A global map of species at risk of extinction due to natural hazards.

An often-overlooked question of the biodiversity crisis is how natural hazards contribute to species extinction risk. To address this issue, we explored how four natural hazards, earthquakes, hurricanes, tsunamis, and volcanoes, overlapped with the distribution ranges of amphibians, birds, mammals, and reptiles that have either narrow distributions or populations with few mature individuals. To assess which species are at risk from these natural hazards, we combined the frequency and magnitude of each natural hazard to estimate their impact. We considered species at risk if they overlapped with regions where any of the four natural hazards historically occurred (n = 3,722). Those species with at least a quarter of their range subjected to a high relative impact were considered at high risk (n = 2,001) of extinction due to natural hazards. In total, 834 reptiles, 617 amphibians, 302 birds, and 248 mammals were at high risk and they were mainly distributed on islands and in the tropics. Hurricanes (n = 983) and earthquakes (n = 868) affected most species, while tsunamis (n = 272), and volcanoes (n = 171) affected considerably fewer. The region with the highest number of species at high risk was the Pacific Ring of Fire, especially due to volcanoes, earthquakes, and tsunamis, while hurricane-related high-risk species were concentrated in the Caribbean Sea, Gulf of Mexico, and northwestern Pacific Ocean. Our study provides important information regarding the species at risk due to natural hazards and can help guide conservation attention and efforts to safeguard their survival.

The growing inadequacy of an open-ended Saffir-Simpson hurricane wind scale in a warming world.

Global warming increases available sensible and latent heat energy, increasing the thermodynamic potential wind intensity of tropical cyclones (TCs). Supported by theory, observations, and modeling, this causes a shift in mean TC intensity, which tends to manifest most clearly at the greatest intensities. The Saffir-Simpson scale for categorizing damage based on the wind intensity of TCs was introduced in the early 1970s and remains the most commonly used metric for public communication of the level of wind hazard that a TC poses. Because the scale is open-ended and does not extend beyond category 5 (70 m/s windspeed or greater), the level of wind hazard conveyed by the scale remains constant regardless of how far the intensity extends beyond 70 m/s. This may be considered a weakness of the scale, particularly considering that the destructive potential of the wind increases exponentially. Here, we consider how this weakness becomes amplified in a warming world by elucidating the past and future increases of peak wind speeds in the most intense TCs. A simple extrapolation of the Saffir-Simpson scale is used to define a hypothetical category 6, and we describe the frequency of TCs, both past and projected under global warming, that would fall under this category. We find that a number of recent storms have already achieved this hypothetical category 6 intensity and based on multiple independent lines of evidence examining the highest simulated and potential peak wind speeds, more such storms are projected as the climate continues to warm.

Hurricane wind regimes for forests of North America.

Despite the ubiquity of tropical cyclones and their impacts on forests, little is known about how tropical cyclone regimes shape the ecology and evolution of tree species. We used a simple meteorological model (HURRECON) to estimate wind fields from hurricanes in the Western North Atlantic and Eastern North Pacific tropical cyclone basins from storms occurring between 1851 and 2022. We characterize how the intensity and frequency of hurricanes differ among geographically distinct hurricane regimes and define four hurricane regimes for North America (Continental, Inland, Coastal, and Fringe). Along this coastal-to-inland gradient, we found major differences in the frequency and intensity of hurricane wind regimes. The Fringe regime experiences category 1 winds relatively frequently [return period (RP) 25 y], whereas the Inland regime experiences category 1 winds very infrequently (RP ~3,000 y). We discuss how species traits related to tree windfirmness, such as mechanical properties and crown traits, may vary along hurricane regime gradients. Quantitative characterization of forest hurricane regimes provides a critical step for understanding the evolutionary and ecological role of hurricane regimes in wind-prone forests.

Pelagic seabirds reduce risk by flying into the eye of the storm.

Cyclones can cause mass mortality of seabirds, sometimes wrecking thousands of individuals. The few studies to track pelagic seabirds during cyclones show they tend to circumnavigate the strongest winds. We tracked adult shearwaters in the Sea of Japan over 11 y and found that the response to cyclones varied according to the wind speed and direction. In strong winds, birds that were sandwiched between the storm and mainland Japan flew away from land and toward the eye of the storm, flying within ≤30 km of the eye and tracking it for up to 8 h. This exposed shearwaters to some of the highest wind speeds near the eye wall (≤21 m s-1) but enabled them to avoid strong onshore winds in the storm's wake. Extreme winds may therefore become a threat when an inability to compensate for drift could lead to forced landings and collisions. Birds may need to know where land is in order to avoid it. This provides additional selective pressure for a map sense and could explain why juvenile shearwaters, which lack a map sense, instead navigating using a compass heading, are susceptible to being wrecked. We suggest that the ability to respond to storms is influenced by both flight and navigational capacities. This may become increasingly pertinent due to changes in extreme weather patterns.

Tropical cyclone winds and precipitation stimulate cone production in the masting species longleaf pine (Pinus palustris).

Many trees exhibit masting - where reproduction is temporally variable and synchronous over large areas. Several dominant masting species occur in tropical cyclone (TC)-prone regions, but it is unknown whether TCs correlate with mast seeding. We analyzed long-term data (1958-2022) to test the hypothesis that TCs influence cone production in longleaf pine (Pinus palustris). We integrate field observations, weather data, satellite imagery, and hurricane models to test whether TCs influence cone production via: increased precipitation; canopy density reduction; and/or mechanical stress from wind. Cone production was 31% higher 1 yr after hurricanes and 71% higher after 2 yr, before returning to baseline levels. Cyclone-associated precipitation was correlated with increased cone production in wet years and cone production increased after low-intensity winds (≤ 25 m s-1 ) but not with high-intensity winds (> 25 m s-1 ). Tropical cyclones may stimulate cone production via precipitation addition, but high-intensity winds may offset any gains. Our study is the first to support the direct influence of TCs on reproduction, suggesting a previously unknown environmental correlate of masting, which may occur in hurricane-prone forests world-wide.

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.

Damage to tropical forests caused by cyclones is driven by wind speed but mediated by topographical exposure and tree characteristics.

Each year, an average of 45 tropical cyclones affect coastal areas and potentially impact forests. The proportion of the most intense cyclones has increased over the past four decades and is predicted to continue to do so. Yet, it remains uncertain how topographical exposure and tree characteristics can mediate the damage caused by increasing wind speed. Here, we compiled empirical data on the damage caused by 11 cyclones occurring over the past 40 years, from 74 forest plots representing tropical regions worldwide, encompassing field data for 22,176 trees and 815 species. We reconstructed the wind structure of those tropical cyclones to estimate the maximum sustained wind speed (MSW) and wind direction at the studied plots. Then, we used a causal inference framework combined with Bayesian generalised linear mixed models to understand and quantify the causal effects of MSW, topographical exposure to wind (EXP), tree size (DBH) and species wood density (ρ) on the proportion of damaged trees at the community level, and on the probability of snapping or uprooting at the tree level. The probability of snapping or uprooting at the tree level and, hence, the proportion of damaged trees at the community level, increased with increasing MSW, and with increasing EXP accentuating the damaging effects of cyclones, in particular at higher wind speeds. Higher ρ decreased the probability of snapping and to a lesser extent of uprooting. Larger trees tended to have lower probabilities of snapping but increased probabilities of uprooting. Importantly, the effect of ρ decreasing the probabilities of snapping was more marked for smaller than larger trees and was further accentuated at higher MSW. Our work emphasises how local topography, tree size and species wood density together mediate cyclone damage to tropical forests, facilitating better predictions of the impacts of such disturbances in an increasingly windier world.

Coming to the Caribbean: Eighty-five years of rhesus macaques (Macaca mulatta) at Cayo Santiago-A rare nonhuman primate model for the studies of adaptation, diseases, genetics, natural disasters, and resilience.

The Cayo Santiago rhesus macaque colony represents one of the most important nonhuman primate resources since their introduction to the Caribbean area in 1938. The 85 years of continuing existence along with the comprehensive database of the rhesus colony and the derived skeletal collections have provided and will continue to provide a powerful tool to test hypotheses about adaptive and evolutionary mechanisms in both biology and medicine.

Arthropods are not declining but are responsive to disturbance in the Luquillo Experimental Forest, Puerto Rico.

A number of recent studies have documented long-term declines in abundances of important arthropod groups, primarily in Europe and North America. These declines are generally attributed to habitat loss, but a recent study [B.C. Lister, A. Garcia, Proc. Natl. Acad. Sci. USA 115, E10397-E10406 (2018)] from the Luquillo Experimental Forest (LEF) in Puerto Rico attributed declines to global warming. We analyze arthropod data from the LEF to evaluate long-term trends within the context of hurricane-induced disturbance, secondary succession, and temporal variation in temperature. Our analyses demonstrate that responses to hurricane-induced disturbance and ensuing succession were the primary factors that affected total canopy arthropod abundances on host trees, as well as walkingstick abundance on understory shrubs. Ambient and understory temperatures played secondary roles for particular arthropod species, but populations were just as likely to increase as they were to decrease in abundance with increasing temperature. The LEF is a hurricane-mediated system, with major hurricanes effecting changes in temperature that are larger than those induced thus far by global climate change. To persist, arthropods in the LEF must contend with the considerable variation in abiotic conditions associated with repeated, large-scale, and increasingly frequent pulse disturbances. Consequently, they are likely to be well-adapted to the effects of climate change, at least over the short term. Total abundance of canopy arthropods after Hurricane Maria has risen to levels comparable to the peak after Hurricane Hugo. Although the abundances of some taxa have declined over the 29-y period, others have increased, reflecting species turnover in response to disturbance and secondary succession.

Hurricane annual cycle controlled by both seeds and genesis probability.

Understanding tropical cyclone (TC) climatology is a problem of profound societal significance and deep scientific interest. The annual cycle is the biggest radiatively forced signal in TC variability, presenting a key test of our understanding and modeling of TC activity. TCs over the North Atlantic (NA) basin, which are usually called hurricanes, have a sharp peak in the annual cycle, with more than half concentrated in only 3 mo (August to October), yet existing theories of TC genesis often predict a much smoother cycle. Here we apply a framework originally developed to study TC response to climate change in which TC genesis is determined by both the number of pre-TC synoptic disturbances (TC "seeds") and the probability of TC genesis from the seeds. The combination of seeds and probability predicts a more consistent hurricane annual cycle, reproducing the compact season, as well as the abrupt increase from July to August in the NA across observations and climate models. The seeds-probability TC genesis framework also successfully captures TC annual cycles in different basins. The concise representation of the climate sensitivity of TCs from the annual cycle to climate change indicates that the framework captures the essential elements of the TC climate connection.

Evacuate or social distance? Modeling the influence of threat perceptions on hurricane evacuation in a dual-threat environment.

This study investigates how different risk predictors influenced households' evacuation decisions during a dual-threat event (Hurricane Laura and COVID-19 pandemic). The Protective Action Decision Model (PADM) literature indicates that perceived threat variables are the most influential variables that drive evacuation decisions. This study applies the PADM to investigate a dual-threat disaster that has conflicting protective action recommendations. Given the novelty, scale, span, impact, and messaging around COVID-19, it is crucial to see how hurricanes along the Gulf Coast-a hazard addressed seasonally by residents with mostly consistent protective action messaging-produce different reactions in residents in this pandemic context. Household survey data were collected during early 2021 using a disproportionate stratified sampling procedure to include households located in mandatory and voluntary evacuation areas across the coastal counties in Texas and parishes in Louisiana that were affected by Hurricane Laura. Structural equation modeling was used to identify the relationships between perceived threats and evacuation decisions. The findings suggest affective risk perceptions strongly affected cognitive risk perceptions (CRPs). Notably, hurricane and COVID-19 CRPs are significant predictors of hurricane evacuation decisions in different ways. Hurricane CRPs encourage evacuation, but COVID-19 CRPs hinder evacuation decisions.

A data-driven method for identifying the locations of hurricane evacuations from mobile phone location data.

How evacuations are managed can substantially impact the risks faced by affected communities. Having a better understanding of the mobility patterns of evacuees can improve the planning and management of these evacuations. Although mobility patterns during evacuations have traditionally been studied through surveys, mobile phone location data can be used to capture these movements for a greater number of evacuees over a larger geographic area. Several approaches have been used to identify hurricane evacuation patterns from location data; however, each approach relies on researcher judgment to first determine the areas from which evacuations occurred and then identify evacuations by determining when an individual spends a specified number of nights away from home. This approach runs the risk of detecting non-evacuation behaviors (e.g., work trips, vacations, etc.) and incorrectly labeling them as evacuations where none occurred. In this article, we developed a data-driven method to determine which areas experienced evacuations. With this approach, we inferred home locations of mobile phone users, calculated their departure times, and determined if an evacuation may have occurred by comparing the number of departures around the time of the hurricane against historical trends. As a case study, we applied this method to location data from Hurricanes Matthew and Irma to identify areas that experienced evacuations and illustrate how this method can be used to detect changes in departure behavior leading up to and following a hurricane. We validated and examined the inferred homes for representativeness and validated observed evacuation trends against past studies.

Drivers of natural disaster risk-reduction actions and their temporal dynamics: Insights from surveys during an imminent hurricane threat and its aftermath.

To improve preparedness for natural disasters, it is imperative to understand the factors that enable individual risk-reduction actions. This study offers such insights using innovative real-time (N = 871) and repeated (N = 255) surveys of a sample of coastal residents in Florida regarding flood preparations and their drivers during an imminent threat posed by Hurricane Dorian and its aftermath. Compared with commonly employed cross-sectional surveys, our methodology better represents relationships between preparedness actions undertaken during the disaster threat and their drivers derived from an extended version of Protection Motivation Theory (PMT). The repeated survey allows for examining temporal dynamics in these drivers. Our results confirm the importance of coping appraisals and show that risk perceptions relate more strongly to emergency protection decisions made during the period of the disaster threat than to decisions made well before. Moreover, we find that several personal characteristics that we add to the standard PMT framework significantly relate to undertaking preparedness actions, especially locus of control and social norms. Significant changes in key explanatory variables occur following the disaster threat, including a decline in risk perception, a potential learning effect in coping appraisals, and a decline in risk aversion. Our results confirm the advantage of the real-time and repeated survey approach in understanding both short- and long-term disaster preparedness actions.

Emergency communication networks on Twitter during Hurricane Irma: information flow, influential actors, and top messages.

This study combined network analysis with message-level content analysis to investigate patterns of information flow and to examine messages widely distributed on social media during Hurricane Irma of 2017. The results show that while organisational users and media professionals dominated the top 100 information sources, individual citizens played a critical role in information dissemination. Public agencies should increase their retweeting activities and share the information posted by other trustworthy sources; doing so will contribute to the timely exchange of vital information during a disaster. This study also identified the active involvement of nonprofit organisations as information brokers during the post-event stage, indicating the potential for emergency management organisations to integrate their communication efforts into those of nonprofit entities. These findings will inform emergency management practices regarding implementation of communication plans and policies, facilitate the embracement of new partner organisations, and help with establishing and sustaining effective communication ties with a wide range of stakeholders.

Mental models for inclusive, socially-just disaster planning: a multi-community study in Saint Martin after Hurricane Irma.

Local perspectives provide different insights into disaster planning and response as compared to those of experts. Eliciting them, however, can be challenging, particularly for marginalised groups whose viewpoints have historically been excluded from planning processes. Fuzzy cognitive mapping (FCM) provides a semi-quantitative approach to representing the collective understanding or 'mental models' of diverse individuals and communities. This study involved 23 FCM interviews across three neighbourhoods of Saint Martin to comprehend: (i) how individuals' mental models of Hurricane Irma (2017) differ based on their context; (ii) how aligned mental models are with policy and planning documents; and (iii) the implications for the inclusiveness and representativeness of disaster response policies. It found that the residents of different neighbourhoods provided unique insights into the factors driving the social-ecological system, and that official policies aligned closely with priorities. The paper argues that the inclusion of the perspectives of different groups in disaster recovery is essential for an equitable process.

The impact of cultural stress on family functioning among Puerto Rican displaced families and the effect on mental health.

Hurricane María caused significant devastation on the island of Puerto Rico, impacting thousands of lives. Puerto Rican crisis migrant families faced stress related to displacement and relocation (cultural stress), often exhibited mental health symptoms, and experienced distress at the family level. Although cultural stress has been examined as an individual experience, little work has focused on the experience as a family. To address this gap, we conducted a mixed-methods study designed to examine the predictive effects of cultural stress on family conflict and its mental health implications among Puerto Rican Hurricane María parent and child dyads living on the U.S. mainland. In the quantitative phase of the study, 110 parent-child dyads completed an online survey assessing cultural stress, family dynamics, and mental health. As part of our primary analysis, we estimated a structural equation path model. Findings from the quantitative phase showed a significant positive relationship between family cultural stress and family conflict, as well as individual parent and child mental health symptoms. In the qualitative phase of the study, 35 parent-child dyads participated in individual interviews. Findings from the interviews revealed variations in difficulties related to language, discrimination, and financial burdens, with some participants adapting more quickly and experiencing fewer stressors. Findings also highlight the impact on mental health for both parents and youth, emphasizing the family-level nature of cultural stress, while noting a potential discrepancy between qualitative and quantitative findings in the discussion of family conflict.

The interplay of drought and hurricanes on tree recovery: insights from dynamic and weak functional responses.

Identifying the functional traits that enable recovery after extreme events is necessary for assessing forest persistence and functioning. However, the variability of traits mediating responses to disturbances presents a significant limitation, as these relationships may be contingent on the type of disturbance and change over time. This study investigates the effects of traits on tree growth-for short and longer terms-in response to two vastly different extreme climatic events (droughts and hurricanes) in a Puerto Rican forest. I found that trees display a dynamic functional response to extreme climatic events. Leaf traits associated with efficient photosynthesis mediated faster tree growth after hurricanes, while trees with low wood density and high water use efficiency displayed faster growth after drought. In the longer term, over both drought and hurricanes, tree size was the only significant predictor of growth, with faster growth for smaller trees. However, despite finding significant trait-growth relationships, the predictive power of traits was overall low. As the frequency of extreme events increases due to climate change, understanding the dynamic relationships between traits and tree growth is necessary for identifying strategies for recovery.

Floating Debris in the Northern Gulf of Mexico after Hurricane Katrina.

Hurricane Katrina (category 5 with maximum wind of 280 km/h when the eye is in the central Gulf of Mexico) made landfall near New Orleans on August 29, 2005, causing millions of cubic meters of disaster debris, severe flooding, and US$125 billion in damage. Yet, despite numerous reports on its environmental and economic impacts, little is known about how much debris has entered the marine environment. Here, using satellite images (MODIS, MERIS, and Landsat), airborne photographs, and imaging spectroscopy, we show the distribution, possible types, and amount of Katrina-induced debris in the northern Gulf of Mexico. Satellite images collected between August 30 and September 19 show elongated image features around the Mississippi River Delta in a region bounded by 92.5°W-87.5°W and 27.8°N-30.25°N. Image spectroscopy and color appearance of these image features indicate that they are likely dominated by driftwood (including construction lumber) and dead plants (e.g., uprooted marsh) and possibly mixed with plastics and other materials. The image sequence shows that if aggregated together to completely cover the water surface, the maximal debris area reached 21.7 km2 on August 31 to the east of the delta, which drifted to the west following the ocean currents. When measured by area in satellite images, this perhaps represents a historical record of all previously reported floating debris due to natural disasters such as hurricanes, floodings, and tsunamis.

Determinants of exposure to endocrine disruptors following hurricane Harvey.

Hurricane Harvey was a category four storm that induced catastrophic flooding in the Houston metropolitan area. Following the hurricane there was increased concern regarding chemical exposures due to damage caused by flood waters and emergency excess emissions from industrial facilities. This study utilized personal passive samplers in the form of silicone wristbands in Houston, TX to both assess chemical exposure to endocrine disrupting chemicals (EDCs) immediately after the hurricane and determine participant characteristics associated with higher concentrations of exposure. Participants from the Houston-3H cohort (n = 172) wore a wristband for seven days and completed a questionnaire to determine various flood-related and demographic variables. Bivariate and multivariate analysis indicated that living in an area with a high Area Deprivation Index (ADI) (indicative of low socioeconomic status), identifying as Black/African American or Latino, and living in the Houston neighborhoods of Baytown and East Houston were associated with increased exposure to EDCs. These results provide evidence of racial/ethnic and socioeconomic injustices in exposure to EDCs in the Houston Metropolitan Area. Since the multiple regression models conducted did not fully explain exposure (0.047 < R2 < 0.34), more research is needed on the direct sources of EDCs within this area to create effective exposure mitigation strategies.

Hurricanes Irma and Maria and Diabetes incidence in Puerto Rico.

OBJECTIVE: To evaluate the impact of Hurricanes Irma/Maria on diabetes incidence in Puerto Rico. Mortality increased substantially after the hurricanes, but morbidity was not assessed. METHODS: We recruited 364 participants from the San Juan Overweight Adults Longitudinal Study (SOALS) aged 40-65 years who completed a three-year follow-up and were free of diabetes. We conducted additional questionnaires 1.7-2.5 years after hurricanes. Glycosylated hemoglobin (HbA1c), fasting glucose and insulin were assessed at all three visits. We compared diabetes incidence between pre-hurricane visits and between visits spanning the hurricanes using Generalized Estimating Equation (GEE) adjusting for within person repeated measures, age, and body mass index (BMI). RESULTS: Diabetes incidence was significantly higher spanning the hurricanes than pre-hurricane (multivariate GEE model: IRR = 2.1; 95% CI: 1.4-3.1). There was a significantly higher increase spanning the hurricanes compared to pre-hurricanes for Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) (median: 0.3 uIU/mL vs. 0.2 uIU/mL). HbA1c levels increased by 0.4% spanning the hurricanes. CONCLUSION: Increases in diabetes incidence, HOMA-IR and HbA1c were higher spanning the hurricanes compared to the pre-hurricanes period. The increase in diabetes incidence remains significant after adjusting for age and BMI.