Historical records reveal the distinctive associations of human disturbance and extreme climate change with local extinction of mammals.

Accelerated anthropogenic impacts and climatic changes are widely considered to be responsible for unprecedented species extinction. However, determining their effects on extinction is challenging owing to the lack of long-term data with high spatial and temporal resolution. In this study, using historical occurrence records of 11 medium- to large-sized mammal species or groups of species in China from 905 BC to AD 2006, we quantified the distinctive associations of anthropogenic stressors (represented by cropland coverage and human population density) and climatic stressors (represented by air temperature) with the local extinction of these mammals. We found that both intensified human disturbances and extreme climate change were associated with the increased local extinction of the study mammals. In the cold phase (the premodern period of China), climate cooling was positively associated with increased local extinction, while in the warm phase (the modern period) global warming was associated with increased local extinction. Interactive effects between human disturbance and temperature change with the local extinction of elephants, rhinos, pandas, and water deer were found. Large-sized mammals, such as elephants, rhinos, and pandas, showed earlier and larger population declines than small-sized ones. The local extinction sensitivities of these mammals to the human population density and standardized temperature were estimated during 1700 to 2000. The quantitative evidence for anthropogenic and climatic associations with mammalian extinction provided insights into the driving processes of species extinction, which has important implications for biodiversity conservation under accelerating global changes.

Zinc application alleviates the adverse renal effects of arsenic stress in a protein quality control way in common carp.

The potential antagonistic mechanism between zinc (Zn) and arsenic (As) on renal toxicity was investigated in common carp. The results showed that by increased Zn efflux and retention (as reflected by zinc transporter 1 (ZnT-1), Zrt- and Irt- 1ike protein (ZIP) and metallothionein (MT) expression), Zn co-administration significantly recovered the antioxidant function (catalase, CAT) and the level of renal barrier function (Occludin, Claudins and Zonula Occludens) in comparison to As treatment. Interestingly, Zn co-administration with As resulted in carps undergoing reduction of heat shock response (HSPs), a low induction of autophagy flux (Beclin-1, microtubule-associated protein 1 light chain 3 (LC3) and sequestosome 1 (P62)) and decreased endoplasmic reticulum (ER) stress (activating transcription factor 6 (ATF-6), inositol requiring-1α (IRE1) and PKR-like ER kinase (PERK)) in the aspect of mRNA or protein levels. All these alleviated protein quality control processes induced by Zn under As stress was correlated with the no longer loosen tight connection, less swollen endoplasmic reticulum as well as reduced formation of autophagosomes and autophagic vesicles. Mechanically, post-transcriptional regulated protein quantities compromising phosphatidylinositol-3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathway was demonstrated true causative forces inside the cell for Zn against As poisoning. In conclusion, we suggested the potential renal protective effect of Zn supplementation against As exposure by the modulation of protein quality control processes.

Gut microbiota and fecal metabolites in captive and wild North China leopard (Panthera pardus japonensis) by comparsion using 16 s rRNA gene sequencing and LC/MS-based metabolomics.

BACKGROUND: Gut microbes significantly contribute to nutrient digestion and absorption, intestinal health and immunity, and are essential for the survival and environmental adaptation of wild animals. However, there are few studies on the gut microbiota of captive and wild North China leopard (Panthera pardus japonensis). RESULTS: A total of 10 mainly bacterial phyla were identified in the fecal microbiota of North China leopard, Lachnoclostridium (p = 0.003), Peptoclostridium (p = 0.005), Bacteroides (p = 0.008), Fusobacterium (p = 0.017) and Collinsella (p = 0.019) were significantly higher than those of wild North China leopard. Distinct differences in the fecal metabolic phenotypes of captive and wild North China leopard were found, such as content of l-methionine, n-acetyl-l-tyrosine, pentadecanoic acid and oleic acid. Differentially abundant gut microbes were associated with fecal metabolites, especially the bacteria in Firmicutes and Bacteroidetes, involved in the metabolism of N-acetyl-L-alanine and D-quinovose. CONCLUSION: This study reports for the first time the differences in gut microbiota abundance between captive and wild North China leopard, as well as significant differences in fecal metabolic phenotypes between two groups.

Ascarid infection in wild Amur tigers (Panthera tigris altaica) in China.

BACKGROUND: Wild Amur tigers are a sparsely populated species, and the conservation of this species is of great concern worldwide, but as an important health risk factor, parasite infection in them is not fully understanding. RESULTS: In this study, sixty-two faecal samples were collected to investigate the frequency and infection intensity of Toxocara cati and Toxascaris leonina in wild Amur tigers. The T. cati and T. leonina eggs were preliminary identified by microscopy, and confirmed by molecular techniques. Infection intensity was determined by the modified McMaster technique. Phylogenetic trees demonstrated that T. cati of wild Amur tiger had a closer relationship with which of other wild felines than that of domestic cats. T. leonina of Amur tiger and other felines clustered into one clade, showing a closer relationship than canines. The average frequency of T. cati was 77.42% (48/62), and the frequency in 2016 (100%) were higher than those in 2013 (P = 0.051, < 0.1; 66.6%) and 2014 (P = 0.079, < 0.1; 72.2%). The infection intensity of T. cati ranged from 316.6 n/g to 1084.1 n/g. For T. leonina, only three samples presented eggs when the saturated sodium chloride floating method was performed, indicating that the frequency is 4.83% (3/62). Unfortunately, the egg number in faecal smears is lower than the detective limitation, so the infection intensity of T. leonina is missed. CONCLUSIONS: This study demonstrated that ascarids are broadly prevalent, and T. cati is a dominant parasite species in the wild Amur tiger population.

Discrepant effects of copper (II) stress on different types of skeletal muscles in chicken: Elements and amino acids.

Different distributions of 28 elements and 17 amino acids in pectoralis, wing biceps brachii and leg gastrocnemius of chicken upon CuSO4 (300 mg/kg) exposure for 90 days were investigated. Accompanied by copper accumulation, pathological injuries were observed in those three kinds of skeletal muscles using histological and ultrastructural methods. Based on data obtained, we analyzed leg gastrocnemius displayed the most increases (P < 0.000) in all three kinds of elements detected, including macroelements (131%), essential microelements (129%) and toxic microelements (179%) than the other two skeletal muscles. Furthermore, decreased total amino acids (P = 0.006), a susceptibility of lipid peroxidation/oxidative stress and a disequilibrium of nutrition and taste were analyzed in the leg gastrocnemius, indicating an unsuitability for human consumption. Intriguingly, these anomalies were scarce in pectoralis and wing biceps brachii. Combined with multivariate analysis we may conclude that leg gastrocnemius are more vulnerable to copper stress than pectoralis and wing biceps brachii in chicken.

Metagenomic analysis of captive Amur tiger faecal microbiome.

BACKGROUND: The gastrointestinal tracts of animals are home to large, complex communities of microbes. The compositions of these communities ultimately reflect the coevolution of microorganisms with their animal host and are influenced by the living environment, diet and immune status of the host. Gut microbes have been shown to be important for human disease and health, but little research exists in the gut microbiome of the Amur tiger, which is one of the most endangered species in the world. RESULTS: In this study, we present the use of whole-metagenome shotgun sequencing to analyze the composition and functional structures of the gut microbiota in captive Amur tigers. Our results showed a high abundance of four major phyla in captive Amur tigers, including Proteobacteria, Firmicutes, Actinobacteria and Fusobacteria. Moreover, at the genus level, Escherichia, Collinsella and Fusobacterium were most abundant in the captive Amur tiger fecal metagenome. At the species level, Escherichia coli, Fusobacterium ulcerans and Fusobacterium varium were the species with highest abundances in the captive Amur tiger gut microbiota. The primary functional categories of the Amur tiger faecal metagenome were associated mainly with Carbohydrate metabolism, Membrane transport and Amino acid metabolism based on the KEGG pathway database. The comparative metagenomic analyses showed that the captive Amur tiger fecal metagenome had a lower abundance of Spirochaetes, Cyanobacteria and Ascomycota than other animals, and the primary functional categories were primarily associated with carbohydrate metabolism subsystems, clustering-based subsystems and protein metabolism. CONCLUSIONS: We presented here for the first time the use of the shotgun metagenomic sequencing approach to study the composition and functional structures of the gut microbiota in captive Amur tiger.

Three-dimensional forest foodscape in large herbivores' habitat based on UAV with LiDAR detection.

With the development of artificial intelligence, the integration of LiDAR technologies and foodscape theories to study wildlife habitat, nutritional ecology, species coexistence, and other existing hot and difficult issues would become an international frontier in the field of wildlife habitat ecology and management.

Combination of facial and nose features of Amur tigers to determine age.

We found that the area of black round or irregular-shaped spots on the tiger's nose increased with age, indicating a positive relationship between age and nose features. We used the deep learning model to train the facial and nose image features to identify the age of Amur tigers, using a combination of classification and prediction methods to achieve age determination with an accuracy of 87.81%.

The genetic status and rescue measure for a geographically isolated population of Amur tigers.

The Amur tiger is currently confronted with challenges of anthropogenic development, leading to its population becoming fragmented into two geographically isolated groups: smaller and larger ones. Small and isolated populations frequently face a greater extinction risk, yet the small tiger population's genetic status and survival potential have not been assessed. Here, a total of 210 samples of suspected Amur tiger feces were collected from this small population, and the genetic background and population survival potentials were assessed by using 14 microsatellite loci. Our results demonstrated that the mean number of alleles in all loci was 3.7 and expected heterozygosity was 0.6, indicating a comparatively lower level of population genetic diversity compared to previously reported studies on other subspecies. The genetic estimates of effective population size (Ne) and the Ne/N ratio were merely 7.6 and 0.152, respectively, representing lower values in comparison to the Amur tiger population in Sikhote-Alin (the larger group). However, multiple methods have indicated the possibility of genetic divergence within our isolated population under study. Meanwhile, the maximum kinship recorded was 0.441, and the mean inbreeding coefficient stood at 0.0868, both of which are higher than those observed in other endangered species, such as the African lion and the grey wolf. Additionally, we have identified a significant risk of future extinction if the lethal equivalents were to reach 6.26, which is higher than that of other large carnivores. Further, our simulation results indicated that an increase in the number of breeding females would enhance the prospects of this population. In summary, our findings provide a critical theoretical basis for further bailout strategies concerning Amur tigers.

Whole-genome analysis of Escherichia coli isolated from wild Amur tiger (Panthera tigris altaica) and North China leopard (Panthera pardus japonensis).

Background: Escherichia coli is an important intestinal flora, of which pathogenic E. coli is capable of causing many enteric and extra-intestinal diseases. Antibiotics are essential for the treatment of bacterial infections caused by pathogenic E. coli; however, with the widespread use of antibiotics, drug resistance in E. coli has become particularly serious, posing a global threat to human, animal, and environmental health. While the drug resistance and pathogenicity of E. coli carried by tigers and leopards in captivity have been studied intensively in recent years, there is an extreme lack of information on E. coli in these top predators in the wild environment. Methods: Whole genome sequencing data of 32 E. coli strains collected from the feces of wild Amur tiger (Panthera tigris altaica, n = 24) and North China leopard (Panthera pardus japonensis, n = 8) were analyzed in this article. The multi-locus sequence types, serotypes, virulence and resistance genotypes, plasmid replicon types, and core genomic SNPs phylogeny of these isolates were studied. Additionally, antimicrobial susceptibility testing (AST) was performed on these E. coli isolates. Results: Among the E. coli isolates studied, 18 different sequence types were identified, with ST939 (21.9%), ST10 (15.6%), and ST3246 (9.4%) being the most prevalent. A total of 111 virulence genes were detected, averaging about 54 virulence genes per sample. They contribute to invasion, adherence, immune evasion, efflux pump, toxin, motility, stress adaption, and other virulence-related functions of E. coli. Sixty-eight AMR genes and point mutations were identified. Among the detected resistance genes, those belonging to the efflux pump family were the most abundant. Thirty-two E. coli isolates showed the highest rate of resistance to tetracycline (14/32; 43.8%), followed by imipenem (4/32; 12.5%), ciprofloxacin (3/32; 9.4%), doxycycline (2/32; 6.3%), and norfloxacin (1/32; 3.1%). Conclusions: Our results suggest that E. coli isolates carried by wild Amur tigers and North China leopards have potential pathogenicity and drug resistance.

Decomposing the Spatial and Temporal Effects of Climate and Habitat on a Hazel Grouse (Tetrastes bonasia) Population in Northeastern Chinese Mountains.

Habitat, climate, and human disturbances have important effects on wildlife, and these are especially critical for threatened species. In this study, we used infrared camera traps to monitor the population dynamics of the hazel grouse (Tetrastes bonasia) from 2012 to 2021 in northeast China and explore the effects of habitat, climate, and human disturbance on their distribution. We analyzed 16 environmental variables related to significant differences between presence recordings and absence recordings within and between seasons. Temperatures and roads influenced the distribution of the hazel grouse, but topography and vegetation types did not. The hazel grouse preferred deciduous forest and oak forest from spring to autumn. This study provides ecological information to help guide the mountain habitat management of the hazel grouse in national parks.

Individual automatic detection and identification of big cats with the combination of different body parts.

The development of facial recognition technology has become an increasingly powerful tool in wild animal individual recognition. In this paper, we develop an automatic detection and recognition method with the combinations of body features of big cats based on the deep convolutional neural network (CNN). We collected dataset including 12 244 images from 47 individual Amur tigers (Panthera tigris altaica) at the Siberian Tiger Park by mobile phones and digital camera and 1940 images and videos of 12 individual wild Amur leopard (Panthera pardus orientalis) by infrared cameras. First, the single shot multibox detector algorithm is used to perform the automatic detection process of feature regions in each image. For the different feature regions of the image, like face stripe or spots, CNNs and multi-layer perceptron models were applied to automatically identify tiger and leopard individuals, independently. Our results show that the identification accuracy of Amur tiger can reach up to 93.27% for face front, 93.33% for right body stripe, and 93.46% for left body stripe. Furthermore, the combination of right face, left body stripe, and right body stripe achieves the highest accuracy rate, up to 95.55%. Consequently, the combination of different body parts can improve the individual identification accuracy. However, it is not the higher the number of body parts, the higher the accuracy rate. The combination model with 3 body parts has the highest accuracy. The identification accuracy of Amur leopard can reach up to 86.90% for face front, 89.13% for left body spots, and 88.33% for right body spots. The accuracy of different body parts combination is lower than the independent part. For wild Amur leopard, the combination of face with body spot part is not helpful for the improvement of identification accuracy. The most effective identification part is still the independent left or right body spot part. It can be applied in long-term monitoring of big cats, including big data analysis for animal behavior, and be helpful for the individual identification of other wildlife species.

Recognition of big mammal species in airborne thermal imaging based on YOLO V5 algorithm.

Unmanned aerial vehicle (UAV) technology, artificial intelligence, and the relevant hardware can be used for monitoring wild animals. However, existing methods have several limitations. Therefore, this study explored the monitoring and protection of Amur tigers and their main prey species using images from UAVs by optimizing the algorithm models with respect to accuracy, model size, recognition speed, and elimination of environmental interference. Thermal imaging data were collected from 2000 pictures with a thermal imaging lens on a DJI M300RTK UAV at the Hanma National Nature Reserve in the Greater Khingan Mountains in Inner Mongolia, Wangqing National Nature Reserve in Jilin Province, and Siberian Tiger Park in Heilongjiang Province. The YOLO V5s algorithm was applied to recognize the animals in the pictures. The accuracy rate was 94.1%, and the size of the model weight (total weight of each model layer trained with the training set) was 14.8 MB. The authors improved the structures and parameters of the YOLO V5s algorithm. As a result, the recognition accuracy rate became 96%, and the model weight was 9.3 MB. The accuracy rate increased by 1.9%, the model weight decreased by 37.2% from 14.8 MB to 9.3 MB, and the recognition time of a single picture was shortened by 34.4% from 0.032 to 0.021 s. This not only increases the recognition accuracy but also effectively lowers the hardware requirements that the algorithm relies on, which provides a lightweight fast recognition method for UAV-based edge computing and online investigation of wild animals.

Impacts of top predators and humans on the mammal communities of recovering temperate forest regions.

Top predators are important drivers in shaping ecological community structure via top-down effects. However, the ecological consequences and mechanisms of top predator loss under accelerated human impacts have rarely been quantitatively assessed due to the limited availability of long-term community data. With increases in top predator populations in northern China over the past two decades, forests with varying densities of top predators and humans provide an opportunity to study their ecological effects on mammal communities. We hypothesized a priori of conceptual models and tested these using structural equation models (SEMs) with multi-year camera trap data, aiming to reveal the underlying independent ecological effects of top predators (tigers, bears, and leopards) and humans on mammal communities. We used random forest models and correlations among species pairs to validate results. We found that top predator reduction could be related to augmented populations of large ungulates ("large ungulate release") and mesopredators ("mesopredator release"), consistent with observations of mammal communities in other ecosystems. Additionally, top predator reduction could be related to reduced small mammal abundance. Hierarchical SEMs identified three bottom-up pathways from forest quality to human activities, large ungulates, and some small mammals, and five top-down pathways from human activities and top predators to some small mammals, large ungulates, and mesopredators. Furthermore, our results suggest that humans showed predominant top-down effects on multiple functional groups, partially replacing the role of top predators, rather than be mediated by them; effects of humans and top predators appeared largely independent. Effects of humans on top predators were non-significant. This study provides novel insights into the effects of top predators and humans as super-predators on mammal communities in forest ecosystems and presents cues of bottom-up effects that can be translated into actionable management plans for improving forest quality, thereby supporting top predator recovery and work/life activities of local people.

Estimation of body weight in captive Amur tigers (Panthera tigris altaica).

So far, there has been no safe and convenient method to weigh the large fierce animals, like Amur tigers. To address this problem, we built models to predict the body weight of Amur tigers based on the fact that body weight is proportional to body measurements or age. Using the method of body measurements, we extracted the body measurements from 4 different kinds of the lateral body image of tigers, that is, total lateral image, central lateral image, ellipse fitting image, and rectangle fitting image, and then we respectively used artificial neural network (ANN) and power regression model to analyze the predictive relationships between body weight and body measurements. Our results demonstrated that, among all ANN models, the model built with rectangle fitting image had the smallest mean square error. Comparatively, we screened power regression models which had the smallest Akakai information criteria (AIC). In addition, using the method of age, we fitted nonlinear regression models for the relationship between body weight and age and found that, for male tigers, logistic model had the smallest AIC. For female tigers, Gompertz model had the smallest AIC. Consequently, this study could be applied to estimate body weight of captive, or even wild, Amur tigers safely and conveniently, helping to monitor individual health and growth of the Amur tiger populations.

Temporal activity patterns of North China leopards and their prey in response to moonlight and habitat factors.

The nocturnal activities of predators and prey are influenced by several factors, including physiological adaptations, habitat quality and, we suspect, corresponds to changes in brightness of moonlight according to moon phase. In this study, we used a dataset from 102 camera traps to explore which factors are related to the activity pattern of North China leopards (Panthera pardus japonensis) in Shanxi Tieqiaoshan Provincial Nature Reserve (TPNR), China. We found that nocturnal activities of leopards were irregular during four different lunar phases, and while not strictly lunar philic or lunar phobic, their temporal activity was highest during the brighter moon phases (especially the last quarter) and lower during the new moon phase. On the contrary, roe deer (Capreolus pygargus) exhibited lunar philic activity, while wild boar (Sus scrofa) and tolai hare (Lepus tolai) were evidently lunar phobic, with high and low temporal activity during the full moon, respectively. In terms of temporal overlap, there was positive overlap between leopards and their prey species, including roe deer and tolai hare, while leopard activity did not dip to the same low level of wild boar during the full moon phase. Human activities also more influenced the temporal activity of leopards and wild boar than other species investigated. Generally, our results suggested that besides moonlight risk index (MRI), cloud cover and season have diverse effects on leopard and prey nocturnal activity. Finally, distinct daytime and nighttime habitats were identified, with leopards, wild boar, and tolai hare all using lower elevations at night and higher elevations during the day, while leopards and roe deer were closer to secondary roads during the day than at night.

Effects of spatially heterogeneous warming on gut microbiota, nutrition and gene flow of a heat-sensitive ungulate population.

Effects of climate warming on trophic cascades are increasingly reported for large herbivores occupying northern latitudes. During the last 40 years, moose (Alces alces) in northeast China have lost nearly half of their historical distribution through their habitat shifting northwards. There are many possible causes of bottom-up and top-down effects of temperature and for moose in northeast China they are poorly understood. Of particular relevance are the effects of extrinsic environmental factors on gene flow, nutritional adaptions, and gut microbiota that occur as moose populations retreat northwards. We combined molecular biology, nutritional ecology and metagenomics to gain deeper mechanistic insights into the effects of temperature on moose populations. In this study, we revealed that the direction and intensity of gene flow is consistent with global warming driving retreats of moose populations. We interpret this as evidence for the northward movement of moose populations, with cooler northern populations receiving more immigrants and warmer southern populations supplying emigrants. Comparison across latitudes showed that warmer late spring temperatures were associated with plant community composition and facilitated related changes in moose protein and carbohydrate intake through altering forage availability, forage quality and diet composition. Furthermore, these nutrient shifts were accompanied by changes in gut microbial composition and functional pathways related to nutrient metabolism. This study provided insights into mechanisms driving effects of spatial heterogeneous warming on genetic, nutritional and physiological adaptions related to key demographic rates and patterns of survival of heat-sensitive ungulates along a latitude gradient. Understanding such changes helps to identify key habitat areas and plant species to ensure accurate assessment of population status and targeted management of moose populations.

Behavioral-psychological motivations encoded in the vocal repertoire of captive Amur tiger (Panthera tigris altaica) cubs.

BACKGROUND: The Amur tiger (Panthera tigris altaica) is the largest and one of the most endangered cats in the world. In wild and captive cats, communication is mainly dependent on olfaction. However, vocal communication also plays a key role between mother and cubs during the breeding period. How cubs express their physiological and psychological needs to their mother and companions by using acoustic signals is little known and mainly hindered by the difficult process of data collection. Here, we quantitatively summarized the vocal repertoire and behavioral contexts of captive Amur tiger cubs. The aim of the present work was to investigate the behavioral motivations of cub calls by considering influential factors of age, sex, and rearing experiences. RESULTS: The 5335 high-quality calls from 65 tiger cubs were classified into nine call types (Ar-1, Ar-2, Er, eee, Chuff, Growl, Hiss, Haer, and Roar) produced in seven behavioral contexts. Except for Er, eight of the nine call types were context-specific, related to Play (Ar-2, eee, and Roar), Isolation (Ar-1), Offensive Context (Haer, Growl, and Hiss), and a friendly context (Chuff). CONCLUSIONS: The results suggest that cubs are not quiet, but instead they express rich information by emitting various call types, which are probably crucial for survival in the wild. We herein provide the first detailed spectrogram classification to indicate vocal repertoires of calls and their coding with respect to behavioral contexts in Amur tiger cubs, and we pave the steps for revealing their social communication system, which can be applied for conservation of populations. These insights can help tiger managers or keepers to improve the rearing conditions by understanding the feline cubs' inner status and needs by monitoring their vocal information expressions and exchanges.

Wavelet methods reveal big cat activity patterns and synchrony of activity with preys.

Appropriate temporal and spatial scales are important prerequisites for obtaining reliable results in studies of wildlife activity patterns and interspecific interactions. The spread of camera-trap technology has increased interest in and feasibility of studying the activity patterns and interspecific interactions of wildlife. However, such studies are often conducted at arbitrary spatial and temporal scales, and the methods used impose scale on the study rather than determining how activity and species interactions change with spatial scale. In this study, we used a wavelet-based approach to determine the temporal and spatial scales for activity patterns and interspecific interactions on Amur leopard and their ungulate prey species that were recorded using camera traps in the main Amur leopard occurrence region in northeast China. Wavelets identified that Amur leopards were more active in spring and fall than summer, and fluctuated with periodicities of 9 and 17 days, respectively. Synchronous relationships between leopards and their prey commonly occurred in spring and fall, with a periodicity of about 20 days, indicating the appropriate seasons and temporal scales for interspecific interaction research. The influence of human activities on the activity patterns of Amur leopard or prey species often occurred over longer time periods (60-64 days). Two-dimensional wavelet analyses showed that interactions between leopard and prey were more significant at spatial scales of 1 km2 . Overall, our study provides a feasible approach to studying the temporal and spatial scales for wildlife activity patterns and interspecific interaction research using camera trap data.

Threats to Site Occupation of Carnivores: A Spatiotemporal Encroachment of Non-native Species on the Native Carnivore Community in A Human-dominated Protected Area.

Interspecific interactions of commensal non-native species such as domestic dogs and livestock with native wildlife are evident issues in protected areas (PAs). We studied spatiotemporal interactions by combining camera trap photographic sampling over three years. We used a generic multiseason occupancy and co-occurrence analysis and kernel density estimates of temporal activity. We accumulated a total of 1,305 and 1,557 independent photo-captures respectively for non-native and carnivore species during 26,216 trap nights. We found that non-native and carnivore species did not show substantial changes in occupancy rate over time. Yet both kinds of species were frequently detected. Carnivores had lower values of occupancy equilibrium than non-native species in seasons one and two. Domestic dogs directly occurred with native carnivores (except with leopards in season one), while the human and livestock presence displayed direct (Species Interaction Factors > 1) and indirect (Species Interaction Factors close to 1) co-occurrence, respectively, with the leopard and two mesocarnivores. The leopard cat was the least spatially influenced carnivore by the non-native species interactions. Furthermore, the leopard had higher temporal overlap (high Δ4) with all non-native species than the leopard cat and red fox (low Δ4). Our study exposes the negative impact of free-ranging non-native species across this protected area on native carnivore occupancy. An evaluation of the interconnections among non-native and carnivore species across diverse PA management regimes is crucial to develop robust landscape-scale conservation strategies.