Area Spread Research Articles

Overlap of spike and ripple propagation onset predicts surgical outcome in epilepsy.

Interictal biomarkers are critical for identifying the epileptogenic focus. However, spikes and ripples lack specificity while fast ripples lack sensitivity. These biomarkers propagate from more epileptogenic onset to areas of spread. The pathophysiological mechanism of these propagations is elusive. Here, we examine zones where spikes and high frequency oscillations co-occur (SHFO), the spatiotemporal propagations of spikes, ripples, and fast ripples, and evaluate the spike-ripple onset overlap (SRO) as an epilepsy biomarker. We retrospectively analyzed intracranial EEG data from 41 patients with drug-resistant epilepsy. We mapped propagations of spikes, ripples, and fast ripples, and identified their onset and spread zones, as well as SHFO and SRO. We then estimated the SRO prognostic value in predicting surgical outcome and compared it to onset and spread zones of spike, ripple, and fast ripple propagations, and SHFO. We detected spikes and ripples in all patients and fast ripples in 12 patients (29%). We observed spike and ripple propagations in 40 (98%) patients. Spike and ripple onsets overlapped in 35 (85%) patients. In good outcome patients, SRO showed higher specificity and precision (p < 0.05) in predicting resection compared to onset and zones of spikes, ripples, and SHFO. Only SRO resection predicted outcome (p = 0.01) with positive and negative predictive values of 82% and 57%, respectively. SRO is a specific and precise biomarker of the epileptogenic zone whose removal predicts outcome. SRO is present in most patients with drug-resistant epilepsy. Such a biomarker may reduce prolonged intracranial monitoring and improve outcome.

Estimating the extent of water erosion in the Wadi Al-Rumaitha Basin, northeast of Al-Muthanna Governorate

The Wadi Rumaitha Basin is located astronomically between two latitudes (30° 39' 18" - 30° 29' 56") north, between two longitudes (45° 52' 4" - 45° 45' 10") east, with an area of (68.5) km2, located in the southern part of Iraq within the administrative borders of Al-Muthanna Governorate, which is characterized by a dry climate. The research aims to study and estimate the extent of water erosion in the Wadi Rumaitha basin, detect risks and conditions that affect the properties and quality of soil and land uses in the region, highlighting the role of natural characteristics affecting its activity, different types of water erosion prevail in the study area, between rain erosion, stream erosion, and gully erosion. The locations and areas of the basins of the river network and the stream, gully, and rain erosion network were determined, by adopting several criteria, including the Fournier equation to measure rain erosion, and the Bergsma 1982 equation (to measure the degree of stream and gully erosion, then, modeling the areas of spread of each of them, by the use of geographic information systems technology. It became clear through the research that the Fournier index in the stations of the study area reached (19.87, 21.66, 16.53), respectively, this indicates that the Wadi Rumaitha basin area falls within the range of weak rain erosion, while funicidal erosion included (4) cases limited to the range of high and very severe fluid erosion, gully erosion included (7) areas confined between the (very light and very high) ranges, and their geographical distribution varies in the basin lands.

PREVENTION OF TECHNOLOGICAL EMERGENCIES IN THE WARFARE ZONE

In a war zone, there are potential risks of the spread of an emergency due to harmful (polluting) substances in the environment above the maximum permissible concentrations. The causes of the danger are explosions, detonations, chemical spills, military vehicles, shelling or destruction of the infrastructure of oil facilities, and damage to the infrastructure of water supply and drainage. Method of preventing emergencies of a technological nature includes procedures using modern technologies and information systems to ensure timely response and minimise risks for the population and the environment. The algorithm for implementing the method of technological emergency prevention due to harmful (polluting) substances in the atmospheric air above the maximum permissible concentration in the combat zone consists of procedures. Procedures include work on planning and preparation, measurement and data collection, data analysis and processing, management decision-making, and control. Using a laser complex to prevent emergencies is an innovative approach that helps to identify potential threats and control their development accurately and effectively. The laser complex solves the dual task of detecting and immediately evaluating polluting gases and aerosols. The article also describes the algorithm for preventing technological emergencies due to harmful (polluting) substances in drinking water above the maximum permissible concentration in the combat zone. Groundwater is the predominant object of danger. The procedures consist of collecting and analysing statistical data, deciding the priority of monitoring areas, determining goals by types of hazards, setting tasks, choosing a monitoring scheme, determining monitoring procedures and their characteristics, solving monitoring issues, monitoring, making management decisions to limit the spread of the consequences of hazards. Effective emergency prevention procedures planned and carried out using modern tools and instruments can contain the spread of the consequences of a technological emergency, limiting the number of victims and injured and the area of hazard spread. Keywords: soil, air, monitoring, laser complex, emergency.

KozhukhovaE.I., MustafinKh.Kh., SemenovV.A., UchanevaE.N. Reconstructing Ethnocultural Processes in the Sausken Valley (Tuva) during the Later Half of the 1st Millennium BC

The article represents findings of the group research devoted to reconstructing ethnocultural processes of the second half of the 1st millennium BC (Sausken Terrain Feature, Tuva). The research comprehensively studies local population groups who left behind their burial monuments in Eerbek River Valley. The study engages geneticist, ancient technologies experts, anthropologists and archaeologists. Kurgans of the middle and late Uyuk-Sagly Culture (5th–2nd century BC) were excavated in 2011–2016 by Tuva archaeological expedition arranged by the Russian Academy of Sciences Institute for the History of Material Culture. Nearly all burials in the kurgans had been robbed back in the ancient days. The study analyses above-ground structures and internal layouts of the kurgans, the burial ritual and tools (weapons, mirrors, belt accessories, bone items, embellishments). It allows to conclude that the kurgans have varying cultural attributions. The research also implies instrumental process analysis of glass and stone beads, chromatography of fabrics and proteomic analysis of archaeological leather. The paper reveals radiocarbon dating (14C) and correlations with other burial monuments of the Scythian Tuva. Craniological materials analysed allow to determine populations that could have been related to the aliens who arrived at the Eerbek River Valley in the Uyuk times. The Ozen-Ala-Belig groups differ from their peers from other territories in Tuva. It might be explained through the Uyuyk migrants mixing with the Eerbek Valley people who had been living there since the late Bronze Age. The paleogenetic study of 19 items especially focuses on researching the Y-chromosome DNA. For many researched samples the study determines haplogroups Q1b1a3-L330 and R1a1a1b2-Z93 (or its subgroups). The area of spread for these haplogroups is Soviet Central Asia, Central Asia, West and South Siberia. One samples is assigned to I2a1b1-M223 haplogroups with the area of spread in the Balkans and South-Eastern Europe. The obtained findings may indicate that the Western and Eastern nomads kept in touch during the researched period. The archaeological, anthropological and genetic data lead to a conclusion that the Scythian cultures in the given region is complex and multi-faceted.

Deep learning for 4D modeling of glioblastoma multiforme with tumor treating fields (TTFields) therapy.

e14032 Background: Prediction of future tumor growth and recurrence are critical in the management of patients with glioblastoma multiforme (GBM). This study develops a deep learning method for estimating future areas of GBM spread across multiple timepoints using MRI in patients receiving tumor treating fields (TTFields) therapy. Methods: A single institutional database was queried to identify adult patients with histologically confirmed newly diagnosed and/or recurrent GBM undergoing TTFields therapy. For newly diagnosed GBM, patients received TTFields with temozolomide after maximal debulking surgery and chemoradiation therapy. For recurrent GBM, patients received TTFields as monotherapy. For each patient, all serial follow-up MRI exams were obtained, including T1 (pre-/post-contrast), T2, and T2/FLAIR sequences. On each exam, all regions of enhancing tumor core (excluding peritumoral edema, necrotic core, or resection cavity) were delineated and aligned across time points using nonlinear deformable registration. For any given pair of serial exams, a convolutional neural network (CNN) was designed to predict future GBM tumor on the follow-up exam given the precursor exam and time interval between the studies. The model is implemented as a 3D encoder-decoder architecture yielding a dense per-voxel prediction of future tumor probability optimized using a binary cross-entropy loss function. Class weights were used to develop high sensitivity and high positive predictive value (PPV) model variants. To generate final logit scores, time information is concatenated to the penultimate feature map as an additional feature channel, allowing the model to calibrate each estimate based on elapsed time between any pair of exams. Upon convergence, a 4D learned representation allows for prediction of spatial distribution of GBM tumor at any future time point. Results: A total of 123 patients (1112 total MR exams) were identified. For any given single patient, a median of 6 follow-up exams (IQR 2.5-12.5) at a median interval follow-up time of 46 days (IQR 15.75-63 days) between exams was observed. Upon five-fold cross-validation, the model demonstrated a 0.44 Dice score overlap between predicted and true areas of future GBM tumor growth. The high sensitivity model yielded a per-voxel sensitivity of 0.91 (IQR 0.77-0.99) and PPV of 0.26 (IQR 0.17 to 0.32), while the high PPV model yielded a per-voxel sensitivity of 0.14 (IQR 0.00 to 0.46) and PPV of 0.75 (IQR 0.56 to 0.94). Upon visual confirmation, model predictions across incremental time values for any given exam yielded expected gradual growth of tumor over time. Conclusions: A deep learning model can accurately predict future areas of GBM tumor growth in patients receiving TTFields therapy, with optimal performance that may be calibrated for high sensitivity or high PPV based on clinical use case.

Integrating Real-Time Meteorological Conditions into a Novel Fire Spread Model for Grasslands

Accurate comprehension of grassland fires is imperative for maintaining ecological stability. In this study, we propose a novel fire model that incorporates real-time meteorological conditions. Our methodology integrates key meteorological factors including relative humidity, temperature, degree of solidification of combustible materials, and wind speed. These factors are embedded into a comprehensive function that determines both the downwind and upwind spreading speeds of the fire. Additionally, the model accommodates fire spread in the absence of wind by incorporating the direction perpendicular to the wind, with wind speed set to zero. By precisely determining wind speed, the model enables real-time calculation of fire spread speeds in all directions. Under stable wind conditions, the fire spread area typically adopts an elliptical shape. Leveraging ellipse properties, we define the aspect ratio as a function related to wind speed. Consequently, with knowledge of the fire duration, the model accurately estimates the area of fire spread. Our findings demonstrate the effectiveness of this model in predicting and evaluating fires in the Hulunbuir Grassland. The model offers an innovative method for quantifying grassland fires, contributing significantly to the understanding and management of grassland ecosystems.

Ganglionic Local Opioid Analgesia at the Superior Cervical Ganglion: MRI-Verified Solution Spread.

Ganglionic local opioid analgesia (GLOA) at the superior cervical ganglion (SCG) is performed for pain control and is known to be an effective procedure. In this study, we evaluated the spread of the injectate in the area of the SCG. Our expectation was that there would be a correlation between the area and volume of the injectate spread and post-procedural outcome measures. This was a retrospective blinded review of magnetic resonance imaging (MRI) scans. Assessors evaluated the anatomical area of fluid spread, the furthermost spread from midline, any hampered spread and contact of contrast fluid with other structures. The efficacy of GLOA and complications were estimated. The main solution spread reached from the C1 to C3 vertebrae. The furthest spread in the lateral and sagittal planes was 21.2 and 15.2mm, respectively. The furthest craniocaudal spread was 63.5mm. In 53.3% and 33% of interventions, the solution was found in the parapharyngeal space and in its "medial compartment," respectively. A correlation was found between pain relief and both solution spread and volume of solution spread. No hampered spread was recorded. A negative correlation between pain reduction and number of GLOA was observed. Higher pre-procedural pain intensity was correlated with higher pain reduction. We estimated pain relief in 93% of procedures correctly. No correlation between post-procedural Numerical Rating Scale (NRS) scores and different needle approaches was found. For the transoral blocking technique, a strict laterodorsal needle direction is recommended to prevent possible block failures. A total volume of 2ml injected into the parapharyngeal space and its "medial compartment" is recommended. Higher volumes may lead to uncontrolled distribution patterns. Clinicaltrials.gov identifier NCT05257655; date of registration 2022-02-25; patient enrollment date from 2023-01-09 to 2023-08-31.

Atypical neoplastic solitary focal uptake of 18F-PSMA-1007 in PET/CT in patients with biochemically recurrent prostate cancer

It is established that prostate-specific membrane antigen (PSMA), despite its name, is expressed in many tissues other than the prostate gland, both within physiological conditions and in various pathological processes. Additionally, apart from prostate cancer, other malignant tumors are characterized by increased PSMA expression which, according to many authors, is associated with neoangiogenesis. These factors are reflected in the results of PSMA-radioligand imaging and require comprehensive approach to image interpretation including evaluation of computed tomography and magnetic resonance semiotics. In addition, rare cases of distant visceral prostate cancer metastasis in the form of solitary lesions also should be considered during interpretation of the results of radiologic imaging including positron emission tomography/computed tomography.We present two clinical cases in which positron emission tomography/computed tomography revealed solitary foci of pathological 18F-PSMA-1007 uptake outside the areas of typical metastatic spread (with exception of advanced disease) of prostate cancer, specifically in the stomach wall and the left cerebellar hemisphere. In the first case histological examination results revealed a metachronous low grade neuroendocrine tumor of the stomach, in the second case a metastatic lesion of the cerebellum was diagnosed as part of the underlying disease.

Mesoscopic mapping of hemodynamic responses and neuronal activity during pharmacologically induced interictal spikes in awake and anesthetized mice

Imaging hemodynamic responses to interictal spikes holds promise for presurgical epilepsy evaluations. Understanding the hemodynamic response function is crucial for accurate interpretation. Prior interictal neurovascular coupling data primarily come from anesthetized animals, impacting reliability. We simultaneously monitored calcium fluctuations in excitatory neurons, hemodynamics, and local field potentials (LFP) during bicuculline-induced interictal events in both isoflurane-anesthetized and awake mice. Isoflurane significantly affected LFP amplitude but had little impact on the amplitude and area of the calcium signal. Anesthesia also dramatically blunted the amplitude and latency of the hemodynamic response, although not its area of spread. Cerebral blood volume change provided the best spatial estimation of excitatory neuronal activity in both states. Targeted silencing of the thalamus in awake mice failed to recapitulate the impact of anesthesia on hemodynamic responses suggesting that isoflurane’s interruption of the thalamocortical loop did not contribute either to the dissociation between the LFP and the calcium signal nor to the alterations in interictal neurovascular coupling. The blood volume increase associated with interictal spikes represents a promising mapping signal in both the awake and anesthetized states.

Дронның журналистикада қолданылуы: мүмкіндіктер мен шектеулер

The field of journalism has not been spared from the rapid development of technology. With the development of communication technologies, traditional journalism has been transformed. In the past, news was produced by media and consumed by the masses. However, the advent of drones has led to the emergence of citizen journalism as an alternative source of information in the news gathering process. Considered the «eyes in the air» of journalists, drones are offering new opportunities for both citizen journalists and large media companies. Drones have a great physical advantage in that they can display the area of damage spread in disasters such as fires, earthquakes, floods, the scale of events on battlefields, sporting events and concerts. It also creates conditions for quick access to the journalist's news and informative publication. However, the dangers posed by drone technology in areas such as national security, public health and safety, personal life and public safety, as well as legal and ethical issues, cannot be ignored in addition to expanding the possibilities of journalistic reporting. This article analyzes the new breath and contribution that the use of drones has brought to journalism, as well as its possibilities and limitations

Determination of Risks of Occurrence and Areas of Brucellosis Infection Spread in the Territory of the Republic of Kazakhstan

Determination of Risks of Occurrence and Areas of Brucellosis Infection Spread in the Territory of the Republic of Kazakhstan

Artificial intelligence-based analysis of time-lapse images of sphere formation and process of plate adhesion and spread of pancreatic cancer cells.

Background: Most pancreatic cancers are pancreatic ductal adenocarcinomas (PDAC). Spherical morphology formed in three-dimensional (3D) cultures and the effects of anticancer drugs differ between epithelial and mesenchymal PDAC cell lines. In the human pancreas, cancer cells form 3D tumors, migrate to adjacent tissues, and metastasize to other organs. However, no effective methods exist to examine the ability of the tumor mass to migrate to surrounding tissues in vitro. We used spheres formed in 3D culture to investigate whether the migratory ability of tumors of PDAC cell lines, including epithelial and mesenchymal cell lines, varies. Methods: Sphere formation and adhesion and spread on culture plates were examined by artificial intelligence-based analysis of time-lapse imaging using five epithelial and three mesenchymal PDAC cell lines. Fused and non-fused areas of the sphere surface during sphere formation on low-attachment plates, the adhesion area to normal culture plates, and the sphere area maintaining its original form during adhesion to plates were measured. Results: Immunocytochemical staining confirmed that E-cadherin was highly expressed in epithelial PDAC spheres, as was vimentin in mesenchymal PDAC spheres, in 2D culture. When forming spheres using low-attachment plates, most epithelial PDAC cell lines initially showed decreased sphere area, and then the covering cells fused to form a smooth surface on the sphere. Mesenchymal PANC-1 and MIA PaCa-2 cells showed little reduction in sphere area and few areas of sphere surface fusion. When formed PDAC spheres were seeded onto normal culture plates, spheres of epithelial PK-8 cells-which have the highest E-cadherin expression, form numerous cysts, and have smooth sphere surfaces-did not adhere to normal plates even after 60h, and epithelial PK45-P and T3M-4 spheres hardly adhered. Conversely, the area of adhesion and spread of mesenchymal PANC-1 and KP4 cell spheres on normal plates markedly increased from early on, forming large areas of attachment to plates. Conclusion: Seeding spheres formed in 3D culture onto culture plates can clarify differences in tumor migration potential to surrounding areas. The masses formed by each PDAC cell line varied in migratory ability, with mesenchymal PDAC masses being more migratory than epithelial PDAC masses.

Re-emergence of Lassa fever in Nigeria: A new challenge for public health authorities.

The Lassa virus is an RNA virus belonging to the Arenaviridae family. It is responsible for Lassa fever, an acute viral zoonosis of the severe hemorrhagic fever type with manifestations of fever, muscle pain, sore throat, nausea, vomiting, and chest and abdominal pain. Lassa fever is endemic in West Africa, where the first case was reported in 1969 in Lassa, a town in Nigeria, more than 50 years ago, and it is estimated that nearly 5000 deaths occur in West Africa each year. Nigeria is one of the endemic hotspots and has experienced numerous recurrent outbreaks of Lassa fever due to the increased multiplication of the host reservoir, Mastomys natalensis. For the Lassa epidemics in 2022 and January 2023 alone, Nigeria accounts for a quarter of the annual deaths from this disease. Poor lifestyle and hygiene, difficulty in diagnosis due to nonspecific symptomatology, lack of effective treatment based on clinical evidence, an ineffective human immunization program combined with a health system that is not adapted or equipped to control and prevent recurrent deadly epidemics, and an outdated regional disease surveillance system in West Africa are some of the challenges that must be overcome to rapidly and effectively eradicate this disease, whose area of spread is constantly expanding as a result of the movement of populations in the context of economic and socio-cultural activities.

Construction of Solutions and Study of Their Closeness in L2 for Two Boundary Value Problems for a Model of Multicomponent Suspension Transport in Coastal Systems

Three-dimensional models of suspension transport in coastal marine systems are considered. The associated processes have a number of characteristic features, such as high concentrations of suspensions (e.g., when soil is dumped on the bottom), much larger areas of suspension spread than the reservoir depth, complex granulometric (multifractional) content of suspensions, and mutual transitions between fractions. Suspension transport can be described using initial-boundary value diffusion–convection–reaction problems. According to the authors' idea, on a time grid constructed for the original continuous initial-boundary value problem, the right-hand sides are transformed with a “delay” so that the right-hand side concentrations of the components other than the underlying one (for which the initial-boundary value problem of diffusion–convection is formulated) are determined at the preceding time level. This approach simplifies the subsequent numerical implementation of each of the diffusion–convection equations. Additionally, if the number of fractions is three or more, the computation of each of the concentrations at every time step can be organized independently (in parallel). Previously, sufficient conditions for the existence and uniqueness of a solution to the initial-boundary value problem of suspension transport were determined, and a conservative stable difference scheme was constructed, studied, and numerically implemented for test and real-world problems. In this paper, the convergence of the solution of the delay-transformed problem to the solution of the original suspension transport problem is analyzed. It is proved that the differences between these solutions tends to zero at an O(τ) rate in the norm of the Hilbert space L2 as the time step t approaches zero.

Estimating biocontrol agent spread: A case study using introduced dung beetles

Abstract Insect biological control agents may be released in relatively few locations; thus, the rate of spread is critical to predicting the spatial distribution of the agent. Exotic dung beetles have been introduced into Australia since the 1960s to bury dung, reduce bush fly populations, increase pasture productivity and improve livestock health. We use a stochastic cellular automata model to predict the historical occupancy and abundance of introduced dung beetles in the South West agricultural region of Western Australia. The model predicts the spread of four species of dung beetles in six‐month time steps for 10 years following initial release. Our model includes release locations, species‐specific ecological parameters, dung resource availability and weather variables. The average rate of spread varied between species from a high of ca. 79 km/year (Euoniticellus intermedius) to a low of 28 km/year (Onthophagus taurus). Thus, after 10 years, the area of spread varied between 99,175 and 34,175 km2 and abundance varied from 88,100 to 4,189 beetles/km2. These findings provide an estimate of the spread patterns of dung beetles. The model can be used to guide future dung beetle release programmes in Australia and elsewhere.

Reconsideration of Urbanization in Tokyo Metropolitan Area Since 1923 Great Kanto Earthquake from the Perspective of Exposure

The year 2023 marks the 100th commemoration of the disastrous Kanto Earthquake in Japan, which shattered the urban fabric of Tokyo and other southern prefectures. In the years following 1923, much research into disaster risk reduction (especially fire prevention) was undertaken. This study evaluated research trends and the impact of the earthquake on the city using metropolitan population data. The following is reported: (1) This study summarized English and Japanese academic papers and reports on the Great Kanto Earthquake that have been published over the last 100 years. (2) The area of fire spread and number of damaged buildings in Tokyo due to the Great Kanto Earthquake were overwhelmingly larger than those in other areas. (3) The difference in the relative amount of damage caused by natural disasters with more than 1,000 death toll to the annual national budget in Japan became clear. (4) The Great Kanto Earthquake was the only natural disaster that caused a net worth of damage exceeding the Japanese national budget by 3.8 times. (5) The expansion of the Tokyo metropolitan area over the 100 years since the Great Kanto Earthquake was visually clarified based on demographics. (6) Today, many people live densely on soft ground, with an amplification factor of 1.8 or higher, which is 23.0% of the total population.

DATA MINING APPLICATION FOR CLUSTERING COVID-19 SPREAD AREAS IN DKI JAKARTA USING THE K-MEANS ALGORITHM

Coronavirus Disease 2019 (coronavirus disease2019, abbreviated as COVID-19) is an infectious disease caused by SARS-Cov-2, a type of coronavirus. Covid-19 patients can experience fever, dry batik, and difficulty breathing. The infection spreads from one person to another through a splash (droplet) from the respiratory tract produced when coughing or sneezing. The number of residents until 2019 reached 11,063,324 people spread across 6 cities consisting of 44 districts and 267 urban villages, making Covid-19 easy to spread. To be able to see the area of spread of Covid-19, it is necessary to group based on the attributes used consisting of Suspect Cases, Probable, Cases, Close Contacts, Confirmed Cases and Deaths. In this study, to cluster the data, the K-Means method and the Euclidean distance measurement method were used. This study produced a prototype application for grouping data on the distribution of Covid-19 patients. The result of the implementation of the K-Means Algorithm is that the Covid-19 spread cluster in DKI Jakarta is divided into 3 (three) clusters, namely cluster 1, cluster 2 and cluster 3. Cluster 1 is a medium case zone, Cluster 2 is a high case zone and Cluster 3 is a low case zone.

Integrating active fire behavior observations and multitemporal airborne laser scanning data to quantify fire impacts on tree growth: A pilot study in mature Pinus ponderosa stands

Methods that integrate pre-, active-, and post-fire measurements to quantify fire effects across multiple spatial scales are needed to improve our understanding of ecological effects following fire and for informing natural resource management decisions that rely on post-fire growth and yield estimates. Given growth and yield modeling systems require tree level measurements to parameterize diameter and height distributions, effective datasets require both tree and stand level characterization. However, most stand-to-landscape scale fire effects studies use optical multispectral data (e.g., 30 m spatial resolution Landsat data) which are too coarse to quantify tree-level effects and is limited in its ability to quantify changes in forest structure. Most studies also fail to integrate active fire behavior observations, such as heat flux, limiting their ability to identify mechanisms of tree injury and mortality and/or predict fire effects. Combining active fire observations and structural measurements derived from multitemporal airborne laser scanning (ALS) data has been proposed to quantify fire effects on tree structure and growth but has yet to be tested. In this pilot study, we used a combination of fire behavior and heat flux metrics, including Fire Radiative Power per unit area (FRP: W m−2) and Fire Radiative Energy per unit area (FRE: J m−2), along with multitemporal field and ALS measurements to quantify fire intensity impacts on mature tree height growth. Prescribed fires were conducted in 2014 in thinned and unthinned mature Pinus ponderosa stands and plot-scale fire behavior and heat flux metrics were quantified using standard videography methods and tower-mounted infrared radiometers. Tree height growth was quantified using multitemporal field and ALS data and included pre-fire measurements and post-fire measurements up to eight years post-fire. Results show that trees exposed to the surface fire treatments had height growth that was less than unburned trees. The results also show that height growth 5–8 years post-fire is reduced in trees exposed to greater fire intensities, in terms of maximum FRP per unit area and rate of spread. There was no significant relationship between height growth and other fire behavior metrics (FRE per unit area, average flame length, flame residence time), although height growth decreased with greater FRE per unit area and increased with greater flame residence time. These findings, taken together with similar sapling-, mature tree- and landscape-scale studies, suggest that an integrated active-fire behavior and ALS-data approach may provide a quantitative, scalable method for assessing fire effects on tree structure and growth.

Estimating potential global sources and secondary spread of freshwater invasions under historical and future climates

AbstractAimWe employed a climate‐matching method to evaluate potential source regions of freshwater invasive species to an introduced region and their potential secondary spread under historical and future climates.LocationGlobal source regions, with primary introductions to the Laurentian Great Lakes and secondary introductions throughout North America.MethodsWe conducted a climate‐match analysis using the CLIMATE algorithm to estimate global source freshwater ecoregions under historical and future climates with an ensemble of global climate models for climate‐change scenario SSP5‐8.5. Given existing research, we use a climate match of ≥71.7% between ecoregions to indicate climatic conditions that will not inhibit the survival of introduced freshwater organisms. Further, we estimate the secondary spread of freshwater invaders to the ecoregions of North America under historical and future climates.ResultsWe identified 54 global freshwater ecoregions with a climate match ≥71.7% to the recipient Laurentian Great Lakes under historical climatic conditions, and 11 additional ecoregions were predicted to exceed the threshold under climate change. Three of the 11 ecoregions were located in South America, a continent where no matches existed under historical climates and eight were located in the southern United States, southern Europe, Japan and New Zealand. Further, we identify 34 North American ecoregions of potential secondary spread of freshwater invasions from the Great Lakes under historical climatic conditions, and five ecoregions were predicted to exceed the threshold under climate change.Main ConclusionWe provide a climate‐match method that can be employed to assess the sources and spread of freshwater invasions under historical and future climate scenarios. Our climate‐match method predicted increases in climate match between the recipient region and several potential source regions, and changes in areas of potential spread under climate change. The identified ecoregions are candidates for detailed biosecurity risk assessments and related management actions.

Transmission risk of Oropouche fever across the Americas

BackgroundVector-borne diseases (VBDs) are important contributors to the global burden of infectious diseases due to their epidemic potential, which can result in significant population and economic impacts. Oropouche fever, caused by Oropouche virus (OROV), is an understudied zoonotic VBD febrile illness reported in Central and South America. The epidemic potential and areas of likely OROV spread remain unexplored, limiting capacities to improve epidemiological surveillance.MethodsTo better understand the capacity for spread of OROV, we developed spatial epidemiology models using human outbreaks as OROV transmission-locality data, coupled with high-resolution satellite-derived vegetation phenology. Data were integrated using hypervolume modeling to infer likely areas of OROV transmission and emergence across the Americas.ResultsModels based on one-support vector machine hypervolumes consistently predicted risk areas for OROV transmission across the tropics of Latin America despite the inclusion of different parameters such as different study areas and environmental predictors. Models estimate that up to 5 million people are at risk of exposure to OROV. Nevertheless, the limited epidemiological data available generates uncertainty in projections. For example, some outbreaks have occurred under climatic conditions outside those where most transmission events occur. The distribution models also revealed that landscape variation, expressed as vegetation loss, is linked to OROV outbreaks.ConclusionsHotspots of OROV transmission risk were detected along the tropics of South America. Vegetation loss might be a driver of Oropouche fever emergence. Modeling based on hypervolumes in spatial epidemiology might be considered an exploratory tool for analyzing data-limited emerging infectious diseases for which little understanding exists on their sylvatic cycles. OROV transmission risk maps can be used to improve surveillance, investigate OROV ecology and epidemiology, and inform early detection.