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.


Meandering meerkats

Dispersal – the movement of individuals to a new location – is a complex process that ecologists divide into three stages: emigration (leaving the group), transience through an unfamiliar landscape, and settlement in a suitable habitat. Dispersal is fraught with danger, as dispersers usually have a higher chance of starving, of getting eaten by predators, and may suffer a low reproductive rate.  So why move?

The problem is that there are major issues with not moving.  First, if nobody disperses, population densities could increase alarmingly, putting strains on resources and increasing the incidence of disease transmission.  Second, if nobody disperses, close relatives would tend to live near each other.  If these relatives mate, there would be a high probability of bad combinations of genes being expressed, leading to developmental abnormalities or high offspring mortality (geneticists call this inbreeding depression). In social species, such as meerkats, Suricata suricatta, the issues are even more complex, as dispersal could break up social groups that work well together to detect predators or find resources.  Nino Maag and his colleagues explored what factors influence meerkat dispersal decisions, their survival and reproduction, and how those factors affected overall population dynamics in the Kuruman River Reserve in South Africa.


A group of vigilant meerkats. Credit: Arpat Azgul

Meerkats live in groups of 2-50 individuals, with a dominant pair that monopolizes reproduction.  While pregnant, the dominant female usually evicts some subordinate females from the group; this coalition of evictees will either remain apart from the group (but within the confines of the territory) and eventually be allowed back in, or else emigrate to a new territory. By attaching radio collars to subordinate females, the researchers were able to follow emigrants to determine their fates.


Nino Maag collects data in the Kalahari Desert while a meerkat, wearing a radio collar, strolls by. Credit: Gabriele Cozzi.

How does population density affect emigration rates of evicted females?  You might think that meerkats would be most likely to emigrate at high population density, as a way of avoiding resource competition.  As it turns out the story is more complicated.  First, individual females (solid lines in graph below) are more likely to remain with the group (not emigrate) than are groups of two or more females (dashed lines). Second, emigration rates were highest at low population density, intermediate at high population density and lowest at intermediate population density. This nonlinear effect can be explained by low benefits of remaining in a very small group, so evictees are more likely to emigrate.  But as population density (and group size) increase, then the meerkats enjoy higher success as a result of cooperation between individuals  (in particular, detecting and avoiding predators).  But when population densities get too high, there are not enough resources to go around, and evictees are more likely to emigrate.


Proportion of evicted female meerkats that had not yet emigrated in relation to time since eviction at low (red), medium (light blue) and high (dark blue) population density.  Solid lines represent individual females, while dashed lines are coalitions of two or more females.

In addition to the density effects we just discussed, association with unrelated males from other groups early after eviction increased the probability that females would emigrate – presumably this increased the probability females would quickly create offspring in their new territory. Females also dispersed longer distances if unrelated males did not meet up with them, possibly to avoid inbreeding with closely-related males from neighboring groups.

Coalitions were more likely to return to the group if females were not pregnant – in fact 62% of pregnant evictees aborted their litters before being allowed back into the group.  Of the ones that did not abort before returning, only 42% of their litters survived to the first month.

The period of transience, when emigrators are seeking new territories can be prolonged and dangerous.  The mean dispersal distance was 2.24 km, and averaged about 46 days.  Larger coalitions with males present tended to disperse the shortest distances (left graph below). Dispersers took longest to settle at high population density – perhaps there were fewer available territories under those conditions (right graph below).


A. Effect of coalition size and presence of unrelated males on dispersal distance. B. Effect of population density on transience time (interval between emigration and settling).

Large coalitions settled more quickly than did small coalitions, particularly if accompanied by unrelated males.  Once settled, females successfully carried through 89% of their pregnancies (compare that to the 62% abortion rate of females that returned to their original group).  These females had a litter survival rate (to the first month) of 65%.

Social and non-social species are influenced by population density in different ways.  The situation is relatively simple for non-social species; as population size increases, competition between individuals increases, so dispersal is more likely.  However, even for non-social species, we might expect dispersal at very low population levels, if there are no mates available. For social species such as meerkats, the situation is more complex.  Cooperation enhances survival and reproduction, so it is better to be in a larger group (with more cooperators). At the same time, if the group is too large, then resource competition starts being an increasingly disruptive factor. As ecologists collect more dispersal data from other social species, they will be able to test the hypothesis that population density in many species influences dispersal in a non-linear way.

note: the paper that describes this research is from the journal Ecology. The reference is Maag, N. , Cozzi, G. , Clutton‐Brock, T. and Ozgul, A. (2018), Density‐dependent dispersal strategies in a cooperative breeder. Ecology, 99: 1932-1941. doi:10.1002/ecy.2433. 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.