Search Results (25)

Spatiotemporal niche differentiation plays a critical role in facilitating mutual adaptation and sustaining coexistence among sympatric species. We investigated these patterns in sympatric ungulates through an infrared camera trap survey conducted in the Kazila Mountain region of southwestern China from July 2023 to May 2025. A total of seven species were recorded across 54 camera sites, with tufted deer (Elaphodus cephalophus) being the most frequently detected, while forest musk deer (Moschus berezovskii) and Chinese goral (Naemorhedus griseus) were the least. Nocturnality indices (β > 0.54 indicating nocturnal, β < 0.54 indicating diurnal, and β = 0.54 indicating no distinct diel preference) revealed significant differences in activity patterns among the five species. Tufted deer (β = 0.415), alpine musk deer (Moschus chrysogaster) (β = 0.438), and wild boar (Sus scrofa) (β = 0.234) were predominantly diurnal. In contrast, sambar (Rusa unicolor) (β = 0.571) was nocturnal, while the Chinese serow (Capricornis milneedwardsii) (β = 0.534) showed no strong diel preference. Nine of ten species pairs exhibited significant diel rhythm differences, with the exception of sambar-Chinese serow, and these rhythms showed marked seasonal variation, particularly in tufted deer, Chinese serow, and sambar. Temporal overlap was generally higher in the cold season for seven species pairs, suggesting that such overlap may be related to resource availability and increased interspecific competition under harsher conditions. Pianka’s overlap index (Oik) (ranging from 0 to 1, where 0 indicates no overlap and 1 indicates complete overlap) was used to assess spatial niche overlap, with values ranging from 0.16 (alpine musk deer–wild boar) to 0.86 (tufted deer–wild boar). Spatial autocorrelation and clustering analysis showed that tufted deer exhibited significant positive spatial autocorrelation, indicating a clustered high-value distribution, while the other species were randomly distributed. Spatial hotspot analysis revealed substantial overlap between tufted deer and wild boar, while the remaining species showed higher levels of spatial segregation. Collectively, these results suggest that seasonal variation in activity patterns, coupled with spatial segregation, mitigates interspecific competition and supports the stable sympatric coexistence of ungulates in this montane ecosystem. Full article

Bactrocera dorsalis (Hendel, 1912) is a highly destructive pest affecting fruits and vegetables, making population monitoring essential for farmers to implement timely control measures. In recent years, although automatic monitoring systems for B. dorsalis have been introduced, challenges such as limited accuracy, difficulty in accurately identifying the target pest using infrared interruption sensors alone, and high labor requirements persist. This study presents an automatic monitoring system consisting of intelligent bait equipment (IBE), an advanced detection model based on YOLOv8, and an online monitoring platform. The developed IBE is equipped with cameras, attractant-based lures, and an automatic removal mechanism for B. dorsalis. Field tests demonstrated the IBE exhibited an attractiveness to B. dorsalis comparable to conventional traps, achieved a near-perfect cleaning efficiency (~100%), and maintained a reliable wireless transmission system. The YOLOv8l-based automatic pest detection model outperformed other YOLOv8 variants (n, s, m, x), achieving the highest precision (95.17%), recall (94.15%) and F1 score (94.66%), underscoring its effectiveness in pest detection. Further analysis of the impact of B. dorsalis density on YOLOv8l’s detection performance revealed a decline in accuracy as density increased; however, even at high densities, the model maintained a strong F1 score of 93.36%, demonstrating robustness. Finally, the automatic pest detection model was integrated into ‘YunShanPu’, an online platform for real-time pest monitoring. The proposed method has demonstrated promising performance in the automatic identification and counting of B. dorsalis and has potential for monitoring B. dorsalis populations continuously, providing early warning and forecasting for integrated pest management. Full article

Understanding how prey and predator species partition activity patterns across time and space is essential for elucidating behavioral adaptation and ecological coexistence. In this study, we examined the diel and seasonal activity rhythms of two sympatric rodent species—Rhombomys opimus (Great gerbil) and Meriones meridianus (Midday gerbil)—and their primary predators, Otocolobus manul (Pallas’s cat) and Vulpes vulpes (Red fox), in a desert-steppe ecosystem on the northern slopes of the Qilian Mountains, China. Using over 8000 camera trap days and kernel density estimation, we quantified their activity intensity and spatiotemporal overlap. The two rodent species showed clear temporal niche differentiation but differed in their synchrony with predators. R. opimus exhibited a unimodal diurnal rhythm with spring activity peaks, while M. meridianus showed stable nocturnal activity with a distinct autumn peak. Notably, O. manul adjusted its activity pattern to partially align with that of R. opimus, whereas V. vulpes maintained a crepuscular–nocturnal rhythm overlapping more closely with that of M. meridianus. Despite distinct temporal rhythms, both rodent species shared high spatial overlap with their predators (overlap index OI = 0.64–0.83). These findings suggest that temporal partitioning may reduce predation risk for R. opimus, while M. meridianus co-occurs more extensively with its predators. Our results highlight the ecological role of native carnivores in rodent population dynamics and support their potential use in biodiversity-friendly rodent management strategies under arid grassland conditions. Full article

Activity patterns constitute a critical adaptive trait in large carnivores, enabling them to manage interspecific competition, enhance their foraging efficiency, and adapt to fluctuating environmental conditions. At the community level, elucidating the temporal activity allocation of sympatric large carnivores is essential for understanding species coexistence mechanisms. However, the activity patterns of most large carnivores remain inadequately explored. In this study, spanning a survey period from June 2014 to April 2024, we employed infrared camera technology to collect a total of 3312, 352, 240, and 79 independently validated photographs of snow leopards (Panthera uncia Schreber, 1775), wolves (Canis lupus Linnaeus, 1758), brown bears (Ursus arctos Linnaeus, 1758), and Eurasian lynx (Lynx lynx Linnaeus, 1758), respectively, across six distinct regions in the Sanjiangyuan Region (SR) and during different monitoring time periods. We utilized kernel density estimation and the coefficient of overlaps to assess diel activity pattern overlap and competitive intensities through pairwise comparisons among these four large carnivores. An analysis of the diel activity rhythm curves revealed that all four large carnivores predominantly exhibited nocturnal behavior, although their peak activity periods differed notably. Furthermore, the diel activity rhythm overlap between each pair of species showed moderate to high intensity throughout the year (0.5 ≤ Δ < 1), including during both the cold and warm seasons. Specifically, the diel activity rhythms of snow leopards and wolves, snow leopards and Eurasian lynx, and wolves and Eurasian lynx exhibited high levels of overlap annually and during the cold season (0.8 ≤ Δ < 1) but only moderate overlap during the warm season (0.5 ≤ Δ < 0.8). Our findings suggest that the diel activity rhythms of these four large carnivore species exhibited considerable overlap, potentially intensifying interspecific competition. This study advances our knowledge on the competitive and coexistence mechanisms of large carnivores in high-altitude mountainous ecosystems, offering critical data for their conservation and management. Full article

The growing population of wild boars (Sus scrofa) in all highly anthropized countries represents a current challenge for the protection of ecosystems, agriculture and urban environments. This study introduces an innovative capture solution based on IoT systems designed to enable the selective capture of sub-adult wild boars in an ethical manner and minimize stress and bycatch. Conducted over five years in a Natura 2000 area in Campania, Italy, the research integrates advanced technologies, including AI-based infrared cameras, LoRa communication and autonomous feeding systems, to monitor, control and operate a specially designed selective cage trap. The results obtained demonstrate how technological innovation improves wildlife and hunting management by selecting younger animals without interfering with group dynamics. Selective capture ensures healthy population control, does not conflict with hunting and reduces pressure on habitats, especially if these fall within areas of particular importance for European biodiversity. Full article

Grouping behavior is a fundamental component of animal population dynamics, shaped by both environmental factors and the social interactions among individuals, ultimately enhancing adaptability to their habitats. However, the social organization of the wapiti subspecies inhabiting the Tian Shan Mountains remains poorly understood. In this study, we investigated the grouping behavior of Tianshan wapiti in the Bogda Peak Nature Reserve, northwestern China from July 2019 to November 2020. Using infrared-triggered camera traps, we analyzed seasonal variation in group size and group frequency, as well as sex-specific aggregation and segregation pattern. Our results showed that Tianshan wapiti group sizes varied considerably, ranging from 1 to 32 individuals, with most groups being relatively smaller, typically consisting of 1 to 9 individuals. Seasonal differences in group size were significant (H = 28.91, df = 3, p < 0.05). Additionally, group type showed significant variation across seasons (χ² = 93.32, df = 18, p < 0.05). Anakysis of sex-specifia aggregation and segregation (SSAS) indicated no consistent segregation of females and males throughout the year. However, there was a notable tendency for sex-specific aggregation during July and from October to December. These findings provide new insights into the social organization and seasonal grouping behavior of Tianshan wapiti, contributing to a better understanding of their behavioral ecology and informing conservation and management strategies for this subspecies. Full article

In traditional pest monitoring, specimens are manually inspected, identified, and counted. These techniques can lead to poor data quality and hinder effective pest management decisions due to operational and economic limitations. This study aimed to develop an automatic detection and early warning system using the European Pepper Moth, Duponchelia fovealis (Lepidoptera: Crambidae), as a study model. A prototype water trap equipped with an infrared digital camera controlled using a microprocessor served as the attraction and capture device. Images captured by the system in the laboratory were processed to detect objects. Subsequently, these objects were labeled, and size and shape features were extracted. A machine learning model was then trained to identify the number of insects present in the trap. The model achieved 99% accuracy in identifying target insects during validation with 30% of the data. Finally, the prototype with the trained model was deployed in the field for result confirmation. Full article

The global focus on fostering harmonious interactions and promoting rational coexistence among wildlife species to uphold or reinstate biodiversity remains a prominent area of interest. We conducted a study on the sable and yellow-throated marten in Taipinggou National Nature Reserve, Heilongjiang, China, using the line transect method and infrared camera traps from 2022 to 2023. We then analyzed the overlap of their suitable habitats and niches with the aim of gaining insight into the interspecific competition between these two species. We found that the suitable habitat areas for the sable and yellow-throated marten were 55.20 km² and 23.28 km², accounting for 24.86% and 10.48% of the total area of this study, respectively. The overlap between the suitable habitats for the sable and yellow-throated marten was 15.73 km², accounting for 28.5% and 67.6% of their suitable habitat, supporting our Hypothesis 1. The first principal component (Dim1) of the niche explained 35.4% of the overall variability, which is mainly related to the environmental variables “Distance from Settlements” and “Distance from Roads”. Overall, 25.5% of the total variability was explained by the second principal component (Dim2), associated with “Slope” and “Distance from Coniferous and Broadleaved Mixed Forest”. The niches occupied by the sable and yellow-throated marten were both off-center of the environmental background space, with the niches of the sable being larger than those of the yellow-throated marten. Schoener’s D index was 0.56, indicating a high degree of niche overlap between the sable and yellow-throated marten, supporting our Hypothesis 2. Our study is helpful in terms of formulating conservation and management policies for the sable and yellow-throated marten. Full article

Understanding the mechanisms by which tropical forest fragmentation can affect the persistence of species and populations is of scientific and practical interest. However, nest survival has been one the least addressed of the potentially harmful effects associated with habitat fragmentation, and studies involving nest predator’s identification are still underdeveloped. The Pernambuco Endemism Center (PEC) is the part of the Atlantic Forest located north of the São Francisco River, in northeastern Brazil, where large forest tracts no longer exist and a wave of bird extinctions has occurred recently. Here, we investigated the nest survival of forest understory birds from three PEC fragments (690, 979, and 1036 ha), and we used infra-red camera traps for predators’ identification. Overall, the apparent nest survival was 15.5%, and nest-day-based survival probability for the four more representative species (including two endemic and threatened taxa) were 2.6, 4.4, 6.9, and 18.9%, being 2.7 to 8.5 times smaller than populations or related taxa from the Atlantic Forest of southeastern Brazil. Predators were marmosets (25%), opossums (25%), tegu (19.4%), coati (16.7%), snakes (8.3%), and hawks (5.5%). Jackknife2 model-predicted nest predator’s richness was 20.7 (SD = 1.6). We reinforce the evidence that nest predation associated with fragmentation can affect negatively the bird populations from tropical forests. Full article

Camera traps, an invaluable tool for biodiversity monitoring, capture wildlife activities day and night. In low-light conditions, near-infrared (NIR) imaging is commonly employed to capture images without disturbing animals. However, the reflection properties of NIR light differ from those of visible light in terms of chrominance and luminance, creating a notable gap in human perception. Thus, the objective is to enrich near-infrared images with colors, thereby bridging this domain gap. Conventional colorization techniques are ineffective due to the difference between NIR and visible light. Moreover, regular supervised learning methods cannot be applied because paired training data are rare. Solutions to such unpaired image-to-image translation problems currently commonly involve generative adversarial networks (GANs), but recently, diffusion models gained attention for their superior performance in various tasks. In response to this, we present a novel framework utilizing diffusion models for the colorization of NIR images. This framework allows efficient implementation of various methods for colorizing NIR images. We show NIR colorization is primarily controlled by the translation of the near-infrared intensities to those of visible light. The experimental evaluation of three implementations with increasing complexity shows that even a simple implementation inspired by visible-near-infrared (VIS-NIR) fusion rivals GANs. Moreover, we show that the third implementation is capable of outperforming GANs. With our study, we introduce an intersection field joining the research areas of diffusion models, NIR colorization, and VIS-NIR fusion. Full article

Global warming is influenced by an increase in greenhouse gas (GHG) concentration in the atmosphere. Consequently, Net Ecosystem Exchange (NEE) is the main factor that influences the exchange of carbon (C) between the atmosphere and the soil. As a result, agricultural ecosystems are a potential carbon dioxide (CO₂) sink, particularly rice paddies (Oryza sativa). Therefore, a static chamber with a portable CO₂ analyzer was designed and implemented for three rice plots to monitor CO₂ emissions. Furthermore, a weather station was installed to record meteorological variables. The vegetative, reproductive, and maturation phases of the crop lasted 95, 35, and 42 days post-sowing (DPS), respectively. In total, the crop lasted 172 DPS. Diurnal NEE had the highest CO₂ absorption capacity at 10:00 a.m. for the tillering stage (82 and 89 DPS), floral primordium (102 DPS), panicle initiation (111 DPS), and flowering (126 DPS). On the other hand, the maximum CO₂ emission at 82, 111, and 126 DPS occurred at 6:00 p.m. At 89 and 102 DPS, it occurred at 4:00 and 6:00 a.m., respectively. NEE in the vegetative stage was −25 $\mathsf{\mu }\mathrm{m}\mathrm{o}\mathrm{l}\mathrm{C}\mathrm{O}2 {\mathrm{m}}^2 {\mathrm{s}}^{-1}$, and in the reproductive stage, it was −35 $\mathsf{\mu }\mathrm{m}\mathrm{o}\mathrm{l}\mathrm{C}\mathrm{O}2 {\mathrm{m}}^2 {\mathrm{s}}^{-1}$, indicating the highest absorption capacity of the plots. The seasonal dynamics of NEE were mainly controlled by the air temperature inside the chamber (Tc) (R = −0.69), the relative humidity inside the chamber (RHc) (R = −0.66), and net radiation (R_n) (R = −0.75). These results are similar to previous studies obtained via chromatographic analysis and eddy covariance (EC), which suggests that the portable analyzer could be an alternative for CO₂ monitoring. Full article

We evaluated the hourly dynamics of ground-dwelling invertebrate communities in farmland using infrared camera traps between August and September 2022. No significant variations within 24 h nor between any two time points of each day were observed in the taxonomic richness and abundance of the entire community. However, the periods from 4:00 to 7:00 and 13:00 to 20:00 showed relatively high taxonomic richness, while those from 2:00 to 6:00 and 16:00 to 21:00 showed relatively high abundance. Millipede abundance varied significantly in a 24 h period, with higher abundance from 3:00 to 4:00 and 1:00 to 2:00. Additionally, slug, beetle, and grasshopper abundances were significantly higher from 22:00 to 23:00, 17:00 to 18:00, and 23:00 to 24:00, respectively. The abundance of other taxa did not show significant variations between any two time points of a day. Predominant generalist predators showed positive correlation in their activity times. These results suggest that significant variations within each 24 h period are uncommon at either community or taxa (except for millipedes) levels in farmland ground-dwelling invertebrates. Further, while most taxa had significantly preferred active hours, the total community did not. Therefore, hourly dynamics should be considered to understand biodiversity maintenance. Full article

Mammalian DNA derived from invertebrates (iDNA), including blowfly iDNA, is an alternative tool to conventional camera trapping in assessing mammalian diversity. The method has been used in tropical mammal surveillance but no attempt has been made to compare the efficacy of blowfly iDNA and camera trapping for monitoring mammal diversity in subtropical forests. We compared the blowfly iDNA monitoring with camera trapping to assess mammal diversity in the subtropical Jiulongfeng Nature Reserve (JLF), China, over a one-month period. The camera traps captured 2508 animal photos of 11 species belonging to four orders, eight genera, and eight families, whereas the blowfly iDNA method successfully detected ten species from six orders, eight genera, and eight families in JLF. Both methods were complementing each other instead of competing due to the low overlaps of mammal species detected. Of the total number of mammal species listed in JLF’s threatened list, 40% and 10% were detected through camera traps and blowfly iDNA methods, respectively. The estimated species richness curves indicated that combining camera traps and blowfly traps would increase the detection of mammal species. The strategy would significantly contribute to mammalian diversity surveillance and conservation programs in the tropical and subtropical forests. Full article

The habitat plays a crucial role in ensuring the survival of wildlife. However, the increasing disturbances caused by human activities present a substantial threat to habitats, especially for species such as the leopard cat (Prionailurus bengalensis), which is a significant small predator. Currently, research on leopard cats predominantly focuses on low-altitude regions within its distribution range, leaving plateau areas understudied. To enhance our understanding of the impact of human disturbances on leopard cat habitats, we undertook a study employing infrared camera trappings to monitor leopard cats’ activity in Xinlong of southwestern China between 2015 and 2023. We analyzed the spatial distribution and habitat suitability of the leopard cats by utilizing ensemble species distribution models (ESDMs). Moreover, we employed two-species occupancy models to investigate the spatial interaction between leopard cats and human disturbances. The results indicated that (1) the potential suitable habitat area for leopard cats encompassed approximately 1324.93 km² (14.3%), primarily located along the banks of Yalong river. (2) The distribution of suitable habitat was predominantly influenced by competitors, specifically the yellow-throated marten (YTM), accounting for 52.4% of the influence, as well as environmental factors such as distance to water (DTW) at 12.0% and terrain roughness index (TRI) at 10.0%. Human interference, including cattle presence (4.6%), distance to road (DTD, 4.9%), and distance to settlement (DTS, 3.5%), had a limited impact on the habitat distribution. (3) Within a 5 km radius, habitat suitability increased with proximity to human settlements. (4) Leopard cats exhibited spatial independence from humans and domestic cattle (species interaction factor (SIF) = 1.00) while avoiding domestic horses (SIF = 0.76 ± 0.03). The relatively minor impact of human disturbances in Xinlong could be attributed to traditional cultural practices safeguarding wildlife and the leopard cat’s environmental adaptability. We recommend establishing a novel conservation paradigm based on the living dynamics of wildlife communities in Xinlong, thereby offering a more targeted approach to biodiversity preservation in the future. Full article

To reduce the use of insecticides, silo operators are reconsidering their practices and implementing integrated pest management (IPM) to manage insect infestations. IPM requires the early detection of insects to react before infestation spread or to isolate infested lots. Depending on their position in the storage and handling chain, operators will favor monitoring or rapid detection tools. To simplify monitoring in storage, an internet-connected trap has been designed. It includes a camera located above a tank that allows for the captured insects to be counted. A total of 89 traps were installed in elevators for a proof-of-concept phase. Compared to sample monitoring, the traps detected an average of three additional insect species in an infested batch. To improve the detection of insects in wheat, methods for detecting and quantifying live adult insects (Sitophilus oryzae, Rhyzoperta dominica, and Tribolium confusum) using NIRS and HSI have been developed. The used instruments, a near-infrared spectrometer and a hyperspectral camera, allow for an in-flow analysis, which reduces sampling errors. The cross-validation errors of the NIRS models ranged from 2.44 insects/kg to 2.56 insects/kg, and the prediction error of the HSI ones ranged from 0.70 insect/kg to 2.07 insect/kg, depending on the insect species. Full article