Warming effects on marine microbial food web processes: how far can we go when it comes to predictions?

Abstract

Previsions of a warmer ocean as a consequence of climatic change point to a 2-6 degrees C temperature rise during this century in surface oceanic waters. Heterotrophic bacteria occupy the central position of the marine microbial food web, and their metabolic activity and interactions with other compartments within the web are regulated by temperature. In particular, key ecosystem processes like bacterial production (BP), respiration (BR), growth efficiency and bacterial-grazer trophic interactions are likely to change in a warmer ocean. Different approaches can be used to predict these changes. Here we combine evidence of the effects of temperature on these processes and interactions coming from laboratory experiments, space-for-time substitutions, long-term data from microbial observatories and theoretical predictions. Some of the evidence we gathered shows opposite trends to warming depending on the spatio-temporal scale of observation, and the complexity of the system under study. In particular, we show that warming (i) increases BR, (ii) increases bacterial losses to their grazers, and thus bacterial-grazer biomass flux within the microbial food web, (iii) increases BP if enough resources are available (as labile organic matter derived from phytoplankton excretion or lysis), and (iv) increases bacterial losses to grazing at lower rates than BP, and hence decreasing the proportion of production removed by grazers. As a consequence, bacterial abundance would also increase and reinforce the already dominant role of microbes in the carbon cycle of a warmer ocean.

Figure 1.

A simplified view of the major components of the marine microbial food web and their interactions (carbon fluxes) indicated by arrows.

Figure 2.

(a) Arrhenius plot showing the effect of temperature (1/kT) on BP in natural systems (µgC ml⁻¹ h⁻¹, prior to Ln transformation). The black line represents the linear relationship between Ln (PB) and 1/kT (y = 17.413 – 0.667x, N = 190, r² = 0.21, F_1,189 = 50.1, p < 0.0001, the dashed line represents the 95% confidence interval of the slope); (b) Arrhenius plot showing the effect of temperature (1/kT) on total bacterial losses to grazing in natural systems (µgC ml⁻¹ h⁻¹, prior to Ln transformation).The black line represents the linear relationship between Ln (GB) and 1/kT (y = 9.770 – 0.456x, N = 128, r² = 0.28, F_1,127 = 50.0, p < 0.0001, the dashed line represents the 95% confidence interval of the slope).

Figure 3.

Arrhenius plot showing the effect of the temperature (1/kT) on (a) BP and on (b) GB measured in perturbation experiments (µgC ml⁻¹ h⁻¹, prior to Ln transformation).

Figure 4.

(a) Changes observed in the Microbial Observatory of Blanes Bay in the last decade in chlorophyll a and (b) in bacterial abundance determined with two different methodologies (DAPI counts on epifluorescence microscopy and flow cytometry). The relationships are: log_{Chl a} = 78.14–0.039 time (years), F_1,115 = 7.77, p < 0.01 and log_Bact = 57.6–0.025 time (years), F_1,62 = 5.5, p = 0.02 for DAPI counts and log_Bact = 53.3–0.023 time (years), F_1,95 = 8.6, p < 0.01 for flow cytometry counts. Solid lines with filled circles, DAPI; dashed lines with open circles, flow cytometry.