Man versus machine: cost and carbon emission savings of 4G-connected Artificial Intelligence technology for classifying species in camera trap images

Timely and accurate detection and identification of species are crucial for monitoring wildlife for conservation and management. Technological advances, including connectivity of camera traps to mobile phone networks and artificial intelligence (AI) algorithms for automated species identification, can potentially improve the timeliness and accuracy of species detection and identification. Adoption of this new technology, however, is often seen as cost-prohibitive as it has been difficult to calculate the cost savings or qualitative benefits over the life of the program. We developed a decision tool to quantify potential cost savings associated with incorporating the use of mobile phone network connectivity and AI technologies into monitoring programs. Using a feral cat eradication program as a case study, we used our decision tool to quantify technology-related savings in costs and carbon emissions, and compared the accuracy of AI species identification to that of experienced human observers. Over the life of the program, AI technology yielded cost savings of $0.27 M and when coupled with mobile phone network connectivity, AI saved $2.15 M and 115,838 kg in carbon emissions, with AI algorithms outperforming human observers in both speed and accuracy. Our case study demonstrates how advanced technologies can improve accuracy and cost-effectiveness and improve monitoring program efficiencies.

Automated Detection and Counting of Wild Boar in Camera Trap Images

Camera traps are becoming widely used for wildlife monitoring and management. However, manual analysis of the resulting image sets is labor-intensive, time-consuming and costly. This study shows that automated computer vision techniques can be extremely helpful in this regard, as they can rapidly and automatically extract valuable information from the images. Specific training with a set of 1600 images obtained from a study where wild animals approaching wild boar carcasses were monitored enabled the model to detect five different classes of animals automatically in their natural environment with a mean average precision of 98.11%, namely 'wild boar', 'fox', 'raccoon dog', 'deer' and 'bird'. In addition, sequences of images were automatically analyzed and the number of wild boar visits and respective group sizes were determined. This study may help to improve and speed up the monitoring of the potential spread of African swine fever virus in areas where wild boar are affected.

Camera traps reveal overlap and seasonal variation in the diel activity of arboreal and semi-arboreal mammals

Our study aimed to investigate seasonal variation in the activity of arboreal and semi-arboreal mammals and investigate their overlap in temporal activity, as well temporal shifts in activity because of behavioural interference. In our camera trapping study in a fragmented landscape in south-eastern Australia, a total of ten arboreal and semi-arboreal species were found, with 35,671 independent observations recorded over 6517 camera trap nights. All species were found to be nocturnal; however, a notable number of daytime observations were made for several species (i.e. brown antechinus, Antechinus stuartii; sugar glider, Petaurus breviceps; bush rat, Rattus fuscipes; brown rat, Rattus norvegicus). Seasonal variations in diel activity were observed through an increase in crepuscular activity in spring and summer for antechinus, sugar gliders, brown rats, brushtail possums, Trichosurus vulpecula and ringtail possums, Pseudocheirus peregrinus. Diel activity overlap between species was high, that is 26/28 species comparisons had overlap coefficients (Δ) > 0.75. The species pair with the least amount of overlap was between southern bobucks, Trichosurus cunninghami and brown antechinus (Δ4 = 0.66). The species pair with the most overlap was between the native sugar glider and introduced brown rat (Δ4 = 0.93). When comparing the activity of sugar gliders in sites with low and high abundance of brown rats, sugar gliders appear to shift their activity relative to the brown rats. Similarly, behavioural interference was also observed between antechinus and sugar gliders, and when comparing sites of low and high abundance of sugar glider, antechinus had a shift in activity. Our work provides some of the first quantification of temporal patterns for several of the species in this study, and the first for a community of arboreal and semi-arboreal mammals. Our results indicate that some shifts in behaviour are potentially occurring in response to behavioural interference, allowing for coexistence by means of temporal partitioning.

Night of the hunter: using cameras to quantify nocturnal activity in desert spiders

Invertebrates dominate the animal world in terms of abundance, diversity and biomass, and play critical roles in maintaining ecosystem function. Despite their obvious importance, disproportionate research attention remains focused on vertebrates, with knowledge and understanding of invertebrate ecology still lacking. Due to their inherent advantages, usage of camera traps in ecology has risen dramatically over the last three decades, especially for research on mammals. However, few studies have used cameras to reliably detect fauna such as invertebrates or used cameras to examine specific aspects of invertebrate ecology. Previous research investigating the interaction between wolf spiders (Lycosidae: Lycosa spp.) and the lesser hairy-footed dunnart (Sminthopsis youngsoni) found that camera traps provide a viable method for examining temporal activity patterns and interactions between these species. Here, we re-examine lycosid activity to determine whether these patterns vary with different environmental conditions, specifically between burned and unburned habitats and the crests and bases of sand dunes, and whether cameras are able to detect other invertebrate fauna. Twenty-four cameras were deployed over a 3-month period in an arid region in central Australia, capturing 2,356 confirmed images of seven invertebrate taxa, including 155 time-lapse images of lycosids. Overall, there was no clear difference in temporal activity with respect to dune position or fire history, but twice as many lycosids were detected in unburned compared to burned areas. Despite some limitations, camera traps appear to have considerable utility as a tool for determining the diel activity patterns and habitat use of larger arthropods such as wolf spiders, and we recommend greater uptake in their usage in future.