In Conservation Planning, Some Data are More Important Than Others

Provided by Heini Kujala and José Lahoz-Monfort

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Spatial Conservation Planning and the Quest for Perfect Data

Conservation planners and managers often need to make decisions with imperfect information. When deciding what action to take or how to divide resources between candidate locations, we rarely have all the information we’d like on what species are present at a site or which areas are most critical for supporting their population viability. A large volume of ecological research focuses on answering these very questions.

To make conservation decisions, we need other types of data as well. These include information on things like the cost of carrying out a given conservation action, current condition of sites, the distribution and intensity of threats in a region, and much more. Many conservation problems are spatial, meaning that we often need to decide between multiple candidate locations and that there are spatial dependencies between sites that need to be accounted for. All these different pieces of information are needed to make cost-efficient and effective conservation decisions.

Ecologists and conservation biologists are usually concerned about the completeness and accuracy of the ecological data used to make these decisions (understandably). But less effort has been spent in researching and verifying the accuracy of the types of data mentioned above. At the same time, we have relatively poor understanding of how data gaps influence solutions optimised across multiple species and locations, and the relative importance of gaps in different types of data. This is what we set out to find in ‘Not all data are equal: Influence of data type and amount in spatial conservation prioritisation’. Continue reading

RSS Meeting on Model Averaging: Elephants, Oscars and Spiky Data

Post provided by Dr Eleni Matechou

Eleni is a Lecturer in Statistics and a member of the Statistical Ecology @ Kent (SE@K) group at the University of Kent. She develops statistical models motivated by ecological applications to study populations of birds, insects and, more recently, humans.

On September 15th 2016, a half-day meeting on Model Averaging – organised by the Environmental Statistics section and the East Kent local group of the Royal Statistical Society (RSS) – took place at the University of Kent in Canterbury .

There were three invited speakers: Professor Richard Chandler, from University College London, Professor Jonty Rougier, from the University of Bristol and Dr Kate Searle, from the Centre for Ecology and Hydrology, who presented via Skype.

All three talks included interesting motivating data, clever modelling and great insight.

Taming the Pachyderm

elephant-in-the-roomProfessor Richard Chandler presented joint work with Marianna Demetriou on “The interpretation of climate model ensembles”. Projecting future global temperatures is clearly a timely topic and Richard’s talk highlighted the challenges of doing this reliably. And they’re certainly not minor challenges, in his own words, this is a problem he has spent 10 years thinking about! Continue reading

Spatially-explicit Power Analysis: A First Step for Occupancy-Based Monitoring

Post provided by Martha Ellis and Jody Tucker

Where’s Waldo? Trying to find this fisher somewhere in a giant landscape is going to be tricky! ©Mike Schwartz

Where’s Waldo? Trying to find this little guy somewhere in a giant landscape is going to be tricky! © Mike Schwartz

The seemingly basic question of whether a population is increasing, decreasing, or stable can be one of the most difficult to answer. Collecting data on rare and elusive species is hard. Imagine trying to detect a handful of fisher or wolverine across hundreds of thousands of acres – it is physically demanding, time consuming and logistically complicated. And that’s just to do it once! To monitor a population for changes, you have to repeat these surveys regularly over many years. The long-term monitoring that is necessary for conservation requires careful planning and a substantial commitment of resources and funding. So before we spend these valuable resources, it’s critical to know whether the data we are collecting can help us to answer our questions. Continue reading