Search for: All records

Abstract Ocean ecological time series grow more useful with longevity, but practical constraints hinder consistency, and evolving scientific priorities necessitate sampling adjustments. We leveraged 30 years of zooplankton observations (five species, 1993–2024) from the western Antarctic Peninsula to quantify how shifts in sampling intensity, timing, and survey frequency influenced accuracy, precision, and predictability. A 67% decline in sample size aliased a long-term trend in ice krill and increased uncertainty by 47% in log₁₀space across species. Moving survey dates by two weeks influenced the density of salps, pteropods, and Antarctic krill by 48–83%. The ability to predict krill species density declined 47% in a simulated shift from annual to biennial survey frequency. Reduced spatial resolution and slight changes in timing can be accounted for statistically, but temporal gaps represent a challenge. Autonomous approaches are complementary to (rather than substitutable for) net sampling, necessitating ship operations to maintain valuable zooplankton time series. 

Climate change is increasing the frequency of large-scale, extreme environmental events and flattening environmental gradients. Whether such changes will cause spatially synchronous, large-scale population declines depends on mechanisms that limit metapopulation synchrony, thereby promoting rescue effects and stability. Using long-term data and empirical dynamic models, we quantified spatial heterogeneity in density dependence, spatial heterogeneity in environmental responses, and environmental gradients to assess their role in inhibiting synchrony across 36 marine fish and invertebrate species. Overall, spatial heterogeneity in population dynamics was as important as environmental drivers in explaining population variation. This heterogeneity leads to weak synchrony in the California Current Ecosystem, where populations exhibit diverse responses to shared, large-scale environmental change. In contrast, in the Northeast U.S. Shelf Ecosystem, gradients in average environmental conditions among locations, filtered through nonlinear environmental response curves, limit synchrony. Simulations predict that environmental gradients and response diversity will continue to inhibit synchrony even if large-scale environmental extremes become common. However, if environmental gradients weaken, synchrony and periods of large-scale population decline may rise sharply among commercially important species on the Northeast Shelf. Our approach thus allows ecologists to 1) quantify how differences among local communities underpin landscape-scale resilience and 2) identify the kinds of future climatic changes most likely to amplify synchrony and erode species stability. 

The role of phenotypic plasticity in adaptive evolution has been debated for decades. This is because the strength of natural selection is dependent on the direction and magnitude of phenotypic responses to environmental signals. Therefore, the connection between plasticity and adaptation will depend on the patterns of plasticity harbored by ancestral populations before a change in the environment. Yet few studies have directly assessed ancestral variation in plasticity and tracked phenotypic changes over time. Here we resurrected historic propagules of Daphnia spanning multiple species and lakes in Wisconsin following the invasion and proliferation of a novel predator (spiny waterflea, Bythotrephes longimanus ). This approach revealed extensive genetic variation in predator-induced plasticity in ancestral populations of Daphnia . It is unlikely that the standing patterns of plasticity shielded Daphnia from selection to permit long-term coexistence with a novel predator. Instead, this variation in plasticity provided the raw materials for Bythotrephes -mediated selection to drive rapid shifts in Daphnia behavior and life history. Surprisingly, there was little evidence for the evolution of trait plasticity as genetic variation in plasticity was maintained in the face of a novel predator. Such results provide insight into the link between plasticity and adaptation and highlight the importance of quantifying genetic variation in plasticity when evaluating the drivers of evolutionary change in the wild. 

Anthropogenic environmental change is altering the behavior of animals in ecosystems around the world. Although behavior typically occurs on much faster timescales than demography, it can nevertheless influence demographic processes. Here, we use detailed data on behavior and empirical estimates of demography from a coral reef ecosystem to develop a coupled behavioral–demographic ecosystem model. Analysis of the model reveals that behavior and demography feed back on one another to determine how the ecosystem responds to anthropogenic forcing. In particular, an empirically observed feedback between the density and foraging behavior of herbivorous fish leads to alternative stable ecosystem states of coral population persistence or collapse (and complete algal dominance). This feedback makes the ecosystem more prone to coral collapse under fishing pressure but also more prone to recovery as fishing is reduced. Moreover, because of the behavioral feedback, the response of the ecosystem to changes in fishing pressure depends not only on the magnitude of changes in fishing but also on the pace at which changes are imposed. For example, quickly increasing fishing to a given level can collapse an ecosystem that would persist under more gradual change. Our results reveal conditions under which the pace and not just the magnitude of external forcing can dictate the response of ecosystems to environmental change. More generally, our multiscale behavioral–demographic framework demonstrates how high-resolution behavioral data can be incorporated into ecological models to better understand how ecosystems will respond to perturbations. 

Small pelagic fish support some of the largest fisheries globally, yet there is an ongoing debate about the magnitude of the impacts of environmental processes and fishing activities on target species. We use a nonparametric, nonlinear approach to quantify these effects on the Pacific sardine (Sardinops sagax) in the Gulf of California. We show that the effect of fishing pressure and environmental variability are comparable. Furthermore, when predicting total catches, the best models account for both drivers. By using empirical dynamic programming with average environmental conditions, we calculated optimal policies to ensure long-term sustainable fisheries. The first policy, the equilibrium maximum sustainable yield, suggests that the fishery could sustain an annual catch of ∼2.16 × 10 5 tonnes. The second policy with dynamic optimal effort, reveals that the effort from 2 to 4 years ago impacts the current maximum sustainable effort. Consecutive years of high effort require a reduction to let the stock recover. Our work highlights a new framework that embraces the complex processes that drive fisheries population dynamics yet produces simple and robust advice to ensure long-term sustainable fisheries. 

Abstract Complex nonlinear dynamics are ubiquitous in marine ecology. Empirical dynamic modelling can be used to infer ecosystem dynamics and species interactions while making minimal assumptions. Although there is growing enthusiasm for applying these methods, the background required to understand them is not typically part of contemporary marine ecology curricula, leading to numerous questions and potential misunderstanding. In this study, we provide a brief overview of empirical dynamic modelling, followed by answers to the ten most frequently asked questions about nonlinear dynamics and nonlinear forecasting.