Angel RA, Conrad R. 2009. In situ measurement of methane fluxes and analysis of transcribed particulate methane monooxygenase in desert soils. Environmental Microbiology 11: 2598-2610.
These authors examined the methanotroph communities of sub-tropical desert soils in Israel, using both field and lab measurements of methane fluxes and molecular investigation of sampled microbes. Negative surface flux, indicating consumption of atmospheric methane by soil, was found only at an undisturbed site in this study; the 4 other sites were varying degrees of agricultural and did not show clear patterns of consumption of methane at low concentrations. Addition of water, simulating a typical local rainfall event, eliminated methanotroph activity for about 12 hours, then this activity rebounded to well above background for up to 48 hours. This process of apparent short-term community dynamics was not investigated or discussed in much detail by these authors, though I found it one of the most interesting observations.
Methanotrophs were identified in soil samples by the usual suite of molecular biology methods. One set of primers used here is described as also targeting certain clades of amoA, a gene prominent in ammonia oxidation. These primers were successful at amplifying sequences even from soils in which methanotrophic activity had not been detected, suggesting that many or all of the sequences amplified by these primers were not actually methanotroph sequences, but rather sequences from apparently ubiquitous ammonia oxidizing bacteria.
The target gene for methanotrophs encodes a membrane-bound protein involved in transporting methane into the cytoplasm. From the way some primers also targeted amoA, I think perhaps there is a shared ancestry among the pathways for scavenging environmental ammonia and for scavenging environmental methane, though these authors do not delve into that discussion.
This paper was apparently instrumental in structuring the thoughts of my co-author (Dr. Siciliano) regarding how we should structure the manuscripts we are preparing based on the 2009 Alexandra Fjord field season. Up to this paper, we had been considering including both molecular analysis (based mainly on qPCR) and soil-properties (nutrients, root exudates, moisture, trace gases, etc.) in our nascent “Pits & Probes” manuscript. However, this paper demonstrates the considerable volume of work required to achieve a useful molecular dataset, suggesting that we would be better off saving these DNA data for a subsequent study, where they can be described and analyzed at the appropriate level of detail.
Thursday, November 26, 2009
Thursday, November 12, 2009
Wrage et al. 2004
Wrage N, Lauf J, del Prado A, Pinto M, Pietrzak S, Yamulki S, Oenema O, Gebauer G. 2004. Distinguishing sources of N2O in European grasslands by stable isotope analysis. Rapid Communications in Mass Spectrometry 18: 1201-1207.
These authors used the signature ratios of stable isotopes of oxygen and nitrogen in a range of soil chemicals and microbial metabolic pathways to identify the source of N2O produced in grasslands monitored as part of a long-term greenhouse gas international experiment. There are 3 known pathways to N2O production: nitrification, in which N2O is produced as a by-product of ammonium oxidation to nitrate, nitrifier denitrification, in which nitrifying organisms reduce nitrite to dinitrogen gas via N2O, especially under anaerobic conditions, and denitrification, in which nitrate is reduced to dinitrogen gas via N2O by denitrifying organisms.
Previous studies had often used acetylene to inhibit N2O production, but this has been found to be unreliable. In contrast, the stable isotope approach used here was able to detect both N2O production and consumption even when reservoirs of N2O were very low. Nitrification was the most important N-transforming process found in these systems, with most N2O produced probably from reduction pathways.
These authors used the signature ratios of stable isotopes of oxygen and nitrogen in a range of soil chemicals and microbial metabolic pathways to identify the source of N2O produced in grasslands monitored as part of a long-term greenhouse gas international experiment. There are 3 known pathways to N2O production: nitrification, in which N2O is produced as a by-product of ammonium oxidation to nitrate, nitrifier denitrification, in which nitrifying organisms reduce nitrite to dinitrogen gas via N2O, especially under anaerobic conditions, and denitrification, in which nitrate is reduced to dinitrogen gas via N2O by denitrifying organisms.
Previous studies had often used acetylene to inhibit N2O production, but this has been found to be unreliable. In contrast, the stable isotope approach used here was able to detect both N2O production and consumption even when reservoirs of N2O were very low. Nitrification was the most important N-transforming process found in these systems, with most N2O produced probably from reduction pathways.
Tack et al. 2006
Tack FMG, Van Ranst E, Lievens C, Vandeberghe RE. 2006. Soil solution Cd, Cu and Zn concentrations as affected by short-time drying or wetting: the role of hydrous oxides of Fe and Mn. Geoderma 137: 83-89.
These authors examined the effects of short-term changes in redox conditions on the interaction between trace heavy metals and oxides of iron and manganese in agricultural soils of Flanders. The expectation was that two weeks of water-saturated and hence reducing conditions would allow these iron and manganese oxides to dissolve, and then re-precipitate when soils were returned to oxidizing conditions at field capacity or dry conditions. This process of iron and manganese chemistry would dominate redox conditions in soil solution, and dominate the chemistry of trace metals, controlling the solubilities of the trace metals.
Contrary to expectations, short-term wetting and drying cycles did not push the chemistry of trace metals around to a significant degree. The authors state that they cannot distinguish between the competing explanatory hypotheses of very slow transformations of the expected type or that these processes occurred at the expected rates but reverted during the later stages of the incubations of soils at particular moisture levels.
In the conclusion, these authors describe the importance of periods of drying, where soil moisture levels fall far below field capacity. Unlike cycles of saturation and field capacity, dried soil has much higher oxygen levels, and the moisture shortage has important effects on soil microorganisms, and the local redox conditions in microhabitats. Occasional very dry periods have a disproportionate effect on heavy-metal chemistry in soils.
For my purposes, this paper was most useful for the clear description of the methods used to measure iron oxides in soils, from a distinctly geochemistry perspective. These authors clearly state that measurement of soil levels of “amorphous” and “crystalline” Fe(III)-oxides are based on operational definitions, as the measurements are based on not-entirely-specific dissolutions of particular fractions of soil iron with particular solutions. These dissolution methods are widely used, and it was useful to see the limitations of these methods clearly described.
These authors examined the effects of short-term changes in redox conditions on the interaction between trace heavy metals and oxides of iron and manganese in agricultural soils of Flanders. The expectation was that two weeks of water-saturated and hence reducing conditions would allow these iron and manganese oxides to dissolve, and then re-precipitate when soils were returned to oxidizing conditions at field capacity or dry conditions. This process of iron and manganese chemistry would dominate redox conditions in soil solution, and dominate the chemistry of trace metals, controlling the solubilities of the trace metals.
Contrary to expectations, short-term wetting and drying cycles did not push the chemistry of trace metals around to a significant degree. The authors state that they cannot distinguish between the competing explanatory hypotheses of very slow transformations of the expected type or that these processes occurred at the expected rates but reverted during the later stages of the incubations of soils at particular moisture levels.
In the conclusion, these authors describe the importance of periods of drying, where soil moisture levels fall far below field capacity. Unlike cycles of saturation and field capacity, dried soil has much higher oxygen levels, and the moisture shortage has important effects on soil microorganisms, and the local redox conditions in microhabitats. Occasional very dry periods have a disproportionate effect on heavy-metal chemistry in soils.
For my purposes, this paper was most useful for the clear description of the methods used to measure iron oxides in soils, from a distinctly geochemistry perspective. These authors clearly state that measurement of soil levels of “amorphous” and “crystalline” Fe(III)-oxides are based on operational definitions, as the measurements are based on not-entirely-specific dissolutions of particular fractions of soil iron with particular solutions. These dissolution methods are widely used, and it was useful to see the limitations of these methods clearly described.
Nemergut et al. 2007
Nemergut DR, Anderson SP, Cleveland CC, Martin AP, Miller AE, Seimon A, Schmidt SK. 2007. Microbial community succession in an unvegetated, recently deglaciated soil. Microbial Ecology 53: 110-122.
These authors describe the partly-predictable patterns of succession among the soil microbes of a glacial foreland in Peru. Primary succession on new terrain, as found in front of a receding glacier, has been studied to some extent, especially regarding the vegetation. Studies of the microbial communities have been rarer, but the few that have been conducted have suggested that these communities also show predictable patterns of community assembly and turnover associated with soil age. Basic ecological theory has led to the nitrogen paradigm of primary succession in soils: nitrogen is absent from new mineral substrate, thus nitrogen fixing organisms have a competitive advantage and are therefore abundant. The presence of nitrogen fixers is tightly linked to the accumulation of soil nitrogen; hence these organisms may facilitate later successional stages.
The study site in this paper is in Peru, at a glacier that seems to be receding quickly. These authors sampled from 3 transects arranged parallel to the front of the glacier, located adjacent to the glacier on soil less than a year old, 100m away on soil about 4 years old, and 500m away on soil about 20 years old. This area receives very high inputs of pollen, leading to the hypothesis that heterotrophic, nitrogen-fixing organisms may be present, using the pollen as a carbon source but drawing nitrogen from the atmosphere because the C:N ratio of pollen is higher than that of microbial biomass. Surface soil samples were collected, kept at 0C, and analyzed in Colorado. Much of the analyses were detailed phylogenetic examination, including the P-test of Martin (2002); note that he is one of the authors of this paper. OTU and a range of sequence-data fine-tuning techniques were also employed.
Over the study area, autotrophic nitrogen fixers were abundant. The bacteria found were extremely diverse at the highest taxonomic levels, and many sequences identified were not closely related to existing sequences in public databases. Diversity increased rapidly from the youngest soils to the 4-year-old, then plateaued.
One very interesting group of bacteria found are the Comamodaceae; sequences reported in other studies were in many cases derived from glacial or ice-sheet ice. The Comamodaceae found in the youngest soils here may have persisted as viable populations in the glacier; differences between the two closely-examined youngest communities suggest physical and genetic isolation for hundreds to thousands of years, allowing speciation events to accumulate differences.
Other patterns among the sequences identified suggest that the earliest colonizers of new terrain may be cosmopolitan – some of the Comamodaceae sequences, for example, are similar to those derived from a glacier in Nunavut. Later colonizers may be more endemic, and displace the earliest colonizers as soils age. The trophic status of the first colonizers is not clear; these authors did not have a test for definite autotrophs or heterotrophs, as Comamodaceae are known to include both modes. At the macrobiological level, the earliest arrivals on new terrain are typically heterotrophs, insects that feed on deposited organic matter such as wind-blown pollen.
This paper is very useful to me, describing as it does a complete set of analytical procedures for my planned biogeographic / phylogenetic studies, as well as providing data in the form of publicly-accessible sequences and analyzed information on patterns of soil microbial community assembly.
These authors describe the partly-predictable patterns of succession among the soil microbes of a glacial foreland in Peru. Primary succession on new terrain, as found in front of a receding glacier, has been studied to some extent, especially regarding the vegetation. Studies of the microbial communities have been rarer, but the few that have been conducted have suggested that these communities also show predictable patterns of community assembly and turnover associated with soil age. Basic ecological theory has led to the nitrogen paradigm of primary succession in soils: nitrogen is absent from new mineral substrate, thus nitrogen fixing organisms have a competitive advantage and are therefore abundant. The presence of nitrogen fixers is tightly linked to the accumulation of soil nitrogen; hence these organisms may facilitate later successional stages.
The study site in this paper is in Peru, at a glacier that seems to be receding quickly. These authors sampled from 3 transects arranged parallel to the front of the glacier, located adjacent to the glacier on soil less than a year old, 100m away on soil about 4 years old, and 500m away on soil about 20 years old. This area receives very high inputs of pollen, leading to the hypothesis that heterotrophic, nitrogen-fixing organisms may be present, using the pollen as a carbon source but drawing nitrogen from the atmosphere because the C:N ratio of pollen is higher than that of microbial biomass. Surface soil samples were collected, kept at 0C, and analyzed in Colorado. Much of the analyses were detailed phylogenetic examination, including the P-test of Martin (2002); note that he is one of the authors of this paper. OTU and a range of sequence-data fine-tuning techniques were also employed.
Over the study area, autotrophic nitrogen fixers were abundant. The bacteria found were extremely diverse at the highest taxonomic levels, and many sequences identified were not closely related to existing sequences in public databases. Diversity increased rapidly from the youngest soils to the 4-year-old, then plateaued.
One very interesting group of bacteria found are the Comamodaceae; sequences reported in other studies were in many cases derived from glacial or ice-sheet ice. The Comamodaceae found in the youngest soils here may have persisted as viable populations in the glacier; differences between the two closely-examined youngest communities suggest physical and genetic isolation for hundreds to thousands of years, allowing speciation events to accumulate differences.
Other patterns among the sequences identified suggest that the earliest colonizers of new terrain may be cosmopolitan – some of the Comamodaceae sequences, for example, are similar to those derived from a glacier in Nunavut. Later colonizers may be more endemic, and displace the earliest colonizers as soils age. The trophic status of the first colonizers is not clear; these authors did not have a test for definite autotrophs or heterotrophs, as Comamodaceae are known to include both modes. At the macrobiological level, the earliest arrivals on new terrain are typically heterotrophs, insects that feed on deposited organic matter such as wind-blown pollen.
This paper is very useful to me, describing as it does a complete set of analytical procedures for my planned biogeographic / phylogenetic studies, as well as providing data in the form of publicly-accessible sequences and analyzed information on patterns of soil microbial community assembly.
Monday, November 9, 2009
van Bodegom et al. 2004
van Bodegom PM, Scholten JCM, Stams AJM. 2004. Direct inhibition of methanogenesis by ferric iron. FEMS Microbiology Ecology 49: 261-268.
These authors present the novel finding that inhibition of methanogenesis in anaerobic sediments by Fe(III) is a direct effect, and not the result of competition for resources between different species of microbes. They used three pure strains of methanogenic archaea under controlled-atmosphere conditions, and found a clear signal of methanogenesis inhibition related to the amount of Fe(III) added to liquid culture.
This paper raises some issues I need to consider in the methanogenic, anaerobic soils at some of the systems of Alexandra Fjord, especially regarding redox conditions and available electron acceptors. Additionally, this paper provides references for widely-accepted and apparently highly effective methods for measuring Fe(II) and Fe(III) in soil solutions.
These authors present the novel finding that inhibition of methanogenesis in anaerobic sediments by Fe(III) is a direct effect, and not the result of competition for resources between different species of microbes. They used three pure strains of methanogenic archaea under controlled-atmosphere conditions, and found a clear signal of methanogenesis inhibition related to the amount of Fe(III) added to liquid culture.
This paper raises some issues I need to consider in the methanogenic, anaerobic soils at some of the systems of Alexandra Fjord, especially regarding redox conditions and available electron acceptors. Additionally, this paper provides references for widely-accepted and apparently highly effective methods for measuring Fe(II) and Fe(III) in soil solutions.
Lindsay 1991
Lindsay WL. 1991. Iron oxide solubilization by organic matter and its effect on iron availability. Plant and Soil 130: 27-34.
This author reviews the chemistry of bioavailable iron in soil solutions. The major controls on the availability of iron in soil solution, which is normally very low, are pH, redox status, and the presence of organic matter and microsites where organic matter is decomposed by microorganisms under oxygen-limited conditions.
The usual concentration of iron in solution in soils is extremely low, and its exact value suggests contributions from multiple solid iron species, including amorphous and a range of crystalline forms of Fe(III) oxides. Organic matter produces transient small organic acids as it is decomposed, which complex with iron and help to bring it into solution. However, these organic acids are in the middle of the soil organic matter decomposition pathway, and do not persist for long in soils. Bringing more iron into solution relies on a combination of local reducing conditions around respiring roots and among microbe-and-SOM microsites, and local pH. Plants and other organisms secrete compounds that are effective at solubilizing iron and making it available to plants. The other major source of iron for organisms is local fluctuations of reducing and oxidizing conditions, which bring iron into solution and precipitate it as metastable, mixed-valence ferrosic hydroxide, which provides iron to solution at much higher concentrations than most other solid forms of iron.
This paper provides useful background information about the chemistry of iron in soils, but it is not clear to me which forms of iron should be targeted and measured in soils if one wishes to learn something about local aerobic and redox conditions.
This author reviews the chemistry of bioavailable iron in soil solutions. The major controls on the availability of iron in soil solution, which is normally very low, are pH, redox status, and the presence of organic matter and microsites where organic matter is decomposed by microorganisms under oxygen-limited conditions.
The usual concentration of iron in solution in soils is extremely low, and its exact value suggests contributions from multiple solid iron species, including amorphous and a range of crystalline forms of Fe(III) oxides. Organic matter produces transient small organic acids as it is decomposed, which complex with iron and help to bring it into solution. However, these organic acids are in the middle of the soil organic matter decomposition pathway, and do not persist for long in soils. Bringing more iron into solution relies on a combination of local reducing conditions around respiring roots and among microbe-and-SOM microsites, and local pH. Plants and other organisms secrete compounds that are effective at solubilizing iron and making it available to plants. The other major source of iron for organisms is local fluctuations of reducing and oxidizing conditions, which bring iron into solution and precipitate it as metastable, mixed-valence ferrosic hydroxide, which provides iron to solution at much higher concentrations than most other solid forms of iron.
This paper provides useful background information about the chemistry of iron in soils, but it is not clear to me which forms of iron should be targeted and measured in soils if one wishes to learn something about local aerobic and redox conditions.
Friday, November 6, 2009
Elberling et al. 2004
Elberling B, Jakobsen BH, Berg P, Sondergaard J, Sigsgaard C. 2004. Influence of vegetation, temperature, and water content on soil carbon distribution and mineralization in four High Arctic soils. Arctic, Antarctic, and Alpine Research, 36: 528-538.
These authors examined the carbon pools and carbon dioxide effluxes from four ecosystems at Zackenberg, in north-east Greenland. Their four ecosystems are very similar to the Alexandra Fjord systems of Dryas (CAVM P1), Cassiope (P2), Salix (G3), and Wet Sedge Meadow (W1).
There are two major sources of soil CO2: respiration by plant roots, and microbial respiration. Which of these two processes dominates CO2 production is a matter of some debate, with studies in the 1990s and 2000s indicating either when measuring similar arctic ecosystems. This study does not settle that debate, with estimated ratios of the two processes ranging from 9:1 to 1:9. What is clear is that plants and microbes compete for resources in arctic soils, with considerable variation in both time and space, even among vegetation communities in one valley with a consistent above-ground climate.
These soils include a buried A-horizon, with birch leaves present in pockets of organic-rich former topsoil indicative of surface conditions during the previous climatic mild period approximately 5000 years ago. These pockets of “Ab” create something of a wildcard situation for CO2 evolution, being responsible for a considerable fraction of the measured CO2 efflux at all ecosystems to varying extent.
To measure subsurface concentrations of CO2, these authors extended a probe to a range of depths and connected it to their gas analyzer also used for measuring surface fluxes, much as we have done at Alexandra Fjord. However, their gas analyzer only measures CO2, and they did not allow their probes to equilibrate to subsurface conditions for very long; a few minutes seems to be the usual protocol in this case.
A range of soil parameters were measured, and in general variation between vegetation types in these parameters exceeded variation within. The Cassiope system was the most variable, but also had the most variable Ab layers, which probably accounted for most of the variation. These patterns of variation at all ecosystems, however, suggest that the effects of climate change will not be uniform across the High Arctic, with increased temperatures leading to perhaps increases or decreases in the decomposition of buried organic matter and CO2 effluxes.
Like our own results from Alexandra Fjord, the Salix ecosystem at Zackenberg showed the highest below-ground CO2 concentrations. At Zackenberg, CO2 concentrations in Salix were mostly related to microbial decomposition of organic matter, with reduced soil water content leading to more oxygenation and higher temperatures, both increasing the rate of decomposition. In contrast, the water-saturated Eriophorum system had very high carbon stores and the highest CO2 efflux, but a decrease in water levels here leads to a shift from methane production to CO2 production, rather than a simple increase in one rate.
Overall, this paper provides some results and considerations of high relevance to my own work, especially given the high overlap in the range of ecosystems under consideration and the range of methods employed in their analysis. Their systems are not identical to those I studied; for example, the Dryas system at Zackenberg appears to be considerably drier and with less vegetation cover compared to the system with the same name at Alexandra Fjord.
These authors examined the carbon pools and carbon dioxide effluxes from four ecosystems at Zackenberg, in north-east Greenland. Their four ecosystems are very similar to the Alexandra Fjord systems of Dryas (CAVM P1), Cassiope (P2), Salix (G3), and Wet Sedge Meadow (W1).
There are two major sources of soil CO2: respiration by plant roots, and microbial respiration. Which of these two processes dominates CO2 production is a matter of some debate, with studies in the 1990s and 2000s indicating either when measuring similar arctic ecosystems. This study does not settle that debate, with estimated ratios of the two processes ranging from 9:1 to 1:9. What is clear is that plants and microbes compete for resources in arctic soils, with considerable variation in both time and space, even among vegetation communities in one valley with a consistent above-ground climate.
These soils include a buried A-horizon, with birch leaves present in pockets of organic-rich former topsoil indicative of surface conditions during the previous climatic mild period approximately 5000 years ago. These pockets of “Ab” create something of a wildcard situation for CO2 evolution, being responsible for a considerable fraction of the measured CO2 efflux at all ecosystems to varying extent.
To measure subsurface concentrations of CO2, these authors extended a probe to a range of depths and connected it to their gas analyzer also used for measuring surface fluxes, much as we have done at Alexandra Fjord. However, their gas analyzer only measures CO2, and they did not allow their probes to equilibrate to subsurface conditions for very long; a few minutes seems to be the usual protocol in this case.
A range of soil parameters were measured, and in general variation between vegetation types in these parameters exceeded variation within. The Cassiope system was the most variable, but also had the most variable Ab layers, which probably accounted for most of the variation. These patterns of variation at all ecosystems, however, suggest that the effects of climate change will not be uniform across the High Arctic, with increased temperatures leading to perhaps increases or decreases in the decomposition of buried organic matter and CO2 effluxes.
Like our own results from Alexandra Fjord, the Salix ecosystem at Zackenberg showed the highest below-ground CO2 concentrations. At Zackenberg, CO2 concentrations in Salix were mostly related to microbial decomposition of organic matter, with reduced soil water content leading to more oxygenation and higher temperatures, both increasing the rate of decomposition. In contrast, the water-saturated Eriophorum system had very high carbon stores and the highest CO2 efflux, but a decrease in water levels here leads to a shift from methane production to CO2 production, rather than a simple increase in one rate.
Overall, this paper provides some results and considerations of high relevance to my own work, especially given the high overlap in the range of ecosystems under consideration and the range of methods employed in their analysis. Their systems are not identical to those I studied; for example, the Dryas system at Zackenberg appears to be considerably drier and with less vegetation cover compared to the system with the same name at Alexandra Fjord.
Monday, November 2, 2009
Jones and Henry 2003
Jones GA, Henry GHR. 2003. Primary plant succession on recently deglaciated terrain in the Canadian High Arctic. Journal of Biogeography 30: 277-296.
These authors examined five glacial foregrounds on Ellesmere Island, one intensively and the other 4 “extensively”, to determine patterns of succession among plant communities on sterile ground. The ecological literature recognizes several different modes of succession, including a categorization by Henry and Svoboda (1987) based on the relative strengths of biotic and abiotic factors. This model of succession recognizes 3 modes; directional succession with species replacement, directional succession without species replacement, and non-directional succession without replacement. They are arranged in increasing importance of abiotic factors, referred to here as “environmental resistance”, which operates in opposition to “biological driving forces”.
In temperate regions, where much of the relevant ecological theory has been developed, biotic factors are mainly competition. In the High Arctic, a successional pattern consistent with directional-with-replacement was found, demonstrating that this can occur even in environments with obviously severe abiotic factors. However, these authors argue that the biotic factor driving this succession was probably not competition, because total plant cover remains below 10% by area even at the fourth stage recognized here, and species richness is always very low. The polar oasis landscape with 80-100% plant cover was never reached within the approximately 50-year old glacial forelands examined by these authors, though it is likely that competition is important in that “stage 5” level of High Arctic succession.
Other biotic variables suggested playing a role in successional dynamics in the High Arctic included facilitation and life-history characteristics. These factors are not independent; later successional species such as Salix arctica appear not to be able to establish until soil fertility has been improved by mats of very-early-colonizing mosses, and are long-lived, slow-growing species that contribute little to the early seed bank and seed rain. Thus, multiple plant and environmental characteristics appear to interact when structuring early communities.
I read this paper to try to gain some understanding of ecological succession and the role of time-since-deglaciation among the ecosystems of Alexandra Fjord. Rather than being distinct successional stages in sequence as I had previously supposed, it appears the various lowland ecosystems are all of a similar age, and have different vegetation communities as a result of other factors besides simply relative proximity to the Twin Glacier. Dryas integrefolia and Cassiope tetragona were important parts of this study, and both appear in stage 4, after primary-colonizing mosses, and early-colonizing forbs such as Papaver radicatum and early-colonizing deciduous shrubs like Saxifraga spp. Both Dryas and Cassiope form associations with mycorrhyzal fungi, a requirement that may slow their colonization of novel habitats; earlier-spreading plants do not form these associations, and instead may be limited by seed dispersal.
This was helpful in organizing the structure of the manuscript I am currently working on, which will describe some of the soil biotic communities both in the Alexandra Fjord lowlands and in the adjacent polar desert. It is not a simple story of succession from one ecosystem to the next, but succession does play a role.
These authors examined five glacial foregrounds on Ellesmere Island, one intensively and the other 4 “extensively”, to determine patterns of succession among plant communities on sterile ground. The ecological literature recognizes several different modes of succession, including a categorization by Henry and Svoboda (1987) based on the relative strengths of biotic and abiotic factors. This model of succession recognizes 3 modes; directional succession with species replacement, directional succession without species replacement, and non-directional succession without replacement. They are arranged in increasing importance of abiotic factors, referred to here as “environmental resistance”, which operates in opposition to “biological driving forces”.
In temperate regions, where much of the relevant ecological theory has been developed, biotic factors are mainly competition. In the High Arctic, a successional pattern consistent with directional-with-replacement was found, demonstrating that this can occur even in environments with obviously severe abiotic factors. However, these authors argue that the biotic factor driving this succession was probably not competition, because total plant cover remains below 10% by area even at the fourth stage recognized here, and species richness is always very low. The polar oasis landscape with 80-100% plant cover was never reached within the approximately 50-year old glacial forelands examined by these authors, though it is likely that competition is important in that “stage 5” level of High Arctic succession.
Other biotic variables suggested playing a role in successional dynamics in the High Arctic included facilitation and life-history characteristics. These factors are not independent; later successional species such as Salix arctica appear not to be able to establish until soil fertility has been improved by mats of very-early-colonizing mosses, and are long-lived, slow-growing species that contribute little to the early seed bank and seed rain. Thus, multiple plant and environmental characteristics appear to interact when structuring early communities.
I read this paper to try to gain some understanding of ecological succession and the role of time-since-deglaciation among the ecosystems of Alexandra Fjord. Rather than being distinct successional stages in sequence as I had previously supposed, it appears the various lowland ecosystems are all of a similar age, and have different vegetation communities as a result of other factors besides simply relative proximity to the Twin Glacier. Dryas integrefolia and Cassiope tetragona were important parts of this study, and both appear in stage 4, after primary-colonizing mosses, and early-colonizing forbs such as Papaver radicatum and early-colonizing deciduous shrubs like Saxifraga spp. Both Dryas and Cassiope form associations with mycorrhyzal fungi, a requirement that may slow their colonization of novel habitats; earlier-spreading plants do not form these associations, and instead may be limited by seed dispersal.
This was helpful in organizing the structure of the manuscript I am currently working on, which will describe some of the soil biotic communities both in the Alexandra Fjord lowlands and in the adjacent polar desert. It is not a simple story of succession from one ecosystem to the next, but succession does play a role.
Thursday, October 15, 2009
Hashimoto and Suzuki 2002
Hashimoto S, Suzuki M. 2002. Vertical distributions of carbon dioxide diffusion coefficients and production rates in forest soils. Soil Science Society of America Journal 66: 1151-1158.
These authors inverted the usual soil-gas measurement approach of inserting probes into soil: they inserted soil into their apparatus. “Undisturbed” soil samples approximately 20cm in diameter and 40cm long were collected from a research forest in Japan, dried for up to 17 days, and then placed into the laboratory apparatus. This consists of a sample cylinder big enough to take the soil samples, with chambers above and below that allow control of boundary conditions. Sample ports through the side of the cylinder allow measurement of CO2 concentrations at various positions in the sample. A set of pumps, valves, and tubes allow control of soil water conditions, including manipulation of water potential.
The point of this device is to measure CO2 diffusion in large soil samples, and control for water and temperature effects. Theories of soil gas diffusion can be tested using this apparatus.
These authors inverted the usual soil-gas measurement approach of inserting probes into soil: they inserted soil into their apparatus. “Undisturbed” soil samples approximately 20cm in diameter and 40cm long were collected from a research forest in Japan, dried for up to 17 days, and then placed into the laboratory apparatus. This consists of a sample cylinder big enough to take the soil samples, with chambers above and below that allow control of boundary conditions. Sample ports through the side of the cylinder allow measurement of CO2 concentrations at various positions in the sample. A set of pumps, valves, and tubes allow control of soil water conditions, including manipulation of water potential.
The point of this device is to measure CO2 diffusion in large soil samples, and control for water and temperature effects. Theories of soil gas diffusion can be tested using this apparatus.
Kammann et al. 2001
Kammann C, Grünhage L, Jäger H-J. 2001. A new sampling technique to monitor concentrations of CH4, N2O and CO2 in air at well-defined depths in soils with varied water potential. European Journal of Soil Science 52: 297-303.
These authors invented a buried probe based on silicone tubing for long-term monitoring of soil gas concentrations. In essence, this is simply a length of silicone tubing coiled into a flat “snail” shape and secured with wire mesh, with silicone stoppers at both ends. One end is penetrated by a stainless steel tube that extends to the surface, and is topped with a stopcock that allows sampling by syringe. These authors tested their design in a few laboratory and field studies, and demonstrated the gases CH4, N2O and CO2 do indeed diffuse into the hollow interior of the probe, and reach 95% equilibration in as little as 7 hours. They state the advantages of their design over other soil gas probes, most notably the ability to use this design in very wet and saturated soils, which is where CH4 processes may be of greatest interest.
The downside of this probe design from my point of view is the need to dig a pit for these probes, and the consequent long wait before the disturbance has dissipated and accurate sampling can begin. However, for long-term monitoring of soil gas processes, particularly in wetlands and soils prone to heavy rainfall events, these probes appear to be very useful.
These authors invented a buried probe based on silicone tubing for long-term monitoring of soil gas concentrations. In essence, this is simply a length of silicone tubing coiled into a flat “snail” shape and secured with wire mesh, with silicone stoppers at both ends. One end is penetrated by a stainless steel tube that extends to the surface, and is topped with a stopcock that allows sampling by syringe. These authors tested their design in a few laboratory and field studies, and demonstrated the gases CH4, N2O and CO2 do indeed diffuse into the hollow interior of the probe, and reach 95% equilibration in as little as 7 hours. They state the advantages of their design over other soil gas probes, most notably the ability to use this design in very wet and saturated soils, which is where CH4 processes may be of greatest interest.
The downside of this probe design from my point of view is the need to dig a pit for these probes, and the consequent long wait before the disturbance has dissipated and accurate sampling can begin. However, for long-term monitoring of soil gas processes, particularly in wetlands and soils prone to heavy rainfall events, these probes appear to be very useful.
Friday, October 9, 2009
Nemergut et al. 2005
Nemergut DR, Costello EK, Meyer AF, Pescador MY, Weintraub MN, Schmidt SK. 2005. Structure and function of alpine and arctic soil microbial communities. Research in Microbiology 156: 775-784.
These authors review the current state of knowledge of microbial communities in cold- and snow-affected soils. Their primary study site is a ridge in Colorado with a range of habitats from sub-alpine forest to glaciated mountain-tops; all areas receive significant snow cover for much of the year. They describe only three studies of microbial communities in the Arctic, stating these are the only such studies to their knowledge at the time of preparation of this paper.
The referenced work in this review clearly demonstrates that microbial communities are active when snow covered, contrary to the previous assumption that low temperatures would effectively prohibit microbial metabolisms during winter. Indeed, microbial biomass is actually highest in winter in the alpine tundra systems studied and lowest in spring after an apparent population crash. A wide diversity of microbes has been found, from Bacteria, Archaea, and Eucaryea, including deeply divergent lineages with no known associations with described groups. The physiologies and ecological functions of many of these microbes are completely unknown.
This paper provides a useful overview of the state of the field of cold-soils microecology, with many interesting references and some surprising synthesized findings. This research group in Colorado appears to be one of the few groups in the world studying cold soil microbial communities and their links to climate change.
These authors review the current state of knowledge of microbial communities in cold- and snow-affected soils. Their primary study site is a ridge in Colorado with a range of habitats from sub-alpine forest to glaciated mountain-tops; all areas receive significant snow cover for much of the year. They describe only three studies of microbial communities in the Arctic, stating these are the only such studies to their knowledge at the time of preparation of this paper.
The referenced work in this review clearly demonstrates that microbial communities are active when snow covered, contrary to the previous assumption that low temperatures would effectively prohibit microbial metabolisms during winter. Indeed, microbial biomass is actually highest in winter in the alpine tundra systems studied and lowest in spring after an apparent population crash. A wide diversity of microbes has been found, from Bacteria, Archaea, and Eucaryea, including deeply divergent lineages with no known associations with described groups. The physiologies and ecological functions of many of these microbes are completely unknown.
This paper provides a useful overview of the state of the field of cold-soils microecology, with many interesting references and some surprising synthesized findings. This research group in Colorado appears to be one of the few groups in the world studying cold soil microbial communities and their links to climate change.
Thursday, October 8, 2009
Lipson et al. 2009
Lipson DA, Monson RK, Schmidt SK, Weintraub MN. 2009. The trade-off between growth rate and yield in microbial communities and the consequences for under-snow soil respiration in a high elevation coniferous forest. Biogeochemistry 95: 23-35.
These authors conducted a multiply-combined approach study that examined soil microbial communities in the sub-alpine forest of Colorado. They investigated growth and respiration of microbes including both bacteria and fungi, how those processes varied between summer (snow free) and winter (snow covered), and linked these processes to measures of community composition, and built a mathematical model of soil microbial metabolism and temperature. The overall purpose of this study was to thoroughly examine soil microbial processes relating to CO2 emissions and carbon cycling.
The major finding of this study was that there are effectively two distinct microbial communities in this ecosystem. In summer, there is a community of slow-growing, high biomass-yield microbes with a low specific respiration; in other words, the summer microbes grow slowly but efficiently, capturing much of the available carbon as biomass and releasing relatively little CO2 per unit biomass. In winter, the community is composed of fast-growing, low yield microbes that release much more CO2 per unit biomass.
There are effectively two ecological strategies at work, during different seasons. The winter strategy is one of competition. Available nutrients are consumed rapidly, releasing large amounts of CO2 but producing little growth. In summer, the strategy is more cooperative, with slower, less scramble-like growth that more fully uses available nutrients in growing new cells.
In general, the bacteria in the system seem more capable of the high-competition strategy, as these authors found little contribution of fungi to total ecosystem respiration in winter, by using a set of bacterial and fungal inhibitors. The winter community has a much higher response to temperature (Q10) than the summer community. A winter community at intermediate temperatures produces much more CO2 than does a summer community.
In analyzing the composition of the communities, these authors employed the P-test method of Martin (2002), as I intend to as well. I found this paper through a Web of Science search for papers citing Martin (2002); this was one of 153 papers found. The first author of this paper, D.A. Lipson, appears to have a substantial history of publications examining soil microbial communities.
These authors conducted a multiply-combined approach study that examined soil microbial communities in the sub-alpine forest of Colorado. They investigated growth and respiration of microbes including both bacteria and fungi, how those processes varied between summer (snow free) and winter (snow covered), and linked these processes to measures of community composition, and built a mathematical model of soil microbial metabolism and temperature. The overall purpose of this study was to thoroughly examine soil microbial processes relating to CO2 emissions and carbon cycling.
The major finding of this study was that there are effectively two distinct microbial communities in this ecosystem. In summer, there is a community of slow-growing, high biomass-yield microbes with a low specific respiration; in other words, the summer microbes grow slowly but efficiently, capturing much of the available carbon as biomass and releasing relatively little CO2 per unit biomass. In winter, the community is composed of fast-growing, low yield microbes that release much more CO2 per unit biomass.
There are effectively two ecological strategies at work, during different seasons. The winter strategy is one of competition. Available nutrients are consumed rapidly, releasing large amounts of CO2 but producing little growth. In summer, the strategy is more cooperative, with slower, less scramble-like growth that more fully uses available nutrients in growing new cells.
In general, the bacteria in the system seem more capable of the high-competition strategy, as these authors found little contribution of fungi to total ecosystem respiration in winter, by using a set of bacterial and fungal inhibitors. The winter community has a much higher response to temperature (Q10) than the summer community. A winter community at intermediate temperatures produces much more CO2 than does a summer community.
In analyzing the composition of the communities, these authors employed the P-test method of Martin (2002), as I intend to as well. I found this paper through a Web of Science search for papers citing Martin (2002); this was one of 153 papers found. The first author of this paper, D.A. Lipson, appears to have a substantial history of publications examining soil microbial communities.
Tuesday, October 6, 2009
Bohannan and Hughes 2003
Bohannan BJM, Hughes J. 2003. New approaches to analyzing microbial biodiversity data. Current Opinion in Microbiology. 6: 282-287.
These authors review the use of three broad approaches to studying microbial biodiversity in environments. The three are 1) parametric, 2) nonparametric, and 3) community phylogenetics. Each has advantages and disadvantages, and these authors suggest a combined approach may be most beneficial. Both 1) and 2) are based on Operational Taxonomic Units, to avoid the many problems of bacterial species identification, while 3) is based on molecular phylogenies, typically 16s rDNA.
Parametric approaches make simplifying assumptions and are based on some model of species richness in microbial communities; often this model is log-normal, in which some taxa are rare, some are abundant, and most are intermediate. These approaches extrapolate from patterns in a sample to the total environment. The obvious downside to parametric approaches is the vulnerability of the model to incorrect and difficult to test assumptions.
Nonparametric approaches avoid assuming any model, and instead are typically built on an approach analogous to mark-release-recapture. Sequences encountered more than once in a sample are recaptures, and the frequency of these doubletons is assumed to be related to how many unique sequences are present: more doubletons means fewer total sequences. As a downside, these approaches provide only a lower limit to actual richness, thus generally underestimating total diversity.
Community phylogenetics approaches avoid the OTU concept and thereby preserve useful data in the form of genetic information about sequences and sequence relationships. The downside of community phylogenetics approaches is they sample a clone library derived from the environment, not the environment directly, and can therefore not extrapolate from the sample to the environment.
This paper provides several useful examples of each approach, and supports the utility of Martin’s (2002) combined approach, which is what I would like to apply to my data to be collected in 2010. Figure 3 in this paper, for example, provides a useful overview of what Martin (2002) did, and how to make inferences about observed patterns.
These authors review the use of three broad approaches to studying microbial biodiversity in environments. The three are 1) parametric, 2) nonparametric, and 3) community phylogenetics. Each has advantages and disadvantages, and these authors suggest a combined approach may be most beneficial. Both 1) and 2) are based on Operational Taxonomic Units, to avoid the many problems of bacterial species identification, while 3) is based on molecular phylogenies, typically 16s rDNA.
Parametric approaches make simplifying assumptions and are based on some model of species richness in microbial communities; often this model is log-normal, in which some taxa are rare, some are abundant, and most are intermediate. These approaches extrapolate from patterns in a sample to the total environment. The obvious downside to parametric approaches is the vulnerability of the model to incorrect and difficult to test assumptions.
Nonparametric approaches avoid assuming any model, and instead are typically built on an approach analogous to mark-release-recapture. Sequences encountered more than once in a sample are recaptures, and the frequency of these doubletons is assumed to be related to how many unique sequences are present: more doubletons means fewer total sequences. As a downside, these approaches provide only a lower limit to actual richness, thus generally underestimating total diversity.
Community phylogenetics approaches avoid the OTU concept and thereby preserve useful data in the form of genetic information about sequences and sequence relationships. The downside of community phylogenetics approaches is they sample a clone library derived from the environment, not the environment directly, and can therefore not extrapolate from the sample to the environment.
This paper provides several useful examples of each approach, and supports the utility of Martin’s (2002) combined approach, which is what I would like to apply to my data to be collected in 2010. Figure 3 in this paper, for example, provides a useful overview of what Martin (2002) did, and how to make inferences about observed patterns.
Fang and Moncrieff 1998
Fang C, Moncrieff JB. 1998. Simple and fast technique to measure CO2 profiles in soil. Soil Biology and Biochemistry 30: 2107-2112.
These authors present a method they developed to measure sub-surface CO2 concentrations in soil. Their test environment was a slash pine (Pinus elliotti) plantation in Florida, with sandy soil subject to a broadly fluctuating water table that occasionally comes to the surface.
Their method, essentially, involves burying a perforated aluminum probe connected to the surface with flexible tubing, waiting several weeks for the disturbance to settle, and then measuring recirculated gas samples by injecting them with a syringe into an IRGA. Recirculation breaks the trade-off between errors associated with the syringe sucking air out of surrounding soils at depths different from the intended sample, and large buffer volumes inside probes become dead spaces with internal gas concentration gradients.
This is an interesting approach to soil gas probes, but is fundamentally unsuitable for my own studies because of the necessity of waiting weeks before sampling due to the disturbance of burying the probes.
These authors present a method they developed to measure sub-surface CO2 concentrations in soil. Their test environment was a slash pine (Pinus elliotti) plantation in Florida, with sandy soil subject to a broadly fluctuating water table that occasionally comes to the surface.
Their method, essentially, involves burying a perforated aluminum probe connected to the surface with flexible tubing, waiting several weeks for the disturbance to settle, and then measuring recirculated gas samples by injecting them with a syringe into an IRGA. Recirculation breaks the trade-off between errors associated with the syringe sucking air out of surrounding soils at depths different from the intended sample, and large buffer volumes inside probes become dead spaces with internal gas concentration gradients.
This is an interesting approach to soil gas probes, but is fundamentally unsuitable for my own studies because of the necessity of waiting weeks before sampling due to the disturbance of burying the probes.
Cockell and Stokes 2004
Cockell CS, Stokes MD. 2004. Widespread colonization by polar hypoliths. Nature 431: 414.
These authors present a short report about the colonization of the undersides of rocks in the polar deserts by cyanobacteria and unicellular green algae. Where rocks have a protected but accessible underside, these organisms colonize, forming a pale green band a few centimetres across, between the part of the rock too exposed and dry, and too dark for photosynthesis. In polygon terrain, where the ground is sorted by frost heave (“periglacial processes”) and even large rocks are periodically jostled, areas of finer texture form in the centers of polygons, with larger rocks around the edges. The edge rocks were 100% colonized, while central areas were 5% colonized.
These authors present a short report about the colonization of the undersides of rocks in the polar deserts by cyanobacteria and unicellular green algae. Where rocks have a protected but accessible underside, these organisms colonize, forming a pale green band a few centimetres across, between the part of the rock too exposed and dry, and too dark for photosynthesis. In polygon terrain, where the ground is sorted by frost heave (“periglacial processes”) and even large rocks are periodically jostled, areas of finer texture form in the centers of polygons, with larger rocks around the edges. The edge rocks were 100% colonized, while central areas were 5% colonized.
Fierer and Jackson 2006
Fierer N, Jackson RB. 2006. The diversity and biogeography of soil bacterial communities. Proceedings of the National Academy of Sciences of the U.S.A. 103: 626-631.
These authors measured biodiversity of soil bacterial communities from 98 samples across North and South America. Rather than the expected variables that structure macroorganism biodiversity such as climate and latitude, the single most important factor for bacterial community diversity was soil pH. Soils with higher pH had greater biodiversity, regardless of geographic separation between sites or geographic position. Because soils with pH greater than 8.5 are rare, it is impossible to distinguish between a unimodal distribution, and a plateau at near-neutral pH.
Most surprising to me was the lack of correlation between bacterial diversity, as either species richness or Shannon-index diversity (richness and evenness) and plant diversity. While these authors did not assess plant diversity, they did express their own surprise that sites in the Peruvian Amazon, with acidic soils, had very low bacterial diversity despite having one of the highest measured plant biodiversities on Earth, and expanded their soil collecting sites to include other tropical and sub-tropical forests with very high plant diversity. Sites with near-neutral pH provided the highest estimates of bacterial diversity, and were primarily dry-grassland, dry-forest, and humid temperate forest sites, with low-to-intermediate plant diversity.
The method used to estimate diversity of bacterial communities was terminal-restriction fragment length polymorphism analysis, or T-RFLP. This technique relies on PCR to amplify the sequence of interest, in this case 16S rDNA, followed by digestion with restriction endonucleases and generation of “fingerprints” for each community. This is a fairly low-resolution method, with less than 100 bands per community, and no ability to distinguish between species with similar restriction sites. However, it does permit high throughput and costs much less per sample than does cloning and sequencing.
This paper is an excellent example of a recent study supporting the hypothesis that microbial global biodiversity is controlled by factors quite distinct from the factors controlling macroorganism (plant and animal) biodiversity. In this case, soil pH is the master control variable, rather than climate or climate factors.
These authors measured biodiversity of soil bacterial communities from 98 samples across North and South America. Rather than the expected variables that structure macroorganism biodiversity such as climate and latitude, the single most important factor for bacterial community diversity was soil pH. Soils with higher pH had greater biodiversity, regardless of geographic separation between sites or geographic position. Because soils with pH greater than 8.5 are rare, it is impossible to distinguish between a unimodal distribution, and a plateau at near-neutral pH.
Most surprising to me was the lack of correlation between bacterial diversity, as either species richness or Shannon-index diversity (richness and evenness) and plant diversity. While these authors did not assess plant diversity, they did express their own surprise that sites in the Peruvian Amazon, with acidic soils, had very low bacterial diversity despite having one of the highest measured plant biodiversities on Earth, and expanded their soil collecting sites to include other tropical and sub-tropical forests with very high plant diversity. Sites with near-neutral pH provided the highest estimates of bacterial diversity, and were primarily dry-grassland, dry-forest, and humid temperate forest sites, with low-to-intermediate plant diversity.
The method used to estimate diversity of bacterial communities was terminal-restriction fragment length polymorphism analysis, or T-RFLP. This technique relies on PCR to amplify the sequence of interest, in this case 16S rDNA, followed by digestion with restriction endonucleases and generation of “fingerprints” for each community. This is a fairly low-resolution method, with less than 100 bands per community, and no ability to distinguish between species with similar restriction sites. However, it does permit high throughput and costs much less per sample than does cloning and sequencing.
This paper is an excellent example of a recent study supporting the hypothesis that microbial global biodiversity is controlled by factors quite distinct from the factors controlling macroorganism (plant and animal) biodiversity. In this case, soil pH is the master control variable, rather than climate or climate factors.
Tuesday, September 29, 2009
Martin 2002
Martin AP. 2002. Phylogenetic approaches for describing and comparing the diversity of microbial communities. Applied and Environmental Microbiology 68: 3673-3682.
This author presents a synthesis of a set of statistical techniques for detailed analysis of biodiversity in the context of microbial communities. One new test, the P-test (for phylogenetics) is combined with the FST test to generate inferences about the quantified levels of difference in community composition when examining multiple microbial communities.
A review of existing methods for quantifying diversity is provided first, rapidly pointing out the not-unlikely circumstances under which inter-community differences would be either under- or over-estimated in the absence of explicit phylogenetic inference. Other types of phylogenetic inference in this context are examined, but one main problem with techniques such as the Shannon-Wiener index is its dependency on accurate information about frequency of taxa. The P-test, novel to this paper as far as I can tell, avoids this pitfall, and instead is based on an examination of the covariance between a phylogeny and the distribution of taxa in communities.
Figure 3 from Martin (2002). The basis of the P test is the covariance between which community a sequence was found in, and the positions of sequences on the phylogenetic tree.
The P test is combined with the FST test to examine the partitioning of sequence variation between communities. A P test on its own is not particularly informative, because it says little about how variation is partitioned between communities vs. the total pool.
The 2x2 grid of comparison of P test and FST test results, from Figure 4 of Martin (2002). Each possible outcome of significance for the two tests allows inference about the evolutionary and ecological history of a particular situation of microbial communities.
The raw data for the P test is sequence data, typically 16S rDNA. This author advocates whole-gene sequences for comparison, to provide the maximum data and maximum compatibility between different studies, but acknowledges the trade-off between sequence length and number of sequences that can be produced. These are also the raw data for FST, but how those raw data are treated before going into each test varies.
Under the P test, the sequence data are used to construct a phylogeny, incorporating all sequence data from all communities. This phylogeny is set to equal total branch lengths from the root to the tips (the tips being the currently-measured sequences), and a null model of branching through time (lineage-per-time) is built. Then the community occurrence of each sequence is mapped onto the phylogeny, and the covariance calculated.
The FST test takes in Theta values as its meat of calculation. Theta is the total genetic variation in a sample, and in FST the grand total theta for all communities combined is compared to the average within-community theta for all communities under consideration.
This combined approach is intended to be complimentary to existing methods of examining microbial diversity, such as methods for estimating species richness, and methods for examining microbial phylogenies. I think the author’s own words at the beginning of the discussion section provide a good summary:
“In this study I used standard quantitative methods of analysis borrowed from population genetics and systematics for describing and comparing microbial communities. Information gained from analysis of DNA sequences provided the basis for statistical analysis of communities in ways that advance inferences about the processes that may govern the compositions and functions of microbial communities. Furthermore, the analytical approaches advocated here make it possible to accomplish broad comparisons of ecological communities. For instance, a comparison of lineage-per-time plots across a diverse set of ecosystems might reveal differences in the phylogenetic compositions of ecological communities that would be invisible with standard ecological statistics that ignore the magnitude of genetic differences among sampled sequences.”
I think I would like to use this approach in the analysis of microbial communities I will conduct based on soil samples from the polar desert. This method seems at this point like a useful way to quantify diversity across the gradient of latitude I will be covering.
This author presents a synthesis of a set of statistical techniques for detailed analysis of biodiversity in the context of microbial communities. One new test, the P-test (for phylogenetics) is combined with the FST test to generate inferences about the quantified levels of difference in community composition when examining multiple microbial communities.
A review of existing methods for quantifying diversity is provided first, rapidly pointing out the not-unlikely circumstances under which inter-community differences would be either under- or over-estimated in the absence of explicit phylogenetic inference. Other types of phylogenetic inference in this context are examined, but one main problem with techniques such as the Shannon-Wiener index is its dependency on accurate information about frequency of taxa. The P-test, novel to this paper as far as I can tell, avoids this pitfall, and instead is based on an examination of the covariance between a phylogeny and the distribution of taxa in communities.
Figure 3 from Martin (2002). The basis of the P test is the covariance between which community a sequence was found in, and the positions of sequences on the phylogenetic tree.The P test is combined with the FST test to examine the partitioning of sequence variation between communities. A P test on its own is not particularly informative, because it says little about how variation is partitioned between communities vs. the total pool.
The 2x2 grid of comparison of P test and FST test results, from Figure 4 of Martin (2002). Each possible outcome of significance for the two tests allows inference about the evolutionary and ecological history of a particular situation of microbial communities.The raw data for the P test is sequence data, typically 16S rDNA. This author advocates whole-gene sequences for comparison, to provide the maximum data and maximum compatibility between different studies, but acknowledges the trade-off between sequence length and number of sequences that can be produced. These are also the raw data for FST, but how those raw data are treated before going into each test varies.
Under the P test, the sequence data are used to construct a phylogeny, incorporating all sequence data from all communities. This phylogeny is set to equal total branch lengths from the root to the tips (the tips being the currently-measured sequences), and a null model of branching through time (lineage-per-time) is built. Then the community occurrence of each sequence is mapped onto the phylogeny, and the covariance calculated.
The FST test takes in Theta values as its meat of calculation. Theta is the total genetic variation in a sample, and in FST the grand total theta for all communities combined is compared to the average within-community theta for all communities under consideration.
This combined approach is intended to be complimentary to existing methods of examining microbial diversity, such as methods for estimating species richness, and methods for examining microbial phylogenies. I think the author’s own words at the beginning of the discussion section provide a good summary:
“In this study I used standard quantitative methods of analysis borrowed from population genetics and systematics for describing and comparing microbial communities. Information gained from analysis of DNA sequences provided the basis for statistical analysis of communities in ways that advance inferences about the processes that may govern the compositions and functions of microbial communities. Furthermore, the analytical approaches advocated here make it possible to accomplish broad comparisons of ecological communities. For instance, a comparison of lineage-per-time plots across a diverse set of ecosystems might reveal differences in the phylogenetic compositions of ecological communities that would be invisible with standard ecological statistics that ignore the magnitude of genetic differences among sampled sequences.”
I think I would like to use this approach in the analysis of microbial communities I will conduct based on soil samples from the polar desert. This method seems at this point like a useful way to quantify diversity across the gradient of latitude I will be covering.
Monday, September 28, 2009
Nannipieri et al. 2003
Nannipieri P, Ascher J, Ceccherini MT, Landi L, Pietramellara G, Renella G. 2003. Microbial diversity and soil functions. European Journal of Soil Science 54: 655-670.
These authors present a review of the current state of knowledge about microbial diversity and ecosystem function such as organic matter decomposition in soils. They devote sections of the paper to the structure of soil as a habitat for microbes and other soil-dwelling organisms, methods of measuring microbial diversity, measuring soil functions, the current understanding of these methods and prominent results, and how these measures fit together in various contexts.
Unlike above-ground systems, soils appear to have no link between function and microbial diversity, or the direction and magnitude of the relationship varies considerably with which function is studied. General ecology theory and results suggest there should be a hump-shaped relationship between biodiversity (species richness and evenness) and productivity, such that productivity increases with diversity to some point, before declining. This relationship has not typically been found in soil systems, though there are relatively few studies of this relationship specifically in soils.
Measuring function in soils is complicated by the structure of soil. It is largely composed of non-living matter, some of which such as clay surfaces are capable of catalyzing reactions normally associated with living cells. In addition, these surfaces can adsorb large organic molecules such as enzymes and nucleic acids and protect them from degradation while still allowing some catalytic activity. Thus, even after all cells have been killed in a soil sample, enzymatic activity may be detectable. Distinguishing between biotic and abiotic chemical reactions in natural soil systems is therefore extremely difficult.
Measuring biodiversity in soil is not much easier than measuring function. Plate-count methods have been widely criticized because they will measure only culturable organisms, variously estimated to compose a small fraction of actual biodiversity. Countering this criticism, some researchers have suggested that the biomass, rather than species richness, of unculturable microbes is a minority, rendering plate counts of culturable species much more relevant to ecological studies. However, much attention has been focused recently on molecular methods, further divided into DNA-based techniques and fatty-acid based techniques.
DNA-based techniques deployed to study microbial diversity in soils often include a PCR step. However, DNA extraction methods for soil must balance several trade-offs, for example gram positive bacteria have very tough cell wall structures that require harsh treatment to break down and access their DNA. This same harsh treatment can shred DNA from less-tough cells to under 1kb fragments, which will often form chimeras during PCR, especially when using universal primers for such popular markers as 16s rDNA. Similarly, high-efficiency methods of DNA extraction and isolation are also efficient at extracting humic acids, which interfere with PCR. Despite these concerns, a large number of studies based on PCR of soil-derived DNA templates have been published, providing a large database of sequences for phylogenetic comparison.
Fatty-acid based techniques avoid the PCR-based concerns of DNA methods, but are less specific in their results: fatty acid composition is generally not species-specific the way DNA sequence data can be. However, techniques such as PFLA provide useful estimates of soil microbial biomass.
There is an ecological puzzle in the observed high biodiversity of near-surface soils. Two competing, though probably not mutually-exclusive hypotheses centre on a lack of competition among soil microbes. Under the first hypothesis, microbial microhabitats tend to be isolated from each other, preventing contact and competition. Community mixing occurs when water droplets bridge the gaps between soil aggregates, as during rainfall when soil pore spaces are filled. Countering this hypothesis is the observation that much of the near-surface soil environment is not especially prone to pore-drying, for example the plant root-soil interfaces, yet contains high species richness. The second hypothesis suggests that high specialization for organic substrates (i.e. microbe food) prevents competition among cells in close physical proximity. There are higher quantity and diversities of organic molecules in surface soils compared to greater depths, but flow channels such as cracks, fissures, and worm burrows also have high levels of organic molecules, and high microbial biomass, but do not show higher diversity than the surrounding bulk soil. The puzzle remains unsolved.
Much of the discussion of various measurements in this paper is of direct relevance to my own work. The various methods for assessing soil function, for example, are almost all measures of enzyme activity, which is precisely what my gas-flux measurements are as well. I intend to measure biodiversity, by molecular means, and the references and discussion here are valuable. Overall, this review paper does a good job of providing an overview of some issues I will also be exploring.
These authors present a review of the current state of knowledge about microbial diversity and ecosystem function such as organic matter decomposition in soils. They devote sections of the paper to the structure of soil as a habitat for microbes and other soil-dwelling organisms, methods of measuring microbial diversity, measuring soil functions, the current understanding of these methods and prominent results, and how these measures fit together in various contexts.
Unlike above-ground systems, soils appear to have no link between function and microbial diversity, or the direction and magnitude of the relationship varies considerably with which function is studied. General ecology theory and results suggest there should be a hump-shaped relationship between biodiversity (species richness and evenness) and productivity, such that productivity increases with diversity to some point, before declining. This relationship has not typically been found in soil systems, though there are relatively few studies of this relationship specifically in soils.
Measuring function in soils is complicated by the structure of soil. It is largely composed of non-living matter, some of which such as clay surfaces are capable of catalyzing reactions normally associated with living cells. In addition, these surfaces can adsorb large organic molecules such as enzymes and nucleic acids and protect them from degradation while still allowing some catalytic activity. Thus, even after all cells have been killed in a soil sample, enzymatic activity may be detectable. Distinguishing between biotic and abiotic chemical reactions in natural soil systems is therefore extremely difficult.
Measuring biodiversity in soil is not much easier than measuring function. Plate-count methods have been widely criticized because they will measure only culturable organisms, variously estimated to compose a small fraction of actual biodiversity. Countering this criticism, some researchers have suggested that the biomass, rather than species richness, of unculturable microbes is a minority, rendering plate counts of culturable species much more relevant to ecological studies. However, much attention has been focused recently on molecular methods, further divided into DNA-based techniques and fatty-acid based techniques.
DNA-based techniques deployed to study microbial diversity in soils often include a PCR step. However, DNA extraction methods for soil must balance several trade-offs, for example gram positive bacteria have very tough cell wall structures that require harsh treatment to break down and access their DNA. This same harsh treatment can shred DNA from less-tough cells to under 1kb fragments, which will often form chimeras during PCR, especially when using universal primers for such popular markers as 16s rDNA. Similarly, high-efficiency methods of DNA extraction and isolation are also efficient at extracting humic acids, which interfere with PCR. Despite these concerns, a large number of studies based on PCR of soil-derived DNA templates have been published, providing a large database of sequences for phylogenetic comparison.
Fatty-acid based techniques avoid the PCR-based concerns of DNA methods, but are less specific in their results: fatty acid composition is generally not species-specific the way DNA sequence data can be. However, techniques such as PFLA provide useful estimates of soil microbial biomass.
There is an ecological puzzle in the observed high biodiversity of near-surface soils. Two competing, though probably not mutually-exclusive hypotheses centre on a lack of competition among soil microbes. Under the first hypothesis, microbial microhabitats tend to be isolated from each other, preventing contact and competition. Community mixing occurs when water droplets bridge the gaps between soil aggregates, as during rainfall when soil pore spaces are filled. Countering this hypothesis is the observation that much of the near-surface soil environment is not especially prone to pore-drying, for example the plant root-soil interfaces, yet contains high species richness. The second hypothesis suggests that high specialization for organic substrates (i.e. microbe food) prevents competition among cells in close physical proximity. There are higher quantity and diversities of organic molecules in surface soils compared to greater depths, but flow channels such as cracks, fissures, and worm burrows also have high levels of organic molecules, and high microbial biomass, but do not show higher diversity than the surrounding bulk soil. The puzzle remains unsolved.
Much of the discussion of various measurements in this paper is of direct relevance to my own work. The various methods for assessing soil function, for example, are almost all measures of enzyme activity, which is precisely what my gas-flux measurements are as well. I intend to measure biodiversity, by molecular means, and the references and discussion here are valuable. Overall, this review paper does a good job of providing an overview of some issues I will also be exploring.
Wednesday, September 23, 2009
Freeman et al. 2009
Freeman KR, Pescador MY, Reed SC, Costello EK, Robeson MS, Schmidt SK. 2009. Soil CO2 flux and photoautotrophic community composition in high-elevation, ‘barren’ soil. Environmental Microbiology 11: 674-686.
These authors measured photosynthetic carbon fixation and microbial community composition in sub-nival barren soils in the Colorado Front Range of the United States, at 40ºN latitude and approximately 3600m altitude. Like polar desert soils, these sub-nival soils lack conspicuous macrophytic vegetation (vascular plants and bryophytes) and are snow-covered for most of the year. Previous examinations of these systems had suggested the majority of carbon input to these soils was derived from wind-blown dust, but this study demonstrated a much larger input of carbon from in-situ photosynthesis.
Net carbon fixation was estimated by subtracting in-light measurements from in-dark measurements of CO2 flux. All measurements were made using an IRGA system with a 1.18L transparent chamber; dark measurements were made by covering the chamber with a dark, opaque cloth. After measurement of CO2 flux, one site was carefully dug up and transported to the laboratory for molecular-phylogenetic analysis.
The soil was divided into 2 depths: 0-2cm and 2-4cm, then DNA was extracted and PCR using universal bacterial primers for the 16s region was carried out, followed by sequencing. This generated more than 1000 sequences, in 4 bacterial divisions containing known photoautotrophic microorganisms, plus some sequences from eukaryotic green algae.
The most intriguing group of bacteria found were the Chloroflexi, an understudied group found in both depth layers. The taxa composition found in the deeper layer was highly different from the community found in the surface, light-receiving zone, and the authors suggest, based on a few studies done of Chloroflexi in hot-springs environments, that this group may use longer-wavelength light which penetrates deeper in soils. These authors do not make it, but this suggests to me the microphotoautotrophs in this system may be partitioning their environment in both space (depth) and spectrum (red).
This paper includes a large number of references and introductory descriptions for techniques and findings I will need to incorporate into the planning stages (at least) of my future studies in the polar desert. In particular, the molecular approach to the phylogenetics and biodiversity of the soil photoautotrophs seems both powerful and relatively uncomplicated. There are many procedures to carry out, to be sure, but the justification for each is clear, and the sequence of operations appears to be linear.
These authors measured photosynthetic carbon fixation and microbial community composition in sub-nival barren soils in the Colorado Front Range of the United States, at 40ºN latitude and approximately 3600m altitude. Like polar desert soils, these sub-nival soils lack conspicuous macrophytic vegetation (vascular plants and bryophytes) and are snow-covered for most of the year. Previous examinations of these systems had suggested the majority of carbon input to these soils was derived from wind-blown dust, but this study demonstrated a much larger input of carbon from in-situ photosynthesis.
Net carbon fixation was estimated by subtracting in-light measurements from in-dark measurements of CO2 flux. All measurements were made using an IRGA system with a 1.18L transparent chamber; dark measurements were made by covering the chamber with a dark, opaque cloth. After measurement of CO2 flux, one site was carefully dug up and transported to the laboratory for molecular-phylogenetic analysis.
The soil was divided into 2 depths: 0-2cm and 2-4cm, then DNA was extracted and PCR using universal bacterial primers for the 16s region was carried out, followed by sequencing. This generated more than 1000 sequences, in 4 bacterial divisions containing known photoautotrophic microorganisms, plus some sequences from eukaryotic green algae.
The most intriguing group of bacteria found were the Chloroflexi, an understudied group found in both depth layers. The taxa composition found in the deeper layer was highly different from the community found in the surface, light-receiving zone, and the authors suggest, based on a few studies done of Chloroflexi in hot-springs environments, that this group may use longer-wavelength light which penetrates deeper in soils. These authors do not make it, but this suggests to me the microphotoautotrophs in this system may be partitioning their environment in both space (depth) and spectrum (red).
This paper includes a large number of references and introductory descriptions for techniques and findings I will need to incorporate into the planning stages (at least) of my future studies in the polar desert. In particular, the molecular approach to the phylogenetics and biodiversity of the soil photoautotrophs seems both powerful and relatively uncomplicated. There are many procedures to carry out, to be sure, but the justification for each is clear, and the sequence of operations appears to be linear.
Uchida et al. 2002
Uchida M, Muraoka H, Nakatsubo T, Bekku Y, Ueno T, Kanda H, Koizumi H. 2002. Net photosynthesis, respiration, and production of the moss Sanionia uncinata on a glacier foreland in the High Arctic, Ny-Ålesund, Svalbard. Arctic, Antarctic, and Alpine Research 34: 287-292.
These authors constructed a model of moss physiology that uses meteorological data to estimate productivity, based on data collected during one field season at Svalbard. In 2000, these authors measured the response of a common High Arctic moss species to water content, temperature, and light, then determined the relationship between those variables and available meteorological data, then applied previous-years meteorological data to their model and estimated previous-years productivity. These estimates suggest a great deal of variation in year-to-year productivity, driven largely by differences in water availability. Water content of fresh moss tissue was the single most important controlling variable in moss photosynthesis rates. The response to temperature was nearly flat between 7 and 23ºC, with near-freezing photosynthetic rates still a large fraction of maximum under saturating light conditions. Saturating light conditions were estimated at near 800µmol/m^2/s, which is not uncommon on sunny days in this environment.
The glacial foreground in question is at 79º North, but is not polar desert as it receives approximately 360mm of precipitation per year. The moss species studied is dominant in the local ecosystem, but appears to represent an intermediate successional stage, with high-productivity vascular plants replacing bryophytes in older sites in the area (i.e. further from the toe of the glacier).
These authors constructed a model of moss physiology that uses meteorological data to estimate productivity, based on data collected during one field season at Svalbard. In 2000, these authors measured the response of a common High Arctic moss species to water content, temperature, and light, then determined the relationship between those variables and available meteorological data, then applied previous-years meteorological data to their model and estimated previous-years productivity. These estimates suggest a great deal of variation in year-to-year productivity, driven largely by differences in water availability. Water content of fresh moss tissue was the single most important controlling variable in moss photosynthesis rates. The response to temperature was nearly flat between 7 and 23ºC, with near-freezing photosynthetic rates still a large fraction of maximum under saturating light conditions. Saturating light conditions were estimated at near 800µmol/m^2/s, which is not uncommon on sunny days in this environment.
The glacial foreground in question is at 79º North, but is not polar desert as it receives approximately 360mm of precipitation per year. The moss species studied is dominant in the local ecosystem, but appears to represent an intermediate successional stage, with high-productivity vascular plants replacing bryophytes in older sites in the area (i.e. further from the toe of the glacier).
Tuesday, September 22, 2009
Floyd et al. 2002
Floyd R, Abebe E, Papert A, Blaxter M. 2002. Molecular barcodes for soil nematode identification. Molecular Ecology 11: 839-50.
These authors present a detailed description of and theory behind the MOTU concept. This analysis technique uses molecular sequence data to identify taxonomic units, hence the name Molecular Operational Taxonomic Unit. This paper uses the MOTU concept to examine and draw inferences about a collection of nematodes from a Scottish farm, finding high levels of species richness, and demonstrating a set of methods for rapid, inexpensive phylogenetics of a taxonomically-difficult group of animals.
These authors present a detailed description of and theory behind the MOTU concept. This analysis technique uses molecular sequence data to identify taxonomic units, hence the name Molecular Operational Taxonomic Unit. This paper uses the MOTU concept to examine and draw inferences about a collection of nematodes from a Scottish farm, finding high levels of species richness, and demonstrating a set of methods for rapid, inexpensive phylogenetics of a taxonomically-difficult group of animals.
Büdel et al. 2009
Büdel B, Darienko T, Deutschewitz K, Dojani S, Friedl T, Mohr KI, Salisch M, Reisser W, Weber B. 2009. Southern African biological soil crusts are ubiquitous and highly diverse in drylands, being restricted by rainfall frequency. Microbial Ecology 57: 229-247.
These authors examined biological soil crusts (BSCs) along a 2000km transect running roughly north-south through Namibia and South Africa. A number of hypotheses relating to BSC composition, frequency, and succession were proposed and tested, with most hypotheses partly confirmed. In general, BSCs are an important and abundant component of these dryland ecosystems, and show patterns of biodiversity associated with biomass, as measured by chlorophyll-a concentrations and species counts.
The major finding of this study, as implied in the title, is that BSC distribution and composition is primarily controlled by patterns of rainfall, but not total rainfall. Species richness and successional stage of BSCs was highest in the winter rain zone, which has a shorter dry season though less total annual rainfall than the summer rain zone. This implies that most BSC organisms are limited by drought tolerance rather than annual water input.
This study is interesting to me for a number of reasons. First, it includes in the references a number of reviews of BSCs and methods to study them, such as protocols for measuring chlorophyll-a concentrations per square metre, and molecular methods for species richness estimation. Second, because BSCs are expected to be the major photosynthetic organisms in the polar desert, I need to know what patterns of their distribution and diversity I should expect. This paper’s Hypothesis 4, that biomass (and productivity) of BSCs increases with species richness, which was essentially confirmed, is of particular interest in this context, as it provides another layer of background expected pattern in addition to my general expectation of a species-richness gradient associated with latitude, particularly as one crosses Lancaster Sound north of Baffin Island. This paper provides some ideas for ways to measure species richness in BSCs, which (third) contribute strongly to the overall biodiversity of dryland regions and therefore will be interesting in their own right in studies of Arctic Biogeography.
These authors examined biological soil crusts (BSCs) along a 2000km transect running roughly north-south through Namibia and South Africa. A number of hypotheses relating to BSC composition, frequency, and succession were proposed and tested, with most hypotheses partly confirmed. In general, BSCs are an important and abundant component of these dryland ecosystems, and show patterns of biodiversity associated with biomass, as measured by chlorophyll-a concentrations and species counts.
The major finding of this study, as implied in the title, is that BSC distribution and composition is primarily controlled by patterns of rainfall, but not total rainfall. Species richness and successional stage of BSCs was highest in the winter rain zone, which has a shorter dry season though less total annual rainfall than the summer rain zone. This implies that most BSC organisms are limited by drought tolerance rather than annual water input.
This study is interesting to me for a number of reasons. First, it includes in the references a number of reviews of BSCs and methods to study them, such as protocols for measuring chlorophyll-a concentrations per square metre, and molecular methods for species richness estimation. Second, because BSCs are expected to be the major photosynthetic organisms in the polar desert, I need to know what patterns of their distribution and diversity I should expect. This paper’s Hypothesis 4, that biomass (and productivity) of BSCs increases with species richness, which was essentially confirmed, is of particular interest in this context, as it provides another layer of background expected pattern in addition to my general expectation of a species-richness gradient associated with latitude, particularly as one crosses Lancaster Sound north of Baffin Island. This paper provides some ideas for ways to measure species richness in BSCs, which (third) contribute strongly to the overall biodiversity of dryland regions and therefore will be interesting in their own right in studies of Arctic Biogeography.
Monday, September 21, 2009
Pilegaard et al. 2006
Pilegaard K, Skiba U, Ambus P, Beier C, Bruggemann N, Butterbach-Bahl, Dick J, Dorsey J, Duyzer J, Gallagher M, Gasche R, Horvath L, Kitzler B, Leip A, Pihlatie MK, Rosenkranz P, Seufert G, Vesala T, Westrate H, Zechmeister-Boltenstern S. 2006. Factors controlling regional differences in forest soil emission of nitrogen oxides (NO and N2O). Biogeosciences 3: 651-661.
These (abundant) authors present an analysis of a large combined dataset covering NO and N2O emissions from a range of forest systems in Europe. The measurements contributing to this large dataset were continuous measures (at least daily, usually hourly or better) and run at least one year. This provides a high-quality dataset that includes variation induced by seasonality.
One of the most interesting findings in this study is a scale-dependent relationship between soil parameters and N2O emissions. Within-forests, soil temperature and moisture were highly predictive of N2O flux, but not at scales encompassing multiple forests in comparison. At larger spatial scales, stand age and C/N ratio were much better predictors.
These (abundant) authors present an analysis of a large combined dataset covering NO and N2O emissions from a range of forest systems in Europe. The measurements contributing to this large dataset were continuous measures (at least daily, usually hourly or better) and run at least one year. This provides a high-quality dataset that includes variation induced by seasonality.
One of the most interesting findings in this study is a scale-dependent relationship between soil parameters and N2O emissions. Within-forests, soil temperature and moisture were highly predictive of N2O flux, but not at scales encompassing multiple forests in comparison. At larger spatial scales, stand age and C/N ratio were much better predictors.
Chen et al. 2008
Chen Y, Dumont MG, Neufeld JD, Bodrossy L, Stralis-Pavese N, McNamara NP, Ostle N, Briones MJI, Murrell JC. 2008. Revealing the uncultivated majority: combining DNA stable-isotope probing, multiple displacement amplification and metagenomic analyses of uncultivated Methylocystis in acidic peatlands. Environmental Microbiology 10: 2609-2622.
These authors used a multiple-methods approach to isolate and identify DNA from a group of methanotrophic prokaryotes that have previously resisted attempts at culture. These microbes were previously estimated to be highly abundant in peatland soils, and were found in soils from a range of peatlands in Europe.
The three methods used to investigate these microbes were 1. a microarray built using sequences derived from a key enzyme in the methanotrophic process, 2. DNA-SIP, DNA Stable-Isotope Probing, used to examine DNA replicated with an injection of 13C-labelled CH4 (such that only methanotrophs would be able to use the carbon in their metabolisms), and 3. MDA, Multiple-Displacement Amplification to generate sufficient template DNA for fosmid-library construction and subsequent DGGE and cladistic analysis.
This triple-combined approach allowed the isolation, identification, and some basic phylogenetic analysis of a group of ecologically-important microbes previously unstudied in such a way. From my perspective, currently the most useful parts of this paper are the references (containing reviews of metagenomics and microarrays) and the methods section, as I may be attempting similar analyses of polar desert soils.
These authors used a multiple-methods approach to isolate and identify DNA from a group of methanotrophic prokaryotes that have previously resisted attempts at culture. These microbes were previously estimated to be highly abundant in peatland soils, and were found in soils from a range of peatlands in Europe.
The three methods used to investigate these microbes were 1. a microarray built using sequences derived from a key enzyme in the methanotrophic process, 2. DNA-SIP, DNA Stable-Isotope Probing, used to examine DNA replicated with an injection of 13C-labelled CH4 (such that only methanotrophs would be able to use the carbon in their metabolisms), and 3. MDA, Multiple-Displacement Amplification to generate sufficient template DNA for fosmid-library construction and subsequent DGGE and cladistic analysis.
This triple-combined approach allowed the isolation, identification, and some basic phylogenetic analysis of a group of ecologically-important microbes previously unstudied in such a way. From my perspective, currently the most useful parts of this paper are the references (containing reviews of metagenomics and microarrays) and the methods section, as I may be attempting similar analyses of polar desert soils.
Friday, September 18, 2009
Barrett et al. 2006
Barrett JE, Virginia RA, Wall DH, Cary SC, Adams BJ, Hacker AL, Aislabie JM. 2006. Co-variation in soil biodiversity and biogeochemistry in northern and southern Victoria Land, Antarctica. Antarctic Science 18: 535-548.
These authors examined soil biota at three sites across about 7 degrees of latitude in the drier part of Antarctica. The latitudinal gradient here covers a range of different ecosystems, from relatively wet, more northern and coastal systems to extremely arid and barren southern systems. Here, latitude is not studied for its effects on ecosystems; its effects on ecosystems are exploited to cover the widest available range of conditions. Within each of the three sites, one wet and one dry location were chosen a priori based on obvious surface features such as meltwater drainage channels and the presence of moss beds. At each location, a set of transects were laid out and samples were collected. To quote them directly:
Soil invertebrates were investigated using both morphological and molecular techniques. There are only four metazoan phyla with any significant presence in Antarctica’s soils (Arthropoda, Nematoda, Rotifera, and Tardigrada), all of which are difficult to identify to species using standard morphological methods. While these authors were able to identify nematodes to species, rotifers, tardigrades, and mites were handled as MOTUs, molecular operational taxonomic units (Floyd et al. 2002). These MOTUs, based on ribosomal DNA sequences, were also used to generate a series of cladograms used to assess biodiversity at the research sites. Unfortunately, while the text descriptions of the methods and results are reasonably clear, the figures relating to the biodiversity and metazoan-molecular work are confusing and poorly described.
The results of the microbial analyses are broadly similar to the metazoan dataset. These authors were able to examine biodiversity at the level of microbes, and compare this diversity to both soil chemical characteristics such as water content and C:N ratio, and to the metazoan diversity. Perhaps surprisingly, they found no evidence to support the hypothesis of top-down control on bacterial populations by metazoan predators, as there was no correlation between DGGE and FAME-derived estimates of bacterial population size and species richness and cladogram and sugar-extract-derived estimates of nematode biodiversity. Bacterial diversity is described as not varying across sites, though community composition does. I take this to mean that while total species richness of bacteria (as measured by DGGE) was constant across sites, species turnover (Beta-diversity) was high. This is interesting to me, though not mentioned in the paper, because it seems to directly contradict the microbial-biogeography hypothesis of “everything is everywhere”. There is a mention in the description of this comparison of the importance of geography in structuring biodiversity, which reads to me like an opportunity to apply explicit geospatial techniques to their dataset.
Overall, while it is true that Antarctic soil ecosystems are extremely simple relative to other systems, there are a great many complex and variable interactions between even the few components of these systems, creating a great deal of complexity. This paper will be very useful to me in structuring some of my own investigations in the Arctic.
These authors examined soil biota at three sites across about 7 degrees of latitude in the drier part of Antarctica. The latitudinal gradient here covers a range of different ecosystems, from relatively wet, more northern and coastal systems to extremely arid and barren southern systems. Here, latitude is not studied for its effects on ecosystems; its effects on ecosystems are exploited to cover the widest available range of conditions. Within each of the three sites, one wet and one dry location were chosen a priori based on obvious surface features such as meltwater drainage channels and the presence of moss beds. At each location, a set of transects were laid out and samples were collected. To quote them directly:
"We investigated the structure (bacterial and metazoan diversity) and functioning (soil respiration) of soil communities and the influence of soil biogeochemical properties (organic matter, inorganic nutrients, physicochemical properties) on habitat suitability."This is quite similar in many respects to my planned investigations in the Arctic polar desert. The list of molecular techniques used in this paper, for example, serves as a useful guide or checklist of the procedures I intend to use.
Soil invertebrates were investigated using both morphological and molecular techniques. There are only four metazoan phyla with any significant presence in Antarctica’s soils (Arthropoda, Nematoda, Rotifera, and Tardigrada), all of which are difficult to identify to species using standard morphological methods. While these authors were able to identify nematodes to species, rotifers, tardigrades, and mites were handled as MOTUs, molecular operational taxonomic units (Floyd et al. 2002). These MOTUs, based on ribosomal DNA sequences, were also used to generate a series of cladograms used to assess biodiversity at the research sites. Unfortunately, while the text descriptions of the methods and results are reasonably clear, the figures relating to the biodiversity and metazoan-molecular work are confusing and poorly described.
The results of the microbial analyses are broadly similar to the metazoan dataset. These authors were able to examine biodiversity at the level of microbes, and compare this diversity to both soil chemical characteristics such as water content and C:N ratio, and to the metazoan diversity. Perhaps surprisingly, they found no evidence to support the hypothesis of top-down control on bacterial populations by metazoan predators, as there was no correlation between DGGE and FAME-derived estimates of bacterial population size and species richness and cladogram and sugar-extract-derived estimates of nematode biodiversity. Bacterial diversity is described as not varying across sites, though community composition does. I take this to mean that while total species richness of bacteria (as measured by DGGE) was constant across sites, species turnover (Beta-diversity) was high. This is interesting to me, though not mentioned in the paper, because it seems to directly contradict the microbial-biogeography hypothesis of “everything is everywhere”. There is a mention in the description of this comparison of the importance of geography in structuring biodiversity, which reads to me like an opportunity to apply explicit geospatial techniques to their dataset.
Overall, while it is true that Antarctic soil ecosystems are extremely simple relative to other systems, there are a great many complex and variable interactions between even the few components of these systems, creating a great deal of complexity. This paper will be very useful to me in structuring some of my own investigations in the Arctic.
Tuesday, September 15, 2009
Ettema & Wardle 2002
Ettema CH, Wardle DA. 2002. Spatial soil ecology. Trends in Ecology & Evolution 17: 177-183.
These authors review the growing use of explicit geospatial analysis techniques in soil biology. As this is a TREE article, there are several helpful boxes that explain fundamentals of geospatial analysis such as the terminology and key case studies. This is also a review article, so there are descriptions of various previous studies that include evidence useful in answering the questions set out in this paper. These questions are 1) What are the scales, patterns and causes of spatial variability in soil organism distributions? 2) What are the implications of spatial variability for the structure and function of soil communities? 3) How do spatial properties of the soil biota influence plant communities?
Regarding question 1, the scales and patterns of spatial variability in soil organisms range from 10s and 100s of metres down to millimetres. Studies of soil microbes including methanogenic Archaea have included soil corers of 1mm diameter (based on a hollow needle) and aggregations of organisms separated by distances of 2 to 4mm.
Soil communities and their influence on plant communities were found to be highly non-uniform, and show predictable though complex spatial patterns. However, while much was made of the role of individual plants (especially trees) to structure the soils around them and create spatial patterns of microbes and invertebrates on the same scale as the trees themselves are distributed, very little was made of the role that small-scale aggregations play in structuring larger patterns. This is surprising, given the highly biased view of soil processes in this paper and more generally in the soil science literature: soil is viewed as something that exists primarily to support plants, rather than a system of its own independent importance. That is the impression I have gotten, at least.
This paper is a very useful overview of geospatial analysis, and the reference list includes a number of similarly useful papers. In particular, further exploration of the statistics of semivariance patterns seems useful.
These authors review the growing use of explicit geospatial analysis techniques in soil biology. As this is a TREE article, there are several helpful boxes that explain fundamentals of geospatial analysis such as the terminology and key case studies. This is also a review article, so there are descriptions of various previous studies that include evidence useful in answering the questions set out in this paper. These questions are 1) What are the scales, patterns and causes of spatial variability in soil organism distributions? 2) What are the implications of spatial variability for the structure and function of soil communities? 3) How do spatial properties of the soil biota influence plant communities?
Regarding question 1, the scales and patterns of spatial variability in soil organisms range from 10s and 100s of metres down to millimetres. Studies of soil microbes including methanogenic Archaea have included soil corers of 1mm diameter (based on a hollow needle) and aggregations of organisms separated by distances of 2 to 4mm.
Soil communities and their influence on plant communities were found to be highly non-uniform, and show predictable though complex spatial patterns. However, while much was made of the role of individual plants (especially trees) to structure the soils around them and create spatial patterns of microbes and invertebrates on the same scale as the trees themselves are distributed, very little was made of the role that small-scale aggregations play in structuring larger patterns. This is surprising, given the highly biased view of soil processes in this paper and more generally in the soil science literature: soil is viewed as something that exists primarily to support plants, rather than a system of its own independent importance. That is the impression I have gotten, at least.
This paper is a very useful overview of geospatial analysis, and the reference list includes a number of similarly useful papers. In particular, further exploration of the statistics of semivariance patterns seems useful.
Monday, September 14, 2009
Garten et al. 2007
Garten CT Jr., Kang S, Brice DJ, Schadt CW, Zhou J. 2007. Variability in soil properties at different spatial scales (1m-1km) in a deciduous forest ecosystem. Soil Biology & Biochemistry 39: 2621-2627.
These authors examined some of the fundamental assumptions of geospatial analysis as applied to soil properties, in a pair of transects that I strongly suspect have been used repeatedly for many studies in Tennessee (see, e.g. Zhou et al. 2008). One of the fundamental assumptions is of spatial autocorrelation, that is, samples in close proximity will be more similar to each other than samples separated by greater distances. In this study, this assumption was stated as the null hypothesis “there are no differences in variance at different spatial scales”; a rejection of this null hypothesis can be interpreted as support for the “common sense” (their wording) principle of spatial autocorrelation, at least among the spatial scales discussed here (i.e. metres to kilometres). This and other important assumptions of geospatial analysis come from a series of papers applying these principles to soils, which I should probably read soon.
The 11 soil variables examined in this paper were distinctly non-orthogonal in their relationships. Many of the variables were calculated directly from other variables, and the majority takes the form of either ratios (such as C-to-N) or fractions (such as silt content). The Principle Components Analysis (PCA) these authors conducted on their final, grand-total dataset indicated that the usual suspects of soil properties were important – soil Carbon, soil Nitrogen, and soil Texture are one way to summarize the first three PC variables.
I looked up and read this paper mainly because of the statistical tests used here and the discussion of them. They conducted 5 main statistical tests.
1. Bartlett’s test for equal variances at different distances.
2. Bartlett’s test is sensitive to non-normal data, so they also used the non-parametric Spearman’s Rank Correlation between coefficients of variation (100 x S.D./mean). The other reason a non-parametric test was used was that the functional relationship (linear vs. non-linear) between variance and sampling distance was unknown.
3. Mantel and Partial Mantel tests. These were the central analysis, I think, and provided most of the key results regarding the tests of the main hypotheses. Apparently, Burrough (1993) recommends semivariogram analysis, but the present data set was not amenable to such.
4. PCA, as mentioned above.
5. Power analysis. How many samples would they need to collect to be more certain of being close to the true mean value in their estimates?
Besides the PCA, which produced utterly unsurprising results, I think the statistical tests deployed here will serve as models for my own analysis of 2009 and putative 2010 datasets from the High Arctic. In particular, the Mantel tests and the Power analysis should be very useful in my own examinations.
Overall, the geospatial assumption of spatial autocorrelation was not very well supported by this study. Many soil properties appear to be highly variable at small spatial scales, such that samples collected within a few metres of each other are as variable as samples collected from up to a kilometre away, at least in a temperate forest ecosystem as studied here. This is particularly surprising in light of the consideration of the structure of such a forest, where individual trees presumably have strong impacts on soil properties within perhaps 5 to 10 metres of their trunks.
These authors examined some of the fundamental assumptions of geospatial analysis as applied to soil properties, in a pair of transects that I strongly suspect have been used repeatedly for many studies in Tennessee (see, e.g. Zhou et al. 2008). One of the fundamental assumptions is of spatial autocorrelation, that is, samples in close proximity will be more similar to each other than samples separated by greater distances. In this study, this assumption was stated as the null hypothesis “there are no differences in variance at different spatial scales”; a rejection of this null hypothesis can be interpreted as support for the “common sense” (their wording) principle of spatial autocorrelation, at least among the spatial scales discussed here (i.e. metres to kilometres). This and other important assumptions of geospatial analysis come from a series of papers applying these principles to soils, which I should probably read soon.
The 11 soil variables examined in this paper were distinctly non-orthogonal in their relationships. Many of the variables were calculated directly from other variables, and the majority takes the form of either ratios (such as C-to-N) or fractions (such as silt content). The Principle Components Analysis (PCA) these authors conducted on their final, grand-total dataset indicated that the usual suspects of soil properties were important – soil Carbon, soil Nitrogen, and soil Texture are one way to summarize the first three PC variables.
I looked up and read this paper mainly because of the statistical tests used here and the discussion of them. They conducted 5 main statistical tests.
1. Bartlett’s test for equal variances at different distances.
2. Bartlett’s test is sensitive to non-normal data, so they also used the non-parametric Spearman’s Rank Correlation between coefficients of variation (100 x S.D./mean). The other reason a non-parametric test was used was that the functional relationship (linear vs. non-linear) between variance and sampling distance was unknown.
3. Mantel and Partial Mantel tests. These were the central analysis, I think, and provided most of the key results regarding the tests of the main hypotheses. Apparently, Burrough (1993) recommends semivariogram analysis, but the present data set was not amenable to such.
4. PCA, as mentioned above.
5. Power analysis. How many samples would they need to collect to be more certain of being close to the true mean value in their estimates?
Besides the PCA, which produced utterly unsurprising results, I think the statistical tests deployed here will serve as models for my own analysis of 2009 and putative 2010 datasets from the High Arctic. In particular, the Mantel tests and the Power analysis should be very useful in my own examinations.
Overall, the geospatial assumption of spatial autocorrelation was not very well supported by this study. Many soil properties appear to be highly variable at small spatial scales, such that samples collected within a few metres of each other are as variable as samples collected from up to a kilometre away, at least in a temperate forest ecosystem as studied here. This is particularly surprising in light of the consideration of the structure of such a forest, where individual trees presumably have strong impacts on soil properties within perhaps 5 to 10 metres of their trunks.
Thursday, September 10, 2009
Zhou et al. 2008
Zhou J, Kang S, Schadt CW, Garten CT Jr. 2008. Spatial scaling of functional gene diversity across various microbial taxa. Proceedings of the National Academy of Sciences of the USA 105: 7768-7773.
These authors used a microarray-based technique to estimate biodiversity of soil microbes across a pair of transects in a forest in Tennessee. Their analysis found rates of species turnover through space much lower than rates for macroorganisms such as “higher” plants and animals.
The species-area relationship, generalized to the Taxa-Area-Relationship (TAR), is S=cA^z, where S is the number of species, A is the area, c is the intercept in log-log space, and z is a measure of the rate of species turnover across space. Values of z for macroorganisms have been estimated close the theoretically derived value of 0.25, while previous estimates for microbes have been often much lower, but occasionally much higher. This study found a range of z-values, all a bit less than 0.1.
The key technique used in this study was the GeoChip, a microarray with nearly 25000 50-mer probes for more than 10000 genes in functional groups such as denitrification or heavy-metal resistance. As such, it represents an excellent tool for such investigations, because it reduces or avoids many of the microbe-diversity sampling artifacts such as undersampling that plague other methods.
A large fraction of the observed variation in sequences across the transects was unexplained. These authors speculate that a fraction of this unexplained variation may be driven by unexamined patterns and processes including biotic interactions (competition, trophic interaction), abiotic interactions (O2 concentrations, labile C pool), and microscale effects below 1m scales.
One interesting suggestion by these authors is to use metagenomic approaches to characterize key sequences of interest in a particular system, and then examine biodiversity using a microarray customized for these sequences. This is in line with what I was thinking in regards to using such techniques in polar desert soils – first, characterize what is there; second, look at biodiversity and patterns within diversity relating to groups of interest.
These authors used a microarray-based technique to estimate biodiversity of soil microbes across a pair of transects in a forest in Tennessee. Their analysis found rates of species turnover through space much lower than rates for macroorganisms such as “higher” plants and animals.
The species-area relationship, generalized to the Taxa-Area-Relationship (TAR), is S=cA^z, where S is the number of species, A is the area, c is the intercept in log-log space, and z is a measure of the rate of species turnover across space. Values of z for macroorganisms have been estimated close the theoretically derived value of 0.25, while previous estimates for microbes have been often much lower, but occasionally much higher. This study found a range of z-values, all a bit less than 0.1.
The key technique used in this study was the GeoChip, a microarray with nearly 25000 50-mer probes for more than 10000 genes in functional groups such as denitrification or heavy-metal resistance. As such, it represents an excellent tool for such investigations, because it reduces or avoids many of the microbe-diversity sampling artifacts such as undersampling that plague other methods.
A large fraction of the observed variation in sequences across the transects was unexplained. These authors speculate that a fraction of this unexplained variation may be driven by unexamined patterns and processes including biotic interactions (competition, trophic interaction), abiotic interactions (O2 concentrations, labile C pool), and microscale effects below 1m scales.
One interesting suggestion by these authors is to use metagenomic approaches to characterize key sequences of interest in a particular system, and then examine biodiversity using a microarray customized for these sequences. This is in line with what I was thinking in regards to using such techniques in polar desert soils – first, characterize what is there; second, look at biodiversity and patterns within diversity relating to groups of interest.
Friday, September 4, 2009
Broll et al. 1999
Broll G, Tarnocai C, Mueller G. 1999. Interactions between vegetation, nutrients and moisture in soils in the Pangnirtung Pass area, Baffin island, Canada. Permafrost and Periglacial Processes 10: 265-277.
These authors examined soils from 6 pedons in Pangnirtung Pass, a north-south pass between mountains on Cumberland Peninsula. Three pedons were from moist soils, and three from dry soils. The moisture content drove a major difference in soil structure: dry soils are not cryoturbated, resulting in strong differences in nutrient content and mineralization rates.
The goal of the study was to compare in detail these differences between dry and moist soils. This seems very similar to my PhD goals surrounding examinations of Polar Desert soils. This study thus represents a possible template for some of my own investigations.
These authors examined soils from 6 pedons in Pangnirtung Pass, a north-south pass between mountains on Cumberland Peninsula. Three pedons were from moist soils, and three from dry soils. The moisture content drove a major difference in soil structure: dry soils are not cryoturbated, resulting in strong differences in nutrient content and mineralization rates.
The goal of the study was to compare in detail these differences between dry and moist soils. This seems very similar to my PhD goals surrounding examinations of Polar Desert soils. This study thus represents a possible template for some of my own investigations.
Wednesday, September 2, 2009
Bockheim 1979
Bockheim JG. 1979. Properties and relative age of soils of southwestern Cumberland peninsula, Baffin island, N.W.T., Canada. Arctic and Alpine Research 11: 289-306.
This author sampled soils from more than 60 sites on the Cumberland peninsula of Baffin Island, mostly near the hamlet of Pangnirtung. This covered soils from two tundra vegetations (Dwarf shrub-sedge-moss-lichen on lowlands and coastal, stony sedge-moss-lichen in highlands and northern fjords) and the Polar Desert of Baffin island. The tundra soils ranged from mesic to subxeric, while the desert near Penny icecap was xeric. A similar gradient driven by latitude rather than altitude is referenced in Tedrow (1973).
Descriptions are made of the pH and various exchangeable and free minerals in the soils, along with how those components change with depth in each area. pH increases with depth, for example, especially in the Polar Desert. Phosphorus was found in surprisingly high levels in all soils. The active layer, or at least the layer above the permafrost, is much deeper than found on Ellesmere island, and appears to be deeper than 1m everywhere studied in this paper.
This author sampled soils from more than 60 sites on the Cumberland peninsula of Baffin Island, mostly near the hamlet of Pangnirtung. This covered soils from two tundra vegetations (Dwarf shrub-sedge-moss-lichen on lowlands and coastal, stony sedge-moss-lichen in highlands and northern fjords) and the Polar Desert of Baffin island. The tundra soils ranged from mesic to subxeric, while the desert near Penny icecap was xeric. A similar gradient driven by latitude rather than altitude is referenced in Tedrow (1973).
Descriptions are made of the pH and various exchangeable and free minerals in the soils, along with how those components change with depth in each area. pH increases with depth, for example, especially in the Polar Desert. Phosphorus was found in surprisingly high levels in all soils. The active layer, or at least the layer above the permafrost, is much deeper than found on Ellesmere island, and appears to be deeper than 1m everywhere studied in this paper.
Niederberger et al. 2008
Neiderberger TD, McDonald IR, Hacker AL, Soo RM, Barrett JE, Wall DH, Cary SC. 2008. Microbial community composition in soils of Northern Victoria Land, Antarctica. Environmental Microbiology 10: 1713-1724.
These authors present an analysis of a large collection of data regarding both microbial and metazoan biodiversity at relatively small scales in one part of Taylor Valley, Antarctica, one of the famous Dry Valleys. This contributes to both the Latitudinal Gradient Project, an international effort to characterize Antarctica, and to the biogeographical debate regarding the distribution and community assemblages of microbes and soil microfauna.
Biodiversity was higher than expected based on the physical characteristics of this extreme environment, and was much more variable at small (~200m) spatial scales. While the microbes identified by 16s sequences were not particularly surprising, the changes in community composition between study sites was high. This supports the hypothesis that extreme environments “select for” particular microbial physiologies, and that differences in soil physical features such as moisture and temperature are highly important, in distinct contrast to the “everything is everywhere” hypothesis of microbial biogeography.
NB October 1 2009: the “everything is everwhere” hypothesis (Beijerinck 1913) includes the second clause “the environment selects”, which implies my earlier impressions, above, are incorrect. This paper’s demonstration that extreme environments select for particular soil communities, and that local-scale variables such as moisture and temperature, rather than regional-scale variables such as climate factors, actually supports Beijerinck’s (1913) hypothesis, rather than countering it.
These authors present an analysis of a large collection of data regarding both microbial and metazoan biodiversity at relatively small scales in one part of Taylor Valley, Antarctica, one of the famous Dry Valleys. This contributes to both the Latitudinal Gradient Project, an international effort to characterize Antarctica, and to the biogeographical debate regarding the distribution and community assemblages of microbes and soil microfauna.
Biodiversity was higher than expected based on the physical characteristics of this extreme environment, and was much more variable at small (~200m) spatial scales. While the microbes identified by 16s sequences were not particularly surprising, the changes in community composition between study sites was high. This supports the hypothesis that extreme environments “select for” particular microbial physiologies, and that differences in soil physical features such as moisture and temperature are highly important, in distinct contrast to the “everything is everywhere” hypothesis of microbial biogeography.
NB October 1 2009: the “everything is everwhere” hypothesis (Beijerinck 1913) includes the second clause “the environment selects”, which implies my earlier impressions, above, are incorrect. This paper’s demonstration that extreme environments select for particular soil communities, and that local-scale variables such as moisture and temperature, rather than regional-scale variables such as climate factors, actually supports Beijerinck’s (1913) hypothesis, rather than countering it.
Monday, April 20, 2009
Rolston 1986
Rolston DE. 1986. Gas diffusivity. Pp 1089-1102 in Methods of Soil Analysis Part 1: Physical and Mineralogical Methods 2nd Ed. ed. A Klute. American Society of Agronomy Inc. Soil Science Society of America Inc, Madison, WI.
This author presents a review of the principles and measurement methods of soil gas diffusion, including formulae and relevant calculations. At the heart of all considerations of soil gas diffusion is Fick’s law and the measurement of Dp, the soil gas diffusion constant for a particular gas. There are a wide range of laboratory methods for measuring gas diffusion, but all are based on measuring the passive movement of a target gas through a volume of soil, often by measuring the accumulation of the target gas in a chamber that initially lacks that gas.
Many variables will impact rates of gas diffusion; perhaps of greatest importance is the moisture content of the soil. Wet soils make take hours to measure, while dry soils only a few minutes. Temperature also has a strong effect, and this author urges the reporting of temperatures with all measures of soil diffusion. Additionally, a simple formula is presented that relates diffusion at one temperature to diffusion at a second temperature.
Further calculations surround the determination of Dp, and correcting for errors associated with the details of the measurement chamber. For example, a correction factor can be applied when the ratio of soil air volume to chamber volume is more than about 0.005; this corrects for the gas “stored” in the soil of the measurement apparatus.
This paper is the first of two adjacent chapters in this edited volume by this author, both dealing with soil gas movements. The calculations and formulae here will be very useful in attempts to calibrate the FTIR and the flux chambers.
This author presents a review of the principles and measurement methods of soil gas diffusion, including formulae and relevant calculations. At the heart of all considerations of soil gas diffusion is Fick’s law and the measurement of Dp, the soil gas diffusion constant for a particular gas. There are a wide range of laboratory methods for measuring gas diffusion, but all are based on measuring the passive movement of a target gas through a volume of soil, often by measuring the accumulation of the target gas in a chamber that initially lacks that gas.
Many variables will impact rates of gas diffusion; perhaps of greatest importance is the moisture content of the soil. Wet soils make take hours to measure, while dry soils only a few minutes. Temperature also has a strong effect, and this author urges the reporting of temperatures with all measures of soil diffusion. Additionally, a simple formula is presented that relates diffusion at one temperature to diffusion at a second temperature.
Further calculations surround the determination of Dp, and correcting for errors associated with the details of the measurement chamber. For example, a correction factor can be applied when the ratio of soil air volume to chamber volume is more than about 0.005; this corrects for the gas “stored” in the soil of the measurement apparatus.
This paper is the first of two adjacent chapters in this edited volume by this author, both dealing with soil gas movements. The calculations and formulae here will be very useful in attempts to calibrate the FTIR and the flux chambers.
Tuesday, March 17, 2009
Widén & Lindroth 2003
Widén B, Lindroth A. 2003. A calibration system for soil carbon dioxide-efflux measurement chambers: description and application. Soil Science Society of America Journal, 67: 327-334.
These authors describe a system for the absolute calibration of CO2-flux from soils, for both open- and closed-chamber type systems. The basic design is a large box, topped with a layer of sand, into which CO2 is pumped at a known rate. The measurement chamber sits on top of the layer of sand, and the actual gas flux can be calculated and compared to that measured by the machine.
The system appears to be useful, and a significant improvement in the field. The authors caution that improvements need to be made to the system, cheifly in its size and consideration of the effects of water in the soil on gas flux variations.
These authors describe a system for the absolute calibration of CO2-flux from soils, for both open- and closed-chamber type systems. The basic design is a large box, topped with a layer of sand, into which CO2 is pumped at a known rate. The measurement chamber sits on top of the layer of sand, and the actual gas flux can be calculated and compared to that measured by the machine.
The system appears to be useful, and a significant improvement in the field. The authors caution that improvements need to be made to the system, cheifly in its size and consideration of the effects of water in the soil on gas flux variations.
Staal et al. 2001
Staal M, te Lintel-Hekkert S, Harren F, Stal L. 2001. Nitrogenase activity in cyanobacteria measured by the acetylene reduction assay: a comparison between batch incubation and on-line monitoring. Environmental Microbiology 3(5): 343-351.
These authors present two methods for measuring nitrogenase activity in cyanobacteria, both based on continuous on-line measurement of ethylene produced by the reduction of acetylene by nitrogenase. One method relies on a gas chromatograph to detect ethylene, the other on a not-yet-commercially available laser system. Nitrogenase normally reduces N2 to NH3, but will also reduce other triple bonds such as that between the carbon atoms in acetylene, hence this measurement assay was developed in the late 1960s. The nitrogenase enzyme is inhibited by oxygen, but is very energy-intensive when reducing N2, thus cyanobacteria may fix Nitrogen in a manner dependent upon but separated from photosynthesis in either (at night) time or space (specialized cells).
Previous ethylene-based methods were based on incubations of cells in air-tight containers, for incubation periods sufficient to saturate nitrogenase with acetylene and accumulate sufficient ethylene for detection. Changes in O2 and CO2 concentrations during these hours-long incubations introduce conflating variables; O2 is depleted and CO2 accumulates in the dark, vice-versa in the light. CO2 concentration affects pH, while O2 inhibits nitrogenase and indirectly relates to available energy. In addition, long incubations will fail to detect any event occuring on a frequency shorter than the incubation time, such that processes occurring on time scales of seconds to minutes will not be registered. Finally, saturation of nitrogenase with acetylene eventually leads to nitrogen starvation and the synthesis of more nitrogenase.
In contrast, on-line methods involve the continuous flow of gas over the sample. This can be used to measure gas flux only when the system reaches a steady state (however, see the discussion of steady-state and non-steady-state modes in gas sampling chambers in Davidson et al., 2002). For nitrogenase-ethylene, this steady state may be reached as quickly as 1 minute under ideal, high-surface-area conditions. In addition, while O2 and CO2 concentrations are controlled during on-line measurement, ethylene cannot accumulate, thus only very low concentrations will be present.
Nitrogenase activity was higher under light-saturation conditions than in the dark, but became inhibitory with longer incubation times. Changes in nitrogenase activity with time and light level probably relate to both energy limitation in the dark and oxygen inhibition in the light. Changes relating to growth, internal rythms, or energy depletion only occurred after very long incubations, such as 24 hours. I am not certain how long-term energy depletion is distinct from short term energy limitation in the dark.
This paper suggests it may be possible for us to measure nitrogenase activity with acetylene and ethylene using the Gasmet FTIR system and its chambers.
These authors present two methods for measuring nitrogenase activity in cyanobacteria, both based on continuous on-line measurement of ethylene produced by the reduction of acetylene by nitrogenase. One method relies on a gas chromatograph to detect ethylene, the other on a not-yet-commercially available laser system. Nitrogenase normally reduces N2 to NH3, but will also reduce other triple bonds such as that between the carbon atoms in acetylene, hence this measurement assay was developed in the late 1960s. The nitrogenase enzyme is inhibited by oxygen, but is very energy-intensive when reducing N2, thus cyanobacteria may fix Nitrogen in a manner dependent upon but separated from photosynthesis in either (at night) time or space (specialized cells).
Previous ethylene-based methods were based on incubations of cells in air-tight containers, for incubation periods sufficient to saturate nitrogenase with acetylene and accumulate sufficient ethylene for detection. Changes in O2 and CO2 concentrations during these hours-long incubations introduce conflating variables; O2 is depleted and CO2 accumulates in the dark, vice-versa in the light. CO2 concentration affects pH, while O2 inhibits nitrogenase and indirectly relates to available energy. In addition, long incubations will fail to detect any event occuring on a frequency shorter than the incubation time, such that processes occurring on time scales of seconds to minutes will not be registered. Finally, saturation of nitrogenase with acetylene eventually leads to nitrogen starvation and the synthesis of more nitrogenase.
In contrast, on-line methods involve the continuous flow of gas over the sample. This can be used to measure gas flux only when the system reaches a steady state (however, see the discussion of steady-state and non-steady-state modes in gas sampling chambers in Davidson et al., 2002). For nitrogenase-ethylene, this steady state may be reached as quickly as 1 minute under ideal, high-surface-area conditions. In addition, while O2 and CO2 concentrations are controlled during on-line measurement, ethylene cannot accumulate, thus only very low concentrations will be present.
Nitrogenase activity was higher under light-saturation conditions than in the dark, but became inhibitory with longer incubation times. Changes in nitrogenase activity with time and light level probably relate to both energy limitation in the dark and oxygen inhibition in the light. Changes relating to growth, internal rythms, or energy depletion only occurred after very long incubations, such as 24 hours. I am not certain how long-term energy depletion is distinct from short term energy limitation in the dark.
This paper suggests it may be possible for us to measure nitrogenase activity with acetylene and ethylene using the Gasmet FTIR system and its chambers.
Martin et al. 2004
Martin JG, Bolstad PV, Norman JM. 2004. A carbon dioxide flux generator for testing infrared gas analyzer-based soil respiration systems. Soil Science Society of America Journal 68: 514-518.
These authors constructed a system for calibrating soil CO2 flux using a closed-chamber Infrared Gas Analyzer (IRGA), in this case a Li-Cor 6400. Two detectors were used: one to monitor the CO2 concentration inside the reservoir, and one as the test machine placed on top of the artificial soil on top of the reservoir. The basic construction was quite simple, compared with the systems of Butnor and Johnsen (2004) and Widen and Lindroth (2003). Essentially, this system is just a cylinder topped by a level layer of uniform glass beads. CO2 is added to the reservoir beneath, apparently by the simple method of exhaling into the input valve, and diffuses through the reservoir (mixed by a small fan) and through the glass bead layer.
Much of the refinement of this system concerns the placement of mixing fans to 1) ensure the reservoir is well-mixed but not pressurized and 2) disrupt the boundary layer on top of the glass beads. Boundary layer effects are blamed for some of the measurement error reported here.
The test system underestimated low fluxes, and overestimated high fluxes. These authors suggest that wind-speed differences inside vs. outside the closed chamber, and associated boundary layer differences, are the main drivers of these measurement errors. They also strongly caution that variation in the set point inside the reservoir has a large effect on measured flux rates. Under field conditions, with soil composed of smaller particles, these errors are expected to be less important.
These authors constructed a system for calibrating soil CO2 flux using a closed-chamber Infrared Gas Analyzer (IRGA), in this case a Li-Cor 6400. Two detectors were used: one to monitor the CO2 concentration inside the reservoir, and one as the test machine placed on top of the artificial soil on top of the reservoir. The basic construction was quite simple, compared with the systems of Butnor and Johnsen (2004) and Widen and Lindroth (2003). Essentially, this system is just a cylinder topped by a level layer of uniform glass beads. CO2 is added to the reservoir beneath, apparently by the simple method of exhaling into the input valve, and diffuses through the reservoir (mixed by a small fan) and through the glass bead layer.
Much of the refinement of this system concerns the placement of mixing fans to 1) ensure the reservoir is well-mixed but not pressurized and 2) disrupt the boundary layer on top of the glass beads. Boundary layer effects are blamed for some of the measurement error reported here.
The test system underestimated low fluxes, and overestimated high fluxes. These authors suggest that wind-speed differences inside vs. outside the closed chamber, and associated boundary layer differences, are the main drivers of these measurement errors. They also strongly caution that variation in the set point inside the reservoir has a large effect on measured flux rates. Under field conditions, with soil composed of smaller particles, these errors are expected to be less important.
Marion et al. 1997
Marion GM, Henry GHR, Freckman DW, Johnstone J, Jones G, Jones MH, Levesque E, Molau U, Molgaard P, Parsons AN, Svoboda J, Virginia RA. 1997. Open-top designs for mainpulating field temperature in high-latitude ecosystems. Global Change Biology 3 (suppl. 1): 20-32.
These authors evaluated 4 different chamber designs under field conditions, examining many variables but focusing on temperature differences between the inside and outside of the chambers, and unintended ecological effects. The four designs were termed “ITEX corners”, “cone chambers”, “hexagon chambers”, and “plastic tent”. There were 6 field sites, 5 in the Arctic from Sweden to Canada, and 1 in Antarctica.
This paper represents one of the outcomes of a meeting that established the International Tundra Experiment (ITEX); at this meeting a list of requirements for long-term temperature manipulation devices was constructed, leading to these 4 designs and a requirement to measure ecological effects such as changes in snow accumulation or melting.
The results were fairly consistent across chamber designs. In general, open-top chambers cause fewer and less severe ecological side-effects than closed designs, but warm the surface of the soil by 1-2 degrees compared with up to 10 or 15 degrees for some closed designs. Side-effects of the open-top chambers included some shading and interception of PAR by the chamber materials, changes in moisture concentrations in the air immediately above the soil surface (though these may have been driven by changes in temperature), and the possibility of interference from animals, such as nutrient addition by birds perching on the chambers. However, CO2 concentrations were not affected by chambers.
One of these authors, GHR Henry, will be working with me this summer at Alexandra Fjord; this was also one of the study sites in this paper.
These authors evaluated 4 different chamber designs under field conditions, examining many variables but focusing on temperature differences between the inside and outside of the chambers, and unintended ecological effects. The four designs were termed “ITEX corners”, “cone chambers”, “hexagon chambers”, and “plastic tent”. There were 6 field sites, 5 in the Arctic from Sweden to Canada, and 1 in Antarctica.
This paper represents one of the outcomes of a meeting that established the International Tundra Experiment (ITEX); at this meeting a list of requirements for long-term temperature manipulation devices was constructed, leading to these 4 designs and a requirement to measure ecological effects such as changes in snow accumulation or melting.
The results were fairly consistent across chamber designs. In general, open-top chambers cause fewer and less severe ecological side-effects than closed designs, but warm the surface of the soil by 1-2 degrees compared with up to 10 or 15 degrees for some closed designs. Side-effects of the open-top chambers included some shading and interception of PAR by the chamber materials, changes in moisture concentrations in the air immediately above the soil surface (though these may have been driven by changes in temperature), and the possibility of interference from animals, such as nutrient addition by birds perching on the chambers. However, CO2 concentrations were not affected by chambers.
One of these authors, GHR Henry, will be working with me this summer at Alexandra Fjord; this was also one of the study sites in this paper.
Mastepanov et al. 2008
Mastepanov M, Sigsgaard C, Dlugokencky EJ, Houweling S, Strom L, Tamstorf MP, Christensen TR. 2008. Large tundra methane burst during onset of freezing. Nature 456: 628-631.
These authors describe a large emission of methane from a wet tundra site in the Greenland High Arctic, which occurred in late autumn and early winter as the ground froze. This burst of methane emission is of a similar magnitude to the total methane emission from this site during the growing season, and accounts for the previously observed “shoulder” of methane in autumn at high altitudes.
The site is Zackenberg Valley, in the north-east of Greenland at about 74ºN latitude. This site appears to be broadly similar to other High Arctic tundra meadows such as Truelove Lowlands (Devon Island) and Alexandra Fjord (Ellesmere Island) and large parts of northern Russia, with an active layer 20 to 100 cm thick. The growing season measurements here were similar to previous years, and similar to another study in Siberia.
These measurements were made using an automated methane-only laser-based system, that took readings of methane flux every hour, with a data-gathering time of 1 second. Late-season pulses of methane were not observed at lower-latitude sites, possibly because a deeper permafrost “floor” allows methane to diffuse down to deeper soil layers rather than being forced upwards. Spatial and temporal variablity of the freezing methane emissions were very high, suggesting the diffusion paths of methane squeezed out of the soil were dependent upon plant root systems and similar structures.
This paper is the reason my field season at Alexandra Fjord in 2009 may extend as late as August 25 (planned) or September 10 (worst-case scenario). The figures in this paper imply the difference between measured and modeled methane emissions became apparent approximately in late August.
These authors describe a large emission of methane from a wet tundra site in the Greenland High Arctic, which occurred in late autumn and early winter as the ground froze. This burst of methane emission is of a similar magnitude to the total methane emission from this site during the growing season, and accounts for the previously observed “shoulder” of methane in autumn at high altitudes.
The site is Zackenberg Valley, in the north-east of Greenland at about 74ºN latitude. This site appears to be broadly similar to other High Arctic tundra meadows such as Truelove Lowlands (Devon Island) and Alexandra Fjord (Ellesmere Island) and large parts of northern Russia, with an active layer 20 to 100 cm thick. The growing season measurements here were similar to previous years, and similar to another study in Siberia.
These measurements were made using an automated methane-only laser-based system, that took readings of methane flux every hour, with a data-gathering time of 1 second. Late-season pulses of methane were not observed at lower-latitude sites, possibly because a deeper permafrost “floor” allows methane to diffuse down to deeper soil layers rather than being forced upwards. Spatial and temporal variablity of the freezing methane emissions were very high, suggesting the diffusion paths of methane squeezed out of the soil were dependent upon plant root systems and similar structures.
This paper is the reason my field season at Alexandra Fjord in 2009 may extend as late as August 25 (planned) or September 10 (worst-case scenario). The figures in this paper imply the difference between measured and modeled methane emissions became apparent approximately in late August.
Kammann et al. 2005
Kammann C, Grünhage L, Grüters U, Janze S, Jäger H-J. 2005. Response of aboveground grassland biomass and soil moisture to moderate long-term CO2 enrichment. Basic and Applied Ecology 6: 351-365.
These authors present the results of the first 5 years of the GiFACE experiment in Germany (see Jäger et al. 2003). The major findings, as alluded to in the title, concern the response of aboveground biomass and soil moisture to moderate, year-round (but not 24-hour) CO2 enrichment in a temperate, mesic, semi-natural grassland ecosystem.
Compared to other similar studies, the GiFACE experiment found increased grass biomass under CO2 enrichment, no increase in forbs, and no changes in soil moisture. Other studies found less biomass increase, especially of grasses, generally increased forbs both by measures of diversity and by biomass, and generally increased soil moisture. Differences associated with GiFACE include the low CO2 step increase of 20% compared with much higher in other studies, such as doubling, the cutting frequency that is lower than most other studies, and the year-round CO2 enrichment compared with many studies enriching only during the active growing season. Additionally, the mix of species at Giessen may have been “right” for a strong biomass response, with an interaction from the low cutting frequency allowing these strongly responding grasses to increase above ground biomass to a large degree.
This paper suffers from an irritating flaw – a non-significant difference in annual biomass yield between enriched and control plots is described as “non-significantly higher”, an oxymoron. If it’s not significantly higher, it’s not higher.
These authors present the results of the first 5 years of the GiFACE experiment in Germany (see Jäger et al. 2003). The major findings, as alluded to in the title, concern the response of aboveground biomass and soil moisture to moderate, year-round (but not 24-hour) CO2 enrichment in a temperate, mesic, semi-natural grassland ecosystem.
Compared to other similar studies, the GiFACE experiment found increased grass biomass under CO2 enrichment, no increase in forbs, and no changes in soil moisture. Other studies found less biomass increase, especially of grasses, generally increased forbs both by measures of diversity and by biomass, and generally increased soil moisture. Differences associated with GiFACE include the low CO2 step increase of 20% compared with much higher in other studies, such as doubling, the cutting frequency that is lower than most other studies, and the year-round CO2 enrichment compared with many studies enriching only during the active growing season. Additionally, the mix of species at Giessen may have been “right” for a strong biomass response, with an interaction from the low cutting frequency allowing these strongly responding grasses to increase above ground biomass to a large degree.
This paper suffers from an irritating flaw – a non-significant difference in annual biomass yield between enriched and control plots is described as “non-significantly higher”, an oxymoron. If it’s not significantly higher, it’s not higher.
Jäger et al. 2003
Jäger HJ, Schmidt SW, Kammann C, Grünhage L, Müller C, Hanewald K. 2003. The University of Giessen free-air Carbon dioxide enrichment study: description of the experimental site and of a new enrichment system. Journal of Applied Botany – Angewandte Botanik 77: 117-127.
These authors describe the study site and technical details of the operation of a long-term experiment designed to study the impact of rising atmospheric Carbon dioxide concentrations, the GiFACE. In essence, this study system is unique and important, being the only such study currently ongoing in Europe, and is based on what appears to be the leading edge of relevant technology. At its heart, the system consists of a circular open-topped chamber into which CO2 is released under the control of a concentration monitor in the center. Release occurs at the upwind side of the ring, and consistently acheives the target enrichment of about 25% additional CO2 at 40cm above ground. Grassland canopy heights at this site and similar sites in Europe are almost never higher than 50cm.
Turbulence from the blowers disrupts microclimates in and near the rings during the ambient quiet at night, so the blowers are only run during daylight hours. Control plots without enrichment show the expected pattern of higher ambient CO2 concentrations at night, associated with nocturnal respiration and diurnal photosynthesis. These authors do not address the effects of this blower and enrichment schedule may have on a simulation of globally enriched atmospheric CO2.
This paper is the reference provided by Dr. Kammann to provide needed details for my application to the Canadian Food Inspection Agency to import soil samples from the GiFACE site to Canada.
These authors describe the study site and technical details of the operation of a long-term experiment designed to study the impact of rising atmospheric Carbon dioxide concentrations, the GiFACE. In essence, this study system is unique and important, being the only such study currently ongoing in Europe, and is based on what appears to be the leading edge of relevant technology. At its heart, the system consists of a circular open-topped chamber into which CO2 is released under the control of a concentration monitor in the center. Release occurs at the upwind side of the ring, and consistently acheives the target enrichment of about 25% additional CO2 at 40cm above ground. Grassland canopy heights at this site and similar sites in Europe are almost never higher than 50cm.
Turbulence from the blowers disrupts microclimates in and near the rings during the ambient quiet at night, so the blowers are only run during daylight hours. Control plots without enrichment show the expected pattern of higher ambient CO2 concentrations at night, associated with nocturnal respiration and diurnal photosynthesis. These authors do not address the effects of this blower and enrichment schedule may have on a simulation of globally enriched atmospheric CO2.
This paper is the reference provided by Dr. Kammann to provide needed details for my application to the Canadian Food Inspection Agency to import soil samples from the GiFACE site to Canada.
Holtan-Hartwig et al. 2002
Holtan-Hartwig L, Dörsch P, Bakken LR. 2002. Low temperature control of soil denitrifying communities: kinetics of N2O production and reduction. Soil Biology & Biochemistry 34: 1797-1806.
These authors measured the activation energies of N2O production and reduction in soils taken from agricultural settings in Finland, Sweden, and Germany. The underlying observation is that temperate soils show an unexpectedly large emission profile of N2O in late winter and early spring. Other authors have attributed this release to freeze-thaw effects, such as release of N2O trapped in frozen soils. Differences in activation energies could also explain these observations if these activation energies are asymmetrical at low temperatures, such that the activation energy of N2O reduction is much higher than that for N2O production.
N2O is both a greenhouse gas and an ozone-layer depleter. From soils, it is produced in the penultimate step in a series of reactions known collectively as the denitrification pathway: these reactions when run to completion convert nitrate (NO3-) to N2. N2 of course represents a net loss of nitrogen from an ecosystem, since it is no longer available to organisms. However, N2 is utterly harmless, while N2O has important physical effects on the atmosphere. The basic biochemistry and temperature response of this pathway is described in Firestone (1982).
Another underlying observation for this study is that the product ratio of N2O/N2 increases with decreasing temperature; in other words, proportionally more N2O is released from the system compared to N2. If N2O reduction (to N2) has a higher activation energy than N2O production (from NO), this would explain this observation. Another possibility is that the enzyme responsible for N2O reduction is strongly inhibited at some critical low temperature threshold.
The laboratory analyses carried out for this paper are strongly divergent from field conditions, involving anaerobic slurries with an excess of electron acceptors and the removal of NO3-. However, the differences observed between the different soils support other conclusions that N2O emissions from soils varies strongly with soil types and soil sources.
Previously reported activation energies for NO3- loss by denitrification range between about 41 and 89 kJ/mol; a similar range of activation energies was found here for both N2O production and reduction. This suggests that asymmetrical activation energies are not driving the observed changes in N2O flux by season. It seems temperatures close to 0ºC represent a particular challenge to the microbial communities of these soils, but the nature of this challenge remains unclear – this study did not examine community dynamics in any detail. Some details of the methods of preparing soils used here may be important in this regard.
Another possibility, not mutually exclusive with this threshold effect, is that strong decreases in metabolic rates at low temperatures (60-70% per 10ºC) combined with weak decreases in N2O diffusion rates (20-25% per 10ºC in water) allow N2O to escape the biological pathway as temperatures approach zero.
This paper was recommended to me by Dr. Steven Siciliano, as a guide to some of the calculations and comparisons we are doing with soils and greenhouse gases (including N2O) from Alexandra Fjord.
These authors measured the activation energies of N2O production and reduction in soils taken from agricultural settings in Finland, Sweden, and Germany. The underlying observation is that temperate soils show an unexpectedly large emission profile of N2O in late winter and early spring. Other authors have attributed this release to freeze-thaw effects, such as release of N2O trapped in frozen soils. Differences in activation energies could also explain these observations if these activation energies are asymmetrical at low temperatures, such that the activation energy of N2O reduction is much higher than that for N2O production.
N2O is both a greenhouse gas and an ozone-layer depleter. From soils, it is produced in the penultimate step in a series of reactions known collectively as the denitrification pathway: these reactions when run to completion convert nitrate (NO3-) to N2. N2 of course represents a net loss of nitrogen from an ecosystem, since it is no longer available to organisms. However, N2 is utterly harmless, while N2O has important physical effects on the atmosphere. The basic biochemistry and temperature response of this pathway is described in Firestone (1982).
Another underlying observation for this study is that the product ratio of N2O/N2 increases with decreasing temperature; in other words, proportionally more N2O is released from the system compared to N2. If N2O reduction (to N2) has a higher activation energy than N2O production (from NO), this would explain this observation. Another possibility is that the enzyme responsible for N2O reduction is strongly inhibited at some critical low temperature threshold.
The laboratory analyses carried out for this paper are strongly divergent from field conditions, involving anaerobic slurries with an excess of electron acceptors and the removal of NO3-. However, the differences observed between the different soils support other conclusions that N2O emissions from soils varies strongly with soil types and soil sources.
Previously reported activation energies for NO3- loss by denitrification range between about 41 and 89 kJ/mol; a similar range of activation energies was found here for both N2O production and reduction. This suggests that asymmetrical activation energies are not driving the observed changes in N2O flux by season. It seems temperatures close to 0ºC represent a particular challenge to the microbial communities of these soils, but the nature of this challenge remains unclear – this study did not examine community dynamics in any detail. Some details of the methods of preparing soils used here may be important in this regard.
Another possibility, not mutually exclusive with this threshold effect, is that strong decreases in metabolic rates at low temperatures (60-70% per 10ºC) combined with weak decreases in N2O diffusion rates (20-25% per 10ºC in water) allow N2O to escape the biological pathway as temperatures approach zero.
This paper was recommended to me by Dr. Steven Siciliano, as a guide to some of the calculations and comparisons we are doing with soils and greenhouse gases (including N2O) from Alexandra Fjord.
Davidson et al. 2002
Davidson EA, Savage K, Verchot LV, Navarro R. 2002. Minimizing artifacts and biases in chamber-based measurements of soil respiration. Agricultural and Forest Meteorology 113: 21-37.
These authors review published examples of measurements of CO2 flux from soils, especially forest soils, with an emphasis on identifying major sources of error in these measurements and possible strategies to minimize these errors. As suggested by the title, they divide these sources of error into artifacts (systematic errors caused by details of the construction or operation of measurement devices), biases (consistent patterns of over- or under-estimation of fluxes), and sampling uncertainties (including spatial and temporal heterogeneities in both actual and measured gas fluxes).
Photosynthesis is the primary driver of CO2 flux, with soil respiration a close second in terrestrial ecosystems. Soil respiration may account for 60-90% of the total respiration of a temperate forest, but can be difficult to measure. The two primary methods of measurement are eddy covariance, often using tower-based systems, and chambers that are typically placed on or embedded into the soil. Direct comparisons between these methods have found large variances, suggesting that one or both methods includes inherent artifacts and biases that need to be addressed.
Chambers can be operated in one of two modes: steady-state and non-steady-state. In the steady-state mode, the flux of gas from the soil is calculated based on the difference in CO2 concentration between the inflow and outflow openings into the chamber, after the conditions inside the chamber have reached dynamic equilibrium. In the non-steady-state mode, the rate of change of gas concentration inside the chamber is measured over some time interval. Both modes have inherent problems.
Achieving a steady-state is time consumming and uncertain. In addition, the details of the rate of flow of carrier gas through the chamber, as well as the soil type, moisture level, vegetation and litter, and other variables can have a large influence on the measurements of gas concentration. There are also significant difficulties associated with determining when a true equilibrium has been attained, and the relevance of that equilibrium to “natural” conditions immediately above undisturbed soil.
The non-steady-state is easier and quicker to achieve, but again there are difficulties and uncertainties surrounding a large number of other variables. Of principle importance is the concentration gradient of the gas of interest through the soil. Higher or lower pressures inside the chamber, either of total atmosphere or the partial pressure of the gas of interest, will alter the concentration gradient and thereby change the rate of gas diffusion (i.e. the flux).
These authors seem to prefer the non-steady-state mode, at least partly because it is very rapid to get measurements compared to the wait of up to days to ensure equilibrium under the steady-state mode. They include some helpful calculations, based mainly on linear regression, to smooth the process of measuring gas flux under non-steady-state conditions. Essentially, near-continuous monitoring of gas concentrations in the non-steady-state mode allows a fit to a regression, and the disturbance effects induced by placing and initiating the chamber can be ignored.
Despite these mathematical techniques, most chambers tend to underestimate true flux rates, usually by between a trivial amount and 15%. Taller chambers and deeper penetration of collars into soil tend to reduce these sources of error, though again many variables including wind conditions and soil parameters have strong influences.
Minimizing pressure effects is another important factor in reducing errors. Fans for mixing air inside the chamber are probably unnecessary except for the largest chamber designs, though vents are probably critical in nearly all cases. External air entering a chamber through the vents will cause some error, but this is likely to be trivial compared to the avoidance of a pressure differential between the inside and outside of the chamber, especially under windy conditions.
Other minor pieces of advice include always restricting the flow rate through the chamber with a valve, to even out the effects of battery charge on the pump, and careful recalibration of chambers after any change in configuration, especially of vents. The disturbance effects associated with the placement of collars or chambers are mostly attenuated within a day, such that it may be very beneficial to emplace collars well in advance of measuring gas flux with chambers.
Spatial and temporal variation can occur at scales both much larger and much smaller than the sampling footprint of a typical chamber. These authors provide statistical advice to determine the sampling design needed to achieve a given level of confidence that one is measuring something close to the actual mean flux; for a temperate forest system in New England, as few as 6 chambers monitored for a little as 5 minutes may be sufficient to achieve 90% confidence in being within 20% of the true mean.
Diel variation is an important part of the patterns of gas flux in soils. Night-time respiration by plants in the absence of photosynthesis can alter concentration gradients to a large degree, such that true long-term fluxes may only be estimated from 24-hour monitoring. How this may apply to Arctic systems experiencing 24-hour sunlight is beyond the scope of this review.
The extensive list of relevant literature in this paper may be very useful for more information and advice for the calibration, use, and analysis of our FTIR system.
These authors review published examples of measurements of CO2 flux from soils, especially forest soils, with an emphasis on identifying major sources of error in these measurements and possible strategies to minimize these errors. As suggested by the title, they divide these sources of error into artifacts (systematic errors caused by details of the construction or operation of measurement devices), biases (consistent patterns of over- or under-estimation of fluxes), and sampling uncertainties (including spatial and temporal heterogeneities in both actual and measured gas fluxes).
Photosynthesis is the primary driver of CO2 flux, with soil respiration a close second in terrestrial ecosystems. Soil respiration may account for 60-90% of the total respiration of a temperate forest, but can be difficult to measure. The two primary methods of measurement are eddy covariance, often using tower-based systems, and chambers that are typically placed on or embedded into the soil. Direct comparisons between these methods have found large variances, suggesting that one or both methods includes inherent artifacts and biases that need to be addressed.
Chambers can be operated in one of two modes: steady-state and non-steady-state. In the steady-state mode, the flux of gas from the soil is calculated based on the difference in CO2 concentration between the inflow and outflow openings into the chamber, after the conditions inside the chamber have reached dynamic equilibrium. In the non-steady-state mode, the rate of change of gas concentration inside the chamber is measured over some time interval. Both modes have inherent problems.
Achieving a steady-state is time consumming and uncertain. In addition, the details of the rate of flow of carrier gas through the chamber, as well as the soil type, moisture level, vegetation and litter, and other variables can have a large influence on the measurements of gas concentration. There are also significant difficulties associated with determining when a true equilibrium has been attained, and the relevance of that equilibrium to “natural” conditions immediately above undisturbed soil.
The non-steady-state is easier and quicker to achieve, but again there are difficulties and uncertainties surrounding a large number of other variables. Of principle importance is the concentration gradient of the gas of interest through the soil. Higher or lower pressures inside the chamber, either of total atmosphere or the partial pressure of the gas of interest, will alter the concentration gradient and thereby change the rate of gas diffusion (i.e. the flux).
These authors seem to prefer the non-steady-state mode, at least partly because it is very rapid to get measurements compared to the wait of up to days to ensure equilibrium under the steady-state mode. They include some helpful calculations, based mainly on linear regression, to smooth the process of measuring gas flux under non-steady-state conditions. Essentially, near-continuous monitoring of gas concentrations in the non-steady-state mode allows a fit to a regression, and the disturbance effects induced by placing and initiating the chamber can be ignored.
Despite these mathematical techniques, most chambers tend to underestimate true flux rates, usually by between a trivial amount and 15%. Taller chambers and deeper penetration of collars into soil tend to reduce these sources of error, though again many variables including wind conditions and soil parameters have strong influences.
Minimizing pressure effects is another important factor in reducing errors. Fans for mixing air inside the chamber are probably unnecessary except for the largest chamber designs, though vents are probably critical in nearly all cases. External air entering a chamber through the vents will cause some error, but this is likely to be trivial compared to the avoidance of a pressure differential between the inside and outside of the chamber, especially under windy conditions.
Other minor pieces of advice include always restricting the flow rate through the chamber with a valve, to even out the effects of battery charge on the pump, and careful recalibration of chambers after any change in configuration, especially of vents. The disturbance effects associated with the placement of collars or chambers are mostly attenuated within a day, such that it may be very beneficial to emplace collars well in advance of measuring gas flux with chambers.
Spatial and temporal variation can occur at scales both much larger and much smaller than the sampling footprint of a typical chamber. These authors provide statistical advice to determine the sampling design needed to achieve a given level of confidence that one is measuring something close to the actual mean flux; for a temperate forest system in New England, as few as 6 chambers monitored for a little as 5 minutes may be sufficient to achieve 90% confidence in being within 20% of the true mean.
Diel variation is an important part of the patterns of gas flux in soils. Night-time respiration by plants in the absence of photosynthesis can alter concentration gradients to a large degree, such that true long-term fluxes may only be estimated from 24-hour monitoring. How this may apply to Arctic systems experiencing 24-hour sunlight is beyond the scope of this review.
The extensive list of relevant literature in this paper may be very useful for more information and advice for the calibration, use, and analysis of our FTIR system.
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