Disentangling niche competition from grazing mortality in phytoplankton dilution experiments

Abstract

The dilution method is the principal tool used to infer in situ microzooplankton grazing rates. However, grazing is the only mortality process considered in the theoretical model underlying the interpretation of dilution method experiments. Here we evaluate the robustness of mortality estimates inferred from dilution experiments when there is concurrent niche competition amongst phytoplankton. Using a combination of mathematical analysis and numerical simulations, we find that grazing rates may be overestimated-the degree of overestimation is related to the importance of niche competition relative to microzooplankton grazing. In response, we propose a conceptual method to disentangle the effects of niche competition and grazing by diluting out microzooplankton, but not phytoplankton. Our theoretical results suggest this revised "Z-dilution" method can robustly infer grazing mortality, regardless of the dominant phytoplankton mortality driver in our system. Further, we show it is possible to independently estimate both grazing mortality and niche competition if the classical and Z-dilution methods can be used in tandem. We discuss the significance of these results for quantifying phytoplankton mortality rates; and the feasibility of implementing the Z-dilution method in practice, whether in model systems or in complex communities with overlap in the size distributions of phytoplankton and microzooplankton.

Fig 1. Schematic of the classical dilution method of Landry and Hassett.

1. Sample Environmental samples are prefiltered to focus on microbial communities—this is termed whole seawater (WSW). Dilution method theory assumes WSW contains microzooplankton and the phytoplankton they graze upon. 2. Filtration The classic dilution method filters some WSW to create a diluent containing no phytoplankton or microzooplankton. 3. Dilution series A series of bottles are filled with a proportion F of WSW and mixed with a proportion (1 − F) of the diluent creating a dilution series. The blue and red bars represent the relative abundance of phytoplankton and microzooplankton. Apparent growth rates are calculated by measuring the differences in phytoplankton population sizes in each bottle across the dilution series at two time points (the beginning and end of an incubation period). The microzooplankton grazing rate is estimated by finding the gradient of a linear regression model between the dilution level F and the apparent growth rate.

Fig 2. The classical dilution method may overestimate rates of mortality via grazing.

(A) Expected baseline microzooplankton associated mortality rates and rates estimated using the classical dilution method for three levels of grazing pressure; low grazing pressure (1000 microzooplankton ml⁻¹), intermediate grazing pressure (10000 microzooplankton ml⁻¹) and high grazing pressure (20000 microzooplankton ml⁻¹). The maximum mortality rate is calculated for the condition when total mortality, m, is equal to the phytoplankton growth rate r. (B) Mortality rate bias across the full gradient of grazing pressure. The grazing pressure associated with each of the examples given in (A) are shown on the x-axis.

Fig 3. Proposed revision to the classical dilution method.

Whilst the classical dilution method (see Fig 1) uses a filter excluding phytoplankton and microzooplankton, the proposed method instead uses an alternative filter, able to exclude microzooplankton, but through which phytoplankton can pass. Thus constituent levels of microzooplankton and phytoplankton within each bottle, shown by red and blue bars respectively, differ to those in the classical dilution experiment.

Fig 4. Dilution curves show the classical dilution method is insensitive to niche competition.

Apparent growth rates are plotted against the proportion of whole seawater for each bottle in the in silico dilution series after a 24h incubation period when using the classical dilution method and the Z-dilution method respectively. Three cases, each with different microzooplankton grazing pressure conditions (LP: Low pressure, IP: Intermediate pressure and HP: high pressure, as defined in Fig 2) are shown. The estimated mortality rate (m_est) found as the linear regression slope, the baseline mortality rate (m_act) and the percentage error in estimation are shown for each subplot (all rounded to 3 s.f.).

Fig 5. A comparison of classical and Z-dilution method estimates.

(A) Mortality rates and their estimates at three levels of grazing pressure after 24h incubation period. The maximum mortality rate is calculated for the condition when the mortality, m, is equal to the phytoplankton growth rate r. Baseline mortality rates are shown for each condition. (B) Mortality rate bias is plotted against the level of grazing pressure (δ_Z)—the three conditions shown in (A) are marked on the x-axis. Bands indicating ±10% and ±25% differences from the true mortality rate in the sample are shown.