High resolution time series reveals cohesive but short-lived communities in coastal plankton

Abstract

Because microbial plankton in the ocean comprise diverse bacteria, algae, and protists that are subject to environmental forcing on multiple spatial and temporal scales, a fundamental open question is to what extent these organisms form ecologically cohesive communities. Here we show that although all taxa undergo large, near daily fluctuations in abundance, microbial plankton are organized into clearly defined communities whose turnover is rapid and sharp. We analyze a time series of 93 consecutive days of coastal plankton using a technique that allows inference of communities as modular units of interacting taxa by determining positive and negative correlations at different temporal frequencies. This approach shows both coordinated population expansions that demarcate community boundaries and high frequency of positive and negative associations among populations within communities. Our analysis thus highlights that the environmental variability of the coastal ocean is mirrored in sharp transitions of defined but ephemeral communities of organisms.

Microbial communities across nearshore to offshore coastal transects are primarily shaped by distance and temperature

“…Stations B and C), diversity was statistically equivalent beyond the nearshore station. Interestingly, the farthest offshore Station E exhibits higher Shannon diversity than Stations B–D (although the difference is not statistically significant), which could be due to the influence of distinct water masses, for example, Gulf Stream meanders or eddies (Martin‐Platero et al ., ). The divergence of environmental parameters and diversity at the estuary mouth (Station A) raises the question how the microbial community composition transitions across the continental shelf from diverse nearshore waters to the oligotrophic open ocean.…”

“…3). Yet, all stations have statistically equivalent microbial community dispersions (betadisper, p > 0.05), suggesting that offshore microbes could be sensitive to small environmental changes (Shade et al, 2012) or represent distinct water masses (Martin-Platero et al, 2018). In addition, we used this data set to examine the relationship between microbial community composition and environmental variables, including distance from shore, water temperature, chlorophyll a, salinity and insolation.…”

“…Although the Bayesian modelling allows partitioning of the taxon-level response between multiple environmental variables, the environmental factors considered here (temperature and distance from shore) likely represent proxies for a number of environmental factors, which will require further observational and manipulative experiments to differentiate. Specifically, the question of how movement of distinct water masses across these transects such as the Gulf Stream and associated eddies influences the relative composition of offshore and shelf microbial communities remains to be determined (Martin-Platero et al, 2018). This coastal environment is subject to perturbations due to annual cycles as well as major disturbances such as hurricanes and other large storms Ward et al, 2017), which alter environmental factors and enhance export of nutrients and organic material from the coastal to open oceans.…”

“…Previous studies have identified key environmental variables associated with marine microbial community composition including temperature, salinity, light, depth, wind speed, distinct water masses and up or down-welling (Morris et al, 2005;Fuhrman et al, 2006;Fortunato et al, 2012;Gilbert et al, 2012;Giovannoni and Vergin, 2012;Bryant et al, 2016;Ward et al, 2017;Martin-Platero et al, 2018). However, recent studies employing high-resolution (daily), Eulerian (fixedpoint) sampling schemes have revealed unexpectedly dynamic microbial communities linked to high turnover in phytoplankton blooms or the passage of oceanographic features (Needham and Fuhrman, 2016;Martin-Platero et al, 2018), raising questions about the validity of linking microbial phylotypes with specific environmental parameters. Additionally, few studies have repeatedly sampled onshore-to-offshore transitions, which encompass gradients in environmental factors including primary production, nutrients, exchange with the benthos, among others, although the relative importance of these individual factors remains difficult to tease apart.…”

The intrinsic predictability of ecological time series and its potential to guide forecasting

“…Growth rate, r Time series measured at the appropriate time scales over long periods of time are rare, despite the knowledge that they are among the most effective approaches at resolving long-standing questions regarding environmental drivers (Lindenmayer et al 2012, Giron-Nava et al 2017, Hughes et al 2017). This problem is beginning to be resolved with automated measurements of system states, such as chlorophyll a concentrations in aquatic systems (Blauw et al 2018, Thomas et al 2018, assessment of community dynamics in microbiology (Trosvik et al 2008, Faust et al 2015, Martin-Platero et al 2018, and phenological (Pau et al 2011) and flux measurements (Dietze 2017). Such high-frequency, longterm data are likely to provide a more accurate picture of the range of possible system states, even when systems are non-ergodic and change through time (e.g., Fig.…”