Tracking animals with particles

Post provided by Edward Lavender, Andreas Scheidegger, Carlo Albert, Stanisław W. Biber, Janine Illian, James Thorburn, Sophie Smout, Helen Moor. It’s morning on Scotland’s west coast. In the Firth of Lorn, the deep-blue water sparkles in the early sunlight. Heading south, I glance back across the sea, taking in the snow-speckled mountains beyond. Two hundred metres below, I know the seascape is just as rugged. … Continue reading Tracking animals with particles

The photo that got away: Camera traps may monitor less space than we think

Post provided by Brendan Carswell. Brendan (he/him/his) is currently a PhD student in Biology at the University of Calgary in the Weaving Wildlife and Land Based Knowledges lab. This paper, however, came from Brendan’s Masters work at the Memorial University of Newfoundland and Labrador in the Wildlife Evolutionary Ecology Lab. Motivation Our research team is interested in facilitating inclusive and accessible wildlife management across Canada. … Continue reading The photo that got away: Camera traps may monitor less space than we think

From lab tanks to river banks: taking fish cognition research into the wild

Post provided by Catarina Vila Pouca This post is also available in Portuguese Hello there! My name is Catarina Vila Pouca and I study how and why animals behave and learn in different ways. I have had a passion for sharks and swimming for as long as I can remember, and so in my career I have mostly focused on sharks and fish. My latest … Continue reading From lab tanks to river banks: taking fish cognition research into the wild

From a frustrated undergraduate to a motivated PhD: The story of YOLO-Behaviour for automated behavioural coding from videos

Post provided by Alex Chan Hoi Hang, PhD student, Centre for the Advanced Study of Collective Behaviour, University of Konstanz The story of this project can be traced back to 2019, as a second-year undergraduate in biological sciences at Imperial College London, UK, where I took an animal behaviour course. For one of the hands-on sessions, Dr. Julia Schroeder (who later became my undergraduate and … Continue reading From a frustrated undergraduate to a motivated PhD: The story of YOLO-Behaviour for automated behavioural coding from videos

Addressing observational biases in data-driven approaches of zoonotic hazard prediction

Post provided by Andrea Tonelli Over the past five decades, more than half of emerging infectious diseases in humans originated from animals, with zoonotic pathogens posing a growing threat to global health. Shifts in land use, climate change, direct use of wildlife and biodiversity loss all influence human exposure to pathogens of wild animals, shaping the likelihood of zoonotic spillover events. In the wake of … Continue reading Addressing observational biases in data-driven approaches of zoonotic hazard prediction

Into the Swarm-Verse: quantifying collective motion across species and contexts

Post provided by Marina Papadopoulou Authors We are three researchers interested in collective animal behaviour. Marina Papadopoulou is a postdoctoral researcher at Tuscia University in Italy, Simon Garnier is a Professor at the New Jersey Institute of Technology (USA), and Andrew King is an Associate Professor at Swansea University (UK). As a Greek-French-Welsh team with empirical, mathematical, and computational backgrounds in different study systems, we … Continue reading Into the Swarm-Verse: quantifying collective motion across species and contexts

Avoiding Confusion: Modelling Image Identification Surveys with Classification Errors

Post provided by Jon Barry We are a group comprised of statisticians, ecologists and a computer scientist. Back in 2021 when this work started, we were all employed at the Centre for Environment, Fisheries and Aquacultural Science (Cefas) at Lowestoft, U.K. Since then, Robert, our computer scientist, has ‘jumped ship’ (no pun intended) to the Alan Turing Institute. We were aware that AI image recognition … Continue reading Avoiding Confusion: Modelling Image Identification Surveys with Classification Errors

Ten practical guidelines for microclimate research in terrestrial ecosystems

Post provided by  Jonas Lembrechts. Blogpost adapted from: http://www.the3dlab.org: Ten practical guidelines | The 3D lab Ecologists and biogeographers are increasingly recognizing the critical role of microclimate in addressing a wide range of research questions. Consequently, many researchers are incorporating microclimate sensors into their studies. While deploying these sensors might seem straightforward—simply plugging them in and collecting data—there are numerous important factors to consider. Until … Continue reading Ten practical guidelines for microclimate research in terrestrial ecosystems

Look inside: a handy tool for casting the enclosed nest structure of birds

Post provided by Jing-Chia Guo. To understand something, we often describe its appearance and shape: The ball is round, the can is cylinder, and the pillow is kind of rectangle. However, most natural creatures are irregular in shape, so it’s difficult for people to quantify or define them. Sometimes, scientists are even unable to get their hands on the objects they need, and that is … Continue reading Look inside: a handy tool for casting the enclosed nest structure of birds

For worse and for better: the complicated marriage between biologging and wild animal welfare

Post provided by Michaël Beaulieu A cold Encounter in the Wild When talking about animal welfare to scientists who commonly use biologging tools to monitor the behaviour or physiology of wild animals in an ecological or conservation context, I have noticed that the first thing that usually comes to mind for them is the unwanted impact that biologging may have on animal welfare. Much has … Continue reading For worse and for better: the complicated marriage between biologging and wild animal welfare