Accounting for complementary to maximize monitoring power for species management

Congratulations to Ayesha Tulloch. We have a new paper in Conservation Biology that addresses how to monitor management actions. I really like that paper and I hope it will become a good reference, check it out! Note that we also provide the Matlab code.

One challenge faced by researchers and conservation practitioners is designing and implementing effective monitoring programs particularly when funds are limited. Decisions about how to monitor are hindered by uncertainty in management outcomes. This research demonstrates a new framework for addressing the uncertainties in selecting species for monitoring change due to a management action or policy, using network theory and decision analysis.

Tulloch A.I.T., Chadès I., Possingham H.P. (2013) Accounting for Complementarity to Maximize Monitoring Power for Species Management. Conservation Biology 27, 988-999. Abstract

Adaptive management of migratory birds

We have a new paper published at IJCAI (top Artificial Intelligence conference, ranked A*, probably the most selective conference, congratulations to Sam and team!).

Nicol S, Buffet O, Iwamura T, Chadès I (2013). Adaptive management of migratory birds under sea level rise. Proceedings of IJCAI-13, Beijing, China. (PDF);

Or read the blog version on the computational sustainability website.

In this paper we are posing an adaptive management challenge to the AI community:

  • Why do we care? Because solving adaptive management problem is a complex optimisation problem and efficient methods are lacking!
  • What are we hoping? We hope that future AI research will account for the specific description of adaptive management problems using our problem as a classic benchmark problem.
  • How can you help, what’s next? If you have a complex problem feel free to submit a challenge to the AI community!


Sam at IJCAI 2013

Sam at IJCAI 2013 – Photo: O. Buffet

Migratory connectivity magnifies habitat loss

Graph representing the migratory flyway of the eastern curlew

Tak‘s paper is out! Don’t miss the bottleneck index that we derived – a handy tool to predict the most important nodes.

Iwamura, T., Possingham, H.,  Chadès, I., Minton, C., Murray, N., Rogers, D., Treml, E., Fuller, R. (2013) Migratory connectivity magnifies the consequences of habitat loss from sea-level rise for shorebird populations Proc R Soc B 280: 20130325


Sea-level rise (SLR) will greatly alter littoral ecosystems, causing habitat change and loss for coastal species. Habitat loss is widely used as a measurement of the risk of extinction, but because many coastal species are migratory, the impact of habitat loss will depend not only on its extent, but also on where it occurs. Here, we develop a novel graph-theoretic approach to measure the Continue reading

New paper out: Growing biodiverse carbon-rich forests

Congratulations to JB Pichancourt and team: An excellent work in an excellent journal! Feel free to contact JB directly if you require additional information on our paper.Pichancourt, JB; Firn, J,; Chades, I.; Martin T.G. 2013. Growing Biodiverse Carbon-Rich Forests. DOI: 10.1111/gcb.12345

Regrowing forests on cleared land is a key strategy to achieve both biodiversity conservation and climate change mitigation globally. Maximizing these co-benefits, however, remains theoretically and technically challenging because of the complex relationship between carbon sequestration and biodiversity in forests, the strong influence of climate variability and landscape position on forest development, the large number of restoration strategies possible, and long time-frames needed to declare success.Through the synthesis of three decades of knowledge on forest dynamics and plant functional traits combined with decision science, we demonstrate that we cannot always maximize carbon sequestration by simply increasing the functional trait diversity of trees planted. Continue reading

Complex decisions made simple

We recently had a paper accepted in Methods in Ecology and Evolution. I can’t say too much about it yet, but I hope it will be well received and useful to many. Well done Lucile and team!

Marescot L., Chapron G., Chadès I., Fackler P.L., Duchamp C., Marboutin E. & Gimenez, O. (Accepted 10/06/2013) Complex decisions made simple: a primer on stochastic dynamic programming. Methods in Ecology and Evolution.