Davidson et al. 1991

Davidson EA, Hart SC, Shanks CA, Firestone MK. 1991. Measuring gross nitrogen mineralization, immobilization, and nitrification by 15N isotopic pool dilution in intact soil cores. Journal of Soil Science 42: 335-349.

These authors evaluated the use and limitations of the isotope-pool dilution technique when studying nitrogen dynamics in soil. Because addition of inorganic nitrogen compounds (NH4+, NO3-) can stimulate microbial activity in N-limited systems such as most soils, estimating the rate of these processes by tracking 15N through a system will almost certainly overestimate these rates. The isotope-pool dilution method, on the other hand, measures the dilution of enrichment in the nitrogen pool at the end of a particular process, relying on the assumption that additional product of metabolism will have negligible effects on the magnitude of that metabolism. In this study, immobilization of nitrogen was the main focus of investigation, comparing 15N isotope dilution in pools of either 15NH4+ or 15NO3-.

There are three key assumptions for the isotope-pool dilution method in this context. 1. Microorganisms do not discriminate between 15N and 14N; 2. rates of processes measured remain constant over the incubation period; 3. 15N assimilated during the incubation period is not remineralized. Previously, these assumptions had been evaluated for well-mixed soils, but not for unmixed field-collected soil samples. While fractionation by biological processes certainly does result in discrimination between isotopes of nitrogen, it is of negligible importance when injected solutions are very highly enriched and incubation periods are relatively short; in this case, injections were more than 90% 15N and incubations ran for 24 hours. Rates of measured processes will change if the population and / or activity of microorganisms changes, but again, over a 24-hour incubation period under controlled conditions this is unlikely. Highly enriched injections allow the use of small injection volumes, limiting the impact of nutrient enrichment. These authors were able to measure the remineralization of immobilized 15N, and estimated that between 1.0 and 1.6% of injected 15NH4+ appeared in the 15NO3- pool after 24 hours; they consider this an insignificant amount, but caution that longer incubations would almost certainly result in much more problematic amounts of remineralization.

This paper is clearly a major part of the basis of the project I am currently engaged in with Katherine from our 2009 field season at Alexandra Fjord. I probably should have read this paper long ago. The three main conclusions stated by these authors at the end of their paper I think can be quoted verbatim as justification for both why I (should have earlier) read this paper, and as a reminder to myself to include this paper in the methods & materials section of the eventual manuscript.

"Three points should be considered when applying the isotope dilution method.
1. Accurate estimation of both 14N and 15N initial pool sizes is important. Abiotic consumption of label, such as by clay fixation, can cause significant errors. A subset of intact cores may need to be destructively sampled directly after adding 15N for estimation of initial pool sizes.
2. Homogeneity of 15N enrichment throughout a soil sample is not possible, and perfectly uniform distribution of added label is not necessary. However, significant errors can arise from a bias in 15N distribution that is concurrent with a non-random
distribution of microbial processes. Distribution of label should, therefore, be as uniform as possible.
3. In situ gross immobilization rates may be overestimated by isotope dilution methods and underestimated by chloroform fumigation methods, depending on which (if any) kN factor is applied to the latter. Gross mineralization and gross nitrification estimates from isotope dilution are more reliable because these rates should not be affected by addition of 15N label in the form of the process products."

Schmidt et al. 2008

Schmidt SK, Reed SC, Nemergut DR, Grandy AS, Cleveland CC, Weintraub MN, Hill AW, Costellow EK, Meyer AF, Neff JC, Martin AM. 2008. The earliest stages of ecosystem succession in high-elevation (5000 metres above sea level), recently deglaciated soils. Proceedings of the Royal Society of London, Series B 275: 2793-2802.

These authors describe the microbial community and soil parameters of a chronosequence at the foreground of a receding glacier high in the Peruvian Andes. From a combination of aerial photography and previous work at this site, a series of sites of soils of increasing ages from zero to 79 years old was established. No surface plants, even lichens, are present on any of these new soils, and soil nutrient levels (carbon, nitrogen) are very low; the only organisms present are microorganisms.

Two previous hypotheses had been proposed to explain the dynamics of very early primary succession on new soil. Organic matter has been observed to accumulate slowly in new soils; the source of this material is either aeolian deposits (i.e. wind-borne plant detritus and pollen) or in-situ fixation of CO2 and N2. These are not mutually exclusive hypotheses, but the relative contributions of each are explored in this study.

The methods used here cover an extensive list of soil parameters. Three sets of soil samples were collected: for microbiological analysis, N-fixation measurement, and all other chemical analyses. The other chemical analyses include photosynthetic pigment extraction, soil total and mineral nitrogen, pyrolysis for identifying sources of carbon compounds (i.e. microbial-autotroph, microbial-heterotroph, plant), enzyme assays for common and informative microbial enzymes, and soil stability analysis of the resistance of these new soils to erosion forces such as water runoff.

These authors focused on the cyanobacterial fraction of the microbial community in this study; some details of other components of the biota are described in an earlier paper, Nemergut et al. (2007). Cyanobacteria are autotrophs also capable of fixing atmospheric nitrogen, thus they are ideal primary colonizers of new soil as they require little more than a source of moisture and air. Analysis of the community included the use of the P-test (Martin 2002); note that as in Nemergut et al. (2007), he is one of the authors of this study. The analytical approach is very similar to that employed in the earlier study, with a comparison of discovered sequences to published sequences from around the world. In this study, cyanobacterial sequences from zero and 4-year-old soils were similar to sequences from an extremely broad sample of habitats, including Antarctic lake ice, marine subseafloor sediments, urban aerosols, forest soils, and oil-polluted soils.

The soil chronosequence showed a clear pattern of stages of primary succession at every level of analysis. The soil microbial community became both more abundant and more diverse through time, soil nutrients increased, the chemical environment included increasing amounts and diversity of complex organic molecules, key enzyme pathways became established, and soil stability increased as soils aged. N-fixation showed a peak, with increasing N-fixation activity from the zero to 4-year-old soils (by two orders of magnitude), then declining by about half in the 79-year-old soils. This mirrors and precedes a widely-observed pattern in plant primary succession, in which nitrogen-fixing plants are among the first colonizers, but decline in abundance at later stages of succession. Enzyme and organic molecule patterns were consistent with a total absence of heterotrophs in the extremely young soils, increasing occurrence of organisms capable of decomposing plant matter in the 4-year-old soils, and a molecular ecology qualitatively similar to a mature plant-associated soil in the 79-year-old soil.

The list of procedures and level of detail of analysis in this paper is impressive. Many, though certainly not all, of these techniques will be models for my own work, especially in the summer of 2010. The molecular-diversity techniques pioneered by Martin (Martin 2002, Nemergut et al. 2007, this paper) as well as the techniques of analyzing soil pigments and soil nutrients are all very interesting.

Sørensen et al. 2006

Sørensen LI, Holmstrup M, Maraldo K, Christensen S, Christensen B. 2006. Soil fauna communities and microbial respiration in high Arctic tundra soils at Zackenberg, Northeast Greenland. Polar Biology 29: 189-195.

These authors sampled soil animals from three sites at Zackenberg station, Greenland, over three days in mid-summer. Two of the sites were considered mesic heath, with a mix of Cassiope tetragona and other High Arctic species of plants, while the third site was dominated by Dryas spp. and was considered dry heath; snow melts from the dry heath up to 20 days earlier than from the mesic heaths. Soil samples ranging down to about 6cm depth were collected, stored at 5ºC for up to two weeks, and analyzed by a range of methods in the laboratories in Europe.

Different groups of soil animals were extracted by varying methods. Soil microarthropods, a diverse group dominated by Collebola and Acari, were extracted by modified MacFadyen funnels into Benzoic acid. Enchytraeids and dipteran larvae were extracted in Baermann wet funnels with heating of the samples, into tap water. Protozoa were washed from soils in water and grown on media plates in the dark at 10ºC. Nematodes were collected by the Blender-Cotton wool method of Schouten and Arp (1991). Soil microbial respiration was measured in serum bottles, with the CO2 concentration in the headspace measured at zero, 5 and 25 hours, with a fully factorial design of nutrient amendments of C, N, and P. Soil pH and soil organic matter content, but not moisture content or other nutrient concentrations were determined using methods not clearly described, though presumably these procedures were similar to standard methods.

Once abundance and biomass data was collected, comparisons between plots were made using multivariate analysis and a software package named PRIMER 5.0. My understanding is the species counts were (log+1) transformed to reduce the influence of very abundant species, then analyzed using an approach similar to Principal Components Analysis. The result of this analysis was a clear difference between the dry heath and the two mesic heaths, while the two mesic heaths were not different from each other in parameter-space. A Bray-Curtis similarity matrix was also involved, though I’m not certain I understand how.

Different taxonomic groups were identified to different taxonomic levels; 19 species of Collembola and 7 species of Enchytraeids were found, for example, but Acari were identified to suborder (Cryptostigmata (oribatids), Prostigmata, Mesostigmata) and nematodes and protozoans were counted at those high taxonomic levels. While the two mesic heath sites were only marginally significantly different from each other, there was a clear increase in abundances in the dry heath site. For collembola at least, the dry heath site was also dominated by two highly abundant species, which differed from the majority of species in the mesic sites by being unpigmented and associated with sub-surface, rather than soil-surface, regions in the soil. The higher abundance of probably bacteria-eating nematodes at the dry heath strongly suggests higher turnover of microorganisms as well as generally higher biological activity from the higher populations of most soil animals.

These authors suggest higher organic matter decomposition rates at the dry heath, which seems reasonable given the higher animal populations there. However, their attribution of higher soil pH there to higher respiration levels seems like more of a stretch, absent supporting mineralogical and soil-nutrient data.

This paper provides an excellent example of the data that can be collected and analyzed from a brief but intensive study of soil invertebrates at a High Arctic site. In addition, meaningful information about differences in biodiversity between locations can be derived from studies of organisms not identified to fine taxonomic levels.

O'Neill et al. 2010

O’Neill KP, Godwin HW, Jiménez-Esquilín AE, Battigelli JP. 2010. Reducing the dimensionality of soil microinvertebrate community datasets using Indicator Species Analysis: Implications for ecosystem monitoring and soil management. Soil Biology & Biochemistry 42: 145-154.

These authors used a dataset of soil microarthropods to evaluate a method for identifying indicator species for ecosystem monitoring. The method centres on the Indicator Value (IV) of a species, a number that integrates the degree of uniqueness to a place of a species and the abundance of that species within a given habitat. A high IV value indicates both high information content and a high probability of being sampled. The IV is apparently robust to differences in site number and species absolute abundances, and provides a single value for evaluating observed or expected changes in an ecosystem. Indicator species, furthermore, integrate habitat conditions over their lifespans, in contrast to measures of chemical and physical parameters that capture a snapshot of an ecosystem.

The basic evaluation approach here was to identify indicator species along a clear environmental gradient from meadow to forest in West Virginia. The habitat was divided into three zones, with an edge patch between the open meadows and closed-canopy forest. Near-surface soil cores were collected from each zone every month from April 2004 to April 2005 (n = 180), using the top of the mineral soil as the reference depth. Microarthropods were extracted in a modified Macfadyen funnel with a strong and increasing temperature gradient, into 70% ethanol.

Diversity measures, including Simpson’s and Shannon indices, were based on counts of individuals identified to family level (suborder for Acari). Differences between sites were analyzed by 2-way repeated measures ANOVA and Principle Components Analysis, after rare taxa (those that occurred in less than 10% of samples) were removed; rare taxa are extremely unlikely to be identified as indicator species.

Calculating IV for each taxon, regardless of the taxonomic resolution, provides large advantages in labour time and taxonomic expertise, as many microfauna are very difficult to identify to genus or species. These authors state that enumeration of a single sample required more than 1 hour of a trained taxonomist’s time. In studies such as this one, there are further advantages of IV associated with its robustness in the face of many zero measurements (i.e. taxa absent from samples) and the general messiness of these kinds of datasets. However, the ISA approach is intended for 2-stage studies, where an intensive initial survey identifies indicator species (taxa), and later long-term monitoring ignores other species. For studies specificially designed to address biodiversity, such as my own, excluding rare taxa would not be beneficial, and there may be no easy escape from time-consuming morphotaxa sorting.

I have spoken with Dr. Battigelli, the trained taxonomist in this study. He has indicated that while this IV-based approach may not be appropriate for my own work, it nonetheless demonstrates the types of analyses that can be conducted with soil invertebrates identified to middle taxonomic levels. He has assured me I could probably be trained to identify Collembola to Family and Acari to Suborder in a matter of a few days, and he would be interested in futher studies of collected soil invertebrates based on interesting patterns that emerge at these taxonomic levels.

Liptzin 2006

Liptzin D. 2006. A banded vegetation pattern in a High Arctic community on Axel Heiberg Island, Nunavut, Canada. Arctic, Antarctic, and Alpine Research 38: 216-223.

This author attempted to explain the observation of banded vegetation on a slope that lacked the usual factors that generate such patterns. In temperate and tropical locations, banded vegetation, also known as “tiger stripes”, forms on shallow slopes in dry areas with a consistent direction of water flow. Plants at a position on the slope increase water retention and facilitate further colonization by plants. Similarly, some locations experience consistent wind direction carrying sea spray that kills trees at some positions. In cold environments, patterned ground from cryoturbation on shallow slopes can also lead to banded vegetation. However, the study site in this paper lacks all of these features, including cryoturbation despite the presence of permafrost within 50cm at most locations.

Some aspect of soil properties is the obvious explanatory hypothesis, which this author explores after describing the transects measuring plant diversity and the soil pits used to examine soil properties. In general, features that would normally be expected to influence plant diversity and abundance such as soil moisture or exchangeable cation levels, had no significant impact in the various statistical tests employed in this study. However, soil type did have some effect, as a few species of plants were found only on sandy soil, and nitrogen levels were negatively correlated with species richness.

The discussion section of this paper is an excellent example of a chain of logical reasoning working through a series of potential explanations. While this paper is interesting, it’s only relevant to my own studies in a narrow area around potential starting points in looking for explanations for whatever patterns I may find in my biogeography studies in 2010. However, this paper seems remarkably suitable as an introduction to the basics of modern soil science research, and may be relevant to my not-quite-mothballed interest in an undergraduate course about the current state of the scientific literature.

Li et al. 2009

Li X-R, Du B, Fu H-X, Wang R-F, Shi J-H, Wang Y, Jetten MSM, Quan ZX. 2009. The bacterial diversity in an anaerobic ammonium-oxidizing (anammox) reactor community. Systematic and Applied Microbiology 32: 278-289.

These authors studied the bacterial community that developed inside a bioreactor running on sewage sludge under anaerobic conditions. Like Lim et al. (2008), the main focus of this study was in the applications of ammonia-oxidizing bacteria (AOB) to water treatment facilities. The expected chemistry of anaerobic ammonia oxidation catalyzed by microorganisms (“anammox”) includes the use of nitrite as the electron acceptor in a near-one-to-one ratio with the consumption of ammonia or ammonium. The energy derived from this process is used by the cell to fix CO2, thus making these organisms autotrophs. This alters the underlying stoichiometry slightly, as some nitrite is diverted to CO2 fixation rather than ammonia oxidation.

The study of anaerobic AOB is still quite new, with the five described genera of such organisms all named with “Candidatus” prefixes, indicating recent species descriptions. All are in one group (taxonomic level unknown), the Brocadiales, within the phylum Planctomycetes. Aerobic AOB are in other groups, and include some species within the genus Nitrosomonas in the Beta-Proteobacteria that are capable of limited ammonia-oxidizing activity under anaerobic conditions, and can apparently survive long periods without oxygen.

These authors did not develop novel primers for PCR or qPCR in this study. Instead, they used published primer sets; I gather they did not use the TaqMan double-dye system for qPCR, as no mention of probes is made. The target genomic sequences were portions of the 16s rRNA gene, using E. coli as a standard. Oddly, the overall procedure included normal PCR, followed by cloning and insertion into plasmids, followed by qPCR of plasmid DNA containing the 16s sequences. It is unclear to me exactly why this was done, though later in the paper there are a few sequence-based phylogenetic trees that might have been based on sequences derived from this cloning procedure. In any case, the qPCR did provide informative results regarding the composition of bacterial groups within the reactor.

Of the sequences identified, the great majority were unlike cultivated organisms, highlighting the utility of these techniques in studying environmental samples. AnAOB produced approximately 16% of sequences, with aerobic AOB less than 1%. Non-AOB in three phyla constituted the majority of sequences, including 38% Chlorobi, 21% Chloroflexi, and 7% Bacteriodetes. These are filamentous heterotrophic bacteria, and appear to be closely associated with the granules that formed in the reactor solution after a few months. These authors suggest further research on the ecophysiology of these groups to answer questions regarding energy and material cycles within these systems.

In addition to 16s sequences, the hzo locus was also studied. This is a gene that produces an enzyme that catalyzes the oxidation of hydrazine (rocket fuel; N2H4) to N2 gas. No mention is made of the possibilities for N2O production or consumption in this process. The gene is restricted to AnAOB only, or at least that is the inference based on the observation that hydrazine is a unique intermediate molecule of the anammox process.

This study provides a useful example of the combination of qPCR and molecular-phylogenetic approaches in studying a microbiological system. Applied together, the two approaches allow the extraction of useful information regarding taxonomic diversity, both richness and evenness, among functional groups of organisms.

Himmelheber et al. 2009

Himmelheber DW, Thomas SH, Löffler FE, Taillefert M, Hughes JB. 2009. Microbial colonization of an in situ sediment cap and correlation to stratified redox zones. Environmental Science & Technology 43: 66-74.

These authors previously studied the changes in geochemistry associated with the common practice of adding a sediment cap to cover contaminated sediments at the sediment-water interface. Such caps are commonly clean sand, with the underlying idea being the layer of sand provides a transport barrier to various contaminants moving through the system by diffusion. Sediment geochemistry, like soils, includes layers of redox conditions generated by both biotic and abiotic factors. These zones of chemical conditions migrate upwards when a sediment cap is added; not surprising considering the effect the cap has on diffusion of oxygen and other chemicals important for redox considerations.

This study shows that the microbial populations also migrate upwards when a cap is added. The primary concern here seems to be the effect this population shift may have on the transport and decontamination of such pollutants as are often found in the river-bottom sediments of the eastern USA. The primary effect is likely positive: populations of bacteria and archaea in sediments will metabolize, mineralize, and generally detoxify most compounds moving up from the sediments to the cap. A few classes of contaminants, however, may not be decontaminated and it is possible their transport and release into the water column may be accelerated by these microbes.

There are two key parts of the methods of this paper that interest me. First, the microbial populations were analyzed by a range of techniques including real-time quantitative PCR (qPCR). The procedure of primer design, evaluation, and data interpretation looks very similar to what I will be attempting with my own samples. Second, diversity estimates for the various strata within the sediments, derived from qPCR data, includes the use of the statistical technique Canonical Correspondence Analysis. This allows direct testing of hypotheses regarding the relationship between environmental parameters, in this case depth below surface, and estimates of biodiversity such as the Shannon-Weiner index.

Kellman and Kavanaugh 2008

Kellman L, Kavanaugh K. 2008. Nitrous oxide dynamics in managed northern forest soil profiles: is production offset by consumption? Biogeochemistry 90: 115-128.

These authors measured surface flux and subsurface profiles of N2O at a number of paired sites in the managed forest of Nova Scotia. Half of the sites were clear-cut harvested three years before the study, the other half more than 50 years previously. Climate factors such as air temperatures and solar radiation were consistent across the study area. Fluxes and profiles were measured periodically through a 9-month snow-free period in 2005, from early March to late November.

Surface fluxes were measured by pulling samples into evacuated containers from chambers mounted on permanent collars. Similarly, profiles were measured by sampling from permanent probes buried in the walls of soil pits. Actual measurement of gas concentrations were in the laboratory using a gas chromatograph system.
The soil probes consist of 50cm PVC tubes, covered with a “water resistant porous membrane” (could they be using Gore-tex?) and buried in the walls of pits at depths of 0, 5, 20, and 35cm, with 0 at the mineral soil-organic layer interface. This provides a 50cm-long sampling space at four depths, replicated across 40 sites.

The relationship between profile N2O concentrations and surface flux was almost always non-significant. These authors attribute this lack of correlation to consumption of N2O in the soil profile. In contrast, the studies that have linked CO2 profiles to surface flux have relied on the (probably true) assumption that CO2 is not consumed in the soil, and moves through diffusion in a manner that can be predicted from soil physics. N2O profiles that include regions of consumption are complicated by the biological and chemical factors that control production and consumption, as well as movement. All of this leads to a disconnection between soil N2O cycling and surface-atmosphere exchange.

This paper should almost certainly be included in the introduction, methods, and/or discussion section(s) of my pits & probes manuscript. This is one of the few studies I have found that examined N2O in soil profiles; most others appear to focus on CO2 or in some cases the biogeochemistry of CH4.

Lamb et al. 2006

Lamb EG, Cahill JF, Dale MRT. 2006. A nonlinear regression approach to test for size-dependence of competitive ability. Ecology 87: 1452-1457.

These authors describe a statistical analytical technique, “nonlinear regression”, that potentially provides more information than linear regression techniques including ANCOVA. The basic linear regression formula includes the intercept and the slope as parameters; nonlinear regression adds an exponent parameter. In this paper, these parameters are referred to as k1 (intercept), k2 (slope), and k3 (exponent), in the formula

y = k1 + k2x^k3

where y is the response variable and x is the explanatory variable.

These authors tested their technique on three example datasets from previous studies. The first example is most thoroughly examined, and involves a plant competition experiment. One key feature of all of the example analysis is the dataset must be paired, such that each data point on the x axis corresponds to a partner data point on the y axis. In the plant competition example, individual plants that did not experience competition are paired with individuals that did, because each pair of plants was grown in a communal pot that was treated at the pot level with manipulations such as fertilizer application. The continuous dataset is plant size, measured as the absolute gain in mass over the course of the growing season.

The exponent parameter k3 can take on any value between negative and positive infinity, to describe curves that may be accelerating, saturating, or straight. At values of 1 or -1, k3 is not informative as a parameter, and should be discarded from the model. This analysis is based on a model-building and model-testing technique, where models with various values for the three parameters are tested against null models and each other in an iterative fashion to find the model that best fits the data.

This approach is likely to be useful in the analysis of some of the data collected at Alexandra Fjord in 2009.

Wardle and Nilsson 1997

Wardle DA, Nilsson M-C. 1997. Microbe-plant competition, allelopathy and arctic plants. Oecologia 109: 291-293.

These authors critique Michelsen et al. (1995), a study that came to several important conclusions regarding the interactions between Arctic plants and the soil microbial communities. This is a very negative review of that paper, in which these authors question almost all of the conclusions of Michelsen et al. (1995).

These authors make two main criticisms. First, they question the measures of soil microbial activity used by the earlier paper. Second, they question the conclusions regarding the allelopathy of Empetrum hermaphroditum. Soil microbial activity was measured by Michelsen et al. (1995) in two ways: soil respiration, and soil ergosterol content. Neither approach is necessarily informative about one of Michelsen et al.’s (1995) main claims, that soil microbial biomass was increased by the addition of plant leaf extracts. There are a number of studies, many of them with Nilsson as a co-author, in which a lack of association between microbial biomass and soil respiration was demonstrated. Furthermore, ergosterol is presented by Michelsen et al. (1995) as an indicator of fungal biomass, but previous work by Newell and colleagues (e.g. Newell and Fallon, 1991; Newell 1992) showed that ergosterol is not a reliable indicator of biomass nor is it useful as a proxy measure of soil fungal activity; the ratio of ergosterol to fungal biomass is highly variable.

From the reference list in this short paper, it appears that Wardle and Nilsson had, by early 1997, completed a considerable body of work regarding the allelopathic and other ecological interactions of E. hermaphroditum in sub-arctic environments. The conclusion by Michelsen et al. (1995) that the chemicals released by this plant have a greater impact on microbial communities than potential surface-plant competitors is not supported by this work by Wardle, Nilsson, and their colleagues.

The conclusion of Michelsen et al. (1995) that currently has the most direct bearing on my own work is that key plant traits often possessed by prostrate shrubs in tundra ecosystems such as a high root: shoot ratio and storage of nutrients such as nitrogen in the roots allow those plants to escape from or outcompete soil microorganisms. This conclusion was not addressed by these authors, but given the devastation inflicted upon the other conclusions, my confidence in the utility of Michelsen et al. (1995) in addressing issues of interactions between Cassiope tetragonal and soil microbial communities has been shaken.

Michelsen et al. 1995

Michelsen A, Schmidt IK, Jonasson S, Dighton J, Jones HE, Callaghan TV. Inhibition of growth, and effects on nutrient uptake of arctic graminoids by leaf extracts – allelopathy or resource competition between plants and microbes? Oecologia 103: 407-418.

These authors conducted an experiment to examine the potential allelopathic effects of plant leaf extracts among a few species of arctic tundra plants. Three arctic/subarctic plants suspected of releasing phytotoxic compounds upon their competitors including Cassiope tetragonal were harvested and their leaves and branches ground up to make leaf extracts. Three species of arctic graminoids (Carex bigelowii, Festuca vivipara, Luzula arcuata) were then treated with these extracts while growing in either sterilized or non-sterilized soil in greenhouses in southern Sweden. All of the graminoids, the soil they grew in, and two of the leaf extract-providing plants came from a montaine subarctic hillside in northern Sweden; the third leaf extract came from Betula pubescens ssp. tortuosa, a birch, were collected from individuals growing near the tree line at 450m altitude near Abisko Scientific Research Station, above the Arctic Circle in a subarctic ecosystem.

The experimental design was factorial, with two soil types (sterilized vs. non-sterilized) and four leaf-extract treatments including a control of distilled water. In addition to growth of the graminoids, measurements were made of the chemicals in the leaf extracts and soils, nutrient uptake by excised roots, soil ergosterol content, and soil respiration. Excised roots take up nutrients in a manner directly correlated to the nutrient-limitation status of the plant; more phosphorus-starved plants, for example, have roots that more rapidly take up phosphorus when offered. Soil ergosterol content is a measure of fungal biomass, while soil respiration was taken as a measure of total microbial activity.

Sterilized soil had higher extractable nutrients, probably as a result of the breakdown of microbial cells during autoclaving. Nitrate levels were negligible, both in soils and in leaf extracts; nitrate was a component of the dilute nutrient water used to maintain the plants while growing. Some mycorrhizae were found, but they covered less than 1% of the roots in non-sterilized soil, and had no impact on other measured parameters.

The highest growth of all three test graminoids was recorded in sterilized soil with no extract added (i.e. distilled water added instead of leaf extract solution). Plants growing under these conditions experienced no inhibition from the materials of other plants, and did not compete with soil microbes for nutrients, at least during the early stages of the experiment before microbes recolonized the sterilized soils. Recolonization was much faster by prokaryotes than by fungi, as measured by the contrast in soil respiration rates and soil ergosterol contents. Recolonization also varied between leaf extract treatments, with a negative correlation between microbial activity and plant growth; strongly growing plants were able to outcompete colonizing microbes, while poorly growing plants were further inhibited by colonizing and rapidly growing microbes.

All three leaf extracts significantly reduced growth of all three graminoid species. However, it is not clear that allelopathy alone was responsible for this effect. The results of this study indicate that competition between plants and microbes also played a major role. In particular, the components of the leaf extracts, especially labile carbon and (in the case of the Betula extract) phosphorus, appeared to stimulate the microbial community, increasing competitive pressure on the plants. Added nitrogen, for example, appears not to have much benefited the plants, as their roots were N-limited when grown in non-sterilized soil even though the leaf extracts included high concentrations of inorganic nitrogen.

The susceptibility of plants to this combined effect of allelopathy and microbial competition probably varies by species. Plant traits of particular importance are probably the root: shoot ratio, in which plants with more robust roots are less harmed, and the storage of nutrients such as nitrogen in plant roots, in which plants with a growth strategy favouring nutrient storage rather than immediate use are less harmed. Such traits appear to be widespread among the dominant plants of the Arctic tundra, including Cassiope tetragonal and probably other prostrate shrubs. Many of these plants may form associations with mycorrhizal fungi, which provide some protection against microbial competition.

This paper is directly relevant to the discussion section of my current-high-priority Pits & Probes manuscript. The patterns of soil respiration and microbial GHG activity under some of the lowland communities are consistent with successful competition against soil microbes by Cassiope tetragonal and possibly Salix arctica plant roots.

This paper was critiqued quite harshly by Wardle and Nilsson (1997).

Yates et al. 2007

Yates TT, Si BC, Farrell RE, Pennock DJ. 2007. Time, location, and scale dependence of soil nitrous oxide emissions, soil water, and temperature using wavelets, cross-wavelets, and wavelet coherency analysis. Journal of Geophysical Research 112, D09104.

These authors analyzed a dataset of soil parameters and N2O emission using three subtly-different wavelet-based statistical techniques. There were two main purposes to this study; first, to examine the predictive relationships (if any) between soil parameters such as water filled pore space (WFPS) or temperature and N2O emissions; second, to evaluate the utility of these 3 wavelet techniques in analyzing this type of data.

N2O emission data is characterized by high variance in space and time, and frequent extreme values. These characteristics make many sophisticated geospatial statistical techniques not suitable, and the high spatial and temporal autocorrelation of many soil parameters eliminates many other techniques. These authors describe these limitations and some of the techniques that have been employed, and settle on 3 varieties of wavelet analysis.

Wavelet techniques are related to Fourier-transforms, and they appear to be highly complex and sophisticated methods to transform data for analysis, rather than being analytical methods per se. A large fraction of this paper is concerned with detailed description of the parameters of the transformation, and the interpretation of the results. One of the key advantages of these techniques is they usually allow examination of data across a broad range of spatial scales, thus permitting identification of the spatial scale at which important soil processes occur. Beyond that, I did not understand much of this paper.

Besides the interpretation of the differences between the 3 wavelet techniques, which was quite frankly beyond my understanding, the main result of this study was that the soil parameters that can predict N2O emissions in this landscape vary through the season. Early, around snowmelt and soil thawing, soil temperature is predictive of emissions. Later in the season, temperature loses its usefulness, and individual landscape features may present WFPS as predictive, but not in a global sense. By mid-summer, the soil parameters measured in this study no longer bore any relationship to N2O emissions. This loss of predictive value shows how complex this system is, and shows how some modeling efforts need to change in order to improve estimates of landscape-scale N2O processes.

Besides demonstrating my ignorance of advanced geospatial statistical techniques, this paper is primarily useful to me for its clear introduction describing the basic controls on and processes of N2O production in soils. My previous understanding centred on the role of water in restricting O2 availability in soils leading to changes at both the community and cell-physiology levels and consequently N2O production patterns in space and time appears to be essentially correct, and is reinforced by the early introduction section of this paper and the references therein.

Pennock 2004

Pennock DJ. 2004. Designing field studies in soil science. Canadian Journal of Soil Science 84: 1-10.

This author reviews the major issues surrounding field-based (as opposed to strictly laboratory-based) research, focusing on issues specific or of greatest importance to soil science. Soil science’s history could perhaps be described as a fusion of physical geography and geology with agronomy, and many published studies in the soil science journals show these roots. Following the lead of previous authors, who have included ecologists, statisticians, and philosophers and historians of science, this author divides field research into 2 major categories, broadly manipulative studies and mensurative studies. Manipulative studies are, under some definitions including one tentatively employed in this paper, the only type of study that qualify for the name “experiment”, and involve complete control over experimental conditions by the researcher. Treatments in an experiment are directly related to replication, and can be applied with great precision. Mensurative studies are those that at least partly use features of the environment beyond the control of the researcher to test hypotheses or discover new information. The key feature of a mensurative study is that the features of interest are clearly defined but not controlled (i.e. not randomized) by the person conducting the study.

Replication, and avoiding pseudoreplication, is of great importance in all types of studies. However, the replication built into a manipulative experiment in the form of repeated application of treatments is distinct from the replication of a mensurative study using repeated features of the environment. That these are different types of replication is stated in this paper, but I found no more detail or explanation than that. Pseudoreplication in this paper is discussed little in the context of independence of samples; rather the discussed risk is of attempting to draw inferences beyond the inference space of the study. This is a problem in both major types of study, and can be avoided by carefully determining and describing the inference space, and expanding that space by greater replication; too-small sample sizes are quite simply labeled as unpublishable in this paper, a sentiment I can agree with.

Determining the required sample size is a major issue for all types of studies. In this author’s presentation, this is an early step in the design of the study, after the biological and statistical questions have been established but before data collection begins. There is some discussion here as well of statistical power (the chance of avoiding a Type II error, that is of failing to reject a false null hypothesis) and recommendations of flexibility regarding especially alpha values (the chance of making a Type I error, that is of rejecting a null hypothesis that is not false). For a number of reasons, some of which are practical and logistical, alpha values larger than the ubiquitous 0.05 are encouraged, because in many cases the consequences of the 2 types of error are not even, and one may wish to concentrate on reducing the probability of a Type II error.

This paper describes 10 commonly-encountered study designs in soil science and related disciplines, and then discusses study-design concerns common to all such as replication and the need to clearly define study units, samples, populations, and other important aspects. Finally, this author presents the conclusions from all of these examples and considerations in the form of a short list of key recommendations. Quoting directly:

1. A clear definition of the research question is the initial (and most critical) step. This definition dictates the type of research design that is appropriate and the specific design issues associated with different research types.
2. The appropriateness of a given research design can be judged only after a thorough review of what is known about the research question. Exploratory pattern studies can be very informative at an early stage of research, but yield little new information for well-established research topics. Equally, the imposition of a set of treatments if little is known of the processes controlling responses is unlikely to produce comprehensive interpretations.
3. There is never a good reason for haphazard sampling – the rationale for selecting sampling points in pedological, soil geomorphic, or inventory studies should be clearly stated.
4. A clear definition of the population and the elements that comprise the population under study is very important.
5. The definition of the population dictates the extent of the study and the physical or temporal space that the results pertain to, which is critical to avoid pseudoreplication.
6. The sample support, spacing, and extent of the study must be consistent with what is known of the processes controlling the phenomena being studied.
7. The construction of hypotheses for formal testing should be based on sound physical or biological reasoning, and sufficient samples should be taken to allow reliable testing of the alternative hypotheses.
8. The exclusion of phenomena because they cannot be replicated is inherently limiting to the expansion of our knowledge of soils. Innovative approaches must continue to be developed and applied so that we can expand the scale at which field studies can be undertaken.

Zuur et al. 2010

Zuur AF, Ieno EN, Elphick CS. 2010. A protocol for data exploration to avoid common statistical problems. Methods in Ecology & Evolution doi: 10.1111/j.2041-210X.2009.00001.x

These authors present a step-by-step guide and recommendations for data exploration, a procedure in analysis of statistical data that should be carried out before primary statistical techniques such as regression. The point of data exploration is to look for errors in measurement, calculation or data-entry, to remove outliers, and to ensure no critical assumptions are being violated. Data exploration is not an instantaneous process, and may take up to 50% of the time spent on data analysis.

Their Figure 1 shows the steps in data exploration. Not all steps need be conducted for every dataset, for example, PCA is not sensitive to normal distribution, so the construction of histograms to evaluate normality is not necessary. On the other hand, almost all statistical techniques are very sensitive to violations of the assumption of independence.

(To avoid potential copyright issues, I have not pasted Fig. 1 from the paper here)

Figure 1 from Zuur et al. (2010). The procedures in italics are described in detail in this paper.
This paper was assigned reading for a course I am taking, Plant Sciences 813, Statistical Methods in the Life Sciences. I think the advice and instructions here will be useful.