Yu K, Patrick WH Jr. 2004. Redox window with minimum global warming potential contribution from rice soils. Soil Science Society of America Journal 68: 2086-2091.
These authors followed up a previous study (Yu and Patrick 2003) that discovered a critical range of soil redox potential (Eh) across a range of pH for rice-agriculture soils, by examining soil Eh in more detail. The critical range is based on minimizing total global warming potential of all 3 major greenhouse gases, in terms of CO2-equivalents; methane and nitrous oxide have much higher radiative forcing than does CO2, when looked at on a 100-year horizon.
The critical range, for all 8 soils studied, is between 180 and -150 mV, what might be considered “moderately reducing” for soils. CO2 production is modest in this range, though it is lower at more reducing conditions. CH4 production is nearly absent in this range, but is very large at redox conditions below -150 mV. N2O production is modest in this range as well, with much higher N2O production under oxidizing conditions (Eh > 180) due to strong nitrification activity.
This paper serves to support earlier ideas about the net effects of redox conditions on the production and consumption dynamics of these gases. The story with CO2 and CH4 is fairly simple, while N2O dynamics are more complicated because there are more pathways for both production and consumption of this gas.
Thursday, January 28, 2010
Ettwig et al. 2009
Ettwig KF, van Alen T, van de Pas-Schoonen KT, Jetten MSM, Strous M. 2009. Enrichment and molecular detection of denitrifying methanotrophic bacteria of the NC10 phylum. Applied and Environmental Microbiology 75: 3656-3662.
These authors describe a series of experiments and procedures designed to investigate an enigmatic organism known as NC10, a bacteria in its own eponymous phylum that currently represents the only demonstrated case of biological reduction of nitrate coupled to oxidation of methane under anaerobic conditions. While anaerobic methane consumption has been observed in some archaea, it has not been found coupled to denitrification.
A laboratory culture eventually dominated by NC10 organisms of group a (a distinction within the phylum) was established, based on sediment collected from a eutrophic ditch draining agricultural land on the floodplain of the Rhine river in the Netherlands. This culture was grown and maintained under conditions in which the only carbon source was the sparge gas of CH4-CO2, and nitrogen was supplied with the mineral inputs as nitrate and nitrite, along with a wide range of other inorganic compounds and trace elements.
The major finding of this study was a wealth of knowledge of the basic characteristics of the NC10 organism, and confirmation that it does indeed oxidize methane under anaerobic conditions coupled to denitrification. This process is energetically favourable, and the theoretical stoichiometry matches the observed changes in chemical composition in these experiments, with the nitrite reduction to methane consumption ratio of 8:3.5, versus 8:3 based on mass balance calculations.
One of the surprising aspects of this organism is that its methane-oxidizing activity is completely inhibited by black butyl rubber, as is found in black rubber stoppers for serum vials and other glassware. Grey or red butyl rubber stoppers do not show such inhibition, and repeated boiling of black butyl rubber stoppers in HCl did not remove the inhibitory effects. Strictly anoxic conditions are not required for all aspects of working with this organism; brief exposure to atmospheric oxygen during liquid transfer, for example, did not inhibit methanotrophic activity.
Another strange feature of NC10 concerns its 16s rDNA sequences. General 16s primers do not amplify NC10 DNA. These authors developed new primers for the 16s region based on the DNA in their culture, which they were able to confirm as NC10 based on FISH observations. The new primers allowed them to work more easily with the NC10 DNA, which is not surprising, but the sequences of NC10 16s found did not differ in critical ways from the target regions of the general 16s primers. So, it is unknown why the general 16s primers do not work on NC10 DNA.
This paper was recommended to me and I would not likely have discovered it without this recommendation. I have results from the 2009 work at Alexandra Fjord that suggest simultaneous consumption of CH4 (oxidation) and N2O (reduction), and I did not know if these two processes might be linked in a single organism or within a system such as a symbiosis or food-chain as 2 halves of a redox couple.
My results may be more suggestive of an alternate situation. Rather than anaerobic oxidation of methane (weirdness) coupled to nitrate reduction, I may be looking for cases of reduction of nitrous oxide under aerobic conditions (weirdness) coupled to methane oxidation.
These authors describe a series of experiments and procedures designed to investigate an enigmatic organism known as NC10, a bacteria in its own eponymous phylum that currently represents the only demonstrated case of biological reduction of nitrate coupled to oxidation of methane under anaerobic conditions. While anaerobic methane consumption has been observed in some archaea, it has not been found coupled to denitrification.
A laboratory culture eventually dominated by NC10 organisms of group a (a distinction within the phylum) was established, based on sediment collected from a eutrophic ditch draining agricultural land on the floodplain of the Rhine river in the Netherlands. This culture was grown and maintained under conditions in which the only carbon source was the sparge gas of CH4-CO2, and nitrogen was supplied with the mineral inputs as nitrate and nitrite, along with a wide range of other inorganic compounds and trace elements.
The major finding of this study was a wealth of knowledge of the basic characteristics of the NC10 organism, and confirmation that it does indeed oxidize methane under anaerobic conditions coupled to denitrification. This process is energetically favourable, and the theoretical stoichiometry matches the observed changes in chemical composition in these experiments, with the nitrite reduction to methane consumption ratio of 8:3.5, versus 8:3 based on mass balance calculations.
One of the surprising aspects of this organism is that its methane-oxidizing activity is completely inhibited by black butyl rubber, as is found in black rubber stoppers for serum vials and other glassware. Grey or red butyl rubber stoppers do not show such inhibition, and repeated boiling of black butyl rubber stoppers in HCl did not remove the inhibitory effects. Strictly anoxic conditions are not required for all aspects of working with this organism; brief exposure to atmospheric oxygen during liquid transfer, for example, did not inhibit methanotrophic activity.
Another strange feature of NC10 concerns its 16s rDNA sequences. General 16s primers do not amplify NC10 DNA. These authors developed new primers for the 16s region based on the DNA in their culture, which they were able to confirm as NC10 based on FISH observations. The new primers allowed them to work more easily with the NC10 DNA, which is not surprising, but the sequences of NC10 16s found did not differ in critical ways from the target regions of the general 16s primers. So, it is unknown why the general 16s primers do not work on NC10 DNA.
This paper was recommended to me and I would not likely have discovered it without this recommendation. I have results from the 2009 work at Alexandra Fjord that suggest simultaneous consumption of CH4 (oxidation) and N2O (reduction), and I did not know if these two processes might be linked in a single organism or within a system such as a symbiosis or food-chain as 2 halves of a redox couple.
My results may be more suggestive of an alternate situation. Rather than anaerobic oxidation of methane (weirdness) coupled to nitrate reduction, I may be looking for cases of reduction of nitrous oxide under aerobic conditions (weirdness) coupled to methane oxidation.
Firestone et al. 1980
Firestone MK, Firestone RB, Tiedje JM. 1980. Nitrous oxide from soil denitrification: Factors controlling its biological production. Science 208: 749-751.
These authors measured the faction of N2O in nitrogen gas outputs from soil slurries under a range of conditions of substrate and oxygen availability. Slurries were employed to avoid problems associated with diffusion of materials through a soil matrix, and the process of denitrification was studied using isotopic tracers, especially in the form of 13N in nitrate and other inputs.
The controls on the production of N2O from denitrification are the concentration of nitrite (NO2-) and the availability of oxygen (O2), with time-since-anoxic another important factor. Increasing nitrite increases N2O production and increasing NO3- does as well, but less strongly, suggesting the role of NO3- is indirect, and it is the NO2- produced from NO3- that matters. Aerobic conditions inhibit denitrification, rendering the entire pathway moot. The establishment of anaerobic conditions turns on denitrification, but in a stepwise process apparently related to protein synthesis. In a series of experiments, these authors found that in the initial period of anaerobiosis, N2 is the major output. Later, N2O production increases without an increase in its consumption, and N2O is the major output. Finally, N2O consumption catches up with production, and N2 is once again the major output. Adding O2 increases the proportion of total denitrification output that is N2O, but eventually O2 does inhibit denitrification completely.
These authors measured the faction of N2O in nitrogen gas outputs from soil slurries under a range of conditions of substrate and oxygen availability. Slurries were employed to avoid problems associated with diffusion of materials through a soil matrix, and the process of denitrification was studied using isotopic tracers, especially in the form of 13N in nitrate and other inputs.
The controls on the production of N2O from denitrification are the concentration of nitrite (NO2-) and the availability of oxygen (O2), with time-since-anoxic another important factor. Increasing nitrite increases N2O production and increasing NO3- does as well, but less strongly, suggesting the role of NO3- is indirect, and it is the NO2- produced from NO3- that matters. Aerobic conditions inhibit denitrification, rendering the entire pathway moot. The establishment of anaerobic conditions turns on denitrification, but in a stepwise process apparently related to protein synthesis. In a series of experiments, these authors found that in the initial period of anaerobiosis, N2 is the major output. Later, N2O production increases without an increase in its consumption, and N2O is the major output. Finally, N2O consumption catches up with production, and N2 is once again the major output. Adding O2 increases the proportion of total denitrification output that is N2O, but eventually O2 does inhibit denitrification completely.
Patrick and DeLaune 1972
Patrick WH Jr., DeLaunce RD. 1972. Characterization of the oxidized and reduced zones in flooded soil. Soil Science Society of America Proceedings 36: 573-576.
These authors measured the thickness of the oxidized layer in flooded soils. For Eh measurements, a platinum electrode was pushed down through the soil at a rate of 2mm/hour, sufficiently slowly for the electrode tip to reach near-equilibrium conditions as it descended. Concentrations of reduced and oxidized forms of Manganese, Iron, Sulfur, and Nitrogen were also measured.
Within a few days of submergence, soils showed a clear redox-potential profile as measured by the platinum electrode, with the oxidized layer above the reduced layer, and a transition from above 200 mV to below 200 mV across a relatively narrow intermediate layer. The profiles as measured by the chemical species distribution were similar, though Mn showed a narrower and S a deeper oxidized layer, probably relating to the redox conditions needed to reduce the oxidized compounds present in the soil; sulfate, for example, requires lower Eh values to be reduced than do ferric oxides.
Manganese, Iron, and Sulfur did not diffuse appreciably in these experiments, but Nitrogen compounds did. These authors propose the following process is occurring in these flooded soils:
These authors measured the thickness of the oxidized layer in flooded soils. For Eh measurements, a platinum electrode was pushed down through the soil at a rate of 2mm/hour, sufficiently slowly for the electrode tip to reach near-equilibrium conditions as it descended. Concentrations of reduced and oxidized forms of Manganese, Iron, Sulfur, and Nitrogen were also measured.
Within a few days of submergence, soils showed a clear redox-potential profile as measured by the platinum electrode, with the oxidized layer above the reduced layer, and a transition from above 200 mV to below 200 mV across a relatively narrow intermediate layer. The profiles as measured by the chemical species distribution were similar, though Mn showed a narrower and S a deeper oxidized layer, probably relating to the redox conditions needed to reduce the oxidized compounds present in the soil; sulfate, for example, requires lower Eh values to be reduced than do ferric oxides.
Manganese, Iron, and Sulfur did not diffuse appreciably in these experiments, but Nitrogen compounds did. These authors propose the following process is occurring in these flooded soils:
“…ammonium diffusion from the reduced layer to the oxidized layer -> ammonium oxidation to nitrate (nitrification) -> nitrate diffusion from the oxidized layer to the reduced layer -> denitrification…”To explain the observation that nitrate was absent from the reduced layer, and never very abundant in the oxidized layer, and that ammonium was rapidly depleted in the oxidized layer. In this system, nitrification and denitrification are occurring simultaneously at different positions and redox potentials.
Wednesday, January 27, 2010
Yates et al. 2007
Yates TT, Si BC, Farrell RE, Pennock DJ. 2007. Time, location, and scale dependence of soil nitrous oxide emissions, soil water, and temperature using wavelets, cross-wavelets, and wavelet coherency analysis. Journal of Geophysical Research 112, D09104.
These authors analyzed a dataset of soil parameters and N2O emission using three subtly-different wavelet-based statistical techniques. There were two main purposes to this study; first, to examine the predictive relationships (if any) between soil parameters such as water filled pore space (WFPS) or temperature and N2O emissions; second, to evaluate the utility of these 3 wavelet techniques in analyzing this type of data.
N2O emission data is characterized by high variance in space and time, and frequent extreme values. These characteristics make many sophisticated geospatial statistical techniques not suitable, and the high spatial and temporal autocorrelation of many soil parameters eliminates many other techniques. These authors describe these limitations and some of the techniques that have been employed, and settle on 3 varieties of wavelet analysis.
Wavelet techniques are related to Fourier-transforms, and they appear to be highly complex and sophisticated methods to transform data for analysis, rather than being analytical methods per se. A large fraction of this paper is concerned with detailed description of the parameters of the transformation, and the interpretation of the results. One of the key advantages of these techniques is they usually allow examination of data across a broad range of spatial scales, thus permitting identification of the spatial scale at which important soil processes occur. Beyond that, I did not understand much of this paper.
Besides the interpretation of the differences between the 3 wavelet techniques, which was quite frankly beyond my understanding, the main result of this study was that the soil parameters that can predict N2O emissions in this landscape vary through the season. Early, around snowmelt and soil thawing, soil temperature is predictive of emissions. Later in the season, temperature loses its usefulness, and individual landscape features may present WFPS as predictive, but not in a global sense. By mid-summer, the soil parameters measured in this study no longer bore any relationship to N2O emissions. This loss of predictive value shows how complex this system is, and shows how some modeling efforts need to change in order to improve estimates of landscape-scale N2O processes.
Besides demonstrating my ignorance of advanced geospatial statistical techniques, this paper is primarily useful to me for its clear introduction describing the basic controls on and processes of N2O production in soils. My previous understanding centred on the role of water in restricting O2 availability in soils leading to changes at both the community and cell-physiology levels and consequently N2O production patterns in space and time appears to be essentially correct, and is reinforced by the early introduction section of this paper and the references therein.
These authors analyzed a dataset of soil parameters and N2O emission using three subtly-different wavelet-based statistical techniques. There were two main purposes to this study; first, to examine the predictive relationships (if any) between soil parameters such as water filled pore space (WFPS) or temperature and N2O emissions; second, to evaluate the utility of these 3 wavelet techniques in analyzing this type of data.
N2O emission data is characterized by high variance in space and time, and frequent extreme values. These characteristics make many sophisticated geospatial statistical techniques not suitable, and the high spatial and temporal autocorrelation of many soil parameters eliminates many other techniques. These authors describe these limitations and some of the techniques that have been employed, and settle on 3 varieties of wavelet analysis.
Wavelet techniques are related to Fourier-transforms, and they appear to be highly complex and sophisticated methods to transform data for analysis, rather than being analytical methods per se. A large fraction of this paper is concerned with detailed description of the parameters of the transformation, and the interpretation of the results. One of the key advantages of these techniques is they usually allow examination of data across a broad range of spatial scales, thus permitting identification of the spatial scale at which important soil processes occur. Beyond that, I did not understand much of this paper.
Besides the interpretation of the differences between the 3 wavelet techniques, which was quite frankly beyond my understanding, the main result of this study was that the soil parameters that can predict N2O emissions in this landscape vary through the season. Early, around snowmelt and soil thawing, soil temperature is predictive of emissions. Later in the season, temperature loses its usefulness, and individual landscape features may present WFPS as predictive, but not in a global sense. By mid-summer, the soil parameters measured in this study no longer bore any relationship to N2O emissions. This loss of predictive value shows how complex this system is, and shows how some modeling efforts need to change in order to improve estimates of landscape-scale N2O processes.
Besides demonstrating my ignorance of advanced geospatial statistical techniques, this paper is primarily useful to me for its clear introduction describing the basic controls on and processes of N2O production in soils. My previous understanding centred on the role of water in restricting O2 availability in soils leading to changes at both the community and cell-physiology levels and consequently N2O production patterns in space and time appears to be essentially correct, and is reinforced by the early introduction section of this paper and the references therein.
Tuesday, January 26, 2010
Conrad 1999
Conrad R. 1999. Contribution of hydrogen to methane production and control of hydrogen concentrations in methanogenic soils and sediments. FEMS Microbiology Ecology 28: 193-202.
This author reviews the chemistry behind methane production by Archaea in anaerobic environments, focusing on the contribution of H2 rather than acetate to methanogenesis. The thermodynamics and kinetics of H2-driven CH4 production are distinct from those of acetate-driven, and the stoichiometry of the situation indicates that H2 should contribute 33% of the CH4 from a given ecosystem.
Methanogenesis in anaerobic sediments and soils is the end of a short chain of microbial interactions. First, organic matter is broken down by fermenting bacteria. The products of fermentation includes H2, and the other components such as alcohols and fatty acids, are further decomposed by syntrophic bacteria, also supplying some acetate to the environment. Finally, methanogens consume either H2 and CO2 or acetate (CH3CO2-) to produce methane.
There are many studies that show this expected pattern of methanogenesis, but many other that show either over- or under-representation of H2. Where H2 contributes less CH4 than expected, the most likely explanations involve sulfate reducers, microbes capable of outcompeting H2-consuming methanogens by more efficient use of H2 and faster population growth, based on the thermodynamics of the two guilds respective metabolisms. Such situations are common in marine and acidic freshwater sediments.
Where H2 contributes more CH4 than expected, including an Antarctic soil where H2 is the basis of 100% of CH4 production, the explanation is not as well established. The explanations that have been proposed, by this and other authors, include additional sinks of acetate such as scavenging by other organisms, additional sources of H2 including geological sources, or measurements of the system taken when it was far from equilibrium. The models of H2 and CH4 dynamics are mostly based on equilibrium conditions.
That addition of sulfate inhibits methanogenesis is well established. Competition explains this observation in sediments and soils where the biological community has had time to reach something like equilibrium, with methanogens outcompeted by sulfate reducers. However, addition of sulfate to sediment immediately and completely inhibits H2-driven CH4 production, which cannot be explained by ecosystem dynamics. A model involving a threshold H2 concentration, in which H2 levels lower than some critical level determined by the thermodynamics of the situation shut down that pathway, does explain these observations.
This author reviews the chemistry behind methane production by Archaea in anaerobic environments, focusing on the contribution of H2 rather than acetate to methanogenesis. The thermodynamics and kinetics of H2-driven CH4 production are distinct from those of acetate-driven, and the stoichiometry of the situation indicates that H2 should contribute 33% of the CH4 from a given ecosystem.
Methanogenesis in anaerobic sediments and soils is the end of a short chain of microbial interactions. First, organic matter is broken down by fermenting bacteria. The products of fermentation includes H2, and the other components such as alcohols and fatty acids, are further decomposed by syntrophic bacteria, also supplying some acetate to the environment. Finally, methanogens consume either H2 and CO2 or acetate (CH3CO2-) to produce methane.
There are many studies that show this expected pattern of methanogenesis, but many other that show either over- or under-representation of H2. Where H2 contributes less CH4 than expected, the most likely explanations involve sulfate reducers, microbes capable of outcompeting H2-consuming methanogens by more efficient use of H2 and faster population growth, based on the thermodynamics of the two guilds respective metabolisms. Such situations are common in marine and acidic freshwater sediments.
Where H2 contributes more CH4 than expected, including an Antarctic soil where H2 is the basis of 100% of CH4 production, the explanation is not as well established. The explanations that have been proposed, by this and other authors, include additional sinks of acetate such as scavenging by other organisms, additional sources of H2 including geological sources, or measurements of the system taken when it was far from equilibrium. The models of H2 and CH4 dynamics are mostly based on equilibrium conditions.
That addition of sulfate inhibits methanogenesis is well established. Competition explains this observation in sediments and soils where the biological community has had time to reach something like equilibrium, with methanogens outcompeted by sulfate reducers. However, addition of sulfate to sediment immediately and completely inhibits H2-driven CH4 production, which cannot be explained by ecosystem dynamics. A model involving a threshold H2 concentration, in which H2 levels lower than some critical level determined by the thermodynamics of the situation shut down that pathway, does explain these observations.
Pennock 2004
Pennock DJ. 2004. Designing field studies in soil science. Canadian Journal of Soil Science 84: 1-10.
This author reviews the major issues surrounding field-based (as opposed to strictly laboratory-based) research, focusing on issues specific or of greatest importance to soil science. Soil science’s history could perhaps be described as a fusion of physical geography and geology with agronomy, and many published studies in the soil science journals show these roots. Following the lead of previous authors, who have included ecologists, statisticians, and philosophers and historians of science, this author divides field research into 2 major categories, broadly manipulative studies and mensurative studies. Manipulative studies are, under some definitions including one tentatively employed in this paper, the only type of study that qualify for the name “experiment”, and involve complete control over experimental conditions by the researcher. Treatments in an experiment are directly related to replication, and can be applied with great precision. Mensurative studies are those that at least partly use features of the environment beyond the control of the researcher to test hypotheses or discover new information. The key feature of a mensurative study is that the features of interest are clearly defined but not controlled (i.e. not randomized) by the person conducting the study.
Replication, and avoiding pseudoreplication, is of great importance in all types of studies. However, the replication built into a manipulative experiment in the form of repeated application of treatments is distinct from the replication of a mensurative study using repeated features of the environment. That these are different types of replication is stated in this paper, but I found no more detail or explanation than that. Pseudoreplication in this paper is discussed little in the context of independence of samples; rather the discussed risk is of attempting to draw inferences beyond the inference space of the study. This is a problem in both major types of study, and can be avoided by carefully determining and describing the inference space, and expanding that space by greater replication; too-small sample sizes are quite simply labeled as unpublishable in this paper, a sentiment I can agree with.
Determining the required sample size is a major issue for all types of studies. In this author’s presentation, this is an early step in the design of the study, after the biological and statistical questions have been established but before data collection begins. There is some discussion here as well of statistical power (the chance of avoiding a Type II error, that is of failing to reject a false null hypothesis) and recommendations of flexibility regarding especially alpha values (the chance of making a Type I error, that is of rejecting a null hypothesis that is not false). For a number of reasons, some of which are practical and logistical, alpha values larger than the ubiquitous 0.05 are encouraged, because in many cases the consequences of the 2 types of error are not even, and one may wish to concentrate on reducing the probability of a Type II error.
This paper describes 10 commonly-encountered study designs in soil science and related disciplines, and then discusses study-design concerns common to all such as replication and the need to clearly define study units, samples, populations, and other important aspects. Finally, this author presents the conclusions from all of these examples and considerations in the form of a short list of key recommendations. Quoting directly:
This author reviews the major issues surrounding field-based (as opposed to strictly laboratory-based) research, focusing on issues specific or of greatest importance to soil science. Soil science’s history could perhaps be described as a fusion of physical geography and geology with agronomy, and many published studies in the soil science journals show these roots. Following the lead of previous authors, who have included ecologists, statisticians, and philosophers and historians of science, this author divides field research into 2 major categories, broadly manipulative studies and mensurative studies. Manipulative studies are, under some definitions including one tentatively employed in this paper, the only type of study that qualify for the name “experiment”, and involve complete control over experimental conditions by the researcher. Treatments in an experiment are directly related to replication, and can be applied with great precision. Mensurative studies are those that at least partly use features of the environment beyond the control of the researcher to test hypotheses or discover new information. The key feature of a mensurative study is that the features of interest are clearly defined but not controlled (i.e. not randomized) by the person conducting the study.
Replication, and avoiding pseudoreplication, is of great importance in all types of studies. However, the replication built into a manipulative experiment in the form of repeated application of treatments is distinct from the replication of a mensurative study using repeated features of the environment. That these are different types of replication is stated in this paper, but I found no more detail or explanation than that. Pseudoreplication in this paper is discussed little in the context of independence of samples; rather the discussed risk is of attempting to draw inferences beyond the inference space of the study. This is a problem in both major types of study, and can be avoided by carefully determining and describing the inference space, and expanding that space by greater replication; too-small sample sizes are quite simply labeled as unpublishable in this paper, a sentiment I can agree with.
Determining the required sample size is a major issue for all types of studies. In this author’s presentation, this is an early step in the design of the study, after the biological and statistical questions have been established but before data collection begins. There is some discussion here as well of statistical power (the chance of avoiding a Type II error, that is of failing to reject a false null hypothesis) and recommendations of flexibility regarding especially alpha values (the chance of making a Type I error, that is of rejecting a null hypothesis that is not false). For a number of reasons, some of which are practical and logistical, alpha values larger than the ubiquitous 0.05 are encouraged, because in many cases the consequences of the 2 types of error are not even, and one may wish to concentrate on reducing the probability of a Type II error.
This paper describes 10 commonly-encountered study designs in soil science and related disciplines, and then discusses study-design concerns common to all such as replication and the need to clearly define study units, samples, populations, and other important aspects. Finally, this author presents the conclusions from all of these examples and considerations in the form of a short list of key recommendations. Quoting directly:
1. A clear definition of the research question is the initial (and most critical) step. This definition dictates the type of research design that is appropriate and the specific design issues associated with different research types.
2. The appropriateness of a given research design can be judged only after a thorough review of what is known about the research question. Exploratory pattern studies can be very informative at an early stage of research, but yield little new information for well-established research topics. Equally, the imposition of a set of treatments if little is known of the processes controlling responses is unlikely to produce comprehensive interpretations.
3. There is never a good reason for haphazard sampling – the rationale for selecting sampling points in pedological, soil geomorphic, or inventory studies should be clearly stated.
4. A clear definition of the population and the elements that comprise the population under study is very important.
5. The definition of the population dictates the extent of the study and the physical or temporal space that the results pertain to, which is critical to avoid pseudoreplication.
6. The sample support, spacing, and extent of the study must be consistent with what is known of the processes controlling the phenomena being studied.
7. The construction of hypotheses for formal testing should be based on sound physical or biological reasoning, and sufficient samples should be taken to allow reliable testing of the alternative hypotheses.
8. The exclusion of phenomena because they cannot be replicated is inherently limiting to the expansion of our knowledge of soils. Innovative approaches must continue to be developed and applied so that we can expand the scale at which field studies can be undertaken.
Monday, January 25, 2010
Bremer et al. 2009
Bremer C, Braker G, Matthies D, Beierkuhnlein C, Conrad R. 2009. Plant presence and species combination, but not diversity, influence denitrifier activity and the composition of nirk-type denitrifier communities in grassland soil. FEMS Microbiology and Ecology 70: 377-387.
These authors ran a manipulative, common-garden experiment to examine interactions between surface-plant community and soil denitrifier community diversities. The major finding of this paper, as described in the title, is that denitrifier community diversity is influenced by the species of plants in the system, but not how many species are there.
I saw 2 major problems with this paper that calls their major finding into question at least in my mind. First, the single greatest effect on denitrifier community composition found here was the very distinct community in the control, no-plant plots. These authors never acknowledge that zero plants is a point on their spectrum of species diversity; they state their range of plant community species richness was 2 to 8, but it was actually 0 to 8, with a strong effect of the 0 community. They do not analyze their data in this way that I can see, so I do not know if this 0-community effect does or does not reverse their conclusion that plant species diversity does not influence denitrifier diversity.
Second, the single most distinct with-plants community that was included in analysis is probably an outlier and should be excluded, because the plant community was 2 species of grasses (rather than mixed grass / forb), which also had the highest productivity in one of the study years. Furthermore that year was a high-temperature drought year across much of Europe including the study site. This probably-outlier result is acknowledged by these authors as having some of these problems, but their discussion of the probable role of greater niche-space in the soil under the more-diverse-but-same-species-richness plots does not suggest they have considered the confounding effects.
Despite the suspect results, this paper provides a useful overview, especially in the introduction and large parts of the discussion sections of denitrifier communities in soils and their probable interactions with plant communities.
These authors ran a manipulative, common-garden experiment to examine interactions between surface-plant community and soil denitrifier community diversities. The major finding of this paper, as described in the title, is that denitrifier community diversity is influenced by the species of plants in the system, but not how many species are there.
I saw 2 major problems with this paper that calls their major finding into question at least in my mind. First, the single greatest effect on denitrifier community composition found here was the very distinct community in the control, no-plant plots. These authors never acknowledge that zero plants is a point on their spectrum of species diversity; they state their range of plant community species richness was 2 to 8, but it was actually 0 to 8, with a strong effect of the 0 community. They do not analyze their data in this way that I can see, so I do not know if this 0-community effect does or does not reverse their conclusion that plant species diversity does not influence denitrifier diversity.
Second, the single most distinct with-plants community that was included in analysis is probably an outlier and should be excluded, because the plant community was 2 species of grasses (rather than mixed grass / forb), which also had the highest productivity in one of the study years. Furthermore that year was a high-temperature drought year across much of Europe including the study site. This probably-outlier result is acknowledged by these authors as having some of these problems, but their discussion of the probable role of greater niche-space in the soil under the more-diverse-but-same-species-richness plots does not suggest they have considered the confounding effects.
Despite the suspect results, this paper provides a useful overview, especially in the introduction and large parts of the discussion sections of denitrifier communities in soils and their probable interactions with plant communities.
Friday, January 22, 2010
Bedard-Haughn et al. 2006
Bedard-Haughn A, Matson AL, Pennock DJ. 2006. Land use effects on gross nitrogen mineralization, nitrification, and N2O emissions in ephemeral wetlands. Soil Biology and Biochemistry 38: 3398-3406.
These authors used a combination of stable-isotope and measurements of chemical pools and emissions from soils techniques to examine the role of various microbial-mediated processes in contributing to N2O production in an agricultural landscape. N2O emissions are the result of a complicated suite of metabolic activity in soils, with local oxygen concentrations, driven by soil moisture, and concentrations of reactants in these chemical pathways both contributing to net processes.
In the Canadian prairies, gross N2O production is positively correlated with soil moisture, with the highest emissions associated with lower-slope and wetland soils. This is consistent with the major contributing process in N2O emissions being denitrification, the process that reduces NO3- under anaerobic conditions. However, nitrification, the production of NO3- from NH4+, has also been observed to contribute to N2O emissions, especially from drier and aerobic soils.
Simple measurements of NO3- and NH4+ concentrations in soils will not capture information about the processes cycling N between these and other pools of soil matter. Used in conjunction with measurements of those processes, such as the 15N technique used here, does provide information about the factors controlling those processes. In this case, little variation through time or space in either pool combined with patterned variation in N2O emission and 15N movements allowed these authors to infer that both nitrification and denitrification are not limited by the substrate pools, despite the quite different other aspects of these processes.
This paper provides a very detailed description of the 15N procedures used, as well as a clear discussion of the various N-cycling processes in soils.
These authors used a combination of stable-isotope and measurements of chemical pools and emissions from soils techniques to examine the role of various microbial-mediated processes in contributing to N2O production in an agricultural landscape. N2O emissions are the result of a complicated suite of metabolic activity in soils, with local oxygen concentrations, driven by soil moisture, and concentrations of reactants in these chemical pathways both contributing to net processes.
In the Canadian prairies, gross N2O production is positively correlated with soil moisture, with the highest emissions associated with lower-slope and wetland soils. This is consistent with the major contributing process in N2O emissions being denitrification, the process that reduces NO3- under anaerobic conditions. However, nitrification, the production of NO3- from NH4+, has also been observed to contribute to N2O emissions, especially from drier and aerobic soils.
Simple measurements of NO3- and NH4+ concentrations in soils will not capture information about the processes cycling N between these and other pools of soil matter. Used in conjunction with measurements of those processes, such as the 15N technique used here, does provide information about the factors controlling those processes. In this case, little variation through time or space in either pool combined with patterned variation in N2O emission and 15N movements allowed these authors to infer that both nitrification and denitrification are not limited by the substrate pools, despite the quite different other aspects of these processes.
This paper provides a very detailed description of the 15N procedures used, as well as a clear discussion of the various N-cycling processes in soils.
Tuesday, January 19, 2010
Zuur et al. 2010
Zuur AF, Ieno EN, Elphick CS. 2010. A protocol for data exploration to avoid common statistical problems. Methods in Ecology & Evolution doi: 10.1111/j.2041-210X.2009.00001.x
These authors present a step-by-step guide and recommendations for data exploration, a procedure in analysis of statistical data that should be carried out before primary statistical techniques such as regression. The point of data exploration is to look for errors in measurement, calculation or data-entry, to remove outliers, and to ensure no critical assumptions are being violated. Data exploration is not an instantaneous process, and may take up to 50% of the time spent on data analysis.
Their Figure 1 shows the steps in data exploration. Not all steps need be conducted for every dataset, for example, PCA is not sensitive to normal distribution, so the construction of histograms to evaluate normality is not necessary. On the other hand, almost all statistical techniques are very sensitive to violations of the assumption of independence.
(To avoid potential copyright issues, I have not pasted Fig. 1 from the paper here)
Figure 1 from Zuur et al. (2010). The procedures in italics are described in detail in this paper.
This paper was assigned reading for a course I am taking, Plant Sciences 813, Statistical Methods in the Life Sciences. I think the advice and instructions here will be useful.
These authors present a step-by-step guide and recommendations for data exploration, a procedure in analysis of statistical data that should be carried out before primary statistical techniques such as regression. The point of data exploration is to look for errors in measurement, calculation or data-entry, to remove outliers, and to ensure no critical assumptions are being violated. Data exploration is not an instantaneous process, and may take up to 50% of the time spent on data analysis.
Their Figure 1 shows the steps in data exploration. Not all steps need be conducted for every dataset, for example, PCA is not sensitive to normal distribution, so the construction of histograms to evaluate normality is not necessary. On the other hand, almost all statistical techniques are very sensitive to violations of the assumption of independence.
(To avoid potential copyright issues, I have not pasted Fig. 1 from the paper here)
Figure 1 from Zuur et al. (2010). The procedures in italics are described in detail in this paper.
This paper was assigned reading for a course I am taking, Plant Sciences 813, Statistical Methods in the Life Sciences. I think the advice and instructions here will be useful.
Friday, January 15, 2010
Michalyna 1971
Michalyna W. 1971. Distribution of various forms of aluminum, iron and manganese in the orthic gray wooded, gleyed orthic gray wooded and related gleysolic soils in Manitoba. Canadian Journal of Soil Science 51: 23-36.
This author examined soil Al, Fe, and Mn in some poorly drained soils of the Gleysolic order in western Manitoba, looking for indicators for soil classification that would cover some of the deficiencies of the previous criteria. The distribution of these metals, including the ratio of oxalate-extractable to dithionite-extractable iron representing amorphous and total Fe(III)-oxide forms, respectively, was a useful criterion for classification.
Iron of all types was concentrated in the upper horizons of these soils, with the highest levels in the BA and B horizons. The ratio of amorphous to total Fe(III) was also highest in these horizons, and declined with depth. This suggests amorphous Fe(III) is most abundant in relatively oxidizing conditions in these wet soils. Water content is not reported, except to note that some soils are “imperfectly drained”, others are “poorly drained”.
The ratio of amorphous to total Fe(III) found in these soils ranged from about 0.1 to about 1.2, with most measurements between 0.4 and 0.8. My own measurements, converted to the same ratio, range between 0.14 and 0.83.
This author examined soil Al, Fe, and Mn in some poorly drained soils of the Gleysolic order in western Manitoba, looking for indicators for soil classification that would cover some of the deficiencies of the previous criteria. The distribution of these metals, including the ratio of oxalate-extractable to dithionite-extractable iron representing amorphous and total Fe(III)-oxide forms, respectively, was a useful criterion for classification.
Iron of all types was concentrated in the upper horizons of these soils, with the highest levels in the BA and B horizons. The ratio of amorphous to total Fe(III) was also highest in these horizons, and declined with depth. This suggests amorphous Fe(III) is most abundant in relatively oxidizing conditions in these wet soils. Water content is not reported, except to note that some soils are “imperfectly drained”, others are “poorly drained”.
The ratio of amorphous to total Fe(III) found in these soils ranged from about 0.1 to about 1.2, with most measurements between 0.4 and 0.8. My own measurements, converted to the same ratio, range between 0.14 and 0.83.
Howarth 1979
Howarth RW. 1979. Pyrite: Its rapid formation in a salt marsh and its importance in ecosystem metabolism. Science 203: 49-51.
This author investigated sulfur and iron dynamics in a salt marsh in the United States. Previous work by other authors had suggested pyrite (FeS2), one end-product in sulfur reduction, forms slowly over years or decades in marine sediments. This paper includes an experiment involving buried Teflon bags in which pyrite formation was detected after 48 hours. From this and other measurements, an estimate of total marshland bacterial sulfur-driven respiration was formed that is of a similar magnitude in CO2 release as is total net productivity of the marshland.
Iron metabolism in this system involves formation of amorphous iron compounds under oxidizing conditions, with a predominance of crystalline forms only under more reducing conditions.
This author investigated sulfur and iron dynamics in a salt marsh in the United States. Previous work by other authors had suggested pyrite (FeS2), one end-product in sulfur reduction, forms slowly over years or decades in marine sediments. This paper includes an experiment involving buried Teflon bags in which pyrite formation was detected after 48 hours. From this and other measurements, an estimate of total marshland bacterial sulfur-driven respiration was formed that is of a similar magnitude in CO2 release as is total net productivity of the marshland.
Iron metabolism in this system involves formation of amorphous iron compounds under oxidizing conditions, with a predominance of crystalline forms only under more reducing conditions.
Thursday, January 14, 2010
Soulides and Allison 1961
Soulides DA, Allison FE. 1961. Effect of drying and freezing soils on carbon dioxide production, available mineral nutrients, aggregation, and bacterial population. Soil Science 91: 291-298.
These authors conducted a series of experiments to investigate previously reported claims of a burst of CO2 production following drying or freezing of soils, with an associated change in soil bacterial populations. Drying soils killed large fractions of bacterial populations; freezing as well, to a lesser extent. Combined drying and freezing killed many bacteria, but did not sterilize soils. CO2 production was raised 20 to 40% over controls following drying and rewetting under different schemes, which these authors attribute to rapid breakdown of organic material by large numbers of bacterial cells in an early growth phase; CO2 production declines as populations stabilize.
I was hoping this paper would provide clues to the soil water levels tolerable by bacteria, but these authors do not discuss critical levels of moisture or temperature, beyond noting that severe drying is detrimental, and temperatures below 2ºC prevent most bacterial growth.
These authors conducted a series of experiments to investigate previously reported claims of a burst of CO2 production following drying or freezing of soils, with an associated change in soil bacterial populations. Drying soils killed large fractions of bacterial populations; freezing as well, to a lesser extent. Combined drying and freezing killed many bacteria, but did not sterilize soils. CO2 production was raised 20 to 40% over controls following drying and rewetting under different schemes, which these authors attribute to rapid breakdown of organic material by large numbers of bacterial cells in an early growth phase; CO2 production declines as populations stabilize.
I was hoping this paper would provide clues to the soil water levels tolerable by bacteria, but these authors do not discuss critical levels of moisture or temperature, beyond noting that severe drying is detrimental, and temperatures below 2ºC prevent most bacterial growth.
Wednesday, January 13, 2010
Clément et al. 2005
Clément J-C, Shrestha J, Ehrenfeld JG, Jaffe PR. 2005. Ammonium oxidation coupled to dissimilatory reduction of iron under anaerobic conditions in wetland soils. Soil Biology and Biochemistry 37: 2323-2328.
These authors observed an unexpected chemical reaction involving the accumulation of both nitrite (NO2-) and ferrous iron (Fe(II)) under anaerobic conditions. They investigated this phenomenon further, and propose a chemical reaction in wet soils in which ammonium is oxidized under reducing conditions by transferring electrons to Fe(III), generating NO2- and Fe(II).
Nitrite does not usually accumulate in soils. These authors suggest that under normal conditions, it is consumed at least as fast as it is produced, but their experimental conditions included inhibition of denitrification, allowing nitrite to build up to detectable levels. Other oxidizers besides Fe(III), such as Mn(IV), were not detected in soil samples and were not included in the experiment.
The proposed chemical pathway is thermodynamically feasible at pH 7, though it appears to rely on goethite as the ferric iron source; from my understanding of dissimilatory iron reduction (e.g. Lovley 1991), I would expect strongly crystalline forms of iron oxide such as goethite to be highly resistant to such destructive forces, and the iron source in the systems (natural and experimental) described here to be amorphous ferric oxides instead. But the underlying chemistry appears plausible to me.
One unexpected aspect of this short communication was the authors’ use of a Dionex ion chromatography system, apparently very similar to the device I will be using to analyze root exudates. Additionally, this paper discusses the “ferrous wheel”, a memorable name for chemical cycling of iron between valencies, as an established hypothesis; I need to track down the origins of this term and learn its importance regarding my own attempts to relate measured Fe(III) contents to redox conditions.
These authors observed an unexpected chemical reaction involving the accumulation of both nitrite (NO2-) and ferrous iron (Fe(II)) under anaerobic conditions. They investigated this phenomenon further, and propose a chemical reaction in wet soils in which ammonium is oxidized under reducing conditions by transferring electrons to Fe(III), generating NO2- and Fe(II).
Nitrite does not usually accumulate in soils. These authors suggest that under normal conditions, it is consumed at least as fast as it is produced, but their experimental conditions included inhibition of denitrification, allowing nitrite to build up to detectable levels. Other oxidizers besides Fe(III), such as Mn(IV), were not detected in soil samples and were not included in the experiment.
The proposed chemical pathway is thermodynamically feasible at pH 7, though it appears to rely on goethite as the ferric iron source; from my understanding of dissimilatory iron reduction (e.g. Lovley 1991), I would expect strongly crystalline forms of iron oxide such as goethite to be highly resistant to such destructive forces, and the iron source in the systems (natural and experimental) described here to be amorphous ferric oxides instead. But the underlying chemistry appears plausible to me.
One unexpected aspect of this short communication was the authors’ use of a Dionex ion chromatography system, apparently very similar to the device I will be using to analyze root exudates. Additionally, this paper discusses the “ferrous wheel”, a memorable name for chemical cycling of iron between valencies, as an established hypothesis; I need to track down the origins of this term and learn its importance regarding my own attempts to relate measured Fe(III) contents to redox conditions.
Tuesday, January 12, 2010
Lovley 1991
Lovley DR. 1991. Dissimilatory Fe(III) and Mn(IV) reduction. Microbiological Reviews 55: 259-287.
This author comprehensively reviews microbe-mediated reduction of iron and manganese in soils and sediments, in a long and detailed paper. Dissimilatory reduction is distinct from assimilatory reduction, in which metal ions are reduced when they are incorporated into cellular macromolecules such as enzymes and cofactors. Dissimilatory reduction is a process that ends with the accumulation of reduced metal outside the cell, and is responsible for the majority of iron and manganese reduction in sediments. While it has been observed in aerobic environments, such reduction occurs mainly in anaerobic conditions. Fe(III) in particular is most often reduced when it is the final electron acceptor in the anaerobic oxidation of organic molecules.
Microbes capable of dissimilatory metal reduction can be categorized in a number of ways. This author presents 5 categories, though I think there is considerable overlap between them, as in cases where one cell is able to reduce Fe(III) and metabolize a range of carbon sources. In the first category, reducing fermenting bacteria, the amount of Fe(III) reduced during metabolism is far less than the stoichiometry of the redox couple would suggest. This implies that Fe(III) is a minor electron acceptor during fermentation reactions, rather than the electron acceptor of choice or necessity for these organisms. Sulfur-oxidizing species in contrast do appear to reduce quantities of iron in line with stoichiometric predictions, but do not seem to gain significant energy from these reactions which occur under aerobic conditions on elemental sulfur. Hydrogen-oxidizing reducers appear to be abundant in anaerobic sediments, and seem to have high affinity for hydrogen gas; where Fe(III) is being reduced, hydrogen concentrations are low, and when hydrogen is added, Fe(III) reduction increases. These organisms need other material, such as simple organic molecules, to grow, as this reaction provides energy but little else. Organic-acid oxidizing reducers and aromatic-oxidizers are probably in many cases the same cells. As these molecules are sometimes the result of fermentation metabolisms, one possible food chain in anaerobic environments is fermentation, with some Fe(III) reduction, followed by greater levels of Fe(III) reduction linked to the decomposition of smaller organic molecules such as acetate. Such an ecological pairing is probably widespread, given the known abundance and diversity of fermenting species and the probable abundance of more aggressively iron-reducing species, many of which are probably Archaea rather than Bacteria.
There are three competing models for how Fe(III) is reduced in natural environments. The first is the enzymatic model, in which microbial cells employ membrane-bound or intracellular enzymes to transfer electrons to Fe(III) ions during the process of anaerobic oxidation of organic matter. The second is termed the redox model, and posits the majority of Fe(III) reduction is driven by equilibrium thermodynamics, with the relative levels of Fe(III) and Fe(II) in sediments controlled by abiotic factors such as temperature and pH. The third model is termed the direct-reduction model, in which some organic molecules react directly with Fe(III), without the intervention of cells or enzymes.
At first glance, the observation that Fe(III) reduction rates fall when microbes are removed from sediments supports the enzymatic model, but in fact all three models rely on microbial metabolisms. In the redox model, competing electron acceptors such as oxygen and nitrate are consumed by microbes, lowering their concentrations to levels too low to influence the transitions between Fe(III) and Fe(II). And the direct model relies on microbes releasing key organic molecules known to reduce Fe(III) in vitro. However, several other lines of evidence, such as the lack of spontaneous shifts in iron valency ratios in stored sediments, the large changes in pH associated with widely-used extraction methods, and the general rarity of rapidly-acting direct-reducing molecules all lead to the conclusion that while the other mechanisms may contribute some iron reducing activity in some situations, the overwhelming majority of Fe(III) reduction to Fe(II) occurring is driven by microbes and their enzymes.
This author spends nearly as much time discussing Mn(IV) reduction as Fe(III) reduction, but I have little interest in Mn chemistry at this time. However, in the discussion of the competing models of metal reduction, mention is made that Fe(II) in solution may reduce Mn(IV), removing accumulated Fe(II) from iron reduction and abiotically returning the iron to Fe(III) while generating Mn(II). This abiotic back-reaction closes the loop on cycling Fe(III).
Iron reduction is postulated as one of the first, if not the first, globally important metabolic pathway, with early Archaea using Fe(III) as their final electron acceptor in a generally reducing environment lacking free oxygen and nitrate. If Fe(III), a non-soluble, precipitating substance is the primary oxidizing agent, the redox environment of the Earth 2 billion years ago was upside-down compared to today: the surface and atmosphere was reducing, while buried and water-saturated sediments were oxidizing.
Freshwater swamps differ from aquatic and marine sediments in a number of ways, including a generally high organic content and plenty of sulfates. Under these conditions, both iron and manganese may cycle rapidly between reduced and oxidized forms, further reinforcing the idea that iron may cycle in a closed or nearly-closed loop between Fe(III) and Fe(II) in wet soils. Soils that periodically dry and become oxic, such as rice paddies, may also employ molecular oxygen in this cycling, with the formation of amorphous Fe(III) oxides during the dry season, and reduction of this iron during the wet season. These reactions would restrict methane production, at least during the early part of the wet season, because Fe(III) reduction diverts electrons away from methane production.
The physical structure of iron oxides in the environment has a large effect on rates of Fe(III) reduction and populations of microbes. More strongly crystalline forms, such as goethite and hematite, are not readily reduced, while amorphous forms are consumed rapidly. Presumably it is amorphous forms that accumulate when Fe(II) is oxidized to Fe(III) and precipitates from solution as an oxide, leading to a labile pool of iron distinct from the highly resistant pool of crystalline mineral iron.
When it is not back-oxidized rapidly, Fe(II) and Mn(II) accumulate in solution, and are subject to water movements, potentially removing them from the site of production. Dissolved, reduced metal can be problematic, as these ions are readily oxidized by atmospheric oxygen if water flows contact the atmosphere, and will precipitate as rusty powder in drinking water and irrigation infrastructure. This also suggests that Fe(II) will not accumulate in natural systems over long periods, and that measuring the amount of Fe(II) in a sample is not a good indicator of iron-reducing microbial populations outside of microcosm experiments.
Iron oxides tend to provide strong adsorption surfaces for many other substances, including phosphate and heavy metals. The release to solution and movement of these substances can be a major concern when iron oxides are reduced.
Banded iron formations in some sediments and rocks, in which magnetite is deposited, appear to be the result of dissimilatory iron reduction. Magnetite is a mixed-valence iron oxide that behaves magnetically; small, characteristically-shaped crystals of it are produced intracellularly by magnetotactic bacteria, but much larger amounts are produced by a range of iron-reducing bacteria. The associated organic matter, masses and crystal structures of banded iron formations strongly suggest ancient dissimilatory iron reduction coupled to the decomposition of organic matter.
There are a range of factors controlling iron and manganese reduction in natural environments. Metal reduction is decreased in the presence of alternate electron acceptors, especially oxygen and nitrate. Oxygen is a thermodynamically favourable electron acceptor compared to either Fe(III) or Mn(IV), and nitrate appears to inhibit Fe(III) reduction by lowering electron availability below necessary levels. From a biological perspective, aerobic bacteria can usually outcompete iron reducers, many of whom are obligate anaerobes and are killed or inhibited by the presence of oxygen.
As previously described, the form of metal available in the environment also has a major effect on metal reduction rates, with more strongly crystalline forms most resistant to chemical alteration by microorganisms. “Poorly-crystalline” forms, presumably including amorphous metal oxides, are the major source of oxidized metals for reducing cells. Thus, extraction and measurement procedures that involve only the least crystalline forms of Fe(III) oxides are a good measure of the iron available for reduction by microbes. The widely-used oxalate extraction method normally does not extract significant quantities of Fe(III) oxides bound in strongly crystalline forms, except when “catalytic quantities” of Fe(II) are also available, as when weakly crystalline mixed-valence minerals such as magnetite are present. In such systems, oxalate extraction will gather a larger fraction of the total dithionate-citrate extractable iron, even though much of the iron so extracted will be in a form not actually available to soil microbes.
This paper is an enormous review of iron metabolisms in soils and sediments. It did not actually answer my current question, about the cycling of Fe(III) in soils and how comparisons of amorphous (oxalate-extractable) and total (dithionate-extractable) can be used to support inferences about long-term redox status in soils. However, I do think I now have a better grasp of general soil iron and manganese conditions and chemical transformations.
This author comprehensively reviews microbe-mediated reduction of iron and manganese in soils and sediments, in a long and detailed paper. Dissimilatory reduction is distinct from assimilatory reduction, in which metal ions are reduced when they are incorporated into cellular macromolecules such as enzymes and cofactors. Dissimilatory reduction is a process that ends with the accumulation of reduced metal outside the cell, and is responsible for the majority of iron and manganese reduction in sediments. While it has been observed in aerobic environments, such reduction occurs mainly in anaerobic conditions. Fe(III) in particular is most often reduced when it is the final electron acceptor in the anaerobic oxidation of organic molecules.
Microbes capable of dissimilatory metal reduction can be categorized in a number of ways. This author presents 5 categories, though I think there is considerable overlap between them, as in cases where one cell is able to reduce Fe(III) and metabolize a range of carbon sources. In the first category, reducing fermenting bacteria, the amount of Fe(III) reduced during metabolism is far less than the stoichiometry of the redox couple would suggest. This implies that Fe(III) is a minor electron acceptor during fermentation reactions, rather than the electron acceptor of choice or necessity for these organisms. Sulfur-oxidizing species in contrast do appear to reduce quantities of iron in line with stoichiometric predictions, but do not seem to gain significant energy from these reactions which occur under aerobic conditions on elemental sulfur. Hydrogen-oxidizing reducers appear to be abundant in anaerobic sediments, and seem to have high affinity for hydrogen gas; where Fe(III) is being reduced, hydrogen concentrations are low, and when hydrogen is added, Fe(III) reduction increases. These organisms need other material, such as simple organic molecules, to grow, as this reaction provides energy but little else. Organic-acid oxidizing reducers and aromatic-oxidizers are probably in many cases the same cells. As these molecules are sometimes the result of fermentation metabolisms, one possible food chain in anaerobic environments is fermentation, with some Fe(III) reduction, followed by greater levels of Fe(III) reduction linked to the decomposition of smaller organic molecules such as acetate. Such an ecological pairing is probably widespread, given the known abundance and diversity of fermenting species and the probable abundance of more aggressively iron-reducing species, many of which are probably Archaea rather than Bacteria.
There are three competing models for how Fe(III) is reduced in natural environments. The first is the enzymatic model, in which microbial cells employ membrane-bound or intracellular enzymes to transfer electrons to Fe(III) ions during the process of anaerobic oxidation of organic matter. The second is termed the redox model, and posits the majority of Fe(III) reduction is driven by equilibrium thermodynamics, with the relative levels of Fe(III) and Fe(II) in sediments controlled by abiotic factors such as temperature and pH. The third model is termed the direct-reduction model, in which some organic molecules react directly with Fe(III), without the intervention of cells or enzymes.
At first glance, the observation that Fe(III) reduction rates fall when microbes are removed from sediments supports the enzymatic model, but in fact all three models rely on microbial metabolisms. In the redox model, competing electron acceptors such as oxygen and nitrate are consumed by microbes, lowering their concentrations to levels too low to influence the transitions between Fe(III) and Fe(II). And the direct model relies on microbes releasing key organic molecules known to reduce Fe(III) in vitro. However, several other lines of evidence, such as the lack of spontaneous shifts in iron valency ratios in stored sediments, the large changes in pH associated with widely-used extraction methods, and the general rarity of rapidly-acting direct-reducing molecules all lead to the conclusion that while the other mechanisms may contribute some iron reducing activity in some situations, the overwhelming majority of Fe(III) reduction to Fe(II) occurring is driven by microbes and their enzymes.
This author spends nearly as much time discussing Mn(IV) reduction as Fe(III) reduction, but I have little interest in Mn chemistry at this time. However, in the discussion of the competing models of metal reduction, mention is made that Fe(II) in solution may reduce Mn(IV), removing accumulated Fe(II) from iron reduction and abiotically returning the iron to Fe(III) while generating Mn(II). This abiotic back-reaction closes the loop on cycling Fe(III).
Iron reduction is postulated as one of the first, if not the first, globally important metabolic pathway, with early Archaea using Fe(III) as their final electron acceptor in a generally reducing environment lacking free oxygen and nitrate. If Fe(III), a non-soluble, precipitating substance is the primary oxidizing agent, the redox environment of the Earth 2 billion years ago was upside-down compared to today: the surface and atmosphere was reducing, while buried and water-saturated sediments were oxidizing.
Freshwater swamps differ from aquatic and marine sediments in a number of ways, including a generally high organic content and plenty of sulfates. Under these conditions, both iron and manganese may cycle rapidly between reduced and oxidized forms, further reinforcing the idea that iron may cycle in a closed or nearly-closed loop between Fe(III) and Fe(II) in wet soils. Soils that periodically dry and become oxic, such as rice paddies, may also employ molecular oxygen in this cycling, with the formation of amorphous Fe(III) oxides during the dry season, and reduction of this iron during the wet season. These reactions would restrict methane production, at least during the early part of the wet season, because Fe(III) reduction diverts electrons away from methane production.
The physical structure of iron oxides in the environment has a large effect on rates of Fe(III) reduction and populations of microbes. More strongly crystalline forms, such as goethite and hematite, are not readily reduced, while amorphous forms are consumed rapidly. Presumably it is amorphous forms that accumulate when Fe(II) is oxidized to Fe(III) and precipitates from solution as an oxide, leading to a labile pool of iron distinct from the highly resistant pool of crystalline mineral iron.
When it is not back-oxidized rapidly, Fe(II) and Mn(II) accumulate in solution, and are subject to water movements, potentially removing them from the site of production. Dissolved, reduced metal can be problematic, as these ions are readily oxidized by atmospheric oxygen if water flows contact the atmosphere, and will precipitate as rusty powder in drinking water and irrigation infrastructure. This also suggests that Fe(II) will not accumulate in natural systems over long periods, and that measuring the amount of Fe(II) in a sample is not a good indicator of iron-reducing microbial populations outside of microcosm experiments.
Iron oxides tend to provide strong adsorption surfaces for many other substances, including phosphate and heavy metals. The release to solution and movement of these substances can be a major concern when iron oxides are reduced.
Banded iron formations in some sediments and rocks, in which magnetite is deposited, appear to be the result of dissimilatory iron reduction. Magnetite is a mixed-valence iron oxide that behaves magnetically; small, characteristically-shaped crystals of it are produced intracellularly by magnetotactic bacteria, but much larger amounts are produced by a range of iron-reducing bacteria. The associated organic matter, masses and crystal structures of banded iron formations strongly suggest ancient dissimilatory iron reduction coupled to the decomposition of organic matter.
There are a range of factors controlling iron and manganese reduction in natural environments. Metal reduction is decreased in the presence of alternate electron acceptors, especially oxygen and nitrate. Oxygen is a thermodynamically favourable electron acceptor compared to either Fe(III) or Mn(IV), and nitrate appears to inhibit Fe(III) reduction by lowering electron availability below necessary levels. From a biological perspective, aerobic bacteria can usually outcompete iron reducers, many of whom are obligate anaerobes and are killed or inhibited by the presence of oxygen.
As previously described, the form of metal available in the environment also has a major effect on metal reduction rates, with more strongly crystalline forms most resistant to chemical alteration by microorganisms. “Poorly-crystalline” forms, presumably including amorphous metal oxides, are the major source of oxidized metals for reducing cells. Thus, extraction and measurement procedures that involve only the least crystalline forms of Fe(III) oxides are a good measure of the iron available for reduction by microbes. The widely-used oxalate extraction method normally does not extract significant quantities of Fe(III) oxides bound in strongly crystalline forms, except when “catalytic quantities” of Fe(II) are also available, as when weakly crystalline mixed-valence minerals such as magnetite are present. In such systems, oxalate extraction will gather a larger fraction of the total dithionate-citrate extractable iron, even though much of the iron so extracted will be in a form not actually available to soil microbes.
This paper is an enormous review of iron metabolisms in soils and sediments. It did not actually answer my current question, about the cycling of Fe(III) in soils and how comparisons of amorphous (oxalate-extractable) and total (dithionate-extractable) can be used to support inferences about long-term redox status in soils. However, I do think I now have a better grasp of general soil iron and manganese conditions and chemical transformations.
Saturday, January 9, 2010
Liang and Balser 2008
Liang C, Balser TC. 2008. Preferential sequestration of microbial carbon in subsoils of a glacial-landscape toposequence, Dane County, WI, USA. Geoderma 148: 113-119.
These authors examined the microbial communities at a range of depths in soils near the University of Wisconsin, Madison campus. Soil organic carbon includes markers of microbial groups such as amino sugars, molecules that are absent from plants and specific to some groups of soil microorganisms. As markers, these molecules have several advantages; besides their utility in identifying organisms, they are stable in soils, persist after cell depth, and can apparently be extracted and examined using fairly simple laboratory techniques plus access to a gas chromatograph.
This study represents a general survey of soil carbon in this system, an examination of the pools and fates of different carbon molecule classes as well as the contributions of broad groups such as bacteria and fungi to soil physiology in different soil horizons. There were three main conclusions:
1. Upper soil horizons are relatively enriched both in total SOC and amino sugars. The source of this material almost certainly is some combination of surface plant litter and root exudates, not surprisingly supporting a large community of microorganisms in the near-surface soil.
2. Amino sugars accumulate in subsoils, despite the redox environment (presumably somewhat negative) associated with the water table.
3. Amino sugars, while useful, are not sufficient on their own to elucidate mechanisms of SOC turnover and sequestration by soil microbes. Variability between sites and between horizons suggests a major role of both history and site-specific factors in structuring communities at a level distinguishable by ratios of various amino sugars.
This paper is one of a handful I have that explicitly examine microbial communities and variation by depth. However, as this paper describes what I think is a first-look at a soil microbiological system, it lacks some detail and strong conclusions. Amino sugars may be useful in my own research, though I think our lab has more familiarity with other techniques useful for examining interactions between soil bacteria and fungi.
Beyond my current research, this paper is clearly written, not too long, and presents a set of well-described investigations built on a solid foundation of general theory. This suggests it may be useful as a teaching tool, perhaps as a paper a 2nd-year undergraduate would have the skills and knowledge to understand.
These authors examined the microbial communities at a range of depths in soils near the University of Wisconsin, Madison campus. Soil organic carbon includes markers of microbial groups such as amino sugars, molecules that are absent from plants and specific to some groups of soil microorganisms. As markers, these molecules have several advantages; besides their utility in identifying organisms, they are stable in soils, persist after cell depth, and can apparently be extracted and examined using fairly simple laboratory techniques plus access to a gas chromatograph.
This study represents a general survey of soil carbon in this system, an examination of the pools and fates of different carbon molecule classes as well as the contributions of broad groups such as bacteria and fungi to soil physiology in different soil horizons. There were three main conclusions:
1. Upper soil horizons are relatively enriched both in total SOC and amino sugars. The source of this material almost certainly is some combination of surface plant litter and root exudates, not surprisingly supporting a large community of microorganisms in the near-surface soil.
2. Amino sugars accumulate in subsoils, despite the redox environment (presumably somewhat negative) associated with the water table.
3. Amino sugars, while useful, are not sufficient on their own to elucidate mechanisms of SOC turnover and sequestration by soil microbes. Variability between sites and between horizons suggests a major role of both history and site-specific factors in structuring communities at a level distinguishable by ratios of various amino sugars.
This paper is one of a handful I have that explicitly examine microbial communities and variation by depth. However, as this paper describes what I think is a first-look at a soil microbiological system, it lacks some detail and strong conclusions. Amino sugars may be useful in my own research, though I think our lab has more familiarity with other techniques useful for examining interactions between soil bacteria and fungi.
Beyond my current research, this paper is clearly written, not too long, and presents a set of well-described investigations built on a solid foundation of general theory. This suggests it may be useful as a teaching tool, perhaps as a paper a 2nd-year undergraduate would have the skills and knowledge to understand.
Wagner et al. 2009
Wagner D, Kobabe S, Liebner S. 2009. Bacterial community structure and carbon turnover in permafrost-affected soils of the Lena Delta, northeastern Siberia. Canadian Journal of Microbiology 55: 73-83.
These authors examined the microbial communities at two depth bands (near-surface and near-permafrost) in low-centred tundra polygons at the vast permafrost wetland of the delta of the Lena River. The delta covers more than 60 000 km^2, and much of it appears to be a reserve or national park of Russia. The CAVM (Walker et al. 2002) describes most of the delta as vegetation type W2, sedge, moss, dwarf-shrub wetland, and satellite images from Google maps shows very extensive lake and pond coverage of the landscape. In short, it’s pretty wet, and generally cold.
The general finding of this paper is that while near-surface communities include a wide diversity of aerobic and facultatively-anaerobic bacteria, the deeper, colder, anaerobic portions of the soil contain almost no aerobes, and are instead dominated by “fermenting” species capable of decomposing recalcitrant organic carbon molecules under negative-redox conditions. There is a sharp temperature gradient, which combined with the poorer quality of carbon, the lack of oxygen and negative redox conditions, and the general water saturation at depth creates conditions near the permafrost suitable only for the slow microbial metabolisms. None of this is particularly surprising, but the observation of decreased biodiversity with water saturation does suggest the worrying possibility that increased water in this system, driven by melting permafrost and climate change (particularly upstream in the long and North-flowing Lena) could drive these microbial communities to lose some “physiological skills” such as the ability to oxidize methane, a metabolic pathway possessed only by some aerobic prokaryotes.
This paper is quite important to my own work, I think. Besides emphasizing the role of water content in structuring soil chemical and especially biological conditions, the description of the methods used to measure microbial biodiversity should be useful. However, while the BIOLOG plates seem interesting, the results of this technique are not at all well explained in this paper. I do not know what is indicated by the relationship shown in Figure 3, for example, of changes in colour development associated with carbon turnover of various categories of organic substrates. Several of the figures are simple plots of principal component analysis (PCA), literally just PC1 vs. PC2 with some outlines drawn around some clusters. I’m sure there is more of interest in this paper besides the coarse outline of biodiversity differences in communities, but without a more thorough explanation of the nearly-raw data I cannot see it.
These authors examined the microbial communities at two depth bands (near-surface and near-permafrost) in low-centred tundra polygons at the vast permafrost wetland of the delta of the Lena River. The delta covers more than 60 000 km^2, and much of it appears to be a reserve or national park of Russia. The CAVM (Walker et al. 2002) describes most of the delta as vegetation type W2, sedge, moss, dwarf-shrub wetland, and satellite images from Google maps shows very extensive lake and pond coverage of the landscape. In short, it’s pretty wet, and generally cold.
The general finding of this paper is that while near-surface communities include a wide diversity of aerobic and facultatively-anaerobic bacteria, the deeper, colder, anaerobic portions of the soil contain almost no aerobes, and are instead dominated by “fermenting” species capable of decomposing recalcitrant organic carbon molecules under negative-redox conditions. There is a sharp temperature gradient, which combined with the poorer quality of carbon, the lack of oxygen and negative redox conditions, and the general water saturation at depth creates conditions near the permafrost suitable only for the slow microbial metabolisms. None of this is particularly surprising, but the observation of decreased biodiversity with water saturation does suggest the worrying possibility that increased water in this system, driven by melting permafrost and climate change (particularly upstream in the long and North-flowing Lena) could drive these microbial communities to lose some “physiological skills” such as the ability to oxidize methane, a metabolic pathway possessed only by some aerobic prokaryotes.
This paper is quite important to my own work, I think. Besides emphasizing the role of water content in structuring soil chemical and especially biological conditions, the description of the methods used to measure microbial biodiversity should be useful. However, while the BIOLOG plates seem interesting, the results of this technique are not at all well explained in this paper. I do not know what is indicated by the relationship shown in Figure 3, for example, of changes in colour development associated with carbon turnover of various categories of organic substrates. Several of the figures are simple plots of principal component analysis (PCA), literally just PC1 vs. PC2 with some outlines drawn around some clusters. I’m sure there is more of interest in this paper besides the coarse outline of biodiversity differences in communities, but without a more thorough explanation of the nearly-raw data I cannot see it.
Friday, January 8, 2010
Lovley and Phillips 1986
Lovley DR, Phillips EJP. 1986. Organic matter mineralization with reduction of ferric iron in anaerobic sediments. Applied and Environmental Microbiology 51: 683-689.
These authors examined the reduction of iron, both supplemented and already present, in sediments collected from the bottom of the Potomac river across a salinity gradient from freshwater to brackish estuarine. A previous hypothesis in the literature suggested that observed decreases in methane production in the presence of trivalent iron, Fe(III) were caused by Fe(III) being toxic to methanogenic prokaryotes. This hypothesis was disproved in this study, and the results of this study suggest instead that methanogens are outcompeted by iron-reducing species because of the greater thermodynamic benefits of Fe(III) reduction compared to methane production. Van Bodegom et al. (2004) reported instead that rather than competition, Fe(III) directly inhibits methanogenesis, though I think this is due to metabolic switching within individual cells, not interactions between distinct methanogenic and iron-reducing populations.
The other major finding of this paper is that the form of the Fe(III) in the environment has a major effect on Fe(III) reduction. Amorphous ferric oxyhydroxides are reduced much more readily than are crystalline forms. These authors do not speculate on the mechanism underlying this difference, though I suspect surface area exerts a major controlling influence.
These authors did not measure Fe(III) forms in native sediments, rather they added amorphous Fe(III) and measured Fe(II) after incubation. Thus, while my own studies of the ratios of amorphous to crystalline Fe(III) are not assisted by these techniques, these authors do provide a clear and apparently fairly simple protocol for the measurement of Fe(II), involving extraction by HCl and reaction with a molecule that turns purple when complexed with Fe(II) allowing measurement of Fe(II) amounts from the absorbance spectrum of the resulting solution. I need to learn more about Fe(III) biogeochemistry before deciding to pursue such an analysis; I suspect one fate of Fe(III) is to cycle through an organism and be returned to the oxidized state, rather than shuttling directly from Fe(III) to Fe(II).
These authors examined the reduction of iron, both supplemented and already present, in sediments collected from the bottom of the Potomac river across a salinity gradient from freshwater to brackish estuarine. A previous hypothesis in the literature suggested that observed decreases in methane production in the presence of trivalent iron, Fe(III) were caused by Fe(III) being toxic to methanogenic prokaryotes. This hypothesis was disproved in this study, and the results of this study suggest instead that methanogens are outcompeted by iron-reducing species because of the greater thermodynamic benefits of Fe(III) reduction compared to methane production. Van Bodegom et al. (2004) reported instead that rather than competition, Fe(III) directly inhibits methanogenesis, though I think this is due to metabolic switching within individual cells, not interactions between distinct methanogenic and iron-reducing populations.
The other major finding of this paper is that the form of the Fe(III) in the environment has a major effect on Fe(III) reduction. Amorphous ferric oxyhydroxides are reduced much more readily than are crystalline forms. These authors do not speculate on the mechanism underlying this difference, though I suspect surface area exerts a major controlling influence.
These authors did not measure Fe(III) forms in native sediments, rather they added amorphous Fe(III) and measured Fe(II) after incubation. Thus, while my own studies of the ratios of amorphous to crystalline Fe(III) are not assisted by these techniques, these authors do provide a clear and apparently fairly simple protocol for the measurement of Fe(II), involving extraction by HCl and reaction with a molecule that turns purple when complexed with Fe(II) allowing measurement of Fe(II) amounts from the absorbance spectrum of the resulting solution. I need to learn more about Fe(III) biogeochemistry before deciding to pursue such an analysis; I suspect one fate of Fe(III) is to cycle through an organism and be returned to the oxidized state, rather than shuttling directly from Fe(III) to Fe(II).
Wednesday, January 6, 2010
Siciliano et al. 2009
Siciliano SD, Ma WK, Ferguson S, Farrell RE. 2009. Nitrifier dominance of Arctic soil nitrous oxide emissions arises to due fungal competition with denitrifiers for nitrate. Soil Biology and Biochemistry 41: 1104-1110.
These authors examined the nitrous oxide emissions, microbial communities, and some components of nitrogen cycling in soils from three landforms at Truelove Lowland, on Devon Island. Previous results (Ma et al. 2007) had indicated that Arctic nitrous oxide emissions are not sensitive to soil moisture, at least in the range of 50% to saturated water filled pore space. This study includes a series of incubations of soil samples at a range of temperatures similar to ambient conditions, and treatments to disrupt fungi or particular types of prokaryotes.
Large differences in community composition were found between the three landforms, with the highest biomass and fungi:bacteria ratio in the wet sedge meadow and lowest in the raised beach crest (the lower foreslope was intermediate by these measures). Competition between fungi and denitrifiers for soil nitrate pools was inferred as the mechanism allowing dominance of emitted N2O by nitrifiers; fungi and denitrifiers are busy scavenging every available electron acceptor starting with nitrate and running all the way down to N2 gas, so almost any N2O that escapes was generated by nitrifiers in conditions not favoured by either of the other major groups.
This paper serves to demonstrate the very complex nature of soil biology, especially regarding the multiple and interacting pathways that may produce or consume materials of interest such as N2O. The references in this paper should be useful for digging into this complexity.
These authors examined the nitrous oxide emissions, microbial communities, and some components of nitrogen cycling in soils from three landforms at Truelove Lowland, on Devon Island. Previous results (Ma et al. 2007) had indicated that Arctic nitrous oxide emissions are not sensitive to soil moisture, at least in the range of 50% to saturated water filled pore space. This study includes a series of incubations of soil samples at a range of temperatures similar to ambient conditions, and treatments to disrupt fungi or particular types of prokaryotes.
Large differences in community composition were found between the three landforms, with the highest biomass and fungi:bacteria ratio in the wet sedge meadow and lowest in the raised beach crest (the lower foreslope was intermediate by these measures). Competition between fungi and denitrifiers for soil nitrate pools was inferred as the mechanism allowing dominance of emitted N2O by nitrifiers; fungi and denitrifiers are busy scavenging every available electron acceptor starting with nitrate and running all the way down to N2 gas, so almost any N2O that escapes was generated by nitrifiers in conditions not favoured by either of the other major groups.
This paper serves to demonstrate the very complex nature of soil biology, especially regarding the multiple and interacting pathways that may produce or consume materials of interest such as N2O. The references in this paper should be useful for digging into this complexity.
Tuesday, January 5, 2010
Elberling 2007
Elberling B. 2007. Annual soil CO2 effluxes in the High Arctic: the role of snow thickness and vegetation type. Soil Biology and Biochemistry 39: 646-654.
This author studied the total annual efflux of CO2 at three vegetation communities in Endalen valley on Svalbard. The three communities are each dominated by one characteristic species of plant, and are named accordingly: Dryas, Cassiope, and Salix, and from the description of the sites and their environmental parameters, there appears to be high agreement between these communities and those found at Alexandra Fjord, Ellesmere Island.
The depth and duration of snow cover was a major factor controlling (directly and indirectly) soil conditions and thus respiration. Snow depth varied with vegetation type, though the causal relationship is probably snow to plants, via soil temperature (more snow = higher winter temperatures) and soil moisture content (snow accumulates at and melts into depressions and certain slope positions). Higher temperatures and wetter conditions correlated with higher soil respiration, both in winter and summer. All sites experienced a brief period of water saturation in the upper 5cm of the soil during spring thaw, though sites varied in when thaw happened, with Dryas first and Salix last, corresponding with winter snow cover depth.
Soil conditions among the sites seem to have been broadly similar; not surprising considering the close proximity of sites and the consistent soil type across the valley, though soil under Cassiope tetragonal patches was more acidic. This acidity seems related to a reduced concentration of base cations (especially Ca2+ and K+) under Cassiope plants.
Summer water content did not correlate with annual CO2 flux, which this author attributes to the generally well-drained soils, a lack of large precipitation events, and long periods without rain leading to typically dry soils everywhere, though soil respiration at the Dryas site may have been water-limited, as this was the driest site.
Winter temperatures in the soil averaged warmer than -10ºC at all sites, warm enough for microbial activity. A burst of CO2 during spring thaw was not predicted from soil parameters, but was attributed to increasing microbial activity associated with warming temperatures and the release of high-quality organic material from winter-killed microbial cells. Winter CO2 efflux averages were 0.11 to 0.28 µmol / m^2 / s, not far from values we found (for example) at the Cassiope site at Alexandra Fjord.
This paper contains much that is valuable to my current research, including both the data and patterns found and the discussion with other relevant references.
This author studied the total annual efflux of CO2 at three vegetation communities in Endalen valley on Svalbard. The three communities are each dominated by one characteristic species of plant, and are named accordingly: Dryas, Cassiope, and Salix, and from the description of the sites and their environmental parameters, there appears to be high agreement between these communities and those found at Alexandra Fjord, Ellesmere Island.
The depth and duration of snow cover was a major factor controlling (directly and indirectly) soil conditions and thus respiration. Snow depth varied with vegetation type, though the causal relationship is probably snow to plants, via soil temperature (more snow = higher winter temperatures) and soil moisture content (snow accumulates at and melts into depressions and certain slope positions). Higher temperatures and wetter conditions correlated with higher soil respiration, both in winter and summer. All sites experienced a brief period of water saturation in the upper 5cm of the soil during spring thaw, though sites varied in when thaw happened, with Dryas first and Salix last, corresponding with winter snow cover depth.
Soil conditions among the sites seem to have been broadly similar; not surprising considering the close proximity of sites and the consistent soil type across the valley, though soil under Cassiope tetragonal patches was more acidic. This acidity seems related to a reduced concentration of base cations (especially Ca2+ and K+) under Cassiope plants.
Summer water content did not correlate with annual CO2 flux, which this author attributes to the generally well-drained soils, a lack of large precipitation events, and long periods without rain leading to typically dry soils everywhere, though soil respiration at the Dryas site may have been water-limited, as this was the driest site.
Winter temperatures in the soil averaged warmer than -10ºC at all sites, warm enough for microbial activity. A burst of CO2 during spring thaw was not predicted from soil parameters, but was attributed to increasing microbial activity associated with warming temperatures and the release of high-quality organic material from winter-killed microbial cells. Winter CO2 efflux averages were 0.11 to 0.28 µmol / m^2 / s, not far from values we found (for example) at the Cassiope site at Alexandra Fjord.
This paper contains much that is valuable to my current research, including both the data and patterns found and the discussion with other relevant references.
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