Review: COVID-19 highlights the importance of camera traps for wildlife conservation research and management

Leveraging camera traps and artificial intelligence to explore thermoregulation behaviour

Behavioural thermoregulation has critical ecological and physiological consequences that profoundly influence individual fitness and species distributions, particularly in the context of climate change. However, field monitoring of this behaviour remains labour-intensive and time-consuming. With the rise of camera-based surveys and artificial intelligence (AI) approaches in computer vision, we should try to build better tools for characterizing animals' behavioural thermoregulation. In this study, we developed a deep learning framework to automate the detection and classification of thermoregulation behaviour. We used lizards, the Rough-tail rock agama (Laudakia vulgaris), as a model animal for thermoregulation. We colour-marked the lizards and curated a diverse dataset of images captured by trail cameras under semi-natural conditions. Subsequently, we trained an object-detection model to identify lizards and image classification models to determine their microclimate usage (activity in sun or shade), which may indicate thermoregulation preferences. We then evaluated the performance of each model and analysed how the classification of thermoregulating lizards performed under different solar conditions (sun or shade), times of day and marking colours. Our framework's models achieved high scores in several performance metrics. The behavioural thermoregulation classification model performed significantly better on sun-basking lizards, achieving the highest classification accuracy with white-marked lizards. Moreover, the hours of activity and the microclimate choices (sun vs shade-seeking behaviour) of lizards, generated by our framework, are closely aligned with manually annotated data. Our study underscores the potential of AI in effectively tracking behavioural thermoregulation, offering a promising new direction for camera trap studies. This approach can potentially reduce the labour and time associated with ecological data collection and analysis and help gain a deeper understanding of species' thermal preferences and risks of climate change on species behaviour.

Supporting function of vegetation in urban riparian ecological corridors for ground-dwelling faunal diversity in Beijing, China

Rapid global urbanization has resulted in increased biodiversity problems, particularly the loss of ground-dwelling fauna in urban areas. Urban riparian corridors are an important green infrastructure for biodiversity conservation, in which urban vegetation plays an essential role. The influence of urban vegetation on ground-dwelling faunal diversity is poorly understood. In this study, we used camera traps to collect the species, functional and phylogenetic diversity of ground-dwelling fauna in the Wenyu River-North Canal riparian corridor in Beijing, and analyzed the effects of the vegetation structure and plant community composition on the diversity and community composition of ground-dwelling animals. A plant-ground dwelling animal interaction network was also built to investigate the food supply of plants for ground-nesting animals. We found that at the vegetation structure level, the high connectivity within a radius of 2000 m and the homogeneous distribution within a radius of 1000 m of vegetation patches had generally positive effects on ground-dwelling animals, and shrublands exhibited a supportive role for mammals in riparian corridors. At the plant community level, tall herbs were instrumental in increasing the willingness of ground-dwelling animals to stay in and pass through the area. Native plants were the main plant food resource for ground-dwelling animals. Given the significant effects of vegetation on ground-dwelling fauna, we advocate that habitat conservation and food supply for ground-dwelling animals be supported through appropriate plant landscape planning and design strategies in ecological corridors in urban areas in the future.

Opportunities and challenges for monitoring a recolonizing large herbivore using citizen science

Monitoring is a prerequisite for evidence-based wildlife management and conservation planning, yet conventional monitoring approaches are often ineffective for species occurring at low densities. However, some species such as large mammals are often observed by lay people and this information can be leveraged through citizen science monitoring schemes. To ensure that such wildlife monitoring efforts provide robust inferences, assessing the quantity, quality, and potential biases of citizen science data is crucial. For Eurasian moose (Alces alces), a species currently recolonizing north-eastern Germany and occurring in very low numbers, we applied three citizen science tools: a mail/email report system, a smartphone application, and a webpage. Among these monitoring tools, the mail/email report system yielded the greatest number of moose reports in absolute and in standardized (corrected for time effort) terms. The reported moose were predominantly identified as single, adult, male individuals, and reports occurred mostly during late summer. Overlaying citizen science data with independently generated habitat suitability and connectivity maps showed that members of the public detected moose in suitable habitats but not necessarily in movement corridors. Also, moose detections were often recorded near roads, suggestive of spatial bias in the sampling effort. Our results suggest that citizen science-based data collection can be facilitated by brief, intuitive digital reporting systems. However, inference from the resulting data can be limited due to unquantified and possibly biased sampling effort. To overcome these challenges, we offer specific recommendations such as more structured monitoring efforts involving the public in areas likely to be roamed by moose for improving quantity, quality, and analysis of citizen science-based data for making robust inferences.

Camera trapping expands the view into global biodiversity and its change

Growing threats to biodiversity demand timely, detailed information on species occurrence, diversity and abundance at large scales. Camera traps (CTs), combined with computer vision models, provide an efficient method to survey species of certain taxa with high spatio-temporal resolution. We test the potential of CTs to close biodiversity knowledge gaps by comparing CT records of terrestrial mammals and birds from the recently released Wildlife Insights platform to publicly available occurrences from many observation types in the Global Biodiversity Information Facility. In locations with CTs, we found they sampled a greater number of days (mean = 133 versus 57 days) and documented additional species (mean increase of 1% of expected mammals). For species with CT data, we found CTs provided novel documentation of their ranges (93% of mammals and 48% of birds). Countries with the largest boost in data coverage were in the historically underrepresented southern hemisphere. Although embargoes increase data providers' willingness to share data, they cause a lag in data availability. Our work shows that the continued collection and mobilization of CT data, especially when combined with data sharing that supports attribution and privacy, has the potential to offer a critical lens into biodiversity. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

Daily and Seasonal Activity Patterns of Plateau Pikas (Ochotona curzoniae) on the Qinghai-Tibet Plateau, China, and Their Relationship with Weather Condition

Exploring the activity patterns of small mammals is important for understanding the survival strategies of these animals, such as foraging and mating. The purpose of the present study was to determine the activity of free-living plateau pikas (Ochotona curzoniae) in different months and seasons (cold and warm seasons), with a particular emphasis on the effects of weather condition. Based on a camera-trapping survey conducted from October 2017 to September 2018, we evaluated the activity patterns and activity levels of plateau pikas inhabiting the eastern Qinghai-Tibet Plateau in China. The effects of environmental factors on the activity of plateau pikas were examined using the generalized additive mixed model (GAMM). The results showed that: (1) The plateau pikas exhibited unimodal patterns of activity during the cold season (October-April). During the warm season (May-September), the activity patterns of the plateau pikas were bimodal. Their activity levels were highest in June. (2) During the cold season, their activity levels rose gradually over the course of the day to a peak near noon, and they were not significantly higher after sunrise than they were before sunset. During the warm season, their activity peaks were in the morning and afternoon, and their activity levels were substantially lower after sunrise than they were before sunset. (3) The plateau pikas were more active under conditions with lower ambient temperatures and precipitation during the cold and warm seasons. While relative air humidity was positively correlated with the activity of the plateau pikas during the warm season, wind speed was negatively correlated with the pikas' activity during the cold season. Overall, these results collectively indicate that plateau pikas occupy habitats with cool and less windy microclimates during the cold season, and with cool and moist microclimates during the warm season. Information on the time allocation of pikas' activity levels during different seasons should provide a baseline for understanding their potential for adaptation to climate change.

Human recreation impacts seasonal activity and occupancy of American black bears (Ursus americanus) across the anthropogenic-wildland interface

Protected areas serve an important role in wildlife conservation, yet most wildlife occur outside these areas, subject to varying degrees of human disturbance. In the Upper Peninsula of Michigan, American black bears (Ursus americanus), a highly mobile, opportunistic species, are common despite an extensive outdoor recreation industry with the potential to affect black bear spatial and temporal activity. We investigated how environmental and anthropogenic factors influence black bear occupancy, detection, and diel activity patterns across the anthropogenic-wildland interface before and after hibernation. Using 30 camera traps deployed across a rural-wildland interface, we captured black bears at 23 camera sites (~ 77%), which exhibited co-occurrence with humans at 10 sites (~ 33%), revealing that human presence and human population density exert negative effects on black bear seasonal occupancy. Bears were more nocturnal during the hunting season, before hibernation. Human recreational activity increased ~ 38% after hibernation, but bear diurnal activity also increased ~ 36%, except when cubs were present. Our results suggest bears prioritize avoiding humans spatially, rather than temporally, except during the hunting season and when cubs are present. Understanding black bear responses to human recreation patterns and environmental variation is essential for minimizing human-mediated disturbance, and fueling conservation efforts of large, charismatic carnivores.

Human impacts on mammals in and around a protected area before, during, and after COVID-19 lockdowns

The dual mandate for many protected areas (PAs) to simultaneously promote recreation and conserve biodiversity may be hampered by negative effects of recreation on wildlife. However, reports of these effects are not consistent, presenting a knowledge gap that hinders evidence-based decision-making. We used camera traps to monitor human activity and terrestrial mammals in Golden Ears Provincial Park and the adjacent University of British Columbia Malcolm Knapp Research Forest near Vancouver, Canada, with the objective of discerning relative effects of various forms of recreation on cougars (Puma concolor), black bears (Ursus americanus), black-tailed deer (Odocoileus hemionus), snowshoe hares (Lepus americanus), coyotes (Canis latrans), and bobcats (Lynx rufus). Additionally, public closures of the study area associated with the COVD-19 pandemic offered an unprecedented period of human-exclusion through which to explore these effects. Using Bayesian generalized mixed-effects models, we detected negative effects of hikers (mean posterior estimate = -0.58, 95% credible interval [CI] -1.09 to -0.12) on weekly bobcat habitat use and negative effects of motorized vehicles (estimate = -0.28, 95% CI -0.61 to -0.05) on weekly black bear habitat use. We also found increased cougar detection rates in the PA during the COVID-19 closure (estimate = 0.007, 95% CI 0.005 to 0.009), but decreased cougar detection rates (estimate = -0.006, 95% CI -0.009 to -0.003) and increased black-tailed deer detection rates (estimate = 0.014, 95% CI 0.002 to 0.026) upon reopening of the PA. Our results emphasize that effects of human activity on wildlife habitat use and movement may be species- and/or activity-dependent, and that camera traps can be an invaluable tool for monitoring both wildlife and human activity, collecting data even when public access is barred. Further, we encourage PA managers seeking to promote both biodiversity conservation and recreation to explicitly assess trade-offs between these two goals in their PAs.

Cultivating scientific literacy and a sense of place through course-based urban ecology research

Undergraduate research experiences have been shown to increase engagement, improve learning outcomes, and enhance career development for students in ecology. However, these opportunities may not be accessible to all students, and incorporating inquiry-based research directly into undergraduate curricula may help overcome barriers to participation and improve representation and inclusion in the discipline. The shift to online instruction during the COVID-19 pandemic has imposed even greater challenges for providing students with authentic research experiences, but the pandemic may also provide a unique opportunity for creative projects conducted remotely. In this paper, I describe a course-based undergraduate research experience (CURE) designed for an upper-level ecology course at California State University, Dominguez Hills during remote learning. The primary focus of student-led research activities was to explore the potential impacts of the depopulation of campus during the pandemic on urban coyotes (Canis latrans), for which there were increased sightings reported during this time. Students conducted two research studies, including an evaluation of urban wildlife activity, behavior, and diversity using camera traps installed throughout campus and analysis of coyote diet using data from scat dissections. Students used the data they generated and information from literature reviews, class discussions, and meetings with experts to develop a coyote monitoring and management plan for our campus and create posters to educate the public. Using the campus as a living laboratory, I aimed to engage students in meaningful research while cultivating a sense of place, despite being online. Students' research outcomes and responses to pre- and post-course surveys highlight the benefits of projects that are anchored in place-based education and emphasize the importance of ecological research for solving real-world problems. CUREs focused on local urban ecosystems may be a powerful way for instructors to activate ecological knowledge and capitalize on the cultural strengths of students at urban universities.