New altitudinal records of Panthera onca (Carnivora: Felidae) in the Andean region of Ecuador

We report two records of jaguars (Panthera onca) registered with camera traps at 2300 and 2660 m a.s.l. in the Ecuadorian Andes, which represent the first verifiable records of the species above 2000 m in Ecuador. As the first records of jaguars from Río Negro-Sopladora National Park and Tapichalaca Reserve, these records raise important questions about the species’ ecology and conservation in Andean montane forests. From a regional perspective, these records may indicate connectivity between jaguar populations inhabiting both sides of the Andes. Sustained monitoring of wildlife populations is necessary to discern the significance of these records and help develop strategies to ensure the conservation of this highly mobile species across the increasingly fragmented Andean-Amazonian landscapes of southern Ecuador.

An IoT System Using Deep Learning to Classify Camera Trap Images on the Edge

Camera traps deployed in remote locations provide an effective method for ecologists to monitor and study wildlife in a non-invasive way. However, current camera traps suffer from two problems. First, the images are manually classified and counted, which is expensive. Second, due to manual coding, the results are often stale by the time they get to the ecologists. Using the Internet of Things (IoT) combined with deep learning represents a good solution for both these problems, as the images can be classified automatically, and the results immediately made available to ecologists. This paper proposes an IoT architecture that uses deep learning on edge devices to convey animal classification results to a mobile app using the LoRaWAN low-power, wide-area network. The primary goal of the proposed approach is to reduce the cost of the wildlife monitoring process for ecologists, and to provide real-time animal sightings data from the camera traps in the field. Camera trap image data consisting of 66,400 images were used to train the InceptionV3, MobileNetV2, ResNet18, EfficientNetB1, DenseNet121, and Xception neural network models. While performance of the trained models was statistically different (Kruskal–Wallis: Accuracy H(5) = 22.34, p < 0.05; F1-score H(5) = 13.82, p = 0.0168), there was only a 3% difference in the F1-score between the worst (MobileNet V2) and the best model (Xception). Moreover, the models made similar errors (Adjusted Rand Index (ARI) > 0.88 and Adjusted Mutual Information (AMU) > 0.82). Subsequently, the best model, Xception (Accuracy = 96.1%; F1-score = 0.87; F1-Score = 0.97 with oversampling), was optimized and deployed on the Raspberry Pi, Google Coral, and Nvidia Jetson edge devices using both TenorFlow Lite and TensorRT frameworks. Optimizing the models to run on edge devices reduced the average macro F1-Score to 0.7, and adversely affected the minority classes, reducing their F1-score to as low as 0.18. Upon stress testing, by processing 1000 images consecutively, Jetson Nano, running a TensorRT model, outperformed others with a latency of 0.276 s/image (s.d. = 0.002) while consuming an average current of 1665.21 mA. Raspberry Pi consumed the least average current (838.99 mA) with a ten times worse latency of 2.83 s/image (s.d. = 0.036). Nano was the only reasonable option as an edge device because it could capture most animals whose maximum speeds were below 80 km/h, including goats, lions, ostriches, etc. While the proposed architecture is viable, unbalanced data remain a challenge and the results can potentially be improved by using object detection to reduce imbalances and by exploring semi-supervised learning.

Activity pattern of Asiatic black bear (Ursus thibetanus) in Machiara National Park, Azad Jammu and Kashmir, Pakistan

The Asiatic black bear is considered an indicator species of the environment, hence, any change in the environment may alter its activity pattern. We monitored the monthly activity pattern of black bears in the moist temperate forests of Machiara National Park, AJ&K, Pakistan. We used infrared camera traps and indigenous knowledge for data collection from April 2019 to April 2021. Camera traps recorded 109 (inside the forest = 107, outside the forest = 2) independent registrations (IR) within 5541 (692.63 ± 36.72, mean ± SD) camera days. We found that (i) spring and autumn were the lowest activity seasons of black bears inside the forest. (ii) Whereas, the highest activities were recorded in summer with peak activities in August followed by July (χ2 = 203.5, df= 7, P< 0.05). (iii) The activity level sharply declined after August and halted from late November to late April which was clear indication of bears’ hibernation period. We collected indigenous knowledge from 70 selected persons, including hunters, herders, temporary residents and crop raiding victims. We used the data of human observation of latest three years and found that (i) bears remained active from May to November and hibernated rest of the period. (ii) The activities were at their peak inside the forest in summer (May – August) and out of the forest in autumn (September – November) when it preferred to raid the widely cultivated maize crop (Zea mays) in the area. The capturing of black bears by camera traps outside the forest further supported the data provided by local people. Such switching over might have occurred due to the food preferences for Zea mays or easy access to abundant food availability out of the forest area. The current data can help mitigate human black bears conflict and consequently future conservation of black bears in the area.

Fauna diversity in the southern part of the Kon Ka Kinh National Park, Gia Lai province

Kon Ka Kinh National Park (KKK NP) is a priority zone for biodiversity protection in Vietnam as well as ASEAN. In order to survey the current fauna species diversity in the southern part of the KKK NP, we conducted camera trapping surveys in 2017, 2018, and 2019. 28 infrared camera traps were set up on elevations between 1041 to 1497 meters. In total, there were 360 days of survey using camera trap. As result, we recorded a total of 27 animal species of those, five species are listed in the IUCN Red List of Threatened Species (IUCN, 2020). The survey results showed a high richness of wildlife in the southern park region, and it also revealed human disturbance to wildlife in the park. The first-time camera trap was used for surveying wildlife diversity in the southern region of the KKK NP. Conducting camera trap surveys in the whole KKK NP is essential for monitoring and identifying priority areas for wildlife conservation in the national park.

The monk parakeet (Myiopsitta monachus) as a potential pest for agriculture in the Mediterranean basin

The monk parakeet (Myiopsitta monachus) has been introduced in the last decades to many cities in many parts of the world. For most of this time it has been restricted primarily to urban areas, but it is starting to spread to rural habitats. In its native range, the monk parakeet is considered a pest for agriculture, consuming a wide variety of crops such as grains, fruits, and vegetables. However, there is very little information about its potential role as a pest for agriculture in the areas where it is exotic. Here we conducted an experimental survey of the impact of the monk parakeet on corn in SE Spain using camera traps. The monk parakeet was the animal that produced the highest damage, being responsible for 98.6% of the time employed by all animals consuming corn. The percentage of cobs damaged ranged from 36.8 to 100% depending on the cultivar, whereas the crop loss (measured as the length of the cob consumed with respect to the total length of the cob) ranged from 17.7 to 71.1%. The results suggest that the monk parakeet may be a serious pest for agriculture in the Mediterranean basin if their populations continue growing.

Annotated Checklist and Conservation Status of Mammal Species in Sarpang District, Bhutan

Bhutan has a total geographical area of 38,394 Km² located in between the Indo-Malayan and Palearctic region, out of which 51.44% (19750.75 km²) of its total geographical area has been designated as the protected area. However, none of the districts have a structured baseline checklist of mammal species documented till date. Therefore, Sarpang Forest Division under the Department of Forests and Park Services had carried out five rigorous camera trap surveys including a nationwide tiger survey that covers representable areas of the district from 2014 till 2020. The survey shows that district has 36 mammal species that belong to 18 families under seven orders. Felidae and Cervidae families has the highest species abundance (n = 17%), while, Canidae, Herpestidae, Leporidae, Manidae, Melinae, Muridae, Mustelidae, Tupaiidae, Proboscidae, Pteromyidae, Suidae and Ursidae were the lowest (n = 3%). Above all, Sarpang homed 29.90% of total mammal species of Bhutan, out of which 3% of mammal species were categorized under Critically Endangered, 14% Endangered, 14% Vulnerable, 22% Near Threatened, and 47% Least Concern as per IUCN Red List. However, only 20 mammal species are listed under CITES and nine in Schedule I of Forest and Nature Conservation Act of Bhutan, 1995. Therefore, landscape-based planning such as the Division-based Conservation & Management plan; periodic monitoring of wildlife species using camera traps, and validation of Schedule I species are suggested for long-term conservation and management of globally threatened species inside the landscape of Sarpang district in Bhutan.

NONVOLANT MAMMALS IN A FRAGMENT OF ARBOREAL CAATINGA IN NORTHEASTERN BRAZIL

The state of Paraiba is one of those with the most degraded Caatinga that presents the large gap of knowledge concerning the mammal fauna. Mammals are among the taxa most affected by this. In this sense, we evaluated non-volant mammals’ richness and composition between March 2013 and February 2020 in a Caatinga fragment (121 ha). We used active search (336 hours) and camera traps (1,200 night traps). We recorded 20 species, including four threatened ones. Carnivora was the most representative order (7 species), followed by Rodentia (4 species). The richness of non-volant mammals found represents 35.6 % of the total number of such species in the Caatinga. This species richness is greater than that found in other studies in the state. The presence of these mammal species was mainly due to the recovering vegetation that resulted from the great planting effort and also due to cessation of hunt, cattle and sheep breeding that had existed on the farm for over thirty years. Our findings highlight the importance of this particular reserve due to the large number of species registered.

Two Methods of Monitoring Cats at a Landscape-Scale

Feral cats are difficult to manage and harder to monitor. We analysed the cost and the efficacy of monitoring the pre- and post-bait abundance of feral cats via camera-traps or track counts using four years of data from the Matuwa Indigenous Protected Area. Additionally, we report on the recovery of the feral cat population and the efficacy of subsequent Eradicat® aerial baiting programs following 12 months of intensive feral cat control in 2019. Significantly fewer cats were captured in 2020 (n = 8) compared to 2019 (n = 126). Pre-baiting surveys for 2020 and 2021 suggested that the population of feral cats on Matuwa was very low, at 5.5 and 4.4 cats/100 km, respectively, which is well below our target threshold of 10 cats/100 km. Post-baiting surveys then recorded 3.6 and 3.0 cats/100 km, respectively, which still equates to a 35% and 32% reduction in cat activity. Track counts recorded significantly more feral cats than camera traps and were cheaper to implement. We recommend that at least two methods of monitoring cats be implemented to prevent erroneous conclusions.

Harpy Eagle Harpia harpyja nest activity patterns: Potential ecotourism and conservation opportunities in the Amazon Forest

Summary Tourism can be a powerful tool for wildlife conservation if well controlled and responsibly managed. Apex predators constitute particularly attractive subjects for tourism, but simultaneously they may generate conflict with local communities. Harpy Eagles Harpia harpyja are the largest eagle species and are highly sought-after by ecotourists. The last stronghold of the Harpy Eagle is the Amazon Forest, which is being deforested for cattle ranching. We tested methods for developing Harpy Eagle ecotourism as a potential tool to harmonize these issues. Using camera traps, we collected data on timing of Harpy Eagle visits to their nests, as well as on probabilities of viewing an eagle. Harpy Eagles can only be seen predictably during the first 12 of the 30–36 month nest cycle. In nests with nestlings (up to 5–7 months), adults are visible on a daily basis, and this period lasts 16.6% of the nesting cycle, demanding a minimum of 13, 17, and 26 nests to have at least one nest with a nestling on 90%, 95% and 99% of the days. After this 5–7 month window, we found that two and 4.16 days spent at nests afforded high probabilities of sighting a fledgling or adult eagle, respectively. Harpy Eagles were mainly active at the beginning and the end of the day. Activity core lasted 6.5 decimal hours for adults, peaking at 10h00, and 7.45 decimal hours for fledged eagles, peaking at 15h00. Our results demonstrate that Harpy Eagles fit several criteria for a viable wildlife attraction: predictable in activity and location, viewable, and diurnal, even though at the same time they are considered a rarity. In a broader perspective, Harpy Eagle tourism shows every indication of being a significant tool for more robust rainforest conservation.

Optical design challenges of subnivean camera trapping under extreme Arctic conditions

Camera trapping is widely used in different ecological studies and is particularly important for remote locations and extreme environments. However, the application of camera traps in Arctic regions remains very limited. One of the challenges is the formation of hoar on the lens of cameras. In this article, we propose a solution to address this problem by changing the camera parameters and its position in order to optimize the camera trap for long-term subnivean deployment in the Canadian Arctic. Preliminary field tests show that this approach allows tracking lemmings in the frozen environment without natural light or external electrical power supply, where the direct observations are impossible for the most part of the year. We obtained the first videos of lemmings under the snow during the Arctic winter. Extending the observational network of the newly designed camera traps will help to better understand lemming population dynamics. The demonstrated approach is also promising for other polar applications.