‘Tis the Season for Modelling Mortalities

Post provided by ELIE GURARIE

A warning: Halloween is nigh, and the following post contains graphic real-life imagery of maggot-eaten eye-sockets and deadly pianos. Read on… if you dare!

A Death in the Woods 

In the vast and often frozen boreal forest of northern Canada there is a slow-burning forensic investigation into a death. The victim: a woodland caribou, an iconic species that is threatened or endangered throughout its range.

Kyle Joly

The scene is very much made for TV neo-Scandinavian neo-noir. From a not-too-luxurious regional office in the town of Fort Smith, just north of the Alberta border, over a steaming cup of coffee, world-weary biologist Allicia Kelly – who’s seen it all and then some – is monitoring the movements of collared animals on her computer screen. It’s the middle of May. The females, nearly all pregnant, are scattering to higher ground to find suitably cozy and secluded sites to calve. All is as peaceful and idyllic as a bunch of blips on a computer screen can be.

But then (cue slightly unsettling dissonance in the soundtrack) one of the little blips seems to have stopped moving. Kelly raises her eyebrow, tells herself to keep an eye out. A moment later she makes the call: “Team, we’ve got another ringer … let’s roll!Continue reading

Inverse Modelling and IPMs: Estimating Processes from Incomplete Information

Post provided by Edgar J. González

In demography, a set of processes (survival, growth, fecundity, etc.) interacts to produce observable patterns (population size, structure, growth rate, etc.) that change over time. With traditional approaches you follow the individuals of a population over some timespan and track all of these processes.

Demographic patterns and processes (Click to expand)

Demographic patterns and processes (Click to expand)

However, depending on the organism, some processes may be very hard to quantify (e.g. mortality or recruitment in animals or plants with long lifespans). You may have observed the patterns for the organism that you’re studying and, even better, measured some, but not all, of the processes. The question is: can we use this limited information to estimate the processes we couldn’t measure? Continue reading