Innovations in Camera Trapping Technology and Approaches: The Integration of Citizen Science and Artificial Intelligence

Camera trapping has become an increasingly reliable and mainstream tool for surveying a diversity of wildlife species. Concurrent with this has been an increasing effort to involve the wider public in the research process, in an approach known as ‘citizen science’. To date, millions of people have contributed to research across a wide variety of disciplines as a result. Although their value for public engagement was recognised early on, camera traps were initially ill‐suited for citizen science. As camera trap technology has evolved, cameras have become more user‐friendly and the enormous quantities of data they now collect has led researchers to seek assistance in classifying footage. This has now made camera trap research a prime candidate for citizen science, as reflected by the large number of camera trap projects now integrating public participation. Researchers are also turning to Artificial Intelligence (AI) to assist with classification of footage. Although this rapidly‐advancing field is already proving a useful tool, accuracy is variable and AI does not provide the social and engagement benefits associated with citizen science approaches. We propose, as a solution, more efforts to combine citizen science with AI to improve classification accuracy and efficiency while maintaining public involvement

A semi-automatic workflow to process images from small mammal camera traps

Camera traps have become popular for monitoring biodiversity, but the huge amounts of image data that arise from camera trap monitoring represent a challenge and artificial intelligence is increasingly used to automatically classify large image data sets. However, it is still challenging to combine automatic classification with other steps and tools needed for efficient, quality-assured and adaptive processing of camera trap images in long-term monitoring programs. Here we propose a semi-automatic workflow to process images from small mammal cameras that combines all necessary steps from downloading camera trap images in the field to a quality checked data set ready to be used in ecological analyses. The workflow is implemented in R and includes (1) managing raw images, (2) automatic image classification, (3) quality check of automatic image labels, as well as the possibilities to (4) retrain the model with new images and to (5) manually review subsets of images to correct image labels. We illustrate the application of this workflow for the development of a new monitoring program of an Arctic small mammal community. We first trained a classification model for the specific small mammal community based on images from an initial set of camera traps. As the monitoring program evolved, the classification model was retrained with a small subset of images from new camera traps. This case study highlights the importance of model retraining in adaptive monitoring programs based on camera traps as this step in the workflow increases model performance and substantially decreases the total time needed for manually reviewing images and correcting image labels. We provide all R scripts to make the workflow accessible to other ecologists

Monitoring the UK’s wild mammals: A new grammar for citizen science engagement and ecology

Anthropogenic activities have imperilled not just global ecosystems, but also the ecosystem services they provide which are crucial for human livelihoods. To understand these changes, there is a need for effective monitoring over large spatial and temporal scales. This thesis will build on two proposed solutions. First, citizen science – defined here as the involvement of non-professionals in scientific enquiry – allows the crowdsourcing of data collection and classification to expand monitoring in ways that are logistically infeasible for ecologists alone. Second, motion-sensing camera traps can reduce the labour needed for monitoring since they can be deployed for long periods and provide continuous, relatively unbiased observations. In this thesis, I describe MammalWeb, a citizen science project in north-east England where I enlisted the aid of the local community in wild mammal monitoring. Motivated by the current unevenness of survey effort and data for mammals in Great Britain, MammalWeb involves citizen scientists in both the collection and classification of camera trap images, a novel combination. This is a multidisciplinary project, and in the following chapters I will begin, in Chapter 2, with a detailed reflection on the organisation of the MammalWeb citizen science project and approaches to evaluating its performance. I observe that the majority of contributions came from a small subset of citizen scientists. In Chapter 3, I develop an economical approach to deriving consensus classifications from the aggregated input of multiple users, which is a crucial part of many citizen science projects. This is followed in Chapter 4 by a case study of a partnership I initiated between MammalWeb and the local Belmont Community School, where we empowered a group of secondary school students to not only aid in collecting data for MammalWeb, but also design and deliver ecological outreach to their community. This is now the template for a wider network of school partnerships we are pursuing. Chapter 5 will examine common concerns around estimating species occupancy from camera trap data, including post-hoc discretisation of observations and effects of missing data. I also develop a resampling method to account for uncertain detections, a common issue when crowdsourcing data classifications. I show that, through resampling, the estimated parameters from occupancy models are robust against high uncertainty in the underlying detections. Lastly, Chapter 6 will discuss how my work on MammalWeb has laid the foundation for a wider citizen science camera trapping network in the United Kingdom and avenues for future work. Importantly, I show that MammalWeb citizen scientists have been empowered to be more than “mobile sensors” and act as independent researchers who have initiated ecological studies elsewhere

Mammal species inventory using various trapping methods in Zone 4 of Billy Barquedier National Park, Belize during rainy season

Belize is a small country, but it is extremely ecologically diverse. Based on the few studies conducted in Belize, the abundance of mammals is low but diversity is high. Particular findings note the number and identity of species differed between four sites in the Maya Mountains of Belize, indicating that a data set from a single site is not representative of the Neotropical region. Insufficient data is available to estimate current species richness of many areas in Belize, including Billy Barquedier National Park (BBNP). The objective of this study was to explore trapping and documentation methods of terrestrial mammals in BBNP, particularly in Zone 4, and to provide a baseline study of the present species. To accomplish the objectives, four methods were used: 1) direct visual observation; 2) observation of animal tracks; 3) live traps; and 4) game cameras. As expected based on previous studies, endangered species were present amongst the 16 mammal species documented. The various documentation methods presented unique biases towards species, with game cameras capturing the greatest mammal diversity. Further monitoring of animals in BBNP is needed for more accurate information regarding species richness and biodiversity. A controlled, consistent, long-term assessment of the number and composition of mammal species within BBNP could potentially improve management practices and conservation efforts

Camera trap distance sampling for terrestrial mammal population monitoring: lessons learnt from a UK case study

Accurate and precise density estimates are crucial for effective species management and conservation. However, efficient monitoring of mammal densities over large spatial and temporal scales is challenging. In the United Kingdom, published density estimates for many mammals, including species considered to be common, are imprecise. Camera trap distance sampling (CTDS) can estimate densities of multiple species at a time and has been used successfully in a small number of studies. However, CTDS has typically been used over relatively homogeneous landscapes, often over large time scales, making monitoring changes (by repeating surveys) difficult. In this study, we deployed camera traps at 109 sites across an area of 2725 km2 of varied habitat in North-East England, United Kingdom. The 4-month survey generated 51 447 photos of wild mammal species. Data were sufficient for us to use CTDS to estimate the densities of eight mammal species across the whole-survey area and within four specific habitats. Both survey-wide and habitat-specific density estimates largely fell within previously published density ranges and our estimates were amongst the most precise produced for these species to date. Lower precision for some species was typically due to animals being missed by the camera at certain distances, highlighting the need for careful consideration of practical and methodological decisions, such as how high to set cameras and where to left-truncate data. Although CTDS is a promising methodology for determining densities of multiple species from one survey, species-specific decisions are still required and these cannot always be generalized across species types and locations. Taking the United Kingdom as a case study, our study highlights the potential for CTDS to be used on a national scale, although the scale of the task suggests that it would need to be integrated with a citizen science approach

Assessing mammal diversity, distribution, and abundance: piloting arboreal camera trapping as a tool for monitoring endangered red panda in temperate forest of Eastern Nepal : A thesis submitted in partial fulfilment of the requirements for the Degree of Master at Lincoln University

I investigated the diversity, abundance and terrestrial activity patterns of medium and large sized wild mammals including a dedicated camera trapping survey for endangered and arboreal red pandas in the non-protected forests of Ilam, Panchthar and Taplejung districts of eastern Nepal. This thesis presents the first camera trap-based inventory of the southern Kangchenjunga region. The mammalian inventory was done during the winter and spring season of 2018 with 107 different camera trap locations (53 in winter and 54 in spring). The dedicated camera trapping survey for red panda camera was conducted in 19 different locations of Ilam and Panchthar districts using a pair of camera traps at each site (one on ground and one in tree canopy). There were 903 photographs (96 from ground camera and 807 from arboreal camera) of red panda from 1,620 camera trap days. Over 3,014 camera trap days there were 93,336 photographs taken (5,176 of wild mammals, 3,621 of birds, 11,692 of people, and livestock, 65,488 of false triggers and 6,061 during camera set ups). 5,177 photographs of medium to large sized mammals were used for the analysis in Camera Base. There were 17 species of medium to large sized wild mammals observed belonging to 4 orders and 12 families. Notable species records from this study were red panda Ailurus fulgens, common leopard Panthera pardus, marbled cat Pardofelis marmorata, Asiatic golden cat Catopuma temminckii, Himalayan serow Capricornis thar, Himalayan goral Naemorhedus goral, Assam macaque Macaca assamensis, Himalayan black bear Ursus thibetanus, and Spotted linsang Prionodon pardicolor. The leopard cat Prinonailurus bengalensis was found to have the most diverse distribution covering temperate to alpine habitat. The Northern red muntjac Muntiacus vaginalis was found to be the most abundant species followed by wild boar Sus scrofa, leopard cat, and red fox Vulpes vulpes. Despite some limitations, camera trapping was found to be effective in monitoring medium to large sized mammals in this study, particularly for red panda. Employing camera trap surveys for similar kinds of studies, and also for the long-term monitoring of mammals in a study area, is recommended for management of wildlife and effective conservation

Preliminary assessment on the distribution and density of the carnivores and ungulates of the Iona National Park

In Angola, the terrestrial mammals were harshly affected during the civil war and post-war periods suffering from pressures such as poaching, habitat loss and human-wildlife conflicts. Protected areas play nowadays an important role for their recovery and conservation but there is a lack of contemporary studies. We conducted a preliminary assessment on the distribution and relative abundance of the large and medium-sized mammals in Iona National Park, one of the largest protected areas in Angola, using camera traps, opportunistic observations, and local knowledge. A total of 19 mammal species were recorded being springbok, gemsbok, aardvark and aardwolf the more common. Our research concluded that despite the arid conditions and war effects there is still a reasonable diversity of species within the park and we raise attention to the potential threats facing these due to the increasing human and livestock pressure; Resumo: Em Angola, a comunidade de mamíferos terrestres foi fortemente afetada nos períodos de guerra civil e pós-guerra, sofrendo pressões de caça furtiva, perda de habitat e conflitos homem-animal. As áreas protegidas desempenham atualmente um papel fundamental para a sua recuperação e conservação, mas existe uma lacuna de estudos contemporâneos. Realizamos um estudo preliminar da distribuição e abundância relativa de mamíferos de grande e médio porte no Parque Nacional do Iona, uma das maiores áreas protegidas de Angola, utilizando armadilhagem fotográfica, observações oportunistas e o conhecimento local. Um total de 19 espécies foram registadas sendo que as mais comuns foram: cabra-de-leque, guelengue-do-deserto, porco-formigueiro e protelo. Com este estudo concluímos que apesar das condições áridas e dos efeitos da guerra, ainda existe uma diversidade razoável de espécies dentro do parque e alertamos para as potenciais ameaças que estas enfrentam devido à crescente pressão humana e de gado

¿Qué tan efectivo es el fototrampeo para el monitoreo de especies de pastizal en el sur de la ecorregión Pampas?

We assessed the efficiency of camera trapping in monitoring bird and mammal species in the grasslands of Tandilia Mountains by calculating the naïve occupancy, capture rate, and time to the first detection for each species. We compared the observed richness with the reported richness from online databases. We performed species accumulation curves to estimate the sampling effort necessary to detect bird and mammal species. We detected 50 bird and 15 mammal species. The top 5 bird species (Chalk-browed Mockingbird, Rufous-collared Sparrow, Rufous Hornero, Great Pampa-Finch, and Spotted Nothura) accounted for 48% of all detected individual birds, with naïve occupancy of 21-25% and mean times for the first detection between 6 and 9 days. The top 5 mammal species (Pampas fox, large hairy armadillo, European hare, Molina’s hog-nosed skunk, and Geoffroy’s cat) accounted for 81% of all detected individual mammals, with naïve occupancy of 32-77% and mean times for the first detection between 4 and 7 days. A sampling effort of 2 weeks was the optimal balance between effort and result qualities. We detected all the reported richness of mammals and half of the reported grassland-associated birds. We provide valuable information for future grassland species monitoring with camera trapping in Neotropical grasslands.Evaluamos la eficiencia del fototrampeo para monitorear aves y mamíferos en pastizales del sistema de Tandilia mediante la ocupación naïve, tasa de captura y tiempo hasta la primera detección de cada especie. Comparamos la riqueza observada con aquella reportada en bases de datos en línea. Realizamos curvas de acumulación de especies para estimar el esfuerzo de muestreo necesario para detectar la riqueza de especies. Detectamos 50 especies de aves y 15 de mamíferos. Las principales especies de aves (calandria común, chingolo, hornero, verdón e inambú campestre) representaron 48% de todas las detecciones de este grupo, con una ocupación naïve de 21-25% y tiempos promedios hasta la primera detección de entre 6 y 9 días. Las principales especies de mamíferos (zorro pampeano, peludo, liebre europea, zorrino y gato montés) contituyeron 81% de las detecciones de este grupo, con una ocupación naïve de 32- 77% y tiempos promedios hasta la primera detección de entre 4 y 7 días. Un muestreo de 2 semanas fue el balance óptimo entre esfuerzo y calidad de los resultados. Se detectó toda la riqueza reportada de mamíferos y la mitad de las aves asociadas a pastizales. Brindamos información valiosa para futuros monitoreos con fototrampeo en pastizales neotropicales.Fil: Trofino Falasco, Clara. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto Multidisciplinario de Ecosistemas y Desarrollo Sustentable; ArgentinaFil: Simoy, Maria Veronica. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto Multidisciplinario de Ecosistemas y Desarrollo Sustentable; ArgentinaFil: Aranguren, Maria Florencia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto Multidisciplinario de Ecosistemas y Desarrollo Sustentable; ArgentinaFil: Pizzarello, María Gimena. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto Multidisciplinario de Ecosistemas y Desarrollo Sustentable; ArgentinaFil: Cortelezzi, Agustina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto Multidisciplinario de Ecosistemas y Desarrollo Sustentable; ArgentinaFil: Vera, David Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. División Zoología de Vertebrados. Sección Herpetología; ArgentinaFil: Simoy, Mario Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto Multidisciplinario de Ecosistemas y Desarrollo Sustentable; ArgentinaFil: Marinelli, Claudia Beatriz. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto Multidisciplinario de Ecosistemas y Desarrollo Sustentable; ArgentinaFil: Cepeda, Rosana Esther. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto Multidisciplinario de Ecosistemas y Desarrollo Sustentable; ArgentinaFil: Di Giacomo, Adrian Santiago. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Centro de Ecología Aplicada del Litoral. Universidad Nacional del Nordeste. Centro de Ecología Aplicada del Litoral; ArgentinaFil: Berkunsky, Igor. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto Multidisciplinario de Ecosistemas y Desarrollo Sustentable; Argentin

Science, Community, and Culture: A Holistic Approach to Ecological Research and Education

Global biodiversity has declined at an alarming rate over the past century as a result of many complex human-induced environmental changes. Standardized surveys have historically been used to identify drivers of species declines, but such studies are often resource-intensive, resulting in significant spatial and temporal data gaps when researchers lack the resources necessary to maintain such studies. One promising solution for overcoming gaps in standardized studies is the integration of species observations by community members (e.g., community science). Along with improving modeling techniques to address biodiversity declines, the education of future ecologists on the importance of Indigenous ecological knowledge, robust scientific research, and community engagement in addressing myriad environmental problems is also imperative in addressing ecological challenges. Thus, my goals are 1) determine the efficacy of integrating standardized survey data with community-sourced observations to create species distribution models (SDMs) for species with varying responses to human-mediated environmental change and 2) create a curriculum that synergizes Indigenous ecological knowledge, scientific research techniques, and community science to establish a more holistic learning experience. I used data from Snapshot USA, a standardized nation-wide camera trap survey, and iNaturalist, an online community science platform, to create species distribution models and hands-on ecology lessons. My results demonstrate that integrated SDMs do produce informative predictions of the environmental factors that influence species distributions and provide a scaffolded framework for creating a more holistic approach to ecological education