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: 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

Resolving Conservation Conflicts: The Nominal Group Technique

Post provided by Jean Hugé

Conservation conflicts are actually conflicts among people with different priorities and values

Conservation conflicts are actually conflicts among people with different priorities.

Conservation issues seem to be getting ever more complex and challenging. Practitioners and society at large agree on the need to gather – and somehow use – as much information as possible before making any conservation-related decisions. Talking to all kinds of people, ranging from local villagers, fishermen and hunters to international experts, community leaders and environmentalists, is now common practice in conservation research. Not everyone will agree on the eventual conservation decisions, but the idea is that decisions should only be made after (almost) everyone’s opinion has been heard.

So far so good. The calls for inclusive conservation are being acknowledged, and we should be ready to move on and make better decisions, right? Well, it’s not always that easy. Conservation conflicts are actually conflicts among people with different priorities and values. Just calling for dialogue and hoping that consensus and effective conservation action will just follow isn’t enough. Continue reading

Using Interviews in Conservation Science Research

Post provided by David Christian Rose

Why Use Interviews in Conservation?

Key herder interviews by Chandrima Home (co-author) in the Upper Spiti Landscape © Kesang Chunit

Key herder interviews by Chandrima Home (co-author) in the Upper Spiti Landscape © Kesang Chunit

Conservation interventions need to be implemented on the ground, so a range of people are required to make decisions. Decision-makers can be people like conservation practitioners, policy-makers, and stakeholders who could be affected by an intervention. This usually includes local residents, as well as people who make their living in the area, like fishers, farmers, hunters, and other businesses.

Since decision-making structures are complex and multi-layered, scientific evidence alone is not enough to guide the implementation of a conservation intervention. Researchers need to understand who’s involved in making decisions, who could be affected by the proposed intervention, and gain an appreciation of how local communities use and value their land. Often they’ll also need to find out what local communities think of particular species and habitats. Continue reading

New Studies Aim to Boost Social Science Methods in Conservation Research

Below is a press release about the Methods Special Feature ‘Qualitative Methods for Eliciting Judgements for Decision Making‘ taken from the University of Exeter.

Scientists have produced a series of papers designed to improve research on conservation and the environment.

A group of researchers have contributed to a Special Feature of the journal Methods in Ecology and Evolution to examine commonly used social science techniques and provide a checklist for scientists to follow.

Traditional conservation biology has been dominated by quantitative data (measured in numbers) but today it frequently relies on qualitative methods such as interviews and focus group discussions. The aim of the special issue is to help researchers decide which techniques are most appropriate for their study, and improve the “methodological rigour” of these techniques. Continue reading