the estimation of burn severity, relative vegetation loss, and minimises the effects of differing soil conditions in the highly heterogenous landscape of Kangaroo Island. Results suggest that this new application of TCT is better suited to diverse environments like Mediterranean and semi-arid coastal regions than existing indices and can be used to better assess the effects of fire and potential remobilisation of coastal dune systems.

Implantable defibrillator-computed respiratory disturbance index predicts new-onset atrial fibrillation: the DASAP-HF study

Introduction Sleep apnea (SA), as measured by polysomnography, is a risk factor for atrial fibrillation (AF). The DASAP-HF study previously demonstrated that the Respiratory Disturbance Index (RDI) computed by an implantable cardioverter defibrillator (ICD) algorithm accurately identifies severe SA, is associated with cardiovascular events, and independently predicts death. Purpose In the present analysis we tested the hypothesis that device-detected RDI could also predict AF burden. Methods Patients with left ventricular ejection fraction ≤35% implanted with an ICD were enrolled and followed-up for 24 months. One month after implantation, patients underwent a polysomnographic study. The weekly average RDI value was considered, as calculated by the algorithm during the entire follow-up period and over a 1 week period preceding the sleep study, and patients were stratified according to an RDI value ≥ or <30 episodes/hour. The endpoints were: daily AF burden of ≥5 minutes, ≥6 hours, ≥23 hours. Results 164 enrolled patients had usable RDI values during the entire follow-up period. Severe SA (RDI≥30 episodes/h) was diagnosed in 92 (56%) patients at the time of the polysomnographic study. During a median follow-up of 25 months, AF burden ≥5 minutes/day was documented in 70 (43%), ≥6 hours/day in 48 (29%), and ≥23 hours/day in 33 (20%) patients. Device-detected RDI≥30 episodes/h at the time of the polysomnographic study, as well as the polysomnography-measured apnea hypopnea index ≥30 episodes/h, were not associated with the occurrence of the endpoints, using a Cox regression model. However, using time-dependent Cox model continuously measured weekly average RDI≥30episodes/h was independently associated with AF burden ≥5 minutes/day (HR: 2.13, 95% CI: 1.24–3.65, p=0.006), ≥6 hours/day (HR: 2.75, 95% CI: 1.37–5.49, p=0.004), and ≥23 hours/day (HR: 2.26, 95% CI: 1.05–4.86, p=0.037), after correction for history of AF, left atrial diameter, and gender. Conclusions In heart failure patients implanted with an ICD, device-diagnosed severe SA is associated with a higher risk of AF. In particular, severe SA on follow-up data review identifies patients who are from two- to three-fold more likely to experience an AF episode, according to various thresholds of daily AF burden. FUNDunding Acknowledgement Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): Promoted by the Italian Heart Rhythm Society (AIAC).Supported by a research grant from Boston Scientific.

A validation study of an esophageal probe–based polygraph against polysomnography in obstructive sleep apnea

Study objectives The aim of this study was to validate the automatically scored results of an esophageal probe–based polygraph system (ApneaGraph® Spiro) against manually scored polysomnography (Nox A1, PSG) results. We compared the apnea–hypopnea index, oxygen saturation index, and respiratory disturbance index of the devices. Methods Consenting patients, referred for obstructive sleep apnea workup, were tested simultaneously with the ApneaGraph® Spiro and Nox A1® polysomnograph. Each participant made one set of simultaneous registrations for one night. PSG results were scored independently. Apnea–hypopnea index, oxygen desaturation index, and respiratory disturbance index were compared using Pearson’s correlation and scatter plots. Sensitivity, specificity, and positive likelihood ratio of all indices at 5, 15, and 30 were calculated. Results A total of 83 participants had successful registrations. The apnea–hypopnea index showed sensitivity of 0.83, specificity of 0.95, and a positive likelihood ratio of 5.11 at an index cutoff of 15. At a cutoff of 30, the positive likelihood ratio rose to 31.43. The respiratory disturbance index showed high sensitivity (> 0.9) at all cutoffs, but specificity was below 0.5 at all cutoffs. Scatterplots revealed overestimation in mild OSA and underestimation in severe OSA for all three indices. Conclusions The ApneaGraph® Spiro performed acceptably when OSA was defined by an AHI of 15. The equipment overestimated mild OSA and underestimated severe OSA, compared to the PSG.

GNSS positioning error forecasting in the Arctic: ROTI and Precise Point Positioning error forecasting from solar wind measurements

A model forecasting ionospheric disturbances and its impact on GNSS positioning is proposed, called HAPEE (High lAtitude disturbances Positioning Error Estimator). It allows predicting ROTI index and corresponding Precise Point Positioning (PPP) error in Arctic region (i.e. latitudes > 50° ). The model is forecasting for the next hour a probability of a disturbance index or PPP error to exceed a given threshold, from solar wind conditions measured at L1 Lagrange point. Or alternatively, it is forecasting a disturbance index level that is exceeded during the next hour for a given percentage of the time. The ROTI model has been derived from NMA network measurements, considering a database covering the years 2007 up to 2019. It is demonstrated that the statistical variability of the ROTI index is mainly following a lognormal distribution. The proposed model has been tested favorably on measurements performed using measurements from stations of the NMA network that were not used for the model derivation. It is also shown that the statistics of PPP error conditioned by ROTI is following a Laplace distribution. Then a new compound model has been proposed, based on a conditional probability combining ROTI distribution conditioned by solar wind conditions and error distributions conditioned by ROTI index level.

Response of Landscape Evolution to Human Disturbances in the Coastal Wetlands in Northern Jiangsu Province, China

Human disturbance is one of the essential driving forces of landscape evolution. The quantitative evaluation of the spatial and temporal characteristics of landscape evolution and its relationship with human disturbance are of great significance to regional ecological protection and management and are crucial for achieving coordinated socioeconomic development and ecological–environmental protection. In this study, we took the coastal wetlands in northern Jiangsu province, China, as the research area, and proposed a quantitative evaluation method for directional landscape evolution. On this basis, the spatiotemporal characteristics of the landscape evolution from 1980 to 2020 and the relationship with human disturbance were quantitatively evaluated by combining a human disturbance index and statistical methods. The results showed that: (1) The area of the natural wetlands decreased significantly over the past 40 years, while the areas of artificial wetlands and non-wetlands increased significantly. (2) The landscape evolution process was dominated by the degradation process. The main types of degradation were natural wetland conversion to artificial wetland and non-wetland areas and Spartina alterniflora invasion. The restoration type was mainly restoration among artificial and natural wetlands. (3) The degradation of wetland landscapes demonstrated a southward shift trend and the spatial consistency with the change of the human disturbance index was high (the correlation coefficient was 0.89). (4) The human disturbance index was significantly and positively correlated with the rate of degradation, with a correlation coefficient of 0.43, and was not significantly and positively correlated with the restoration rate, with a correlation coefficient of 0.14. The findings in this paper provide additional information and theoretical guidance for the control of coastal wetland development and utilization, as well as for achieving coordinated wetland resource development together with utilization and ecological protection in the coastal wetlands of Jiangsu province, China.

Compared to Individuals with Mild to Moderate Obstructive Sleep Apnea (OSA), Individuals with Severe OSA Had Higher BMI and Respiratory-Disturbance Scores

Objective: Individuals with obstructive sleep apnea (OSA) are at increased risk to suffer from further somatic and sleep-related complaints. To assess OSA, demographic, anthropometric, and subjective/objective sleep parameters are taken into consideration, but often separately. Here, we entered demographic, anthropometric, subjective, and objective sleep- and breathing-related dimensions in one model. Methods: We reviewed the demographic, anthropometric, subjective and objective sleep- and breathing-related data, and polysomnographic records of 251 individuals with diagnosed OSA. OSA was considered as a continuous and as categorical variable (mild, moderate, and severe OSA). A series of correlational computations, X2-tests, F-tests, and a multiple regression model were performed to investigate which demographic, anthropometric, and subjective and objective sleep dimensions were associated with and predicted dimensions of OSA. Results: Higher apnea/hypopnea index (AHI) scores were associated with higher BMI, higher daytime sleepiness, a higher respiratory disturbance index, and higher snoring. Compared to individuals with mild to moderate OSA, individuals with severe OSA had a higher BMI, a higher respiratory disturbance index (RDI) and a higher snoring index, while subjective sleep quality and daytime sleepiness did not differ. Results from the multiple regression analysis showed that an objectively shorter sleep duration, more N2 sleep, and a higher RDI predicted AHI scores. Conclusion: The pattern of results suggests that blending demographic, anthropometric, and subjective/objective sleep- and breathing-related data enabled more effective discrimination of individuals at higher risk for OSA. The results are of practical and clinical importance: demographic, anthropometric, and breathing-related issues derived from self-rating scales provide a quick and reliable identification of individuals at risk of OSA; objective assessments provide further certainty and reliability.