Large‐scale mammal monitoring: The potential of a citizen science camera‐trapping project in the United Kingdom

Abstract

1. In light of global biodiversity loss, there is an increasing need for large-scale wildlife monitoring. This is difficult for mammals, since they can be elusive and nocturnal. In the United Kingdom, there is a lack of systematic, widespread mammal monitoring, and a recognized deficiency of data. Innovative new approaches are required.2. We developed MammalWeb, a portal to enable UK-wide camera trapping by a network of citizen scientists and partner organizations. MammalWeb citizen scientists contribute to both the collection and classification of camera trap data.Following trials in 2013-2017, MammalWeb has grown organically to increase its geographic reach (e.g. ∼2000 sites in Britain). It has so far provided the equivalent of over 340 camera trap-years of wild mammal monitoring, and produced nearly 440,000 classified image sequences and videos, of which, over 180,000 are mammal detections.3. We describe MammalWeb, its background, its development and the novel approaches we have for participation. We consider the data collected by Mammal-Web participants, especially in light of their relevance to the main goals of wildlife monitoring: to provide spatial data, abundance data and temporal behavioural data. MammalWeb can complement existing approaches to mammal monitoring. Explicit accounting for spatial and temporal patterns in animal activity enables accountingThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Camera trapping with photos and videos: implications for ecology and citizen science

“…More coordinated monitoring efforts are needed to identify global trends in biodiversity (Scotson et al., 2017; Steenweg et al., 2017) and there are now several initiatives combining camera trap footage from a range of participants in order to monitor wildlife across a wide area, such as MammalWeb (Hsing et al., in press), the Tropical Ecology Assessment and Monitoring (TEAM) Network (Rovero & Ahumada, 2017), and both Snapshot USA (Cove et al., 2021) and Snapshot Europe (https://www.ab.mpg.de/358074/snapshot-europe). These projects rely on large numbers of participants to collect enough data for meaningful ecological analysis.…”

“…We ran common camera trap analyses, including species richness, occupancy, activity level and detection rate, to determine whether there were any ecologically meaningful differences between the photo and video datasets. Data were uploaded to the citizen science platform, MammalWeb (http://www.mammalweb.org) (Hsing et al., in press), into parallel photo and video projects for classification. We compared classification accuracy between different lengths of photo sequence and video footage as well as looking at participation and engagement with both types of media.…”

Efficient data collection for camera trap‐based density estimation: A preliminary assessment

“…Furthermore, the simplification of setting up a camera site even when compared to methods requiring calibration (Haucke et al., 2022; Henrich et al., 2023; Wearn et al., 2022) makes the process less cumbersome, which can increase community engagement (Wiggins & Crowston, 2011). This can help solve the recent issue of volunteers becoming increasingly hard to enlist in citizen science projects (Willi et al., 2019), which is—otherwise—a promising approach to tackling the problems of data collection in large‐scale camera trap studies (Hsing et al., 2022; McShea et al., 2016; Swanson et al., 2015). While recently proposed automated alternatives (Johanns et al., 2022) are exciting and offer hope, they are at an early stage of development, with little assessment of generalisability (Rees, 2023).…”

Improvement of information technology tools to collect, process and analyse data on wildlife population

“…14 MammalWeb has collected over 1.7 million images and video files at over 2300 sites across Britain (Hsing et al 2022). The MammalNet project has collected over 125,000 uploaded sequences, and more than 64,000 of these have been classified.…”

“…MammalWeb project organisation. NGOs, non-governmental organizations; EC2, Amazon Elastic Compute Cloud 2; S3, Amazon Simple Storage Service; RDS, Amazon Relational Database Service (fromHsing et al 2022)…”