When hypothesizing about complex processes in social-ecological systems, simulations can produce useful 'what-if' scenarios. BUT, how do we know which simulation(s) best represent the real world and exactly how well they match? See how in our paper just out in Land Use Policy

Working with @MbaroukO of Community Forests Pemba (@CanadaTrees), we stared with a simple question: What's driving agricultural expansion into coral rag forests of Pemba, Tanzania, and how might conservation help slow it down?

Here's the link: sciencedirect.com/science/ar… This work was supported by @BoiseState @BoiseState_HCRI and @MPI_EVA_Leipzig. Special thanks to @rlmcelreath and Anne Kandler of @MPI_EVA_Leipzig for encouraging us to learn about & use approximate Bayesian computation. It's the future!

Last but not least, THANK YOU to my amazing coauthors: Jeff Andrews of @MPI_EVA_Leipzig, @MbaroukO, and @nickkolarik & @vickenhillis of @HumEnviroSystem.

And I almost forgot. We produced a web app for Community Forests Pemba staff to make informed decisions about interventions. matthewclark.shinyapps.io/La… The app uses our model estimates to make predictions about land cover change under different intervention scenarios

Working with @MbaroukO of Community Forests Pemba (@CanadaTrees), we stared with a simple question: What's driving agricultural expansion into coral rag forests of Pemba, Tanzania, and how might conservation help slow it down?