Applications of Multi-Criteria Decision Analysis in Conservation Research

Post provided by Blal Adem Esmail & Davide Geneletti

Comparing Apples and Oranges

©Ruth Hartnup

In real-life situations, it is far more common for decisions to be based on a comparison between things that can’t be judged on the same standards. Whether you’re choosing a dish or a house or an area to prioritise for conservation you need to weigh up completely different things like cost, size, feasibility, acceptability, and desirability.

Those three examples of decisions differ in terms of complexity – you’d need specific expert knowledge and/or the involvement of other key stakeholders to choose conservation prioritisation areas, but probably not to pick a dish. The bottom line is they all require evaluating different alternatives to achieve the desired goal. This is the essence of multi-criteria decision analysis (MCDA). In MCDA the pros and cons of different alternatives are assessed against a number of diverse, yet clearly defined, criteria. Interestingly, the criteria can be expressed in different units, including monetary, biophysical, or simply qualitative terms. Continue reading


Using Focus Group Discussions in Conservation Research

Post provided by Christina Derrick

Focus Group Discussions: What are They and Why Use Them?

A focus group discussion with local farmers in Trans Mara district, Kenya, carried out by Tobias O. Nyumba (co-author)

A focus group discussion with local farmers in Trans Mara district, Kenya, carried out by Tobias O. Nyumba (co-author)

To paraphrase Nelson Mandela: ultimately, conservation is about groups of people. On a global scale it’s our collective human footprint that drives habitat destruction and species extinction, and the joint action of large groups that makes positive change. At a smaller scale, groups of people make decisions about conservation policy or management. In turn, communities of people feel the positive or negative effects of these actions, directly or indirectly. From global to local scales, groups of people make changes and groups of people feel the effects of those changes.

To improve conservation action and understand how decisions affect communities on the ground we need to talk to those communities. This is where focus group discussions become an asset to conservation research. They bring participants together in the same place where they can draw from their own personal beliefs and experiences, and those of other group members in a collective discussion. The researcher takes more of a backseat (facilitator) role in focus group discussions compared to interviews, allowing the group conversation to evolve organically. We can get a more holistic view of a situation from this method than from one-on-one interviews alone. Also, as respondents are interviewed at the same time and in the same place, travelling times and costs can be reduced for the researcher. Continue reading

Code-Based Methods and the Problem of Accessibility

Post provided by Jamie M. Kass, Matthew E. Aiello-Lammens, Bruno Vilela, Robert Muscarella, Cory Merow and Robert P. Anderson

The namesake of our software and founder of the field of biogeography, Alfred Russel Wallace. Photo ©G. W. Beccaloni

The namesake of our software and founder of the field of biogeography, Alfred Russel Wallace. Photo ©G. W. Beccaloni

In ecology, new methods are increasingly being accompanied by code, and sometimes even full command-line software packages (usually in R). This is great, as it makes analyses more reproducible and transparent, which is essential for the development of open science. In an ideal world, code would have informative annotation, generalized functions for multipurpose use, and be written in a legible and consistent manner. After all, the code may be used by ecologists with a wide range of programming experience.

In reality, code is often poorly commented (or not commented at all!), hard to reuse for other projects, and difficult to interpret. To add to that, most code isn’t actively maintained, so users are on their own if they try to commandeer it for new purposes. Further, ecologists with little or no programming knowledge are unlikely to benefit from methods that exist only as poorly documented code. In a positive development, some new methods are accessible through software with graphic user interfaces (GUIs) developed by programmers spending significant time and effort. But too often these end up as tools with flashy controls and insufficient instruction manuals. Continue reading

Editor Recommendation: A Practical Guide to Structured Expert Elicitation Using the IDEA Protocol

Post provided by Barbara Anderson

Today is International Women’s Day to mark the occasion I have the privilege of recommending, ‘A practical guide to structured expert elicitation using the IDEA protocol by Victoria Hemming et al. The IDEA behind the IDEA protocol – ‘Investigate’, ‘Discuss’, ‘Estimate’ and ‘Aggregate’ – is to provide a framework for Structured Expert Elicitation.

As a quantitative ecologist, I sometimes attempt to model species’ abundance and distribution changes in response to environmental change. Often these are species that, for one reason or another, we know a lot about. They may be high profile species of conservation concern, or have some economic or cultural importance. Some are simply model species that many people have studied because they’re easy to study because many people have studied them. Just as often though, we’re missing crucial data on one or more parameters. Frustratingly we don’t always have the time or resources to collect the new ecological or biological data required. Continue reading

Editor Recommendation: A Multi-State Species Distribution Modelling Framework for Species Using Distinct Habitats

Post provided by Jana McPherson

© Amélie Augé

© Amélie Augé

Correlative distribution models have become essential tools in conservation, macroecology and ecology more generally. They help turn limited occurrence records into predictive maps that help us get a better sense of where species might be found, which areas might be critical for their protection, how large their range currently is, and how it might change with climate change, urban encroachment or other forms of habitat conversion.

It can be frustrating, however, when species distribution models (and the predictive maps they produce) don’t adequately capture what we already know about the habitat needs of a species. A major challenge to date has been to represent the environmental needs of species that require distinct habitats during different life stages or behavioural states. Rainbow parrotfish (Scarus guacamaia), for example, spend their youth sheltered from predators in mangrove areas before moving onto coral reefs, and European nightjars (Caprimulgus europaeus) breed in heathland but require access to grazed grassland for foraging. Correlative distribution models confronted with occurrence records from both life stages or behavioural modes tend to produce poor predictive maps because they confound these distinct requirements. Continue reading

Editor Recommendation: How Do Trait Distributions Differ Across Species and Their Environments?

Post provided by Pedro Peres-Neto

The rise of trait ecology led to many quantitative frameworks to understand the underlying rules that determine how species are assembled into local communities from regional pools. Ecologists are interested in understanding whether environmental features select for particular traits that optimise local fitness and regulate species co-existence.

In ‘Assessing the joint behaviour of species traits as filtered by environment’, Erin Schliep and her co-authors aimed to develop a joint probabilistic model under a Bayesian framework to help explain the correlations among traits and how trait distributions differ across species and their environments. The end product is a model of trait-environmental relationships that takes full advantage of information on intra- and interspecific variation typically found within and among species.  Continue reading

Editor recommendation: Predicting Animal Behaviour Using Deep Learning

Post provided by Jana McPherson

Common guillemots were one of the species used in this study. ©Richard Crossley

Common guillemots were one of the species used in this study. ©Richard Crossley

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

Remote Sensing for Counting Animals: Polar Bears, Sheep and Everything In-Between

Post provided by Tracey Hollings

In an age of rapid technological advances, ecologists need to keep abreast of how we can improve or reinvent the way we do things. Remote sensing technology and image analysis have been developing rapidly and have the potential to revolutionise how we count and estimate animal populations.

Using remotely sensed imagery isn’t new in ecology, but recent innovations mean we can use it for more things. Land use change and vegetation mapping are among the areas of ecology where remote sensing has been used extensively for some time. Estimating animal populations with remotely sensed imagery was also demonstrated more than 40 years ago by detecting indirect signs of an animal with some success: think wombat burrows and penguin poop.

A polar bear from a helicopter

A polar bear from a helicopter

Thanks to improved spatial and spectral resolution (see the text box at the bottom of the post for a definition), accessibility, cost and coverage of remotely sensed data, and software development we have now reached a point where we can detect and count individual animals in imagery. Many of the first studies to demonstrate automated and semi-automated techniques have taken computer algorithms from other disciplines, such as engineering or biomedical sciences, and applied them to automate counting of animals in remotely sensed imagery. It turns out that detecting submarines is not so different to detecting whales! And finding abnormal cells in medical imaging is surprisingly similar to locating polar bears in the arctic! Continue reading

Remotely Tracking Movement and Behaviour with Biologgers: How to Add Accelerometer Data to the Mix

Post provided by Sam Cox, Florian Orgeret and Christophe Guinet

Animal biologging is a technique that’s quickly becoming popular in many cross-disciplinary fields. The main aim of the method is to record aspects of an animal’s behaviour and movement, alongside the bio-physical conditions they encounter, by attaching miniaturised devices to it. In marine ecosystems, the information from these devices can be used not only to learn how we can protect animals, many of whom are particularly vulnerable to disturbance (e.g. large fish, marine mammals, seabirds and turtles), but also more about the environments they inhabit.

Challenges when Tracking Marine Animals

Many marine animals have incredibly large ranges, travelling 1000s of kilometres. A huge advantage of biologging technologies is the ability to track an individual remotely throughout its range. For animals that dive, information on sub-surface behaviour can be obtained too. This information can then be retrieved when an animal returns to a set location. If this isn’t possible (e.g. individuals that make trips that are too long or die at sea), carefully constructed summaries can be relayed via satellite. This option provides information in real time, which can be very useful for researchers.

Tracks of juvenile southern elephant seals. Red tracks are individuals that returned to their natal colony. Grey are those individuals whose information would have been lost had it not been transmitted via the Argos satellite system.

Tracks of juvenile southern elephant seals. Red tracks are individuals that returned to their natal colony. Grey are those individuals whose information would have been lost had it not been transmitted via the Argos satellite system.

Continue reading

#EpicDuckChallenge Shows we can Count on Drones

Below is a press release about the Methods in Ecology and Evolution  article ‘Drones count wildlife more accurately and precisely than humans‘ taken from the University of Adelaide.

Lead author Jarrod Hodgson, University of Adelaide, standing in one of the replica colonies of seabirds constructed for the #EpicDuckChallenge.

Lead author Jarrod Hodgson, University of Adelaide, standing in one of the replica colonies of seabirds constructed for the #EpicDuckChallenge.

A few thousand rubber ducks, a group of experienced wildlife spotters and a drone have proven the usefulness and accuracy of drones for wildlife monitoring.

A study from the University of Adelaide showed that monitoring wildlife using drones is more accurate than traditional counting approaches. This was published recently in the British Ecological Society journal Methods in Ecology and Evolution.

“For a few years now, drones have been used to monitor different animals that can be seen from above, including elephants, seals and nesting birds. But, until now, the accuracy of using drones to count wildlife was unclear,” says the study’s lead author, Jarrod Hodgson from the University’s Environment Institute and School of Biological Sciences. Continue reading