Fennec Fox Research Articles

The comparative morphology of the oral cavity glands in captive South African painted dogs (Lycaon pictus pictus) and captive fennec foxes (Vulpes zerda) (Carnivora: Canidae)

BackgroundThe African painted dog is classified as a relic canid lineage, inhabiting areas south of the Sahara. The fennec fox is the smallest member of the Canidae family, found in the Arabian Peninsula and northern Sahara.MethodsThe gross anatomy and light microscopic examination of the oral cavity glands were studied in five adult captive South African painted dogs and five adult captive fennec foxes from the Wroclaw Zoological Garden, Poland. In this research, the zygomatic gland, monostomatic sublingual gland, polystomatic sublingual gland, mandibular gland, and parotid gland were examined for their topography, morphometry, histology, and histochemistry using hematoxylin and eosin, azan trichrome, mucicarmine, PAS, AB pH 1.0, AB pH 2.5, AB pH 2.5 PAS, and HID.ResultsWe found that the parotid glands were consistently the largest, followed by the mandibular and sublingual glands (both monostomatic and polystomatic). The zygomatic gland was the smallest in both South African painted dogs and fennec foxes. Interestingly, there were noticeable differences in the size, shape, and even composition of the secretory products between the two species. The zygomatic and polystomatic sublingual glands in the South African painted dog and the fennec fox were complex branched tubular. In the South African painted dog, the monostomatic gland was a branched tubular compound gland, while in the fennec fox, it was a branched tubuloalveolar compound gland. The mandibular gland in hunting dogs was a branched tubular compound gland, while in the fennec fox a branched tubuloalveolar compound gland. The parotid gland in the fennec fox was a branched acinar compound gland, whereas in the painted dog was a branched tubuloacinar.ConclusionsThe basic structure of their glands is similar to that of other terrestrial carnivores, indicating a shared evolutionary origin and function. However, differences in the composition of their secretory products can reflect adaptations to their specific diets. This research provides valuable insights for veterinary medicine and underscores the importance of further studies. By analyzing wild canid populations and including a broader range of species with diverse diets, we could gain a deeper understanding of how diet influences salivary gland morphology within the Canidae.

Global MPPT based on Fennec Fox algorithm for control of photovoltaic systems

Global MPPT based on Fennec Fox algorithm for control of photovoltaic systems

Multi-Energy Load Prediction Method for Integrated Energy System Based on Fennec Fox Optimization Algorithm and Hybrid Kernel Extreme Learning Machine.

To meet the challenges of energy sustainability, the integrated energy system (IES) has become a key component in promoting the development of innovative energy systems. Accurate and reliable multivariate load prediction is a prerequisite for IES optimal scheduling and steady running, but the uncertainty of load fluctuation and many influencing factors increase the difficulty of forecasting. Therefore, this article puts forward a multi-energy load prediction approach of the IES, which combines the fennec fox optimization algorithm (FFA) and hybrid kernel extreme learning machine. Firstly, the comprehensive weight method is used to combine the entropy weight method and Pearson correlation coefficient, fully considering the information content and correlation, selecting the key factors affecting the prediction, and ensuring that the input features can effectively modify the prediction results. Secondly, the coupling relationship between the multi-energy load is learned and predicted using the hybrid kernel extreme learning machine. At the same time, the FFA is used for parameter optimization, which reduces the randomness of parameter setting. Finally, the approach is utilized for the measured data at Arizona State University to verify its effectiveness in multi-energy load forecasting. The results indicate that the mean absolute error (MAE) of the proposed method is 0.0959, 0.3103 and 0.0443, respectively. The root mean square error (RMSE) is 0.1378, 0.3848 and 0.0578, respectively. The weighted mean absolute percentage error (WMAPE) is only 1.915%. Compared to other models, this model has a higher accuracy, with the maximum reductions on MAE, RMSE and WMAPE of 0.3833, 0.491 and 2.8138%, respectively.

High-resolution computed tomographic (HRCT) image series from 413 canid and 18 felid skulls

Computed tomography (CT) is a non-invasive, three-dimensional imaging tool used in medical imaging, forensic science, industry and engineering, anthropology, and archaeology. The current study used high-resolution medical CT scanning of 431 animal skulls, including 399 dog skulls from 152 breeds, 14 cat skulls from 9 breeds, 14 skulls from 8 wild canid species (gray wolf, golden jackal, coyote, maned wolf, bush dog, red fox, Fennec fox, bat-eared fox), and 4 skulls from 4 wild felid species (wildcat, leopard, serval, caracal). This comprehensive and unique collection of CT image series of skulls can provide a solid foundation not only for comparative anatomical and evolutionary studies but also for the advancement of veterinary education, virtual surgery planning, and the facilitation of training in sophisticated machine learning methodologies.

DEMFFA: a multi-strategy modified Fennec Fox algorithm with mixed improved differential evolutionary variation strategies

The Fennec Fox algorithm (FFA) is a new meta-heuristic algorithm that is primarily inspired by the Fennec fox's ability to dig and escape from wild predators. Compared with other classical algorithms, FFA shows strong competitiveness. The “No free lunch” theorem shows that an algorithm has different effects in the face of different problems, such as: when solving high-dimensional or more complex applications, there are challenges such as easily falling into local optimal and slow convergence speed. To solve this problem with FFA, in this paper, an improved Fenna fox algorithm DEMFFA is proposed by adding sin chaotic mapping, formula factor adjustment, Cauchy operator mutation, and differential evolution mutation strategies. Firstly, a sin chaotic mapping strategy is added in the initialization stage to make the population distribution more uniform, thus speeding up the algorithm convergence speed. Secondly, in order to expedite the convergence speed of the algorithm, adjustments are made to the factors of the formula whose position is updated in the first stage, resulting in faster convergence. Finally, in order to prevent the algorithm from getting into the local optimal too early and expand the search space of the population, the Cauchy operator mutation strategy and differential evolution mutation strategy are added after the first and second stages of the original algorithm update. In order to verify the performance of the proposed DEMFFA, qualitative analysis is carried out on different test sets, and the proposed algorithm is tested with the original FFA, other classical algorithms, improved algorithms, and newly proposed algorithms on three different test sets. And we also carried out a qualitative analysis of the CEC2020. In addition, DEMFFA is applied to 10 practical engineering design problems and a complex 24-bar truss topology optimization problem, and the results show that the DEMFFA algorithm has the potential to solve complex problems.

Balancing data privacy and sharing in IIoT: Introducing the GFL-LFF aggregation algorithm

As the Industrial Internet of Things (IIoT) continues to evolve, the need for effective data aggregation schemes that balance the imperatives of data sharing and individual data privacy becomes paramount. Traditional data aggregation methods often entail risks of sensitive information exposure during data transmission and storage. This paper proposes a novel Graphical Federated Learning-based Local Fennec Fox (GFL-LFF) algorithm to ensure secure aggregation by minimizing the revelation of individual data. In this study, a Graph Neural Network (GNN) with federated learning is employed to enhance privacy protection for IIoT's data aggregation scheme. A Local search-based fennec fox optimization is utilized for tuning the parameters of GNN. The GFL and LFF approaches are integrated to enhance the security of the data that can be shared through the IIoT system. The MNIST dataset, CIFAR-10 dataset, and LFW dataset were taken to conduct the experimentation results, and the evaluation measures, such as throughput, end-to-end delay, network lifetime, latency, and energy consumption, are utilized to evaluate the proposed GFL-LFF method, and these results are compared with other approaches. The GFL-LFF method achieved a throughput of 0.98 Mbps, an end-to-end delay of 1.2 s, a network lifetime of 5610 rounds, a latency of 1.6 s, and an energy consumption of 0.2 mJ. The experimental results illustrate the effectiveness of the proposed GFL-LFF method for IIoT's data aggregation scheme in privacy protection.

Comparative anatomy of the caudate nucleus in canids and felids: Associations with brain size, curvature, cross-sectional properties, and behavioral ecology.

The evolutionary history of canids and felids is marked by a deep time separation that has uniquely shaped their behavior and phenotype toward refined predatory abilities. The caudate nucleus is a subcortical brain structure associated with both motor control and cognitive, emotional, and executive functions. We used a combination of three-dimensional imaging, allometric scaling, and structural analyses to compare the size and shape characteristics of the caudate nucleus. The sample consisted of MRI scan data obtained from six canid species (Canis lupus lupus, Canis latrans, Chrysocyon brachyurus, Lycaon pictus, Vulpes vulpes, Vulpes zerda), two canid subspecies (Canis lupus familiaris, Canis lupus dingo), as well as three felids (Panthera tigris, Panthera uncia, Felis silvestris catus). Results revealed marked conservation in the scaling and shape attributes of the caudate nucleus across species, with only slight deviations. We hypothesize that observed differences in caudate nucleus size and structure for the domestic canids are reflective of enhanced cognitive and emotional pathways that possibly emerged during domestication.

Parameter Extraction of Single, Double, and Triple-Diode Photovoltaic Models Using the Weighted Leader Search Algorithm.

This study presents the parameter extraction of single, double, and triple-diode photovoltaic (PV) models using the weighted leader search algorithm (WLS). The primary objective is to develop models that accurately reflect the characteristics of PV devices so that technical and economic benefits are maximized under all constraints. For this purpose, 24 models, 6 for two different PV cells, and 18 for six PV modules, whose experimental data are publicly available, are developed successfully. The second objective of this research is the selection of the most suitable algorithm for this problem. It is a significant challenge since the evaluation process requires using advanced statistical tools and techniques to determine the reliable selection. Therefore, seven brand-new algorithms, including WLS, the spider wasp optimizer, the shrimp and goby association search, the reversible elementary cellular automata, the fennec fox optimization, the Kepler optimization, and the rime optimization algorithms, are tested. The WLS has yielded the smallest minimum, average, RMSE, and standard deviation among those. Its superiority is also verified by Friedman and Wilcoxon signed-rank test based on 144 pairwise comparisons. In conclusion, it is demonstrated that the WLS is a superior algorithm in PV parameter extraction for developing accurate models.

A hybrid fennec fox and sand cat optimization algorithm for clustering scheme in VANETs

The popularity of intelligent vehicles with cutting-edge vehicular applications has fueled the rapid expansion of Vehicular Ad hoc Networks (VANETs) in recent years. VANETs are a network of vehicles designed to exchange and explore real-time data using a well-developed and effectively organized data transport technology. However, the major issue of dynamic topology and cluster stability always has an impact on choosing an optimal path between the cars. At this point, an intelligent clustering technique in VANETs that handles dynamic topology and cluster stability is critical for efficient route selection between vehicular nodes. This is an NP-hard issue that can be effectively solved using an intelligent nature-inspired algorithm that can discover near-optimal solutions in the search space. An Intelligent Hybrid Fennec Fox and Sand Cat Optimization Algorithm (HFFSCOA) -Based Clustering Scheme is proposed in this paper as a novel route clustering optimization strategy that takes grid size, orientation, velocity node density, and communication range into account while achieving its goal. This HFFSCOA contributed to the route clustering process, which determines dependable and optimal routes between vehicular nodes for the purpose of building and evaluating ideal Cluster Heads (CHs) in the network. HFFSCOA's findings clearly demonstrated its usefulness and efficacy in terms of the number of vehicles, network size, changeable communication ranges, and number of clusters built in the network. The statistical results of HFFSCOA also confirmed an enhanced cluster Optimization rate of 56.21% and an increased cluster stability of 92.34.

A State-of-Health Estimation Method for Lithium Batteries Based on Fennec Fox Optimization Algorithm–Mixed Extreme Learning Machine

A reliable and accurate estimation of the state-of-health (SOH) of lithium batteries is critical to safely operating electric vehicles and other equipment. This paper proposes a state-of-health estimation method based on fennec fox optimization algorithm–mixed extreme learning machine (FFA-MELM). Firstly, health indicators are extracted from lithium-battery-charging data, and grey relational analysis (GRA) is employed to identify highly correlated features with the state-of-health of the battery. Subsequently, a state-of-health estimation model based on mixed extreme learning machine is constructed, and the hyperparameters of the model are optimized using the fennec fox optimization algorithm to improve estimation accuracy and convergence speed. The experimental results demonstrate that the proposed method has significantly improved the accuracy of the state-of-health estimation for lithium batteries compared to the extreme learning machine. Furthermore, it can achieve precise state-of-health estimation results for multiple batteries, even under complex operating conditions and with limited charge/discharge cycle data.

Assessing animal biodiversity in Nafud al-ʽUrayq natural reserve, Qassim region, Saudi Arabia: A preliminary study

Nafud al-ʽUrayq is a protected natural reserve, it is located in the arid zone in central Saudi Arabia's Qassim area, covering 2036.1 square kilometers, and gained protected status in 1995. Only during two months, we roughly documented the status of 15 species belonging to three major taxonomic classes of animals, which include reptiles, birds, and mammals, including the sand boa, the Saudi fringe-fingered lizard, the Arabian fringe-fingered lizard, and the Egyptian mastigure. Three mammal species were observed, namely the fennec fox, the sand cat, and the gerbil. Birds constituted the most diverse group, with a total of eight species recorded, including the hoopoe, lesser sand plover, Egyptian nightjar, Lanner falcon, Great bustard, Bonelli's eagle, Yemen serin, and the hoopoe lark. The study recommends further research to monitor and identify all vertebrates and invertebrates residing in the reserve due to the lack of precise data about them. The study also advises the preservation of the environment for these animals and the introduction of more wildlife into the reserve while considering ecological balance criteria.

Da-resbigru -brain tumor classification using Dual attention residual bi directional gated recurrent unit using MRI images

Brain tumors are a major health issue that causes enormous problems for people’s health. Detection is a very complicated process of classifying tumor types, where early detection can fix the problem as soon as possible. Manual diagnosis and detection pose a risk to human life. In addition, the classification of malignant tumors and gliomas is difficult due to the asymmetric or uneven boundary of the skull. For resolving the classification issues, the Dual Attention method based on the Resnet-50 with bidirectional gated recurrent unit (DA_ResBiGRU) model is proposed. Firstly, MRI images are pre-processed using Advanced Median Filter (AMF), and then the pre-processed data is transferred to the feature extraction phase. Significant features are extracted using Convolutional Neural Network (CNN), Haralick Texture Features and Speed-up Robust Features (SURF). Using the extracted features, optimized features are retrieved further by the Enhanced Fennec Fox Optimization (IFFO) algorithm. Here, brain tumor classification datasets and Figshare datasets are used for experimental analysis. Performance metrics like accuracy, F1 score, recall, precision, etc., are used to study the model performance. The proposed model achieves 98.53% accuracy, 97.7% precision, 97% recall, and 98% F1 score in brain tumor classification datasets, and 99.3% accuracy, 98.8% precision, 98.8% recall and 98.7% at F1 score are achieved in Figshare dataset. The values ​​obtained show that the proposed model overtakes other models.

Gastrointestinal and respiratory parasites in captive mammals at Rabat zoo, with the first record of Capillaria spp. in the Fennec fox (Vulpes zerda).

The aim of the present study was to broaden the understanding of parasitism in captive wild mammals in Morocco. For this purpose, an investigation on gastrointestinal and respiratory parasites in African mammals from Rabat Zoo was carried out. A total of 47 fecal samples were collected from 30 species from November 2021 to March 2022 and examined macroscopically and microscopically. Parasites were detected in 21 species at a prevalence of 70%, with a parasite positivity rate of 89% in artiodactyls, 50% in perissodactyls, 67% in both carnivores and primates. No parasitic infection was detected in proboscideans. The most frequent infection was by nematodes with a percentage of 50%, followed by both protozoa and mixed infection with a prevalence of 10%. In conclusion, the results demonstrated that parasite prevalence remains high, even in enclosed spaces like zoos. Therefore, in order to ensure animal welfare and staff safety, sanitary measures should be implemented in such facilities, including routine diagnostic tests followed by appropriate treatment.

Factors influencing the timing and frequency of litters in captive fennec foxes (Vulpes zerda)

Maintaining reproductive seasonality can be vital to the fitness of wild animals. Certain species, however, may display aseasonal reproduction and may produce multiple yearly litters when maintained in captivity. Wild fennec foxes (Vulpes zerda), for example, produce a single litter in March or April although their reproductive behaviors are reportedly variable in captivity. Here, we used the fennec fox studbook to extract traits related to reproductive variability in 220 captive-born litters. The captive litters in our dataset were born during every month of the year and nearly half (47%) were born outside of the expected months. The production of multiple litters in a single year was common, where 67% of the litters represented a second annual litter for a given dam. We detected several traits related to multi-litter years, including the dam’s ability to habituate to the birth location, the dam’s age, the dam’s number of previous litters, and the dam’s birth month. Although producing multiple litters within a year has been anecdotally associated with the loss of a previous litter, we did not detect a relationship between multi-litter years and the survivorship of previous litters. These findings suggest that captive populations of fennec foxes may experience a destabilization of their reproductive patterns, which may culminate in the production of multiple litters outside of the typical window of reproduction. Fennec foxes are a common captive species bred in zoos worldwide. Developing a greater understanding of their reproduction can allow for more successful captive management, which may improve future reproductive successes.

UROLITHIASIS IN FOXES: ASSESSMENT OF 65 UROLITH SUBMISSIONS TO THE MINNESOTA UROLITH CENTER FROM 1981 TO 2021.

This article summarizes urinary stone submissions from foxes in human care to the Minnesota Urolith Center over 40 years. A previous report documented the analysis of uroliths from foxes that were submitted between 1981 and 2007.13 New data compiled from 2008 to 2021 included an additional 38 stones submitted from foxes, totaling 65 fox urolith submissions from 1981 to 2021. Struvite and cystine uroliths were most common, with the remainder comprised of calcium phosphate, calcium oxalate, compound, mixed, or miscellaneous material. Most stones were submitted from male foxes. Seventy-two percent of the stones were urocystoliths, and from 2010 to 2021, most stones were diagnosed antemortem and removed surgically. More than half of the stones were submitted from red foxes (Vulpes vulpes) and fennec foxes (Vulpes zerda). Urolithiasis in foxes may be an underrecognized condition, and data from this study suggest that clinicians should consider routine urinalysis and diagnostic imaging as part of the preventive medicine program for fox species, especially red foxes and fennec foxes.

Call Me

Call Me Terri Nowak (bio) Air conditioning blasted inside the library. Though it was late September, a heat wave had struck. I shivered and shelved books. The liveliest day of the year was here, the Friday of Banned Books Week, and the library was electric. This year, I dreaded going alone to the employee party in the evening. Everyone dressed up and brought their plus ones to Sjonan, a restaurant awash in natural light, with timbered beams and Scandinavian decor and complicated food. Last year, my boyfriend at the time, Steven, went with me, and after each introduction, he would take me aside and whisper things like, “What happened to her face?” or, “Didn’t anyone tell him the dress code?” He chatted up the blonde server with a high ponytail. This was the same Steven, a photographer for the Duluth News Tribune, who would later break up with me because he wanted to date someone more interesting. At 5:25, another librarian, Laura, approached through the aisle of books, lit from within. “Ellen, remember to bring your banned book for the exchange tonight.” She sang the last words like a show tune. I liked Laura. We bonded the day I caught her in the break room plucking an empty Diet Coke can from the garbage and dropping it into the recycle bin with an expression of disgust. She was unusually interested in my love life, which I didn’t think was that interesting. Maybe after being married to an insurance adjuster for 24 years and raising two children, anyone single seemed exotic. Maybe she thought of me the way a zookeeper thinks of the fennec fox, a rare canine with a tiny body and huge ears. It’s hard to look away from something like that. I tugged on my left braid and nodded. I was excited to bring my banned book, The Graveyard by Marek Hłasko, a cautionary tale about the realities of life for the average comrade under Poland’s communist regime. I hadn’t been too interested in my Polish ancestry until a few years ago, when a visiting author commented on my last name. I began to pull fragmented memories from childhood, how my father called me his myszka, little mouse, and told vignettes of hardship from the old country, though he was born in Minnesota and had never been to Poland. “It might be too soon to ask,” Laura said. She put her hand on my shoulder. “Are you bringing a date?” [End Page 93] I hoped I didn’t look pathetic. “No date.” I smoothed the crop of stray hairs that formed at my crown. “I’ll probably have more fun than last year. Steven was so rude.” Laura’s mouth tensed. I knew she couldn’t agree with me. Steven had charmed her. “At any rate, I’m glad you’re coming,” she said. I wasn’t sure. Going to a social event without a date was the Olympics of single womanhood. Laura gave me a double thumbs-up with a grim smile and buzzed away. The shelving of books relaxed me. Genre, fiction. Author, Austen Jane. Title, Pride and Prejudice. I used my fingers to make a space between Persuasion and Sense and Sensibility and slid the trade paperback into place. ________ After work I meandered home and thought up wild excuses for missing the party. I stopped short when I saw an old payphone kiosk, a concrete post with rusty holes where the phone had been. Across the top was the cornflower blue and white graphic of a phone and circled bell. I could almost see my father reach for the receiver in a flash of aviator sunglasses and lip-dangled cigarette, a pause from so many life imperatives to call his daughter. In his head were promises he wanted to keep. He would be home in time for my birthday. He would take me to Poland to meet distant cousins after my high school graduation. He loved me. The last time I heard from him, his parting words imprinted on my ten-year-old self, “I’ll call again soon, myszka.” I circled the relic and ran...

Fennec Fox Optimization: A New Nature-Inspired Optimization Algorithm

This paper proposes a new nature-based metaheuristic algorithm called Fennec Fox Optimization (FFA), mimicking two natural behaviors of the animal Fennec Fox in nature. Concretely, Fennec’s digging ability and escape strategy from wild predators were the fundamental inspiration for the proposed FFA. The mathematical model of FFA is presented in two phases based on imitating these two behaviors. First, the efficiency of FFA was evaluated in the optimization of sixty-eight standard benchmark functions and four engineering design problems. Second, FFA performance is challenged against eight well-known optimization algorithms. The optimization results show that FFA perfectly balances exploration and exploitation in searching for the global optimum. Hence, FFA can provide suitable solutions to optimization problems. The comparison of results indicates the superiority of FFA in most objective functions over competitor algorithms in providing the optimal solution.

Hematometra associated with fetal death in a fennec fox (Vulpes zerda)

A 5-year-old female fennec fox weighing 1 kg presented to the Veterinary Medical Center, Chungbuk National University with swelling of the mammary glands and hematuria. There were no significant complete blood count (CBC) or serum chemistry findings. The uterus obtained by ovariohysterectomy was filled with blood-clot-like material. The uterine fluid contained erythrocytes, a few leukocytes, and bilirubin crystals without bacteria. The progesterone concentration in the blood serum the day before ovariohysterectomy was 7.3 ng/mL, which is higher than anestrus and lower than a true pregnant condition in a fennec fox. Despite the low blood progesterone concentration and absence of a fetus in the uterus, the histopathological zonary placental findings indicated that the fennec fox had been pregnant. This is the first case report of hematometra associated with fetal death in a captive fennec fox.

Glucocorticoid Production, Activity Levels, And Personality Traits Of Fennec Foxes (Vulpes zerda) Managed For Different Roles In Zoos

ABSTRACT Fecal glucocorticoid metabolite (FGM) concentrations, activity, and personality were assessed for 35 fennec foxes (Vulpes zerda) to determine whether animals managed as ambassadors differed from exhibit or off-exhibit animals. A FGM assay, pedometer, and personality assessment tool were validated. Then, fecal samples and movement data were collected during winter and summer periods. Handling was recorded, and the personality of each fox was evaluated. Generalized linear mixed models assessed the relationships between FGM concentrations, activity, personality, handling, sex, season, rearing type, and role. FGM concentrations did not differ in relation to role or handling. Foxes were most active at night; the time of peak activity did not vary with role or handling. Foxes were more active in winter; males were more active than females, and ambassador foxes were more active than off-exhibit animals. Hand-reared foxes were more sociable, and, at one institution, ambassador foxes were more sociable than foxes in other roles. These results suggest that management for ambassador programs is not associated with changes in glucocorticoid production or circadian patterns but may increase activity and be associated with greater sociability.

Comparative genomic characterization of multidrug-resistant Citrobacter spp. strains in Fennec fox imported to China

BackgroundTo investigate the antimicrobial profiles and genomic characteristics of MDR-Citrobacter spp. strains isolated from Fennec fox imported from Sudan to China.MethodsFour Citrobacter spp. strains were isolated from stool samples. Individual fresh stool samples were collected and subsequently diluted in phosphate buffered saline as described previously. The diluted fecal samples were plated on MacConkey agar supplemented with 1 mg/l cefotaxime and incubated for 20 h at 37 °C. Matrix-assisted laser desorption/ionization–time of flight mass spectrometry (MALDI–TOF–MS) was used for identification. Antimicrobial susceptibility testing was performed using the broth microdilution method. Whole-genome sequencing was performed on an Illumina Novaseq-6000 platform. Acquired antimicrobial resistance genes and plasmid replicons were detected using ResFinder 4.1 and PlasmidFinder 1.3, respectively. Comparative genomic analysis of 277 Citrobacter genomes was also performed.ResultsIsolate FF141 was identified as Citrobacter cronae while isolate FF371, isolate FF414, and isolate FF423 were identified as Citrobacter braakii. Of these, three C. braakii isolates were further confirmed to be extended-spectrum β-lactamases (ESBL)-producer. All isolates are all multidrug resistance (MDR) with resistance to multiple antimicrobials. Plasmid of pKPC-CAV1321 belong to incompatibility (Inc) group. Comparative genomics analysis of Citrobacter isolates generated a large core-genome. Genetic diversity was observed in our bacterial collection, which clustered into five main clades. Human, environmental and animal Citrobacter isolates were distributed into five clusters.ConclusionsTo our knowledge, this is the first investigation of MDR-Citrobacter from Fennec Fox. Our phenotypic and genomic data further underscore the threat of increased ESBL prevalence in wildlife and emphasize that increased effort should be committed to monitoring the potentially rapid dissemination of ESBL-producers with one health perspective.