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Changes in the Size of the Active Microbial Pool Explain Short-Term Soil Respiratory Responses to Temperature and Moisture.

Salazar-Villegas A, Blagodatskaya E, Dukes JS - Front Microbiol (2016)

Bottom Line: Most current approaches to model microbial control over soil CO2 production relate responses to total microbial biomass (TMB) and do not differentiate between microorganisms in active and dormant physiological states.TMB responded very little to short-term changes in temperature and soil moisture and did not explain differences in SBR among the treatments.These results suggest that decomposition models that explicitly represent microbial carbon pools should take into account the active microbial pool, and researchers should be cautious in comparing modeled microbial pool sizes with measurements of TMB.

View Article: PubMed Central - PubMed

Affiliation: Department of Biological Sciences, Purdue UniversityWest Lafayette, IN, USA; Purdue Climate Change Research Center, Purdue UniversityWest Lafayette, IN, USA.

ABSTRACT
Heterotrophic respiration contributes a substantial fraction of the carbon flux from soil to atmosphere, and responds strongly to environmental conditions. However, the mechanisms through which short-term changes in environmental conditions affect microbial respiration still remain unclear. Microorganisms cope with adverse environmental conditions by transitioning into and out of dormancy, a state in which they minimize rates of metabolism and respiration. These transitions are poorly characterized in soil and are generally omitted from decomposition models. Most current approaches to model microbial control over soil CO2 production relate responses to total microbial biomass (TMB) and do not differentiate between microorganisms in active and dormant physiological states. Indeed, few data for active microbial biomass (AMB) exist with which to compare model output. Here, we tested the hypothesis that differences in soil microbial respiration rates across various environmental conditions are more closely related to differences in AMB (e.g., due to activation of dormant microorganisms) than in TMB. We measured basal respiration (SBR) of soil incubated for a week at two temperatures (24 and 33°C) and two moisture levels (10 and 20% soil dry weight [SDW]), and then determined TMB, AMB, microbial specific growth rate, and the lag time before microbial growth (t lag ) using the Substrate-Induced Growth Response (SIGR) method. As expected, SBR was more strongly correlated with AMB than with TMB. This relationship indicated that each g active biomass C contributed ~0.04 g CO2-C h(-1) of SBR. TMB responded very little to short-term changes in temperature and soil moisture and did not explain differences in SBR among the treatments. Maximum specific growth rate did not respond to environmental conditions, suggesting that the dominant microbial populations remained similar. However, warmer temperatures and increased soil moisture both reduced t lag , indicating that favorable abiotic conditions activated soil microorganisms. We conclude that soil respiratory responses to short-term changes in environmental conditions are better explained by changes in AMB than in TMB. These results suggest that decomposition models that explicitly represent microbial carbon pools should take into account the active microbial pool, and researchers should be cautious in comparing modeled microbial pool sizes with measurements of TMB.

No MeSH data available.


Related in: MedlinePlus

Soil respiration rates after addition of a glucose and nutrient solution in wet (A) and dry (B) soils at different temperatures (heated soils, red solid circles/solid line; and unheated soils, open blue circles/dashed line). Symbols represent means ± SE. Lines were obtained by fitting the model parameters to measured soil respiration rates (see Materials and Methods Section). Fitted parameters are in Supplementary Table 2. Fitted lines are based on mean parameters values for each treatment. R2-values were calculated based on linearized model (Supplementary Figure 1) but exponential curves are shown to illustrate the exponential nature of the SIGR.
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Figure 2: Soil respiration rates after addition of a glucose and nutrient solution in wet (A) and dry (B) soils at different temperatures (heated soils, red solid circles/solid line; and unheated soils, open blue circles/dashed line). Symbols represent means ± SE. Lines were obtained by fitting the model parameters to measured soil respiration rates (see Materials and Methods Section). Fitted parameters are in Supplementary Table 2. Fitted lines are based on mean parameters values for each treatment. R2-values were calculated based on linearized model (Supplementary Figure 1) but exponential curves are shown to illustrate the exponential nature of the SIGR.

Mentions: Soil respiration curves showed clear responses to substrate addition, with particularly marked differences in response between heated and unheated treatments (Figure 2).


Changes in the Size of the Active Microbial Pool Explain Short-Term Soil Respiratory Responses to Temperature and Moisture.

Salazar-Villegas A, Blagodatskaya E, Dukes JS - Front Microbiol (2016)

Soil respiration rates after addition of a glucose and nutrient solution in wet (A) and dry (B) soils at different temperatures (heated soils, red solid circles/solid line; and unheated soils, open blue circles/dashed line). Symbols represent means ± SE. Lines were obtained by fitting the model parameters to measured soil respiration rates (see Materials and Methods Section). Fitted parameters are in Supplementary Table 2. Fitted lines are based on mean parameters values for each treatment. R2-values were calculated based on linearized model (Supplementary Figure 1) but exponential curves are shown to illustrate the exponential nature of the SIGR.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4836035&req=5

Figure 2: Soil respiration rates after addition of a glucose and nutrient solution in wet (A) and dry (B) soils at different temperatures (heated soils, red solid circles/solid line; and unheated soils, open blue circles/dashed line). Symbols represent means ± SE. Lines were obtained by fitting the model parameters to measured soil respiration rates (see Materials and Methods Section). Fitted parameters are in Supplementary Table 2. Fitted lines are based on mean parameters values for each treatment. R2-values were calculated based on linearized model (Supplementary Figure 1) but exponential curves are shown to illustrate the exponential nature of the SIGR.
Mentions: Soil respiration curves showed clear responses to substrate addition, with particularly marked differences in response between heated and unheated treatments (Figure 2).

Bottom Line: Most current approaches to model microbial control over soil CO2 production relate responses to total microbial biomass (TMB) and do not differentiate between microorganisms in active and dormant physiological states.TMB responded very little to short-term changes in temperature and soil moisture and did not explain differences in SBR among the treatments.These results suggest that decomposition models that explicitly represent microbial carbon pools should take into account the active microbial pool, and researchers should be cautious in comparing modeled microbial pool sizes with measurements of TMB.

View Article: PubMed Central - PubMed

Affiliation: Department of Biological Sciences, Purdue UniversityWest Lafayette, IN, USA; Purdue Climate Change Research Center, Purdue UniversityWest Lafayette, IN, USA.

ABSTRACT
Heterotrophic respiration contributes a substantial fraction of the carbon flux from soil to atmosphere, and responds strongly to environmental conditions. However, the mechanisms through which short-term changes in environmental conditions affect microbial respiration still remain unclear. Microorganisms cope with adverse environmental conditions by transitioning into and out of dormancy, a state in which they minimize rates of metabolism and respiration. These transitions are poorly characterized in soil and are generally omitted from decomposition models. Most current approaches to model microbial control over soil CO2 production relate responses to total microbial biomass (TMB) and do not differentiate between microorganisms in active and dormant physiological states. Indeed, few data for active microbial biomass (AMB) exist with which to compare model output. Here, we tested the hypothesis that differences in soil microbial respiration rates across various environmental conditions are more closely related to differences in AMB (e.g., due to activation of dormant microorganisms) than in TMB. We measured basal respiration (SBR) of soil incubated for a week at two temperatures (24 and 33°C) and two moisture levels (10 and 20% soil dry weight [SDW]), and then determined TMB, AMB, microbial specific growth rate, and the lag time before microbial growth (t lag ) using the Substrate-Induced Growth Response (SIGR) method. As expected, SBR was more strongly correlated with AMB than with TMB. This relationship indicated that each g active biomass C contributed ~0.04 g CO2-C h(-1) of SBR. TMB responded very little to short-term changes in temperature and soil moisture and did not explain differences in SBR among the treatments. Maximum specific growth rate did not respond to environmental conditions, suggesting that the dominant microbial populations remained similar. However, warmer temperatures and increased soil moisture both reduced t lag , indicating that favorable abiotic conditions activated soil microorganisms. We conclude that soil respiratory responses to short-term changes in environmental conditions are better explained by changes in AMB than in TMB. These results suggest that decomposition models that explicitly represent microbial carbon pools should take into account the active microbial pool, and researchers should be cautious in comparing modeled microbial pool sizes with measurements of TMB.

No MeSH data available.


Related in: MedlinePlus