Impact of climate-induced floods and typhoons on geriatric disabling health among older Chinese and Filipinos: a cross-country systematic review.

BACKGROUND: Apart from both China and the Philippines continuing to be exposed to and affected by different climate-induced hazards, in particular floods and typhoons, they are also reported to be witnessing rapid ageing populations of 60 years and older. As such, this systematic review synthesized the existing evidence about the impacts aggravated by floods and typhoons on the geriatric disabling health of older Chinese and Filipinos, respectively. METHODS: Four (4) electronic databases were systematically searched to identify eligible studies published between 2000 and early 2023. This process had to confirm the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PRISMA), as well as the standard protocol registered with PROSPERO (CRD42023420549). RESULTS: Out of 317 and 216 initial records retrieved for China and the Philippines, respectively, 27 (China) and 25 (Philippines) studies were eligible for final review. The disabling conditions they reported to affect the health of older adults were grouped into 4 categories: cognitive and intellectual, physical, chronic and terminal illnesses, and mental and psychological, with the latter identified as the most prevalent condition to affect older Chinese and Filipinos. On a sub-category level, posttraumatic stress disorder (PTSD) was the most common condition reported in 27 flood-related studies in China, while injuries and wounds prevailed in the Philippines, according to 25 typhoon-related studies. CONCLUSION: The increasing occurrence of extreme climate hazards, especially floods and typhoons in China and the Philippines, respectively, impacted the health of their older adults with various disabling effects or conditions. Therefore, this calls for appropriate geriatric-informed interventions in the context of climate change and rapidly ageing settings beyond China and the Philippines to others that are also prone to floods and typhoons.

Ocean state rising: Storm simulation and vulnerability mapping to predict hurricane impacts for Rhode Island's critical infrastructure.

Predicting the consequences of a major coastal storm is increasingly difficult as the result of global climate change and growing societal dependence on critical infrastructure (CI). Past storms are no longer a reliable predictor of future weather events, and the traditional approach to vulnerability assessment presents accumulated loss in largely quantitative terms that lack the specificity local emergency managers need to develop effective plans and mitigation strategies. The Rhode Island Coastal Hazards Modeling and Prediction (RI-CHAMP) system is a geographic information system (GIS)-based modeling tool that combines high-resolution storm simulations with geolocated vulnerability data to predict specific consequences based on local concerns about impacts to CI. This case study discusses implementing RI-CHAMP for the State of Rhode Island to predict impacts of wind and inundation on its CI during a hurricane, tropical storm, or nor'easter. This paper addresses the collection and field verification of vulnerability data, along with RI-CHAMP's process for integrating those data with storm models. The project deeply engaged end-users (emergency managers, facility managers, and other stakeholders) in developing RI-CHAMP's ArcGIS Online dashboard to ensure it provides specific, actionable data. The results of real and synthetic storm models are presented along with discussion of how the data in these simulations are being used by state and local emergency managers, facility owners, and others.

Microorganisms uniquely capture and predict stony coral tissue loss disease and hurricane disturbance impacts on US Virgin Island reefs.

Coral reef ecosystems are now commonly affected by major climate and disease disturbances. Disturbance impacts are typically recorded using reef benthic cover, but this may be less reflective of other ecosystem processes. To explore the potential for reef water-based disturbance indicators, we conducted a 7-year time series on US Virgin Island reefs where we examined benthic cover and reef water nutrients and microorganisms from 2016 to 2022, which included two major disturbances: hurricanes Irma and Maria in 2017 and the stony coral tissue loss disease outbreak starting in 2020. The disease outbreak coincided with the largest changes in the benthic habitat, with increases in the percent cover of turf algae and Ramicrusta, an invasive alga. While sampling timepoint contributed most to changes in reef water nutrient composition and microbial community beta diversity, both disturbances led to increases in ammonium concentration, a mechanism likely contributing to observed microbial community shifts. We identified 10 microbial taxa that were sensitive and predictive of increasing ammonium concentration. This included the decline of the oligotrophic and photoautotrophic Prochlorococcus and the enrichment of heterotrophic taxa. As disturbances impact reefs, the changing nutrient and microbial regimes may foster a type of microbialization, a process that hastens reef degradation.

Immediate Injury Deaths Related to the Remnants From Hurricane Ida in New York City, September 1-2, 2021.

The remnants from Hurricane Ida in September 2021 caused unprecedented rainfall and inland flooding in New York City (NYC) and resulted in many immediate deaths. We reviewed death records (electronic death certificates and medical examiner reports) to systematically document the circumstances of death and demographics of decedents to inform injury prevention and climate adaptation actions for future extreme precipitation events. There were 14 Ida-related injury deaths in NYC, of which 13 (93%) were directly caused by Ida, and 1 (7%) was indirectly related. Most decedents were Asian (71%) and foreign-born (71%). The most common circumstance of death was drowning in unregulated basement apartments (71%). Themes that emerged from the death records review included the suddenness of flooding, inadequate exits, nighttime risks, and multiple household members were sometimes affected. These deaths reflect interacting housing and climate crises, and their disproportionate impact on disadvantaged populations needing safe and affordable housing. Climate adaptation actions, such as improving stormwater management infrastructure, informing residents about flood risk, implementing Federal Emergency Management Agency recommendations to make basements safer, and expanding emergency notification measures can mitigate risk. As climate change increases extreme precipitation events, multi-layered efforts are needed to keep residents safe.

Spatial and temporal assessment of snake encounters in urban Delhi, India.

Delhi, the capital city of India is, highly urbanized and surrounded by remnant forest, farms, ridges, and other green areas experience regular snake encounters in and around residential, institutional, and industrial areas. A total of 41 months of sampling from January 2019 to May 2022 was conducted wherein we, studied the snake assemblage in Delhi to determine the species composition, encounter frequency, seasonal activity patterns, and probable encounter sites in an urban setup. We documented 372 individuals belonging to 15 species from seven families out of 23 species found in Delhi. Snakes were found inside forests, public parks, homes, drain networks, streets, office buildings, and even in school-college buildings. The most recorded species being Ptyas mucosa (37.37%, n = 139), Naja naja (19.62%, n = 73), and Lycodon aulicus (13.44%, n = 50). The highest numbers of incidents were reported in the month of July (22.04%, n = 82) and August (19.89%, n = 74) during the peak monsoon season, for identifying high encounter sites, we used a geostatistical modeling tool, Ordinary kriging to identify places having more snake occurrences. We further used a statistical spatial method called average nearest neighbor distance to detect the pattern distribution of snake species. Spatial interpolation done through Ordinary kriging highlighted two areas having concentrated snake encounters. The results of the average nearest neighbor distance analysis showed three species having clustered and two species having dispersed distribution. The incidence of snake encounters was found to be highly seasonal and appeared to be associated mainly with monthly rainfall, temperature, and humidity. The findings of this study on snakes' distribution patterns provide valuable insights into the conservation of these species. Understanding their habitat preferences and spatial distribution is crucial for the implementation of effective conservation strategies.

Determining the Impact of Hurricane Dorian and the Covid-19 Pandemic on Moral Distress in Emergency Medical Providers at the Rand Memorial Hospital: Moral distress in emergency medical personnel.

OBJECTIVES: The aim of this work was to determine the impact of Moral Distress (MD) in emergency physicians, nurses, and emergency medical service staff at the Rand Memorial Hospital (RMH) in the Bahamas, and the impact of Hurricane Dorian and the COVID-19 pandemic on Moral Distress. METHOD: A cross-sectional study utilizing a 3-part survey, which collected sociodemographic information, Hurricane Dorian and COVID-19 experiences, as well as responses to a validated modified Moral Distress Scale (MDS). RESULTS: Participants with 2 negatively impactful experiences from COVID-19 had statistically significantly increased MD compared to participants with only 1 negatively impactful experience (40.4 vs. 23.6, P = 0.014). Losing a loved one due to COVID-19 was associated with significantly decreased MD (B = - 0.42, 95% CI -19.70 to -0.88, P = 0.03). Losing a loved one due to Hurricane Dorian had a non-statistically significant trend towards higher MD scores (B = 0.34, 95% CI -1.23 to 28.75, P = 0.07). CONCLUSION: The emergency medical staff at the RMH reported having mild - moderate MD. This is one of the first studies to look at the impact of concurrent disasters on MD in emergency medical providers in the Bahamas.

Can cyclone exposure explain behavioural and demographic variation among lemur species?

Madagascar has a harsh and stochastic climate because of regular natural disturbances. This history of regular cyclones has been hypothesised to have directed evolutionary changes to lemur behaviour and morphology that make them more resilient to sudden environmental change. These adaptations may include: small group sizes, high degrees of energy-conserving behaviours, generalist habitat use, small home ranges, small body size, and a limited number of frugivorous species. To date, however, no one has tested how variation in cyclone exposure across Madagascar is associated with variation in these resilience traits. In this study, we created a detailed cyclone impact map for Madagascar using Koppen-Geiger climate class, historical cyclone tracks, the Saffir Class of cyclone and hurricane intensity, and precipitation data. We also used existing literature to calculate a resilience score for 26 lemur species for which data existed on resilience traits. Our cyclone impact map was then overlaid on known geographic ranges of these species and compared to resilience score while controlling for phylogenetic non-independence and spatial autocorrelation. We found no association between cyclone impact in a lemur range and their resilience score. When assessing traits individually, however, we found that cyclone impact was positively associated with body size, suggesting that the more impacted a species is by cyclones the smaller they are. We also found cyclone impact to be negatively associated with frugivory, with species in higher impact zones eating more fruit. While unexpected, this could reflect an increased production in fruit in tree fall gaps following cyclones. While we did not find a pattern between cyclone impact and behavioural resilience in lemurs, we suggest a similar study at a global scale across all primates would allow for more taxonomic variation and reveal larger patterns key to understanding past and future vulnerability to natural disturbances in primates.

Using Inundation Extents to Predict Microbial Contamination in Private Wells after Flooding Events.

Disaster recovery poses unique challenges for residents reliant on private wells. Flooding events are drivers of microbial contamination in well water, but the relationship observed between flooding and contamination varies substantially. Here, we investigate the performance of different flood boundaries─the FEMA 100 year flood hazard boundary, height above nearest drainage-derived inundation extents, and satellite-derived extents from the Dartmouth Flood Observatory─in their ability to identify well water contamination following Hurricane Florence. Using these flood boundaries, we estimated about 2600 wells to 108,400 private wells may have been inundated─over 2 orders of magnitude difference based on boundary used. Using state-generated routine and post-Florence testing data, we observed that microbial contamination rates were 7.1-10.5 times higher within the three flood boundaries compared to routine conditions. However, the ability of the flood boundaries to identify contaminated samples varied spatially depending on the type of flooding (e.g., riverine, overbank, coastal). While participation in testing increased after Florence, rates were overall still low. With <1% of wells tested, there is a critical need for enhanced well water testing efforts. This work provides an understanding of the strengths and limitations of inundation mapping techniques, which are critical for guiding postdisaster well water response and recovery.

The effect of repeated hurricanes on the age of organic carbon in humid tropical forest soil.

Increasing hurricane frequency and intensity with climate change is likely to affect soil organic carbon (C) stocks in tropical forests. We examined the cycling of C between soil pools and with depth at the Luquillo Experimental Forest in Puerto Rico in soils over a 30-year period that spanned repeated hurricanes. We used a nonlinear matrix model of soil C pools and fluxes ("soilR") and constrained the parameters with soil and litter survey data. Soil chemistry and stable and radiocarbon isotopes were measured from three soil depths across a topographic gradient in 1988 and 2018. Our results suggest that pulses and subsequent reduction of inputs caused by severe hurricanes in 1989, 1998, and two in 2017 led to faster mean transit times of soil C in 0-10 cm and 35-60 cm depths relative to a modeled control soil with constant inputs over the 30-year period. Between 1988 and 2018, the occluded C stock increased and δ13C in all pools decreased, while changes in particulate and mineral-associated C were undetectable. The differences between 1988 and 2018 suggest that hurricane disturbance results in a dilution of the occluded light C pool with an influx of young, debris-deposited C, and possible microbial scavenging of old and young C in the particulate and mineral-associated pools. These effects led to a younger total soil C pool with faster mean transit times. Our results suggest that the increasing frequency of intense hurricanes will speed up rates of C cycling in tropical forests, making soil C more sensitive to future tropical forest stressors.

Memristor-based circuit design of episodic memory neural network and its application in hurricane category prediction.

Episodic memory, as a type of long-term memory (LTM), is used to learn and store the unique personal experience. Based on the episodic memory biological mechanism, this paper proposes a bionic episodic memory memristive neural network circuit. The proposed memristive neural network circuit includes a neocortical module, a parahippocampal module and a hippocampus module. The neocortical module with the two paths structure is used to receive the sensory signal, and is also used to separate and transmit the spatial information and the non-spatial information involved in the sensory signal. The parahippocampal module is composed of the parahippocampal cortex-MEA and the perirhinal cortex-LEA, which receives the two types of information from the neocortical module respectively. As the last module, the hippocampus module receives and integrates the output information of the parahippocampal module as well as generates the corresponding episodic memory. Meanwhile, the specific scenario information with the certain temporal signal from the generated episodic memory is also extracted by the hippocampus module. The simulation results in PSPICE show that the proposed memristive neural network circuit can generate the various episodic memories and extract the specific scenario information successfully. By configuring the memristor parameters, the proposed bionic episodic memory memristive neural network circuit can be applied to the hurricane category prediction, which verifies the feasibility of this work.

Hurricane season hindsight 2020: Applying the IDEA model toward local tropical cyclone forecasts.

Hurricane Laura began as a disorganized tropical depression in August 2020. Early forecast guidance showed that the tropical cyclone could either completely dissipate or strengthen to a major hurricane as it approached the United States Gulf Coast. While this uncertainty was known by meteorologists, it was not necessarily communicated to the public in a direct manner. As it turned out, the worst-case scenario was the correct one. The tropical depression rapidly intensified and made landfall near Cameron, Louisiana, with sustained winds of 150 mph, making Laura a Category 4 hurricane on the Saffir-Simpson scale. Laura's rapid intensification caught some people off guard. Ideally, weather forecasts would have begun warning Louisiana residents to prepare for the possibility of a devastating hurricane in the early stages of tropical cyclone development. No one is suggesting that meteorologists did anything wrong. However, with the benefit of hindsight and decades of scholarly research in risk communication, we can speculate how an ideal forecast would have been written. This paper demonstrates that there are some simple considerations that could be made that might better alert the public to future hurricane worst-case scenarios, even in uncertain situations.

Severe hurricanes increase recruitment and gene flow in the clonal sponge Aplysina cauliformis.

Upright branching sponges, such as Aplysina cauliformis, provide critical three-dimensional habitat for other organisms and assist in stabilizing coral reef substrata, but are highly susceptible to breakage during storms. Breakage can increase sponge fragmentation, contributing to population clonality and inbreeding. Conversely, storms could provide opportunities for new genotypes to enter populations via larval recruitment, resulting in greater genetic diversity in locations with frequent storms. The unprecedented occurrence of two Category 5 hurricanes in close succession during 2017 in the U.S. Virgin Islands (USVI) provided a unique opportunity to evaluate whether recolonization of newly available substrata on coral reefs was due to local (e.g. re-growth of remnants, fragmentation, larval recruitment) or remote (e.g. larval transport and immigration) sponge genotypes. We sampled A. cauliformis adults and juveniles from four reefs around St. Thomas and two in St. Croix (USVI). Using a 2bRAD protocol, all samples were genotyped for single-nucleotide polymorphisms (SNPs). Results showed that these major storm events favoured sponge larval recruitment but did not increase the genetic diversity of A. cauliformis populations. Recolonization of substratum post-storms via clonality was lower (15%) than expected and instead was mainly due to sexual reproduction (85%) via local larval recruitment. Storms did enhance gene flow among and within reef sites located south of St. Thomas and north of St. Croix. Therefore, populations of clonal marine species with low pelagic dispersion, such as A. cauliformis, may benefit from increased frequency and magnitude of hurricanes for the maintenance of genetic diversity and to combat inbreeding, enhancing the resilience of Caribbean sponge communities to extreme storm events.

Competition between ocean thermal structure and tropical cyclone characteristics modulates ocean environmental responses in the Yellow and Bohai Seas.

To study the environmental responses of tropical cyclones (TCs) in continental shelf regions, TCs passing over the Yellow Sea and Bohai Sea (YBS) during 2002-2020 were investigated, with a special focus on how competition between ocean thermal structure and TC characteristics modulates ocean surface changes. The spatial distributions of the climatic mixed layer depth (MLD), accumulated wind forcing power index (WPi), accumulated sea surface temperature (SST) changes and accumulated chlorophyll (Chl-a) changes in the YBS were calculated. The linear regressions indicate that both the TC-induced SST cooling and TC-induced Chl-a increase are correlated with the TC wind speed rather than the translation speed, especially when the TC forcing depth (Zmixing) is greater than the MLD. Otherwise, both the changes in SST and Chl-a are correlated with the TC translation speed when Zmixing is shallower than the MLD. Further study has shown that whether TCs can break the MLD is also a key condition for oceanic responses. In the southern YBS, which has a deep-sea basin and MLD, the TC wind speed is the major factor affecting SST cooling and Chl-a increase, as TCs need more strength to reach the MLD. However, in the northern YBS, which has the shallowest sea basin and MLD, even weak TCs can easily break the MLD and reach the seabed; thus, ocean surface changes are associated mainly with the TC translation speed. The composite results reveal that both the maximum SST cooling center (1.64 °C) and the maximum Chl-a increasing center (0.14 log10(mg/m3)) are located on the right and behind the TC center, respectively. In addition, TC-induced SST cooling and Chl-a increase were initiated two days prior to TC passage and then reached their maximum values after 1 day. It takes approximately 7-8 days for the Chl-a concentration to recover, but it takes a much longer time (>15 days) for the SST to recover.

Unravelling the role of tropical cyclones in shaping present species distributions.

Driven by climate change, tropical cyclones (TCs) are predicted to change in intensity and frequency through time. Given these forecasted changes, developing an understanding of how TCs impact insular wildlife is of heightened importance. Previous work has shown that extreme weather events may shape species distributions more strongly than climatic averages; however, given the coarse spatial and temporal scales at which TC data are often reported, the influence of TCs on species distributions has yet to be explored. Using TC data from the National Hurricane Center, we developed spatially and temporally explicit species distribution models (SDMs) to examine the role of TCs in shaping present-day distributions of Puerto Rico's 10 Anolis lizard species. We created six predictor variables to represent the intensity and frequency of TCs. For each occurrence of a species, we calculated these variables for TCs that came within 500 km of the center of Puerto Rico and occurred within the 1-year window prior to when that occurrence was recorded. We also included predictor variables related to landcover, climate, topography, canopy cover and geology. We used random forests to assess model performance and variable importance in models with and without TC variables. We found that the inclusion of TC variables improved model performance for the majority of Puerto Rico's 10 anole species. The magnitude of the improvement varied by species, with generalist species that occur throughout the island experiencing the greatest improvements in model performance. Range-restricted species experienced small, almost negligible, improvements but also had more predictive models both with and without the inclusion of TC variables compared to generalist species. Our findings suggest that incorporating data on TCs into SDMs may be important for modeling insular species that are prone to experiencing these types of extreme weather events.

Changes in Breastfeeding and Related Maternity Care Practices After Hurricanes Irma and Maria in Puerto Rico.

Background: Breastfeeding is recommended globally for most infants, especially during and after natural disasters when risk of adverse outcomes increases because of unsanitary conditions and lack of potable water. Materials and Methods: Using 2017-2019 data from Puerto Rico's Pregnancy Risk Assessment Monitoring System for 2,448 respondents with a recent live birth, we classified respondents into 4 hurricane exposure time periods based on infant birth month and year relative to when Hurricanes Irma and Maria occurred: (1) prehurricane; (2) acute hurricane; (3) posthurricane, early recovery; and (4) posthurricane, long-term recovery. We examined the association between maternity care practices during delivery hospitalization and exclusive breastfeeding at 3 months overall and stratified by time period. We also examined the associations between each maternity care practice and exclusive breastfeeding separately by time period. Results: Exclusive breastfeeding at 3 months was higher during the acute hurricane time period (adjusted prevalence ratio [aPR]: 1.43, 95% confidence interval: 1.09-1.87) than the prehurricane time period. Supportive maternity care practices were positively associated with exclusively breastfeeding, and practices that are risk factors for discontinuing breastfeeding were negatively associated with exclusive breastfeeding. Breastfeeding in the first hour (aPR range: 1.51-1.92) and rooming-in (aPR range: 1.50-2.58) were positively associated with exclusive breastfeeding across all time periods, except the prehurricane time period. Receipt of a gift pack with formula was negatively associated with exclusive breastfeeding (aPR range: 0.22-0.54) across all time periods. Conclusions: Maternity care practices during delivery hospitalization may influence breastfeeding behaviors and can improve breastfeeding during and after natural disasters. Strategies to maintain and improve these practices can be further supported during and after natural disasters.

Effects of typhoon events on coastal hydrology, nutrients, and algal bloom dynamics: Insights from continuous observation and machine learning in semi-enclosed Zhanjiang Bay, China.

Typhoons can induce variations in hydrodynamic conditions and biogeochemical processes, potentially escalating the risk of algal bloom occurrences impacting coastal ecosystems. However, the impacts of typhoons on instantaneous changes and the mechanisms behind typhoon-induced algal blooms remain poorly understood. This study utilized high-frequency in situ observation and machine learning model to track the dynamic variations in meteorological, hydrological, physicochemical, and Chlorophyll-a (Chl-a) levels through the complete Typhoon Talim landing in Zhanjiang Bay (ZJB) in July 2023. The results showed that a delayed onset of algal bloom occurring 10 days after typhoon's arrival. Subsequently, as temperatures reached a suitable range, with an ample supply of nutrients and water stability, Chl-a peaked at 121.49 µg L-1 in algal bloom period. Additionally, water temperature and air temperature decreased by 1.61 °C and 2.8 °C during the typhoon, respectively. In addition, wind speed and flow speed increased by 1.34 and 0.015 m s-1 h-1 to peak values, respectively. Moreover, the slow decline of 8.2 % in salinity suggested a substantial freshwater input, leading to an increase in nutrients. For instance, the mean DIN and DIP were 2.2 and 8.5 times higher than those of the pre-typhoon period, resulting in a decrease in DIN/DIP (closer to16) and the alleviation of P limitation. Furthermore, pH and dissolved oxygen (DO) were both low during the typhoon period and then peaked at 8.93 and 19.05 mg L-1 during the algal bloom period, respectively, but subsequently decreased, remaining lower than those of the pre-typhoon period. A preliminary learning machine model was established to predict Chl-a and exhibited good accuracy, with R2 of 0.73. This study revealed the mechanisms of eutrophication status formation and algal blooms occurrence in the coastal waters, providing insights into the effects of typhoon events on tropical coastal biogeochemistry and ecology.

The impact of tropical cyclones and water conservancy projects on island's flash floods.

The analysis of the influencing factors of flash floods, one of the most destructive natural disasters, is the basis of scientific disaster prevention and mitigation. There is little research considering the influence of tropical cyclones (TCs) and water conservancy projects on flash floods, which cannot be ignored in the island areas where flash floods often occur due to the complex influence of various factors. In this study, under the pressure-state-response framework (PSR framework), the factors affecting the distribution of flash floods on Hainan Island, China, from 1970 to 2010 were quantitatively analyzed by using the geographical detector method. By dividing the time period, give full play to the advantages of the PSR framework and show the evolution process of various factors. Different from inland areas, extreme precipitation and tropical cyclones play a major role in the spatial distribution of flash floods on Hainan Island, China, and the driving force of tropical cyclones is 1.1 times that of extreme precipitation on average. Medium-sized reservoirs play the greatest role in the prevention of flash floods on Hainan Island, and their driving forces reach 0.38 times of extreme precipitation on average, followed by large-sized reservoirs and small-sized reservoirs. Large-sized reservoirs are limited in quantity and have limited effectiveness in preventing flash floods on Hainan Island. Therefore, in the forecasting and risk management of flash flood in the island area, more attention should be paid to the impact of extreme precipitation and TCs, and the role of medium-sized reservoir should be fully exerted.

High resilience of Pacific Island forests to a category- 5 cyclone.

Assessing how forests respond to, and recuperate from, cyclones is critical to understanding forest dynamics and planning for the impacts of climate change. Projected increases in the intensity and frequency of severe cyclones can threaten both forests and forest-dependent communities. The Pacific Islands are subject to frequent low-intensity cyclones, but there is little information on the effects of high intensity cyclones, or on how forest stewardship practices may affect outcomes. We assess the resistance and resilience of forests in three community-stewarded sites on the island of Tanna, Vanuatu, to the wind-related effects of 2015 Category-5 Cyclone Pam, one of the most intense cyclones to make landfall globally. Drawing on transect data established pre-and post-cyclone, we (1) test whether windspeed and tree structural traits predict survival and damage intensity, and whether this varies across sites; (2) assess post-cyclone regeneration of canopy, ground cover, seedlings, and saplings, and how community composition shifts over time and across sites. In sites that sustained a direct hit, 88 % of trees were defoliated, 34 % sustained severe damage, and immediate mortality was 13 %. Initial mortality, but not severe damage, was lower in areas that received an indirect hit and had lower windspeed. Larger trees and those with lighter wood had a higher probability of uprooting and snapping, respectively. Canopy and ground cover regenerated within three years and seedling and sapling regeneration was widespread across life histories, from pioneer to mature forest species. Three species of non-native vines recruited post-cyclone but within 5 years had largely declined or disappeared with canopy closure. Tanna's historical cyclone frequency, combined with customary stewardship practices that actively maintain a diversity of species and multiplicity of regeneration pathways, are likely responsible for the island's resistance and resilience to an intense tropical cyclone.

Neighborhood-level economic characteristics and depression and PTSD symptoms among Houstonians who have experienced Hurricane Harvey and COVID-19.

Little is known about how neighborhood economic characteristics relate to risk of depression and Posttraumatic Stress Disorder (PTSD) in the context of multiple disasters. We sampled 88 super neighborhoods in Houston, Texas and surveyed 872 residents who were living in Houston during Hurricane Harvey and COVID-19 and lived in the same residence since Hurricane Harvey, about their demographics and symptoms of depression and PTSD. Using data from the American Community Survey, we estimated neighborhood-level unemployment, median income, and income inequality (i.e., Gini coefficient). We investigated whether these underlying neighborhood socioeconomic factors were associated with the mental health consequences of mass traumatic events. We examined associations between neighborhood-level constructs and individual-level depression and PTSD, using multilevel linear models. Partially adjusted multilevel models showed that lower neighborhood median income was associated with higher symptom scores of PTSD, while greater neighborhood income inequality was associated with higher symptom scores of depression and PTSD. However, fully adjusted models showed that these associations are better accounted for by event-specific stressors and traumas. These findings suggest that in the context of multiple large scale traumatic events, neighborhood socioeconomic context may structure individual-level exposure to stressful and traumatic events.