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Diverse forest landscapes contribute to reaching various forest policy goals. Understanding how the diversity of forests in a landscape is distributed among forest properties and how it is related to biogeographical and ownership factors can be helpful for effective policy implementation. We created a forest characteristics-based typology of non-industrial private forest properties aiming to capture the between-property forest diversity in a municipality in southern Sweden, and studied how it was related to owner age and gender, landscape position, and storm damage. Using public data of forests and latent profile analysis, we detected five clusters of properties. Four clusters differed mainly by age structure and species composition. One of them was clearly marked by a high proportion of young mixed forest following severe storm damage >15 years prior. The fifth cluster was marked by a greater occurrence of nature conservation agreements and conservation value forests. Conifer-dominated properties were larger than broadleaf-dominated properties. Owner age only slightly differed between clusters, being higher for properties characterized by a prevalence of older coniferous or by noble broadleaved forests and nature conservation. Properties in the latter cluster were more often owned by women and located close to lakes. [ABSTRACT FROM AUTHOR]

Wang, P.; Royer, E.L.; Jackson, K., and Gutierrez, S., 2024. Impacts of Hurricane Ian along the low-lying southwest Florida coast (USA) in 2022: Lessons learned. Journal of Coastal Research, 40(5), 827–851. Charlotte (North Carolina), ISSN 0749-0208. Hurricane Ian made landfall in the low-lying, densely populated, and developed southwestern Florida coast on 28 September 2022 as a large and slow-moving category 4 hurricane. Various U.S. federal and state agencies collected a large and comprehensive data set, including pre- and poststorm airborne LIDAR topography, in situ water level and wave measurements at numerous locations before, during, and after the storm, and poststorm high-water marks over a large area. This study reports results from a series of poststorm field investigations including ground observations of beach-dune erosion and deposition, catastrophic damage to various infrastructure, and widespread distribution of non-biodegradable materials washed into the estuary and numerous mangrove islands. Hurricane Ian induced large-scale inundation in low-lying southwest Florida, submerging all the barrier islands bordering Charlotte Harbor estuary, all the islands within the estuary, and up to 5 km into the mainland. Dense tree-type vegetation limited the landward penetration of beach-dune erosion and overwash deposition along the barrier islands. Net sand-volume loss from the beach-dune system ranged 10–25 m3/m and was controlled by the deep submergence of the system during the peak of the storm. The extremely high storm surge of up to 5.2 m above mean sea level generated by Hurricane Ian caused severe damage to the built environments over a large area. High storm waves superimposed on the elevated water level, reaching 1.2 m at the seaward edge of vegetated dunes, contributed to the destruction along the barrier islands. Hurricane Ian distributed a tremendous amount of non-biodegradable artificial debris over a large area and into sensitive natural environments, including numerous mangrove islands, barrier-island interior wetlands, and the estuary waterbody. Measures to prevent materials such as single-use plastics, insulation fibers, and household appliances from being washed into sensitive environments should be a significant part of prestorm preparation. [ABSTRACT FROM AUTHOR]

On 1‐2 November 2023, Storm Ciarán impacted the British Isles, causing widespread wind damage and significant disruption to the Channel Islands and parts of southern England. Three areas within this wider swathe ‐ Jersey (Channel Islands), Loders in Dorset and Sompting/Lancing in West Sussex ‐ suffered additional, more severe, localised wind damage. These areas were investigated by the Tornado and Storm Research Organisation (TORRO). Each of these sites was found to have been affected by a tornado. The most intense of these was in Jersey, where one of the strongest tornadoes in the UK and Channel Islands since 1954 occurred. [ABSTRACT FROM AUTHOR]

Cyclonic storms (i.e., hurricanes) are powerful disturbance events that often cause widespread forest damage. Storm‐related canopy damage reduces rainfall interception and evapotranspiration, but impacts on streamflow regimes are poorly understood. We quantify streamflow changes in Puerto Rico following Hurricane Maria in September 2017, and evaluate whether forest cover and storm‐related canopy damage account for the differences. Streams are particularly vulnerable to flooding in early post‐disturbance stages during hurricane season, so we focus on 3 months (Oct–Dec) following the hurricane. To discern changes in rainfall responses, we partitioned streamflow into baseflow and quickflow using a digital filter. We collected 2010–2017 streamflow and rainfall data from 18 watersheds and compared the relative magnitude of post‐ to pre‐hurricane double mass curve slopes of baseflow and quickflow volumes against rainfall. Several watersheds displayed higher post‐hurricane quickflow and baseflow, however, the response was variable. The magnitude of quickflow increase was greater in watersheds with high forest damage. Under the same level of relative damage, watersheds with low initial forest cover had greater quickflow increases than highly forested ones. Conversely, baseflow generally increased, but increases were greater in highly forested watersheds and smaller in highly damaged watersheds. These results suggest that post‐storm baseflow increases were due to recharge of hurricane‐related rainfall, as well as forest transpiration interruption and soil disturbance enhancing recharge of post‐hurricane rainfall, while increases to quickflow are related to loss of canopy rainfall interception and higher soil saturation decreasing infiltration. Our research demonstrates that forest damage from disturbance lowers quickflow and elevates baseflow in highly forested watersheds, and elevates quickflow and lowers baseflow in less‐forested watersheds. Less‐forested watersheds may be closer to the forest cover loss threshold needed to elicit a streamflow response following disturbance, suggesting higher flooding potential downstream, and a lower storm‐related forest disturbance threshold than in heavily forested watersheds. [ABSTRACT FROM AUTHOR]

Devastation from hurricanes can cause multiple problems for turfgrass managers, sod producers, and homeowners. Damage may include visible factors such as prolonged periods of standing water, uprooted trees, shading and obstruction from demolished structures, deposition of silt or mud, and damage to irrigation systems. Less visible problems may include damage to root systems resulting from compacted soil from heavy equipment used during cleanup and recovery, reduced drainage, and injury resulting from effects of saltwater intrusion. Suggested guidelines for correcting these problems are included in the text.

In the lower Florida Keys, the endangered Florida Key deer and numerous other wildlife species inhabit a vulnerable island environment susceptible to storm surges and rising seawater due to low elevation and flat terrain. Timely and reliable assessment of vegetation damage from natural disasters, such as Hurricane Irma, is crucial for effective habitat management. The study’s overall objective is to examine Hurricane Irma’s impact on vegetation on No Name Key, Florida, using remote sensing. The study relates the area change in vegetation obtained from remote sensing analysis to Florida Key deer population changes following the storm. The methodology involved performing a thematic change detection analysis using the following data sources: (1) aerial multispectral images (for pre- and post-Hurricane), (2) airborne lidar data (for pre- and post-Hurricane), (3) an existing vegetation map, and (4) soil data. A Support Vector Machine (SVM) image classification algorithm was applied to pre- and post-storm input image stacks to create pre- and post-Hurricane Irma vegetation maps. We were then able to obtain the area change information (for various vegetation categories) by performing the change detection analysis of the 2 SVM-classified images. The differences in areas following the storm were calculated for 7 affected vegetation types. Using the area change information following Hurricane Irma, we estimated the number of deer supported by the storm-affected vegetation. These estimated deer numbers, based on the area differences in post-Hurricane Irma vegetation types, were compared to observed deer numbers collected during the post-Hurricane Irma Texas A&M Natural Resources Institute (NRI) deer field survey. The results showed the following: mangroves had the largest negative area changes (area loss), followed by pinelands, hardwoods/hammocks, developed areas, and buttonwoods. Freshwater marshes had the largest positive area changes (area gain). The deer's preferred vegetation areas had decreased post-Hurricane Irma, resulting in a reduced deer population compared to pre-storm numbers. The predicted number of the Key deer post-Hurricane Irma fell within a 95% confidence interval of the observed deer population from the post-storm field survey. The study findings and techniques could be applied to study climate change impact, especially sea level rise. This methodology can be valuable in assessing the impact of storms on other wildlife species in similar environments. The applications and methodology are especially relevant considering the increasing frequency and intensity of storm surges and the accelerating rate of sea level rise.

Detailed information on coastal storm impacts is crucial to evaluate the degree of damages caused by floods, implementing effective recovery actions for risk prevention and preparedness, and to design appropriate coastal zone management plans. This article presents a new database containing information on extreme storm events that generated damage and flooding along European coastlines between 2010 and 2020. The storm events, associated with specific locations, define the test cases which are then used to retrieve information from different extreme coastal storms that hit the same area. The database is a workbook that collects items organised in worksheets and constitutes an inventory of resources defined as a collection of different types of information used to characterize the event (i.e., hydrodynamics, weather information) and its consequences (impacts, flood extent, etc.). The guidelines and polygons in GeoJSON format that define the domain of the sites are also provided together with the workbook. The database contains 11 coastal storm events, 26 sites, 28 test cases, and 232 resources and is designed to allow the addition of new events and resources. Descriptive statistical analyses were performed to define the types and topics addressed by the resources and the distribution of types of resources per country. Lastly, an example of application of the database to European-scale flood modelling is provided. [ABSTRACT FROM AUTHOR]

Adverse weather conditions from acute events (e.g., storms causing lodging, flooding, or hail) or short‐duration weather patterns (i.e., periods of cold events; extended waterlogged field conditions) can result in yield losses, though management practices may play key roles in aiding with crop recovery or avoidance of these stress events. This review summarizes current knowledge (with emphasis placed on the US Midwest) related to corn response to short‐term weather stresses of (i) cold temperature, (ii) excess water, (iii) hail/defoliation damage, and (iv) wind damage. Each section presents summaries of how corn growth and yield are affected, provides context into past events experienced, identifies agronomic or production recommendations to correct or alleviate the stress condition, and proposes areas where future research is needed. This review also highlights challenges associated with controlled simulation work on these stressors, and also identifies key areas to expand future research efforts. In general, yield losses associated with strong storms and short‐term weather events often ranged from 5% to 35%, but extreme cases could result in up to 80%–100% yield loss. Much of the literature on these topics was published prior to 1995, though it still forms the basis for modern agronomic guidance, which is problematic given the changes in agriculture in the last 20 years in management practices, available genetics and technologies, and changing environmental conditions. Revisiting these foundational studies and expanding them to examine current and future weather conditions are critical for better informing agronomic recommendations, for devising mitigation strategies, and for determining accurate yield loss expectations following these stresses. Core Ideas: Climatic shifts are resulting in more frequent strong storms and adverse weather for corn.Storms and weather stress reduce corn yield 5%–35%, though greater losses are possible.Foundational knowledge produced prior to 1995 should be re‐assessed to ensure accuracy in modern systems.Updating agronomic recommendations with modern technology is critical to ensure crop security. [ABSTRACT FROM AUTHOR]

Barrier islands span 10% of the world's coastlines and dominate along the Atlantic and Gulf of Mexico coasts in the USA routinely exposed to storm surge. These islands serve as buffers between the open coast and the mainland, and protect the mainland from storm damage. During storms, significant morphological change can occur, including substantial erosion of the islands' vegetated dunes. In this study, the focus is on the influence of belowground biomass – namely dune plant roots – and dune topographic characteristics on barrier-island erosion during storms. The numerical model XBeach was employed to simulate storm-induced sediment transport. A parameter study was conducted by varying distance from the shoreline to the dune, dune shape, sediment grain size, and sediment mobility as an analogue for biomass. The influence of individual parameters and the collective impact of parameters were analyzed. The results help improve our knowledge of barrier island dynamics and lay a solid groundwork for future investigations. [ABSTRACT FROM AUTHOR]

Addressing human-made environmental problems such as deforestation is an ongoing educational challenge. Promising educational approaches include cooperative decision-making and attempt via a high level of motivation to promote pro-environmental behaviors. Knowledge about the forest ecosystem, including its threats, is supposed to strengthen responsibilities and individual behavioral preferences. The "Save the Forests!" module engages students in hands-on learning activities under the frame of an educational Escape Game (Edu Breakout). Based on nine workstations, it includes various cooperative activities focusing on the forest ecosystem, its ecosystem services, and common tree species. Students realize advantages of recycling, gain insight into paper production and associated resource consumption, compare eco-labels for sustainable paper products, and reflect on consumer decisions. Additionally, the students learn about habitat situations after clear-cutting, forest fires, or storm damages (succession), including strategies for dealing with deadwood based on scientific data. Besides experiments and challenging tasks, students learn about the ecological footprint and greenwashing by clarifying often-used terms in sustainability contexts. In an accompanied quantitative study approach, students participating in the learning module significantly increased their knowledge scores in a pre-post comparison (n = 135, p < 0.001, d = 0.58). [ABSTRACT FROM AUTHOR]

The proton radiation belt contains high fluxes of adiabatically trapped protons varying in energy from ~one to hundreds of megaelectron volts (MeV). At large radial distances, magnetospheric field lines become stretched on the nightside of Earth and exhibit a small radius of curvature RC near the equator. This leads protons to undergo field line curvature (FLC) scattering, whereby changes to the first adiabatic invariant accumulate as field strength becomes nonuniform across a gyroorbit. The outer boundary of the proton belt at a given energy corresponds to the range of magnetic L shell over which this transition to nonadiabatic motion takes place, and is sensitive to the occurrence of geomagnetic storms. In this work, we first find expressions for nightside equatorial RC and field strength Be as functions of Dst and L* to fit the TS04 field model. We then apply the Tu et al. (2014, https://doi.org/10.1002/2014ja019864) condition for nonadiabatic onset to solve the outer boundary L*, and refine our expression for RC to achieve agreement with Van Allen Probes observations of 1-50 MeV proton flux over the 2014-2018 era. Finally, we implement this nonadiabatic onset condition into the British Antarctic Survey proton belt model (BAS-PRO) to solve the temporal evolution of proton fluxes at L ≤ 4. Compared with observations, BAS-PRO reproduces storm losses due to FLC scattering, but there is a discrepancy in mid-2017 that suggests a ~5 MeV proton source not accounted for. Our work sheds light on outer zone proton belt variability at 1-10 MeV and demonstrates a useful tool for real-time forecasting. [ABSTRACT FROM AUTHOR]

The floodplains of the Southeast's stream network once hosted immense brakes of rivercane (Arundinaria gigantea), a disturbance-dependent native bamboo with both cultural and ecological significance. Ecologically, rivercane alters its local environments, boosts biodiversity and biomass, and protects streambanks from erosion and storm damage. Indigenous peoples of the Southeast have used rivercane for millennia, for material and cultural purposes, and formerly maintained its health and extent through harvesting and fire. Settler-colonial incursions largely destroyed rivercane, through the more intense disturbance of different land management practices, and brakes now exist mainly in relatively small areas. While numerous rivercane restoration projects are in process throughout its natural range, no comprehensive inventory of living rivercane exists. In this paper, we present both human context and the results of LiDAR analysis that identifies canebrakes based on the physical characteristics of the plant and brake. In our study area on the Little Tennessee River in western North Carolina, we found rivercane on about 9 percent of the floodplain area, based on QL1 LiDAR data available from the state of North Carolina. The technique can be applied in any part of rivercane's range, and the resulting inventory used in support of both cultural and ecological goals. [ABSTRACT FROM AUTHOR]