Stereo DOV: A Non-Invasive, Non-Destructive Way to Study Fish Populations

It’s more important than ever for us to have accurate information to help marine conservation efforts. Jordan Goetze and his colleagues have provided the first comprehensive guide for researchers using diver operated stereo-video methods (or stereo-DOVs) to survey fish assemblages and their associated habitat.

But what is Stereo DOV? What makes it a better method than the traditional UVC (Underwater Visual Census) method? And when should you use it? Find out in this video:

To find out more about stereo DOVs, read the full Methods in Ecology and Evolution article ‘A field and video analysis guide for diver operated stereo‐video
(No Subscription Required).

If you’re using interesting new field techniques like this, why not submit a Practical Tools manuscript about them? You can find out more about Practical Tools manuscripts here.

Assessing Sea Turtle Populations: Can We Get a Hand From Drones and Deep Learning?

Post provided by PATRICK GRAY

An olive ridley sea turtle in Ostional, Costa Rica. ©Vanessa Bézy.

Understanding animal movement and population size is a challenge for researchers studying any megafauna species. Sea turtles though, add a whole additional level of complexity. These wide-ranging, swift, charismatic animals spend much of their time underwater and in remote places. When trying to track down and count turtles, this obstacle to understanding population size becomes a full-on barricade.

Censusing these animals doesn’t just satisfy our scientific curiosity. It’s critical for understanding the consequences of unsound fishing practices, the benefits of conservation policy, and overall trends in population health for sea turtles, of which, six out of seven species range from vulnerable to critically endangered. Continue reading

Where do Animals Spend Their Time and Energy? Theory, Simulations and GPS Trackers Can Help Us Find Out


 An adult sleepy lizard with a GPS tracker and body temperature logger strapped to her tail. ©Mike Bull.

An adult sleepy lizard with a GPS tracker and body temperature logger strapped to her tail. ©Mike Bull.

Changes in temperature and available food determine where and when animals move, reproduce, and survive. Our understanding of how environmental change impacts biodiversity and species survival is well-established at the landscape, country and global scales. But, we know less about what could happen at finer space and time scales, such as within habitats, where behavioural responses by animals are crucial for daily survival.

Simulating Movement and Daily Survival with Individual-Based Movement Models

Key questions at these scales are how the states of individuals (things like body temperature and nutritional condition) influence movement decisions in response to habitat change, and how these decisions relate to patchiness in microclimates and food. So we need tools to make reliable forecasts of how fine-scale habitat use will change under future environments. Individual-based movement simulation models are powerful tools for these kinds of studies. They let you construct habitats that vary in temperature and food conditions in both space and time and ask ‘what if’ questions. By populating these models with activity, behaviour, and movement data of animals, we can simulate different habitat conditions and predict how animals will respond to future change. Continue reading

Issue 10.5: Movement Ecology, Palaeobiology, Monitoring and More

The May issue of Methods is now online!

The May issue of Methods in Ecology and Evolution is absolutely packed! We’ve got a new ecoacoustics method from Metcalf et al. and a new inference and forecasting method from Cenci et al. There’s also a forum article on image analysis, and papers on physiology, palaeobiology, capture-recapture and much more. We’ve got SIX papers that are freely available to absolutely everyone this month too.

Find out a little more about the new issue of Methods in Ecology and Evolution (including details about what the diver is doing to the coral in the cover image) below. Continue reading

How Can Understanding Animal Behaviour Help Support Wildlife Conservation?

Below is a press release about the Methods in Ecology and Evolution article ‘A novel biomechanical approach for animal behaviour recognition using accelerometers‘ taken from the EPFL.

©Arpat Ozgul, University of Zurich

Researchers from EPFL and the University of Zurich have developed a model that uses data from sensors worn by meerkats to gain a more detailed picture of how animals behave in the wild.

Advancement in sensor technologies has meant that field biologists are now collecting a growing mass of ever more precise data on animal behaviour. Yet there is currently no standardised method for determining exactly how to interpret these signals. Take meerkats, for instance. A signal that the animal is active could mean that it is moving; alternatively, it could indicate that it is digging in search of its favourite prey, scorpions. Likewise, an immobile meerkat could be resting – or keeping watch.

In an effort to answer these questions, researchers from EPFL’s School of Engineering Laboratory of Movement Analysis and Measurement (LMAM) teamed up with colleagues from the University of Zurich’s Population Ecology Research Group to develop a behavior recognition model. The research was conducted in affiliation with the Kalahari Research Centre. Continue reading

Quantifying Animal Movement from Videos

Quantifying animal movement is central to research spanning a variety of topics. It’s an important area of study for behavioural ecologists, evolutionary biologists, ecotoxicologists and many more. There are a lot of ways to track animals, but they’re often difficult, especially for people who don’t have a strong background in programming.

Vivek Hari SridharDominique G. Roche and Simon Gingins have developed a new, simple software to help with this though: Tracktor. This package provides researchers with a free, efficient, markerless video-based tracking solution to analyse animal movement of single individuals and groups.

Vivek and Simon explain the features and strengths of Tracktor in this new video:

Read the full Methods in Ecology and Evolution article ‘Tracktor: Image‐based automated tracking of animal movement and behaviour
(No Subscription Required).

Download and start using Tracktor via GitHub.

Field Work on a Shoestring: Using Consumer Technology as an Early Career Researcher

Post provided by CARLOS A. DE LA ROSA

Esta entrada de blog también está disponible en español

Champagne Tastes on a Beer Budget

Freshly outfitted with a VACAMS camera and GPS unit, #1691 heads off into the forest with her calf. ©Carlos A. de la Rosa

Freshly outfitted with a VACAMS camera and GPS unit, #1691 heads off into the forest with her calf. ©Carlos A. de la Rosa

There’s a frustrating yin and yang to biological research: motivated by curiosity and imagination, we often find ourselves instead defined by limitations. Some of these are fundamental human conditions. The spectrum of light detectable by human eyes, for example, means we can never see a flower the way a bee sees it. Others limitations, like funding and time, are realities of modern-day social and economic systems.

Early career researchers (ECRs) starting new projects and delving into new research systems must be especially creative to overcome the odds. Large grants can be transformative, giving a research group the equipment and resources to complete a study, but they’re tough to get. Inexperienced ECRs are at a disadvantage when competing against battle-hardened investigators with years of grant writing experience. Small grants of up to about $5000 USD, on the other hand, are comparatively easy to find. So, how can ECRs make the most of small, intermittent sources of funding?

I found myself faced with this question in the second year of my PhD field work. Continue reading

Monitoring Ecosystems through Sound: The Present and Future of Passive Acoustics

Post provided by Ella Browning and Rory Gibb

AudioMoth low-cost, open-source acoustic sensor ©

AudioMoth low-cost, open-source acoustic sensor ©

As human impacts on the world accelerate, so does the need for tools to monitor the effects we have on species and ecosystems. Alongside technologies like camera traps and satellite remote sensing, passive acoustic monitoring (PAM) has emerged as an increasingly valuable and flexible tool in ecology. The idea behind PAM is straightforward: autonomous acoustic sensors are placed in the field to collect audio recordings. The wildlife sounds within those recordings are then used to calculate important ecological metrics – such as species occupancy and relative abundance, behaviour and phenology, or community richness and diversity.

The Pros and Cons of Passive Acoustic Monitoring

Using sound to monitor ecosystems, rather than traditional survey methods or visual media, has many advantages. For example, it’s much easier to survey vocalising animals that are nocturnal, underwater or otherwise difficult to see. Also, because acoustic sensors capture the entire soundscape, it’s possible to calculate acoustic biodiversity metrics that aim to describe the entire vocalising animal community, as well as abiotic elements in the environment.

The use of PAM in ecology has been steadily growing for a couple of decades, mainly in bat and cetacean studies. But with sensor costs dropping and audio processing tools improving, there’s currently a massive growth in interest in applying acoustic methods to large-scale or long-term monitoring projects. As very low-cost sensors such as AudioMoth start to emerge, it’s becoming easier to deploy large numbers of sensors in the field and start collecting data. Continue reading

How do You Know that the Top Dog is Really the Top Dog? Using Elo-Ratings and Bayesian Inference to Determine Rankings in Animal Groups

Post provided by Julia Fischer

A female chacma baboon (rear) signals her submission to another female by raising her tail. ©Julia Fischer.

A female chacma baboon (rear) signals her submission to another female by raising her tail. ©Julia Fischer.

Anyone who studies social animals in the wild (or human groups, for that matter), will soon find that some individuals threaten or attack others frequently, while others try to get out of the way or signal their submission in response to aggression. Observers tally the outcome of such aggressive interactions between any given two individuals (or ‘dyads’) and try to deduce the rank hierarchy from such winner-loser matrices. One drawback of this approach is that all temporal information is lost.

Imagine Royal, a baboon, dominating over Power, another baboon, 20 times, and Power dominating over Royal 20 times as well. If we just look at these data, we might think that they have the same fighting ability and similar ranks. But, if we know that Royal beat Power the first 20 of the interactions, then Power beat Royal in all further interactions, we’d come to a totally different conclusion. We’d infer that Power had toppled Royal and a rank change had taken place.

How do Rank Hierarchies Change Over Time?

One prominent method that takes the temporal dynamics of winner-loser interactions into account was originally developed to calculate the relative skill level of chess players. This method was introduced by Arpad Elo and is hence known as Elo-Rating. Elo-Rating has also been applied to rate the relative skills in a variety of competitive fields, including Major League Baseball, video games, and Scrabble. Continue reading