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.

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.

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.

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).

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.

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.

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.