Disturbance Variables Research Articles

Anas platyrhynchos (Mallard) has been replacing Anas rubripes (American Black Duck) in human-altered landscapes in Ontario, 1996 to 2019

Abstract Anas rubripes (American Black Duck) has received much attention over the years as a popular game bird species that experienced historical declines on its wintering grounds. Declines may be due to changes in the quality and quantity of breeding habitat, competition with A. platyrhynchos (Mallard), or both. Although the A. rubripes population has stabilized, spatial variation in regional population trends of A. rubripes on their breeding grounds can provide insight into the relative importance of these alternative hypotheses at provincial and local scales. We analyzed indicated breeding pairs count data collected in Ontario between 1996 and 2019 through the Eastern Waterfowl Survey to evaluate the correlation in breeding densities and trends of the 5 most abundant waterfowl species. We also tested whether habitat and anthropogenic disturbance variables could explain the distribution of those species. Overall, A. platyrhynchos breeding pair densities increased across the survey area, whereas A. rubripes breeding pair densities decreased in the southern and northern part of the survey area but remained stable in the central part. Densities of breeding pairs of A. rubripes and A. platyrhynchos were negatively correlated across survey plots but the trends in breeding densities were not correlated. Densities of A. platyrhynchos breeding pairs increased in human altered landscapes, whereas the density of A. rubripes breeding pairs was negatively correlated with agriculture. Our results suggest that A. platyrhynchos did not competitively exclude A. rubripes on the breeding grounds, but instead, A. rubripes were replaced by A. platyrhynchos following encroachment of agriculture into A. rubripes breeding habitat. Habitat management plans focused on breeding A. rubripes should emphasize reduction in the expansion of anthropogenic perturbations and increases in habitat conservation efforts in the central area of the breeding range in Ontario.

Symptom Burden Contributes to Sleep Problems Through Depressive Symptoms in Middle-Aged and Older Adults With Type 2 Diabetes: A Multigroup Analysis.

The purpose of this study was to examine the relationships between symptom burden and sleep problems and the role of depressive symptoms on these relationships in middle-aged and older adults with type 2 diabetes. The study employed a cross-sectional, correlational design with secondary analysis. De-identified data sets from three original studies were combined. A total of 189 men and women with type 2 diabetes were recruited using convenience sampling in midwestern United States. Symptom burden, sleep impairment and sleep disturbance, depressive symptoms, demographics, and diabetes-related variables were assessed. The participants were grouped into glucose-controlled and -uncontrolled groups to examine a multigroup effect. Multigroup path analyses were conducted. The results indicated that symptom burden had direct and indirect effects through depressive symptoms on sleep disturbance in the controlled group, whereas only a direct effect was found in the uncontrolled group. For sleep-related impairment, significant direct and indirect effects of symptom burden were found via depressive symptoms in both groups, and the strength of the effects on each path differed between the groups. Diabetes symptom burden was associated with sleep disturbance and sleep-related impairment in middle-aged and older adults with diabetes. A different approach should be considered for sleep management according to their A1C levels, and depressive symptoms can be a therapeutic target to treat sleep problems in the population.

Characteristics of sleep disturbance across two waves of the COVID-19 pandemic among nursing staffs

ObjectivesCOVID-19 has impacted human lifestyles, including sleep quality. For nursing staff, sleep disorders not only impact their health and daily lives but also have implications for patient safety. The objective of this study is to explore the impact of the COVID-19 pandemic on the psychological and social aspects of nursing staff and the factors influencing their sleep quality through a two-wave survey. MethodsNursing staff from a psychiatric hospital in southern Taiwan were recruited in two waves during the COVID-19 epidemic. The level of sleep disturbance and related variables, such as Lo's Healthy and Happy Lifestyle Scale (LHHLS) and Societal Influences Survey Questionnaire (SISQ), were collected through self-report questionnaires. Factors related to the level of sleep disturbance were examined using univariate linear regression and multilevel linear regression. Results508 nursing staff members were included in the study, with 254 members in each wave. A significant difference was found between the two waves in the positive thinking of LHHLS and all subscales of SISQ. During the second wave, sleep disturbances were mainly related to self-efficacy, positive thinking, social anxiety, and social desirability. At the fourth wave, sleep disturbances were mainly related to self-efficacy, positive thinking, and social anxiety. However, these effects change when the trend of the epidemic shifts, and other factors are taken into account. ConclusionsThis study analyzed the factors related to the sleep quality of nursing staff during the COVID-19 pandemic. We preliminarily explored the impact of the COVID-19 pandemic on the sleep quality of nursing staff. However, determining whether the end of the epidemic has reduced the impact on nursing staff requires further research.

Characteristics of Sleep Disturbance and Comparison Across Three Waves of the COVID-19 Pandemic Among Healthcare Workers.

Healthcare workers (HCWs) suffered from a heavy mental health burden during the coronavirus disease-2019 (COVID-19) pandemic. We aimed to explore the differences in sleep disturbance in three waves of the COVID-19 pandemic in Taiwan among HCWs. Moreover, factors associated with sleep disturbances in the third wave were investigated. This study, with three waves of cross-sectional surveys, recruited first-line and second-line HCWs. The level of sleep disturbance and related demographic variables were collected through self-report questionnaires. Differences in sleep disturbance across the three waves were compared with analysis of variance. Factors associated with the level of sleep disturbance were identified using univariate linear regression and further used for multivariate stepwise and bootstrap linear regression to identify the independent predictors. In total, 711, 560, and 747 HCWs were included in the first, second, and third waves, respectively. For first-line HCWs, sleep disturbance was significantly higher in the third wave than in the first wave. The level of sleep disturbance gradually increased across the three waves for all HCWs. In addition, sleep disturbance was associated with depression, posttraumatic stress disorder (PTSD) symptoms, anxiety about COVID-19, vaccine mistrust, and poorer physical and mental health among first-line HCWs. Among second-line HCWs, sleep disturbance was associated with younger age, depression, PTSD symptoms, lower preference for natural immunity, and poorer physical health. The current study identified an increase in sleep disturbance and several predictors among HCWs. Further investigation is warranted to extend the application and generalizability of the current study.

Capturing patient-reported sleep disturbance in atopic dermatitis clinical trials

BackgroundPatient-focused approaches to capturing day-to-day variability in sleep disturbance are needed to properly evaluate the sleep benefits of new treatments. Such approaches rely on patient-reported outcome (PRO) measures validated in the target patient population.MethodsUsing atopic dermatitis (AD) as an example of a disease in which sleep is commonly disturbed, we developed a strategy for measuring sleep disturbance in AD trials. In developing this strategy, we conducted a targeted literature review and held concept elicitation interviews with adolescents and adults with AD. We subsequently identified potentially suitable PRO measures and cognitively debriefed them. Finally, we evaluated their psychometric properties using data from phase 2b (NCT03100344) and phase 3 (NCT03985943 and NCT03989349) clinical trials.ResultsThe literature review confirmed that sleep disturbance is a key impact of AD but failed to identify validated PRO measures for assessing fluctuations in sleep disturbance. Subsequent concept elicitation interviews confirmed the multidimensional nature of sleep disturbance in AD and supported use of a single-item measure to assess overall sleep disturbance severity, complemented by a diary to capture individual components of sleep disturbance. The single-item sleep disturbance numerical rating scale (SD NRS) and multi-item Subject Sleep Diary (SSD)—an AD-adapted version of the Consensus Sleep Diary—were identified as potentially suitable PRO measures. Cognitive debriefing of the SD NRS and SSD demonstrated their content validity and their understandability to patients. Psychometric analyses based on AD trial data showed that the SD NRS is a well-defined, reliable, and fit-for-purpose measure of sleep disturbance in adults with AD. Furthermore, the SD NRS correlated with many SSD sleep parameters, suggesting that most concepts from the SSD can be covered using the SD NRS.ConclusionsUsing these findings, we developed an approach for measuring sleep disturbance in AD trials. Subject to further research, the same approach could also be applied to future trials of other skin diseases where itch causes sleep disturbance.

Enhancing Sustainable Afforestation through Innovative Earth Auger Design: A Simulation Study in Hilly Regions

The objective of this study was to advance sustainable forestry development through the creation of mechanical equipment, taking into account forestry operational methods. A suspended automatic feeding and retracting excavation device for tree pits was engineered, and its interaction with soil was investigated by integrating the Discrete Element Method (DEM) with Multi-Flexible Body Dynamics (MFBD). Based on simulation results, the research explored the impact mechanisms of the machine on soil transportation, working load, and fatigue lifespan of the spiral blades for different terrains and operating conditions. The coupling simulation method demonstrated the potential for designing and testing forestry equipment in specific operating environments, reducing time and resource consumption for field testing. Terrain significantly influenced soil disturbance variability, while the effect of operating direction was minor. Operational parameters should consider soil and water conservation, favoring the formation of fish-scale pits. Field tests in forested areas validate the practicality of the apparatus, providing valuable insights for the operation and equipment design of earth augers in hilly regions.

Concept and Realisation of ISFET-Based Measurement Modules for Infield Soil Nutrient Analysis and Hydroponic Systems

Ion-selective field-effect transistors (ISFETs) offer potential as micro-sensors for in situ monitoring of complex target variables in real-time closed loop actions. This article presents the concept and realisation of application-specific ISFET-based measurement systems for two different agricultural domains: infield soil measurements and hydroponic systems. Commercially available ISFETs were integrated as multi-sensor modules as well as single-sensor units for the measurement of plant-available nutrients, such as H2PO4−, NO3−, K+ or NH4+, and pH-values. Moreover, application-relevant pH values as well as temperatures for calibration purposes were measured. ISFETs were selected according to the relevant measurement dynamics for the applications. For the development and testing procedures, a laboratory setup was built up. Supported by reference materials, the outputs of the ISFETs were evaluated with respect to stability under the influence of disturbance variables, reproducibility and settling time. The results were used to develop new readout electronics. Next to stability, conditioning and calibration processes were relevant. The micro-sensors were integrated in new application-specific mechatronic handling systems and process flows. The realisation and tests are presented as well as first measurements in outdoor fields and indoor hydroponic environments.

Fish beta diversity associated with hydrologic and anthropogenic disturbance gradients in contrasting stream flow regimes

Understanding the role of hydrologic variation in structuring aquatic communities is crucial for successful conservation and sustainable management of native freshwater biodiversity. Partitioning beta diversity into the additive components of spatial turnover and nestedness can provide insight into the forces driving variability in fish assemblages across stream flow regimes. We examined stream fish beta diversity across hydrologic and anthropogenic disturbance gradients using long-term (1916–2016) site occurrence records (n = 17,375) encompassing 252 species. We assessed total beta diversity (Sørensen dissimilarity), spatial turnover, and nestedness of fish assemblages in contrasting stream flow regimes across a gradient of decreasing flow stability: groundwater stable (n = 77), groundwater (n = 67), groundwater flashy (n = 175), perennial runoff (n = 141), runoff flashy (n = 255), and intermittent (n = 63) streams. Differences in total beta diversity among the stream flow regimes were driven predominantly (>86 %) by spatial turnover (i.e. species replacement) as opposed to nestedness (i.e. species loss or gain). Total fish beta diversity and spatial turnover were highest in streams with intermediate flow stability (groundwater flashy), while more flow-stable streams (groundwater stable and groundwater) had lower turnover and higher nestedness. Species turnover was also strongly associated with seasonal variation in hydrology across all flow regimes, but these relationships were most evident for assemblages in intermittent streams. Distance-based statistical comparisons showed significant correlations between beta diversity and anthropogenic disturbance variables, including dam density, dam storage volume and water withdrawals in catchments of groundwater stable streams, while hydrologic variables were more strongly correlated with beta diversity in streams with runoff-dominated and flashy flow regimes. The high spatial turnover of species implies that fish conservation actions would benefit from watershed-focused approaches targeting multiple streams with wide spatial distribution, as opposed to simply focusing on preserving sites with the greatest number of species.

Detection of forest disturbance across California using deep-learning on PlanetScope imagery

California forests have recently experienced record breaking wildfires and tree mortality from droughts, However, there is inadequate monitoring, and limited data to inform policies and management strategies across the state. Although forest surveys and satellite observations of forest cover changes exist at medium to coarse resolutions (30–500 m) annually, they remain less effective in mapping small disturbances of forest patches (<5 m) occurring multiple times a year. We introduce a novel method of tracking California forest cover using a supervised U-Net deep learning architecture and PlanetScope’s Visual dataset which provides 3-band RGB (Red, Green, and Blue) mosaicked imagery. We created labels of forest and non-forest to train the U-Net model to map tree cover based on a semi-unsupervised classification method. We then detected changes of tree cover and disturbance with the U-Net model, achieving an overall accuracy of 98.97% over training data set, and 95.5% over an independent validation dataset, obtaining a precision of 82%, and a recall of 74%. With the predicted tree cover mask, we created wall to wall monthly tree cover maps over California at 4.77 m resolution for 2020, 2021, and 2022. These maps were then aggregated in a post-processing step to develop annual maps of disturbance, while accounting for the time of disturbance and other confounding factors such as topography, phenological and snow cover variability. We compared our high-resolution disturbance maps with wildfire GIS survey data from CALFIRE, and satellite-based forest cover changes and achieved an F-1 score of 54% and 88% respectively. The results suggest that high-resolution maps capture variability of forest disturbance and fire that wildfire surveys and medium resolution satellite products cannot. From 2020 to 2021, California maintained 30,923.5 sq km of forest while 5,994.9 sq km were disturbed. The highest observed forest loss rate was located at the Sierra Nevada mountains at 21.4% of the forested area being disturbed between 2020 and 2021. Our findings highlight the strong potential of deep learning and high-resolution RGB optical imagery for mapping complex forest ecosystems and their changes across California, as well as the application of these techniques on a national to global scale.

Future Climate Change and Anthropogenic Disturbance Promote the Invasions of the World's Worst Invasive Insect Pests.

Invasive insect pests adversely impact human welfare and global ecosystems. However, no studies have used a unified scheme to compare the range dynamics of the world's worst invasive insect pests. We investigated the future range shifts of 15 of the world's worst invasive insect pests. Although future range dynamics varied substantially among the 15 worst invasive insect pests, most exhibited large range expansions. Increases in the total habitat suitability occurred in more than ca. 85% of global terrestrial regions. The relative impacts of anthropogenic disturbance and climate variables on the range dynamics depended on the species and spatial scale. Aedes albopictus, Cinara cupressi, and Trogoderma granarium occurred four times in the top five largest potential ranges under four future climate scenarios. Anoplophora glabripennis, Aedes albopictus, and Co. formosanus were predicted to have the largest range expansions. An. glabripennis, Pl. manokwari, Co. formosanus, and So. invicta showed the largest range centroid shifts. More effective strategies will be required to prevent their range expansions. Although the strategies should be species-specific, mitigating anthropogenic disturbances and climate change will be essential to preventing future invasions. This study provides critical and novel insights for developing global strategies to combat the invasions of invasive insect pests in the future.

Atmospheric dryness removes barriers to the development of large forest fires

Large forest fires have far-reaching impacts on the environment, human health, infrastructure and the economy. Forest fires become large when all forest types across a landscape are dry enough to burn. Mesic forests are the slowest to dry and can act as a barrier to fire growth when they are too wet to burn. Therefore, identifying the factors influencing fire occurrence in mesic forests is important for gauging fire risk across large landscapes. We quantified the key factors influencing the likelihood that an active wildfire would propagate through mesic forest. We analysed 35 large forest fires (> 2500 ha) that occurred in Victoria, Australia where mesic and drier eucalypt forests are interspersed across mountainous terrain. We used a random forest model to evaluate 15 meteorological, topographic and disturbance variables as potential predictors of fire occurrence. These variables were extracted for points within burnt and unburnt patches of mesic forest. The likelihood of an active wildfire spreading through mesic forest increased by 65 % as vapour pressure deficit (VPD, i.e., atmospheric dryness) rose from 2.5 to 7 kPa. Other variables had substantially less influence (< 20 % change in fire occurrence) and their effects were further reduced when VPD was very high (> 6.5 kPa). Mesic forests were less likely to burn in areas with lower aridity, shallower slopes, and more sheltered topographic positions. Mesic forests 13–15 years following stand-replacing disturbance had 6 % higher chance of burning than long undisturbed forests (50 years post-disturbance). Overall, we show that topography and disturbance history cannot substantially counter the effects of high VPD. Therefore, the effectiveness of mesic forest as a barrier to the development of large forest fires is weakening as the climate warms. Our analysis also identifies areas less likely to burn, even under high VPD conditions. These areas could be prioritised as wildfire refugia.

Recovery rates and long‐term olfactory dysfunction following COVID‐19 infection

AbstractObjectivesOlfactory dysfunction is one of the most recognized symptoms of COVID‐19, significantly impacting quality of life, particularly in cases where recovery is prolonged. This review aims to explore patterns of olfactory recovery post‐COVID‐19 infection, with particular focus on delayed recovery.Data SourcesPublished literature in the English language, including senior author's own work, online and social media platforms, and patients' anecdotal reports.MethodA comprehensive review of the literature was undertaken by the authors with guidance from the senior author with expertise in the field of olfaction.ResultsBased on self‐report, an estimated 95% of patients recover their olfactory function within 6 months post‐COVID‐19 infection. However, psychophysical testing detects higher rates of persistent olfactory dysfunction. Recovery has been found to continue for at least 2 years postinfection; negative prognostic indicators include severe olfactory loss in the acute phase, female sex, and older age. Variability in quantitative and qualitative disturbance in prolonged cases likely reflects both peripheral and central pathophysiological mechanisms. Limitations of many of the reviewed studies reflect lack of psychophysical testing and baseline olfactory assessment.ConclusionsPost‐COVID‐19 olfactory dysfunction remains a significant health and psychosocial burden. Emerging evidence is improving awareness and knowledge among clinicians to better support patients through their olfactory rehabilitation, with hope of recovery after several months or years. Further research is needed to better understand the underlying pathogenesis of delayed recovery, identify at risk individuals earlier in the disease course, and develop therapeutic targets.

Dynamic Changes in Terrestrial Water Balance Using Remote Sensing on the Loess Plateau

In recent decades, the water cycle process in the Loess Plateau has undergone drastic changes under the influence of anthropogenic disturbance and climate variability. The Loess Plateau has been greatly affected by human activities and climate change, and the dynamics of water balance and its key influencing factors remain unknown in this region. To deepen our understanding of water resource status in the Loess Plateau, we analyzed the dynamic changes in the hydrological cycle components and terrestrial water balance via remote sensing during the 2001–2020 period. Moreover, we also discussed the dominant factors affecting the terrestrial water balance. The results indicate that precipitation and ET exhibited increasing trends, with upward rates of 2.56 mm/yr and 5.27 mm/yr, respectively. Spatially, the annual average precipitation and ET showed increasing trends from the north to south. Precipitation in 62.05% of the entire region presented a significant upward trend, with a change rate of 0~2 mm/yr, and the annual change rate of ET in a range of 0~30 mm/year accounted for 89.12%. The runoff exhibited a fluctuating and significantly upward trend during the 2000–2022 period, with a change rate of 3.92 × 108 m3/yr, and was relatively large in the middle reach of the Yellow River. The annual average water consumption in the upper reach of the YRB presented a significant decreasing trend, with a downward rate of −0.06 × 108 m3/yr from 2001 to 2020, and yet it displayed a significant increasing trend in the middle and lower reaches of the YRB with the upward rate of 0.07~0.11 × 108 m3/yr. Based on the principle of water balance, the recharge amount was calculated at less than the discharge amount during the 2001–2020 period, and the difference between recharge and discharge is gradually expanding, with a change rate of −3.72 × 108 m3/yr. The spatial distributions of TWSC revealed that the eastern region was in an imbalanced state, while the western region was in a relatively balanced state. Terrestrial water balance changes were mainly affected by climate factors and human disturbance, and land use/cover change was the dominant factor. The results will be of great significance for optimizing water resource management and formulating various water-saving strategies in the Loess Plateau.

Effects of human disturbance on detectability of non-breeding birds in urban green areas

Animals adapted to disturbed habitats have evolved multiple behavioural strategies, spanning from hiding to displacing to less disturbed microhabitats. Urban areas pose new evolutionary challenges since animals often need to deal with novel environmental conditions. In this context, urban parks may constitute biodiversity hotspots within the concrete jungle. Nonetheless, the recent increase in recreational activities in urban parks potentially puzzles the ability of urban-dwelling animals to exploit these environments. In this study, we evaluated the effect of human disturbance and other contextual variables on the activity patterns of four bird species commonly found in European urban parks, covering a wide range of ecological characteristics: the blackbird (Turdus merula), the hooded crow (Corvus cornix), the Eurasian robin (Erithacus rubecula), and the wood pigeon (Columba palumbus). We performed repeated counts of these bird species in six urban parks in northern Italy and we fitted Bayesian N-mixture models to estimate the relationship between detection probability and human disturbance (number of people present in the park), phenology (date and time of the day), and weather conditions (temperature and precipitation). For all the species but the blackbird, we found a negative relationship between the number of people present in the park and the detection probability of the focal species. We also found species-specific effects of both phenology and weather conditions on the detection probability. Our results suggest that urban dwelling species can finely modulate their activity patterns in response to the level of human disturbance, suggesting a possible key role of behavioural phenotypic plasticity. Furthermore, uncovering patterns of detectability of urban fauna can help in planning biodiversity monitoring and conservation, as it provides useful information to carry out surveys when the probability of detecting individuals is highest, optimising resource investments and reliability of biodiversity estimates.

Hubungan Kecanduan Game dengan Gangguan Tidur Pada Remaja di MTsS Al-Washliyah 27 Sei Rampah

This study aims to find out the correlation between game addiction and sleep disturbance in MTsS Al – Al-Washliyah 27 Sei Rempah. The method used in this research is quantitative. The research subjects used were 186 students. The sampling technique used in this research is the Purposive Sampling technique with certain criteria. The hypothesis put forward in this study is there is a positive correlation between game addiction and adolescent sleep disturbance with the assumption that the higher the game addiction, the higher the sleep disturbance in adolescents. This study uses the Likert scale to measure game addiction and sleep disturbance variables. This study used Pearson Product Moment Correlation data analysis techniques using the SPSS version 22.00 application. Based on the results of the data analysis we obtained P sig (0.000) 0.05 with rxy = 0.945 which indicates that the hypothesis is accepted. Thus, it can be stated that there is a significant positive relationship between game addiction and sleep disturbance. The correlation between game addiction and sleep disturbance is high. Game addiction has an effect of 89,4% on sleep disorder.

Projected impacts of climate change and anthropogenic effects on habitat distribution of endangered Javan Hawk-Eagle in Indonesia

Changing climate will jeopardize biodiversity, particularly the geographic distribution of endemic species. One such species is the Javan Hawk-Eagle (JHE, Nisaetus bartelsi), a charismatic raptor found only on Java Island, Indonesia. Thus, it is crucial to develop an appropriate conservation strategy to preserve the species. Ecological niche modeling is considered a valuable tool for designing conservation plans for the JHE. We provide an ecological niche modeling approach and transfer its model to future climate scenarios for the JHE. We utilize various machine learning algorithms under sustainability and business-as-usual (BAU) scenarios for 2050. Additionally, we investigate the conservation vulnerability of the JHE, capturing multifaceted pressures on the species from climate dissimilarities and human disturbance variables. Our study reveals that the ensemble model performs exceptionally well, with temperature emerging as the most critical factor affecting the JHE distribution. This finding indicates that climate change will have a significant impact on the JHE species. Our results suggest that the JHE distribution will likely decrease by 28.41% and 40.16% from the current JHE distribution under sustainability and BAU scenarios, respectively. Furthermore, our study reveals high-potential refugia for future JHE, covering 7,596 km2 (61%) under the sustainability scenario and only 4,403 km2 (35%) under the BAU scenario. Therefore, effective management and planning, including habitat restoration, refugia preservation, habitat connectivity, and local community inclusivity, should be well-managed to achieve JHE conservation targets.

Incorporating small‐scale disturbances in models of forest structure and aboveground biomass of tropical mountains

AbstractSeveral efforts have been made to model forest structure and estimate global aboveground biomass (AGB) magnitude and distribution. However, AGB models still show large uncertainties, especially over tropical mountains that are difficult to survey and understudied. Although forest disturbance and land use greatly influence forest structure and AGB accumulation, they are rarely considered in forest structure and AGB models. Including the effect of forest disturbance and land use could improve model performance. In this study, we used Landsat time series analysis and forest inventory data to assess and model the effect of small‐scale disturbance and land use on tropical montane forest structure and AGB. We explored two approaches: abrupt forest change detection, using the algorithm Breaks For Additive Seasonal Trend (BFAST), and gradual vegetation change by calculating the variation of remote sensing vegetation indices over time. We found that tropical montane landscapes are very dynamic and heterogenous. Out of the 284 forest plots analyzed, 27% had abrupt disturbances at least once between 1993 and 2014, and some of them showed abrupt disturbances several times. Forest plots with abrupt disturbances exhibit statistically significant lower basal area, tree height, and AGB than plots without abrupt disturbances. Using linear mixed‐effects models, we found that the number of breakpoints, annual Normalized Difference Vegetation Index SD, and Normalized Difference Water Index minimum values over time were the most informative variables for predicting forest structure, particularly basal area (adjusted R2 = 0.61). These variables are easy to calculate and could add significant power to forest structure and AGB models. In conclusion, incorporating small‐scale disturbance to model forest structure and AGB at regional scales is feasible through the identification of recent abrupt and gradual forest change using remote sensing time series. Including recent forest disturbance variables as predictors in forest structure models can greatly improve biomass predictability and mapping in dynamic landscapes.

Occupational Therapy’s Role in Return to Occupations Post-Concussion in High School Athletes

Aim This study was designed to explore experiences of high school athletes in order to understand their occupational engagement after sustaining a sports-related concussion. The study explored the role occupational therapists (OTs) can play in post-concussion care while supporting adolescents in returning to meaningful occupations. Methods The study utilized a qualitative, phenomenological approach by conducting interviews with high school athletes to understand their participation in occupations during recovery. Six student-athletes from 14–18 years of age were interviewed. Results The five identified themes from the study included impacts on ADL performance, school performance, sleep, mental health, and driver safety. Student-athletes reported feelings of loneliness and loss of identity. Dressing, showering, grooming, and driving were disturbed due to balance deficits, headaches, and nausea. Participants reported decreased participation in social, sports, and leisure occupations due to heightened symptoms. Conclusions Due to the considerable variability of disturbance in occupational participation post-concussion, occupational therapists can assist in creating and implementing individualized treatment plans to support high school athletes while recovering from a sports-related concussion.

Climatology of Martian Ionospheric Disturbances Deduced From MAVEN Data in 2014–2023

AbstractWe investigate the climatology of Martian ionospheric disturbances using Mars Atmosphere and Volatile Evolution missioN (MAVEN) data in 2014–2023. The disturbance strength is estimated by calculating residuals of in situ density from its large‐scale (filter window size ∼560 km) background and normalizing the residual with the background, as has been commonly used in terrestrial aeronomy. The disturbances are statistically stronger (a) in the local winter hemisphere than in summer and (b) on the nightside than on the dayside, with stark contrast across the terminator. The disturbances are more intense over the regions with strong radial magnetic fields (i.e., Martian crustal anomaly) than at unmagnetized regions, especially during the nighttime. Day‐to‐day variability of the Martian ionospheric disturbances does not exhibit a strong correlation with those of thermospheric CO2 disturbances or solar wind electron density/temperature at Mars.

Upland forest retreat lags behind sea-level rise in the mid-Atlantic coast.

Ghost forests consisting of dead trees adjacent to marshes are striking indicators of climate change, and marsh migration into retreating coastal forests is a primary mechanism for marsh survival in the face of global sea-level rise. Models of coastal transgression typically assume inundation of a static topography and instantaneous conversion of forest to marsh with rising seas. In contrast, here we use four decades of satellite observations to show that many low-elevation forests along the US mid-Atlantic coast have survived despite undergoing relative sea-level rise rates (RSLRR) that are among the fastest on Earth. Lateral forest retreat rates were strongly mediated by topography and seawater salinity, but not directly explained by spatial variability in RSLRR, climate, or disturbance. The elevation of coastal tree lines shifted upslope at rates correlated with, but far less than, contemporary RSLRR. Together, these findings suggest a multi-decadal lag between RSLRR and land conversion that implies coastal ecosystem resistance. Predictions based on instantaneous conversion of uplands to wetlands may therefore overestimate future land conversion in ways that challenge the timing of greenhouse gas fluxes and marsh creation, but also imply that the full effects of historical sea-level rise have yet to be realized.