Proximity to urban fringe recreational facilities increases native biodiversity in an arid rangeland

© 2018 Australian Rangeland Society. Urban developments affect neighbouring ecosystems in multiple ways, usually decreasing native biodiversity. Arabian arid rangeland was studied to identify the primary causes of biodiversity variation. Al Marmoum is a 990 km2 area on the urban edge of Dubai, designated for ecological \u27enhancement\u27 and outdoor recreational use. The area lacks historical biodiversity data, but is thought to be primarily influenced by Arabian camel (Camelus dromedarius Linnaeus, 1758) herbivory. Perennial floral and faunal diversity was assessed at 54 sites. Counts of reintroduced ungulates (Arabian oryx Oryx leucoryx (Pallas, 1777), Arabian gazelle Gazella gazella cora (C.H. Smith, 1827) and sand gazelle G. subgutturosa marica (Thomas, 1897)) were made at 79 separate sites. Correlations of observed biodiversity with substrate type, anthropogenic structures, and ungulate distribution were assessed. Native biodiversity was substantially higher in north-north-west locations near recreational facilities, with the most likely cause being differential browsing pressure. Camel browsing faced greater communal regulation in the north-north-west, whereas oryx and gazelles congregated at feed points in the south-south-east that were farther from human activity. Arid rangeland in this socioecological landscape exhibits greater natural biodiversity at the urban fringe. Human activity reduces ungulate density, enabling a greater diversity of perennial flora, which then attracts non-ungulate fauna. Anthropogenic features can therefore offer conservation value in landscapes where ungulate populations are artificially elevated

Deep Learning based Animal Detection and Tracking in Drone Video Footage

In this paper, we propose a multiple animal tracking system in drone footage that is designed and implemented using a Deep Neural Network (DNN) based tracking-by-detection approach. The proposed system consists of two main components, namely the sub-system for animal detection, and the sub-system for animal tracking. In the animal detection component, we exploit the effective use of YOLO-V5 to detect individual animals and in the tracking component, we use a centroid tracking algorithm to associate the location of the detected animals in consecutive video frames. The performance of the proposed system is analyzed on drone video footage containing herds of Arabian Oryx with complex patterns of movement of individual animals. All videos were recorded by using a drone flying over known oryx feeding points in the desert areas of the UAE. The experimental results showed that our tracking system can detect and track individual oryxes within herds, accurately, even when the oryxes are very close to each other, partially occluded and their walking paths cross each other

Crimean-Congo hemorrhagic fever virus endemicity in United Arab Emirates, 2019

© 2020 Centers for Disease Control and Prevention (CDC). All rights reserved. We conducted a cross-sectional survey of Crimean-Congo hemorrhagic fever virus (CCHFV) in dromedary camels and attached ticks at 3 locations in the United Arab Emirates. Results revealed a high prevalence of CCHFV-reactive antibodies in camels and viral RNA in ticks and camel serum, suggesting the virus is endemic in this country

Hyper-arid tall shrub species have differing long-term responses to browsing management

© 2019, © 2019 Taylor & Francis Group, LLC. Hyper-arid rangeland vegetation is typically dominated by large woody species which are often overlooked in herbivory studies. Long-term responses of tall shrub populations to herbivory change are poorly understood in the Arabian Peninsula. Population and size of 1559 individuals from four shrub species were assessed over an 11-year period under two herbivory regimes, one in which domestic livestock (camels) were replaced by semi-wild ungulates (Oryx and gazelles) before, and the other during, the study period. Each shrub species exhibited a different response to the change in herbivory. Populations of Calotropis procera decreased dramatically. Populations of both Calligonum polygonoides and Lycium shawii increased through sexual reproduction, but the spatial distribution of recruits indicated different modes of seed dispersal. Average lifespans were estimated at 22 and 20years respectively. The persistence strategy of Leptadenia pyrotechnica was similar to tree species of this habitat in that vegetative regrowth was prioritized over recruitment, and average lifespan was estimated at 95years. Shrub responses to changes in ungulate management are therefore species-specific. The response of individual plant size was faster than the response of population size, which was limited by slow sexual recruitment (L. pyrotechnica) or localized seed dispersal (C. polygonoides)

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

A first update on mapping the human genetic architecture of COVID-19

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Conservation of Biodiversity in Hyper-arid Commodified Protected Areas Under Grazing Pressure in Dubai (United Arab Emirates).

También muestra cómo la principal causa de degradación, perturbación y pérdida de biodiversidad de los ecosistemas de Arabia es la herbívora de libre acceso. Se estudia cómo la actividad humana en las zonas desérticas protegidas especialmente designadas para la “mejora” ecológica y el uso recreativo al aire libre (Reserva de Conservación Al Al Marmoum Dubäi) reduce la densidad de población de ungulados criados artificialmente (camellos, orix y gacelas) y por tanto la presión del pastoreo facilitando una mayor diversidad de flora perenne y en consecuencia un aumento de la biodiversidad. Finalmente, se estudian las respuestas individuales y de las poblacionales a largo plazo de grandes arbustos dominantes en el desierto (Calotropis procera, Calligonum polygoides, Lycium shawii y Leptadenia pyrotechnica) a los cambios en los regímenes herbívoros: ganado doméstico (camellos) reemplazado por ungulados semisalvajes (orix y gacelas) en ecosistemas desérticos de Dubäi (EAU). Puntos destacados: - Cómo la importancia de la función y el desarrollo de la Dubäi Desert Conservation Reserve (DDCR), un área protegida desértica sometida al impacto del pastoreo de ungulados y camellos, se ve facilitada por la mercantilización resultante de la construcción de un centro turístico de lujo (Al Maha Resort), - Cómo la actividad humana en el área protegida de Al Marmoum Dubäi, el área protegida más grande de Dubái, reduce la densidad de población de ungulados artificialmente elevados (orix, gacelas y camellos) facilitando el aumento de plantas y fauna nativas perennes; y, -Cómo los cambios en los regímenes herbívoros: el ganado doméstico (camellos) reemplazado por ungulados semisalvajes (orix y gacelas) resultan en una dramática disminución de la población de Calotropis procera, c-omo Leptadenia pyrotechnica prioriza el rebrote vegetativo y las poblaciones de Calligonum polygonoides y Lycium. shawii aumentan a través de la reproducción sexual, pero la distribución espacial de sus plantúlas varía y depende de los modos de dispersión de semillas de los arbustos estudiados.En los ecosistemas áridos desérticos, debido a las duras condiciones naturales y al impacto de causas antropogénicas, la biodiversidad está constantemente amenazada, lo que en ocasiones podría conducir a la extinción de especies. Todos los países productores de petróleo del Golfo de Arabia se están desarrollando rápidamente, lo que conduce a una expansión de las actividades humanas que amenaza a las poblaciones de vida silvestre. La memoria de doctorado que lleva por título: CONSERVACIÓN DE LA BIODIVERSIDAD EN ÁREAS PROTEGIDAS MERCANTILIZADAS HIPERÁRIDAS BAJO PRESIÓN DE PASTOREO EN DUBÄI, EMIRATOS ÁRABES UNIDOS (EAU) se llevó a cabo en Al Marmoom Reserva y en la Reserva de Conservación del Desierto de Dubäi, que son la primera y segunda áreas protegidas (AP) más grandes del Emirato de Dubäi. respectivamente. La DDCR está ubicada en la parte sureste del Emirato de Dubäi, se extiende hacia el norte cerca de la frontera del Emirato de Sharjah, y es el entorno biológicamente más diverso y próspero del Emirato de Dubäi. Al Marmoon está situado en la zona desértica de Saih Al Salam, que se extiende a lo largo de las arenas del vasto desierto. La memoria de doctorado describe la Reserva de Conservación del Desierto de Dubäi (DDCR), un área protegida en el Emirato de Dubäi, como un modelo de gestión eficaz para la conservación de la biodiversidad en áreas protegidas mercantilizadas desérticas en regiones desérticas como los Emiratos Árabes Unidos (EAU). El proceso de mercantilización de la naturaleza y el paisaje es una continuación y evolución de la transformación capitalista instigada por el uso comercializable de tierras protegidas, donde las prácticas de cría de camellos son la actividad dominante en esta transformación. La creación de la DDCR garantiza el futuro de los hábitats desérticos y la gestión de la biodiversidad de acuerdo con principios ecológicos científicos para proteger el patrimonio de las actividades tradicionales reconocidas por las Naciones Unidas

Shrub species exhibit differing long-term responses to a change in the species of ungulate browsing

Hyper-arid rangeland vegetation is typically dominated by large woody species which are often overlooked in herbivory studies. Knowledge of long-term large shrub population responses to change in browsing system in the Arabian Peninsula has been anecdotal. Population and size of 1559 individuals from four shrub species were opportunistically assessed over an 11-year period under two browsing regimes, one in which domestic livestock (camels) were replaced by semi-wild ungulates (oryx and gazelles) before, and the other during, the study period. Each shrub species exhibited a different response to the change in herbivory. Populations of Calotropis procera decreased dramatically. Populations of both Calligonum comosum and Lycium shawii increased through sexual reproduction, but the spatial distribution of recruits indicated different modes of seed dispersal. Average lifespans were estimated at 22 and 20 years respectively. The strategy of Leptadenia pyrotechnica was similar to tree species of this habitat, prioritizing vegetative regrowth, and average lifespan was estimated at 95 years. Hyper-arid large shrub populations may take many decades to adjust to a major change of browsing regime if they have adopted a vegetative method of persistence, though the size of surviving individuals may adjust relatively quickly.peerReviewe

Ghaf Tree Detection from Unmanned Aerial Vehicle Imagery Using Convolutional Neural Networks

The Ghaf is a drought-resilient tree native to some parts of Asia and the Indian Subcontinent, including the United Arab Emirates (UAE). To the UAE, the Ghaf is a national tree, and it is regarded as a symbol of stability and peace due to its historical and cultural importance. Due to increased urbanization and infrastructure development in the UAE, the Ghaf is currently considered an endangered tree, requiring protection. Utilization of modern-day aerial surveillance technologies in combination with Artificial Intelligence (AI) can particularly be useful in keeping count of the Ghaf trees in a particular area, as well as continuously monitoring unauthorized use to feed animals and to monitor their health status, thereby aiding in their preservation. In this paper, we utilize one of the best Convolutional Neural Networks (CNN), YOLO-V5, based model to effectively detect Ghaf trees in images taken by cameras onboard light-weight, Unmanned Aircraft Vehicles (UAV), i.e. drones, in some areas of the UAE. We utilize a dataset of over 3200 drone captured images partitioned into data-subsets to be used for training (60%), validation (20%), and testing (20%). Four versions of YOLO-V5 CNN architecture are trained using the training data subset. The validation data subset was used to fine tune the trained models in order to realize the best Ghaf tree detection accuracy. The trained models are finally evaluated on the reserved test data subset not utilized during training. The object detection results of the Ghaf tree detection models obtained by the use of four different sub-versions of YOLO-V5 are compared quantitatively and qualitatively. YOLO-V5x model produced the highest average detection accuracy of 81.1%. In addition, YOLO-V5x can detect and locate Ghaf trees of different sizes moreover in complex natural environments and in areas with sparse distributions of Ghaf trees. The promising results presented in this work offer fundamental grounds for AI-driven UAV applications to be used for monitoring the Ghaf tree in real-time, and thus aiding in its preservation

Deep Neural Networks Based Multiclass Animal Detection and Classification in Drone Imagery

There is a growing interest among the research community in the search for possible technology-driven strategies for the conservation of the much-needed, historically rich and culturally important, desert life. In this work, we investigate the use of one of the best available Deep Neural Networks, YOLO Version-5 (v5), to enable offline detection, identification and classification of three popular desert animals (i.e Camels, Oryxes, and Gazelles) in a Drone Imagery Dataset captured by the Dubai Desert Conservation Reserve (DDCR), United Arab Emirates. The dataset contains over 1200 images, which were partitioned into training, validation, and testing data sub-sets in a 8:1:1 ratio, respectively. We trained three multi-class models, animal classification models, based on YOLO v5 Small(S), Medium(M) and Large(L), representing increasingly deep and complex architectures, to simultaneously detect and label the 3 kinds of animals. Models\u27 performance was compared on the basis of classification accuracy (F1-Measure), The multi-class detector models generated were also compared with the single animal detector models created using the same network architectures, to assess the trained network\u27s robustness against detecting more than one class of object. YOLO v5 L achieved the highest multi-class average classification accuracy of 96.71 percent (95.39 - 98.98). In comparison with the single animal detector models, the multi-class models exhibited the ability to correctly detect the target objects even for cases where the objects are located close to each other. We show that the promising results achieved in this work provide a promising foundation for the development of real-time multiclass identification and classification applications utilizing UAV imagery, to aid in the conservation efforts of fauna, particularly in the urbanized modern-day deserts and semi-desert places, such as the DDCR. We provide comprehensive test results and an analysis of results to demonstrate the effectiveness of the proposed models