Search Results (78)

Mangroves form the dominant coastal plant community of low-energy tropical intertidal habitats and provide critical ecosystem services to humans and the environment. However, more frequent and increasingly powerful hurricanes and storm surges are creating additional pressure on the natural resilience of these threatened coastal ecosystems. Advances in remote sensing techniques and approaches are critical to providing robust quantitative monitoring of post-storm mangrove forest recovery to better prioritize the often-limited resources available for the restoration of these storm-damaged habitats. Here, we build on previously utilized spatial and temporal ranges of European Space Agency (ESA) Sentinel satellite imagery to monitor and map the recovery of the mangrove forests of the British Virgin Islands (BVI) since the occurrence of back-to-back category 5 hurricanes, Irma and Maria, on September 6 and 19 of 2017, respectively. Pre- to post-storm changes in coastal mangrove forest health were assessed annually using the normalized difference vegetation index (NDVI) and moisture stress index (MSI) from 2016 to 2023 using Google Earth Engine. Results reveal a steady trajectory towards forest health recovery on many of the Territory’s islands since the storms’ impacts in 2017. However, some mangrove patches are slower to recover, such as those on the islands of Virgin Gorda and Jost Van Dyke, and, in some cases, have shown a continued decline (e.g., Prickly Pear Island). Our work also uses a linear ANCOVA model to assess a variety of geospatial, environmental, and anthropogenic drivers for mangrove recovery as a function of NDVI pre-storm and post-storm conditions. The model suggests that roughly 58% of the variability in the 7-year difference (2016 to 2023) in NDVI may be related by a positive linear relationship with the variable of population within 0.5 km and a negative linear relationship with the variables of northwest aspect vs. southwest aspect, island size, temperature, and slope. Full article

Research on hurricane impacts in Florida’s coastal regions has been extensive, yet there remains a gap in comparing the effects and potential damage of different hurricanes within the same geographical area. Additionally, there is a need for reliable discussions on how variations in storm surges during these events influence evacuation accessibility to hurricane shelters. This is especially significant for rural areas with a vast number of aging populations, whose evacuation may require extra attention due to their special needs (i.e., access and functional needs). Therefore, this study aims to address this gap by conducting a comparative assessment of storm surge impacts on the evacuation accessibility of southwest Florida communities (e.g., Lee and Collier Counties) affected by two significant hurricanes: Irma in 2017 and Ian in 2022. Utilizing the floating catchment area method and examining Replica’s OD Matrix data with Geographical Information Systems (GISs)-based technical tools, this research seeks to provide insights into the effectiveness of evacuation plans and identify areas that need enhancements for special needs sheltering. By highlighting the differential impacts of storm surges on evacuation accessibility between these two hurricanes, this assessment contributes to refining disaster risk reduction strategies and has the potential to inform decision-making processes for mitigating the impacts of future coastal hazards. Full article

Coastal mangrove forests provide numerous ecosystem services, which can be disrupted by natural disturbances, mainly hurricanes. Canopy height (CH) is a key parameter for estimating carbon storage. Airborne Light Detection and Ranging (LiDAR) is widely viewed as the most accurate method for estimating CH but data are often limited in spatial coverage and are not readily available for rapid impact assessment after hurricane events. Hence, we evaluated the use of systematically acquired space-based Synthetic Aperture Radar (SAR) and optical observations with airborne LiDAR to predict CH across expansive mangrove areas in South Florida that were severely impacted by Category 3 Hurricane Irma in 2017. We used pre- and post-Irma LiDAR-derived canopy height models (CHMs) to train Random Forest regression models that used features of Sentinel-1 SAR time series, Landsat-8 optical, and classified mangrove maps. We evaluated (1) spatial transfer learning to predict regional CH for both time periods and (2) temporal transfer learning coupled with species-specific error correction models to predict post-Irma CH using models trained by pre-Irma data. Model performance of SAR and optical data differed with time period and across height classes. For spatial transfer, SAR data models achieved higher accuracy than optical models for post-Irma, while the opposite was the case for the pre-Irma period. For temporal transfer, SAR models were more accurate for tall trees (>10 m) but optical models were more accurate for short trees. By fusing data of both sensors, spatial and temporal transfer learning achieved the root mean square errors (RMSEs) of 1.9 m and 1.7 m, respectively, for absolute CH. Predicted CH losses were comparable with LiDAR-derived reference values across height and species classes. Spatial and temporal transfer learning techniques applied to readily available spaceborne satellite data can enable conservation managers to assess the impacts of disturbances on regional coastal ecosystems efficiently and within a practical timeframe after a disturbance event. Full article

Since 2017, Puerto Rico has faced environmental, economic, and political crises, leading to the emigration of healthcare workers and weakening the healthcare system. These challenges have affected cancer treatment continuity, exacerbating healthcare access challenges island-wide. In this study, we estimate the effect of the residence region on cancer treatment disruption following Hurricanes Irma and María (2017). Telephone surveys were conducted with 241 breast and colorectal cancer patients aged 40 and older who were diagnosed within six months before the hurricanes and were receiving treatment at the time of the hurricanes. Treatment disruption was defined as any pause in surgery, chemotherapy, radiotherapy, or oral treatment due to the hurricanes. Prevalence ratios (PRs) of treatment disruption by residence region were estimated using the San Juan Metropolitan Area (SJMA) as the reference. Fifty-nine percent of respondents reported treatment disruption; among them, half experienced disruptions lasting more than 30 days, with 14% of these enduring disruptions longer than 90 days. Adjusted models showed a 48% higher prevalence of disruption outside the SJMA (PR = 1.48, 95% CI: 1.06–2.07). Specific geographic regions (Arecibo, Bayamón, Caguas, and Mayagüez) exhibited higher disruption prevalence. These findings emphasize the need for disaster preparedness strategies that ensure equitable healthcare access for all cancer patients following environmental calamities. Full article

Background: Mental health in Puerto Rico is a complex and multifaceted issue that has been shaped by the island’s unique history, culture, and political status. Recent challenges, including disasters, economic hardships, and political turmoil, have significantly affected the mental well-being of the population, coupled with the limitations in the accessibility of mental health services. Thus, Puerto Rico has fewer mental health professionals per capita than any other state or territory in the United States. Objective: This comprehensive review examines the impact of disasters on mental health and mental health services in Puerto Rico. Given the exodus of Puerto Ricans from the island, this review also provides an overview of mental health resources available on the island, as well as in the continental United States. This review identifies efforts to address mental health issues, with the intent of gaining a proper understanding of the available mental health services, key trends, as well as observable challenges and achievements within the mental health landscape of the Puerto Rican population. Design: A comprehensive search using the PRIMO database of the University of Central Florida (UCF) library database was conducted, focusing on key terms related to disasters and mental healthcare and services in Puerto Rico. The inclusion criteria encompassed studies on Puerto Rican individuals, both those who remained on the island and those who migrated post-disaster, addressing the mental health outcomes and services for adults and children. We included peer-reviewed articles published from 2005 onwards in English and/or Spanish, examining the impact of disasters on mental health, accessibility of services, and/or trauma-related consequences. Results: In this scoping review, we identified 39 studies addressing the mental health profile of Puerto Ricans, identifying significant gaps in service availability and accessibility and the impact of environmental disasters on mental health. The findings indicate a severe shortage of mental health services in Puerto Rico, exacerbated by disasters such as Hurricanes Irma and Maria, the earthquakes of late 2019 and early 2020 that followed, and the COVID-19 pandemic, resulting in substantial delays in accessing care, and limited insurance coverage, particularly in rural regions. Despite these challenges, efforts to improve mental health services have included substantial federal funding and community initiative aimed at enhancing care availability and infrastructure. Limitations include the use of a single database, language restrictions, and potential variability in data extraction and synthesis. Conclusions: This scoping review highlights the significant impact of disasters on mental health in Puerto Rico and the challenges in accessing mental health services exacerbated by disasters. Despite efforts, significant gaps in mental healthcare and services persist, emphasizing the need for more rigorous research and improvements in infrastructure and workforce to enhance mental health outcomes for Puerto Ricans both on the island and in the continental United States. Full article

Utilization of remote sensing-derived meteorological data is a valuable alternative for tropical insular territories such as Puerto Rico (PR). The study of ecosystem resilience in insular territories is an underdeveloped area of investigation. Little research has focused on studying how an ecosystem in PR responds to and recovers from unique meteorological events (e.g., hurricanes). This work aims to investigate how an ecosystem in Western Puerto Rico responds to extreme climate events and fluctuations, with a specific focus on evaluating its innate resilience. The Antillean islands in the Caribbean and Atlantic are vulnerable to intense weather phenomena, such as hurricanes. Due to the distinct tropical conditions inherent to this region, and the ongoing urban development of coastal areas, their ecosystems are constantly affected. Key indicators, including gross primary production (GPP), normalized difference vegetation index (NDVI), actual evapotranspiration (ET), and land surface temperature (LST), are examined to comprehend the interplay between these factors within the context of the Culebrinas River Watershed (CRW) ecosystem over the past decade during the peak of hurricane season. Data processing and analyses were performed on datasets provided by Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 8–9 OLI TRIS, supplemented by information sourced from Puerto Rico Water and Energy Balance (PRWEB)—a dataset derived from Geostationary Operational Environmental Satellite (GOES) data. The findings revealed a complex interrelationship among atmospheric events and anthropogenic activities within the CRW, a region prone to recurrent atmospheric disruptions. NDVI and ET values from 2015 to 2019 showed the ecosystem’s capacity to recover after a prolonged drought period (2015) and Hurricanes Irma and Maria (2017). In 2015, the NDVI average was 0.79; after Hurricanes Irma and Maria in 2017, the NDVI dropped to 0.6, while in 2019, it had already increased to 0.8. Similarly, average ET values went from 3.2339 kg/m²/day in 2017 to 2.6513 kg/m²/day in 2018. Meanwhile, by 2019, the average ET was estimated to be 3.8105 kg/m²/day. Data geoprocessing of LST, NDVI, GPP, and ET, coupled with correlation analyses, revealed positive correlations among ET, NDVI, and GPP. Our results showed that areas with little anthropogenic impact displayed a more rapid and resilient restoration of the ecosystem. The spatial distribution of vegetation and impervious surfaces further highlights that areas closer to mountains have shown higher resilience while urban coastal areas have faced greater challenges in recovering from atmospheric events, thus showing the importance of preserving native vegetation, particularly mangroves, for long-term ecosystem stability. This study contributes to a deeper understanding of the dynamic interactions within urban coastal ecosystems in insular territories, emphasizing their resilience in the context of both natural atmospheric events and human activity. The insights gained from this research offer valuable guidance for managing and safeguarding ecosystems in similar regions characterized by their susceptibility to extreme weather phenomena. Full article

An increasing sea surface temperature as a result of climate change has led to a higher frequency and strengthening of hurricanes across the northeastern Caribbean in recent decades, with increasing risks of impacts to endangered corals and to the sustainability of coral reefs. Category five Hurricanes Irma and María during 2017 caused unprecedented damage to coral reef ecosystems across northeastern Puerto Rico, including mechanical destruction, localized sediment bedload (horizontal sediment transport and abrasion), and burial by hurricane-generated rubble fields. Hurricanes inflicted significant site-, depth-, and life history trait-specific impacts to endangered corals, with substantial and widespread mechanical damage to branching species, moderate mechanical damage to foliose species, and moderate to high localized damage to small-sized encrusting and massive morphotypes due to sediment bedload and burial by rubble. There was a mean 35% decline in Acropora palmata live cover, 79% in A. cervicornis, 12% in Orbicella annularis, 7% in O. faveolata, 12% in O. franksi, and 96% in Dendrogyra cylindrus. Hurricane disturbances resulted in a major regime shift favoring dominance by macroalgae, algal turf, and cyanobacteria. Recovery from coral recruitment or fragment reattachment in A. palmata was significantly higher on more distant coral reefs, but there was none for massive endangered species. Stronger hurricanes under projected climate change may represent a major threat to the conservation of endangered coral species and reef sustainability which will require enhancing coral propagation and restoration strategies, and the integration of adaptive, ecosystem-based management approaches. Recommendations are discussed to enhance redundancy, rapid restoration responses, and conservation-oriented strategies. Full article

Puerto Rico (PR) has faced environmental and public health challenges that could have significantly affected cancer screening access. Using administrative claims data from PR’s Medicaid population, this study assessed trends in colorectal and breast cancer screening from 2016 to 2021, the impact of disasters in screening, and the absolute deficit in screening due to the pandemic. The monthly rates of claims were analyzed using Poisson regression. Significant reductions in breast and colorectal cancer screening utilization were observed. The colorectal cancer screening rate in 2017 was 77% lower a month after Hurricanes Irma and María [RR_adj: 0.23; 95% CI: 0.20, 0.25] compared to the same time period in 2016. Breast cancer screening dropped 50% in November 2017 compared to November 2016 [RR_adj: 0.50; 95% CI: 0.47, 0.54]. Prospectively, a recovery in utilization has been observed only for breast cancer screening. The results revealed that cancer screening utilization substantially declined after environmental disasters and the pandemic. These findings have potentially severe long-term implications for cancer health disparities and mortality in PR. Full article

Irma was a major hurricane that developed during the 2017 season. It was a category 5 on the Saffir–Simpson Hurricane wind scale. This hurricane caused severe damage in the Caribbean area and the Florida Keys. The social, economic, and environmental impacts, mainly related to coastal flooding, were also significant in Cuba. The maximum limits of coastal flooding caused by this hurricane were determined in this research. Field trips and the use of the GPS supported our work, which focused on both the northern and southern coasts of the Ciego de Ávila province. This work has been critical for improving coastal flooding scenarios related to a strong hurricane, as it has been the first experience according to hurricane data since 1851. Results showed that the Punta Alegre and Júcaro towns were the most affected coastal towns. The locals had never seen similar flooding in these places before. The differences between flood areas associated with Hurricane Irma and previous modeled hazard scenarios were evident (the flooded areas associated with Hurricane Irma were smaller than those modeled for categories 1, 3, and 5 hurricanes). The effects of this hurricane on the most vulnerable coastal settlements, including the impacts on the archeological site “Los Buchillones”, were also assessed. Full article

Hans Magnus Enzensberger, who called tourism an industry “whose production is identical to its advertisement”, also wrote about the pitfalls of what he called the “tourism of the revolution” that flourished between the world wars in Soviet Russia. This essay combines both perspectives in a discussion of the experience of making a film about ecology in Cuba in 2019, Cuba: Living Between Hurricanes, which includes a section on the tourist industry. Informed by the perspectives of autoethnography and phenomenology, the author explores the cognitive dissonance of the filmmaker’s ambiguous relationship, as a professional tourist, to the contradictions of the tourist industry as refracted through the small coastal town of Caibarién on the north coast where Hurricane Irma made landfall in 2017. Full article

This article presents a summary of the results obtained as part of the ANR (French National Research Agency)-RELEV project, which focuses on the long-term recovery and reconstruction of the island of Saint Martin following the passage of Hurricane Irma in 2017. This hurricane was classified as category five on the Saffir-Simpson scale, with an average wind speed of 287 km/h. It caused catastrophic damage along its path and highlighted the significant vulnerability of Caribbean societies to this type of phenomenon. This article focuses on the reconstruction of residential buildings on the French part of the island of Saint Martin. It aims to identify and analyze the factors that have favorably or unfavorably influenced their reconstruction and their structural vulnerability reduction. The research is based mainly on a series of interviews with local actors (construction and insurance companies, architects, territorial services, etc.), an online survey of residents (180 responses), and a field survey involving visits to 104 buildings with interviews of the occupants. The results obtained show that having access to financial resources for the reconstruction of buildings is central. However, different parameters must be considered to understand the disparity of situations and identify the factors that have most favorably contributed to the speed and quality of reconstruction and reduction of vulnerability. Even five years after Irma, a significant number of buildings on the island remain either unrepaired or abandoned. These buildings nevertheless constitute a danger in the case of strong winds (becoming a source of projectiles) and have a negative impact on the reputation and attractiveness of the island. The results reveal that in general, buildings in Saint Martin are slightly more resilient than they were prior to Irma, while presenting a great heterogeneity of situations. Full article

In September 2017, Hurricane Irma made landfall in South Florida, causing a great deal of damage to mangrove forests along the southwest coast. A combination of hurricane strength winds and high storm surge across the area resulted in canopy defoliation, broken branches, and downed trees. Evaluating changes in mangrove forest structure is significant, as a loss or change in mangrove forest structure can lead to loss in the ecosystems services that they provide. In this study, we used lidar remote sensing technology and field data to assess damage to the South Florida mangrove forests from Hurricane Irma. Lidar data provided an opportunity to investigate changes in mangrove forests using 3D high-resolution data to assess hurricane-induced changes at different tree structure levels. Using lidar data in conjunction with field observations, we were able to model aboveground necromass (AGN; standing dead trees) on a regional scale across the Shark River and Harney River within Everglades National Park. AGN estimates were higher in the mouth and downstream section of Shark River and higher in the downstream section of the Harney River, with higher impact observed in Shark River. Mean AGN estimates were 46 Mg/ha in Shark River and 38 Mg/ha in Harney River and an average loss of 29% in biomass, showing a significant damage when compared to other areas impacted by Hurricane Irma and previous disturbances in our study region. Full article

This paper presents an analysis of a new method for retrieving the parameters of the atmospheric boundary layer in hurricanes. This method is based on the approximation of the upper parabolic part of the wind speed profile and the retrieval of the lower logarithmic part. Based on the logarithmic part, the friction velocity, near-surface wind speed and the aerodynamic drag coefficient are obtained. The obtained data are used for the verification of the modeling data in the WRF-ARW model. The case of the Irma hurricane is studied. Different configurations of the model are tested, which differ in the use of physical parameterizations. The difference of wind profiles in various sectors of the hurricane is studied. Full article

Maintaining smooth traffic during disaster evacuation is a lifesaving step. Traffic resilience is often used to define the ability of a roadway during disaster evacuation to withstand and recover its functionality from disturbances in terms of traffic flow caused by a disaster. However, a high level of variances due to system complexity and inherent uncertainty associated with disaster and evacuation risks poses great challenges in predicting traffic resilience during evacuation. To fill this gap, this study aimed to propose a new integrated data-driven predictive resilience framework that enables incorporating traffic uncertainty factors in determining road traffic conditions and predicting traffic performance using machine learning approaches and various space and time (spatiotemporal) data sources. This study employed an augmented Long Short-Term Memory (LSTM)-based approach with correlated spatiotemporal traffic data to predict traffic conditions, then to map those conditions to traffic resilience levels: daily traffic, segment traffic, and overall route traffic. A case study of Hurricane Irma’s evacuation traffic was used to demonstrate the effectiveness of the proposed framework. The results indicated that the proposed method could effectively predict traffic conditions and thus help to determine traffic resilience. The data also confirmed that the traffic infrastructures along the US I-75 route remained resilient despite the disturbances during the disaster evacuation activities. The findings of this study suggest that the proposed framework is applicable to other disaster management scenarios to obtain more robust decisions for the emergency response during disaster evacuation. Full article

Disasters triggered by natural hazards are becoming more frequent and more intense, causing damage to infrastructure and causing loss of life. One way to reduce disaster risk is by evacuating the hazardous area. However, despite the amount of literature that exists on evacuation behavior, there is still a lack of agreement on which variables can be used as predictors for individuals (or households) to actually evacuate. This lack of agreement can be related to the many variables that can affect the evacuation decision, from demographics, geographic, the hazard itself, and also local or cultural differences that may influence evacuation. Hence, it is essential to analyze and understand these variables based on the specifics of a case study. This study aims to find the most significant variables to be used as predictors of evacuation on the island of Sint Maarten, using data collected after the disaster caused by Hurricane Irma in September 2017. The results suggest that the variables gender, homeownership, percentage of property damage, quality of information, number of storeys of the house, and the vulnerability index are the most significant variables influencing evacuation decisions on the island. We believe the results of this paper offer a clear view to risk managers on the island as to which variables are most important in order to increase evacuation rates on Sint Maarten and to plan more efficiently for future evacuations. In addition, the variables found in this study have the potential to be the base information to set up, validate, and calibrate evacuation models. Full article