Improving estimates of the state of global fisheries depends on better data

A summary of Ovando et al. (2021) "Improving estimates of the state of global fisheries depends on better data"

Dan Ovando

7 minute read

There is a saying adapted from the fisheries scientist John Shepherd that managing fisheries is just like managing trees except they move and you can’t see them. This means that actually figuring out how many fish are in the water can be very difficult, and determining what sustainable levels of harvest are likely to be even more challenging. In Ovando et al. (2021), we looked at the potential for models based largely on the volume and shape a fisheries catch history to estimate the state of…

Assessing the Population-Level Effects of MPAs

A summary of Ovando et al. (2021)

Dan Ovando

13 minute read

If you’ve ever spent time exploring a part of the ocean protected from fishing you’ve probably been struck by the amazing abundance of marine life living there. These places, currently covering between 3-7% of the world’s oceans, are a form of Marine Protected Area (MPA). MPAs can be a powerful conservation tool, and there is a growing movement to expand MPAs to cover 30% of the world’s oceans by 2030. However, actually measuring the effect that MPAs have on fish populations can be very…

Fitting Bayesian Models using Stan and R

An introduction to fitting Bayesian models using Stan and R

54 minute read

Stan is a programming language designed to make statistical modeling easier and faster, especially for Bayesian estimation problems. Stan can help you estimate complex models with large numbers of parameters, and can generally do it faster than alternative like JAGS/BUGS