Comparison of six methods for stabilizing metapopulation dynamics and the robustness of performance rankings to census noise

Abstract

Stabilizing extinction-prone populations is a central challenge in conservation, particularly for species with overcompensatory dynamics that generate boom-bust cycles. In spatially structured populations, dispersal can synchronize these fluctuations and amplify instability, while imperfect census data can misguide interventions, making both factors critical determinants of management outcomes. Using a two-patch metapopulation model based on the Ricker equation, we evaluate six rule-based population control methods under spatial coupling and census uncertainty. We compare their relative performance across 12 ecological conditions defined by two intrinsic growth rates, two carrying capacities, and three dispersal scenarios, using constancy-targeted and persistence-targeted analyses that integrate multiple stability metrics with implementation cost. Uncontrolled metapopulations exhibited distinct stability profiles across parameter combinations. Against these baseline regimes, augmenting populations to a fixed fraction of their previous size (Adaptive Limiter Control) emerged as the strongest overall performer under persistence-targeted analyses, while augmenting populations whenever they fell below a threshold (Lower Limiter Control) performed most favourably overall under constancy-targeted analyses. Under simulated census error, the relative ranking of methods was often broadly preserved across noise levels. Our results provide a comparative framework for evaluating rule-based interventions in spatially structured populations exhibiting overcompensatory (Ricker-type) dynamics, including semelparous species with high fecundity.