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Use of Camera Trap for a Better Wildlife Monitoring and Conservation

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A special issue of Animals (ISSN 2076-2615). This special issue belongs to the section "Ecology and Conservation".

Deadline for manuscript submissions: closed (25 April 2023) | Viewed by 44510

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Special Issue Editor

Dr. Limin Feng

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Guest Editor

College of Life Science, Beijing Normal University, Beijing 100875, China
Interests: big cats; apex carnivore; predator-prey interaction; human-wildlife coexistence; habitat; animal behaviour; camera trapping; survey and monitoring of biodiversity; advanced technique on conservation; ecology and evolution; interdisciplinary research; environmental education

Special Issue Information

Dear Colleagues,

The application of camera traps is one of the fastest developing and most widely used technology in wildlife monitoring and conservation in the past 20 years. A camera trap can detect cryptic wildlife, and their operation is convenient. They can obtain massive first-hand pictures or video data in the field, providing abundant information for understanding the individual, population, community, behavior and habitat of wildlife. This Special Issue will collect original research and reviews related to camera traps in ecology and wildlife biology, especially regarding the innovation of methodology and technology. Potential topics include:

The field methodology of a camera trap.
The data processing methods of camera traps.
Application of camera traps in species distribution, population and community.
Application of camera traps in animal behavior.
Application of camera traps in conservation biology.
Application of camera traps in habitat and conservation management.
Innovative application of camera traps.

Dr. Limin Feng
Guest Editor

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Keywords

camera trap
population ecology
conservation biology
animal behaviour
wildlife management
innovative application
methodology
data processing of camera trap

Published Papers (14 papers)

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Research

13 pages, 2229 KiB

Open AccessArticle

Camera Traps Uncover the Behavioral Ecology of an Endemic, Cryptic Monkey Species in the Congo Basin

by Charlene S. Fournier, Steven McPhee, Junior D. Amboko and Kate M. Detwiler

Animals 2023, 13(11), 1819; https://doi.org/10.3390/ani13111819 - 31 May 2023

Viewed by 1173

Abstract

Guenons are the most diverse clade of African primates, and many species living within the core of the Congo Basin rainforest are still understudied. The recently described guenon species, Cercopithecus lomamiensis, known as lesula, is a cryptic, semi-terrestrial species endemic to the central Congo Basin in the Democratic Republic of the Congo. The recent IUCN Red List Assessment recognizes lesula’s risk of extinction in the wild as Vulnerable. The objective of our study was to use camera traps to expand knowledge on the behavioral ecology of lesula. We conducted three systematic, terrestrial camera trap (CT) surveys within Lomami National Park and buffer zone (Okulu: 2013; Losekola: 2014; E15: 2015). We accumulated 598 independent events of lesula over 5960 CT days from 92 CTs. Typical of Cercopithecus species, camera trap videos reveal that lesula has a diurnal activity pattern, birth seasonality, a group size of up to 32 individuals, and social organization with female philopatry and male dispersal. Results also suggest that lesula are highly terrestrial, distinguishing them from other Cercopithecus species, which are mostly arboreal. Our study provides new information about the behavioral ecology of this little-studied primate, generating species-specific knowledge of a threatened species for successful conservation planning. Full article

(This article belongs to the Special Issue Use of Camera Trap for a Better Wildlife Monitoring and Conservation)

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24 pages, 24750 KiB

Open AccessArticle

Animal Species Recognition with Deep Convolutional Neural Networks from Ecological Camera Trap Images

by Sazida Binta Islam, Damian Valles, Toby J. Hibbitts, Wade A. Ryberg, Danielle K. Walkup and Michael R. J. Forstner

Animals 2023, 13(9), 1526; https://doi.org/10.3390/ani13091526 - 02 May 2023

Cited by 8 | Viewed by 5794

Abstract

Accurate identification of animal species is necessary to understand biodiversity richness, monitor endangered species, and study the impact of climate change on species distribution within a specific region. Camera traps represent a passive monitoring technique that generates millions of ecological images. The vast numbers of images drive automated ecological analysis as essential, given that manual assessment of large datasets is laborious, time-consuming, and expensive. Deep learning networks have been advanced in the last few years to solve object and species identification tasks in the computer vision domain, providing state-of-the-art results. In our work, we trained and tested machine learning models to classify three animal groups (snakes, lizards, and toads) from camera trap images. We experimented with two pretrained models, VGG16 and ResNet50, and a self-trained convolutional neural network (CNN-1) with varying CNN layers and augmentation parameters. For multiclassification, CNN-1 achieved 72% accuracy, whereas VGG16 reached 87%, and ResNet50 attained 86% accuracy. These results demonstrate that the transfer learning approach outperforms the self-trained model performance. The models showed promising results in identifying species, especially those with challenging body sizes and vegetation. Full article

(This article belongs to the Special Issue Use of Camera Trap for a Better Wildlife Monitoring and Conservation)

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15 pages, 1655 KiB

Open AccessArticle

Temporal Activity Patterns of Sympatric Species in the Temperate Coniferous Forests of the Eastern Qinghai-Tibet Plateau

by Jia Jia, Yun Fang, Xinhai Li, Kai Song, Wendong Xie, Changli Bu and Yuehua Sun

Animals 2023, 13(7), 1129; https://doi.org/10.3390/ani13071129 - 23 Mar 2023

Cited by 2 | Viewed by 1495

Abstract

Temporal niche partitioning is an important strategy for sympatric species or populations when utilizing limited resources while minimizing competition. Different resource availability across seasons may also influence the intensity of competition, resulting in a varied temporal niche partitioning pattern between species. These competitive interactions are important drivers for the formation of biodiversity patterns and species coexistence on the eastern Qinghai-Tibet Plateau. To clarify these interspecies relationships among sympatric species, we carried out a camera trap survey from 2017 to 2020. We deployed 60 camera traps in the temperate coniferous forests of the eastern Qinghai-Tibet Plateau. We analyzed the daily activity patterns of birds and mammals to reveal the temporal niches and seasonal relationships among the species-specific activity rhythms. The results are summarized as follows: (1) Eight major species, including mammals and birds, have different temporal peak activity rhythms to reduce intense competition for resources. (2) The activity rhythm of a species varies seasonally, and the competition among species is more intense in the warm season than in the cold season. (3) Among 15 pairs of competitor species, seven pairs had significantly different coefficients, with higher winter values than summer values, perhaps due to the abundance of resources in summer and the scarcity of resources in winter causing intensified competition. Among the predators and prey, the summertime coefficients were higher than those in winter, perhaps due to the need to replenish energy during the summer breeding season. The main purpose of animals in winter is to survive the harsh environment. Our results provide important information on temporal and interspecies relationships and contribute to a better understanding of species-coexistence mechanisms. Full article

(This article belongs to the Special Issue Use of Camera Trap for a Better Wildlife Monitoring and Conservation)

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11 pages, 2770 KiB

Open AccessArticle

Ungulates’ Behavioral Responses to Humans as an Apex Predator in a Hunting-Prohibited Area of China

by Mingzhang Liu, William J. McShea, Yidan Wang, Fan Xia, Xiaoli Shen and Sheng Li

Animals 2023, 13(5), 845; https://doi.org/10.3390/ani13050845 - 25 Feb 2023

Cited by 3 | Viewed by 1741

Abstract

Large mammals can perceive humans as predators and therefore adjust their behavior to achieve coexistence with humans. However, lack of research at sites with low hunting intensity limits our understanding of how behavioral responses of animals adapt to different predation risks by humans. At Heshun County in North China, where hunting has been banned for over three decades and only low-intensity poaching exists, we exposed two large ungulates (Siberian roe deer Capreolus pygarus and wild boar Sus scrofa) to the sounds of humans, an extant predator (leopard Panthera pardus) and a control (wind), and examined their flight responses and detection probabilities when hearing different type of sounds. Both species showed higher flight probabilities when hearing human vocalization than wind, and wild boar were even more likely to flee upon hearing human vocalization than leopard roar, suggesting the behavioral response to humans can equal or exceed that of large carnivores in these two ungulates even in an area without hunting practices. Recorded sounds had no effect on detection probability of both ungulates. Additionally, with repeated exposure to sounds, regardless of treatment, roe deer were less likely to flee and wild boars were more likely to be detected, indicating a habituation-type response to sound stimuli. We speculate that the immediate flight behavior rather than shifts in habitat use of the two species reflect the low hunting/poaching pressure at our study site and suggest further examination of physiological status and demographic dynamics of the study species to understand human influence on their long-term persistence. Full article

(This article belongs to the Special Issue Use of Camera Trap for a Better Wildlife Monitoring and Conservation)

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16 pages, 7163 KiB

Open AccessArticle

A Lightweight Automatic Wildlife Recognition Model Design Method Mitigating Shortcut Learning

by Yujie Zhong, Xiao Li, Jiangjian Xie and Junguo Zhang

Animals 2023, 13(5), 838; https://doi.org/10.3390/ani13050838 - 25 Feb 2023

Cited by 4 | Viewed by 1299

Abstract

Recognizing wildlife based on camera trap images is challenging due to the complexity of the wild environment. Deep learning is an optional approach to solve this problem. However, the backgrounds of images captured from the same infrared camera trap are rather similar, and shortcut learning of recognition models occurs, resulting in reduced generality and poor recognition model performance. Therefore, this paper proposes a data augmentation strategy that integrates image synthesis (IS) and regional background suppression (RBS) to enrich the background scene and suppress the existing background information. This strategy alleviates the model’s focus on the background, guiding it to focus on the wildlife in order to improve the model’s generality, resulting in better recognition performance. Furthermore, to offer a lightweight recognition model for deep learning-based real-time wildlife monitoring on edge devices, we develop a model compression strategy that combines adaptive pruning and knowledge distillation. Specifically, a student model is built using a genetic algorithm-based pruning technique and adaptive batch normalization (GA-ABN). A mean square error (MSE) loss-based knowledge distillation method is then used to fine-tune the student model so as to generate a lightweight recognition model. The produced lightweight model can reduce the computational effort of wildlife recognition with only a 4.73% loss in accuracy. Extensive experiments have demonstrated the advantages of our method, which is beneficial for real-time wildlife monitoring with edge intelligence. Full article

(This article belongs to the Special Issue Use of Camera Trap for a Better Wildlife Monitoring and Conservation)

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15 pages, 2040 KiB

Open AccessArticle

Temporal Response of Mesocarnivores to Human Activity and Infrastructure in Taihang Mountains, Central North China: Shifts in Activity Patterns and Their Overlap

by Yanzhi Chen, Beibei Liu, Deqing Fan and Sheng Li

Animals 2023, 13(4), 688; https://doi.org/10.3390/ani13040688 - 16 Feb 2023

Cited by 2 | Viewed by 1785

Abstract

Mesocarnivores play essential roles in terrestrial ecosystems, but anthropocentric disturbances have profoundly transformed their intraguild interactions worldwide. In this study, we explored how a guild of four mesocarnivores (red fox Vulpes vulpes, leopard cat Prionailurus bengalensis, Asian badger Meles leucurus, and hog badger Arctonyx collaris) partition their temporal niche in the temperate montane forests in North China under different human influences. We conducted a systemic camera-trapping survey on the study species in the central Taihang Mountains from 2016 to 2020. With an extensive survey effort of 111,063 camera-days from 187 camera stations, we obtained 10,035 independent detections of the four mesocarnivores and examined the activity patterns of each species under different levels of human disturbance and their overlaps. The results showed that, while the leopard cat and the badgers shifted their activity towards nocturnality, the red fox showed no significant change. The leopard cat’s degree of nocturnality varied between growing and non-growing seasons, likely a response to avoid humans and other competitors. However, the activity overlaps between species pairs demonstrated no statistically significant difference, indicating a long-developed coexistence mechanism that is homogenous across the landscape. Demonstrating how mesocarnivores shift activity patterns in response to human risks while partitioning resources, this study enhances our understanding of mesocarnivore behavioral changes and interspecific interactions at human–nature interfaces. Full article

(This article belongs to the Special Issue Use of Camera Trap for a Better Wildlife Monitoring and Conservation)

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14 pages, 2298 KiB

Open AccessArticle

The Ecological Roles of Medium and Small Carnivores in the Terrestrial Animal Community in Liancheng National Nature Reserve, China

by Tengwei Su, Qian Li, Xiaojuan Wang, Guofa Cui, Zihong Man, Wentao Li and Minyan Zhao

Animals 2022, 12(24), 3518; https://doi.org/10.3390/ani12243518 - 13 Dec 2022

Cited by 1 | Viewed by 2930

Abstract

It is vitally important to understand the ecological roles of medium and small carnivores in the context of the massive decline in the number of large carnivores around the world. Based on a spatial association network of terrestrial birds and mammals, this study analyzed the ecological roles of medium and small carnivores in the community in Liancheng National Nature Reserve. From October 2019 to June 2020, we obtained 3559 independent detections of 20 terrestrial birds and mammals from 112 camera traps. There are seven species that are medium and small carnivores present in the study area, including red fox (Vulpes vulpes), leopard cat (Prionailurus bengalensis), Chinese mountain cat (Felis bieti), stone marten (Martes foina), Asian badger (Meles leucurus), Siberian weasel (Mustela sibirica) and mountain weasel (Mustela altaica). By calculating the Phi coefficient of all species pairs, a spatial association network composed of twelve species was constructed. We analyzed the characterization of spatial associations by the Shannon–Wiener index and Lambda statistic. The results showed that: (1) the status of the network reflects the changes of community composition and structure after the decline in large carnivores and other species; (2) with the exception of the Chinese mountain cat and stone marten, the other five medium and small carnivores were located in the network, which played an important role in the complexity of the network and the maintenance of the community; (3) the medium and small carnivores could not take the place of the large carnivores in order to control the population of herbivores, such as Siberian roe deer (Capreolus pygargus) and Himalayan marmot (Marmota himalayana). The results of this study provide guidance for determining the direction and focus of conservation efforts. Full article

(This article belongs to the Special Issue Use of Camera Trap for a Better Wildlife Monitoring and Conservation)

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12 pages, 4690 KiB

Open AccessArticle

Spatio-Temporal Niche of Sympatric Tufted Deer (Elaphodus cephalophus) and Sambar (Rusa unicolor) Based on Camera Traps in the Gongga Mountain National Nature Reserve, China

by Zhiyuan You, Bigeng Lu, Beibei Du, Wei Liu, Yong Jiang, Guangfa Ruan and Nan Yang

Animals 2022, 12(19), 2694; https://doi.org/10.3390/ani12192694 - 07 Oct 2022

Cited by 3 | Viewed by 2296

Abstract

Clarifying the distribution pattern and overlapping relationship of sympatric relative species in the spatio-temporal niche is of great significance to the basic theory of community ecology and integrated management of multi-species habitats in the same landscape. In this study, based on a 9-year dataset (2012–2021) from 493 camera-trap sites in the Gongga Mountain National Nature Reserve, we analyzed the habitat distributions and activity patterns of tufted deer (Elaphodus cephalophus) and sambar (Rusa unicolor). (1) Combined with 235 and 153 valid presence sites of tufted deer and sambar, the MaxEnt model was used to analyze the distribution of the two species based on 11 ecological factors. The distribution areas of the two species were 1038.40 km² and 692.67 km², respectively, with an overlapping area of 656.67 km². Additionally, the overlap indexes Schoener’s D (D) and Hellinger’s-based I (I) were 0.703 and 0.930, respectively. (2) Based on 10,437 and 5203 independent captures of tufted deer and sambar, their daily activity rhythms were calculated by using the kernel density estimation. The results showed that the daily activity peak in the two species appeared at dawn and dusk; however, the activity peak in tufted deer at dawn and dusk was later and earlier than sambar, respectively. Our findings revealed the spatio-temporal niche relationship between tufted deer and sambar, contributing to a further understanding of the coexistence mechanism and providing scientific information for effective wild animal conservation in the reserve and other areas in the southeastern edge of the Qinghai–Tibetan Plateau. Full article

(This article belongs to the Special Issue Use of Camera Trap for a Better Wildlife Monitoring and Conservation)

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16 pages, 5283 KiB

Open AccessArticle

Animal Detection and Classification from Camera Trap Images Using Different Mainstream Object Detection Architectures

by Mengyu Tan, Wentao Chao, Jo-Ku Cheng, Mo Zhou, Yiwen Ma, Xinyi Jiang, Jianping Ge, Lian Yu and Limin Feng

Animals 2022, 12(15), 1976; https://doi.org/10.3390/ani12151976 - 04 Aug 2022

Cited by 19 | Viewed by 7416

Abstract

Camera traps are widely used in wildlife surveys and biodiversity monitoring. Depending on its triggering mechanism, a large number of images or videos are sometimes accumulated. Some literature has proposed the application of deep learning techniques to automatically identify wildlife in camera trap imagery, which can significantly reduce manual work and speed up analysis processes. However, there are few studies validating and comparing the applicability of different models for object detection in real field monitoring scenarios. In this study, we firstly constructed a wildlife image dataset of the Northeast Tiger and Leopard National Park (NTLNP dataset). Furthermore, we evaluated the recognition performance of three currently mainstream object detection architectures and compared the performance of training models on day and night data separately versus together. In this experiment, we selected YOLOv5 series models (anchor-based one-stage), Cascade R-CNN under feature extractor HRNet32 (anchor-based two-stage), and FCOS under feature extractors ResNet50 and ResNet101 (anchor-free one-stage). The experimental results showed that performance of the object detection models of the day-night joint training is satisfying. Specifically, the average result of our models was 0.98 mAP (mean average precision) in the animal image detection and 88% accuracy in the animal video classification. One-stage YOLOv5m achieved the best recognition accuracy. With the help of AI technology, ecologists can extract information from masses of imagery potentially quickly and efficiently, saving much time. Full article

(This article belongs to the Special Issue Use of Camera Trap for a Better Wildlife Monitoring and Conservation)

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19 pages, 5714 KiB

Open AccessArticle

Temporal and Spatial Activity Patterns of Sympatric Wild Ungulates in Qinling Mountains, China

by Jia Li, Yadong Xue, Mingfu Liao, Wei Dong, Bo Wu and Diqiang Li

Animals 2022, 12(13), 1666; https://doi.org/10.3390/ani12131666 - 28 Jun 2022

Cited by 6 | Viewed by 2368

Abstract

Dramatic increases in populations of wild ungulates have brought a new ecological issue in the Qinling mountains. Information on species’ niche differentiation will contribute to a greater understanding of the mechanisms of coexistence, so as to ultimately benefit the conservation and management of ecological communities. In this study, camera trapping was used to investigate spatial and temporal activity patterns of sympatric wild ungulates in the Qinling Mountains of China, where top predators were virtually absent. We obtained 15,584 independent detections of seven wild ungulate species during 93,606 camera-trap days from April 2014 to October 2017. Results showed that (i) the capture rate differed significantly across species, with the capture rate of reeve muntjac being significantly higher than that of other species; (ii) the wild boar had a higher occupancy rates (ψ = 0.888) than other six ungulates, and distance to settlements had a negative relationship with wild boar (β = −0.24 ± 0.17); (iii) the forest musk deer and mainland serow had low spatial overlaps with other five wild ungulates, while spatial overlap indices of any two given pairs of wild ungulates were relatively high; (iv) all wild ungulates species (expect wild boar) were mainly active during crepuscular and diurnal periods, and showed bimodal activity peaks at around 05:00–07:00 and 17:00–19:00; and finally, (v) all wild ungulates showed moderate to high temporal overlaps. The results provided detailed information of the spatial and temporal ecology of wild ungulate communities in forest ecosystems of China, which also would be a guide to establish conservation priorities as well as efficient management programs. Full article

(This article belongs to the Special Issue Use of Camera Trap for a Better Wildlife Monitoring and Conservation)

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16 pages, 5690 KiB

Open AccessArticle

Camera Trapping Reveals Spatiotemporal Partitioning Patterns and Conservation Implications for Two Sympatric Pheasant Species in the Qilian Mountains, Northwestern China

by Dexi Zhang, Bei An, Liuyang Chen, Zhangyun Sun, Ruirui Mao, Changming Zhao and Lixun Zhang

Animals 2022, 12(13), 1657; https://doi.org/10.3390/ani12131657 - 28 Jun 2022

Cited by 7 | Viewed by 2386

Abstract

Studying the spatio-temporal niche partitioning among closely related sympatric species is essential for understanding their stable coexistence in animal communities. However, consideration of niche partitioning across multiple ecological dimensions is still poor for many sympatric pheasant species. Here, we studied temporal activity patterns and spatial distributions of the Blue Eared Pheasant (EP, Crossoptilon auritum) and Blood Pheasant (BP, Ithaginis cruentus) in the Qilian Mountains National Nature Reserve (QMNNR), Northwestern China, using 137 camera traps from August 2017 to August 2020. Kernel density estimation was applied to analyze diel activity patterns, and the Maxent model was applied to evaluate their suitable distributions and underlying habitat preferences. Eight Galliformes species were captured in 678 detection records with 485 records of EP and 106 records of BP over a total of 39,206 camera days. Their monthly activity frequencies demonstrate temporal partitioning but their diel activity patterns do not. Furthermore, 90.78% of BP distribution (2867.99 km²) overlaps with the distribution of EP (4355.86 km²) in the QMNNR. However, BP manifests a high dependence on forest habitats and shows larger Normalized Difference Vegetation Index (NDVI) values, while EP showed obvious avoidance of forest with NDVI greater than 0.75. Hence, differentiation in monthly activity patterns and partitioning in habitat preference might facilitate their coexistence in spatiotemporal dimensions. Conservation actions should give priority to highly overlapping areas in the center and east of the QMNNR and should strengthen forest landscape connectivity, as they provide irreplaceable habitats for these threatened and endemic Galliformes. Full article

(This article belongs to the Special Issue Use of Camera Trap for a Better Wildlife Monitoring and Conservation)

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13 pages, 5149 KiB

Open AccessArticle

Recognition of Coat Pattern Variation and Broken Tail Phenomenon in the Asiatic Golden Cat (Catopuma temminckii)

by Yuan Wang, Dajiang Li, Pubu Dunzhu, Wulin Liu, Limin Feng and Kun Jin

Animals 2022, 12(11), 1420; https://doi.org/10.3390/ani12111420 - 31 May 2022

Viewed by 4997

Abstract

The Asian golden cat (Catopuma temminckii) is the most varied wild cat species in terms of coat color. Understanding coat pattern variation will help to elucidate the mechanisms behind it as well as its relationship with the environment. We conducted long-term (2013–2021) monitoring of Asian golden cats in the Yarlung Zangbo Grand Canyon National Nature Reserve, Tibet, using camera traps at 283 points over 89,991 camera days. A total of 620 cat photos were recorded, including 344 (55.48%) with recognizable color patterns. Vector graphics of the coat patterns were extracted from the field image data, which revealed 10 color types in the ratio common: cinnamon: reddish-brown long hair: ocelot: blackening: melanistic: gray: brown: brown short hair: pure black = 123:76:57:35:22:8:7:7:5:4. The genes for coat pattern variation are widespread in the Asian golden cat population and are relatively stable. The increase in population size intraspecific competition has led to the tail break phenotype in individual cats. The gene encoding for tail breakage in Asian golden cats remains unknown. This study provides basic information for understanding faunal diversity in the Eastern Himalayan biodiversity hotspot and serves as a reference for studies on the formation mechanisms for feline color pattern diversity. Full article

(This article belongs to the Special Issue Use of Camera Trap for a Better Wildlife Monitoring and Conservation)

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16 pages, 5700 KiB

Open AccessArticle

Multiobject Tracking of Wildlife in Videos Using Few-Shot Learning

by Jiangfan Feng and Xinxin Xiao

Animals 2022, 12(9), 1223; https://doi.org/10.3390/ani12091223 - 09 May 2022

Cited by 5 | Viewed by 2207

Abstract

Camera trapping and video recording are now ubiquitous in the study of animal ecology. These technologies hold great potential for wildlife tracking, but are limited by current learning approaches, and are hampered by dependence on large samples. Most species of wildlife are rarely captured by camera traps, and thus only a few shot samples are available for processing and subsequent identification. These drawbacks can be overcome in multiobject tracking by combining wildlife detection and tracking with few-shot learning. This work proposes a multiobject-tracking approach based on a tracking-by-detection paradigm for wildlife to improve detection and tracking performance. We used few-shot object detection to localize objects using a camera trap and direct video recordings that could augment the synthetically generated parts of separate images with spatial constraints. In addition, we introduced a trajectory reconstruction module for better association. It could alleviate a few-shot object detector’s missed and false detections; in addition, it could optimize the target identification between consecutive frames. Our approach produced a fully automated pipeline for detecting and tracking wildlife from video records. The experimental results aligned with theoretical anticipation according to various evaluation metrics, and revealed the future potential of camera traps to address wildlife detection and tracking in behavior and conservation. Full article

(This article belongs to the Special Issue Use of Camera Trap for a Better Wildlife Monitoring and Conservation)

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16 pages, 2900 KiB

Open AccessArticle

The Use of Selfie Camera Traps to Estimate Home Range and Movement Patterns of Small Mammals in a Fragmented Landscape

by Ana Gracanin and Katarina M. Mikac

Animals 2022, 12(7), 912; https://doi.org/10.3390/ani12070912 - 02 Apr 2022

Cited by 8 | Viewed by 3171

Abstract

The use of camera traps to track individual mammals to estimate home range and movement patterns, has not been previously applied to small mammal species. Our aim was to evaluate the use of camera trapping, using the selfie trap method, to record movements of small mammals within and between fragments of habitat. In a fragmented landscape, 164 cameras were set up across four survey areas, with cameras left to record continuously for 28 nights. Live trapping was performed prior to ear mark animals to facilitate individual identification on camera. Four small mammal species (sugar glider; Petaurus breviceps; brown antechinus; Antechinus stuartii, bush rat; Rattus fuscipes, and brown rat; Rattus norvigecus) were recorded on camera (N = 284 individuals). The maximum distance travelled by an individual sugar glider was 14.66 km, antechinus 4.24 km; bush rat 1.90 km and brown rat 1.28 km. Movements of both female and male sugar gliders in linear fragments were recorded at much higher rates than in larger patches of forest sampled in grids. Short term core homes ranges (50% KDE) of 34 sugar gliders ranged from 0.3 ha to 4.2 ha. Sugar glider core home ranges were on average 1.2 ha (±0.17) for females and 2.4 ha (±0.28) for males. The selfie trap is an efficient camera trapping method for estimating home ranges and movements due to its ability to obtain high recapture rates for multiple species and individuals. In our study landscape, linear strips of habitat were readily utilised by all small mammals, highlighting their importance as wildlife corridors in a fragmented landscape. Full article

(This article belongs to the Special Issue Use of Camera Trap for a Better Wildlife Monitoring and Conservation)

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