iadine | The Conservation Decisions Team

Nov 3

Small data call for big ideas

Urgent decision making can’t wait for big data!

In this week Nature’s correspondence, Iadine and Sam raise that the shift of private and public funding towards big data problems could impact our ability to solve some of our most urgent decision problems – for which we have no or very little amount of data available: biodiversity, health and biosecurity issues to cite a few. Sam and Iadine also provide some solutions and call for big ideas. It’s free for all to read.

Chades, I. & Nicol, S. (2016) Information: Small data call for big ideas. Nature, 539, 31-31.

Iadine and Sam wrote a bigger piece on the topic. We welcome your comments: Chades, I. & Nicol, S. (2016, November 2). Small data, big ideas. Zenodo. http://doi.org/10.5281/zenodo.164443

Jul 15

Free toolbox to solve stochastic dynamic programming problems in R, MATLAB, OCTAVE and SciLab

If you are interested in finding the best decisions over time to save or eradicate the cutest species, then you are probably interested in using Stochastic Dynamic Programming (SDP) or its mathematical model Markov Decision Process (MDP). If you have a burning problem ready to be solved but not sure how to, then good news we have released the MDPToolbox (ver. 4) in R, Matlab, Octave and Scilab. Please spread the word, the toolbox is free! Thanks to Ecography, you can now support our efforts by citing our paper:

Chadès, I., Chapron, G., Cros, M.-J., Garcia, F. and Sabbadin, R. (2014), MDPtoolbox: a multi-platform toolbox to solve stochastic dynamic programming problems. Ecography. doi: 10.1111/ecog.00888

To download the toolbox: http://www7.inra.fr/mia/T/MDPtoolbox/

If you are still unsure about SDP, try: Marescot, L., G. Chapron, I. Chadès, P. Fackler, C. Duchamp, E. Marboutin, and O. Gimenez. 2013. Complex decisions made simple: a primer on stochastic dynamic programming. Methods in Ecology and Evolution 4:872-884.

May 30

Prioritising species for monitoring conservation actions: Combining cost-effectiveness with complementarity

We have a decision point article that just came out this month! A great opportunity to communicate on how we can use complementarity between species to improve our monitoring efficiency, and of course remain cost-effective. In Tulloch et al (2013), we used network theory and a lot of ecology to find the best way of modelling and solving this problem. In the end, we were very pleased to show that it is possible to increase your monitoring power by selecting the most complementary species and also reducing the cost. A win-win situation that is rarely available in conservation. Read more

May 30

Complex decisions made simple: a primer on stochastic dynamic programming

Do you need to find the best decisions to maximize your chances of protecting a threatened species today but also in the future? Yes? Then you might be interested by our primer on stochastic dynamic programming (SDP). Stochastic Dynamic Programming (SDP) is an essential tool in conservation biology and natural resources management.

Marescot L., Chapron G., Chadès I., Fackler P., Duchamp C., Marboutin E. & Gimenez O. (2013). Complex decisions made simple: a primer on stochastic dynamic programming. Methods in Ecology and Evolution, 4, 872-884.

Join our team: 3-year postdoctoral fellowship on optimizing adaptive management

We are seeking a highly motivated and dynamic postdoctoral research fellow to join CSIRO Ecosystem Sciences’ conservation decisions team to undertake research on optimizing adaptive management decisions under imperfect detection. Read more