Progress 08/01/16 to 08/31/21
Outputs
Target Audience:The target audiences are scientists in the field. of soil sciences and biogeochemical modeling. We also have presented the work at the University of Florida research and Education Center Field day, where audiences include Cattle Operation clientele. Changes/Problems:We made several changes to the project: 1) we had difficulty maintaining the plants in the greenhouse and therefore a full factorial experiment was not possible 2) Our research was interrupted by COVID, with restrictions for the lab, greenhouse and travel to the field sites. 3) Modeling lead to significant change in research direction in that we focused on anaerobic microsites, which we haven't considered in the plan. However, this lead to positive insights. What opportunities for training and professional development has the project provided?The work supported undergraduate, graduate students and a post-doc. The undergraduate students gained lab experiience and training in labarotary and field safety procedures. Graduate students were involved and trained in project planning, experimental design, data generation, modeling, data analysis and interpretation, including gas efflux measurements in field and laboratory, field sampling, soil sample analysis (bulk density, gas production, biogeochemical parameters). One graduate student was trained in high throughput sequencing and analysis. A post-doc also lead the charge in data analysis and interpretation of the results. Modeling concepts were used in graduate classses to demonstrate how models can be used for hypothesis generation. Results were used in classrooms of for both undergraduate and graduate classes. How have the results been disseminated to communities of interest?Results were presented at various conferences and at a field. We are currently revising a paper that has unfortuantely been rejected. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
IMPACT STATEMENT Our work informs how management decisions impact carbon sequestration in Florida's rangeland. We show that deep and potentially long-lived soil carbon in the Bh horizon has been affected by pasture management. Microbial community analysis reveals shifts from bacterial to fungal communities with improved management, with increased potential for soil carbon storage and organic matter accumulation. Our experiments with rangeland soils show that enzyme activities, an indicator of microbial soil organic matter processing, are much more sensitive to short term shifts in water availability under warmer temperature. This is important w.r.t. carbon storage and nutrient availability under precipitation shifts and expected warming. Our modeling effort using microbial explicit approaches show pathways to better represent microscale variation in oxygen availability in landscape and Earth system model, allowing for better prediction of carbon cycling and oxygen sensitive greenhouse gas production such as methane (CH4) and nitrous oxide (N2O). In addition, modeling suggests temperature sensitivities of soil microbial carbon processing may depend on the concentration of carbon in soils, with implications for different soil layers and structures. RESULTS UNDER EACH SPECIFIC SOBJECTIVES (SO) SO1 This objective targets our limited understanding of management effects on soil C processes where most research has centered on impacts to surface soils. Using a sub-tropical grassland ecosystem subjected to more than 25 years of management, we contrasted the effect of improved (vegetation shift + annual N fertilization + grazing at 350 animal days ha-1 yr-1) pasture management to that in a native rangeland (no N fertilization + grazing at 125 animal days ha-1 yr-1) on both surface and deep (>0.5 m) soil C and N stocks, and soil microbial processes, including microbial abundance and functional groups. Improved pasture resulted in almost 2x higher surface (19.6 vs. 10.3 Mg ha-1) and deep (25.3 vs. 13.3 Mg ha-1) soil C stock than the native. Similarly, N stock (0-10 cm) increased 2.9x in improved pasture (1.4 Mg ha-1) vs. native rangeland (0.5 Mg ha-1). Analysis of labile C and N fractions for both the surface and spodic (Bh) horizons suggest that long-term management effects on soil organic carbon (SOC) cycling extend to deep soils. Interestingly, soil microbial respiration and biomass-specific soil enzyme activities was lower in the deep soil horizons of the improved pasture despite higher labile C fractions. Increased N availability and decrease in fungal/bacterial ratio observed for the deep soils of improved pasture potentially suppressed microbial turnover of SOC. A surprising trend in diversity is supported by sequencing of the bacterial community, based on the 16S rRNA gene. Improved pastures soils supported a significantly higher bacterial diversity, evenness, and richness, with the highest values within the A1 versus Bh horizon. This is unexpected as improved pastures are essentially monoculture. Taxonomic summary at the phylum level showed that ~60% and ~48% of the community were unclassified fungi in the improved pasture and native land, respectively. Quantitative PCR for the 16S rRNA gene and nosZ gene shows that improved pastures harbored a significantly larger population of denitrifiers. Overall, these modifications in substrate quality, shifts in microbial functional groups, and N availability due to long-term improved management may further stabilize deep soil C in sub-tropical grasslands. SO2 We used bulk surface soils from the Ona rangeland site (native vs improved pasture) in a controlled temperature environment at two temperatures (ambient vs. +5ºC) and moisture regimes (drying/wetting cycles vs. constant moisture) for > six months. Soil samples were periodically analyzed for changes in biogeochemical parameters. Microbial processes significantly respond to both soil moisture and soil temperature changes; but varies with pasture management. Moisture impacts were evident on soil microbial function (enzyme activities) that tended to follow the moisture phase (peak > intermediate > dry) and was more pronounced for warmed soils from improved management sites. Increased moisture also positively impacted the microbial biomass N content, but the microbial biomass C was more sensitive to temperature in the native soils. Variable moisture regimes also appear to negatively impact soil respiration and microbial C use efficiency. Vegetation presence also positively influenced specific soil C- and N acquiring extracellular enzyme activities in improved management soils versus the native soils. There was increased soil enzyme activity with moisture availability, particularly for the elevated temperature suggesting that moisture availability is critical for soil microbial processes at higher temperatures. Diminished respiration rates in the variable moisture treatment likely means reduced soil microbial activity; however, drying/wetting cycles accentuated the activity of NAG enzyme indicating more fungal presence. Further study is warranted to investigate if improved management increases the vulnerability of the soils to the temperature and moisture and if the impact is short or long term. SO3 The work on a microbial model was done in two prongs. First, we use a microbial explicit model to investigate how carbon density affects microbial processing. This was motivated by the variability of carbon concentrations along our soil profiles. We found that two feedbacks link carbon density and soil organic matter processing: With increasing density soil carbon and thus availability to microbes increase, but potential self-predation and mortality may curb microbial growth in such environments and reduce decomposition. Second, we have developed an analytical model to represent anaerobic microsites, based on first principles from soil aggregate distribution, oxygen diffusion and combined this with water-filled pore space. This allows for efficient, yet mechanistic scaling of small-scale heterogeneity in oxygen availability to a whole soil column, or Earth system model grid. Our work relies on previous disparate consideration of fractal distribution of soil particle sizes, its relationship with soil moisture, and the diffusion of gases in soils. SO4 The models from specific SO3 were applied to biogeochemical scenarios. We found that the temperature response of soil C loss depends on the density of C and therefore on accurate representation of soil horizons. We found a V shaped curve with depth of typical soils, that shows low temperature sensitivity in purely organic soil found in the litter layer, high sensitivity with relatively high organic carbon content which may be in the transition from the litter layer to the soil, and then decreasing sensitivity as the fraction of minerals increase. In our Florida soils however, this is modified, as we have no purely organic litter layer, but a Bh horizon rich in organics depth. More critical, this carbon-density-temperature feedback is stronger, when microbial explicit models are considered, compared to traditional CENTURY type soil models. Application of the new model of anaerobic microsites leads to readily testable hypotheses: The sizes of anaerobic microsites depend on a system's productivity. The response to soil moisture w.r.t. anaerobic greenhouse gas production (N2O, CH4) is temperature dependent, with increasing temperature leading to larger anaerobic fractions under identical moisture regimes. For our sites, this would mean higher anaerobic fractions in improved pastures, and under global change scenarios, implying higher amount of N2O and potentially CH4 production in the wet summer months, exacerbated by more pronounced periods of wetness.
Publications
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2021
Citation:
Subedi, P., Inglett, P.W, Sandhu, S., Rai, D., Silveira, M., Gerber, S., Inglett, K. S, 2021, Distinct surface and deep soil C, N, and microbial responses to long-term pasture management in two sub-tropical grasslands,ASA, CSSA, SSSA International Annual Meeting, Salt Lake City, UT Nov 7-10, 2021, Virtual Poster Presentation
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2021
Citation:
Gerber S., and Brookshire E.N.J., 2021, Predicting Anaerobic Microsites in Soils, Soil Modeling Consortium Annual (Virtual) Meeting, Virtual Poster Presentation
|
Progress 08/01/19 to 07/31/20
Outputs
Target Audience:The major audience are scientist in the field of carbon cycling, greenhouse gas emissions, soil management and grazingland research. Changes/Problems:Vegetated pots did not survive the greenhouse variable cycle. Therefore, vegetated pots were subjected to constant moisture variable temperature treatments. Experiment was put on hold because of COVID-19 in Spring/Summer. We are evaluating whether this prolonged hold affected the mesocosms in the greenhouse. What opportunities for training and professional development has the project provided?The work supports 1 post doc. These students started in year 1 of the project with course work. They were further trained in field and laboratory safety and procedures, as well as having first encounters and insights How have the results been disseminated to communities of interest?The modeling approach has been presented at the Ecological Society Virtual Meeting in 2020. What do you plan to do during the next reporting period to accomplish the goals?We are awaiting decision for a no-cost extension that would as allow to carry out final experiments that have been delayed by COVID-19, and complete the modeling aspects and to publish the material. We will focus on 1) Greenhouse experiment: We are wrapping up our experiments in the greenhouse, where we subjected the soils to various levels of soil moisture and temperature. We also tested temperature effects on the potted plants with constant moisture levels. We started the experiments in January, with the intention to run it for 10-11 month. The treatments are control, warming, planted, bare soil, management practices, and episodic high water. The treatments are almost full factorial, except the water/temperature interaction. The data are being analyzed. 2) Finalizing the first manuscript for publication. The field study results are being presented in that manuscript. 3) Analyze molecular data in conjunction with greenhouse gas fluxes: We have regularly sampled soils in the field for analysis for molecular (genetic) data. We will continue collection of soil data. Further, we also analyze the greenhouse experiment for molecular data. 4) Finalize modeling, by incorporating the microbial model into a landscape version. Parameterize the model with specific data (microbial biomass, respiration), temperature and soil moisture factors..
Impacts
What was accomplished under these goals?
IMPACT STATEMENT Our work informs how management decisions impact carbon sequestration in Florida's rangeland. We show that deep and potentially long-lived soil carbon in the Bh horizon has been affected by pasture management. Microbial community analysis reveals shifts from bacterial to fungal communities with improved management, with increased potential for soil carbon storage and organic matter accumulation. Our experiments with rangeland soils show that enzyme activities, a direct signal of microbial soil organic matter processing, are much more sensitive to short term shifts in water availability under warmer temperature. This is important w.r.t. carbon storage and nutrient availability under precipitation shifts and expected warming. Our modeling effort using microbial explicit approaches show pathways to better represent microscale variation in oxygen availability in landscape and Earth system model, allowing for better prediction of carbon cycling and oxygen sensitive greenhouse gas production such as methane and N2O. RESULTS UNDER EACH OBJECTIVE SO1 Results from various analyses (decomposition rates, microbial structure and functional analyses, carbon extractions, and molecular genetic analysis) on samples collected in March 2017, September 2017, January 2018, and July 2018 were analyzed and written up for submission to a peer- reviewed journal. The manuscript is now being finalized and the plan is to submit in the next few weeks. The microbial community structure was analyzed within the field samples using the analyses of biomarkers of phospholipid fatty acids for bacterial and fungal communities. Briefly, soil samples were collected from three horizons, A, E and Bh. Further, the A horizon was divided into A1 (0-10 cm) and A2 (remaining depth of the A). The microbial community structure was analyzed using the analyses of biomarkers of phospholipid fatty acids for bacterial and fungal communities. Results from our study shows that pasture management had significant differences in the soil C fraction. Soils from improved management resulted in significantly higher hot water extractable fraction compared to that in native. Furthermore, our results also show that management induced differences in the recalcitrance of soil C extends to sub-surface soils, with higher recalcitrant C in the native Bh horizons than improved. While the amount of litter and root inputs partly drive these responses, difference in the quality of C inputs presumably dictated the variation in soil C fraction for these grasslands. Isotopic analysis on the soils of our study site provides further supported that management drove soil C accumulation. Overall, improved pastures store a significantly higher amount of carbon compared to native rangelands. While a considerable amount of C is stored in the Bh horizon, surface horizon also stores a significant amount of C that is labile. Increased enzyme activities in the surface horizon suggest that improved pastures are more active biogeochemically than native rangelands. Labile C inputs from vegetation, nutrient inputs via fertilization and manure inputs from grazing animals in the improved pastures likely regulated soil enzyme activity in these systems. Shifts in soil microbial communities from fungi-dominated to bacteria dominated with improved pasture management provides additional evidence to support that management induced changes in substrate quality (more labile C and N fractions) has to potential to accelerate C and nutrient cycling in these systems. From a management perspective, gained C stocks for these improved pastures are more likely to be recycled because of management induced shifts in C quality and soil microbial functional groups. SO2 Bulk soil surface samples taken from the Ona field management experiment (native vs improved pasture) were subjected to two temperature (ambient vs. +5ºC elevated) and moisture regimes (drying and wetting cycles vs. constant moisture) in a temperature-controlled greenhouse setup with replicated treatments. Subsets of soils from each treatment (and replicate) were collected in June 2020 and subsequently analyzed for MBC, MBN, and soil microbial extracellular enzymes. For soils with drying and wetting cycle moisture treatment, samples were collected three times- one each for the peak moisture, intermediate moisture, and dry moisture. Concurrently, we measured soil CO2 efflux from these mesocosms. Soil microbial processes significantly respond to both soil moisture and soil temperature changes. Soil moisture phase in the drying and wetting cycle (peak, intermediate, and dry) affected soil extracellular enzyme activities, MBC, and MBN. Microbial enzyme activities followed a trend: Peak phase > Intermediate phase > Dry phase. This suggests that for sandy soils such as ours, moisture availability is critical for soil microbial processes as soil temperature is elevated. Interestingly, this trend was much more pronounced for soils with improved management history subjected to +5C elevated temperature treatment. Diminished soil respiration rates for elevated temperature treatments, provides additional evidence to support reduced soil microbial activity potentially due to moisture limitation associated with higher soil temperature. This was supported by negative effects of temperature on enzyme activity. Additionally, increased soil enzyme activities, and soil respiration for soils with intact vegetation highlights the potential role of understory vegetation in supplying resources for soil microbes. SO3 The work on a microbial model is occurring in two prongs. First, we show that current microbial models need to account for variability of potential organic matter vs. mineral concentrations along a soil profile. This consideration allows for better representation of key parameters, such as maximum depolymerization rates, and potentially also the mortality rates of microbes. In fact, we can link the potential to store carbon directly to a total volume of the soil matrix available. This becomes very important, as we address different horizons. For example, the A horizons experience a large organic input in a rather small volume. This creates two important feedback: The density of soil carbon and thus availability to microbes increase, but potential self-predation and mortality may curb microbial growth in such environments and reduce decomposition. In contrast low input and low density in the E horizon may cause little microbial self-thinning, but also limits further the availability of carbon. More critical, we found that the temperature sensitivity depends on the density of carbon with a V shaped curve that shows low temperature sensitivity in purely organic soil, high sensitivity with high organic carbon content, and decreasing sensitivity as the fraction of minerals increase. This feedback is stronger, when microbial explicit models are considered, compared to traditional CENTURY type soil models. Second, we have developed an analytical model to represent anaerobic microsites, based on first principles from soil aggregate distribution, oxygen diffusion and combined this with water-filled pore space. This allows for efficient, yet mechanistic scaling of small-scale heterogeneity in oxygen availability to a whole soil column, or Earth system model grid. Our work relies on previous disparate consideration of fractal distribution of soil particle sizes, its relationship with soil moisture, and the diffusion of gases in soils. SO4: We are waiting for the mesocosm experiments to provide us parameterization of the DNDC model. We have data for climate and climate projection, a refined set of candidates of specific microbial models from SO3 that we are in the process of incorporating into the DNDC model. Specifically, our model allows us to replace the anaerobic balloon concept with a physically more robust representation.
Publications
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2020
Citation:
Gerber and Sihi, 2020, When organic matter is the soil matrix: Challenges of using microbial explicit decomposition models in predominantly organic soils, Ecological Society of America virtual meeting.
|
Progress 08/01/18 to 07/31/19
Outputs
Target Audience:The major audience are scientist in the field of carbon cycling, greenhouse gas emissions, soil management and grazingland research. Changes/Problems:A minor problem was the set up of the greenhouse experiments. We had difficulties to control the environment in the mesocosms. Additional problems arose when growing plants in pots in greenhouses. We had minor issues with test and with soil moisture control in the mesocoms. These hiccups lead to the application for a no-cost extension, which has been granted and which we are grateful for. What opportunities for training and professional development has the project provided?Three graduate students haveworked exclusively on aspects of the specific project, and we are training a post-doc for data analysis and modeling. How have the results been disseminated to communities of interest?This far, we have shown preliminary results of our work at various conferences. Further we have presented our work at the field day of the Ona Range and Cattle Station, which was an event created for stakeholders of the University of Florida's research and education center. What do you plan to do during the next reporting period to accomplish the goals?We will complete the mesocosm experiments in SO2. The greenhouse gas fluxes the enzyme and the molecular analysis will provide us a framework to parameterize the microbial model and then for upscaling of the landscape model (DNDC).
Impacts
What was accomplished under these goals?
Grazing lands are among the largest ecosystems in the world and contain about one-third of global soil carbon reserves. While there is concern that release of stored carbon from agricultural soils further accelerates climate warming, there is also potential to manage soils effectively to remove anthropogenic greenhouse gases. Our work takes advantage of adjacent grazingland fields in Ona, FL, which are differently managed. Fields of intense management (improved pasture) are contrasted with a treatment that is considered native rangelands. At the core of greenhouse gas emissions are microbes residing in the soils. These lifeforms digest organic matter stemming from plant production, and their waste products are ultimately mineral forms of nutrients that are dissolved or escape as gases (including greenhouse gases). Intermediate microbial waste products in contrast help to build up carbon and nutrient reserves. In order to understand the transformation that lead to carbon storage and healthy functional soils, it becomes important to know 1) who is in the soil, and 2) what are they doing. Work is now underwaythat would enable us to predict greenhouse gas emissions and microbial functioning under a changing environment, including a mesocosm experiment and the adaptation of a prediction model. Results so far suggest that more intense management (as we have in the improved pasture), lead to a faster processing of carbon and nutrients, and therefore also increased greenhouse gas production. This is corroborated by preliminary analysis that shows that improved pastures harbored a significantly larger population of denitrifiers, indicating a potential for higher rates of denitrification. Improved pastures also supported a significantly larger bacterial community, However, the faster processing leads also to more carbon intake and longer-term carbon storage. Hence management in subtropical grazinglands can help with the global management of greenhouse gases. We currently evaluate the exact significance for the future. Detailed acomplishments under the objectives SO1: Improved pasture significantly increased microbial biomass carbon (C) and nitrogen (N) in the Bh horizon than native pasture. This trend was also weakly observed for the E horizon. Soil C stock and C fraction concentrations are higher in improved pastures compared to native pastures. The main effect of seasonality was significant in the cold water extractable C (CWEC) and acid extractable C (AEC) fractions. The CWEC fraction generally declined from summer to winter. On the contrary, the AEC fraction increased from summer to winter. Improved pastures had higher total C and N concentration in the soil profile compared to native pastures. Though not significant, the C/N ratio tended to be lower in the improved pastures than in the native pasture across all horizons. While C:N ratio increased from summer to winter season in the improved pasture, it decreased from summer to winter in the native pasture suggesting contrasting seasonal dynamics in C:N ratios. In the surface horizon, the extracellular enzymbes beta-glucosidaseand cellohydrolase (CBH) activities generally tended to be higher (CBH weakly significant) with improved pasture management compared to the native. However, there is greater degree of variability in soil enzyme activity within a soil horizon. Sequencing of the bacterial community, based on the 16S rRNA gene, indicated significant treatment and depth effects. Improved pastures soils supported a significantly higher bacterial diversity, evenness, and richness, with the highest values within the A1 versus Bh horizon. Interestingly, the phyla that most impacted the differences according to management were the Crenarchaeota. This may be due to their role in ammonia oxidation which will be further validated by qPCR of the amoA gene. In order to examine the fungal community, DNA extracted from soils was amplified based on the Internal Transcribed Spacer (ITS) region of the 18S rRNA gene. Preliminary results showed that improved pasture had significantly higher alpha diversity indices, i.e. Margalef's richness, Pielou's evenness and Shannon diversity, compared to native land. Taxonomic summary at the phylum level showed that ~60% and ~48% of the community were unclassified fungi in the improved pasture and native land, respectively. PERMANOVA found significant differences (p<0.05) between soil horizons, sampling date, and management practice. Quantitative PCR has been completed for the 16S rRNA gene and nosZ gene. Preliminary analysis shows that improved pastures harbored a significantly larger population of denitrifiers, indicating a potential for higher rates of denitrification. Improved pastures also supported a significantly larger bacterial community, with the differences being most pronounced in the A1 horizon, versus the Bh horizon. We are currently quantifying the last of the functional genes which includes nifH, nirS, nirK, amoA, and the fungal ITS gene for quantification of the total fungal community. SO2 An experimental study to establish the interactive effect of moisture and temperature on microbial C use, organic matter turnover, and greenhouse production is currently underway. Soil mesocosms (0.07 m2) were established in a temperature-controlled glasshouse with factorial treatments for vegetation (vegetated or bare soil), site (Native rangeland or Improved pasture), temperature (20C or 25C), and moisture pattern (constant 10% or variable 5-20%). Temperature treatments are conducted using thermostat-controlled heating mats, while moisture levels are manually controlled based on readings from soil moisture probes installed in each mesocosm. The experiment has been initiated and monitored for 2 months to stabilize soil microbes at the treatment temperatures and avoid short term acclimation responses. Following collection of baseline data (GHG fluxes, microbial biomass, enzymes, molecular characterization), moisture levels will be adjusted and the mesocosms will be monitored for changes in the soil and microbial activities during moisture extremes (comparison with constant moisture treatment) with major comparisons between sites and temperatures. SO3: We further developed a microbial decomposition model to evaluate the effect of population and substrate density on rates of soil organic matter transformation. Current models make implicit assumption of these factors, but they vary with soil depth and as such can greatly alter prediction of soil organic carbon storage. This is especially true for a litter layer in which the model would predict very little accumulation. Yet in soils with high mineral content, storage would increases substantially. A second thrust of model development went into the consideration of anaerobic microsites. While the overall volume of anaerobic microsites is considered in current model, they rely on a single oxygen diffusion coefficient that is phenomenologically tied to water filled pore space. In contrast, we explictly use diffusion of dissolved oxygen into volumes of individual microsites, to form a probability density function of the overall soil fraction that is anaerobic. This allows us to better represent the diffusion of substrate (C, NH4, NO3) as well as individual transformation (respiration, nitrification, denitrification) at the whole soil level. SO4: We are waiting for the mesocosm experiments to provide us parameterization of the DNDC model. We have data for climate and climate projection, a set of candidates of specific microbial models from SO3 that we intend to incorporate into the DNDC model.
Publications
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2019
Citation:
Rai, Dipti, S. Gerber and M. Silveira, 2019, DNDC simulation of soil carbon in subtropical grazing land of Florida requires adjustment in growth and decomposition parameterization, Soil Science Society of America Annual Meeting
|
Progress 08/01/17 to 07/31/18
Outputs
Target Audience:The major audience are scientist in the field of carbon cycling, greenhouse gas emissions, soil management and grazingland research. Changes/Problems:There are no major problems. A minor problem was the set up of the greenhouse experiments. We had difficulties to control the environment. Additional problems arose when growing plants in pots in greenhouses. These issues are solved now, but caused some delay in the exectution of the project. What opportunities for training and professional development has the project provided?Three graduate students are working exclusively on aspects of the specific project. How have the results been disseminated to communities of interest?This far, we have shown preliminary results of our work at various conferences, See alsoo the citations for these. Further we have presented our work at the field day of the Ona Range and Cattle Station, which was an event created for stakeholders of the University of Florida's research and education center. What do you plan to do during the next reporting period to accomplish the goals?During the next reporting period we focus on two specific aspects: 1) Greenhouse experiment: We have finished trials in the greenhouse, where we subjected the soils to various levels of soil moisture and temperature, and are able to grow and maintain the potted plants. We are starting the experiment in October, with the intention to run it for one year. The treatments are control, warming, planted, bare soil, management practices, and episodic high water. The treatments are almost full factorial, except the water/temperature interaction. 2) Analyze molecular data in conjunction with greenhouse gas fluxes: We have regularly sampled soils in the field for analsis for molecular (genetic) data. We will continue collection of soil data. Further, we also analyze the greenhouse experiment for molecular data. 3) Analyze microbial data (enzymes, microbial biomass, lipids), in conjunction with a microbial model to estimate carbon stocks and carbon and nitrous oxide fluxes from field measurements and greenhouse experiments. To that end we are using SEAM, a stand-alone model coupled carbon/nitrogen model. 4) Improve an ecosystem model DNDC (and/or) the ECOSSE models, in order to predict field greenhouse gas emission. parameterize this model based on greenhouse treatments to predict future responses of fields to projected climate change.
Impacts
What was accomplished under these goals?
IMPACT Grazing lands are among the largest ecosystems in the world and contain about one-third of global soil carbon reserves. While there is concern that release of stored carbon from agricultural soils further accelerates climate warming, there is also potential to manage soils effectively to remove anthropogenic greenhouse gases. Our work takes advantage of adjacent grazingland fields in Ona, FL, which are differently managed. Fields of intense management (improved pasture) are contrasted with a treatment that is considered native rangelands. At the core of greenhouse gas emissions are microbes residing in the soils. These lifeforms digest organic matter stemming from plant production, and their waste products are ultimately mineral forms of nutrients that are dissolved or escape as gases (including greenhouse gases). Intermediate microbial waste products in contrast help to build up carbon and nutrient reserves. In order to understand the transformation that lead to carbon storage and healthy functional soils, it becomes important to know 1) who is in the soil, and 2) what are they doing. We found that both carbon dioxide emissions and nitrous oxide emissions are higher in the improved pasture than in the native rangelands, throughout the year. However, the improved pasture had a higher soil organic carbon (SOC) content than the native rangeland, suggesting that over time, more intense management can foster the uptake of anthropogenic carbon. We can corroborate our results also with measurements of isotopes, where we find significant amount (50%) of "newer" carbon in the improved pasture. Interestingly, the carbon in the improved pasture has also a higher amount of labile organic carbon in surface soils, which are forms that are generally more easily to digest by microbes and are therefore thought to be processed swiftly and quickly returned to the atmosphere as carbon dioxide. Following this higher amount of easily digestible material are also an increased microbial enzyme activity, which directly shows that indeed this material is processed at a faster rate by microbes. A molecular analysis that specifically show the community composition of the microbes, and which genes are active in the soil under different conditions is currently underway. And finally, work started that would enable us to predict greenhouse gas emissions and microbial functioning under a changing environment, including a laboratory experiment and the adaptation of a prediction model. Results so far suggest that more intense management (as we have in the improved pasture), lead to a faster processing of carbon and nutrients, and therefore also increased greenhouse gas production. However, the faster processing leads also to more carbon intake and longer-term carbon storage. Hence management in subtropical grazinglands can help with the global management of greenhouse gases. We currently evaluate the exact significance for the future. Detailed acomplishments under the objectives In SO1, we collected soil samples three times during the reporting period (March 2017, September 2017, January 2018, and July 2018) for measurements of decomposition rates, enzyme analysis, carbon extractions, and for genetic analysis for each of the treatments. Soil samples were collected from three horizons, A, E and Bh. Further, the A horizon was divided into A1 (0-10 cm) and A2 (remaining depth of the A). Carbon (C) and nitrogen (N) fractions were analyzed using cold water, hot water and acid extraction. Microbial biomass C (MBC) and N (MBN) concentrations were estimated. Activities of two C acquiring enzymes, and two N acquiring enzymes were measured. Lipid extraction was carried out to get a broad diversity measurement of bacterial and fungal community. Respiration rates (carbon dioxide effluxes) were significantly higher in the improved pasture. Diel and seasonal pattern of CO2, N2O and CH4 fluxes were found be significantly different across management type. In dry season, native rangeland had lower CO2 fluxes (1 to 1.5 umol CO2 m-2s-1) and N2O flux (0.0002 to 0.0009 umol N2O m-2s-1) compared to the improved pastures (1 to 2.8 umol CO2 m-2s-1) and N2O flux (0.0002 to 0.0014 umol N2O m-2s-1). Similar CO2 and N2O fluxes pattern were observed in the native rangelands (0.1 to 0.6 umol CO2 m-2s-1 and -0.015 to 0.0005 umol N2O m-2s-1) and improved pastures (0.6 to 1.4 umol CO2 m-2s-1 and 0.0005 to 0.015 umol N2O m-2s-1). The grazing lands acted as a sink of CH4 in the dry season and a source of CH4 in the wet season for both systems. Improved pastures had greater SOC content and CO2 emissions compared to the native rangelands. Results showed that the contribution of C3-C and C4-C sources in the deep Bh horizon of improved pastures was 50% each for SOC, while C4-C comprised 30% of total soil CO2. The results indicate that the conversion of native rangeland to improved pastures increased the availability of older carbon sources for soil microorganisms in deeper horizon. Results indicate that management practices significantly impacted different SOC, different carbon fractions and enzyme activity. SOC stock in improved pasture was significantly higher (63 Mg ha-1) compared to in native rangeland (33 Mg ha-1). However, labile carbon fractions were only significant in surface (A1) horizon and no significant differences were observed in sub surface horizons. Enzyme activities responded to the availability and quantity of labile substrate (CWEC, HWEC, and AEC), the activities were significantly higher in the A1 horizon of improved pastures compared to native rangeland. Overall, the improved pasture showed an increased activity of C and N acquiring enzymes is regulated by increased quality and quantity of substrate (higher primary production), indicating higher carbon (and nitrogen) turnover, higher processing rate, but also increased carbon storage. Under SO2, we now have finished the setup of the manipulation experiments. A total of 48 buckets (individual samples with 2 management practices * 2 temperatures * 2 moisture contents * 2 with and without plants * 3 replications) for this experiment are set up in a greenhouse. Actual treatments of temperature and moisture have been started and one set of samples were taken from all the buckets to get the base line sampling before starting the temperature and moisture treatments. We have adopted the SEAM model as a tool for data evaluation and integration in SO3. SEAM includes different strategies of enzyme allocation by microbes to acquire substrates. We are working to make modifications that will reflect the swiftness with which the microbial community responds to temperature and specifically moisture treatment. Also underway are formulations that specifically target nitrifying and denitrifying microbes, as these are measured variables. We intent to use the DNDC model as a prediction model for SO4. An initial baseline simulation of the model was first conducted to ensure that the simulated soil carbon attains steady state as expected after long-term management. We modified initial conditions, decomposition rates, vertical distributions of soil organic carbon, as well as maximum growth rates to test whether these modifications can reproduce both respiration and SOC amounts. The results lead to simulated CO2 flux ~4352 kg C ha-1 yr-1 in agreement with field observed data with higher than the model's intrinsic maximum growth rate. When then subjected to improved management SOC increased to 63 Mg C ha-1 CO2 flux of almost doubled to 7570 kg C ha-1 yr-1. We conclude that in adapting DNDC to subtropical systems, the model's basic set up underestimates the vigor of both growth and decomposition.The work under this objective serves as a prediction tool for manager to assess soil carbon storage, greenhouse gas production and ultimately soil health under different management and environmental conditions.
Publications
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2018
Citation:
Rai,D., P. Inglett, K. Inglett, M. Silveira, and S. Gerber, DNDC simulation of soil carbon in subtropical rangelands of Florida requires adjustments in growth and decomposition parameterization, Soil and Water Sciences Research Forum, Gainesville
- Type:
Other
Status:
Published
Year Published:
2018
Citation:
Rai,D., P. Inglett, K. Inglett, M. Silveira, and S. Gerber, Booth on Range and Cattle Research and Education Center, where work was highlighted.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2018
Citation:
Sandhu, S.S., K.S. Inglett, M.L. Silveira, P.W. Inglett and S. Gerber. 2018. Response of soil microbial processes to long-term management practices in subtropical grazing lands during different seasons. Oral presentation at the 21st World Congress of Soil Science held at Rio de Janeiro, Brazil from August 12-17, 2018.
|
Progress 08/01/16 to 07/31/17
Outputs
Target Audience:The target of this research so far are scientist in the field of global change, soil science, and carbon and biogeochemical cycles. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?The work supports 3 graduate (PhD students). These students started in year 1 of the project with course work. They were further trained in field and laboratory safety and procedures, as well as having first encounters and insights into modeling. How have the results been disseminated to communities of interest?The work has been presented so far at one USDA NIFA project director's meeting and is also presented at the Soil Science Society meeting in Tampa, in October 2017. What do you plan to do during the next reporting period to accomplish the goals?SO1: - Evalulate microbial community and function from field samples. - Continue with soil enzyme analyses in field samples, and opportunistically sample during extreme events SO2: Establish labarotary incubations for the following experimental treatment (factorial). management type, soil only vs. planted soil, warmed soil, moist soil. These incubations are set to run for ca. 1 year, where we periodically evaluate greenhouse gas fluxes, microbial community and structure as well as microbial parameters (enzymes and carbon use efficiency). SO3: Test microbial model and add the nessecary code to include microbial adaptation to environmental stressors. Populate the model with data from SO2. SO4: Continue with measurements
Impacts
What was accomplished under these goals?
IMPACT Our results indicate that management of pastures has a strong impact on carbon storage. Over a bit more than two decades, addition of fertilizer and managing grass species lead to an almost doubling of carbon storage in these pastures. These results are critical when evaluating ecosystem services, where greenhouse gas sequestration is a central part next to economic and aesthetic values. These benchmark help farmers with decision on management and offer policymaker concrete data on evaluating the tradeoff in the nexus of food, environment and economy. SO1: Much of our work this far was under SO1: Soil samples were collected in March and September 2017 from three horizons A, E and Bh. The composite samples were divided into two part; for phospholipids (PLFA) analysis and other soil properties. The improved pastures (IP) significantly had highest soil organic carbon (SOC) stock and concentration compared to native rangeland (NR) probably due to the addition of manure and nitrogen fertilizer in IP system. The SOC stock was 94% higher in IP compared to NR. Moreover, SOC stock was significantly 3.3, and 3.2 times higher in A1 and Bh horizons compared to E horizons. This clearly shows that Bh stores a huge amount of organic carbon almost equivalent to A1 horizon. The microbial carbon (MBC) (271 mg kg-1) and microbial nitrogen (MBN) (20 mg kg-1) values for IP were significantly 30 and 32% higher as compared to MBC (209 mg kg-1) and MBN (15.2 mg kg-1) values in NR, respectively. The higher MBC and MBN in IP is due to the high organic carbon content and presence of better quality of litter as indicated by lower C/N ratio in IP systems. Extracellular enzyme activity Improved management practices such as addition of fertilizer and improved grazing significantly affected the enzyme activity of both carbon cycle enzymes and one nitrogen cycle enzyme (LAP), but had no impact on the activity of NAG. The increased activity of BGA and CBH is well correlated with SOC concentration, TN and MBC. The hot water extractable carbon which is usually considered as labile or easily available carbon for microorganisms was positively correlated with the enzyme activities as well. This clearly indicates that more availability of C substrate, quality of C substrate, additional source of N, and more MBC increased the activity of BGA and CBG in IP system. BGA and CBH activities are often related with the characteristics and amount of SOC present in the system. The increased enzyme activity lead to increased heterotrophic respiration in the soil. Similarly, the enzyme activities of BGA and CBH was higher in A1 horizon due to labile C substrate addition through root exudates and high SOC and MBC concentrations. Even though the carbon stock of Bh was equivalent to A1, low MBC, TN and high C/N ratio in Bh horizon compared to A1 could be the reason for low activity of BGA and CBH in Bh horizon compared to A1. Ratios of enzymes to microbial biomass indicate that the overall increased activity of BGA and CBH per unit mass of soil in IP was likely driven by high microbial biomass in the both systems, and important information for modeling. However, the specific enzyme activities of BGA and CBH were significantly higher in Bh horizon. SO1 Conclusions and Relevance: Data from this study clearly indicates that improved pastures store significantly higher amount of carbon compared to native rangelands. A huge amount of this carbon stock is stored in the deep soil Bh horizon. Moreover, IP increased the activity of extracellular enzymes expect NAG and MBC and MBN compared to NR system. The increased enzyme activity is regulated by the quality and quantity of C substrate through increased root exudates in IP systems as indicated by lower C/N ratio and high SOC stock, compared to NR system. Our results indicate that management of pastures has a strong impact on carbon storage. Over a bit more than a decade, addition of fertilizer and managing grass species lead to an almost doubling of carbon storage in these pastures. These results are critical when evaluating ecosystem services, where greenhouse gas sequestration is a central part next to economic and aesthetic values. These benchmark help farmers with decision on management and offer policymaker concrete data on evaluating the tradeoff in the nexus of food, environment and economy. SO2 For this objective, a laboratory incubation study has been planned, and we are currently prototyping a laboratory setup. To that end we collected soil from the 2 management treatments. We have the following experimental and factorial treatment: management type, soil only vs. planted soil, warmed soil, moist soil. Prototypes assures that we can establish workflow for sampling (periodic soil sampling for soil and molecular analysis), gas measurements, maintenance of soil moisture levels, and viability of plants in the experimental setup, and ultimately molecular analysis indicating microbial community and structure. SO2 Relevance The work done under SO2 will elucidate the resilience of the soil microbial community to environmental and management changes. Quantifying the changes in microbial community und function under environmental stressors will help with mitigation/adaptation decisions. SO3 Work has begun to evaluate existing microbial models, including the MEND and the MIMIC model. We developed analytical solutions for steady state, i.e. the state of the model variables (microbial biomass, enzyme activity, soil organic matter dynamics) under long-term stable conditions. These are helpful as they potentially indicate the trajectory under change scenario from management and environmental stressors. Analytical solutions allow a more detailed and straightforward analysis and therefore help with the integration of data obtained under SO2. SO3 Relevance Models and in particular mechanistic models are indispensable tools for prediction. In particular as we enter an era of unseen changes (climate change, environmental pressure, technical advances), models are helpful for planning and risk analyses (e.g. what if analyses). In our case, they offer also insights for scenario evaluation and generating new hypotheses on microbial soil interactions. SO4 We have started to evaluate specific process-based model that we intend to apply and use for soil carbon and soil organic matter dynamics under global change scenarios. These models include DNDC as well as ECOSSE. At this point we favor ECOSSE. While both model represent similar mechanisms with similar details, ECOSSE offers better flexibility. The chosen model will be modified to include equations from SO3, and will be evaluated against field measurements of greenhouse gas emissions (CH4, N2O and CO2). Work has also begun to generate field data of essential variables. Diel patterns of CO2 and CH4 fluxes were compared between the two management sites and were found be significantly different with each other. Native rangeland had lower CO2 fluxes compared to the managed grassland in both dry and wet season. Negative CH4 fluxes were observed in the dry season whereas positive CH4 fluxes in the wet season in both sites. δ13C values varies for different vegetation; saw-palmetto = -27.3‰ (Silveira et al., 2013) and bahiagrass = -13.4‰ (Haile et al., 2010; Silveira et al., 2013). For CO2 isotopic composition, greater δ13C - CO2 values observed in improved pasture indicated the contribution of newly added C4-derived C inputs to SOC decomposition. These values give further benchmarks on long-term carbon storage and greenhouse gas sequestration under different management schemes. SO4 Relevance: The resulting model and its evaluation will provide an important evaluation and decision making tool when assessing the tradeoffs between food production, economy and ecosystem services under climate change and deepening climate variability.
Publications
|
|