New Associate Editor: Chris Sutherland

Today, we are pleased to welcome the latest new member of the Methods in Ecology and Evolution Associate Editor Board. Chris Sutherland joins us from the University of Massachusetts, USA and you can find out a little more about him below.

Chris Sutherland

“I’m an applied ecologist with a focus on spatial population ecology. I am particularly interested in understanding how spatial processes such as movement, dispersal and connectivity, influence the dynamics of spatially structured populations. Most of my research involves the development and application of spatially realistic hierarchical models for observations of individuals, populations and metapopulations.”

Chris has had a couple of articles published in Methods in Ecology and Evolution in recent years. In his 2015 article ‘Modelling non-Euclidean movement and landscape connectivity in highly structured ecological networks‘ Chris and his co-authors (Angela K. Fuller and J. Andrew Royle) evaluated the consequences of not accounting for movement heterogeneity when estimating abundance in highly structured landscapes, and demonstrated the value of this approach for estimating biologically realistic space-use patterns and landscape connectivity.

A multiregion community model for inference about geographic variation in species richness‘ by Chris, Mattia Brambilla, Paolo Pedrini and Simone Tenan was published in the journal in 2016. This paper reported on a new approach that provided a mechanism for testing hypotheses about why and how species richness varies across space.

Last year, Chris was also involved in ‘Quantifying spatial variation in the size and structure of ecologically stratified communities‘, which was published in the August issue of Methods. In this article, the authors provided a novel hierarchical multi-region community model for direct modelling of trait-based patterns of species richness along environmental gradients by splitting communities into ecologically relevant strata.

Chris currently has a number of ongoing projects including a long term (20 year) metapopulation study on water voles in North West Scotland with the objectives of better understanding the spatial drivers of colonisation-extinction dynamics and persistence of spatially structured populations. He is also working on monitoring and density estimation of a recovering population of American marten using photographic capture-recapture using a novel camera trapping design.

We are thrilled to welcome Chris as a new Associate Editor and we look forward to working with him on the journal.

The Value of Information: Does More Data Mean Better Decisions?

Post provided by Dr Stefano Canessa

Applied ecology can be defined as scientific knowledge that helps in making good management decisions. Scientists have a natural desire to collect information, managers want that information so that they know they are doing the right thing, and both generally act under the assumption that more information equals better decisions. This is generally correct, since information helps us make, well, informed decisions. Therefore, when our ecological knowledge is uncertain (which is practically always the case) we usually advocate further research.

On the other hand, however, information comes at a cost. It may cost money to collect it and take time to set up studies: both are usually in short supply. We can’t learn everything and often the information we can actually collect is still imperfect. So how do we determine if that additional piece of information we’d like to have is really valuable for our management?

In ‘When do we need more data? A primer on calculating the value of information for applied ecologists’ , Stefano Canessa and colleagues provide a tutorial to the calculation of value of information (VOI) for applied ecologists and managers who would like to know more about it, but are not familiar with decision-theoretic principles and notation.

What is ‘Value of Information’?

In decision analysis, the value of information is the improvement in the outcomes of our actions that we would expect if we could reduce or eliminate uncertainty before making a decision. Previously applied in engineering, economics and healthcare planning, VOI is also intuitively appealing for environmental management, where decisions must be made in the face of ubiquitous uncertainty.  Knowing the value of information can assist in designing monitoring and experimental programs, implementing adaptive management and prioritising sources of uncertainty. In other words, it can help applied ecologists and conservation managers find a focused, transparent way to address the inevitable need for “more data”.

An increasing number of studies are applying VOI to conservation management; however, in spite of its potential the technique is still underused in real-world applications, particularly beyond the small community of applied ecologists trained in decision-analytic methods.

Click Image to begin a Prezi Presentation on Value of Information

Click Image to begin a Prezi Presentation on Value of Information

In summary, three things determine the value of information:

  1. How much we already know (the more we know, the less beneficial it is to collect more information)
  2. Whether and how we would react to that extra information by changing actions, and how much better would the updated action be
  3. How good is the information we can actually get (think about sample sizes, imperfect detection, time lags, etc)

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