Habitat loss and degradation are the leading threats to the continuation of the isolated Asian tiger (Panthera tigris) population. In 2010, the Global Tiger Recovery Program (GTRP) committed to doubling wild tigers by 2022 (Tx2 goal), but monitoring changes in habitat fragmentation or quality is not generally included in species recovery plans. Here we adopted a dual-indicator landscape risk classification framework to assess the spatiotemporal dynamics of disturbances in 76 tiger conservation landscapes (TCLs) between 2000 and 2020. Across the 76 landscapes, the human footprint and forest fragmentation showed a widespread and significant increasing trend over 20 years and accelerated after 2010 with growth rate increased by 0.58 % and 0.36 %. The 29 landscapes deemed most critical for the Tx2 goal did not curb habitat degradation but showed relatively lower disturbance rates. In addition, 64.39 % of the TCLs were at risk, which is consistent with current evidence and is associated with the ongoing decline of the wild tiger population. However, disturbance rates were unevenly distributed across tiger subspecies habitats, with low-disturbance landscapes offering more favourable conditions for population recovery. Especially in Southeast Asia, both tiger populations and habitats were under acute threat, with local extirpations already recorded in Vietnam, Laos, and Cambodia. Our findings underscored the urgent need to integrate habitat conditions into tiger recovery planning and offers critical insights for transboundary conservation.

Anthropogenic noise, which is a novel and pervasive pollutant, can interfere with animal's perception and processing of environmental information, resulting in detrimental physiological and behavioural impacts on various taxa. Although natural ecosystems are exposed to a variety of anthropogenic noise, few studies have addressed the effects of different types of noise on mammalian behaviours, particularly age/sex-dependent variations in behavioural responses. Here, a field-based playback experiment was conducted in Northeast China to investigate the behavioural responses of sika deer, Cervus nippon, to traffic noise, grazing noise (cowbell) and the human voice. Results show that when sika deer were exposed to human or traffic treatments, they presented a significantly greater probability of fleeing compared with cowbell and bird (control) playback. Even when deer did not leave the experimental site, noise increased vigilance, which supports the risk-disturbance hypothesis. Grazing noise remarkably increased vigilance and reduced foraging rather than induced fleeing, thereby supporting the masking hypothesis. Deer had marked differences in foraging behaviours among sex, age and reproductive groups. Moreover, vigilance and foraging increased with the group size of sika deer. This study highlights that the antipredator behaviour responses of wild ungulates to noise-induced risk depend on the disturbance type and intraspecific traits. Thus, quantifying the behavioural and fitness costs associated with diverse sources of noise is crucial for better understanding the ecological consequences of human disturbances and developing targeted mitigation measures for species and communities. (c) 2025 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

Understanding how forest vegetation structure shapes acoustic environments is essential for linking biodiversity patterns with ecosystem complexity. However, few studies have systematically examined how fine-scale three-dimensional (3D) vegetation features influence soundscape dynamics across diel cycles. Here, we investigated how vegetation structure is associated with acoustic variation over time. We integrated light detection and ranging-derived 3D vegetation metrics with passive acoustic monitoring across 52 plots in Northeast China Tiger and Leopard National Park. Through a combination of acoustic indices and frequency-specific power spectral density (PSD) analysis, we examined the associations between six vegetation variables and soundscape characteristics across four diel phases: dawn, day, dusk and night. Canopy structure (e.g. canopy height, crown volume) was most strongly associated with soundscape characteristics during the day and dusk, while understorey openness showed a closer relationship with nocturnal acoustic patterns. Among the acoustic metrics, the Acoustic Evenness Index was especially responsive to vegetation structure variables. PSD results further revealed frequency-specific vocal stratification, suggesting that different acoustic groups may align their signalling activity with distinct structural layers, a pattern consistent with the ecological niche partitioning hypothesis. Synthesis and applications. Forest soundscapes reflect the composition and activity of local biological communities, both of which are closely linked to vegetation structure. Our findings demonstrate that fine-scale vegetation heterogeneity is a key correlate of diel soundscape variation, highlighting structural complexity as a key ecological mediator between habitat structure and species behaviour-even in moderately diverse temperate systems. Incorporating 3D structural information into acoustic monitoring provides a robust framework for tracking biodiversity and ecosystem functioning, offering a scalable approach for forest conservation and management.

Abstract Large herbivores can strongly influence plant community, but their effects may vary across habitats that differ in disturbance history, vegetation structure, and recovery potential. Here, we compared plant communities and their short-term responses to sika deer (Cervus nippon) browsing between fuelbreaks and adjacent forest understories in the Northeast China Tiger and Leopard National Park. We used exclosure experiments to assess species composition, woody seedling recovery, community-weighted mean (CWM) functional traits, and phylogenetic structure after one year of deer exclusion. Plant communities differed significantly between the two habitats. Fuelbreaks had greater herbaceous and woody seedling cover and higher CWM values for leaf mass, leaf size, and nutrient-related traits than forest understories. In fuelbreaks, mowing had ceased both inside and outside exclosures, and the paired comparison showed that deer browsing altered species composition and reduced woody seedling richness and cover outside exclosures. These changes were accompanied by lower CWM values for leaf size, water content, calcium, crude fat, flavonoids, and alkaloids outside exclosures, together with broader-scale phylogenetic overdispersion (sesMPD > 0). In forest understories, deer effects were mainly reflected in herbaceous species composition and lower CWM values for crude fat outside exclosures. Forest understory communities showed broader-scale phylogenetic overdispersion both inside and outside exclosures (sesMPD > 0), but only outside exclosures showed finer-scale phylogenetic clustering (sesMNTD < 0). Overall, large herbivore effects on plant community were strongly mediated by habitat context. Future assessments should consider local habitat conditions, vegetation recovery trajectories, and longer-term monitoring of woody regeneration and community assembly.

Understanding livestock-wildlife interactions, especially in forest ecosystems, is critical for biodiversity conservation and sustainable land management. However, the long-term and cascading impacts of livestock grazing on forest structure and community bioacoustics are important yet largely neglected areas of research. Here, we used acoustic indices and a sound event detection (SED) model to evaluate the effects of continuous cattle grazing on seasonal soundscapes in Northeast China. We collected and analyzed over 18,785 h of recordings from 10 cattle-grazed forest plots and 10 ungrazed forest plots in Northeast China. We identified sound events in each recording via deep learning and calculated six acoustic indices, as well as extracted vegetation characteristics using light detection and ranging point cloud data. Our results revealed that grazing activities significantly changed seasonal soundscape dynamics, with biophony being highest in grazed forests and lowest in ungrazed forests in winter. Livestock shifted the forest soundscape composition by increasing the audibility of birds and insects while decreasing the vocalizations of sika deer (Cervus nippon) and crows, resulting in reduced sound diversity and complexity in grazed forests. We also found that grazing can reduce the leaf area index, herbaceous plants, and canopy density, which can influence these effects indirectly. Interestingly, cowbells noticeably altered the dawn chorus of birds; during spring and summer grazing periods, the chorus was characterized by an increased bird calling rate and greater vocal complexity (elevated Acoustic Complexity Index), patterns consistent with a behavioral adjustment to acoustic masking. This study highlights how livestock modify forest acoustic communities. To preserve natural soundscapes, we suggest mitigating cowbell noise through silent trackers (e.g., GPS) or reduced bell density in priority zones. Sustainable practices, including rotational grazing and buffer zones, are also vital to maintain forest structure and acoustic diversity. We suggest that integrating SED models with acoustic indices provides a robust framework for monitoring such anthropogenic disturbances.

If not managed effectively, livestock grazing can pose a major threat to the structure and function of forest ecosystems. However, little is known about the responses of soil fauna to grazing in temperate forests. Here, we examined the effects of free-ranging livestock on soil nematodes across different soil horizons (0–10 cm vs. 10–20 cm) in a Northeast China temperate forest shared by cattle. We assessed the relative effects of cattle grazing on the abundance and community composition of soil nematodes. We found that the effects of livestock grazing on soil nematode community varied with soil depth and trophic level. Compared with ungrazed forestland, grazing decreased total nematode abundance. This decline intensified significantly with increasing grazing intensity in the 10–20 cm soil layer at the site level, but not in the 0–10 cm layer. A structural equation model (SEM) revealed that the increase in soil bulk density caused by grazing was the primary reason for the decrease in total nematode abundance. However, grazing altered the nematode community composition in the 0–10 cm layer: the relative abundance of herbivores increased with increasing grazing intensity. SEM further indicated that these shifts were likely attributed to the direct effects of grazing. Our findings highlight the importance of soil stratification in evaluating the ecological impacts of forest grazing and the need for depth-explicit frameworks in understanding aboveground–belowground linkages in forest ecosystems.

Understanding free-ranging livestock-wildlife interactions in shared forest landscapes is critical for balancing the conflict between human exploitation of natural resources and wildlife conservation. However, little is known about the responses of ground-dwelling birds to grazing in temperate forests. We compiled a camera-trapping dataset of 1446 detections of 22 bird species over 6363 trap days from June to October 2020 at 25 cattlegrazed forest sites and 22 ungrazed sites, from which we assessed the relative impacts of cattle grazing, vegetation and predator (red fox Vulpes vulpes and leopard cat Prionailurus bengalensis) presence on the richness, site use, and diel activity patterns of understory birds (including frugivores and insectivores) in Northeast China. Our results revealed that ground-dwelling forest bird community assemblages were similar in both forest habitats; however, bird species richness was significantly greater in grazed forests than in ungrazed forests. The bird species richness increased with increasing plant diversity (Shannon index) in grazed forests and was positively associated with fox and leopard cat presence. The site use intensity of both frugivorous and insectivorous birds was positively associated with plant diversity in grazed forests, but negatively in ungrazed forest. Compared with insectivorous birds, frugivorous bird activities were significantly and positively associated with fox and leopard cat presence and an increase in leaf area index. Temporally, we found that diel activity significantly changed with increasing cattle grazing pressure for frugivorous birds. In contrast, insectivorous birds had similar daily activity patterns but shifted their activity peaks toward dawn in grazed forests. This work highlights that managing grazing practices and their effects on vegetation can positively affect temperate forest bird species richness and abundance.

Individual identification is essential for elucidating animal population structures, tracking population dynamics, and uncovering social networks. Advances in computational technology have enabled the application of deep learning-based methods for individual wildlife identification. However, accurately identifying individual animals in complex wild environments remains a significant challenge. Motivated by the need for accurate and efficient identification of individual animals in the wild, a deep learning-based individual identification framework, the object tracking-face extraction-sampling-recognition (OFSR) approach, is proposed. This framework uses deep learning to extract facial features and a multitask module with cross-task information sharing to integrate supplementary data, enhancing individual identification accuracy. By employing the OFSR framework, we identified individual white-tailed eagles in the Jingxin Wetland during the overwinter period. Our results demonstrated that the OFSR framework could accurately identify individual white-tailed eagles in wild environments, achieving an accuracy exceeding 93 %. In addition, in the multitask module of the OFSR framework, age recognition is used to increase the individual identification accuracy, successfully separating recurring and new individuals and increasing the accuracy by 2 % without adding extra costs. Our results demonstrate the potential of deep learning in identifying individual animals in complex wild environments, and the proposed OFSR framework is universally applicable to other raptors. The findings highlight that the added multitask module increases the accuracy of identifying individual animals. Our framework could improve the accuracy of identifying individuals in complex wild environments, offering a promising method for population detection and conservation research involving wild animals.

Bird migration is a fascinating behavioral phenomenon on earth, with annual movements along migratory routes forming complex migration networks. Stopovers, which serve as fuel stations for migratory birds, are critical to the success of long‐distance migrations. However, there is growing concern that stopover habitat has been converted and degraded due to intense human disturbances, which severely threaten migratory populations. New remote automated approaches for collecting data, such as passive acoustic monitoring (PAM) technology, provide a promising avenue for the continuous measurement of vocally active species. In this study, we applied PAM to monitor migrating birds in the stopovers of the Jingxin wetland in China, aiming to explore the activity and habitat use of migratory species through soundscape and deep learning approaches. We collected acoustic data from October 16, 2022, to December 15, 2022 (autumn migration season) and from February 19, 2023, to April 28, 2023 (spring migration season) across three habitats: degraded wetland, farmland, and forest. We applied multilabel classification via the ResNet50 convolutional neural network (CNN) to identify a total of 2.45 million 10‐s audio clips collected. Our results revealed that the 1–2‐kHz vocal signals of Anatidae dominated the soundscapes of the two migratory periods. Two automated measures—compound acoustic indices and a CNN‐derived migratory bird activity—reflected avian habitat use gradients and diel patterns in two migratory periods, with the compound indices model explaining 52% and 47% of the variation in migratory intensity, respectively. Furthermore, farmland is the most intensively utilized habitat by migratory species because of the food resources available. This novel use of combining reproducible acoustic data with deep learning can be used to track the temporal changes and spatial distribution of avian migrants effectively and highlights the importance of agricultural ecosystem management at dominated‐human stopover sites. Managers should consider using cost‐effective acoustic sensors for long‐term monitoring of avian movements and for refining conservation practices in a rapidly changing world.

China initiated its national parks in 2016 for safeguarding biodiversity and ecosystem integrity. The newly established Northeast Tiger and Leopard National Park (NTLNP) is essential for saving endangered large cats, but its adequacy for supporting apex predators and their prey remains largely unassessed. We evaluated NTLNP’s effectiveness in providing habitat and connectivity for the Amur tiger (Panthera tigris altaica) and sika deer (Cervus nippon). Furthermore, we examined the adequacy of the park’s current zoning and quantified direct anthropogenic disturbances in conservation-critical areas to identify management challenges. We developed a multiscale species distribution model with Bayesian additive regression trees (BART) to simulate habitat distribution for the Amur tiger and sika deer, and employed a circuit theory model to identify potential corridors. Additionally, large-scale monitoring data were used to assess disturbances spatial patterns within core habitat patches and dispersal corridors of tigers. Our results found that tiger and sika deer had highly overlapping habitats (> 50

Global increases in road networks have been a significant ecological stressor. There is a growing awareness of its negative effects on wildlife and soundscapes, particularly through habitat fragmentation and the introduction of anthropogenic noise. Passive acoustic monitoring (PAM) of biodiversity may provide integrative indices for assessing road effects. However, little is known about the responses of soundscape characteristics to roads with different traffic volume levels, especially in temperate forests. Here, we combined acoustic scene classification (ASC) and acoustic indices to examine the effects of road disturbance on soundscape attributes and composition in Northeast China. We collected and analysed over 3300 h of recordings from 28 sites across high-, medium-, and low-traffic roads. We classified each recording into different acoustic scenes based on the ResNet50 Convolutional Neural Network (CNN) and calculated the acoustic complexity index (ACI), bioacoustic index (BIO), acoustic diversity index (ADI), normalized difference soundscape index (NDSI), and power spectral density (PSD) values. Our results showed that acoustic indices and the daily audibility of birds, insects, amphibians and mammals significantly responded to road disturbances over 24 h diel cycles but with contrasting patterns; roads with intensifying traffic volume advanced the peak of biophony (BIO). As the traffic volume increased, the soundscape composition became more simplified, as measured by significantly lower ADI2K and NDSI values and significantly fewer daily audibility of the mammals. The ASC results further revealed that vehicle and insect sounds dominated the soundscape along the high-traffic road where nocturnal insects became the strongest acoustic markers. This study highlights the complex interactions between road disturbances and diverse biological taxa and presents important evidence that the effects of traffic noise and road networks should be considered in ecosystem conservation and management plans for the wildlife and acoustic communities of the landscape. We argue that the ASC combined with multiple acoustic indices is required to adequately account for the complex responses of soundscapes to large-scale anthropogenic disturbances.

Characterizing the dietary niche partitioning of sympatric mesocarnivores is fundamental for understanding their mechanisms of coexistence and ecosystem function. By utilizing scat DNA and DNA metabarcoding, our study revealed a detailed picture of the trophic interaction between two mesocarnivores in a cool temperate forest ecosystem in Northeast China. Both red foxes ( Vulpes vulpes ) and leopard cats ( Prionailurus bengalensis ) consumed a diverse range of prey (52 prey taxa from 11 orders) dominated by Rodentia (56.5–64.9%). Bipartite trophic network analysis suggested that both predators are generalists and have a high degree of niche overlap (Pianka's index = 0.77). However, diet patterns differed between the predators. Both predators consumed more diverse prey during the snow‐free period than during the snow‐covered period, which resulted in lower niche overlap between the predators (Pianka's index = 0.43). Another important source of diet niche partitioning was the proportion of large prey consumed, with red foxes consuming more ungulates than leopard cats do throughout the year in regions with two apex carnivores, tigers ( Panthera tigris ) and leopards ( P. pardus ). The presence of apex carnivores provides more stable carrion resources, which facilitates dietary niche partitioning and the coexistence of mesocarnivores. Our study provides important clues about the strategies of dietary niche partitioning between sympatric mesocarnivores, which is critical for understanding coexistence within carnivore communities.

Mineral licks are indispensable habitats to the life history of large mammal herbivores (LMH). Geophagy at licks may provide the necessary minerals for LMH, while LMH may be ecosystem engineers of licks by altering vegetation cover and soil physicochemical properties (SPCP). However, the precise relationship between the LMH and licks remains unclear. To clarify the geophagy function of licks for LMH and their influence on soil at licks, we recorded visitation patterns of sika deer around licks and compared SPCP and microbial communities with the surrounding matrix in a firebreak adjacent to the Sino-Russian border. Our study indirectly supports the "sodium supplementation" hypothesis. Proofs included (1) a significantly higher sodium, iron, and aluminum contents than the matrix, while lower carbon, nitrogen, and moisture contents; (2) significantly higher deer visitation during sodium-demand season (growing season), along with an avoidance of licks with high iron contents, which is toxic when overdose. The microbes at the licks differed from those at the matrix, mainly driven by low soil carbon and nitrogen and altered biogeochemical cycles. The microbial communities of licks are vulnerable because of their unstable state and susceptibility to SPCP changes. Structural equation modeling (SEM) clearly showed a much stronger indirect effect of deer on microbes at licks than at the matrix, especially for bacteria. Multiple deer behaviors at licks, such as grazing, trampling, and excretion, can indirectly shape and stabilize microbes by altering carbon and nitrogen input. Our study is the first to characterize soil microbial communities at mineral licks and demonstrate the processes by which LMH shapes those communities. More studies are required to establish a general relationship between the LMH and licks to promote the conservation of natural licks for wildlife.

Camera traps are widely used for wildlife monitoring and making informed conservation and land-management decisions, but the resulting ‘big data’ are laborious to process. Deep learning-based methods have been adopted for wildlife detection in camera traps. However, these methods detect large mammals in uncomplicated scenes, where powerful deep-learning models work effectively. Few studies have been conducted to develop artificial intelligence for recognizing wild birds that live in complicated field scenes with protective colors and small sizes. Here we used a dataset of 9717 images from 15 bird species based on camera traps to test 8 object detection algorithms (Faster RCNN, Cascade RCNN, RetinaNet, FCOS, RepPoints, ATSS, Deformable-DETR, and Sparse RCNN) and assess their performance. We also explored the effect of different backbones on model accuracy. Among them, the Cascade RCNN model performs best, with a mAP of 0.693 in model capabilities. Models perform differently in certain species, and backbones significantly affect the accuracy of the model. Cascade RCNN utilizing the Swin-T backbone is the best-performing combination, with a mAP of 0.704. This study could help researchers identify birds efficiently and inspires research on wildlife recognition in complex ecological settings.

Fuelbreaks are used to manage wildfires worldwide. Regular mowing within fuelbreaks can alter species composition and transform them into grassland habitats. These changes may provide more herbaceous plants to large herbivores, subsequently influencing their distribution. To clarify the impact of fuelbreaks on herbivores' food resources, we conducted molecular dietary analysis to quantify the dietary composition of sika deer ( Cervus nippon) ) in both the Sino-Russian border fuelbreak and forest interior, with an average distance of 1.6 km away from the fuelbreak. We constructed a local barcode database to enhance the resolution of the molecular dietary analysis. In addition, we surveyed the vegetation in these two habitats to determine the availability of food resources. We also used camera traps to monitor the visitation intensity of sika deer in both habitats. The results indicated that sika deer increased their visitation intensity at the fuelbreak during the snow-free season. The biomass of graminoids and herbaceous plants was high in the fuelbreak. However, the results of the molecular dietary analysis showed that during the snow-free season, the sika deer that visited the fuelbreak consumed fewer herbaceous plants. We used the Jacobs index to determine the dietary preferences of the sika deer and found that they were consistent browsers with a stable preference for woody plants. By assessing habitat quality, specifically the proportion of preferred plants, we found that the habitat quality of the fuelbreak was relatively low. In conclusion, fuelbreaks may attract herbivores. However, for browsers, such as sika deer, the major function of fuelbreaks is not to provide food resources.

为探讨地形对林下灌草层植物生物量的影响，该研究采用嵌套设计法在东北虎豹国家公园调查了138个密林下样地共1 685个植物样方，通过嵌套方差分析与有序逻辑斯蒂回归模型对林下灌草层植物生物量受地形的影响进行了分析。结果表明：(1)不同坡位之间，谷底的灌草层植物生物量高于坡上，坡上高于坡下(P<0.01);不同坡向之间，阴坡灌草层植物生物量低于阳坡及平地(P<0.01),后二者间无显著差异；不同坡度之间，平坡灌草层植物生物量高于陡坡，陡坡高于缓坡(P<0.01)。(2)坡位与坡向的交互作用显著，坡下平地、坡上平地、坡上阳坡与谷底的所有坡位灌草层植物生物量最高，坡下阴坡、坡下阳坡及坡上阴坡之间无显著差异。(3)研究区现行状态下，有序逻辑斯蒂回归结果显示，灌草层植物生物量在不同海拔、坡位及坡向坡度组合下不同。坡位、坡向及坡度对林下灌草层植物生物量有显著影响，3个坡位等级间谷底最高而坡下最低，3个坡度等级间陡坡最高而缓坡最低，不同坡向比较，阴坡最低。(4)在不排除人为干扰、森林放牧的现实情况下，谷底、陡坡地带灌草层植物生物量概率最高。该研究结果可为准确估计东北虎豹国家公园林下灌草层植物对虎豹猎物种群的承载力提供重要参考，从而为濒危虎豹的保护和管理提供科学依据。

The gut microbiota of wild animals, influenced by various factors including diet, nutrition, gender, and age, plays a critical role in their health and disease status. This study focuses on raccoon dogs (Nyctereutes procyonoides), a commonly found wild animal, and its gut microbiota composition in response to dietary shifts. The study aimed to compare the fecal bacterial communities and diversity of rescued raccoon dogs fed three different diet types (fish and amphibians, mixed protein with maize, and solely maize) using high-throughput sequencing. Results indicated that the dietary composition significantly influenced the gut microbiota, with notable differences in the abundance of several key phyla and genera. The study identified Firmicutes as the dominant phylum in all diet groups, with notable variations in the relative abundances of Bacteroidota, Proteobacteria, and Verrucomicrobiota. Notably, the group solely fed maize exhibited a significant increase in Proteobacteria, potentially linked to dietary fiber and lignin degradation. The genus-level analysis highlighted significant differences, with Lactobacillus and Bifidobacterium responding to dietary shifts. The genus Akkermansia in Verrucomicrobiota can be identified as a marker for assessing the health of the gut and deserves further investigation. Gender-specific differences in the gut microbiota were observed, highlighting the influence of individual variation. Furthermore, the analysis of bacterial functions suggested a connection between diet and host metabolism, emphasizing the need for further research to understand the complex mechanisms underlying the relationship between dietary composition and gut microbiota in wild animals. These findings provide crucial insights into conservation and rescue efforts for wild animals.

ABSTRACTLitter decomposition is critical for maintaining productivity and nutrient cycling in forest ecosystems. Large herbivores play an essential role in determining the processes of nutrient cycling. Asian temperate forests are becoming degraded and fragmented by the widespread intensification of anthropogenic activities, including excessive livestock grazing. However, the effects of livestock grazing and wild ungulates on forest litter decomposition remain less explored. In this study, we used a litterbag experiment to investigate the effects of the addition of cattle (Bos taurus) and sika deer (Cervus nippon) feces on litter decomposition. The study was conducted in Northeast China from July 2022 to October 2023. We found that the addition of deer feces significantly reduced litter decomposition, but the addition of cattle feces greatly increased litter decomposition. The presence of cattle and deer excrement significantly accelerated the release of C after 1 year of litter decomposition. Compared with the results of the control group (no addition of feces), the addition of cattle and sika deer feces increased C release by 37.45% and 22.69%, respectively. Fecal addition increased the release of N; however, for the three treatment groups, the maximum accumulation of N occurred in the middle of litter decomposition, which may have been due to the initial chemical quality of the leaves and snow melt as well as nutrient limitations at the sites. Compared with the results of the control group, P release in the feces of cattle increased by 4.35%, but P release in the feces of deer decreased by 27.55%. This work highlights that feces deposition by large herbivores (e.g., wild or domestic) in the forest has nonequivalent effects on litter decomposition. Such effects may further alter the nutrient cycling in temperate forest ecosystems, with far‐reaching effects on the ecosystem that deserve closer attention. We suggest that conservation managers should seek evidence‐based interventions to optimize livestock use of forest habitats shared with wildlife.

Aims:In light of the profound impact of urbanization on wildlife habitats,understanding the circadian activity patterns and ecological dynamics of urban terrestrial mammals is crucial for biodiversity conservation. Methods:This study employed 60 camera traps from November 2019 to November 2021 across urban areas of Tianjin,China,to assess the circadian rhythms and temporal overlaps of key terrestrial mammal species,such as dogs(Canis lupus),cats(Felis catus),Siberian weasels(Mustela sibirica),Amur hedgehogs(Erinaceus europaeus),Tolai hares(Lepus tolai)and Asian badgers(Meles leucurus).Various circadian rhythm indices,including mean vector,concentration,circular variance,activity level,and attributes,were utilized alongside kernel density estimation to determine temporal overlaps.Additionally,the study employed a generalized additive model(GAM)to explore the influence of urbanization level on temporal overlap coefficients. Results:With a sampling effort totaling 11,517 camera nights and 2,428 independent terrestrial mammal detections,the study revealed diverse activity patterns.Dogs were predominantly diurnal,while Siberian weasels,Amur hedgehogs,and Asian badgers exhibited nocturnal tendencies.Cats and Tolai hares displayed cathemeral behavior.Tolai hares exhibited the highest activity level(0.68,95％CI:0.56-0.73),whereas Asian badgers displayed the lowest(0.40,95％CI:0.29-0.44).Despite substantial(80％)temporal niche overlaps,according to the Mardia-Watson-Wheeler test results,significant differences were observed in diurnal activity patterns among species.For instance,cats and Siberian weasels demonstrated the highest temporal overlaps((^Δ)=0.88,95％CI:0.82-0.93),while dogs and Amur hedgehogs exhibited the lowest((^Δ)=0.35,95％CI:0.31-0.40).Moreover,the temporal niche overlap of cats-hedgehogs and hedgehogs-hares correlated positively with urbanization levels.In contrast,the overlap coefficient of dogs-hedgehogs showed a non-linear trend with the urbanization level. Conclusion:This pioneering study offers a systematic analysis of circadian rhythms in terrestrial mammals in urban areas of Tianjin,China.Findings underscore the considerable heterogeneity in circadian behaviors across mammalian species and unveil a nuanced multi-response model depicting temporal overlaps in response to urbanization levels.These insights contribute to understanding wildlife coexistence mechanisms within urban landscapes,and offer valuable guidance for the conservation and management of urban wildlife in China.