That is now official, I am the new team leader of the conservation decisions team and we will be hiring this year! So stay tuned if you are looking for a wicked postdoc position in adaptive management/computational sustainability!
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 New paper out: Growing biodiverse carbon-rich forests
A small post from Baltimore, I gave my talk this morning and I have been asked for the slides. I had many interesting feedback for this talk. I will try to account for as many as I can. Thanks!
I’m currently involved in 3 projects where data is not available but we still need to provide guidance to managers on what action will be most efficient. In such cases, we have no choice but eliciting information from experts. There are many ways of proceeding, and you can find relevant information on google, but I still find that the details of how exactly doing it isn’t written anywhere. I feel that there is a big part of non-written way of proceeding that would benefit many of us. So if you are an expert in expert elicitation, please write us a guide – e.g. not another review!
For example we had trouble using 4-point estimates* data, and explaining to our experts what the confidence value represented. We did explain it many times, but we still get errors when we analyze the data. I do feel sorry for our experts that constantly have to rethink their values.
With internship student Martin Peron, we have developed a program to fit beta distribution to 4-point estimates. We are hoping to submit this program to MATLAB exchange very soon (and GNU Octave). So stay tuned if you are looking for such a program!
* 4 point estimates: best guess, min, max and confidence that the true value of the parameter we are estimating lies in this interval.
I’m heading to ICCB very soon. I am looking forward to seeing motivating presentations and exchanging ideas.
I will present my current work on organizing social networks to achieve best biodiversity outcome (Monday 21st). I’m also involved in a project with Jonathan Rhodes in which we try to assess the importance of influence in networks. More on our symposium here.
Feel free to send me an email if you want to chat, I will have some time in between sessions!
After ICCB I’m heading to Europe and France. I will work with my colleagues from INRIA – Olivier, in particular. I can’t wait to challenge him with some complex problems we have no solutions for!
I had good news yesterday.
1) I received a Julius Career Award to help me doing my research on adaptive management over the next 3 years and in particular a 6-month sabbatical.
2) We made substantial progress on our research project where we are trying to find the best social network for a given ecological network. We spent the day brainstorming and programming with Sam Nicol, Shaun Coutts and Angela. Jesse Hoey has been very helpful too and kindly updated SPUDD for the purpose of this study. I feel that this project has the potential to be a kick-ass paper. It feels great to do some cool fresh science!
3) I’m also the new Team Leader of our Conservation Decisions team. I hope I can keep managing my time efficiently so that I can produce good science and mentoring to the team.
I’m off to ICCB in 15 days (Baltimore) and then France for more adaptive management research!
I’m trying to start and finish a project in the next month. The project involves a lot of thinking and programming. I’m trying to solve a large action space Factored MDP. It’s challenging because the actions can’t be factored. It’s almost a flat MDP.
I’m hoping that the results will be easily interpretable. There is no point finding an optimal solution if I can’t explain it :-)
I’ll try to report the progress I make as we go.