Recruitment variability and sampling design interact to influence the detectability of protected area effects

Abstract

Correctly identifying the effects of a human impact on a system is a persistent challenge in ecology, driven partly by the variable nature of natural systems. This is particularly true in many marine fishery species, which frequently experience large temporal fluctuations in recruitment that produce interannual variations in populations. This variability complicates efforts to maintain stocks at management targets or detect the effects of rebuilding efforts. We address this challenge in the context of no‐take marine reserves by exploring how variable larval recruitment could interact with the timing of reserve establishment and choice of sampling design to affect population dynamics and the detectability of reserve effects. To predict population changes in the years following a no‐take reserve implementation, we first tested for periodicity in larval recruitment in an important U.S. Pacific coast recreational fishery species (kelp bass, Paralabrax clathratus) and then included that pattern in a population model. We also used this model to determine the detectability of population increases under alternative sampling approaches and minimum age sampled. Kelp bass larval recruitment in the Channel Islands, California, peaked every about six (major) and about two (minor) years. Our model showed that establishing a reserve during a peak or trough enhanced or delayed, respectively, the post‐reserve population increases. However, establishing a reserve during a recruitment peak could obscure a failing reserve, that is, a reserve that is unable to secure longer‐term metapopulation persistence. Recruitment peaks and troughs also interacted with sampling design to affect the detectability of reserve effects. Designs that compared inside‐outside were the most robust to variable recruitment, but failed to capture whether the reserve has improved metapopulation growth. Designs that included a time element (e.g., before‐after) are more suited to assessing reserve effectiveness, but were sensitive to recruitment variation and detectability can change year‐to‐year. Notably, detectability did not always increase monotonically with reserve age; the optimal time for detectability depended on the minimum age of organisms sampled and was greatest when the cohort of a major recruitment peak first appeared in the sampling. We encourage managers to account for variable recruitment when planning monitoring and assessment programs.

Environment-driven trends in fish larval abundance predict fishery recruitment in two temperate reef congeners: Mechanisms and implications for fishery recovery under a changing ocean

“…Perhaps one of the most important conclusions of our study is that these two basses have different population dynamics: 1) larval recruitment patterns indicate differences in the persistence of their populations in southern California (e.g., background recruitment levels for KB are higher and less episodic, which is consistent with locally-sourced recruitment (Selkoe et al 2007) and higher densities (Warner 1985) and has implications regarding their resilience to harvest impacts and climate change), 2) relative to KB, BSB larval recruitment is more closely tied to temperature, which is consistent with historical reports of BSB availability in southern California (Jarvis Mason et al 2024) and which also has implications for resilience to harvest impacts and climate change, and 3) the offshore islands in the northern SCB are a notable hotspot for KB larval recruitment, which has implications associated with habitat protection (e.g., Marine Protected Areas, Hopf et al 2022). In contrast, BSB larval recruitment is limited to the mainland coast and given its sporadic nature and more southerly larval distribution in the SCB, may be influenced more so by El Niño-driven sporadic northward advection of larvae from Baja California (Jarvis Mason et al 2024) as has been suggested for other fishery species in the region (Smith & Moser 1988, Allen & Franklin 1992, Ben-Aderet et al 2020).…”

Protection promotes energetically efficient structures in marine communities

“…We also showed that results can be highly dependent on the number of annual sampling events. The seasonal variations in fish populations affects population dynamics, which causes temporal changes in composition (56). Therefore, we conducted a rarefaction analysis on the entire dataset to assess the effect of sampling effort on species richness at a given location and time (year).…”