Describing ecosystem contexts with single-species models: a theoretical synthesis for fisheries

Fished populations exist within complex ecosystems but are typically assessed using single-species models. It is often lamented that stock assessments rarely account for other ecosystem components explicitly, but in most fisheries there are clear difficulties in implementing data-intensive ecosystem-based assessment approaches. Addressing these competing challenges requires prioritizing investments in expanded assessment frameworks. To provide high-level conceptual guidance to such prioritization, here we use general analytical theory to identify (i) characteristics of fish stocks that tend to facilitate or inhibit the precision and accuracy of reference points from single-species assessments, (ii) characteristics of ecosystem components that introduce the greatest bias/imprecision into single-species reference points and (iii) warning signs within single-species frameworks that important ecosystem components may not be adequately accounted for. We synthesize and expand on theories from various branches of applied mathematics addressing analogous questions. Our theory suggests that (i) slow population dynamics (relative to the dynamics of other ecosystem components) and a wide range of abundance observations promote precision and accuracy of single-species reference points; (ii) ecosystem components that strongly influence the focal stock's growth, and change on similar timescales as the focal stock's abundance, introduce the greatest bias/imprecision to single-species reference points; and (iii) signs of potential challenges for single-species assessment include fast population dynamics, ‘hydra effects’ (i.e. abundance and fishing pressure simultaneously increase), and recently detected extinctions, invasions or regime shifts in closely connected ecosystem components. Our results generalize to other levels of abstraction and provide strategic insights complementing tactical simulation approaches such as management strategy evaluation.

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