What grows up must go down: plant species richness and soils below.

Almost 20 years ago, Dorota Porazinska was a postdoctoral researcher investigating whether plant diversity influenced the diversity of organisms that lived in the soil below these plants, including bacteria, protists, fungi and nematodes (collectively known as soil biota).  Surprisingly, she and her colleagues discovered no linkages between aboveground and belowground species diversity.  She suspected that two issues were responsible for this lack of linkage. First, the early study lumped related species into functional groups – for example nematodes that eat bacteria, or nematodes that eat fungi.  Lumping simplifies data collection but loses a lot of data because individual species are not distinguished.  Back in those days, identifying species with DNA analysis was time-consuming, expensive, and often impractical. The second issue was that even if aboveground-belowground diversity was linked, it might be difficult to detect.  Ecosystems are very complex, and many belowground species make a living off of legacies of carbon or other nutrients that are the remains of organisms that lived many generations ago.   These legacy organic nutrient pools allow for indirect (and thus more difficult to detect) linkages between aboveground and belowground species.

Porazinska and her colleagues reasoned that if there were aboveground/belowground relationships, they would be easiest to detect in the simplest ecosystems that lacked significant pools of legacy nutrients. They also used molecular techniques that were not readily available for earlier studies to identify distinct species based on DNA analysis. The researchers established 98 1-m radius circular plots at the Niwot Ridge Long Term Ecological Research Site in the Colorado, USA Rocky Mountains. At each plot, they identified and counted each vascular plant, and recorded the presence of moss and lichen.  They also censused soil biota by using a variety of DNA amplification and isolation techniques that allowed them to identify bacteria, archaea, protists, fungi and nematodes to species.

PorazinskaOpening9256 Photo

Field assistant Jarred Huxley surveys plants in a high species richness plot. Credit Dorota L. Porazinska.

As expected in this alpine environment, plant species richness was quite low, averaging only 8 species per plot (range = 0 – 27).  In contrast to what had been found in other ecosystems, high plant diversity was associated with high diversity of soil biota.


Relationship between plant richness (x-axis) and soil biota richness (y-axis) for (A) bacteria, (B) eukaryotes (excluding fungi and nematodes), (C) fungi, and (D) nematodes.  OTUs are operational taxonomic units, which represent organisms with very similar or identical DNA sequences on a marker gene.  For our purposes, they represent distinct species.

Looking at the graphs above, you can see that different groups responded to different degrees; nematodes had the strongest response to increases in plant richness while fungi had the weakest response.  When viewed at a finer level, some groups of soil organisms, including photosynthetic microorganisms such as cyanobacteria and green algae actually decreased, presumably in response to competition with aboveground plants for light and possibly nutrients.

Given the strong relationship between plant species richness and soil biota richness, Porazinska and her colleagues next explored whether high plant richness was associated with soil nutrient levels (nutrient pools).  In general, there was a strong correlation between plant species richness and nutrient pools (see graphs below).  But soil moisture, and the ability of soil to hold moisture were the two most important factors associated with nutrient pools.


Amount (micrograms per gram of soil) of carbon (left graph) and nitrogen (right graph) in relation to plant species richness.

Ecologists studying soil processes can measure the rates at which microorganisms are metabolizing nutrients such as carbon, phosphorus and nitrogen.  The expectation was that if high plant species richness was associated with higher soil biota richness, and larger soil nutrient pools, then the activity of enzymes that metabolize soil nutrients should proportionally increase with these factors.  The researchers found that enzyme activity was very low where plants were absent or rare, and greatest in complex plant communities.  But the most important factors influencing enzyme activity were the amount of organic carbon present within the soil, and the ability of the soil to hold water.


Patchy vegetation at the field site. Credit: Cliffton P. Bueno de Mesquita.

Porazinska and her colleagues hypothesize that the relationship between plant species richness, soil biota richness, nutrient pools, and soil processes such as enzyme activity, exist in most ecosystems, but are obscured by indirect linkages between these different levels.  They hypothesize that these relationships in other ecosystems such as grasslands and forests are difficult to observe.  In these more complex ecosystems, carbon inputs into the soil form large legacy carbon pools. These carbon pools, and the ability of the soil to hold nutrient pools, fundamentally influence the abundance and richness of soil biota. In contrast, in nutrient-poor soils, such as high Rocky Mountain alpine meadows, legacy carbon pools are rare and small. Consequently, plants and soil biota interact more directly, and correlations between plant species diversity and soil biota diversity are much easier to detect.

note: the paper that describes this research is from the journal Ecology. The reference is Porazinska, D. L., Farrer, E. C., Spasojevic, M. J., Bueno de Mesquita, C. P., Sartwell, S. A., Smith, J. G., White, C. T., King, A. J., Suding, K. N. and Schmidt, S. K. (2018), Plant diversity and density predict belowground diversity and function in an early successional alpine ecosystem. Ecology, 99: 1942-1952. doi:10.1002/ecy.2420. Thanks to the Ecological Society of America for allowing me to use figures from the paper. Copyright © 2018 by the Ecological Society of America. All rights reserved.


Homing in on the micro range

I’ve always been fascinated by geography. As a child, I memorized the heights of mountains, the populations of cities, and the areas encompassed by various states and countries. I can still recite from memory many of these numbers – at least based on the 1960 Rand McNally World Atlas. Part of my fondness for geography is no doubt based on my brain’s ability to recall numbers but very little else.

Most geographic ecologists are fond of numbers, exploring numerical questions such as how many organisms or species are there in a given area, or how large an area does a particular species occupy? They then look for factors that influence the distribution and abundance of species or groups of species. Given that biologists estimate there may be up to 100 million species, geographic ecologists have their work cut out for them.

As it turns out, most geographic ecologists have worked on plants, animals or fungi, while relatively few have worked on bacteria and archaeans (a very diverse group of microorganisms that is ancestral to eukaryotes).


Two petri plates with pigmented Actinobacteria. Credit: Mallory Choudoir.

Until recently, bacteria and archaeans were challenging subjects because they were so small and difficult to tell apart. But now, molecular/microbial biology techniques allow us to distinguish between closely related bacteria based on the sequence of bases (adenine, cytosine, guanine, and uracil) in their ribosomal RNA. Bacteria which are identical in more than 97% of their base sequence are described as being in the same phylotype, which is roughly analogous to being in the same species.

As a postdoctoral researcher working in Noah Fierer’s laboratory with several other researchers, Mallory Choudoir wanted to understand the geographic ecology of microorganisms. To do so, they and their collaborators collected dust samples from the trim above an exterior door at 1065 locations across the United States (USA).


Dr. Val McKenzie collects a dust sample from the top of a door sill. Credit: Dr. Noah Fierer.

The researchers sequenced the ribosomal RNA from each sample to determine the bacterial and archaeal diversity at each location. Overall they identified 74,134 gene sequence phyloypes in these samples – that took some work.

On average, each phylotype was found at 70 sites across the USA, but there was enormous variation. By mapping the phylotypes at each of the 1065 locations, the researchers were able to estimate the range size of each phylotyope. They discovered a highly skewed distribution of range sizes, with most phylotypes having relatively small ranges, while only a very few had large ranges (see the graph below). As it turns out, we observe this pattern when analyzing range sizes of plant and animal species as well.


Mean geographic range (Area of occupancy) for each phylotype in the study.  The y-axis (Density) indicates the probability that a given phylotype will occupy a range of a particular size (if you draw a straight line down from the peak to the x-axis, you will note that most phylotypes had an AOO of less than 3000 km2

Taxonomists use the term phylum (plural phyla) to indicate a broad grouping of similar organisms. Just to give you a feel for how broad a phylum is, humans and fish belong to the same phylum. Some microbial phyla had much larger geographic ranges than others. Interestingly, it was not always the case that the phylum with the greatest phylotype diversity had the largest range. For example, phylum Chrenarchaeota had the greatest median geographic range (see the graph below), but ranked only 19 (out of 50 phyla) in number of phylotypes (remember that a phylotype is kind of like a species in this study).


Box plots showing range size distribution for individual phyla. Middle black line within each box is the median value; box edges are the 25th and 75th percentile values (1st and 3rd quartiles).  Points are outlier phylotypes. Notice that the y-axis is logarithmic.

With this background, Choudoir and her colleagues were prepared to investigate whether there were any characteristics that might influence how large a range would be occupied by a particular phylotype. We could imagine, for example, that a phylotype able to withstand different types of environments would have a greater geographic range than a phylotype that was limited to living in thermal pools. Similarly, a phylotype that dispersed very effectively might have a greater geographic range than a poor disperser.

The researchers expected that aerobic microorganisms (that use oxygen for their metabolism) would have larger geographic ranges than nonaerobic microorganisms, which are actually poisoned by oxygen. The data below support this prediction quite nicely.


Geographic range size in relation to oxygen tolerance.  In this graph, and the graphs below, the points have been jittered to the right and left of their bar for ease of viewing (otherwise even more of the points would be on top of each other).

Some bacterial species form spores that protect them against unfavorable environmental conditions. The researchers expected that spore-forming bacteria would have larger geographic ranges than non-spore-forming bacteria.


Geographic range in relation to spore formation (left graph) and pigmentation (right graph).

Choudoir and her colleagues were surprised to discover exactly the opposite; the spore forming bacteria had, on average, slightly smaller geographic ranges. Choudoir and her colleagues also expected that phylotypes that are protected from harsh UV radiation by pigmentation would have larger geographic ranges than unpigmented phylotypes – this time the data confirmed their expectations.

The researchers identified several other factors associated with range size. For example, bacteria with more guanine and cytosine in their DNA or RNA tend to have larger geographic ranges. Some previous studies have shown that a higher proportion of guanine and cytosine is associated with greater thermal tolerance, which should translate to a greater geographic range. Choudoir and her colleagues also discovered that microorganisms with larger genomes (longer DNA or RNA sequences) also had larger ranges. They reason that larger genomes (thus more genes) should correspond to greater physiological versatility and the ability to survive variable environments.

This study opens up the door to further studies of microbial geographic ecology. Some patterns were expected, while others were surprising and beg for more research. Many of these microorganisms are important medically, ecologically or agriculturally, so there are very good reasons to figure out why they live where they do, and how they get from one place to another.

note: the paper that describes this research is from the journal Ecology. The reference is Choudoir, M. J., Barberán, A., Menninger, H. L., Dunn, R. R. and Fierer, N. (2018), Variation in range size and dispersal capabilities of microbial taxa. Ecology, 99: 322–334. doi:10.1002/ecy.2094. Thanks to the Ecological Society of America for allowing me to use figures from the paper. Copyright © 2017 by the Ecological Society of America. All rights reserved.