Low Population Density Research Articles

Native forest and proximity to humans are stronger drivers of Brazilian cottontail habitat use than invasive European hare

AbstractHuman activities and biological invasions have caused unprecedented biodiversity loss over the past 500 years. Proximity to humans drives the spatial distribution of species toward less disturbed habitats. Invasive species can competitively exclude native species, but species may coexist due to different habitat preferences. Here, we investigated how proximity to farms and the presence of the non‐native European hare (Lepus europaeus) influence the habitat use by the Brazilian cottontail (Sylvilagus minensis) in southeastern Brazil. We found that the probability of cottontail site use increased with native forest cover and decreased with farmhouse proximity, ranging from 0.05 (SE = 0.02) at sites close to farmhouses (≅900 m) with no native forest to 0.70 (SE = 0.15) at sites far from farmhouses (≅2500 m) dominated by native forest. Higher risk of harassment and predation by free‐roaming dogs and cats may explain the negative effect of farmhouse proximity on cottontail habitat use. We found little evidence for competitive exclusion by the European hare. Instead, our results suggest that the two species spatially segregate due to different habitat preferences. While the European hare more likely uses farmland in its native and non‐native range, our results suggest that the Brazilian cottontail is a forest dweller. Although we found only weak evidence of competitive exclusion, we advise caution because invasive species may delay the onset of detrimental effects due to initial low population densities in newly invaded areas as is the case of the European hare in southeastern Brazil.Abstract in Portuguese is available with online material.

Flood Risk Identification of Zhengzhou Metropolitan Area Based on Invest Model

Rainstorm and urban flood are always one of the most serious natural disasters in China due to the change of ecological environment, terrain conditions and climate change. Rainstorm and flood disasters seriously threaten the security and development of regional economy and society. Therefore, how to identify the high-risk areas of flood disasters is an important issue to be solved in the prevention of flood disasters. Taking Zhengzhou metropolitan area as the research object, based on the Urban Flood Risk Mitigation module of InVEST model, the vulnerability of flood disaster, the supply capacity of flood regulation service and the supply-demand ratio of ecosystem service in the study area are obtained through analysis, and the areas vulnerable to flood disaster in the study area are identified. The results show that : (1) The flood regulation service supply capacity is mainly manifested in the spatial distribution pattern of high in the west and low in the east. The northern Jiaozuo, northern Xinyang, western Zhengzhou and western Xuchang have higher supply service levels. (2) Affected by factors such as population density, economic development level and land use development degree, there are also obvious spatial differences in the spatial distribution of flood regulation service demand. The high demand area of flood regulation service is concentrated in the central urban area. (3) In areas with low population density and high vegetation coverage, the high supply and low demand of flood regulation services lead to a higher service supply-demand ratio. In the central urban area of the city, due to the large proportion of construction land and dense population, the supply and demand of services is relatively low.

Automated Hyperspectral Feature Selection and Classification of Wildlife Using Uncrewed Aerial Vehicles

Timely and accurate detection and estimation of animal abundance is an important part of wildlife management. This is particularly true for invasive species where cost-effective tools are needed to enable landscape-scale surveillance and management responses, especially when targeting low-density populations residing in dense vegetation and under canopies. This research focused on investigating the feasibility and practicality of using uncrewed aerial systems (UAS) and hyperspectral imagery (HSI) to classify animals in the wild on a spectral—rather than spatial—basis, in the hopes of developing methods to accurately classify animal targets even when their form may be significantly obscured. We collected HSI of four species of large mammals reported as invasive species on islands: cow (Bos taurus), horse (Equus caballus), deer (Odocoileus virginianus), and goat (Capra hircus) from a small UAS. Our objectives of this study were to (a) create a hyperspectral library of the four mammal species, (b) study the efficacy of HSI for animal classification by only using the spectral information via statistical separation, (c) study the efficacy of sequential and deep learning neural networks to classify the HSI pixels, (d) simulate five-band multispectral data from HSI and study its effectiveness for automated supervised classification, and (e) assess the ability of using HSI for invasive wildlife detection. Image classification models using sequential neural networks and one-dimensional convolutional neural networks were developed and tested. The results showed that the information from HSI derived using dimensionality reduction techniques were sufficient to classify the four species with class F1 scores all above 0.85. The performances of some classifiers were capable of reaching an overall accuracy over 98%and class F1 scores above 0.75, thus using only spectra to classify animals to species from existing sensors is feasible. This study discovered various challenges associated with the use of HSI for animal detection, particularly intra-class and seasonal variations in spectral reflectance and the practicalities of collecting and analyzing HSI data over large meaningful areas within an operational context. To make the use of spectral data a practical tool for wildlife and invasive animal management, further research into spectral profiles under a variety of real-world conditions, optimization of sensor spectra selection, and the development of on-board real-time analytics are needed.

Growth, Physiological, and Biochemical Variations in Tomatoes after Infection with Different Density Levels of Meloidogyne enterolobii.

Meloidogyne enterolobii is an extremely important plant parasitic nematode. Tomato (Solanum lycopersicum) is an essential worldwide vegetable, and M. enterolobii poses a major threat to its production. The present research investigated the effects of different levels of inoculum density of M. enterolobii (100, 500, 1000, 1500, and 2000 second-stage juveniles (J2s)/plant) on tomato growth, physiological, and biochemical changes at 7, 14, 21, and 28 days post-inoculation (dpi). The negative impact of M. enterolobii on plants gradually increased when the inoculum level increased. Therefore, M. enterolobii population densities (500-2000 J2s/plant) significantly (p < 0.05) reduced plant growth, photosynthetic pigmentation, gas exchange, and chlorophyll fluorescence compared to control plants, while the low population density (100 J2s/plant) showed very little influence. Furthermore, plants with the highest M. enterolobii inoculum (2000 J2s/plant) exhibited a greater number of egg masses and galls. The inoculum densities of M. enterolobii exhibited a notable correlation with the significant elevation of both malondialdehyde (MDA) and hydrogen peroxide (H2O2) levels, which are recognized as very detrimental stresses in plants. Similarly, a rise in the activity of several defensive antioxidant enzymes, namely superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD), indicates the defensive mechanism used to combat the oxidative destruction produced by M. enterolobii. The specific activity of glutathione (GSH) and ascorbate (ASA) increased as potent antioxidant defense molecules in response to induced oxidative damage. In addition, our findings also demonstrated that the highest population density (2000 J2s/plant) increased the secondary metabolites responsible for scavenging oxidative stress in the plants. However, further research is required to explore the underlying reasons for this phenomenon and to develop efficient chemical or biocontrol strategies for managing M. enterolobii.

THE INCLUSION OF DISASTER RISK REDUCATION IN CLASSROOM AND EXTRA-CURRICULAR ACTIVITIES: A CASE OF RURAL BALOCHISTAN, PAKISTAN

Purpose – Balochistan, which makes up roughly 44 percent of Pakistan’s total land area, is home to 6 percent of the nation’s inhabitants. Due to long distances and low population density, service delivery is particularly challenging. The province’s educational services are impacted by natural disasters like earthquakes, floods, droughts, and migration. Disaster risk reduction is a widely recognized concept that emphasizes appropriate education to lower an individual’s personal, familial, and communal vulnerability. The role of the school is crucial in Disaster Risk Reducation (DRR) education. As a result, the study’s goal was to explore the approaches adopted for the inclusion of DDR through teaching in classroom and school activities. Methodology – A focus group discussion with three groups of Pakistan studies and Geography teachers was conducted that consistedof 10 male and 14 female members. Findings – Findings demonstrate that the current textbook continues to teach students less about disaster risk reduction; teachers include knowledge from their personal experience in planning lessons about DRR. School assemblies, child clubs and activities designed by school management, and social organizations play a prominent role in DRR education. Further, the role of teachers and school management was identified in psycho-social support during disasters and pandemics. Significance – The study concludes that in addition to extracurricular activities and the teacher’s role, prior disaster experience, school, and social organization played a significant role in DRR education in rural Balochistan. The study results will assist curriculumdevelopers, policymakers, and education leadership in developing more effective school disaster management plans. The results willalso clarify how schools and teachers can close the knowledge gap in disaster preparedness education. Organizations working on disaster risk education and education in emergencies will also benefit from additional research to respond to the need readily and effectively.

Geohistorical changes and space exploration: a study of the Baikonur Cosmodrome

This study attempts to identify the geohistorical changes resulting from the establishment of space launch sites based on the experience of the Baikonur Cosmodrome. The concept of geohistory proposed by Braudel (2015, p.630), bibliographic information, memoirs of Soviet scientists and military officers, and official documents were used for the analysis. First, geographical and socio-political aspects related to the establishment of space launch centers were studied, such as proximity to the equator, low population density, and others. It turns out that the Baikonur region suited the interests of the Soviet government at the time, which led to the transformation of a desert region into a dynamic center of interstate disputes during the Cold War. After the end of the Soviet Union, changes in the socioeconomic conditions of the city and the cosmodrome led to a loss of dynamism in the region. Currently, environmental issues and the new techno-economic paradigms of the space sector pose challenges to the continued importance of the Baikonur space center.

The Automatic Context Measurement Tool (ACMT) to Compile Participant-Specific Built and Social Environment Measures for Health Research: Development and Usability Study.

The environment shapes health behaviors and outcomes. Studies exploring this influence have been limited to research groups with the geographic information systems expertise required to develop built and social environment measures (eg, groups that include a researcher with geographic information system expertise). The goal of this study was to develop an open-source, user-friendly, and privacy-preserving tool for conveniently linking built, social, and natural environmental variables to study participant addresses. We built the automatic context measurement tool (ACMT). The ACMT comprises two components: (1) a geocoder, which identifies a latitude and longitude given an address (currently limited to the United States), and (2) a context measure assembler, which computes measures from publicly available data sources linked to a latitude and longitude. ACMT users access both of these components using an RStudio/RShiny-based web interface that is hosted within a Docker container, which runs on a local computer and keeps user data stored in local to protect sensitive data. We illustrate ACMT with 2 use cases: one comparing population density patterns within several major US cities, and one identifying correlates of cannabis licensure status in Washington State. In the population density analysis, we created a line plot showing the population density (x-axis) in relation to distance from the center of the city (y-axis, using city hall location as a proxy) for Seattle, Los Angeles, Chicago, New York City, Nashville, Houston, and Boston with the distances being 1000, 2000, 3000, 4000, and 5000 m. We found the population density tended to decrease as distance from city hall increased except for Nashville and Houston, 2 cities that are notably more sprawling than the others. New York City had a significantly higher population density than the others. We also observed that Los Angeles and Seattle had similarly low population densities within up to 2500 m of City Hall. In the cannabis licensure status analysis, we gathered neighborhood measures such as age, sex, commute time, and education. We found the strongest predictive characteristic of cannabis license approval to be the count of female children aged 5 to 9 years and the proportion of females aged 62 to 64 years who were not in the labor force. However, after accounting for Bonferroni error correction, none of the measures were significantly associated with cannabis retail license approval status. The ACMT can be used to compile environmental measures to study the influence of environmental context on population health. The portable and flexible nature of ACMT makes it optimal for neighborhood study research seeking to attribute environmental data to specific locations within the United States.

Morbidity and Mortality of Birds of Prey Admitted to Rehabilitation Centers for Barbed Wire Injuries, New Mexico, USA, 2016-2021.

Interest in the role of fences in wildlife movement and injuries is growing, especially in the western US, where many miles of barbed wire fences crisscross the landscape. However, literature is limited on the effect of barbed wire on avian populations. From 2016 to 2021, six New Mexico, USA, rehabilitation centers accepted 49 raptors injured by barbed wire. Eight species were represented; the majority were Great Horned Owls (Bubo virginianus). Other owls, buteos, and a single falcon were also affected. Most of the injured birds came from counties with low human population density. The injuries tended to be severe, and most birds died or were euthanized; 11 survived, and only eight birds were released. During the study period, barbed wire injuries accounted for over 12% of Great-horned Owl admissions to rehabilitation centers and 7% of all owl admissions. At one New Mexican wildlife rehabilitation center, raptors admitted for barbed wire-associated injuries were more likely to die or be euthanized compared with those admitted for other reasons. Given the welfare effects to these birds, more research is needed to determine whether wildlife-friendly fence modifications, such as a smooth top wire or rail, would mitigate injuries to birds of prey.

Impact of spatial and temporal resource distribution on rabies dynamics in the Arctic

In the Arctic, rabies is endemic in the Arctic fox (Vulpes lagopus), posing a significant and ongoing health risk for people and domestic animals. The mechanisms by which rabies is maintained within the low-density fox populations in the Arctic remain unclear. In this study, we developed a spatially explicit individual-based stochastic epidemiological model and performed an uncertainty analysis to better understand Arctic fox rabies dynamics. Rabies persisted in 25.68% of model simulations, with several variables having significant impact on rabies persistence: probability of rabies transmission, spatial and temporal distribution food resources, mean litter size and variability of rabies incubation periods. Where rabies is endemic, we identified 5 key parameters for rabies dynamics: spatiotemporal resource distribution, probability of birth for adult females, mean and standard deviation of litter size, and incubation period of rabies. Our study demonstrates that Arctic rabies can persist in its primary host under conditions consistent with existing empirical data in the literature and showed the important role played by the spatial and temporal distribution of resources. Finally, our results suggest that the ecological impacts of rapid climate warming could decrease the overall persistence of rabies in the Arctic and the associated health risk in Arctic communities.

Inferring storefront vacancy using mobile sensing images and computer vision approaches

Storefront vacancy has been a widespread and worldwide phenomenon, raising concerns about the changing characteristic of the retail landscape, loss of community vitality, and hollowing out of cities. Although the causes leading to this phenomenon have been extensively debated, little granular data are available to evaluate the issue in a timely manner. Therefore, this study aims to develop a data-driven approach to capture the commercial structure of vacant storefronts on a store-by-store basis as well as to analyze their evolution patterns. First, street-level images were collected using mobile sensing in a low-cost, large-scale and efficient manner; then, a storefront vacancy estimation model was developed using computer vision techniques to infer the storefront location, operation status, business category, and vacancy rates. Three volunteers spent five days collecting street-level images from an urban area of 964 km2 in the case city of Xining, China. As a result, 93,069 stores were identified in the city in March 2022, of which 25,488 were vacant. Moreover, the storefront vacancy rate increased significantly after the epidemic, from 21.8% in 2018 to 30.0% in 2022. Stores in shopping, catering, and life services had the maximum vacancies. The factors that had the greatest impact on storefront vacancy were, in order of importance, far from commercial zonings, low population density, and far from the urban center. However, these factors influenced the vacancy in diverse and complex ways, and in the future, urban planning strategies to address vacancy issues should be well considered and differentiated.

Strengthening the Resilience and Perseverance of Rural Accommodation Enterprises in the Iberian Depopulated Areas through Enterprise Architecture

The research objective of this work is to develop and evaluate an enterprise architecture for rural accommodation in the Iberian Peninsula that responds to the demand of the remote labor market. Through an extensive literature review and the application of ArchiMate modeling, this study focuses on providing an enterprise architecture that promotes business resilience and environmental sustainability and boosts the local economy. The proposed enterprise architecture is remotely evaluated by experts, highlighting potential benefits, challenges, and areas for improvement. The results show that the proposed enterprise architecture has the potential to improve the long-term success of rural lodging businesses, enhance the customer experience, promote sustainability, and contribute to economic growth in rural areas through value exchange among stakeholders. The ArchiMate model provides a holistic perspective on stakeholder interactions and interoperability across all functional business areas: Customer Service, Product Management, Omnichannel Commerce, Human Resources, Business Strategy, Marketing, and Sustainability Management. The idea is to empower rural lodging businesses to create a better customer experience, achieve energy and environmental efficiency, contribute to local development, respond quickly to regulatory changes and compliance, and develop new revenue streams. The main goal is to improve offers, mitigate seasonal effects, and reverse the continuous cycle of decline in areas with low population density. Therefore, this ArchiMate modeling can be the initial basis for the digitization or expansion of the rural lodging industry in other geographies.

Dinophysis, a highly specialized mixoplanktonic protist

Several Dinophysis species produce lipophilic toxins (diarrhetic shellfish poisoning, DSP and pectenotoxins PTX) which are transferred through the food web. Even at low cell densities (&amp;lt; 103 cell L-1), they can cause human illness and shellfish harvesting bans; toxins released into the water may kill early life stages of marine organisms. Dinophysis species are mixotrophs: they combine phototrophy (by means of kleptoplastids stolen from their prey) with highly selective phagotrophy on the ciliate Mesodinium, also a mixotroph which requires cryptophyte prey of the Teleaulax/Geminigera clade. Life cycle strategies, biological interactions and plastid acquisition and functioning in Dinophysis species make them exemplars of resilient holoplanktonic mixoplankters and of ongoing speciation and plastidial evolution. Nevertheless, 17 years after the first successful culture was established, the difficulties in isolating and establishing cultures with local ciliate prey, the lack of robust molecular markers for species discrimination, and the patchy distribution of low-density populations in thin layers, hinder physiological experiments to obtain biological measurements of their populations and slow down potential advances with next-generation technologies. The Omic’s age in Dinophysis research has only just started, but increased efforts need to be invested in systematic studies of plastidic diversity and culture establishment of ciliate and cryptophyte co-occurring with Dinophysis in the same planktonic assemblages.

Mapping conservation priorities for wild yak (Bos mutus) habitats on the Tibetan Plateau, China

The wild yak (Bos mutus) is a cold-tolerant herbivore native to the Tibetan Plateau and has been categorized as vulnerable by the International Union for Conservation of Nature and Natural Resources. Low population densities within currently fragmented habitats and unclear landscape conservation priorities warrant attention. Herein, we employed the maximum entropy (MaxEnt) model using over 900 wild yak occurrence records to model wild yak habitat suitability. Our analysis revealed unprotected wild yak landscapes covering 30.79 % of the habitat area, indicating a conservation gap between protected areas (PAs) and wild yak habitats. To protect metapopulation dynamics and mitigate high risks of poaching, habitat degradation and fragmentation, resource competition, and degenerated genetic characterization of wild yaks in fragmented and degraded habitat, we identified eight habitat patches as landscape conservation units (LCUs) and 14 linkages among the LCUs, enhancing the connectivity between LCUs to decrease negative effects of genetic threats. A centrality analysis demonstrated that Changtang, Arjinshan, and Hoh Xil national nature reserves and their linkages are all critical for the maintenance of habitat connectivity. Here, we suggest that habitat- and LCU-specific conservation strategies should be highlighted during the establishment of PAs and transboundary cooperation. Ultimately, our results can assist conservationists and land managers in comprehending wild yak distribution, movement, and habitat requirements, as well as for the development of effective protection strategies. Furthermore, the combined modeling method (MaxEnt–Zonation–InVEST) could be utilized as a component for identifying conservation priorities and linkages between core patches for species and assessing the efficiency of PAs, core habitats, and corridors in achieving conservation goals. Our study can provide a framework in identifying priority conservation and connectivity between habitat patches to facilitate effectively conservation and genetic resilience for endangered species in fragmented habitats.

Cumulative trophic curves elucidate tropical coral reef ecosystems

There are few generalizable patterns in ecology, with widespread observations and predictability. One possible generalizable pattern is the cumulative trophic theory, which consistently exhibits S-curves of cumulative biomass over trophic level (TL) for over 200 different marine ecosystems. But whether those cumulative biomass patterns persist in some of the more distinct marine ecosystems, coral reefs, is unclear. Coral reefs are unique among marine ecosystems, representing global biodiversity hotspots and providing crucial ecosystem services. They are subject to many pressures, including both global (e.g., climate and ocean changes, warming, acidification) and local (e.g., overexploitation/overfishing, increase in turbidity, bleaching, habitat destruction, invasive species) stressors. The analysis of emergent ecosystem features, such as cumulative biomass S-curves, could represent a useful and new analytical option that can also be implemented for coral reefs. The cumulative biomass approach was applied to 42 U.S. Pacific islands (Guam and the Commonwealth of Northern Mariana Islands, American Samoa, the Pacific Remote Islands Areas, and the Northwestern and Main Hawaiian Islands), using data collected from fish surveys. Results show that coral reef ecosystems do indeed follow the S-curve patterns expected from cumulative trophic theory, which is not trivial for tropical reef systems that tend to be less widely examined and strongly dominated by structuring organisms like corals. The curve parameters results are also consistent with both fish assemblage diversity indexes and the benthic substrate ratio, which suggests this measure could serve as a useful ecosystem indicator to measure the ecological status of reefs. Moreover, the curve shape was consistent with what one would expect for different levels of perturbation, with the areas more densely inhabited showing less pronounced S-curves, in contrast to those observed in low human population density islands. All this is reflected in the curve parameters, particularly inflection point of the TL and steepness, generally showing a negative response to both natural and anthropogenic disturbances. Cross-archipelago differences have also been detected with the Hawaiian Island chain tending to have lower inflection points for biomass and TL than other regions. Collectively our findings demonstrate the potential application of the cumulative biomass approach to evaluate coral reef ecosystems.

Опыт оказания помощи больным с инсультом в телеконсультируемых первичных сосудистых отделениях в Свердловской области.

Introduction. One of the problems of providing specialized care for ischemic stroke is to achieve high rates of intravenous thrombolytic therapy (IVT) in areas characterized by low population density and large distance from the nearest stroke unit (delivery time more than 1 h). In Sverdlovsk region, in order to solve this problem in such territories, three teleconsulted stroke units equipped with CT scanners and having resuscitation beds were organized in 2021. Objective. To study the dynamics of the rates of intravenous thrombolytic therapy for ischemic stroke in the territories with a teleconsulted stroke units (in addition to the stroke unit). Materials and Methods. We retrospectively analyzed the data of 85 patients treated in three teleconsulted stroke units (teleSU) of the Sverdlovsk region in 2022 and compared the dynamics of the increase in the IVT rate (R parameter,%/year) in these territories in comparison with the rest of the municipalities of the Sverdlovsk region. Results. According to the results of the study, it was found that the rate of IVT in teleSU was 9,0%, which is generally higher than the average value in the Sverdlovsk Region (5,1%) in the analyzed period. The analysis of the statistical data from 2020 to 2022 revealed that establishment of additional teleconsulted stroke units in the territories with low population density in 2022 has led to the increase of the number of procedures of IVT for ischemic stroke. Dynamics of growth of this indicator, became equale of that in the rest of the municipalities of the region. Conclusions. The organization of teleSU in addition to the main SU in the territories with low population density allows to increase the availability of specialized medical care and to increase the IVT rate in patients with ischemic stroke.

Взаимосвязь воспроизводства населения с репродуктивным здоровьем женщин фертильного возраста в Красноярском крае.

Relevance. Problems of population reproduction and reproductive health of women of fertile age [1] attract much attention from both domestic and foreign researchers. Important demographic indicators that characterize population reproduction are fertility and mortality, the level of which significantly affects the population size, natural growth and determines the demographic situation not only of the territories, but also of the country as a whole [2]. Purpose of the study: to analyze literary sources and compare with official statistical data of the Krasnoyarsk Territory, both for the region with low population density, and separately for the western medical district of the Krasnoyarsk Territory, fertility rates, women’s reproductive health, the frequency of abortions and the number of births. Material and methods. For an objective assessment, information was taken from Rosstat for the Krasnoyarsk Territory and data from dashboards of the situation center of the Krasnoyarsk Territory, data from the state report on the state of public health and health care activities in the Krasnoyarsk Territory in 2022, a retrospective analysis of medical documentation and state statistics materials was carried out with copying data. Results of the study. Over the past three years, negative changes have emerged in the demographic development of the Russian Federation, expressed in a decrease in the number of births and an increase in the number of deaths. Total fertility rate in Russia in 2020. amounted to – 9.8‰, in 2021. – 9.6‰, in 2022 – 8.9‰. In the Krasnoyarsk Territory in 2020. – 10.1‰, 2021 – 10.0‰, 2022 – 9.9‰ [3]. The indicator both for the country as a whole and for the Krasnoyarsk Territory did not reach the following values: 1980. – 15.9‰ and 1990 – 13.4‰. In the western medical district of the Krasnoyarsk Territory, the birth rate in 2020–12.4‰, in 2021–12.2‰ and in 2022 amounted to 12.0‰. The average age of women giving birth in Russia is 26 years in 2022, in the Krasnoyarsk Territory in 2022 it was 29.2 years and in the western medical district of the region – 29.5 years. The share of premature births among women who completed pregnancy increased over 5 years by 11.2% and in 2022 amounted to 5.8% in the Krasnoyarsk Territory as a whole, and in the western medical district of the region 5.4%. Population reproduction is largely related to women’s reproductive health. Conclusions. The relationship between population reproduction and the reproductive health of women of fertile age in the Krasnoyarsk Territory has been established, based on a study of literature data and statistical data for a region with low population density.

Automated Large-Scale Tornado Treefall Detection and Directional Analysis Using Machine Learning

Abstract In many regions of the world, tornadoes travel through forested areas with low population densities, making downed trees the only observable damage indicator. Current methods in the EF scale for analyzing tree damage may not reflect the true intensity of some tornadoes. However, new methods have been developed that use the number of trees downed or treefall directions from high-resolution aerial imagery to provide an estimate of maximum wind speed. Treefall Identification and Direction Analysis (TrIDA) maps are used to identify areas of treefall damage and treefall directions along the damage path. Currently, TrIDA maps are generated manually, but this is labor-intensive, often taking several days or weeks. To solve this, this paper describes a machine learning– and image-processing-based model that automatically extracts fallen trees from large-scale aerial imagery, assesses their fall directions, and produces an area-averaged treefall vector map with minimal initial human interaction. The automated model achieves a median tree direction difference of 13.3° when compared to the manual tree directions from the Alonsa, Manitoba, tornado, demonstrating the viability of the automated model compared to manual assessment. Overall, the automated production of treefall vector maps from large-scale aerial imagery significantly speeds up and reduces the labor required to create a Treefall Identification and Direction Analysis map from a matter of days or weeks to a matter of hours. Significance Statement The automation of treefall detection and direction is significant to the analyses of tornado paths and intensities. Previously, it would have taken a researcher multiple days to weeks to manually count and assess the directions of fallen trees in large-scale aerial photography of tornado damage. Through automation, analysis takes a matter of hours, with minimal initial human interaction. Tornado researchers will be able to use this automated process to help analyze and assess tornadoes and their enhanced Fujita–scale rating around the world.

Reduced gene flow and bottleneck in the threatened giant armadillo (Priodontes maximus): implications for its conservation.

The progressive fragmentation and loss of habitats represent the main threats for endangered species, causing genetic consequences that may have potential implications for a population's long-term persistence. Large mammals are the most affected species among vertebrates. The giant armadillo Priodontes maximus is a large South American mammal threatened species, showing nocturnal, solitary and fossorial behavior, occurring at low population densities, and its population dynamics are still poorly known. In this study, we carried out the first assessment of genetic variability and population genetic structure of the species, using a panel of 15 polymorphic microsatellites developed by high-throughput genome sequencing. The spatial Bayesian clustering, Fst and Dest results indicated the presence of two genetic clusters (K = 2) in the study area. These results suggest a reduction in gene flow between individuals inhabiting the Brazilian savanna (Cerrado) and the Pantanal wetlands, with the increased human-driven habitat modifications possibly contributing for this scenario. A bottleneck signal was detected in both populations, and a subpopulation structuring in the Cerrado may also be reflecting consequences of the extensive habitat modifications. Findings from this study provide important and useful information for the future maintenance of genetic diversity and long-term conservation of this flagship species.

The incidence, and spatial trends of cholera in Sabah over 15 years: Repeated outbreaks in coastal areas.

Vibrio cholerae remains a notable public health challenge across Malaysia. Although the Malaysian state of Sabah is considered a cholera-affected area, gaps remain in understanding the epidemiological trends and spatial distribution of outbreaks. Therefore, to determine longitudinal and spatial trends in cholera cases data were obtained from the Sabah State Health Department for all notified cases of cholera between 2005-2020. A cholera outbreak is defined as one or more confirmed cases in a single locality with the evidence of local transmission. All records were geolocated to village level. Satellite-derived data and generalised linearized models were used to assess potential risk factors, including population density, elevation, and distance to the sea. Spatiotemporal clustering of reported cholera cases and zones of increased cholera risk were evaluated using the tau statistic (τ) at 550m, 5km and 10km distances. Over a 15-year period between 2005-2020, 2865 cholera cases were recorded in Sabah, with a mean incidence rate of 5.6 cases per 100,000 (95% CI: 3.4-7.9). From 2015-2020, 705 symptomatic cases and 727 asymptomatic cases were reported. Symptomatic cases primarily occurred in local Malaysian populations (62.6%, 441/705) and in children and adolescents under 15-years old (49.4%, 348/705). On average, cases were reported in areas with low population density (19.45 persons/km2), low elevations (19.45m) and near coastal areas. Spatiotemporal clustering of cholera cases was identified up to 3.5km, with increased village-level cholera risk within 500m and 5 days of initial case presentation to a health facility (Risk Ratio = 9.7, 95% CI: 7.5-12.4). Cholera incidence has high spatial and temporal heterogeneity within Sabah, with some districts experiencing repeated outbreaks. Cholera cases clustered across space and time, with village-level risk of cholera highest within 5 days and within close proximity to primary case villages, suggesting local transmission.

«Ядро-периферия» и периферийность в региональной науке

The article presents an analytical review of the development of the core-periphery and peripherality concepts in economic theory. The stages of formation of the core-periphery approach are marked by the contributions of the school of Latin American structuralism, theories of polarized development, dependency theory and world-system theory associated with the names of R. Prebisch, J. Friedmann, F. Perroux, S. Furtado, I. Wallerstein. The core-periphery concept has proved to be a useful analytical tool in studies of international trade and economic growth in the world economy. At the same time, uneven structures of distribution of economic activity in space, similar to the core-periphery structure, appear in many models of regional economy, starting with the model of agricultural production location by I. Thunen and ending with the core-periphery model by P. Krugman. These structures emerge without the help of the core-periphery concept, but as a result of the interaction of two fundamental factors – transport costs and economies of scale – and represent various combinations of dispersion and agglomeration. With regional inequality growing worldwide, the combination of the core-periphery approach and basic concepts of regional economics allows us to analyze the complex mechanisms of spatial polarization of economic space. Over time, the periphery has gone beyond the core-periphery dichotomy and developed into an independent category defined, defined by a combination of low accessibility of large markets, low population density and remoteness from decision-making centers. The concept of peripherality allows us to understand the processes of peripheralisation of previously prosperous territories through the interaction of power asymmetry and agglomeration effects