Anthropogenic climate change drives non-stationary phytoplankton variance

Abstract

Abstract. Multiple studies conducted with Earth System Models suggest that anthropogenic climate change will influence marine phytoplankton over the coming century. Light limited regions are projected to become more productive and nutrient limited regions less productive. Anthropogenic climate change can influence not only the mean state, but also the variance around the mean state, yet little is known about how variance in marine phytoplankton will change with time. Here, we quantify the influence of anthropogenic climate change on internal variability in marine phytoplankton biomass from 1920 to 2100 using the Community Earth System Model 1 Large Ensemble (CESM1-LE). We find a significant decrease in the internal variance of global phytoplankton carbon biomass under a high emission (RCP8.5) scenario, with heterogeneous regional trends. Decreasing variance in biomass is most apparent in the subpolar North Atlantic and North Pacific. In these high-latitude regions, zooplankton grazing acts as a top-down control in reducing internal variance in phytoplankton biomass, with bottom-up controls (e.g., light, nutrients) having only a small effect on biomass variance. Grazing-driven declines in phytoplankton variance are also apparent in the biogeochemically critical regions of the Southern Ocean and the Equatorial Pacific. Our results suggest that climate mitigation and adaptation efforts that account for marine phytoplankton changes (e.g., fisheries) should also consider changes in phytoplankton and zooplankton variance driven by anthropogenic warming, particularly on regional scales.

Global Warming Increases Interannual and Multidecadal Variability of Subarctic Atlantic Nutrients and Biological Production in the CESM1‐LE

“…One might expect that these strong downward trends in the biomass, production, nutrients and their physical drivers might be accompanied by reductions in the corresponding interannual and multidecadal variability (Elsworth et al., 2022). And, indeed, the interannual stdev of the chlorophyll declines by about 30% during the RCP8.5 scenario (Figure 1b) in conjunction with declines in the interannual stdevs of the March MLD and the AMOC (Figures 1k and 1n).…”

“…Circumventing these difficulties, this study uses output from a large ensemble of simulations with the Community Earth System Model (CESM1-LE) (Kay et al, 2015) to quantify how the characteristics of the internal variability of ocean biological production change during the high-emissions RCP8.5 scenario. As demonstrated by several recent studies of ocean biogeochemistry (Elsworth et al, 2022;Li & Ilyina, 2018;Long et al, 2016;Lovenduski et al, 2016;McKinley et al, 2016;Schlunegger et al, 2019), a single-model large ensemble is a valuable complement to an ensemble of simulations with different models (as in the Coupled Model Intercomparison Project archive), because the differences between the simulations are attributable to internal Earth system variations without convoluting differences due to model formulation (Deser et al, 2020).…”

Long‐Term Trends in the Distribution of Ocean Chlorophyll

“…Regional changes in upper quantiles described above also correspond to changes in CHL variability with increase in the North Pacific Subarctic Province, North Atlantic Drift Province, and Subantarctic Provinces, and declining variability in Pacific Equatorial and North Pacific Subtropical Gyre Province. Those regions are characterized by noticeable ecological and biogeochemical seasonal variability that is closely related to strong annual cycles in light, nutrients, temperature, wind force, and zooplankton grazing at surface (Elsworth et al., 2022; Henson et al., 2010). At the regional scale, large‐scale climate patterns such as El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and North Atlantic Oscillation (NAO) are known drivers of CHL trends and variability (Corno et al., 2007; Gao et al., 2020; Kang et al., 2017; Le Grix et al., 2021; L. Zhai et al., 2013).…”

Impacts of ENSO on Tropical Pacific Chlorophyll Biomass Under Historical and RCP8.5 Scenarios

“…The model has been well validated and compared against various observations (Long et al., 2013; Moore et al., 2004, 2013). In general, CESM can capture the global distributions of ocean physical and biogeochemical fields with some overestimates in the mean‐state of chlorophyll concentration, especially in the eastern equatorial Pacific (Elsworth et al., 2023, also see Figure S3 in Supporting Information ). However, the amplitude of simulated anomalies in chlorophyll concentrations is reasonable compared to observations, making the model suitable for investigating the variability in chlorophyll.…”