Intermittent instability is widespread in plankton communities

Abstract

Chaotic dynamics appear to be prevalent in short-lived organisms including plankton and may limit long-term predictability. However, few studies have explored how dynamical stability varies through time, across space and at different taxonomic resolutions. Using plankton time series data from 17 lakes and 4 marine sites, we found seasonal patterns of local instability in many species, that short-term predictability was related to local instability, and that local instability occurred most often in the spring, associated with periods of high growth. Taxonomic aggregates were more stable and more predictable than finer groupings. Across sites, higher latitude locations had higher Lyapunov exponents and greater seasonality in local instability, but only at coarser taxonomic resolution. Overall, these results suggest that prediction accuracy, sensitivity to change and management efficacy may be greater at certain times of year and that prediction will be more feasible for taxonomic aggregates.

Chaotic turnover of rare and abundant species in a strongly interacting model community

“…Adding a degree of structure to our species-level model to represent multiple functional groups would offer a way to investigate the connection between fluctuations at different scales. Empirical findings to replicate are the weakening signal for chaos as taxa are aggregated at higher orders ( 8 ) and more dynamical regularity and predictability in succession patterns at the level of functional groups ( 78 ). In fact, even our unstructured model captures the feature that fluctuations are less severe at the aggregated level (e.g.…”

“…While chaos can be readily identified in simple mathematical models, its presence in empirical time series is challenging to ascertain, and the relevance of chaos for natural communities has been controversial ( 5 , 6 ). However, recent methodological advances and systematic assessment of a large ecological time series database using validated, nonparametric methods showed that ecological chaos is generally not rare ( 7 , 8 ) and is particularly prevalent in planktonic communities, where it was found in of time series.…”

When can higher‐order interactions produce stable coexistence?

“…As such, our approach can only describe the dynamics near the equilibrium produced by the higher-order interactions. The unstable equilibria we identified may sometimes lead to coexistence, rather than species exclusions, either through other equilibria (Section 11 of the Supplementary Information) or more complex dynamics (Hastings & Powell, 1991;Huisman & Weissing, 1999, 2001Lever et al, 2020;McCann & Yodzis, 1994;Rogers et al, 2022Rogers et al, , 2023. Conversely, even when the target abundance equilibrium is stable, it may not be globally stable (Section 11 of the Supplementary Information).…”

Patterns in the temporal complexity of global chlorophyll concentration

“…The roughness or complexity of a time series can strongly indicate multiple phenomena: high stochasticity in a target process, measurement error, long tails in the data, rapidly changing system states, or the confluence of all these factors and more. As phytoplankton populations display chaotic dynamics, non-linear behavior, and intermittent instability 14 – 16 , measurements of the complexity of [chl- a ] time series might also capture large-scale patterns that structure global phytoplankton communities. There are many ways of estimating the natural complexity of a time series, such as calculating the fractal or Hausdorff dimension 17 , permutation entropy 18 , or Lyapunov exponents 19 , 20 .…”