Working on FLightR, the package for analysis of data obtained from solar geolocation tracking devices, we were haunted by the unpleasant feeling of investing in technology which will soon be out of date. Until now solar geolocators have been popular in ornithological studies. This is because they’re small, light-weight (< 1/3 g) tracking devices that can be deployed even on miniature birds, such as swallows and warblers. They’ve also been the longest-lasting data loggers, with the most storage space and, of course, the most affordable ones.
Are Solar Geolocators Finished?
There are apparent drawbacks of using this technique though. To begin with, solar geolocation simply does not work for some species. You can’t use it to study birds living in dense tropical forests or in cavities, because of the light-pattern bias. For the same reason, it doesn’t provide fantastic results in light-polluted areas. Data from geolocators cannot be retrieved remotely, and this is why you need to have high recapture rates for the species you’re studying. Continue reading →
Opportunistically collected species observation data, or citizen science data, are increasingly available. Importantly, they’re also becoming available for regions of the world and species for which few other data are available, and they may be able to fill a data gap.
In Sweden, over 60 million citizen science observations have been collected – an impressive number given that Sweden has a population of about 10 million people and that the Swedish Species Observation System, Artportalen, was created in 2000. For bird-watchers (or plant, fungi, or other animal enthusiasts), this is a good website to bookmark. It will give you a bit of help in finding species and as a bonus, has a lot of pretty pictures of interesting species. Given the amount of data citizen science can provide in areas with few other data, it’s important to evaluate whether they can be used reliably to answer questions in applied ecology or conservation. Continue reading →
Researchers are increasingly interested in how social behaviour influences a range of biological processes. Social data have the interesting mathematical property that the number of potential connections among individuals is typically much larger than the number of individuals (because individuals can interact with every other member of their group). This introduces a huge challenge when it comes to collecting data on social interactions—not only does the amount of data needed increase exponentially with group size, the data can also be more difficult to record.
Larger groups have more simultaneous interactions, making it harder for observers to capture a complete or representative sample. It’s also more difficult for observers to tell individuals apart in larger groups. Coloured markers are often used to distinguish different members of a group – the bigger the group, the more complex the markers are needed.
Group-level properties or behaviours can also emerge or change rapidly over time or depending on the situation. This means that observations have to be made at high temporal resolution. To study social behaviour with group sizes that resemble those occurring in nature, we need new techniques to extract sufficient information from social groups. Continue reading →
Ecologists have long been fascinated by animal sounds and in recent decades there’s been growing interest in the field of ‘bioacoustics’. This has partially been driven by the availability of high-definition digital audio recorders that can withstand harsh field conditions, as well as improvements in software technology that can automate sound analysis.
Each year an uncountable number of airborne organisms, mainly birds and insects, venture out on long journeys across the globe. In particular, the mass movements of birds have fascinated humankind for hundreds of years and inspired a wealth of increasingly sophisticated studies. The development and improvement of individual tracking devices in animal research and has provided amazing insights into such extensive journeys. Study of mass movements of biological organisms is still a challenge on continent-wide or cross-continental scales.
One tool that can effectively track and/or monitor large numbers of birds is radar technology. Radars offer many advantages over other methods such as visual counts or ringing. They’re less expensive, need less effort, offer better visibility and detectability, and are more applicable for large-scale monitoring. Networks of meteorological radars (as opposed to individual radars) seem particularly promising for large-scale studies. Continue reading →
Understanding key habitat requirements is critical to the conservation of species at risk. For highly mobile species, discerning what is key habitat as opposed to areas that are simply being traversed (perhaps in the search for key habitats) can be challenging. For seabirds, in particular, it can be difficult to know which areas in the sea represent key foraging grounds. Devices that record birds’ diving behaviour can help shed light on this, but they’re expensive to deploy. In contrast, devices that record the birds’ geographic position are more commonly available and have been around for some time.
In their recent study entitled ‘Predicting animal behaviour using deep learning: GPS data alone accurately predict diving in seabirds,’ Ella Browning and her colleagues made use of a rich dataset on 399 individual birds from three species, some equipped with both global positioning (GPS) and depth recorder devices, others with GPS only. The data allowed them to test whether deep learning methods can identify when the birds are diving (foraging) based on GPS data alone. Results were highly promising, with top models able to distinguish non-diving and diving behaviours with 94% and 80% accuracy. Continue reading →
Technological advancements in the past 20 years or so have spurred rapid growth in the study of migratory connectivity (the linkage of individuals and populations between seasons of the annual cycle). A new article in Methods in Ecology and Evolution provides methods to help make quantitative comparisons of migratory connectivity across studies, data types, and taxa to better understand the causes and consequences of the seasonal distributions of populations.
The seasonal long-distance migration of all kinds of animals – from whales to dragonflies to amphibians to birds – is as astonishing a feat as it is mysterious and this is an especially exciting time to study migratory animals. In the past 20 years, rapidly advancing technologies – from tracking devices, to stable isotopes in tissues, to genomics and analytical techniques for the analysis of ring re-encounter databases – mean that it’s now possible to follow many animals throughout the year and solve many of the mysteries of migration.
What is Migratory Connectivity?
One of the many important things we’re now able to measure is migratory connectivity, the connections of migratory individuals and populations between seasons. There are really two components of migratory connectivity:
Linking the geography of where individuals and populations occur between seasons.
The extent, or strength, of co-occurrence of individuals and populations between seasons.
Measurements of morphological features are important for ecological studies, especially on free-ranging wild animal species. Conventionally, specimens either dead or in captivity are used for morphometric studies, which is difficult in the case of wild species for several reasons.‘In situ measurements of animal morphological features: a non-invasive method’ presents a new way to estimate an individual’s morphometric measurements using metadata from digital photographs.
Dr. Mylswamy Mahendiran and Mr. Mylswamy Parthiban, two of the authors of the article, discuss their paper in the video below. The authors cover the main messages of the article – including who will benefit from reading it; how their method is relevant to animal welfare and wildlife studies; the scope and utility of digital photographic advancements; and how other disciplines could use this method.