Every harvest policy in the world rests on compensation: the idea that a fished population responds to declines by growing, surviving or reproducing better, and that somewhere in that response is a sweet spot where yield is highest and the stock persists. Reference points, harvest control rules and rebuilding targets are all downstream of it.
Yet the relationship between spawning stock and the recruits it produces is routinely described as the great unresolved problem in fisheries ecology. In practice we usually assume its shape, fitting a Beverton–Holt or a Ricker curve, and then read resilience off the fitted parameters. The shape is an input, not a result.
We take the opposite approach: build a size- and age-structured population from its ecological parts, and see what stock–recruitment relationship emerges. The parts that matter are the ones individual fish actually experience: how cohorts compete for food, whether competition is size-structured, and how maturation responds plastically to growth, with age or size at maturity free to shift. We then run those processes across a pace-of-life gradient, from fast populations with high adult mortality and few age classes to slow ones that live long, mature late and grow large.
The shape of the recruitment curve turns out to be an emergent property of that machinery. A dome-shaped relationship appears most strongly where every cohort competes density-dependently, maturation age is plastic, and the pace of life is slow. An asymptotic relationship emerges at faster pace of life with size-structured exploitative competition. Which curve a population “has” is a consequence of its biology, not a modelling convention.
This is the result that most interests us. Conventional wisdom holds that slow, long-lived, late-maturing species are less resilient to fishing, and in one sense that is right: they support lower fishing mortality at maximum sustainable yield. But their drawn-out demography makes them more resistant once abundance is low, with higher steepness and higher compensation ratios, and they tolerate more fishing mortality relative to their natural mortality than fast species do.
So resilience has at least two components: the magnitude of harvest a population can sustain, and the compensatory strength that pulls it back from low abundance. Across the pace-of-life gradient those two move in opposite directions. A single index cannot carry both. Which means that whenever we call a species “resilient”, we have quietly chosen one of them, and the reference points we derive inherit that choice.
We also find that environmental noise is not transmitted neutrally. Random variation in early-life survival is amplified in slow populations when size at maturation is plastic, and dampened when age at maturation is plastic instead. Much of the recruitment variability attributed to the environment may be filtered, before we ever observe it, by the population’s own life history.
This is a theoretical programme with a lot of open ground, and it is one of the places where a student can contribute quickly:
If resilience indices and reference points are emergent properties of life history rather than free parameters, then theory can supply informative priors for them, including for the many populations with too little data to estimate them directly. That is the practical payoff: a principled way to say what a stock–recruitment relationship for a given kind of fish should plausibly look like, before any data arrive.
Much of this work is simulation and analysis rather than fieldwork, and it suits students who enjoy building models and thinking about why populations behave as they do. If that sounds like you, get in touch.